Are humans the only species who drink milk as adults?

Good observation!
Gene coding for the lactase
Gene LCT
Mammals have a gene (called LCT C/T-13910) coding for the lactase enzyme, a protein able to digest lactose. Lactose is a disaccharide sugar found in milk.
Expression of LCT
In mammals, the gene LCT is normally expressed (see gene expression) only early in development, when the baby feeds on his/her mother's milk. Some human lineages have evolved the ability to express LCT all life long, allowing them to drink milk and digest lactose at any age.
Today, the inability to digest lactose at all ages in humans is called lactose intolerance.
Evolution of lactose tolerance in human
Three independent mutations
Tishkoff et al. 2007 found that the ability to express LCT at an old age has evolved at least three times independently. Indeed, they found three different SNPs (stands for Single Nucleotide Polymorphism; it is a common type of mutation), two of them having high prevalence in Africa (and people of African descent) and one having high prevalence in Europe (and people of European descent). The three SNPs are G/C-14010, T/G-13915 and C/G-13907.
Pastoralist populations
Lactose tolerance is much more common in people descending from pastoralist populations than in people descending from non-pastoralist populations, suggesting a strong selection for lactose tolerance Durham 1991.
Selective sweep
On top of that, Tishkoff et al. 2007 focusing on the locus 14010 (one of the three SNP's mentioned above) showed that there is a clear selective sweep (which is a signature of past and present selection) around this locus.
They estimated the age of the allele allowing lactose tolerance at this locus (allele C is derived, the ancestral being G; see nucleotide) at around 3,000 to 7,000 years (with a 95% confidence interval ranging from 1,200 to 23,200 years) and a selection coefficient of 0.04 - 0.097 (with a 95% confidence interval ranging from 0.01 to 0.15).
I recommend reading Tishkoff et al. 2007. It is a classic, is short and is relatively easy to read, even for someone with only basic knowledge in evolutionary biology.
Are humans the only animal that is able to drink milk as adults?
I don't really know... but I would think so, yes!
Drink vs digest thoroughly
As @anongoodnurse rightly said in his/her answer

"Drink" and "digest thoroughly" are two different things

Pets
According to many dog health websites (such this one for example) claim that there is also variance among dogs where some dogs are lactose tolerant and others are lactose intolerant. I could not find any paper on the underlying genetics of lactose intolerance in dogs or other pets. It is not impossible our pets have also been under selection to be able to digest lactose as we humans could have given milk to them. It is also possible that pets do not actually produce any lactase at adult age but rather that some pets are just able to deal with having indigestible lactose in their guts! But then again, "Drink" and "digest thoroughly" are two different things.
Tits and robins in 20th century England
A funny and famous case is the case of blue tits and robins in the 20th century, in England. At that time, in England, the milkman was bringing the milk at home in the morning and would leave glass bottles with a simple aluminum cap in front of people's home. At some point, blue tits and robins learnt that by pecking through the aluminum they can get access to the milk. See this (non-peer-reviewed) article that tells the story.
Somewhat related
There are already a number of good posts on milk digestion in humans on Biology.SE. Consider having a look at:

What inactivates pepsin in infants? and Seriously, do humans produce rennin?
Are there any non-mammalian species known that lactate?
Can an adult without genetic lactase persistence still develop a tolerance for dairy foods?


How did so many types of larvae become known as worms?

Excellent question. My zoology professor during biology undergrads explained this by clarifying that "worm" is a term that relates to one type of shape of animals. As such it does not carry any additional information on the relatedness of animals or their developmental stage.
This view also seems to align with wikipedia.


Regarding apoptosis and turning it 'back on'

Yes, tons of things induce apoptosis. Here is a good list that you can get for research grade

Sigma-Aldrich

Even your immune system can tell cells to "commit suicide." Now the trick is, getting drugs, proteins, pathways, and your immune system to selectively target cancer cells.


What might earlier versions of caddisfly shelter-building behavior have looked like?

Your intuition seems fairly correct. Mouro et al 2016 show some findings relevant to your question...

Caddisflies have been around for a very long time. Much of the fossil record of their existence is of preserved shelter cases rather than the insects themselves.
Early cases seem to be made up of more variety of materials, whereas selective cases made of very specific materials are observed more recently in the fossil record and today. This suggests that they first just collected random pebbles and organic materials, and later evolved more refined construction techniques.

As far as evolution of their silk, I think it's important to recognize that these insects are closely related to Lepidoptera, the moths and butterflies. Many Lepidoptera species, like caddisflies, spin silk cocoons as part of their development cycle, so it can be inferred that the silk and many of its properties precedes any construction behavior using other materials.

Mouro, L. D., Zatoń, M., Fernandes, A. C., & Waichel, B. L. (2016). Larval cases of caddisfly (Insecta: Trichoptera) affinity in Early Permian marine environments of Gondwana. Scientific reports, 6, 19215.


Basic Modelling in Quantitative Genetics

Trait z is represented by k genes: z1....zk (I am using k instead of l because the former is visually differentiable from 1 ).
For simplicity let's assume that there is only one mutable site in a gene. So a mutation can impart a change of $\pm \Delta z$. Starting from initial state of z at zero, the system will proceed to equilibrium where the rate of forward mutation would be same as that of backward mutation; since the rates are same the deterministic steady state of z should be zero.

A mutation event can also be considered a binomially distributed RV. After n events, the mean number of forward mutations would be 0.5×n.   Mean fitness = mean forward mutation — mean backward mutations = 0

You can also model the mutation events as a simple random walk. The mean of that is 0 and the variance is n. But what about large n; I am not sure. You should read about random walks or ask in CrossValidated. With $t\to \infty$, you would get a lot of variants but variants would be filtered out by selection (as the optimum is at 0). I think selection can be incorporated in the random walk with death rate being proportional to the distance from 0. But again I do not have much experience with such hybrid models.

I tried a simulation with n=10000000 (using Monte Carlo); different colours denote different runs (or in another words different loci). Y-axis denotes the value of z.


Was there a time in Earth's history when some animal life existed on land but humans could not have breathed?

There isn't evidence that the worldwide air has ever been toxic compared to today since animals came to land 530+ million years ago.

At some times in history, there has been lots of mercury vapor and perhaps other poisons in the atmosphere, for example recent research indicates that the late dinosaurs had at least 10 times as much environmental mercury from the Deccan traps eruptions which give most of southern india it's current geology. That said, the air would have been breathable, but some apex predators would have had mercury poisoning from their diets. Imprecise studies have found mercury levels in sediment go up to 1000 ppb for hundreds of years, compared to perhaps 100 ppb as they are today... other studies may find that there were higher mercury spikes, up to 30 times those of today perhaps. https://www.researchgate.net/figure/Temporal-correlation-of-mercury-records-with-other-indicators-of-Large-Igneous-Province_fig15_328051765

For oxygen, ever since the first insects emerged on land 530 million years ago, the oxygen levels have been safe for humans. https://en.wikipedia.org/wiki/Timeline_of_the_evolutionary_history_of_life


How do I measure bacterial growth in agar dishes (either by cell mass or by cell count)?

The most simple way is seeding the plates with a suspension of bacteria ensuring that you spread the solution properly. Then you can count the number of colonies, wich would be equal to the number of single cells.

If you want to mesure the growth speed, usually it's simpler to just measure the diameter of the colonies, always ensuring you inoculate the plates with the same amount of inoculum.

Lastly, it's even easier to estimate the growth if your culture is un liquid media and you measure the optic density with an spectophotometer.


Chromatin shearing: what is it and what are the effects of high-sensitivity?

Shear forces are experienced by all molecules, and molecular complexes when they are treated roughly. So, for example, if you have a solution of high molecular weight DNA it will be very viscous, but if you treat it roughly by pipetting up and down through a narrow aperture the DNA strands will suffer shear forces strong enough to break covalent bonds and the solution will become less viscous. Another example of the use of shear forces in biology is lysis of yeast cells using small glass beads. As the slurry of beads and cells is vortexes the cells experience intense shearing forces (forces tending to pull different parts of the cell in different directions) and they break open. They are not being physically ground by the beads.

In the specific case that you quote, you apparently have a multimolecular complex (MSL-DCC) held together by weak (non-covalent) interactions and interacting with the nucleosomes through a component called MSL-3. Without looking at the paper, it seems that this complex is prone to falling apart (during isolation?) as a result of shear forces strong enough to overcome the non-covalent binding interactions. Think of a helicopter with a man hanging on to the undercarriage with both hands. Then imagine a second man hanging on to the first man's boot lace with his thumb and finger. Who will fall off first due to the shearing forces experienced as they are buffeted by the wind?

The helicopter is the nucleosome, the first man is MSL-3 and the second man is the rest of the complex.

added later in response to MattDMo
looks from this that I was wrong - it's actually a French press and other homogenizers that generate shear forces. I don't think I made the glass bead story up, but I can't remember who told me. The BeadBeater people also refer to "cell cracking" not shear. Apologies everyone, I think the rest of the post still holds up, and thanks to MattDMo for the challenge.


Why are proteins that will be exported to the outer of cell are not made in the ER directly? What is the function of ER in intracellular protein synthesis? What is the purpose of co-translational transport?
This is a eukaryotic cell that we are talking about.Once the mRNA is synthesized , it has to move out from the nucleus to the cytoplasm.During its exit, SRP (Signal Recognition Particle) recognizes specific signal sequences in the mRNA and forms a complex with that mRNA.then SRP complex targets ER membrane proteins for cotranslational-transport.
If the secretory proteins are not moved into the ER , disulfide bonds would not be formed from cysteine residues . Because the necessary Enzymes required for this process are found only and only in the ER (namely PDI and ERO1).
Plus, these secretory proteins often have to be glycosylated to perform their action correctly.The Enzymes are located in the ER.
Moreover I believe that these secretory proteins will aggregate and degraded later if they are not transported into the ER.
I do not know WHY this process exists this way. That is Evolution and it is just about adaptation to the environment and not necessarily based on pure logical reasons.
Further readings : Molecular Cell Biology Lodish et al 8th ed at sections 13-1
and 13-3.
In addition see : Protein translocation across biological membranes , Targeting proteins to membranes: structure of the signal recognition particle   Post-translational translocation  Regarding to Ero1 and DPI
Formation and transfer of disulphide bonds in living cells


How can I download a gene sequence from GenBank (NCBI)?

Go to the NCBI website, fill the search field with relevant information in the upper part of page, select "nucleotide" from the drop-down menu just to the left of the search field and click search. You will get a list of items, by clicking "FASTA" link below any of them will bring you the corresponding sequence.
Depending on your interest, you can choose other databases from that menu, and some of them are interlinked. For example you can do the search by selecting "gene" instead of "nucleotide" and when displaying a selected gene info, you can see the links that lead to nucleotide database for getting the sequence.


Like other animals, why humans don't have species & breeds?

If you with 'humans' refer to our genus Homo (which is often the case), we do have multiple species, see wikipedia for an overview. The difference to many other organism groups is just that all species except Homo sapiens are extinct.

Also, taxonomic ranks below the species level - such as breed, subspecies, population and race - are very poorly definined and are usually used in different ways in different taxonomic groups. It is therefore difficult to draw one-to-one comparisons between these types of ranks across taxonomic groups. It is even relatively meaningless to compare e.g. taxonomic families between taxonomic orders, since they are used in such different ways, and compared to ranks below the species level taxonomic 'order' and 'family' have much clearer definitions.

However, if you with breeds of dogs are referring to distict phenotypes (which is basically what they are), you can easily see that some human populations also have distict phenotypes, so in this sense they are similar.

The reason why the concept of human races is largely obsolete and controversial (along with breeds) is clearly our human collective history of racism, nazism and eugenics.


Is this adaption of the Gillespie algorithm using Michaelis constants justifiable?

The stochastic simulation algorithm by Gillespie makes the assumption that reaction propensity (probability) in an infinitesimally small interval of time is same as the macroscopic reaction rate. (For details, you can see my answer in Chemistry.SE).

You can model and simulate every step of enzyme catalysis or you can also use the Michaelis-Menten model. In any case, you can extend the same approximations to the stochastic model.

This is also applicable to other Michaelis-Menten like (or Hill) functions of the form $$\frac{x^n}{k^n+x^n} \qquad \text{or}\qquad \frac{k^n}{k^n+x^n}$$.

There are many papers that have done this. Note that the non-linear nature of these functions results in deviation of the stochastic behaviour from the deterministic behaviour. Read about stochastic focussing. Modelling each step exactly (binding, unbinding and catalysis) may result in different behaviour depending on your parameters. Whether you should use Michaelis-Menten function to describe reaction rate totally depends on how reasonable your approximation is.


Even if the atmosphere is mostly transparent in the radio domain, most of sunlight is visible light.

Also, to make photosynthesis work, you need photons of high energy (say: wavelength shorter than 700nm) in order to excite electrons in the reaction centres. Radio waves cannot do that.

The most widespread photosynthetic organisms make use of visible light and water, which are plentiful on Earth.


Could the Warburg effect be used to starve cancer cells in situ?

The human body needs energy (ATP) for even the most basic function. I guess when you decrease glucose levels (which is broken down for ATP), you will be in affect taking away the ability of the body to function normally by depriving it of energy. This is my theory so I would be happy to if someone with more information on the topic could tell me if I am right or wrong.


identification of purposeful (engineered) genetic changes vs. random mutations

One should be able to tell this from comparison of the sequence with that of the original organism in GenBank etc. The differences in an engineered organism will generally be extensive and of such a kind that a specialist in the field will be able to identify their origin and deduce that they did not arise naturally.

However there is no general and guaranteed method. If I were to engineer a single base change, there would be no way to distinguish that from a natural mutation. The only thing is that if the mutation were beneficial then it would probably have occurred naturally and I wouldn’t have needed to engineer it.


Unlike our underwater ancestors, land animals have evolved eye lids or nictitating membranes to protect our eyes and keep them moist periodically by blinking. During the sleep state, closing our lids protects the eyes from drying out and getting damaged while unconscious.  In addition to the lids themselves blocking light stimulus (not totally), our eyes also roll back to attenuate light stimulation.  Fish also sleep and don't need eyelids to do so, thus closing eyes is not a prerequisite for the sleep state.

Textbook Source: Butler, Ann B.; Hodos, William (2 September 2005). Comparative Vertebrate Neuroanatomy: Evolution and Adaptation. John Wiley & Sons. p. 215. ISBN 978-0-471-73383-6.


Can pulmonary infarction be asymptomatic?

No. Based on experience. Lungs are very active organs.


Why are there two replicase proteins translated from tobacco mosaic virus RNA?

Very Short Answer
As of 2021 it does not appear to be known why Tobacco Mosaic Virus (TMV) produces two proteins from its replicase gene.
Relatively Short Answer
I have done a brief literature search on the topic, and found papers from 2008, and 2012 which relate to the replicase and studiously avoid the question of why there is a 126-kDa and 183-kDa form of the TMV RNA-dependent RNA replicase. I am therefore of the view that there has been no advance since the review by Buck (Phil. Trans. R. Soc. Lond. B (1999) 354, 613–627). From this I glean the following:

“…both the TMV-encoded 126-kDa and 183-kDa proteins are required for maximum efficiency of TMV RNA replication”. The full-length protein is absolutely required; preventing the production of the smaller protein reduces the replication rate to 20% of normal.
“The read-through portion of the 183-kDa protein contains amino-acid motifs characteristic of RNA- dependent RNA polymerases (RdRps) and hence the 183-kDa protein is likely to provide the catalytic activity for the synthesis of TMV RNA from NTP substrates.”
“The C-terminal domain of the TMV 126-kDa protein is helicase-like. Although helicase activity has not yet been demonstrated for the 126-kDa protein of any tobamovirus, these proteins contain six amino-acid motifs, which are highly conserved in known helicases, such as the translational initiation factor eIF-4A.”
“The TMV 126-kDa protein contains two domains. An N-terminal domain with amino-acid motifs and predicted secondary structure typical of S-adenosylmethionine binding proteins, methyltransferases and guanylyltrans- ferases is probably required for synthesis of the 5' m7GpppG cap structure. The TMV 126-kDa protein has been shown to have guanylyltransferase activity.”
There is some evidence in other viruses for association of two forms of replicase. However this is indirect, and there are no data for TMV. The implication in the original wording of the question that the two forms in TMV were two subunits of a replicase is not supported by any evidence and is not assumed to be the case.

The only suggestion that Buck makes is that as helicase activity is required for two separate purposes — to unwind double-stransded RNA during replication, and to remove secondary structure from single-stranded RNA when this is used as a template for multiple copies of the complementary strand —  the two forms of the replicase may have a different substrate specificity in their helicase activity.
[Updates welcome — I may have missed something recent.]


In most situations the lack of sufficient CO2 is not what is limiting algal growth. In general the limits to growth are set by the availability of nutrients such as iron, nitrogen and silica. They actually touch on that in the paper. For example removing iron limitation has a much more dramatic impact on algal growth or blooms than increasing CO2 by a few percentage points (see here). This also explains why there are more algal blooms, the increase of fertilizer use results in more food for the algae to grow on and all round bad things (see here).

Perhaps some algae will benefit since they will not have to invest much energy/nitrogen in creating carbon concentrating mechanisms. However several species of algae use calcium for their cell walls and these would actually suffer by increased CO2 concentrations as this leads to ocean acidification (e.g. coccolithophores). Taking into account that these are heavy sinking algae that take a lot of carbon with them to the ocean floor and you see that ocean acidification is not likely to be a good thing.


Why and how does complexity usually tend to increase through time?

This is actually a very interesting yet difficult question to give a single precise answer to. I will try and summarize for you a "meta answer":

Complexity Science Some consider complexity not to be a Biological topic as such, since it is a property that accumulates in non-biological systems e.g. economics, technology, music, language - in fact anything that "evolves" through time. This new field of science is called "Complexity Science" or "Complex Systems" and is primarily a field of mathematics or information theory: Complex systems

Complexity in Biology What I can say is that these kinds of questions have started an almost new field in Biology, called "diversity evolution", here is a very interesting paper: Diversity Evolution.

Defining Complexity You were right to mention Complexity first needs to be defined, and as an early field of science this is where much focus has been recently. There are quite a few definitions but it is perhaps too controversial to list any particulars... HERE is a whole UCL lecture dedicated to defining Complexity!

Topics of Complexity Science I have written enough, so perhaps this lovely diagram of the topics of Complexity Science will be of some help:


Are there any generic (not dependent on symptoms) ways to find parasite infections?

The first thing that comes to mind would be eosinophils numeration. It is a specific type of white blood cell that handles parasitic infections. So in most cases, a blood sample would show an increase in this type of cell.


According to this Wikipedia article:

  "The Shine-Dalgarno (SD) sequence is a ribosomal binding site in
  bacterial and archaeal messenger RNA, generally located around 8 bases
  upstream of the start codon AUG.1 The RNA sequence helps recruit the
  ribosome to the messenger RNA (mRNA) to initiate protein synthesis by
  aligning the ribosome with the start codon.

  The Shine-Dalgarno sequence exists both in bacteria and archaea. It is
  also present in some chloroplast and mitochondrial transcripts. The
  six-base consensus sequence is AGGAGG; in Escherichia coli, for
  example, the sequence is AGGAGGU..."

I hope this gives the insight that you needed.


When our skin is exposed to the sun, this can cause some damage in the upper layers of skin. This activates DNA damage repair and also induces signalling towards the melanocytes (which produce the pigment). Signalling means the excretion of signalling molecules (mostly alpha-Melanocyte stimulating hormone, aMSH) which binds to the MC1R receptor (melanocortin 1 receptor) on the surface of the melanocyte (the cell which produces the pigment) and induces (or increases) the production of melanin. The melanin is then transferred in the melanosomes to the adjacent keratinocytes, which are then better protected from the sun. This figure (from this article) illustrates this process nicely:

Short term tans (the fast reaction) are based on the changed distribution of melanosomes (granules containing pigment) from the melanocytes to keratinocytes. Longer term suntans are caused by increased pigmentation in the skin as a reaction to the UV exposure by the accumulation of melanin and by the burning of cells. So it is no wonder that it looks like increased pigmentation, it really is. People tan differently because of their genetic background. This influences their ability to react to sun exposure.

There is relatively little known about the degradation of the melanosomes (the granules containing the melanin). What is known is that they are degraded in the lysosome, and that the melanin is most likely degraded through oxidation. There happens to be a permanent turnover of the melanosomes, and when the body is producing fewer new melanosomes than are degraded, your skin will get lighter again.

References:

Shining light on skin pigmentation: the darker and the brighter side
of effects of UV radiation.
Melanocyte biology and skin pigmentation.
Melanosome Degradation: Fact or Fiction


Why are some genomic regions sequenced more than the others?

For RNAseq, the differences in the read depth can simply arise because of expression (that's trivial). Highly expressed regions will have higher number of reads.

However the read depth non-uniformity also arises because of the nucleotide composition of the regions. This is true for all kinds of nucleic acid sequencing such as RNAseq, whole genome sequencing and ChIP seq. This is called sequence bias. This also depends on the sequencing methodology. A variety of factors play a role such as how well can the region be sheared, how well can it be amplified etc.

For details have a look at this article by Ross et al (2013).

  Sequencing technologies are vulnerable to multiple sources of bias.
  Methods based on bacterial cloning and Sanger-chemistry sequencing [8]
  were subject to many coverage-reducing biases, notably at GC extremes,
  palindromes, inverted repeats, and sequences toxic to the bacterial
  host [9–17]. Illumina sequencing [18] has been shown to lose coverage
  in regions of high or low GC [19–22], a phenomenon also seen in other
  'next-generation' technologies [3, 6]. PCR amplification during
  library construction is a known source of undercoverage of GC-extreme
  regions [20, 21] and similar biases may also be introduced during
  bridge PCR for cluster amplification on the Illumina flowcell [23].
  Illumina strand-specific errors can lead to coverage biases by
  impairing aligner performance [24]. Ion Torrent [25], like 454 [26],
  utilizes a terminator-free chemistry that may limit its ability to
  accurately sequence long homopolymers [4, 27, 28], and may also be
  sensitive to coverage biases introduced by emulsion PCR in library
  construction. Complete Genomics [29] also uses amplification along
  with a complex library construction process. The Pacific Biosciences
  [30] process is amplification-free; therefore, one might expect it to
  exhibit lower levels of coverage bias than the other technologies.

  In addition to sources in the wet lab, bias can be introduced by any
  of the computational steps in the sequencing pipeline.
  Signal-processing and base calling limitations could result in
  under-representation or increased error rates in some locations, as
  can inaccurate alignment. An inaccurate reference or sample-reference
  differences can cause coverage or accuracy variations that may be
  misdiagnosed as sequencing bias. Therefore, detecting bias is only the
  first step and must be followed by more detailed experiments to assign
  responsibility to the library preparation, sequencing, or
  computational stages.

Some analysis software try to correct for these biases while estimating the read abundance.

Ross, Michael G., et al. "Characterizing and measuring bias in sequence data." Genome Biol 14.5 (2013): R51.


How many chemical species are on average in a typical plant and animal cell?

There is no average plant cell.  However this article describes a whole plant flux balance model with 333 metabolites. This won't describe a lot of the molecules plants make.

I seem to remember a natural product analysis of garlic that had scores of sulphur containing compounds that give its distinctive smell for instance.  This model would be a simplified plant which has no special characteristics like that, which probably doesn't exist.  Its probably not less than half the number of compounds that some plants produce or use.


Why do we have two of some organs, but not all?

Here is my overly succinct answer.

I doubt we will ever know this for sure. But, it basically comes down to ancestral bilateral symmetry in development; this defaults to two organs and is broadly symmetrical except where the organs are central. See this article for a more thorough answer regarding bilateral symmetry.

Further exceptions to symmetry occur where evolution pressured the body into not bothering to grow the second of an organ due to a waste of resources for the body, or functional advantages emerged from asymmetrical evolution. I always like the ears of an owl for an excellent example of two asymmetrical features that provided a discrete advantage when it comes to locating the source of a sound.


This isn't particular to eyes. Anything without mirrors would show the same behavior.


Firstly, I'd like to emphasize that the understanding of memories and learning as we know it is still in its very early stages. In fact, the mechanisms behind short-term memory are still under intense debate.

As for long-term memory, it is essentially caused by chemical changes in synapses between neurons in the brain. When you sense stimuli from your environment, action potentials follow a specific trail of afferent neurons towards the central nervous system, which then sends a message back through efferent neurons to initiate a response. The high frequency of these action potentials from the same stimuli of whichever sense allows for the strengthening of specific connections between neurons, which is called long-term potentiation. This phenomenon is one of the major components of synaptic plasticity, which also applies to the weakening of synaptic connections between neurons due to lack of transmission, as well as the change in the number of connections the neurons are receiving and making. Synaptic plasticity is also influenced by the change in quantities of neurotransmitters being expulsed into the synaptic cleft, and how cells react to these neurotransmitters, which is highly regulated by calcium levels. Ultimately, synaptic plasticity in accordance with learning is referred to as Hebbian theory.

We are still not exactly sure where memories are stored within the brain, but we do know that the hippocampus does play a big part. It definitely aids in the storing and structuring of memories in the form of these millions of synaptic changes. Finally, memory consolidation occurring in others regions of the brain over longer periods of time is likely, but still debated by some.


How should lentil roots grow in a microgravity system?

It sounds like your first issue is with seed germination. I am assuming you are doing a seed sterilization. You may want to try allowing them to imbibe water for about an hour after the sterilization process, and then wrapping them with aluminum foil and placing them in a fridge for a day or two. I've done this with Medicago, which is another legume. However, not sure if it works for your lentils.

The root may also have trouble developing given the micro-nutrients in the media. I am curious what recipe for media you are using, as the amount of agar may also affect the ability for these roots to penetrate the media. I have had trouble germinating legume seeds when there were 100+ seeds in a plate as they inhibit each others growth.

It's hard to give a clear answer, but try optimizing your seed sterilization protocol and media recipe and best of luck!


I have also hit this issue. I was interested in full length amino acid sequences for the classical class I mouse MHC alleles. I was able to find a number of them on uniprot but not all. Here is my list below. Interested if anyone knows additional sequences to extend this:

H-2 D

H-2 Db
H-2 Dd
H-2 Dp
H-2 Dk
H-2 Dq

H-2 K

H-2 Kb
H-2 Kd
H-2 Kk
H-2 Kq

H-2 L

H-2 Ld
H-2 Lq


I very much doubt it. You may however die from whatever's causing the pain. The reason you feel pain is so you stop doing whatever is causing the pain. Hence someone knows not to touch a hot fire because it is painful. But the pain itself is not actually the danger - it's the fire burning away skin. So pain is actually a good thing, a survival mechanism. So for something that is meant to prevent death it's hard to imagine it doing the opposite.

Perhaps if you were in SO much pain you may be unable to breath and paralysed - but even then I still think you'd go unconscious before that would happen, and you'd start breathing again, etc.

The only other thing I can imagine is having a cardiac event, and the heart stopping. Again, this would be because of stress. Other than that - you may commit suicide on account of insufferable pain, however it's a different situation.

However pain never comes on its own for no reason, just like smoke needs a fire. In this case it's the fire - not the smoke, that will kill you!

People who've ever been in a desperate or life threatening situation like a car accident, have often walked on a broken leg for example - feeling no pain. In this case the body was giving them a chance to escape what might have been a lion, etc.

In short, no - I don't think you can. However I cannot give a 100% correct answer. It would take just one example to prove that however!


As Roland mentioned in the comments, in the well fed state, not all of the Acyl coA is converted to Acetyl coA. This picture from Harper's Biochemistry, 29th, should come handy.

It is the CPT-1 gateway that regulates the amount of acyl-coA (from FFA) that enters into the mitochondria to form acetyl-coA.

In the Fed state, the CPT gateway is shutdown (regulation by malonyl-CoA) - allowing esterification by sending them back as VLDLs. In the starved state, the gates open, leading to beta oxidation giving acetyl-CoA.

The acetyl coA then can enter the Kreb's cycle to get completely oxidised and give ATP + CO2 (this ATP the liver readily utilises). Or, the acetyl-CoA can be channeled into ketogenesis, where this energy can be used by other tissues (since liver lacks the enzyme thiolase and hence can't metabolise ketone bodies). How the liver distributes the acetyl-coA for ketogenesis/Kreb's cycle is a different story altogether.


Models of quorum sensing for multi-agent systems

I found this paper[1], which might be relevant; it uses is a more chemically inspired approach. Another paper[2] also might be interesting, it takes a more dynamical systems approach.

My personal instinct would be to use ordinary differential equations: generate a population of cells in random positions, assign each cell levels of any relevant molecular species, and come up with a list of ODEs that describe the rates of change of the species in a particular cell in terms of gene expression, degradation, and diffusion. You should then be able to simulate the time evolution of the system just by solving the (large) system of ODEs given your initial conditions. Something like the approach in this paper[3] (read the supplemental info), only your cells would move around during the simulation, rather than remaining still as part of a tissue. The implementation would get thorny, because you would have to accommodate the motion of the cells as you solve the ODEs. I imagine that this could be accomplished by simply treating the initial positions of the cells as part of the system's initial conditions and then defining the ODEs that govern the rate of change in each dimension (either randomly, or perhaps they move in a coordinated manner) so that this aspect of the system can evolve during the integration.

References:

 Rai N, Anand R, Ramkumar K, Sreenivasan V, Dabholkar S, Venkatesh KV, Thattai M. 2012. Prediction by promoter logic in bacterial quorum sensing. PLoS computational biology 8: e1002361.
 Chiang W-Y, Li Y-X, Lai P-Y. 2011. Simple models for quorum sensing: Nonlinear dynamical analysis. Physical Review E 84.
 Lubensky DK, Pennington MW, Shraiman BI, Baker NE. 2011. A dynamical model of ommatidial crystal formation. Proceedings of the National Academy of Sciences of the United States of America 108: 11145–50.


Why can't we breed watermelons without any remaining seeds in the flesh?

The seedless watermelons, like bananas, are a crop that are specifically bred to be trisomic (three copies of a chromosome). The consequence is the seeds are non-viable.


Are some animals, like dogs and cats, color-blind and how do we know that?

TL;DR: We have a good physiological understanding of how eyes work, so by examination of other species' eyes, we can tell a lot about what colours they are capable of seeing.

First, a little bit about the physics of colour

Light is made of photons, and each photon has a wavelength. The distribution of wavelengths coming from sunlight looks like this (wavelengths on the x axis):

Any perceived 'colour' is some sort of summary of the wavelengths of the photons which get into an animal's eyes.

Now, a little about colour perception

There are cells in the eyes which respond to being hit by photons: these are called rods and cones. Colour vision is principally achieved using the cone cells, which have a peak sensitivity at one particular wavelength, and are less sensitive at other wavelengths.

We (non-colourblind humans) have three different types of cone cell, sensitive to photons with wavelengths of 560, 530, or 420 nm, corresponding to the peak sensitivities of three different types of light-sensitive opsins which are present in cone cells. Other types of opsin exist in rod cells (Rhodopsin) and our circadian-rhythm entrainment (melanopsin), but the three different opsins in our cone cells are responsible for our colour vision. Because we have three different types of cone cell, we are referred to as 'cone trichromats'. The sensitivities of the three cone types overlap a bit, looking like this when plotted over the visible spectrum:

When cone trichromats perceive colour, what we're doing is taking the information on how active each of our different types of cone cell are, and using that to infer how many photons there are of each wavelength in the light that hits our eyes.

Of course, cone trichromats can't possibly summarise the whole diversity of wavelengths that are coming into their eyes using just three different measures of intensity - the line is way too complicated to summarise from three points. Also note that for humans, there is no cone cell that is sensitive above about 700 nm, or below about 400 nm. This means that we simply can't see differences in the infra-red or UV parts of the colour spectrum.

How does this all relate to colour-blindness in animals?

It is fairly simple to test the peak sensitivity of a cone cell: you take an eye from a freshly-dead animal, hook up an electrode to a cone cell, and then provide light of different wavelengths, and measure what wavelength causes the cell to 'fire' the most. If you repeat this with a large number of different cells, you can confidently determine how many different types of cone cell the animal has, and what wavelengths those cone cells are most sensitive to. This experiment (or similar ones) has been done for many different species, so we have a good background knowledge of what colours different species are capable of seeing.

Many species, including most non-primate mammals, have only two types of cone cell (i.e., they are cone di-chromats, as against non-colourblind humans, which are cone tri-chromats). This doesn't mean they see no colour, but it does limit the types of colour they are able to see. Many tools exist to simulate the visual ability of cone dichromats, for instance here, or here for browsers without flash support. These tools simulate human vision with different numbers of cone cell types. When comparing across species, it is important to remember that both the number of types of cone cell, and the peak sensitivity of each type, may be different, so the tools do not capture the full range of possible colour-perception abilities across species.

There are also cone tetrachromatic (four types of cone cell) and pentachromatic (five types) species. The record appears to be held by mantis shrimps, which have sixteen different types of cone cell. These species can in principle see a greater diversity of colours than cone trichromats.

Does colourblindness present an evolutionary problem?

Not necessarily. Compared to cone tetrachromatic species, humans are 'colourblind', and it seems to have very little impact on our day-to-day survival. Similarly, most colourblind humans (i.e., with one or more types of cone cell disabled compared to non-colourblind humans) get along perfectly fine - a special test is needed to detect colourblindness in humans. If trichromatic vision gives no particular survival advantage, there is no reason to think that it will be favoured by evolution.


Yes, those are definitely eggs.  And I believe that is a female grass spider (Genus: Agelenopsis).

Eggs are typically laid in late summer or fall and spiderlings emerge
the following spring....A female that has mated with a male can produce more
than one egg sac. For some species,  it’s common to see two sacs at a
time, side by side, attached to a surface (such as the underside of a
rock, piece of wood in a wood pile, or in a rolled up leaf, for
example). Each different species of Agelenopsis may create a slightly
different egg sac, but typically each one contains anywhere from 50 to
200 individual eggs. The mother spider will remain near her eggs,
dutifully guarding them, until she dies around the onset of winter.

This seems to fit the picture to a T.  I'm not 100% about the species, but I believe it is either A. aperta or A. oregonensis.
Edit:
As user Xan pointed out, this could likely be a lynx spider (Genus: Oxyopes; likely species: Oxyopes salticus - female).  This would explain the defined setae (bristles) on the legs.  To really decide, you would need to check the following characteristics:

Eye pattern: Lynx spider eyes form an octoganal pattern, while grass spider eyes form two, parallel, curved rows.
Spinnerets: You would have to search for spinnerets on a lynx spider, while grass spiders have two very prominent hind spinnerets that you can visibly see from above.

I originally thought those were spinnerets in picture 3, but upon closer inspection it looks like one of the hind legs folded underneath.


Why to use transgenic mice in ALS models?

The use of a mouse with the replacement of one of its genes with a human version is to better mimic the human disease phenotype, or to prove something about the biology of the human phenotype with research that can't be conducted in humans.

Genes and their corresponding proteins or RNA usually differ somewhat between mouse and humans. If you wanted to study whether a certain SNP in a gene (found in humans) was the reason for part of your phenotype, you may want to use transgenic mice to test hypotheses with different exacerbations (treatments).  One way to do this is to create a mouse with the human gene replacing the mouse gene, and another mouse with the human gene containing the trait-linked SNP.

If you tried to do this with the mouse gene, you couldn't be sure that the same SNP would have the same functional consequences.  If you didn't remove the endogenous gene from the mouse before replacing it with the human version, you would never be sure if observed experimental phenotypes weren't confounded by both copies of the gene and their corresponding gene products being active in the same animal.

In your example, with SOD1 and ALS, creating a humanized mouse with human SOD1 allows researchers to more fully study the same protein product made in humans, while giving the mouse treatments that would be unethical in humans.

Your understanding in your last part is incorrect. Mice don't lose genes after a few generations.


Alfred Jost's rabbit experiment: how did he actually do it?

Check out Fig. 7 in the document at http://ipubli-inserm.inist.fr/bitstream/handle/10608/4343/MS_1991_3_263.pdf . The caption says: "Castration of a 23 day fetus. [Mother's] womb is open, the rear end of the fetus is pulled out, a flank incision is performed, and the testicle, located on the mesonephros, is exposed, then cut. After bilateral testicular removal, the fetus is re-placed in the womb. [..] For ease of explanation, an older fetus is in fact shown."


How usable is the Human Metabolic Model to predict biomass?

Firstly, it is important to remember that Flux Balance Analysis computes theoretical performance limits, i.e, the theoretically optimal behaviour of the system with respect to the objective and constraints. When growing bacterial cells growing in culture evolve under selection pressure for biomass production, the theoretical limit on biomass production may indeed be approached, see for example Ibarra et al: Nature. 2002 Nov 14;420(6912):186-9. (http://www.ncbi.nlm.nih.gov/pubmed/12432395) and Fong & Palsson: Nat Genet. 2004 Oct;36(10):1056-8 (http://www.ncbi.nlm.nih.gov/pubmed/15448692).

How closely other systems can be expected to approach optimality should be considered on a case-by-case basis, and the constraints should be realistic. In humans, you would for example expect that the physiology of the persons (blood glucose levels, etc.) would greatly affect the growth rate of any cancer cells, in addition to the structure of the tumour (especially blood supply). For cells growing freely in culture, one might expect FBA to be easier to apply.

For HeLa cells growing in culture, the results of at least one study suggests agreement between experimental and FBA-predicted growth rates: See Resendis-Antonio et al: Modeling core metabolism in cancer cells: surveying the topology underlying the Warburg effect. PLoS ONE, 5 (2010), pp. 1–11 (http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0012383)

Whether the precise biomass production rate is predicted or not may actually not be so important, and there has been considerable interest in applying FBA to studying various aspects of cancer metabolism. Here are some papers that may be of interest:

Ashwini Kumar Sharmaa, Rainer König. Metabolic network modeling approaches for investigating the “hungry cancer”. Seminars in Cancer Biology 23:4,2013, 227–234 (http://www.sciencedirect.com/science/article/pii/S1044579X13000436) (Review)

Shlomi et al.: Genome-Scale Metabolic Modeling Elucidates the Role of Proliferative Adaptation in Causing the Warburg Effect. PLoS Coputational Biology 2011 (http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002018).

Lewis & Abdel-Haleem. The evolution of genome-scale models of cancer metabolism. Front. Physiol., September 2013 (http://www.frontiersin.org/Journal/10.3389/fphys.2013.00237/full). (Review)

And a relevant Master's thesis: Computational Metabolic Modeling of
Cellular Growth: From Bacteria to Cancer. http://www.cs.tau.ac.il/thesis/thesis/Benyamini.pdf


Can a virus be transmitted from a sweating person out to another person?

Sweat per se, at the source, is not likely to be contaminated with bacteria or viruses. However, that's a moot point, because as soon as it's produced it's on contact with the sweaty person's skin, which is invariably coated with bacteria and potentially with viruses. Sweat can therefore act as a medium for transferring infectious agents between two hosts.

Examples of this are described in Contact transmission of vaccinia virus from smallpox vaccinees in the United States, 2003–2011:

  Among adult male cases, the most frequently reported activities associated with vaccinia transfers were wrestling, grappling or sparring (n = 18) [12,18–20]; household interactions (e.g., sharing towels, clothing) (n = 6); unspecified “contact” (n = 4); and football or basketball (n = 3).

(Vaccinia virus is the vaccine for smallpox. As such it's far less dangerous than smallpox itself, but as an ancient vaccine it's also much more dangerous than the vast majority of modern vaccines, and exposure to large concentrations of the virus in an uncontrolled setting is potentially risky.)


This is a Bogong Moth,the migration point was really helpful !!
They migrate in masses around the
 1. Victorian alps
 2. southern Australia (Sydney,Canberra)
 3. New Zealand..
Agrotis infusa,
These are pests which affect many plants,they're not neutral and they
Cause some attentive damage

More on this and the site which helped me


Calculating sequence divergence score for a protein from identity or similarity score?

This is a very tentative answer as I haven't done anything like this, but it's a learning experience for me and I hope it could be helpful to get a more knowledgeable response started.
I don't think you can do this.  Per Wang, 2009 and Yona, 2002, divergence scores could be Kullback-Leibler divergence or Jensen-Shannon divergence, but both papers opt for the latter.  Divergence scores are based on "empirical probability distributions between the 20 amino acids".  BLOSUM or PAM matrices may be used.  Simply counting the identical or similar residues wouldn't contain as much information.  Wang, 2004 compared JensenShannon to numerous other scoring methods in the context of PSI-BLAST.
The similarity score is related to the divergence score:  Score = 0.5(1-D)(1+S) where D is the divergence score and S is the significance score. It is equation #15 in Wang, 2009 paper.  If you could safely assume the significance score for some alignments was near 1 (no chance similarities) then maybe you could say D = 1 - similarity score.  Unfortunately, judging by the glossary because I haven't downloaded any of the datasets, for the Ensembl data similarity is merely "How well one sequence matches another determined by calculation by an alignment program of identical and conserved residues/nucleotides."  So from that I take it they may just be counting up the "conserved" amino acids in the old fashioned way, but don't know that.


What does 'half life' of a protein mean?

"Half-life time" is a general term. This is a time after which the amount of substance X decreases by 50%.

If you take a bulk of something (say, 100 protein molecules), if this protein has half-life time of 1 hr, then 1 hr later you'll have 50 molecules left.

In cellular biology it usually means that 50% of protein got recycled/degraded in given half-life time


Most types of snails survive droughts (that would kill otherwise through Dehydratation) by producing much mucos around themselves. This mucos will dry out if the sun comes up, so they hide under leaves or in the ground. If it's raining, those rings of mucos hydralise or "melt" and the snail begins to crawl. Like most amphibians snail take their oxygen by their skin furthermore they have lungs. By raninning they start moving for searching food, cause they dry out in sun.


The Magenta variety is pure breeding, and hence must be homozygous at both loci, (Dominant at Gene A and recessive at Gene B), otherwise, in some of the generation along the family line, there would have been a non-magenta flower, which contradicts the pure breeding nature. But the same cannot be said for the pure breeding white variety, as it can still be homozygous recessive at Gene A and heterozygous at Gene B, it would still exhibit white flowers in all of its progeny after any number of generations.

But the fact that all the progeny of the cross between white and the magenta variety turns out to be red, removes the possibility of the white variety being heterozygous, as that would have produced atleast some magenta plants. Since all were red, we can be certain of the genotype of both the parents, and consequently of the F1 progeny.

This solves your first question. The second question needs the extrapolation of the information gathered while solving the first question into a Punnett square and a simple probability calculation. The third question is a factual question, but it must be mentioned, that this particular type of interaction can be classified under more than one type, and hence a single answer would not be possible for your third question.

ADDENDUM
The third question is actually a bit difficult to answer. The phenotypes will be $\text{A*B*}$=Red, $\text{A*bb}$=Magenta, $\text{aa**}$=white. This gives us $9:3:4$ for Red:Magenta:white. Now the fact that recessive at one locus , Gene A, suppresses the phenotype altogether no matter what the genotype at the other locus, means that one of the phenomenon exhibited is recessive epistasis, where Gene A is the epistatic loci and Gene B is the Hypostatic loci. But, the fact that there are two distinct phenotypes with the epistatic gene dominant, means the interaction is not complementary ($9:7$) but is supplementary ($9:3:4$). This distinction is necessary, and it essentially means that the "intermediate" of the elucidated pathway is also coloured. Otherwise, like in Flower colour in Lathyrus Odoratus, the phenotypes of $\text{aa**}$ and $\text{A*bb}$ are same, and hence the phenotypic ration remains $9:7$. For a ratio of $13:3$ you need domianant epistasis and the phenotypes of double recessive and the epistatic recessive must match. Here, it is recessive epistasis, as the recessive condition at one locus suppresses the expression a other, and not dominant. Feel free to seek further clarifications or simplification.


Why does a blood test show ethanol when no alcohol was consumed?

There are some situations when ethanol-like compounds can be present in the blood stream:

  [...] exposure to hand sanitizers, after shave lotions, perfumes, medications, hygiene products, cosmetics, foods [...]  Uncontrolled diabetes mellitus can cause false positive alcohol tests.

Source: Dr. Kokil Mathur. Answer on: False-Positives for blood alcohol content. Available from MedHelp forums.

Other causes as pointed on eHow.com:

low calorie diets
gasoline, paints, lacquers
lower hematocrit values
diabetes mellitus


How do I compare bacteria growth curves?

1) A Bacterial growth curve:

When we provide a favorable medium for bacteria to divide regulary and increase in number, we get what's called a "growth curve", measuring the concentration of cells against time as time passes.

2) Phases:

A) The first phase is called the "lag phase", in this phase bacteria are adapting to the new medium, preparing enzymes etc, to start dividing. Therefore little to no growth is observed.

B) The second phase is the "Exponential growth phase", bacterial cells are well adjusted to their medium and ready to reach full potential, "maximum division and growth" happens here.

C) The third phase is the "stationary phase", bacteria are no longer able to grow or feed, they run out of nutrients, and growth is stationary/zero again. It can persist for a long period of time. (Cell growth=cell death, no actual increase in cell number=stationary)

D) The final growth phase is the "death phase", no nourishment is available and toxic metabolites have been accumulating during the stationary phase, death occurs (death here means that an increasing number of bacterial cells are dying, unlike the stationary phase where the number of cells dead equals the number of cells viable), following cell death (which now happens at a faster rate than cell growth), the cell concentration starts to decline. However, it doesn't really reach zero and bacteria might be able to regenerate again when the conditions are healthy again.

3) Recording bacterial growth using transmittance or spectrophotometer:

As bacterial cells increase in number, the turbidity of their medium increases (depends on the concentration of cells), and the incident light (if you shoot a beam of light across the medium) is more deflected away from the receiving detector (to detect the intensity of light), which makes spectrophotometer a reliable and accurate method to measure cell growth (proportional to the intensity of light detected).

4) How to compare growth curves?

Looking at the growth curve will give some idea of the rate of growth in relation to a standard growth curve or some other available growth curves (compare phases and their durations, the exponential phase, etc). However there is a way to calculate growth curve and generation time (doubling time) from a growth curve.

The difference in cell concentration/difference in time = growth rate constant. Or dN/dt = kN or you may use this advanced equation: log10N2 – log10N1 = k(t2 – t1)/2.303

Simply plot any two random points of time on your curve: the first point is t1, the second point is t2, N1 is the number of cells (cell concentration) at t1, N2 is cell concentration at t2.

Or you can simply use dN/dt = (N1 – N2)/(t1 – t2) and compare the resulting k between curves.

I hope this answers your question, please know that I am by no means an expert on the subject and you may search further or get expert advice if you need to.

References:

Textbookofbacteriology.net

Miller-lab.net/MillerLab

biotek.com/

Academic.pgcc.edu

Web.mst.edu


Is trembling an advantageous response during periods of anxiety?

Some assumptions made in the question.

There is an implicit assumption in your question which I don't think to be correct: you assume that any reaction of the human organism to stress (let's substitute "fright" by "stress" in your question) is a physiological reaction, meaning that this reaction somehow helps the organism to overcome the stressful situation. From medical viewpoint the reaction to any external action can be:

physiological one (i.e. the one that is expected and is considered "good", helping the organism to adapt to this action).
pathophysiological:

as a side-effect of physiological reaction
as a result of nervous/humoral system overlast and depletion
as a reaction to unknown action
as a reaction to something mistaken for known action that is indeed something else

Mechanisms of tremor.

From mechanical viewpoint our body consists of dozens joints that are absolutely not fixed and have from two (moving in one plane) to three (for free movement in 3D, for example coxofemoral joint), thus giving our extremities an incredibly high number of degrees of freedom.

In order to sustain a certain posture our joints are equipped with antagonistic muscles: muscles that move the joint into opposite direction. The muscles, again, by design are very badly adapted for isotonic action. That basically means they cannot keep the same pressure for long time and the only way to get a fix posture for the whole body is to keep sending repetitive pulses to antagonistic muscles so that none of them actually wins.

Normally the impulses are very short and frequent. They also have to come synchronously and out-of-phase, meaning that whenever one muscles contracts its antagonist should dilate and vise versa, so that no muscle rupture takes place because of the simultaneous contraction of two opposite muscles. This synchrony accounts for very subtle trembling of the body, almost not seen by a naked eye in healthy humans. This trembling is also called physiological tremor to designate its being normal, e.g. physiological.

There are two ways how this trembling can increase so that it becomes visible and sensible:

Due to impaired synchronisation between the pulses sent to the antagonistic muscles. Since these pulses are generated in brainstem nervous centers, the impairment of those (in case of Parkinson's desease) or some inhibiting input into them (as in case of cerebellar deseases) leads to desync of these pulses, the frequency goes down whereas the amplitude might increase, making the trembling visible.
Due to attenuated cell sensitivity to the incoming impulses. This happens if the muscle cells start to overreact to the normal impulses and respond with prolonged contraction (followed by longer refractory period when they are unable to respond any impulse, thereby missing frequent pulses and reducing the effective frequency). These is mainly caused due to special metabolic changes within and in the vicinity of the muscle cells.

The most common metabolic change within the cell is either the increased Calcium concentration within muscle cells, leading to much stronger contraction, or increased sensitivity for Calcium (via Ca and ryanodin receptors), that leads to much abrupter Calcium concentration rise in cells and results in the same.

The reason for Ca to increase within the cells might be the intake of some known Calcium liberators, like caffein, increased concentration of the humoral factors that use Ca as second messenger, like adrenaline, insuline, thyroid factors etc. Those, again, can be released during some stress conditions, during artificial or temporal low sugar level and other factors.

Shivering as a reaction to stress.

The shivering, or in medical terms tremor might appear due to the following mechanisms:

Massive release of adrenaline during the stress: both directly via the adrenaline receptors and indirectly by causing temporal hyperglycemia via the metabolic adrenaline receptors. The action of adrenaline is also increased due to concomitant release of corticosteroids.
(muss less probable in case of fright, however might be common in many other cases) Overlast of the hypothalamic/amygdalic/brainstem structures responsible for stress reaction with probable weakening of deep nuclei controls over the posture and muscle contraction.

Conclusion.

So, as you see, the tremor is rather a pathophysiological reaction when it appears as response to stress, a side-effect manifestation due to acute temporal increase in adrenaline concentration in blood. Funny enough, but exactly this tremor is referenced to as "physiological tremor" in medical literature, because this type of tremor is not indicative for any CNS or endocrine disorder, that is very common for other types of tremor (postural, intentional etc.).


Neuron activity on body parts measurable?

To measure single-unit neuron activity you need to use a microelectrode system, but it is very invasive. How useful the information collected depends on what you searching for. If you interest in studying the neurophysiology of neurons its good way to go. If on the other hand, you are interested actual outcomes stimulation then the average neural response is actually more useful.

Computational work often uses these neural averages as 'the' signal. In the end synchronicity of neurons working together is what really matters in achieving higher order functions.

A good book I have found  " Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems " by Dayan P., Abbott, LF., (2005)
really insightful into how brain activity is measured and analyzed. Prior knowledge in Calculus and Statistics will greatly help make sense of the math, but even without it is enlightening.


Your image comes from the wiki page Aneurysm. The figure legend on the wiki page identifies it as:

  Angiography of an aneurysm in a cerebral artery

I am not an MD so I chose to first dig up a similar appearing cerebral angiography with the aneurysm identified (dark protruding spot indicated by the arrow):

Source: WestJEM, UC Irvine

Taking into account the normal vasculature as seen on this graph from UC Irvine, and given the similarity between the identified aneurysm in this angiopgraph and your wiki angiograph, I tentatively have identified the red-encircled structure in your original image as an aneurysm:


Looking for raw cell videos from a light microscope

The website you want is The Cell: An Image Library. They also have movies. A quick search of 'Homo sapiens tumor' revealed several Creative Commons videos of tumor cells moving around in vitro with attribution and no annotation or anything else. Sometimes the site can be a bit buggy, but it's a pretty awesome resource when it works.


When streaking microbes on a plate to test growth after uv exposure, does how I streak make a difference?

I work with e. coli myself though I do not know if your special strain has anything drastically different than my own so I'll just give advice that I've gotten from post docs and other PhDs on how to handle cultures.

(Note: This is methodology that I can't really find a "source" for so take with a grain of salt and change for your needs)

Typically when streaking I try to ensure that I make the streaks light enough so there aren't colonies within vicinity of each other. It's hard to really give a quantitative answer on how to do this so you will have to experiment on your own so your streaks aren't laden with massive amounts of colonies next to one another. It should look like consecutive "beads" on a string. This is generally what I try to accomplish with my colonies. Keep in mind I am focused on cloning plasmids so I'm not really concerned about experimenting on the e. coli themselves, just getting individual populations that do not have mixed variations of my plasmid. This is why having colonies with good separation is important for my particular project.

As for making sure they are all being affected by the UVC, I'm not entirely sure if having them to heavily grouped together would "shield" from UV. I feel as though UV can easily penetrate through e. coli colonies but I guess its not out of the question. Best bet is to keep your colonies well spread out, enough so you can pickup a single colony with a pipette tip and nothing else. This will make any genetic experiments you may want to do a lot easier as well. Which I think would be interesting if you are interested in the mutations occurring.

Is there something about your project that requires you to streak these out on agar plates? I saw comments suggest liquid broth. Maybe that's easier to do to make sure everything is exposed and then streak them out on a plate to see growth and/or test for mutations.


What is the difference between Amino acids from blood and urine?

Detecting protein and elevated levels of amino acids in the urine is generally a bad thing and is usually indicative of an underlying disease.

Kidneys are supposed to filter out waste products and retain metabolites that your body needs. There are many possible diseases that can cause amino acids to be detected in the urine, some as innocuous as overexertion or exposure to temperature extremes, and some as serious as Hodgkin's lymphoma, Amyloidosis, Malaria, Lupus, etc. For a more complete list see this Mayo Clinic page.

As for the blood, there are certain normal levels of amino acids found naturally in the blood. The reason for testing these levels is that certain imbalances can be indicative of different medical conditions. A doctor can use these levels to help to identify a problem that may not be noticed or may use it to diagnose a disease that you are seeking treatment for. This MedlinePlus page, has information.

Testing of Blood and Urine amino acids can and will be done in conjunction with one another in order to help narrow down the possible diagnoses that are likely.

Disclaimer: Personal medical questions and health advice are off-topic on Biology SE. We cannot safely answer questions for your specific situation and you should always consult a doctor for medical advice.

Edit to address comments

"Also, based on your answer and the Mayo Clinic link, what I understand is in a healthy individual - testing amino acids from urine might give false positives?"

I think that your concept of false positive here is incorrect. A false positive for this test would be indicating higher levels of amino acid in a sample than the sensitivity and standard error for the test would allow for.

That there is a laundry list of reasons why one might find abnormal levels of amino acids only goes to the fact that the kidneys "see" the results of several metabolic processes (normal or abnormal) and urinalysis is only a single datapoint from a spectrum of data for a clinician to begin to recognize a pattern and formulate a diagnosis.

As for greater accuracy, when comparing "Urine Random" to "Urine 24 hour" I would say that the "Urine 24 hour" test is more accurate strictly from a perspective of statistics. The larger the sample size for any test, the greater the level of confidence that the results observed are not due to random chance, error, or outliers in the data.

But this is the same concept for a political poll, marketing research analysis, or medicine; larger sample size gives you a clearer picture, but it does so at an increased cost. So the single screen is there just to look for issues, possibly based on a complaint that brought you into the doctor's office, or a way of monitoring a previously diagnosed condition and/or treatment, while the time courses are done to provide a clearer understanding of what is representative for the levels in that individual.

The single test has a number of reasons why it might be anomalous. Maybe the elevator from the underground parking garage was out of order and you had to walk up several flights of stairs to the office where they were collecting the sample, so it would show an elevated result due to exertion. Or maybe your drank a liter of water before the exam and your urine is dilute, causing a false negative. So to mitigate those anomalies, you run the time course, but usually only if there is a problem suspected because of the fact that it is an increased and unnecessary cost if all other indications are that the person is healthy or the result is easily explainable due to other data collected.

"I also understand that at times they would be used in conjunction - which seems logical. What I am trying to understand is which would give more accurate 'picture'. If one is not more accurate than the other, then what would be the difference between the 'picture' acquired from a blood test and the urine test."

Each test has its own parameters and give you an independent picture, that can be used to put together a more complete whole. Their accuracy will be based on their own sensitivities and built in standard errors and one will not be more accurate than the other because comparing free amino acids in the blood versus in the urine are two different pictures with different normal outcomes.

More samples, i.e. "Urine 24 Hours" or multiple blood draws over a time course is really the only way that you will improve on the accuracy of the individual tests, for the reasons I gave above.

They also have different baselines. Blood you expect to find free amino acids and there are ranges of normal results that you would expect to find in the blood. Here, too much or too little amino acid would be an indicator of a possible problem. For urine on the other hand, one would not expect to see elevated levels of amino acids, so here, a test that indicates elevated levels of amino acids indicates that more follow up is needed.

Think of it in terms of an analogy about astronomical observation. The electromagnetic spectrum is far broader than any one instrument can detect, so astronomers/astrophysicists use different sensors; visible light, radio waves, infrared, x-ray, etc. telescopes to detect many of these different pieces of data coming from the same object to gain a better understanding of what they are studying as a whole. Each gives slightly (or very) different views of the object, all of which contribute to a more complete picture of the object as a whole.


Impact of Alan Turing's approach to morphogenesis

This is a very interesting question. Many people have researched this topic, and many still are. But regardless, I had never heard of Alan Turing's contributions, so thank you!

First of all, I cannot actually find who first coined the term morphogen. Though people had hypothesized that chemicals could play a critical role in development through much of the 20th century, I cannot actually find the first person to use morphogen. But the most important paper really came from a guy named Lewis Wolpert, who came up with the model of a gradient of morphogens leading to differential cell fates. The idea being that if some area of an embryo produces a morphogen at a very high concentration, then as you move away from that area, the concentration goes down. So if this morphogen is required at or above a certain threshold for activity, then only those cells with that concentration will have a certain cell fate, while at lower concentrations, the cells can become something different.

But this does not really answer your question. You are asking how a single cell, which is spherically symmetrical, can determine a particular axis. Though most organisms do this is in slightly different ways, the most common feature is that sperm entry point breaks the symmetry. The best way to explain this is to show you a diagram of Xenopus (frog) eggs.

Image from: http://studentreader.com/nieuwkoop-center/

The Xenopus egg, first of all, is inherently not spherically symmetrical. There is a black animal pole, and a white vegetal pole. The sperm can only enter a marrow region of the egg about 30˚ north of the animal/vegetal line. Upon fertilization, an event occurs where the pigmented areas turn toward the sperm entry point, leaving a gray crescent. Nearby the gray crescent, in the vegetal pole, a structure called the organiser develops. This organiser creates many of the morphogens that then pattern the rest of the embryo.

Researchers have studied this a lot in many different organisms, but a few things really remain constant: eggs are not exactly spherically symmetrical, and the sperm entry point provides asymmetry.


How protein denaturation affects digestion?

This article specifically looks at the question you're asking.  Just jump down to the conclusion if it's too technical.

To summarize, cooking the egg (or heat pre-treatment as they call it in the paper) leads to a significant increase in protein uptake.

I'd call that myth busted via radiolabeling.


What is the difference between a spore and a cyst?

The bacterial spores you are referring to are called endospores. The spore is formed during unfavorable conditions, by duplication of the bacterial chromosomes, and consequent envelopment by various membranes and protective coatings (while still within the original cell). The spore is dormant and remains so as the outer cell degrades during harsh conditions, releasing the spore. I guess I'd call the spore a clone of the original?

You may enjoy reading the relevant sections in this book, which go into greater detail.

edit: as Souvik has pointed out, this is only one type of "protective" spore. Actinomycetes also form spores, via differentiation of the cells, and cyanobacteria form akinetes also via differentiation (but this structure is not as durable as endospores).

Information about cyst formation is difficult to find, but in bacteria it appears to develop via changes in cell wall composition.


Do any terrestrial herbivores use auditory crypsis for predator avoidance?

Does soundproofing count?

Most predators locate prey using visual or olfactory cues; the only predators I can think of that use auditory cues are nocturnal ones - owls and bats. Bats, of course, use echolocation, so even completely silent prey are still detectable. It has been suggested that the soft, fur-like body coverings of some owlet moths (Noctuidae) and tiger moths (within the Arctiinae) help hide them from echolocating predators by passively absorbing sound, although subsequent studies have suggested that they may instead be mimicking the acoustic signature of unpalatable prey.

(public domain image: source)

I have a suspicion this isn't what you meant by 'land-dwelling herbivore', but insects are people too...

Edit: just discovered this paper from May that provides evidence supporting the hypothesis that the twisted tails of luna moths (Actias luna) disrupt tracking by echolocating bats.

Image owned by Shawn Hanrahan, licensed under CC BY-SA 2.5


Are all cone cells connected directly to the brain?

No.  Cones connect to ganglial cells.

Let's explore the numbers.  Our eyes contain about 6 million cone cells, 90 million rods, and comparative handfuls of additional photosensitive cells (ipRGC's) that don't play a role in vision.

The optic nerve is a bundle of roughly 1 million fibers (perhaps up to about 1.7 million).  So by just running the numbers, it doesn't fit.

I was wondering if the human optical system features something similar.   Does the eye compress, encode or time-multiplex the image "pixels" it captures before sending the information to the brain?

Let's focus on photopic vision (color vision, which happens when lighting conditions are sufficient).

Our perception of color starts not with the cones, but with ganglial cells in the retina.  This is different than how an RGB camera works; our brains don't process color in terms of "pure cone signals".  Instead, color is processed in three channels; a "red-green" channel that measures the difference between L cones and M cones;  a "yellow-blue" channel that adds input of L and M cones and subtracts out contributions from S, and a "brightness" channel that computes the sum of all cones.  This is referred to as opponent processes.  Maybe we can call this encoding.

In addition to this, there are ganglial cells in our retina that contribute to edge detection.  These cells work similarly to ganglial cells that perform difference measurements for opponent processes, only they connect to the same cone types.  Since ganglial cells connect locally, if there's a large difference between stimulation of two cones next to each other, it's an indication that there's an image of an edge of something projected onto that spot.  If we can't distinguish individual cones, but these things can distinguish edges which to us are the more interesting property, maybe we can call this lossy compression.

Outside of this, a huge amount of our brain is devoted to visual perception.  There are some really strange quirks about our eyes; most popular is the existence of the blind spot.  Additionally, our 90 million rods are squeezed more into peripheral vision, leading to fuzzier imaging in photopic conditions the farther away we are from the fovea.  Furthermore, chromatic aberration can be quite a pain, but L and M cone sensitivities are very close to each other.  So where absolute sharpness matters, we have less S cones around; in fact, in our foveola, there's nothing but L and M cones.  Our brain makes up for this, by stimulating us to move our eyes constantly and rapidly (saccades).  As we do so, the visual cortex goes into overdrive, filling in that blind spot, crisping up that periphery a bit, painting in an illusory blue in our center vision, etc.  Though this involves "moving the camera around", we could maybe call this a sophisticated, high level form of time multiplexing.

Much of this information is available from wikipedia articles, though you might need to know what to look for; so here's a starting guide:

Cone_cell for cone cell counts
Fovea_centralis for cone density in center in vision, with picture
Optic_nerve for count of optic nerve bundle fibers
Opponent_process for opponent process theory
Receptive_field contains discussion of edge detection


Multiple transcripts matching same gene in de novo assembled RNA-seq data, but FPKM values vary?

If the quantification is done at the transcript level, each identified transcript of a given gene will have a different number of reads attributed to it, hence a different RPKM value.

For the subsequent analysis, you can continue at the transcript level.

I think you cannot sum the FPKM values directly, because they are inversely proportional to the transcript lengths ("K" stands for "by kilobase"). If you want to do the subsequent analysis at the gene level and use FPKM values, you would have to multiply the FPKM values of the transcripts by the corresponding transcript lengths before summing. Then you will have to divide this sum by the gene length, or something like that.


Salt water may have anti-septic properties due to the effect it has on water potential.  Pure water has a water potential (Ψ) of zero.  A concentrated salt solution has a lower (more-negative) water potential.  The water potential of the salt solution is likely to be more negative than that of the pathogen's cytoplasm; the salt solution is therefore referred to as hypertonic.  Therefore water osmoses out of the cell (osmosis being the net movement of water from a higher water potential to a lower water potential across a semi-permeable membrane).  The loss of water from the pathogenic cells causes osmotic crenation - the cell becomes shrivelled and dies.

A hypotonic solution (for example cells placed into pure water) would cause the opposite effect - osmotic lysis.  This is the bursting of the cell due to the movement of water into the cell.  The bacterial cell wall would first have to be damaged (e.g. by penicillin).  This would not be the process by which a salt solution has effect, however.

The fact that the salt water is warm in order to improve solubility may also have the side-effect of causing vasodilation around the infection, increasing the rate at which white blood cells can arrive at the infection site.

It has been more difficult to find a theory as to why a salt solution would have analgesic properties, see the comments below & previous versions of this answer.


Why are bovines different genera if they can interbreed?

Species are not defined by whether they can interbreed, not even close.

In fact, there is no objective, scientific standard for what defines species, or genera, at all. What is a species is determined by little more than the "feels" of the individual naming it, or the committee approving it.

And the same is true of the entire rest of taxonomic structure. It's not really science, it's just a way of organizing ideas that got popular, and in fact is under constant assault now by somewhat more scientific things like genetic testing. The hierarchy of the taxonomic system changes pretty much daily, and has no official structure or definition at all. Even the number of kingdoms is entirely up in the air.

Getting back to the specifics here, since there is no objective, scientific standard for what is a species or genus, it's no surprise that separate ones can interbreed.

And it's not like bovines are the only ones. There are many other intergeneric hybrids possible, like sheep and goats, wheat and rye, camels and llama, house cats and servals, marine and land iguanas, et cetera.

Perhaps someday there will be objective definitions to establish a truly scientific taxonomy. But for the moment, it's just whatever people in positions of power feel makes sense, at any given moment.

List of Intergeneric hybrids


What are some atypical examples of positive transcriptional cooperativity?

Positive co-operativity without feedback from the downstream genes:

I guess Polycomb/Trithorax complexes will fit this criterion nicely.

Polycomb group (PcG) represses Hox and other differentiation related genes (such as neurogenin) while Trithorax (TrxG) group promotes their expression. They are not like usual transcription factors that bind to promoters and recruit/exclude RNA-polymerase; they bind at regions called Polycomb Response Elements/Trithorax Response Elements and mediate epigenetic regulation of nearby genes by histone modifications (primarily methylation).

PcG froms two main complexes PRC1 (Polycomb Repressive Complex-1) and PRC2. Different components of the complex have different molecular functions. For e.g SuZ has a Zinc finger domain and can bind to DNA/RNA, Ezh has histone methyltransferase activity etc.

This is an old review but is still quite informative.


What are the bare minimum nutrients required to survive as a human?

Essential nutrients include (NutrientsReview):

Water
9 amino acids: histidine, isoleucine, leucine, lysine, methionine,
phenylalanine, tryptophan, threonine, valine
2 fatty acids (alpha linolenic and linoleic acid)
Vitamins: A, B1, B2, B3, B5, B6, folic acid, biotin, B12, C,
D, E and K (and choline, which is considered a vitamin-like substance)
Minerals: calcium, chromium, chloride, copper, iodine, iron,
manganese, molybdenum, phosphorus, potassium, selenium, sodium, zinc

The "bare minimum" intakes of most nutrients needed for survival are not known, because they could be determined only by studies in which participants would be given various low amounts of nutrients and observed for how long they can survive. The following are estimations of the lowest intakes of some nutrients needed to remain healthy.. Note, that this are not "recommended" or "optimal" intakes.

Protein = 35 grams per day (Metabolic Basis of Obesity)

Fat = 20% of total calorie intake, that is 44 g per day in a 2,000 Calorie diet (PubMed, 2017)

Carbohydrates = zero (National Academic Press)

Only 2 fatty acids and 9 amino acids are essential, so theoretically, you could consume only those and would be fine. In foods, these acids usually do not appear individually but as part of fats and proteins, so the recommendation is given for fats and proteins - if you meet that, you will likely consume enough of the essential acids. Theoretically, you can survive without consuming any carbohydrates, because all of them you need can be synthesized in your body. People have survived and remained healthy without consuming carbohydrates for a year or more (National Academic Press).

Sodium = 200 mg per day (Recommended Dietary Allowances: 10th Edition)

Water = 1 liter per day (only in ideal circumstances with minimal sweating; in the table, water requirement = "net water loss") (National Academic Press)

Here's a table with dietary reference intakes for vitamins, minerals, carbohydrates, fats (and separately for the 2 essential fatty acids), proteins and water (Nationalacademics.org), which should be sufficient for most individuals in a given sex/age group to remain healthy long-term. These amounts can be considerably greater than what is needed just for survival.

In Recommended Dietary Allowances: 10th Edition, in the Table 6-1, there are "estimates of amino acid requirements" for all 9 essential amino acids.

There was a man who was fasting for more than a year, drinking only water and getting potassium supplements, and the concentrations of most nutrients in his blood remained normal and he had no health issues (Postgraduate Medical Journal, 1973). This shows how difficult is to find "bare minimal" amounts of nutrients.

Yes, it is possible to make a "pill" with only essential nutrients in required amounts included. Such products already exist, but I don't want to promote them, because there is no evidence of their long-term health benefits and safety.


What happens during the fermentation process of the eco-enzyme?

The recipe is using yeast to convert the sugar into alcohol (ethanol). All of the proposed cleaning effect is from the dilute alcohol (and also some vinegar).  The citrus peel provides some aromatic oils. There may be low levels of some particularly hardy enzymes released from the rotting fruit and dying microbes, but it is difficult to imagine that any of those proteins have any effect on removing dirt from clothes, dishes, or surfaces. The solution is also acidic from the fermentation and the dissolved CO2 gas--just like if you used grape pulp and skins you would make a primitive wine with this recipe, and that wine would then turn into vinegar (acetic acid, HOAc).  Mixing some vinegar and alcohol would give you the same cleanser.

The enzyme concentration should be similar to the amount of active enzymes present in homemade beer or wine--would you use either of those for cleaning?


A study found that the hepatitis C virus can live on surfaces for six weeks. Did they end the study before the seventh week began?

The place to find this information would be the Methods section of the paper.

  We spotted 33 µL of plasma spiked with HCVcc on the 24-well plates. They were either immediately tested for viable virus or stored at 4°C, 22°C, and 37°C for up to 6 weeks before testing.

They tested their samples for (up to) 6 weeks. At the time of the 6th week they still found infectious virus. They did not test samples beyond 6 weeks so they can't say anything about infection past that time.


Theoretically...

93 million bp/cell x 650 daltons/bp x 10^13 cells/body x 1.66 * 10^-27 kg/dalton = 0.001 kg

So I would say it's not too much of a difference :P

however this ignores the rest of the chromosomal material: histones


(A little too long for a comment, and maybe useful)

Assuming that a is supposed to represent the degree of a node, and
using the formulas from Wikipedia for the Pareto distribution, I have

mean (which I'm assuming is <a>)  =  gamma*epsilon/(gamma-1)

and
variance (equal to <a^2>-<a>^2, or <a^2>= mean^2  + var) = epsilon^2*gamma/((gamma-1)^2*(gamma-2))

Translating into R code (rather than doing the algebra):

pmean <- function(gamma=2.8,epsilon=0.001) {
    gamma*epsilon/(gamma-1)
}
pvar <- function(gamma=2.8,epsilon=0.001) {
    epsilon^2*gamma/((gamma-1)^2*(gamma-2))
}
prms <- function(gamma=2.8,epsilon=0.001) {
    sqrt(pvar(gamma=gamma,epsilon=epsilon)+ pmean(gamma=gamma,epsilon=epsilon)^2)
}

When I use the value of gamma=2.1 in the figure caption and feed it into equation (4):

2*pmean(gamma=2.1)/(pmean(gamma=2.1)+prms(gamma=2.1))

I get 0.588 (still not right, but closer ... ??)


How does the digestive system determine what to absorb [as nutrients] into the bloodstream?

Does the digestive system attempt to digest everything and from everything it receives and how it determines what is nutritious?

Human digestive system is genetically determined and can digest only those substances for which it has digestive enzymes and absorb only those that can be absorbed through the specific "channels" in the intestinal lining.

Human digestive system can absorb nutrients "from everything" (not literally, though), for example, sugar from raw sugar cane.

Before absorption, complex nutrients (starch, sucrose, lactose, proteins and triglycerides), need to be broken down by the digestive enzymes into simpler nutrients, but some nutrients need no digestion before absorption. The following nutrients can be absorbed in the small intestine:

Water
Monosaccharides: glucose, fructose, galactose...
Fatty acids
Cholesterol
Amino acids
Minerals: calcium, potassium...
Vitamins
Polyphenols, plant sterols and stanols and various other plant-derived nutrients
Sugar alcohols: erythritol, glycerol
Alcohol

Nutrients that are not absorbed in the small intestine:

Sugar alcohols: isomalt, lactitol, maltitol, mannitol, sorbitol, xylitol
Oligosaccharides: raffinose, fructooligosaccharides, etc.
Certain polysaccharides (soluble fiber): beta-glucan, guar gum, etc.

These nutrients travel to the large intestine, where they are broken down (fermented) by normal intestinal bacteria into absorbable nutrients, mainly short-chain fatty acids (SCFAs), and gases.

Can "particles" (e.g., microscopic dirt) pass through to the bloodstream if they are small enough to be absorbed?

There is a countless list of substances that are not nutrients but can be absorbed:

Medicines and other drugs
Certain food additives (preservatives, dyes...)
Toxins (methanol, cyanide...)
Various random substances ("dirt")

And there is another countless list of substances that cannot be absorbed, for example, insoluble fiber, such as cellulose, and certain artificial sweeteners, such as aspartame and steviol glycosides from stevia.

Sources:

Absorption (Nutrients Review)
Chemical Digestion and Absorption: A Closer Look (Lumen Learning)


How do I compare the variance of a distribution of species in one area versus another?

These are just some preliminary ideas...

I think you should look at the seasonal distributions separately, since the bimodal distribution is the outcome of two fairly separate processes. The two distributions might also be controlled by different mechanisms, so that e.g. winter distributions might be more sensitive to yearly climate. If you want to look at population differences and reasons for these I think it is therefore more useful to study seasonal distributions separately. An exploratory analysis could be to compare distribution percentiles (north/south and east/west coordinates) to look at range edges, or to use a fixed number of edge observations to establish borders. The weighted centre-point of population distributions can be used to look for differences in overall position. If you have grid occurences, percentage overlap between species/populations could maybe also be useful.

If you haven't already, you look also look at Maxent, which is a widely used software for modelling species distributions and habitats. Look at Elith et al. (2011) for an overview. If you want to look at changes over time (even if this doesn't seem to be your main point) you should also check out dynamic occupancy models that use occurrence records to model species distribution while taking detectability into account, e.g. MacKenzie et al. (2009).

As for a simple test for differences in variance (basically a test of homoscedasticity), there is Levine's test, which is used to compare variances of distributions between groups. Bartlett's test is an alternative, but Levene's test is supposed to be more robust to non-normality. In R the Levene's and Bartlett's tests are found in library(car). However, these are only suitable for unimodal distributions so, again, you should look at seasons independently.


Can oral baking soda effect tumor cells in mice

What can oral baking soda do?
If your question is (which I don't think it is):

Does baking soda cure cancer?

The answer is that there is no support for that statement.
If your question is:

Can oral bicarbonate alter the pH of tumors in a mouse model?

The answer is yes.
This effect has been observed in this mouse model and replicated many times
This is an effect that has a been used for a while, and was first demonstrated in this 1999 article in the British Journal of Cancer.  The addition of bicarbonate increases the buffering capacity in the live animal model, preventing the acidification of the tumor. It does not increase the pH of other tissues.
How does this work?
The idea here is not that adding a base increases blood or tissue pH directly, but it increases the amount of a physiologic buffer in a situation where that buffer has been depleted or is insufficient, allowing a better response to a pathologic excess of acid. Your question suggests you believe that an oral acid or base load will not change the pH of body tissues. This is true in normal physiology because there is a robust system of buffers. The primary extracellular buffer actually is bicarbonate. However, in diseased states, the buffer may become depleted or be insufficient. Oral (as well as intravenous) bicarbonate therapy is used in humans in several disease states, including certain forms of metabolic acidosis (Cecil Medicine, Ch 63, 120) and kidney disease (Ch 124, 128, 132). What is happening in these cases, and in the mouse model, is not a change in pH from the normal set point, but an increase in buffering capacity that allows the pH to return to the normal set point.
I would caution, though, that just because oral treatment is used in certain specific forms of acid base pathology, however, does not mean that there is support for the various forms of quackery that use arguments about flushing acids from your body, or using alkaline water as a general health tonic. It does address the question about whether it is very strange that orally administered buffer would impact a tissue with excess acid. It's not (strange).
The effect of changing the pH in the tumor microenvironment
The effect in the study behind the article you referenced, as well as others, is an increased sensitivity to cancer chemotherapy in otherwise resistant tumors. This is not horribly surprising, and doesn't mean by any stretch that baking soda cures cancer or that, e.g., an acidic diet causes cancer.  Other studies, including this one (also in this very particular mouse model), show decreased invasion and metastases, also presumably because of the increased buffering capacity (and decreased acidifcation of the tumor and tumor microenvironments), so there may be other possible effects.
There has been a good deal of interest since 1999 in human studies adding bicarbonate to other treatments, but none have been published that I'm aware of, though I haven't checked the clinical trial registry.
EDIT:
On checking the clinical trial registry, on first glance it looks like some safety and tolerability studies have been completed, but it would take a fair amount to do a full analysis of what has been done and what hasn't. Maybe someone else wants to do it and include it in an answer? I'm fairly certain I would have seen and remembered an article showing that bicarbonate cures cancer in humans, though, so I don't think that's on the list :)


The phenotype ratio would be 4:0.

You did not include the complete example including the genotypes, but an example that might produce this result is:

P is a dominant allele that produces purple flowers, and pp homozygotes are white.

    P    p
  -----------
P | PP | Pp |
  -----------
P | PP | Pp |
  -----------

The genotype ratio is 2:2:0 (2 PP : 2 Pp : 0 pp) meaning there are 50% PP and 50% Pp.

The phenotype ratio is 4:0 (4 purple : 0 white) meaning there are 100% purple and 0% white flowers.

To keep things simple, you do not need to reduce the ratio to the lowest terms (in other words, the sum of the numbers in the ratio should equal the number of boxes in the Punnett Square). It would not, however, be incorrect to reduce the genotype ratio to 1:1:0 and the phenotype ratio to 1:0.