Why is too much glucose harmful? I learned the citric acid cycle in biotechnology school and how cells work; about ADP and ATP and how the Cellular respiration (C6H12O6 + 6O2 -> 6CO2+6H2O) works.

I am interested in understanding why exactly too much glucose is harmful, e.g. when having diabetes.

What happens inside the cells so that the organs get damaged over time? Why can't the cells not simply "ignore" the needless glucose or convert it into energy?

High intracellular glucose.

Affects: all cells that do not depend on insulin to take in glucose. Examples: neurons [1], kidney cells, retina cells.

Causes: high extracellular glucose (in most cases hyperglycemia)

Effects: promoting necrotic cell death through $H_2O_2$ (peroxide) formation, which may participate in the development of diabetic vasculopathies and associated disease [2].

High extracellular glucose.

Affects: extracellular matrix, cardiac muscle

Causes: lack of / low levels of insulin, insulin resistance

Effects: enhances collagen production thus affecting kidney by thickening glomerular basal membrane [3, 4]. It promotes cardiomyocyte metabolic stress and altered glucose handling [5]. It is also a potential mechanism involved in cardiac glycogen accumulation [5].

Diabetes mellitus involves:

high extracellular glucose, leading to:
high intracellular glucose in cells that do not depend on insulin to uptake glucose;
low intracellular glucose in cells that depend on insulin (muscle and fat tissue).

References:

David R. Tomlinson and Natalie J. Gardiner. Glucose neurotoxicity (2008). Available from http://didattica.uniroma2.it/assets/uploads/corsi/140868/Glucose_Neurotoxicity_-NATURE_Reviews-Neuro,_Jan_2008.pdf (accessed 27.07.2014)
RnCeus.com. Glucose Homeostasis (2012). Available from http://www.rnceus.com/dmeds/glucose.html (accessed 27.07.2014)
Takeuchi A, Throckmorton DC, Brogden AP, Yoshizawa N, Rasmussen H, Kashgarian M. Periodic high extracellular glucose enhances production of collagens III and IV by mesangial cells. Am. J. Physiol. 1995 Jan;268(1 Pt 2):F13-9. PubMed PMID: 7840239.
Ayo SH, Radnik RA, Garoni JA, Glass WF, Kreisberg JI. High glucose causes an increase in extracellular matrix proteins in cultured mesangial cells. Am. J. Pathol. 1990 Jun;136(6):1339-48. PubMed PMID: 2356864.
Kimberley M. Mellor , Upasna Varma , David I. Stapleton , Lea M. D. Delbridge. Cardiomyocyte glycophagy is regulated by insulin and exposure to high extracellular glucose. American Journal of Physiology - Heart and Circulatory PhysiologyPublished 15 April 2014Vol. 306no. H1240-H1245DOI: 10.1152/ajpheart.00059.2014


Is the basic reproduction number unique? Given any epidemic model of an infectious disease, there are various ways of computing a basic reproduction number($R_0$) such as;  the next-generation method, survival function, largest eigenvalue of the Jacobian matrix and so on.

My question is,

  Do we get the same $R_0$ for the same model but using different methods of computing $R_0$?

If we don't(if $R_0$  is unique) what is the explanation?
Are we allowed to use "this" different $R_0$ in writing a paper?

It should be noted that many of the methods you talk about aren't necessarily for getting a number but rather a formula for $R_0$, all of which should be equivalent.

However, when those methods step into the realm of getting a number by fitting parameters, they may give different results as they handle certain aspects of the data differently.

You are certainly "allowed" to use any formulation of $R_0$ you want - just document what you did.


How did life survive in the Snowball Earth theory? There is this theory that says that the whole Earth was once covered with snow and ice. How was it possible for life to survive this extreme state?

First, the "snowball earth", despite favoured by many scientists, is not a theory in the scientific meaning of the term, but a hypothesis, because it is not widely accepted: https://en.wikipedia.org/wiki/Snowball_Earth#Scientific_dispute. Some models show sea ice at the equator, while some more sophisticated climatic models failed to form sea ice to the equator.

But let's talk about the most famous "snowball earth" event, the Huronian Glaciation. It happened just after the "Great Oxygenation Event": the massive amounts of oxygen (O2) released in the atmosphere decreased methane concentration, and temperatures plummeted. It's supposed that Earth's surface became entirely or nearly entirely frozen.

  How was it possible for life to survive this extreme state?

It's worth mentioning that, by that time (2 and half billion years ago), there were only unicellular organisms (and probably no eukaryotes, just bacteria). There were no pluricelular organisms nor life on land (outside water). Thus, having in mind that there were still a lot of liquid water (under the ice), it's easy to see those bacteria surviving. Sure, many species have become extinct, but not all life forms were threatened.

About the Huronian glaciation:

http://link.springer.com/referenceworkentry/10.1007%2F978-3-642-11274-4_742
http://www.sciencedirect.com/science/article/pii/S1674987113000297


Dynamic of the number of cells over time as the embryo grows I would like to investigate the dynamic of the number of cells over time as the embryo grows. I am interested in any multicellular animal species for which we can have some data. How does the number of cells change over time in an embryo?

I welcome any graphs, empirical data and/or mathematical expression for this dynamics.

A starting point could be this very recent amazing movies and the corresponding research article published yesterday.

This is not my field of expertise, but I think you will find relevant information in the references cited by this article.


What is the difference between average and monoisotopic mass calculations of peptides? I often have to calculate the mass of peptide sequences using calculators such as here.

I have the option of calculating the average and monoisotopic mass, but what is the difference?

The elements that typically make up peptides and proteins can be present in different isotopes. For example, carbon is present to 98.9% as $\ce{^12C}$, and to 1.1% as $\ce{^13C}$.

The monoisotopic mass assumes that every element is present in the most abundant isotope, the average mass uses the actual distribution of the isotopes in nature.

If you have sufficient resolution in your mass spectrum you can see multiple signals corresponding to different isotope compositions of your molecule.


Could a virus produce prions, leading to prion disease? Viruses can make cells produce proteins that are not a part of the new viruses themselves, but are used to help with replication. However in the case of rotavirus, one of these proteins (NSP4) is actually a toxin that causes diarrhoea. Prion diseases like Creutzfeldt–Jakob disease are caused by misfolded proteins that make normal versions of the protein also misfold, causing a chain reaction.

While this might not actually have been observed in real life, is there a biological basis for a virus containing genetic code for producing a prion, that after infecting an organism will cause the production of prions inside of infected cells (or perhaps proteins that cause the production of prions in the body), leading to a prion disease - in a similar way to how rotavirus causes the production the the NSP4 toxin? Since these prion diseases often have 100% fatality, would this mean a virus like the common cold could arise, that spreads quickly and non-fatally, but then triggers a fatal neurodegenerative disease in its victims by causing the production of prions in the host?

Perhaps not prions themselves, but viruses may possibly contain "pieces" or domains of proteins with prion-like chemical activity, which can catalyse refolding of prions from normal to disease state.

Mutation rates put limits on the size of RNA viruses. There is a higher cost for the average RNA virus to allot precious genomic space on encoding a normal protein that would take decades to be pathogenic, and which does not seem to help make copies of the virus.

Because DNA is a more stable molecule, and DNA polymerase has a higher fidelity rate than RNA polymerase, DNA viruses can have a larger genome. They could more easily carry code for encoding prion-like domains inside proteins.

There's a recent paper from George and Victor Tetz that looks for these so-called "prionogenic domains" (regions which encode portions of another protein that could potentially have prion-like behavior) in a catalog of viral genomes, and they find approximately three times more such domains in DNA viruses than in RNA viruses:

  We determined that more PrDs can be found in the DNA-viruses compared with their numbers in the RNA-viruses, and in the enveloped viruses, compared with that in the non-enveloped ones. This may be partially explained by the larger genome size and protein numbers in DNA-viruses.

While the domains themselves are usually part of proteins that are not themselves prions, infection could lead to expression of those proteins, which in turn provides the domain templates that invoke misfolding in the host of normal prions into pathogenic (disease-causing) prions:

  Some viruses may be implicated in the prion misfolding in humans since it was observed that the de novo appearance of prions can be facilitated by another PrD-containing protein

Also! There are retroviruses that have integrated themselves in our genome over millions of years. These are called "endogenous retroviruses" or ERVs, and have been called "junk DNA" by some biologists. However, some get expressed along with our normal genes:

  Although a large percentage of ERVs are replication-defective or are suppressed by host defense mechanisms, some ERVs can be expressed and replicated. The activation of an ERV gene can bring positive co-opted functions to the host, which may be evolutionarily maintained [13,20]. For instance, some ERV proteins may provide important functions during normal development; for example, human protein syncytine-1, which is an ERV Env protein, is involved in the formation of the syncytial layer in the placenta [30,31]. Moreover, the expression of Env proteins encoded by ERVs has been suggested to mediate host resistance to exogenous pathogens [32,33]. However, because of their analogy to exogenous retroviruses, the activation of certain ERVs has been frequently implicated in disease.

The authors observed that some people who develop Creutzfeldt–Jakob disease (CJD) have ERVs that get overexpressed:

  To evaluate the possible relationship between HERVs and human prion disease, we examined the retroviral sequences in cerebrospinal fluid (CSF) obtained from individuals with sporadic CJD. The frequencies of several HERV families, including HERV-W, HERV-L, FRD and ERV-9, were significantly increased in the CSF of individuals with sporadic CJD compared to the frequencies observed in normal control CSF. In addition, when compared to individuals with other neurodegenerative diseases that exhibit similar symptoms to CJD, such as dementia, the incidence rate of HERV-W and HERV-L were significantly higher in the CSF of sporadic CJD patients. Moreover, the frequency of increased HERV-W and HERV-L in the same samples was much higher in sporadic CJD than in either normal or other neurodegenerative diseases CSF samples, and there was no correlation between individual parameters, such as sex and age [61].

The cause may not be expression of proteins with PrD, but with the triggering of signaling pathways that lead to inflammation of tissues, which sets up conditions for normal prions to malform into disease-causing prions:

  According to these studies, ERV proteins may be closely implicated in the pathogenesis of inflammatory diseases, such as multiple sclerosis and rheumatoid arthritis (RA) [51,54,68]. In prion diseases, a correlation between the inflammatory process and neurodegeneration has been suggested because of the activation of large numbers of glial cells and the up-regulated expression of proinflammatory cytokines, which are pathological features of prion diseases [69,70].

Life is complicated.


Helix aspersa or Cornu aspersum The common garden snail was originally assigned as Helix aspersa and stayed that way for over 200 years. Recently, some biologists assigned it to the genus or subgenus Cornu renaming it to Cornu aspersum, yet other researchers assigned it to Cantareus. Still, many texts still use the name Helix aspersa.

My question is what is the correct or official binomial nomenclature (scientific name) of the garden snail as for 2019?

Remark: I read Wikipedia but even there there are inconsistencies about it. E.g. Wikispecies.

I consulted with Prof. Henk Mienis, the curator of the Israeli Mollusca Collection, and the valid name is Cornu aspersum. The Israeli subspecies is Cornu aspersum megalostomum.


Can compounds be predicted from Polyketide synthases gene clusters? I've seen a few talks on the subject. From a gene cluster, there is some decent ability to determine which domains contribute to certain functional groups in the final metabolites. It sounds like this is largely what Warp Drive Bio is trying to do. How realistic is this technology?

I would say that for type I polyketide synthases (PKS), this is possible. These proteins are variations on fatty acid synthases which have modules, each of which adds a two carbon unit as well as a chiral methyl group to an extending chain which may be reduced to give anything from a ketone, an alcohol to a completely reduced carbon chain.  In the illustration below you can see these 3 options, but double bonds are also possible.

Other sorts of PKS pathways (type II and III PKSs) have proteins which are harder to predict in terms of what they produce since a single protein does the extending of the polyketide chain to cyclize it, typically into an aromatic compound.  All this happens in a single protein site, so careful modelling would be required and I'd be suprised if this has been done accurately.

Note the last arrow there 'tailoring steps' - accompanying the PKS genes themselves are often a slew of acetyl and methyl transferases, additional reductases, coupling enzymes, even delivery proteins... the list goes on and on.  These steps would be hard to predict because the substrate for an o-methyl transferase isn't easily determined.

I think there are several companies trying to leverage 'best guess' bioinformatics here.  They are likely to get a good idea of the backbone, but maybe won't place every methyl and acetyl group correctly.

There are definitely people out there who think this could work to deliver diverse candidates to drug discovery.  see Radiant Genomics as well.


Impact of Alan Turing's approach to morphogenesis Shortly before his untimely passing, the computing pioneer Alan Turing published his most cited paper The Chemical Basis of Morphogenesis (1952).

The central question for Turing was: how does a spherically symmetric embryo develop into a non-spherically symmetric organism under the action of symmetry-preserving chemical diffusion of morphogens (as Turing calls them, an abstract term for arbitrary molecules relevant to development)? The insight that Turing made is that very small stochastic fluctuations in the chemical distribution can be amplified by diffusion to produce stable (i.e. not time varying except slow increases in intensity; although also potentially time-varying with 3 or more morphogens) patterns that break the spherical symmetry.

The theory is beautifully simple and abstract, and produces very important qualitative results (and also quantitative results through computer simulation, which unfortunately Turing did not get to fully explore). However, even in the definition Turing discusses some potential limitations such as ignoring mechanical factors, and the inability to explain preferences in handedness. The particular models he considers -- a cycle of discrete cells and a circular tissue -- do not seem particularly relevant. As far as I understand, the key feature is his observation of symmetry breaking through small stochastic noise and instability.

What was the most important contribution of Turing's paper to developmental biology? Is his approach still used, or has the field moved on to other models? If his approach is used, how was the handedness problem resolved?

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.


Why sigmoid curves appear in quantitative analysis of many biological phenomena? I know two examples:

1-The binding of hemoglobin to oxygen (binding of oxygen to one site of hemoglobin induces conformational changes which increase the affinity of the other sites for oxygen - the curve could be interpreted as transition from a low affinity T sate to a high affinity R state). The plot can be seen here

2-The denaturation of DNA by temperature (when one segment of the double helix opens, base stacking is disrupted, making the denaturation of the rest of the molecule easier); Another plot

The two examples I gave were actually of positive cooperative phenomena, that is, the occurence of a first event favours the next events. There is also the titration curve, which is a sigmoid, but I don't think it's correlated.
I'm asking that because I found it amazing that the same sort of curve appeared in the study of such different subjects.
Are these examples somehow correlated, that is, for which sort of phenomena sigmoid curves are expected?

I would suggest following: take any one-dimensional process that is described by gaussian function. If you integrate such process along variable, you will get a sigmoidal curve. For details see normal and cumulative distribution.

Now, the question is: how many biological processes are described/modeled by Gaussian distribution and dependencies? A lot!

Let's take a look at dinosaur growth from Revisiting the Estimation of Dinosaur Growth Rates

This figure describes how size of dinosaur changes with some time (model, I assume). Remember link between gaussian and sigmoidal functions? If you differentiate, that is find how fast aforementioned sigmoidal function changes, you will get gaussian bell-curve! Which tells you: dinosaur grows faster during middle age, and slower before and after that.

DNA denaturation curve is sigmoidal because efficiency of denaturation is again gaussian. At low temperatures very limited amount of molecules will denature, but at high temperature there are no more molecules to denaturate left, so the bell-curve. Anothe explanation goes like that: at low temperature additional heat doesn't change much because it is still too "cold", at higher temperature same amount of heat is just a drop in a bucket, barely noticeable.


Does a man contain all the genes needed to make a woman? This question is brought on by a Sci Fi novel I am thinking about writing. The plot device involves a colonist in charge of building a population on a new planet who loses his supply of embryos and so forth in the landing. With the artificial "wombs" intact, he populates the planet with clones of himself.

If he wanted to introduce enough variation (without making up new genes, only rearranging) in the population to allow them to be able to reproduce naturally without inbreeding problems, would he be able to? In particular, could he make a woman?
Alternately, could a woman (without a Y chromosome) do the the inverse?

At the risk of introducing bias into the answers, the plot as it stands assumes he is a male and he CAN'T do any of the above and he is restricted to clones.

This answer also involves some speculations as the question is about a good theoretical framework for a science fiction.

You can find in this post about how sperm can be used to produce embryonic stem cells. It would still require an oocyte for doing that.

The question now is- Can you produce oocytes from a male?

You may fuse two X bearing haploid spermatids to form a diploid cell with XX. This cell will also have mitochondria and ribosomes — seems like a decent candidate. Gametogenesis has not been shown to happen in-vitro. Moreover a zygote will need a lot more cytoplasmic resources that you can get from a fused spermatid.

Plus there are imprinting issues as already pointed out by Chris.

Conclusion: Next to impossible

For your question "Does a man contain all the genes needed to make a women": yes he has but does not have the biological machinery to do that (exclusive of the womb).

However if you choose to send a female astronaut for this mission then there may be some hope. As Chris said, there are problems with homotypic fusions because of imprinting issues. But with a supply of ova there can be other ways:

Make clones using SCNT: limitation is that there would be very little variability.
Erase imprinting marks and fuse two oocytes: This has not been done yet but this is possible. At this moment we have technology (still incipient for therapy grade), for targeted genome editing. The basic principle involves fusing a DNA-endonuclease with a sequence specific DNA Binding Domain (DBD). Examples include Zinc Finger Nuclease, TALENs and Crispr-Cas. This study demonstrates an engineered system that can deaminate RNA in a sequence specific manner. Based on a similar principle it should be possible to link DNA-(cytosine/adenine)- methyltransferase or DNA-(cytosine/adenine)-demethylase to a sequence specific DBD 1. This system can be used for targeted epigenetic modification. This would have a little more variation than cloning because of meiotic recombination. Limitation is that there won't be any males, this would perhaps become an Amazonian Planet.

Make sure that your space-shuttle has a good biolab facility :P

1 Imprinting is generally implemented by DNA methylation which happens mostly on cytosines.


Have there been any studies on 'surf balls'? (not related to surfing) I know the title sounds like something else, but I'm actually wondering about these things, which are also apparently called 'whale burps':

This one was found on a beach on Lake Michigan.

Does anyone know if any scientific studies have been done on these? If so, can you refer me to them?

These surf or beach balls are made of plant material throughout the structure. They form by wave action along beaches. As the naturalist at Wilderness State Park, the campers and I discovered over 30 of these balls along the beach the summer of 2017.  In previous summers we had found 0. Lake Michigan and Lake Huron were at record levels during the summer of 2017, the highest since 1998. This may explain the formation of these grass balls in abundance. We found some of the balls still in the water, in a depression, just offshore. Others were rolling in and out with the waves. Some had been deposited on the shore and were filled with large quantities of sand. I shook out nearly a cup of sand from one ball. I dissected one surf ball and found predominantly roots and grasses. I will continue to investigate the species of plants that form these curious creations and try to discover the secret to their formation


What did Richard Feynman contribute to molecular biology? Some time ago, I read James Gleick's "Genius: The Life and Science of Richard Feynman", a wonderful biography of Feynman and, by extension, most of modern physics.
In this book, the author mentions that Feynman spent a year working in a biology lab and that during that year he made an important discovery.

I remember that when reading the book as an undergraduate biology student, I knew the discovery in question well enough to be immensely impressed that it had been discovered by someone foreign to the field.

Unfortunately, I no longer have the book and cannot remember what that discovery was. Does anyone know?

According to Gleick, Feynman spent the summer of 1960 in Delbrück's lab at Caltech and discovered intragenic supression.

This is where the expression of a gene which has been knocked out by a mutation may be restored by a second mutation within the same gene.

Fenynman worked with the rII mutant of phage T4 and was looking for back mutations in E.coli strain K.

He noted some unusual plaques which he labelled idiot r's.

Feynman correctly deduced that these revertants were due to a second mutation which cancelled the effect of the first, but he did not publish the result, possibly because he had no molecular explanation for what was going on.

The Delbrück lab referred to these revertants as Feyntrons.

Cricks and co-workers in Cambridge, UK, correctly explained the phenomenon.  If, for example, a mutation caused a gene to be read out of sequence (a frameshift mutation) then a second mutation within the same gene could put the message back 'in phase', thus cancelling out the effect of the first mutation.

All the above is taken from James Gleick (1992) Genius.  Richard Feynman and modern physics, a great book.


A good software for agent based modelling? Hello i'm gonna start my master degree in systems biology and i'm thinking of working with agent based modelling, but i really don´t know which platform can be the best to simulate interactions between cells, like chemotaxis communication or between molecules. Some of my advisors have recommended me Netlogo because his simplicity and good interface, but i don´t know if it is enough powerful to run simulations of many interactions between a lot of agents. I hear that MASON is also good but you need a little background in java programming. So, which one do you think it could be the most appropriate or which other platform can you recommend me that also can be good?

My boss is a big fan of Repast HPC, but since Repast is a C++ framework it might not be the right choice for you. It takes a loooong time to write a good C++ program (even for someone who already knows the language fairly well), although it will run very quickly once it's written. A one or even two year long Master's program will end up going by surprisingly quickly, so if I was in your shoes I'd choose to start with the simplest thing possible (ie Netlogo). Once you have a finished product, even if it's somewhat more simplistic than you'd like, it'll be much easier to work your way up from there.

Really though, consider the choice of modeling framework to be part of your research project! Only you can come up with the right choice for your project, though as a practical matter you should heavily favor any framework that at least one person in your department already has some experience using. Things will go wrong, you will have questions, and Stack Overflow won't be able to answer all of them.

Here's a list of the more interesting agent-based modeling frameworks that I found from a few minutes of googling:

Repast HPC

pros:

C++ based
The only performance focused one of the bunch

cons:

C++ based
For simple models, would be like building a supercomputer to use as a pocket calculator

Netlogo

pros:

Focused on being accessible to non-programmers
Scripting language seems pretty straightforward

cons:

In my experience frameworks that try to implement their own scripting language in an attempt to be accessible to non-programmers ultimately end up being much more complicated to use than frameworks based around an established language. But I'm not the target audience.

Mesa

This one is Python based, so it's the one I would personally try first since I find Python to be the best language for quickly writing scientific programs of reasonable complexity. That's my own personal bias, so your mileage may vary

MASON


Are there dog breeds that are so far apart genetically that they can't produce viable offspring? Obviously, a very large dog would have difficulties mating with a very small dog and vice versa.

But putting that problem aside (using, say, insemination), considering the large variation of dog breeds, are there any two breeds that are so different genetically that they can't produce viable offspring together?

I actually found some sort of reference for this.  Apparently in the case of a beagle and irish setter pairing, they had a lot of difficulty in producing pups, but as breeds have a lot of genetic quirks, this might be due to a genetic accident; this is probably a case of mutual infertility rather than speciation.  There are probably mutations in their genomes which are causing non viability in the pups the way that it does with some human parents who have difficulty having children - an immunological incompatibility or traits which cause most offspring non-viable.

In fact the discussion points out that the species designation does not always mean they cannot produce offspring, but simply do not.  Coyotes and wolves will produce offspring too if they are encouraged to do so, but are competing and antagonistic in the wild and so never do mate in practice.

So the answer is probably no. (the beagle/setter pups did show up, but with a much smaller litter than usual with just 2 pups).


Pasteurisation of orange juice and Vitamin C In the UK at present, one of the examination boards has set a "controlled assessment" (an experiment that pupils do at school under exam conditions) that involves testing a hypothesis that vitamin C is removed from fruit juice by heating it (i.e. in the pasteurisation process).

I am massively skeptical about this. The teacher guidance suggests "Treating fresh orange juice in boiling water for between 10 and 30 mins gives an easily measurable decrease in vitamin C levels". Leaving aside that this hardly represents a simulation of the pasteurisation process(!), does anybody know of any solid, academic studies of the effect of pasteurisation on the vitamin C content of fruit juice? I have tried (as a scientist, but non-biologist) my usual routes to reliable information and they fail miserably - the www is full of crackpots on this one.

As a follow-up to that, is it not the case anyway that the oxidation of the orange juice when it is boiled in this experiment, plus simple exposure to light could also be responsible for any decrease in vitamin C observed?

Hodgins AM, Mittal GS, Griffiths MW. 2002. Pasteurization of Fresh Orange Juice Using Low-Energy Pulsed Electrical Field. J Food Sci 67(6):2294-2299

This is a study of non-thermal food preservation, but it cites two studies that measured ascorbate loss from pasteurisation. I can't cite the studies directly because I can't find them online. According to these authors, they reported losses of 7.0-15.0% and 18.0% after 95°C for 15s. This is high compared to the pulsed electrical field method.

Yeom HW, Streaker CB, Zhang QW, Min DB. 2000. Effects of Pulsed Electric Fields on the Quality of Orange Juice and Comparison with Heat Pasteurization. J Agric Food Chem 48(10):4597-4605

This study compared ascorbate loss during storage after PEF or thermal treatment. While no difference was observed when stored at 22°C, PEF treated orange juice maintained significantly higher ascorbate concentration than thermally treated orange juice when stored at 4°C. The authors attribute this to the "higher processing temperature".

They also say (and reference other studies):

  Ascorbic acid is a typically heat sensitive nutrient. High temperatures during processing and storage cause loss of ascorbic acid.


With over 400 chromosomes, does mitosis in a species of butterfly happen in the same way as in humans? The beginning of the Ars Technica article Gene editing crunches an organism’s genome into single, giant DNA molecule begins:

  Complex organisms have complex genomes. While bacteria and archaea keep all of their genes on a single loop of DNA, humans scatter them across 23 large DNA molecules called chromosomes; chromosome counts range from a single chromosome in males of an ant species to more than 400 in a butterfly.

Thanks to @Remi.b for tracking down Lukhtanov (2015) The blue butterfly Polyommatus (Plebicula) atlanticus (Lepidoptera, Lycaenidae) holds the record of the highest number of chromosomes in the non-polyploid eukaryotic organisms.

Does mitosis happen in this species of butterfly cells, and if so, does the process that separates the pairs take place in a similar way mechanically to the way it happens in mammal cells such as the 23 pairs in human cells even though there seems to be almost twenty times the number of individual chromosomes?

Has the mechanics of this process ever been imaged or visualized?

above: from here and here.

above: " Image of the mitotic spindle in a human cell showing microtubules in green, chromosomes (DNA) in blue, and kinetochores in red." from here

Mitosis was displayed in a lot of organism, also in organism with a very high number of chromosomes. Here's an example of the analysis made in a fish with an average count of 280 chromosomes. Look at the metaphasis of a cell with higher number of chromosomes (Acipenser transmontanus):

This doesn't mean that every chromosome is equal to others: there're microchromosomes, acrocentric chromosomes, meta, sub-meta.. So, the size required into the nucleus (because where're obviously talking about eukaryotic cells) isn't strictly connected with the chromosomes number.

The answer to your question isn't a clear "yes" : the high number of chromosome in a butterfly is connected with a karyotype instability, where some cells received a wrong number of chromosomes into an alterated mitosis. Actually isn't fully clear why and how these errors come out. Here's something else about butterfly karyotype and phylogeny.


How can a ligand be an integral membrane protein? My background is in mathematics, and not biology, so please bear with me. I am currently working on a project involving the effects of Epidermal growth factor treatment (EGF) on cell migration. I am reading a review of EGF signaling (Epidermal growth factor receptor targeting in cancer: A review of trends and strategies by Chetan Yewale, et. al.), and it states that "Various ligands can activate EGFR ... These ligands are expressed as integral membrane proteins." This statement makes absolutely no sense to me, and makes me question my understanding of signal transduction. I think of ligands as freely floating molecules that may eventually come into contact with the cell membrane and attach to some receptor. But a ligand expressed as an integral membrane protein? This seems contradictory to my understanding of ligands, which (I thought) are released from the cell in order to signal with cells (be it the same, neighbor, or distant cells). Integral membrane protein ligands would only be useful for autocrine signaling, which I don't think is true of EGF.

A perfectly reasonable definition of a ligand from Wikipedia:

In biochemistry and pharmacology, a ligand is a substance that forms a complex with a biomolecule to serve a biological purpose.

A ligand can be anything, so long as it binds to a biomolecule. Often, the ligand is a small molecule or peptide, and the thing that it binds to is a protein. On the other hand, both ligand and binding partner can certainly be proteins (or one could be a Mg$^{2+}$ ion and the other an RNA molecule, etc.). Ligand is a very broad term, and is often used in other biochemical areas aside from signaling. For example, the things that an enzyme binds to (substrates, allosteric regulators, etc) can be called its ligands.
Also, the things you describe in your post:

This seems contradictory to my understanding of ligands, which (I thought) are released from the cell in order to signal with cells (be it the same, neighbor, or distant cells).

are hormones, which is a much more specific category of thing than is ligand.
Edit
There seem to be some 'ahem'... doubters as to the broadness of the definition of ligand, so, time for some examples from the literature:
From the biochemistry textbook Berg, 7e (emphasis added):

The final step is affinity chromatography with the use of a ligand specific for the target enzyme.

From the paper Electrostatic steering and ionic tethering in enzyme–ligand binding: Insights from simulations, Wade et al (emphasis added):

To bind at an enzyme’s active site, a ligand must diffuse or be transported to the enzyme’s surface, and, if the binding site is buried, the ligand must diffuse through the protein to reach it.

From the paper Geometries of functional group interactions in enzyme-ligand
complexes: Guides for receptor modelling, Tintelnot et al (emphasis added):

There are many more examples of arginine-carboxyl interactions that appear to have key functional
roles in enzymes, including some in which an arginine-like structure in the ligand interacts
with a carboxyl group from the binding site (i.e., the reverse of that described above).

It is true that the one particular compound that natively binds to an enzyme's active site is often called a substrate, in part to differentiate it from allosteric regulators and other ligands that can also bind to the enzyme. Thus, the set of all of an enzyme's substrates can be thought of as a subset of the enzyme's ligands. Again, ligand is an extremely broad concept that simply refers to something which binds.
Edit 2
Fun fact! The modern word ligand comes from the latin verb ligāre, meaning "to bind". More specifically, ligand derives from the gerundive form of ligāre, ligandus, which translates to something like "(that which is) to be bound".
Not that this has much bearing on how it's used in the modern scientific literature. I just thought it was cool.


Are all dead plant cells (that die to do a job), have secondary wall? Can we say that all plant cells that die to do a job (they are dead now), like the outer cell surface of the root cap, have secondary cell wall?

Not all plant cells perform a function when they die.
But a lot do.
Sclerenchyma is refereed to as:

Sclerenchyma is the tissue which makes the plant hard and stiff...

Mature sclerenchyma is composed of dead cells with extremely thick cell walls (secondary walls).

Plant cell death includes necrosis, apoptosis and autophagy and studying how and why they occur is an active area of plant research.
Some plant cells die because they are not provided enough energy. Plants garner energy via the sun and biochemical process known as photosynthesis.
When the days start to become shorter there is less sunlight and parts of some plants die.
E.g. Leaves die.


Introductory biology text for an outsider I'm a maths major and I have an interest in learning biology. I know very, very little; I know how babies are made and that's about it. Could anyone recommend a stimulating text to read for its own sake and also to use to learn biology?

I found the Campbell Biology textbook to be quite comprehensive and approachable. I think many introductory biology courses use it.

http://www.amazon.com/Campbell-Biology-Edition-Jane-Reece/dp/0321558235


What is the name of this flower? The photo was taken in the Okanagan Valley, British Columbia This little flower was growing on dry ranchland in Kelowna, it flowered in April:


Calculating chromosome number in meiosis: Why is the crossbreed between a fox and a dog (dox) sterile? Given the following example/question (originally found here):

I worked out the haploid number of the dox to be 29 and the diploid number of the dox to be 58. 58 is an even number, so surely 29 homologous pairs of chromosomes can form for the dox to be fertile. Why is it sterile?

Thanks

This is not simply a question of math, just determining if the diploid number is even or odd. If it was that easy, all hybrids with an even diploid number would be fertile, and that doesn't happen. The problem is way more complex, and it has to do with chromosome pairing.

In the question described, we have the following numbers:

Canis lupus (dog): 2N = 78, therefore N = 39;
Vulpes vulpes (fox): 2N = 38, therefore N = 19;

Now, let's suppose, in an exaggerated simplification, that all 19 chromosomes in the fox's gamete find an exact homologous in the dog's gamete (again, this is very unlikely). So, in this oversimplified scenario, we would have 19 pairs of homologous chromosomes in the hybrid's cells.

However, even if that's the case, we still have 20 chromosomes in the dog's gamete that didn't find any homologue in the fox's gamete.

That mismatch, alone, is enough to block meiosis, particularly at the pachitene checkpoint.


Is Zeiss Primo Start microscope worth the price for student use? I study physics but I have got interested about biology too. Surfing around the web, I have found out that in buying microscopes one needs to decide between the cheaper no-name brands vs. the four big ones: Zeiss, Nikon, Leica, and Olympus.

From the four big ones, only Zeiss delivers directly to my country. The price for Primo Star with phototube and Full-Kohler illumination is 1.8k euro or 2.3k usd. It has only bright-field optics but dark-field (if I got it correctly) is easy to add, as well as phase-contrast.

Anyway, I was wondering how much I would get out of the scope as a home user. I would probably do plant biology. I would also like to learn some staining techniques.

How difficult it would be to run some mini-studies at home? Do research? I would know about imaging quite a lot..

(There was some other similar questions but they did not mention home use.)

I'm defenitly no fan of the Primostar. It's made to order for Zeiss, probably by Meji.

It's a fine microscope allright, but compared to the gray and beige Standards, it's a toy.

And those gray and beige Standards were already kind of toys, compared to the former black GF stands...

Being a "home user" there are far better and at the same time much cheaper  alternatives availlable on the second-hand market.

In Europe, a Standard 14, basicaly equipped (4,10,40,100 achromats, 0.9 condenser, build in 6V/10W HAL illuminator, binocular) can be bought for anything between 100 and 200 Euro.

This is a universal platform, designed with flexibility regarding applications such as DF, FC, DIC, fluorescense... in mind. The same can't be said to that extend regarding the Primostar.


Population Genetics Question Can someone please help with this question? Here is my working (just in case it is not clear: 1/300*1/30*1/2) but is this actually correct or do I need to multiply by 0.5 once again? I appreciate any help!

Question is: If an Ashkenazi(1/30) and(multiply) French-Canadian(1/30) ....
Where 1/300 came from ?

I duno, I may missing something - but may it be like  that

Parrent1(=1/30 * 1/2)*Parrent2(=1/30 * 1/2) = P(child with both mutations)


Hebbian theory "fire together" clarification Donald Hebb states it as follows:

  "Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability.… When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased."
  Or we can conclude in short: "Neurons that fire together, wire together".

As I understand it, this means that synapses that already exist become stronger between neurons.

Could new synapses form between neighboring neurons that "fire together", but are not necessarily directly connected through an axon?
And if so, what is the mechanism to direct the new synapse formation towards that other neighboring neuron that "fires together"?

Strictly stated, Hebb's rule applies only to existing synapses, and not to the formation of new synapses. (This answer applies to biological neurons, not to ANNs).

Synapse formation is a topic of active research. During development (and in fact continuously even during adulthood), many synapses are created and destroyed. It is not unreasonable to suspect that a similar form of rule is used to decide which synapses are removed and which should remain.

Synaptic connections between neurons show a good deal of specificity -- for example, in the projection from the retina to the optic tectum, synaptic connections are made only with target neurons at an appropriate retinotopic location. This happens because growing axons follow molecular gradients.

Within a cortical column, some possible connection pathways seem to be actively sought -- for example, axo-axonal cells connect specifically to the axon initial segments of target neurons. Neurons certainly have membrane molecules that could be used to identify target cell classes.

So there are probably a number of rules used to determine when a new synapse is made. However, I am not aware of a mechanism for a pre-synaptic neuron to detect how a putative post-synaptic parter is firing, without a synapse already being present. So it seems likely that some form of random process is involved to form new synapses with reasonable post-synaptic partners, after which some activity-dependent rule (like Hebb's) could be applied.


How did the orchids evolve to support pseudocopulation when they do not have any organ for vision to see how insects look like? How could they guess so perfectly how a moth or whatever the pseudocopulating organism looks like. They do not have eyes to see the shape or structure. What could possibly be the reason they evolved with such accuracy to deceive an animal?

Evolution does not work based on an organism (or designer) "seeing" a problem and seeking a solution. Evolution via natural selection works when members of a population that have a certain heritable trait are better at reproducing than other members of that population. Because they are better at reproducing, subsequent generations of the population have a greater percentage of individuals that have that heritable trait, and the process continues, sometimes to the extent that all the individuals of that species have that trait (this is called "fixation").

The way something like this would evolve is that some predecessor to modern orchids has some morphology or chemical secretion that was particularly attractive to insects. This increased the ability of that predecessor to reproduce. Over generations, any other random mutations that further promoted attraction of insects also were selected for, until they accumulated all of the adaptations we see in a modern orchid.

Today, we can study that process and realize post facto that "Oh, these adaptations worked because they tricked the insects into thinking they were copulating, when really they were just dispersing pollen."

However, the flower never needed any knowledge of insect copulation, it just happened that flowers that had those traits did better at propagating their genes to the next generation.

These types of questions are more easily understood with a broad understanding of evolution. One great resource is Understanding Evolution from Berkeley.


What are the uses of centrioles and matrix of centrosomes? In centrosomes, the gamma-tubulin ring complexes (gamma-TuRC) located on the surface are essential as the nucleation site for the growing (with polarity) of microtubules.
However, I see that there is also a centriole (made by 2 centriole units in T-shape structure) and a centrosomal matrix. According to Wikipedia, it seems without centrioles, the cells can still function normally and grow (please correct me if I am incorrect), and it seems I cannot find much information in the internet suggesting the use of both centrioles and centrosomal matrix.
Therefore, I would like to ask what are there functional significance? And I would like to ask if we are able to make a synthetic sphere with many gamma-TuRC on its surface (without any rejection), can the cell perform a normal cell cycle?

THis was too long for a comment.
It would be helpful for you to indicate what exactly you mean by "cells can still function normally and grow".
There are a few observations related to your question about absence of centrioles (from your wiki page):

In Drosophila mitosis and development can occur to some extent in centriolar mutants, but "they die shortly after birth" due to flagellar and ciliar defects.

Some organisms do not have centrioles and use other mechanisms (e.g. angiosperms).

So, in the sections of your wiki page "Fertility", "Ciliogenesis", etc., those list the functional significance of centrioles.
If what you mean is "what is the role of centrioles in mitosis", then we of course have a separate question. You can find a lot of resources on this topic via google searches.
As for your last question, about the synthetic sphere, you will have to spell out the experiment in much more detail- for example, what do you mean by "synthetic sphere"? A sphere defined by a lipid bilayer with gamma-TuRC (for example) on its surface and no other features is not a cell and won't go through a cell cycle.


In the future, it is plausible that we can change the physical appearance of a living animal by editing DNA? http://www.independent.co.uk/news/science/revealed-scientists-edit-dna-to-correct-adult-genes-and-cure-diseases-9273555.html

This article explains that scientists managed to change the DNA of adult laboratory mice with an inherited liver disease, thereby curing them of the disease.

The change in the liver is not be a change in physical size and shape, instead it was a change in the liver metabolism.

If we used this same method to edit our hair follicles, could we alter our hair color? The new hairs would have altered DNA, and come out a different color depending on what the cells have been altered to.

And then, is it possible to change the physical size and shape of a living animal by editing DNA? For example, if an animal has porous and small bones, is it plausible that we could edit its DNA so that its bones start to become more dense and thick? The physical appearance of the living animal would be changed, since the bones are larger than before.

Along these lines, could we then edit DNA of an adult human to change bone structure so that we have sharper noses? Larger eyes?

This article explains that scientists managed to change the DNA of adult laboratory mice with an inherited liver disease, thereby curing them of the disease.

Yes, Read about CRISPR-CAS9 method of gene editing. This is not the only method which can achieve this. There are many others like TALEN or Zinc Finger.

  If we used this same method to edit our hair follicles, could we alter our hair color?

Yes, similar studies like this has already shown this potential but using different method as mentioned in article you linked.

  The new hairs would have altered DNA, and come out a different color depending on what the cells have been altered to.

For this you need to express such constructs in cell specific manner. Drosophila geneticists are doing such things for long long time.

  And then, is it possible to change the physical size and shape of a living animal by editing DNA? For example, if an animal has porous and small bones, is it plausible that we could edit its DNA so that its bones start to become more dense and thick? The physical appearance of the living animal would be changed, since the bones are larger than before.

Plausible but remember such characteristics are controlled by many factors which will be hard to control. Plus there will be age/environmental/epigenetic factors which you can't control with such techniques.

  Along these lines, could we then edit DNA of an adult human to change bone structure so that we have sharper noses? Larger eyes?

Most of these techniques required change in germ cells. Hence it will be difficult to implement such techniques in adults. However 'ideally' you can use techniques like RNAi which can be triggered by specific inducers at any stage of life (like temperature sensitive UAS-Gal4 system used in fly genetics).


What happens to the umblical cord inside the mother? After giving birth to a child, the umblical cord is cut (and stored if they want). The end connected to the child's navel will fell off eventually but what happens to the end inside the mother?

Will it be removed right after birth by doctors or what happens?

Labor is typically divided into 3 stages:

Stage 1: From the onset of contractions (true labor pains) to full dilatation of the cervix (which is about 10 cm) - this takes about 12 to 18 hours
Stage 2: From full dilatation of cervix to expulsion of fetus - This takes about ~ 30 minutes
Stage 3. From expulsion of fetus to expulsion of placenta - this takes about ~ 15 minutes. During the third stage, the umblical cord which is attached to placenta is expelled along with the placenta. This would be the answer to your question.

Source:Hympath.com


Are the irises an exact match in a human's set of eyes? Are the irises an exact match in a human's set of eyes? Assuming the eyes are healthy with 20/20 vision.

Short answer
No. Not two irises are alike, including the irises of identical twins and even the two irises of one and the same person. This uniqueness of the human iris is used in iris scans. The variety of the iris is caused by its complex structure and coloring pattern.

Source: Jean-François Mainguet

Background
The iris is explained on Biometric Technology's website, and I quote:

  The iris [...] is a thin, circular structure in the eye, responsible for controlling the diameter [...] of the pupil [...]. “Eye color” is the color of the iris, which can be green, blue, or brown. In some cases it can be hazel (a combination of light brown, green and gold), grey, violet, or even pink. In response to the amount of light entering the eye, muscles attached to the iris expand or contract the aperture at the center of the iris, known as the pupil.

A striking example of the dissimilarity of the iris in one person are people with heterochromia. Heterochromia can result in both eyes having a different color. Examples are given in the figure below: On the left is Demi Moore (if you look closely her right eye is hazel, while her left eye is green). On the right-hand side a more striking example is shown (taken from the Kliproject):

Heterochromia iridium (differing iris colors) and heterochromia iridis (a variety of color within a single iris) are relatively rare in humans and result from increased or decreased pigmentation of the iris. Most cases are the result of an alteration in the expression of the EYCL3 gene (which codes for brown/blue eye color) and EYCL1 (which codes for green/blue eye color), among other genes within the cells of the entire iris or even a particular section. Other potential causes include trauma around the time of birth or later in life, congenital pigmented nevi or even medications such as those used in the treatment of glaucoma.

Fun fact
David Bowie's eyes are in fact of the same color - his pupils are of a different size:

Reference
Scientific American (November issue, 2001).


What are these tiny insects? I live in Italy (Emilia Romagna), and my house, seasonally in spring, is full of these guys, someone knows their name and if they could represent a problem?
They are very tiny slightly less than 0,5 cm including the antennae.

It could be Anthrenus verbasci.

These insects are not dangerous, but they can damage carpets, clothing and furniture.


Why do you get prion diseases from eating animal brains but not other parts of the animal? Eating animal brains is considered a delicacy in parts of China. We know that eating animal brains can lead to prion related diseases.

Prions are misfolded proteins that are potentially infectious. But the whole body of an animal is full of proteins. What makes the brain special? (or specially infectious?)

My question is: Why do you get prion diseases from eating animal brains but not other parts of the animal?

The notion that you get prion diseases like BSE only by consumption of brain is not correct. Any part of the infected animal that contains nervous system tissue or lymphatic tissue can be infectious, although I guess this is dose-related.

Quote from OIE, "BSE. General disease information sheet" ([1]):

  The risk linked with consumption is addressed by the requirement for
  routine removal of all visible nervous and lymphatic tissue (Specified
  Risk Materials (SRMs)) from carcasses during the processing of
  cattle as well as the removal of any suspect animals from the human
  food chain.

  Appropriate handling of nervous and lymphatic tissue tissues from
  BSE-suspect animals in abattoirs and laboratories is indicated to
  avoid accidental exposure (ocular or oronasal). Milk and milk products
  are considered safe.

[1] http://www.oie.int/fileadmin/Home/eng/Media_Center/docs/pdf/Disease_cards/BSE-EN.pdf

The OIE is the animal equivalent of the WHO.


What is the signal conversion from hair cells to cochlear nerve cells? If I understood correctly, inner hair cells generates a graded potential (receptor potential), this potential maps the stereocilia deflection. On the other hand, the cochlear nerve cells transmit action potentials to the brain.

The question is how and where the graded potential is converted to action potentials. In particular, as action potential signals are characterized by the interval between triggers, how are the sound properties (power and frequency) mapped into this interval?

Short answer
Sound level is coded in spike rate, frequency is coded by a place-frequency map.

Background
Spiral ganglion cells (SGCs, the secondary sensory neurons making up the auditory nerve) are continuously firing cells in a healthy ear (they fall silent when the hair cells degenerate, leading to deafness). In fact, their base frequency in silence is pretty high. The only thing the hair cell input does is lowering, or elevating the threshold and hence affecting firing rate. During a sine wave stimulus (a pure tone), the stereocilia of the hair cells deflect in one phase, and inflect on the other. One phase hence depolarizes the SGC, the other hyperpolarizes it. This generates a near-perfect representation of the sine wave input at low frequencies. At high frequencies the SGCs may skip a phase or two, but because multiple SGCs are involved, the population code is still stochastically spot on.

Sound level is coded in spike rate, frequency is coded by a place-frequency map (Müller, 1996). The base of the cochlea codes high frequencies, the apex low frequencies. Hence, loudness is coded by every SGC, while frequency determines which SGC is activated. An informative overview of hair cell signalling is provided in Fig. 1.

Fig. 1. Hair cell transduction. source: Pasadena City College

References
- Kandel et al., Principles of Neural Science, 4th ed.
- Müller, Hear Res (1996), 94(1-2): 148-56


Why would the citrulline content of the watermelon be so high? Citrulline is a non-proteinogenic amino acid (that is, citrulline is an amino acid that is not coded for in mRNA), and it is an important metabolic intermediate in the Urea Cycle. The Urea Cycle is critical for nitrogen (e.g. ammonia) excretion in humans as well as other mammals.

Citrulline is an interesting amino acid, given its vital function in the Urea Cycle, but also because it has such a high concentration in the watermelon. The name citrulline is actually derived from citrullus vulgaris, which is the Latin word for watermelon.

A notable fact about the watermelon is that the watermelon is the only food known to have such high content of citrulline. There are NO other foods that have such high endogenous levels of this amino acid.

As a physiologist citrulline is very interesting metabolically, but I wonder why the watermelon would have such a high concentration? Why would that occur? Would high citrulline content offer some type of competitive advantage to the watermelon in terms of out-competing other plants? As biologists, we usually think about things from a teleologic perspective in order to make sense of the world around us. With that perspective, is there a logical reason that citrulline would be so enriched in the watermelon? It seems very odd that it would be the only plant with notable quantities.

According to molecular botanists and plant physiologists, watermelon is the only plant that is known to contain significant amounts of citrulline. Interestingly, it appears that the reason for this tremendous enrichment in citrulline stems from the environment in which wild watermelons naturally thrived hundreds of years ago prior to the development of agriculture.

According to botanists, drought is one of the most severe stresses to which a plant can be exposed. Drought generates a high level of free radicals and oxidative stress, in part because plants maintain their photosynthetic machinery even in the face of severe drought. A number of investigators have shown that different plants have unique molecular mechanisms/systems to allow them to tolerate such harsh conditions and oxidative stress.

Wild watermelon plants inhabit the Kalahari Desert in Botswana, where the annual rainfall is less than 2 cm. Despite the minimal rainfall, the watermelon (a xerophyte) can tolerate the extreme conditions well with an exceedingly high drought tolerance. Surprisingly, this tolerance to intense drought conditions by watermelon plants even persists despite a sub-optimally developed root system. In the case of the watermelon, citrulline is overproduced in the leaves (and apparently the rest of the plant) and citrulline acts as the major hydroxy radical scavenger that allows wild watermelon to tolerate the drought-induced oxidative stress. From this same source (Annals of Botany - link below), there are also other proteins that may also be involved in these mechanisms as well. Even though the citrulline content is predominately used in the leaves to buffer oxidative stress, it appears that it secondarily accumulates in the melon itself.

Note: The image below is from Annals of Botany paper in the links below - it is OPEN ACCESS, which is why I posted the picture and included the reference link. You can clearly see the before and after pictures of drought and how the watermelon leaves appear minimally changed, unlike the radish and cucumber leaves.

See below for some interesting Papers about citrulline, watermelon, and mechanisms of drought-resistance:

Ann Bot. 2002 Jun;89 Spec No:825-32.
Citrulline and DRIP-1 protein (ArgE homologue) in drought tolerance of wild watermelon.

FEBS Lett. 2001 Nov 23;508(3):438-42.
Citrulline, a novel compatible solute in drought-tolerant wild watermelon leaves, is an efficient hydroxyl radical scavenger.


Good pipetting technique? Good pipetting technique is essential for many biologists, but it can be hard to get right. When I take 1 µl of liquid using a micropipette, I seem to always take less than 1 µl, and that amount is variable/inconsistent. I would like to know what could be wrong.

What is the proper pipetting technique? Could it be that the pipette is inaccurate?

Here's some step-by-step advice on good pipetting technique:

Make sure the pipette is set for the correct volume
Ensure the tip is firmly attached
Keep the pipette vertical when pipetting
Slowly and smoothly depress the plunger to the correct point (the first stop position)
Insert the tip in to the liquid to be pipetted. Ensure the tip is properly immersed in the liquid, but not touching/near any surfaces of the container
Slowly and smoothly release the plunger back, keeping the pipette upright, and tip immersed, and making sure no bubbles form - you can try pre-wetting (see video linked below, around 3:00)
Withdraw the pipette from the liquid
Carefully dispense the liquid in to the desired container by steadily depressing the plunger to the second stop position (fully depressed), making sure all liquid is dispensed without spills or splashes.

  "Put the tip in a 45-degree angle onto the wall of the container; then
  start pushing down up until the first stop; then push through to the
  second stop; keep the plunger depressed and remove pipette and check
  whether the drop is in the container and pipette tip is empty" -
  Christiaan

Discard the tip using the release plunger

Also check you've got the right size/type of tip, and are using a suitable pipette (e.g. don't use a 10-100 µl pipette for 120 µl)

If this still causes incorrect measures then you could need to get your pipette calibrated.

Test a pipette by taking several samples. If the pipetted volume is consistent but incorrect (e.g. always 10% under the target) it suggests the pipette needs calibrating, it's probably not the technique that's wrong. If it is inconsistent (both under and over pipetting) then it's either technique or the pipette (bad/damaged pipettes can be inconsistent, poorly but good calibrated pipettes will more likely be consistent and only need calibrating).

Try using multiple pipettes, if they are each consistent but variance is among them (pipette 1 is always under by ~10%, pipette 2 is always over by 15%, pipette 3 is always over by ~2%...) then your technique is good, and you need better pipettes. Also get an experienced pipetter to check your technique and try the pipettes themselves.

Calibration can be done internally by lab techs or by external specialists, speak to your lab responsible person.

Also see this video which is well explained.


Can an emulsion enter a cell? I've been tempted on cooking.stackexchange to answer a question, and I did, out of my mind.

(In retrospect, I shouldn't have done so, based on my lack of citable resources.)

I've heard that a water in oil emulsion can penetrate cell walls.

Is it true, and how does it work?

Under the right conditions, emulsions of lipids (fatty compounds) and water can cross cell membranes. If the emulsion is prepared correctly, a structure known as a liposome forms, which is essentially a "bubble" with a layer of fatty molecules on the outside and water at the center. This has been studied intensely in biotechnology, because such liposomes can be used to carry DNA inside (DNA is water-soluble) and then be used to deliver DNA to cells, as in gene therapy.

Typically, oil, which contains triglycerides, is not used for this though, but another compound known as a phospholipid. This is also a "fatty" substance, but unlike triglycerides, one end of the molecule is polar, which helps it interface with water. Phospholipids are the main ingredient in cell membranes, and therefore liposomes made of this stuff can interact with cell membranes. Essentially, the liposome can "merge" with the cell membrane in such a way that the water inside it (and any other contents) ends up inside the cell. For an example of how this technique is used, see this article.

As for the cooking-related question, I would say oil-water emulsions found in foodstuffs are unlikely to cross cell membranes. They contain mostly triglycerides which are not so effective at this, and they are probably not prepared in the right conditions (oil/water concentrations, etc) for liposomes to form.

Also, even if there would be liposomes in some foods that could cross cell membranes, foodstuffs do not actually get into contact with cell membranes in the digestive system, until they are broken down into smaller (harmless) molecules. In the mouth, esophagus, stomach, etc, tissues that come into contact with foods are heavily protected by layers of mucus to prevent cells getting "attacked" by all the weird biomolecules (and organisms) that we eat.

Finally, various molecules from food don't actually enter the cells of taste buds; instead, they are sensed by taste receptors present on the outside of the cells. (Well, the sour taste sensor involves transport of small ions, but not larger molecules.) So you should probably revise you answer on Cooking SE.


Number of introns in a genome Humans have approximately 21000 genes but they probably make more proteins than that. This has been explained by many mechanisms like alternative RNA splicing.

My question is - If what we call as "introns" and "exons" vary so much, then how is the  number of introns present in a genome determined ?

Yes, the individual number of exons/introns will vary in a transcript, but what you can do is just count all possible exons of a gene
For example, lets say you have an alternative exon in these two isoforms. The XX's are exons

XX---XX---XX---XX

XX--------XX---XX

We would say this gene has 4 exons and 3 introns, even though one isoform only has 3 exons. Its the transcript that varies in number of exons, the gene remains constant.

Heres a slightly more complex example. Mutually exclusive exons

XX---XX--------XX

XX--------XX---XX

We would still say it has four exons. Pretend that every exon of every isoform is included and thats how you get the number of exons in gene. So for the above example, just pretend both mutually exclusive exons are included

XX---XX---XX---XX

According to this old paper there are 8.8 exons per gene (7.8 introns). Their gene number count is high because its older, but they estimate that there are 207,344 introns in the human genome.


What are the lower and upper hearing limits of the human ear? I am looking for the loudness limits, expressed in decibels, for the human ear.

Google and Wikipedia is only giving me the frequency limit that the human ear can receive, but I cannot find mention about the decibel limits.

Related question on acoustic frequency: why-do-humans-hear-better-between-2khz-and-5khz

Short answer
Hearing threshold is 0 dB SPL at 1 kHz, and pain threshold is around 125 dB SPL at that frequency.

Background
Loudness thresholds depend on acoustic frequency (pitch), as depicted in the following figure:

Loudness contours in human. Source: Stanford Uni

When expressed in dB sound pressure level (dB SPL) the threshold of pain is approximately 125 dB SPL. The lower bound peaks at a hearing threshold of about -5 dB SPL at 4 kHz (maximum sensitivity). Outside that frequency, hearing sensitivity declines (and threshold hence increases).

Note that dB SPL references to a sound pressure of 20 µPa = 2 × 10−5 Pa. This sound pressure corresponds to the hearing threshold at 1 kHz and is hence defined as 0 dB SPL. (Stanford Uni).

Further reading
Why do humans hear better between 2kHz and 5 kHz


Do new neurons divide propotionally? Do new neurons divide propotionally?

if i try to improve my reasoning skills,are the new neurons only made for that specific region of the brain that controls reasoning skill?
i have heard that one side of the brain controls the other side of the body, if i try to use my non-dominant hand(left hand in my case),are new neurons only made for right side of the brain,does it improve only some of the brain regions?

It seem's you are assuming that your / the adult human brain produces new neurons over time- this is (largely) incorrect: neurons are non-dividing cells and are all formed throughout embryogenesis and very early childhood / infancy (see also this question).

Only very exceptions to this are known as adult neurogenesis (generation of new neurons), the most likely or active region in humans would be the hippocampus, however the extent or importance of the process in humans is still not really known. Additionally the hippocampus is an area of the brain that mostly holds memories and is not really related to reasoning skills or body / motor control.


Is this statement in agreement with Darwin's theory of evolution? Is the following statement in agreement with Darwin's theory of evolution?

  The number of offspring is not related to fitness.

If so, why? This is not a homework assignment, I just want to justify the reason for which this statment is in agreement (which I really hope it is).

Short Answer

The statement "The number of offspring is not related to fitness." is wrong! In other words, The number of offspring is related to fitness.

Various definitions of fitness exist depending on the model you want to use but whatever is the model you want to use the number of offspring is always related to fitness. For the purpose of a beginner in evolutionary biology, it is probably enough to assume that the number of offsprings that managed to survive to some adult age and fitness are actually the exact same thing.

Long Answer

Darwin's theory of evolution?

What do you call Darwin's theory of evolution? Do you mean the theory of evolution as it was formulated by Charles Darwin at its time or do you mean the current theory of evolution? Charles Darwin never used the word fitness (if I am not mistaken), so I will talk about the modern theory of evolution only.

Generalities

For most of the purpose it is enough to consider fitness as being the expected number of offsprings that manage to survive to some adult age of an individual given its environment and its genotype. The word "expected" used above refers to the first statistical moment (mean) of the random variable which is the number of offspring of an individual given its genotype and its environment. In other words, the number of offsprings is "related" to fitness.

Absolute versus Relative fitness

In general, we talk about absolute and relative fitness, where the absolute fitness of an individual is its number of offsprings and the relative fitness of an individual is its absolute fitness divided by either the mean fitness of the population or more often divided by the absolute fitness of the fittest individual in the population.

Fitness is a function of fecundity and survival

To be a bit more accurate, fitness is a function of both age-specific survival and age-specific fecundity. A very good measure of fitness is given be the elements of leading eigenvalue of the Leslie matrix $L$ in $\overrightarrow n_{t+1} = L \overrightarrow n_t $ where $\overrightarrow n_t$ is a vector that gives the number of individuals of a given genotype of each age living at time $t$. $\overrightarrow n_t = (n_{1t}, n_{2t}, …, n_{nt})^T$, where $T$ indicates transpose and $n_{xt}$ is the number of individuals of age classe $x$ at time $t$.

Definitions of fitness slightly varies depending on the model you want to use

One may want to use an even more complex definitions of fitness, typically when using models that apply to species that have an alternation of generation. Or when considering, genotypes that have different norms of reactions and considering a changing environment through time.

Anyway, whatever is the model you want to apply, fitness is always related to the expected number of offsprings. It would be wrong though to reduce fitness to the expected number of offsprings only, because a more complex definition might be necessary in some special cases. In any case, fitness is always an index of how much will a variant spread in a population and is therefore closely linked to the number of offsprings.


What is the genetic distance where linkage can be ignored? I heard several times that two SNPs, that have at least 1'000 nucleotides between them, can be seen as 'unlinked' due to frequent recombination events. I also once saw a paper showing a graph "degree of linkage vs. genetic distance". Unfortunately I can't remember which paper it was. Does anyone know where this number (1000) comes from?

PS: I'm aware that this topic is much more complex, especially if you are interested selective sweeps.

I think you must have misremembered what you heard.

The cut-off distance for genetic linkage is 50 centimorgans which corresponds to 50% recombination. In the human genome 1 centimorgan is approximately 106 base pairs, so the 'unlinked distance' is 5 * 107 base pairs.


What kind of spider is this? I have never seen one like this before This was on my butterfly bush yesterday with a moth by the neck.  I have never seen one like this before.  Just wondering what the name is.  This is in southern Illinois.

On iNaturalist I found a very similar picture, of a White-Banded Crab Spider.  It is found in your area.  It's a possibility.


What inhibits linkage between actin and myosin filaments What is the mechanism behind the inhibition for cross-bridge linkage between actin and myosin filaments in the binding-tilting cycle? There are 2 possible ways that are in my mind:
a.  Tn-I (tropnin-I), binding to F-actin: when [Ca2+] falls below the threshold, Tn-C are inactivated. Therefore, Tn-I relocates and SOMEHOW this causes the cross-bridge to break (ref)
b.  ATP rebinds to the myosin head, forming ATP-myosin complex. This has a relatively low affinity towards binding the myosin-binding sites on F-actin (than myosin-ADP-Pi complex). Therefore, the cross-bridge break.
From my understanding, (a) is strange: when Tn-C is inactivated, it should cause Tn-T to change conformation so that tropomyosin covers the binding sites again. But I think I am wrong as otherwise, Tn-I is useless, but I really don't know how Tn-I exerts its inhibitory effect.
Thank you.

I am not sure if you are referring to a mechanochemical cycle of "stepping" of a myosin molecule along an actin filament, or a cycle of contraction and relaxation of a muscle cell as a whole. These take place on completely different timescales and control the binding and unbinding of the two proteins in entirely different ways.
In the mechanochemical cycle, there are no proteins directly involved other than actin and myosin themselves, and the breaking and re-formation of contacts is controlled by the nucleotide occupying the ATPase site of myosin. ATP binding leads to a low affinity (weak interaction) state and ADP binding leads to a high affinity (strong interaction) state. ATP hydrolysis and nucleotide binding/unbinding "power" this cycle.
The cycles of contraction and relaxation of the cell occurs on a much longer timescale--each contraction involves many repetitions of the actin/myosin "stepping" cycle across many actin and myosin molecules, while relaxation involves slowing or stopping this cycle. This is where calcium and the troponin I/C complex come in--they are a "switch" that allows the stepping cycle to happen or not. So when the calcium is low and the troponin complex is bound, the actin/myosin interaction is continuously disengaged, whereas when calcium is high and the troponin complex releases, the cross-bridges form and release in a cyclical manner as ATP binds to myosin and is hydrolyzed.
As an analogy, think of a person walking across a room full of chairs. As the person is walking, his feet alternately make and break contact with the ground, and this is due to the coordinated movement of the legs. If the person sits down in a chair, then his legs stop propelling him entirely for a while and are still, and this is like when calcium is low in a muscle cell.


B-cell antibody production I've just learned about B cells in immunology lectures and some things are not clear to me.

Here's what I know:

1) Apparently, each B cell produces a specific antibody, determined randomly at the birth of that cell.

2) A B-cell expresses 250000 different antibodies on its surface

My question:

Are both these facts true? If so, how can they both be true if each B cell only produces a single specific antibody?

Statement 1 is true and Statement 2, false.

B cells, in the absence of antigenic stimulation express surface receptors(B-cell receptors or BCRs), which look like normal secreted antibodies (but these are membrane bound and not secreted). What is amazing is that each B cell at a particular time expresses the same B cell receptor - same as in, all receptors produced off one B cell are of the same type, say, antigen A. Now, another B cell produces another type of receptors, say, those which detect Antigen B. There is not just one BCR on the B-cell, but many - just like any other cellular receptor.

Now, there are many B cells in the body. Very much like antigen A and antigen B, there so many more antigens that our body can produce antibodies against. (The source I quote below says $\ 10^{12} $) It is a wrong notion that just one little B cell is doing that all. There are specific B cells for each specific antibody.

Each B cell isn't necessarily producing a unique antibody, but yeah, specific. It isn't unique since there must be a few more similar B cells producing the same receptor against antigen A. So it is not just one single B cell producing antibody against 'A'.

How does the body produce so many types of specific proteins?

Being proteins, they must be encoded by genes. B-cells while maturing, undergo a recombination (shuffling) of their immunoglobulin genes which leads to this differential expression of receptors, hence the diversity.

For further reading on genetics of immunoglobulins and the generation of diversity, I'd suggest - http://www.ncbi.nlm.nih.gov/books/NBK26860/


What are the implications/predictions of the selfish gene theory? Are there any testable predictions or implications of the selfish gene theory? Or it is just interesting interpretation of the observations/experimental data? If this theory is not falsifiable and doesn't generate any predictions, how can it be helpful anyway?

The Selfish Gene theory "can be defined as the idea that the gene is the ultimate beneficiary of selection".   Argren, in Selfish genetic elements and the gene’s-eye view of evolution lays out the history of the theory and the arguments for and against it.

The theory is almost certainly correct; and it's almost certainly incomplete. The theory is testable.  It predicts, for example, that there will be genes whose sole function is to self-propagate.  Those genes can't confer much fitness disadvantage to their host or they will quickly be weeded out of the population; and they don't necessarily need to confer a fitness advantage. But to the extent that different individuals have different versions of the same genes, the versions that convey a fitness advantage are likely to win the evolutionary competition.

There are, of course parasitic genes like transposons which impose a cost by requiring the host to adapt to their presence.  As long as the host is able to adapt without losing too much fitness, the parasitic genes can ride along for free.

The Selfish Gene theory provides useful insights, but it is incomplete, because combinations of genes,  arrangements of genes, and even genetic diversity within a population can provide a fitness advantage or disadvantage. Even genes are subject to "group selection", where gene A can provide a disadvantage unless gene B is also present, in which case A and B together provide an advantage. This leads to selective pressure to link the two, e.g., by placing them close together on one chromosome, which is analogous to a cooperative relationship between the genes that provides a mutual fitness advantage.


Do lunar rhythms have impact on human biology, if so, how? I'm approaching this question from the circadian rhythm perspective. A circadian rhythm is a 24 hour cycle. While doing research on deep sea circadian rhythms, I found this abstract which seemed to imply that there are some kinds of lunar rhythms (about a month long cycle). Lunar Rhythms in the Deep Sea: Evidence from the Reproductive Periodicity of Several Marine Invertebrates:

  While lunar rhythms are commonly documented in plants and animals
  living in terrestrial and shallow-water environments, deep-sea
  organisms have essentially been overlooked in that respect.

What do the authors mean by the lunar rhythms? The roughly month long menstrual cycle, or are there other ways that the moon actually influences animal/human biology?

The moon doesn't have a direct effect on metabolism. Nor does it affect menstruation (an archaic theory existed which claimed so!!). The lunar effects are due to its gravitational field which is known to affect tides (Spring tides and neap tides).
Even on a daily basis if you might have observed the sea advances into the beach in the night and recedes in the day. This effect is also because of the lunar gravity.

The abstract of the article, that you mentioned, says that moonlight may have some effect on certain organisms; I am highly skeptical about that.

I think it is just the tidal patterns that might affect the behavior of marine/coastal organisms. I am also slightly skeptical about whether the currents produced by lunar gravitation would be deep enough to affect benthic life. In that case even the heating effect of the sun can produce sea currents. Perhaps it can also produce an upward current because of differential heating.


Why don't mammals have more than 4 limbs? Arthropods have 6 or more limbs and arthropods with 6 limbs appear to move faster than arthropods with 8 limbs so I wonder whether this might have something to do with fast and efficient locomotion. But, this is just a guess. I wonder what the official explanation is, if it exists.

Number of legs in terrestrial vertebrates

Not only do mammals have four legs but actually all terrestrial vertebrates (which include mammals) have four legs. There are slight exceptions though as some lineages have lost their legs. Typically snakes have no legs anymore. Apesteguia and Zaher (2006) discuss the evolution of snakes legs reduction and report a fossil of snakes with a robust sacrum. Cetaecea (whales and friends) have lost their hind legs but we can still spot them on the skeleton. See for example the orca (killer whale, easily recognizable to its teeth) on the picture below. Pay attention to the small bones below its vertebral column at the level on the left side of the picture.

I also want to draw attention to the importance of the definition of legs. I guess that we would call something a pair of legs if it is constructed using a similar developmental pathway than current existing legs. If we are using some broader definition, then a prehensile tail as found in some new world monkeys, for example, could be considered as a leg (but only a single leg, not a pair of legs obviously). A list of animals having a prehensile tail can be found here (Wikipedia).

Did you say Natural Selection?

I think (might be wrong) that you have too selectionist a view of evolution. What I mean is that you are wondering why mammals have four legs and you're looking for an explanation of the kind "because mammal have this kind of need of locomotion and for this purpose four is the most optimal number of legs". Consider the following sentence: "If there is a need, natural selection will find a way!". This sentence is wrong! Evolution is not that easy. This false view of evolution is sometimes referred to as panselectionist.

The reality is that it is not easy to evolve such a developmental pathway as drastic as having an extra pair of legs that are well integrated into the body of the carrier of this new trait. Such an individual would need a brain, a nerve code, a heart and some other features that are adapted to have extra legs. Also, assuming such a thing came to existence it is rather complicated to imagine how it could be selected for. To go slightly further, you have to realize that there are many stochastic processes in evolution (including mutation and random variation in reproductive success) and an organism is a piece of complex machinery and is not necessarily easily transformable to some other form that would be more efficient (have higher reproductive success). Often going from one form to another may involve a "valley crossing" meaning that if several mutations are needed, intermediate forms may have low reproductive success and therefore a high amount of genetic drift (stochasticity in reproductive success) to cross such valley of low reproductive success. See shifting balance theory. Finally, even if there is selection for another trait, it may take time for the mean trait in the population to shift especially if there is only little genetic variance. A complete discussion on why the sentence "If there is a need, natural selection will find a way!" is wrong would fill up a whole book.

Gould (1979) is a classic article on the subject and is very easy to read even for a layperson.

Why 4 legs?

Terrestrial vertebrates have four legs because they evolved from a fish ancestor that had four members that were not too far from actual legs (members that could "easily" evolve into legs). This is what we call a phylogenetic signal. The explanation is as simple and basic as that. You can have a look at the diversity of terrestrial vertebrates here (click on the branches).

Number of legs in invertebrates

Arthropoda (Spiders (and other chelicerata), insects (and other hexapods), crustaceans (crabs, shrimps…) and Myriapoda (millipedes) and Trilobite as well)) evolved from a common ancestor who had a highly segmented body. From this ancestor, many groups have fused some segments. In these taxa, each pair of legs is attached to a particular segment (I don't think the segments are still visible in spiders today). In insects, for example, all 6 legs are attached to the thorax but to 3 different segments of the thorax, the pro- meso and meta-thorax (see below).

As a side note, it is interesting to know that the wings in insects did not evolve from the legs (as it is the case in birds and bats). There are two competing hypotheses for the origin of insect wings. Wings either developed from gills or from sclerite (chitine plate, the hard part of the insect). When insect first wings, they actually evolved three pairs of wings (one on each segment of the thorax). At least one pair has then been lost in all modern species. In the diptera, a second pair of wings have been lost and are replaced by halteres, particularly easy to spot in craneflies (see below picture). In millipedes, the link between segmentation and legs is even more obvious (see picture below). You can have a look at the diversity of Arthropoda here (click on the branches).

Pictures

Update 1

Asking how likely it is for a given population to evolve a given trait is extremely hard to answer. There are two main issues: 1) a definition of the question issue and 2) a knowledge issue. When asking for a probability one always needs to state the a priori knowledge. If everything is known a priori, then there is nothing stochastic (outside quantum physics). So to answer the question one has to decide what we take for granted and what we don't. The second issue is a knowledge issue. We are far from having enough knowledge in protein biophysics (and many other fields)  to answer that question. There are so many parameters to take into account. I would expect that creating a third pair of legs would need major changes and therefore one mutation will never be enough in order to develop a third pair of legs. But, no I cannot cite you any reference for this, I am just guessing!

Following the wings example in insects. Insects have had three pairs of wings. While some mutation(s) prevented the expression of the third (the first actually) pair many of the genetic information for this third pair remain in the genotype of insects as they still use it for the two other pairs. Taking advantage of that, Membracidae (treehoppers) developed some features using a similar biochemical pathway than the one used to develop wings. Those structures are used as protection or batesian mimicry.

Update 2

Let's imagine that an extremely unlikely series of mutations occur that create some rodent with 6-legs. Let's imagine this rodent with six legs has a larger heart in order to pump blood to these extra legs and it has a brain that is adapted to using six legs and some changes in its nerve cord so that it can control its 3rd pair of legs. Will this rodent have higher reproductive success than other individuals in the population? Well… let's imagine that with its six legs, it can run faster or whatever and has a very high fitness. How would the offspring of a six-leg mother (or father) and a four-leg father (or mother) look like? Will it be able to reproduce? See the issue is that it is hard for such trait to come to existence because 1) it needs many steps (mutations) and 2) it is hard to imagine how it could be selected for. For those reasons, there exist no vertebrates with 6 fully functional legs.

Well, let's assume it does and in consequence, after 200 generations or so, the whole population is only made of 6-legged individuals. Maybe the species got extinct then and no fossil record has ever been found. This is possible. It is not because something has existed that we necessarily find something in the fossil record.


L-system rule for different plant types I have coded an implementation of L-systems (Lindenmayer systems) and would like to use it to generate realistic looking trees. Is there a reference list that shows which rules are most appropriate for different types of trees? For instance, which rules are best for an oak tree, which are best for cherry trees, etc.?

There are many good papers by Karl J. Niklas where he models tree growth. I'm not sure if he used L-systems in particular, but I'm sure his work can inform you about the 'rules'. You can find out more here and here.


How does aminoacyl-tRNA synthetase recognize different tRNAs? There are about 20 aminoacyl-tRNA synthetases, one for each amino acid. Each aminoacyl-tRNA synthetase has a binding site that recognizes a specific amino acid, and other binding areas that recognize a particular tRNA through unique identity sites at the acceptor stem and/or anticodon loop of the tRNA.

When there are different tRNAs for the same amino acid, the aminoacyl-tRNA synthetase that recognizes a specific amino acid must also recognize the set of tRNAs that can be charged with that amino acid. Given that all tRNAs have different anticodons, how does the enzyme achieve the aforementioned task?

You give the answer in your question:

  binding areas that recognize a particular tRNA through unique identity sites at the acceptor stem and/or anticodon loop of the tRNA.

The point is that aminoacyl-tRNA synthetases that recognize tRNAs with different anticodons have to supplement any partial codon recognition with recognition of common features elsewhere, in particular the anticodon loop. Unfortunately this has evolved on a case-by-case basis and there is no simple ‘code’ one can refer to.

Thus, Berg et al. (Chapter 29), in discussing  threonyl-tRNA synthetase, write (my emphasis):

  As expected, the CCA arm extends into the zinc-containing activation
  site, where it is well positioned to accept threonine from threonyl
  adenylate. The enzyme interacts extensively not only with the acceptor
  stem of the tRNA, but also with the anticodon loop. The interactions
  with the anticodon loop are particularly revealing. The bases within
  the sequence CGU of the anticodon each participate in hydrogen bonds
  with the enzyme; those in which G and U take part appear to be more
  important because the C can be replaced by G or U with no loss of
  acylation efficiency.

The four codons for Thr are ACN, so in this case recognition of two bases of the anticodon will identify all tRNAs.

A diagram from Berg et al. showing the multiple interactions in threonine tRNA-synthatase is shown below.