CharonY

What do you mean? There were only three episodes and they were quite awesome.

You mean the historical Silk Road? Well that one got pretty started to disintegrate with the fall of the Mongol Empire. By the end of the 15th century it pretty much ceased to exist.

Sometimes the free version is the pre-proof or the ahead of print version. After the article goes into print it gets moved to a paywall.

Work with Bordetalla pertussis follows standard BSL2 protocols. While it is highly infectious, there are treatment options. Technically, event at BSL1 theoretically you should not come into contact with the agents. BSL2 adds a few extra layers of caution. The biggest risk is typically complacency as no protocol in the world can replace situational awareness, knowledge of workflow and common sense. For your specific question, typically you should prepare your slides under aerosol-controlled conditions, and treat it as infectious material subsequently. You should ask your safety officer, and request the rulings on it. However, you can always protect yourself more than asked for. It is your health, after all. If e.g. the protocol does not ask for sealing of the slides, depending on what you intend to do, you may still do it. Or, even if your instructions does not tell you disinfect the slide holder, you may still want to do it even if you have not made a spill (but keep solutions away from the optical parts). Remember that material only gets airborne if you somehow cause aerosols or turbulence. So, minimize it and be aware e.g. of areas where you have drafts (such as vents and doors with pressure differentials as commonly found in BSL2 labs). If you move through those areas, you must have your samples closed off, for example. And additional part of this is also self-monitoring, in case you develop cold symptoms, for example. Much of that should be covered in your respective safety protocols, but again, use common sense on top. These manual are rarely exhaustive.

Worst combination: someone who does not shut up but only has little knowledge about what he/she is talking about. Triple points when doing it among professionals that actually do.

Typically I ask them how deep of an answer they want to get rather than trying to force feed them more than they are willing to take up. Also, as others already mentioned, the trick is not to lecture them but to figure out what pieces they need to understand a particular concept.

Well, the overarching issue is that toxicological regulation of industrial production is, at best, poor. Many useful products, such as organohalogens are now found to bioaccumulate and pose unrecognized risks to human and wildlife health. Then there are materials such as nanoparticles for which at best conflicting tox results are found in literature. Nonetheless, they are produced and released in high amounts and historically regulation are done in a reactionary fashion, if at all. REACH, I think, was somewhat intended as a compromise as the only alternative would be a centralized tox-assessment, that would severely hamper the use and development of novel compounds and materials. As compromises go, they are excellent in pissing off everyone, as the tox information gathering and reporting would be mostly under the control of the companies (which have a clear interest to suppress potential issues), and on the other hand the companies have to deal with the added cost. And of course there is on top the whole issue of how informative traditional testing for human health is to begin with. But that will not be touched with a ten-foot pole as we need the assumption that things we are exposed to are relatively safe. The real issue is IMO that we do not have a good idea how to balance industrial use and production with a decent assessment of environmental and human health effects. If we do it as it is right now, we have to wait until after damage has occurred to do something, which is very bad for non-or very slowly degrading compounds. If we ant to test until we are certain that something is safe, material production and development will come to a grinding halt. Yeah, I have no good solution except maybe developing improved, faster and more accurate tox test systems.

Calculating CO2 sequestration is actually trickier than one would imagine and there have been huge variation in calculations, depending on the parameters being measured (but obviously also dependent on type or age of the forest). Typically value range from 2-60 lbs CO2 per year. In urban settings these value are typically much lower.

Suffocation is probably not the best way to describe cellular processes (though it is not completely wrong). The mechanisms are correct. cell death occurs due to inability to create ATP. Proximately this is caused by blocking the cytochrome c oxidase, the terminal step in the electron transfer chain to oxygen. As the effect is similar to present tissues to hypoxic or anoxic environments it could be termed suffocation in a casual way.

Yeah I assume that mathematics has slightly different rules from the experimental sciences. But there are also very different rules depending on the publisher. Nature, for example, only charges color pages, analytical chemistry is completely free, whereas some high-ranked society papers have a publication charges of up to 170$ per page. One distinguishing factor is that acceptance is independent of the fee and if you cannot pay an accepted paper is typically covered by the journal. But there are also various degrees of licenses ranging from open access to some rather restrictive agreements.

One should also note that many reputable journals charge publication fees. Most notably for open access, but also often color images and sometimes general page charges. The impact factor can also be a relevant metric, as a high one indicates that articles are frequently cited. A common strategy is to look up the journals in your field and aim the for the highest IF for your paper that is reasonable. Do you mean journals for the scientific community or for the the public? The former happens on an international level and national journals (i.e. published in non-English languages) are typically marginalized in most disciplines.

There are many reasons why people pursue academic careers. Some because they love teaching, others (me included) because it is pretty much the only job where you can work to satisfy your curiosity about the world and still get paid for it. But what is true that academia is not a 9-5 job where you can do your job and just be satisfied by it. You have to be driven to a point to pursue a career that is risky (low success rate) less monetary rewarding than alternatives and eating much more of your time and brainpower than your other jobs. If that does not sound attractive to you, you are well advised to look for other jobs, This is a good plan, I will add that you should try to start networking as at that level a good network has a much higher chance to score a rewarding career than waiting for an opportunity to present itself. Remember, a postdoc is not a career, it is a waiting position that you have to utilize to get one.

Well, conviction and/or the need to carve a niche for their career. Of course at the beginning there will always be a bit of overselling, before there is enough data to demonstrate the actual impact of new findings.

Very clear explanation, hopefully this will clear things up (considering that previous attempts obviously failed). It is sometimes amusing (and slightly worrying) how convinced people can be about their misconceptions.

What is described in the OP has to be seen and discussed as multiple steps otherwise a discussion will be very confusing. First is the appearance or existing of allelic variances. There are dark moths and light moths even before the industrial revolution. However, before we talk about frequencies we have to distinguish their emergence due to mutation (which is random) from stochastic effects on the gene pool. While mutations are random, it is not what is meant with random or stochastic events when we talk about allele changes in populations. The observed frequencies or frequency changes (i.e. increased prevalence of dark moths since the industrial revolution, at least before changes in air quality) are instead the result of ongoing selection. I.e. the amount of soot resulted in dark moths to be more successful than light ones. Hence the observed frequency is not the result of (random) mutations, but clearly of selection. An example of genetic drift as a stochastic even would be more like this. Assume that there only a handful of moths alive, say with a 50:50 ratio. All but one randomly die (i.e. the color of the moth has no bearing on whether it lives or dies). Now all progeny come from this moth . Ignoring the obvious biological issue with this thought experiment the entire population will now be either light or dark, but not because the environmental pressures (i.e. soot) resulted in the frequency change but to an event that is mechanistically not related the traits conferred by the phenotype. To summarize: the increase of dark moths (which are actually now decreasing with reduced particles in the air) is clearly deterministic and non-random. Selective pressures (predation in this case) favored the black phenotype.

I wished those were around 10 years ago (but my own has grown sufficiently to be workable now). With regards to tools I can only recommend to use a decent system for organizing and citing papers and stick to it. Other than that probably figuring out whether one really wants to stay with something like Word (or other office packages) or try to use something like Latex (later on there will be less time to try out things). Other than that most tools would be somewhat specific to the type of research one is doing I would think. However a very useful tool in many areas is the use of something like onenote or similar that can take and organize a variety of data types (e.g. microscopic images as well as spectra for example). While many still like to use a lab book as primary source, I found that in my area the amount of data easily overwhelms paper-based organization. And hybrid approaches tend not to work out too well, especially for the PI, trying to make sense out of them.

Of course that reasoning is just plain silly. I am going to provide a real example, but will use some reasonable but made up narratives to explain them (simply because I have no time to dig out the actual available data). Sickle cell anemia. Physiologically this disorder and can result in negative heatlh outcomes. Thus as a whole one would expect that the involved alleles would be under negative selection. Thus the occurrence in a population should be mostly driven by mutations, for example ( there are other contributing mechanisms that could stabilize an otherwise detrimental allele, but I will ignore them for now). In many populations this is the case, the incidence of this allele is fairly low. However, there are notable populations that have a higher frequency of that allele than others. Now there a number of possible mechanisms, but let us focus on two alternatives that have been the subject of this thread: - drift: the populations with high sickle alleles may have been randomly started with sub-population that had a high amount of sickle allele carriers and not enough time has passed for selection to kick in and reduce the frequency by much, or: - selection: for some reasons in these populations the sickle cell is under less negative selection than in the other populations. This can then be investigated by looking at population variance (to see whether there was indeed a small starting population), migration patterns and distribution of incidence over the world. What we see is that distribution is quite wide, spans many somewhat separate populations and as whole does not fit the assumption of drift. Thus one can speculate that some balancing selection is going on that allows higher frequencies than in other populations. Further studies have correlated incidence of high frequency populations with malaria incidence. I.e. in regions with high sickle cell incidence, there is also strong selective pressure from malaria (or vice versa). This is an example where the data clearly favors selective forces rather than stochastic ones. It also (hopefully) illustrates that a) one need quite a bit of data and has to look into population rather than focusing on individual events to understand the way selection and other elements shape populations and b) that there are means to do it, but it requires more than just simple narratives. And again, I am using simplifications (but which follow existing data).

As I mentioned earlier, the studies have to be on populations and expanded over larger time scale. You cannot go in immediately after a landslide look at survivors and deduce that. That would be like standing in the rain and try to use that singular information to determine where the water came from and predict whether there will be more rain over the next year. Rather, looking at frequency distributions you could see that at some point there was a genetic drift in that population. You will likely never know whether it was a landslide, or something else, though (unless the area has a high propensity for such effects). The reason is that ongoing selection will eventually result in a different distribution. For example, even if after the event an allele is over represented, over time, and assuming sufficient generations have passed, a equilibrium of sorts will be found. If there was positive selection of one allele it will increase in frequency and eventually become fixed (i.e. there will be no other alleles in the population). If the population was large to begin with, the stochastic events will have little to know influence (unlike selection). It is true that especially in very small populations and if sudden things happen recently (i.e. not enough time has passed to have a sort of equilibrium), it will be very tricky to figure these things out. But again, just because we have trouble seeing them, it does not mean that they do not happen. They predict different outcomes which we can observe. Just not for each and every population. In other words, it is important to look at these aspects in a population and time-dependent manner which will smooth over singular events (unless large enough that it affects many generations). Note that I am doing extreme simplifications. Evolutionary sciences have been looking at many things which a fine comb that I have little or no knowledge of as it is not my field of expertise. Actual research and existing models are orders of magnitude more complex than what is being discussed (and sometimes dismissed) here. And I am certain that my simplifications will not hold when we actually start looking at the complex matters (rather than trying to get some basic misunderstandings out of the way). If someone really wants to learn a bit more about what it is all about and why the stuff you learned in high school (and even sometimes basic courses in college) are not nearly enough to claim understanding, I warmly recommend Evolutionay Biology by Futuyma, in which the explanatory framework is explained nicely and accessibly (and I admit, that I should re-read it at some point, too). Starlarvae, as I said before, these distinctions and uses are important for evolutionary research and have provided a massive amount of research. Just because the models are not fine enough to explain everything, they still yield useful predictions that can and have been tested. Claiming something else is ignoring the existing body of literature. "There is no way to know" is simply false as you can build models in which either drift dominated or selection, run it over genomic data and see where the best fit is. You will not know in detail what happened in the history of every organism, but that is not what evolutionary sciences is about. It is like trying to through out all physical models on fluid flow because they are very unreliable to predict turbulent flow. Context matters. Overtone, I am tired of repeating myself. It appears that others got the salient points, feel free to redefine things to better fit your world view rather than learning about the world. For some that is the easier approach to get them through life.

Yep, That is what I meant. Under that circumstance the type of the allele (and any traits they may have conferred) had no influence on whether they survive that particular event. I would like to stress that while I also used survival as an example, the real thing to look at is reproductive success. If the catastrophe had hit only a group of non-reproducing individuals (e.g. animals that are past their reproductive age who also do not social activity that may influence reproductive success of relatives) the effect would not be the same if it hit a potentially reproductive group,

I would say that these things go hand in hand, if you realize that you are talking about different things, you more likely to use different terms or otherwise try to distinguish them, If you conflate concepts, you have missed the finer points.

I hoped that I made it clear in the last posts but unfortunately I see that you are confusing things again. I will provide a simple example and leave it at that as I feel I am just repeating very simple things over and over again. Imagine a population in which 100 individuals of allele A, B and C exist (each). Now a rockslide kill 25 individuals, independent of their alleles. As the population is small we will see a change in allele frequency (drift) but it is absolutely independent of what the alleles the 25 killed individuals had. Thus we have a stochastic and not a selection event (and you cannot handwave that distinction away). In a large population the same event may leave no trace over generations and will be hard to impossible to spot. Second example: Imagine some organisms in deep sea with a distinct life cycle: Sessile and motile. The amount of time they spend in either form is determined by two alleles, A (mostly sessile) B (more motile). According to various influences there is a given frequency distribution in the population we are looking at. Now suddenly a thermal vent opens. This releases compounds that are harmful to the organisms. Directly at the vent, both alleles are killed similarly (i.e. stochastically) but toward the edge, B has an advantage, they start moving slightly further away and have a higher reproductive rate than A that just tend to stick around and need to invest much more energy into their stress responses than into reproduction. Now if we sample the population over time, we will see a continuous increase of allele B in the give population. In the second example a catastrophic event created two effects, a stochastic one, that changes frequencies randomly but then exerts a selective pressure that shapes the allele distribution in distinct way. The reason why have to distinguish (not dismiss) these different mechanisms is because they create different outcomes. As we can see these differences it makes not sense to claim that they are indistinguishable. I honestly get the feeling that you kind of see that but have a hard time to admit to ignorance and need to explain those things away. Which is a pity as it is another lost learning opportunity.

A similar thing, albeit at a somewhat lower level can also be found in bio, mostly in the area of evolution. Almost everyone has a rough idea what it is and are pretty convinced that they can understand and explain it. Yet the detailed complexity of evolutionary theory is highly complex and even as a biologist I cannot claim that I actually understand it with the same certainty that many layperson exhibit when talking about it. Typically that does not end in crackpottery, unless people start extrapolating from their assumptions. With regards to OP, crackpotter in this forum appears to dominant in physics, but in the wider scope of things I still feel that in biology we may have a larger amount of high-end crackpottery. With that I mean scientists (often emeritus or at least established ones with a fulfilled career) that start looking at bio and try to explain things differently. This is a great thing, mind you, unless they decided that they can skip existing data and knowledge (similar to regular crackpots). In the area of astrobiogy there are some very weird things (most being self-published, but every now and then a weird regular article pops up). Which is a bit of a shame as it may negatively affect this off-discipline approaches that are actually worthwhile to investigate deeper. Every now and then there is also the opposite where someone from a different discipline tries to do physics (of sorts, I recall a prominent example on our very own boards). But that is the beauty of physics, often it can be easily demonstrated to be nonsense by maths. Bio and some extent Chem lack those rigors and makes it harder to spot the crackpot.

What Wilson refers to is the complexity of the elements and contrasts it with our potential ability at some point in the future to manipulate genes (or something to that extent). Why is natural selection important? Because we know it exists and that it shapes allelic distributions. This can be demonstrated experimentally quite easily, although it is difficult in the field. Just because we cannot explain it completely for every populations does not mean that it is worthless. If that was the case we would ditch the concept of gravity as even as concept it is not completely understood (at least afaik). With regards to physiolgy, that is a weird statement, as physiology does not happen in a vacuum. Our understanding of molecular physiology has sky-rocketed, yet the interplay with the environment has not kept up (as it is much harder to research), It is possible that this may have skewed your view a bit). However, one just need to look at the most prevalent organisms (i.e. bacteria) to see that it is certainly no the case. Environmental factors play a huge role in their genotype, which is much more fluid than in more complex organisms.

This is precisely what I try to tell you. If the shift is independent on the alleles and their properties (i.e. allele A is not more likely to be eliminated as allele B, unless by pure chance) this is non-selective, but stochastic. Genetic drift is a stochastic effect. Founder effect is more a starter position that affects the spread of alleles and both, stochastic and selection events can be involved. As I said, you got the right things in your mind, you just need to separate them a bit more.

Very long read but the first few sentences already highlight lack of understanding of basic biology: The immune system adapts itself depending on what it is exposed to. Moreover there are variable regions in the recognition part of antibodies that get reshuffled so that mammals have a large variation of potential antigens they can potentially identify. None of them has anything to do with evolution as they happen in individuals (evolution is a population game) and on top within its life time. What do mutations have to do with pathogens? What are pathogenic stresses? Why would they increase mutation rates? However, the single most important misunderstanding here is mixing up mechanisms that effect the physiology of a given individual and try to extrapolate evolutionary mechanisms from it.If an organisms reacts to a stress, we are talking physiology, not evolution. If we talk about mechanisms and their spread and prevalance in a given population, we are starting to touch upon evolution.