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This is part of an interesting and ongoing discussion among historians. A position that was developed directly post WWII is basically grounded in a similar reasoning provided here. If an invasion was necessary, the losses would have been huge. Thus the loss of civilian lives would have been acceptable. Since then another school of thought has been formed which basically takes overtures from the Japanese into account. For example, in secret Japan's leader were trying to mediate peace via the Soviet Union. But these overtures where dashed when the Soviets invaded Manchuria and Korea. The Japanese Supreme War Council itself was split, i.e. while to the outside an all out war until self-destruction was propagated to the masses, what is known from internal deliberations were basically at a stalemate. The issue was not so much whether to surrender, but under which condition they would accept it. This included for example the preservation of the status of the Emperor but also who would be responsible for demobilization and so on. However, that would have been unacceptable to allies. As a whole it is of course pure speculation whether the stalemate could have been broken say with only one bomb, or even without goes into the realm of speculation, of course. But it is rather clear that the bombs have helped the faction which was in favour of peace anyway. But I think the fact that in the background Japanese leadership was trying to figure out a way to surrender shows that the situation was more complex than the stereotype of fanatically death wish may make it seem (which, to be fair, was part of their propaganda system instilled into their troops). As such, answers to these questions are also complex and, at least without contemporary documents highlighting the thought processes of the involved leadership, very difficult or impossible to answer with certainty.

These are great points, though I would add to 2) that I do not think that the Trump administration is an anomaly per se. Rather I think it is almost the next logical development, considering the unholy alliance of anti-science agendas that have been effectively collected under the GOP tent. We have got the religious anti-evolution movement, the industrial-backed anti-global warming movement and so on. Some anti-science movements which were either diffuse or had left leaning roots (e.g. the pseudo-eco anti-vax elements) have been fully embraced and integrated into a right-wing movement which basically has declared science and associated elements as enemies. Strategically it is of course a tactic to avoid accountability but has become a mentality. 3) is spot on, it does not seem to me that the parties in the US have actually any real cohesive philosophy. It is basically an identity of sorts that folks associate themselves with with massive internal inconsistencies.

Found the link https://www.wsj.com/graphics/kwc/ It seems that some of the embedded items are defunct, unfortunately.

Yes, probably. I have been going through quite a few student theses recently and my brain just blanks out things that do not make sense for self-preservation, I think.

... have you been around for 2020? You know, the whole respiratory virus thing? The reason why sweatpants are the new business casual?

The WSJ also had an interactive website where you could explore parts of the old Kowloon Walled City. I am not sure how much of it still worked. I always wondered how interesting that must be for street photography.

Just to add to the issue of variants. Even if vaccines are effective against the new variants, there is the issue that by now it is pretty clear that they have a higher transmissibility. B.1.1.7 has effectively replaced the wildtype and has up to 90% higher transmissibility. Based on preliminary studies B1.617.2 seems to be even higher (and in places is starting to replace B.1.1.7). The reason why that is relevant is that a higher level of immunity within a population is required to deal with a higher transmissibility. A value to indicate the ability to spread is based on the basic reproduction number (R0) which is the average number of folks infected by a given infected person within a susceptible community. The effective reproduction number (Re) is then dependent on the susceptibility (s) of the population, taking e.g. immunity due to vaccination and other measures into account. I.e. Re= s*R0. In order for the disease to vanish, the effective reproduction number needs to go below 1. As the immunity in a population is given by 1-s we can then look for 1-s > 1-1/R0 to estimate how much immunity we need for that to happen. Originally the R0 for the wildtype SARS-CoV-2 was estimated to be around 2.5, which would require only 60% immunity in the population to stop. However estimates with larger data sets (and with the unknown impact of undetected spread) have put R0 quite a bit higher (3.6 and up), which would require over 72% immunity to achieve herd immunity, with estimates as high as 84% Now if we increase R0 even higher for B.1.1.7 and B.1.617.2 we are approaching required immunity levels of 90%, which is basically impossible to achieve just by immunization.

Well, one does not even need to look at what he said. He held rallies in the thick of the pandemic. https://siepr.stanford.edu/research/publications/effects-large-group-meetings-spread-covid-19-case-trump-rallies

Your argument was that basically that because many species are promiscuous, one selected one (humans) must therefore also be promiscuous. This is not a logical conclusion, as you said yourself that there are apparently differences in promiscuity in nature ("most" does not equal "all"). In other words, you would first have to figure out why certain species are more or less promiscuous in order to establish whether it likely (or not) applies to humans. If nature was based on majority rule, we all would still be bacteria and just reproduce asexually. Likewise, you cannot dismiss whether our society makes promiscuity more or less likely, as you have not established conditions that are associated with promiscuity that we could discuss. I am going make an analogous argument to yours to demonstrate why your original argument does not hold water: Most animals are arthropods (well above 80%). Therefore animals are evolutionary primed to live like insects. What we can discuss, which is somewhat outside biology is about human society and how that influences partner structure. But again, doing sweeping positive correlations and then somehow invoke evolution is just bad science (and which is why evolutionary psychology as a discipline is in deep trouble). But even using somewhat shaky arguments in that area, it is very weird that you focus on female promiscuity. Assuming big fitness arguments (and again, research has shown that it is actually far more complex than these simple narratives), in most mammals, including humans, males benefit more from being promiscuous than females. The reason is fairly intuitive, because a) in most species females invest more into the offspring and b) extra-pair copulation for the female does not automatically result in more offspring as for males. Now, this view has been challenged to various degrees, mostly using insect models, again highlighting my above argument, if you will. In observational studies In birds, reproductive success seem to increase for both, male and female partners in a number of partners. However, the advantage for males is still more obvious than females (and the latter is trickier to study). If we focus on humans, there is of course the issue of social norms- in many societies it is more permissive for men to be promiscuous than women. As such, it is not surprising that most surveys indicate higher promiscuity in men, but this again is challenged with changing gender roles. So again, another societal, rather than evolutionary factor. I suspect that what you tried to say that serial monogamy is in polygyny (succession of female partners, as the reverse does not make sense) but why not polyandry? This is not to say that the area of research is not fascinating, but I think the way you start off is far too narrow and biased toward a certain narrative that it actually runs counter to existing research. To kick off such a discussion with a focus on human species you may want to look at a few accessible papers such as Schacht and Kramer (Front. Ecol. Evol. 2019) for a general review. The paper does actually discuss (and refutes) some of the common popsci narratives.

Link to survey does not seem to work. In nature you can find every single strategy in partner search. Using the majority argument to try to apply it to a specific species is silly, of course. Every species has their particular constraint and is more or less likely to have a specific reproductive strategy. Note that in humans many potential constraints are changed due to e.g. availability of reproductive control, but also things like easy availability of food or water (for most) and other technological and social elements. Finally, few things are that hardwired to begin with. We have learned to live in a highly artificial environment. None of us are hardwired to move faster than running speed, yet we can drive cars, for example.

I think that actually kind of illustrates how the public misunderstands how population risks are estimated. Sure, individually speaking a mask could be beneficial, so is a hazmat suit, so is hand washing and so on. So for public health recommendations the actual question is not whether these measure fundamentally work, but whether in public setting they can reduce overall transmission. The gold standard here are trials, where you have got groups of folks asked to e.g. either wear masks and wash hands, only wash hands and then calculate the overall reduction compared to a control group. As mentioned, this data was mixed and the outcome was sometimes not significantly significant, or had moderate reduction. The largest effects of facemasks where seen in clinical settings (e.g. workers cleaning rooms of infected people), which suggests that focused mask wearing in high-risk environments. Moreover, around that time, only few known cases existed in USA and Canada, and I suspect that officials at that time point were thinking that the pandemic will play out like SARS-1. I.e. few cluster cases that will be tracked rather quickly with a concentration of cases in hospitals. So if you identify folks quickly and make them wear masks (and have everyone interacting with them do the same) would be an effective way of PPE use. Remember that health officials where ridiculed for overhyping SARS (as well as H1N1) so that could also have coloured the response. It was only after that that we understood the differences in SARS-CoV-2 (in my potentially faulty memory) it seems that really the outbreak in Europe has made folks wonder over in NA that things may not go as well.

Perhaps just a minor point, but these articles are not science papers, they are part of the news section. If someone found valid scientific evidence for an accidental release (whatever it may look like), it will for sure be published in a highly ranked journal as it is clearly a hot topic. I doubt this argument is in good faith, but for those interested I will say that a) epidemiological studies in the past on respiratory diseases such as influenza had mixed results and were generally much lower than e.g. hand sanitizing; b) significantly better effects were seen when symptomatic patients wore masks and c) effectiveness was also sometimes quite low because many folks in theses studies did not wear the masks consistently or correctly. In addition to this, there were other factors that came into play at the time masks were not recommended: a) the assumed infection numbers were still low (which might have been an underestimate base on what we know now) b) folks did not know that pre-symptomatic spread was likely significant, c) supply chain issue limited access even for health care professionals. So in total the risk assessment at that point was pointing toward the fact that mask wearing was likely not helpful. The calculation shifted once it became clear that a) large scale contact tracing failed, b) even folks without symptoms could spread, making it much more important that everyone masks up. In other words, the messaging was based on risk assessment using available info and changed once new information came up. The other example that you provided is acting on virtually no information and then keep denying reality even as bodies piled up. No one looking at facts would see equivalency there.

I have no idea what reaction 1-5 means. Without documentation these descriptors only make sense to you and you'll have to better describe what precisely you are doing and how you are doing it. That being said, assuming that this is just a lab course, I would talk to instructors/TAs to have them take a look what you are doing. If it is part of undergrad research you need to talk to your supervisor. Especially if we have many students we do not necessarily know the issues that are (as we rely on reports an what the student tells us). If the reports/descriptions are superficial or based on things folks may have read on a random forum, it actually makes troubleshooting harder for us. We generally do have certain protocols for a reason (e.g. the way we set up master mixes) a precise description of what you did (at every step, in detail) can help spot deviations and issues. One simple thing you can do for yourself is to use water and check how precise your volumes are using an precision scale.

If the reaction is well established and the components worked in the hands of others it is quite likely pipetting error. Inhibition is unlikely if the actual target worked well. It is possible that the internal control (depending on what you use) may have degraded, but again, if the same material worked for others, it is unlikely.

There many articles about that and even a wikipedia page https://en.wikipedia.org/wiki/Trump_administration_political_interference_with_science_agencies. The only thing Biden had to do was basically not to do that. If you have missed the last year, there is a little thing called COVID-19 and one of the presidents said that it would go away on its own. Guess which one that was. A colleague of mine basically characterized the left-right attitude to science the following (aptly, I might add): the left ignores science that hurts them politically. The right actively antagonizes and suppresses science. The various science journals (which includes medical journals, btw. who were shocked by the Trump administration) typically do not protest because something does not align with them political. What they protest is the undermining of science, which includes muzzling of governmental scientists, limiting free research and data exchange, enforcing a worldview that simply is not grounded in reality (e.g. climate change denial, pandemic denial) and so on. Trump obviously is not the first one, there have been long standing challenges regarding e.g. evolution with creationist lawmakers, muzzling of climate scientists in Canada under the Harper government and so on. Trump was egregious because how rapidly he dismantled agencies that were supposedly in place to protect folks but then on top it fell apart when he mismanaged the pandemic (by combining mostly useless actions with denial). So going back to OP, if politics decides to shape science in their image by suppressing research and free thought, then absolutely science has to become politic to fulfil its core function, which is to extend knowledge.

! Moderator Note Since it appears that the post is not about discussing a topic here but airing grievances against random folks on twitter, the topic is locked.

If the compounds have different solubility the results in disk diffusion are difficult to interpret at best. While some folks use organic solvents as carriers, I am quite skeptical about the usefulness of such tests. MIC determination in broth is better but you would still need to see if solubility is an issue (and run the test with organic diluent and an appropriate control). Considering that you likely have a good idea of the mechanism of inhibition I would actually also check whether the medium composition has an impact- we found MICs to be a bit of a moving target and does depend on a number of factors (including medium manufacturer, but also growth state of the diluted microbe).

So there is a view that metabolites of the acetyl coA pathway are ancient. However, there is also the discovery that certain alloys can convert hydrogen and carbon dioxide into formate, acetate and pyruvate. I.e. they can be formed without enzymatic activities which would in theory allow organisms to utilize them, without having any producers first. (Preiner et al. 2020; https://doi.org/10.3390/life8040041)

Not my field of expertise, but fundamentally the purification step (e.g. columns vs liquid vs magnetic bead extraction) is less critical as there are many variations to improve yield or other critical parameters, depending how you scale them. Often the issues before that step, such as how fresh the specimens are and the lysis steps which have a higher impact. And how critical it is, also depends on the precise workflow after isolation. If you just want to do a PCR e.g. on mtDNA, it is easier than getting high quality DNA for whole genome sequencing, for example. From what I can see it is fairly straightforward for fresh feathers, but if you are dealing with older ones, you might want to look at protocols that specifically refer to molted feathers.

Somewhat possible, but the compound should still have some influence. In the assay you should have sufficient nutrient and cell density to create a lawn in absence of interfering compounds. However, nutrient levels do decline with growth and the ability to grow in presence of stressors is dependent on the cellular status. Another issue is that the assay cannot identify e.g. dormancy or tolerance. One way to check it is to remove the disk and replace it with one soaked with medium. If you see small colonies in the inhibition zone, or even a lawn developing, that would be indicative of growth inhibition instead of killing, for example.

If you want your product to be biotinylated, you need to attach a biotin. This can be done directly during synthesis (i.e. order it if you get them commercially), but there are also labelling kits if for some reasons you want to do it on your own. If you want to get a new restriction enzyme site, you need to add it to your oligo upstream of your priming site. I think "Molecular Cloning" (Green and Sambrook) should have chapter about it, but it is fairly common nowadays and I would think that many suppliers (e.g. NEB) will have information about that (though of course they also want to peddle their specific products, you can ignore that).

And that is precisely why we did not manage to stamp out the disease in the first place and why the chances of stamping it out is diminishing. I wished I could say I was surprised but I really am just disappointed. In addition what has already been mentioned, one can get more details from state/provincial data as well from COVID-Net (USA). Looking at the cumulative values, about 20% of all recorded COVID-19 related hospitalizations in the US were folks below 40 years. Also, being fit is is not confer magic protection. There have been plenty of hospitalizations of folks who had no known comorbidities. The data in papers are pretty broad (as they are all over the world with different cohorts), but we can see among folks in the 40s without comorbidities about 15% develop severe symptoms, including death. I.e. while there is a correlation with worse outcomes in cases of certain risk factors, thinking that you are safe just because you have no (known) issues is very risk (and again, at minimum you would be likely become a spreader and incubator). Also when it comes to background monitoring of effects, COVID-19 vaccines are administered as a much higher rate than other vaccines (influenza, for example is typically only as high as 40% among the target age group). So we do not have good apples to apples comparisons here. However, there is clinical data from the trials and if we look at e.g. the Pfizer documents, about 0.6% of the vaccine group had at least one serious adverse event compared to 0.5% in the placebo group. Adverse effects in case of COVID-19 in the 30s age bracket (minimum hospitalization) is somewhere around 14-20%. So if the question is not between two different vaccines but between vaccines and COVID-19 the answer is clear, even if one ignores the public health need of vaccinations (which at this point one really, really shouldn't).

Polio is still endemic in Afghanistand and Pakistan and I believe there have been irregular detections elsewhere. To OP, at this point it is not clear. If vaccination was available early in the pandemic and/or if the infection levels where kept at a low level until now, and if everyone was getting vaccinated, then the answer would have been a yes. However, one should take a step back in understanding how eradication works. It is not necessarily just a matter of vaccination, but it is about creating a situation where an infected person is unable to infect enough folks to sustain pathogen spread. Herd immunity could be achieved by a combination of vaccination, immunity, as well as social measures (e.g. distancing) for example. But right now we have still over 14.8 million detected infections (and likely many more undetected) which is a huge reservoir for the virus and has a high risk of the creation of new variants. I have lost track of how many variants there are now in circulation, though only relatively few are classified to be of concern. Nonetheless, there is a big risk that for at least some of the variants, the vaccine will be less effective. We have already observed across the world that the UK variant (B.1.1.7) has displaced the wildtype. And this also affects how we should interpret vaccine efficacy data. Pfizer/BioNTech and Moderna efficacy data were generated earlier in the pandemic where mostly the wildtype was around. However, AstraZeneca already included data from patients with the B.1.351 (South African) strain, against which the vaccines might not work as well. Some smaller data sets indicate for example that the Pfizer/BioNTech vaccine is about 89.5% effective against any infection with the B.1.1.7 variant and only 75% against B.1.351 in some groups (DOI: 10.1056/NEJMc2104974). However, they still protected with over 90% against severe diseases. The issue there is that while it prevents hospitalizations, it is still possible that folks get infected and may potentially transmit it to vulnerable persons. Aside from variants we got the issue that in many (most) populations we will not achieve anything close 100% compliance. Surveys in various countries, including the US, UK and Canada, indicate that up to 35% of those surveyed indicated that they won't get the vaccine. Another big issue is worldwide-timing. If vaccines are only provided in richer countries, then those who cannot afford it are basically a reservoir for the virus. If we take another year to vaccinate them, it will be a full year where new variants can rise. But even if just focus on local issues (and I want to emphasize that this would be really stupid to address a pandemic), we can do a little bit of a back-of-the-envelope calculation here. Let's focus on vaccination as the sole measure and let's assume we need ~80% immunity in the population to reach herd immunity. Let us further assume that the vaccines have an effectiveness of 90%. In order to achieve 80% immunity, it would be necessary to vaccinate 89% of the population to reach the herd immunity target. Only few countries (according to polls) are at that level of theoretical compliance. If we use US polls as an estimate of vaccine willingness (~75%), we can estimate that with a 90% effective vaccine we will have ~68% immunity, lower than almost all current estimated requirement for herd immunity. If the vaccine effectiveness goes down to 80% (due to variants for example) we would need to vaccinate every single person. So even if there are no barriers to providing vaccines to folks, it is tricky to rely on it alone to push down viral numbers to a degree that there is no net transmission. So no, based on the current situation I actually do not think that the current rollout in practice is likely going to eradicate the virus completely. The more likely scenario (I believe) for now is that it will become endemic. However, the optimistic scenario is that it will be better controlled via regular vaccines (and treatments) and won't have the same horrible death toll in the future. It might indeed become something like a flu, which, I want to emphasize has regularly costed many lives and is not really harmless either (though compared to COVID-19 it is comparatively tame). And as a minor sidenote, I would like to emphasize how behavioral changes have affected flu-related deaths. In the years prior 20-50k folks are estimated to have died each year from influenza in the US. Last year it was a few hundred reported so far.

For the most part it is used semi-quantitatively by measuring and comparing inhibition zones. It is in principle possible to try to estimate concentration, but it is a bit tricky. As the process is diffusion, the concentration decreases with the square of the distance. But then you also need the diffusion coefficient of the compound and also consider that diffusion happens also in three dimensions. But often the theoretical values or simulation are going to bit off unless you spend a lot of time to make the assay very accurate. However that is counter the typical benefit of such assays, i.e. being quick. There are quite a few other issues with quantifying antimicrobial activities (e.g. factors that influence MICs) but that is not specific to disk diffusion assays.

The use if siRNA itself to knock down genes is universal and been discussed as an antiviral for quite some time. The tricky bit is the delivery to target sites. In this case, they took advantage of the fact that certain lipid nanoparticle compositions have been shown earlier to accumulate in lungs, so when delivered intravenously they were able enrich the siRNA in lung tissues. For other tissues and cell targets (which include HIV) it may be more difficult to deliver the siRNA there. Difficult to tell, normally they need a controlled trial on humans first to make sure that it is safe. One issue of the paper is the use of a mouse model, which might have rather different results than in humans. The target of SARS-CoV-2 spike protein is the ACE2 protein, but the one in mice is sufficiently different to have reduced binding efficiency. Folks have expressed human ACE2 in mice (and the authors of the paper used such a mouse line) to improve their use as model. While on the symptomatic side they are closer to human infections than the wildtype mice, the transgenic mouse line has a few issues which and differences, which makes transferring treatments directly to humans without trials quite difficult. However, there are other therapeutics in play, such as Plitidepsin which are already in trials (Phase 3) and have been established in similar animal models.