CharonY

It sounds to me that it might be about folks who profess a superficial love for science or anything sounding "sciency" (or like science ficton-y) but do not have actual interests in that area as such. Essentially folks that assume that liking science memes being the same as liking science. I also disagree that one needs to have a higher degree to get into science. There are many hobbies that provide in-depth knowledge about certain parts of that natural words, including e.g. bird watching or wildlife photography. It is more about to what depth you involve yourself into it. Fundamentally anyone running an aquarium or doing birdwatching is learning and applying more science that self-professed geeks who want to use Crispr to make superhumans.

Fundamentally the mindset of most students and parents (as well as many teachers) has become grade-oriented. Folks confuse grades with understanding the material and looking at students just entering college it is clear that few have developed deep interests or even reading skills. Over the years it has become apparent that learning is paper-thin to the test and students have been adept in further optimizing the process. In student evaluations you see an increase in complaints that instructors teach too much, which in the end does not appear in tests. I.e. it shows a mindset where folks are highly focused on the grades as sole outcome, and anything not related to it (e.g. deepen understanding, or foundational knowledge that is important for higher classes) tend to get neglected. Traditionally this was more common in pre-meds, who optimize class selection in order to get into med school, but it seems to have affect majors, too now. Big issue there is that even in advanced classes you realize at some point that a big proportion of the class has no recollection of previous courses, they just learned for the test and after that it is gone. It could also be connected with how younger folks consume media and information in general, but sometimes a class seems to be full of amnesiacs. One can still shame individual students into re-learning bits when you recognize them from former classes, but as a whole I feel it has been getting harder over the last decade or so. There is also the mindset that the teacher's job is not to teach, but to facilitate high grades, which does not really help.

This is one of the questions where there are a large number of "correct" answers. Also I do not think that it can be answered by one or two papers. It is one of the fundamental questions of "omics" research. I.e. how do molecular changes on the transcriptome/proteome/metabolome level relate to physiological changes in the organism. In some cases where the mechanisms are well known you could indeed find pathways that can explain certain features. However, they are not necessarily protein-protein interactions. Metabolic pathways, for example, are connected via the metabolites rather than direct protein interactions (for the most part). But even identifying groups of genes involved in connected functions, it is often unclear how that affects the organism. Apoptosis, inflammation markers and so on are often indicative of damages of some sorts, but it does not necessarily tell you what kind of disease it is and how it causes these damages. For microarrays there are additional challenges as they generally only indicate relative changes, which may or may not relate to physiological outcomes. Even more problematic, an increase in mRNA does not necessarily indicate a similar increase in protein. If you go through papers using microarray or other "omics" techniques, you will often see that authors often use these techniques as mere screening methods to identify significant changes (which has its own set of issues) and then often use validation studies or literature to hypothesize what their connection to a disease or condition is. Other attempts are more quantitative, e.g. using a variety of modeling approaches, mostly using metabolomics and proteomics information, to reconstruct the metabolic pathways. This often is not as easy for other less well-known networks. As a whole these are open-ended questions and instead of focusing on right or wrong you might want to explore what we can or cannot learn from this type of data (it also leads into the issue of high-dimensional data sets).

As a whole qPCR tend to use fairly short target regions (usually <250 bp), this helps to keep amplification cycles really short and probes usually are only between 18-30 bp. Part of the limitation s that the labelled probe needs to be quenched and with longer probes it can cause issues. But they are ways around that (e.g. using free quenchers), so in theory one could design longer probes. But often that is not ideal for the performance of the assay. 30 bp or shorter is typically enough to be highly specific for a target gene within an organism, if run under sufficiently stringent conditions (your signal has to come from successful binding of the primers as well as a probe between them). However things get tricky when we are e.g. looking for SNPs in mixed samples. There are approaches for community analyses where probes can be designed to fit certain taxa, but obviously the require quite a bit of validation work. There is now a move toward doing more sequencing for validation, but despite cost reductions it may still be a bad hit to the budget.

Fundamentally PCR has not changed (let's just call it PCR, it is what it has been called forever). So not much has changed in diagnosis of the correct amplicon. But I think the confusion might be due to the fact that not all qPCRs are created equal. Some use intercalating dyes to detect double strand DNA and in this case, there is no real additional information of the amplicon over PCR (aside from a melting curve, which can be generated after the run and which is kind of helpful in that regard). However, there are qPCRs that use a probe that binds to the target region, similar to a Southern blot. That one is what the author refers to as being more specific.

Edit: I started typing some thoughts, but I am wondering what your thoughts are, first.

I think that is a reasonable assumption.

Well, the disorders stay. Management means that folks exhibit normative behavior (or emulate it). But it is not that the folks will suddenly feel empathy. They might learn that folks expect not to behave a certain way, but that is the best you can hope for. The issue with harm is that folks with certain antisocial disorders simply are unable to see that doing harm is a bad thing. It is like trying to cure blindness by telling folks to behave as if they were able to see. Both require ongoing management. What makes it really difficult is that folks with this disorder are unable to see that something is wrong to begin with. While they can learn to pretend, it is often difficult as typically they do not feel to the need to fit social norms and do not understand soecietal expectations. I think the otherness of the disorder is really difficult to convey as you and me would frame it in a context that makes sense to us, but for people with this disorder it simply would be gibberish. Again, it is part of their personality and cannot be changed and it is quite a different beast than, say, mental illnesses.

When reports came out that Trump had abolished Obama's pandemic response team, there was an Op-Ed in the NYTimes (I think) where the remaining folks Trump pandemic team claimed that they did not disband it but rather just restructured it to make it more nimble and agile. Well, whatever it was, the remaining bits and pieces were clearly not able to do anything beyond repeating Trump's random thoughts. Agile indeed.

I think it should be then expanded to cover all mental illnesses. The important bit relevant to OP is that for many, if not most there is no cure or rehabilitation. It is about managing it. Punishment does nothing to improve things like antisocial personality disorder. In fact, they tend to make things worse. There are behavioural therapies that can help folks to fit in, but it is more expensive and time consuming and therefore typically not available. And if you are rich enough some of this behaviours might even be beneficial (i.e. there is also a socioeconomic component to it). So fundamentally I would say no to forcing a cure, as there is none. Treatment and support even if they do not want it, probably yes, if it can be done in a non-harmful way.

The weird thing is that no one is really surprised that had no strategy. But it kind of boggles ones mind to some degree.

And again, I think some of the discussion here is a bit problematic due to the different uses of "psychopathy". It is not quite clear what OP specifically meant. Hearing voices is not part of that, for example. Rather they are associated with a broad range of other psychiatric disorders but can also be caused by brain tumors. Not taking help is not a cure and could be caused by paranoid conditions, traumatic episodes and a whole range of other issues. Taking money or going to a shelter is not a cure, but would be consider normative behaviour, something that a person may willingly reject or is unable to conduct due to a disorder. Or to put it differently, someone suffering from the consequences of trauma cannot be cured per se and not certainly by forcing them to behave normally. Instead, they need help to manage their trauma and it is not something you can really force upon someone.

I have not seen Fauci that happy since the start of the pandemic. Sorry, I meant "Gina-Virus".

It goes toward the need for free and informed consent, which is a critical element in all medical procedures. However, there are of course many cases, even in recent times, when folks where compelled to certain unnecessary procedures, which goes against this principle. And there are still grey zones when there are medically relevant procedures, but the patient is, for whatever reasons, unable to give free consent.

There is also confusingly a range of uses associated with the term psychopathy but I do not think it is diagnostic order in the proper sense. Rather there are commonly used to refer to a set of traits that are associated with certain disorders. At the same time MigL point about spectrum is relevant, as even the diagnosis of actual disorders are not trivial and rarely as black and white as some other medical diagnoses.

I think I mentioned before that countries with strong centralized responses had typically better outcomes that fractured-state level regulations. Now that likely also applies to vaccine roll-outs. I mean, it is hard to say for the US, for example as apparently they had no real plans, at all.

Again, I would be highly suspicious if there is only one researcher in the world being able to create a cohort that shows an effect.

Yeah the poll is obviously made with a very specific viewpoint in mind. How about you are sexually abused but no one believes you? Or you are sexually abused, and report it but lose your career over it? How about you are sexually abused and have to explain your browser history in front of a jury? Or you are sexually abused and folks tell you not to be a slut? Or you are sexually abused and folks try to help you but you cannot overcome the resulting psychological problems? I mean, some things happen more commonly than others.

I would look into the methodology in much more detail, but fundamentally if an effect is only found in one cohort, and not reproducibly it is generally not sufficient for a call to action. If there was a significant biological effect you would usually find many more studies pointing to various issues and from there a view emerges of potential issues. It takes years of efforts to get to the point and it is indeed strange if no one had found similar effects. That being said, I am not actually familiar with the current state of the lit in that regard. However, from a layperson's perspective, I would not start to be worried unless it is being reproduced in a broader context by other research groups. That being said, not being physically connected to your cellphone all day long probably has at least some mental health benefits....

This also does not make sense. The believing the victim proposals are aimed at looking into the possible crimes in the first place. The actual trial will be as any other one. And again, that at least in part explains low conviction rates. It should be noted that the false rape allegation rate is roughly in line false accusations of other criminal acts and it is somewhat peculiar that this type of allegations is what get folks riled up. Indeed. One of the things that both prosecutors and defenders probe is credibility of the victim. And these types of probes can be very aggressive. E.g. and steeped in moralism. E.g. women who had multiple sex partners are more likely to be assumed to be responsible for being assaulted than men. Of course credibility is important as they need to look into motivations such as custody proceedings, financial interests and so on, but obviously it is quite a harrowing process for an actual victim and that on top of social stigma and psychological wounds.

OK so perhaps one should look at broad picture and at the justice system rather than using individual anecdotes to extrapolate cases. We can address the rate of false accusations. Studies on college students have shown that in this group roughly 5% were false allegations. Or conversely 95% of allegations brought to police were not found to be false. Moreover, only about 10% of all rapes get reported to authorities to begin with. So from the get go we have a situation were we have 0.5% of wrongful allegations vs about 99.5% actual cases. The conviction rate is incredibly low, though. Even among the 10% reported cases only a fraction (again, about 10%) are actually resulting in conviction. So the likelihood of conviction in an actual rape is very low (~1%) and the likelihood of wrongful conviction much lower than that. So again, we are not talking about a symmetric situation here. There are a couple of issues, of course, especially in the absence of evidence convictions are unlikely and then of course victims (especially male victims) are very unlikely to come forward as they see no point in doing so and want to avoid social consequences. The other issue on the justice level side is that often rape allegations, even when reported, were simply not pursued. There are many reports, articles and internal investigations throughout at least UK, US and Australia which have shown that allegations from certain folks, especially indigenous folks, drug addicts, younger victims, victims from what are classified as problematic households, homeless and so on, were often routinely dismissed. In the US rape kits were often not submitted for analyses and so on. This is all because in those cases police deemed the victims unreliable from the get-go and decided not to even start investigating. It is also possible that due to low likelihood of success police focuses on the more winnable cases which might improve their statistics. Some of the campaigns, such as believe the victim slogans and alternative hotlines for rape reporting are attempts to address this systemic issue. Edit: crossposted with iNow, but same idea.

That still does not seem to address the issue of undetected infection. The rate gives you a good idea to die from COVID-19 if you are tested positive. Obviously, the more folks are tested, the more these two values converge. But you are right, it is an estimate for death by being diagnosed with the disease at a given point in a given area.

Sorry, brainfart; case-control are retrospective studies. I meant controlled prospective studies (or similar) where the treatment is controlled.

My take on these retrospective studies is that a single one at best points to something to look out for, but one needs either big studies and /or case-control studies to really establish a link. As larger studies so far have failed to reproduce these effects I would not consider the initial findings critical. I would not entirely dismiss the study, either but would take it as a piece of the big view. If it was the only study finding the effect I would assume a spurious correlation, but there have been a few, but most showed rather weak effects IIRC. The key would really be to find whether there are any mechanistic links, and for that the evidence level is very weak.

Yes, but not everyone that dies will have a test performed (potentially for COVID-19 but certainly not for all diseases). Some folks may die from pneumonia, for example but it is not clear whether it was caused by an influenza infection, or not (folks are more wary of COVID-19 and may test more now, but it was not the case early last year). Similarly you may have a lot of folks that had the disease but were not tested (which is a big issue with COVID-19). So the death rate is typically just the fraction of diagnosed cases who eventually die. Yet many think of it as the fraction of deaths as a fraction of total infections. For example, if there were much more asymptomatic cases than current diagnostics indicate (i.e. the true total infection rate was higher than measured), then the COVID-19 death rate might drop as low as 0.1%, yet it clearly would underestimate the health burden it poses. And conversely, deaths that were not properly coded (because they were not tested) or missing infections could increase it. Also, the case fatality rate also changes depending on condition (it was way as high as 31% in Italy). So again, one needs to use the metric in the proper context. At best, it is a very crude measure of how bad a disease is.