CharonY

The basic question may as well be how and when are sexual preferences formed. Which leads to lots of literature but no simple models or answers. Considering the regional and historic variations of ideals obviously hard-wired biological explanations is unlikely to yield a useful answer. Rather, it is likely that preferences may have their origins in childhood exposure. I am not sure about the literature in this area, though (in humans at least).

Uh, that is incorrect. Decomposition can happen in the absence of oxygen (quite a bit of it actually) although it is typically slower than oxic degradation. Temperature is only so far relevant that it is not too low for biochemical reaction. Well, water is correct insofar as all living processes require water to some degree. The question in OP cannot be answered, however, as it simply does not describe sufficient parameters. What type of substances? How much? What system are we talking about?

No, since you cannot grow wings by wishing it, you can eliminate consciousness or wishful thinking from the discussion as well. I have also no idea why you add mental power, as you will note that many insects are quite able flyers. Also note that I mentioned active flight. There are reports of others, including cephalopods to use jet propulsion to glide out of water. You can discuss things better if you either focus more on the topic and leave out baseless/wild speculation, or at least separate that part out to indicate that you are wildly speculating. For example you are speculating about mollusks (for some reasons, it was meant to illustrate a completely different point, but alright). But the next paragraph gets completely off the rails with unfounded statements presented as fact: Why? And why only for them and not for other flying animals? Uhm. No. At least not the way you presented it. To be fair, I am not sure what point you tried to make, though.

The free will part is unnecessary (and obfuscating to a degree), and it does not need necessarily the actions of animals, as the abiotic factors are complex enough. But if we take out all the elements of free will that you put in, the general argument stands. It only appears to be directed after the fact, as you can potentially trace back the major streams and create a plausible hypothesis how it arrived there. But starting from the point of origin there are too many degrees of freedom to predict some inevitability. Some things could have happened but didn't due to some major events, other may have happened only because of them. Likewise, the small steps can probably be modeled to a degree, i.e. small scale changes in the gene pool (or in the analogy, likely travel routes in the next few minutes/hours) but once we reach a certain level of complexity things become close to impossible to predict. In the background of that complexity it makes little sense to me assume a direction. The latter would require some level of predictability. For example, why do we have actively flying arthropods, but not, e.g. molluscs? What made it inevitable for one group, but not the other? Why do insects fly, but not other arthropods? Why do most birds fly, but only the bats among the mammals? Similar to throwing a ball into the ocean, looking back from the end point it may appear obvious, but if you if you look at the whole journey, you will realize it is far from that.

I disagree. Bodily parts are typically used in the context of larger organisms. Physiology is a general term used to describe biological functions at various scales with a focus on the underlying mechanisms. The study of cell or microbial physiology (which technically do not have bodies in the common sense of the word) refers to other elements than plant or animal physiology, for example. Similarly, the function of an organ could be described in the context of body parts, whereas metabolic pathways, which are crucial elements of cellular physiology would not be. So to summarize, I would characterize physiology as the study of the mechanism of biological functions, or how elements work together to perform biological functions. What they are, specifically, depends on the scale you are looking at. Edit: because some recent posts typo-shamed me.

Also context. Posting on a forum where people may or may not read your post has different requirements than e.g. job applications where you not only want the receiver to read it, but to use it to create an opinion of you.

Let's try an analogy. You throw a rubber ball into the ocean. Based on the knowledge of general flows there is a huge set of potential destinations the moment you throw it in. After a few years it arrives at the shore at one of these destinations. At the moment when you throw the ball in would you think that it is inevitable that it arrives at precisely that location?

Well, there is also the matter of having a bad conscience due to spending too much time here. As an offset, I mostly write fast without really double-checking the post. I realize that it is not ideal, but at least it gives me less anxiety.

The study is a bit problematic for a number of reasons. The first is that the diabetes cases were only few (34 cases) and only in the high consumption categories. Also the model they used showed significant changes in relative risk between simple and fully adjust models, indicating that there are residuals not accounted for. Basically it means more data is needed.

Based on the ones I have seen I am pretty sure that it mus be a one that is based on life-expectancy measures or one of its derivatives. One of the reasons is that in the USA infant mortality is one of the highest in the developed countries this is one of man reports. Of note is that some claim that this is entirely due to different measures of the definition of live birth, but even when corrected the USA is doing pretty bad in OECD standards (just somewhere below Poland). The US has also some of the highest pre-term births. What the USA is doing surprisingly well is giving high-end care to ensure survival of pre-terms, but once that the infants are post ~37 weeks, their survival rate is way lower than in other OECD countries. Other studies have shown that minorities, especially African American are disproportionately affected by this issue. It is no surprise that states with better access to health care (such as Massachusetts and Vermont) have the lowest infant mortality rates, whereas Mississippi and Alabama have more than double of that.

Even if present, viruses to not cause the same pathologies in all hosts. In fact there are many examples in which viruses that have co-evolved with their hosts cause few or no symptoms. Eventually they may get integrated into the genome and just get propagated with the host. I think it has not been firmly established that fruit bats are the sources, but they are considered a very likely candidate.

No I think you are still slightly missing the point. The reason why I am astonished is in almost all studies I am aware of that utilize some form of survival after diagnosis overestimate the performance of the US system. On the other hand, measures that are based on life expectancy (as the one you cited) show a different picture. I am not sure what you mean with "survival of disease metrics". Do you mean the the survival time after diagnosis? That one is problematic and overestimates the US health care system for reasons outlined a couple of times. But I am not sure to which data set you may be referring to (again, the one cited does not measure survival, see below). One fundamental issue is also that for many diseases survival time is not tracked. The reason why YLL is used (in the study you cited) is because it basically categorizes the cause of death (e.g. coronoary disease, lung cancer or car accident) looks at the time of death and estimate how much longer the patient would have lived if he/she hadn't died. For this, data is easier to find (although comparisons in different systems is still difficult). All in all, I think we are in agreement (many posts ago actually) about the actual pattern, but I think the discussion also shows that the type of metric matters and different measures are better in identifying underlying issues than others. There is simply no one-size-fits all solution that accurately ranks performance of health care, but by using different data sets it is possible to assess general trends. And these show that the biggest issue of the US is unequal access to health care (or no access at all). While we are at the topic, YLL and other life expectancy measures tend to weigh children and infant death higher. And actually that is one of the areas where the US system seems to be failing massively as I mentioned before. Various health measures have shown that preterm births and associated health issues as well as infant survival in the US compares very unfavorably compared to other OECD nations. In this context the pro-life movement and associated policies are probably a major factor.

No, actually this what large consortia (not US-based) have been using to assess cancer survival. Note that you suggested that survival after diagnosis would be the best measure to do so, with which I disagreed. The only difference is that you mentioned it should be survival length after diagnosis, which to my knowledge is not monitored anywhere. However,, the figure 4 in your link uses a completely different metric. It does not indicate survival but years of life lost (YLL). If that is the one you remember, that is fine. It just means that your initial post was wrong in stating that you were discussing survival after diagnosis and would explain the presented issues here (so there is no need to vigorously defend early diagnostics as it actually opposes your point). YLL itself is not a raw number (such as counting the time between diagnosis and death, for which AFAIK there are no large databases), but the derivative of the number of deaths (due to a given condition) and the standard life expectancy at age of death. A better and more commonly used measure is DALY (disability adjusted life years) which takes YLL and years lived with disability into account. DALY therefore present the overall health burden due to disability, ill health or death. This is part of what I am alluding to, as this measure does not only take death into account, but overall disease burden. Obviously, a good health care system should not only keep people alive, but also healthy. Similarly there is DALE (disability-adjusted life expectancy) which is often used for international comparisons. It indicates the number of years expected to be in full health. This probably comes closest to your idea of a lump value. The disadvantage is that it does not tell you anything about the type of disease or issues that a population may face. This btw. is a common trend. The US perform well in metrics that are based on survival of diseases, but fare less well when it comes to measures that are associated or derived from life expectancy. More detailed studies typically indicate that low-income, Afro-American and Native Americans are most severely affected. Edit: also lousy access to support surrounding pregnancies was also found to be a major factor in the US and the crippling of planned parenthood is definitely not going to make it better.

Indeed. The constraints on the possible reactions are governed by many factors. On the most basic level of course by thermodynamics, but more importantly biological systems (and if we talk about evolution we have to talk about whole systems) create specific constraints to make certain reactions favorable. There is a reason why all known life is dependent on membranes, for example.

Uhm the article you linked showed a completely different metrics. death rate, years of life lost, years lived with diasbilities, life expectancy at birth and healthy life expectancy. None of which are the metric you provided. In fact, the numbers are derivatives based on expected life expectancy measures. So no, it does not support your point. In fact, the author actually highlights that if one takes survival as a measure the USA outperforms many OECD countries Thus the USA underperforms if we look at disease and injury burden rather than actual survival. It should be noted that injury, including road injury were among the leading factors of years lost (as well as hear disease, lung cancer pulmonary disease etc. The disadvantage of this metric is that some of the burden would be better addressed by e.g. improving infrastructure and environmental safety rather than the health care system itself. I.e. it is difficult to be sure that just improving health care would change the overall numbers significantly (but that is a different discussion). Now the other issue is that you assume that there is a survival metric that goes measured beyond a fixed number of years. But you seem to be under the impression that by lumping the values together somehow the performance would suddenly drop. While it is not impossible (as it may be a function of frequency for example), I would be wondering why a value that that does not allow us to see where a system underperforms is more helpful? In fact, the discussion would be easier if you could point to the study/chart you are thinking about so we do not need guess around so much. You may be right, after all, but I would like to see the data.

That is actually at the center of the debate. The fundamental issue is that our diagnostic abilities are beginning to outstrip our ability to make proper prognosis. Quite a few diagnostic tools are so sensitive that one could identify aberrations at at stage where we have no clue whether it will actually become symptomatic. This bit is crucial, as the bias does not apply anymore when the disease becomes symptomatic. I.e. we may find indications of a diseases before it affects the organism and we cannot predict whether it ever will within the lifetime of the patient. Ultimately it depends on how the medical professional and the patient deal with it. For example, some may recommend biopsies which may turn up negatively. Depending on the type of cancer the procedure may be more or less invasive. Likewise the screen itself may can be harmful to some degree. While it is unlikely to be fatal, it will affect quality of life without actually improving the health situation. Or, if positive, one might recommend chemo. This has massive impact on quality of life and may also result in hidden damage e.g. in liver of kidneys, that may prove to be problematic later in life. Yet it is quite possible that without treatment the patient may have no issues at all or at least no worse outcomes. Especially for rare diseases (i.e. where the likelihood of true detection is low), the morbidity of exams and follow-up may outstrip potential benefits. And in cases where there are no benefits the net outcome may be negative, if the quality of life and health of the patient is considered and not only the survival. This depends highly on the type of disease and the patient characteristics of course. But it is often not easy to assess at which point the downsides outstrip the benefits. Quite a few have now accepted that a "wait and see" approach may be appropriate that closely monitors progression and only intervene when indicated. The main issue here is that being diagnosed with cancer can be huge mental burden. Note how you mentioned "the time they have left"? It is quite possible that especially in early diagnosis the cancer may never progress to a lethal state, but depending on how it is conveyed and the mindset of the patient it may still be huge, albeit unnecessary blow. The patient may indeed rather die with cancer than from cancer. This is a real issue (Fowler et al 2006, J Gen Intern Med). And maybe more On-topic, the whole procedure costs money. As we have established and all agree, an ideal health care system should maximize health benefit at an affordable cost. However, unnecessary follow-ups can be costly and, as pointed out, unnecessary. There is a reason why NHS has reduced the screening intervals, whereas in the US there is a push to increase screening (or keep it on a high level). I think it boils down to the question of how potentially harmful these procedures are relative to their benefit and whether we can educate the medical professional and the patients in a way that they can use the information in a positive way. 1-3) are partially true, but 4 does not follow from them. You have agreed that a good measure of a health care system needs at least two elements. Health outcome and cost (the Zimbabwe example you provided). Now your argument seems to be that the survival time after diagnosis is able to capture these elements. But there are several issues with it.The basic one is that typically that the length of survival depends on many factors and not only the treatment and most studies are not able to follow patients up until their deaths. I would be surprised if there are actually country comparisons of this metric, but I would kindly request them, if you have them available. Actually providing the actual diseases would also help to figure out whether lead time bias has an overall effect. It certainly has for cancer, but I could try to figure it out for the other diseases. That being said, what is more commonly used in studies is an x-year (typically 5 or 10, sometimes longer) survival after diagnosis. My guess is that the data you have seen has actually been adjusted for a number of factors as it is well-recognized that the raw numbers are useless for comparison. For example, the USA actually outperforms Europe in most cancer forms (see Gatta Cancer 2000) using SEER and EUROCARE data. Which runs counter to your (and also my) arguments. A few subsequent studies have pointed out that this is at least partially due to the fact that in the US more aggressive screens are performed. Based on your argument (4) the US should therefore have a better system than most European ones because a) there are more screens and b) the survival rate is higher. But as I mentioned, a) creates the bias that increases b). In other studies such as CONCORD-1 and CONCORD-2 the USA exhibits highest survival rates (typically within the top 5). However, even by using a slightly different metric such as by estimating the ratio of survival found in cancer patients relative to the expected background mortality rate, the authors were able to find systematic inequalities in the US system. The authors still acknowledged that leas time bias may still inflate the outcome. Taking all-cause survival rates overestimates US performance, for example. Note that these studies do not even try to assess health care performance, just to provide a comparative view on cancer. Either way, the main point is that there is still an ongoing discussion on which metrics to use to analyze a health care system and while certain measures perform well to highlight certain aspects, the fall short in others. And again, if we really only took the simple survival rate, the US system would be one of the best in the world. But, as John said:

Not necessarily. There is actually quite a bit of a discussion about whether early diagnosis actually helps in better health outcomes. And maybe somewhat counter-intuitively the answer is: "not necessarily". This is true for certain types of cancers with very slow progression, for example. In some cases early aggressive treatment may even result in slightly worse outcomes. Another example is breast cancer, for which in the US a yearly screening is recommended, whereas in the UK only all three years screens are conducted. In addition they start earlier in the US (40) than the UK (50) This is partially due to some British studies that have shown that additional screening may not increase treatment outcome, but may actually lead to overtreatment. This is often due to false positive detections, which obviously increase with additional screens. The reason why frequent screens were popularized in the US were actually an observed increase in survival from diagnosis with earlier screens. However, cohort studies showed that the survival characteristic of UK and US cancer patients were pretty much the same (the slopes of survival rate curves were basically equal, if you see what I mean). That actually indicates that the early diagnosis on the US has not resulted in better health outcome, but rather the difference between those two curve were mostly (if not entirely) due to lead time bias. I.e. the added survival time is just due to the early diagnosis, but the disease progression remains the same. In these cases there is a window at which detection can lead to improvement but pushing it earlier does not anymore. Of course for other diseases earlier diagnosis can massively improve quality of life and/or survival. Therefore this a question that cannot be answered with true or false without being wrong in some aspect. Just to reiterate, different approaches to diagnosis (even, or maybe especially with same subsequent treatment) can skew the survival time, but may not affect overall health outcome . As such, there is no single metric that is suitable to estimate the overall quality of a health system. And I agree, cost and access are two major components of a functional health system. Best treatment options mean nothing if you cannot have it. Edit: I should add that at least in the area of cancer newer studies have shown that after accounting for lead time bias there have been increased survival, mostly due to improved treatment options, rather than diagnosis. Also in the two given examples (prostrate and breast cancer) the US actually outperforms Western Europe in terms of survival, but at a higher cost. But I believe if lung cancer is added the US loses out (2010ish data, IIRC). As an additional note defining adequate measures for health care quality is the subject of quite a bit of research, especially in the UK and Canada.

Also, there would be a need for nitrogen and carbon sources. I.e. one would need to consider atmospheric composition.

I don't get it. Is it a reference to something?

A) no one is claiming that everything is known. There is also no argument that more research is needed. However, B) your claim that it is one of the most understood phenomena has no basis. You provide no evidence that the current knowledge is wrong (unless you mean something specific that you have failed to convey). I think you would agree that incomplete and misunderstood have rather different meanings. C) Adding quantum theory for good measure does not help your argument as randomly adding disciplines does not make anything clearer. Likewise I could claim that string and group theory could provide deeper insights. D) Pain has to be painful because otherwise it would not be pain. You may be interested in congenital analgesia.which is mostly connected to SCN9A mutations. E) Are you sure that science is misunderstanding things and not someone else?

Of course. Most analyses would agree that cost (and therefore, access) is what creates the problems in the US health system. If you have the money, you can get some of the best medical care.

Oh boy....

Actually survival length after diagnosis is also quite problematic. The issue here is that in different systems there different guidelines for disease screens. For instance, some countries emphasize very early detection of cancers. However, by diagnosing cancer earlier, the the survival time is pushed upward, although the overall trajectory may not change at all. For instance, assume that there is a form of cancer in which everyone, regardless of therapy dies after 10 years. If you diagnose it 5 years into the development your length of survival after diagnosis is 5. However, assume a country implements a more sensitive method which diagnoses at the onset, your survival length may increase to 10 years, without actually affecting the overall outcome (also called lead time bias). There is a bit of discussion what metric would work better and AFAIK there is no firm consensus beside that many metrics, including access should be included. For example, if a significant proportion of the population has no access to early diagnosis, their deaths would affect life expectancy but not survival length. There is also age-adjusted 5-year survival of cancer. By this metric USA is not doing too bad, however, that, too is confounded by the above mentioned issue. I.e. people with access to health care in the US tend to be overdiagnosed. Another measure is the so-called age-standardized avoidable mortality (i.e. deaths that could have been averted by correct prevention/intervention strategies). But this has similar issues with other aggregate measures. What is clear, however, is that cost and inequality in access is something that skews health trajectories quite a bit in the USA compared to other OECD countries. I have not seen the US system performing that bad if cost is taking out of the equation, though.

Fair enough. Also fair enough. Well, the issue here is that this is a science forum and in contrast to other more free-for-all fora the idea here is that we try to ground our arguments in science. Requesting citations serves three purposes. First, if there are none, OP should reflect whether the stated arguments are based on facts or just opinion. Second is, if citations exist, to educate the reader that the argument has indeed merit and by providing the citation, one can read up and follow the arguments better. Third, OP may base assumptions on some false interpretations of some data. By providing the source it will be possible to clear up misunderstandings. If, on the other hand we treat opinions the same way as data or scientific works then there is now way that a discussion will be grounded in science (or at best just by chance). In that regard this forum is a bit of a niche but there are many others out there that fulfill your need for flights of fantasy. However, typically they degrade very quickly into nonsense, which is one of the reason why I stuck around for so long here (edit although I should say that the role of mods may be a bit off-topic and has been discussed to death here).

As a whole I do not observe the mentioned behaviour on a frequent basis. There are only few examples of early attacks, when either the OP or early posts are seemingly framed in a very soapboxy or crackpot style. I will echo Ophiolite's concern that even in those cases it may just be the result of poor communication skills and care has to be take in the initial responses. I am pretty sure that there are times when out of exasperation I have posted harsher comments than warranted or even intended. That being said, in experience it does happen very rarely and most of the time there are simple requests to follow the rules and pointing out violations and/or nudging the poster into a position in which they can re-examine their initial assumptions. Furthermore, I do not recall that it happened to new posters. Typically, posts that could be construed as attacks (if at all) are due to a series of posts. Nonetheless, if nothing else it is a good exercise to step back every now and then to check whether one had been unduly harsh. Even if the answer is "no". We are (mostly) only human after all.