>the fructose molecule passes through the intestine as glucose.

That's not right. Fructose is converted to glucose in the liver, not in the intestines. That's why eating too much can impair hepatic insulin resistance andn ultimately give you fatty liver disease.

The article says that it needs to be very intense exercise, around 85% of max heart rate.

A vaccine is a drug that trains your immune system to attack a particular thing. A flu vaccine trains your immune system to attack flu viruses. A cancer vaccine trains your immune system to attack cancer cells.

Diseases caused by mutations resulting in toxic gain of function exist. Huntington's disease and some forms of ALS, for example. Generally these are inherited in a dominant fashion, since you only need one copy producing toxic proteins to mess things up.

For toxic gain of function mutations, there are various technologies for silencing the expression of toxic genes currently in clinical trials. Most of them use complementary RNA strands that bind to mRNA, preventing it from being used to synthesize proteins. I don't think any of these are currently FDA approved, but there should be some within a few years.

(Edit: According to Wikipedia, there are actually four RNAi (RNA interference) drugs on the market already).

Conversely, loss-of-function mutations are generally inherited in a recessive fashion, since one copy of a gene will usually produce enough of a protein. I believe that there are a handful of loss-of-function diseases inherited in dominant fashion due to haploinsufficiency (where one good copy cannot produce sufficient quantities of a needed protein).

There's some evidence that c9orf72 hexanucleotide repeat expansions, the most common genetic cause of ALS and FTD, involves both haploinsufficiency and toxic gain of function. Basically, the mutant c9orf72 protein doesn't fold correctly, producing toxic aggregations, and then there isn't enough good c9orf72 protein to clean up the mess. It's inherited in dominant fashion.

The entire sample consisted of psychiatric patients, so everybody, trans or not, was seeking treatment.

> Between April 2014 and January 2021, we administered semistructured diagnostic interviews for DSM-IV disorders to 2,212 psychiatric patients, 69 of whom reported TGD identity (ie, gender identity other than cisgender such as transgender, genderqueer, or nonbinary identity).

So the entire sample consists of psychiatric patients. I'm not sure what we can do with a finding like this, given the selection bias.

I think the benefits of exercise are fairly well established, so I don't want to call that into question. But given the extremely small amounts of exercise described here, I do wonder if these particular results are driven by reverse causation, with people who are healthier being more able to engage in moderate to intense exercise for a minute or two on occasion.

For example, I'm in my early 40s, and I always run up stairs. I don't climb long flights of stairs often enough for this to be a significant contributor to my overall level of fitness, but it is a marker of fitness. If I had a BMI of 35, I probably wouldn't be able to do this.

Obviously doing this much exercise on its own is still better than nothing, but I think we should be skeptical of claims that such large benefits can be realized from such small amounts of exercise, at least when based on evidence of this quality.

You literally have no idea what this study was actually about, do you?

Where does the second clause of the title come from? I don't really see that discussed in the article or paper, though I haven't read the whole thing in detail. Is that just editorializing by OP? I didn't see anything in the paper that could be used to infer that SES causally affected willingness to gamble with stickers.

>The more a certain type of ad is shown to a demographic, the more likely a positive feedback loop is to emerge. If all you see is young white women, you don't even get the chance to contradict the algorithm's assumptions about you.

I'm sure that you and I know more about this issue than people who work on these algorithms full time, but "show people a variety of ads" and "account for the base rate when calculating click-through rates" seem like super basic and obvious things to account for.

If you have a Facebook account, open it up now. Does it look like Facebook is only serving you one specific kind of ad?

These seemed like extremely low ratios. At first I thought Chinese people were just really healthy, but then I realized that because cholesterol and triglycerides have different molar weights, the ratio is different depending on whether HDL and TG are expressed in mmol/L or mg/dL. You need to multiply by about 2.2 to convert mmol/L ratios to mg/dL ratios (the kind you typically get in the US).

It's not clear how useful this is as a diagnostic tool when the differences they found are well within the range of normal variation. If you have a patient who has a fluid intelligence score 0.5 standard deviations below average, is that a person of formerly average intelligence who's in the early stages of cognitive decline, or a person who was always a bit below average? Or maybe a person who started out well above average and has undergone severe decline?

I think you'd have to test patients multiple times over a period of years to get good diagnostic information out of this.

Also, does anyone know what the scale of the fluid intelligence score is? Like what's the mean and standard deviation for control subjects? Eyeballing Figure 1, it looks like the standard deviation might be two points?

Specifically, the half-life of atmospheric methane is about nine years.

I was talking about depth.

It's an anti-snack, because it burns calories rather than adding them.

>You’re pretty much doing a squat any time you sit down

Well, a half squat.

Well, no. They have indexes (PDI, hPDI, and uPDI) which are used to measure the extent to which an individual's diet matches a certain pattern.

> Higher adherence to the PDI, particularly the hPDI, was associated with a lower risk of colorectal cancer, whereas greater adherence to the uPDI was associated with a higher risk of colorectal cancer. Compared with the lowest quintile, the adjusted ORs in the highest quintile were 0.79 (95% CI: 0.66-0.95) for the PDI, 0.45 (95% CI: 0.38-0.55) for the hPDI, and 1.45 (95% CI: 1.18-1.78) for the hPDI, respectively.

So people whose diets scored highest on the PDI were less likely to have colorectal cancer than people whose diets scored lowest (although this was just barely statistically significant), and people whose diets scored highest on the hPDI (healthy PDI) had about half the risk as people whose diets scored lowest. On the other hand, people whose diets scored highest on the uPDI (unhealthy PDI, which I assume means lots of unhealthful plant foods and not much animal food) had significantly higher risk of colon cancer than those who scored lowest.

The ORs are not the result of comparing different PDIs to each other.

The main takeaway here seems to be that healthy diets reduce risk of colon cancer, and unhealthy diets increase it; the effect of vegan vs. omnivorous diet was much weaker and barely statistically significant.

Also, this probably indicates an underpowered study rather than sex differences in how diet affects cancer risk.

> In stratified analysis, the inverse association between the PDI and colorectal cancer risk was not observed in women, and the positive association between the uPDI and colorectal cancer risk was not observed in men.