At least this paper tests both cognitive abilities as well as "amyloid-β pathologies." I'm not at all an expert in this field but gold nanoparticles sounds like something you'd see on a late night infomercial, lol.
At least this paper tests both cognitive abilities as well as "amyloid-β pathologies." I'm not at all an expert in this field but gold nanoparticles sounds like something you'd see on a late night infomercial, lol.
The problem is viewing individual papers as the unit of truth in science. The "self-correcting" nature of science will actually reject entire papers, and entire directions of inquiry. Including, maybe, a casual relationship between beta amyloid and AD, but maybe not.
The other key part of science is holding everything in a state of uncertainty. There's some "facts" but mostly just hints and clues. And with Alzheimer's disease in particular we are trying to make progress with completely inadequate vision; we really can't even measure so much of what we want to measure. Feynman said it back in the 1960s, too, physicists have failed to deliver the tools to biologists to really measure what needs to be measured. There have been advancements, and DNA sequencing technology in the past decade has been turned into the most clever sorts of information theoretic microscopy by combining DNA sequences with many other biochemical processes. But we as a species still can not measure a lot of the things we'd like to measure.
> But my impression is that a lot of labs that were interested in the general idea of beta-amyloid oligomers just took the earlier papers as validation for that interest, and kept on doing their own research into the area without really jumping directly onto the 56 story itself. The bewildering nature of the amyloid-oligomer situation in live cells has given everyone plenty of opportunities for that! The expressions in the literature about the failure to find 56 (as in the Selkoe lab’s papers) did not de-validate the general idea for anyone - indeed, Selkoe’s lab has been working on amyloid oligomers the whole time and continues to do so. Just not Lesné’s oligomer.
And
> Did the 56 Work Lead to Clinical Trials? That’s a question that many have been asking since this scandal broke a few days ago. And the answer is that no, I have been unable to find a clinical trial that specifically targeted the AB56 oligomer itself (I’ll be glad to be corrected on this point, though).
> Every single disease-modifying trial of Alzheimer’s has failed.
> The huge majority of those have addressed the amyloid hypothesis, of course, from all sorts of angles. Even the truest believers are starting to wonder. Dennis Selkoe’s entire career has been devoted to the subject, and he’s quoted in the Science article as saying that if the trials that are already in progress also fail, then “the A-beta hypothesis is very much under duress”. Yep.
And the original expose is quite interesting if you haven't read it yet https://www.science.org/content/article/potential-fabricatio...
However, the particular faked data, despite lots of citations, has apparently not lead to any clinical trials:
> Did the AB*56 Work Lead to Clinical Trials? That’s a question that many have been asking since this scandal broke a few days ago. And the answer is that no, I have been unable to find a clinical trial that specifically targeted the AB*56 oligomer itself (I’ll be glad to be corrected on this point, though).
Marc Tessier-Lavigne https://stanforddaily.com/2023/02/17/internal-review-found-f...
Berislav Zlokovic https://www.science.org/content/article/misconduct-concerns-...
Hoau-Yan Wang https://www.science.org/content/article/co-developer-cassava...
Sylvain Lesné - the researcher from grandparent comment's article
This list taken from Chris Said on Twitter https://x.com/chris_said/status/1724448550493315436?s=46
The plaques are known to be linked to Alzheimer's, the debunking of one paper that messed with its figures does not detract from the whole body of research. The inefficacy of plaque-targeting treatments may not be proof that the plaques are not causal in nature, only that their damage is not reversible/fully understood.
The issue in the Alzheimer's world is the possibility that the very disease mechanism concept underlying the vast majority of research and interventional trials into which countless multiple billions have been poured, is incorrect.
Within that space, this is orders of magnitude more fundamental and serious than a flip aside that lots of trials have problems, so who cares about another?
Not "is incorrect," but might be incorrect. And we almost certainly won't know it is correct until we actually have a therapy.
Those pursuing cures could have waited until there was more solid science, but they and their funders took on the risk, knowing full well that the amyloid hypothesis is not proven.
This is not some indictment of science, this is normal risk taking for a problem that hugely affects society.
That's why the part you quoted is preceded by "the possibility that".
It is the best possible explanation so far, but four decades of research have not reached a definitive conclusion.
An open problem is not a problem for science, that's the fundamental focus of science. The problem is people misrepresenting what science is and what it aims to do.
To be clear: for decades, researchers wishing to pursue lines of inquiry contrary to the a-beta hypothesis struggled for traction and funding, and saw their careers struggle as a result[0]. As such, trying to disprove the a-beta hypothesis was not the core research question for many/most, for long time.
[0] https://www.statnews.com/2019/06/25/alzheimers-cabal-thwarte...
> A top journal told one that it would not publish her paper because others hadn’t.
Oh the horror, not getting published in a top journal! Turns out that most good science gets published outside the top journals.
This sort of behavior is bad, and has always been part of the process, and may actually be better today than it was a century ago, as the clubs are not nearly so tight as they were back then.
Early in my career I remember reading some of ET Jaynes' (an early Bayesian reasoning guy) discussions of his early career, and how he had to very very carefully choose his topics so that he wouldn't upset the big personalities in physics and thereby have his entire career crushed. It's better these days than it was then!
There will be sour grapes about funding, just as there are when VCs all jump on the hype train for the same idea, but my only scientific exposure to the amyloid hypothesis for the past 20 years has been in terms of it being an unproven hypothesis. Starting down exploratory routes for explanatory hypotheses should have been pursued, and was pursued, and will continue to be pursued, but the question of "how much" is exceptionally difficult to answer.
Perhaps I'm biased from being in Science too long, but I've seen so many sensational Stat News article that never pan out when pushed upon. I wouldn't trust them at all with stuff like this.
https://www.science.org/content/article/misconduct-concerns-...
>For more than 150 trials, Carlisle got access to anonymized individual participant data (IPD). By studying the IPD spreadsheets, he judged that 44% of these trials contained at least some flawed data: impossible statistics, incorrect calculations or duplicated numbers or figures, for instance. And in 26% of the papers had problems that were so widespread that the trial was impossible to trust, he judged — either because the authors were incompetent, or because they had faked the data.
Firstly, this is only from one journal, Anesthesiology. Second, the phrase "at least" indicates that while 44% had some amount of (presumably) flawed data, only 26% of the studies were bad enough to be judged fake or severely flawed by this one (admittedly esteemed) researcher in the field of anesthesiology. It's important to be skeptical and do your homework when you hear sweeping and/or shocking results. It's also important to read carefully, especially with science journalism because it is written for clicks and broad audiences, not to reduce ambiguity and adhere to strict standards of accuracy.
That means 11% of the total papers should be discarded, which means 89% of the papers can be used.
It is at least 26%, because that was the percentage of studies that provided access to their data that proved faked or fatally flawed.
It may be substantially higher.
Correct, but this doesn’t constitute “fake data”. It could be that amyloid-β is a marker rather than a causative factor. Or it could be that amyloid-β related damage is downstream, and remove amyloid-β after the damage has been done won’t remove the other damage.
It’s too quick to wave away an entire field because a single theory didn’t pan out. Most medical research proceeds with a lot of dead ends before it is figured out.