That’s just not true, false research gets posted alot in biology and can go for years without getting caught
For example, the whole Alzheimer’s research thing. A paper that was published in nature faked data and sent everybody down the wrong path for Alzheimer’s cure for 20 years. They claimed to have found that a certain protein causes Alzheimer’s, therefore all new research went towards making drugs that strip that protein.
This was a landmark paper that was in a “hard science” field and still fooled alot of people
Sure, there will be examples of problems in any field that has hundreds of thousands to millions of humans working in it. That doesn’t mean there’s a broad crisis, and it doesn’t mean that most research is faked or fallible. In your 2004 example, all of the data wasn’t faked, some images for publication were doctored. There’s been potential links between alzheimer’s and aBeta amyloids since at least 1991 (1), long before this paper that posited a specific aB variant as a causal target. Additionally, other Alzheimer’s causes and treatments are also under investigation, including gut microbiome studies since at leasg 2017 (2). Finally, drugs targeting aB proteins to remove brain plaques work in preclinical trials, indicating that the 2004 paper was at least on the right track even if they cheated to get their paper published. This showcases science working well: bad-faith actors behaved unethically, but the core parts of their work were replicated and found to be effective, so some groups followed that to clinical trials which are still ongoing, and others followed other leads for a more holistic understanding of the disease.
Also, I’d very much argue that human neurological diseases are both bleeding edge and niche, which inherently means that recognizing problems in studies will take more time than something that is cheaper or faster to test and validate, but problems will eventually be recognized as this one was.
Cras P, Kawai M, Lowery D, Gonzalez-DeWhitt P, Greenberg B, Perry G. Senile plaque neurites in Alzheimer disease accumulate amyloid precursor protein. Proc Natl Acad Sci USA. 1991;88:7552–6.
Cattaneo, A. et al. Association of brain amyloidosis with pro-inflammatory gut bacterial taxa and peripheral inflammation markers in cognitively impaired elderly. Neurobiol. Aging 49, 60–68 (2017).
That’s just not true, false research gets posted alot in biology and can go for years without getting caught
For example, the whole Alzheimer’s research thing. A paper that was published in nature faked data and sent everybody down the wrong path for Alzheimer’s cure for 20 years. They claimed to have found that a certain protein causes Alzheimer’s, therefore all new research went towards making drugs that strip that protein.
This was a landmark paper that was in a “hard science” field and still fooled alot of people
Sure, there will be examples of problems in any field that has hundreds of thousands to millions of humans working in it. That doesn’t mean there’s a broad crisis, and it doesn’t mean that most research is faked or fallible. In your 2004 example, all of the data wasn’t faked, some images for publication were doctored. There’s been potential links between alzheimer’s and aBeta amyloids since at least 1991 (1), long before this paper that posited a specific aB variant as a causal target. Additionally, other Alzheimer’s causes and treatments are also under investigation, including gut microbiome studies since at leasg 2017 (2). Finally, drugs targeting aB proteins to remove brain plaques work in preclinical trials, indicating that the 2004 paper was at least on the right track even if they cheated to get their paper published. This showcases science working well: bad-faith actors behaved unethically, but the core parts of their work were replicated and found to be effective, so some groups followed that to clinical trials which are still ongoing, and others followed other leads for a more holistic understanding of the disease.
Also, I’d very much argue that human neurological diseases are both bleeding edge and niche, which inherently means that recognizing problems in studies will take more time than something that is cheaper or faster to test and validate, but problems will eventually be recognized as this one was.