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Professor at a top university, at the forefront of medical research: "lemme just turn my pictures 90 degrees, that'll fool them"

Science is now doing what peer review should have been doing the last 2 decades.

This is why I always photograph extra unpublished blots to create unique forgeries.

The bigger problem is that negative results don’t get published. So everyone will try to fudge their data, conclusions and say there is something significant.

another month another fraud

If there is ever going to be a prize for showing fraud, this should be called the Elizabeth Bik prize.

I think 1. The peer reviewed system needs an overhaul because it’s completely failing at its task. 2. It’s too easy for a “supervisor” to put their name on a paper without doing the leg work and then expect blame to lie elsewhere when they fail at supervising. 3. We need some kind of reward for the person/people who find the scam artists/Lazy work in the system.

A med student friend of mine asked her adviser if she should go into research, or medical practice. He asked her how important it was to her to be able to look at herself in a mirror. Abby asked him to clarify, and he said, "They won't order you to commit fraud, but they'll press you to find a way to get their products approved - whether they help patients or not. Could you still look at yourself in the mirror after doing that?" That was 20 years ago, almost. I never found out which way she went.

When does Elisabeth Bik get a Nobel Prize?

Oh yeah, science is science and people are flawed. That's why we need people like Pete and Elizabeth Bik to identify flaws and perform corrections.

The desperate need for funding has corrupted ALL the sciences 😢

Elisabeth Bik is the real MVP. When these institutions fire some of these fraudsters they should send the discoverer that employee's would-be bonus or 6 months salary upon termination. It would show that they actually care about integrity and encourage academic honesty rather than just acting aghast and brushing things under the rug. Encouraging honesty and sending a message that academia can have a future when trust in institutions is at an all-time low.

As a supervisor it is also your role to verify the data and ask uncomfortable question-At least that is the case in Germany... Maybe you can mess it up once or twice but not 30 times.... You do get so much money BECAUSE you have to do this tidious task, you can not just rest on your past distinctions...

I love the fact that you took note of your audience's reaction to your first academia is broken videos and took action. Your action resulted in this channel becoming one of the most unique channels covering these subjects.

"As the final author on the paper & as a scientist of his caliber" he should NOT just be there in an advisory role: he should be reviewing & confirming the data collected & the work of his co-authors. Let's face it, as a Nobel Prize winner, the paper is flying under his authority & will attract attention in the marketplace because of his name on it. If he's just surfing fame, resting on his laurels & gaining continued fame by co-opting the work of his co-authors, he deserves to go down in flames if THEY fabricated evidence.

When I worked in academia, I was there long enough to hear rumors about specific professors. Some of these rumors even came from their own students. Only a few profs names came up again and again, but it became predictable after a time. There were certain names you came to mistrust, even if you had no direct proof or contact, because the stories never stopped coming. Whether it was an academic integrity problem, or a problem with interpersonal conduct, some names became associated with this stigma. But the truly discouraging part were the recurring counterpart tales about students who supposedly HAD direct involvement in these issues, and took them to the administration, and their concerns were buried or ignored. These stories ALSO came up again and again. These problems don't exist JUST because there are bad actors in academia. They also exist because *administrators* would rather sweep the concerns under the rug, and avoid a scandal that might hurt donations or grants, rather than maintain a rigid standard of integrity. I'm convinced that a lot of the fraudsters are given cover, intentionally or not, by their departments and institutions who are desperate for the gravy train to continue at any cost.

As someone who as owned quite of few dogs, I find them eating my homework more believable than it being "compression artifacts" as would happen with low resolution rendering.

I understand why the process from research to clinical applications is so slow: there's a bunch of contradictory BS data out there.

I have run a lot of Western blots, had published a number of them, and have seen my colleagues publish quite a lot of it. Also had the experience (as a graduate student) to see my fellow grad student forced to falsify a Western blot, pressured by her supervisor. When it came to publication, the lab director thought the blot looked really dodgy (nobody dared tell him it was doctored but he thought it was not right, and explicitly told the PI that he should repeat all the experiments before thinking of publishing it. The PI did not do that, and published without the lab directors name and permission. He got his paper, but the lab director refused to give him a salary raise at his next evaluation because of low scientific standards. In return the PI volunteered to spearhead a witch-hunt against the lab director, that was started by a scumbag high in the academic ladder (with similar standards as the falsifying PI).... Shortly, in my experience there are two very distinct men in academia, and the ONLY commonality between them is that they are extremely smart. One type is extremely smart to come up with new ideas and how to demonstrate them. The other type is the pathological evil-genius, who has no original ideas but is an expert at leeching off the colleagues, scheming to ruin others' reputations and stealing their research and especially: their funding! I have seen the craziest funding thefts, and the most incredible allegations used to ruin careers. It is super sad though that from the outside these extremely different career paths look the same... both are in academia.... and when the pathological cases are caught and shown to the public, the public thinks that this is how every scientist is. Which is the furthest from the truth. Yet, as always, hard work does not get a fraction of the attention that outrage gets.... so the general impression is that academia and science is all about fraud and misconduct, and nobody thinks twice that all the technology around us (from cell phones to liver transplants) came through science. The truth is that the majority of scientists are extremely altruistic, sacrifice much more from their lives as people in general do, work hard hours thanklessly, are abused and discarded by the system which has a lot of unfortunate influences at the top, and stand at a big disadvantage in life compared to a carpenter or a construction worker to have a solid financial foundation for personal life. As always, where money is, trouble follows. As funding for science is becoming more scarce every year, even honest people are forced into desperate measures just to stay floating. While there's a very big difference between totally faking a Western blot and touching up a part of the blot to make it look super clean, the latter is unfortunate as it gets placed in the same category as outright forgery. When you have ran Western blots, you know that sometimes they come out looking not so clean: the lanes might not be perfectly parallel, there might be a small uneven gel pockets skewing the lane, it picked up some dust from the camera, and so many little hickups. The way to take care of those is to run the experiment again until you get the perfect looking one, that's neat enough to get published in PNAS or Cell. However, since 2010 or so, we barely have enough funding to run a single blot for a given experiment. Nobody has the luxury to allow for multiple repeats (which likely require purchasing an additional set of antibodies, and maybe months to run the experiments to get the protein for the blots.) As a post doc, you have a job security that does not extend to more than one year, in lucky cases 2 or 3 years when you have a major lab backing you up (mainly through nepotism, but also happens rarely by sheer luck). Most often if you do not get the blots right the first time, it's the end of your career. You can start looking for a job as an adult with no practical training in any field whatsoever (other than your specialized field, that just chewed you out), and no life savings at all. And it's getting more cut-throat every year as NIH is constantly cutting the funding on R01s and other grants, while reagents go through staggering price increases every year. The funding system is forcing the academia to break, as thriving requires either uncanny luck to have experiments and ideas work right away (they almost never do in biology) or resorting to stealing and faking.

Alternative title, Stanford professor has 35 papers scrutinized, penas retracts

The passive aggression in his response. 😂

When your success in academia depends largely on the quality and relevance of your research, it’s no surprise that people fabricate data. There are essentially an infinite number of directions you can research, and the majority are dead ends. Imagine working your whole life in a merit-based system, climbing to the very top, then getting passed over because you happened to pick a research direction that was a dead-end, which you couldn’t have known was a dead end ahead of time. You can either attribute the last few years of your life to “at least others know not to do it this way now”, but the temptation to fabricate some results is very real.

“Trust the science” has forever become a meme.

The senior author is 100% responsible for the content of the paper.

This is happening ALL OVER ACADEMIA. Thank god it’s finally getting some attention. The social sciences are the absolute worst with this.

last name and being corresponding author on the article means that he is the most responsible. first author is usually PhD student or postdoc. nobel prize is now just for propaganda purposes

"This cannot have happened by chance. As in: much, much less than 10^986" Brutal.

What's shocking to me about this is how crude the manipulations are. I am a researcher myself, and if I ever had the intention to make fake data for a paper, I can think of so many ways of doing it in a much more sophisticated manner so that it would be much harder to find indications for the manipulation than looking for duplicates. And there are MANY people with the technical skills to pull this off -- therefore it stands to reason that people probably are cheating in more sophisticated ways while evading detection.

'Hotshot Bot Sought, Caught Fraught Blot Plot'

Retracted PNAS!... It's just cold 😐

@PeteJudo1, the cloned rectangles shown round 5:30 in the video can actually be artifacts of an image upscale. Actually if you try to upscale an image that has any one-colored area will result in repeated upscale artifacts because the algorithm will make the same "decisions" on what to do there and given it will be seeded with the only non blank area will repeat the same output until it fills the blank area. I am just a software developer and have no idea of the subject of the photos and it's composition, but I have enough experience to say that "well.. I have seen this before" ;)

As a quality engineer I know that it is “easier” to point out the flaws in everyone’s work than it is to be the OG and not generate them. In my experiences this an issue with other people doing the work and the manager not having a flipping clue about the work. Happens all the time bc the manager needs the project result and doesn’t know what the real risks they are taking bc the engineering is trying to minimize concerns. It is absurd that “managers” get their names on others work. This is similar when managers steal patent credit. These scientists need to start doing their own work again so they actually have a real connection and insight.

Video idea: what happens to the professors after being caught in scandals. I'm in research, and here are 2 interesting examples known in our field: 1. David Baker, who is often regarded by professors in my field as the next Nobel prize winner, recenty created and extremely well-funded startup. He also hired Tessier-Lavigne as a CEO. That's the Stanford/Genentech professor with potentially fraudulent papers in Alzheimer's. 2. David Sabatini, famous ex-Harvard and HHMI professor fired for sexual misconduct, recently got big funds for his own lab by 2 wealthy investors.

The idea of AI going through old publications to find duplications like this is actually a fascinating idea (even if that's not what happened this time)! We already have a reproducibility crisis as it stands, so being able to weed out at least the most obvious fraud would be immensely beneficial for science as a whole. Of course, people would learn to "cheat better", but there's no reason why algorithms in the future couldn't be produced to catch that later as well. As sad as it may seem for science now, this could be a major step on the path to "fixing" it.

Lying for money? Who would do that? Certainly all academics have waaay too much integrity to do that...

If people faked data by random sampling from a gaussian with the desired mean/variance, it would be much more difficult to prove anything. It is scary to think about how many experiments can be manipulated that we can never notice

His response is not good!

This has happened before, many, many times. Nobel Prizes seem to bring out the worst in instututions and people. Examples include Jerome Friedman owing his physics Nobel Prize to a graduate student, who never got credit for anything. Or Samuel CC Ting/Burton Richter who owe their prizes to a a third party. The initial discovery was on Long Island Brookhaven National Laboratories. Ting doubted the results and dithered. In desperation a phone call to Stanford was made telling Richter where to look. Stanford had the better PR team, with book authors etc and they won the war of words. The guy who did the work, first, got tenure at MIT but is pretty much only known to the insiders-- this guy does not even have a Wikipedia page! Also Katalin Kariko/Drew Weissman would have stayed unknown too, considering their low status in the academic community if the pandemic hadn't happened.

5:24 I'd guess that the duplicated regions in the noise are due to some lossy image compression used some step along the way. However I'd expect them in all the images, not just one or two of them.

"Also, I found these regions by eye." What an epic line!!!

"And as the result his paper was retracted from PNAS"

It is soooooo common for scientists to photoshop their images to make them look better, even if the general results would not change. And this has real implications. Investors make decisions on how good a discovery appears, and perfect images can convince them to invest.

The first lab I was in, they never told us to fudge the data, but they didn't have the instruments to read a key parameter and essentially told us to make something up, and if the data didn't support the hypothesis the lab manager would be mad for the next week. I tried to build on the work of a couple previous students and was told that was probably a bad idea. It starts from the professor.

The statement I took the most pride in when speaking to any creationist was that our scientific community adheres to the scientific method with integrity, but now I am at a loss for words

Could not happen to a better University.

Sounds to me like a large part of the issue is that the system is built such that professors that are in an advisory role (and a loose enough role that they can't spot faked data in the study) are getting the paper published under their own name. If they didn't do the bulk of the work, their name should not be first on the paper. Instead, established professors names are being put on papers that in reality they had very little to do with, and there is little incentive for those actually doing the work to do it right, because it is not their reputation on the line. For my thesis, I brought the idea to my advisor, and we spoke for 30 minutes once a week, and she never even saw the experimental apparatus or the code. For my cousins thesis, the project was his advisors initial idea, but the only time he got with his advisor was a 20 minute slot once a week, within which 15 students took turns updating the advisor on their own different projects. If all of those are published, that's 15 papers with the professors name at the front, none of which the professor actually knows all that much about.

I thought peer review was supposed to prevent this from happening.

I remember when “the Harvard of the West Coast” was meant to be a compliment.

PNAS is not a peer-reviewed journal. It's the ultimate old-boy's club. NAS member submits the paper on a non-member's behalf. It was meant to be a high profile rapid publication journal of exciting new results. There was a time when there were not any other options (or few options). That time is kind of past. So a retracted paper is egg on some NAS member's face. But I always treated anything in PNAS with a very healthy dose of skepticism.

I'm always amazed on how mindnumbingly dumb they are in faking their data. They don't even add random "noise" onto their excel copypasta.

This sounds like students who are doing dodgy research are deliberately involving Sudhof in some small way because they assume that having a Nobel Prize-winning scientist listed as a coauthor will help their paper get more attention and also possibly make the peer reviewers more reluctant to reject it.

I know academics who publish hundreds of papers per year and are promoted and yet they don't seem to do any work Yet their work gets published in good peer reviewed journals In addition they don't even have access to lab equipment Who can explain this? I feel even the good peer reviewed journals are fraudulent and the editors just OK their friends' work Thanks for highlighting this issue Pete As someone who has worked in academia I can confirm that there is a lot of fraudulent papers

Science is a search for truth. If such discrepancies appeared in my work, rather than being offended I would want to learn why they are there, and what they mean. The off-hand, poorly thought out dismissals are concerning. Whenever someone seems to be saying “don’t look over there”, I have the overwhelming desire to look.

Those duplicated boxes in the images reminded me of something... In 2013 there was a scandal where Xerox photocopiers would sometimes change numbers on copied papers, 6 became 8 most commonly. The cause of this was some algorithm that detected repeated structures in the images and copied the same data onto all these places to save memory, but clearly it wasn't accurate enough to distinguish a small 6 from an 8. Perhaps this or a similar algorithm could cause such weird 'duplications'? There is plenty of information about this online if anyone wants to look more into it.

Thank you for publicising these matters. Thanks to Dr. Bik. for doing her work. Nobel prize or not this is science and all should have their work scrutinized. This is the only way to make progress. I am loving this disobedience to "authority".

I'm currently drown in data for my thesis (biomed) yet I'm still on yt watching scientific beef, totally love it.

As someone who went through the submission process before, JPEG is not an accepted submission format for images, rather ALL images have to be TIFF for that particular reason of avoiding compression artifacts. So, I'm calling bs on that part. But more concerning is that there's definitely a pattern of copy-paste on 'several' occasions.

Issues like this are partially why public trust in academia have fallen drastically as govt policy decisions & products such as medical treatments are developed based on academic findings. I'm extremely happy to see public peer reviews occurring to start weeding out the snakes in the grass that have been an issue imo for far too long. Time to bring credibility back.

Incentives will always attract those more interested in the value of the incentive than the value that the incentive is intended to reward.

From Scooby Doo: and I would have gotten away with it if it wasn’t for you meddling kids.😂

This is disgustingly shameful and should be sanctioned harshly by the governing body.

AI engineer here, modern AI image-generating algorithms cannot produce exact duplication of the kind observed in these plots. They can produce very similar regions, but because of the way they create the image the exact pixel values will never be identical in different regions of the image. (It's similarly as unlikely to random noise being identical in two regions of a natural image.) This seems more like manual photoshopping.

It blows my mind that videogame speedrunning communities have stricter proof standards and perform more in-depth scrutiny than established fields of science

If an accountant or lawyer signs off on something that ends up being false, they don't get to blame an associate.

Elizabeth is like Lone Ranger kicking ass. Respect.

9:29 I think you should mention in the beginning of the video how he most likely didn’t make these errors himself . That kind of changes the outlook on him, though in my opinion it still looks bad, but it doesn’t look like he knew it was happening.

There should be a website database created for scientific papers that had no significant results. So that those papers actually go somewhere, and people can look them up.

just a comment on the first fluorescent images and nothing else: if you turn photo A89P clockwise 90°, you can overlay the yellow box in it on the yellow box in photo 9-89. So what is to the left of the yellow box in A89P is 'above' the yellow box area and what is below the yellow box in 9-89 is 'below' the yellow box area. Because the photo plate is arranged as a bunch of square photos, not rectangular photos, these 2 photos show overlapped fields of view. the areas outside of the yellow box in both photos are as important to show as the yellow box area. so to fit a nice square photo arrangement on a plate of photos, 2 different, overlapping photos were provided. The same with the purple rectangles. I do not see artificial manipulation of the photos, just some overlapping regions in a couple of them. For photography under a microscope this is not unusual. They could have created 2 larger rectangular photos to replace 2 sets of 2 overlapping square ones but the layout of the plate would be disrupted. For those who care about nice visual arrangements of photo plates (I am a microscopist) they have done nothing wrong. For those who don't care about how their plates (or graphs, plots, tables) look, there are plenty of incredibly awful examples in the literature. as for the rest of the stuff, will let the medical community review his papers.

Yeah, the big boss himself is unlikely to be the one who manipulates the data (or even runs the analyses or makes the figures). However, when manipulation is commonplace in a group then it eventually boils down to the head of the group telling people to cover up the ugly stripes in their Western blots and to make some data up when nothing is available (or when the real data doesn't support the hypothesis). In short, it is a culture in his group, and who else to blame for the culture than the head.

For these reasons, I believe it is extremely important to document the exact procedures required to reproduce published results. While creating an "exact" manual is challenging, it would significantly reduce the occurrence of irreproducible results. In most scientific fields, developing such a manual is already a significant challenge, but making it standard practice could shift academia from focusing solely on results to a more comprehensive approach that values reproducibility and reliability of the processes used to obtain them. This shift might lead to slower development but would result in higher-quality publications. As a computer scientist, I recognize that reproducibility can be as simple as sharing code with the paper. However, many computer science papers still fail to do this. Consequently, I tend to disregard papers that only present results without providing a means to reproduce them. Publishing a paper without ensuring reproducibility feels more like showcasing achievements rather than contributing to the scientific community's progress. While some may argue that non-disclosure agreements (NDAs) restrict the sharing of certain details, such cases are rare. If the scientific community emphasizes the importance of understandable and reproducible research, even large research companies would strive to meet these standards.

TBH why couldn't the similar regions in an image be an artefact of an image compression algorithm? That's basically what image compression algorithms do : look for "unimportant" regions (perhaps where all pixels are very similar colours), throw away details, and replace that with a general approximation of the colour / texture. LZW does it most simplistically with stretches of the same colour being replaced by a single pixel and the length of the stretch. I'd guess more complex algorithms might do it with smaller 2d "patches" that are representative of larger areas. So I wouldn't rule out some unusual lossy compression (JPG? etc) creating artefacts like those described here. Also, changing resolution, attempts to brighten or despeckle or do other visual processing algorithms, especially if done at too low a resolution, might leave awkward repeated patterns.

The correct response would be to be concerned about the anamoly and to follow it up with the first author. The actual response leads me to think that their was either direct complicity, or an indirect culture that makes it acceptable to manipulate results. Although I would add that the blot images may have been manipulated for aesthetic reasons ... like someone put their coffee mug down on them and someone made the call to not repeat the expt. edit* Also to add, some supervisors can be really supportive of their teams and phd students, and will defend them really strongly.

Kind of interesting that the cheaters seem pretty lazy about cheating, too.

I’m a photographer and have edited many photos with the goal of getting them to “look right”. Sometimes the unmanipulated result looks misleading so you tweak it. That doesn’t excuse tweaking scientific images, but if an image in 2010 was ok in the meaningful area but had some artefact in the area of the coloured boxes then I would reach for a bandaid type tool to erase the artefact and clone some background area in. No one will ever know! Wrong, this kind of edit is pretty easy to detect if you know how they are done. I can’t tell if this is corrupt science or just the unwise application of photo editing software in the publication process. I would say there are two conflicting ethical standards here and the higher scientific standard rather than the image preparation standard should apply.

Blaming "copy and paste error" is ridiculous - there is no reason whatsoever for copying and pasting regions between images from separate experiments. Cropping to fit the images in the multipanel figure may be OK, but even there one has to be honest and unbiased, and not select what you want to see.

I'm pretty sure I (and many other computer science students) have a good idea of what might have happened here. In 2013, Xerox (major printer and scanner manufacturer if you're unaware) had a PR disaster where an independent researcher, David Kriesel, had found that a large-scale business scanner a friend of his used, had scanned different numbers than shown on the original piece of paper that was scanned. He found out that Xerox used an image compression format known as JBIG2, which creates "patches" of images it scans to be reused in the document. The default settings of the Xerox printer had a very high tolerance (i.e. patches that looked nothing alike were used as copies), causing even numbers in spreadsheets to be entirely incorrect. I'm not saying that's 100% what happened here, but copied regions in images can certainly be explained by lossy image compression.

Sadly, arrogance isn't a good defense in science.

If a person is included in the list of authors of a paper a reasonable assumption is that person is familiar with the contents of the paper and has at the very least reviewed the entire paper, agrees with the hypothesis, methods and materials, data collection and analysis and the conclusions of that paper. If that is not the case then that person has no business being a listed author of the paper.

If someone doesnt make a joke about the guy retracting his PNAS Im going to burst.

I wouldn’t call academia broken just from a misconduct of a scientist. And Academia being able to flag and retract works that might be a product of misconduct and dishonesty, and from a Nobel prize winner at that, sounds like a good system to me. It’s not perfect by a long shot, but hey, it’s there.

Main authors should take more seriously their responsibilities. If you do not want your name attached to articles with this low quality, then do a very thorough revision. You know who to call.

These efforts remind me of the efforts people cheating at speedruns go through.

This is just sad. Sudhof would have reacted with interest and joined in reviewing all the work submitted if he had not known of the false data. Science. You seek the truth, accolades are supposed to be the perks. Outstanding job, Dr. Elisabeth Bik. We need many more of you out there.

To be fair, quite a few of the duplications/errors noted on Pubpeer got responses from the other authors acknowledging their mistakes and showing the original data or offering to correct them. The majority seem to be genuine mistakes. The others don't seem to affect results anyway. But Südhof seems to get irrationally angry at these posts. Sure its annoying to have mistakes constantly pointed out, but its free. Also if the rest really were unintentional, he should get to the bottom of why they happened. Personally I think there were probably irrelevant visual issues with a few images and someone along the way decided (wrongly) to edit them.

This happens rather commonly in academia. It won't stop until the honors are stripped away in a public ceremony or similar exemplary action is meted out. The people who have studied at about the semi conservative model of DNA replication would know the British scientist Rosalind Franklin confirmed the semi conservative model through X ray crystallography process, but the honors and the Nobel Prize went to Watson and Crick. Similarly, the Indian Nobel laureate Amartya Sen probably received the honor because of his influential wife Emma Rothschild ( the richest and most powerful European family) . He currently has allegations of land grabbing a huge plot of university land and some fraudery charges labelled against him. Dr. Südhof's case might be classic PhD slave labour. All in all this hinders the sanctity of the Nobel Prize and disregards visions and scientific temperament of the patrons.

Based on his response to the accusation it would seem that he is a rather disagreeable character. This could have the effect of his subordinates feeling immense pressure to produce "successful" research. So, while he is almost certainly not the individual who is fudging images and concocting data that agrees with the theory, he may be causing that to happen, even if unintentionally. What would be interesting to know is: how does he react when a researcher tells him that the data are inconclusive, or that the test result images are questionable? From the brief exchange we see here, it seems likely that he wouldn't be understanding and pragmatic.

I came for P NAS jokes, I got them. Never change, internet.

Sadly when large sums of money are involved as an incentive in almost any field, not just science, we get stuff like this happening.

The fluorescence image I can believe is an honest mistake. Sometimes when we capture images of the same sample, we accidentally capture part of a previous region. We have hundreds of images to go through and sometimes human error occurs. But, the WB artifacts and copy paste data is laughably obvious... You would think these people would think to cover up their tracks a bit better. Maybe in 2010s it's not as important, but in 2023 you are over 90% going to get caught with copy paste data (10% reserved for low novelty papers published in low impact journals that not many people will read and review in detail).

The people who fake or alter results in the name of fame and fortune is sickening. Knowingly pushing false information in this way can be devastating for years if not decades.

These might be artifacts from the Floyd-Steinberg dithering algorithm, which is used to convert color images into grayscale. This method employs predefined repeating patterns, known as 'error-diffusion,' applied to surrounding pixels in both dimensions to create various shades.

sudof seems to be relatively offensive. which in of its own is absolutely terrible behavior from such a revered scientist. 😮😮😮😮

If people put in so little effort to fake data, they must be getting away with it quite a lot and be very confident

My thing is that Stanford being such an elite university, the students of Stanford are doing this kinds of things. They should definitely investigate the lead authors of these papers, who are probably using their Stanford PhD. to get prestigious teaching or research jobs.

Having identical blocks in an image is actually not as unlikely as the video suggests. It really depends on the encoding method used, digital artifacts really can produce these effects with non-trivial probability. For example, JPEG has a low-quality setting in which entire regions of the image will have the exact same pixel value; i.e., the pattern that's repeating across the image is just a constant value. In audio codec these things happen a lot too, and in measurement devices you have quantization errors... two random floating point values are very unlikely to be the same, but two measurements of very low amplitude signals are very very likely to be the same. Much like the image of basically a white background with low real-life variation being photographed. I'm not sure which codec was used and I can't rule out wrongdoing just from this video, but I think people throw out these "it's as likely as 1 in 10^900" way too much without it being correct. The actual digital processes generating these numbers and images are complex, and NOT purely random, and it's usually really hard to tell the actual probability of something like this happening. On top of that, for someone like Sudhof who has hundreds of published papers, with thousands of images in total, it might not be as unlikely as you might think to have 35 papers with random artifacts. That's before accounting for human error like the paste error in the video (which is really an honest mistake that can happen), and before accounting for the hundreds of thousands of scientists out there that are making mistakes all the time. I'd wager that finding a high-profile scientist with a lot of problematic papers due to no wrongdoing but simple pure chance is not an unlikely event.

Just "what" ISN'T broken?

I'd be most concerned about the pharmaceutical derived "conclusions", which may well be harming patients and/or making lots of money for some pharma-mafiosi. Has anyone investigated which drug and drug-making company benefits from these "errors"?

It’s happening all over the world!

As a visual digital artist of 25 years, that happens when you use a rectangular selection to copy and paste over a region. It looks like they used several small samples, put them together, then copied that again to move it to another area. Yes this is used to cover blemishes