Thank you. Hello. I'm Shannon Brownlee. I'm senior vice president of the Lawn Institute, and I'm the author of Overtreated Why Too Much Medicine is Making Us Sicker and Poor. And I want to welcome all of you to another social distancing social from Future Tense, which is a partnership of Slate, New America, and Arizona State University. And today, we're going to talk about issues with viral medical misinformation, which is appropriate to the COVID-19 virus. And I'm joined by my longtime colleague and friend, Jeannie Lenzer, who's a medical investigative journalist and author of The Danger Within Us, America's Untested, Unregulated Medical Device Industry, and One Man's Battle to Survive It. Welcome, Jeannie.  And today, we're going to start talking with an article that Jeannie and I just published in Issues in Science and Technology. And I don't even remember the topic of our own article, but it is Pandemic Science Out of Control. And what we were talking about was the kind of crazy hysteria that has kind of developed around a number of putative remedies for COVID-19 and the poor science that's being bandied about as if it were proof for efficacy for these various remedies. You'll know the names of a couple of the drugs that we're going to talk about, Hydroxychloroquine and Remdesivir. We're going to talk a little bit about a couple of studies, and we should just get started from that. So, Jeannie, why don't you talk a little bit about how we got interested in this issue and why we thought we needed to write about it? Well, I had originally written an article in the BMJ, formerly the British Medical Journal, about the Hydroxychloroquine because I was just dumbfounded that this study managed to trigger this avalanche of support, including from Trump and a number of doctors and scientists. And when I looked at the study, I was just astounded. So this was a French study conducted by Didier Raoul and I think it was 36 patients and I think about 12 of those were given usual care and the rest were treated with Hydroxychloroquine. And this was announced as a success. You know, this was a great treatment and Trump announced it as 100% successful. In truth, there were a number of problems on that study. One person died three people were transferred to ICU and two people withdrew. And these were people who were given the drug, Hydroxychloroquine. Yeah.  So how does this researcher get to say that it was successful when every bad outcome was in the people who got Hydroxychloroquine and none of those bad outcomes, no deaths, no ICU transfers, and no withdrawals in the people who got usual care? Well, the way he did it was by excluding those six people from analysis. And how did he get to do that? He got to do that because he only included people who made it through today six of the protocol. That sort of can sound reasonable. Let's not look at people who only made it through 12 hours of treatment she was, you know, that's not a real treatment. But when every bad outcome is in that group and they, it's kind of interesting, how do you not make it to six days?  And that's exactly what happened. Those six people were excluded because they didn't make it today six. So he announces the benefit based on a surrogate marker. And a surrogate marker is something that's like a lab outcome or a blood pressure, something that is not relevant to the clinical outcome. So say, which is what we hear about like, does the person get better? Does the person live? Exactly. So a surrogate marker say seems obvious, say you're treating blood pressure, but the real problem you want to treat is the outcome of heart attacks, strokes and deaths.  And that doesn't tell us about the real outcome you want to know. Did they live? And that's exactly what happened with hydroxychloroquine. We use this surrogate marker of how many people had the virus in their nose.  That reminds me of the old joke about the surgeon who comes out to the family in the waiting room and he says, I have good news and bad news. The good news is the surgery was a complete success. The bad news is the patient died. So on the basis of this really questionable study and questionable interpretation of the results, all of a sudden the world explodes thinking hydroxychloroquine is going to save everybody. And I think that's the part that we found kind of astonishing was that there were other studies out there looking at this drug and all of them were inconclusive or didn't find that the drug was effective or were badly done studies. And yet doctors around the country and around the world were suddenly not only prescribing this drug, they were taking it themselves. 40% of doctors said that they had prescribed hydroxychloroquine for COVID and it gets even worse because a common problem now and I'm fascinated by this problem because I'm reading the microbe hunters now and we see a distinct difference between what happened years ago and what's happening now. But the problem is is that once they did a Raul got a single study that said it was beneficial, he said, oh, it's unethical to use placebo or usual care as a control arm anymore because I've proved that it's beneficial. So the subsequent larger studies that he published were simply testing one dose of hydroxychloroquine against another dose. Well, one of them is going to win. So you've got to win either way, but you still don't know if the drug is killing more people than it's helping or if it's useless. And this is a real problem today is that we're leaving medical discovery to corporations with billions of dollars riding on these drugs. And in the past in the microbe hunters, what fascinates me is that these guys would do experiment after experiment after I mean they would repeat their experiments a million times before they were convinced of what they were finding. But now we have these companies who they're not going to let multi millions of dollars on a drug go down the drain. They're going to make sure that it's a win. And once they get that win, they say it's unethical to conduct further studies. Let's back up a minute. Let's back up a minute. Raul wasn't wasn't representing a drug company. He was just a guy at a Institute in France doing these studies. So it's not like a company was supporting this research and hydroxychloroquine has been out for a zillion years. So it's not like anybody's making brand name money on it. Are they? They are. Yes. And even generic, I mean, generic drug makers make generic drugs for a reason. They're getting profits. So it's sort of like McDonald's. It's volume. So they may not have as high a price, but their volume lets them win. And that's why they get in the business. No, you're right. So it's sort of like lung cancer. Not every smoker gets lung cancer, but that's more likely to give you lung cancer. So the problem with remdesivir and many of the other drugs, and I'll talk briefly about the vaccine, is that industry funding is really interfering with what we're going to learn because we know and in fact, the recent withdrawal of this study, Lancet just hours ago withdrew that study you and I were talking about that found that remdesivir was harmful and not beneficial. Well, how did that happen? That was a company that is there to make profit. Well, let's talk about that one in a minute and kind of finish up with hydroxychloroquine. One of the things that I found really interesting in kind of looking historically at what happened in the 1918 pandemic flu pandemic was in addition to really crazy stuff like, you know, boiling hot, hot peppers in your house and, you know, putting onions around and giving people laxatives and stuff like that breathing. Oh, you know, one of the remedies was breathing fumes from factories. So in England, they brought children near a tin factory to breathe the fumes because there had been this sort of observation that people who live near factories were less likely to die of the flu than other people. So, you know, there was there was a lot of crazy stuff, but two of the things that were used in 1918 were based on some reasonable kind of medical knowledge. And one of them was quinine, which is used, was used back then for malaria. It brought down fever from malaria. And then the other one was digitalis, which is a heart drug. I don't know what the reasoning around the digitalis was, but the reasoning around the the reasoning around the quinine was that it brings down the fever and it was thought that the fever was actually part of what was hard on your body and what killed you. Well, so it turned out that in fact, quinine and digitalis were bad and actually harmed people who had flu and that was eventually discovered. But 100 years later, we come along and what drug do we have against COVID-19, another virus hydroxychloroquine, which happens to be related to quinine. Yeah. So, you know, what goes around comes around or, you know, plusage, whatever term you want to use, but we kind of keep making the same kinds of logical leaps and then not actually testing them before we give them to patients. Now, one of the things I think that that really needs people need to kind of understand about hydroxychloroquine, which they may not, is that it may not be like drinking bleach, but it's not a risk-free drug. So, can you talk a little bit about what some of the side effects are? So, the worst one of great concern is something called torsade, torsade du point, which is an abnormal heartbeat that can be deadly. And it doesn't occur often, but if you're, you know, the truth is, is that 99% of people who get coronavirus or COVID-19 survive, 99% of them. So, if that's the case, and you've got a drug that may be, cause a rare harm, but nonetheless a harm, and you give this to everyone, you may actually kill more people than you help. And so, it's not clear yet whether that's the case or whether it's just ineffective, but it's, it's a serious problem and something to look at. Yep. So, let's, let's talk now, talk about this latest study of hydroxychloroquine. So, about, oh gosh, how long ago? Is it three weeks ago? The, yeah, the Lancet, a prominent medical journal, international medical journal published a paper that said that it had looked at tens of thousands of patients at 671 hospitals around the world and found that hydroxychloroquine caused more harm than benefit and therefore should not be used. And a number of governments then reacted to that. The French government said, no more giving hydroxychloroquine. The United States started to be much more cautious about it. I don't know what kind of directive the FDA gave, but this was a very important kind of finding. And the study was actually believed, the results were believed to the point where people said, okay, we, we might not have to do other studies looking at hydroxychloroquine. And we know that this drug causes more harm than good. Well, today, about an hour ago, the Lancet just withdrew that, withdrew that paper. And the reason is that it looks like the paper was fraudulent. So, tell us what we know about that paper at this point, Jeannie. Well, I don't really know much other than that the company, you know, had, it just seemed like a fraudulent company. The, the guy who headed it, I think his name is Desai, had come under scrutiny a number of times in the past for various forms of medical either, I don't know that the word would be misconduct, but some kind of fraud or problems with his work. And apparently their researchers were not qualified to be doing the kind of work, nor did they have enough, I think they had like five people listed as employees. And for those kind of data, you need many, many, many people to handle the data. I think what's interesting is, is that this turning on a single study is a problem in either direction. So they turn, you know, the fact that they are now saying, well, you know, it may not cause harm, that it changes behavior is just as bad as their earlier behavior where everybody was adopting it. I mean, it became part of protocols at many hospitals in the US and the UK, and around the world. China was using it based on what evidence. And a lot of it is just observational evidence or incredibly poor quality evidence like the Raul studies. So now, so for people who don't really understand what a randomized control trial is and why it's more, you can believe it a little bit more than a, than an observational study, what a randomized control study does is it, it basically takes a group of people and it randomly assigns half of them to get a new treatment or the treatment that you want to find out whether or not it works. And the other half get something called a placebo, which is a sugar pill or usual care. But somehow they are there, the two groups are given different treatments, but they don't necessarily know which treatment they're getting. The patients don't know. And it's also important that the researchers, the doctors who are delivering the treatment don't know which one their patients are getting because scientists are not, they're people, they're not infallible. Physicians are people, they're not infallible. And everybody comes into a study with a sort of set of, of prior beliefs. And so what you want a study to do is try to get rid of those assumptions and those prior beliefs as much as you possibly can. So randomized control trials are set up this way so that when you get to the end of the study and you look at who, which group did better, you can say with some confidence that you had gotten rid of as many biases as possible and you might be able to believe the results. Now, once again, believing the results of one randomized trial is not a good idea, especially when it's a teeny trial like the Raul trial and he does tricky things like takes out six of the patients and doesn't analyze them in the end. So, so your point about not believing one trial is really critical. Yet here we are, this is a terrible time. People need to do something. Don't doctors have to do something? Why shouldn't they say, okay, this looks like it might work. I'm going to try it better to be safe than sorry. That's the boogeyman that occurred. We see it when we look back at the 1918 flu pandemic. We look at any pandemic and we look at what's happening now. That's sort of almost a natural reaction. We've got to do something. Isn't something better than nothing? But there's a wonderful saying of doctors who've been through this game and seen how that kind of attitude results in harm. And that is, don't just do something, stand there. But stand there and observe. Do the studies. The feeling that if we don't treat the individual right now with unknown treatments, that that's, and I saw one doctor say that's compassion. Well, it's not compassion because A, if we don't know whether that treatment works or not, we also don't know if it causes excess harm. And so you're not only potentially harming the patient in front of you, but you're depriving all future patients of the knowledge we need to understand whether something works. So going back to yellow fever, which we had originally started our article with, and we remember they were doing bloodletting then. The big problem was is the doctor observed his own patients and said, I got them all better. If they went through seven bloodlettings, they survived. That's sort of a self fulfilling prophecy there. If they live long enough to get through seven bloodlettings, they were going to get through anything. Right. So, you know, and this was Benjamin Rush. This was probably the most, the most prominent and famous physician of his time. This was in 1790s. It was a, it was the yellow fever epidemic in, in Philadelphia, and his support of bloodletting during this yellow fever epidemic led to blood letting persisting long beyond the time when it should have just died. For more than 50 years, based on his observations. And I also happened to be a PA, a physician assistant. And, you know, one doctor said, you know, if this many people were dying from treatment X, we'd know it. We'd see these people dropping like flies. Well, I've got one response to that. And, and that has a lot to do with why I wrote my book. I was fascinated by these medical illusions. And one of those illusions is exemplified by the painkiller by ox. So there was this mild painkiller by ox that was taken off the market years ago. But it was ultimately found to have killed an excess number of about 60,000 people from heart attacks and strokes. And my question, when I understood that, because I prescribed it, was how in God's name did we not see it? Why didn't we see those people dropping like flies? 60,000 people in just about four years? We should have known. But it turns out when you look at anybody's individual practice of about, you know, two to 4,000 patients, and how many patients are over 60 or 70 who take it, and they die of a heart attack?  How would we connect that with this drug? We can't. And that's why we need studies. That's why we need well designed, well controlled studies. Observations have turned out to be wrong over and over again. Over and over and over again. In fact, you know, I, I wrote my book over treated. In part, I was a medical reporter for a long time. And, and you know this, Jeannie, but, and we, we found each other in many ways because of our shared interest in the fact that when you start looking at the history of discarded treatments and the kind of enthusiasm that existed for them, and then realize that it took really dogged research to find out whether it actually worked or not, it made it very clear that there was lots of stuff out there now that is in standard clinical practice that not only doesn't work but actually causes harm because we haven't subjected it to the kind of scrutiny that we need to. So, so let's move to the next drug, Remdesivir, which is a drug by a biotech company based in California, I believe, Gilead. And, and we have what a few more minutes left just yacking away with each other. Before questions, which I think is really fun. So, Remdesivir is a drug that before COVID had never been found to be effective for anything. It was developed for many things. Right. It's been tried on a lot of things, most recently on Ebola virus. There were trials that were done in Africa on Ebola virus and it turned out that it was not effective. But, you know, try, try, try, and try, and try again is the motto here. And there was reason to think that it might actually be effective against COVID. So, so it was, it had promised, but it had not had the real scrutiny that it needed. So the National Institutes of Health created a big clinical trial, a randomized controlled clinical trial to see if Remdesivir actually works or not. And, oh, this is now at least a month ago, the trial was stopped because the drug was found to reduce the time to recovery. Now, I don't know what the right answer is, but it strikes me as a little strange that we are now about to spend massive amounts of money on a drug that reduces time to recovery a little, but we don't actually know whether or not it reduces mortality. It looks like it might, but since the study was stopped, it's going to be very difficult to find out the answer to that question because now people are going to say it would be unethical to not give the drug because it's been shown to reduce time to recovery. Well, and in fact, the fact that they changed to make time to recovery their endpoint, so they changed the goalpost during the study, which- Well, that's a little, you're talking inside baseball, make this really understandable. All right, so- I know what you're saying, but- Say you have a shotgun and a tree and you say, I'm going to hit tree B and there's seven trees out there, but you're going to hit tree B and then you go ahead and you fire your shotgun, but the pellets don't hit tree B, they hit tree F.  I'm a great aim.  So if you can't, you know, you're supposed to have a hypothesis and test that hypothesis, I can hit tree B. If you then just go and say, well, scatter, I can do anything, and I'm going to eat, you have to reproduce that. Okay, well, I'm going to ask you a backup. So what they did, so what they did on that study is the researchers said, here are a bunch of things that we want to know about this drug. One of them is whether or not people are less likely to die if they take this drug from COVID, if they take the drug versus if they don't. Another one, what? That was an original end point. That was an original end point. So I'm saying at the outset of the study, they said, we're going to give this drug to half of the people in this randomized control trial and the other people are going to get a placebo, and we're going to see who lives, who dies, we're going to see who recovers. Well, I don't think recovery was actually even one of the original end points, but they had a whole bunch of it. In a sense, time to decide. But the really important one was, are people going to survive? Are they more likely to survive? And partway through the study, they say, oopsie, doesn't look like people are surviving. So we're going to look at a different end point, which is time to recovery, which is a weaker end point. It's a softer end point. It's not only softer, but if you're dying before your discharge, you could actually have more mortality. So in other words, we could have shorter time to recovery among the people who don't die from the drug. Exactly. It's possible. So it is possible. So we just need better studies. We need studies where money isn't at the center, at the heart of this. And right now, we have a government that is a corporatocracy. I hope we have a second to go to vaccine, because that is conflicted money out the wazoo, not to mention what Gilead has invested in Remdesivir. We also know that stopping a study early, there are studies that show this, and it's well documented, stopping studies early tends to bias towards a mistaken belief that there's benefit. So if they've done several things that are really troubling, they changed the goalpost, they stopped it early. And what was the other one? There was a third thing that was pretty significant. Well, yeah, but this wasn't, this wasn't Gilead that did this. This is the federal government. This was our premier research agency. No, no, no, no, that's the problem. So we have this, we have this game where I'm the, you know, I'm the, I'm the the Patsy. She's the pest to make me get it right. And she does it on purpose because she knows all this. But the thing is, is that NIH studies are almost all quote unquote, partnered with industry. There is no way that the Gilead designed this study. NIH is standing by. And what I know, and I've published this in the New Republic folks should look it up, is that there is no transparency with so-called NIH studies. There's a data in Sunshine Act. And if you read it carefully, it actually reads, thou shalt never release data from NIH funded studies, despite the, and I actually have been writing from the NIH an email in which they told me after I went through a Freedom of Information Act request for NIH data on clinical trials. And they said, despite numerous requests, we have never released data under the Sunshine and Data Act. So we've got money problems we've got transparency problems. Do we have time for vaccine for a second or we're still on one? I think we do. We have two minutes. You have two minutes. Okay. So now the thing that everybody is saying is what we really need is a vaccine. And that's true.  Thank you very much. I'm with you on that. And I also would like to be able to visit my mother in her assisted living home, which is not possible at the moment. Yeah. So who did Trump appoint as the COVID czar for vaccine and treatment development? Development. Well, his name is Monsef Slaoui. And he's a former pharmaceutical executive who resigned as the director of Moderna. Well, what does Moderna do? It just happens to be testing a vaccine for COVID. What a coincidence. And it turns out that Slaoui holds continues to hold $10 million in stock in Moderna. On top of that, the federal government in a nice I'll scratch your back if you scratch my back way a $483 million to Moderna. So once they develop their vaccine, if it seems to be useful, they will have private benefit on the public dime and no transparency. This kills me. Yep. Yep. And, you know, let's just hope it's the best vaccine if that's the one that gets awarded. Yeah. So we're we're we're anything else on vaccines, you want to say? Well, just if we really want to help people, I mean, what we see is how money does interfere with these financial conflicts of interest interfere with honest development of drugs and devices and vaccines. And if we really want to know that something works, I think we have to go back to the idea of independent research. And that means getting these partnerships out of NIH research means treating medicine and healthcare as a common good rather than as a private commodity. Yep. And I know there are groups out there that are working on the cost piece of it. But I think what we also need is and there are some groups that are that are clamoring for more open more transparency around clinical trials, there are groups that are clamoring around better evidence for medical treatments and for the vaccine. And they all have to go hand in hand because a vaccine that doesn't work very well at any price is probably not worth it. A vaccine that works really well has to be priced so that everybody has access to it, including people around the world. So I think I better look at my email now because I think the questions are supposed to come. Look at my phone. Well, I don't see anything at this point. Good, then we get to yak some more. Here they are. Sorry. You have to answer questions for a minute. Okay, so as someone who is looking at this issue from outside the US, it seems to me that the willingness by people to believe the gross misinformation is much greater in the US than in other countries. Do you think that's true? And if it is, what's the explanation? And this is from our good friend, Joel Lexchin. I think that's for you, Shannon. Oh, boy. I don't know if it's true, actually. I think that I think the media as the conduit to the people is so important. And I have to say that I don't think that the media in other countries are that much better than the US around issues of science and technology. And that's really sad because as a former member of card-caring member of the media, it's hard to say how badly we've really done in terms of informing people about a lot of issues in science and technology and the need for evidence. And so I see stories all the time that, you know, that sort of blindly support some terrible study as proof that this or that treatment is absolutely effective. When in fact it's a really terrible study and you don't have to be a statistician or a researcher or a PhD to recognize how bad it really is. So I don't know that it's really true that there's more or less misinformation. What we do have right now is an administration that has fueled an awful lot of misinformation. And I don't know that Canada, for example, has that, which is where Joel lives. Well, I think, you know, coming at it from a different angle. I mean, I think you're right about the media and I've attended some international media conferences and it does appear in part because we are so contaminated with private interests that we've become accustomed to being critical and searching out financial conflicts, some of us. But I think there's a different aspect that Joel was asking about, Dr. Lexchen, and that has to do with are people more willing to believe crazy stuff. And I think in the US that actually has been shown so that, for example, belief in evolution is extremely low in the United States compared to other OECD nations. And I think there was a thing about ghosts that, you know, enormous number of people in the US believe in ghosts that these kinds of superstitions and beliefs that are much more common, I think, in the US than other places. And I do think... There are people who don't think the earth revolves around the sun. I mean, that's kind of scary. We now have people who honestly believe the earth is flat. I mean, they're really are literally flat. We used to say that as a joke. They are literally promote. So, you know, this disconnect from facts and science is huge in this country and it's a serious problem. It is. It absolutely is. And I think it speaks partly to science education. But again, I think it also speaks to the media, which is so important in how much people know and don't know about everything, about medicine, about science, about physics, about all kinds of things. But right now it's so important that people have good information about medicine having to do with this virus. Yeah. So the second question, what can and should be done to stop the spreading of false information when it comes to medication, especially with the proliferation of social media and tons of enablers of lies that proliferate on these medias? And this is from Wolfgang Bearman, who I don't know. But thank you, Dr. Bearman or Mr. Bearman for that question. And thanks to Joel for his question. What can be done? Oh boy. So we have a friend and a colleague, Gary Schweitzer, who had, who ran a website for many years called Health News Review that did an incredibly important service. It's still running. It's still running. It's just, he's doing it on his own dime. On his own dime. And what the website does is it has a series of reviewers, these are people who look at media journal, media articles, and look at them in a very systematic way for how accurate they are and whether or not they mention really key points about any new treatment, about any new study, et cetera. So one of the criteria, for example, is does the article talk about cost for a new product? Does the article actually have anybody quoted who is, who has a different point of view than everybody who's saying this is the greatest thing since slight spread? Conflict of interest needs to be reported. And Health News Review really started to have an impact on how science and medical journalists viewed what they needed to do. Every outlet in the country knew about Health News Review and were a little bit upset when they got bad grades on their articles or their broadcasts. And that's one of the ways to actually start improving the kind of misinformation. But social media is a mess. And I have no idea how you control the incredible level of true mendacity and the kinds of lies that are being spread on social media. Yeah, it's a completely separate animal from journalists reporting, which is troubling enough that Gary Schweitzer had to start that outlet, which I think is wonderful. And journalists should go there. And if anybody has a lot of money and wants to invest in something that's really important, give Gary your dough, because it's really important service. And he has a toolkit there with things that journalists can use to learn about good reporting. There's also the list of industry independent experts listed there. So those are great resources. But when it comes to social media, that is such a mess and such a difficult problem to address that short of turning that into a journalistic outlet for medicine, where it has to go through a third, you know, assessment, I just don't know what you could do. It's a disaster. Let's talk a little bit about the list of independent, independent experts. So this is something that Jeannie and I started about a decade ago. At least, at least, I think it was 2000. And it came out of a story that we wrote about an NPR show. I forgot that's an NPR show. I don't even remember the name of the show, but the show was about mental health and media matters. No, it wasn't. It was something about the mind. Anyway, it was an NPR show. Oh, that's right. That's right. That's right. And the host of the show was a fellow Dr. Fred Goodwin, who had been, he'd been, he'd lost his job at the National Institutes of Health, as the head of National Institutes of Mental Health. No, NIMH. Because of comments, racist comments that he had made. And he had, he was hosting this show pretty regularly. And he had on a series of guests who were talking about antidepressants. And this was an period where the information about the fact that antidepressants can cause suicidal thinking and acts was just really starting to emerge. And he had on three guests, and all of them had conflicts of interest with the very manufacturers of the drugs. And all of them expressed the view that any fears about suicidality being caused by these drugs were completely overblown. And we wrote a story about it and basically exposed the conflicts of interest, which were not disclosed on the show. And it caused a huge flap. NPR dropped the show. The New York Times picked up the story. It made, it caused a really big deal. It was a big deal at the time. And clearly that information has finally gotten out that these drugs, while they can be effective for some people, you have to watch for the potential for them triggering suicidal thoughts and feelings and behavior. So we started thinking about the fact, and we've known this for years, that many journalists don't bother to ask their sources whether or not they have conflicts of interest. Their outlets didn't require that they do that. They didn't make a habit of it. And so a lot of what was appearing in the press was statements by people who had an economic self-interest to say one thing or another. So we just looked in our Rolodexes. Of course, everybody under the age of 30 has no idea what a Rolodex is, but it's an antiquated way of keeping track of average addresses on a piece of a little card. And we just opened up our address books and we created a list of all the experts in medicine, epidemiology, healthcare policy, a whole variety of public health, people that we knew did not take industry money and yet were absolute experts in their fields. And we made that list available to anybody who was a journalist. If you freelance and could show that you were getting stories published in the media, if you were a staff member of a broadcast outlet or a print media outlet, we were happy to give you our list. Ten years later, that list now has grown considerably. It's starting to have a real impact. There is a case of a practice with women who are giving birth, who are pregnant, that has really been changed because the members of the list were recruited to write a letter to a journal that then made it available to for people to make a decision about changing that practice. And the list is now housed at the Lown Institute and I hope any journalists who are listening out there will avail themselves of the list of industry independent medical experts. It's a good resource. It's a really good resource and it was mostly Genie's brainchild, but I like to pretend like I do. No, we did it together and we published an article about it in the BMJ for the British Medical Journal. Sorry, we can't solve the social media problem. Another question, why do you suppose the bad studies made it through the peer review system into prestigious journals like, oops, lost that one. It jumped away. Oh, why did bad studies make it through the peer review system into journals like the Lancet and the New England Journal of Medicine? Are there too few qualified researchers, reviewers, and if so, what should be done about it? Well, you've opened a can of worms, Mr. or Mrs. Anonymous. It's a huge problem. Peer review is very problematic. It lets a lot of things through that really shouldn't get through. And it's kind of understandable because it's really pretty time-consuming to be a peer reviewer. And peer reviewers often don't do the kind of real digging that they need to do to know whether or not, say, the statistics are really correct. And a lot of reviewing, unfortunately, reviewers have their own biases. And when a paper comes in that violates their own biases or goes against their biases, they're very, very tempted to reject it out of hand. And that happens pretty regularly. Whereas if it confirms their biases, they think that it's probably a good paper and they don't necessarily look at it very carefully. But peer review is a problem. Now, I don't know about this hydroxychloroquine paper that made it into the Lancet. I think it got in pretty quickly, so I'm not sure what kind of peer review it actually got. But it is a little shocking that the sort of holes in that study and the gossamer of what this company appears to be didn't get caught. Jeannie, any thoughts about peer review I'd left away? I'd actually love to address the issue of preprints if we have a moment or you need to get on with it. No, no, we're good. So there's been this idea that peer review somehow is rigorous. I think Shannon's pointing out that that's not always the case.  So you're not likely to say someone who is going to trash it. You're going to pick from your tribe. And Shannon and I just completed an article that will be coming out soon on medical tribes and belief systems that she was referencing. But the issue of preprints is interesting because now hundreds of preprints are coming out every day. And it may even be in the thousands, I think, are coming out every single day because of the pandemic. And there's this idea that, you know, we shouldn't pay attention to preprints. It's true because they haven't gone through peer review. However, I want to talk about a little exception to that and really where the line should be drawn with journalists because, yes, these articles have not been accepted into a medical journal. They haven't been put through much scrutiny, if any, and many of the cases. But there was a paper recently that was very controversial about the prevalence of COVID-19. And that actually went through an extraordinarily rigorous process because these researchers put it on the preprint server and put it out to the world, including not just the people they would like to review it, but they threw it out to the lions. And in doing so, you really improve your work. And as a journalist, that's something I try to do. I will talk to people who I know totally disagree with me in order that I can pick up what kinds of problems I might not be seeing. What do I need to address? And so in a way, the preprint service can be fantastic. But it should be kept within the medical community. That should not be picked up by journalists in broadcast, I don't think. I think that's right. And the interesting thing about the preprints is that everybody's going after them in public in a very interesting way. But the problem for journalists is most journalists, actually most physicians, unfortunately, are in the same boat. But most journalists actually don't have the skills to be able to look at papers and be able to dissect them and know what's a reasonable paper and what's something they should pay attention to and what isn't. And so when I was a journalist at a news magazine, a national news magazine, we would get these faxes. Remember, faxes from the major journals every week when they would publish. Or you are dating yourself. I know. And we got emails too. And the journals would basically tell journalists what the important papers were. So what journalists ended up doing was basically trusting the journals, the editors of the journals, and the peer review process for what they then put into the newspapers and magazines across America. And a lot of the stuff that got printed was garbage. A lot of the stuff that got printed in the journals was garbage. At one point, the editor of the New England Journal of Medicine said to me, if we didn't publish the garbage, we wouldn't be able to fill our pages. So that's a problem for journalists. How do they know what they ought to talk about and what they ought to not write about? And relying on the journals was one way to sort of put the responsibility on the journal. And that seems kind of reasonable. But now with these preprints, it's even more problematic. Do you write about a preprint the minute it's out? Or do you need to wait a little while before the lions have a chance to tear it apart and decide whether or not it's really a legitimate piece of work or not? And I don't know the answer to that one. I don't know how journalists are supposed to deal with that one. Yeah, really and truly. Let's move on. Independent trials are important, but do you think independent follow-up, once a drug is approved, has an important role to play? How do we spot the next Vioxx? This is a really great question, anonymous once again. This is an incredibly good question. One of the things that we don't do in this country is track what happens to patients once a drug or a medical device is out on the market. And I was having this conversation with my husband last night because he's in the healthcare community as well. And I was saying what we really need is a registry. If Toyota has a bad brake system, every Toyota driver in the country knows about it and knows there's a recall, they need to take their car in and they need to get those brakes fixed. How come we don't have that with drugs and devices? Yeah, it's absolutely insane. The manufacturers have fought that tooth and nail. They have fought any required registries. So, for example, in Europe, they had and I think Australia had registries for artificial hips and they were able to pick up cobalt poisoning because they had a registry where every... So there was a hip that had coke that was made with cobalt and it was causing cobalt poison. But we didn't know about that and people died and were harmed in this country because we didn't pay attention to what was going on in other countries. Why didn't Australia tell us? I think they probably did. It was probably out there. It was certainly out there as public information. But there's a real tendency in the U.S. to say that no evidence coming from anywhere but us is valid. Of course, that's very hypocritical because the us includes all our contract research organizations which tend to contract out all this trials to impoverish nations where they can basically entrap patients into these studies, some of which are completely unethical and certainly not related to outcomes that we'll see here. Well, let's go back to COVID. This is another question. In a joint statement Sunday, the U.S. and Brazil said hydroxychloroquine will be used as a prophylactic to defend healthcare workers in Brazil against the virus as well as a treatment to help Brazilians who become infected. There was a study announced just today that they did to test prophylaxis and they mentioned Trump using it as prophylaxis and they found no benefit. It just came out today. Now, I don't know the nature of that study or what, but this is really, this is crazy time. It is crazy time. So Brazilians get to get to be subjected to an unproven treatment. And they won't track those people to really know, but even if they do, there's a real problem with that because then it's just an observational study. It's not a randomized controlled trial. That's what we have to have. Yep, we have to have that. Well, let's wrap up with, unless there are more questions, more questions coming in that I'm not seeing, I don't think so. I think that, let's finish up with this whole question of the completely different issue, which is lockdowns. And many people who are listening to this may know that there is a considerable controversy around the current approach to COVID and reducing deaths from COVID. And let me see if I can sort of articulate it correctly, Jeannie. The debate is around whether or not lockdowns, we know that lockdowns are probably damping down the rate at which COVID is being spread. There may be cases where it's not like in hospitals, it may actually be accelerating spread because you're basically cramming a whole lot of people into a small space where a lot of them are infected. But there's a reasonable reason to think that lockdowns do kind of slow down the rate of spread. And there's some evidence that's coming out to suggest that that's actually the case, that it's, quote, flattening the curve of the rate of infection. Absolutely. The controversy comes over the question of whether or not we are actually likely to be saving more lives by doing lockdowns, by preventing COVID infections, than people we may be harming with the lockdowns. And one of the consequences of lockdowns is very clearly that we are disrupting our economy, that many, many millions of people have been thrown out of work, and that may have health consequences for them. So that's the current controversy right now. And I don't know what the right answer is, but I know that we have to ask the question. And part of the problem is complexity. I mean, there is so much complexity in this. What components of lockdown work? Which components don't work? Are there some that are neutral? Are there some that we should be doing? Some that we shouldn't be doing? Some that cause harm? Like, should we all be wearing masks? Is that effective? There's now a new study that suggests that masks do reduce the risk of infection. Yeah. And yet which type of masks? Because another study showed that cloth masks actually did worse than people who didn't wear any masks. So there's all sorts of complexity in this. And, you know, when the pandemic first started in China, I remember thinking, oh, gee, you know, they're doing the right things. They're really locking down. That's preventing stuff. And then you see that Singapore and Indonesia and other countries were doing different aspects of lockdown. They were not doing all the same things. And yet they were also getting excellent results. So the complexity gets even worse when you look at the sort of temporal nature of infectious diseases that tend to come and go. So the flu, terrible flu pandemic of 1918 went. It just went. There was no cure. There was no treatment. There was no vaccine. And that's what happens with a lot of infectious diseases.  The whole issue of the pump handle at Broad Street. I mean, this was the yeah, the father of epidemiology stopped cholera by removing the pump handle on a well in Broad Street. And in London. Yeah. And yet now a number of sources have printed what the actual rate of decline was before he took that pump handle off. And it turns out that there's a decline that goes like this. And about right here is where he took the pump handle off. And it just simply continued to go. Well, he actually had hold of some truth. He was right. Cholera was in the water. But we did the complexity of this kind of stuff observing what happens when and what makes a difference. We need to study those issues and not do what we always do with drugs and devices, which is a soon benefit. And that's what people say when Trump says, what do you have to lose? You have a lot to lose. You have your own life to lose. But we also have truth to lose. We won't know what will help people in the future if we don't do appropriate studies. And we need people asking the right questions, which includes not just what are the benefits? How much do we reduce COVID? But what are the harms of these interventions? Because we know that starvation increases as the food supply is disrupted. And it looks like we stand to have millions of people die from this disruption. That may be many, many more people than would die of COVID. And we also know that unemployment dramatically increases mortality for years to come. So we have to look at the the problems as well as the benefits. And this and what's so fascinating about this particular debate is it's not just in the scientific community. It's been highly politicized. And so there's this polarization of views on the left and the right or on the different spectrum of political views where now it seems to be sort of the standard liberal leaning view that lockdowns are good and the standard right leaning view that lockdowns are bad. And are simplistic. And both are simplistic, exactly. And it's a tragedy because it makes it much more difficult for us to figure out what really would work and what wouldn't. It does. So we're kind of getting to the end of our time. And I just don't know if I've missed questions or not. I don't think I have. So do we have anything, any other things we want to talk about anything else except for the fact that I can't wait for the next article we write together? I don't know what it's going to be. Yeah, who knows? We get in trouble, whatever we do. That's exactly. So I want to thank everybody for being on on the air with us and for participating in this for your questions, for your attention. Oh, hello, sweet pea. Just decided to come in for the ending and say and say so long. This has been this has been a social distancing social from future tense, which is a collaboration between Slate, New America and Arizona State University. I want to thank all three organizations for inviting us to participate in this event. And I hope to I hope we can be on it again in some time in the future. Okay, take care. Thanks, Shannon.


Hello, and welcome to our presentation, taking a page from the Scholarly Communication Notebook to Transform LIS Education. We are Maria Bonn, an associate professor and the director of the Masters of Science in Library and Information Science at the School of Information Sciences at the University of Illinois Urbana-Champaign. We'll cross the director of the Open Knowledge Center and Head of Information Policy at North Carolina State University, and I am Josh Bullock, Scholarly Communication Librarian at the University of Kansas. The intersection of open educational resources, or OER, and library and information studies or science, or LIS, is the original theoretical foundation for our work. Librarians are extremely active and visible in the open education advocacy and support landscapes, but examples of OER for teaching LIS topics were and remain relatively few. Outside of LIS, there are OERs spanning almost every academic discipline because the benefits are so obvious. Increased access to learning material because OER are free of cost and innovative instructional opportunity because OER are free of most copyright and reuse restrictions due to open licensing. But by and large, librarians aren't learning from OER and aren't magically exempted from the unaffordability of textbooks in LIS. This seems like an opportunity. Better meet the needs of LIS learners and instructors by engaging them in the use of OER on LIS topics created by field-based practitioners or experts. That might also lead to greater familiarity with OER and open licenses, which is valuable to a growing number of librarians. So that's where we started, considering an open textbook for our own area of expertise, Scholarly Communication. In 2017, we got a planning grant from IMLS that enabled stakeholder research and a convening in Raleigh, North Carolina where about 40 very smart folks doing SCALCOM work as well as ourselves spent a day and a half brainstorming, critiquing and complicating our notion of what the product might be. The result that took further shape at that convening and through many conversations with colleagues at various conferences is an open book that will be titled, Scholarly Communication Librarianship and Open Culture, Law, Economics and Publishing, and which will be published by ACRL under a Creative Commons Attribution Non-Commercial License. This book, which we are still in the process of creating, consists of three parts. Part one is an introduction to the concept of Scholarly Communication Librarianship and the social, economic, legal and political and technological forces that shape and inform it. Part two deals with the major relevant open movements, open access, open education, open data, and open science and infrastructure. Each of these sections is edited by an expert in that space with contributing authors of their choosing. Part three consists of about 25 short pieces from field-based practitioners who provide their perspective on a SCALCOM topic, examine its intersection with another aspect of library work, or present a case study that explicates a relevant topic issue or problem. While work on this project has been delayed by the pandemic, it has progressed and we are pouring additional energy and wrapping it up as soon as we can. More detail is available on our project site, lisor.wordpress.ncsu.edu. While we still believe in the value of the book just described, we also recognized with the help of our peers that a book is inherently limited by its format. It's linear, relatively static, and even when we include as many people as we can, its perspective is narrower than the reality of our work and the many people who do it. The positions from which they do it, the type of institutions involved, and the issues and perspectives on those issues represented. Maybe in addition to the book, there should be something more modular, open to greater participation and capable of growth, especially as scholarly communication continues to evolve rapidly as it presently is. We also got excited about a concept closely aligned with OER, open pedagogy, or open educational practices, which entails renewable assignments, authenticity in assignments, which is those that deal with real problems or engage in public discussions or in public-facing resources, and students as creators. We're particularly inspired by activist scholars Robin Terosa and Rajiv Jangiani, who have written and spoken on these issues extensively and who created a platform called the Open Pedagogy Notebook. We're so excited about the textbook, but we also know that any textbook is necessarily somewhat static and hierarchical, so we're developing the SCN with generous support from IMLS to be a dynamic and inclusive living community resource. The SCN is both a supplement to the book and a freestanding community hub. It will be first a site for open pedagogy and renewable assignments. We hope that courses will draw in materials from the SCN and contribute back the new materials they create in the process of their coursework. We also hope the SCN will be a bridge between education and practice. We hope that it will broaden, diversify, and update the topics and examples taught in LIS programs and be used for inspiration and self-education in the field. Finally, the SCN has been intentionally designed to fill gaps and create opportunities for underrepresented voices so that we can work towards our highest aspirations for scholarly communication. The platform we settled on is ISCME's OER Commons, where the SCN is set up as a hub. Partnering with OER Commons enabled us to take advantage of their existing platform and support, which is ideally suited to our purpose. It enables easy deposit and description, indexing and discoverability, and we loved features like some basic metrics and the ability for users to rate and review contents. There are currently seven collections or sub-areas of the SCN. Open access, copyright, open education, open data, scholarly sharing, including repositories and library publishing, impact, and a section on the what and why of scholarly communication. To bring in the existing body of OER, we've invited a set of community curators focused on finding, evaluating, and describing discipline-specific materials. They'll also write a summary of what they find and what's missing, and especially the opportunities for development in that particular field. We're hoping each curator will be able to identify between 30 and 50 works over the next six months or so, and then we, Maria, Josh, and Will, will curate the what-why SCALCOM collection. In addition to collecting existing content, which should result in between 200 and 350 or more works added, we've been sponsoring the creation of new content through three calls for proposals. The first in the winter of 2021, the second in the summer of 2021, and right now, closing on December 17th. Roughly 35 works are being created through this process, with creators paid for their work again thanks to the generous support from IMLS. So far, this has resulted in some fantastic new content, some of which Maria's going to discuss momentarily. We're also excited about works currently in production and those that will be created this spring as a result of the final call. Just as our core collaboration is a bridge between practice and instruction, we hope the SCN can connect librarians with LIS faculty and LIS students to our collective and mutual benefit. We see huge potential in open pedagogy as we pursue these goals and are intentionally centering diversity and inclusion in our collaborations, collections, and content creation. All of this activity, we hope, will lead to greater integration of SCALCOM topics into core curricula and build community in the process. And while our focus is on scholarly communication topics, we think there's potential to replicate these practices and other topical spaces to build a more open and accessible curriculum. As you can imagine, we're eager to see the scholarly communication notebook used. I'll share here some of our hopes about how it will be used. As one of the project's leads and as an educator, I benefit in many ways from the scholarly communication notebook. It's personally and professionally thrilling to be part of such an engaged community of practice and to watch the ways in which the members of that community challenge and support each other and witness their commitment to building a sustainable and equitable system of scholarly communication. I teach about academic libraries and about scholarly communication, and I learn all the time from that community. I learn about topics and about developments, a learning that helps keep my course offerings timely and relevant, and I benefit from having so much ready-made course material. You can see here the collections and we'll just refer to those in the scholarly communication notebook. Collections that map very nicely, not entirely coincidentally, to the topics in my scholarly communications course. In fact, I'll be teaching a section of that course this spring and populating my syllabus and class activities with these open educational resources. Timely and engaging material that bonus comes at no cost to the students. Here's one specific example. SCALCOM 2020X created by Stuart Baker at Western Oregon University. It's essentially a text-based video game across between a short story and a website where the user clicks links or types and commands to move the character through the game's plot about a day in the life of a scholarly communication librarian. I'm intending to use it as a sort of pre- and post-test, having the students play on the first and final days of class in the hope that they are more successful after a full semester of engagement with SCALCOM topics. And so I see the scholarly communication notebook in my classroom, but we also imagine it as being useful for the field, helping scholars and the librarians who work with them to tool up and to stay current. For instance, Chris Diaz at Northwestern University has created a lesson plan and tutorials for teaching and learning about static web publishing for digital scholarship. A lesson plan that could be implemented in a workshop developed for those new to communicative modes for digital scholarship. Or a veteran librarian curious about the increasing attention in the library world to bibliodeversity and uncertain about what that might mean for their work, could turn to the introduction to bibliodeversity and scholarly communication developed by Allison Kidinger and Jennifer Solomon at UNC Chapel Hill. Let me give a special shout-out to Allison, who was an LIS student at the time. She's now gainfully employed as a scholarly communication librarian. But such a curious librarian might consult this resource to get a basic foundation and to think about bibliodeversities applications in their field. Finally, we aspire for the SCN to be a platform, a space to listen to new voices in the field, to hear about the experience of scholars outside of the big research universities, and to consider the implications of scholarly communication and the choices it involves. For a diverse population of researchers, educators, and learners. Here we see that platform being used by Tatiana Bryant, the research librarian for digital humanities, history, and African-American studies at UC Irvine. In a module that is designed to help students understand and consider how qualitative research methods can support their practice. We see it being used by Natalie Hill at the University of New England in Jessica Dye from the University of West Virginia, who worked together to create case studies and teaching materials that asked participants to consider how our advocacy for OER and related open practices might have disparate impacts, particularly on those with less intersectional power and privilege. We hope you'll find an opportunity to listen to their voices. We also hope that you'll agree that the SCN already contains a rich body of work. We're very excited about that work, but we're just getting started. So we'd like to conclude by sharing with you some of the places we plan to go next. We're so excited to continue to roll out the resources that are currently just about ready for primetime. Our open textbook will be released in 2022 and begin to be used in LIS courses. Along with the book, we're excited to see how the SCN can be what we hope it will be as a dynamic space that supplements the book in the classroom and supports open pedagogy assignments for students using the book. We also know that the book and the website will benefit from scaffolding that supports use in the classroom. So we'll be developing some resources that make using these materials easier and demonstrate some potential applications and opportunities, maybe something like a teacher's edition. We're also inspired by the opportunities for continual improvement that are baked into open resources. We're particularly excited by the new potential offered by the code of best practice and fair use for OER that opens a lot of new doors for every resource in the SCN. We plan to work with educators to keep building pedagogical apparatus that connects and refreshes resources within SCALCOM and across other disciplines. We've also been thinking a lot about how to make resources that are often primarily textual into something more beautiful and inviting. Simple updates like adding cover images and illustrations can make a huge difference in terms of the quality and credibility of individual resources in the SCN. We've also been intentional about accessibility throughout this work and we have an ongoing commitment to making that a priority. And the core of our work continues to be inclusion and representation. We've put a lot of time and resources into filling gaps and highlighting voices, but there's so much more work to be done. Finally, we know that this project will live or die based on community engagement. We've been intentional about beginning with a North American audience in mind, since that's where we live and work, but we're already getting great interest from international SCALCOM communities. As SCALCOM is increasingly recognized as inherently a global effort, decentering North America and incorporating more global perspectives will be critical. We've also had some exciting discussions about how to tap into the rich set of open materials that aren't quite educational resources quite yet, but could be. More on that soon. We also hope to continue to expand the community and workshops. Parallel to a lot of this work, we've been holding workshops at conferences such as the Collective and ACRL, focused on helping people develop micro OER in a three to four hour timeframe. We're excited to continue and expand that engagement as well. As mentioned, we've also just launched our third call for proposals. With that great support from IMLS, we're able to offer 2,500 to a set of projects to develop new OER that fill gaps and highlight underrepresented voices in scholarly communication. We hope you'll take a look and consider contributing your own ideas. Thank you so much for joining us virtually for this overview of the SCN. We're excited to continue to build momentum. So please reach out to us through our website, via email or on Twitter and submit a proposal through our call for proposals. We can't wait to hear from you.


So with that, I am happy to hand over now to the first presentation, which will be for the PhD award. So hello, everyone. It's my great pleasure today to present to you this year's best graduate paper award, which goes to Viktor Petukov. But before he is going to tell you what he did, actually I want to say a few words why we chose him and what he's done, actually. So this year's theme for the award was machine learning algorithms for advancing spatial biology. And this is a very timely topic, I think. You probably agree, I hope. We even had a session. The last session was just about this. And there are many, many labs around the world who are working on making new protocols and enhancing the current ones in order to get spatial resolved transcriptomics data. So there's a lot of data coming our way. And all of this has to be analyzed in order to make sense of it. And this is where Viktor is coming into the picture. So Viktor is an expert in his field. He already, during his masters, he worked in the closely related field of single third transcriptomics. But then, which happened, I guess, at the St. Petersburg Polytechnic University, I should mention. And then, during his PhD, which happened at the University of Copenhagen, he worked on different things. But among them, he published a paper with the title, Cell Segmentation in Image-Based Spatial Transcriptomics. And this is what he got the award today for. So in his paper, he describes the mechanism how to identify the boundaries of individual cells. And I'm not going to tell you any details about that. He is going to do a much better job at that than I could. But I like to say a few words about it, at least. So what's really nice about his approach is that it's a novel machine learning technique that uses Bayesian mixture models and random marker fields in order to get a good understanding of the data and get rid of all the noise, which is in there. But also that the approach is applicable to a wide variety of different protocols. So it's not tailored to one specific experiment or technology. It's applicable to many different kinds. His code is freely available. And we heard that in the previous session. I think the term was transparent tools. So all the code is freely available. And on top of that, it's not only freely available, but there's also Jupyter notebooks. There's a demo to reproduce all the data to get into the field. The demo you can watch if you want to use it on your own and get into the topic. And of course, there's an extensive benchmarking where he showed that his tool clearly outperforms existing tools. So he's making a significant advancement in the field of spatial biology. And with that, I'd like to hand over the first years. Thank you. So where's the request? So you already got the name. And this was done under supervision of Peter Krochenko. At that moment, it was Heart Medical School, now Altoslabs. And course supervision of Konstantin Kadovich from University of Copenhagen. And in a close collaboration with Jeff Moffitt and with the help of very fine, nice collaborator, Ruslan, Rosalind, and Polo. So first, what data do we have? It all started in 2018 with the publication of the first big data set on spatial electronics by Stan Linnerson's lab, which basically got measured like these 33 genes on multiple cells. You may see the data like here. Each dot is a molecule. And it's colored by its gene of identity. And if you look at the raw data, it's x, y, like coordinates, and gene. And if you look at the clouds, they are likely cells. So you have a lot of molecules together. So it's probably a cell. But what's missing are cell boundaries. So technically, you cannot say which molecules come from each cell. And to fix that, authors used DAPI stains. But they said themselves that the quality is not so great. Usually, segmenting DAPI is not so easy. So the segmentation quality, like published by their paper, was also suboptimal. Currently, there are many more protocols, like for those who visited Jin's lecture, you also heard how they applied. But most popular of them are like Murphy's, Cosmex, Tanex Xenium. And these days, they mostly all provide membrane stains to segment cell boundaries. But I will show you later that it's not enough. So I'll show you how the data looks like. Now, what can we do with that? First of all, of course, all the same stuff which we can do with single-cell RNA sequencing, like clustering, connotating, this analysis. But on top of that, we can study tissue organization, particularly spatial processes, for example, cell migration. A lot of labs currently are working on cells of interactions, because we finally have information about which cells seed together and we expect them to communicate, so we can try to infer what those communications are. And we can go from single-cell level to sub-cell level so we can study processes inside cells. However, the problem is they all really require high-quality segmentation. For example, with single-cell RNA seed, we have the same problem as doublets, but many more of them, when molecules from different cell types got segmented into the same cell. So you might see here all these bridges. Second, if you study tissue organization, then some cell types like your mouse brain would show spatial structure, like excitatory neurons, and some like inhibitory neurons would not. But because of improper segmentation, your inhibitory neurons would have parts of excitatory neurons, so they would also appear like they have spatial structure, but that would be false. The same with cell cell interactions. If your cells seed close to each other and you just estimate their correlation, it's likely to be present just because of improper segmentation and not because of cell communication. And most papers I've read on that don't account and actually capture improper segmentation instead of interactions. So please hear, like, be really careful. Finally, if you are calling sub-cellular structures, like in the example here, if you have this yellow part getting into a blue cell, your algorithm would detect it as a sub-cellular structure, while it's just, you know, parts of another cell. So I told you about membrane stains. However, one uses them. They're really cool, but they are not enough. First of all, because honestly, not always you have them. So maybe experiment failed. Maybe a protocol does not allow that. It's hard to get them. Second, it's still hard to do segmentation. So membrane segmentation would have some errors. Third, sometimes you get membrane signal nice, and the other times you just don't get it. And it's biased toward particular cell types, so you're likely to miss some cell types, and it would be a systematic error. And finally, as with all biological experiments, you would get, like, just mismatch data for whatever reason. Like, you have stains, but you don't have molecules. You have molecules, you don't have stains. A lot. So with all that motivation, we have our method, and I'll briefly explain it, but really for more details, please look at the paper. And I try to focus on the parts which we did not emphasize enough, in my opinion. So it all starts with building a graph, a triangulation graph where each molecule is a node, and then we encode spatial information as a graph coming from continuous space to discrete space, which is easier to deal with. And then we try it for each node to assign some latent label. It may be like cell or cell type, and we make a statistical model for that, and infer those with expectation maximization or its modifications. So we proposed a general model, which basically works for different kinds of labeling problems for molecules, and we applied it in multiple cases. So we started with the filtration of the background, basically two labels, signal versus background, and we assume that dense regions are signals sparsar background, we do magic, and we remove background. So that really helps with the data quality. Like, this is known as a lot. Second, we showed that we can infer cell type information without segmentation, so we modeled it like as a mixture of categorical distributions where each cell type has a gene vector, and we may show that we capture like brain structure, properly like layers, inhibitory neurons, et cetera, neurons. Finally, we do cell segmentation, but it's like the hardest and the most important problem. So we expanded our model here quite a bit and got something like this, for more details I suggest you to look at the paper. But the idea was to use all the data we have. So of course we start like the only required data is the molecule X, Y gene, but we also have background probabilities from the first stage to filter noise. We may infer cell type, or use cell type info, it may be from our algorithm, it may be from another, you just can plug in additional information. And compartment info like nuclear cytoplasm that helps a lot because they have different expression patterns. If you have membranes, you can provide prior cell type assignment, and that also of course helps. And the model is easy to extend to other sources for helpful information. So I cannot take it back, whatever. No, I can. Yep. Sorry. So the thing is like, that's the main meat of the paper, how to segment cells, but there is another part which in my opinion is mostly underappreciated by others is how to do analysis segmentation free without segmenting cells, which you wouldn't expect in a paper on cell segmentation. So the idea is that, let's take all our molecules like here again, each dot is a molecule colored by gene, and take a molecule, take for example, 10 nearest neighbors, and call it a pseudo cell. Then as with any cell, we can extract its gene vector, like we see with a learning seek, and we can do all analysis on those vectors, and they are surprisingly robust, like we can find cell types, expression patterns, without any segmentation, it just works. Of course, there would be some noise, but still work through enough. On top of that, we can take those gene vectors and embed to 3D space, and convert to a color, as any 3D space can be converted. So we get our molecules colored by their local composition, and we call it neighborhood composition vectors, or NCVs, and it shows you different cell types with different colors, the more similar they are, the more similar are the colors. So it allows you to have this nice structure plots, like no segmentation, but you already see layers, you already see cell types, or some crazy UMAPs, not very helpful, but pretty. Also allows you to inspect visually cell boundaries, like you may see composition and whether the boundary actually separates composition. So that's the extent of what we covered in the paper, but currently we are working a lot on extending it, so what else can we do with these neighborhood composition vectors? First of all, let's look at the cellular structure. So here's like gut data, and you may see like gut wall and nuclei here, like in light green, and it get polarized towards the boundary, like the outer part, so just by neighborhood composition, you can clearly see the structure like inside the cell, and you can do it formally, like by taking your molecules, clustering them, and showing it like within each cell type what are sub structures there. Then we can try to interpret NCV dimensions and for example, here's like full NCV, but let's look just at the first dimension here, like colored by the dimension like volume. So you may see that blue actually highlights nuclei, so we didn't do anything, we didn't use any stains, but now we know which molecules are inside nuclei and which are not, so that might be helpful, for example to doing velocity, which gene invented on spatial data. We can also check other dimension and it's a place like a certain cell type here, brown one, and that's also helpful to know. So for example, if you want to study sub-cellular structure, you may remove the dimensions which are responsible for cell types and vice versa. Next, currently these NCVs are estimated only based on molecule data, but these days we have a lot of staining data and stain dots, so they're not very much like into each other. So what we can do, take each molecule, estimate intensity of each staining within this molecule and get a vector of intensities and finally do the same NCV trick. So we may basically show different markers stained separately on our molecule data, like here corresponds to this blue cell in PAN-CK and here corresponds to CD45. So we finally like merge together the staining data and molecule data. With that all, so we may take NCVs, we may filter the signal which we care about, we may add the staining signal. We can also use it in the segmentation model because currently the model expression as a vector which is linear like from the number of genes and it scales poorly so really gets lower with the number of genes and also it doesn't account for gene correlation structure but if you replace this vector with like five dimensional NCV for example and model it as a normal mixture that would be like always four dimensional like 200 times fewer dimensions so memory and also account for correlation structure so with all the benefits of what we described above. Finally, well of course as every pipeline we constantly work on improving it like usability, computational performance. We are in contact with 10X, they asked us to tweak their pipeline because they're going to recommend it for 10X Xenium so we constantly improve all the performance and usability. With that, I'd like to thank you all and if you want to read the publication is here, the code is here like everything package just go read and get in touch with me if you have any questions like special analysis in the cell analysis, I have a bunch of projects which I support so looking forward to meet as many of you as I manage in this conference and thank you for the collaborators and for the organizers. Thank you very much Victor. Questions? If you haven't figured out how to use the mic yet you just have to press and hold and wave your hand first and... Thanks a lot. Do you think modeling RNA diffusion is relevant for this model or do you have an intuition if it affects how segmentation is done if you are diffusing molecules? And do you mean like diffusion within a cell, right? Exactly. Also can be, I guess, depend on the technology in the spot or between spots or I don't know... Well, we don't work with spots to clarify it so we only work with single molecule protocols but if you're speaking about diffusion within a cell and if there are some strong processes which make the distribution of RNA uneven then it would help the model because the better our model is, the easier it is to separate cells. We don't do it at the moment, doesn't seem to be any kind of a bottleneck but if you would see such strong processes it would be nice to add. Any other questions for Victor? Go ahead. Yes, very nice. Can you clarify when you're talking about these NCV dimensions like first dimension captured cytoplasm versus nuclear second dimension cell type? So, did you do some sort of PCA? How did you get which were these different dimensions? I missed that. Yeah, well, it's kind of PCA. So like in the first approximation you may say you may take your gene vector, you run PCA, you run UMAP embedding on that so you get like linear embeddings don't work well in this case but something like UMAP is really nice. So yeah, like normal transformations but to five dimensions or like three dimensions not to deal like we do within the cell. Thank you. Any other questions? Go ahead. Yeah, it works. Thanks. So one question about when you said that you think that the second part of the paper or whatever that part of the paper was not or is not appreciated well enough, right? Yeah. So in there you're saying that you don't need to build boundaries to say what a cell is. You just take the molecules which are the closest neighbors and you sort of look at those at expression profiles of those, right? Mostly I don't mean like you don't need to do that to understand where the cell is but you don't need to understand the tissue composition in terms of both expression and cell types. So if you want cells like exactly cells well, you need cells. Yeah, of course. Yeah, of course, yeah. Okay, thanks. Any further questions? Jochen, do you have a question? No? No. Okay, just to follow up on that. What are the cases where as you showed and following on from that question where you don't need segmentation it still works really well. So what cases where that's actually the more appropriate? Well, I wouldn't say it's necessarily more appropriate. It's just maybe easier and less prone to errors and first of all is like first glance at your data. You take your samples, you run NCVs, you see clusters, you see expression patterns and that gives you feeling of the quality of the data set and of the composition of cell types. So I think that's the first part which I always do in my analysis. Right, thank you very much. I don't see any other hands up. So one, yes, your hand again, go for it. Yeah, we have 54 seconds. Right, thanks. So another question then is you showed the stain images, right, and you showed that you could pinpoint some of the stains from your model. So does that mean that maybe if there will be enough staining data to train on a model like yours could make staining not required anymore in a way? So you just run spatial transcriptomics, you use a model like yours and one day you would be able to say, oh, this spot is actually staining for this specific marker because we have trained on, who knows how many images. Yeah, well, that's a very good question. Theoretically, yes, mostly, except for the parts that the question is how many of the information is actually encoded in our genes and normally we try to do stains of something which we don't know from the RNA data. So yeah, I would expect that when we have a lot of genes and high quality models then a lot of stains would be redundant but then we would just measure other kinds of stains for proteins or like organelles. Thank you. Thanks a lot. Let's please round of applause to congratulate Victor.


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What's the most you ever lost on a coin toss? Sir the most you ever lost a coin toss call it for what? Just go we need to know what we're calling it for here. You need to call it. I can't call it for you It wouldn't be fair. Well, I didn't put nothing up Yes, you're dead.  You just didn't know it You know what date is on this coin? 1958 it's been traveling 22 years to get here and now it's here And it's either heads or tails and you have to say call it. Look, I need to know what I stand to win everything How's that? You stand to win everything call it heads then Well done. Don't put in your pocket Don't put it in your pocket. It's your luggage water Where you want me to put it anywhere not in your pocket or do a good mixing with the others and becoming just a coin Which it is


epic humans we work with. We're really fortunate. Bring it Portland! The only thing that slowed down Sean Rash from having really big scores was a little bit of pin carry leaving a lot of your favorites for 10 pin. Bob Barrett's going to go with a high hard one to start. How teams and players are doing. By the way, the English women's national team watch out for them at the World Cup in France. They are, I don't even know if I can call them a dark horse anymore. They're going to make some noise and Dom will be watching them this summer on Fox and FS1. There's another strike for Dom. Atta boy Dom! Came with Matt Ogle earlier in the season for that Roth Holman PBA double show. Can't wait to see the doubles championship material they hand out next year by the way. So Barrett working on a double try and make it three. Well he's found that groove there on the right lane. Well this is giving Sean Rash a little bit of time to get back in this with the Spirits. Only a 10 pin match. Not this time, 10 pin! Not this time! We're going to run down the lane and take it out ourselves. On that left lane, Andy Markle do. Now the chance is fishing chips. Love it! Fish a chance! Throw a little vinegar on him! It is point one to the Barrett camp. And he's going to move out on the left lane as well. See if it pays off for him in game two. He's got to win it. Something a little bit less aggressive. What a foreign national players to make the field. Belmo, Andres Gomez and the Iceman. And for Spensen, my spirit animal all made the top 24 to get to the first ever PBA playoffs. Spensen bounced by O'Neill back in week five in the round of 16. That's a pretty looking shot. Oh boy. He gets it a little bit right. He gets a little softer with it instinctively. Dom is just not fazed by this crowd at all. He's been that way for a long time. That's some good looking stuff, Dom. Yeah, it is. Sean with the 269. How about the high scores going on here in game two of our final quarter-final showdown. Winner, back here at Bayside Saturday for our semi-final coverage live over on Fox. We'll be teamed with Matt Sanders. Tom Smallwood. I haven't seen Smallwood this season at all. Seen another strike from Barrett. Open up for the first eight. He got it wide. And now he leaves the two-five. I'm not sure what distracted him. I mean, anything short of an earthquake or a fire, you should pretty much be used to this by now, right? Some caught his eye. Likes it. Gets it. Stras. Won a doubles title. Trying to get to the semis for that $100,000 Payday big strike. One more just like it. This for the point and to force a roll-off. What pin did he leave? Pug it with him. And then fires 268. Dom needs all three to tie. There's one. Dom working that clock. Doesn't have a re-rack. Missed it. We're going extras. He rolled about as good as you could possibly bowl that game. I would just stay the course. At one point he reeled off seven straight strikes in our second game. On the left lane. Gets him on a drop. Take that eight pin. A little soft and it looked like he tried to curve it just a little bit. And that may have been because of the last shot.  What is your problem? There's a strike. He's away. What a comeback. We've seen comebacks this entire tournament. It has been the theme. What misfortune for Dom Barrett. That solid eight pin killed any chance he had really. All rash needed to do was step up and throw the money shot. And he did. Dom is packing his bags. Yeah, keep it on the lane. That's it. See ya. Rash, great performance. Moves on. And then there were four. Free beer movement. Moves on to the semis.


Proudly we hail. Hello from Hollywood, ladies and gentlemen. This is C.P. McGregor speaking and welcoming you to Proudly We Hail. Through the courtesy of the Hollywood Coordinating Committee, we are happy to present the distinguished actor, Mr. Barry Fitzgerald, as the start of our play, The Light Burns Brightly, written by Richard Hall with music by Eddie Skravanik. It was raining that night, but the sound of the rain didn't conceal the hurried footsteps and the heavy breathing of the dark figure of a hunted man.  The others were seconds behind, as they rushed up the path to the door of the house. Upon my word, oh, Sheriff Meade. Mr. Kennedy here brings... Yes, of course. Here, what's all this noise? Ah, Sheriff Meade. Now what brings you here at this hour?  We're after a fugitive, a man named Dolan. Oh, that's a lot. Yeah, I read about him in the news papers. He's somewhere in this vicinity, Mr. Kennedy, and I thought I'd better warn you. He's armed and he's desperate. Oh, dear. Hadn't I better drive us, that is, you, into town for tonight, Mr. Kennedy? Nonsense, Briggs. We'll hold down the fort. Well, this is very kind of you, Sheriff. I'm going to leave a detail of men here with you for the night. Ah, that won't be necessary. I've been brought by that private detective agency since I received an extortion letter last month. But, sir, we can take care of ourselves, can't we, Briggs? Er, can we, sir? He's a pretty tough ombre, Mr. Kennedy. Well, if you think so. I think it's an excellent idea, Sheriff Meade. I put a man at each gate entering the grounds here. We've got a net out for him. We know he's in this vicinity somewhere. We'll get him. I do hope so. Briggs, you'd better go to bed. You're shivering as if you had the air. Yes, sir. Yes, thank you, sir. Well, thanks again, Sheriff. That's okay. Sir, you picked a bad night to play cops and robbers, didn't you? Come in, Mr. Dolan. Don't move. Don't move or I'll blast you. I know your reputation, Mr. Dolan. You needn't remind me.   Where are you at, Mr. Dolan? Oh, back up there, behind the telephone. And don't move. Eddie, this is Dolan. Where are you? I'm in a spot, Eddie. But I think there's a way out of it. You wait there. I'll call you and tell you where to meet me. Mr. Dolan, may I put my hands down now? You know, this is very hard on a man of my age. You keep them up there.  Stand back there. Tell him, Mr. Dolan, I'm an old man. I haven't long to live, anyway. You've got a lot of guts, haven't you? Oh, no. You see, I had a son. He'd have been just about your age now. So you see, I know boys. Now, will you put that gun down? What have I got to lose? But you wouldn't mind if I sort of held it handy here, just in case? Oh, not at all, Mr. Dolan. That's better. No, I think we ought to shake hands. My name is Kennedy. I know all about you. This is some joint you got here. Oh, thank you. Would you care to look around? I got other things on my mind. Oh, that's right, Jess. You want to get away, don't you? Well, in case you hadn't heard, there's an armed deputy at each of my gates. Thanks for letting me know. Yes, and there's a half-hundred more in the grounds. You haven't had a prayer of getting away. I'll take my chances. How? I don't know yet.  That's right. And you escaped from the penitentiary. How much longer did you have to serve? Two years. Well, no, that isn't long, is it, sir?  Two long years. Yeah, but you're so young. Tell me, why don't you give yourself up? Then make it very tough for you when they catch you. They won't catch me. You're turning awful hard in a spot like this, don't you? You can say that again. Well, it's too bad you don't use that thinking unstructurally. Save it. You got a car, haven't you, Kennedy? I wondered how soon you'd think of that, of course. And a driver? Yeah, a chauffeur. He's also my butler. All right, get me the keys to the car and one of his uniforms. Eh, well, I'll ring for him. Get away from that cord. It's too late, Mr. Dolan. But don't worry for Briggs. He jumps at his own shatter. You better not try to pull any funny stuff, Kennedy. Really? You rang for me, Mr. Kennedy. Oh, dear. Oh, dear. You see? He's fainted. We pause briefly from our story, the lights burn brightly, starring Barry Fitzgerald to bring you an important message from your war department. 40,000 good jobs are available to young men each month. Yes, the new regular army needs 40,000 men every 30 days to replace those being lost through discharge and other causes. These men are necessary to carry on the new regular army program of scientific research and development. Here is a chance for an ambitious young man to start a career in medicine, aviation, electronics, atomics, engineering, photography, and other interesting fields. The soldier is trained in any one of many industrial trades and scientific skills. An army job is high paying with opportunities for advancement and the chance to retire after only 20 or up to 30 years. The pay for a private in the army is equivalent to a salary in other fields of $342.86 a month. According to the editors of a prominent business magazine. And for a three-year enlistment, a man may choose his branch of service and theater where available. Ask at your nearest army recruiting station today about your chances for one of these 40,000 jobs. Enlist for three years for a career with a future. Act two of the light burns brightly, starring Barry Fitzgerald as Frederick Kennedy, the retired millionaire. Dolan, Frederick Kennedy's uninvited guest, has bound and gagged Briggs after forcing Kennedy to furnish him the chauffeur's uniform which he has put on to make his escape through the police cordon. Dolan is hurrying to get away. Ah, the keys to the car, Kennedy. Here. It better be the right ones. There. Don't you believe me? I must be going nuts, but I do. I still insist you're out of your mind to leave it this hour. Why? The simple reason that my car will leave rarely if it leaves at this hour. You'll be a nice to me, aren't you? Too nice. You're trying to stall me here? But don't you see my point? They'd be very suspicious of my car leaving this early in the morning. I'll stick around a little longer. Well, no, I think you'd be wise to do so.  A little.  How'd you know? The shoes you wear. You're really a screwball. You know, Mr. Dolan, it's the strangest thing about all plants are animals. The really fine ones acquire the best that nature can provide to grow and flourish. Here, come over here. Look at that plant. Isn't that lovely? It's a real Brazilian orchid. Put it in the right soil, provide the right temperature. It grows quickly and blossoms quite unexpectedly. It grows what? Nothing. Do you like beautiful flowers? I don't know. I never thought of it. Well, come on with me. I'll show you some more. So long, Mr. Kennedy. Thanks for your hospitality. Dolan, please. Turn yourself in. You're young. You've got everything in the world ahead of you. Save it.  No, I'm an influential man. I do everything I can for you when you get out. Are you kidding? I've already bought my ticket, Mr. Kennedy. And it only goes one way. All right. Save it. Aren't you going to make another phone call? You remember things, don't you? No thanks, Kennedy. Not now. I do need your phone now. Yeah. I wanted to give it to you. A present. Still don't trust me. Well, you never know. Well, Kennedy, thanks again for your hospitality.  Mr. Kennedy, are you all right? I'm all right, except for this early... Dolan was here last night. Left me a little moment. We know all about it. Well, I could shoot every man in that detective agency. After I got that extortion note last month, they were supposed to check every phone call. Just a minute, Mr. Kennedy. I... Dolan called from my phone. I suppose he'd have had him. I stalled him as long as I could. It's all right, Mr. Kennedy. We got Dolan. You caught him? Nope. He turned himself in. Turned himself in? Yep. Pretty amazing thing. Say, Mr. Kennedy, you better get to a doctor. Oh, that's nothing. So, he turned himself in, did he? Mead, I'm going to call the governor at once. Why? Well, I want to find out what can be done. But look here. Say, look. Look over there. What's that? I mean, that orchid. That Brazilian orchid. It's starting to blossom. What? You think I'm crazy, don't you? Well... Well, I am, Ed. I am crazy, but practical. And at a lot of fun. This is C.P. McGregor speaking. I hope you've enjoyed our proudly-we-hailed story starring Barry Pitch Gerald. Before leaving you, Don Forbes has an important message for all of us. Would you like to know how to make that new white shirt or that new dress last 4,000 years? Well, just keep it in a dry desert climate and protect it from the rays of the sun. According to army scientists, sunlight and fabric mold, most prevalent in damp tropical climates, are the chief causes of deterioration. Regular army researchers are experimenting with fabric materials, preparing them to withstand these effects and prolong the life of cloth garments. They're studying the various types of fungi which attack fabrics and the conditions under which they're most destructive. As a result of these army studies, clothing in the future will be specially treated to extend their length of wearing. Experiments in strengthening the clothing material is a part of the new regular army program of scientific research and development. In other fields, such as medicine, aviation, radio, engineering, and many more, regular army scientists are waging a continuous and winning battle against the elements. Planes are approaching supersonic speed. Man can see in the darkness with an army-developed instrument known as the Snooperscope. New techniques in medicine and surgery, such as the use of penicillin and a substance proving successful in the treatment of anemia, are being developed and utilized in the army. Commercial nitrate fertilizers to improve the quality and yield of our farmers' crops is being manufactured. In all fields, the army is contributing to human progress. Skilled men are doing this work. Many more, 40,000 each month, are needed to carry on the army program. Intelligent young men capable of being educated to handle the complicated scientific equipment of our technically trained army are required. High-paying jobs with security and opportunities for advancement are open to alert young men 18 to 35 or 17 with parents' consent. Ask today at your local recruiting station about the work of the new regular army and the chances for a career in it for you. Thank you, Mr. Barry Fitzgerald, for appearing on this War Department program. Proudly, we hail will come to you again on this station next week. Listen in.