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From Problem to Publication · The Short Coat (Audio): An Inside Look at Getting Into and Getting Through Medical School

• Jeff Goddard: I guess maybe I just need more rizz and people wouldn't yell around me so much. You do need more Riz AJ Chowdhury: always. Thanks Dave. You just need to be the calmest person in the room and , not show any emotion cuz surgeons can pick up on that. Jeff Goddard: They they can, they can smell your emotions. Yes, they will suss it out. AJ Chowdhury: Don't let the riz fool you. Jeff Goddard: I'm gonna be honest my biggest concern for medical school so far is that , I'm really scared that I'm not gonna be able to handle an attending treating me like less than a human being and not say something. AJ Chowdhury: No, you should totally say Jeff Goddard: something. It has to be said like, I can survive one bad eval. Dave Etler: , I'm not trying to say that like I know more than them or that they should, , walk on eggshells around me, just like. Jeff Goddard: Basic human decency. Yeah. Don't be a dick. Yeah. , exactly. That's all I ask. Like, just , , don't yell at me in front of the children that are in the er. That's weird. Yeah. You know? Yeah. Stuff like that. Very weird. Yeah. Dave Etler: I think what I think what it comes down to is figuring out how you would, how you might respond in those situations. AJ Chowdhury: Ah, yes. You know what, Jeff, if I stay here for residency, if you rotate with me. Rules one and two, don't be a dick and don't be a dick, and I'll give you a perfect eval. Jeff Goddard: That's all. Yeah, , that's the dream. Like literally just be a good human being and that should be enough. You know? Dave Etler: Welcome back to the Short Coat Podcast, the show that gives you an inside look at medical school from the students drinking from that fire hose. It's a production of the University of Iowa Carver College Medicine. I'm Dave Etler with me today In the s e P studio, a devoted, tight-knit family of bigger than life, badass co-hosts. He's a fiercely loyal, adrenaline fueled street racer with a pension for high stakes podcasting and a love for family above all else, it's M one. Jeff Goddard shave for your pleasure. Jeff Goddard: He's Dave Etler: a tenacious undercover cop turned outlaw who finds his place as a trusty ally and skilled podcaster. It's MD/PhD student, Daniel Sand. I'm not a cop. Jeff Goddard: He's a fast, don't call me a cop. Officer Sands. Exactly. Nice try, officer. Dave Etler: He's a fast talking wisecracking. Former convict with a pension for high speed co-hosting and a deep bond with his podcasting family. It's M three. AJ Chowdry, thank you for the consult. And she is a hard-hitting, no nonsense. Federal agent turned anti-hero with the short coat crew bringing her unique brand of muscle and charisma to the team. It's M two Mallory Kish. Hello. Anybody want a hazard? A guess as to where I stole , all those ideas from , Jeff Goddard: it felt, it felt very fast AJ Chowdhury: in furious as soon as I heard Family. Family. Daniel Sands: , you need to break out the, , the no cuffs t-shirt if we're gonna make you vin diesel. Dave Etler: Oh, oh, yes. And you need to be more bald. You need to be more comfortable with being bald. That's, you know, that's just, at Daniel Sands: least you're, you're all muscled up anyway, so you got that going AJ Chowdhury: for you. Oh, thank you. I, , saw my dermatologist for , balding recently. Cause I'm like, All right. This hairline's not doing me any favors. Like my mom's already sent out arranged marriage requests. Like I gotta make sure that I'm bringing the best package. , turns out I'm not balding. I just have a really high hairline. Oh, okay. That's good. I mean, that's okay. Yeah. Yeah. I guess I got that. For me, just, I'm just unlucky with my genetics. You get to put away the finasteride Oh, yeah. Those side effects to get Dave Etler: you. Yeah. , what are the side effects of Finesser? I'm AJ Chowdhury: post-op. I don't remember. All I Daniel Sands: know is that you use Finasteride for balding. And also, and prostate cancer and bph and, and, uh, what don't you also No, no. It's, it's an androgen. I'm, I'm sorry, I'm, I'm AJ Chowdhury: thinking about something else. I wanna say it's a five alpha reductase inhibitor. Yeah, it is. Yeah. Yeah. Well that Jeff Goddard: exactly. I took a test on this, literally this morning, so, yes, AJ Chowdhury: he's the most familiar Jeff Goddard: now. Yep. Dave Etler: Today we're focusing in on the mechanics of doing research goals, expectations, how to do things like a lit review and identify a potential project to the IRB process, the actual experiment slash data collection, writing the paper, the submission process, all that shit that I think we haven't covered before. We've talked a lot about like how to find a mentor and, how best to think about, , research in terms of what you want to get out of it and things like that. But this is more of what does research actually look like? AJ you, Started, thinking about this for a show topic. Yeah. How do you wanna start? You wanna start with the goals and expectations Jeff Goddard: part? Yeah. Did, didn't, didn't you get, uh, your name on something recently? AJ Chowdhury: Yeah, I had my, , first paper published in The Spine Journal yeah. Thank you. Yeah, thanks. Yeah, so I've been on a tear of research recently. I'm applying into, , interventional radiology and it's a very academic field, and so because of that, I needed to start doing research right away. , and I learned very quickly that, , even though I have a research background, I know how to identify mentors when it came to actually designing a project, getting knowledge in the field, and actually doing the work required to get like a first or second author publication. There's a lot of stuff that I was just in the dark about. . So I want to talk about how I've learned in the last couple of months, , how to actually do research. And then, , in a very short time span, I've gotten my first publication. I've submitted several other papers for publication. I've been to conferences and I'm about to apply into residency, and I still think there's plenty of time. , is currently near the end of April. I apply in September, and usually by now it's pretty late. And most people are worried. But if you find the right system to work for you, you can still end up being pretty productive as an M three, M four. Jeff Goddard: , I, so obviously the first step is, , trying to find a project, right? And a large part of that is understanding the field. So things like lit review. , my immediate suggestion, , may not be very popular. It's chat, G B T. , and let me tell you why I spent my entire fall. I already knew what the project was, right? The general idea of what the project was going to be, the specific methodology and like how we were gonna structure everything, not so much, but the general idea, right? , I spent months reading papers, talking to specialists that do research in this field, all of this stuff, , critiquing my ideas, , giving , the protocol to somebody to tear apart and then build it back up to make it something useful. I spent about 10 minutes on chat, G B T, , and it gave me all of that., I feel like I, like it was a good experience to go through all of that, but I also feel like I just wasted four months of my life that I could have just done all of that work in 10 minutes. That was really uncomfortable. AJ Chowdhury: Yeah. Chat, G P T and AI in general are actually very helpful. I've used AI in all of my projects now, and , it is not just finding research that it helps you with, but. Also getting , more papers for your lit review and also the entire process of organizing your knowledge from that and connecting dots back and forth. I'm not going to advertise any specific services, but if you just look up like how to do a lit review using AI on YouTube, you'll get plenty of videos with, resources that are very helpful. Jeff Goddard: Yeah, and even like building your studies, right? So like the building the protocol is, I would say far and away the most important thing once you have a base knowledge, , trying to make sure that you are creating a study that is actually going to be useful, right. And, , it's really nice to be able to sit down with an AI that's not gonna get bored of me annoying them all day long and just say, , , what are the limitations to this, , methodology? Or what are your suggestions for data analysis for this approach? And it just, it showed up not only my general knowledge of how to approach these types of studies. So it made me smarter, which I really, I'm glad that I got that. It made my study so much stronger because it poked holes in it and it, and then helped me fill 'em back up. Daniel Sands: I'll be the resident Luddite here. , I'm gonna be strapping, my wooden shoes and starting to trample over some stuff. I don't think that Chad g p t is a good approach. , this is my personal contention with AJ Chowdhury: lit review, but basic science researcher here, basic Daniel Sands: science researcher here, MD/PhD here. Uh should go to read the reviews. Yes. Ais are useful in assembling things, but I think, , Jeff points out really something useful that he did over the past four months was actually try and talk people in the field and try and learn from others. I actually think it was really useful for him to do all that stuff because it, he spent all that time learning and becoming a better researcher and a better scientist in this stuff. Maybe you undersell that, but I think that was actually a really good use of your time in understanding and assembling your ideas of the field. I think, again, the problem with AI is that it only accesses, , information that's already out there. Yeah. , in that it is not generating, , new information and that it's somewhat restricted by the fact that it can only use what's already available. , in that, , I think people oversell, , AI , and right now ,, it's a statistical parrot. Mm-hmm. Honestly, that's how these things work. Um, Markoff chains, you know, I mean, that's my understanding of these statistical analyses, but, I think there really is something to be said for the process of trying to trace through all this information yourself, of talking to the experts , of doing the PubMed searches, , reading the reviews and trying to dive deep into some literature yourself. Dave Etler: But you could do a hybrid approach. Daniel Sands: Absolutely. I think, , solely focusing on just AI instead of doing some of the, , groundwork yourself, I, think that's really, that might be undermining yourself in the long run. AJ Chowdhury: Yeah. So now I have three disclaimers. , for anybody interested in using AI for their research and doesn't have any research background before that first one being AI especially ChatGPT will hallucinate stuff and just make shit up. Like will cite things and make links to those citations that don't actually exist. Be very, very thorough in your double checking. And use this as a guide to help you do your own, do your own research. , and second disclaimer is that when you're using these AI tools, you need to make sure that you're aware of all the background knowledge that is being presented to you. So don't just read the abstracts for any articles that are presented to you, but also look at the citations, read the actual papers themselves, develop a system for reading these articles, because that will take you much further than asking a robot to do all the work for you. With goals and expectations, so I'm in a bunch of different projects now for various different things and have different levels of leadership in them. And when it comes to setting goals and expectations with your projects, you need to make it very clear immediately. How much work are you willing to put into this project? And how much work are other people on the team willing to put? What is everyone's background and levels of comfort with different parts of the process and how are you going to assign them? And then finally, how is this going to figure in with authorship? For listeners who don't know, authorship is like if you're the first author listed on a paper, you are going to be the person that gets the citation, your name on the citation. Generally first author means that you did the most work, second author, and so on, so forth. Less degrees of work can have co-authorship, where two people that did a the most work can share first authorship, and then you can have senior authors, like the PI of the lab is the last author. And generally, those senior authors, if you're within that field, you'll look for that name as well to see, oh, what is the quality of this paper based on my impression of this person's research. What do you guys do for setting goals and expectations for projects? Jeff Goddard: So I'm the PI on a project now, and we didn't, I just started doing stuff and, six months later I'm still doing stuff. So, it's been, a steep learning curve. What does doing stuff entail?, , organizing things with, a sister institution. Obviously creating the, doing all of the lit review, creating the protocol, doing all of the irb, finding all of the funding, arranging the travel so they can go down, and train the people to actually collect the data, because it's the project in South Africa, making sure that we're standardizing our, methodology and how we're delivering the intervention. So it just worked. Dave Etler: So so is this, was it done this way? Would you do it differently, now that you've done it? Jeff Goddard: Yeah, I might have asked for, concrete roles to, to have been established early on,, instead of just doing it all myself. Sure. I have a tendency to just do things. I come from a background that it's like, well, the floor needs swept, so you just sweep it. I don't know whose job it is. I just, I'm gonna sweep it floor. Right. Right. But when you're a medical student and you have a thousand other things to do, it isn't necessarily the healthiest approach to every project. Like at some point you have to be comfortable saying, I need somebody else to cover this part of this. Right. I haven't gotten enough sleep over the last six months, but, you know,, we keep going. It'll work out. Fair enough. In the long Dave Etler: run. Right. You've made your boat. Yeah. AJ Chowdhury: I Jeff Goddard: made my boat and I'm gonna Dave Etler: sail boat. You've made your boat. Now your boat. Don't sink in it. So what's, what is a system that you would AJ Chowdhury: Yeah, yeah. My system personally is, so let's say I have identified my mentor, I have set my goals and expectations, I have some idea of a topic that we wanna talk about. I'll, create an example out of a study that I'm working on right now let's say your institution and specifically your research lab or your attending, , and residents that you're working with, operate on a very specific disease that is rare or just very poorly understood at this point. You don't have an idea for your project, but you just know that you have this specific disease process and there's not much known about it other than it's treated a certain way. So what you want to do, starting off, is, and you can use AI for any of this to help you, but not to do the work for you. Start off by actually reading a review article. Get the knowledge base that you need to know the terminology, what is, the workup, and,, management over a long term period of this disease process. Then start looking at the more basic research. So if you recall your, uh, research pyramid at the top of the pyramid is your systematic review and meta-analysis. So go through that and then start working your way down to, , RCTs. , randomized control trials, go to case reports, anecdotal information. Just gather a wide net of information and then based off of that you can start asking questions like, oh, where are the gaps in the literature on this? Like for a project I'm currently working on very, very heterogeneous disease. We know how to manage it, but we don't actually know much about, , functional outcomes for it. Preoperatively, postoperatively. So that's what we're working on now. Is there any literature on that? And if not, let's start finding out ways we can quantify that with our patients. Let's get our data. Let's start st doing our statistical analyses and see if we can add anything novel to the field. Daniel Sands: on the background too. I think. , read the reviews, but also don't just limit yourself to the treatment processes, but really try and understand the physiology of whatever disease you're trying to study, right? It doesn't have to be a review article. Go back into your textbook and try and find a section on, , said disease. , try and understand what's going on, , because again, understanding this, , physiological basis for the disease you're studying, , will make it a lot easier to also think about treatments in, if you're talking about a cancer or something and you're, or a rheumatological disease and you're using some sort of, , anti, , or some monoclonal antibody, understanding that disease process is going to be a lot easier to understand why you're using that, , antibody , Jeff Goddard: or, or you can do what I do, which is, , applied. Research, because I'm gonna be honest with you guys, monoclonal antibodies bore the crap outta me. Didn't you just AJ Chowdhury: do a podcast episode Jeff Goddard: on this? I do not want to do. And I'm glad that people do basic science research. Mm-hmm. It's like computer programming. I'm not gonna do it, but boy, howdy do. I love the internet, so thank you. Whoever did that, um, Al Gore, that's a joke. , that's an old one for you. , I I find, , the physiology and the mechanisms of disease to be, , just kind of dull for me. I would rather find things in the world that like I can actually do something about now. So Dave Etler: , you're talking the difference between bench and say clinical. , Jeff Goddard: I'm going one step further than that. I'm like taking the research that other people have done and. Just doing it out in the field. Okay. So , I'll explain my project. Right. And it takes all types, right? Like obviously we need all of these things. Sure, sure, sure, sure. the fact that I find my field interesting is why I do it the same Right? Reason everybody does their own, but mine is, , so I'm doing interventional, , malnutrition research, right? So it's essentially I've got an NGO who has all of these resources and they want to know how do I best use these resources that I have? So we design a study, then we're gonna show, okay, this is the best way to use these resources. And , if it works, then they just do it immediately instead of it sitting on a shelf somewhere. For somebody , to come along 10 years from now and maybe, hopefully turn into to useful information to do something with, right? It's because I'm incredibly impatient. I don't have a lot of hope that if I do research, somebody else is going to apply it. I have to do research that I am now going to apply, if that makes sense. Dave Etler: So is this what they call translational Jeff Goddard: research? Somebody might call it that. Sure. , Dave Etler: translating knowledge into action. Yes. What is my understanding of what that is? Is that right, Daniel? I, Daniel Sands: My whole understanding of translational research is more from bench to clinical approach. Mm-hmm. , this sounds more like a policy focused, Jeff Goddard: Approach. Yeah. Which is this is taking clinical to policy. Yeah. Daniel Sands: Okay. So I'm not really talking about,, when I'm talking about physiology, you don't really have to apply physiology to clinical stuff. Pardon of me public policy approach. , , certainly I will say that, , there are things that deserve that approach. , if we're gonna talk about things like masking mandate, like I'm talking about like, okay, airborne particles and like how they interact in a physical environment, stuff like that. But yeah, , when it, when we're talking about like, I don't know, like how cells are doing their thing to policy, that that doesn't really tend to apply, but, but certainly for what AJ is doing, AJ Chowdhury: What we're coming upon is that there's different ways to do research. You can do the basic science bench work in the lab. You can do translational research where you take those findings and create a clinical application for, you can do clinical research, which is what I do. You can do policy research, basically anything that requires data to make some kind of new knowledge or change. Change being something like, quality improvement research is research. And you can be very, very creative with how you perform that research and what approach you take because of that. Jeff Goddard: Yeah. So like I, this is a wonderful example, right? So, , we recently had this, , novel virus that, , went around the world. I don't know if you guys had heard about it a little bit. , and AJ Chowdhury: you had like a computer Jeff Goddard: virus sort of, , except it was in people. , , and there were has its own Daniel Sands: algorithm for reproducing itself. Jeff Goddard: Yeah. And there were of course several different fields that approached it. Right. And they approached it with their own, , methodologies and their own understandings. The people that were doing epidemiology really didn't care about the mechanisms of this disease. They didn't have to all, they had to understand. For what they were trying to do from a policy standpoint is what policy works, whereas they needed other people to know what the mechanism is so that they could treat it on an individual level. Right. Daniel Sands: Epidemiologists though have to know the mechanism of the disease because a respiratory virus versus an arthropod born virus, they're going to function very differently. So I think that thing Dave Etler: that, I mean, there's AJ Chowdhury: gonna be some, they don't need to know how the electrons move. No, Daniel Sands: they don't. But , they ought to know, oh, it's, this is a, this is in the airway. This is what it's doing. And then also mechanism stickly, it's also really important for, covid versus flu. Does it replicate another animal species? actually, I'll push back on , that contention a little bit. , they really ought to know how the disease functions in some broad Dave Etler: shapes. AJ Chowdhury: Right. But that, , perspective of knowledge will differ based on which fuels you're going into. Mallory Kallish: I kind of, I think take a different perspective too. I did more clinical research, and my favorite thing to do to figure out like ways to start looking at what your project should be, is to ask clinicians, like, when you counsel patients, what, when do you say , we don't know which of these two methods is better or , there's a gap in the research here and it's really up to you cuz , clinicians are the people talking to patients and they're the one who can, , a lot of times hopefully if they're practicing evidence-based medicine , they know where the gaps are and they counsel patients on that based on gaps. So I think talking to a lot of different collections about how they counsel their patients is a really cool way too, to see where gaps in the field are. And it's not like diving deep into the literature because , It's stuff that isn't published. , and so it's just kind of a different way to look at it. I don't know if that , really said anything we were talking about, but No, AJ Chowdhury: that, that's a perfect description of what I was literally doing this morning. I was in the IR suite and we were, doing a specific chemoembolization on a patient and we were trying to figure out like what's the best dosage and best, , vehicle for delivery of this, because IR is kinda like the wild west of procedural research. It's just such a new field and we're constantly developing new technologies for it. We were literally doing a lit review during the procedure, the attending and I, while the resident was getting access to see like, okay, what do we need to order from the lab? What will work best for this patient? What risk factors might they have for certain things? Like taking the entire patient's history and actually applying it to the treatment in lifetime. Like it was really Daniel Sands: cool. The patient looks over the doctor's googling how I do AJ Chowdhury: ir, and far as confidence first search, please don't confuse your Google search with my up-to-date search , or my Daniel Sands: pub med AJ Chowdhury: search. The patient had a good outcome. It was a really cool case. Mallory Kallish: Yeah. No, but like doctors do that all the time, right? Absolutely. Like we make educated guesses all the time, but we should be basing it off evidence-based medicine and like even just like sitting in a resident room, like I hear residents just like spouting off random theories about like trends that they seem to notice with patient populations that have no, like evidence based behind it. And like those, that's so many, those are so many little like wells of knowledge that you could dive into by like doing a more systematic review. And I think that's like really underutilized. Cause we think that like everything that we could get is on the internet somewhere. Like we could find these holes, but especially as medical students, like we don't have enough experience necessarily to know where those holes AJ Chowdhury: are. Daniel Sands: Mal you point out a really good point though that, just spouting off ideas. In a sense it's a really weak point of evidence, but still somewhat evidence in that, you notice a trend and then, it's like, oh, , what's going on here? , so I think there, there is a, these are kind of like, if you almost think about like a crystal and it's like crystallization focus. It's like , these like hypotheses or these hunches there's still something that you can build off of it. It's important not to dismiss them as just kind of, I mean, sure some can be truly wild and, you know, maybe you shouldn't survive past that initial hunt stage. But some, some are Jeff Goddard: legitimate. I definitely, and I, mean this with all respect. Imp empiricism is a poor. Approach to medicine in the 21st century, though, explain empiricism is Well, I saw, well, I've noticed. Mm-hmm. Instead of turning to the literature, , I, if you're at the beginning of a novel disease, of course the only thing you have to go off of is the things that you see. But the sooner that actual data can be collected and actual, research can be done, the better. And the sooner you turn to that, the better. Right. If you just keep going off of things like, well, I noticed that we have more, , crazy people on full moons in the ed, and you build your life off of that, even though it's been like demonstrably proven falls for, I don't know, like 17 different studies over the last 20 years. I would consider that particular example may be a little bit innocuous, but that trend of approach to medicine is, on the whole harmful, Dave Etler: well, , I think what they're saying is that you can start with a speculation or a trend that you've noticed and then use that to decide what question that you want. Ask. Jeff Goddard: As long as you go forward with it, there's nothing wrong with it. The problem is that a lot of people will stop. They'll say, oh, I noticed this, and then they'll base their next 30 years of practice Mallory Kallish: off. To be clear, I'm not advocating for you to be like practicing medicine off superstition. I think vibes day medicine baby. So you can use those as springboards to start your research. AJ Chowdhury: Yeah, and that's where the research pyramid is. That's literally what we are discussing. Like you start off with anecdotes and eventually you have case reports, case series. You then are like, oh, we should probably do something more thorough. Have a, randomized controlled trial, have several of them do a systematic review, compare them with the meta-analysis. Suddenly you have developed a new guideline for, whatever hunch that you start off with. And of course, it's not just one person is. Teams of people, multiple institutions doing this, working together to further science? Daniel Sands: something I remember seeing in clinic when I was in clinic for a short time was, , someone came in with there are these cases of pediatric hepatitis going around, which was really interesting. And so I, I've just kind of kept my eye on some papers and they finally identified the cause of agent, which I believe is an adeno-associated virus. But it was a lot of these disparate cases of, yeah, I AJ Chowdhury: saw Reddit posts about these Yeah, about Daniel Sands: weird, weird cases of pediatric hepatitis. No one was really sure why it was happening, but it was happening. And so there are these trends, , right one of the modern things nowadays, it's gonna be Reddit posts, but it, it's going to be a little bit of a foci of information. It's not gonna be ma necessarily the greatest source. But you're going to be able to point to it being like, yeah, there is probably something going on cuz I saw what this, I saw what this person's posting about in my own life. Yeah. And then ultimately it's, made its whole approach to a pretty well researched, , article. I can't remember where it was published. I think maybe nature, but, they followed it through and , it's this actual documented thing now, AJ Chowdhury: so that is really cool. So you mentioned the IRB process. Jeff, what is an irb? Jeff Goddard: An institutional review board, if you're doing research that your institution, , and there are a lot of laws and regulations around this, but your institution deems necessary that they give ethical approval. You have to fill out an irb. So for example, mine is an intervention study. So I am giving an intervention to children, right? And so the question is, if I'm doing an actual research on human beings, how am I proving that my research is, gonna meet all of their ethical expectations? Right? And it is a very long, tedious process and it should be. Mm-hmm. Because the goal of the IRB is to make sure that everybody involved in the process is being, protected. Their job is to protect the people that I'm going to be working with. Yes. And my job is to prove that I'm going to take care of them as best as possible. Right. AJ Chowdhury: Right. And this is usually one of the first things you do upon starting a project. Once you've done your basic background research, start the IRB process because it is time consuming and you do not want to be on the wrong side of the irb. Jeff Goddard: And I think it's very important for anybody that might be doing this on their own for the first time or something like that. Remember, you don't start your actual research until you are approved, right? Correct. Because it's essentially useless in the scientific community if you're just cowboying it up out there without IRB approval doing research on human beings. Daniel Sands: Yeah, we're trying to get a, from the wild West approach of, , doing human research, Dave Etler: Are there types of research that don't require irb? Yes. Daniel Sands: Yeah, I believe so., Dave Etler: , I wanna Daniel Sands: say some cell research. Dave Etler: You probably, I was gonna say like if you're just looking at things in a Petri dish, Daniel Sands: or if you're doing research on, basically, as long as you can demonstrate that there is no possible way for somebody to be harmed, you can do that research. Jeff Goddard: Like you can do, retrospective research on people from the 1850s. Nobody's gonna ask you for an IRB on that, right? Yeah. But if you're doing it on living human beings, they might Dave Etler: IRBs are very complicated and very potentially confusing. AJ Chowdhury: Please clear up any questions you have with your institutional review board. Do Jeff Goddard: not Daniel Sands: quote the podcast host, Dave Etler: please. I love 'em. And Jeff, you mentioned that it's a long, tedious process, but, probably reaching, as you said, reaching out early to the IRB and saying, this is what I intend to do. I know that there is a tool, like an online tool here at the university that you can plug your idea into it and it will tell you, more or less whether you need to do an Jeff Goddard: irb. Yeah, it's like a little survey and so I've only worked with two IRBs at two institutions in my life so far. And both of them have been, willing to go above and beyond to make sure, that we got where we needed to Dave Etler: go. They're very, yeah. It's sometimes I think, seen as an adversarial process, but I don't think that's what the intent is. It's really designed to as you said, protect people and also to, , allow you to do research that , eventually will be useful. Yeah. So that's the irb. AJ Chowdhury: Yep. So we've talked about how to do a lit review and have a system in place for that. So once you have your IRB approved, you've done your lit review, you have an idea of what your project is, you've formulated your question, the next step is actually designing your project and collecting the data. So Jeff Goddard: I think to make sure that the process is well understood. You are designing the project while you're working on your IRB because they want to see your protocol. Yes. That's part of the review is making sure you have an ethical protocol. So these are, these steps aren't necessarily sequential. A lot of them you're taking concurrently. Right, right. Which is fine. A AJ Chowdhury: lot of research is hurry up and waiting. You get a lot of work done in bursts, and then you wait for the next step to be approved or for your statistician to finish your data analysis, so on and so forth. , so let's say you have gotten your IRB approved. Yep. You have started the base of your study design. Of course, things can change throughout your project as you get new findings and you realize like, oh, I need to also ask this question. , which can require an IRB modification at times. That's another thing that. It is useful to know you can modify an IRB once it's approved, but before that you cannot do whatever you're modifying your IRB for. It needs to be approved. So let's say you've done that. Sure. And you have col started collecting data in your project. Mm-hmm. What is your experience with that part of the process now? Mallory Kallish: The collecting data part, AJ Chowdhury: Collecting your data, putting it together onto some piece of software or a database. And then actually looking at, in seeing the trends that you've noticed doing the analysis. Mallory Kallish: Yeah. So the first thing I noted noticed is that , I think as researchers, at least in my, like what I did my research on, we really would love people to fit in like these really beautiful little boxes. Cause that's how we stratify and analyze data. And there's so much interpretation that goes into data collecting that I didn't realize. So full disclosure, I did a chart review type research project. So I was reading through like hundreds, maybe even thousands of different people's medical charts and trying to take every single individual person's chart and story and minimize it into a yes no box or a number box is so much more difficult than I think it was like even having read a lot of articles and looking at other people's research methods, like it seems like every part of data collection is so black and white. But I found that like me doing the data collection, there's so much of like my own personal judgment and my own personal expertise went into collecting that data. And that was something, I did not expect when I started it. just like being pretty open about like writing my thought processes and trying to keep it consistent. To try and keep that scientific integrity was really important for me when collecting data and trying to prove that what I was trying to show was the correct way to do it. Cuz I don't wanna create data that's gonna be confusing or tr or like untrue to whatever I'm trying to study. AJ Chowdhury: And you bring up a lot of really good points there with the subjective nature of collecting and interpreting your data and putting it into these boxes. And that's why we discuss these things when we write the paper as potential limitations in our discussion section, and disclaimers as well. So those are a lot of really good points you brought up Daniel Sands: actually, Mel, you also really point out a important thing about research is that it's always done by people. And people are going to have different biases and so that's also something. That argues in favor of, having a lot of other groups do these kinds of studies cuz they actually helped with the reproducibility and the rigor of this scientific research and really showing, no, this is something that's reproducible, that's not even just done it in our clinic, but it's a generalized, it will human threat. And so in favor of your AJ Chowdhury: reef. This is, actually a topic that's been pretty hot for the last couple years is the whole, reproducibility crisis in science. And it's not just healthcare. I think it actually started with psychology., there was a big discussion about this when I was an undergrad. I was a psych major about the reproducibility crisis and how a lot of research from certain institutions, the staff were just completely made up. Or, like in my psych 1 0 1 class, just talking how unethical studies were that we now base a lot of foundations of psychology Jeff Goddard: on. Just to make sure I'm understanding what you're saying, can you explain what the reproducibility crisis is? AJ Chowdhury: Yeah. Basically a study gets published and let's say it's a landmark study and other labs try to reproduce that study and they cannot come up with data that is representative of the findings made in that initial study. That opens up a lot of questions to the accuracy and reliability of that study. Yeah, Dave Etler: cuz now you have to question, was it done correctly in the first place? Did I do it wrong in my attempt to reproduce it? AJ Chowdhury: Or day forbid did they lie? Yeah. I mean, or Dave Etler: forbid, day forbid. Wow. Jeff Goddard: I, I mean, and, uh people are, I forbid it, that that is Daniel Sands: also an issue in science cuz you can look up,, many instances of scientific malfeasance in terms of, just copy pasting, Western Blots for instance. There's a really great researcher. Her name's, Elizabeth Bick, and she basically, yeah. Okay. Yeah, Mel knows. Mel knows who she is. She's gone through and she's, she has just a hell of an eye for like, Nope, , that's a copy pasted Western blot right there. Yeah. , but yeah, this is a real thing. Jeff Goddard: Yeah. Mallory Kallish: Also, not just like outwardly lying. , I have an background in engineering and mathematics. It is so easy to like, like muddle numbers and make stuff significantly significant when it shouldn't be by like, doing different statistical analyses and you should have a non impartial statistician doing your data, but not everyone has that. And it is so easy to like, correctly, even lie about your data . Dave Etler: I assume also even fool yourself into thinking Oh, a hundred percent. AJ Chowdhury: Oh yeah. Mallory Kallish: You're trying to prove something that you think is true. Right? You go into these studies a lot of times thinking you're gonna prove something one way or the other. And so, if you could make data, follow your preconceived notion, like you're more likely to pick that type of Jeff Goddard: analysis. And part of the reproducibility crisis, the big issue is the structure of academia. Pre-meds get into medical school or don't, based on did they publish, right? Not always, but that's a part of it. It's part of it, yeah. Getting into residency programs, did you publish Right. Getting, , tenure as an academic, did you publish continuing to get funding? How are you publishing? There is, a drive. There's a pressure too. There's a huge pressure publish AJ Chowdhury: or perish. AJ Chowdhury: one important thing that I've really learned from the PhD too , is it's not, do you have positive data? Do you have negative data? But do you have interpretable data? Are your experiments well designed? Daniel Sands: Can you interpret your results? And I'd argue that's more of an important thing to, that academia needs to shift in talking about these things. Because a hypothesis disproved is still one hypothesis less that you have to deal with in the long term. Yeah. Um, and so what everyone talks about,, publisher perish, it's really a big issue also with grant funding too, in this kind of reliance on the system, of, what are you publishing in the Dave Etler: United States? Well now we're getting into the writing up the paper part of AJ Chowdhury: it, aren't we? Yeah, yeah. So let's say we have gone through all the quagmires possible. We have identified. A good idea for our research. We have ethically designed our project and our IRB approves of it. We've collected our data, we've done our analysis, and all in the background of this, you should be doing the thing that we're all doing this for, which is communicate it with other people. And that's where writing and publishing your paper comes into play. So who here has gone through the process of writing a paper from scratch? I am Mallory Kallish: in the middle of it right now. I don't know if that counts, but AJ Chowdhury: No, that's perfect. So when did you actually start writing your paper? Was it after you've gotten all your data and now analyzed it or, no, it was Mallory Kallish: Kind of during my data collection. , I was basically trying to make it as, Correct to the methods I was doing as possible while I was doing them. So I tried to write them concurrently as I was doing my research. Dave Etler: Well, you don't wanna have to go back and rely on your memory or something as, Mallory Kallish: oh, God forbid that's failed AJ Chowdhury: me way too many times. Jeff Goddard: Right. Daniel Sands: Keep a detailed lab notebook, please. For the love of God. If you do lab work , or even if you're doing medical work, I assume any work Dave Etler: you need to take be taking notes, right? Jeff Goddard: Your stuff down, right? Absolutely. Yeah. If there's a methodology writing down, the actual steps that you're taking is probably for the best. AJ Chowdhury: Yeah. So for me that would be writing my methods section as I come up with actually designing study and having all the history of the versions of my methods. So I can refer back and see like, where can I make a modification in this experiment? Where did this clinical trial. Go in the direction where I'm knocking the data I hypothesize to have, what changes do I need to make for the next cohort? So that's your method section. The lit review is your intro. So now we're on our results section. What exactly is the results section? Nice figures, Jeff Goddard: beautiful tables. Preferably your data, not as you have already pointed out, not fudge so much that they say whatever you want them to say. Right. Daniel Sands: Actually, and this is something I wanna bring up too, is that,, it's really not significance that you're really wanting to focus on. You wanna focus on effect size. Like what does it look like? I mean, sure. You know, you could have a 0.01 difference and that can be really significant if you have like a massive end. But, again, we're trying to find something that's like, oh, 1.5 to one. Yeah. Dave Etler: This is, I don't know what any of that means. Okay. So, AJ Chowdhury: okay. I can, you're right, you're right. I'm sorry. I can illustrate this jargon, high yield medical information. You'll get questions on U World about this. Let's say you have a drug that . UWorld is going to be your best friend in a year too. No, it's not. Oh my goodness. Daniel Sands: You're gonna wanna throw a breakthrough AJ Chowdhury: computer screen. It is the most Mallory Kallish: humbling thing you'll ever experience. AJ Chowdhury: Yes. Yes Dave Etler: it is. This is the question set that you study for your boards on if you're just to get you up to speed, AJ Chowdhury: right? Yeah. I wake up and I go to sleep with, or I used to. I'm post step now with the nice split u roll screen of my question that I got wrong in the percentage. People that got it right and the explanation on the other side. Congratulations. Daniel Sands: You're one of 2% of people who selected these answers. AJ Chowdhury: 0% of people. That's the best one. Daniel Sands: Congratulations. You're a certified dumb ass. AJ Chowdhury: It's, it's a process. Any, anyone that gets the year old question wrong. it is not a reflection of your intelligence anyways. So, let's say you get a question and it's a stats question, and in the question it goes like, you are a physician running a clinical trial for a new drug for hypertension that reduces blood pressure. You find that compared to this standard of care drug that your drug has a statistically significant decrease in blood pressure compared to the other. But let's say it only drops the average blood pressure by one point systolic. That is statistically significant, but is that clinically significant? Do I care if my patient's blood pressure goes from 140 to 139 So you're okay. I get it. Yeah. So that's what, that's what dealer is Daniel Sands: referring to. AJ did a much better job of explaining that than I did. Well Dave Etler: that's why I'm here to be the dumbass who goes, don't know. AJ Chowdhury: Dave, you are with me in solidarity. For the 0% on you old. That got the wrong Daniel Sands: answer. Oh, I, I think we've all probably chosen a 0%. Oh yeah. On UWorld, if you've gone through enough questions, you've chosen the 0%. AJ Chowdhury: Absolutely. So then there's the whole pretty figures and nice tables part of your results. How do you guys approach that? Cuz I'm still working on making my bar graphs not look like a complete mess. Jeff Goddard: I guess it's what you're trying depends on what you're trying to show. My suggestion would be if you're going to do a line graph, and time isn't going to be your x-axis. Please make that abundantly clear., nothing is more annoying than seeing something that you're expecting to see. And then turns out you're not seeing that at all. You're seeing something totally different. It's not very helpful. AJ Chowdhury: Please label Jeff Goddard: your axes. Oh yeah. Like, you're not gonna get published if you don't label your axes. Daniel Sands: I've been reading so many goddamn papers in the last like months, but, , just like, don't use a bar graph for showing like time, like if you're using like multiple sequential bar graphs use XY plot. Like, I don't understand, sorry. Dave Etler: Like, so make sure that whatever pretty graph you've chosen is suitable for the data that you're trying to present. Jeff Goddard: And this goes back to this is kind of important, , how we talked about having somebody independent to analyze your data, which is incredibly, , helpful. , not just because frankly, you probably, you, the general researcher may not have, , a PhD in statistics, so you may not be the best person to do it. , it's nice because they're impartial. Yeah. , I would suggest talking to somebody about what the best way to, , model your results as well. That way you're presenting it in a way that's intuitive to not just you, the person who already knows what the answers are. Dave Etler: Right. Yeah. And bet that this is probably among the harder things to do when you're trying to prepare your data for publication is understanding like, what I, is understanding what other people are going to look at and interpret about your work. , I can throw together an email, but whether or not the person on the other side of that email is gonna understand it that's why I might end up spending an hour on an email rather than, throwing it , into outlook, you know? Daniel Sands: Yeah, yeah. , science again is a process of human communication as well. And you need, if people cannot understand your data, , your science is kind of bunk at that point. It doesn't matter. , I was looking at a figure the other day. There's a figure in like a cell journal or something, but all the, it was like a heat map and it was all completely unorganized. Like they, they didn't sort by the subject, they didn't, organize by condition and it, the data was, complete gamosh. I couldn't make heads or tails. Gamosh. I love that word. Yeah. It was complete gamosh. Yeah. Yeah. It was just a mess. it was a stew. It was just, you know, bits of, , meat floating, you know, over here. And I met, she's over here Jeff Goddard: and she's like, what Research meat. My, one of my favorites because of just how Dave awful it was,. At some point during the pandemic trying to show the different, , variants of coronavirus and how contagious they were and how many people had gotten infected , and something like that. Right. They had a spiral. Mm-hmm. So over time that the very center was like day one. Right. And then it spiraled out and then the thickness of the line was supposed to demonstrate exactly how many people had gotten infected that day. And it's a spiral. So it's a spiral that has varying thickness going around in a big circle on a map. And you're like, what the hell am I Dave Etler: looking at? I bet they thought they were really clever. Jeff Goddard: They probably did. And you know what? Sometimes you can be the most clever person in the room and be totally useless. And that's what that graph was. It was clever and useless. Daniel Sands: What, What are those, , pastries that have like the swirls? Yeah, like the cinnamon Jeff Goddard: button? Daniel Sands: No, no, no. It's like a, it's something that you roll up. It's like a little Debbie snack Dave Etler: kick or something. Oh, right, right, right. Oh AJ Chowdhury: yeah. Like a, it's just Daniel Sands: like that one of doom or something. Jeff Goddard: Yeah. It was. I can't imagine a worse way to present that data. Yeah. I just, and so don't do that. Don't try to think of some clever way to present your data. If a bar graph will do, A bar graph will do Dave Etler: better, better to fall back on forms that people understand and recognize instantly. Rather than that they have to sit there and interpret and try to Jeff Goddard: figure out. Most valuable thing about your research is that it is interpretable print. Daniel Sands: A beautiful bar graph is still beautiful. It looks very nice. Yeah. I think Mallory Kallish: that, brings up an important point about like, when you're making your results section, you should be thinking about who and how they'll read it. So I think as much as we think, like when we spend hours and hours on our research, like someone is like painstakingly, like reading every single line and like thinking critically about it. Like a lot of people are really busy and they'll just read like your abstract and like maybe like you're, I'm not saying you should do this, but a lot of people do this. It's like they'll just glance over your figures and like maybe read your like interpretation of them. And so who your audience will be. , are you trying to give this to the public? Are you trying to give this to like a very small other group of researchers? And like that also should really impact how you present your data because you wanna make it as like high yield for the people who are reading it and are her taking the time to look at your Jeff Goddard: research. Going, going back to Riley's suggestion from our Hot Takes episode. This is, a while back, just bringing it back, you know? Yes. , I'm a firm believer that the fourth author on every single paper should be an eighth grader who wrote the abstract. If you can't get that eighth grader to communicate what you wanted in that abstract, it's not worth publishing. Also, you gotta figure Dave Etler: it out. My own personal bugaboo and perhaps that of maybe 10 or 12% of the population out there, if you're gonna use color, Oh God. Please use color blind, friendly if you're Yes. If you're gonna use color, , and just make sure that other people can see those colors. I can't tell Jeff Goddard: you how many Six pastels that are like two shades apart from one another. Like, okay, this is, or worse Dave Etler: ones that go from like one end of the ROYGBIV all the way to the other end of the ROYGBIV And you're like, the two ends look the same to me. Jeff Goddard: Yeah. Daniel Sands: I'm thinking of all the heat maps I've looked at that are just like red to green or something. It's, if you're colorblind, you are so hosed. Yeah. Or microscopy, please use something else that's not red and green. ​ Dave Etler: What about the submission process? Yes. AJ Chowdhury: So you've written your paper, you have done all the painstaking work of creating a project and doing the science thing and writing about it in an effort to communicate with others. Now this is the thing that everybody. At the end wants is for their paper to be published. In order to do that, you must submit it to a journal. This can be sometimes the most painstaking part of the whole process. , and lemme tell you why, because I've just had two articles rejected, from journals. So now I'm rethinking the process for it. When you go to submit your paper, you need to identify the journals that you would be interested in submitting them to. You can only submit to one journal at a time, and they have to, if you want to submit to another journal, you have to have that article rejected or withdraw that article from submission for the journal that you initially Dave Etler: submitted to. Oh, I guess that makes sense. I never thought of that. AJ Chowdhury: It is a weird industry. But I'll save my rant on why scientific literature as an industry is largely a scam. Anyways, so the first thing is identifying the correct journal that will fit for your work. Generally, your pi, if you're a med student, will help you with that process. In picking the right journal, that usually means like Hey, let's submit to a journal that I've, been published at before, or one that I am familiar with that would be a good fit for this field. So that's the first step. And then we get back to the hurry up and wait part of the process. So usually you are stuck in a black box limbo for a couple of weeks to months. The submission process on average for the journals that I submitted to was like 11 weeks from submission to getting a decision. So during this time period, reviewers are looking at your paper and determining whether or not this paper is worthwhile to share with the scientific community at whole on their journal. Once enough. Reviewers, and these are peer reviewers of people in the field that are knowledgeable about what you are submitting. Once they have either agreed or disagreed on whether your paper is publishable or not, you'll either get a rejection or you'll get a decision that they want some revisions before they publish your paper or you'll get a flat out acceptance. Generally, you'll either get a rejection or revisions asked for on your paper Dave Etler: And so the revision requests take the form of like, I don't understand what you are getting at here, can you? Yep. Jeff Goddard: Sometimes they can be petty. Most of the time they're reasonably constructive. Yeah. AJ Chowdhury: I had one paper, I had a comment saying, please use a less language for describing your patients, which was fair and valid, and I learned from that, and other times it could be something as simple as, I don't like the way this figure looks. Yeah, Jeff Goddard: like I said, it can be petty. Yeah, I know. Have you thought about not using something so ugly? AJ Chowdhury: All right, so during the revision process, you are generally in a scramble because they will give you like a certain time period where if you submit or resubmit, they'll expedite the reviewing of your article and hopefully you can submit it in that time and then they'll look at it. And if you have, accomplished all the requests that they have of you for revisions, you'll have your paper accepted. Once it is accepted is a very short, time spann where the publisher will send you the manuscript that will be ultimately published on the journal. You will say, Hey, this looks good, or, Hey, let's make some stylistic changes. Send it back over. And then hopefully within a couple of days you'll have a publication. Congratulations, you're public. Okay. Nevermind. That sounds suggestive. I was giving the golf clap. Jeff Goddard: Don't do that again. Dave Etler: I have a quiz. I have a pop quiz. Oh yeah. Oh hell, I do. I have a pop quiz on research Uhoh. Every day news research comes to light about our world as we've just spent a lot of time talking about, hopefully helping us to understand existence better and better all the time. Or at least giving us some more questions to ask. Right? So let's see if you know about some of these recent findings, which I got from the very prestigious journal study finds.org, which appears to be mostly about, mostly studies from brands trying to drum up news coverage for their bullshit., product. All right, well, let's Daniel Sands: start with which sugary cereal reduces heart Dave Etler: disease. It's more like, you know. Well, anyway, you'll get an idea, This is actually a real preliminary study from Sweden's Karolinska Institute and Italy's University of Padova claims to show that social anxiety is reduced when patients are exposed to what, wait, I think I know this one. We've got a body odor of other people. B CAT videos from the internet., c Old Navy ads from the 1990s, or D photos of pizza. Jeff Goddard: I feel like B is a solid answer. Daniel Sands: Say AJ Chowdhury: D I'm gonna go with cat videos. Jeff Goddard: Cat videos. Yeah. Cat videos make sense? Yeah, I'm Mallory Kallish: just gonna say body odor for like AJ Chowdhury: the fun of it. Dave Etler: Okay. Okay. Well, it turns out that Mallory is correct. Body owner of other people, researchers collected sweat from volunteers who watched clips from horror movies like The Grudge or Happy movies like Mr. Beans Holiday and Sister Act. , patients undergoing treatment for social anxiety were exposed to those chemo signals to see if the emotions experienced. While perspiring had effects on treatment, they found that individuals who undertook one treatment session of mindfulness therapy together with being exposed to human body odors showed a 39% reduction in anxiety scores or comparison in the group receiving only mindfulness. Mindfulness, I e the control group, we saw a 17% reduction in anxiety scores after one treatment session. Wait, I'm sorry. Mallory Kallish: Can the sweat was from people who were scared. Yeah. So then, and it made you less scared. That seems evolutionary AJ Chowdhury: backwards. Well, Dave Etler: this is interesting because,, sweat from a happy person had the same effect as. , bo from a scared person. So it didn't seem to matter what the, Mallory Kallish: we're not that sensitive of what the cause of the sweat was. AJ Chowdhury: Right. It Dave Etler: didn't seem to matter what the person was experiencing. It was just more the fact of the odor. According to this, you're just smelling go, ah, , Jeff Goddard: I'm not alone, I think is the, maybe. Daniel Sands: Yeah. Yeah. Interestingly, , if you like how other people smell, that might mean that your immune systems are more evolutionarily distinct. Yeah. Yeah. Jeff Goddard: And so you should have sex. This, this, yeah, exactly. Daniel Sands: Babies. The smell. This isn't actually, Jeff Goddard: you know, this doesn't seem Daniel Sands: too far off from, , that, that kind of discussion. Jeff Goddard: Okay. So I have never in my life smelled somebody and thought, Hmm, I feel good. This, this is good. Dave Etler: I feel much better. Maybe Daniel Sands: go smells more people, Jeff Goddard: man, they're L'Oreal great. Panting all for it. Their actual skin. It smells like human. I don't know. Yeah. Dave Etler: Memo to myself. Set this up for a future show. All right. Question number two. , a new study from a team, , of University of North Carolina, Harvard, Princeton, and an animal nutrition company has found that genetically identical samples of Clostridium perforin, perforins, perforins, perforins, there you go. A common foodborne illness pathogen produce more sickening toxins when they are a older B, younger C teased AJ Chowdhury: or d hungry. Are the, is this the people that they're referring to or the samples? The samples. The, Jeff Goddard: it sounds like the bug. The bug. I'm kind of wondering how they teased a bug. I'm, are they, are they stressing the, the bacteria? Is that what they're considering a tease here? I don't know. I think it's gonna either Daniel Sands: be B or D hungry, because depending on what the toxin is, it's like, Okay. Sicken toxins, you know, that's probably destroying some amount of cells or something. So, and younger if it's like mid log phase versus older or you know, whatever that AJ Chowdhury: means. But his PhD's in microbiology by the way. Yeah. Yeah. So Daniel Sands: I, it's either Jeff Goddard: B or D. I'm betting, I'm gonna go with a D, just, I'm guessing I'm a metabolism something. I'll go Daniel Sands: younger, Jeff Goddard: screw Mallory Kallish: I'll say teased cuz the, it sounds fun worked for me for the last question AJ Chowdhury: I'll go , with a older, because, I don't know, maybe older bacteria, more curmudgeonly and they just want everyone around them to be less happy. Dave Etler: I have noticed that tendency in myself. Yes. I'd be grumpy as Jeff Goddard: I get older. Now's over here trying to bully bacteria. Mallory Kallish: You can tease someone in a fun way. Jeff Goddard: Yep, yep. Dave Etler: Yeah. The answer is hungry. , bacteria that we're not producing toxins were well fed. Bacteria on the other hand, toxin inducing C perforins cells appear to be lacking those crucial nutrients and offering the. Hangry bacteria, a snack of yummy acetate, reduced not only their number, but also their toxin output. So maybe this is a, this could point to a way to combat the effects of this type of infection, while also tackling antibiotic resist. Jeff Goddard: I guess, again, Daniel Sands: I think, , just points to, understand metabolism of bugs and, how a lot of our antibiotics work functioning, by screwing with me metabolic Jeff Goddard: pathways. So, you know, AJ Chowdhury: ANCO burr, Jeff Goddard: you're teasing the bacteria. Dave Etler: AJ. Yes. I think you've told me your Bangladeshi. AJ Chowdhury: Yes. That's why I chose, thank you for, getting it right. I, Dave Etler: well, this time, this study of Bangladeshi couples found that two-thirds tilt their heads to the right when blank. A what? A, listening to their partner. B, kissing their partner. C thinking about their partner or D threatening their partner. I've AJ Chowdhury: never seen Bengali's Kiss. B can't be correct. Dave Etler: Surely Bengali. The Bun Bengali people enjoy a good kiss. I, AJ Chowdhury: I refuse to believe it. Okay. I would go with thinking about their partner. Dave Etler: All right. Any other guesses? Daniel Sands: I'm throwing in for Dave Etler: a, I don't know, why did they choose Bangladeshi Cup? , that's an interesting Jeff Goddard: idea. They were just sitting there in Bangladesh and they're like, there are partners here. Let's , slate them. I Dave Etler: believe this was a UK study. I don't know AJ Chowdhury: if that helps that. I mean, , south Asians in general are the biggest immigrant demographic in the UK, I believe. Sure, sure. We definitely made their food taste good. Jeff Goddard: Let's go with see. Well, I mean, come on. That was such a low bar. It was literally on AJ Chowdhury: the floor. We are, come on. Chicken Tala is not South Asian. It is a British food. It Dave Etler: is British cuisine. I, I think the point is that, you know, when you're coast, you're, yes. The bar Jeff Goddard: for improving their food was so low. AJ Chowdhury: I know. Dave Etler: Any other guesses? Jeff Goddard: Have we, sorry, SWES? No, AJ Chowdhury: Dr. Swes Australian. Jeff Goddard: Australian? No. He lived in Australia. He's originally from Liverpool. Oh, right, right. Whoa. I only know this because, , he, it's the one lecturer that I actually pay attention to. I guess , he's a wholesome man. He's got the r. Daniel Sands: Swes is good. Swells is good. Jeff Goddard: I'm gonna go c I'll go ahead and thank All right. Thinking about their partner also. B, why not? Dave Etler: Okay. All right. The answer is B, kissing their partner. This was true whether they were initiating or receiving a smooch. Although men were more than 15 times more likely to initiate a lip lock, Bangladesh couples were ideal to study according to the researchers from the University of Bath in the United Kingdom, because they are culturally prohibited from viewing, kissing in TV and movies and so weren't influenced by those sorts of images. I AJ Chowdhury: need to have a conversation with my parents. Jeff Goddard: He's never seen his parents kiss either, so AJ Chowdhury: I have not, I've never seen my parents kiss. I was told about a stork when I was born. Drop me off the stork on my head. The Dave Etler: stork is a culturally relevant, thing in, in Bangladesh. AJ Chowdhury: You have to remember Dave, I grew up in the us Oh yeah. Jeff Goddard: Alright, just , Daniel Sands: come on Dave. Just the researchers, you know, breaking out the binoculars and just tracking people Jeff Goddard: down. Dave Etler: You're like creepy. They do Jeff Goddard: kiss. Creepy. Daniel Sands: Creepy. Yeah. Creepy. This is the voyeuristic researchers. My God. Oh AJ Chowdhury: my. Dave Etler: From the meta zones, they're just like us desk sponges. One of the oldest multicellular organisms in existence do just what a human would do when exposed to an irritant. They what? Scratch themselves, but very slowly leave the area, but very slowly sneeze, but very slowly. Or report it to hr, but very slowly Daniel Sands: think sponges. They're fixed. I think it's Jeff Goddard: sneeze. Okay, I'm gonna go with leave. Okay. I really wanna Mallory Kallish: go with D just for like, AJ Chowdhury: I reported to HR just cause I know the sponge HR desk. I'm with, I'm with Mallory on this one. Have you ever seen SpongeBob Squarepants? He would never, Jeff Goddard: don't think there's hr. They report HR about him. Dave Etler: All right. , the answer is sneeze. , sneeze. When a sponge sucks in a particle that is too big, it will contract muscles to push the waste containing mucus out a sponge. Sneeze takes anyone want to guess how? Two minutes, how long it takes to complete Two hours. Okay, I'm gonna go two minutes. Okay. AJ Chowdhury: Two seconds. I don't know. Or go is Jeff Goddard: a magnitude. Yeah. AJ Chowdhury: Yeah. We're doing prices, right? I remember a SpongeBob episode where he did sneeze and it took about two seconds. Dave Etler: All right. No, the sponge sneeze takes about a half hour to complete. Mm-hmm. So there you go. I think we all learned something new today with my little pop quiz. Sure. Take this knowledge back to your lives and, use it in a way that seems appropriate for you. , Jeff Goddard: this seems like an appropriate lit review. I'm gonna go do a new study now. There you go. Daniel Sands: Time to go,, get my scuba license and go screw some sponges. My work here is done., I remember seeing a study once where they gave sponges die, and they were just like filtering the.so it was coming out of their pores. That sounds fun. Nice. It was actually a very Jeff Goddard: cool picture. That sounds Dave Etler: fun. Well that's our show, AJ. Thanks for,, your help producing today's show. Appreciate it. Thanks for letting me help Jeff. Mallory, Daniel, thanks for, being on the show with us today. Yay. And what kind of dumb meison would I be if I didn't Thank you short quotes for making us part of your week. If you're new and you like what you heard today, follow the show. Rev, fine podcaster available. Spotify, apple Podcast, YouTube, Google Podcast, whatever you want., thank you to this week's editor, AJ Chowdry. The show is made possible by a generous donation by Carver College of Medicine, student government ongoing sport from the writing and humanities program. Our music is by Dr. Vox and atse. I'm Dave Etler saying Don't let the bastards get you down. Talk to you in one week.