 Let's thank you for thank you for coming. Good morning. So I'm not supposed to say so, but I am. This is a fun talk. Okay, and I can adjust it to whatever is appropriate for what you would like. So I have a number of slides and as I as I go through them, we may skip around to part of the talk for me is encouraging all of physicians to be clinician scientists because I think that we owe that to our patients. And I also think that science and medicine lend themselves very much. But anyway, how many here have do science? Yeah. Pardon? Yeah. Right. But are you currently? Yeah. Yeah. Okay. Are you working with? Are you? Have you? Okay. And Reese, I know that you've done clinical. Have you also done? That's right. That's right. I do know that. And so now that all of you have either done or are involved in science, does anyone feel like they never want to do science again? Has anyone had an experience like that? Good. That's great. So science as a clinician, I think it's important. Medicine naturally lends itself to scientific inquiry, right? When our patients are doing well, science provides a method to test ideas without experimenting on patients but can provide the best management. And there's a lot to do in science. It doesn't mean you have to be at the bench. It doesn't even mean you have to be in a clinical trial. I mean, there's scientific inquiry that can be done regarding qualitative type of assessment, how patients, how to best help a patient to have a better management strategy or finding out what the barriers and incentives are for patients who, you know, for example, where you know that something is valuable. An example would be diabetic retinopathy. We know that diabetes causes blindness and that if patients have yearly eye exams, and we detect diabetes diabetic retinopathy early, then we can prevent blindness in over 90% of patients, right? But the compliance with yearly eye exams is like 50% nationwide. So we, you know, what can we do? Why is that? That's an area of science. That's a way of doing scientific inquiry, too. So many people have reasons to go to science to make a difference, to provide better treatment or care, to be involved in the cutting edge. You know, what's the newest type of technology for patients or to evaluate disease. You can also be involved by being able to evaluate manuscripts critically. So I'm thinking in your careers as you get out, there may be periods of time where you really focus on clinical work. And that's fine. You can still be involved in science because you use, you bring to a manuscript that you're reviewing, that critical scientific technique, and then a need that is unmet. And it can be, you know, anywhere, including health literacy, for example. And those are sort of the altruistic reasons that we think about doing science as a clinician. But there's other, there are other reasons, collegiality. You know, one of my, you know, some of my favorite people, the people that I identify with are those on study sections when I go to review grants for NIH. I feel like I connect with other scientists and clinician scientists there. And we get together and we talk about science, but we also talk as friends. Increase knowledge in our discipline. We can also be involved in other non-medical disciplines through collaboration, biomedical engineering, for example. Curiosity to know more and understand more than what is known. And then travel. Every time that you're a visiting professor, you give a talk, but you get to travel. You get to see how another department runs. You get to see how their research laboratories are run. And that can be very rewarding as well. And so I think of those as the fun things being as scientists. I also think it's healthy because when you're, you know, think about it. You finish college. You're 20 years old. You graduated. All your friends who didn't go into medicine are having a great time, right? They've got lots of energy. They're going out. They're traveling. And you're in medical school, right? And a lot of, I don't know, I lost a lot of colleagues because I just was on call. I couldn't do the keep up with social schedule. But that's kind of healthy, maybe. Maybe you don't get involved in some of the activities that may not be as healthy for us in our 20s. And then when you keep yourself going and active intellectually as well as physically, I think it's also healthy in your 90s. And it leads to fulfillment. You know, if you're involved in something that you're really passionate about, that's a key thing, right? I think that's a key thing in wellness. You know, finding what you're passionate about and go for it, right? Have a purpose. Have a passion. And then work toward that. And I think that that leads to greater fulfillment than some of the, you know, maybe money or other things that are less so. So those are healthy reasons. How to start, you know, I don't know the, I change this all the time because I used to say just, you know, get involved in research, get involved with somebody that you want to, you think you might want to be like or at least learn about how their life is. It helps to have an area of interest, but you may not have that path, you may not know what you want to look at. You might know that you want to do science, but you're not really sure what the question is that really drives you. You all, we all have an advantage because we're MDs. And our patients give us a lot of good questions that we understand we need to address. You know, important ones. When they're, we might have a scientific interest that would be a basic interest. We can do that, but when a patient is actually has a disease where they're going blind and we don't have a good management for it, that sometimes is what spurs our passion. Be aware and observant, follow your gut. And passion would be what drives you. And as I said, it may not develop initially, you know, right away. So figure out your goals. And sometimes these evolve over time. You can have a lab. You have to get funding. But the good thing about getting your independent funding is you can ask the questions you want to ask. Once you have funding like that, you can do that. If you're involved in industry, that's fine. But usually you're answering questions that industry wants to answer. And it's a different, it's really a different, it's a different way. The questions are often business model, whereas in science, you're going to talk about hypothesis, which we'll talk about a little later. You can be involved in clinical research. You can simply be contributing patient samples. That's another way that you can be involved. You can develop a new technology. So a lot of ways that you can do this. Clinical research, there are masters of public health degrees, K23s are through NIH that can provide funding. Technology, SBIR, STTR through NIH, industry related. And basic or translational labs, there are independent funding sources through KOA. There are a number of different awards through NIH. And if anyone is interested or would like to talk, I'm happy to talk to individually as well. And the key is you want to develop, your passion allows you to continually learn. So what I like about science in my career is we all have patients where we start a management and we're worried about that patient. We have to give it time to see whether or not whatever management strategy we're doing is helping the problem. During that time, you have to be patient about it, but you're still thinking about that patient. If you're then have to be pulled away, bless you, to the lab, you're all of a sudden focused in the lab. That gives you time. You can let your patient. So in a way, even though you're really pulled in both directions, it allows you to, I think, be able to have a help. It's a better situation. You can actually give time for your patient to get better. It's the same when the lab doesn't work out, you've got your patients that or if you have an experiment running, you've got your patients that can keep you going and interested. So this is a guide to management that can be useful if you're interested in labs. I think this is probably, so for me, one of the most important things is it's important. If you find your passion, it's important to be impatient in that you're always trying to work toward that. For me, it was a laboratory. So I always was working on it. But you also have to be patient because you can't do everything at all at once. So you may be in your residency and you're struggling with how can I learn ophthalmology, which is so new, so different than medical school, right? It's like going to medical school again. How can I do this, learn all my skills, be responsible to my patients? How can I do science? Maybe you can't. Maybe the way you do science then is critically review papers, reading the literature. You're still keeping scientifically active. You're looking at things, maybe developing that passion you have that what you want to do. But you're focused on what you're doing right now, which is residency. You're learning to be a good doctor, and that's really important. So I don't think you have to feel like you're all over the place. I think it's fine to, if the opportunities are there and you need to spend more time doing clinical stuff, you can do that in it and pick up science at a later time. But it also helps it to have kind of like a five-year plan or independent development plan so that you, because time flies, you know, all of a sudden you wake up and you say, gosh, I never got to do that. And if it's something you really want to do, if you put that in your long-term plans and then look at what you've accomplished each year toward that goal, that can be very useful in seeing if you're keeping on the same track. You may change, but it also allows you to see what you have been accomplishing. Mentors, so you, mentors, you're going to develop throughout your life. It's, I found that it's rare that you have one mentor. It's usually that people have multiple mentors depending on what those mentors provide. And they can come and go and you may call on them again later on. I think trust is essential, confidentiality. You want those kinds of things when you're choosing a mentor. And I believe that if you are an MD, I think it's really helpful to have an MD. At least, you know, you may have PhDs as a mentor, but you should, I think, also have a mentor who practices medicine because there are some stresses that come, that you have as a physician that people who aren't in medicine don't quite understand, you know. And it's helpful to have somebody that can give you some tips on how you got, how to move through that. And then this concept of a board of trustees, these are, mentor itself has certain obligations with it. You have a contract. If you're a mentee, you actually come up with what you want to, what you want to develop over a year. You meet with a mentor or you come up with an arrangement to periodically meet, how you're going to meet and communicate and that. That may be more than what you want, but the board of trustees, these are people that you trust and that you may periodically just get together with to, like, you know, run something across, you know, with them and see how they would maybe problem-solve with you about an issue. Various types of research. It can be exploratory, which is hypothesis-generating. This can be clinical, basic science, population studies or mechanistic, which is hypothesis testing. Again, same areas. There is, I think, an important point that I want to bring up and I think it's important in ethics. So in medicine, we're trained to observe outcomes based on intervention, right? We give a patient a medication that has been, you know, tried and true at the approved. I'm talking about treating patients, right? Not research. And we follow that patient over time. In science, we really have a responsibility, not in clinical science, but in basic science. Not only to find out whether or not something is sufficient for an outcome, but whether or not it causes it. So we actually take it away and see whether or not we get back to the original baseline that we had. And that rigor is important and is evaluated in funding. But we wouldn't do that in patients, right? And then another thing about medicine, too, is we can't experiment on our patients, right? And the purpose of an IRB, we might think that this is the best thing for the patient. And part of the purpose of the IRB is that you get a non-biased, you get an objective group of people looking at what you're suggesting and actually giving advice and saying, whoa, this isn't safe or whatever. So remember that. Sometimes you'll see behaviors that suggest that it's okay that people make huge discoveries by experimenting on patients. But we always have to remember to be very ethical with our patients. And all science exploration is part of it. So even though we're going to talk about hypothesis, we always are exploring. We're always learning from science as well. So if I get, I want to make sure that we understand the difference between clinical care and science. And I know I'm going to be going back and forth with that a couple times. So if anything isn't clear, let me know. Clinical care, we don't experiment on patients. If we are doing clinical research, we have an IRB, we follow certain protocols. If we're doing science, that's different. And we have a certain rigor in the science and responsibility to actually test hypotheses as well as explore. So these are examples of exploratory research, qualitative study, assessing barriers. I just mentioned that. Adherence, compliance. Like, for example, we did a study to understand what some of the barriers were for patients with glaucoma in taking their eye drops. And one of the biggest barriers we found, or one of the biggest incentives, I should say, when patients were more compliant, was actually showing individual patients how to use eye drops. So that was more important than all the education that we did explaining the importance of glaucoma and, you know, the eye drops reduce the pressure and you can save visual field and some other examples. So mechanistic studies, clinical mechanistic studies are usually not really possible. I mean, because we, as I said, you can't give a patient something and then take it back. And you can get at a hypothesis, but you can't, like, if we give patients ARIDs formulation for macular degeneration and have outcomes, we can't really test what effect it has on the RPE. We can look at things and see associations, but we're not really testing the mechanism of what's going on. Whereas in basic research, we can. And I'm going to give you some examples here. So qualitative, quantitative, these in clinical research can be like focus groups or interviews, assessing patient adherence, interventional research, like in clinical trials. But in science, basic science, we're going to talk about hypothesis, generation and hypothesis testing. So first of all, what is a hypothesis? I have it up here, but does, I mean, since you've been in your PhD, how do you define a hypothesis? A lot of people have different definitions. That's right. Right, exactly. It can be very broad and it tends to be in biology, right? It tends to be in humans. So a hypothesis is not, we want, you know, we think mice exposed to oxygen will get retinopathy. It's something, for example, in a human being, in ROP and retinopathy. So a hypothesis, it's framed based on our observations or it can be past data, as you said, or past information. So poor post-natal growth causes aberrant developmental angiogenesis in ROP. That could be, you know, that could be a hypothesis. And angiogenic inhibition will change the natural course of diabetic eye disease. That could be a hypothesis. But it can be stated, I mean, it can be framed as a question to, does do angiogenic inhibitors change the natural course of diabetic eye disease? And that's in contrast to an aim. So an aim, this is more if you're thinking about or if you're writing grants. You have a hypothesis which is based in nature. And then your aim is really based on experimental design, right? So how you plan to test the hypothesis. And you might use an animal model, for example, in the first one with oxygen-induced retinopathy. And the animal model you already know reduces the weight in newborn animals. And you might test the effect of some agent or genetic manipulation to see whether or not you can increase the weight of the animal with that. That could be, and whether or not that affects aberrant angiogenesis. That could be an aim to test that hypothesis, the first one about aberrant angiogenesis. Or you find a protein involved in the body weight gain and you compare different groups using knockout or protein acts. That could be another, you know, more of a rigorous genetic approach to test the same hypothesis. Does that make sense? So a clinical aim might be looking at same things. Among premature infants assess the incidence of severe ROP in those born between 1,000 and 1,500 grams birth weight compared to 599 grams birth weight. So that would be, and what you're doing there is you're observing and you're comparing two different groups, right? So it doesn't test causality. So let's talk about that. I mean, what is, what's the difference between causality and association rates? Like, how would you? The fact that your low birth weight doesn't necessarily actually associate with low birth weight. So if there's low birth weight, you know, their gut isn't producing a certain protein. Right. And they may, they may also just have this association. Like I think of the eye disease case control study was a study done pre-arids. And it was, it was a cohort design where they did nutritional surveys on patients who had macular degeneration or not. And that was really sort of a landmark study that found that patients who had carotenoids or greens in their diets were less often to have severe AMD compared to those who didn't. And they, by, by this nutritional survey, they were actually able to get down what, what vegetables like collard greens and spinach and those were good things, right? But one of the vegetables that kind of fell out and was surprising to people was tomatoes. And, but, but tomatoes are also in pizza. So, you know, so it's an association study. It did not prove that taking that eating spinach reduces macular degeneration. It just said that people who had this kind of diet were less likely. And then the clinical trial, the age-related eye disease study, was a clinical trial to really test whether vitamins, supplementing many of the things that were in the vegetables, shown to be associated with less AMD, that, that they were effective in reducing the incidence. Okay, good. Experimental designs. These are just, these are some examples of what to do early on, address the hypothesis and aims. You know, what study do you want to do? It's really helpful to meet with a biostatistician early because they can actually help refine your hypothesis based on how many, you know, if you, if you go up to a biostatistician, you want to test a hypothesis and you find out you need like 10,000 patients to be able to get an outcome. Well, maybe you need to refine that, especially if you only have a year to enroll them. It's not, it's not feasible. But there may be other ways that you can still get at your question. So your question may be too broad. You know, you may need to focus in a little bit. And as you get more information, that helps your overall sort of hypothesis. Develop a collaborative team that is really, really important to, because more than ever, we are, if you take time to get a PhD and you're doing an MD as well, by the time you're done with your PhD and finish your MD, the science that you did as a PhD has evolved, right? And, but that's not, that's not a bad thing because you have in your pocket how to do science. So you just have to research, figure out where you are and, but some things you will not have enough time to become expert in. And so you have to build collaborators in there. You have to find other people that can help you out. If it's clinical, go for an IRB before you do anything. If you ever hear someone say, well, you know, we're just going to do a few patients. You know, it's a red flag. It's no judgment on anyone. But even if you're only going to do a few patients, you need to get IRB. If it involves animals, I mean, even if it's just, well, we're just going to inject a few animals with this new drug. It's very similar. You still need IACUC, an amendment. So always think about the regulatory because you want to be above board. You know, a lot of times it's, it's very quick. It's not that, that bigger thing, but that we just want to make sure that, that, you know, we're always doing things that are appropriate. And I find it helpful to write out my design. Sometimes I think, oh, this would be great. We can do this thing. And you know, we go here and we're going to test this question and we have this result. And until I write it out and realize that there's a, you know, that have you seen that T-shirt where it has all the mathematical writing? And then it has, then there was a miracle and it has outcome. I am one of those aha moments like, oh, I need to work on this miracle part. We need to be a little bit clearer on that. So here are some examples of some basic research type of hypothesis. So increase VEGF causes intravitrial neovascularization in ROP. So an aim might be to use an in vitro model to assess if VEGF triggers signaling through its receptor to cause proliferation. So you get, so you, to see if it's sufficient, you give VEGF to endothelial cells. You measure activation of the receptor and then proliferation of endothelial cells. So you find out that VEGF is associated with VEGF receptor 2 phosphorylation and endothelial cell proliferation. But then you would also see if it's necessary. And so one way you can inhibit either the receptor, you could use an SIRNA to VEGF receptor 2 or the ligand. And just see whether or not it takes away that effect on phosphorylation and also endothelial proliferation. Anyway, is this, there are only four of you. I can change and do whatever if this is not kind of going, do you have any specific questions that I can answer? And then in an animal model you could, you could test if VEGF is increased, for example, during oxygen induced retinopathy. And then you could inhibit VEGF and see whether or not you reduce angiogenesis. So those are some, some examples. Clinical, so clinical designs, you always want to, besides R or B, you also want to consider the ethics of the question. You need to get certified with certain, my screen changed. But you need to certify like with Citi and, I don't know if you've heard that. Sorry. I didn't, I touched it. Okay. Or a various ethics review. And it depends on what institution you're in or if you're in private practice there are, there can be information that you, you can find out about that. One is go on the ARBA website. There is a whole module on clinical, clinical studies and clinical management that has retrospective studies, case control studies, meaning with bio statistician, statistical questions, as well as clinical trials, FDA information. So you can, you can go on the website and, and it's under the educational, one of the educational panels. Are you guys ARBA members? Is anyone, you're an ARBA member? Sometimes that come, come and go depending on, you know, whether or not you're planning to go to the union. I think you can still access it even if you're not a member. But if you can't let me know and I'll send you a link. So we worked on that. That was one of the things I did for ARBA when I was working on the, I forgot what it was. It's some committee that I was working on. So I took care of the clinical studies part of it. So these are sort of very specific kind of information, randomized control, work with a bio statistician up front. Randomization in a clinical study is the, the attempt to equalize the different groups. So if they're, if you enroll patients that are randomized, then they tend to, you, you equalize out some of those confounders that you don't think about up front when you're doing the study. Okay. Let's go on to abstract. And I'm going to ask you to work together in groups to write an abstract also. So an abstract, the important thing whenever you're writing a paper in abstract is to read the journal or what the guidelines are for that abstract or journal up front. So you know what, what it is that they're, they want. Some will ask for structured abstracts where they have a purpose, methods, results, conclusions. Others ask for not having that. And then you just write, but you still want to put all that information in it. But it still comes out a little different based, the, the writing is different. So it's important, you know, have an idea is that 300 words is a 500 words. Is it 150 words? Like when you're writing an abstract for the academy, you have to keep within what is it 90 words, I think. So you have to be really, really concise and focus on what your message is and what's important in those situations. But it's an opportunity to highlight your work. And, and sometimes in an article, it's the only thing that somebody will read. So spending time on the abstract is really, really important. You want to be accurate. You don't want to overstate your conclusions. When you're, when you're submitting something to our vote, that's one of the, like red flags. If you say, say you do a study in cells and you're testing the effect of certain angiogenic substances on endothelial cells. And you find out that substance X causes angiogenesis and your inhibitor inhibits it. You don't want to say we're ready for clinical trial conclusion. We're going to do this in clinical trial. And sometimes you can say things like, you know, this may be important, you know, just being a little bit careful about that. Or this provides insight, you know, whatever the conclusion can be. So your, your purpose, this is how I like abstracts to be. Your purpose is not to write the background and introduction. You need, purpose should be no more in my estimation than three, three senses. And, and that's the way Arvo guidelines are. And they're like that because I helped write the abstract guidelines for Arvo too. So you provide just a brief background of the area and the gap in knowledge. ROP is a leading cause of childhood blindness, but little is known about the characteristics of the microbiome of babies who get severe ROP. That might be, you know, this has a purpose. A concise goal of the study and maybe the hypothesis and then type of research study to clarify. We, so to address, so our hypothesis was that, that bacteria of a certain strain was more associated with severe ROP. And to test this, we reviewed microbiome data. We did an observational study of microbiome data in premature babies, you know. So you know it's clinical, you know, that it's observational study. You gave a little information about why you're doing this study. The method should be clear and succinct descriptions of what you actually did. The experiments performed and should include any controls or comparisons, right, of the experiment group. You know, how you, you know, what was, what was your, what was your question? What was the study design? You know, you had babies that were under maybe 1,000 grams or under between 500 and 1,000 grams. You had babies over 1,000 grams or you had, maybe you started out by the microbiome. Babies that had this type of bacterial strain versus this, this type of bacterial strain and looked at the severity of ROP. Your results should have quantitative data with statistical information, standard deviation error, p-values if appropriate. This is where your biostatistician helps you. And then the conclusion should address the question of hypothesis. So, you know, it's, it's, if your hypothesis is we, we propose that certain microbiome strains was associated with severe ROP. Then you, you would say how your conclusions reflected that. If, if they did, and if, if you didn't find something, you can conclude something else. But you can say, you know, you know, more, more information is needed before this kind of assessment. Okay, so we're going to go through all this. So, independent development plans, there are a lot of different kinds. Here's an example of one, you know, and again, you can also just do five-year plans. But I think it's very important to have an idea of what your goals are. You can include on this personal, this is yours to keep, but it can be personal goals. It can be career goals. It can be, you know, social goals. I don't know, you know, a number of different things. And, and you can share them with your mentors or not. I mean, this is just for you to be able to develop that.