 So, the project that I've been working with Dr. Young and Dr. Ganey has been to understand the role of macrophages and monocytes in nanoparticle interactions for tumor immunotherapy. And that's really important because I work in the field of immunogenering where we're trying to develop biomaterials that can actually modulate immune cell function. And this immune cell function is very important for how tumors grow, or grow shrink in our case. We want to actually develop nanoparticles that can shrink tumors. And so when I first thought about this idea, I thought about making a qualitative review, which is what I typically see, where we're then going through the literature and reading papers and then kind of summarizing what we've seen in the field. And I think those absolutely still have a place and what I'm trying to do is not to displace that in any regard because I think the qualitative perspective kind of reinforced literature is very important. However, I also began to notice as a student even that it's hard to read all of the papers in the field. And it's easy to kind of miss a new paper that's emerged or that may not come from a big lab or that may not have the right words on them. And so it's really hard to do that in a way that you just start kind of not paying attention after the first 200 papers, to be honest. And on the other hand, what was also interesting is that the field of nanoparticle delivery is very proliferative. There's so many different types of particles and it makes it so amazing where you can make. And so I wanted to do this type of systematic process to kind of approach both needs to actually be able to survey the entire literature to really get a sense of what the entire field looks like from like a big point of view for the purposes of making sure that I captured everything, which is very hard to do with how much literature comes out. And also to be able to try to develop trends amongst the different ways you can characterize particles and actually load them with different drugs and how they actually benefit different tumor types. And just this real genuine idea of how do we kind of do science in the world where there is just so many papers coming out daily and how do we keep up with that, how do we synthesize information at a pace that's on par with our publication and certainly how do we synthesize that information for any future translational capability. And I think that need is only going to come stronger. So it kind of feels great honestly to be doing some of the work that might be pioneering this kind of idea of thinking, at least in like a more traditional science where again this is the idea of systematically reviewing or mapping is more of something you've seen in the health sciences. And so how do we think about this for our engineering fields? I think doctors, Ganey and Yango remember where we kind of went from saying this is a systematic review to like, no, we're really mapping what's happening here. And so I think that things have evolved as we kind of realized like the complexity of the question we were actually answering that was based on getting to that first some of that first bits of data and thinking about what the real utility was and how to actually maximize utility of the platform. And so I think they helped in expanding how I thought about literature searches, the tools that we can use, and that was certainly really helpful for my students. They searched her papers and they can find papers way better than I ever can. Like I think I'm just going to ask them, can you just tell me if it's even out there? And I know for a fact now that I believe them a little bit more than I would have before that that paper doesn't or does not exist. Did they tell me there are six papers out here that has this? I'm like, that's pretty precise, but I know that they know how to do it. And then ideas of deduplification, deduplification. So how do you then say we've got 13,000 papers? How do we then search through those? How do we organize those files? How do we put them into databases? How do we search by title abstract or author or year publication date? So these were all things that librarians helped do that. I didn't actually realize we're going to be needed in the project and did not predict because, again, not my field, but having someone or people on the team who knew how to do that made it easier for me to focus on the scientific question. I think that's probably the final thing I'll say here is that I got to focus on the what are macrophages? How do I explain to you what macrophages are or what kind of nanoparticles are? Because I knew that I didn't have to worry as much about or I could. I had another part of the team that could help with the the management of data, the accumulation and kind of making sure that we had a thorough listing. Of every single paper that would ever fit here. Yeah, is that great? Yes, I really saw this as an opportunity to opportunity to engage students to kind of get them interested in research and have a community. And so after, you know, a whole summer of looking at thousands of papers in some students cases, we found that students were reporting that they felt more comfortable or confident reading papers. And in particular, scientific papers that they actually really understood how to search or use algorithms or is algorithmic appropriate word, but to be able to search through databases and find papers with an accuracy they hadn't felt before. So they felt more comfortable with those types of things. And to me, that also felt like a real value of this, which is that they were able to learn some skills that are now applicable to them, because one of the biggest challenges I would argue, especially for an undergraduate audience is like, how do you get them to feel comfortable reading scientific literature? How do you prepare them for graduate school? And that's certainly a tool they can use as they start, how they start identifying problems. And for the grad students, this is definitely true where they like are searching and they're using this now when I ask them to look for certain papers. And so what I do is I tell them, this is a really great activity for their first year grad students who are trying to learn the field that they can actually map out their whole niche area. And this is a great way to kind of add a little bit of quantitative data to their qualitative research or their qualitative review, especially now as more people are writing reviews. I tell them that this will help strengthen their search skills. A huge challenge that people face in terms of knowledge integration is trying to figure out what's important because there's so much information that it that and you don't know because you're kind of a novice, like the idea of finding information might be a little bit, yeah, everyone has Google, we all have PubMed. But how do you figure the trend? How do you figure what's more meaningful than others? And the thought process that it takes to define a question actually makes them do that. And it makes you figure out like, oh, we're the opportunities and we're like, oh, that's been done way too much. And like, let's try to like find a space where you belong. So there's a lot of thought processes that help train students. It's a bit independent in a way, so they can also do that without too much insight. And I think that as I continue this work and as I continue this work of Dr. Young and Dr. Ganey, that's one of the things we like to look into, which is to actually explicitly ask the questions of how did learning and confidence change and how do students who do this kind of program, let's say, of like learning how to actually search through databases, make criteria and try to apply them to problems. How do they then apply them later on?