 Welcome to UWA's weekly seminar series of Science Exchange. We want to promote the relevance of UWA's research and its teaching activities to you all, and we've called it the Science Exchange because we want to hear your questions and comments as much as we're sharing our thoughts with you. I'm Karina Price, the Science Communications Officer for the ARC Centre of Excellence in Plant Energy Biology in UWA's School of Molecular Sciences. And as a science communicator, I'm very excited to be moderating today's session for the ARC Centre, Brady Johnston, all about the use of 3D visualisation and animation to communicate science. Brady is a final year PhD student working in structural biology in the School of Molecular Sciences. Here, his research is focusing on the structural and the biophysical characterisation of human-designed RNA binding proteins. Now, through my own personal acquaintance with Brady, I know him to be an incredibly proactive student who has taken real initiative to learn new skills to enhance his work. Brady has spent a lot of time recently upskilling in the how-to of creating innovative and effective scientific visualisations. And some of these have gone on to garner tens of thousands of engagements across social media, and they've actually featured in scientific magazines, including SciTech's Particle Publication and NOVA from the PBS Digital Studios. So, Brady is obviously here to tell you more. He's included, I know, his social media and other contact details on his first slide and I think again at the end. So he encourages you to follow along with his work and also reach out and get in touch. Over to you, Brady. All right, thanks so much, Karina. And thank you, everyone, for coming. It's nice to see so many people have showed up. I'm going to be touching on a few things today, but we're going to start with, basically, how do we observe the nanoscale and what I sort of mean by that term in the beginning? How do we show what we see once we're sort of looking at these very, very small scales? We're going to put it in some contexts. So in this particular one with COVID-19 and the coronavirus that's currently going around. But also then we're going to talk a bit about sort of new visualization technologies, some of the work that I'm doing and I've played around with, and sort of the potential that it has for science communication more broader. I've chatted with a whole bunch of people about this sort of idea, but if you sort of think about how maybe astronomy and biology might exist in the public consciousness, astronomy, you know, you only need to go outside and look up at the stars and you can sort of get that sense of awe at the galaxy and all this sort of stuff that's going on. And so as a science and as sort of in the public consciousness, it's very easy to engage and it's very easy to promote various sort of scientific concepts and you can sort of see that with going to the moon and all this sort of stuff. But, you know, you basically need a microscope to start appreciating the biological world. To do anything else, you really only interact with the biological world through disease and that sort of thing. But when stuff is happening on the cellular level, you really need to start thinking through a microscope or even at things that you can't actually see. Technology is obviously bringing this a lot closer and I'm going to go through a little bit of that. Now, what do I mean by what we can see? Now, if you're, you know, a colleague of mine and working in the structural biology, you'll know that things are very, very small. But for everyone else, basically, visible light, we're limited by what we can see and what we see ourselves is size-wise from 300 to 700 nanometers. This isn't going to be a lecture on physics. This is just very early primer. But what if things are smaller than that? So, inside a cell, atoms themselves, all this sort of thing, what happens when they're smaller than visible light that we can actually see? So, if we sort of look at this simple diagram on the right here, say we have these two purple atoms. Now, they're smaller than their light around them. If they end up coming too close together, if we're using light that is too big, they basically, we can't tell them apart. They're essentially looking like the same thing. And so, you start coming up against physical limits of physics. Well, you can basically get around this by using smaller waves, which is one strategy. And so, one strategy that my lab and a lot of people in the world use is X-rays. They are a lot smaller. You know, we use them for bone imaging and all that sort of stuff. But this is a slightly different use of it. Again, I'm not going to go into super dense physics of it. And this isn't going to be a scientific lecture, but again, it's just a primer. So, how might we use this information while we can use it through a facility that in Australia is called the Australian synchrotron, which is basically a city block-sized X-ray generator. There's a few other techniques, like electron microscopy, NMR, and AFM. But basically what I want to get across is that you get robust biological data on the 3D positions of atoms. Now, what does that data look like? It looks something like this. All this sort of gray is basically where electrons are and so where by inference atoms are. Again, I'm not going to sort of take you through the minutiae of what's here, but just know that we have this sort of robust data. But how do we go about actually presenting it and communicating it is the important part. I've got four representations here of what people in the structural biology community would be very familiar with. But if you're not, then it might be a bit new. So, the quote-unquote more accurate representation would be this one here on the top left. Each sphere is basically an atom. And so, you know, from all of these experiments with X-rays and with electrons, all that sort of thing, you know where these atoms are. But this doesn't really tell you a lot about what's going on. And visually, it's very busy. It's hard to sort of see what's going on. It's not a very useful representation. And so, in structural biology, we have a couple of other representations, like the one on the top right. One you may see a whole lot in the news and in various scientific textbooks is this cartoon representation on the bottom left. And to me as a structural biologist, this is very useful. I know exactly what's going on. But it's sort of in the broader context. It's not that useful of a representation. And so, one we use quite a lot is the surface. And so, it's basically, we know there's all these atoms here. But what's more important is the overall sort of surface of this clump of atoms that makes up this molecule. You know, we have all this data in structural biology and we have this jargon, which I've probably used unknowingly a little bit myself in this talk, how we communicate as colleagues. And so, it's very efficient. It says sort of exactly what we're meaning it to say. But it's not that useful when you're trying to talk with even people who aren't in your field. So, if you've ever gone to a talk where someone's dives a bit too much into the jargon, you know, you glaze over, it's, you're lost. I'm not going to go through all these terms, but it's just sort of an example of, you know, some of the things that are common in structural biology. And so, while these things are useful, they're not super useful when you're trying to talk to people who aren't in your field or even the general public. So, what you really need is a common language. And so, you know, what sort of common language can you try and use to communicate, you know, atomistic sort of very complicated scientific ideas while remaining accurate to the general public or, you know, to a wider audience. There's actually quite a robust language already out there that essentially everyone shares, and that's like visual language. So, movies, cinema, TV, let's take this still from a fantastic movie, Fantastic Mr. Fox. Even if you haven't seen the movie before, visuals, you know, the color, the composition arrangement in the shot, low angle textures on the clothing, all this sort of thing. If you've never seen the movie before, you're already getting this sort of story that's being told to a single frame. And so, the bandwidth of information that can be communicated very, very quickly through effective graphics and through effective design is quite robust. And so, how can we try and sort of take these concepts and use it in, you know, the molecular sphere or like what I'm going to go through in the context of, say, coronavirus? The coronavirus, I'm sure we've all come across it a whole bunch, and you've probably seen this image here a lot in the news, in news reports, newspapers, all that sort of thing. The artist is a scientific illustrator, Alyssa Eckhart, who actually created this. And so, she's part of a whole team in the CDC. But they have a very specific job, especially when it comes to something like this in terms of public health. How do you communicate the severity of a virus like this? Or even that it is, like, when this virus is too small to see, it's hard for people to conceptualize if they haven't studied it or studied science extensively. And so, you know, some of the things that they really wanted to enforce to this image is that it's something you could actually touch and it's helped sort of display the gravity of the situation. And so, you can look at some of the visual language that's being used here. And so, the colors, the depth of field, the texture, you know, the reds are sort of sinister and imposing the grays and the oranges. There's depth of field, there's some texture. So, even if you don't know a huge amount about virology or by a chemistry or structural biology, even though it's too small to see, you get this sort of idea that maybe it's something that you can interact with and that you should take seriously. Well, how did they go about building this? So, it's filled behind this image was it's full of very robust structural information. And so, there's electron microscopy, like you can see here on the right. These are viral particles of the coronavirus. You can sort of see the spikes that are on the outside and there's sort of basic sphere that's there. And it's, we use structural data from exocrystallography, like I've sort of talked about, another sort of data from similar viruses and you can bring that all together. But you need to sort of think, like I've sort of said, what you want to communicate ultimately in your image. And so, this is the sort of process that they've gone through. They have your structural information. But again, showing something like this in an image to the general public isn't really useful. It's too busy. It doesn't really communicate anything if you don't know what's going on. And so, they take surface view, clean it up a bit to make it a bit simpler, not so busy. And that's sort of the resultant of the spike protein that you see in the coronavirus. And so, this is ultimately what it has come to look like sort of thought process that they've gone into behind making it. And you can take sort of different approaches. So, if you don't want to just make a sort of sinister imposing approach, there's a really great artist and structural biologist, David Goodsell, who does these fantastic cellular paintings. On the right, it's quite clean. There's only the coronavirus and the sort of colour choices are communicating a lot. But on the left, you know, it's much more colourful. It draws you in. It's very, very busy to sort of show how busy it is inside the cell. But you're sort of seeing the same sort of structural information. So, you know, we have, we know what these spikes look like, but there's a slightly simplified version to sort of communicate what it looks like on the inside. Now, I don't want to like make fun of these images on the left here, but it just sort of shows maybe like a simplified version of it is, you know, they're getting the spikes right, the sphere right. But if you want to be sort of more scientifically accurate, you need to be taking an approach that's more like this. And that sort of takes me into some of the my own work that I've done. So when this started out, I saw, you know, all these images of the coronavirus and the news and all the structural biology information is readily available out there for free. And so I started, you know, chatting to people in labs who are researching this kind of thing and getting information from the PDB. And I tried to put together my own illustration of, you know, what it sort of looked like. And something that was really getting to me was all of the images of the coronavirus was this perfect sphere. And it was still, it sat there and it was a perfect sphere. And, you know, from everything we know, it's probably not the case. So let's take this electron micrograph of the coronavirus, for example, none of these are perfect spheres. They're all slightly deformed in one way or another. It's likely also that they would be dynamic. So they would be moving and sort of deforming as they're in a busy cellular environment. And so something I wanted to try and communicate in my own image is the sort of dynamics that's going on. It should hopefully be sort of twirling around and sort of breathing a little bit and sort of going in and out. You sort of get the idea maybe that it's not a static thing. It's more of a sphere that's sort of blobbing in and out. And that's sort of something that I wanted to try and communicate. Now I don't have like a busy cellular environment because I wanted to focus to be just on sort of dynamics. If you do another place, you can watch this video is at this website. So this was actually picked up by a couple of different news organizations. And so Particle, who's a news magazine put out by SciTech and Perth, they thought it, you know, it quite encapsulated that idea that it is this sort of dynamic thing that's going on. So I had a lot of positive reactions to this, which was very, very encouraging. Now go on to sort of how I got started into this journey and maybe how you might want to get started on to this journey as well. And I came about it basically because I wanted to communicate my science a bit better. So this is a perfectly acceptable diagram that I made for a talk at one point during my PhD. This is some of my research. I won't go into it in too much detail. But, you know, I've got my protein here and microscope, all this sort of stuff. And it's, you know, it does its job, but basically during a poster session, I wanted people to be able to approach or get sucked in and sort of be visually appealed to by the poster so that they might come and chat to me. I thought my science was really cool. I wanted to communicate that. And so what I came up with was after playing around a whole bunch of something a bit more like this. And so you can see there's difference in color intensities between the two. So that's something I wanted to communicate. And you can see that without me even saying it to you. Difference in size, position, all that sort of stuff. And so this is sort of how I started out along this sort of journey. It was basically playing around with wanting to communicate my own science better. And so I actually presented this at a scientific conference in February. I thankfully got a poster prize, which is very exciting, but it was a very, very effective. A lot of people really enjoyed it. It made that a lot more people came along and chatted to me about my science than would probably have otherwise. Some other things I sort of did is I recreated my lab in 3D to make some sort of cool little images. This was just a bit of fun, a bit of practice for working in 3D where the lot of interest has been drawn recently is making face filters. So if you've, you know, got young kids or if you use Instagram or Facebook at all, you've probably seen face filters. And so I was going to sleep one night, you know, I was falling asleep and I had the brainwave. It's like, well, what if I could wear GFP like a hat? And so, you know, a lot of people were very into the idea that, you know, if you are unfamiliar with GFP, this is what makes things glow. So if you've ever seen like a glowing bacteria or glowing fungi or something like that, it's going to be one of these proteins. And so I thought, you know, what if I could make it like a hat? And this was my first sort of example of playing around with it. Working from that, I was like, okay, what if I could make a giant thing that you could walk through or something. So in my own building, the Bayless Building, I made this sort of DNA model that is, you know, completely in the phone, but you can now in the FOIA walk, you know, around the sort of giant DNA molecule, you can look inside it. Now I've sort of figured out how it all goes and you can sort of throw any sort of model in there. So any sort of chemical structure or DNA or protein, it's relatively straightforward to make these sort of things. You can do interactive posters like this one that I did in our building to sort of adding a bit of updates to it. But more recently, and what's generated a lot of engagement actually, is this one with ATP synthase. And so it's got to be, you know, most people's favorite enzyme. But it's this very cool sort of engine looking enzyme. And I sort of had this idea again, what if I could make a face filter out of it. And so people were very, very excited to see this. This one actually released that other people could use it. And very surprisingly to me, it took off quite a lot. So I've almost got a hundred thousand or so engagements on it. Tens of thousands of photos have been taken with it. So this, you know, this is just me playing around with this face filter in particular. But it's a lot of potential basically for science communication in general. So for running a class or for, you know, public engagement for an open day or something, this sort of AR experiences hold a lot of potential. And people really seem to enjoy them. So what if you want to have a go at it yourself. I've spent a fair bit of time sort of learning all this sort of stuff. But, you know, the tools are out there. Everything I've shown has been completely free. So most of it's using Blender, Spark AR, Chimera. So there's a whole list of things there. If you're at all, it's sort of interested or sparked your interest. Join CyArt Twitter. So there's a lot of really fantastic artists and scientific illustrators on Twitter. One group that I really wanted to highlight who do fantastic stuff is Smart Biology. So they're making completely animated biochemistry textbooks basically. So they're taking what would have been, you know, maybe some sort of dull illustrations in a textbook into these completely sort of visualized animations. And so they're doing some really cool stuff. If you are super interested in it, I have actually started sharing some of the things that I've learned along the way in my own sort of YouTube channel. I've had a lot of very positive responses because as biochemists sort of coming into this 3D world, it's very, very hard to get started. There's not a lot of things that are built for you. And so I've sort of tried to... I've gone through it the hard way. I'm trying to share some of that knowledge. I've sort of covered a few different things, but I want to sort of wrap things up with these sort of visualizations that you see around the place. Most of the time there's some really robust science that underlies them. But in making them, it's often important to sort of think about how you want to try and communicate it. So the sort of medium animation, this, that, and the other, and what you want to try and communicate. So in this data, there's so much information that it's ridiculous to try and communicate all of it at once. Because even for people who are in the know, it's going to be too much. It's going to wash over them. It's simply going to be ridiculous. But even if you're trying to communicate it to a broader audience, it's super important to find a couple of things that you really want to hit on. So dynamics or size or shape or for public health things that, you know, a picture is worth a thousand words. And so good visuals can really rapidly communicate some really important ideas for your own research or for public health or for general sort of education. And there's also, you know, I've covered a few things that there's a lot of potential in some of the technology. You know, I'm not a 3D artist. I'm just a PhD student who's played around in mostly my free time trying to learn some of this stuff. And so where this sort of technology is going to take us is actually really, really exciting for science communication in general, but also, you know, among peers and with the general public. So, yeah, thank you so much. I'll probably wrap that up now. And I'll take some questions, hopefully. Oh, very awesome, Brady. That's so cool. All right, people, I encourage you to pop any questions that you have for Brady into the Q&A. I can see a few popping up. But while people flip those through, I might just start with my own question. Where did you start with this? You've mentioned a few programs and things that you think people would maybe consider using for this, but for you personally, where did you begin? So personally, it was for, for me, was with Blender. So Blender is a great tool. It's free and open source. There's a lot, like, hundreds and thousands of tutorials on YouTube and the community is really, really nice. It started with some tutorial from, you know, five years ago how to take a protein structure into Blender. Things hadn't been updated in a while. And so it's basically started with that and started tinkering with that. But this is, this software Blender is used for, you know, movie production, TV production. It's like, it's legit stuff. And, but it's completely free, completely open source and a really welcoming community as well. Cool. We have a question here that's perhaps somewhat related. Someone who says, hi Brady, I've been following your work for some time now and it's really great. I wanted to ask you which platform you would recommend for beginners in SIR? I'm going to take that as platform being like a program, maybe, in which case it depends on the field, I suppose that you're working in. So if you're, you know, working in something like structural biology, then Chimera is really great. That does some really, really cool rendering. And then like I sort of said, Blender is a great way to sort of start into it and not to toot my own horn. But, you know, my tutorial series is for exactly that. If you're maybe in sort of a slightly different scientific discipline, then software wise, again, there's lots of free stuff out there. So Blender or Inkscape or there's a few other ones. I can't think them off the top of my head. But just sort of have a look around. Basically a good place to start is looking through the hashtag for SIR on Twitter and looking at different accounts, what they're doing, what programs they're using and sort of taking inspiration from them. And it's a really welcoming community. So asking questions on Twitter is a really great way to get started. I was going to say, I imagine things like Blender and that would have a fair community operating around them. Yeah, they do. Yeah, and they're very, very welcoming. So the great thing about open source software is it's always like such great communities behind it. And so, you know, if you have a question, people are always happy to help. And there's so many tutorials out there. Cool. All right. Now the question here. While discussing the coronavirus spike, you mentioned that they simplified the surface of the spike protein. How do you make the choice of what parts to simplify? Is it based on some specific threshold or personal bias by the maker? Usually, again, it sort of comes down to sort of how and what you're trying to communicate. So say in the instance of the coronavirus. So if we, let me just get my laser pointer back out. So if we look down here at the sort of bottom right, an important thing about the spike is that it's a trimer. So there's three separate proteins that come together to make sort of a spike overall. And so something that most illustrations have is they show them as three separate things. And so you can see, at least in this, that it sort of looks like maybe there's three things that have come together. So you probably don't want to simplify it any more than that. But again, it's down to what sort of audience you're targeting it to. And so, you know, the general public, you know, you have to be able to take into account the atomistic detail as to where all the hydrogens and stuff are. But if you're, you know, making a talk for other structural biologists, you probably include more detail. So it's ultimately at the discretion of the artists. But you also want to take into account and think about what you want to communicate and for what audience you want to communicate it to. Cool. Another question. Are all of the tools only for people who can code Python or other computer languages, do you think there's... Look, excellent question. So none of the tools that I use require any sort of coding. So Blender and so Chimera and all that sort of stuff all have graphical user interfaces. So they don't require coding. If you do have coding knowledge, you can also get a lot more out of them. And it's a great way to actually get started is to start with one of these programs and be like, oh, I just wish I could make this repetitive task easier. But yeah, they don't require coding to begin with, definitely. Yeah. All right. Another one. And I like this one. How heavy the computational power do you need to render a movie of the virus? So for my... In my particular case, the virus... So that was 10 seconds. And it took me 12 hours to render on my computer. And I have a fair... People in the know a GTX 1070. It's a fairly beefy graphics card from a few years ago. Again, it's sort of up to you. Blender has a great option for rendering things a lot quicker. They don't quite look sort of as photorealistic. But again, none of this is photorealistic to begin with. So trying to get nice lighting and stuff is ultimately up to the discretion of the viewer. So I don't have like a super beefy computer. And you could render it on your laptop in a few hours to a day or so. But there's also options out there for very cheap or free rendering farms where your maker animation, you upload it, pay $5. And in a day's time, it sends it back to you all rendered. I've actually just noted that that question was actually from your boss. And I've also just noted that the names of the people asking these questions are actually there. So I apologize for not giving the names of the last few questioners. But Alex is asking... Well, firstly, saying that that was really cool and asking how long did it take you to get this good? Probably quite a while, I suppose. So everything I learnt basically, I learnt from YouTube tutorials. So the good thing being they're all free. But it was probably maybe like a few weeks before I could really start doing anything in Blender. And it was months before, and I make one animation and I revisit it or one image and I revisit it a few weeks later or a few months later. And so I've been doing this fairly intensely for maybe like a year, a year and a half now. But one thing that has been good to see, again, not to toot my own horn too much, but my YouTube tutorials, people have been sending me images through that. And so because I've been targeting it at scientists, when I started, everything was like normals and vertices and this and that. It was catered for scientists. It was catered for 3D artists. And so I've seen some really great results really quickly from people doing that. And so, you know, I've seen some people on Twitter just over the past few months go from no knowledge at all to making some really cool animations to show off some of the research they're doing. Cool. Crystal is asking, are there any particular fields that you think are in need of more visualization like this or a visualization project that you're personally interested in pursuing next? Good question. I mean, all of, I think, molecular biology desperately needs more of this. If you've ever been to like a molecular biology talk, there's so many things where, you know, there's cool figures and good data, but it would just be summed up nicely in a cool visualization, especially if you're trying to talk to other people about it. But I suppose maybe like, I don't know about a specific field. Like, I, yeah, I'm not sure about that. Like, the structural biology has a lot of potential because you have all this data already. But I think a lot of maybe like cellular processes, you know, DNA replication and, you know, chromosomes dividing all that sort of stuff has a lot of potential where you can sort of finally see all of this information that we know we have and you build a mental picture of in your mind. And you can finally see it animated and that sort of, you have that dawning and moment where you're like, oh, this is how it all happens. Okay. This is a real forward-thinking question from Pata. Great job, Brady. How do you imagine taking the next step with the augmented reality? Can you animate some of these things in response to what the viewer is doing? Yeah. Great question. You can. So the, all of the tech that I've been using can respond to like basic inputs. So say like for Facebook and Instagram, if the user like opens their mouth, like, ah, or, you know, closes their eyes or something, you can sort of get responses from that. Some of the tech that is coming out where you can like reach out your hand and your phone will sort of know where it is in 3D space and like press a button is coming about. And there's also, I know, Apple's AR kit, you can have up to around 20 people all looking at the same thing. So even though you all have your own little tablet, you're all looking at exactly the same model and they're communicating between each other. So you can, you know, have a teacher in a room, walk around this animated or massive 3D model and point things out and the students in the room could then see exactly what they're sort of interacting with. That's definitely, I think, where it's going and where it has a lot of potential is sort of that interactivity. It's still, you know, beginning. The tech is starting to get there, but there's very few, I suppose, people who know how to implement it well. I mean, I certainly don't know how to implement it well. I'm just tinkering. But the need for like having artists and stuff who are scientifically minded but also are able to sort of instigate this sort of technology I think is really important. Very cool. That in some way probably leads into this next question from Claudia. Do you think that kids could use this program for science classes and what do you think it will take to get, in your opinion, to get this sort of stuff into schools? Or like for... Again, I'm not sure by program whether you mean something like Blender or to sort of 3D AR stuff in general. Yes, I mean, it's definitely necessary because I think it's really, really effective sort of science communication tech. To go to a prepared slide for something like this, I actually want to highlight some of the work that Karina is doing, so our lovely host. So this is out of our building as well for people who aren't from UWA. This is the virtual plant cell. So it's like a VR version of the inside of a plant cell. And so this, you know, is being deployed in various classrooms for trialing it. And the results we're seeing are really, really cool. I'll go over it quickly, but it's like, say you have like, this is actual results so they'll get kids to like make a sort of play-doh version of what they think a cell looks like after a lesson. But then after like a lesson with the AR, you can like, this is what kids make. They start making like a 3D version of the cell. And so sort of that idea where once you can, eventually you'll get that idea in your head that things are 3D or things are not just this sort of flat image that you see in a textbook, but when you can actually experience that through AR or VR, it's a lot quicker to sort of communicate that idea. So I mean, it's definitely starting to be rolled out, but it's also very, very early days because VR tech is very expensive. It takes, it requires a lot of skill to make that sort of content both scientifically and with computers. So it's definitely still in its infancy, but it's definitely beginning. Thanks for the plug. The virtual plants are going on behind me. I have a great question here from Ipsa. How did you choose the parameters you chose for adding breadth to your virus, temperature, molecular motion, fluidity? Were they based on some evidence? So for me, basically no. So there weren't any sort of simulations like molecular dynamic simulations that I could find on the coronavirus. It basically took it based off of the cryoEM data where you could see the level of deformation that we were seeing in the virion. That's sort of what I took as a guide as to how much I should deform it one way or the other. In terms of actual like how quickly that happens, that's completely, you know, I just winged it because the time scale is basically meaningless anyway. It's probably happening very, very quick on the molecular scale, but I have absolutely no information on that. So in terms of time scale, I don't know, but the amount was based solely off sort of what we see on the electron micrographs, but not on any simulated data. No. Cool. We have an abundance of questions here. We're not going to get through them all. So I'm going to throw you one last one, but I just want to emphasise that anyone who does have questions, I guess feel free to reach out to Brady after. Please do. On Twitter, email, please reach out. There were a few more technical questions in here. I've chosen not to read them out because I think they might require a slightly more detailed... Okay, yeah. Technical, please reach out. I'm happy with tech questions. Love it. Okay. One here from Phillipa, a fellow structural biologist though. Do you think the future of papers will be more videos instead of static figures to display our results more easily and realistically? I mean, I'd like to think yes. It's already in a talk. Now that we can have animations quite easily in a talk or a video, it's already far more effective. Everyone who can is trying to make videos. So during a talk, you can play the video. So what's better than that? If you can explore that structure in 3D in your own time, then yes. There's some... I've seen a couple of attempts to make apps where you can publish a paper and then you can look at the paper with your app and you can sort of see a 3D model of whatever the data they're trying to show. And so I think definitely it's the future. Again, the skill set that is required to do that sort of stuff is still quite low because there aren't a huge amount of people who are structural biologists or biologists who have this sort of 3D knowledge. But it's definitely, I think, where it's going. Because if you can see a paper and be like, okay, cool, I can see that structure, but I want to see what it really looks like. And then you can wrap it up in your computer or if you were to use it on your phone, I think it would be very, very cool. And I think it's definitely the way things will go. Awesome. All right, we're going to wrap up, but Brady, that was incredible. I'm sure the audience is all sitting out there agreeing with me that that was not only super interesting but also a lot of fun and puts a really exciting, cool angle on science and science communication and ways of connecting what I think we do and a university setting out into the world and connecting with audiences. So thank you very much. Thank you all for spending your time with us and goodbye. Thank you, bye.