 with the sharp punctuality we can possibly start. And I'm going to talk about the making of a movie, which is of a short animation to be included in a film, which is titled The Dark Gene. But let's go one step at a time. OK, so this is something. So it all started just over one year ago in July 2013 when I received an email full of very flattering words and interest, signed by two directors working for a movie in the German production company and asking if we were interested in a possible collaboration for the movie. So of course, when you receive an email like that, what do you do? Are we sure? Is this not a joke? Do they really exist? And they do. So that looks better. But they talked about the plot they would send with a mail and there was no plot there. So, well, let's just answer and see what happens. Now, of course, what you really think is something that you keep for yourself. And very professionally, you answer and say, we are most probably very interested. I don't know how I came up with such a sentence. I just found it out in my computer and I said, OK, I'll just show the way it went. And so we started with the negotiations. So the request they had was a few minutes, well, a few small parts of animations of a variable length of time between 20 seconds and two or three minutes for a total of six to 10 minutes. And they wanted to show things starting from the genes and going through protein, through the brain system, the receptors in the neurons, and all sorts of very interesting scientific issues. The idea was that the film should be released in the spring 2014. They are delayed but not for our fault. And they are German. So what we said is, OK, let's say five to eight minutes. What we need is at the very, very least, about 60,000 euros. That's still a very reasonable price, we think. And talking about this, just a small parenthesis, maybe in the Blender Network there might be a discussion about how to price things for private companies that ask for productions from people using Blender. However, that was our request. What the directors told was that the budget available for these animations was 15,000 euros. Now, 15,000 euros for five to eight minutes is really not much. I was informed, now not that I want to make comparison, of course, but the word was that for the making of the movie Avatar, the price was about two and a half million dollars per minute. Two and a half million per minute. So they wanted with 15,000 euros a few minutes of a scientific animation, not just an animation that anyone can draw, but something that was really scientifically correct. So we started negotiating, of course. And so, OK, I'll skip the slide. But finally, we agreed for about 20,000 euros. And the producer, which is this is also something interesting. So all the interesting talk you do with the directors and they say what you want and the compliments and everything. And then you talk with the commercial people, the producers. And they are extremely tough. And I wish I had a commercial someone that could do the negotiation on my side, but we didn't have it. So we had to do everything by ourselves. And finally, one of the requests they sent was this last sentence. Regarding the right situation, we want to be clear. So that was like, make sure we want to be clear. We claim all rights worldwide for unlimited period of time. Now this, of course, something we had to do to negotiate. So we asked, we said that, look, we are going to give you this movie for a very, very small amount of money. We are basically using research money, which is money from the public, to do this work for you. This, what we want in exchange, is that at the very list, you provide these animations. You leave them with us to distribute at our choice. So that's the way we finally. So the final agreement. And it was that we would make five minutes total with three scenes for a total of 20,000. We managed to get a little bit more. The deadline was very, very short. It was to be the 31st of January. And the agreement happened in November. So it was like three months of work. And we would leave the rights in connection with the movie to them until the release of the movie, which in theory should have been before December 24. But after that, that would become available for us. So we started, and we prepared a storyboard. We called it a storyboard. Now please don't be offended. So that's what we were going to show. So we have serotonin, which is a molecule that is very heavily involved in the mood regulation. And it's actually the molecule which is responsible for what goes wrong, or at least this is a view, when people become depressed. So the story of the dark gene is the story of a medical doctor which is afflicted by depression. And he thinks that there is something wrong with his genes that he's genetically predisposed to this disease. And he wants to understand at the molecular level what's happening with himself. And also he is worried about transmitting this predisposition to his son. And so he starts looking for genetic firms that can do genetic analysis and say, what's wrong in his DNA to this? The story what we were going to show is the serotonin molecule, the place where all these things happen, which is the synapse. That is the points in which neurons contact each other in the brain. And the way the synapse works, all the proteins that are there, the way the serotonin works on the receptor in the synapse, and a few other things that happen afterwards. So the work for us was, as usual, what we do when we do a molecular animation. We do some scientific research. We have to check all the molecules, the cellular environment. And we go through the literature. We ask our colleagues or friends or we search online on the scientific websites. Of course, not all molecules are already defined at the atomic level. So we have to build some of the molecules, which are more or less defined, but not completely. This is a process called homology modeling. And it's something that we have to do. Then we have to do some visual research, like for microscopic images, electron microscopy, other techniques that go very much into the detail, into very, very small objects. And then, of course, we have to set up our instruments. First of all, blender and bioblender and some other scientific tools that we used. Now, just a few words about bioblender. We made a talk a few years ago when we presented the program. It is a tool that goes with blender, uses blender. And it's made to fetch information, atomic coordinates from the database, and import the atomic information into blender, uses the blender game engine to elaborate conformational changes. But also what it shows is not the atoms, but it's the entire molecule. So it builds a wrapping around the molecule so that you see a unique shape, which changes while the atoms change underneath. And on this skin, which is the boundary of the molecule, we map a few physical properties of the molecule, which are the lipophilic potential and the electrostatic potential. These properties are very important for the way molecules behave. So they are not animal-like. They feel and they exert different kind of forces. The world of molecules has a physics, which is not different on a physical basis, but it's felt in a different way than what we feel. So for example, in the molecular world, there is no gravity. There is no light. There are no colors that we have in our lives. But there are other forces, which are very important, which are the electric forces. For example, the pH and other features that are possible to calculate, but are very difficult to visualize, the idea of BioBlender is to make these features visible and understandable in an immediate way to the human eye. So BioBlender is a very important tool in the visualization of molecular processes. So the first thing we had to model was serotonin. You can recognize the molecule is really simple. It's like 20 atoms. It's very, very simple. So from the storyboard, this is the final movie that is going in the film. You see the molecule is really small, but it still has some motion. What you see going out are the field lines, because the protein has the protein. The molecule has a small charged part, which produces an electric field that exerts its influence in the surrounding of the molecule itself. The next scene is much more complex, because it is the synaptic cleft. The synaptic cleft is a very, very small space, which is the point of contact between different neurons. As you may know, we have several million neurons in our brain, and each one of them has several thousand connections to other neurons. And that's how we elaborate thought, how we feel the word around, and the way our mind works. So there are many billions of synapse. The synapse are quite well studied. It's a very interesting topic of research in the neuroscience field. And we had to model a synaptic space. So let's see if it does. So this is the synaptic space. As you can see, it's a quite complex environment. The place is crowded with very many proteins on the two sides of the synapse, the so-called presynaptic, the place where the signal comes in, and the post-synaptic membrane, which is the receiver of the signal. Now what happens is that when the presynaptic receives the signal, which is an electric impulse, it will open a vesicle that releases the neurotransmitter. In this case, it's serotonin. It can be glutamate. It can be NMDA. It can be oxytocin. There's several molecules that mediate the transfer of information between different neurons. Once serotonin is released, in this case, we have 6,000 molecules of serotonin being flooding the synaptic space. And of course, this was not a trivial thing to. So this is the scene at the end of the work, the way we rendered, the scene that we rendered. As you can see from the outliner, there's many hundreds of proteins. Each protein is a very complex object, which is present in different forms, in different layers. One is the high-resolution form with the texture map that contains the information on the lipophilic potential and the retripotential. A low-resolution object for the molecules that are more towards the background in the scene. And a bounding box, which is used to calculate the trajectory of the particles, which are the serotonin molecules, the sugar molecules, the ions, calcium, potassium, magnesium, all these small objects that run around in the brain. So the scene is quite complex to render one of them. Well, every frame was about 15 to 20, 25 minutes per frame. But we finally managed to make a minute of this animation. We had to recalculate the particle cache, I don't know how many times, because there were always problems, but in the end, we did get the work done. In the synaptic cleft, the receiving part has receptors. So receptors are the proteins that can sense the presence of the transmitter, in this case, of serotonin, and respond by doing something. What they do is different receptors do different things. So the first one we see here is a quite complex protein made of five different subjects. Serotonin goes and binds in the junction between each two components of the protein. And the result of this binding is the changing conformation such that these five proteins that were all closed like this change and open a channel. In this channel, now that it's open, allows the passage of ions. Ions are charged, so they have a positive charge. This is a calcium ions, two positive charges. And when they pass through the channel and between the two sides of the membrane, they induce a change in the potential which gets propagated, and the signal can propagate to the rest of the neuron and go on around and around. Another protein which is also in the surface of the receiving neuron is a different receptor, which is a much smaller one, that senses the presence of the serotonin and transmits the signal to the interior of the cell where other things go on. But luckily, we didn't have to animate those as well. So the bioblender workflow. We developed bioblenders a few years ago, 10 minutes. Yes, I'll be fast. And basically, what we do since we also try to develop a version of bioblender that works with a newer version of blender, but at this time, they are not really usable. So what we do is we have to import the proteins in old bioblender, make the surface, calculate the mesh that is the skin of the protein, calculate it for every frame of the animation, calculate the surface properties, export the meshes and each mesh with its texture map, input them in the new blender version and use them as objects in the new scene. OK, the reuptake receptor is very beautiful, but I will skip for the sake of time. OK, I'll show you the reuptake. I think it's the most beautiful scene of the entire movie. Look at this. This protein is very well studied because it's the receptor for serotonin and it's also the protein which is the target of one of the most successful drugs, legal drugs, which is Prozac. So Prozac binds to this molecule and stops it from, this is a Prozac going in and instead of going through, it stacks there so that now the receptor cannot take up serotonin anymore. The result is that you have more and more serotonin around in the brain, so the more serotonin, the happier you are. That's why, in theory, how Prozac works. So that was the animation of the serotonin. Let me see what I can skip, something I had to skip. Of course, we had big problems and the major problem was bioblander, bioblander and bioblander. So please help. We have this new version of bioblander that was developed as an addon so that it could go together with new blender versions because the first one was a patched version of blender that included bioblander inside. Now, the major problem with the new one is that for very large molecules, the way the molecule is built is that for every atom, the sphere is introduced in the scene and a joint, which is the chemical bond that connects that atom to its neighbors. For some reasons, which I still fail to understand, blender, for every new object you insert, it rebuilds the infamous dependency graph. And it starts from beginning every single sphere. So that means that when you have a protein with 50,000 atoms, your blender will never be able to get it. I mean, it stacks, it stays there forever and you can't get the protein inside. And this is the very number one major problem. The second problem is the vertex mapping. So the lipophilic potential is mapped into the single, into the surface and it's attributed to the vertices of the mesh as a value that is then translated in a series of render features. Apparently, there is a problem in getting singular vertex. So in having a specific ID for every vertex. Now, I'm a biologist. This is the way people explained the problem to me. If you want more information, I will send you to someone else. So of course, we have this problem and what I did was write it on and say, OK, this is say, please, dear Tom, can you help? So Tom was kind enough to reply, except my computer will not show it. Saying, dear Monica, if you have a public repository of the code for BioBlender, then it should solve automatically. Actually, somebody was there around telling me what is a public repository because I didn't even know what a public repository is. Still, it doesn't mean that I know how to set it up, which means that once again, I need the help of the community and I really hope that you will contribute. Of course, if we solve the problems that BioBlender has now, we can think of any further development. I have plenty of ideas which I don't know how to implement, but I'm sure it's possible and one of them is to change the nature of the protein. So instead of making a protein made of several thousand atoms, make a single object in which each atom is imported as a vertex of the object and in which the bonds between the atoms are the edges of the mesh. Of course, it would not be a closed mesh, not something that can have faces, but maybe it's possible. You can give attributes of specific properties to the vertices and to the edges. So that would, I think, make it easier in some sense and it would make it possible to handle a larger number of proteins in the scene. That would be very nice. Then what we would like is also to have a newer and better way to calculate the surface and the electric potential field lines. And there are other features that we can think about. Ideas are for free and I can have as many as you want as long as someone can make them real. So I would like to keep BioBlender as an open project with things growing all the time. Let's try to make it look a little better. So what did we learn with this experience of making a movie? First of all, let people that know how to do things should do those things. Do not try to make everything. I should have really had someone to deal the business for us because we finally ended up doing a lot of work for a really, an amount of money that was ridiculously low for what we did. Get informatic people to do the informatic work. Maybe they can understand each other. They even know the meaning of words, something that I don't always do and never underestimate problems. We were lucky that a couple of weeks before the deadline we got a call from the producer and said, well, if you need a week or two more to finish your project, just take it because we've been delayed ourselves. Now they are delayed for several months, but we got at least two weeks more that helped a lot. Now, the important part is, as you see, it was like four people doing all this thing in basically four months. So it was a lot of work, but I think we managed to do something which is quite nice. And the film should be released in early January, early 2015, so look for the movie. It's called The Dark Gene. It's a quite interesting movie. Besides the animations that we made, I think we did see a more or less final cut and I think it's a nice movie. Despite the subject, I mean, who would want to go and film on depression? But apparently it's really an interesting film. So please go and see it when it comes out. If you are interested, the web page for the producer is filbtank.de because the Germans slash The Dark Gene. I don't know why it didn't come up. And I think that's all. Oh, here it is. Now, if we are offline, I am allowed to show you in the room, not online, unfortunately. The five minutes of animation with the movie and the explanation done by a professional actor. So if you're interested, I can try to see it. But this cannot go online and cannot go streaming. So I think, well, or next year. It's already four. Maybe we have time for just one or two very quick questions before. You are not the first to mention the topic of doing scientific research, doing really cool things with Blender, and then running into walls of problems with the development. And you should find ways, or better ways, or ways to contact, or whatever it is, what you can get developers more closely to the scientists. And I know there are lots of developers, for example, universities themselves, who are also looking for projects. And then they talk to us and then we want to have a feature in Blender or something. Which is far more difficult in general than, for example, helping out with a research project. Because you are more interested in your work and having your version or your specific thing. And you don't even want to be responsible for making Blender releases. So I think it's a very good opportunity to get universities to connect to the Informatica department or the computer science department, where there's a lot of young eager students hanging out who would like to code for Blender, but they don't know what to code. So that's what we should try to do. Yes, I think this is a good point. And I have to say, I never really look very well, very much into the Blender network. But I actually think that the Blender network might be the place for crossing the interest of different groups, both for the commercial and the research groups interested in using, in developing tools, and in research. Like, for example, the idea of making proteins with one object and introducing features on a vertex basis, on an edge basis. That's, I think it can be an interesting project to develop for a university and informatics group, I think. You will talk about it, and you'll find ways how to solve it, like with shop offers on the website. There must be ways for it, but it's in my attention, and I hope everybody's attention here, too. So one question, really good question, somebody. Want to know something? Does she not tell something? Nobody dares to ask a question. We saw very short video clips of about one minute or more. That is the real time of the behavior of those chemical stuff? Oh, no, no, no, no, no, this actually is very interesting. The release between the time that the electrical signal arrives and the time that the next electrical signal goes through the next neuron, the lag is about 0.6 to 0.8 milliseconds. So we rendered it in one and a half minutes, but the real thing is much, much, much, much faster. OK, thank you, Monica. Thanks again. There will be, in the salon, they ask me anything for developers, but I will go on probably until 5.30. You can only walk in and out. Probably it doesn't fit everybody in the salon.