Adam Cohen is Professor of Chemistry, Chemical Biology, and Physics at Harvard. He obtained Ph.D.s from Stanford and Cambridge, UK. He was an undergraduate at Harvard. Cohen is a recipient of the Blavatnik National Award in Chemistry and the American Chemical Society Pure Chemistry Award. He was named one of the top 35 US technological innovators under 35 by MIT Technology Review and one of the "Brilliant Ten" top young scientists by Popular Science. He founded Q-State Biosciences, which combines optical imaging with stem cell tech for new diagnostics and therapies for neuropsychiatric and neurodegenerative diseases.
We are trying to understand the three dimensional structures of memories in the brain, and one way we're doing this is by genetically engineering neurons to grow little protein fibers inside of each cell that record its activity. Transcript: "OK, what is the most difficult problem that you're trying to solve right now? Well, I'm working, and my students are working on several different problems which none of us knows how to solve. And so we don't know which of these is going to be most difficult, which might be easy to solve, and which might be completely unsolvable. So I'll tell you about one problem that we're interested in. We're interested in trying to understand the three dimensional structures of memories in the brain. So if you think about what you had for breakfast this morning, there's some three dimensional representation of that memory in your brain and some set of biochemical changes in the neurons in your brain. But we have no idea what these maps are, or what are the rules that govern how memories are encoded or represented in the brain. My lab is working on trying to develop tools which we can use to map these changes. One approach that we're working on is to genetically engineer neurons to grow little protein fibers inside of each cell. And as these fibers grow, they incorporate marks of neuronal activity, a little bit like tree rings in a tree, which incorporate information about seasonal climate changes. And by incorporating within each neuron, a little tape recorder of its activity, we hope to be able to then look in the brains of animals, mice, which have learned different things, and to map the patterns of neural activity associated with different memories during the formation of the memory, during the recall of the memory, and during eventually maybe the forgetting of the memory, or changes in the memory."
Neither a Tokamak nor a stellarator have yet produced enough energy to be used in a power supply. To achieve fusion, three types of break even need to be achieved: physics break even, engineering break even and economic break even. Recent progress in renewable energy sources has cast doubt on whether these approaches will ever be economically viable. Transcript: "The question is what is superior for achieving Fusion a Tokamak or a stellarator. So infusion Light Elements typically hydrogen or its Isotopes are smashed together with very high energy and the nuclei fuse and can release a tremendous amount of energy. And for decades, people have thought this would be a great way to produce a source of energy, without any Green House, Green House gases, and with readily available. Fuels the challenge is how to contain the gases which have to be extremely high temperatures during a fusion process. And people have proposed that by using magnetic fields, you can try to build basically, a magnetic bottle, which can hold the gas is away from the walls of the reactor and a Tokamak and stellarator have slightly different geometries for these magnetic bottles in a Tokamak there in a donut. And in a stellarator, it's more like twisted. Donut and to date neither of these techniques has produced enough energy to be usable in a power supply. And so I want to talk a little bit about. What does it mean to achieve Fusion because there's actually three different definitions of success that people use? And it matters which one you're talking about. There's a physics definition which is have you gotten more energy out of the plasma, then you Into the plasma and that's a bare minimum. A more stringent definition is an engineering definition which is if you think about the entire plasma, the entire Fusion, plant can you get more energy out than you put in including all of the in efficiencies in the plant and so to achieve engineering Break, Even you need about tenfold higher output than for physics break even and then the third definition is economic Break. Even what can you actually make more money selling the electricity? Then you spend financing the construction of this plant and that is I think, in many cases, the highest bar and with recent progress in renewable, solar and wind. It's not even clear whether of these approaches will ever be economically viable."
Physical forces play an important role in embryonic development, but the specifics are not yet fully understood. Mechanical forces, electrical signals, and osmotic forces have all been suggested as potential influences on the patterning of cells during development. Transcript: "So the question is, what are the roles of physical forces in embryonic development. This is a very Broad and challenging question to which Nobody Knows the complete answer. Much of our knowledge of biochemistry and biochemical signaling is from experiments on ether purified, proteins or purified solutions or on cells, which are growing in a dish. And those are good systems for learning about how molecules With each other. But if you think about yourself, your body has a three dimensional structure, you have distinct fingers, and toes, and a nose, and so on. And so as a single cell, a fertilized egg grows into a being with a three dimensional structure. The the cells are have to interact with each other physically. And so the formation of body plans, Is some combination of molecular and biochemical signaling and mechanical interactions between the cells. And we don't know to what extent, the biochemical rule interaction sort of set the rules and then mechanics just follow or to what extent, the mechanical interactions actually play a role in the pattern forming process itself. There's increasing evidence of the latter case that mechanical forces are actually important instructive signals in telling cells what Become and where to go. There are many different kinds of physical forces. And so I mechanical forces are one. There are interesting hints that electrical forces. Electrical signals, might also play a role in embryonic development, possibly osmotic forces and that there could be others as well, that we don't even know about. So, the question of, how does an embryo develop is a really fascinating one for which we don't know. Nearly enough yet. And for which modern tools are just getting to the point where they can start to answer these fundamental questions."
Alan Turing and Erwin Schrodinger have similar mathematical equations that they developed. These equations govern different physical phenomena, but have a very similar structure. This means that techniques and ideas developed for one can be used to make predictions about the other. Transcript: "So the question is, what do Alan Turing and Erwin Schrodinger have in common? Well, I don't know what they have in common as people, but I can tell you a little bit about the equations which bear their name. One of the last things that Alan Turing did in his life. Is he developed a mathematical model for embryonic development? He showed how under some conditions, a simple chemical reaction can Spontaneously form patterns that look like zebra stripes or leopard spots are many of the other patterns seen in life. Remarkably the underlying equations that touring developed have a very similar mathematical structure to the Schrodinger equation, which governs quantum mechanics. In fact, there's a third set of equations which also have a similar structure which are called the hodgkin-huxley equations, which govern how electrical Goal signals propagate down neurons. Now. It's probably just a mathematical coincidence that these three equations all have such similar structures, but it means that you can use techniques or ideas developed for trying to solve one set of equations to make predictions about what would happen in the other domains as well."
Microbial rhodopsin proteins were discovered in the 1970s and are used by organisms for a variety of functions. In 2005, scientists at Stanford discovered that these proteins could be introduced into neurons, making them sensitive to light. My lab started studying their basic functioning around 2008 and predicted that it might be possible to run these proteins in reverse, using neural activity to modulate the optical properties of the proteins and produce an optical signal that you could see. After many years of hard work, this prediction was found to be true and proved useful for monitoring electrical activity of neurons in living organisms. Transcript: "The question is, how did you first discover microbial reduction proteins? How and why did you make them run in Reverse? So first, I want to make sure that we didn't discover these proteins. They've been known since the 1970s and in the wild these proteins absorb sunlight and they convert that sunlight into a variety of different biochemical signals, which their host organisms use. So, some creatures use them to capture solar energy, others, use them for a sensing function to try to swim toward or away from certain colors of light. Around 2005 or so, some people at Stanford called ice Roth and Fung, Jang and Ed Boyden discovered that you could take some genes for some of these microbial rhodopsin proteins and introduce them into cell like neurons. And then the neurons would produce the proteins and the neurons would become sensitive to light so that you could then shine light on the neurons in the brain of a mouse and control the animal's behavior. Around 2008 or so, my lab started studying the basic functioning of these proteins. And based on our observations we predicted that it might be possible to run these proteins in reverse. Instead of using light, to control neural activity you might be able to use neural activity to modulate the optical properties of these proteins and produce an optical signal that you could see. And this after many years of hard work, this prediction has been borne out and this turned out to be a really useful tool because it gives us a window literally into seeing the electrical activity of neurons, either in the brain of a mouse or in various salt cell culture systems for instance in modeling different diseases of the nervous system."
We use fluorescent proteins to convert the electrical activity of neurons into flashes of fluorescence that can be seen in a high-speed microscope. We also set up virtual reality systems where the animal is not actually moving, but has a virtual reality display around it. As the animal performs different tasks, the visual environment adjusts. Transcript: "How do you study information processing in the brains of awake behaving, mice and zebrafish? Well, there are many tools that people have developed for Imaging the activity of neurons in my lab. We've developed some fluorescent proteins, which can convert the electrical activity of cells into flashes of fluorescence that you can see in a high-speed microscope. So we genetically modify the mice or the fish to express to produce these ins in their neurons. And then we develop custom microscopes to perform very high-speed ultra-sensitive Imaging in the brains of these animals as they do things. Now, it's hard to have a microscope move around with an animal, if it's really moving through the physical world. So we often set up virtual reality systems where the animal is not actually moving, but it has some sort of a virtual reality display around it. And then as it performs different tasks, the the visual environment around it adjusts."