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Hello, everybody.

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I brought with me today a baby diaper.

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You'll see why in a second.

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Baby diapers have interesting properties.

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They can swell enormously[br]when you add water to them,

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an experiment done[br]by millions of kids every day.

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(Laughter)

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But the reason why

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is that they're designed[br]in a very clever way.

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They're made out of a thing[br]called a swellable material.

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It's a special kind of material that,[br]when you add water,

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it will swell up enormously,

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maybe a thousand times in volume.

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And this is a very useful,[br]industrial kind of polymer.

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But what we're trying to do[br]in my group at MIT

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is to figure out if we can do[br]something similar to the brain.

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Can we make it bigger,

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big enough that you[br]can peer inside

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and see all the tiny building blocks,[br]the biomolecules,

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how they're organized in three dimensions,

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the structure, the ground truth[br]structure of the brain, if you will?

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If we could get that,

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maybe we could have a better understanding[br]of how the brain is organized

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to yield thoughts and emotions

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and actions and sensations.

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Maybe we could try to pinpoint[br]the exact changes in the brain

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that result in diseases,

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diseases like Alzheimer's[br]and epilepsy and Parkinson's,

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for which there are few[br]treatments, much less cures,

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and for which, very often,[br]we don't know the cause or the origins

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and what's really causing them to occur.

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Now, our group at MIT

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is trying to take[br]a different point of view

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from the way neuroscience has[br]been done over the last hundred years.

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We're designers. We're inventors.

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We're trying to figure out[br]how to build technologies

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that let us look at and repair the brain.

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And the reason is,

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the brain is incredibly,[br]incredibly complicated.

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So what we've learned[br]over the first century of neuroscience

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is that the brain is a very[br]complicated network,

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made out of very specialized[br]cells called neurons

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with very complex geometries,

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and electrical currents will flow[br]through these complexly shaped neurons.

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Furthermore, neurons[br]are connected in networks.

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They're connected by little junctions[br]called synapses that exchange chemicals

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and allow the neurons[br]to talk to each other.

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The density of the brain is incredible.

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In a cubic millimeter of your brain,

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there are about 100,000 of these neurons

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and maybe a billion of those connections.

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But it's worse.

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So, if you could zoom in to a neuron,

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and, of course, this is just[br]our artist's rendition of it.

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What you would see are thousands[br]and thousands of kinds of biomolecules,

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little nanoscale machines[br]organized in complex, 3D patterns,

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and together they mediate[br]those electrical pulses,

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those chemical exchanges[br]that allow neurons to work together

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to generate things like thoughts[br]and feelings and so forth.

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Now, we don't know how[br]the neurons in the brain are organized

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to form networks,

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and we don't know how[br]the biomolecules are organized

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within neurons

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to form these complex, organized machines.

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If we really want to understand this,

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we're going to need new technologies.

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But if we could get such maps,

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if we could look at the organization[br]of molecules and neurons

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and neurons and networks,

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maybe we could really understand[br]how the brain conducts information

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from sensory regions,

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mixes it with emotion and feeling,

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and generates our decisions and actions.

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Maybe we could pinpoint the exact set[br]of molecular changes that occur

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in a brain disorder.

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And once we know how[br]those molecules have changed,

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whether they've increased in number[br]or changed in pattern,

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we could use those[br]as targets for new drugs,

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for new ways of delivering[br]energy into the brain

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in order to repair the brain[br]computations that are afflicted

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in patients who suffer[br]from brain disorders.

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We've all seen lots of different[br]technologies over the last century

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to try to confront this.

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I think we've all seen brain scans

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taken using MRI machines.

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These, of course, have the great power[br]that they are noninvasive,

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they can be used on living human subjects.

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But also, they're spatially crude.

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Each of these blobs that you see,[br]or voxels, as they're called,

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can contain millions[br]and millions of neurons.

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So it's not at the level of resolution

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where it can pinpoint[br]the molecular changes that occur

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or the changes in the wiring[br]of these networks

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that contributes to our ability[br]to be conscious and powerful beings.

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At the other extreme,[br]you have microscopes.

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Microscopes, of course, will use light[br]to look at little tiny things.

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For centuries, they've been used[br]to look at things like bacteria.

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For neuroscience,

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microscopes are actually how neurons[br]were discovered in the first place,

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about 130 years ago.

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But light is fundamentally limited.

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You can't see individual molecules[br]with a regular old microscope.

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You can't look at these tiny connections.

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So if we want to make our ability[br]to see the brain more powerful,

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to get down to the ground truth structure,

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we're going to need to have[br]even better technologies.

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My group, a couple years ago,[br]started thinking:

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Why don't we do the opposite?

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If it's so darn complicated[br]to zoom in to the brain,

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why can't we make the brain bigger?

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It initially started

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with two grad students in my group,[br]Fei Chen and Paul Tillberg.

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Now many others in my group[br]are helping with this process.

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We decided to try to figure out[br]if we could take polymers,

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like the stuff in the baby diaper,

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and install it physically[br]within the brain.

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If we could do it just right,[br]and you add water,

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you can potentially blow the brain up

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to where you could distinguish[br]those tiny biomolecules from each other.

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You would see those connections[br]and get maps of the brain.

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This could potentially be quite dramatic.

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We brought a little demo here.

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We got some purified baby diaper material.

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It's much easier[br]just to buy it off the Internet

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than to extract the few grains[br]that actually occur in these diapers.

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I'm going to put just one teaspoon here

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of this purified polymer.

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And here we have some water.

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What we're going to do

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is see if this teaspoon[br]of the baby diaper material

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can increase in size.

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You're going to see it increase in volume[br]by about a thousandfold

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before your very eyes.

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I could pour much more of this in there,

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but I think you've got the idea

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that this is a very,[br]very interesting molecule,

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and if can use it in the right way,

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we might be able[br]to really zoom in on the brain

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in a way that you can't do[br]with past technologies.

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OK. So a little bit of chemistry now.

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What's going on[br]in the baby diaper polymer?

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If you could zoom in,

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it might look something like[br]what you see on the screen.

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Polymers are chains of atoms[br]arranged in long, thin lines.

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The chains are very tiny,

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about the width of a biomolecule,

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and these polymers are really dense.

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They're separated by distances

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that are around the size of a biomolecule.

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This is very good

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because we could potentially[br]move everything apart in the brain.

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If we add water, what will happen is,

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this swellable material[br]is going to absorb the water,

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the polymer chains will move[br]apart from each other,

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and the entire material[br]is going to become bigger.

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And because these chains are so tiny

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and spaced by biomolecular distances,

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we could potentially blow up the brain

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and make it big enough to see.

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Here's the mystery, then:

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How do we actually make[br]these polymer chains inside the brain

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so we can move all the biomolecules apart?

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If we could do that,

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maybe we could get[br]ground truth maps of the brain.

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We could look at the wiring.

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We can peer inside[br]and see the molecules within.

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To explain this, we made some animations

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where we actually look[br]at, in these artist renderings,

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what biomolecules might look[br]like and how we might separate them.

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Step one: what we'd have[br]to do, first of all,

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is attach every biomolecule,[br]shown in brown here,

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to a little anchor, a little handle.

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We need to pull the molecules[br]of the brain apart from each other,

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and to do that, we need[br]to have a little handle

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that allows those polymers to bind to them

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and to exert their force.

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Now, if you just take baby diaper[br]polymer and dump it on the brain,

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obviously, it's going to sit there on top.

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So we need to find a way[br]to make the polymers inside.

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And this is where we're really lucky.

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It turns out, you can[br]get the building blocks,

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monomers, as they're called,

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and if you let them go into the brain

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and then trigger the chemical reactions,

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you can get them to form[br]those long chains,

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right there inside the brain tissue.

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They're going to wind their way[br]around biomolecules

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and between biomolecules,

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forming those complex webs

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that will allow you, eventually,[br]to pull apart the molecules

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from each other.

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And every time one[br]of those little handles is around,

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the polymer will bind to the handle,[br]and that's exactly what we need

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in order to pull the molecules[br]apart from each other.

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All right, the moment of truth.

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We have to treat this specimen

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with a chemical to kind of loosen up[br]all the molecules from each other,

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and then, when we add water,

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that swellable material is going[br]to start absorbing the water,

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the polymer chains will move apart,

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but now, the biomolecules[br]will come along for the ride.

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And much like drawing[br]a picture on a balloon,

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and then you blow up the balloon,

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the image is the same,

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but the ink particles have moved[br]away from each other.

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And that's what we've been able[br]to do now, but in three dimensions.

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There's one last trick.

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As you can see here,

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we've color-coded[br]all the biomolecules brown.

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That's because they all[br]kind of look the same.

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Biomolecules are made[br]out of the same atoms,

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but just in different orders.

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So we need one last thing

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in order to make them visible.

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We have to bring in little tags,

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with glowing dyes[br]that will distinguish them.

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So one kind of biomolecule[br]might get a blue color.

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Another kind of biomolecule[br]might get a red color.

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And so forth.

0:09:05.823,0:09:07.375
And that's the final step.

0:09:07.399,0:09:09.677
Now we can look at something like a brain

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and look at the individual molecules,

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because we've moved them[br]far apart enough from each other

0:09:14.252,0:09:15.950
that we can tell them apart.

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So the hope here is that[br]we can make the invisible visible.

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We can turn things that might seem[br]small and obscure

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and blow them up

0:09:22.597,0:09:25.774
until they're like constellations[br]of information about life.

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Here's an actual video[br]of what it might look like.

0:09:28.197,0:09:30.568
We have here a little brain in a dish --

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a little piece of a brain, actually.

0:09:32.363,0:09:33.959
We've infused the polymer in,

0:09:33.983,0:09:35.450
and now we're adding water.

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What you'll see is that,[br]right before your eyes --

0:09:37.856,0:09:39.779
this video is sped up about sixtyfold --

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this little piece of brain tissue[br]is going to grow.

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It can increase by a hundredfold[br]or even more in volume.

0:09:45.756,0:09:48.705
And the cool part is, because[br]those polymers are so tiny,

0:09:48.729,0:09:51.288
we're separating biomolecules[br]evenly from each other.

0:09:51.312,0:09:52.970
It's a smooth expansion.

0:09:52.994,0:09:55.681
We're not losing the configuration[br]of the information.

0:09:55.705,0:09:58.405
We're just making it easier to see.

0:09:59.333,0:10:01.509
So now we can take[br]actual brain circuitry --

0:10:01.533,0:10:04.667
here's a piece of the brain[br]involved with, for example, memory --

0:10:04.691,0:10:05.954
and we can zoom in.

0:10:05.978,0:10:08.868
We can start to actually look at[br]how circuits are configured.

0:10:08.892,0:10:10.860
Maybe someday we could read out a memory.

0:10:10.884,0:10:13.663
Maybe we could actually look[br]at how circuits are configured

0:10:13.687,0:10:14.839
to process emotions,

0:10:14.863,0:10:17.785
how the actual wiring[br]of our brain is organized

0:10:17.809,0:10:20.376
in order to make us who we are.

0:10:20.400,0:10:22.447
And of course, we can pinpoint, hopefully,

0:10:22.471,0:10:25.630
the actual problems in the brain[br]at a molecular level.

0:10:25.654,0:10:28.223
What if we could actually[br]look into cells in the brain

0:10:28.247,0:10:31.330
and figure out, wow, here are the 17[br]molecules that have altered

0:10:31.354,0:10:34.809
in this brain tissue that has been[br]undergoing epilepsy

0:10:34.833,0:10:36.483
or changing in Parkinson's disease

0:10:36.507,0:10:38.024
or otherwise being altered?

0:10:38.048,0:10:41.091
If we get that systematic list[br]of things that are going wrong,

0:10:41.115,0:10:43.314
those become our therapeutic targets.

0:10:43.338,0:10:45.015
We can build drugs that bind those.

0:10:45.039,0:10:47.666
We can maybe aim energy[br]at different parts of the brain

0:10:47.690,0:10:50.377
in order to help people[br]with Parkinson's or epilepsy

0:10:50.401,0:10:52.952
or other conditions that affect[br]over a billion people

0:10:52.976,0:10:54.189
around the world.

0:10:55.246,0:10:57.452
Now, something interesting[br]has been happening.

0:10:57.476,0:11:00.181
It turns out that throughout biomedicine,

0:11:00.205,0:11:02.871
there are other problems[br]that expansion might help with.

0:11:02.895,0:11:06.129
This is an actual biopsy[br]from a human breast cancer patient.

0:11:06.505,0:11:08.693
It turns out that if you look at cancers,

0:11:08.717,0:11:10.328
if you look at the immune system,

0:11:10.352,0:11:12.865
if you look at aging,[br]if you look at development --

0:11:12.889,0:11:17.386
all these processes are involving[br]large-scale biological systems.

0:11:17.410,0:11:21.434
But of course, the problems begin[br]with those little nanoscale molecules,

0:11:21.458,0:11:25.327
the machines that make the cells[br]and the organs in our body tick.

0:11:25.351,0:11:27.573
So what we're trying[br]to do now is to figure out

0:11:27.597,0:11:31.063
if we can actually use this technology[br]to map the building blocks of life

0:11:31.087,0:11:32.832
in a wide variety of diseases.

0:11:32.856,0:11:35.752
Can we actually pinpoint[br]the molecular changes in a tumor

0:11:35.776,0:11:38.145
so that we can actually[br]go after it in a smart way

0:11:38.169,0:11:42.113
and deliver drugs that might wipe out[br]exactly the cells that we want to?

0:11:42.137,0:11:44.472
You know, a lot of medicine[br]is very high risk.

0:11:44.496,0:11:46.278
Sometimes, it's even guesswork.

0:11:46.626,0:11:50.501
My hope is we can actually turn[br]what might be a high-risk moon shot

0:11:50.525,0:11:52.294
into something that's more reliable.

0:11:52.318,0:11:54.373
If you think about the original moon shot,

0:11:54.397,0:11:56.295
where they actually landed on the moon,

0:11:56.319,0:11:57.763
it was based on solid science.

0:11:57.787,0:11:59.390
We understood gravity;

0:11:59.414,0:12:00.755
we understood aerodynamics.

0:12:00.779,0:12:02.174
We knew how to build rockets.

0:12:02.198,0:12:04.666
The science risk was under control.

0:12:04.690,0:12:07.443
It was still a great, great[br]feat of engineering.

0:12:07.467,0:12:10.112
But in medicine, we don't[br]necessarily have all the laws.

0:12:10.136,0:12:13.245
Do we have all the laws[br]that are analogous to gravity,

0:12:13.269,0:12:15.613
that are analogous to aerodynamics?

0:12:15.637,0:12:17.367
I would argue that with technologies

0:12:17.391,0:12:19.263
like the kinds I'm talking about today,

0:12:19.287,0:12:20.980
maybe we can actually derive those.

0:12:21.004,0:12:23.861
We can map the patterns[br]that occur in living systems,

0:12:23.885,0:12:28.443
and figure out how to overcome[br]the diseases that plague us.

0:12:29.499,0:12:31.578
You know, my wife and I[br]have two young kids,

0:12:31.602,0:12:34.836
and one of my hopes as a bioengineer[br]is to make life better for them

0:12:34.860,0:12:36.589
than it currently is for us.

0:12:36.613,0:12:40.343
And my hope is, if we can[br]turn biology and medicine

0:12:40.367,0:12:44.724
from these high-risk endeavors[br]that are governed by chance and luck,

0:12:44.748,0:12:48.675
and make them things[br]that we win by skill and hard work,

0:12:48.699,0:12:50.597
then that would be a great advance.

0:12:50.621,0:12:51.827
Thank you very much.

0:12:51.851,0:13:02.234
(Applause)