[MUSIC PLAYING]
Perfect.
Welcome, guys.
Today, as Brenda mentioned, I'm going to kind of discuss
what we're doing in the brain field
but first talk about the technology that we did.
So the format of this talk-- I thought
it would be better and friendlier to just go over
what we've done so you guys have an idea of what I'm doing.
And then I have my team members here I'll introduce at the end
and you guys can ask us any questions.
So I'll keep this one short and if you have any questions,
just pop in and out during my presentation.
So the title you see here is long.
This is from our paper.
Hopefully at the end of this presentation,
you'll understand why is the precision important
That's to "digitally specify the spatially heterogeneous
engineered."
This is one of the constructs that we made that you
will see in a later slide.
So first, I want to see by a show of hands
how many people know about hydrogels or cross-linking.
All right.
So I'm going to give a little bit of a background
so you guys have a better understanding
of the technical terms of what we're doing.
Hydrogels-- you actually see it a lot in daily life.
We biotissue engineers use it as 3D scaffolds
to guide the cells.
Why do we do that?
Well, first and foremost, it's because it's simple to make.
The other one is it's reproducible and cheap.
This is very important.
If you're going to end up making a tissue or something 3D,
you want to be cost-efficient in that way.
It's moldable to any shape-- again, very important.
You guys can understand if you're making a tissue,
you don't want rigid constructs.
You want something that's flexible.
And probably one of the most important,
you can encapsulate cells inside.
This means you have the ability to manipulate the environment
and have a little bit of a control in the cell's
environment.
This is of a picture from the cover.
You'll see this again.
We made one of these constructs.
Each one of these squares or cubes
is a gel that you will see.
So hydrogels-- "hydro" because the majority of it
is water so it's good for the biosystems-- "gels"
because once it's cross-linked, it turns into a gel.
So that brings me to the idea of cross-linking.
There are many types of cross-linking.
We use optical cross-linking.
Basically in the layman's terms, I
would say if you have a polymer that
has branches-- you've probably seen this
in your basic chemistry-- when you add a photo initiator
and you expose it to UV light, these branches combine
and become more stable.
So when you start with a liquid-- which
is your hydrogel's in liquid form--
and you suspend your cells inside of it,
you end up with a gel that you can manipulate.
Any questions on this in the two terms that we've gone over?
Great.
So what was our goal in designing this technology?
Well, spatially position multiple cell types
within high precision.
You're going to see why high precision is important.
It's important because if you're doing something complicated
as a brain tissue, you want to exactly specify
which layer goes where and you want to be able to place that.
We've done this a little bit with bioprinting technologies.
You've probably seen some robotic printers.
But one of the goals you're going to see
is the low cost, as well.
Heterogeneous pattern-- very important.
We want to be able to alternate between the cell types.
We want to have a little bit of a freedom.
So the reason why we're doing this--
this is actually from an ad LEGO put some time ago.
What we want to do is you've guys
seen in the previous slide some cube-shaped gels.
We want to bring them together and kind of
just like LEGO does, put together a brain tissue.
Of course, we're not aiming to put a whole brain together
but we're aiming to put some part of it that's damaged
or we want to regenerate.
So what is important for us in this technology
that we want to build?
Well, 10-micron error in positioning
seems good when we're doing it by hand, not robotically.
Low cost-- again, we want to have this available outside
of a lab and at low cost.
We don't want a million-dollar robotic printer
that you would need.
And this is probably, for me personally
one of the most important ones.
You want to be able to alternate between cell types.
I should have added also cell densities in the XYZ-plane.
If you know about brain, you know a little bit
that in each layer, there are multiple layers
and the cell density is not the same.
So you would like to be able to arrange that when
you're using this technology, not be confined into one type.
So this was the goal.
Whoops.
This is the technology that we designed in collaboration
with Ed from the Media Lab.
It's very simple.
The photoresistor technology has been
around from semiconductors, if there
are any EE people in the room.
We use, again, the photo mask.
What we do that's different is we use multiple photo masks.
So we align them under the microscope.
We have certain points that we match with all the masks
so that you have that precision.
We design them on the computer so you know exactly
that what you designed is the precision where
you want to place it.
And then here, we are constructing our gels.
Each color represents a different cell type
or a different environment, just to show you guys
that we can place wherever we want
what cell type, what cell density--
we might have some growth serum inside.
You can alternate.
So these are some of the pictures
that we got from the paper.
We can see this.
c, d, e, and f shows the gradual placement of each gel.
We start with one square.
Then we design it this way.
You can see that we have different shapes that you
can design whatever you want because that's
where the "digitally" comes in.
You can do it on the computer any way you want.
So here, we tried to write "BAMM," "BWH,"
"HST," and "MIT," although it seems like a nice trend
to do every time you do something,
you write those names.
So these are the microscopic pictures,
which are important because we want to aim, again remember,
for a precise placement.
So 10 microns were what we were aiming for.
So following these, we did some analysis on the-- you
would think I would be able to work this out.
Oh, there you go.
For the precision, Ganes is one of the people in my team.
We did some of the analysis.
You can see that the concentric ones
are the most difficult ones because you're from all sides.
If you're aligning something and you miss something, all of them
are messed up.
But for the most part, we were in the range of 10 microns,
which was by hand a very good result.
I don't think there is another low-cost system that
can achieve this.
So we want to be able to-- let me go back-- say,
if we're placing, that we actually
place-- I am a shame for electrical engineers, right?
OK-- that we exactly place the cell types
that we want because this is one of our claims.
So each color is a tracker for a cell.
And we saw that in each compartment, indeed,
we placed the cells that we wanted in the way we wanted it.
If you have further-- I didn't include any graphs or details
but if you have any questions at the end, please feel free.
So that comes to the neuron part.
This was one of the most interesting parts in the paper.
We had two different sizes.
One of them is 10 micron by 10 micron
and the other one was 500 by 500.
We wanted to see the behavior of a neuron.
So we were able to encapsulate one in the 100 by 100.
You can imagine it was so small that the probability of getting
one was pretty high compared to two or three.
And we saw that indeed, the geometry mattered and it passed
through to the bigger gel.
This is the good news because if you're
going to bring these pieces together and claim that you're
going to build a tissue, you want
to see that it goes from one gel to the other
when you're aligning them.
So these are the results for different geometries,
different volumes-- we saw that it was best in a bigger volume.
Some of the images for this-- you
can see the nice network forming in the 500.
So these are what the gel originally looks
like after you construct them.
So the next slide I'm going to show
is-- if it lets me-- is the staining for different kinds
of cells within.
So in the brain tissue, you have not just the neurons.
You have glial cells and whatnot.
So we wanted to see what kind of different cells we're getting.
Again, there are some graphs about this.
You can check the paper and look at them.
And one more time-- so again, after that, that
was 2D in the xy-direction.
So we wanted to see how well can we go up to the z-direction.
These are some of the methods, the same method,
and then we used spacers to lift it up to go to another level.
So now it's a little bit more tricky
because you have xy-alignment with the z-alignment.
There are bigger pictures here you can see.
So we did this on purpose so that you guys
can see there are different levels to it in the paper.
This is a final product where you have three layers here.
This is a half, one layer on top a second layer,
again, to see that we were able to come up.
This is an array of them constructed.
Again, we were able to get very interesting shapes
by manipulating the colors, the way light diffracts
within the color.
So you were able to get very complicated constructs
in an easy way.
So this is what we've done.
The next question is what we're doing next.
This is one of confocal images that we
have for one of the gels, a nice network.
So what's next is, of course, now you have to look at the way
the cells are communicating with each other.
In the brain, neurons, the way they have that circuitry
is not very well-defined.
So what I'm working on right now is
we have the cells within the gels now.
So what is the function of getting some signals,
having them communicate with each other-- manipulating
and being able to see the axons and where they go?
Can I manipulate and have it go to x
and y instead of x1 and xy?
So that's where we are right now and one of my colleagues
that was in the team, Umut is working
on manipulating the cells on a pattern-interpret surface.
So this is what I have prepared for the what we've done part.
So now I want to introduce some of the lab
members, the people who worked with me on this project.
Dr. Demirci and Dr. Boyden, PIs, Media Lab, and BAMM Labs-- Umut
was the lead postdoc on this, Ganes, MD in training-- Ganes,
can you wave your hand?
So he was working with me on designing the technology
and making sure that it worked.
Visiting postdoc Emel was also working
with me on the constructs that you saw
and Jake was helping us with troubleshooting
the design of that first technology that you saw.
Thank you, guys.
Now, any one of us can answer questions.
So if you have questions-- sure.