Hi, my name is Lokesh Joshi, I'm a Professor of Glycosciences, SFI Stokes Professor based in NUI Galway on the west coast of Ireland.

What we are working on is developing technologies to understand the cell surface signatures. And this is an ecosystem and you can tell by looking at the leaves on the tree, whether the tree is healthy or what season it is. You can say this is winter, this is summer, this is autumn or this is fall, by looking at that. Now cells are the same thing, cells are smaller ecosystems

and by looking at them you should be able to tell whether the cell is young, cell is old. If they have good sugars on them, if they have healthy sugars on them, then we know that the cells or tissues are healthy. And if they have sugars that are wrong, then we know there's a disease. But how do you understand that? How do you study that is important? What we are developing is technology that can get kind of a snapshot of the fingerprints of the cells.

Each cell has a signature of sugars. Here you have a bacterial toxin, here are two different bacteria that cause two different diseases and here's a cancer cell. Each one of these is covered with different sugars or different combinations of sugars. And if you have the technology to capture that combination of the sugars,

then you can generate a pattern or a signature. So that's the technology that we are developing in the lab, that we look at the sugars and we develop these fingerprints of the cells or of the serum samples from the patients. So you can imagine that these are the two fingerprints of the cells' sugars under two different conditions of the growth or two different diseases or two different bacteria, whichever way you look at it.

And then we generate barcode from these sugar signatures and we assign it to the different diseases or different stages of the disease. Now this is what we're doing in the lab. This is amazing technology where we put a set of proteins or molecules that identify specific sugar signatures. So we make them in the lab, we bind them, bind the sample there

and then we generate a pattern. These green signals are the ones where the cell is binding. And I'll show you an example how we do it. So this is a device, a small device, which basically it opens like this. And then you can look at the slide. So this slide has these eight different quadrants. And you can put your sample in there.

Sample could be cancer sample, could be different stem cell sample, bacteria sample. And you can close the whole thing together just like this. And then what you do is that you mix with some reagents there and you what we call incubation. That means you mix the whole thing together like this and you put it in an imager. When you do that, it generates an image.

And this is the image that you see from these slides. It's a beautiful image here of different spots. The green spots show where the reaction is taking place, where there is a difference. And then what you can do here, we have eight different types of cancer cells and each of them is generating a different pattern of binding. So then we know that there are differences in all of these different cancer types.

What we can also do is to make it visually more appealing is that we can convert those little linear plots into radar plots. And here we have all the proteins that bind to sugars on the same microarray slides that I showed you a second ago. And here we have three different cell types. And you can see that the red, the blue, and the green, they all generate a different binding pattern.

And that binding pattern is the fingerprint of the cell or the glyco fingerprint of the cell. In this case, it's even more powerful. We took one of these cell lines. We are also able to see the mutation or the changes that the cell is accumulating during the disease process. So this way, I think the goal is that down the road, the clinicians or the diagnostic people or industry,

they should be able to assign barcodes to every disease, every cell, every stage, every bacteria, every virus. And as soon as the patient walks in, they can match the barcode with what is in the reference library and tell you what the disease there is. And that's the thing that we're developing with a very, very exciting thing that's happening in the field.