In this episode of SciTech Now, a unique approach to studying Alzheimer’s disease; an app that empowers people with disabilities; how to prolong your phone’s battery; and a laser label maker.
SciTech Now 503
Coming up... a unique approach to studying Alzheimer's disease.
Our research here at UTSA has the ability to shed new light on the molecular targets and molecular mechanisms.
...an app that empowers people with disabilities.
Technology should always be adapting to the user, and not the other way around.
...new technology that may prolong your phone's battery.
What we are going to do is to make the electric circuit very efficient using this new material, instead of having a metal semiconductor.
...a laser label-maker.
We don't put any ink or anything into it.
What we do is, we take the pigment out of the outer layer of the skin of the fruit.
It's all ahead.
Funding for this program is made possible by...
I'm Hari Sreenivasan.
Welcome to 'SciTech Now,' our weekly program bringing you the latest breakthroughs in science, technology, and innovation.
Let's get started.
According to a 2018 annual report released by the Alzheimer's Association, there are currently 5.7 million Americans living with Alzheimer's disease.
As this number is projected to increase in the next decades, researchers from the University of Texas at San Antonio have come up with a unique approach to studying the disease in hopes of finding therapies that can slow its progression.
Oftentimes, the terms Alzheimer's disease and dementia are used interchangeably.
In reality, though, there are many different forms of dementia.
Alzheimer's disease is the number-one cause of dementia worldwide.
There are millions of cases, and throughout the years, as deaths from other diseases, such as heart disease, have gone down, Alzheimer's disease deaths just continue to rise.
So, there is a really, really big problem with a lack of available therapies or available drug targets to not cure the disease, but stop its progression.
The problem with there being no cure is that there is a lack of understanding of how the disease operates.
If you're doing diabetes, you know it's insulin you got to worry about.
With Alzheimer's, the only thing they know right now is to worry about senile plaque.
So the goal of this research is to try and find out, what are the molecular players in Alzheimer's, and how do the molecules, the molecular constituents of the brain and the body, change as people progress through the various stages of Alzheimer's?
And, hopefully, if we can understand the biomolecular processes involved in Alzheimer's, we can figure out an interventional method.
Billions of dollars have been spent over the last years trying to better understand the disease pathology.
As of right now, not much is known, and because of that, there's no real way to start developing any potential drug therapy, or really even understand the biomarkers of the disease.
So, basically, what this is, is this is an actual piece of brain from an Alzheimer's-disease patient.
This has been formalin-fixed and paraffin-embedded.
This is a really, really good type of tissue for histology and pathology because it has an infinite lifetime.
Years down the road, you can go back, stain it, look at it under a microscope, and basically look at the different hallmarks in there.
So, there are ways of looking at things like senile plaques and tau with microscopy with this type of tissue What we do with the imagining mass spectrometry is actually cut this tissue onto glass slides, and, with our instrument, we are able to take the tissue, basically raster it with a laser across the tissue, and then localize all of the different components so that you get a really good picture of where on the tissue each thing is localized, and which things are localized in the same area and so on and so forth.
So, senile plaques are some sticky aggregates of what most people consider was nothing but amyloid beta.
And that's one of the reasons we wanted to start, because we know what amyloid beta looks like in our mass-spec.
So, once we figured out the preparation method for amyloid beta -- and being able to do it in a mass spectrometer we're able to actually see the amyloid beta.
And then, to our surprise, we're able to see a whole host of other proteins and peptides that have various known functions in the body, and that are unusual to have been found in the brain.
The optimal thing would be to follow patients, which is unrealistic for us.
But as long as we can use these samples that we have from humans and start to see, 'Okay, what is exaggerated?
What is expressed differently between these healthy brains and these diseased brains?'
We can start to maybe get a new focus.
We feel that, once researches know what the molecular players are, what the proteins and peptides are that are involved in this disease, they will be able to figure out ways of stopping the progression of this disease before it gets to its ultimate end, where the person has the dementia.
Our research here at UTSA has the ability to shed new light on the molecular targets and molecular mechanisms that are at play in the onset and progression of Alzheimer's disease.
And hopefully we have been able to develop a new molecular foci for disease research that will eventually lead to available disease therapies or drug targets.
Technology has the ability to transform the lives of people with disabilities.
One example is SwiftKey, an app for keyboards that helps non-verbal users communicate.
Joe Osborne, Senior Engineering Manager at SwiftKey, joins us to discuss.
First of all, what is SwiftKey, for people who don't know what it is?
So, SwiftKey is probably best known for our keyboard applications.
Best known on Android and iOS devices.
And the technology that sits underneath SwiftKey keyboard also powers a number of our other products.
For example, our product SwiftKey Symbols, which you've mentioned, which is seeking to assist those who perhaps can't use a traditional keyboard, or perhaps don't use language in a traditional sense, to still be able to communicate in a very effective way, to empower them to really communicate with those around them.
Is this just about predicting what your next word is?
Does that shortcut the process of how long it takes to input?
So, this is where it gets very interesting.
So, to step back a little bit, one of the ideas we kind of look at SwiftKey is -- kind of two big things we think about.
One is that technology should always be adapting to the user, and not the other way around.
And secondly that, particularly when it comes to communication, the real input to the system is your intent.
These either messy keystrokes or eye tracking, all these noisy inputs are just a poor proxy for what your intent actually is.
And it's our job to reconcile what your intent was from your messy, incomplete, incorrect input.
That does include an aspect of prediction, but it also is about, in a sense, correction, to label it very, very broadly.
And to do this, we try and understand as much of the text-input process as possible and model it mathematically.
Everything from the physical inputs we see you making to the kind of lexical and typographic errors that you tend to make as an individual, and then all the way down to the language and the linguistics that you use.
How do you learn all that?
Ah, well -- well... As we said, technology should always adapt to the user.
So by observing how the user is using our technology, and the way they're using language, we can build up, on your own device, an understanding of you, how you use your language.
Whether you're multilingual, whether you're monolingual, whether you mix your languages, and what your biases are in your linguistics.
But also the kinds of errors and the error characteristics that you have when you're trying to communicate.
So it's getting smarter the more I type.
And it would be easy to think about prediction and correction as two separate ideas.
But, really, almost everything that we do is a combination of prediction and correction.
The better you can predict, the better you can imagine where someone is trying to do, what their intent is, the better you can correct for them, as well.
So when I type H-A-R-I into my phone, you won't auto-correct for H-A-I-R?
As we learn and observe the way you use and the words you use and when and where you use them, that's exactly right, yeah.
And you also worked with Stephen Hawking.
Tell me a little bit about that.
That's right. So... Perhaps a little bit of history, if that's of interest.
Several years ago, Intel, who had been the provider of Stephen Hawking's whole, complete technology, you know, his whole system, were seeking to do a bit of a revamp of his system.
And they made lots of improvements about the way he could navigate through this applications and things like that, which were great time savers.
But what was clear to them was that is communication rate, the rate at which he could actually enter text, was not what it used to be, and they were looking for ways to improve that.
And they were trying various existing solutions, and they just weren't holding up to scratch.
So we got in touch with Intel, and we started to work with them.
And so we spent quite a lot of time with Hawking and his team, observing both how he uses his system and the nature of the system itself.
Obviously we didn't have all the details about how his system worked, initially.
Understanding where his pain points were in terms of communication, in terms of getting text into his system.
But also observing the issues that he was less aware of, and what the characteristics of his system were, and where the weaknesses were -- for example, in the sensor he uses to actually input.
And, of course, one would expect the error characteristics that he has and that he experiences are very different from what you and I would experience hammering with two thumbs on our phones.
So he will have very different error characteristics.
The utility of what we are trying to do on his behalf is also very different.
The cost of him making an error, or the cost of us making an error on his behalf, are far higher, for example, than they are on our device.
And so building technology which can adapt and exist in both ends of this spectrum, if you can do that well, you're probably doing a good thing.
So, what are other examples of how this technology is being applied?
What have you learned from the Stephen Hawkings of the world?
What have you learned from people like me using the app on the phone?
So, one of the key things we learned from Hawking, of course, is just what a lifeline communication is for people who don't have another means of communication.
So it's very important for you to do your job right.
And that has a number of consequences.
One is that, even by making a small improvement, you can actually radically change someone's life.
The second is that you have to really respect the position you are holding in that life, and not play with it.
It's a very important position to be in.
And so you have to be very aware of that, and respect the role that your technology is playing.
Coming up to the kind of users like you and I who hammer at a very fast rate on our phones, there's so much to learn there.
Everything from the rate with which language is evolving, and the rate with which different languages are evolving.
Just how different each person's view of a given language is.
There is no real idea of what English is.
Everyone has their different blend.
Everyone has their different colloquialisms.
Everyone uses it slightly differently.
And, as we said earlier, given that we believe technology should adapt to you, we shouldn't enforce on you what our idea of English is.
We should allow our tech to get to know your version of English, to help you do what you're doing and say what you're saying better.
You know, culturally -- for example, I text with people who use a form of Hinglish -- that's a mix of Hindi and English.
There's quite a few modifications of words.
Then there's almost what I would consider, like, 10- to 12-year-old English, which has tons of truncations and incredible shorthand and 'IRL' and whatever.
They're just speaking in a way where they've said a whole sentence, and they've only used eight letters.
And, well, that's kind of impressive when you think about the fact that -- But it is an evolution of the language.
You and I don't speak in Shakespeare's English or the Queen's English.
Not every day. That's right.
No, and that's true.
And we have had discussions, and people have asked us in the past about our role as a communication technology.
Should we be involved in trying to redirect people's language towards something 'proper'? I think the answer is no.
I mean, by definition, this is their language.
Are emojis gonna replace --
That's a very good question.
...the A-to-Z alphabet?
[ Laughs ]
Watch this space.
It is very interesting watching the evolution of things like that, emoji, and now with things like GIFs and stickers.
They clearly have semantic content.
They are kind of linguistic elements.
Do they form part of a language in this way or not?
It's gonna be a very interesting area to watch.
Emoji are a very interesting example of that, yeah.
Joe Osborne from SwiftKey.
Thanks so much.
Thank you very much.
Imagine a phone that can last for days on just a single charge.
The invention of a new material may turn this into a reality.
Deepak Singh, an Assistant Professor of Physics at the University of Missouri Columbia and inventor of this technology, joins us via Google Hangout to discuss.
Thanks for being with us.
So, first of all, how is it possible?
It's the discovery of a new material, honeycomb-lattice magnetic material.
But we have to understand that it's a bit of a procedure.
It's only the beginning.
So, what we have found is a magnetic diode behavior.
So, this material has the tendency to exhibit a very low threshold... and that gives you dissipative energy of nanowire per square centimeter, which is at least three orders of magnitude smaller compared to a semiconductor diode or gemstone diode.
So, let me break this down for our audience that might not have advanced degrees.
So, first, your honeycomb lattice -- that's a change in the process of how we're building a battery?
Is that right?
No, we are not building the battery.
So, your cellphone or computer or any electronic device has a circuit, and it draws energy from the battery, and it dissipates that energy.
That's how you run out of battery.
So, batteries are still what it is, but what we are going to do is to make the electric circuit very efficient using this new material.
Instead of having metal semiconductor, we are going to make it out of this magnetic honeycomb lattice.
And that will consume much, much less energy compared to what we have right now, and that will lead to the prolonged battery life.
That's the idea.
So, what is the material that the honeycomb lattice is made from?
The magnetic honeycomb lattice is made of permalloy magnet.
The magnet is permalloy, a combination of nickel, iron, and a little bit of molecule.
It's a well-known magnet, very soft magnet.
And is that expensive to make?
Oh, no, no, no.
The procedure itself -- I mean, it's a nanostructure material.
It's not like a silicon, which can be mass produced very easily.
So there is a procedure.
So, in the beginning, yes, it will cost more than silicon, but you in the long term, if you mass produce, the cost will be much smaller.
Still higher than silicon, but then the benefits are immense.
So, if you pay $10 for something, and then you pay $20 for something, it's not...
So, you said that there are other parts of this that have to come along, that this is really just the first step, right?
So, as you're working on this process, are others working on the processes that are adjacent to where this electricity or where this energy is consumed?
So, my research is funded by DoE, and that's the reason that it happened.
And the funding has very specific goals, and that's science-based.
So I cannot divert the attention from studying the -- So, our goal is to study the underlying physics behind the magnetic honeycomb lattice, but by accident, we discovered this phenomena.
So that will go on.
And we cannot change that route.
But what we have done is to create a spin-off company, and that's where we are trying to make transistor and our crystal amplifier, and then we'll put them together.
So it will take a few years, and we are kind of working so that it's separate than research.
But, again, it's research, but not pure science.
Again, science is involved, but it's more sort of technology-oriented.
In addition to the honeycomb lattice, you still have to work on -- The start-up is gonna work on the adjacent parts, and how the whole thing comes together to consume less energy, right?
And your research through the University, and funded by the --
Department of Energy.
...Department of Energy, DoE, is to look at this specific.
So, what are you able to help the Department of Energy with once you finish your research on this?
So, the basic model of the Department of Energy is energy-efficient materials.
So, in that sense, this is precisely what we are doing.
It serves their model.
The Department of Energy supports a lot of basic research, which, eventually, many of them have helped us in designing new materials that help us every day.
Research is primarily aimed to understand the underlying physics of that material, which is why this magnetic material are [speaking indistinctly] and what kind of properties they have.
That's a separate focus.
Do you see this magnetic honeycomb lattice being used in other types of devices?
I mean, I know we started talking about cellphones, but the technology itself and what you're learning now, can that be applied more broadly?
Yes. That's an excellent question, thank you, Hari.
So, the diode can be immediately used as a small energy-harvesting device.
This is an emerging market, and a small energy-harvesting device has a very big future.
Imagine that you have a small thing, a palm-sized, very small harvesting device in your watch, cellphone.
And cellphone not to consume the battery, but cellphone has other functionality, right?
A camera and other things.
So, a small energy-harvesting device is the big area where we can apply this diode technology to act that way.
And it's quite suitable, because they need very low-threshold for this diode to charge the capacitor or battery, because they don't generate a lot of energy.
Once the diode, the transistor, and amplifier can all get on the same page in energy consumption, you're talking about all of our electronics having an incredibly long scale in the amount of how the energy is used -- or how much it's conserved, I should say.
That is correct, yes.
That's the right statement.
And so that's, what, three years, five years out?
Yeah, it will take time.
I would say five years.
Five years, we're going to estimate, but something on that time scale.
It will take a little time.
Any technology takes time.
So this is no exception.
And how far along are you on the start-up side of things to try to build this out versus the research that you're doing on the DoE side?
So, my research is going well.
On the start-up side, we have talked to some investors, and they seem interested, and there's a big company who is interested.
But we are looking for investors, also.
So if someone is interested, then we can communicate with them, and explain to them what we plan to do.
But it's, I would say, at early stage, very early.
Deepak Singh, Assistant Professor of Physics at the University of Missouri Columbia.
Thanks so much for joining us.
Thank you, Hari.
The North Carolina sweet-potato industry has pioneered a unique method of labeling its potatoes.
Instead of the unwanted stickers typically found on produce at the grocery store, these potatoes are branded using a laser.
Take a look.
Springtime, and another planting of sweet-potato seedlings.
Roughly 50,000 acres of farmland in North Carolina is devoted to sweet-potato production.
That's according to the North Carolina Department of Agriculture.
And it turns out that all of those acres produce enough sweet potatoes for the state to lead the nation in sweet-potato production.
It's also enough to make North Carolina the leading exporter of sweet potatoes.
So it's not surprising that North Carolina's sweet spot is part of a test into what could be the future of produce shopping in America.
It's called natural branding.
That's a low-energy carbon-dioxide laser.
It's marking a North Carolina sweet potato.
Oh, yes -- the warehouse is in the Netherlands.
The company is Eosta.
It's an organic-produce supplier.
We don't put any ink or anything into it.
What we do is, we take the pigment out of the outer layer of the skin of the fruit.
That's basically what happens.
And why do we do that?
It's because, before, we used to have to pack these sweet potatoes in plastic to differentiate them from the non-organic sweet potato.
'Cause the consumer, it's difficult to see whether this is an organic or a non-organic sweet potato.
So what happened was, is we were obliged to pack it in plastic.
Now, people who buy organic, and a lot of other people, they hate plastic.
So it doesn't make sense to do this.
So that's why we developed, together with the University of Valencia, and the company Laserfood, we developed this technology whereby we're actually putting a laser on, taking the pigment out of the skin of the fruit.
So there's a clear difference between the conventional sweet potato and the organic one.
We found those natural-branded sweet potatoes in Malmo, Sweden.
The grocery chain is called ICA.
It's a large chain in Europe.
Natural branding was approved for use in Australia and New Zealand.
It's been recently approved in Europe.
It has not been approved in the United States yet.
You might be wondering, why not just put a tiny sticker on the spud to show the price?
The skin of this apple is very smooth, so the sticker stays on.
When you put a sticker like this on a sweet potato, I would guess, 7 out of 10 times, the sticker would come off.
This method is working extremely well here in ICA.
We started testing this, and now many, many other supermarkets in Europe have come to us and want to do the same thing.
Because when people buy organic, they're very critical consumers.
They want to know, 'What have you done to my fruit?'
But the hatred of this is far bigger than the fact that you've taken some pigment out of the skin of their fruit.
And that's coming out of all the results, all the consumer tests, is that people love this because we're saving this.
The laser doesn't burn the potato skin.
It removes pigment from the skin.
That means the quality and the taste of the potato doesn't change.
I like the sweet potatoes, because it's very smooth and nice, and the flavor is -- it's very good.
The laser draws the programmed logo, which in this case says 'USA,' as well as, 'I love ICA,' the name of the supermarket.
The brand also includes the PLU number, which registers the price.
It helps us to have both conventional and organic in the same time in the store.
Because this is branding that sticks to the product, it doesn't fall off like a normal sticker would do.
You could also, of course, put these organic ones in a punnet with a lot of unnecessary plastic on it, but then it will be an environmental catastrophe to use so much plastic on a perfectly great product like this.
They all think that fiber-based packaging is better than plastic, but if they can choose, they would like to skip the packaging totally.
And that wraps it up for this time.
For more on science, technology, and innovation, visit our website, check us out on Facebook and Instagram, and join the conversation on Twitter.
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Until next time, I'm Hari Sreenivasan.
Thanks for watching.
Funding for this program is made possible by... ♪♪ ♪♪ ♪♪ ♪♪ ♪♪