Browse content similar to 07/05/2016. Check below for episodes and series from the same categories and more!
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This week, a medical special with a professor plugging himself into | :00:00. | :00:18. | |
everything, and optimists -- octopus fights dementia and a cat that does | :00:19. | :00:21. | |
everything. Every single person | :00:22. | :00:37. | |
on the planet is different. Looks different, | :00:38. | :00:45. | |
likes different things, Those genes can also decide | :00:46. | :00:47. | |
which diseases each But of course, for most of history, | :00:48. | :01:00. | |
genetics was unknown territory. This is the Royal Society | :01:01. | :01:10. | |
of Medicine in central London. And this institution has been at | :01:11. | :01:13. | |
the forefront of promoting and the sharing of information | :01:14. | :01:16. | |
throughout the medical community. And in 2003, that community received | :01:17. | :01:21. | |
an explosion of information. The human genome project | :01:22. | :01:28. | |
was declared complete. And this knowledge paved the way | :01:29. | :01:33. | |
for a far deeper understanding of And these days, the talk is all | :01:34. | :01:38. | |
about personalised medicine. But how useful is this genetic | :01:39. | :01:48. | |
information at the moment? Well, after meeting a leading | :01:49. | :01:53. | |
geneticist in San Francisco, Jane decided to embark on | :01:54. | :01:56. | |
her own genetic journey of If you could unlock all | :01:57. | :02:00. | |
of the secrets of your health, how long you will live, what diseases | :02:01. | :02:09. | |
you were at risk of developing, Stanford's genetics | :02:10. | :02:12. | |
department is hoping that this It is studying 100 healthy people | :02:13. | :02:16. | |
and sequencing their DNA to see if they can predict when they will | :02:17. | :02:22. | |
get sick before they do. Leading | :02:23. | :02:36. | |
the research is Professor Michael I'm always keeping | :02:37. | :02:38. | |
my devices very well charged. He is a one-man tracking machine. | :02:39. | :02:44. | |
Along with sequencing his genome, | :02:45. | :02:47. | |
he wears nine different devices every day to monitor his health | :02:48. | :02:51. | |
outputs, including three smart I have a continual glucose monitor | :02:52. | :02:55. | |
that sits just on top of my skin, that continuously | :02:56. | :03:00. | |
measures my glucose levels. For Professor Snyder, the | :03:01. | :03:05. | |
experiment has already been a He found he had | :03:06. | :03:07. | |
a genetic predisposition to type 2 diabetes, despite showing no typical | :03:08. | :03:13. | |
signs of the condition. My genes predicted a number | :03:14. | :03:18. | |
of risks, And as we are actually doing all of | :03:19. | :03:21. | |
these medical analyses, we discovered that | :03:22. | :03:26. | |
my sugar which have been running on perfectly fine actually shot through | :03:27. | :03:28. | |
the roof, and basically to the point The professor keeps track | :03:29. | :03:32. | |
of his genome It looks complex, | :03:33. | :03:41. | |
but it is showing changes happening The outside affects my gene | :03:42. | :03:46. | |
representation of my genome, and all the different changes I have | :03:47. | :03:54. | |
relative to the inner line here. I think we will see a world where | :03:55. | :04:11. | |
this will be relayed to your smartphone and the information will | :04:12. | :04:16. | |
show up and get integrated. Quite frankly, it will go to your | :04:17. | :04:17. | |
physician as well. Inspired by Professor Snyder, | :04:18. | :04:20. | |
I signed up for 23 and Me. It is one of the better-known | :04:21. | :04:22. | |
and cheap services that offers you Rather than looking | :04:23. | :04:25. | |
at your whole genome, it looks of the ones that are significant, | :04:26. | :04:33. | |
using the latest research. Simply send a off sample, | :04:34. | :04:36. | |
and you're left with this. It is getting back 3 billion bits | :04:37. | :04:42. | |
of info, I received 100. These included risk factors | :04:43. | :04:46. | |
for indicators of Alzheimer's disease and ovarian and breast | :04:47. | :04:50. | |
cancer syndrome. The roles of 41 genetic variants | :04:51. | :04:57. | |
that produced different things from I was lucky to find out I didn't | :04:58. | :05:00. | |
have anything significant to report. In fact, the most interesting | :05:01. | :05:08. | |
thing I found out was I was I've changed my diet accordingly, | :05:09. | :05:11. | |
and it has made This small discovery increase | :05:12. | :05:14. | |
my appetite for more genetic After reading forums, | :05:15. | :05:17. | |
I discovered a site which said it can unlock more data | :05:18. | :05:22. | |
from 23 and Me for only $5. So I went for it, | :05:23. | :05:30. | |
and rather wished I hadn't. In ten minutes I was flooded with | :05:31. | :05:35. | |
information on 20,000 genomes. These are marked | :05:36. | :05:39. | |
as not said, good or bad. Instead of nothing to report, I seem | :05:40. | :05:43. | |
to have hundreds of bad genes, and I have a high risk of developing type | :05:44. | :05:54. | |
2 diabetes and various cancer. So I put my results to | :05:55. | :05:57. | |
a clinical geneticists. I'm absolutely baffled by the | :05:58. | :05:59. | |
information that is in this report. Do you find any | :06:00. | :06:05. | |
of this information useful to me? As a clinical geneticist who would | :06:06. | :06:08. | |
be looking at your risk of disease, I would say there is nothing | :06:09. | :06:18. | |
in here that we would find clinically actionable, in terms | :06:19. | :06:22. | |
of setting up screening or It may tell you some things | :06:23. | :06:24. | |
about where you are Adam explained the percentages | :06:25. | :06:27. | |
that scared me actually showed that these genes were fairly common | :06:28. | :06:32. | |
in the general population. It's also just one genetic aspect | :06:33. | :06:36. | |
out of 3 billion molecules that make up your genome, and | :06:37. | :06:41. | |
and that single molecule is not going to change that much about you | :06:42. | :06:46. | |
in this context. What do you think my GP would say | :06:47. | :06:52. | |
to me if I brought them this? I think your GP was struggle to find | :06:53. | :06:55. | |
anything in here that they would A more comprehensive insight | :06:56. | :06:59. | |
into our genes may come from the NHS's 100,000 | :07:00. | :07:06. | |
Genome project. Participants include people with | :07:07. | :07:09. | |
rare diseases and their families. The NHS wants us to form the base | :07:10. | :07:12. | |
for a genomic medical service, potentially offering new and more | :07:13. | :07:16. | |
effective treatments and diagnoses. We will be in Rome -- world where | :07:17. | :07:39. | |
people get their gene is sequenced before they are born. Many times you | :07:40. | :07:46. | |
see mutations and you're not sure whether they are damaging not and | :07:47. | :07:47. | |
that's what makes it tricky. While it may be many years before | :07:48. | :07:50. | |
we can access useful information | :07:51. | :07:52. | |
about our genomes cheaply on a smartphone, a future when | :07:53. | :07:54. | |
genes play a greater role in the healthcare seems increasingly | :07:55. | :08:00. | |
possible. Well that was Jen, | :08:01. | :08:02. | |
and this is Tony Young who was the leader of innovation at the NHS. | :08:03. | :08:04. | |
You're also a surgeon. What do you make of giving what | :08:05. | :08:07. | |
seems a load of raw genetic data to Because Jen seemed quite freaked | :08:08. | :08:13. | |
out. I can understand that, | :08:14. | :08:19. | |
and there are more and more of these offerings coming | :08:20. | :08:22. | |
from the private sector around doing some element of your genomic | :08:23. | :08:26. | |
screening. And when you have that And the experience Jen had was one | :08:27. | :08:32. | |
of confusion, and there is But it's not just the public who is | :08:33. | :08:39. | |
confused. Many clinicians as well don't know | :08:40. | :08:50. | |
what to do with large swathes of And that is one of the reasons in | :08:51. | :08:53. | |
2012, our Prime Minister launched 100,000 Genome project, which was | :08:54. | :08:57. | |
a world-first, really. It was a larger-scale effort than the country | :08:58. | :09:00. | |
had undertaken to that point, to screen 100,000 whole genomes, and | :09:01. | :09:07. | |
through the population to look at both cancer risk and rare genetic | :09:08. | :09:10. | |
disorders, so we at the NHS could say, the results of confusing data | :09:11. | :09:13. | |
but actually, we're going to take Not relying on a commercial company | :09:14. | :09:16. | |
to give you some advice on the risk of diabetes or our son | :09:17. | :09:21. | |
is that may or may not be relevant. We can crack and solve some of the | :09:22. | :09:39. | |
big challenges we face and genomics is one of them. | :09:40. | :09:42. | |
We learned very recently that Google is using | :09:43. | :09:45. | |
its Deep Mind project, machine learning and artificial intelligence | :09:46. | :09:47. | |
systems, to analyse health data from the NHS patients. | :09:48. | :09:53. | |
The programme that you mentioned, with Deep Mind, is all | :09:54. | :09:57. | |
So patients are going to hospital and have an altered blood test or | :09:58. | :10:03. | |
a other test, but the early stages of that. | :10:04. | :10:09. | |
And you are still very well and your kidneys are very well, | :10:10. | :10:12. | |
But you're waiting for a human to look at that blood test result, and | :10:13. | :10:18. | |
the whole point of using a machine learning and artificial intelligence | :10:19. | :10:21. | |
is can we use this to actually pick that up much earlier to prevent | :10:22. | :10:26. | |
that person getting kidney damage and renal failure? | :10:27. | :10:30. | |
The data is there, but we're just not using it. | :10:31. | :10:32. | |
So we can deliver safer, better care. | :10:33. | :10:34. | |
And we have one of the biggest and best data sets but it's how we keep | :10:35. | :10:50. | |
it safe and secure. We have a national data Guardian to make sure | :10:51. | :10:54. | |
those things go forward and all data is encrypted so nope patient | :10:55. | :11:00. | |
identifiable information is shared. It's only the clinician who can know | :11:01. | :11:06. | |
it's their patient in front of them with that data and that's the key | :11:07. | :11:16. | |
thing. Hello. I would love to say it was the week that the inventor of | :11:17. | :11:21. | |
bitcoin was unmasked but after years, an Australian claim to offer | :11:22. | :11:30. | |
proof to three media outlets that he was Satoshi Nakamoto, the mysterious | :11:31. | :11:34. | |
inventor of the currency. That is until lots of people said he hadn't. | :11:35. | :11:39. | |
He has backed out from providing further evidence he said would | :11:40. | :11:43. | |
confirm his claim, saying sorry and goodbye. At IBM, they made a | :11:44. | :11:50. | |
functioning quantum processor available to the public online. Many | :11:51. | :11:56. | |
believe it will pave the way for next gen machines, capable of faster | :11:57. | :12:00. | |
calculations than those of today. Scared of going under the knife? | :12:01. | :12:08. | |
Have no fear, Robo surgeon is here. Researchers in America have built a | :12:09. | :12:13. | |
system that can autonomously so soft tissue. Having successfully operated | :12:14. | :12:18. | |
on a live papers-macro in testing, they say it can be safer and more | :12:19. | :12:22. | |
precise than a human surgeon. The winner for the tech PR Stunt of the | :12:23. | :12:30. | |
Week Award goes to "catterbox". Sick of cats sounding like cats? The | :12:31. | :12:36. | |
custom caller mixes me hows with various phrases giving would-be | :12:37. | :12:40. | |
purring felines a would-be voice. Town-macro. Wow! How purr-fectly | :12:41. | :12:47. | |
pointless. Over 47 million people in the world | :12:48. | :12:54. | |
are suffering from dementia, and an ageing population means that that | :12:55. | :12:58. | |
figure is only likely to increase. So I've been looking at | :12:59. | :13:03. | |
the technology, hoping to better the This week, Sea Hero launches. | :13:04. | :13:07. | |
Designed as a game to appeal to gamers, | :13:08. | :13:15. | |
beneath the surface is real science. While you may in think of | :13:16. | :13:20. | |
the main feature being memory loss, one of the earliest things to be | :13:21. | :13:23. | |
affected is actually spatial So after collecting data | :13:24. | :13:27. | |
about how healthy-minded players navigate the game, and comparing | :13:28. | :13:32. | |
that to how someone with dementia plays, | :13:33. | :13:36. | |
a benchmark can be created to both Just two minutes spent | :13:37. | :13:39. | |
on the app will generate the same amount of data as five | :13:40. | :13:46. | |
hours in a research lab. The design | :13:47. | :13:54. | |
of the game was built from the perspective of the scientists, | :13:55. | :13:57. | |
and what data they needed to understand how people would navigate | :13:58. | :14:03. | |
in 3-D space. This should provide not only a | :14:04. | :14:05. | |
standardised measure of quantifying someone's condition, but also | :14:06. | :14:07. | |
the ability to do so remotely. The key with this research is | :14:08. | :14:18. | |
understanding what goes wrong with So having understood that with this | :14:19. | :14:21. | |
experiment, and this big set of data, | :14:22. | :14:25. | |
we'll armed to go on and do new drug trials, for example, and to | :14:26. | :14:27. | |
investigate particular drugs and how they will have a good idea | :14:28. | :14:32. | |
as to how people navigate. The hope is that now in a crowded | :14:33. | :14:38. | |
market of smartphone games, the app will appeal to enough people | :14:39. | :14:44. | |
to make this mission possible. To bring them back to his beloved | :14:45. | :14:49. | |
Sea Hero. But for the millions this will be | :14:50. | :15:05. | |
too late for, there are other ways technology aims to promote | :15:06. | :15:09. | |
independent living for as long as possible. Like this remotely | :15:10. | :15:13. | |
accessible camera setup. I showed you a while ago and app that | :15:14. | :15:19. | |
re-purpose is smartphones and tablets to turn them into security | :15:20. | :15:23. | |
cameras, but there are many things that can be done with a setup like | :15:24. | :15:28. | |
that and one is to be able to monitor seniors. It's not just about | :15:29. | :15:33. | |
watching with a camera, which many may not want to have done to them, | :15:34. | :15:37. | |
but there are a lot of sensors that come with it. There are entry and | :15:38. | :15:44. | |
motion sensors, full sensors and even a smart pillbox. One of the | :15:45. | :15:49. | |
clever things is that it keeps track of someone's day to day habits so | :15:50. | :15:53. | |
that if they change, you will receive an alert that they could be | :15:54. | :15:58. | |
a problem. Of course, it big worry for loved ones is the risk of their | :15:59. | :16:04. | |
relative falling. So this aims to help. This pair of sensor embedded | :16:05. | :16:08. | |
insoles aims to provide smartphone alerts to chosen contacts should | :16:09. | :16:14. | |
wear red take a tumble. They are also providing feedback. Pressing | :16:15. | :16:22. | |
just here soars -- sort of feels like the vibration of an electric | :16:23. | :16:25. | |
toothbrush and that should help those with sensory issues called by | :16:26. | :16:31. | |
conditions like diabetes, MS or Parkinson's disease. For those whose | :16:32. | :16:35. | |
needs are more focused on keeping and engaged mind, this app provides | :16:36. | :16:40. | |
stimulating games for those with the early stages of dementia as well as | :16:41. | :16:45. | |
a place to log their life story, find exercise and nutrition tips and | :16:46. | :16:49. | |
a tool option to set reminders and to do lists. | :16:50. | :16:51. | |
Many diseases leave markers in the blood. Even detecting these can be | :16:52. | :17:07. | |
tricky and slow. Eight bayou marker may only be there in a tiny amount | :17:08. | :17:12. | |
and then your blood has to be collected and sent to a central | :17:13. | :17:16. | |
pathology lab. The whole thing can take hours or days. But here is | :17:17. | :17:19. | |
something that can take minutes. First, take some blood which may or | :17:20. | :17:30. | |
may not smell like blackcurrant cordial and dip in some of this | :17:31. | :17:37. | |
magic test strip. The blood creeps up the tiny capillaries ready for | :17:38. | :17:42. | |
testing. Pop it into the box, at a cheap smartphone fitted with an even | :17:43. | :17:49. | |
cheaper magnifying lens and an LED. Then add some testing liquids which | :17:50. | :18:02. | |
wash away the blood leaving only the bio-marker which glows. The brighter | :18:03. | :18:07. | |
the image the more the clinician needs to make a judgment on your | :18:08. | :18:12. | |
condition. This is another example of how smartphones, even low-cost | :18:13. | :18:17. | |
ones, can be used for diagnostics either in the developing world or | :18:18. | :18:23. | |
even in hospitals here, too. Let's look at heart attack. There is a | :18:24. | :18:30. | |
bio-marker adopted where heart attacks show chest pain. That is | :18:31. | :18:36. | |
responsible for around 1 million patients every year. Only a quarter | :18:37. | :18:44. | |
have a heart problem. Those patients had to stay overnight before the | :18:45. | :18:50. | |
test which takes so long. But with this, you can do things quicker. | :18:51. | :18:59. | |
This flu row strip has the same refractive index as water which | :19:00. | :19:03. | |
means it comes completely transparent when filled with a clear | :19:04. | :19:07. | |
liquid giving a brilliantly clearly quid of the offending bio-markers, | :19:08. | :19:14. | |
even at low levels. Crucially, it detects them at such low levels | :19:15. | :19:17. | |
which is what has been difficult up to now. Smartphone is a cheap auto | :19:18. | :19:25. | |
electronic component which can do pretty much the same job as other | :19:26. | :19:31. | |
systems and equipment sitting in pathology labs and that it is where | :19:32. | :19:37. | |
it becomes powerful. It is a level and miniaturised version of | :19:38. | :19:42. | |
sophisticated lab equipment -- a clever. Last week, we met Sir James | :19:43. | :19:52. | |
Dyson as he went to war on noisy, hot hairdryers with his own | :19:53. | :19:55. | |
invention. Now it's time to have a little more leisurely look around | :19:56. | :19:56. | |
his HQ. These are things that mean a lot to | :19:57. | :20:09. | |
me you. They mean something. A Harrier jump jet. I had a special | :20:10. | :20:15. | |
model built for me. It's heavy actually. That's pretty heavy. The | :20:16. | :20:22. | |
one out there is only five tonnes. It's very light. This one is carbon | :20:23. | :20:29. | |
fibre, one piece of carbon fibre than in the early 60s. There it was | :20:30. | :20:36. | |
in the 60s and it's a brilliant edition invention. That was my | :20:37. | :20:42. | |
favourite Walkman, an underwater one. I was a great fan in the early | :20:43. | :20:50. | |
days. That is a lovely Sony phone. A very good system. Nice and easy into | :20:51. | :20:59. | |
your pocket. A nice size. This was developed in the early 50s, | :21:00. | :21:05. | |
immediately after the war and it uses hydraulics for the steering and | :21:06. | :21:12. | |
brakes. Very high end cards are using the same system. It's taken | :21:13. | :21:17. | |
years to catch up. So the thing that attracts you is the genius in | :21:18. | :21:22. | |
engineering? Yes, the genius in that. What would you say your role | :21:23. | :21:29. | |
is in now? I can't see you taking a hands-off role. No, I was with the | :21:30. | :21:36. | |
engineers working on new product so I don't build prototype -- | :21:37. | :21:41. | |
prototypes any more but the engineers do. We discuss the design | :21:42. | :21:46. | |
and discuss new technology and how to use it. How many other new ideas | :21:47. | :21:53. | |
of yours? Very few because I have lots of bright young people with the | :21:54. | :21:58. | |
average age of 26 and they are far cleverer than I am. I am like an old | :21:59. | :22:04. | |
tutor going around encouraging them. The vacuum cleaner, I built over | :22:05. | :22:12. | |
5000 prototypes before I got it right. How many? 5100 plus. How long | :22:13. | :22:23. | |
did it take? Three years. I was doing to a day or something like | :22:24. | :22:27. | |
that and testing them then building another one and another one. I was | :22:28. | :22:30. | |
covered in dust but enjoying myself enormously. I asked Twitter what | :22:31. | :22:39. | |
Twitter would like to ask you. My favourite for the hand-held vacuum | :22:40. | :22:43. | |
cleaner, are there plans to bring out the cowboy style holster? If | :22:44. | :22:47. | |
that's what everyone wants, we'll do a holster. More seriously, what | :22:48. | :22:54. | |
inspired you to become an engineer and what ideas inspire you now? I | :22:55. | :22:59. | |
started off being a designer and I realised that just designing the | :23:00. | :23:05. | |
outside of a problem -- product was deeply unsatisfying. You want to | :23:06. | :23:09. | |
understand how its work, how it's made. I wanted to be involved in the | :23:10. | :23:15. | |
whole thing. I went off to an engineering company and it took | :23:16. | :23:19. | |
seven years to learn engineering. Did want to be an engineer at the | :23:20. | :23:24. | |
beginning. I discovered I had to be and then I enjoyed it. What would | :23:25. | :23:30. | |
you say to the next generation of engineers to inspire them if they're | :23:31. | :23:34. | |
trying to decide whether to carry on with it? It's a good point because | :23:35. | :23:39. | |
we're not producing enough engineers. We need more. I would say | :23:40. | :23:44. | |
that engineering is exciting and fulfilling and an -- engineers are | :23:45. | :23:49. | |
the happiest people. Is exciting even though you have failure. You | :23:50. | :23:55. | |
have exciting breakthroughs and you're making real things for people | :23:56. | :23:58. | |
and satisfying their needs. Thanks for having us. Thank you. That was | :23:59. | :24:05. | |
Sir James Dyson. Who knows what secrets are lurking in that | :24:06. | :24:14. | |
building? That if it from us. Thanks for watching and we'll see you soon. | :24:15. | :24:20. |