To detect diseases earlier, let's speak bacteria's secret language
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0:02 - 0:03You don't know them.
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0:04 - 0:05You don't see them.
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0:06 - 0:08But they're always around,
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0:09 - 0:11whispering,
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0:11 - 0:13making secret plans,
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0:14 - 0:17building armies with millions of soldiers.
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0:19 - 0:21And when they decide to attack,
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0:21 - 0:24they all attack at the same time.
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0:27 - 0:29I'm talking about bacteria.
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0:29 - 0:30(Laughter)
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0:30 - 0:32Who did you think I was talking about?
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0:34 - 0:38Bacteria live in communities
just like humans. -
0:38 - 0:39They have families,
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0:39 - 0:40they talk,
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0:40 - 0:42and they plan their activities.
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0:42 - 0:45And just like humans, they trick, deceive,
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0:45 - 0:47and some might even cheat on each other.
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0:48 - 0:52What if I tell you that we can listen
to bacterial conversations -
0:52 - 0:56and translate their confidential
information into human language? -
0:56 - 1:01And what if I tell you that translating
bacterial conversations can save lives? -
1:03 - 1:04I hold a PhD in nanophysics,
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1:04 - 1:09and I've used nanotechnology
to develop a real-time translation tool -
1:09 - 1:11that can spy on bacterial communities
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1:11 - 1:14and give us recordings
of what bacteria are up to. -
1:16 - 1:18Bacteria live everywhere.
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1:18 - 1:20They're in the soil, on our furniture
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1:20 - 1:21and inside our bodies.
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1:22 - 1:27In fact, 90 percent of all the live cells
in this theater are bacterial. -
1:28 - 1:30Some bacteria are good for us;
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1:30 - 1:33they help us digest food
or produce antibiotics. -
1:33 - 1:35And some bacteria are bad for us;
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1:35 - 1:37they cause diseases and death.
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1:38 - 1:40To coordinate all
the functions bacteria have, -
1:40 - 1:42they have to be able to organize,
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1:42 - 1:44and they do that just like us humans --
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1:44 - 1:46by communicating.
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1:47 - 1:48But instead of using words,
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1:48 - 1:51they use signaling molecules
to communicate with each other. -
1:52 - 1:53When bacteria are few,
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1:53 - 1:56the signaling molecules just flow away,
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1:56 - 1:59like the screams of a man
alone in the desert. -
2:00 - 2:04But when there are many bacteria,
the signaling molecules accumulate, -
2:04 - 2:07and the bacteria start sensing
that they're not alone. -
2:07 - 2:09They listen to each other.
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2:09 - 2:12In this way, they keep track
of how many they are -
2:12 - 2:16and when they're many enough
to initiate a new action. -
2:17 - 2:20And when the signaling molecules
have reached a certain threshold, -
2:20 - 2:24all the bacteria sense at once
that they need to act -
2:24 - 2:25with the same action.
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2:26 - 2:30So bacterial conversation consists
of an initiative and a reaction, -
2:30 - 2:33a production of a molecule
and the response to it. -
2:35 - 2:38In my research, I focused on spying
on bacterial communities -
2:38 - 2:40inside the human body.
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2:40 - 2:42How does it work?
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2:42 - 2:44We have a sample from a patient.
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2:44 - 2:47It could be a blood or spit sample.
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2:47 - 2:50We shoot electrons into the sample,
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2:50 - 2:54the electrons will interact with any
communication molecules present, -
2:54 - 2:56and this interaction
will give us information -
2:56 - 2:58on the identity of the bacteria,
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2:58 - 3:00the type of communication
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3:00 - 3:02and how much the bacteria are talking.
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3:04 - 3:07But what is it like
when bacteria communicate? -
3:08 - 3:12Before I developed the translation tool,
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3:12 - 3:15my first assumption was that bacteria
would have a primitive language, -
3:15 - 3:19like infants that haven't developed
words and sentences yet. -
3:19 - 3:22When they laugh, they're happy;
when they cry, they're sad. -
3:22 - 3:23Simple as that.
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3:24 - 3:28But bacteria turned out to be nowhere
as primitive as I thought they would be. -
3:29 - 3:31A molecule is not just a molecule.
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3:31 - 3:34It can mean different things
depending on the context, -
3:34 - 3:37just like the crying of babies
can mean different things: -
3:37 - 3:39sometimes the baby is hungry,
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3:39 - 3:40sometimes it's wet,
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3:40 - 3:42sometimes it's hurt or afraid.
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3:42 - 3:45Parents know how to decode those cries.
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3:46 - 3:48And to be a real translation tool,
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3:48 - 3:51it had to be able to decode
the signaling molecules -
3:51 - 3:55and translate them
depending on the context. -
3:55 - 3:57And who knows?
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3:57 - 3:59Maybe Google Translate
will adopt this soon. -
3:59 - 4:01(Laughter)
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4:02 - 4:04Let me give you an example.
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4:04 - 4:08I've brought some bacterial data
that can be a bit tricky to understand -
4:08 - 4:09if you're not trained,
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4:09 - 4:10but try to take a look.
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4:12 - 4:13(Laughter)
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4:15 - 4:18Here's a happy bacterial family
that has infected a patient. -
4:20 - 4:22Let's call them the Montague family.
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4:24 - 4:27They share resources,
they reproduce, and they grow. -
4:28 - 4:30One day, they get a new neighbor,
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4:33 - 4:35bacterial family Capulet.
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4:35 - 4:36(Laughter)
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4:36 - 4:39Everything is fine,
as long as they're working together. -
4:40 - 4:43But then something unplanned happens.
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4:44 - 4:49Romeo from Montague has a relationship
with Juliet from Capulet. -
4:49 - 4:50(Laughter)
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4:51 - 4:54And yes, they share genetic material.
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4:54 - 4:56(Laughter)
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4:59 - 5:01Now, this gene transfer
can be dangerous to the Montagues -
5:01 - 5:05that have the ambition to be the only
family in the patient they have infected, -
5:05 - 5:07and sharing genes contributes
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5:07 - 5:10to the Capulets developing
resistance to antibiotics. -
5:12 - 5:16So the Montagues start talking internally
to get rid of this other family -
5:16 - 5:18by releasing this molecule.
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5:19 - 5:20(Laughter)
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5:21 - 5:22And with subtitles:
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5:22 - 5:24[Let us coordinate an attack.]
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5:24 - 5:25(Laughter)
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5:26 - 5:27Let's coordinate an attack.
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5:29 - 5:32And then everybody at once responds
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5:32 - 5:37by releasing a poison
that will kill the other family. -
5:37 - 5:38[Eliminate!]
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5:40 - 5:42(Laughter)
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5:43 - 5:48The Capulets respond
by calling for a counterattack. -
5:48 - 5:49[Counterattack!]
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5:49 - 5:50And they have a battle.
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5:52 - 5:57This is a video of real bacteria
dueling with swordlike organelles, -
5:57 - 5:58where they try to kill each other
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5:58 - 6:01by literally stabbing
and rupturing each other. -
6:03 - 6:07Whoever's family wins this battle
becomes the dominant bacteria. -
6:08 - 6:12So what I can do is to detect
bacterial conversations -
6:12 - 6:14that lead to different
collective behaviors -
6:14 - 6:15like the fight you just saw.
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6:16 - 6:19And what I did was to spy
on bacterial communities -
6:19 - 6:21inside the human body
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6:21 - 6:22in patients at a hospital.
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6:23 - 6:25I followed 62 patients in an experiment,
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6:25 - 6:29where I tested the patient samples
for one particular infection, -
6:29 - 6:32without knowing the results
of the traditional diagnostic test. -
6:32 - 6:37Now, in bacterial diagnostics,
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6:37 - 6:39a sample is smeared out on a plate,
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6:39 - 6:42and if the bacteria grow within five days,
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6:42 - 6:44the patient is diagnosed as infected.
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6:46 - 6:49When I finished the study
and I compared the tool results -
6:49 - 6:52to the traditional diagnostic test
and the validation test, -
6:52 - 6:53I was shocked.
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6:53 - 6:57It was far more astonishing
than I had ever anticipated. -
6:58 - 7:00But before I tell you
what the tool revealed, -
7:00 - 7:03I would like to tell you about
a specific patient I followed, -
7:03 - 7:04a young girl.
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7:05 - 7:06She had cystic fibrosis,
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7:06 - 7:10a genetic disease that made her lungs
susceptible to bacterial infections. -
7:11 - 7:13This girl wasn't a part
of the clinical trial. -
7:13 - 7:16I followed her because I knew
from her medical record -
7:16 - 7:18that she had never had
an infection before. -
7:19 - 7:22Once a month, this girl
went to the hospital -
7:22 - 7:24to cough up a sputum sample
that she spit in a cup. -
7:25 - 7:28This sample was transferred
for bacterial analysis -
7:28 - 7:30at the central laboratory
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7:30 - 7:33so the doctors could act quickly
if they discovered an infection. -
7:34 - 7:37And it allowed me to test my device
on her samples as well. -
7:37 - 7:41The first two months I measured
on her samples, there was nothing. -
7:42 - 7:43But the third month,
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7:43 - 7:46I discovered some bacterial
chatter in her sample. -
7:46 - 7:50The bacteria were coordinating
to damage her lung tissue. -
7:51 - 7:55But the traditional diagnostics
showed no bacteria at all. -
7:56 - 7:58I measured again the next month,
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7:58 - 8:01and I could see that the bacterial
conversations became even more aggressive. -
8:02 - 8:05Still, the traditional
diagnostics showed nothing. -
8:06 - 8:10My study ended, but a half a year later,
I followed up on her status -
8:10 - 8:13to see if the bacteria
only I knew about had disappeared -
8:13 - 8:15without medical intervention.
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8:16 - 8:18They hadn't.
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8:18 - 8:21But the girl was now diagnosed
with a severe infection -
8:21 - 8:22of deadly bacteria.
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8:24 - 8:28It was the very same bacteria
my tool discovered earlier. -
8:29 - 8:31And despite aggressive
antibiotic treatment, -
8:31 - 8:34it was impossible
to eradicate the infection. -
8:35 - 8:38Doctors deemed that she would not
survive her 20s. -
8:40 - 8:43When I measured on this girl's samples,
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8:43 - 8:45my tool was still in the initial stage.
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8:45 - 8:47I didn't even know
if my method worked at all, -
8:47 - 8:50therefore I had an agreement
with the doctors -
8:50 - 8:52not to tell them what my tool revealed
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8:52 - 8:54in order not to compromise
their treatment. -
8:54 - 8:57So when I saw these results
that weren't even validated, -
8:57 - 8:58I didn't dare to tell
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8:58 - 9:01because treating a patient
without an actual infection -
9:01 - 9:04also has negative
consequences for the patient. -
9:05 - 9:07But now we know better,
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9:07 - 9:10and there are many young boys
and girls that still can be saved -
9:11 - 9:15because, unfortunately,
this scenario happens very often. -
9:15 - 9:16Patients get infected,
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9:16 - 9:20the bacteria somehow don't show
on the traditional diagnostic test, -
9:20 - 9:24and suddenly, the infection breaks out
in the patient with severe symptoms. -
9:24 - 9:26And at that point, it's already too late.
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9:27 - 9:31The surprising result
of the 62 patients I followed -
9:31 - 9:33was that my device
caught bacterial conversations -
9:33 - 9:36in more than half of the patient samples
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9:36 - 9:39that were diagnosed as negative
by traditional methods. -
9:40 - 9:43In other words, more than half
of these patients went home thinking -
9:43 - 9:45they were free from infection,
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9:45 - 9:48although they actually carried
dangerous bacteria. -
9:49 - 9:52Inside these wrongly diagnosed patients,
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9:52 - 9:55bacteria were coordinating
a synchronized attack. -
9:56 - 9:57They were whispering to each other.
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9:58 - 10:00What I call "whispering bacteria"
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10:00 - 10:03are bacteria that traditional
methods cannot diagnose. -
10:03 - 10:07So far, it's only the translation tool
that can catch those whispers. -
10:08 - 10:12I believe that the time frame
in which bacteria are still whispering -
10:12 - 10:15is a window of opportunity
for targeted treatment. -
10:16 - 10:19If the girl had been treated
during this window of opportunity, -
10:19 - 10:21it might have been possible
to kill the bacteria -
10:21 - 10:23in their initial stage,
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10:23 - 10:25before the infection got out of hand.
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10:27 - 10:31What I experienced with this young girl
made me decide to do everything I can -
10:31 - 10:33to push this technology into the hospital.
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10:34 - 10:35Together with doctors,
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10:35 - 10:38I'm already working
on implementing this tool in clinics -
10:38 - 10:40to diagnose early infections.
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10:41 - 10:45Although it's still not known
how doctors should treat patients -
10:45 - 10:46during the whispering phase,
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10:46 - 10:50this tool can help doctors
keep a closer eye on patients in risk. -
10:51 - 10:54It could help them confirm
if a treatment had worked or not, -
10:54 - 10:57and it could help answer simple questions:
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10:57 - 10:58Is the patient infected?
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10:58 - 11:00And what are the bacteria up to?
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11:01 - 11:03Bacteria talk,
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11:03 - 11:05they make secret plans,
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11:05 - 11:08and they send confidential
information to each other. -
11:08 - 11:11But not only can we catch them whispering,
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11:11 - 11:13we can all learn their secret language
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11:13 - 11:16and become ourselves bacterial whisperers.
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11:17 - 11:19And, as bacteria would say,
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11:20 - 11:23"3-oxo-C12-aniline."
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11:24 - 11:25(Laughter)
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11:25 - 11:26(Applause)
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11:26 - 11:27Thank you.
- Title:
- To detect diseases earlier, let's speak bacteria's secret language
- Speaker:
- Fatima AlZahra’a Alatraktchi
- Description:
-
Bacteria "talk" to each other, sending chemical information to coordinate attacks. What if we could listen to what they were saying? Nanophysicist Fatima AlZahra'a Alatraktchi invented a tool to spy on bacterial chatter and translate their secret communication into human language. Her work could pave the way for early diagnosis of disease -- before we even get sick.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 11:41
Oliver Friedman edited English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Oliver Friedman edited English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Oliver Friedman edited English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Brian Greene approved English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Brian Greene edited English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Camille Martínez accepted English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Camille Martínez edited English subtitles for To detect diseases earlier, let's speak bacteria's secret language | ||
Camille Martínez edited English subtitles for To detect diseases earlier, let's speak bacteria's secret language |