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