Luyện nói tiếng Anh bằng Shadowing qua video: Brain Balls | Radiolab Podcast
Chọn chế độ luyện tập
Mỗi chế độ mở một phòng luyện tập toàn màn hình.
771 câu
Nếu các câu quá ngắn hoặc quá dài, hãy bấm Edit để chỉnh sửa.
1
Oh, wait, you're listening.
2
Okay.
3
All right.
4
Okay.
5
All right.
6
You're listening to Radiolab.
7
Radiolab. From WNYC.
8
See?
9
See?
10
Yeah.
11
Okay, Lulu.
12
Yeah.
13
We're going to start today.
14
Mm-hmm.
15
Back in 2010 in a lab in Vienna.
16
Oh, jumping right in.
17
Yeah.
18
Just picture sort of a lab with microscopes, computers, experiments.
19
And off in one corner.
20
Hello.
21
Hi, how's it going?
22
Wearing glasses and a white lab coat is this scientist named Dr. Madeline Lancaster.
23
Call me Madeline.
24
Madeline has just finished her PhD and moved to Austria, just joined the lab to start her postdoc research.
25
So still sort of making friends.
26
Still trying to make a good impression.
27
Getting to know people, you know.
28
And one of the first things her boss asked her to
29
do was something called a screen just basically looking for specific genes in mouse neural stem cells.
30
So that's like baby brain cells of mice?
31
Yeah.
32
Now, she hadn't done exactly this kind of gene screen before.
33
And that's probably why I didn't really, you know, I was kind of naive about it all.
34
Hmm.
35
But she got to work.
36
You put this enzyme on, it just cuts those proteins.
37
Preparing the baby mouse cells.
38
The cells all become loose and apart from each other.
39
That part she'd actually done before, so, you know, easy enough.
40
Yeah, but.
41
Then, something she hadn't done before, she needed to get those cells to stick flat to the glass bottom of her dish
42
so that she could do that screen.
43
And to do that, she needed to use special organic proteins as a glue.
44
And I hadn't, they hadn't come in yet.
45
I'd ordered them, but they hadn't come in yet.
46
And instead of just, you know, waiting for them to arrive.
47
I don't know.
48
I was so anxious to do the experiment.
49
She decided to improvise.
50
And so I just kind of like rummaged through the freezer.
51
Found a random tube of glue-like proteins.
52
I don't know how old they were.
53
And anyway, and I used those.
54
Squirted it on the dishes, pipetted in the cells, popped them in the incubator, and went home for the night.
55
Next morning.
56
Came in.
57
Took a look in her Petri dishes, hoping to see a nice, clean, clear layer of cells.
58
Like flat on the dish.
59
But instead, everything in there was...
60
Really cloudy.
61
Hmm.
62
Shouldn't be cloudy.
63
Cloudy means those cells are floating freely around in there, which means that those tubes of protein glue she used...
64
You know, we're no good, and the cells hadn't stuck.
65
And if the cells aren't stuck in the protein, that means they're probably dead.
66
Yeah, all the cells are dead.
67
I'll just throw it away.
68
And I don't know why I did this, but...
69
Right before she tossed it, she thought...
70
You know, but I'll check it.
71
I'll just take a peek.
72
Why not?
73
So she slides these cloudy dishes under the microscope, peers into the eyepiece, and in the circle of light, she sees...
74
These weird.. blobs.
75
The cells weren't dead.
76
They were...
77
Alive and healthy and...
78
Plumped into three or four blobs.
79
Huh.
80
Yeah, can you as vividly as you can describe them?
81
I mean, they're like a sort of beige color, like an off-white tiny...
82
About the size of a grain of sand.
83
Or these floating balls of cells. And she's like, huh.
84
Weird.
85
So she zeroes in on one of these blobs, turns the dial on the microscope to zoom in until she's looking basically inside the blob.
86
And that's when she sees a tube, a tube.
87
Yeah.
88
So she's like looking down into like one end of the tube.
89
So it looks almost like a donut shape.
90
Had you ever seen anything like that before?
91
No. No. Huh.
92
Yeah.
93
I mean, as far as she knew, if the cells weren't in that protein stuff, stuck, you know, flat to the bottom,
94
they should sort of die and fall apart and make a big random mess.
95
But these ones seem to be coming together to make this shape.
96
So she gets up from the microscope and starts.
97
Sort of going around the lab a little bit subtly at first, kind of just like, hey,
98
has anybody ever like seen cells do funny things, you know?
99
clump up together.
100
And everybody was just sort of like, oh, well, if they're supposed to be laying flat, if they're not laying flat, you screwed it up.
101
Like, they just weren't that interested.
102
No. So I just kind of like put it in formaldehyde, put it away in the fridge for a little while and was like, okay.
103
Let's try this gene screen again.
104
But this time, no floaty clumps, gonna get those cells to stick flat on the bottle.
105
And eventually she decides to try something new.
106
This thing that I had read about called Matrigel.
107
Basically, cellular crazy glue.
108
Like, she's not taking any chances.
109
I'm just going to put a whole bunch in my dish.
110
So she squirts a lot of it on there.
111
Okay.
112
She puts her cells on top. And again.
113
Pops them in the incubator, crosses her fingers, and goes home for the night.
114
She comes back in the morning.
115
Yeah, same thing.
116
You go to the incubator, you take it out of the incubator, you look at it, and I was like, okay, this is weird.
117
Once again.
118
There's a bunch of stuff floating in there.
119
Huh.
120
I was like, okay, well, the Matrigel didn't work like it was supposed to.
121
Again, it seemed like the cells had started clumping together.
122
And that's when I then took them, put them on the tissue culture microscope, looked down the eyepiece, and again...
123
There they were.
124
Funny-shaped balls.
125
These ones were also beige-ish.
126
Off-white kind of color.
127
But they were bigger.
128
And they sort of have, like, bulges coming off of them.
129
And this time, when she looked inside, she saw full-on...
130
Architecture.
131
There was a tube, but also...
132
A little circle, sort of oblong-shaped thing.
133
And a fat layer of tightly packed cells...
134
All lined up around a space in the middle.
135
They were making structures, they were making things.
136
Kind of like what cells do as an embryo is developing, which to Madeline didn't make any sense.
137
Everybody had always taught me that cells need things coming from other tissues in the body,
138
you know, of the embryo that are necessary for building that embryo.
139
And here was a situation where nothing was telling them what to do because they'd been completely taken out of the embryo.
140
And they were like forming structures with no instructions.
141
She's like, oh my God, like this is like there are things developing here. But toward what?
142
Well, to Madeline, it kind of looked like...
143
They were building a brain.
144
So these are neural stem cells, which inside a developing mouse...
145
Starts out as a sheet of cells, and then they fold up and close and form a tube.
146
And then the neural tube elongates, and that becomes the spinal cord.
147
One end of it balloons out, and that becomes the brain.
148
And that's what it looked like the cells in Madeline's dish were doing.
149
It seemed like these cells on their own were starting to try to make themselves into a mouse brain.
150
At the time, yeah, at the time, I was just kind of confused.
151
So she showed some other people around the lab what she'd seen.
152
I showed some of these structures.
153
The tubes, the circles, the lines, but...
154
Several people in the lab were just kind of, I think they were just totally bored.
155
They were like, I don't know, sometimes things just grow weird.
156
You probably just did the gel wrong.
157
And the director of the lab, her boss, was like, I thought you were going to do a screen.
158
You know, make a flat dish of cells to screen for genes.
159
What are you doing?
160
And I was like, don't worry, I'm working on it.
161
And so over the next few months,
162
Madeline focused on getting a nice flat layer of mouse neural stem cells on the bottom of her Petri dishes
163
so she could do those screens.
164
And so that was like mostly what I was talking about with people in the lab.
165
But at the same time...
166
Off by herself, in her little corner, no one was paying attention.
167
I was always still playing around with Matrigel, growing these weird balls of cells.
168
Tweaking the recipe.
169
Trying to make sure I could get it to happen reproducibly.
170
And then one day, she gets her hands on some human stem cells.
171
Cells that come from skin or blood that you can reprogram to an embryonic state.
172
Where do you get those from?
173
I think these were actually made from discarded human foreskin.
174
Wow. So specific.
175
Okay.
176
What a detail.
177
All right.
178
Thank you for that.
179
Because it's just a bit of tissue that's thrown away.
180
Yeah.
181
Right. Of course. Of course.
182
Literally thrown away.
183
All right.
184
Okay. So, wow.
185
Yeah.
186
So anyway, so then...
187
So she got these human stem cells.
188
She put them in the matrigel, swirled them around in this nutrient-rich fluid so they could kind of eat.
189
and she would watch as these formerly foreskin cells started forming into clumpy parts of a human brain.
190
Oh my God.
191
And then she kept tweaking when and how much of the matrigel she would add
192
and she would just watch these blob shapes over time get bigger.
193
I mean, they can get as big as like a pencil eraser.
194
Side note, at the time she was pregnant.
195
Yeah, my oldest, I was pregnant with her.
196
So she said she had this extra maternal instinct and she was like just really nurturing these little brain balls.
197
Yeah.
198
And then one day, a couple months after, she's been tweaking her ball recipe.
199
And I looked under the microscope.
200
Inside.
201
Yeah.
202
On this beige lump, she could see a perfect ring of black pigment.
203
And that was just, I looked at that.
204
I was like, that's a developing eye.
205
Shut up.
206
And it was growing on a developing human brain.
207
You're like, no, what?
208
Yeah.
209
No, you, what?
210
And then, then.
211
That was then when she went to her weekly lab meeting.
212
I presented this data.
213
I showed this picture of this beginning of an eye.
214
And I remember hearing audible gasps.
215
And then she showed them pictures of the cells forming tubes and lobes and...
216
Ventricles, like an actual brain.
217
Everybody in the lab started to get it.
218
They were like, hey, wait a second.
219
It's like you have a version of an early human brain in this dish,
220
and you can actually watch the earliest stages of this process of development.
221
That we know almost nothing about. Is that true, though?
222
Do we not know anything about early human brain development?
223
I just think you get all these little...
224
Like when you're pregnant, you get a scan here, a scan there.
225
Maybe we know something from animal models.
226
But this was literally the first time anyone in human history
227
had ever watched the early brain develop right from the beginning like this.
228
Yeah.
229
Which is especially important when something in the brain has gone wrong.
230
Now we can actually watch this process instead of just looking at the end when the person is already severely suffering.
231
We can try to understand how it got there.
232
So Madeline and her boss, Jurgen Knoblik, who's on board with the whole project now,
233
in 2013, they team up with a bunch of other researchers and publish a paper in the journal Nature.
234
In that paper, they describe how this disorder microcephaly develops in a fetal brain.
235
And they were like, oh, and to see all of this, we use these tiny 3D brain balls, which we have decided to call cerebral organoids.
236
That's when, like, everything changed.
237
If you were studying human brain development, it was like someone just invented the microscope.
238
Yes.
239
You can see things that were invisible before.
240
So this is Carl Zimmer, science journalist, New York Times columnist, book writer.
241
Ah, you got Zimmer.
242
Yeah, as soon as I heard about this stuff, of course, he's my first phone call.
243
And he was all over it.
244
Sort of like humanoid, organoid, very sci-fi.
245
And the first thing that he pointed out is that there are so many neurological disorders where...
246
The key moments are during development.
247
It's like the key plot points are happening when we can't watch the movie.
248
Right.
249
Totally off limits. But 2013...
250
Madeline and Juergen published their paper and boom.
251
We could watch human progenitor brain cells give rise to parts of the brain.
252
What would you do with that?
253
Like, what would you see?
254
So one example is a, there's a scientist at Stanford, Sergio Pasca, and he studied a very rare disease called Timothy syndrome.
255
It's caused by a genetic mutation that causes severe neurodevelopmental problems.
256
And he basically created an organoid with that mutation so that he could see how a brain with Timothy syndrome develops, like from the beginning.
257
Yeah.
258
Now you can actually see what
259
Timothy syndrome is about.
260
So when, what did he see?
261
So there are certain kinds of cells called interneurons, and they make very important connections between different parts of the brain.
262
And with kids with Timothy syndrome, they just don't.
263
They just fail to get where they need to go.
264
And now that he knew what was going wrong...
265
He started testing out some drugs to see if he could fix that.
266
Yeah.
267
And he and his colleagues actually ended up finding a small drug that actually did help these neurons to find their way.
268
Ah.
269
In an organoid.
270
So he cured it in an organoid.
271
Right.
272
Huh.
273
And they are on track to actually start clinical trials with that drug next year.
274
Wow.
275
And you could imagine that's one disorder.
276
That's right.
277
A lot of other conditions.
278
Epilepsy, schizophrenia.
279
Fetal alcohol syndrome.
280
Any of these brain conditions that have an issue starting in development
281
or where we might even suspect they might start that early but aren't sure yet, now you can see it.
282
A lot of people in the field said, whoa, I got to try this.
283
This whole field of neural organoids has just totally exploded.
284
I think there's thousands of labs actually using these tools now.
285
The study of the brain is fundamentally different now.
286
That's what we are doing on Radiolab today.
287
We are just, Lulu, we're gonna jump into the ball pit of brain balls.
288
Okay.
289
In which there are tons of new opportunities, but also confounding questions.
290
Are there thoughts in there?
291
Is there thinking in there?
292
How brainy are these balls?
293
We are gonna get there after the break.
294
All right, here we are.
295
I'm in the 72nd
296
Street subway station, and I am walking to go see a fridge full of brains.
297
Hey, I'm Latif Nasser.
298
I'm Lulu Miller.
299
This is Radiolab.
300
More specifically, a fridge full of brain organoids.
301
Just before the break, we learned from Madeline that now thousands of labs around the world are growing these brain organoids.
302
And it turns out that one of them happens to be just up the street from our studio in New York City.
303
Only when you're recording are you truly conscious of, like, how much you breathe.
304
So we sent our producer, Mona McGaulker.
305
Laboratory, caution, hazardous materials.
306
To check them out.
307
Where are we entering?
308
So we're entering, so we have special rooms called cell culture rooms where we grow, oops, we grow the organoids.
309
This is Dr. Howard Fine.
310
I'm a medical and neuro-oncologist.
311
And this is his lab at the Weill Cornell Medical Center where he studies brain cancer.
312
The type of brain tumor known as a glioblastoma.
313
A very bad kind.
314
Probably now the most lethal of all human cancers.
315
The average survival is about 15 or 16 months.
316
And Dr. Fine says around 15 years ago or so, he hit a wall in his research.
317
We've probably made the least amount of progress with.
318
So he'd been studying glioblastoma, mostly, of course, in mice, right?
319
And he admits he actually calls this at the time it was the dirty little secret of oncology
320
that for all this research, they were basically getting nowhere.
321
Whoa.
322
But then, you know, he came across Madeline's work on organoids.
323
And it was Lancaster's paper.
324
I read in Nature, and it's like, literally, not many times in my 37 career, did I truly have a light bulb moment?
325
And I read that paper and said, this is what we're looking for.
326
And that's when he pivoted away from mice and started making brain organoids.
327
Can we see them?
328
We can take a look.
329
Okay, so he's opening the incubator and he's pulling out.
330
These are the stem cells.
331
And they looked just like Madeline described.
332
They're kind of like a beige color.
333
They look like a kidney bean or like a nerd candy.
334
Little beige balls floating in liquid in a dish.
335
It feels surrounded by a major child.
336
And under the microscope.
337
I see like a dark shape and then I see these little bubbles off the side, almost like little popcorn-y shapes.
338
You can see structure.
339
Dr. Vint, these are from specific patients, like your patients?
340
Yes.
341
But the difference between these organoids and Madeline's organoids was that these ones had cancer.
342
So the idea is we're going to make a mini brain from an individual patient. And then...
343
Oh, these are the glioma cells.
344
Wow.
345
They take cells from that patient's brain tumor.
346
Almost just looks like sugar that hasn't dissolved in tea.
347
And then we retroengineer the patient's own glioma stem cells into the mini brain.
348
Basically, they can put a version of your brain tumor on your...
349
A version of your brain on a version of your brain, and they can basically make a bunch of those.
350
We can test hundreds or thousands of drugs.
351
And then try a bunch of medicines on them.
352
To look for the drugs or combination of drugs that might be most effective.
353
So you're saying that, like, you can try every chemotherapy that's out there and decide, like, which one?
354
Everything, only limited by resources, as you could imagine.
355
Oh, my God.
356
That is beautiful.
357
I mean, that just thinking about a way of like a kind of bespoke medical future exploration.
358
Right.
359
Way better than just using mice.
360
Oh, my gosh.
361
Partly
362
because it also could help us leapfrog one of the biggest
363
reasons on average 90 percent of clinical trials for neurological drugs fail.
364
And for brain cancer, by the way, that number is even higher, 95 percent.
365
They're failing because they're not predicting whether the drug actually works on the disease.
366
And this is something that Madeline told me, too.
367
You might have a drug that works really well for treating mouse spinal cord injury.
368
Like it's like, OK, great.
369
This is not going to kill you.
370
Because you've got the animal work to show you that it's safe.
371
But it also doesn't make them better after the spinal cord injury.
372
But now, sure, they can do a mouse trial for safety.
373
But they can also test that drug to see if it works on a spinal cord organoid,
374
which is, you know, just a tiny version of an actual human spinal cord.
375
Wait, what?
376
I thought we were talking brain organoids.
377
Are there are there spinal cord organoids?
378
Spinal cord organoids?
379
Yeah.
380
Okay.
381
So as Madeline was developing her brain organoids, independently, around the same time,
382
other scientists all over the world are growing intestinal organoids, lung organoids, liver organoids, muscle organoids,
383
skin organoids, ancreas organoids, stomach organoids, heart organoids, kidney organoids, breast tissue organoids that actually produce milk.
384
Ah, they can have a breast tissue organoid that can make milk?
385
Yes.
386
Weird.
387
Has anyone tasted that milk?
388
I certainly haven't.
389
I've only read about it.
390
I don't know.
391
I don't know.
392
That's a good question.
393
Anyway.
394
That's science writer
395
Carl Zimmer again.
396
And he says now you can make an organoid of basically any part of the body.
397
And then you can connect them.
398
What?
399
You can, like, you can...
400
Does that work?
401
You can do that?
402
Oh, yeah.
403
They call them assembloids.
404
Assembloids.
405
Yeah.
406
No, like you can Mr. Potato Head assemble.
407
Correct.
408
But then do they attach to each other?
409
They attach to each other, yeah.
410
And do they communicate with each other?
411
They communicate with each other, yeah.
412
Okay, and then what? Do what?
413
With your charm bracelet human body?
414
So here's an example.
415
So Sergio Pasca...
416
Neuroscientist at Stanford University and his colleagues thought, can we use an assembloid to study pain?
417
The pathway of pain.
418
So they started with the finger.
419
A finger organoid?
420
No, no, no, sorry.
421
Just a nerve in the finger.
422
Oh, okay.
423
The sensory organoid.
424
Connect that.
425
Like with some other cells in the dish.
426
Another organoid, the spinal cord.
427
Yeah, it's the little teeny piece of spinal cord.
428
Now we're going to connect that.
429
To a brain organoid that is specifically the thalamus, which is the central hub in the brain that directs signals in all sorts of different ways.
430
And finally, we're going to connect that one to one more brain organoid, a cortex organoid.
431
Whoa, this is so weird.
432
I mean, it's like Legos.
433
It's like Legos.
434
With the human body.
435
Correct.
436
So then they took capsaicin.
437
That's the molecule in...
438
In like spicy food, is that right?
439
In spicy food, in chili peppers, yeah.
440
It can be very painful to the skin.
441
Okay.
442
And they said, okay, let's hit it with capsaicin and see what happens.
443
Uh-huh.
444
Boom.
445
Immediately, that sensory organoid goes...
446
Right.
447
And starts sending really strong signals.
448
And those signals, Carl says, zoom right up through this assembloid.
449
To the spinal cord, the thalamus, to the cortex.
450
Just like it would in your own body.
451
And they can see some kind of registering?
452
Correct.
453
And when they watch the way the signal travels, which is something that's normally hidden inside a body...
454
They discovered all sorts of things about what happens when we feel pain that they didn't know about before.
455
Like, for example, signals from different parts of the assembloid began firing together in these synchronized waves of signals.
456
Okay.
457
And the more you know about how those signals work or move, the better chance you have at stopping them.
458
You could, for example, say, okay, can I put a molecule into this assembloid that will stop the pain?
459
Oh, wow.
460
But, um, So if they're using these things to study pain, is it feeling pain?
461
No, probably not.
462
These organoids are just little bits of human tissue.
463
In order to feel pain the way we feel pain, there are other parts of the brain that come into play.
464
The assembloid is just this super basic circuit that you send a signal through.
465
So like this pain, it seems to be superficially registering it.
466
And like what is it, I think?
467
The capsaicin in that case.
468
No, no, no. I'm the first it.
469
It's like it is this little ball, but is the it a thing?
470
Like, what is it?
471
Well, they crackle with electricity.
472
They form connections called synapses.
473
They replicate parts of the human brain with astonishing accuracy.
474
But, Carl says...
475
They're not brains.
476
They're not brains.
477
That's right.
478
So if there's like a slider and on one end is brains
479
and then on the other hand is just like some neurons in a dish, where is this on the slider and how do you?
480
Yeah, I would say
481
that it's closer still for the time being to the neuron end of the slider simply based on numbers.
482
Our brain has something like 80 billion neurons neurons.
483
And the biggest human brain organoids contain about 2 million cells.
484
That's 0.0025%.
485
Well under 1%.
486
Yeah.
487
And you know, these things don't have blood vessels.
488
So that is a very important limiting factor to how big and complex it can get.
489
Yeah.
490
And they're not in a body.
491
So they can't interact with the world in like a meaningful way.
492
Okay.
493
Well, but when I was talking to Carl about this. So, um...
494
He said that a lot of that might no longer be true.
495
Some scientists have, you know, taken organoids from human cells and put them into the brains of rats.
496
What?
497
So basically what they did is they basically took a rat and they, like, carved out a chunk of its brain.
498
But they left some of it?
499
They left most of it.
500
And it's almost like, think about it, it's almost like they gave a rat a little human tumor something.
501
I mean, it doesn't...
502
But the tumor is like just brain, human brain.
503
It's human brain.
504
It's human brain.
505
And these human organides are pretty happy in there.
506
It's sort of wired in.
507
They connect up with the rat neurons.
508
They get supplied by the rat blood system.
509
So they have made, in a real sense, like a new kind of being.
510
Yeah, yeah, yeah.
511
That did not exist before this.
512
Correct.
513
Okay.
514
It feels like there should have been a bigger press release, but okay, do the rats act any differently?
515
Are they suddenly like into podcasts and coffee?
516
When you do studies on these rats, behavioral tests, memory tests, all sorts of things, they're just rats.
517
There seems to be nothing human-y about them.
518
Okay.
519
But one thing they did notice, when you tickle its whiskers...
520
Yeah.
521
You can actually measure signals from the human brain organoid neurons.
522
The human part of the brain lights up.
523
What?
524
Yeah.
525
So it's registering the feeling?
526
They are receiving signals from the rat's senses.
527
I mean, strictly speaking, they are receiving signals from the rat's senses.
528
Are they feeling it?
529
feeling it gets hard because it's kind of the pain question again.
530
But yeah, but now they're in a body.
531
I mean, they're in a being.
532
Yes, but they're not the like driving force of that being.
533
They're like a house guest in the attic.
534
Okay, Latif, would you put, make a brain ball, brain organoid of your brain cell and put in a rat?
535
If I'm being honest, probably not.
536
Probably not.
537
Okay.
538
So I don't know, but I just think you're more on my side
539
that this is a little scary than you in your little with your reporter's wand are letting on to because, yes, there's exciting research,
540
but it just feels like every time you try to comfort me with what we know about these things, you then end up not comforting me.
541
And then the scientists take it one step further anyway.
542
Um, okay.
543
Well, it's as if you have seen the future and what the next chapter holds, because that exact thing is going to happen.
544
It's going to get weirder and creepier and stranger, and that's all after the break.
545
Stick with us.
546
Latif.
547
Lulu, Radiolab.
548
We are back talking about brain balls, you know, bitty brains, boba brains, the brain-ish in a dish.
549
Yes, ha ha, with all your clever wordplay.
550
But you are about to send us into the next existential tailspin about how people are using these things.
551
It is possible.
552
So the final thing I was told to do is push record.
553
Record, yes.
554
That's an important button.
555
Now, tell me who you are.
556
So I'm Brett.
557
This is Brett Kagan.
558
He's a neuroscientist.
559
I'm the chief scientific officer here at Cortical Labs.
560
Cortical Labs.
561
We're a small tech startup here in Melbourne, Australia.
562
Did you start it?
563
Did someone else start it?
564
No, well, it was founded by, there was a few of us, and I was contacted by Dr. Hon Weng Chong and Andy Kitchen,
565
and they were looking for a neuroscientist.
566
Brett had been an academic, obsessed with this particular question.
567
How do you get intelligence out of brain cells that are in a dish?
568
And this company was like, why don't you leave academia and help us find out?
569
The question they had was, can brain cells in a dish do anything at all that we might want them to do?
570
Hmm.
571
Like, do what?
572
What better to pick than Pong?
573
Pong?
574
The, like, 70s computer game?
575
Yeah, the game with the paddles and the little ball.
576
Why that?
577
Everybody knows Pong.
578
It was one of the first computer games.
579
It was the first thing that machine learning, which people now like to call AI, really was trained on as a big breakout success.
580
And he figured the brain runs on electricity.
581
And it's also a shared language as silicon computing.
582
So why wouldn't we be able to get neurons to do something a computer could do? That exactly.
583
Like play a simple video game.
584
We used some hardware that allowed us to record the activity of the cells, process that, and then deliver small electrical pulses back into the cultures.
585
And they did it.
586
Scientists just put pieces of human and mice brain on a plate and wired it to a computer to play pong.
587
They learned to track the ball and control a paddle.
588
Seriously, this is one of the craziest things I've ever covered.
589
So here's what's going on.
590
What?
591
No. Yeah.
592
And this wasn't even an organoid.
593
This was just a flat sheet of neurons in a dish.
594
I mean, how could it possibly be doing that?
595
Like, I mean, can really dumb things do that?
596
Could like a tree do that?
597
Trees don't have neurons.
598
I don't think a tree could do that.
599
Okay, so, but well, what does this mean?
600
Like, are they learning?
601
Well, Brett says yes.
602
I called it learning.
603
And I think learning was an incredibly fair definition
604
because what would an improvement over time in a way that would suit a goal be called other than learning?
605
But other people, including Madeline Lancaster...
606
I actually remain to be convinced anybody has really shown that.
607
Say no. because it's really hard to interpret the signals coming from the neurons.
608
She says when you teach brain cells to play Pong, they're, you know, connected to a computer.
609
So what people do is they use algorithms to sort of decode that message and then send a signal back to neurons.
610
And so you kind of have like two black boxes that you've just hooked up.
611
It's sort of a collaboration between the brain cells and the computer.
612
And you don't really know what either of them are doing.
613
Anyway, whatever is happening here, what Brett and his team took away from this is if neurons can do something a computer does,
614
why don't we use neurons as computers?
615
What?
616
Yeah.
617
Literally a couple months ago, they released their first computer called the CL1.
618
And it is, they don't call it this, but it's effectively a biocomputer.
619
It has neurons in it.
620
Ew.
621
Brain, sticky, real human brain matter in it?
622
Yeah.
623
It's got like little brain organoids in it.
624
It has 800,000 neurons interfaced with a silicon chip you can use it to do computer stuff with.
625
Okay.
626
I mean, I can get behind the brain balls being used for neurological disorder research.
627
Great.
628
You know what?
629
Bespoke cancer treatments?
630
Cool.
631
But why are we hooking up human brain cells to computers to, like, make money?
632
That, to me, feels like not worth the risk.
633
Well, think about the problems we are having right now with all of these data centers chugging all this energy, right?
634
Absolutely wrecking the planet.
635
Right.
636
So our brains are so impressively efficient.
637
Energy wise, we have like a dim light bulb like screwed into our heads.
638
Right.
639
That's the amount of energy that we need to do all the complex things that we do.
640
If AI or if some supercomputer was doing the equivalent, it would need millions of times more power.
641
Like the difference between a single light bulb and a large town. So flattering.
642
The other thing is that, like, think about these AIs.
643
You need to train it on the whole Internet, right?
644
A human brain is much quicker to learn.
645
If you could harness that energy efficiency, if you could harness that kind of like a knowledge efficiency in a computer, you could move mountains.
646
OK, but I guess my authentic question at this point is like, OK, you have shown us all this stuff.
647
At this point, it seems pretty clear that they can definitely register input, right?
648
Like there's the tickle, the pain, the signal they're getting from Pong.
649
Okay.
650
And then this Pong example at least shows us they are then able, based on that input, to produce some kind of output.
651
Yeah.
652
Okay.
653
So let's say it is.
654
Yeah.
655
Okay.
656
So my question is, if they can do those things, wouldn't they have to have some thrumming level of consciousness?
657
No, actually.
658
No, they really don't.
659
Like a bunch of the things you just talked about, AI can do those.
660
Is AI conscious?
661
Even going further than that, like a Roomba can do, like navigate a room.
662
Is a Roomba conscious?
663
That's a signal in and out.
664
Yeah, right.
665
A Roomba's going, oh, there's an edge.
666
Let me go this way.
667
That's a signal in and out.
668
When we talk about human consciousness, we mean self-consciousness.
669
Like you are aware of yourself.
670
You have a past.
671
You have a future that you're concerned about.
672
There's like that continuity of experience.
673
This is Dr. In-Soo Hyun.
674
I'm the director of the Center for Life Sciences at the Museum of Science in Boston.
675
He's a bioethicist, and he's worked on a bunch of teams with scientists who are studying brain organoids.
676
We try to identify what are the emerging scientific and ethical issues.
677
You're like kind of like their conscience?
678
Is that sort of the thing?
679
You know what?
680
Sometimes I feel like a priest in secular clothes.
681
And he says at this point, he is not worried about brain organoids having anything like human consciousness.
682
The brain organoids in the dish don't have that continuity.
683
They don't have all the regions.
684
They don't have the interaction with the outside world.
685
But when he thinks about the future that
686
Brett and others are trying to create,
687
where maybe people start connecting more and more complicated and even more and more structured clumps of human brain cells to computers.
688
Maybe you get, it might not even human consciousness, but some kind of consciousness could emerge.
689
he's hooked up to the world
690
yeah okay so what about this Latif
691
I would if I may I would like to just issue a commandment that all the smart people who are like
692
excited by brain organoids.
693
They all take one year to stop making organoids
694
and use their smarts and their technologies
695
and their labs to like try to understand the consciousness of the organoids that have already been made.
696
You know, like ideally they could all be in a dark room and just have candles and quietly,
697
meditatively watch for any flickers to understand what's going on.
698
And then And then we have a grand assembly where everyone reports back and we all collectively decide what to do.
699
But I know that like some of these scientists have this fire inside them to be like,
700
how many cures am I not going to find in that year?
701
Like how many people am I not going to help in that year?
702
Like the glioblastoma, like those people don't have a year.
703
And those people are telling me to just shut up because this is a piece of discarded foreskin.
704
That's right.
705
If we have a tool that we don't use.
706
Madeline Lancaster again.
707
And there are millions of actually conscious human beings out there that don't have treatments.
708
But we decide, no, we're going to put the value of organoids higher than those people. That would be unethical.
709
It's funny, like at the beginning, like you asked me, like, would you make a brain ball of yourself?
710
And I said no. And then at some point, like my thinking switch where I'm like,
711
oh, no, unless it would save someone's life.
712
Well, that's noble.
713
And now I feel even worse saying I don't know that I would.
714
I just I mean, yeah.
715
OK, if it's my own kid, sure.
716
I don't care if I'm like a little enslaved human consciousness, if it saves my kid.
717
But as you have shown us, the scientists are going to do more.
718
They're going to try new things.
719
They're going to build bigger brains.
720
And like, there is a line and we will cross it and we won't know that we've crossed it, you know?
721
Right.
722
And the thing about these organoids is that they're already crossing all kinds of lines.
723
You disrupt categories that we thought were so neat and tidy and distinguishable.
724
Life, non-life.
725
Human, non-human.
726
Human, computer.
727
We thought those were pretty clean categories.
728
But this research is kind of upsetting the very foundations of what we think separates these categories apart.
729
It does feel like it's like, oh, we've created a new category of thing, like a new category of thing that is maybe alive.
730
It is alive.
731
We have created a new category of thing that is alive.
732
That is weird.
733
Oh, yeah.
734
It's hard.
735
It's hard to actually put it into a category that already exists, I think, because they're not actual brains that we can say absolutely certainly.
736
But they're also not just a few neurons in a dish either.
737
We almost don't really even have the words for it.
738
I think it's kind of a new thing.
739
Latif Nasser.
740
This episode was produced by Annie McKeown, Mona Madgaukar, and Pat Walters.
741
It was edited by Alex Neeson and Pat Walters with fact-checking by Natalie Middleton and Rebecca Rand.
742
Special thank-you shout-outs to Lynn Levy, Jason Yamada-Hanf, David Fagenbaum, Andrew Verstein, Anne Hamilton, Christopher Mason, Madeline Mason-Mariarty,
743
plus Howard Fine and his whole team at Weill Cornell for hosting us.
744
And if you're looking for more musings on the nature of life and what it means to be alive,
745
Carl Zimmer has a terrific book out all about this stuff.
746
It's called Life's Edge, the search for what it means to be alive.
747
Get it at your local bookstore.
748
That's it for us from our brain balls to yours.
749
See you next week.
750
Okay, start now.
751
I almost practiced.
752
No, you don't need to.
753
You don't need to practice anymore.
754
Shh.
755
We're recording now.
756
Hi, I'm Ellie Columns, and I'm from Louisville, Kentucky, and here are the staff credits.
757
And she's Molly's niece.
758
Yeah.
759
Radio Lab is hosted by Lulu Miller and Latif Nasser.
760
Sorin Wheeler is our executive editor.
761
Sarah Sandback is our executive director.
762
Our managing editor is Pat Walters.
763
Dylan Keefe is our director of sound design.
764
Our staff includes Jeremy Bloom, W.
765
Harry Fortuna, David Gable, Maria Paz Gutierrez, Sindhu Nana Sambandan
766
Matt Kilty Mona Madgavkar Annie McEwan Alex Neeson Sarah Kari
767
Anissa Vietes Arian Wack
768
Molly Webster and Jessica Young With help from Rebecca Rand Our fact checkers are Diane Kelly Emily Krieger
769
and Natalie Middleton I love your giggle
770
leadership support for radio lab science programming is provided by the simons foundation
771
and the john templeton foundation foundational support for radio lab was provided by the alfred p sloan foundation
Tải Ứng Dụng
Mọi thứ bạn cần để nói trôi chảy
Chấm điểm AIChấm từng câu nói
Luyện IPAThành thạo mọi âm
Từ vựngMở rộng vốn từ
Game Từ vựngHọc qua chơi
Cùng kênh
FOR YOU
Video gợi ý
C1552 câu
The Professor Who Taught People How To Think (1962)
Daily ConversationUniversity StudentsWorking Adults
C13
33 câu
Your Memories & Emotions Impact Immune Status
Daily ConversationUniversity StudentsWorking Adults
B21
137 câu
What Happens If a Child Never Hears Language?
Daily ConversationUniversity StudentsWorking Adults
C185 câu
We Can Now Simulate a Human Brain, Scientists Show
Daily ConversationUniversity StudentsWorking Adults
C11
380 câu
A man hiked in the woods. Every brain cell got cooked.
Daily ConversationUniversity StudentsWorking Adults
C12
201 câu
Cleo Abram Answers The Web's Most Searched Questions | WIRED
Business EnglishDaily ConversationUniversity Students
B21
34 câu
Echolocation: How Dolphins and Bats See with Sound
American AccentBritish AccentDaily ConversationUniversity StudentsWorking Adults
C181
42 câu
How playing an instrument benefits your brain - Anita Collins
Daily ConversationUniversity StudentsWorking Adults
C11
50 câu
We Fell For The Oldest Lie On The Internet
Daily ConversationUniversity StudentsWorking Adults
C18
55 câu
When AIs act emotional
Daily ConversationUniversity StudentsWorking Adults
C112
14 câu
Would You Upload Your Mind?
Daily ConversationUniversity StudentsWorking Adults
C14
204 câu
The Insane Biology of: The Octopus
Daily ConversationUniversity StudentsWorking Adults
Từ vựng và ghi chú luyện nói cho bài học này
Những từ được nhắc lại nhiều nhất trong bài: brain, organoid, cell. Video này có 771 câu và 6651 từ để luyện shadowing. Phần lời nói dài 41:20. Người nói nói với tốc độ tự nhiên, khoảng 161 từ mỗi phút, gần với hội thoại hằng ngày. Chỉ 81% số từ nằm trong 3.000 từ tiếng Anh thông dụng nhất, nên từ vựng khá khó.
Từ vựng quan trọng trong video
15 từ đáng học trong video, kèm phiên âm và nghĩa:
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| dish danh từ | /dɪʃ/ | đĩa |
| mouse danh từ | /maʊs/ | chuột |
| tube danh từ | /tuːb/ | ống, lọ |
| consciousness danh từ | /ˈkɑnʃəsnəs/ | ý thức |
| microscope danh từ | /ˈmaɪ.kɹəˌskoʊp/ | kính hiển vi |
| connect động từ | /kəˈnɛkt/ | nối |
| tissue danh từ | /ˈtɪʃ.(j)u/ | khăn giấy |
| syndrome danh từ | /ˈsɪndɹoʊm/ | hội chứng |
| tumor danh từ | /tuː.məɹ/ | u |
| gene danh từ | /d͡ʒiːn/ | gen, di tố |
| disorder danh từ | /dɪsˈɔɹdɚ/ | rối loạn |
| rat danh từ | /ɹæt/ | chuột |
| float động từ | /fləʊt/ | nổi |
| glue danh từ | /ɡlu/ | keo, hồ |
| cloudy tính từ | /ˈklaʊ̯diː/ | có mây |
Cụm động từ bạn sẽ nghe
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| shut up | /ʃʌt ʌp/ | câm, câm mồm |
| throw away động từ | vất, vứt |
Những câu đáng luyện lại
Các câu ngắn, trọn ý trong video mà bạn có thể dùng lại khi giao tiếp hằng ngày:
- Had you ever seen anything like that before?
- Where do you get those from?
- You're like, no, what?
- What would you do with that?
- You're like kind of like their conscience?
Ngữ pháp trong video
Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:
| Cấu trúc | Trong video |
|---|---|
| Câu điều kiện if + mệnh đề, will/would + động từ — điều kiện và kết quả | if they can do those things, wouldn't they · if I may I would like |
| Thì hiện tại hoàn thành have/has + quá khứ phân từ — việc đã xảy ra nhưng còn liên quan đến hiện tại | has just finished · has gone · have decided |
| Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làm | were actually made · was told · was founded |
| Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vật | there, which means · thalamus, which is · travels, which is |
Phát âm cần chú ý
Người nói dùng 131 dạng rút gọn, ví dụ don't, they're, I'm. Hãy nói theo dạng ngắn đúng như bạn nghe.
- Âm “th”: breathe /bɹiːð/, thalamus /ˈθæləməs/
- Âm “sh” và “zh”: dish /dɪʃ/, consciousness /ˈkɑnʃəsnəs/, tissue /ˈtɪʃ.(j)u/, conscious /ˈkɑn.ʃəs/, sheet /ʃit/
- Từ dài — đặt trọng âm cho đúng: neurological /nɝəˈlɑd͡ʒɪkəl/, electricity /ɪˌlɛkˈtɹɪsɪti/, efficiency /ɪˈfɪʃ.ən.si/, experiment /ɪkˈspɛɹ.ə.mənt/, communicate /kəˈmjuːnɪkeɪt/
Những âm người Việt thường gặp khó:
- Cụm phụ âm cuối — đọc đủ từng âm, đừng nuốt âm cuối: cord /ˈkoɹd/, connect /kəˈnɛkt/, bulb /ˈbʌlb/, experiment /ɪkˈspɛɹ.ə.mənt/, breast /bɹɛst/
- Âm /tʃ/, /dʒ/ và /ʒ/ — tiếng Việt không có, đừng đọc thành “ch” hay “gi”: gene /d͡ʒiːn/, neurological /nɝəˈlɑd͡ʒɪkəl/, attach /əˈtæt͡ʃ/, architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, journalist /ˈd͡ʒɝnəlɪst/
- Âm /æ/ — mở miệng rộng hơn âm “e”: lab /læːb/, rat /ɹæt/, scan /skæn/, attach /əˈtæt͡ʃ/, sand /sænd/
Cách luyện với video này
- Nghe hết video một lần, chưa cần nói, và ghi lại những từ bạn chưa biết.
- Bắt đầu ở tốc độ 0,75×, nói đuổi từng câu, rồi quay lại tốc độ bình thường khi đã quen.
- Ghi âm giọng mình rồi so với bản gốc, chú ý các từ như dish, mouse, tube.
Phương Pháp Shadowing Là Gì?
Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.