Building a dinosaur from a chicken | Jack Horner

1,245,414 views ใƒป 2011-06-07

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Avishai Abbo ืžื‘ืงืจ: Sigal Tifferet
00:15
When I was growing up in Montana,
0
15260
4000
ื›ืฉื’ื“ืœืชื™ ื‘ืžื•ื ื˜ื ื”
00:19
I had two dreams.
1
19260
3000
ื”ื™ื• ืœื™ ืฉื ื™ ื—ืœื•ืžื•ืช
00:22
I wanted to be a paleontologist,
2
22260
2000
ืจืฆื™ืชื™ ืœื”ื™ื•ืช ืคืœื™ืื•ื ื˜ื•ืœื•ื’ (ื—ื•ืงืจ ืžืื•ื‘ื ื™ื ื•ืฆื•ืจื•ืช ื—ื™ื™ื ืงื“ื•ืžื•ืช),
00:24
a dinosaur paleontologist,
3
24260
2000
ืคืœื™ืื•ื ื˜ื•ืœื•ื’ ืฉืœ ื“ื™ื ื•ื–ืื•ืจื™ื,
00:26
and I wanted to have a pet dinosaur.
4
26260
3000
ื•ืจืฆื™ืชื™ ืฉื™ื”ื™ื” ืœื™ ื“ื™ื ื•ื–ืื•ืจ ืžื—ืžื“.
00:29
And so that's what I've been striving for
5
29260
3000
ื•ื›ืš, ื–ื” ืžื” ืฉืฉืืคืชื™ ืืœื™ื•
00:32
all of my life.
6
32260
3000
ื›ืœ ื—ื™ื™.
00:35
I was very fortunate
7
35260
2000
ื”ื™ื” ืœื™ ื”ืจื‘ื” ืžื–ืœ
00:37
early in my career.
8
37260
2000
ื‘ืชื—ื™ืœืช ื”ืงืจื™ื™ืจื” ืฉืœื™.
00:39
I was fortunate
9
39260
2000
ื”ืชืžื–ืœ ืžื–ืœื™
00:41
in finding things.
10
41260
2000
ืœืžืฆื•ื ื“ื‘ืจื™ื.
00:43
I wasn't very good at reading things.
11
43260
2000
ืœื ื”ื™ื™ืชื™ ืžืื•ื“ ื˜ื•ื‘ ื‘ืœืงืจื•ื ื“ื‘ืจื™ื.
00:45
In fact, I don't read much of anything.
12
45260
3000
ืœืžืขืฉื”, ืื ื™ ืœื ืงื•ืจื ื”ืจื‘ื” ืžืฉื•ื ื“ื‘ืจ.
00:48
I am extremely dyslexic,
13
48260
2000
ื™ืฉ ืœื™ ื“ื™ืกืœืงืฆื™ื” ืงืฉื”.
00:50
and so reading is the hardest thing I do.
14
50260
3000
ื•ืงืจื™ืื” ื”ื™ื ื”ื“ื‘ืจ ื”ืงืฉื” ื‘ื™ื•ืชืจ ืฉืื ื™ ืขื•ืฉื”.
00:53
But instead, I go out and I find things.
15
53260
3000
ืื‘ืœ ื‘ืžืงื•ื ื–ืืช, ืื ื™ ื™ื•ืฆื ื”ื—ื•ืฆื” ื•ืื ื™ ืžื•ืฆื ื“ื‘ืจื™ื.
00:56
Then I just pick things up.
16
56260
2000
ื•ืื– ืื ื™ ืคืฉื•ื˜ ืžืจื™ื ื“ื‘ืจื™ื.
00:58
I basically practice for finding money on the street.
17
58260
3000
ืื ื™ ืคืฉื•ื˜ ืžืชืืžืŸ ื‘ืœืžืฆื•ื ื›ืกืฃ ื‘ืจื—ื•ื‘.
01:01
(Laughter)
18
61260
2000
(ืฆื—ื•ืง)
01:03
And I wander about the hills,
19
63260
2000
ื•ืื ื™ ืžืฉื•ื˜ื˜ ื‘ื’ื‘ืขื•ืช.
01:05
and I have found a few things.
20
65260
3000
ื•ืžืฆืืชื™ ื›ืžื” ื“ื‘ืจื™ื.
01:08
And I have been fortunate enough
21
68260
3000
ื•ื”ื™ื” ืœื™ ืžืกืคื™ืง ืžื–ืœ
01:11
to find things like the first eggs in the Western hemisphere
22
71260
5000
ืœืžืฆื•ื ื“ื‘ืจื™ื ื›ืžื• ื”ื‘ื™ืฆื™ื ื”ืจืืฉื•ื ื•ืช ืฉื ืžืฆืื• ื‘ื—ืฆื™ ื”ื›ื“ื•ืจ ื”ืžืขืจื‘ื™,
01:16
and the first baby dinosaurs in nests,
23
76260
4000
ื•ืชื™ื ื•ืงื•ืช ื“ื™ื ื•ื–ืื•ืจื™ื ื‘ืงื™ื ื™ื ืฉืœื”ื,
01:20
the first dinosaur embryos
24
80260
2000
ืขื•ื‘ืจื™ ื”ื“ื™ื ื•ื–ืื•ืจื™ื ื”ืจืืฉื•ื ื™ื,
01:22
and massive accumulations of bones.
25
82260
4000
ื•ืžืืกืคื™ ืขืฆืžื•ืช ื’ื“ื•ืœื™ื.
01:26
And it happened to be at a time
26
86260
2000
ื•ื–ื” ืงืจื” ื‘ืื•ืชื• ื”ื–ืžืŸ
01:28
when people were just starting to begin to realize
27
88260
4000
ืฉื‘ื• ืื ืฉื™ื ืจืง ื”ืชื—ื™ืœื• ืœื”ื‘ื™ืŸ
01:32
that dinosaurs weren't the big, stupid, green reptiles
28
92260
4000
ืฉื”ื“ื™ื ื•ื–ืื•ืจื™ื ืœื ื”ื™ื• ื”ืœื˜ืื•ืช ื”ื’ื“ื•ืœื•ืช, ื™ืจื•ืงื•ืช ื•ื˜ื™ืคืฉื•ืช
01:36
that people had thought for so many years.
29
96260
3000
ืฉื”ืื ืฉื™ื ื—ืฉื‘ื• ืขืœื™ื”ื ื›ืœ ื›ืš ื”ืจื‘ื” ืฉื ื™ื.
01:39
People were starting to get an idea
30
99260
2000
ืื ืฉื™ื ื”ื—ืœื• ืœื”ื‘ื™ืŸ
01:41
that dinosaurs were special.
31
101260
2000
ืฉื”ื“ื™ื ื•ื–ืื•ืจื™ื ื”ื™ื• ืžื™ื•ื—ื“ื™ื.
01:43
And so, at that time,
32
103260
3000
ื•ื›ืš ื‘ื–ืžื ื•,
01:46
I was able to make some interesting hypotheses
33
106260
3000
ื™ื›ื•ืœืชื™ ืœื”ืขืœื•ืช ื›ืžื” ืจืขื™ื•ื ื•ืช ืžืขื ื™ื™ื ื™ื
01:49
along with my colleagues.
34
109260
2000
ื™ื—ื“ ืขื ืขืžื™ืชื™ื™.
01:51
We were able to actually say
35
111260
2000
ื™ื›ื•ืœื ื• ืžืžืฉ ืœื•ืžืจ
01:53
that dinosaurs -- based on the evidence we had --
36
113260
3000
ืฉื”ื“ื™ื ื•ื–ืื•ืจื™ื -- ื‘ื”ืชื‘ืกืก ืขืœ ื”ืจืื™ื•ืช ืฉื”ื™ื• ืœื ื• --
01:56
that dinosaurs built nests
37
116260
3000
ืฉื”ื“ื™ื ื•ื–ืื•ืจื™ื ื‘ื ื• ืงื™ื ื™ื,
01:59
and lived in colonies
38
119260
3000
ื•ื—ื™ื• ื‘ืžื•ืฉื‘ื•ืช,
02:02
and cared for their young,
39
122260
2000
ื•ื“ืื’ื• ืœืฆืืฆืื™ื ืฉืœื”ื,
02:04
brought food to their babies
40
124260
2000
ื”ื‘ื™ืื• ืื•ื›ืœ ืœืชื™ื ื•ืงื•ืช ืฉืœื”ื
02:06
and traveled in gigantic herds.
41
126260
3000
ื•ื ื“ื“ื• ื‘ืขื“ืจื™ื ืขื ืงื™ื™ื.
02:09
So it was pretty interesting stuff.
42
129260
3000
ืื– ืืœื” ื”ื™ื• ื“ื‘ืจื™ื ืžืžืฉ ืžืขื ื™ื™ื ื™ื.
02:12
I have gone on to find more things
43
132260
3000
ื”ืžืฉื›ืชื™ ื”ืœืื” ืœืžืฆื•ื ืขื•ื“ ื“ื‘ืจื™ื
02:15
and discover that dinosaurs really were very social.
44
135260
4000
ื•ืœื’ืœื•ืช ืฉื”ื“ื™ื ื•ื–ืื•ืจื™ื ื”ื™ื• ืœืžืขืฉื” ืžืื•ื“ ื—ื‘ืจืชื™ื™ื.
02:19
We have found a lot of evidence
45
139260
3000
ืžืฆืื ื• ื”ืจื‘ื” ืจืื™ื•ืช
02:22
that dinosaurs changed
46
142260
2000
ืœื›ืš ืฉื”ื“ื™ื ื•ื–ืื•ืจื™ื ื”ืฉืชื ื•
02:24
from when they were juveniles to when they were adults.
47
144260
2000
ืžื”ืจื’ืข ืฉื”ื™ื• ืฆืขื™ืจื™ื ืขื“ ืฉื ื”ื™ื• ืœื‘ื•ื’ืจื™ื.
02:26
The appearance of them would have been different --
48
146260
3000
ื”ื”ื•ืคืขื” ืฉืœื”ื ื”ื™ื™ืชื” ืฉื•ื ื” --
02:29
which it is in all social animals.
49
149260
2000
ื•ื›ืš ื–ื” ื‘ื›ืœ ื”ื—ื™ื•ืช ืฉืžื ื”ืœื•ืช ื—ื™ื™ ื—ื‘ืจื”.
02:31
In social groups of animals,
50
151260
2000
ื‘ืงื‘ื•ืฆื•ืช ื—ื‘ืจืชื™ื•ืช ืฉืœ ื‘ืขืœื™ ื—ื™ื™ื
02:33
the juveniles always look different than the adults.
51
153260
3000
ื”ืฆืขื™ืจื™ื ื ืจืื™ื ืฉื•ื ื” ืžื”ื‘ื•ื’ืจื™ื.
02:36
The adults can recognize the juveniles;
52
156260
2000
ื”ื‘ื•ื’ืจื™ื ื™ื›ื•ืœื™ื ืœื–ื”ื•ืช ืืช ื”ืฆืขื™ืจื™ื,
02:38
the juveniles can recognize the adults.
53
158260
2000
ื”ืฆืขื™ืจื™ื ื™ื›ื•ืœื™ื ืœื–ื”ื•ืช ืืช ื”ื‘ื•ื’ืจื™ื.
02:40
And so we're making a better picture
54
160260
3000
ื•ื›ืš ืื ื• ืžืฆื™ื™ืจื™ื ืชืžื•ื ื” ื˜ื•ื‘ื” ื™ื•ืชืจ
02:43
of what a dinosaur looks like.
55
163260
2000
ืฉืœ ืื™ืš ื“ื™ื ื•ื–ืื•ืจ ื ืจืื”.
02:45
And they didn't just all chase Jeeps around.
56
165260
3000
ื•ื”ื ืœื ืจืง ืจื“ืคื• ืื—ืจื™ ื’'ื™ืคื™ื ื›ืœ ื”ื™ื•ื.
02:48
(Laughter)
57
168260
2000
(ืฆื—ื•ืง)
02:50
But it is that social thing
58
170260
3000
ืื‘ืœ ื–ื” ื”ืขื ื™ื™ืŸ ื”ื—ื‘ืจืชื™
02:53
that I guess attracted Michael Crichton.
59
173260
4000
ืฉืœื“ืขืชื™ ืžืฉืš ืืช ืžื™ื™ืงืœ ืงืจื™ื™ื˜ื•ืŸ.
02:57
And in his book, he talked about the social animals.
60
177260
4000
ื•ื”ืกืคืจ ืฉืœื•, ื”ื•ื ื“ื™ื‘ืจ ืขืœ ื”ื™ืฆื•ืจื™ื ื”ื—ื‘ืจืชื™ื™ื.
03:01
And then Steven Spielberg, of course,
61
181260
2000
ื•ื›ืฉืกื˜ื™ื‘ืŸ ืกืคื™ืœื‘ืจื’, ื›ืžื•ื‘ืŸ,
03:03
depicts these dinosaurs
62
183260
2000
ืžืชืืจ (ื‘ืกืจื˜ื•) ืืช ื”ื“ื™ื ื•ื–ืื•ืจื™ื ื”ืืœื”
03:05
as being very social creatures.
63
185260
3000
ื›ื™ืฆื•ืจื™ื ืžืื•ื“ ื—ื‘ืจืชื™ื™ื.
03:08
The theme of this story is building a dinosaur,
64
188260
2000
ื”ื ื•ืฉื ืฉืœ ื”ืกื™ืคื•ืจ ื”ื–ื” ื”ื•ื ืœื‘ื ื•ืช ื“ื™ื ื•ื–ืื•ืจ,
03:10
and so we come to that part of "Jurassic Park."
65
190260
4000
ื•ื›ืš ืื ื• ื—ื•ื–ืจื™ื ืœืื•ืชื• ื—ืœืง ืžืชื•ืš "ืคืืจืง ื”ื™ื•ืจื”".
03:14
Michael Crichton really was one of the first people
66
194260
3000
ืžื™ื™ืงืœ ืงืจื™ื™ื˜ื•ืŸ ื‘ืืžืช ื”ื™ื” ืื—ื“ ืžื‘ื™ืŸ ื”ืจืืฉื•ื ื™ื
03:17
to talk about bringing dinosaurs back to life.
67
197260
4000
ืฉื“ื™ื‘ืจื• ืขืœ ืœื”ื—ื™ื•ืช ื“ื™ื ื•ื–ืื•ืจื™ื ืžื—ื“ืฉ.
03:21
You all know the story, right.
68
201260
2000
ืืชื ื™ื•ื“ืขื™ื ืืช ื”ืกื™ืคื•ืจ, ื ื›ื•ืŸ?
03:23
I mean, I assume everyone here has seen "Jurassic Park."
69
203260
3000
ื›ืœื•ืžืจ, ืื ื™ ืžื ื™ื— ืฉื›ื•ืœื ืจืื• ืืช "ืคืืจืง ื”ื™ื•ืจื”".
03:26
If you want to make a dinosaur,
70
206260
2000
ืื ืืชื” ืจื•ืฆื” ืœื™ืฆื•ืจ ื“ื™ื ื•ื–ืื•ืจ,
03:28
you go out, you find yourself a piece of petrified tree sap --
71
208260
4000
ืืชื” ื™ื•ืฆื ื”ื—ื•ืฆื”, ืžื•ืฆื ืœืขืฆืžืš ื—ืชื™ื›ื” ืฉืœ ืฉืจืฃ ืžืื•ื‘ืŸ --
03:32
otherwise known as amber --
72
212260
2000
ืฉื™ื“ื•ืข ื‘ืฉื ืขื ื‘ืจ --
03:34
that has some blood-sucking insects in it,
73
214260
3000
ืฉื™ืฉ ื‘ื• ืื™ื–ื” ื—ืจืง ืžื•ืฆืฅ ื“ื ื‘ืชื•ื›ื•,
03:37
good ones,
74
217260
2000
ื›ืžื” ื˜ื•ื‘ื™ื,
03:39
and you get your insect and you drill into it
75
219260
3000
ื•ืืชื” ืœื•ืงื— ืืช ื”ื—ืจืง ืฉืœืš ื•ืงื•ื“ื— ืืœื™ื• ืคื ื™ืžื”
03:42
and you suck out some DNA,
76
222260
2000
ื•ืฉื•ืื‘ ื”ื—ื•ืฆื” ืžืขื˜ ื“ื "ื,
03:44
because obviously all insects that sucked blood in those days
77
224260
3000
ืžืคื ื™ ืฉื‘ืจื•ืจ ืฉื›ืœ ื”ื—ืจืงื™ื ืฉืžืฆืฆื• ื“ื ื‘ืื•ืชื• ื”ื–ืžืŸ
03:47
sucked dinosaur DNA out.
78
227260
3000
ืžืฆืฆื• ื”ื—ื•ืฆื” ื“ื "ื ืฉืœ ื“ื™ื ื•ื–ืื•ืจื™ื.
03:50
And you take your DNA back to the laboratory
79
230260
3000
ื•ืืชื” ืœื•ืงื— ืืช ื”ื“ื "ื ื—ื–ืจื” ืœืžืขื‘ื“ื”
03:53
and you clone it.
80
233260
3000
ื•ืืชื” ืžืฉื›ืคืœ ืื•ืชื•.
03:56
And I guess you inject it into maybe an ostrich egg,
81
236260
3000
ื•ืื ื™ ืžื ื™ื— ืฉืืชื” ืžื–ืจื™ืง ืื•ืชื• ืื•ืœื™ ืœื‘ื™ืฆืช ื™ืขืŸ,
03:59
or something like that,
82
239260
2000
ืื• ืžืฉื”ื• ื‘ืกื’ื ื•ืŸ.
04:01
and then you wait,
83
241260
2000
ื•ืืชื” ืžืžืชื™ืŸ,
04:03
and, lo and behold, out pops a little baby dinosaur.
84
243260
3000
ื•ืื–, ื”ืคืœื ื•ืคืœื, ืงื•ืคืฅ ืœื• ื”ื—ื•ืฆื” ืชื™ื ื•ืง ื“ื™ื ื•ื–ืื•ืจ ืงื˜ืŸ.
04:06
And everybody's happy about that.
85
246260
3000
ื•ื›ื•ืœื ืฉืžื—ื™ื ืขืœ ื–ื”.
04:09
(Laughter)
86
249260
3000
(ืฆื—ื•ืง)
04:12
And they're happy over and over again.
87
252260
2000
ื•ื”ื ืฉืžื—ื™ื ืฉื•ื‘ ื•ืฉื•ื‘.
04:14
They keep doing it; they just keep making these things.
88
254260
3000
ื”ื ืžืžืฉื™ื›ื™ื ืœืขืฉื•ืช ื–ืืช; ื”ื ืคืฉื•ื˜ ืžืžืฉื™ื›ื™ื ืœืขืฉื•ืช ืืช ื”ื“ื‘ืจื™ื ื”ืืœื”.
04:17
And then, then, then, and then ...
89
257260
4000
ื•ืื–, ืื–, ืื–, ื•ืื–...
04:21
Then the dinosaurs, being social,
90
261260
3000
ืื– ื”ื“ื™ื ื•ื–ืื•ืจื™ื, ื‘ื”ื™ื•ืชื ื—ื‘ืจืชื™ื™ื,
04:24
act out their socialness,
91
264260
3000
ืžื™ื™ืฉืžื™ื ืืช ื”ื—ื‘ืจืชื™ื•ืช ืฉืœื”ื.
04:27
and they get together,
92
267260
2000
ื•ื”ื ืžืชืงื‘ืฆื™ื ื™ื—ื“,
04:29
and they conspire.
93
269260
3000
ื•ื”ื ืขื•ืฉื™ื ืงื ื•ื ื™ื™ื”.
04:32
And, of course, that's what makes Steven Spielberg's movie --
94
272260
4000
ื•ื›ืžื•ื‘ืŸ, ื–ื” ืžื” ืฉืขื•ืฉื” ืืช ื”ืกืจื˜ ืฉืœ ืกืคื™ืœื‘ืจื’ --
04:36
conspiring dinosaurs chasing people around.
95
276260
3000
ื“ื™ื ื•ื–ืื•ืจื™ื ืชื—ืžื ื™ื ืฉืจื•ื“ืคื™ื ืื—ืจื™ ืื ืฉื™ื.
04:39
So I assume everybody knows
96
279260
2000
ืื ื™ ืžื ื™ื— ืฉื›ื•ืœื ื™ื•ื“ืขื™ื
04:41
that if you actually had a piece of amber and it had an insect in it,
97
281260
3000
ืฉืื ื‘ืืžืช ื”ื™ืชื” ืœื›ื ื—ืชื™ื›ื” ืฉืœ ืขื ื‘ืจ ื•ื”ื™ื” ื‘ืชื•ื›ื• ื—ืจืง,
04:44
and you drilled into it,
98
284260
3000
ื•ื”ื™ื™ืชื ืงื•ื“ื—ื™ื ื‘ื•,
04:47
and you got something out of that insect,
99
287260
2000
ื•ืžืฆืœื™ื—ื™ื ืœื”ื•ืฆื™ื ืžืฉื”ื• ืžื”ื—ืจืง ื”ื–ื”,
04:49
and you cloned it, and you did it over and over and over again,
100
289260
3000
ื•ืžืฉื‘ื˜ื™ื ืื•ืชื• ืฉื•ื‘ ื•ืฉื•ื‘ ื•ืฉื•ื‘,
04:52
you'd have a room full of mosquitos.
101
292260
2000
ื”ื™ื™ืชื ืžืงื‘ืœื™ื ื—ื“ืจ ืžืœื ื™ืชื•ืฉื™ื.
04:54
(Laughter)
102
294260
2000
(ืฆื—ื•ืง)
04:56
(Applause)
103
296260
5000
(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
05:01
And probably a whole bunch of trees as well.
104
301260
3000
ื•ื›ื ืจืื” ื’ื ื›ืžื” ืžื”ืขืฆื™ื ื”ืืœื”.
05:04
Now if you want dinosaur DNA,
105
304260
2000
ืื– ืื ืืชื ืจื•ืฆื™ื ื“ื "ื ืฉืœ ื“ื™ื ื•ื–ืื•ืจ,
05:06
I say go to the dinosaur.
106
306260
3000
ืื ื™ ืื•ืžืจ - ืœื›ื• ืœื“ื™ื ื•ื–ืื•ืจ.
05:09
So that's what we've done.
107
309260
2000
ื•ื–ื” ืžื” ืฉืขืฉื™ื ื•.
05:11
Back in 1993 when the movie came out,
108
311260
2000
ื‘-1993 ื›ืฉื”ืกืจื˜ ื™ืฆื,
05:13
we actually had a grant from the National Science Foundation
109
313260
3000
ืงื™ื‘ืœื ื• ืžืขื ืง ืžืงืจืŸ ื”ืžื“ืข ื”ืœืื•ืžื™ืช
05:16
to attempt to extract DNA from a dinosaur,
110
316260
3000
ืขืœ ืžื ืช ืœื ืกื•ืช ื•ืœื”ืคื™ืง ื“ื "ื ืžื“ื™ื ื•ื–ืื•ืจ.
05:19
and we chose the dinosaur on the left,
111
319260
3000
ื•ื‘ื—ืจื ื• ื‘ื“ื™ื ื•ื–ืื•ืจ ืžืฉืžืืœ,
05:22
a Tyrannosaurus rex, which was a very nice specimen.
112
322260
3000
ื˜ื™ืจื ื•ื–ืื•ืจื•ืก ืจืงืก, ืฉื”ื™ื” ืžืžืฆื ืžืื•ื“ ื™ืคื”.
05:25
And one of my former doctoral students,
113
325260
2000
ื•ืื—ืช ืžืชืœืžื™ื“ื•ืช ื”ื“ื•ืงื˜ื•ืจื˜ ืฉืœื™ ืœืฉืขื‘ืจ,
05:27
Dr. Mary Schweitzer,
114
327260
2000
ื“"ืจ ืžืจื™ ืฉื•ื•ื™ื™ืฆืจ,
05:29
actually had the background
115
329260
2000
ื”ื™ื” ืœื” ื”ืจืงืข ื”ื ื“ืจืฉ
05:31
to do this sort of thing.
116
331260
2000
ื›ื“ื™ ืœืขืฉื•ืช ืžืฉื”ื• ื›ื–ื”.
05:33
And so she looked into the bone of this T. rex,
117
333260
3000
ื•ื”ื™ื ื”ืชื‘ื•ื ื ื” ื‘ืขืฆื ื”ื–ื• ืฉืœ ื”ื˜ื™. ืจืงืก,
05:36
one of the thigh bones,
118
336260
2000
ืื—ืช ืžืขืฆืžื•ืช ื”ื™ืจืš,
05:38
and she actually found
119
338260
2000
ื•ื”ื™ื ืžืฆืื”
05:40
some very interesting structures in there.
120
340260
3000
ืžื‘ื ื™ื ืžืื•ื“ ืžืขื ื™ื™ื ื™ื ืฉื ื‘ืคื ื™ื.
05:43
They found these red circular-looking objects,
121
343260
4000
ื”ื ืžืฆืื• ื’ื•ืคื™ื ืฉื ืจืื• ืื“ื•ืžื™ื ืžืขื•ื’ืœื™ื ื›ืืœื”.
05:47
and they looked, for all the world,
122
347260
2000
ื•ื”ื ื ืจืื• ืœื›ืœ ื”ืขื•ืœื
05:49
like red blood cells.
123
349260
2000
ื›ืžื• ืชืื™ ื“ื ืื“ื•ืžื™ื.
05:51
And they're in
124
351260
2000
ื•ื”ื ื ืžืฆืื™ื ื‘ืชื•ืš
05:53
what appear to be the blood channels
125
353260
2000
ืžื” ืฉื ืจืื” ื›ืžื• ืชืขืœื•ืช ื“ื
05:55
that go through the bone.
126
355260
2000
ืฉืขื•ื‘ืจื•ืช ื“ืจืš ื”ืขืฆื.
05:57
And so she thought, well, what the heck.
127
357260
3000
ื•ื”ื™ื ื—ืฉื‘ื”, ื•ื‘ื›ืŸ, ืœืžื” ืœื?
06:00
So she sampled some material out of it.
128
360260
3000
ื•ื”ื™ื ื“ื’ืžื” ื—ืœืง ืžื”ื—ื•ืžืจ ืžืชื•ืš ื”ืขืฆื.
06:03
Now it wasn't DNA; she didn't find DNA.
129
363260
3000
ื•ื–ื” ืœื ื”ื™ื” ื“ื "ื; ื”ื™ื ืœื ืžืฆืื” ื“ื "ื.
06:06
But she did find heme,
130
366260
3000
ืื‘ืœ ื”ื™ื ืžืฆืื” ื”ื (heme),
06:09
which is the biological foundation
131
369260
2000
ืฉื–ื” ื”ืชืฉืชื™ืช ื”ื‘ื™ื•ืœื•ื’ื™ืช
06:11
of hemoglobin.
132
371260
2000
ืฉืœ ื”ืžื•ื’ืœื•ื‘ื™ืŸ.
06:13
And that was really cool.
133
373260
2000
ื•ื–ื” ื”ื™ื” ืžืžืฉ ืžื’ื ื™ื‘.
06:15
That was interesting.
134
375260
2000
ื–ื” ื”ื™ื” ืžืขื ื™ื™ืŸ.
06:17
That was -- here we have 65-million-year-old heme.
135
377260
5000
ื–ื” ื”ื™ื” -- ื”ื ื” ื™ืฉ ืœื ื• ื”ื ื‘ืŸ 65 ืžื™ืœื™ื•ืŸ ืฉื ื”.
06:22
Well we tried and tried
136
382260
2000
ื•ื ื™ืกื™ื ื•, ื•ื ื™ืกื™ื ื•
06:24
and we couldn't really get anything else out of it.
137
384260
2000
ื•ืœื ืžืžืฉ ื”ืฆืœื—ื ื• ืœื”ื•ืฆื™ื ืžื–ื” ืฉื•ื ื“ื‘ืจ ื ื•ืกืฃ.
06:26
So a few years went by,
138
386260
2000
ื•ื›ืš ืขื‘ืจื• ื›ืžื” ืฉื ื™ื,
06:28
and then we started the Hell Creek Project.
139
388260
2000
ื•ืื– ื”ืชื—ืœื ื• ืืช ืคืจื•ื™ื™ืงื˜ "ื”ืœ ืงืจื™ืง".
06:30
And the Hell Creek Project was this massive undertaking
140
390260
3000
ื•ืคืจื•ื™ื™ืงื˜ "ื”ืœ ืงืจื™ืง" ื”ื™ื” ืžืืžืฅ ืื“ื™ืจ
06:33
to get as many dinosaurs as we could possibly find,
141
393260
3000
ืœืžืฆื•ื ืžื” ืฉื™ื•ืชืจ ื“ื™ื ื•ื–ืื•ืจื™ื ื›ื›ืœ ืฉื™ื“ื ื• ืžืฉื’ืช,
06:36
and hopefully find some dinosaurs
142
396260
2000
ื‘ืชืงื•ื•ื” ืฉื ืžืฆื ื›ืžื” ื“ื™ื ื•ื–ืื•ืจื™ื
06:38
that had more material in them.
143
398260
3000
ืฉื™ืฉ ื‘ื”ื ืขื•ื“ ื—ื•ืžืจ.
06:41
And out in eastern Montana
144
401260
3000
ื•ืฉื ื‘ืžื–ืจื— ืžื•ื ื˜ื ื”
06:44
there's a lot of space, a lot of badlands,
145
404260
2000
ื™ืฉ ื”ืจื‘ื” ืžืงื•ื, ื”ืจื‘ื” ืฉื˜ื—ื™ื ืคืชื•ื—ื™ื,
06:46
and not very many people,
146
406260
2000
ื•ืœื ื”ืจื‘ื” ืื ืฉื™ื.
06:48
and so you can go out there and find a lot of stuff.
147
408260
2000
ื•ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืฆืืช ืœืฉื ื•ืœืžืฆื•ื ื”ืจื‘ื” ื“ื‘ืจื™ื.
06:50
And we did find a lot of stuff.
148
410260
2000
ื•ืžืฆืื ื• ื”ืจื‘ื” ื“ื‘ืจื™ื.
06:52
We found a lot of Tyrannosaurs,
149
412260
2000
ืžืฆืื ื• ื”ืจื‘ื” ื˜ื™ืจื ื•ื–ืื•ืจื•ืกื™ื,
06:54
but we found one special Tyrannosaur,
150
414260
2000
ืื‘ืœ ืžืฆืื ื• ื˜ื™ืจื ื•ื–ืื•ืจ ืื—ื“ ืžืกื•ื™ื,
06:56
and we called it B-rex.
151
416260
2000
ื•ืงืจืื ื• ืœื• ื‘ื™. ืจืงืก.
06:58
And B-rex was found
152
418260
2000
ื•ืืช ื”ื‘ื™. ืจืงืก ืžืฆืื ื•
07:00
under a thousand cubic yards of rock.
153
420260
2000
ืžืชื—ืช ืืœืคื™ ืžื˜ืจื™ื ืžืขื•ืงื‘ื™ื ืฉืœ ืกืœืข.
07:02
It wasn't a very complete T. rex,
154
422260
3000
ื•ื–ื” ืœื ื”ื™ื” ื˜ื™. ืจืงืก ืžืื•ื“ ืฉืœื,
07:05
and it wasn't a very big T. rex,
155
425260
3000
ื•ื–ื” ืœื ื”ื™ื” ื˜ื™. ืจืงืก ืžืื•ื“ ื’ื“ื•ืœ,
07:08
but it was a very special B-rex.
156
428260
3000
ืื‘ืœ ื–ื” ื”ื™ื” ื‘ื™. ืจืงืก ืžืื•ื“ ืžื™ื•ื—ื“.
07:11
And I and my colleagues cut into it,
157
431260
2000
ื•ืื ื™ ื•ืขืžื™ืชื™ื™ ื—ืชื›ื ื• ืœืชื•ื›ื•,
07:13
and we were able to determine,
158
433260
2000
ื•ื™ื›ื•ืœื ื• ืœืงื‘ื•ืข,
07:15
by looking at lines of arrested growth, some lines in it,
159
435260
3000
ืขืœ ื™ื“ื™ ื”ืชื‘ื•ื ื ื•ืช ื‘ืงื•ื•ื™ ื’ื™ื“ื•ืœ, ื›ืžื” ืงื•ื•ื™ื ื‘ืชื•ื›ื•,
07:18
that B-rex had died at the age of 16.
160
438260
3000
ืฉื”ื‘ื™. ืจืงืก ืžืช ื‘ื’ื™ืœ 16.
07:21
We don't really know how long dinosaurs lived,
161
441260
3000
ืื ื• ืœื ืžืžืฉ ื™ื•ื“ืขื™ื ื›ืžื” ืฉื ื™ื ื—ื™ื• ื“ื™ื ื•ื–ืื•ืจื™ื,
07:24
because we haven't found the oldest one yet.
162
444260
2000
ื‘ื’ืœืœ ืฉืขื•ื“ ืœื ืžืฆืื ื• ืืช ื”ื–ืงืŸ ื‘ื™ื•ืชืจ.
07:26
But this one died at the age of 16.
163
446260
3000
ืื‘ืœ ื”ืื—ื“ ื”ื–ื” ืžืช ื‘ื’ื™ืœ 16.
07:29
We gave samples to Mary Schweitzer,
164
449260
2000
ื”ื‘ืื ื• ื“ื•ื’ืžืื•ืช ืœืžืจื™ ืฉื•ื•ื™ื™ืฆืจ,
07:31
and she was actually able to determine
165
451260
2000
ื•ื”ื™ื ื™ื›ืœื” ืœืงื‘ื•ืข
07:33
that B-rex was a female
166
453260
2000
ืฉื”ื‘ื™. ืจืงืก ื”ื™ื” ืœืžืขืฉื” ื ืงื‘ื”
07:35
based on medullary tissue
167
455260
2000
ื‘ื”ืชื‘ืกืก ืขืœ ืจืงืžื•ืช ืคื ื™ืžื™ื•ืช
07:37
found on the inside of the bone.
168
457260
2000
ืฉื ืžืฆืื• ื‘ืชื•ืš ื”ืขืฆื.
07:39
Medullary tissue is the calcium build-up,
169
459260
3000
ื”ืจืงืžื•ืช ื”ืคื ื™ืžื™ื•ืช ื”ืŸ ืžืคืขืœ ื”ืกื™ื“ืŸ,
07:42
the calcium storage basically,
170
462260
2000
ืžืื’ืจ ื”ืกื™ื“ืŸ, ืœืžืขืฉื”,
07:44
when an animal is pregnant,
171
464260
2000
ืฉืžืฉืžืฉ ื—ื™ื” ืฉื ืžืฆืืช ื‘ื”ืจื™ื•ืŸ,
07:46
when a bird is pregnant.
172
466260
2000
ืฆื™ืคื•ืจ ืฉื ืžืฆืืช ื‘ื”ืจื™ื•ืŸ.
07:48
So here was the character
173
468260
2000
ืื– ื”ื ื” ื ืžืฆื ืžืืคื™ื™ืŸ
07:50
that linked birds and dinosaurs.
174
470260
2000
ืฉืžืงืฉืจ ืฆื™ืคื•ืจื™ื ื•ื“ื™ื ื•ื–ืื•ืจื™ื.
07:52
But Mary went further.
175
472260
2000
ืื‘ืœ ืžืจื™ ื”ืžืฉื™ื›ื” ื”ืœืื”.
07:54
She took the bone, and she dumped it into acid.
176
474260
3000
ื”ื™ื ืœืงื—ื” ืืช ื”ืขืฆื, ื•ื–ืจืงื” ืื•ืชื” ืœื—ื•ืžืฆื”.
07:57
Now we all know that bones are fossilized,
177
477260
3000
ื›ื•ืœื ื• ื™ื•ื“ืขื™ื ืฉืขืฆืžื•ืช ื”ืŸ ืžืื•ื‘ื ื•ืช,
08:00
and so if you dump it into acid,
178
480260
2000
ื•ืื ืชื–ืจื•ืง ืื•ืชื ืœืชื•ืš ื—ื•ืžืฆื”,
08:02
there shouldn't be anything left.
179
482260
2000
ืœื ืืžื•ืจ ืœื”ื™ืฉืืจ ื“ื‘ืจ.
08:04
But there was something left.
180
484260
2000
ืื‘ืœ ืžืฉื”ื• ื ืฉืืจ.
08:06
There were blood vessels left.
181
486260
3000
ื ืฉืืจื• ืฉื ื›ืœื™ ื“ื.
08:09
There were flexible, clear blood vessels.
182
489260
4000
ื”ื ื”ื™ื• ื›ืœื™ ื“ื ื’ืžื™ืฉื™ื, ื•ืฉืงื•ืคื™ื.
08:13
And so here was the first soft tissue from a dinosaur.
183
493260
3000
ื•ื”ื ื” ื ืžืฆื ื”ืื™ื‘ืจ ื”ืจืš ื”ืจืืฉื•ืŸ ืžืชื•ืš ื“ื™ื ื•ื–ืื•ืจ.
08:16
It was extraordinary.
184
496260
2000
ื–ื” ื”ื™ื” ื™ื•ืฆื ื“ื•ืคืŸ.
08:18
But she also found osteocytes,
185
498260
3000
ืื‘ืœ ื”ื™ื ื’ื ืžืฆืื” ืื•ืกื˜ื™ืื•ืฆื™ื˜ื™ื (ืชืื™ ืขืฆื),
08:21
which are the cells that laid down the bones.
186
501260
3000
ืฉื”ื ื”ืชืื™ื ืฉืžืจื›ื™ื‘ื™ื ืืช ื”ืขืฆืžื•ืช.
08:24
And try and try, we could not find DNA,
187
504260
4000
ื•ื ืกื™ื•ืŸ ืื—ืจ ื ืกื™ื•ืŸ, ืœื ื”ืฆืœื—ื ื• ืœืžืฆื•ื ื“ื "ื,
08:28
but she did find evidence of proteins.
188
508260
3000
ืื‘ืœ ื”ื™ื ืžืฆืื” ืจืื™ื•ืช ืœืงื™ื•ืžื ืฉืœ ื—ืœื‘ื•ื ื™ื.
08:31
But we thought maybe --
189
511260
3000
ื•ื—ืฉื‘ื ื• ืื•ืœื™ --
08:34
well, we thought maybe
190
514260
2000
ื•ื‘ื›ืŸ, ื—ืฉื‘ื ื• ืื•ืœื™
08:36
that the material was breaking down after it was coming out of the ground.
191
516260
3000
ืฉื”ื—ื•ืžืจ ืžืชืคืจืง ื•ืงื•ืจืก ืื—ืจื™ ืฉืžื•ืฆื™ืื™ื ืื•ืชื• ืžืชื•ืš ื”ืงืจืงืข.
08:39
We thought maybe it was deteriorating very fast.
192
519260
2000
ื—ืฉื‘ื ื• ืฉืื•ืœื™ ื”ื•ื ืžืชื‘ืœื” ืžืื•ื“ ืžื”ืจ.
08:41
And so we built a laboratory
193
521260
2000
ืื– ื‘ื ื™ื ื• ืžืขื‘ื“ื”
08:43
in the back of an 18-wheeler trailer,
194
523260
3000
ืžืื—ื•ืจื™ ืžืฉืื™ืช ื˜ืจื™ื™ืœืจ 18 ื’ืœื’ืœื™ื,
08:46
and actually took the laboratory to the field
195
526260
3000
ื•ืžืžืฉ ื”ื‘ืื ื• ืืช ื”ืžืขื‘ื“ื” ืœืฉื“ื”
08:49
where we could get better samples.
196
529260
2000
ื”ื™ื›ืŸ ืฉื™ื›ื•ืœื ื• ืœื”ืฉื™ื’ ืžืžืฆืื™ื ื˜ื•ื‘ื™ื.
08:51
And we did. We got better material.
197
531260
3000
ื•ืžืฆืื ื•. ื”ืฉื’ื ื• ื—ื•ืžืจ ื˜ื•ื‘ ื™ื•ืชืจ.
08:54
The cells looked better.
198
534260
2000
ื”ืชืื™ื ื ืจืื• ื™ื•ืชืจ ื˜ื•ื‘.
08:56
The vessels looked better.
199
536260
2000
ื›ืœื™ ื”ื“ื ื ืจืื• ื™ื•ืชืจ ื˜ื•ื‘.
08:58
Found the protein collagen.
200
538260
2000
ืžืฆืื ื• ื—ืœื‘ื•ื ื™ ืงื•ืœื’ืŸ (ืกื—ื•ืก).
09:00
I mean, it was wonderful stuff.
201
540260
3000
ื–ื” ื”ื™ื” ื—ื•ืžืจ ื ื”ื“ืจ.
09:03
But it's not dinosaur DNA.
202
543260
4000
ืื‘ืœ ื–ื” ืœื ื“ื "ื ืฉืœ ื“ื™ื ื•ื–ืื•ืจ.
09:07
So we have discovered
203
547260
2000
ืื– ื’ื™ืœื™ื ื•
09:09
that dinosaur DNA, and all DNA,
204
549260
2000
ืฉื“ื "ื ืฉืœ ื“ื™ื ื•ื–ืื•ืจ, ื•ื›ืœ ืกื•ื’ ืฉืœ ื“ื "ื,
09:11
just breaks down too fast.
205
551260
2000
ืคืฉื•ื˜ ืžืชืคืจืง ืžื”ืจ ืžื“ื™.
09:13
We're just not going to be able
206
553260
2000
ืœื ืชื”ื™ื” ืœื ื• ืืคืฉืจื•ืช ืœืขืฉื•ืช
09:15
to do what they did in "Jurassic Park."
207
555260
3000
ืžื” ืฉืขืฉื• ื‘-"ืคืืจืง ื”ื™ื•ืจื”".
09:18
We're not going to be able to make a dinosaur
208
558260
3000
ืœื ื ื”ื™ื” ืžืกื•ื’ืœื™ื ืœืขืฉื•ืช ื“ื™ื ื•ื–ืื•ืจ
09:21
based on a dinosaur.
209
561260
3000
ื‘ื”ืชื‘ืกืก ืขืœ ื“ื™ื ื•ื–ืื•ืจ.
09:24
But birds are dinosaurs.
210
564260
4000
ืื‘ืœ ืฆื™ืคื•ืจื™ื ื”ืŸ ื“ื™ื ื•ื–ืื•ืจื™ื.
09:29
Birds are living dinosaurs.
211
569260
3000
ืฆื™ืคื•ืจื™ื ื”ืŸ ื“ื™ื ื•ื–ืื•ืจื™ื ื—ื™ื™ื.
09:32
We actually classify them
212
572260
2000
ืื ื—ื ื• ืžืžืฉ ืžืกื•ื•ื’ื™ื ืื•ืชื (ื‘ื™ื•ืœื•ื’ื™ืช)
09:34
as dinosaurs.
213
574260
2000
ื›ื“ื™ื ื•ื–ืื•ืจื™ื.
09:36
We now call them non-avian dinosaurs
214
576260
2000
ืื ื—ื ื• ืงื•ืจืื™ื ืœื”ื ืขื›ืฉื™ื• ื“ื™ื ื•ื–ืื•ืจื™ื ืœื ืžืขื•ืคืคื™ื
09:38
and avian dinosaurs.
215
578260
2000
ื•ื“ื™ื ื•ื–ืื•ืจื™ื ืžืขื•ืคืคื™ื.
09:40
So the non-avian dinosaurs
216
580260
2000
ืื– ื”ื“ื™ื ื•ื–ืื•ืจื™ื ื”ืœื ืžืขื•ืคืคื™ื
09:42
are the big clunky ones that went extinct.
217
582260
2000
ื”ื ื”ื™ืฆื•ืจื™ื ื”ื’ื“ื•ืœื™ื ื”ืžื’ื•ืฉืžื™ื ื”ืืœื” ืฉื ื›ื—ื“ื•.
09:44
Avian dinosaurs are our modern birds.
218
584260
3000
ื“ื™ื ื•ื–ืื•ืจื™ื ืžืขื•ืคืคื™ื ื”ื ื”ืฆื™ืคื•ืจื™ื ื”ืžื•ื“ืจื ื™ื•ืช ืฉืœื ื•.
09:47
So we don't have to make a dinosaur
219
587260
2000
ืื– ืื ื—ื ื• ื‘ื›ืœืœ ืœื ืฆืจื™ื›ื™ื "ืœื™ื™ืฆืจ" ื“ื™ื ื•ื–ืื•ืจ;
09:49
because we already have them.
220
589260
3000
ื‘ื’ืœืœ ืฉื›ื‘ืจ ื™ืฉ ืœื ื• ืื•ืชื.
09:54
(Laughter)
221
594260
4000
(ืฆื—ื•ืง)
09:58
I know, you're as bad as the sixth-graders.
222
598260
4000
ืื ื™ ื™ื•ื“ืข, ืืชื ื’ืจื•ืขื™ื ื›ืžื• ื”ื™ืœื“ื™ื ืžื›ื™ืชื” ื•'.
10:02
(Laughter)
223
602260
2000
(ืฆื—ื•ืง)
10:04
The sixth-graders look at it and they say, "No."
224
604260
3000
ื”ื™ืœื“ื™ื ืžื›ื™ืชื” ื•' ืžืกืชื›ืœื™ื ืขืœ ื–ื” ื•ืื•ืžืจื™ื, "ืœื."
10:07
(Laughter)
225
607260
2000
(ืฆื—ื•ืง)
10:09
"You can call it a dinosaur,
226
609260
2000
"ืืชื” ื™ื›ื•ืœ ืœืงืจื•ื ืœื–ื” ื“ื™ื ื•ื–ืื•ืจ,
10:11
but look at the velociraptor: the velociraptor is cool."
227
611260
3000
ืื‘ืœ ืชืกืชื›ืœ ืขืœ ื”ื•ืœื•ืกื™ืจืคื˜ื•ืจ: ื”ื•ืœื•ืกื™ืจืคื˜ื•ืจ ืžื’ื ื™ื‘."
10:14
(Laughter)
228
614260
2000
(ืฆื—ื•ืง)
10:16
"The chicken is not."
229
616260
2000
"ื”ืชืจื ื’ื•ืœืช ืœื."
10:18
(Laughter)
230
618260
2000
(ืฆื—ื•ืง)
10:20
So this is our problem,
231
620260
2000
ืื– ื–ืืช ื”ื‘ืขื™ื” ืฉืœื ื•.
10:22
as you can imagine.
232
622260
3000
ื›ืคื™ ืฉืืชื ื™ื›ื•ืœื™ื ืœื“ืžื™ื™ืŸ.
10:25
The chicken is a dinosaur.
233
625260
2000
ื”ืชืจื ื’ื•ืœืช ื”ื™ื ื“ื™ื ื•ื–ืื•ืจ.
10:27
I mean it really is.
234
627260
2000
ืื ื™ ื‘ืืžืช ืžืชื›ื•ื•ืŸ ืœื–ื”.
10:29
You can't argue with it
235
629260
2000
ืืชื ืœื ื™ื›ื•ืœื™ื ืœื”ืชื•ื•ื›ื— ืขื ื–ื”.
10:31
because we're the classifiers and we've classified it that way.
236
631260
3000
ื‘ื’ืœืœ ืฉืื ื—ื ื• ืืœื” ืฉืžืกื•ื•ื’ื™ื, ื•ื›ื›ื” ืกื™ื•ื•ื’ื ื• ืื•ืชื.
10:34
(Laughter)
237
634260
2000
(ืฆื—ื•ืง)
10:36
(Applause)
238
636260
4000
(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
10:41
But the sixth-graders demand it.
239
641260
2000
ืื‘ืœ ื™ืœื“ื™ ื›ื™ืชื” ื•' ื“ื•ืจืฉื™ื ืืช ื–ื”.
10:43
"Fix the chicken."
240
643260
2000
"ืชืงืŸ ืืช ื”ืชืจื ื’ื•ืœืช."
10:45
(Laughter)
241
645260
2000
(ืฆื—ื•ืง)
10:47
So that's what I'm here to tell you about:
242
647260
2000
ืื– ืขืœ ื–ื” ื‘ืืชื™ ืœื“ื‘ืจ ืื™ืชื›ื:
10:49
how we are going to fix a chicken.
243
649260
3000
ืื™ืš ืื ื—ื ื• ืžืชื›ื•ื•ื ื™ื ืœืชืงืŸ ืชืจื ื’ื•ืœืช.
10:52
So we have a number of ways
244
652260
3000
ืื– ื™ืฉ ืœื ื• ื›ืžื” ื“ืจื›ื™ื
10:55
that we actually can fix the chicken.
245
655260
5000
ืฉื‘ื”ืŸ ืื ื—ื ื• ืžืžืฉ ื™ื›ื•ืœื™ื ืœืชืงืŸ ืืช ื”ืชืจื ื’ื•ืœืช.
11:00
Because evolution works,
246
660260
2000
ื‘ื’ืœืœ ืฉื”ืื‘ื•ืœื•ืฆื™ื” ืขื•ื‘ื“ืช,
11:02
we actually have some evolutionary tools.
247
662260
3000
ื™ืฉ ืœื ื• ื›ืžื” ื›ืœื™ื ืื‘ื•ืœื•ืฆื™ื•ื ื™ื™ื.
11:05
We'll call them biological modification tools.
248
665260
3000
ื ืงืจื ืœื”ื ื›ืœื™ ื”ืชืืžื” ื‘ื™ื•ืœื•ื’ื™ื™ื.
11:08
We have selection.
249
668260
2000
ื™ืฉ ืœื ื• ื”ืฉื‘ื—ื”.
11:10
And we know selection works.
250
670260
2000
ื•ืื ื—ื ื• ื™ื•ื“ืขื™ื ืฉื”ื”ืฉื‘ื—ื” ืขื•ื‘ื“ืช.
11:12
We started out with a wolf-like creature
251
672260
3000
ื”ืชื—ืœื ื• ืขื ื™ืฆื•ืจ ื“ืžื•ื™ ื–ืื‘
11:15
and we ended up with a Maltese.
252
675260
3000
ื•ืงื™ื‘ืœื ื• ืืช ื”ืžืœื˜ื–ื™ (ื›ืœื‘).
11:18
I mean, that's --
253
678260
3000
ืื ื™ ืžืชื›ื•ื•ืŸ, ื–ื” --
11:21
that's definitely genetic modification.
254
681260
4000
ื–ื” ื‘ื”ื—ืœื˜ ืฉื™ื ื•ื™ ื’ื ื˜ื™.
11:25
Or any of the other funny-looking little dogs.
255
685260
4000
ืื• ืื—ื“ ืื—ืจ ืžืชื•ืš ืžื™ื ื™ ื”ื›ืœื‘ื™ื ื”ืงื˜ื ื™ื ื”ืžืฆื—ื™ืงื™ื.
11:30
We also have transgenesis.
256
690260
2000
ื™ืฉ ืœื ื• ื”ืฉืชืœื” ื’ื ื˜ื™ืช.
11:32
Transgenesis is really cool too.
257
692260
2000
ื”ืฉืชืœื” ื’ื ื˜ื™ืช ื”ื™ื ื’ื ืžืžืฉ ืžื’ื ื™ื‘ื”.
11:34
That's where you take a gene out of one animal and stick it in another one.
258
694260
3000
ื–ื” ื›ืฉืืชื” ืœื•ืงื— ื’ืŸ ืžืชื•ืš ื—ื™ื” ืื—ืช ื•ืชื•ืงืข ืื•ืชื• ื‘ืื—ืจืช.
11:37
That's how people make GloFish.
259
697260
3000
ื›ื›ื” ืื ืฉื™ื ื™ื•ืฆืจื™ื ื“ื’ื™ื ื–ื•ื”ืจื™ื.
11:40
You take a glow gene
260
700260
3000
ืœื•ืงื—ื™ื ื’ืŸ ื–ืจื—ื ื™
11:43
out of a coral or a jellyfish
261
703260
4000
ืžืชื•ืš ืืœืžื•ื’ ืื• ืžื“ื•ื–ื”
11:47
and you stick it in a zebrafish,
262
707260
2000
ื•ืชื•ืงืขื™ื ืื•ืชื• ื‘ื“ื’ ื–ื‘ืจื”,
11:49
and, puff, they glow.
263
709260
2000
ื•-- ืคื•ืฃืฃ -- ื”ื ื–ื•ื”ืจื™ื.
11:51
And that's pretty cool.
264
711260
2000
ื•ื–ื” ื“ื™ ืžื’ื ื™ื‘.
11:53
And they obviously make a lot of money off of them.
265
713260
3000
ื•ื›ืžื•ื‘ืŸ ื”ื ืขื•ืฉื™ื ืžื–ื” ื”ืจื‘ื” ื›ืกืฃ.
11:56
And now they're making Glow-rabbits
266
716260
2000
ืขื›ืฉื™ื• ื”ื ืขื•ืฉื™ื ื’ื ืืจื ื‘ื™ื ื–ื•ื”ืจื™ื
11:58
and Glow-all-sorts-of-things.
267
718260
2000
ื•ื›ืœ ืžื™ื ื™ ื“ื‘ืจื™ื ืื—ืจื™ื ื–ื•ื”ืจื™ื.
12:00
I guess we could make a glow chicken.
268
720260
3000
ืื ื™ ืžื ื™ื— ืฉื ื•ื›ืœ ืœื™ืฆื•ืจ ืชืจื ื’ื•ืœืช ื–ื•ื”ืจืช.
12:03
(Laughter)
269
723260
2000
(ืฆื—ื•ืง)
12:05
But I don't think that'll satisfy the sixth-graders either.
270
725260
3000
ืื‘ืœ ืœื ื ืจืื” ืœื™ ืฉื–ื” ื™ืกืคืง ืืช ื”ื™ืœื“ื™ื ืžื›ื™ืชื” ื•'.
12:08
But there's another thing.
271
728260
2000
ืื‘ืœ ื™ืฉ ืžืฉื”ื• ืื—ืจ.
12:10
There's what we call atavism activation.
272
730260
3000
ื™ืฉ ืžื” ืฉืื ื• ืงื•ืจืื™ื ื”ืคืขืœืช ื’ื ื™ื ืจื“ื•ืžื™ื.
12:13
And atavism activation
273
733260
2000
ื•ื”ืคืขืœืช ื’ื ื™ื ืจื“ื•ืžื™ื
12:15
is basically --
274
735260
2000
ื”ื™ื ืœืžืขืฉื” --
12:17
an atavism is an ancestral characteristic.
275
737260
4000
ื’ืŸ ืจื“ื•ื ื”ื•ื ืžืืคื™ื™ืŸ ืฉื™ืฆื•ืจ ื™ืจืฉ ืžืื‘ื•ืชื™ื•.
12:21
You heard
276
741260
2000
ืฉืžืขืชื
12:23
that occasionally children are born with tails,
277
743260
3000
ืฉืœืคืขืžื™ื ื™ืœื“ื™ื ื ื•ืœื“ื™ื ืขื ื–ื ื‘ื•ืช,
12:26
and it's because it's an ancestral characteristic.
278
746260
4000
ื•ื–ื” ื‘ื’ืœืœ ืฉื–ื• ืชื›ื•ื ื” ืฉื™ืจืฉื ื• ืžืื‘ื•ืชื™ื ื•.
12:30
And so there are a number of atavisms
279
750260
3000
ื•ื›ืš ื™ืฉ ื›ืžื” ื”ืชืขื•ืจืจื•ื™ื•ืช ืฉืœ ื’ื ื™ื ืจื“ื•ืžื™ื ื›ืืœื”
12:33
that can happen.
280
753260
2000
ืฉื™ื›ื•ืœื•ืช ืœื”ืชืจื—ืฉ.
12:35
Snakes are occasionally born with legs.
281
755260
3000
ื ื—ืฉื™ื ืœืคืขืžื™ื ื ื•ืœื“ื™ื ืขื ืจื’ืœื™ื™ื.
12:38
And here's an example.
282
758260
2000
ื•ื”ื ื” ื“ื•ื’ืžื.
12:40
This is a chicken with teeth.
283
760260
3000
ื”ื ื” ืชืจื ื’ื•ืœืช ืขื ืฉื™ื ื™ื™ื.
12:43
A fellow by the name of Matthew Harris
284
763260
2000
ืขืžื™ืช ืฉืœื™ ื‘ืฉื ืžืช'ื™ื• ื”ืจื™ืก
12:45
at the University of Wisconsin in Madison
285
765260
3000
ืžืื•ื ื™ื‘ืจืกื™ื˜ืช ื•ื•ื™ืกืงื•ื ืกื™ืŸ ื‘ืžื“ื™ืกื•ืŸ
12:48
actually figured out a way to stimulate
286
768260
3000
ืžืฆื ื“ืจืš ืœืขื•ืจืจ
12:51
the gene for teeth,
287
771260
3000
ืืช ื”ื’ืŸ ืœืฉื™ื ื™ื™ื,
12:54
and so was able to actually turn the tooth gene on
288
774260
3000
ื•ื›ืš ื”ื•ื ื™ื›ื•ืœ ื”ื™ื” ืœื”ืคืขื™ืœ ืืช ื’ืŸ ื”ืฉื™ื ื™ื™ื
12:57
and produce teeth in chickens.
289
777260
3000
ื•ืœื™ื™ืฆืจ ืฉื™ื ื™ื™ื ื‘ืชืจื ื’ื•ืœื•ืช.
13:00
Now that's a good characteristic.
290
780260
3000
ืื– ื–ื” ืžืืคื™ื™ืŸ ื˜ื•ื‘.
13:03
We can save that one.
291
783260
3000
ืืคืฉืจ ืœืฉืžื•ืจ ืื•ืชื•.
13:06
We know we can use that.
292
786260
2000
ืื ื• ื™ื•ื“ืขื™ื ืฉืืคืฉืจ ืœื”ืฉืชืžืฉ ื‘ื•.
13:08
We can make a chicken with teeth.
293
788260
3000
ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื™ืฆื•ืจ ืชืจื ื’ื•ืœืช ืขื ืฉื™ื ื™ื™ื.
13:12
That's getting closer.
294
792260
2000
ื–ื” ืžืชืงืจื‘.
13:14
That's better than a glowing chicken.
295
794260
2000
ื–ื” ื™ื•ืชืจ ื˜ื•ื‘ ืžืชืจื ื’ื•ืœืช ื–ื•ื”ืจืช.
13:16
(Laughter)
296
796260
2000
(ืฆื—ื•ืง)
13:18
A friend of mine, a colleague of mine,
297
798260
2000
ื—ื‘ืจ, ืขืžื™ืช ืฉืœื™,
13:20
Dr. Hans Larsson at McGill University,
298
800260
2000
ื“"ืจ ื”ื ืก ืœืืจืกื•ืŸ ื‘ืื•ื ื™ื‘ืจืกื™ื˜ืช ืžืงื’ื™ืœ,
13:22
is actually looking at atavisms.
299
802260
2000
ืžืชื‘ื•ื ืŸ ื‘ื’ื ื™ื ืจื“ื•ืžื™ื.
13:24
And he's looking at them
300
804260
2000
ื•ื”ื•ื ื—ื•ืงืจ ืื•ืชื
13:26
by looking at the embryo genesis of birds
301
806260
3000
ืขืœ ื™ื“ื™ ื”ืชื‘ื•ื ื ื•ืช ื‘ื”ื™ื•ื•ืฆืจื•ืช ื”ืขื•ื‘ืจื™ืช ืฉืœ ืฆื™ืคื•ืจื™ื
13:29
and actually looking at how they develop,
302
809260
3000
ื•ื‘ื—ื™ื ื” ืฉืœ ื”ืื•ืคืŸ ืฉื‘ื• ื”ื ืžืชืคืชื—ื™ื
13:32
and he's interested in how birds actually lost their tail.
303
812260
4000
ื•ื”ื•ื ืžืชืขื ื™ื™ืŸ ื‘ืื™ืš ื”ืฆื™ืคื•ืจื™ื ืื™ื‘ื“ื• ืืช ื”ื–ื ื‘ ืฉืœื”ืŸ.
13:36
He's also interested in the transformation
304
816260
2000
ื”ื•ื ื’ื ืžืชืขื ื™ื™ืŸ ื‘ื”ืคื™ื›ืชื”
13:38
of the arm, the hand, to the wing.
305
818260
3000
ืฉืœ ื”ื–ืจื•ืข, ื”ื™ื“, ืœื›ื ืฃ.
13:41
He's looking for those genes as well.
306
821260
2000
ื”ื•ื ื’ื ืžื—ืคืฉ ืืช ื”ื’ื ื™ื ื”ืœืœื•.
13:43
And I said, "Well, if you can find those,
307
823260
3000
ื•ืื ื™ ืืžืจืชื™, "ื˜ื•ื‘, ืื ืชื•ื›ืœ ืœืžืฆื•ื ืื•ืชื,
13:46
I can just reverse them
308
826260
2000
ืื ื™ ื™ื›ื•ืœ ืคืฉื•ื˜ ืœื”ืคื•ืš ืื•ืชื
13:48
and make what I need to make for the sixth-graders."
309
828260
3000
ื•ืœื™ื™ืฆืจ ืืช ืžื” ืฉืื ื™ ืฆืจื™ืš ื‘ืฉื‘ื™ืœ ื™ืœื“ื™ ื›ื™ืชื” ื•' ื”ืืœื”."
13:51
And so he agreed.
310
831260
2000
ื•ื”ื•ื ื”ืกื›ื™ื.
13:53
And so that's what we're looking into.
311
833260
2000
ื•ื–ื” ืžื” ืฉืื ื—ื ื• ื‘ื•ื—ื ื™ื.
13:55
If you look at dinosaur hands,
312
835260
2000
ืื ืชืกืชื›ืœื• ื‘ื™ื“ื™ื™ื ืฉืœ ื“ื™ื ื•ื–ืื•ืจ,
13:57
a velociraptor
313
837260
2000
ื”ื•ืœื•ืกื™ืจืคื˜ื•ืจ,
13:59
has that cool-looking hand with the claws on it.
314
839260
2000
ื™ืฉ ืœื• ื™ื“ ืžื’ื ื™ื‘ื” ื›ื–ื• ืขื ื˜ื•ืคืจื™ื.
14:01
Archaeopteryx, which is a bird, a primitive bird,
315
841260
3000
ืืจื›ื™ืื•ืคื˜ืจื™ืงืก, ืฉื”ื•ื ืฆื™ืคื•ืจ, ืฆื™ืคื•ืจ ืคืจื™ืžื™ื˜ื™ื‘ื™ืช,
14:04
still has that very primitive hand.
316
844260
3000
ืขื“ื™ื™ืŸ ื™ืฉ ืœื• ื™ื“ ืžืื•ื“ ืคืจื™ืžื™ื˜ื™ื‘ื™ืช.
14:07
But as you can see, the pigeon,
317
847260
2000
ืื‘ืœ ื›ืžื• ืฉืืชื ื™ื›ื•ืœื™ื ืœืจืื•ืช, ื”ื™ื•ื ื”,
14:09
or a chicken or anything else, another bird,
318
849260
2000
ืื• ืชืจื ื’ื•ืœืช ืื• ื›ืœ ื“ื‘ืจ ืื—ืจ, ืฆื™ืคื•ืจ ืื—ืจืช,
14:11
has kind of a weird-looking hand,
319
851260
3000
ื™ืฉ ืœื” ืžื™ืŸ ื™ื“ ืžื•ื–ืจื” ื›ื–ื•,
14:14
because the hand is a wing.
320
854260
2000
ื‘ื’ืœืœ ืฉื”ื™ื“ ื”ื™ื ื›ื ืฃ.
14:16
But the cool thing is
321
856260
2000
ืื‘ืœ ื”ื“ื‘ืจ ื”ืžื’ื ื™ื‘ ื”ื•ื
14:18
that, if you look in the embryo,
322
858260
3000
ื”ื•ื, ืื ืชืชื‘ื•ื ื ื• ื‘ืขื•ื‘ืจ,
14:21
as the embryo is developing
323
861260
2000
ื›ืฉื”ืขื•ื‘ืจ ืžืชืคืชื—
14:23
the hand actually looks
324
863260
3000
ื”ื™ื“ ื ืจืื™ืช ืžืžืฉ
14:26
pretty much like the archaeopteryx hand.
325
866260
2000
ื›ืžื• ื”ื™ื“ ืฉืœ ื”ืืจื›ื™ืื•ืคื˜ืจื™ืงืก.
14:28
It has the three fingers, the three digits.
326
868260
3000
ื™ืฉ ืœื” ืืช ืฉืœื•ืฉ ื”ืืฆื‘ืขื•ืช.
14:31
But a gene turns on that actually fuses those together.
327
871260
3000
ืื‘ืœ ื™ืฉ ื’ืŸ ืฉืคื•ืขืœ ื•ืžืื—ื” ืื•ืชืŸ ื™ื—ื“.
14:34
And so what we're looking for is that gene.
328
874260
3000
ืื– ื”ื’ืŸ ื”ื–ื” ื”ื•ื ืžื” ืฉืื ื—ื ื• ืžื—ืคืฉื™ื.
14:37
We want to stop that gene from turning on,
329
877260
2000
ืื ื• ืจื•ืฆื™ื ืœืขืฆื•ืจ ืืช ื”ืคืขื•ืœื” ืฉืœ ื”ื’ืŸ ื”ื–ื”,
14:39
fusing those hands together,
330
879260
2000
ืžืœืื—ื•ืช ืืช ื”ืืฆื‘ืขื•ืช ื™ื—ื“,
14:41
so we can get a chicken that hatches out with a three-fingered hand,
331
881260
3000
ื›ื“ื™ ืฉื ื•ื›ืœ ืœืงื‘ืœ ืชืจื ื’ื•ืœืช ืฉื‘ื•ืงืขืช ื”ื—ื•ืฆื” ืขื ื™ื“ ืฉื™ืฉ ื‘ื” 3 ืืฆื‘ืขื•ืช,
14:44
like the archaeopteryx.
332
884260
2000
ื›ืžื• ื”ืืจื›ื™ืื•ืคื˜ืจื™ืงืก.
14:46
And the same goes for the tails.
333
886260
3000
ื•ืื•ืชื• ื”ื“ื‘ืจ ืชืงืฃ ืœื’ื‘ื™ ื–ื ื‘ื•ืช.
14:49
Birds have basically
334
889260
3000
ืœืฆื™ืคื•ืจื™ื ื™ืฉ ืœืžืขืฉื”
14:52
rudimentary tails.
335
892260
2000
ื–ื ื‘ื•ืช ืœื ืžืคื•ืชื—ื™ื.
14:54
And so we know
336
894260
3000
ื•ืื ื—ื ื• ื™ื•ื“ืขื™ื
14:57
that in embryo,
337
897260
2000
ืฉื‘ืขื•ื‘ืจ,
14:59
as the animal is developing,
338
899260
2000
ื›ืฉื”ื™ืฆื•ืจ ืžืชืคืชื—,
15:01
it actually has a relatively long tail.
339
901260
3000
ื™ืฉ ืœื• ื–ื ื‘ ืืจื•ืš ื™ื—ืกื™ืช.
15:04
But a gene turns on
340
904260
2000
ืื‘ืœ ื’ืŸ ื ื›ื ืก ืœืคืขื•ืœื”
15:06
and resorbs the tail, gets rid of it.
341
906260
3000
ื•ืกื•ืคื’ ื—ื–ืจื” ืืช ื”ื–ื ื‘, ื ืคื˜ืจ ืžืžื ื•.
15:09
So that's the other gene we're looking for.
342
909260
3000
ืื– ื–ื” ื”ื’ืŸ ื”ื ื•ืกืฃ ืฉืื ื—ื ื• ืžื—ืคืฉื™ื.
15:12
We want to stop that tail from resorbing.
343
912260
4000
ืื ื—ื ื• ืจื•ืฆื™ื ืœืขืฆื•ืจ ืืช ื”ื–ื ื‘ ืžืœื”ื™ืกืคื’.
15:16
So what we're trying to do really
344
916260
3000
ืื– ืžื” ืฉืื ื—ื ื• ืžื ืกื™ื ื‘ืืžืช ืœืขืฉื•ืช
15:19
is take our chicken,
345
919260
3000
ื”ื•ื ืœืงื—ืช ืืช ื”ืชืจื ื’ื•ืœืช ืฉืœื ื•,
15:22
modify it
346
922260
2000
ืœืฉื ื•ืช ื•ืœื”ืชืื™ื ืื•ืชื”
15:24
and make the chickenosaurus.
347
924260
2000
ื•ืœืขืฉื•ืช ืžืžื ื” ืชืจื ื’ื•ืœื•ื–ืื•ืจื•ืก.
15:26
(Laughter)
348
926260
3000
(ืฆื—ื•ืง)
15:29
It's a cooler-looking chicken.
349
929260
3000
ื–ื• ืชืจื ื’ื•ืœืช ืฉื ืจืื™ืช ืžื’ื ื™ื‘ื” ื™ื•ืชืจ.
15:32
But it's just the very basics.
350
932260
3000
ืื‘ืœ ื–ื” ืจืง ื”ื‘ืกื™ืก.
15:35
So that really is what we're doing.
351
935260
2000
ืื– ื–ื” ื‘ืืžืช ืžื” ืฉืื ื—ื ื• ืขื•ืฉื™ื.
15:37
And people always say, "Why do that?
352
937260
2000
ื•ืื ืฉื™ื ืชืžื™ื“ ืื•ืžืจื™ื, "ืœืžื” ืœืขืฉื•ืช ืืช ื–ื”?
15:39
Why make this thing?
353
939260
2000
ืœืžื” ืœื™ืฆื•ืจ ืืช ื”ื“ื‘ืจ ื”ื–ื”?
15:41
What good is it?"
354
941260
2000
ืื™ื–ื” ื˜ื•ื‘ ื™ืฆื ืžื–ื”?"
15:43
Well, that's a good question.
355
943260
2000
ื•ื‘ื›ืŸ, ื–ื• ืฉืืœื” ื˜ื•ื‘ื”.
15:45
Actually, I think it's a great way to teach kids
356
945260
2000
ืœืžืขืฉื”, ืื ื™ ื—ื•ืฉื‘ ืฉื–ื• ื“ืจืš ื ื”ื“ืจืช ืœืœืžื“ ื™ืœื“ื™ื
15:47
about evolutionary biology
357
947260
2000
ืขืœ ื‘ื™ื•ืœื•ื’ื™ื” ืื‘ื•ืœื•ืฆื™ื•ื ื™ืช
15:49
and developmental biology
358
949260
2000
ื•ื‘ื™ื•ืœื•ื’ื™ื” ื”ืชืคืชื—ื•ืชื™ืช
15:51
and all sorts of things.
359
951260
2000
ื•ื›ืœ ืžื™ื ื™ ื“ื‘ืจื™ื ืื—ืจื™ื.
15:53
And quite frankly, I think
360
953260
3000
ื•ืื ื™ ืžืžืฉ ื—ื•ืฉื‘,
15:56
if Colonel Sanders
361
956260
2000
ืฉืื ืงื•ืœื•ื ืœ ืกื ื“ืจืก (ืž-KFC)
15:58
was to be careful how he worded it,
362
958260
3000
ื”ื™ื” ื–ื”ื™ืจ ื‘ื ื™ืกื•ื— ืฉืœื•,
16:01
he could actually advertise an extra piece.
363
961260
3000
ื”ื•ื ื™ื›ื•ืœ ื”ื™ื” ืœืคืจืกื ืžื ื” ื ื•ืกืคืช.
16:04
(Laughter)
364
964260
4000
(ืฆื—ื•ืง)
16:08
Anyway --
365
968260
2000
ื‘ื›ืœ ืžืงืจื” --
16:12
When our dino-chicken hatches,
366
972260
4000
ื›ืฉื”ืชืจื ื’ื•ืœื•ื–ืื•ืจื•ืก ืฉืœื ื• ื™ื‘ืงืข,
16:16
it will be, obviously, the poster child,
367
976260
3000
ื”ื•ื ื™ื”ื™ื”, ื›ืžื•ื‘ืŸ, ื ืขืจ ื”ืคื•ืกื˜ืจ,
16:19
or what you might call a poster chick,
368
979260
3000
ืื• ืžื” ืฉืื•ืœื™ ืชื›ื ื•, ื ืขืจืช ื”ืฉืขืจ (chick),
16:22
for technology, entertainment and design.
369
982260
3000
ืœื˜ื›ื ื•ืœื•ื’ื™ื”, ื‘ื™ื“ื•ืจ, ื•ืขื™ืฆื•ื‘.
16:25
Thank you.
370
985260
2000
ืชื•ื“ื” ืจื‘ื”.
16:27
(Applause)
371
987260
3000
(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

https://forms.gle/WvT1wiN1qDtmnspy7