1
00:00:00,320 --> 00:00:01,880
Speaker 1: I get a team. It's a you project.

2
00:00:01,880 --> 00:00:04,520
Speaker 2: It's Tiffany and Cook, it's Craig Anthony Harper, and it's

3
00:00:04,559 --> 00:00:04,920
Speaker 2: the doc.

4
00:00:05,000 --> 00:00:08,280
Speaker 1: We'll introduce her in a moment tif Hi, Top of

5
00:00:08,320 --> 00:00:10,200
Speaker 1: the Morning, Harps, Top of the morning.

6
00:00:10,200 --> 00:00:10,360
Speaker 3: To you.

7
00:00:10,400 --> 00:00:13,000
Speaker 2: It's five past seven in the thriving metropolis of Melbourne.

8
00:00:13,039 --> 00:00:15,600
Speaker 2: It's a Tuesday. I've got my radio voice backer. Why

9
00:00:15,640 --> 00:00:17,480
Speaker 2: do I do that? Shit, don't do that.

10
00:00:17,520 --> 00:00:19,960
Speaker 1: It's a podcast. It raises me up.

11
00:00:19,960 --> 00:00:20,840
Speaker 4: I'll quite like it.

12
00:00:20,880 --> 00:00:24,599
Speaker 2: Actually, just talk like a regular human. There's no station ideas.

13
00:00:24,640 --> 00:00:27,120
Speaker 2: There's no time checks, there's no weather checks, and there's

14
00:00:27,120 --> 00:00:29,960
Speaker 2: no upcoming announcements of what's on after the news.

15
00:00:29,960 --> 00:00:30,680
Speaker 1: There's none of that.

16
00:00:31,440 --> 00:00:34,800
Speaker 2: There's just you and me and clever people, cleverer people

17
00:00:35,280 --> 00:00:37,000
Speaker 2: than you and I every day, which is not a

18
00:00:37,080 --> 00:00:39,319
Speaker 2: high watermark to meet, is it right?

19
00:00:42,040 --> 00:00:48,960
Speaker 1: Really? No? No, but that's all right. We're nice. Well

20
00:00:49,000 --> 00:00:50,760
Speaker 1: you're pretty high watermark.

21
00:00:50,840 --> 00:00:53,240
Speaker 4: You're almost a doctor. This to be No, you're almost

22
00:00:53,240 --> 00:00:53,720
Speaker 4: a doctor.

23
00:00:53,840 --> 00:00:57,080
Speaker 2: Now I'm a doctor. At like, even when i'm a doctor,

24
00:00:57,120 --> 00:01:00,560
Speaker 2: I'm not really a doctor. It's like, you know, Hi, Sabine,

25
00:01:00,600 --> 00:01:01,960
Speaker 2: welcome to the Youth Project.

26
00:01:02,920 --> 00:01:04,600
Speaker 4: Thank you, thank you for having me.

27
00:01:05,400 --> 00:01:07,440
Speaker 1: Wow, we love to have you.

28
00:01:07,520 --> 00:01:10,280
Speaker 2: I had a look at you yesterday and I read

29
00:01:10,319 --> 00:01:14,679
Speaker 2: about you, and I watched you on some YouTube stuff

30
00:01:14,720 --> 00:01:19,039
Speaker 2: and I listened to you, and you're quite clever, So congratulate.

31
00:01:19,440 --> 00:01:20,759
Speaker 2: I'm being a smarty pants.

32
00:01:22,319 --> 00:01:25,120
Speaker 3: I just ask a lot of questions. I don't know

33
00:01:25,160 --> 00:01:28,399
Speaker 3: if I'm clever. I'm just I like to play detective.

34
00:01:28,680 --> 00:01:31,319
Speaker 3: I ask a lot of questions.

35
00:01:31,400 --> 00:01:32,560
Speaker 1: And you did.

36
00:01:32,760 --> 00:01:34,800
Speaker 2: As you and I were talking about three minutes ago.

37
00:01:34,920 --> 00:01:36,759
Speaker 2: I wrote a book with fuck on the front cover,

38
00:01:36,840 --> 00:01:40,080
Speaker 2: which is fine, I will say it was. It was

39
00:01:40,120 --> 00:01:42,920
Speaker 2: before Mark Manson's fuck book. I just want to say that.

40
00:01:43,600 --> 00:01:45,880
Speaker 2: And you wrote a book with shit on the front cover,

41
00:01:46,040 --> 00:01:50,080
Speaker 2: which you were sharing with us that and your book.

42
00:01:49,960 --> 00:01:54,320
Speaker 1: Was called, of course, let's talk shit hucking. When I

43
00:01:54,360 --> 00:01:56,880
Speaker 1: read that, when I think I like her, I think

44
00:01:56,920 --> 00:01:57,919
Speaker 1: I like her.

45
00:01:58,160 --> 00:02:00,560
Speaker 3: I'm in the shit business, right, so I'm trying to

46
00:02:00,600 --> 00:02:04,680
Speaker 3: make sense of all this shit. And basically, I said,

47
00:02:05,000 --> 00:02:07,560
Speaker 3: if I wrote it like, let's talk about it, right.

48
00:02:08,040 --> 00:02:12,119
Speaker 3: Let's not talk micro biome because that's too nice. Let's

49
00:02:12,200 --> 00:02:15,320
Speaker 3: just call it what it is. Let's talk shit. And

50
00:02:15,400 --> 00:02:17,680
Speaker 3: I said, look, if I was, if I'm full of shit,

51
00:02:18,000 --> 00:02:19,919
Speaker 3: or if I know my shit, let's talk about it

52
00:02:19,960 --> 00:02:22,240
Speaker 3: either way, one hundred percent.

53
00:02:22,360 --> 00:02:27,120
Speaker 2: Why do you think that we are like My background is,

54
00:02:27,560 --> 00:02:30,000
Speaker 2: for a long time I set up the first personal

55
00:02:30,240 --> 00:02:32,960
Speaker 2: training center in Australia. So for a long time I

56
00:02:33,040 --> 00:02:36,800
Speaker 2: was training people humans, thousands of humans right for decades.

57
00:02:36,960 --> 00:02:41,480
Speaker 2: And so you know, I'm talking about bums or as

58
00:02:41,520 --> 00:02:44,640
Speaker 2: you would say, asses, and legs and calories and micros

59
00:02:44,680 --> 00:02:50,440
Speaker 2: and macros, and menopause and perimenopause and shitting and constipation

60
00:02:51,440 --> 00:02:56,680
Speaker 2: and andropause and physical, mental, emotional, social health and the

61
00:02:56,800 --> 00:03:00,880
Speaker 2: myriad of variables that make us feel good.

62
00:03:00,320 --> 00:03:01,000
Speaker 1: Or in the middle.

63
00:03:01,720 --> 00:03:04,120
Speaker 2: And so I spent my life a lot of my

64
00:03:04,160 --> 00:03:06,480
Speaker 2: life talking about stuff that people don't talk about too

65
00:03:06,560 --> 00:03:07,360
Speaker 2: much publicly.

66
00:03:07,480 --> 00:03:11,079
Speaker 1: So I'm used to talking about all this stuff.

67
00:03:11,080 --> 00:03:13,960
Speaker 2: But it feels like as soon as out in the

68
00:03:14,000 --> 00:03:19,200
Speaker 2: public forum you talk about pooing or shitting or having

69
00:03:19,240 --> 00:03:24,200
Speaker 2: a bowel movement, that it's a thing that everyone in

70
00:03:24,240 --> 00:03:27,280
Speaker 2: the world does, let's not talk about it.

71
00:03:28,040 --> 00:03:28,880
Speaker 1: What is that about?

72
00:03:29,840 --> 00:03:33,040
Speaker 3: And by the way, that's something everybody's obsessed about, you know.

73
00:03:33,160 --> 00:03:35,560
Speaker 3: As a gas gentrologist, I cannot tell you how many

74
00:03:35,600 --> 00:03:39,320
Speaker 3: people have sent me pictures of their poop, have talked

75
00:03:39,360 --> 00:03:43,720
Speaker 3: to me about their poop? Have you know, explained to

76
00:03:43,800 --> 00:03:48,480
Speaker 3: me all the details about it? Everybody's obsessed about it, right, so,

77
00:03:49,040 --> 00:03:52,680
Speaker 3: you know, and it's it's an obsession that we need

78
00:03:52,720 --> 00:03:53,320
Speaker 3: to understand.

79
00:03:53,360 --> 00:03:54,920
Speaker 4: Maybe there's secrets in that poop.

80
00:03:55,120 --> 00:03:58,320
Speaker 3: Maybe we all have a gut feeling that there's secrets

81
00:03:58,360 --> 00:04:00,800
Speaker 3: in it, you know, Maybe that's our launcher. Maybe we

82
00:04:00,840 --> 00:04:04,520
Speaker 3: need to understand it. Maybe the secret of staying living

83
00:04:04,560 --> 00:04:05,680
Speaker 3: longer is in the poop.

84
00:04:06,720 --> 00:04:08,440
Speaker 2: Well, if you give me your digits, I'll send you

85
00:04:08,480 --> 00:04:12,200
Speaker 2: a nice photo after the after the show.

86
00:04:13,280 --> 00:04:13,920
Speaker 1: Now I won't.

87
00:04:13,920 --> 00:04:17,560
Speaker 2: I wouldn't do that, all right, So give give my

88
00:04:17,640 --> 00:04:21,359
Speaker 2: audience a quick snapshot of rather than me read a

89
00:04:21,400 --> 00:04:24,800
Speaker 2: bio or you know, mislead people, just tell us who

90
00:04:24,839 --> 00:04:27,400
Speaker 2: you are, what you do, and how you got to

91
00:04:27,440 --> 00:04:30,000
Speaker 2: be where you're at in terms of your work and

92
00:04:30,040 --> 00:04:33,840
Speaker 2: your research and your curiosity and the education of the

93
00:04:33,880 --> 00:04:35,120
Speaker 2: masses that you're at today.

94
00:04:36,800 --> 00:04:40,640
Speaker 3: I'm basically the girl that started with a question when

95
00:04:40,640 --> 00:04:42,720
Speaker 3: I was little, where do we go after we die?

96
00:04:43,200 --> 00:04:47,680
Speaker 3: And I went into medicine to understand that simple process,

97
00:04:47,760 --> 00:04:50,920
Speaker 3: which is not so simple medicine. Did you know I

98
00:04:50,960 --> 00:04:54,039
Speaker 3: was obsessed with asking patients, you know, where do what

99
00:04:54,200 --> 00:04:56,440
Speaker 3: happened when you died for about a second and then

100
00:04:56,480 --> 00:05:01,279
Speaker 3: we resuscitated you. You know, medicine didn't really guide me

101
00:05:01,440 --> 00:05:04,400
Speaker 3: very well into that answering that question, and somewhere along

102
00:05:04,400 --> 00:05:06,640
Speaker 3: the line, I kind of lost interest of that question

103
00:05:07,400 --> 00:05:10,000
Speaker 3: and started treating patients. And I was always the girl

104
00:05:10,040 --> 00:05:13,920
Speaker 3: that was basically wanting what's on the cutting edge, Like

105
00:05:14,160 --> 00:05:16,919
Speaker 3: you have chrons. I don't care what's in the guidelines.

106
00:05:16,960 --> 00:05:19,239
Speaker 3: I want to know what's the newest thing for my patients.

107
00:05:19,240 --> 00:05:22,160
Speaker 3: So I was the girl that was bringing clinical trials

108
00:05:22,160 --> 00:05:24,800
Speaker 3: for pharma. I was, you know, one could say, in

109
00:05:24,839 --> 00:05:28,240
Speaker 3: bed with pharmaceutical companies, you know, testing their products one

110
00:05:28,279 --> 00:05:31,200
Speaker 3: after the other. I was known as the Queen of

111
00:05:31,279 --> 00:05:34,200
Speaker 3: seed dip. Seed dip is a bacteria that basically people

112
00:05:34,240 --> 00:05:37,920
Speaker 3: get from taking a lot of antibiotics and gives them diarrhea.

113
00:05:38,080 --> 00:05:38,840
Speaker 4: And I would.

114
00:05:38,640 --> 00:05:42,200
Speaker 3: Recruit a lot of patients with that condition with the

115
00:05:42,560 --> 00:05:46,880
Speaker 3: intent of doing a procedure called fecal transplant in case

116
00:05:47,120 --> 00:05:50,760
Speaker 3: those products didn't work. So I would try the newest

117
00:05:50,760 --> 00:05:53,240
Speaker 3: product of pharma, and if it didn't work, I would

118
00:05:53,320 --> 00:05:55,760
Speaker 3: use the money from pharma from the clinical trial to

119
00:05:55,839 --> 00:06:00,279
Speaker 3: put my patients through fecal transplant. When fecal trans plan

120
00:06:00,360 --> 00:06:03,440
Speaker 3: started showing a lot of other things improving, you know,

121
00:06:03,600 --> 00:06:07,560
Speaker 3: Alzheimer's improving one case in me with me in a

122
00:06:07,640 --> 00:06:12,120
Speaker 3: patient two cases of alopecia areata with Collin Kelly, et cetera,

123
00:06:12,200 --> 00:06:15,400
Speaker 3: et cetera. I started asking the question, what is in

124
00:06:15,440 --> 00:06:19,440
Speaker 3: the stools that's changing the microboma and changing the disease,

125
00:06:19,880 --> 00:06:22,960
Speaker 3: even if it's for an end of one right, And

126
00:06:23,040 --> 00:06:28,800
Speaker 3: then when capsules of poop came on my desk as

127
00:06:28,880 --> 00:06:33,440
Speaker 3: a clinical trial, I went completely rogue because I said,

128
00:06:33,440 --> 00:06:35,080
Speaker 3: wait a minute, we're in the ship business and we

129
00:06:35,160 --> 00:06:37,560
Speaker 3: have no idea what the hell we're doing. What kind

130
00:06:37,560 --> 00:06:40,000
Speaker 3: of research is that? What kind of science is that?

131
00:06:40,640 --> 00:06:43,279
Speaker 3: We're just here to sell products like and what makes

132
00:06:43,640 --> 00:06:46,560
Speaker 3: the poop of a kid from Mit the right poop

133
00:06:46,640 --> 00:06:50,360
Speaker 3: to give to my poor little frail lady from California,

134
00:06:50,920 --> 00:06:54,680
Speaker 3: you know? And is the microbauma of a person from

135
00:06:54,720 --> 00:06:57,479
Speaker 3: Mexico good to give to a person from Japan?

136
00:06:57,680 --> 00:06:59,200
Speaker 4: And all these questions.

137
00:06:59,240 --> 00:07:02,640
Speaker 3: And then as I got into the microbiome, I had

138
00:07:02,680 --> 00:07:06,040
Speaker 3: even more questions. And then here we are. I'm here

139
00:07:06,080 --> 00:07:10,920
Speaker 3: to try to find answers of a you know, a huge,

140
00:07:11,000 --> 00:07:14,920
Speaker 3: huge curiosity. So I went from being a gastr entrologist

141
00:07:15,000 --> 00:07:18,120
Speaker 3: to CEO of a company that did clinical trials for pharma,

142
00:07:18,160 --> 00:07:22,800
Speaker 3: where we did over three hundred clinical trials, two basically

143
00:07:23,280 --> 00:07:26,920
Speaker 3: leading the microboom research where we found we were the

144
00:07:26,960 --> 00:07:30,000
Speaker 3: first lab that found COVID in the stools, which got

145
00:07:30,000 --> 00:07:33,480
Speaker 3: our government to look at the septic tanks and basically

146
00:07:33,520 --> 00:07:38,040
Speaker 3: from there we discovered biffetobacteria, this important microbe that helps,

147
00:07:38,720 --> 00:07:43,560
Speaker 3: you know, breakdown sugar is disappearing in a lot of diseases.

148
00:07:43,800 --> 00:07:47,720
Speaker 3: And so from there, how do we increase it? How

149
00:07:47,720 --> 00:07:51,800
Speaker 3: do we decrease it? You know, what decreases it? What

150
00:07:51,960 --> 00:07:55,320
Speaker 3: increases it? What are the microbes play a role in it?

151
00:07:56,120 --> 00:07:59,480
Speaker 3: What are the microbombs doing, What are the microbes doing

152
00:07:59,680 --> 00:08:00,280
Speaker 3: in the gut?

153
00:08:00,560 --> 00:08:03,320
Speaker 4: And how do we get to the level of having.

154
00:08:03,400 --> 00:08:09,320
Speaker 3: Increase Parkinson's, Alzheimer's, cancer, autism, mental health? Is it all

155
00:08:09,400 --> 00:08:12,040
Speaker 3: because we're messing up our guts?

156
00:08:12,400 --> 00:08:14,520
Speaker 4: And here we are, and.

157
00:08:14,880 --> 00:08:18,560
Speaker 2: I mean, obviously everything's still a work in progress, still

158
00:08:18,600 --> 00:08:20,960
Speaker 2: research still a long way to go, but we know

159
00:08:21,640 --> 00:08:24,720
Speaker 2: we know more than we did than It's like all science,

160
00:08:24,760 --> 00:08:29,320
Speaker 2: it's evolving, And what are your and This is not

161
00:08:29,400 --> 00:08:31,640
Speaker 2: you throwing your reputation on the line, but like, what

162
00:08:31,720 --> 00:08:34,880
Speaker 2: do you think the Like what do you hope might

163
00:08:35,120 --> 00:08:35,880
Speaker 2: happen in.

164
00:08:35,800 --> 00:08:37,920
Speaker 1: The next five, ten, twenty years in this area?

165
00:08:37,960 --> 00:08:42,079
Speaker 2: What do you what's your kind of intuition and feeling

166
00:08:42,520 --> 00:08:46,160
Speaker 2: on top of also of course your research, Like what

167
00:08:46,240 --> 00:08:48,240
Speaker 2: do you think we might be able to do but

168
00:08:48,520 --> 00:08:51,440
Speaker 2: create achieve heading down this path.

169
00:08:51,600 --> 00:08:53,520
Speaker 3: I think we're going to I think we're going to

170
00:08:53,640 --> 00:08:58,600
Speaker 3: realize that we've been killing too much. I think the microbiome,

171
00:08:58,960 --> 00:09:03,240
Speaker 3: you know, the idea idea of microbes causing disease is

172
00:09:03,440 --> 00:09:08,080
Speaker 3: one path, but also the microbes that we're killing in

173
00:09:08,200 --> 00:09:11,040
Speaker 3: order to kill those microbes that killed that start the

174
00:09:11,080 --> 00:09:14,600
Speaker 3: disease is the second path. We're to start paying attention

175
00:09:14,720 --> 00:09:19,120
Speaker 3: to the microbes we're killing because the microbes that we're killing.

176
00:09:19,600 --> 00:09:20,559
Speaker 1: You know, have.

177
00:09:22,520 --> 00:09:23,079
Speaker 4: A role.

178
00:09:23,800 --> 00:09:27,240
Speaker 3: You know, when we're you know, breaking down sugar. When

179
00:09:27,280 --> 00:09:32,520
Speaker 3: we're breaking down you know, when we're absorbing iron, when

180
00:09:32,559 --> 00:09:36,679
Speaker 3: we're absorbing calcium, when we're absorbing sugar, there's microbes that

181
00:09:36,840 --> 00:09:37,400
Speaker 3: play there.

182
00:09:37,679 --> 00:09:40,120
Speaker 4: Which microbes How did we lose it? How do we

183
00:09:40,160 --> 00:09:43,320
Speaker 4: gain them back? You know, when you start looking at

184
00:09:43,320 --> 00:09:44,959
Speaker 4: the population and you start.

185
00:09:44,720 --> 00:09:48,000
Speaker 3: Seeing there's a group of there's a group of patients

186
00:09:48,080 --> 00:09:52,480
Speaker 3: with Alzheimer's that are lacking these microbes, and then there's

187
00:09:52,520 --> 00:09:56,560
Speaker 3: a population that is healthy or at least deemed healthy that.

188
00:09:56,640 --> 00:09:57,760
Speaker 4: Have those microbes.

189
00:09:58,080 --> 00:10:00,640
Speaker 3: How do we, you know, correlate all that, you know,

190
00:10:00,679 --> 00:10:02,800
Speaker 3: how do we put all that together? So I think

191
00:10:02,800 --> 00:10:06,280
Speaker 3: there's gonna be a lot more people asking questions. I

192
00:10:06,280 --> 00:10:09,280
Speaker 3: think there's gonna be you know, I think with AI,

193
00:10:10,120 --> 00:10:11,560
Speaker 3: AI is going to help us.

194
00:10:11,440 --> 00:10:12,680
Speaker 4: And hurt us in a way.

195
00:10:13,160 --> 00:10:16,960
Speaker 3: But for those that are critically critical thinkers, they're going

196
00:10:17,040 --> 00:10:20,240
Speaker 3: to know how to use AI to speed them up.

197
00:10:20,760 --> 00:10:22,680
Speaker 4: In other words, use your brain.

198
00:10:23,480 --> 00:10:29,000
Speaker 3: Don't do the the crap work, like the whole write.

199
00:10:28,760 --> 00:10:29,880
Speaker 4: Up of I and D.

200
00:10:30,040 --> 00:10:32,319
Speaker 3: In my case, you know, when I submit submissions to

201
00:10:32,400 --> 00:10:35,280
Speaker 3: the FDA, you have to do like thirty page document

202
00:10:35,360 --> 00:10:37,880
Speaker 3: of I and D. Have AI do it for you,

203
00:10:37,920 --> 00:10:41,800
Speaker 3: because that's time consuming. Start using your brain more to

204
00:10:41,920 --> 00:10:45,000
Speaker 3: go to the next level. So I think I think

205
00:10:45,040 --> 00:10:49,559
Speaker 3: there's gonna be an increase in utilizing our brain cells

206
00:10:49,600 --> 00:10:54,839
Speaker 3: to reach areas that are that we're not touched or

207
00:10:55,000 --> 00:10:58,720
Speaker 3: not thought of. You know, we have the ability now

208
00:10:58,880 --> 00:11:00,160
Speaker 3: with the technology.

209
00:11:00,760 --> 00:11:03,199
Speaker 2: I think it allows you to use your to put

210
00:11:04,000 --> 00:11:06,560
Speaker 2: to make the best use of your brain, you know,

211
00:11:06,720 --> 00:11:09,800
Speaker 2: not filling out those thirty pages. It's like you can

212
00:11:09,840 --> 00:11:12,600
Speaker 2: do the reveal, thinking, creating, problem solving.

213
00:11:12,960 --> 00:11:13,520
Speaker 4: That's right.

214
00:11:13,880 --> 00:11:18,480
Speaker 3: That's our gift as humans is not to be robots.

215
00:11:18,559 --> 00:11:18,760
Speaker 1: Right.

216
00:11:18,800 --> 00:11:21,959
Speaker 3: So I kind of got bored of the whole GI

217
00:11:22,120 --> 00:11:24,040
Speaker 3: field in a way because I was a robot. I

218
00:11:24,080 --> 00:11:27,920
Speaker 3: was doing one kronoscopy after another, and then even clinical trials,

219
00:11:27,920 --> 00:11:29,880
Speaker 3: I was doing one clinical trial after another.

220
00:11:30,840 --> 00:11:34,560
Speaker 4: You know, we're meant to do bigger things as humans.

221
00:11:34,600 --> 00:11:39,839
Speaker 3: I think we're meant to innovate, and I think AI

222
00:11:40,000 --> 00:11:44,440
Speaker 3: is going to allow us to innovate, to push that

223
00:11:44,440 --> 00:11:48,600
Speaker 3: that narrative a little bit to a different level.

224
00:11:49,800 --> 00:11:57,440
Speaker 2: Well, in what regard facal transplants or po transplants held

225
00:11:57,480 --> 00:12:01,920
Speaker 2: by the mainstream medical community right now, is it did?

226
00:12:01,960 --> 00:12:07,440
Speaker 2: I think it's bullshit that I think it's emerging science today.

227
00:12:07,520 --> 00:12:13,520
Speaker 3: So there's the community is divided, right because they understand

228
00:12:13,559 --> 00:12:17,160
Speaker 3: it's all research. So you know, all research needs to

229
00:12:17,200 --> 00:12:21,800
Speaker 3: be valid, verified and reproducible. So when doctor Tom Barotti

230
00:12:21,880 --> 00:12:26,359
Speaker 3: in Australia says I've cured twenty eight patients with fecal transplant,

231
00:12:27,000 --> 00:12:29,480
Speaker 3: the rest of the GI community is like, oh well,

232
00:12:29,520 --> 00:12:30,480
Speaker 3: let me try doing.

233
00:12:30,320 --> 00:12:33,400
Speaker 4: Fecal transplant for Crons disease. Wait a minute, I'm not

234
00:12:33,480 --> 00:12:36,120
Speaker 4: improving patients with Crohn's disease.

235
00:12:35,920 --> 00:12:39,240
Speaker 3: Right, So then that becomes what is doctor Baroti doing

236
00:12:39,280 --> 00:12:44,680
Speaker 3: on Australia that doctor Jones in New York is not doing?

237
00:12:45,000 --> 00:12:49,720
Speaker 3: That reaches that improvement right, and that's where they both

238
00:12:49,840 --> 00:12:53,120
Speaker 3: must have the same exact protocol to be reproduced.

239
00:12:53,360 --> 00:12:55,840
Speaker 4: So unfortunately, until there is.

240
00:12:56,160 --> 00:12:59,600
Speaker 3: You know, when we when doctor Einsman in nineteen fifty

241
00:12:59,640 --> 00:13:03,079
Speaker 3: eight set himself out to take stools and give it

242
00:13:03,120 --> 00:13:06,320
Speaker 3: to two patients to see this by enema, he just

243
00:13:06,360 --> 00:13:08,720
Speaker 3: probably had a gut feeling. You know, he knew that

244
00:13:08,800 --> 00:13:12,440
Speaker 3: if you go back to fifth century China, the Chinese

245
00:13:12,440 --> 00:13:16,680
Speaker 3: were giving you know, poop, you know, the yellow soup

246
00:13:17,080 --> 00:13:19,000
Speaker 3: to the patients to improve polera.

247
00:13:19,160 --> 00:13:23,800
Speaker 4: Right. So what probably happened with Einsman.

248
00:13:23,440 --> 00:13:25,719
Speaker 3: Is he said, hey, why don't I these people are

249
00:13:25,800 --> 00:13:28,560
Speaker 3: dying because you know, we as doctors, when we have

250
00:13:28,600 --> 00:13:31,400
Speaker 3: a patient and they're dying, we try everything.

251
00:13:31,480 --> 00:13:31,680
Speaker 4: Right.

252
00:13:31,720 --> 00:13:34,480
Speaker 3: That's the art of innovation, as the art of medicines.

253
00:13:34,559 --> 00:13:37,240
Speaker 3: That gut feeling of like hmm, let me give this.

254
00:13:37,520 --> 00:13:37,719
Speaker 3: Let me.

255
00:13:38,000 --> 00:13:39,240
Speaker 4: It's like that recipe.

256
00:13:39,280 --> 00:13:41,800
Speaker 3: You're a chef in the kitchen and you're basically saying,

257
00:13:42,400 --> 00:13:44,240
Speaker 3: let me put some salt, let me put some cumin,

258
00:13:44,360 --> 00:13:45,439
Speaker 3: let me put some turmeric.

259
00:13:45,520 --> 00:13:48,440
Speaker 4: Let me bring this meal that's going to be delicious. Right.

260
00:13:49,200 --> 00:13:51,240
Speaker 4: So it's the same thing with medicine.

261
00:13:51,240 --> 00:13:53,920
Speaker 3: It's kind of like figuring out how to use drugs

262
00:13:54,000 --> 00:13:57,120
Speaker 3: off label to achieve improvement, and you don't want to

263
00:13:57,200 --> 00:14:00,640
Speaker 3: let the patient die, so that's why you go into

264
00:14:00,679 --> 00:14:06,040
Speaker 3: the field, right. So innovation is a big part of medicine.

265
00:14:06,400 --> 00:14:10,040
Speaker 3: So doctor Einsman when he started with nineteen in nineteen

266
00:14:10,080 --> 00:14:14,280
Speaker 3: fifty eight with his two cases, it took sixty two

267
00:14:14,679 --> 00:14:18,760
Speaker 3: years for fecal transplant to be part of the guidelines.

268
00:14:19,680 --> 00:14:22,800
Speaker 3: That's how long it took. So you can imagine that

269
00:14:22,880 --> 00:14:26,440
Speaker 3: in nineteen fifty eight, when doctor Einsman said, Hey, I'm

270
00:14:26,440 --> 00:14:30,920
Speaker 3: coming out with fecal transplant for see this, the community

271
00:14:31,120 --> 00:14:34,840
Speaker 3: was probably going, is he crazy? Who's going to play

272
00:14:34,880 --> 00:14:38,920
Speaker 3: with poop? Are we even mad to think about that?

273
00:14:39,520 --> 00:14:41,720
Speaker 3: You know, because there's a lot of questions that happen,

274
00:14:41,880 --> 00:14:45,040
Speaker 3: right like what poop, what's in poop? Are we risking

275
00:14:45,080 --> 00:14:45,520
Speaker 3: the life?

276
00:14:45,520 --> 00:14:45,960
Speaker 4: Et cetera.

277
00:14:46,120 --> 00:14:49,280
Speaker 3: So where's the GI community. Well, I think the gr

278
00:14:49,320 --> 00:14:52,480
Speaker 3: community wants to see this happening.

279
00:14:53,400 --> 00:14:54,560
Speaker 4: I just think that.

280
00:14:54,440 --> 00:14:58,520
Speaker 3: They're cautious because there's a trillion microbes out there and

281
00:14:58,560 --> 00:15:01,880
Speaker 3: we barely touch the surface of the microbiome. Look, I'm

282
00:15:01,880 --> 00:15:06,440
Speaker 3: in the same situation right before. When I started working

283
00:15:06,480 --> 00:15:10,160
Speaker 3: with doctor Barotti, and he's the father of fecal transplant. Essentially,

284
00:15:10,200 --> 00:15:13,520
Speaker 3: he took doctor Einsman's work and decided to do it

285
00:15:13,560 --> 00:15:17,960
Speaker 3: on a larger scale. And when I started working with him,

286
00:15:18,000 --> 00:15:23,160
Speaker 3: it was because I had improved two cases of Crohn's disease.

287
00:15:23,240 --> 00:15:27,160
Speaker 3: And I remember doctor Neil Stolman who basically introduced that

288
00:15:27,240 --> 00:15:30,240
Speaker 3: at the American College of gastro and said, doctor BARROTI

289
00:15:30,320 --> 00:15:33,160
Speaker 3: do you know doctor Hays And she also improved Crohn's

290
00:15:33,200 --> 00:15:35,480
Speaker 3: disease in two of her patients. So he was just

291
00:15:36,120 --> 00:15:39,040
Speaker 3: delighted that somebody was reproducing his data.

292
00:15:39,200 --> 00:15:39,360
Speaker 4: Right.

293
00:15:40,200 --> 00:15:42,400
Speaker 3: But when I started talking to him, he kept saying

294
00:15:42,440 --> 00:15:45,800
Speaker 3: to me, you'll see fecal transplant with autism. Be ready,

295
00:15:45,880 --> 00:15:49,160
Speaker 3: be ready, And I was like, I'm not going to

296
00:15:49,200 --> 00:15:50,240
Speaker 3: see kids with autism.

297
00:15:50,280 --> 00:15:52,080
Speaker 4: I'm an adult gastrentrologist.

298
00:15:52,720 --> 00:15:56,320
Speaker 3: And then doctor Adams came out with his data, the

299
00:15:56,360 --> 00:16:02,400
Speaker 3: initial data that basically showed fecal transplant helped eighteen fifty

300
00:16:02,400 --> 00:16:04,680
Speaker 3: percent of his kids with autism that he had done

301
00:16:04,720 --> 00:16:06,960
Speaker 3: on the study. It was like eighteen patients and nine

302
00:16:06,960 --> 00:16:09,960
Speaker 3: of them improved with fecal transplant, and he showcased this

303
00:16:10,080 --> 00:16:12,720
Speaker 3: case of a kid that was basically verbal and back

304
00:16:12,800 --> 00:16:13,320
Speaker 3: to the normal.

305
00:16:13,400 --> 00:16:13,600
Speaker 4: Right.

306
00:16:14,360 --> 00:16:19,640
Speaker 3: And then that moment, kids with autism started coming in

307
00:16:19,720 --> 00:16:23,480
Speaker 3: my office. And the first thing I did was submit

308
00:16:23,560 --> 00:16:26,440
Speaker 3: an I and D to the FDA because I wanted

309
00:16:26,440 --> 00:16:31,760
Speaker 3: to see the data. I didn't trust, you know, others.

310
00:16:31,960 --> 00:16:35,160
Speaker 3: I wanted to see it for myself. When I saw

311
00:16:35,360 --> 00:16:39,400
Speaker 3: a seventeen year old who then became nineteen twenty years old,

312
00:16:39,440 --> 00:16:41,480
Speaker 3: when I did nineteen year old, when I did him

313
00:16:42,080 --> 00:16:48,400
Speaker 3: improve his speech with fecal transplant, become calmer with fecal transplant,

314
00:16:48,600 --> 00:16:51,840
Speaker 3: I knew there was something to this, and I knew

315
00:16:52,040 --> 00:16:56,680
Speaker 3: it needed to be more. And so that's how it starts.

316
00:16:56,760 --> 00:17:00,040
Speaker 3: You get hooked on something. You see something, and you

317
00:17:00,080 --> 00:17:01,880
Speaker 3: want to see more and you want to know more,

318
00:17:02,280 --> 00:17:04,800
Speaker 3: and then you get hooked and then it takes over

319
00:17:04,800 --> 00:17:05,320
Speaker 3: your life.

320
00:17:05,359 --> 00:17:06,120
Speaker 4: And here we are.

321
00:17:07,400 --> 00:17:08,480
Speaker 1: It's bunny amazing.

322
00:17:08,640 --> 00:17:14,000
Speaker 2: It's also I read something about some identical autistic twins

323
00:17:14,000 --> 00:17:19,040
Speaker 2: who are both nonverbal and aggressive and lacking is it biffitol,

324
00:17:19,400 --> 00:17:22,280
Speaker 2: bacterium or something at Bislin.

325
00:17:21,920 --> 00:17:25,000
Speaker 3: So that case has come Yeah, that case is coming

326
00:17:25,160 --> 00:17:28,760
Speaker 3: out at the American collegere of Gastro and publishing it.

327
00:17:29,320 --> 00:17:33,760
Speaker 3: And these two identical twins have the exact same microbes,

328
00:17:34,280 --> 00:17:38,560
Speaker 3: and those microbes disappeared, and then the good microbes started

329
00:17:38,640 --> 00:17:43,760
Speaker 3: climbing up exactly resuming speech. And now nine months later

330
00:17:43,800 --> 00:17:47,760
Speaker 3: they're fully verbal, fully non aggressive. I don't even think

331
00:17:47,800 --> 00:17:49,560
Speaker 3: you can call them autistic anymore.

332
00:17:49,800 --> 00:17:52,359
Speaker 4: But the amazing thing is seeing.

333
00:17:52,040 --> 00:17:55,760
Speaker 3: The microbes that were the culprit of their autism at

334
00:17:55,800 --> 00:18:00,879
Speaker 3: the beginning in both identical you know, out of trillions

335
00:18:00,880 --> 00:18:04,840
Speaker 3: of microbes, to pick up in two separate stool samples,

336
00:18:05,240 --> 00:18:09,560
Speaker 3: taking at different times and analyze at different times, to

337
00:18:09,720 --> 00:18:17,080
Speaker 3: find the three identical microbes on both a DNA platform

338
00:18:17,119 --> 00:18:20,000
Speaker 3: which is basically looking at dead or live microbes, and

339
00:18:20,040 --> 00:18:23,600
Speaker 3: then reproducing that in an RNA PI platform, which is

340
00:18:23,800 --> 00:18:27,040
Speaker 3: just the live microbes in two identical twins is just

341
00:18:27,280 --> 00:18:31,040
Speaker 3: unbelievable because it puts the whole field of.

342
00:18:30,960 --> 00:18:32,280
Speaker 4: Autism to start.

343
00:18:32,680 --> 00:18:37,000
Speaker 3: We need to start paying attention to the microbiome in

344
00:18:37,160 --> 00:18:40,480
Speaker 3: kids with autism, and more importantly, we need to pay

345
00:18:40,520 --> 00:18:44,320
Speaker 3: attention to what are we doing to destroy that microbiome

346
00:18:44,760 --> 00:18:48,920
Speaker 3: that these kids are autistic and aggressive and nonverbal. We're

347
00:18:48,960 --> 00:18:53,160
Speaker 3: not talking about the spectrum that you know ADHD here,

348
00:18:53,240 --> 00:18:57,680
Speaker 3: we're talking about nonverbal, aggressive kids that are banging their

349
00:18:57,680 --> 00:18:59,800
Speaker 3: head on the wall and have to wear a hum

350
00:19:00,080 --> 00:19:02,840
Speaker 3: it to stay alive. That's what we're talking about.

351
00:19:03,040 --> 00:19:04,280
Speaker 1: Wow, that's incredible.

352
00:19:04,320 --> 00:19:08,760
Speaker 2: And so now both of those twins speak, they're not aggressive,

353
00:19:09,080 --> 00:19:10,720
Speaker 2: and they're fully fun.

354
00:19:10,840 --> 00:19:14,560
Speaker 3: They're doing they're doing amazing, they're reading books, they're going

355
00:19:14,600 --> 00:19:15,240
Speaker 3: to school.

356
00:19:15,400 --> 00:19:17,920
Speaker 4: The mom is above and beyond.

357
00:19:18,680 --> 00:19:21,000
Speaker 3: So we want to you know, obviously these cases, you know,

358
00:19:21,000 --> 00:19:23,320
Speaker 3: because everybody's asking me, oh, can we see So I

359
00:19:24,080 --> 00:19:26,879
Speaker 3: took a video and I kind of like removed the

360
00:19:26,920 --> 00:19:30,040
Speaker 3: face of the child to kind of showcase the speech.

361
00:19:30,640 --> 00:19:32,320
Speaker 4: But you know, you want to say, you don't want

362
00:19:32,320 --> 00:19:34,240
Speaker 4: to put these kids in the limelight. You want to

363
00:19:34,359 --> 00:19:36,200
Speaker 4: keep them growing nicely.

364
00:19:36,280 --> 00:19:39,119
Speaker 3: You don't want to make you know, there's so much

365
00:19:40,240 --> 00:19:44,280
Speaker 3: anger out there, there's so much corruption out there, especially

366
00:19:44,320 --> 00:19:45,440
Speaker 3: in the field of autism.

367
00:19:45,920 --> 00:19:47,880
Speaker 4: I feel because there's.

368
00:19:47,760 --> 00:19:51,359
Speaker 3: So many people blaming so many things with autism, and

369
00:19:51,400 --> 00:19:55,360
Speaker 3: there's such a business that developed with autism too that

370
00:19:56,359 --> 00:20:01,080
Speaker 3: unfortunately it's very hot out there and these poor kids

371
00:20:01,080 --> 00:20:01,959
Speaker 3: are caught in between.

372
00:20:03,200 --> 00:20:07,120
Speaker 2: How wide if it older, you open the door in

373
00:20:07,280 --> 00:20:11,080
Speaker 2: terms of nutrition and doughtry habits, because of course that

374
00:20:11,160 --> 00:20:17,040
Speaker 2: has an extreme impact on the micro bio So to

375
00:20:17,040 --> 00:20:17,560
Speaker 2: what if.

376
00:20:17,520 --> 00:20:22,080
Speaker 3: You don't control If you don't control the nutrition, the vitamins,

377
00:20:22,119 --> 00:20:28,160
Speaker 3: the quality of the vitamins there, everything, the environment, the mold, everything,

378
00:20:28,560 --> 00:20:32,560
Speaker 3: you might as well do a thousand fegal transplant. You're

379
00:20:32,600 --> 00:20:34,760
Speaker 3: never going to achieve all that. You're never going to

380
00:20:34,800 --> 00:20:38,520
Speaker 3: achieve improvement. Part of the reason that there's no reproducibility

381
00:20:38,560 --> 00:20:41,920
Speaker 3: in the field of fecal transplant is because doctors are

382
00:20:41,920 --> 00:20:44,679
Speaker 3: doing fecal transplant, they're using a donor that they believe

383
00:20:44,760 --> 00:20:47,440
Speaker 3: is the right donor for the patient. But then they

384
00:20:47,440 --> 00:20:51,960
Speaker 3: don't discuss what needs to be stopped at the clinic level.

385
00:20:52,280 --> 00:20:56,800
Speaker 3: They don't discuss all the environmental checks that you need

386
00:20:56,880 --> 00:20:59,480
Speaker 3: to do to make sure your house doesn't have mold,

387
00:20:59,560 --> 00:21:02,040
Speaker 3: to make sure sure your kid is not eating some

388
00:21:02,119 --> 00:21:06,239
Speaker 3: vitamins with arsenic in there. There's so much work that

389
00:21:06,320 --> 00:21:10,439
Speaker 3: needs to be done to restore the microbiome properly, and

390
00:21:10,520 --> 00:21:13,600
Speaker 3: so yes, you can put stools in there, but if

391
00:21:13,600 --> 00:21:17,400
Speaker 3: you go back to a diet of garbage and you're

392
00:21:17,480 --> 00:21:20,040
Speaker 3: killing your microbiome, what's the point. You know, it's like

393
00:21:20,080 --> 00:21:25,160
Speaker 3: taking antibiotics right after giving right after giving a new microbiome.

394
00:21:26,200 --> 00:21:27,720
Speaker 4: You know you're killing the microbiome.

395
00:21:28,440 --> 00:21:31,879
Speaker 1: This is probably a dumb question, but it's definitely not

396
00:21:32,000 --> 00:21:36,359
Speaker 1: my area. So how do we how do we identify

397
00:21:36,480 --> 00:21:38,720
Speaker 1: what microbes are lacking?

398
00:21:38,880 --> 00:21:42,960
Speaker 2: Or how do we assess somebody's microbe biome? Like what

399
00:21:43,160 --> 00:21:47,080
Speaker 2: is that you just take a facal examine the examine

400
00:21:47,119 --> 00:21:48,679
Speaker 2: their pooh, or how does that happen?

401
00:21:49,400 --> 00:21:51,720
Speaker 3: So I'll tell you you know what happened to me.

402
00:21:51,920 --> 00:21:55,600
Speaker 3: I was seeing these successes in the field of medicine,

403
00:21:55,680 --> 00:21:58,640
Speaker 3: these end of ones, and I wanted to see the microbiome.

404
00:21:58,640 --> 00:22:01,680
Speaker 3: And I started utilizing all the labs that are out

405
00:22:01,720 --> 00:22:05,640
Speaker 3: there consumer products right, And what I discovered was when

406
00:22:05,680 --> 00:22:08,720
Speaker 3: I was testing the microbiome with those labs, I would

407
00:22:08,720 --> 00:22:12,800
Speaker 3: always send like two samples of the same stool that

408
00:22:12,920 --> 00:22:17,800
Speaker 3: I mixed in and homogenized, and then I would get

409
00:22:17,800 --> 00:22:22,040
Speaker 3: two different results. In one I would have an overgrowth

410
00:22:22,080 --> 00:22:24,600
Speaker 3: of a certain microbe and another one I would have

411
00:22:24,600 --> 00:22:27,600
Speaker 3: an overgrowth of another microbe. And then when I looked

412
00:22:27,600 --> 00:22:29,480
Speaker 3: at that, I go, well, which one is it? I mean,

413
00:22:29,520 --> 00:22:32,800
Speaker 3: how can I put my money on one or the other?

414
00:22:32,880 --> 00:22:33,080
Speaker 1: Right?

415
00:22:33,160 --> 00:22:36,480
Speaker 3: So I realized early on in the field that the

416
00:22:36,560 --> 00:22:41,200
Speaker 3: whole genetic sequencing of stool testing was just flawed.

417
00:22:41,320 --> 00:22:42,920
Speaker 4: And I actually spoke about.

418
00:22:42,600 --> 00:22:47,960
Speaker 3: It in twenty nineteen at the Microbiome Congress in Washington, DC,

419
00:22:48,640 --> 00:22:51,240
Speaker 3: because I said, what are we looking at here if

420
00:22:51,240 --> 00:22:53,919
Speaker 3: we can't even validate and we have two different samples,

421
00:22:54,320 --> 00:22:57,639
Speaker 3: we're comparing apples and oranges. And here's the bigger problem.

422
00:22:57,960 --> 00:23:02,720
Speaker 3: Everybody's different. So the girl from Venezuela that drinks water

423
00:23:02,840 --> 00:23:06,639
Speaker 3: from the river and has giardia in her stools and

424
00:23:06,800 --> 00:23:09,800
Speaker 3: is healthy.

425
00:23:08,480 --> 00:23:12,600
Speaker 4: You know, she's in her environment. Giardia is healthy for her.

426
00:23:12,960 --> 00:23:15,600
Speaker 3: But the girl in America that goes to Mexico and

427
00:23:15,680 --> 00:23:18,760
Speaker 3: drinks water gets giardia and gets diarrhea. I have to

428
00:23:18,800 --> 00:23:23,120
Speaker 3: treat that because unfortunately, in she's not developed a resilience

429
00:23:23,280 --> 00:23:24,320
Speaker 3: for giardia.

430
00:23:25,000 --> 00:23:26,720
Speaker 4: So that's when you.

431
00:23:26,720 --> 00:23:31,439
Speaker 3: Start realizing there's a difference in the microbiome. So if

432
00:23:31,480 --> 00:23:34,439
Speaker 3: there's a difference, how do you compare? How do you

433
00:23:34,640 --> 00:23:38,040
Speaker 3: test if you can't even get the same stool samples

434
00:23:38,080 --> 00:23:38,520
Speaker 3: to match.

435
00:23:38,560 --> 00:23:42,359
Speaker 4: So I basically created my own lab, my own genetic lab.

436
00:23:42,680 --> 00:23:45,640
Speaker 3: I'm actually very fortunate to have this genetic sequencing lab

437
00:23:45,680 --> 00:23:50,120
Speaker 3: because I really believe it kind of saved me, saved

438
00:23:50,119 --> 00:23:53,399
Speaker 3: me from COVID because I was testing. You know, we

439
00:23:53,520 --> 00:23:56,960
Speaker 3: all have a scientist a hypothesis, right, we all.

440
00:23:57,080 --> 00:23:57,760
Speaker 4: You know, some.

441
00:23:57,640 --> 00:24:00,520
Speaker 3: People believe in this drug, and some people believe in

442
00:24:00,600 --> 00:24:03,720
Speaker 3: this tea cell, and I believe in the power of

443
00:24:03,760 --> 00:24:07,760
Speaker 3: the bifidobacteria. Right, I'm all about save the bit of biffodobacteria. Right,

444
00:24:08,200 --> 00:24:12,679
Speaker 3: Because during COVID, I discovered that loss of bifidobacteria was

445
00:24:12,720 --> 00:24:17,520
Speaker 3: linked with COVID, severe COVID, with long COVID, with autism,

446
00:24:17,640 --> 00:24:23,480
Speaker 3: with Alzheimer's, with line disease, with Crohn's disease, with invasive cancer.

447
00:24:24,000 --> 00:24:28,800
Speaker 3: So bifitdobacteria became this bug that I just like followed, right,

448
00:24:29,600 --> 00:24:32,280
Speaker 3: And so I was testing my stools, right, I was

449
00:24:32,320 --> 00:24:36,560
Speaker 3: testing my bifito bacteria throughout the pandemic. I learned a lot.

450
00:24:37,240 --> 00:24:40,120
Speaker 3: So what we did in our lab is we took

451
00:24:40,160 --> 00:24:44,520
Speaker 3: the technology that's out there, but we made it valid, verified,

452
00:24:44,560 --> 00:24:47,040
Speaker 3: and reproducible. In other words, if I test my stools

453
00:24:47,040 --> 00:24:49,280
Speaker 3: today tomorrow, if I don't, if I do the same

454
00:24:49,280 --> 00:24:52,159
Speaker 3: thing like I eat my you know, my malbatoast and

455
00:24:52,200 --> 00:24:54,600
Speaker 3: my Creatures cream cheese in the morning, and my yogurt

456
00:24:54,640 --> 00:24:59,320
Speaker 3: and my tuna whatever, you know, diet, same diet, same day,

457
00:24:59,440 --> 00:25:03,679
Speaker 3: every day days, and my microbiome doesn't change, I should

458
00:25:03,680 --> 00:25:05,679
Speaker 3: see the same exact poop.

459
00:25:05,880 --> 00:25:06,080
Speaker 4: Right.

460
00:25:06,720 --> 00:25:09,600
Speaker 3: The other thing is we go super deep into the microbiome.

461
00:25:09,760 --> 00:25:11,760
Speaker 3: So we're not looking at what you ate last night

462
00:25:11,800 --> 00:25:15,720
Speaker 3: for breakfast, for dinner. We're looking at what's living in

463
00:25:15,760 --> 00:25:19,560
Speaker 3: your gut, okay, because that really is what's telling us

464
00:25:19,560 --> 00:25:23,320
Speaker 3: a story. Now, could we be better? Could we be

465
00:25:23,560 --> 00:25:27,399
Speaker 3: improving our technology? Of course, that's why it's a research lab.

466
00:25:28,040 --> 00:25:32,800
Speaker 3: So we are a genetic sequencing lab that's research, and

467
00:25:32,840 --> 00:25:36,480
Speaker 3: we have a foundation that's a nonprofit that basically helps.

468
00:25:36,280 --> 00:25:37,480
Speaker 4: Us do studies.

469
00:25:37,520 --> 00:25:40,879
Speaker 3: When we want to analyze sixty samples of Parkinson's and

470
00:25:40,920 --> 00:25:43,760
Speaker 3: we have to do a bioinformatics pipeline, we have a

471
00:25:43,800 --> 00:25:49,600
Speaker 3: foundation that basically supports you know, these studies. So essentially

472
00:25:49,760 --> 00:25:55,440
Speaker 3: that's what So we do genetic sequencing, and we've seen

473
00:25:55,480 --> 00:26:00,560
Speaker 3: some things we've seen that vitamin C increases biffito bacteria. Yeah,

474
00:26:00,720 --> 00:26:04,439
Speaker 3: so we tested patients before and after and we noticed

475
00:26:04,520 --> 00:26:07,280
Speaker 3: vitamin C. Now, you and I know when you have

476
00:26:07,320 --> 00:26:09,119
Speaker 3: a call, the first thing you go to is your

477
00:26:09,160 --> 00:26:12,760
Speaker 3: vitamin C. Right, and we also know that vitamin C

478
00:26:13,600 --> 00:26:16,480
Speaker 3: has had great reviews over the years. This is not

479
00:26:16,600 --> 00:26:21,560
Speaker 3: something that's you know, basically of you know, it's not

480
00:26:21,880 --> 00:26:26,880
Speaker 3: a new thing. It's something that we've known about it. Right,

481
00:26:28,680 --> 00:26:32,040
Speaker 3: when you see the data that vitamin C increases bifitrobactery

482
00:26:32,119 --> 00:26:36,600
Speaker 3: in vitro and then you can reproduce it in humans.

483
00:26:36,160 --> 00:26:39,160
Speaker 4: In a clinical picture, you know you're on the right path.

484
00:26:39,240 --> 00:26:43,080
Speaker 3: You know your lab is validated because it's reproducing what

485
00:26:43,160 --> 00:26:48,320
Speaker 3: you're showing. When you are showing two identical twins with

486
00:26:48,440 --> 00:26:54,200
Speaker 3: the same exact microbes and you're showing that you improve

487
00:26:54,320 --> 00:26:58,400
Speaker 3: the microbiome of these kids and that microbe those microbes disappear,

488
00:26:58,880 --> 00:27:00,480
Speaker 3: that's a validated assay.

489
00:27:01,040 --> 00:27:03,080
Speaker 4: That's how we look at the microbiome.

490
00:27:03,200 --> 00:27:07,000
Speaker 3: So how do we it's basically forensic medicine of the

491
00:27:07,040 --> 00:27:11,000
Speaker 3: microbiome to basically say this is what you should have,

492
00:27:11,760 --> 00:27:14,480
Speaker 3: this is what you're lacking. Now, it's not very easy

493
00:27:14,600 --> 00:27:18,520
Speaker 3: because there's different genetics, different populations. So I tend to

494
00:27:18,560 --> 00:27:22,119
Speaker 3: look at the microbiome of families. So I'll go to

495
00:27:22,240 --> 00:27:25,520
Speaker 3: Venezuela and I'll say, you know, yes, you want me

496
00:27:25,560 --> 00:27:28,320
Speaker 3: to treat your kid with autism, but let me look

497
00:27:28,320 --> 00:27:29,080
Speaker 3: at the family.

498
00:27:29,160 --> 00:27:30,520
Speaker 4: What does the family look like?

499
00:27:30,680 --> 00:27:32,520
Speaker 3: Because if I look at the kid and I see

500
00:27:32,840 --> 00:27:35,000
Speaker 3: he's got giardia, for example, I'm going to think, well,

501
00:27:35,000 --> 00:27:38,600
Speaker 3: that's the giardia causing his autism, but not necessarily because

502
00:27:38,600 --> 00:27:41,199
Speaker 3: everybody in the family may have giardia, so that's not

503
00:27:41,840 --> 00:27:45,560
Speaker 3: his microbe that's out of balance. So it's really doing

504
00:27:45,680 --> 00:27:50,600
Speaker 3: forensics of the gut to basically understand the microbiome and

505
00:27:50,640 --> 00:27:55,719
Speaker 3: then from there determine what's overgrown, what's elevated, that's above

506
00:27:55,760 --> 00:28:00,119
Speaker 3: and beyond, and then what's lost above and beyond, and

507
00:28:00,160 --> 00:28:05,280
Speaker 3: then from there trying to readjust that balance, you know,

508
00:28:05,440 --> 00:28:09,360
Speaker 3: get back into a balance, try different things. But now

509
00:28:09,440 --> 00:28:12,840
Speaker 3: we have an assay that can tell us even though

510
00:28:12,880 --> 00:28:17,240
Speaker 3: it's a research tool, it can tell us yes, this improved,

511
00:28:17,240 --> 00:28:22,880
Speaker 3: this didn't improve. So it's a fascinating field. It's all research.

512
00:28:23,280 --> 00:28:25,840
Speaker 3: I work with a lot of doctors who practice the

513
00:28:25,960 --> 00:28:29,199
Speaker 3: art of medicine and who basically, you know, give a

514
00:28:29,200 --> 00:28:32,160
Speaker 3: lot of different things, and they'll test their patients before

515
00:28:32,160 --> 00:28:33,960
Speaker 3: and after and they'll say, sabbe and I'm sending you

516
00:28:33,960 --> 00:28:36,720
Speaker 3: a stool sample, and then we look at the tool

517
00:28:36,720 --> 00:28:39,800
Speaker 3: sample before and after together and if we see something interesting,

518
00:28:39,920 --> 00:28:42,920
Speaker 3: then we do more patients and then we get to

519
00:28:43,000 --> 00:28:46,000
Speaker 3: see what happens there, right, and then we get to

520
00:28:46,200 --> 00:28:48,320
Speaker 3: come out with a great paper, like the vitamin C

521
00:28:48,480 --> 00:28:50,000
Speaker 3: increases the biffito bacteria.

522
00:28:52,480 --> 00:28:54,280
Speaker 1: You're not excited about this stuff at all?

523
00:28:54,320 --> 00:28:54,560
Speaker 3: Are you?

524
00:28:55,560 --> 00:28:55,640
Speaker 2: Not?

525
00:28:55,800 --> 00:28:56,080
Speaker 1: At all?

526
00:28:56,120 --> 00:28:56,960
Speaker 4: It's really not.

527
00:28:58,040 --> 00:28:59,920
Speaker 1: It doesn't show, it doesn't show.

528
00:29:00,560 --> 00:29:03,440
Speaker 4: It's like, I'll tell you what I'm more. I'll tell

529
00:29:03,440 --> 00:29:04,920
Speaker 4: you what I'm more excited about.

530
00:29:05,000 --> 00:29:08,160
Speaker 3: This is all you know, this is great clinical I'm

531
00:29:08,200 --> 00:29:13,000
Speaker 3: more excited. I'm doing a expedition in the Amazon jungle

532
00:29:13,440 --> 00:29:16,600
Speaker 3: in February, and we're gonna be documenting the whole thing.

533
00:29:17,040 --> 00:29:21,440
Speaker 3: But I'm more excited about like collecting the stools, the soil,

534
00:29:22,040 --> 00:29:25,960
Speaker 3: the microbes, finding microbes, collecting the stools of the animals

535
00:29:26,000 --> 00:29:31,160
Speaker 3: in the Amazon jungle, collecting the soil, finding microbes.

536
00:29:30,640 --> 00:29:33,120
Speaker 4: That are new. That's what I'm more excited about.

537
00:29:33,960 --> 00:29:37,880
Speaker 2: I'm not sure how well, I'm not sure how how

538
00:29:38,600 --> 00:29:42,200
Speaker 2: well received the Hey, could you pooh into this bag

539
00:29:42,280 --> 00:29:42,600
Speaker 2: for me?

540
00:29:43,560 --> 00:29:47,320
Speaker 1: For the locals. You know, I'm doctor Sabine, can have

541
00:29:47,400 --> 00:29:48,120
Speaker 1: some shit.

542
00:29:49,200 --> 00:29:52,000
Speaker 3: I'm gonna collect what's already dropped in the soil.

543
00:29:52,960 --> 00:29:54,960
Speaker 4: I'm gonna go, you know I I do that.

544
00:29:55,080 --> 00:29:57,760
Speaker 3: By the way, I have I have coyotes and mountain

545
00:29:57,800 --> 00:30:00,000
Speaker 3: lions in my backyard, so they always.

546
00:29:59,720 --> 00:30:01,240
Speaker 4: Leave me these little gifts.

547
00:30:01,880 --> 00:30:04,600
Speaker 3: So I always collect the stools of the coyote and

548
00:30:04,640 --> 00:30:07,480
Speaker 3: the mountain lion. And my staff is really funny because

549
00:30:07,520 --> 00:30:10,080
Speaker 3: they got doctor hees. And you know, these stool samples

550
00:30:10,080 --> 00:30:13,120
Speaker 3: are very expensive. You're just spending like two grand on

551
00:30:13,160 --> 00:30:16,200
Speaker 3: a coyote poop? Is that really what you should be doing?

552
00:30:16,440 --> 00:30:20,200
Speaker 3: And basically, here we are, what can we do?

553
00:30:20,880 --> 00:30:21,400
Speaker 1: Here we are?

554
00:30:21,520 --> 00:30:25,520
Speaker 2: You know what's it's interesting because of many reasons, but

555
00:30:26,840 --> 00:30:30,600
Speaker 2: like you're at the coal face of personalized medicine. Because

556
00:30:31,280 --> 00:30:34,000
Speaker 2: you know, when you think about when people rock up

557
00:30:34,000 --> 00:30:36,520
Speaker 2: to a doctor and they go, you know, I've got

558
00:30:36,520 --> 00:30:38,680
Speaker 2: this pain or that pain. I say, all right, we'll

559
00:30:38,680 --> 00:30:40,680
Speaker 2: start you on one hundred milligrams of that and then

560
00:30:40,720 --> 00:30:42,800
Speaker 2: we'll see how it goes. It's all very kind of

561
00:30:43,480 --> 00:30:46,840
Speaker 2: well you've got arthreatic pain there so therefore, or you've

562
00:30:46,840 --> 00:30:49,600
Speaker 2: got high blood pressure, we'll start you on aviprob one fifty.

563
00:30:49,680 --> 00:30:53,080
Speaker 2: Will you know, We'll do whatever, right, And so we go,

564
00:30:53,200 --> 00:30:56,160
Speaker 2: what's your ailment? Right, Well, we tend to use this

565
00:30:56,240 --> 00:31:00,600
Speaker 2: drug for that. The dosage varies or the varies a

566
00:31:00,640 --> 00:31:03,280
Speaker 2: little bit, so let's try you on this drug that does.

567
00:31:03,400 --> 00:31:07,440
Speaker 2: Let's see what happens. Whereas with this it's like every

568
00:31:07,520 --> 00:31:11,360
Speaker 2: medication for every patient is personally developed based on their

569
00:31:11,400 --> 00:31:12,760
Speaker 2: individual physiology.

570
00:31:12,840 --> 00:31:15,360
Speaker 4: Right, Yes, and that's actually the future.

571
00:31:15,440 --> 00:31:17,480
Speaker 3: Of course, it's not going to be of my lifetime,

572
00:31:17,520 --> 00:31:20,239
Speaker 3: but it's definitely going to be in the future. It

573
00:31:20,320 --> 00:31:26,280
Speaker 3: is not It is not so far fetched to think

574
00:31:26,360 --> 00:31:28,160
Speaker 3: that in the future you're going to go to a

575
00:31:28,200 --> 00:31:32,960
Speaker 3: pharmacy that's basically going to give you microbes to adjust

576
00:31:33,000 --> 00:31:36,280
Speaker 3: your microbiome based on a test that you have where

577
00:31:36,280 --> 00:31:38,840
Speaker 3: it can see what you have too much of and

578
00:31:38,880 --> 00:31:41,600
Speaker 3: what you have too little of. So I think that's

579
00:31:41,760 --> 00:31:44,920
Speaker 3: that might be the future, truly, so we might we

580
00:31:45,000 --> 00:31:45,680
Speaker 3: might go back.

581
00:31:45,560 --> 00:31:47,880
Speaker 1: To the compounding days the apostogy here.

582
00:31:47,960 --> 00:31:48,960
Speaker 4: But here's the problem.

583
00:31:49,000 --> 00:31:54,480
Speaker 3: We're killing faster than we are building. And my biggest

584
00:31:54,520 --> 00:31:58,240
Speaker 3: problem is we are going to be left with disappearing microbes.

585
00:31:58,840 --> 00:32:02,000
Speaker 3: When you look at lacto bisillas, for example, when you

586
00:32:02,040 --> 00:32:06,400
Speaker 3: look at biffotobacteria, less than one percent of people out

587
00:32:06,440 --> 00:32:09,000
Speaker 3: there probably have lack too basillas and less than five

588
00:32:09,080 --> 00:32:13,000
Speaker 3: percent have biffetobacteria, those two important microbes that are important

589
00:32:13,000 --> 00:32:16,960
Speaker 3: in breaking down sugar and breaking down calcium. So what

590
00:32:17,160 --> 00:32:20,240
Speaker 3: happens when those microbes disappear. Part of the reason I'm

591
00:32:20,240 --> 00:32:22,360
Speaker 3: going to the Amazon jungle and then I'm going to

592
00:32:22,400 --> 00:32:24,320
Speaker 3: go to Baku, and then I'm going to go to

593
00:32:25,040 --> 00:32:29,400
Speaker 3: Greece and all these different regions is to really find

594
00:32:29,600 --> 00:32:30,720
Speaker 3: lost microbes.

595
00:32:31,240 --> 00:32:35,480
Speaker 4: And those lost microbes really could be in the animals.

596
00:32:35,520 --> 00:32:38,160
Speaker 3: You know, when I was in Zimbabwe, I was interested

597
00:32:38,160 --> 00:32:40,760
Speaker 3: in testing the microboom of the elephants and the zebra

598
00:32:40,840 --> 00:32:45,720
Speaker 3: and the lions, because that's where you find missing microbes.

599
00:32:45,800 --> 00:32:51,440
Speaker 3: You know, to find ticks in an elephant dung was

600
00:32:51,640 --> 00:32:57,520
Speaker 3: really impressive, you know, to basically say, Wow, the guide

601
00:32:57,520 --> 00:33:00,440
Speaker 3: that touches the dung of the elephant doesn't have line disease.

602
00:33:00,880 --> 00:33:04,080
Speaker 3: But yet my person that goes hiking in the Malibu

603
00:33:04,240 --> 00:33:08,120
Speaker 3: Mountains has line from a bit from a tick. What's

604
00:33:08,120 --> 00:33:11,480
Speaker 3: the difference between the microbiome of the guy in Zimbabwe

605
00:33:12,120 --> 00:33:16,920
Speaker 3: versus the person that's hiking in the Santa Monica, you

606
00:33:16,960 --> 00:33:17,600
Speaker 3: know mountain.

607
00:33:18,680 --> 00:33:23,320
Speaker 2: You know that's what Like, we don't have any well,

608
00:33:23,360 --> 00:33:26,200
Speaker 2: I guess we don't have a lot of historical data

609
00:33:26,280 --> 00:33:30,200
Speaker 2: or research. I mean, you know, I know it's kind

610
00:33:30,200 --> 00:33:33,120
Speaker 2: of kicked off in the fifties or whatever, but is

611
00:33:33,440 --> 00:33:38,280
Speaker 2: do we have an idea of how much the for

612
00:33:38,360 --> 00:33:41,520
Speaker 2: one of the better term, the health of our microbiome

613
00:33:41,760 --> 00:33:44,240
Speaker 2: is declining? Like do you think it's worse than it's

614
00:33:44,240 --> 00:33:46,880
Speaker 2: ever been or it's always been bad, but we just

615
00:33:46,920 --> 00:33:49,280
Speaker 2: didn't know because the research wasn't there. Like, do you

616
00:33:49,280 --> 00:33:53,920
Speaker 2: think in twenty twenty five it's in general terms worse

617
00:33:53,960 --> 00:33:56,720
Speaker 2: than it was for the average American or Australian say

618
00:33:56,760 --> 00:33:57,920
Speaker 2: twenty or thirty years ago.

619
00:33:59,040 --> 00:34:03,640
Speaker 3: I think COVID and you know, COVID and the whole

620
00:34:03,960 --> 00:34:08,640
Speaker 3: you know pandemic really damaged the microbiome of humanity in

621
00:34:08,640 --> 00:34:11,440
Speaker 3: my opinion, and everything we did for COVID, you know,

622
00:34:11,480 --> 00:34:16,880
Speaker 3: the response from treatment to prophilaxis. I think that really

623
00:34:17,080 --> 00:34:20,680
Speaker 3: I can tell you from analyzing those tools before COVID

624
00:34:21,280 --> 00:34:25,040
Speaker 3: to analyzing those tools now, there's a huge loss of

625
00:34:25,120 --> 00:34:27,440
Speaker 3: microbes and a huge loss of diversity.

626
00:34:29,320 --> 00:34:30,719
Speaker 4: If I you.

627
00:34:30,600 --> 00:34:32,800
Speaker 3: Know, if I, if I had a if I could

628
00:34:32,840 --> 00:34:36,800
Speaker 3: go back to the past and to the eighteen hundreds,

629
00:34:36,800 --> 00:34:39,360
Speaker 3: I would love to have stool samples of eighteen hundred

630
00:34:39,360 --> 00:34:42,040
Speaker 3: to compare to today. But I bet you it had

631
00:34:42,080 --> 00:34:45,239
Speaker 3: a lot more diversity than we have now. And I

632
00:34:45,280 --> 00:34:48,360
Speaker 3: think with the loss of diversity of microbes, we're having

633
00:34:48,520 --> 00:34:51,760
Speaker 3: a lot more diseases. And that's why there's an increase

634
00:34:51,760 --> 00:34:54,839
Speaker 3: in diseases. When you again, when you look at lime

635
00:34:54,960 --> 00:34:59,720
Speaker 3: disease in you know, it's not really a problem in Africa,

636
00:34:59,760 --> 00:35:03,240
Speaker 3: but it's a problem in California.

637
00:35:03,480 --> 00:35:05,799
Speaker 4: We have a problem. We've killed too much here. We're

638
00:35:05,880 --> 00:35:09,160
Speaker 4: overdoing it. We're over sterilizing. Think about the pandemic.

639
00:35:09,200 --> 00:35:14,080
Speaker 3: They had an alcohol bottle on every store, in every direction.

640
00:35:14,280 --> 00:35:16,560
Speaker 4: They sterilized the heck out of you. They put you

641
00:35:16,640 --> 00:35:19,480
Speaker 4: in masks. You weren't a bubble. You can't live in

642
00:35:19,520 --> 00:35:20,000
Speaker 4: a bubble.

643
00:35:20,200 --> 00:35:23,000
Speaker 3: I mean, anybody knows you need microbes to live, right,

644
00:35:23,880 --> 00:35:26,160
Speaker 3: And that's what we're learning with the microbiome is you

645
00:35:26,200 --> 00:35:26,960
Speaker 3: need microbes.

646
00:35:27,000 --> 00:35:27,520
Speaker 4: You need that.

647
00:35:28,080 --> 00:35:32,480
Speaker 3: Hugging of humans, to that contact to share microbes to

648
00:35:32,520 --> 00:35:36,840
Speaker 3: continue living and continue developing that resilience. I'll tell you

649
00:35:36,880 --> 00:35:41,319
Speaker 3: what the microbiome to me is, It is where the

650
00:35:41,440 --> 00:35:46,600
Speaker 3: hemoglobin was years ago. When people were bleeding in the

651
00:35:46,640 --> 00:35:50,200
Speaker 3: olden days, we had no idea how to fix the bleeding.

652
00:35:50,280 --> 00:35:53,520
Speaker 3: We would let them bleed. So what we started doing

653
00:35:53,640 --> 00:35:57,239
Speaker 3: was we started developing a marker called the hemoglobin. If

654
00:35:57,239 --> 00:36:00,840
Speaker 3: they were low below seven, we would say, hey, let's transfuse.

655
00:36:01,400 --> 00:36:03,920
Speaker 3: If they were high at twelve, we would say, we

656
00:36:03,960 --> 00:36:07,400
Speaker 3: don't need to transfuse. Right, we're not even there yet,

657
00:36:08,080 --> 00:36:10,840
Speaker 3: So we are people are essentially.

658
00:36:10,440 --> 00:36:11,839
Speaker 4: Bleeding, right.

659
00:36:12,000 --> 00:36:15,360
Speaker 3: They have a leaky gut, a this biosis, and we

660
00:36:15,480 --> 00:36:18,520
Speaker 3: don't even know what a this biosis is. There's a

661
00:36:18,600 --> 00:36:22,319
Speaker 3: lot of hypothetical workout there based on animal studies of

662
00:36:22,360 --> 00:36:26,080
Speaker 3: what a leaky gut is, but clinically there's not much.

663
00:36:26,160 --> 00:36:29,560
Speaker 3: There's not a real definition of what a leaky gut

664
00:36:29,760 --> 00:36:33,520
Speaker 3: is and what even is a normal microbiome and how

665
00:36:33,520 --> 00:36:36,840
Speaker 3: do you find that normal microbiome in a world where

666
00:36:36,880 --> 00:36:40,640
Speaker 3: everybody has this biosis of some sort or has some

667
00:36:40,760 --> 00:36:45,000
Speaker 3: kind of element of disease from mental health to dyspepsia

668
00:36:45,080 --> 00:36:48,640
Speaker 3: to bloating, to autism to Parkinson's to Alzheimer's. So where

669
00:36:48,680 --> 00:36:52,200
Speaker 3: do you find that needle in the haystack of health

670
00:36:52,480 --> 00:36:55,839
Speaker 3: fee individual that you could say, oh my god, this

671
00:36:55,880 --> 00:36:58,120
Speaker 3: is the golden goose and I'm going to take that

672
00:36:58,200 --> 00:37:01,320
Speaker 3: boo and I'm going to fix everyone. You can't really,

673
00:37:01,520 --> 00:37:06,160
Speaker 3: So now let's go back to the hemoglobin when you're

674
00:37:06,560 --> 00:37:10,359
Speaker 3: When we had the hemoglobin, we knew hemoglobin of seven,

675
00:37:10,400 --> 00:37:11,759
Speaker 3: We're going to do a blood transfusion.

676
00:37:12,160 --> 00:37:15,879
Speaker 4: We then did blood transfusions and we.

677
00:37:15,800 --> 00:37:18,640
Speaker 3: Realized, wait a minute, we have this thing called HIV

678
00:37:19,320 --> 00:37:22,800
Speaker 3: or hepatitis C. We got to be careful, slow down,

679
00:37:23,120 --> 00:37:25,719
Speaker 3: and we got to start testing for HIV and hepatitis

680
00:37:25,760 --> 00:37:29,640
Speaker 3: C because we're giving our hemophiliacs HIV and hepatitis C.

681
00:37:30,160 --> 00:37:33,319
Speaker 3: So it took years to get to this level. Right,

682
00:37:33,360 --> 00:37:36,440
Speaker 3: that's where we're at in the microbiome. We do not

683
00:37:36,560 --> 00:37:40,000
Speaker 3: even have a marker for this biosis. We do not

684
00:37:40,160 --> 00:37:43,880
Speaker 3: even have a I have some ideas, but nothing that

685
00:37:43,920 --> 00:37:45,719
Speaker 3: I'm going to be publishing. First of all, we can't

686
00:37:45,719 --> 00:37:49,719
Speaker 3: even publish right now because they're retracting all these papers,

687
00:37:50,040 --> 00:37:53,520
Speaker 3: So we can't even advance the science to get us

688
00:37:53,600 --> 00:37:57,240
Speaker 3: further down. So imagine everything I've done all my research,

689
00:37:57,760 --> 00:38:01,959
Speaker 3: all this, you know, these exposition his expeditions in Zimbabwe

690
00:38:02,120 --> 00:38:06,640
Speaker 3: and Malaysia and analyzing the store microboma of different populations.

691
00:38:07,160 --> 00:38:11,160
Speaker 3: I can't even publish because there's such a control.

692
00:38:12,120 --> 00:38:14,880
Speaker 1: Wow, that's that's tough.

693
00:38:14,960 --> 00:38:19,880
Speaker 2: Why so why are people or why are certain people

694
00:38:19,960 --> 00:38:27,120
Speaker 2: or organizations or government departments or whatever not positive or

695
00:38:27,160 --> 00:38:29,920
Speaker 2: not supportive of this kind of research?

696
00:38:30,160 --> 00:38:33,640
Speaker 1: If if it's obviously it is so important?

697
00:38:34,480 --> 00:38:37,480
Speaker 2: Is it because it might be they weren't because financially,

698
00:38:38,040 --> 00:38:41,320
Speaker 2: financially disadvantageous to some organizations.

699
00:38:41,440 --> 00:38:43,880
Speaker 4: Yes, it is definitely disadvantageous.

700
00:38:43,920 --> 00:38:46,000
Speaker 3: Now, remember I told you at the beginning, I said, well,

701
00:38:46,080 --> 00:38:48,880
Speaker 3: doctor burlready had twenty eight cases of Cron's disease that

702
00:38:48,920 --> 00:38:55,319
Speaker 3: he improved. Yeah, imagine the whole biologics industry, you know,

703
00:38:55,440 --> 00:38:59,600
Speaker 3: ten thousand dollars a month to these kids for biologics

704
00:38:59,600 --> 00:39:02,640
Speaker 3: to fix or chrones. That doesn't mean biologics is not

705
00:39:02,680 --> 00:39:05,600
Speaker 3: the answer to Crohn's disease. It just means that there

706
00:39:05,640 --> 00:39:07,840
Speaker 3: might be a new kid on the block which is

707
00:39:07,880 --> 00:39:12,359
Speaker 3: going to displace the biologics. Right, So what happens Those

708
00:39:12,400 --> 00:39:15,160
Speaker 3: people that control the biologics want to take over the

709
00:39:15,280 --> 00:39:19,080
Speaker 3: data and the and the creator and the work to

710
00:39:19,200 --> 00:39:23,600
Speaker 3: get a better product, right well, that they can phase

711
00:39:23,640 --> 00:39:26,040
Speaker 3: out the biologic and bring on the new product.

712
00:39:27,040 --> 00:39:33,120
Speaker 2: Yeah, so that's do you feel like ironically the obsession

713
00:39:33,239 --> 00:39:36,319
Speaker 2: that I'm not saying everyone, but like a lot of

714
00:39:36,360 --> 00:39:39,040
Speaker 2: people have a lot of people in Australia are obsessed

715
00:39:39,080 --> 00:39:42,719
Speaker 2: with cleanliness and avoiding germs at all costs and as

716
00:39:42,760 --> 00:39:46,920
Speaker 2: you said, wiping their hands every eight seconds, with alcohol

717
00:39:47,160 --> 00:39:52,319
Speaker 2: based whatevers and masks that like wearing a I say,

718
00:39:52,400 --> 00:39:56,280
Speaker 2: people still out walking wearing a mask or driving their car.

719
00:39:56,160 --> 00:39:59,239
Speaker 1: With a mask on. I feel like.

720
00:39:59,200 --> 00:40:03,759
Speaker 2: Perhaps this session with never being exposed to anything is

721
00:40:03,880 --> 00:40:07,720
Speaker 2: ironically perhaps making some of a sicker or more predisposed

722
00:40:07,760 --> 00:40:11,160
Speaker 2: to get sick because of the impact on our microbion

723
00:40:12,239 --> 00:40:13,320
Speaker 2: So when.

724
00:40:13,120 --> 00:40:16,560
Speaker 3: You're you can live in a sterile environment, and you

725
00:40:16,600 --> 00:40:18,960
Speaker 3: can live a long time in a sterile environment, but

726
00:40:19,000 --> 00:40:21,400
Speaker 3: the problem is when you go from that sterile environment

727
00:40:21,560 --> 00:40:27,000
Speaker 3: to an unsterile, diverse environment, you're going to have a problem. Right,

728
00:40:27,719 --> 00:40:30,719
Speaker 3: So that's the problem is that you can live in

729
00:40:30,760 --> 00:40:33,800
Speaker 3: a diverse environment, or you can live in a sterile environment,

730
00:40:33,880 --> 00:40:36,480
Speaker 3: but the problem is when you go from steril to diverse,

731
00:40:37,360 --> 00:40:42,200
Speaker 3: you get yourself into a problem, and so the aim

732
00:40:42,760 --> 00:40:48,760
Speaker 3: for you know, ever since Louis pasteur has been sterilization.

733
00:40:49,040 --> 00:40:52,200
Speaker 3: Think about the first guy that came out with washing

734
00:40:52,239 --> 00:40:55,439
Speaker 3: his hand, washing our hands. He ended up being put

735
00:40:55,440 --> 00:40:59,200
Speaker 3: in an insane asylum. Right, So because he said we

736
00:40:59,320 --> 00:41:02,520
Speaker 3: have to wash our hands before going to surgery, that

737
00:41:02,800 --> 00:41:05,120
Speaker 3: came to stay. Yeah, so he went into an insaness

738
00:41:05,120 --> 00:41:07,080
Speaker 3: They put him in an insane asylum. But then it

739
00:41:07,120 --> 00:41:10,600
Speaker 3: became standard of care. Then they came out with, oh,

740
00:41:10,640 --> 00:41:14,080
Speaker 3: we need to pasteurize and sterilize everything, and that became

741
00:41:14,320 --> 00:41:18,000
Speaker 3: again standard of care. Now here I am coming back

742
00:41:18,040 --> 00:41:21,319
Speaker 3: and saying, well, maybe sterilization is not we need to

743
00:41:21,360 --> 00:41:25,799
Speaker 3: go back. Here's the problem we overdo as humans. We

744
00:41:25,880 --> 00:41:29,000
Speaker 3: tend to believe it's one way or the other, but

745
00:41:29,080 --> 00:41:32,200
Speaker 3: it's not. Look, let's go back to hemoglobin. Hemoglobin of

746
00:41:32,280 --> 00:41:35,319
Speaker 3: seven and above is fine. You don't need to give

747
00:41:35,360 --> 00:41:39,160
Speaker 3: blood below you need a blood. So there's a point

748
00:41:39,840 --> 00:41:43,880
Speaker 3: in time where you're no longer in balance. So maybe

749
00:41:43,920 --> 00:41:46,880
Speaker 3: you need a certain amount of sterility, and maybe you

750
00:41:46,920 --> 00:41:50,440
Speaker 3: need a certain amount of microbes. It's that middle ground

751
00:41:50,960 --> 00:41:54,000
Speaker 3: which we as humans don't do very well. We don't

752
00:41:54,040 --> 00:41:56,799
Speaker 3: do middle grounds. We either do left or we do right.

753
00:41:57,520 --> 00:41:57,759
Speaker 4: Right.

754
00:41:58,320 --> 00:42:01,520
Speaker 3: It's either right or wrong. What if there's no right

755
00:42:01,640 --> 00:42:04,440
Speaker 3: or wrong? And that's what science is right away, by

756
00:42:04,480 --> 00:42:07,719
Speaker 3: the way, there's no right or wrong. It can all fit,

757
00:42:08,000 --> 00:42:10,240
Speaker 3: it can all be right, or it could all be wrong.

758
00:42:10,320 --> 00:42:11,919
Speaker 3: It could be middle point.

759
00:42:12,200 --> 00:42:15,120
Speaker 4: We don't know. You know, when you find me a human.

760
00:42:14,880 --> 00:42:17,640
Speaker 3: That lives forever, then I'll follow that human and I'll

761
00:42:17,640 --> 00:42:21,200
Speaker 3: say that human's completely right, and we'll follow what that

762
00:42:21,280 --> 00:42:25,000
Speaker 3: human is doing. Until then, we're all searching for some

763
00:42:25,200 --> 00:42:28,120
Speaker 3: truth on how to live longer and how to better

764
00:42:28,200 --> 00:42:28,800
Speaker 3: our lives.

765
00:42:28,960 --> 00:42:30,320
Speaker 4: So we got to be objective.

766
00:42:31,360 --> 00:42:33,279
Speaker 1: We do doc, doc. We've got to wind up in

767
00:42:33,320 --> 00:42:33,960
Speaker 1: a few minutes.

768
00:42:33,960 --> 00:42:37,560
Speaker 2: But before we do so, somebody's listening to this and

769
00:42:38,360 --> 00:42:42,480
Speaker 2: they're like, well, this is fascinating. The docs fast cibilians fascinating,

770
00:42:43,920 --> 00:42:48,200
Speaker 2: and they want to do something to improve their gut health.

771
00:42:48,600 --> 00:42:51,439
Speaker 2: Now I know there's no three step plan, but any

772
00:42:51,600 --> 00:42:52,560
Speaker 2: general advice.

773
00:42:54,080 --> 00:42:56,480
Speaker 3: So we they can enroll in one of our clinical

774
00:42:56,560 --> 00:43:00,600
Speaker 3: trials where we're testing basically the microviolement disease. They pay

775
00:43:00,600 --> 00:43:03,600
Speaker 3: a certain portion of the test to do that because

776
00:43:03,640 --> 00:43:06,640
Speaker 3: it's you know, these tests are costly, but we do

777
00:43:06,719 --> 00:43:10,000
Speaker 3: give them some kind of you know, we see some

778
00:43:10,160 --> 00:43:12,719
Speaker 3: microbes that are you know, we we give them the

779
00:43:12,800 --> 00:43:17,279
Speaker 3: proper nutritional guidance, you know, from what we've learned and vitamins,

780
00:43:17,320 --> 00:43:21,040
Speaker 3: et cetera. If you don't want to do that and

781
00:43:21,080 --> 00:43:24,320
Speaker 3: you're perfectly healthy, then do nothing. Keep doing what you're doing.

782
00:43:25,040 --> 00:43:28,200
Speaker 3: If you have a disease, you know, obviously we started

783
00:43:28,239 --> 00:43:29,120
Speaker 3: with Let's Talk Shit.

784
00:43:30,560 --> 00:43:32,479
Speaker 4: Read the book. Order the book Let's Talk Shit.

785
00:43:33,000 --> 00:43:35,839
Speaker 3: There's a lot in there, there's a lot of information.

786
00:43:35,960 --> 00:43:38,840
Speaker 3: I wrote it during COVID. Actually we published the December

787
00:43:38,880 --> 00:43:41,880
Speaker 3: twenty twenty. I think it helped a lot of people.

788
00:43:41,920 --> 00:43:44,200
Speaker 4: There's a lot of cool recipes in there that can

789
00:43:44,239 --> 00:43:44,880
Speaker 4: help them.

790
00:43:45,600 --> 00:43:47,920
Speaker 3: There's a lot of podcasts. Your podcast is going to

791
00:43:47,920 --> 00:43:51,120
Speaker 3: be on the projena biome dot com website, so please,

792
00:43:51,440 --> 00:43:55,920
Speaker 3: you know, feel free to go. I always give out

793
00:43:56,040 --> 00:44:00,359
Speaker 3: a pearl on all these podcasts from what I've learned

794
00:44:00,360 --> 00:44:04,320
Speaker 3: from research, and you know, support us, support the Microbiome

795
00:44:04,360 --> 00:44:07,719
Speaker 3: Research Foundation dot org because that's how we, you know,

796
00:44:07,800 --> 00:44:12,600
Speaker 3: continue the research, continue the science that is really a science.

797
00:44:12,719 --> 00:44:15,560
Speaker 3: Nobody wants to do this is I always joke and

798
00:44:15,600 --> 00:44:17,520
Speaker 3: say we do the research.

799
00:44:17,200 --> 00:44:19,120
Speaker 4: No one wants to do, but everyone wants to know.

800
00:44:19,640 --> 00:44:21,680
Speaker 3: Think about you know, actually I'm doing a study with

801
00:44:21,719 --> 00:44:24,560
Speaker 3: New Zealand right now on Manuka honey. We're testing the

802
00:44:24,600 --> 00:44:26,759
Speaker 3: Manuka honey before and after.

803
00:44:27,560 --> 00:44:29,799
Speaker 4: So who's going to test that, you.

804
00:44:29,719 --> 00:44:34,480
Speaker 3: Know, except the company that's sell alling the honey, or

805
00:44:35,680 --> 00:44:38,640
Speaker 3: you know, just a curious mind, Like I'm testing cuman.

806
00:44:38,760 --> 00:44:39,480
Speaker 4: What is cuman?

807
00:44:39,520 --> 00:44:42,239
Speaker 3: There's no patents on cuman, but I want to know

808
00:44:42,280 --> 00:44:43,960
Speaker 3: what cuman does to the microbiome.

809
00:44:44,719 --> 00:44:48,239
Speaker 4: So these are the studies I'm excited about. This is

810
00:44:48,280 --> 00:44:51,200
Speaker 4: what is needed to be done. There's no product behind it.

811
00:44:52,000 --> 00:44:54,760
Speaker 4: I think I love those studies.

812
00:44:54,280 --> 00:44:59,440
Speaker 3: Because it keeps me grounded, it keeps me advancing the science,

813
00:44:59,680 --> 00:45:02,560
Speaker 3: and it educates the public onto what are the right things?

814
00:45:02,920 --> 00:45:05,880
Speaker 4: Now? You know, what can the public do other.

815
00:45:05,719 --> 00:45:08,279
Speaker 3: Than you know, listening and reading the book and all

816
00:45:08,320 --> 00:45:15,040
Speaker 3: that they can decrease their stress. That's the number one stop.

817
00:45:15,120 --> 00:45:18,719
Speaker 3: Let's this link the things that upset you. You know,

818
00:45:18,760 --> 00:45:22,279
Speaker 3: when you're feeling a not in your stomach because you're

819
00:45:22,360 --> 00:45:26,120
Speaker 3: stressed about something or you're anxious, it's time to stop.

820
00:45:26,239 --> 00:45:30,800
Speaker 3: That's your body telling you you're anxious. Stop it calm

821
00:45:30,840 --> 00:45:31,840
Speaker 3: down because I'm.

822
00:45:33,400 --> 00:45:35,520
Speaker 4: You're killing me. You're killing the microbio.

823
00:45:37,800 --> 00:45:43,560
Speaker 3: Good food, regenerative food from the farm, good nutrients, good vitamins,

824
00:45:43,840 --> 00:45:46,959
Speaker 3: very important, exercise, sun.

825
00:45:47,440 --> 00:45:49,320
Speaker 4: The sun is extremely important.

826
00:45:49,800 --> 00:45:53,360
Speaker 3: We've been fearful of the sun and telling everybody puts

827
00:45:53,360 --> 00:45:54,640
Speaker 3: on screen and puts on screen.

828
00:45:54,680 --> 00:45:57,319
Speaker 4: But you know we all need some vitamin D from

829
00:45:57,320 --> 00:45:59,479
Speaker 4: the sun and we all need the benefits of the sun.

830
00:46:00,000 --> 00:46:00,600
Speaker 1: I understand.

831
00:46:01,280 --> 00:46:05,160
Speaker 2: So the book is called Let's Talk Shit ah best

832
00:46:05,200 --> 00:46:08,520
Speaker 2: title ever, Doctor Sabine Hazan.

833
00:46:08,760 --> 00:46:13,040
Speaker 1: Is it Hazan or Hazen Hazen Hazen. Hey, we appreciate.

834
00:46:13,120 --> 00:46:15,640
Speaker 2: We're going to say goodbye affair, but thank you so much,

835
00:46:15,840 --> 00:46:17,399
Speaker 2: like I would like to get you back one day

836
00:46:17,440 --> 00:46:18,759
Speaker 2: and expand.

837
00:46:18,840 --> 00:46:20,840
Speaker 1: But so good, so interesting.

838
00:46:21,840 --> 00:46:24,440
Speaker 2: I'm so glad you're doing the research you're doing and

839
00:46:24,680 --> 00:46:27,239
Speaker 2: opening the door on something that really needs to be

840
00:46:27,520 --> 00:46:31,360
Speaker 2: understood and exposed to more and more people because it's

841
00:46:31,840 --> 00:46:36,240
Speaker 2: I think it's such a massive contributor to overall health

842
00:46:36,239 --> 00:46:39,000
Speaker 2: that we don't fully understand. But for now, thanks so

843
00:46:39,080 --> 00:46:41,839
Speaker 2: much for and on the you project. We appreciate you.

844
00:46:42,800 --> 00:46:44,319
Speaker 4: Thank you so much for having me.

845
00:46:44,960 --> 00:46:46,719
Speaker 1: Thanks Doc, Thanks TIV, thank you