1
0:00:00 --> 0:00:04
All right, everybody, welcome to Medical Doctors for COVID Ethics.

2
0:00:04 --> 0:00:08
I'm your moderator in Australia where it's 5 a.m. in the morning.

3
0:00:08 --> 0:00:11
And I am Australia's passion provocateur.

4
0:00:11 --> 0:00:13
This is a place of passion.

5
0:00:13 --> 0:00:16
That's why I wear my red jacket to remind you, you come here.

6
0:00:16 --> 0:00:20
This was a reminder to all of you to be passionate.

7
0:00:20 --> 0:00:24
And the example of Anna and Stephen Frost, who started this group and the presenters

8
0:00:24 --> 0:00:31
that we have are passionately fighting for truth, for justice and freedom.

9
0:00:31 --> 0:00:36
And when you look at all of the wars that have been fought by many,

10
0:00:36 --> 0:00:39
by almost all countries, have always been about freedom.

11
0:00:39 --> 0:00:43
So and the freedom that Anna was just talking about, the freedom to speak up,

12
0:00:43 --> 0:00:46
the freedom to speak your mind.

13
0:00:46 --> 0:00:50
So we're here in a true spirit of exploration and discovery.

14
0:00:50 --> 0:00:53
James, you probably know because you've joined us previously that

15
0:00:53 --> 0:00:58
we have doctors and lawyers and journalists and engineers and writers and researchers

16
0:00:58 --> 0:01:07
and nurses, investors, dentists, financiers, all sorts of strange people, not just doctors.

17
0:01:07 --> 0:01:10
Most understand we're here in World War Three.

18
0:01:10 --> 0:01:16
And if you haven't, if you missed Daniel Estreland's presentation on Monday, then

19
0:01:16 --> 0:01:23
was it on Monday, Sunday, then please reacquaint yourself of who's behind World War Three.

20
0:01:23 --> 0:01:25
We go for two and a half hours.

21
0:01:25 --> 0:01:28
James, we do your presentation and then Q&A.

22
0:01:28 --> 0:01:31
Hopefully you can stay as long as you can.

23
0:01:31 --> 0:01:35
And then we have a less moderated, less controlled telegram video chat.

24
0:01:35 --> 0:01:41
For those who have more time, there's no censorship and but there's proper moderation.

25
0:01:41 --> 0:01:45
So so there's an important distinction, everybody.

26
0:01:45 --> 0:01:48
You are you don't get censored because I say that's enough.

27
0:01:48 --> 0:01:53
We're moving on. It's just it's a constant battle between all these wonderful people

28
0:01:53 --> 0:01:55
that you are and all have opinions.

29
0:01:55 --> 0:01:56
And that's the interesting thing.

30
0:01:56 --> 0:01:59
You have many different opinions about many different things.

31
0:01:59 --> 0:02:06
So we are here to have a conversation, free speech, crucial, as I said, no censorship.

32
0:02:06 --> 0:02:11
And we understand the development of science.

33
0:02:11 --> 0:02:13
Michael Crichton quotes.

34
0:02:13 --> 0:02:19
When somebody tells you the science is settled, reach for your wallet.

35
0:02:19 --> 0:02:22
We are here and we come from love, not fear.

36
0:02:22 --> 0:02:24
And that's all about passion as well.

37
0:02:24 --> 0:02:26
Passion comes from your soul, your spirit.

38
0:02:26 --> 0:02:29
So does love. Fear comes from your mind.

39
0:02:29 --> 0:02:31
We are not driven by fear.

40
0:02:31 --> 0:02:37
Have an open mind, particularly welcome to new to new first time attendees.

41
0:02:37 --> 0:02:41
If this is your first time, please introduce yourself in the chat

42
0:02:42 --> 0:02:46
and please have your name displayed on your screen.

43
0:02:46 --> 0:02:48
Now, James Thorpe is a superstar.

44
0:02:48 --> 0:02:50
Many of us saw someone just put a note in there.

45
0:02:50 --> 0:02:52
You're on the Epoch Times, James.

46
0:02:52 --> 0:02:59
I've been we've been watching your data and we're looking forward to you sharing your genius.

47
0:02:59 --> 0:03:02
And hopefully the hurricane doesn't arrive before you finish.

48
0:03:04 --> 0:03:07
Thank you, Charles. Can you hear me OK?

49
0:03:07 --> 0:03:10
Yep. And I'm going to share my screen.

50
0:03:10 --> 0:03:12
Let me know if you can see my screen.

51
0:03:12 --> 0:03:14
Yep. Can do. All good.

52
0:03:15 --> 0:03:18
You see it? Good. Yep.

53
0:03:18 --> 0:03:21
Well, first off, I want to thank you, Charles.

54
0:03:22 --> 0:03:26
And thank you, Stephen, for your incredibly brilliant platform.

55
0:03:26 --> 0:03:31
It's such an important beacon of truth worldwide.

56
0:03:31 --> 0:03:36
And to all my brothers and sisters around the world, thank you for joining us.

57
0:03:38 --> 0:03:42
I very much appreciate the opportunity to share some of the data

58
0:03:43 --> 0:03:49
that I have with you and with this very special family worldwide.

59
0:03:49 --> 0:04:00
So I see today that there's there's a few notable early recent publications that are on review.

60
0:04:00 --> 0:04:08
And but mostly I would like to spend most of the time on the data that we have accumulated

61
0:04:09 --> 0:04:10
on this side of the pond.

62
0:04:11 --> 0:04:16
And thanks to a lot of my co-authors that really deserve credit for this work.

63
0:04:16 --> 0:04:21
I know Albert Benavides, the world expert, and is with us.

64
0:04:21 --> 0:04:23
And he's presented in this platform.

65
0:04:23 --> 0:04:29
I see several other notable individuals around the world, some from down and under.

66
0:04:29 --> 0:04:33
I don't want to call them out because I know it's a tense situation.

67
0:04:33 --> 0:04:36
Some from Canada. I see Dr. Mahalika.

68
0:04:36 --> 0:04:41
She won't mind me calling her out because she's been on the show.

69
0:04:41 --> 0:04:42
She's a fellow truth.

70
0:04:43 --> 0:04:44
And yeah, thank you very much.

71
0:04:44 --> 0:04:50
So I'm going to review what we've seen in women of reproductive age.

72
0:04:50 --> 0:04:56
See if I can see my slide transitioning for you there.

73
0:04:56 --> 0:05:00
Can you see my slides?

74
0:05:00 --> 0:05:02
Is James all good?

75
0:05:02 --> 0:05:04
Yep.

76
0:05:04 --> 0:05:06
How much?

77
0:05:06 --> 0:05:08
How much do you think?

78
0:05:09 --> 0:05:10
James?

79
0:05:10 --> 0:05:10
James?

80
0:05:10 --> 0:05:11
All good.

81
0:05:11 --> 0:05:11
Yep.

82
0:05:11 --> 0:05:12
How much?

83
0:05:12 --> 0:05:13
How long do you want me to go, Charles?

84
0:05:15 --> 0:05:16
45, 50 minutes?

85
0:05:16 --> 0:05:16
Hour?

86
0:05:16 --> 0:05:21
Look, because we're here for two and a half hours, so please, you know,

87
0:05:22 --> 0:05:27
give us, don't rush it because what you share is so important for all of us to understand

88
0:05:27 --> 0:05:33
and to be, and really to be rejuvenated into what's happening to our humanity.

89
0:05:34 --> 0:05:35
Well, thank you, Charles.

90
0:05:35 --> 0:05:37
And I love that passionate red jacket.

91
0:05:38 --> 0:05:39
It's very appropriate.

92
0:05:40 --> 0:05:41
Thank you.

93
0:05:41 --> 0:05:44
So I don't have any conflicts of interest.

94
0:05:44 --> 0:05:44
Do you guys?

95
0:05:45 --> 0:05:49
And you know, I've made it, I think that it's,

96
0:05:51 --> 0:06:00
it's part of presenting or publishing or voting to, or being employed or being a member of the

97
0:06:00 --> 0:06:01
human race.

98
0:06:01 --> 0:06:05
We always upfront our conflicts of interest, right?

99
0:06:06 --> 0:06:10
I don't have any, but if we're asking people for conflicts of interest,

100
0:06:12 --> 0:06:16
what happened to this, to the rest of the world?

101
0:06:16 --> 0:06:19
What happened to the powers at be?

102
0:06:20 --> 0:06:23
Where are their conflicts of interest?

103
0:06:24 --> 0:06:32
The FDA and the CDC have an operating budget of millions of dollars and over 40%

104
0:06:33 --> 0:06:40
of their operating budget is provided by cash from the vaccine pharmaceutical industry

105
0:06:40 --> 0:06:45
and from royalties that they own on the patents.

106
0:06:47 --> 0:06:54
Now, if that's not the Fox guarding the chicken house, I don't know what is.

107
0:06:54 --> 0:07:01
In 1986, the FDA and the CDC were on their knees to the government.

108
0:07:02 --> 0:07:10
Two in the United States of America and to president Reagan begging for immunity,

109
0:07:10 --> 0:07:15
not sovereign immunity, but legal immunity, not quite sovereign like an ambassador has,

110
0:07:15 --> 0:07:17
but it's pretty close and it's pretty tight.

111
0:07:18 --> 0:07:19
And he gave it to them.

112
0:07:19 --> 0:07:29
And then the vaccine industry went rampant with massive disgusting profits at the expense of

113
0:07:30 --> 0:07:30
the human race.

114
0:07:32 --> 0:07:37
And what I'd like to do is talk about these conflicts of interest a little bit on this slide.

115
0:07:38 --> 0:07:49
So what is it about the 21 advisors who voted and pushed the FDA and the CDC

116
0:07:49 --> 0:07:57
to push this legal vaccine on children aged six months to 11?

117
0:07:58 --> 0:07:59
How does that happen?

118
0:07:59 --> 0:08:01
Well, there are no data.

119
0:08:02 --> 0:08:04
Everybody knows there are no data.

120
0:08:05 --> 0:08:10
It's just like the emperor, the naked emperor and the emperor's clothes syndrome.

121
0:08:10 --> 0:08:18
There are no long-term data despite what the critics state.

122
0:08:18 --> 0:08:19
There are none.

123
0:08:19 --> 0:08:21
Zilchow zero.

124
0:08:21 --> 0:08:25
The efficacy of the vaccine was never 95%.

125
0:08:26 --> 0:08:33
That was artificial fake relative risk reduction.

126
0:08:33 --> 0:08:39
The absolute risk reduction was more like 0.9% reduction in disease.

127
0:08:39 --> 0:08:43
These are some of the games that they play and they played for a long time

128
0:08:43 --> 0:08:47
but they're in our face much more egregiously now.

129
0:08:48 --> 0:08:55
What about Eric Rubin, the editor-in-chief of the flagship fraudulent journal

130
0:08:56 --> 0:08:59
of the medical industrial complex?

131
0:08:59 --> 0:09:03
It's no longer this is all supported and they're all on the take.

132
0:09:04 --> 0:09:10
He goes and he votes to push this legal vaccine in children

133
0:09:13 --> 0:09:16
that have zero risk of dying from COVID.

134
0:09:16 --> 0:09:19
Literally there are experts in the United States of America

135
0:09:20 --> 0:09:28
that contend that there has been no child 0 to 18 that has died from COVID-19

136
0:09:28 --> 0:09:31
in the United States of America as a sole cause.

137
0:09:32 --> 0:09:40
They've died with COVID-19 with a PCR but the ones that have died

138
0:09:40 --> 0:09:46
have multiple other catastrophic comorbidities.

139
0:09:46 --> 0:09:48
Give you some real numbers.

140
0:09:52 --> 0:09:58
You can procure this data from the CDC itself across Florida, across Texas.

141
0:09:59 --> 0:10:07
There are just this year there's less than 50 children that have died from COVID-19

142
0:10:07 --> 0:10:11
and they all have major comorbidities.

143
0:10:12 --> 0:10:17
So when we look at trying to make a difference in pregnant women or in children,

144
0:10:20 --> 0:10:22
there is no risk-benefit ratio.

145
0:10:22 --> 0:10:31
It's dramatically lopsided and the vaccine using it in pregnancy and using it in children

146
0:10:31 --> 0:10:39
is a huge disaster with five to tenfold, maybe a hundredfold increase in complications

147
0:10:39 --> 0:10:46
compared to the alleged number of lethal COVID-19 cases that could prevent.

148
0:10:47 --> 0:10:49
So what about Eric Rubin?

149
0:10:49 --> 0:10:50
How did he get in this position?

150
0:10:51 --> 0:10:56
How does he stand up in front of the FDA in May or April whenever it was and say,

151
0:10:56 --> 0:11:00
well, we don't have any data but we're just going to roll the vaccine out in children

152
0:11:00 --> 0:11:01
and see what happens?

153
0:11:01 --> 0:11:06
That's what he said and go look it up yourself.

154
0:11:06 --> 0:11:07
Do your due diligence.

155
0:11:07 --> 0:11:08
It's all over the internet.

156
0:11:09 --> 0:11:17
Does Dr. Eric Rubin, editor-in-chief of the flagship journal of the Medical Industrial Complex,

157
0:11:17 --> 0:11:18
have any conflicts of interest?

158
0:11:20 --> 0:11:20
I don't know.

159
0:11:22 --> 0:11:24
I think history will show that he does.

160
0:11:24 --> 0:11:30
I think it's my opinion that history will show that he has a lot of holdings

161
0:11:30 --> 0:11:40
and so do all the other 21 advisors to the FDA that pushed that egregious

162
0:11:41 --> 0:11:43
recommendation through the FDA.

163
0:11:44 --> 0:11:46
History will show their conflicts of interest.

164
0:11:48 --> 0:11:52
What about the lead authors of the fraudulently published medical journals?

165
0:11:53 --> 0:11:55
What about all of them?

166
0:11:55 --> 0:11:57
They don't get to escape this room.

167
0:11:58 --> 0:12:02
They have demonized and...

168
0:12:02 --> 0:12:04
I'm sorry, James.

169
0:12:04 --> 0:12:06
I'm sorry.

170
0:12:06 --> 0:12:08
Can you hear me?

171
0:12:08 --> 0:12:10
Keep going, James.

172
0:12:10 --> 0:12:12
Yes, again, keep going.

173
0:12:12 --> 0:12:20
They have illegally, unethically, immorally, and fraudulently pushed not just altered data,

174
0:12:20 --> 0:12:27
they have pushed and published completely fraudulent data that is not just fraudulent.

175
0:12:27 --> 0:12:35
As in the case of lead author, Tommy T. Shimabukuro, and the 19 or 20 other authors

176
0:12:35 --> 0:12:40
on the New England Journal of Medicine article 13 months ago, June of 2021,

177
0:12:41 --> 0:12:42
which is completely fraudulent.

178
0:12:43 --> 0:12:50
Can you imagine them having the audacity to state that the vaccine is safe in pregnancy

179
0:12:50 --> 0:12:52
when there's no outcome data?

180
0:12:52 --> 0:12:58
When the vast majority of the patients weren't even followed up to see the outcome of the

181
0:12:58 --> 0:13:06
pregnancy and when they shape, shift, and fraudulently dilute the real spontaneous

182
0:13:07 --> 0:13:14
abortion rate or miscarriage rate, the denominator, the 700 patients that received

183
0:13:14 --> 0:13:20
the COVID-19 vaccination in the third trimester, when it was impossible to have caused

184
0:13:20 --> 0:13:25
a miscarriage because a miscarriage can only occur before 20 weeks.

185
0:13:26 --> 0:13:34
They put those numbers in the denominator and they reduce the real incidence of miscarriage

186
0:13:34 --> 0:13:43
in their study from 82% to population normal of 12 or 13%.

187
0:13:44 --> 0:13:45
This is called fraud.

188
0:13:46 --> 0:13:47
They have a lot of blood on their hands.

189
0:13:47 --> 0:13:49
By the way, do your due diligence.

190
0:13:49 --> 0:13:54
Look and see how many of those authors are employed by the federal government.

191
0:13:56 --> 0:14:00
You'll be shocked to see, I think, that all of them are.

192
0:14:01 --> 0:14:12
Dr. Albert Benavides has some very interesting screenshots of FOIA requests from attorney

193
0:14:12 --> 0:14:21
Aaron Ciri that show the CDC and the FDA communicating with Tommy T. Shimabukuro.

194
0:14:21 --> 0:14:23
Isn't that interesting?

195
0:14:25 --> 0:14:29
Kind of a wink, wink, and a nod, nod, get rid of some of these disastrous cases.

196
0:14:30 --> 0:14:31
You've heard that from Albert.

197
0:14:32 --> 0:14:42
So where is the responsibility of the leaders of this ministry, the doctors, the doctors,

198
0:14:42 --> 0:14:49
of this medical industrial complex, the hospitals, the FDA, the CDC, the fraudulent

199
0:14:49 --> 0:14:57
medical journals, the fraudulent agencies, NGOs that are pushing this?

200
0:14:58 --> 0:15:00
Where is all their honesty?

201
0:15:01 --> 0:15:02
There is none left.

202
0:15:05 --> 0:15:11
I want to just before I get into the obstetrical stuff, I want to review just some really key

203
0:15:12 --> 0:15:16
studies that have been published just in the last 48 hours.

204
0:15:18 --> 0:15:21
Your new king over there on the other side of the pond, what's his name?

205
0:15:21 --> 0:15:22
King what?

206
0:15:22 --> 0:15:23
Whatever his name is.

207
0:15:23 --> 0:15:25
King Charles, is that it?

208
0:15:26 --> 0:15:28
King Charles III or the V, whatever.

209
0:15:30 --> 0:15:38
I want you, my colleagues over there, I want you to get this Dr. Malhotra, the famous cardiologist

210
0:15:38 --> 0:15:41
from England, I want him knighted.

211
0:15:42 --> 0:15:48
I want him officially knighted because he deserves to be knighted and if King Charles

212
0:15:48 --> 0:15:57
doesn't knight him, then I'm going to knight him into the kingdom of truth from maybe confer

213
0:15:57 --> 0:16:02
a knighthood from this brilliant gathering here.

214
0:16:02 --> 0:16:04
He deserves to be knighted.

215
0:16:04 --> 0:16:07
He came out, he was double-backed, so I don't know if he got his boosters.

216
0:16:08 --> 0:16:14
He was pushing the vaccine all over your news media on the TV and this is a gentleman,

217
0:16:16 --> 0:16:25
a real person who has the academic, the spiritual, emotional, ethical, and moral integrity

218
0:16:27 --> 0:16:30
to reevaluate the data and say, I was dead wrong.

219
0:16:31 --> 0:16:32
Stop the vaccine.

220
0:16:33 --> 0:16:34
Can you imagine that?

221
0:16:34 --> 0:16:41
That takes a lot of courage and there is no greater crown for an academician or a member

222
0:16:41 --> 0:16:47
of the human race to admit that they were wrong, do an about face, what I call an academic

223
0:16:47 --> 0:16:55
metanoia and like I've done, apologize for making a mistake and the consequences that it's caused.

224
0:16:56 --> 0:16:58
So I applaud this man.

225
0:16:59 --> 0:17:06
It's Dr. Robert Malone, another one of my heroes, the creator of the mRNA vaccination,

226
0:17:07 --> 0:17:10
did a brilliant substack yesterday if you haven't seen it.

227
0:17:11 --> 0:17:13
Please fetch it and go read it.

228
0:17:13 --> 0:17:20
It's very, very important and germane to our group here, our family around the world.

229
0:17:22 --> 0:17:25
This was just published today or yesterday.

230
0:17:26 --> 0:17:34
This is a great example of Hannah and colleagues and this is another classic

231
0:17:34 --> 0:17:40
corrupted journal of JAMA and the medical industrial complex.

232
0:17:40 --> 0:17:46
They love the journals Lancet, JAMA, New England Journal of Medicine,

233
0:17:46 --> 0:17:48
and you can put countless numbers up there.

234
0:17:49 --> 0:17:54
They're all terminally corrupted and should be disbarred and taken down.

235
0:17:56 --> 0:18:01
So finally, what is it now we've had, is it eight?

236
0:18:01 --> 0:18:10
Let's see, it's been since mid December 2020, you know, we're going on 48 months, shy of 40

237
0:18:10 --> 0:18:17
months, let's call it, of this vaccine pushing to the general population, to pregnant women,

238
0:18:17 --> 0:18:18
to breastfeeding women.

239
0:18:19 --> 0:18:21
Wait a minute, this can't be true, is it?

240
0:18:21 --> 0:18:23
So how can this be?

241
0:18:23 --> 0:18:29
So they're just now publishing studies on the effect on breast milk.

242
0:18:31 --> 0:18:34
This is the kind of nonsense that should have been.

243
0:18:34 --> 0:18:42
This is a very dangerous, very serious, it's not a vaccine, it's a genetic experimental therapy.

244
0:18:42 --> 0:18:47
And they found that it was, they thought that a day late,

245
0:18:48 --> 0:18:59
almost two years short, and they come up with this minuscule, you know, five out of eight samples of

246
0:18:59 --> 0:19:05
breast milk tested, has mRNA in them, and then they try to whitewash this and marginalize.

247
0:19:06 --> 0:19:12
Wait a minute, no, this should have been done years ago before the vaccine was ever rolled out

248
0:19:13 --> 0:19:15
into the general population.

249
0:19:15 --> 0:19:25
Remember, the vaccine, according to the Shimabukuro study, and according to Pfizer's own data and

250
0:19:25 --> 0:19:30
internal documents, if given during the first trimester, it has an abortion rate

251
0:19:32 --> 0:19:37
equaling that of the abortion appeal, RU486, methacrystal.

252
0:19:37 --> 0:19:42
Do your due diligence, look it up, I'm not making this up, I couldn't make this stuff up.

253
0:19:43 --> 0:19:51
The most accurate data that we have estimating the miscarriage rate from a COVID-19 vaccination

254
0:19:51 --> 0:19:55
in the first trimester is north of 80%. And guess where that comes from?

255
0:19:56 --> 0:20:00
That comes from Shimabukuro, who tried to manipulate the data.

256
0:20:01 --> 0:20:03
And by the way, don't tell me that was an accident.

257
0:20:04 --> 0:20:10
I did my due diligence, there's three OBGYN docs that are on that publication.

258
0:20:10 --> 0:20:17
And if Eric Rubin didn't have the brain to edit it, which I know he did, and all the rest of the

259
0:20:17 --> 0:20:23
authors, I know that the three obstetricians wouldn't have missed it. I have a strong suspicion that

260
0:20:23 --> 0:20:30
Shimabukuro article was ghostwritten by Pfizer. That's my suspicion, and I stick by it.

261
0:20:30 --> 0:20:38
Because if you look at the Pfizer document, 5.3.6, just Google it, and you pull down that 30 page

262
0:20:38 --> 0:20:46
document, you go to page seven, 1,223 dead people after the vaccine in less than 90 days.

263
0:20:47 --> 0:20:54
And 46% of the 270 pregnant women had adverse complications from the vaccine.

264
0:20:55 --> 0:21:01
So if the FDA in the United States of America puts a black box warning on RU-486 and says,

265
0:21:01 --> 0:21:06
this is a really dangerous drug because it can cause miscarriage and loss of pregnancy,

266
0:21:06 --> 0:21:12
and it can't be used in the general population, and it's got the black box denotation from the FDA.

267
0:21:14 --> 0:21:19
And it requires extensive informed consent because of its potential risk on pregnancy.

268
0:21:21 --> 0:21:27
Isn't that kind of oxymoronic that there's not a black box warning

269
0:21:28 --> 0:21:32
on a COVID-19 vaccine on pregnancy, or at all?

270
0:21:32 --> 0:21:40
So the authors try to whitewash this finding. And I will say that in my review of the literature and

271
0:21:40 --> 0:21:47
what's going on, it's a very dangerous proposition to get a vaccine while you're breastfeeding.

272
0:21:47 --> 0:21:55
I know of two cases for certain, and there's many, many more. There's probably

273
0:21:55 --> 0:22:03
probably 100 or 1,000 more. But I know of two that I can vouch for the RASIA,

274
0:22:03 --> 0:22:13
and I can provide you evidentiary links to this. One of them, a toddler died at five months,

275
0:22:14 --> 0:22:21
literally. The mother was forced to get a vaccine by employer. The mother took the vaccine

276
0:22:22 --> 0:22:31
on the day before her first breastfeed. Breastfed the kid, the baby. This toddler got immediately

277
0:22:31 --> 0:22:40
upset. The baby could never be cajoled and went downhill, required administration,

278
0:22:41 --> 0:22:50
admission to the hospital, and died dead, no longer with us. Thrombotic thrombocytopenia purpura.

279
0:22:52 --> 0:23:02
A classic vaccine response. Now, this particular case, for all of the naysayers of the database

280
0:23:02 --> 0:23:10
of VAERS, or UK Yelacar, or user vigilance of the WHO, or I should say of the European

281
0:23:11 --> 0:23:27
Medicines Agency, and also the tool of WHO, the VAERS vigilance, or the WHO Vigi access.

282
0:23:27 --> 0:23:34
So they all show the same thing. They all show damning, really concerning

283
0:23:34 --> 0:23:44
adverse events, deaths, and complications from this vaccine. So these perfectly healthy babies,

284
0:23:44 --> 0:23:52
it really meets the standard criteria of causality, at least in one of these cases. If you look at

285
0:23:52 --> 0:24:01
the criteria for causality, and there's nine of those criteria, which are clearly enumerated

286
0:24:02 --> 0:24:09
enumerated in the epidemiological literature, these cases meet, many of these cases meet

287
0:24:09 --> 0:24:17
the Bradford Hill criteria for causality. The other case was in a six, the baby that died was

288
0:24:17 --> 0:24:25
a six-weeker, went on to immediately, after the breastfeed, went on to develop severe

289
0:24:25 --> 0:24:36
autoimmune disease, an atypical Kawasaki-like syndrome, and died. Now that death occurred,

290
0:24:36 --> 0:24:44
you know, weeks or a month or so after, but is clear. And there's many, many more than that.

291
0:24:46 --> 0:24:55
I do want to move on to really what I'm here to talk to you about. And this study is submitted

292
0:24:55 --> 0:25:01
for publication. It will be published. I guarantee it will be published. And I want to

293
0:25:01 --> 0:25:11
acknowledge my co-authors and my co-investigators who were immensely helpful. Dr. Claire Rogers,

294
0:25:11 --> 0:25:20
a physician assistant in Rome, Georgia, Michael Duskovich, PhD, model and expert,

295
0:25:21 --> 0:25:27
Stuart Tankersley, a brilliant family practice doc, lives close by me, a military whistleblower,

296
0:25:27 --> 0:25:35
Albert Venedydez, who needs no introduction, he's with us. He's the world expert on bears,

297
0:25:35 --> 0:25:44
doing incredible work. Megan Redshaw is one of my colleagues. She's a younger attorney colleague,

298
0:25:45 --> 0:25:52
brilliant researcher and writer. She's associated with the Children's Health Defense, RFK Juniors,

299
0:25:52 --> 0:25:57
and she's also their lead counsel and also the lead counsel of TrialSec News. And then finally,

300
0:25:58 --> 0:26:05
Peter McCulloch, and I don't think he needs an introduction. You all know Peter. And

301
0:26:05 --> 0:26:14
I'm, this is basically a thumbnail abstract of our data. So we looked at,

302
0:26:15 --> 0:26:24
very important, that we use the government data. And on a subsequent study, this has not been the,

303
0:26:25 --> 0:26:34
there's data that we use is fresh. It's virgin. It's got all of the CDC and FDA's attempts to try to

304
0:26:35 --> 0:26:42
limit the danger signals coming out of it that have been uncovered by Albert Venedydez.

305
0:26:42 --> 0:26:48
But none of, we left it intact. We didn't touch it. The next series of our publications will be

306
0:26:49 --> 0:26:56
cleaning the data like Albert Venedydez has done and correcting some of the obvious fraudulent

307
0:26:56 --> 0:27:05
manipulation of the CDC and the FDA to try to thwart the danger signals. They have maliciously

308
0:27:05 --> 0:27:12
and aggressively used a scheme of tactics, some of which are not too sophisticated,

309
0:27:12 --> 0:27:17
that Albert Venedydez has shown us. And subsequent publication, we're going to do a publication on

310
0:27:18 --> 0:27:26
the corrected data of Albert and you'll see that it's much worse. So we chose, we put our heads

311
0:27:26 --> 0:27:32
together. We all chose to use the influenza vaccine as a control group. Why? Well, because

312
0:27:32 --> 0:27:37
the influenza vaccine, and I'm not an anti-vaxxer. I've done my confession in front of this group

313
0:27:37 --> 0:27:45
before. I was a mainstream medical physician, extensively published. I was a journal reviewer.

314
0:27:46 --> 0:27:53
I tested for the American Board of Obstetrics and Gynecology. I was a member, not only was I

315
0:27:53 --> 0:27:57
a member of the Society of Maternal and Fetal Medicine, but I was a board of directors and

316
0:27:57 --> 0:28:07
leader for three or four years at the turn of the century. So I'm not, I was in mainstream medicine

317
0:28:07 --> 0:28:14
and I was pushing vaccines up until 10 years ago or so. But I was big on the influenza vaccine. It

318
0:28:14 --> 0:28:24
was approved by the FDA and the CDC in 1997, later 1997. So we chose to start our study

319
0:28:24 --> 0:28:32
in January 1st, 1998. And we continued up until June 30th of this year, just a few weeks ago.

320
0:28:33 --> 0:28:43
So again, recognizing that the influenza vaccine has been now extensive safety, you know,

321
0:28:43 --> 0:28:49
60 plus years. The safety signal out of errors doesn't look bad, looks pretty good.

322
0:28:49 --> 0:28:58
But we chose to use that as our control group. I think, if I'm correct, doing the math, I think

323
0:28:58 --> 0:29:10
that's 284 months since January 1st, 1998 to June 30th, 2022. So that's 284 months. Somebody can do

324
0:29:10 --> 0:29:18
the math here, I think it is. And versus only 18 months or so of the COVID-19 vaccines.

325
0:29:18 --> 0:29:24
Now, one of the things that we did was, I did all the simple statistics. I used just odds,

326
0:29:24 --> 0:29:31
ratio, and relative risk, which were crosstabs, comparison of ratios, which was pretty easy.

327
0:29:33 --> 0:29:40
But my brilliant, beautiful bride, who's an attorney, would not let me discuss any of

328
0:29:40 --> 0:29:48
that until multiple other people verified it, including a PhD modeling expert in mathematics.

329
0:29:48 --> 0:29:54
Well, he came back and he said, yeah, it's right on. The stats are right on, but we can do some

330
0:29:54 --> 0:30:00
much more sophisticated modeling. We can come up with three sets of models. One of the adverse

331
0:30:00 --> 0:30:14
events per shot, one with the adverse event per person vaccinated, and a third adverse event per

332
0:30:14 --> 0:30:21
time period. So we got numerators and denominators for all of those. How do we get denominators?

333
0:30:21 --> 0:30:28
Pretty easily. You can go in and do exercises with multiple different

334
0:30:28 --> 0:30:38
websites, including the CDC, the WHO, GATA around the world, several other sites. And then you can

335
0:30:38 --> 0:30:45
estimate the number of COVID-19 vaccines are easy. They're on the world meter. The influenza

336
0:30:45 --> 0:30:51
vaccine is a little bit more difficult, but you can easily get a very good estimate of the denominator.

337
0:30:51 --> 0:30:57
And that can be achieved by looking at points in time, using all those references, doing models,

338
0:30:57 --> 0:31:05
doing Monte Carlo simulations, and pretty accurately come up. The beauty of our model here is that

339
0:31:05 --> 0:31:15
even if we were off by tenfold, which we're not, it wouldn't change. The data and statistics are so

340
0:31:15 --> 0:31:20
robust that it wouldn't change. It wouldn't change when I know the conclusions. Of course,

341
0:31:20 --> 0:31:26
we didn't do any interventions because this is all de-identified data. And the main outcomes are

342
0:31:26 --> 0:31:36
proportional reporting ratio from the various data. And this in a nutshell is our data, our

343
0:31:36 --> 0:31:43
results. The COVID-19 vaccines, when compared to the influenza vaccines, were associated with an

344
0:31:43 --> 0:31:50
astronomical risk first before pregnancy, an astronomical risk, p-values essentially zero,

345
0:31:51 --> 0:31:56
of menstrual abnormalities, very concerned with menstrual abnormalities before pregnancy.

346
0:31:56 --> 0:32:04
In pregnancy, a substantial risk of miscarriage. And I'll go through the observations on subsequent

347
0:32:04 --> 0:32:12
slides. There's a substantial risk of fetal malformations, a major fetal malformation

348
0:32:12 --> 0:32:19
called a cystic hygroma. Cystic hygroma is a malformation of the lip channels that connect

349
0:32:20 --> 0:32:27
the lymph system to the venous system and seems to be focused in the neck, get massive swelling,

350
0:32:27 --> 0:32:33
tissue swelling, heart failure and death. Now, some of those babies can go on and survive,

351
0:32:34 --> 0:32:40
but many of them don't. A massive increase. This is interesting. Fetal chromosomal abnormalities

352
0:32:40 --> 0:32:49
are significantly increased. And by the way, I chose all of the, there's thousands of symptoms

353
0:32:49 --> 0:32:56
or complications in BEARS database that you can choose from. I chose these not before I went in

354
0:32:56 --> 0:33:05
looked at BEARS. Before I went and looked at BEARS, I selected several issues that I wanted to focus

355
0:33:05 --> 0:33:10
on in BEARS to see if they have outcomes. And indeed they did. So cystic hygroma was one of

356
0:33:10 --> 0:33:16
them. The reason why I looked at fetal chromosomal abnormalities, because in the Pfizer download,

357
0:33:16 --> 0:33:26
that by the way, they tried to suppress for 75 years. It was just released April 1st, April.

358
0:33:26 --> 0:33:33
It's an April Fools joke from Pfizer's. Oh yeah, April Fools. Yeah, we've been killing and maiming

359
0:33:33 --> 0:33:38
a lot of you around the world. No big deal. Nothing here to see. We'll just move on. They tried to

360
0:33:39 --> 0:33:46
suppress that data for 75 years. But if you go and look at that data on page seven of that document,

361
0:33:46 --> 0:33:53
just Google it. Was it 1,223 deaths? And on page 12, there's 46% of the pregnant women that had

362
0:33:53 --> 0:33:58
adverse effects. There were also some of those adverse effects were chromosomal abnormalities.

363
0:33:58 --> 0:34:06
And it makes sense because anything that causes a massive amount of inflammation in the development

364
0:34:06 --> 0:34:12
of the embryo and the fetus will result in embryonic or fetal death, embryonic or fetal

365
0:34:12 --> 0:34:22
malformation. There's eons of data that we've focused on for 40 years. Robert Romero is a

366
0:34:22 --> 0:34:28
maternal fetal medicine physician. He's much my senior, but for 40 years, his whole career has

367
0:34:28 --> 0:34:35
been focused on inflammation, the maldevelopment, embryotoxic, fetotoxic effects of inflammation.

368
0:34:36 --> 0:34:43
But we also see in addition, one of the 13 unspeculable variables we looked at here

369
0:34:43 --> 0:34:49
was a significant risk of cardiac abnormalities. That's how it is versed in theirs, cardiac

370
0:34:49 --> 0:34:56
abnormalities. Also, independent cardiac malformation significantly increased. Also,

371
0:34:57 --> 0:35:09
cardiac disease and also cardiac arrest in the fetus. A substantial increase in the COVID-19

372
0:35:09 --> 0:35:15
vaccinated compared with the influenza vaccinated pregnancies, dramatic increase in fetal growth

373
0:35:15 --> 0:35:22
restriction, interuterine growth restriction, substantial increase in abnormal Doppler

374
0:35:22 --> 0:35:30
velosimetry of the abnormal fetuses due to the abnormal placenta in those patients, those fetuses

375
0:35:30 --> 0:35:38
that had been exposed to the COVID-19 vaccine compared with those that were exposed to the

376
0:35:38 --> 0:35:46
influenza vaccine. Also, a substantial increase in risk of placental, arterial, and venous blood

377
0:35:46 --> 0:35:54
clot. No surprise there, right? Dr. Peter McCullough wouldn't be surprised, he wasn't surprised at all

378
0:35:54 --> 0:36:01
through any of it. Also, substantial increase in what we call oligofibromia or reduced amniotic

379
0:36:01 --> 0:36:09
fluid line. No surprise there because it's very, there's many different mechanisms which I'll

380
0:36:09 --> 0:36:16
maybe go through, but it's not surprising at all that there's severe placental dysfunction

381
0:36:17 --> 0:36:24
related to the very inflammatory effects of the vaccine. I'll show you some of those in

382
0:36:24 --> 0:36:30
placental ultrasounds. So when we have the placenta not working, we get

383
0:36:30 --> 0:36:35
growth restriction of the fetus, we get depth of the fetus. We've seen depth of the fetus,

384
0:36:36 --> 0:36:44
significant risk. So our conclusions from all of these illustrious co-authors that I have,

385
0:36:45 --> 0:36:51
we need to have a moratorium on the vaccine worldwide, a moratorium for sure in pregnancy

386
0:36:51 --> 0:36:59
and breastfeeding modes. I won't dwell a lot, this is one of the, oh my gosh, don't show us this,

387
0:36:59 --> 0:37:07
but you don't have to read all the stuff. I just want to show you that we have all of the raw data,

388
0:37:08 --> 0:37:14
I just want to show you that we have all of the raw data, all of the raw data is in here. So we've

389
0:37:14 --> 0:37:22
got on the front part of the slash, you've got the actual number of adverse events from the

390
0:37:23 --> 0:37:29
COVID-19 vaccination. On the other side of the forward slash, you've got the number of actual

391
0:37:29 --> 0:37:35
raw data from the influenza vaccines. So you can see in this, by the way, these are all global.

392
0:37:36 --> 0:37:41
This is global, this is not US, this is all global. And you see four columns of data here.

393
0:37:46 --> 0:37:54
The first one would be for each shot, in other words, adverse event per vaccine per shot.

394
0:37:55 --> 0:38:01
Remember, several people had more than one shot. The second column would be the adverse

395
0:38:01 --> 0:38:09
event per time, per unit of time. And the third one is the abnormal event per person vaccinated.

396
0:38:10 --> 0:38:20
So it doesn't matter how you slice the cheese, there's a major dangerous signal emanating from

397
0:38:20 --> 0:38:26
this data. Now, table two is the exact same format, except this is just a US data. I won't spend a lot

398
0:38:26 --> 0:38:33
of time on that. Table three is a relative risk by time, dose, and person vaccinated.

399
0:38:33 --> 0:38:38
Some of these P values, I mean, when you get down to a P value of 10 to the minus seven or eight,

400
0:38:41 --> 0:38:51
that's statistical improbability. I love forest charts. This is a forest plot. And on forest plots,

401
0:38:51 --> 0:39:02
we're looking at odds ratio or relative risks denoticated by the marks here.

402
0:39:04 --> 0:39:16
And the flanking the marker, the box, if you will, on its side, on its angle, are the 95%

403
0:39:16 --> 0:39:21
confidence intervals. Now, I want you to know a very important thing about this graph. This is a

404
0:39:21 --> 0:39:31
semi logarithmic graph. Why did we do that? Well, this relative risk, where you're sitting and you're

405
0:39:31 --> 0:39:43
viewing this monitor, this dot, this square would be all the way out about a mile to your right side

406
0:39:43 --> 0:39:49
if this wasn't a logarithmic graph. It would be that far off the graph. Just look at the right side

407
0:39:49 --> 0:39:54
and it would be to your right about a mile or a half a mile. That's how far away it would be.

408
0:39:55 --> 0:40:01
By the way, the CDC and the FDA clearly denote, we've referenced that, that whenever there's an

409
0:40:01 --> 0:40:07
odds ratio or relative risk of two or greater, that's a danger signal and it needs to be

410
0:40:07 --> 0:40:16
investigated. These are so far away from two. You'll see here 1,192 times that by 100 and you'll

411
0:40:16 --> 0:40:24
get the percent of the increase, but this is a increase of 1,192 fold of abnormal menses,

412
0:40:25 --> 0:40:32
women that were menstruating normally before. So, a 57 fold increase in miscarriage. So,

413
0:40:32 --> 0:40:38
this is perfectly consistent with Tommy T. Shimabukuro, the New England Journal of Medicine

414
0:40:38 --> 0:40:47
article, that tried to hide it and also right on spot with what we're finding with the Pfizer 5.3.6

415
0:40:47 --> 0:40:54
post-marketing analytics themselves. The risk of miscarriage is upwards to 80%. This is very,

416
0:40:54 --> 0:41:02
very consistent with that. Very consistent. Fetal malformation, 20 fold increase. Fetal

417
0:41:02 --> 0:41:09
cardiac disease, 16 fold increase. Fetal growth restriction, 56 fold increase. Abnormal fetal

418
0:41:09 --> 0:41:17
surveillance, 25 fold increase. Stillbirth, 38 fold increase. Oligo-hydramyl, low amniotic

419
0:41:17 --> 0:41:24
fluid volume that is consistent with abnormal placental function, 16 fold increase. So,

420
0:41:25 --> 0:41:32
very, very upsetting data, but this is perfectly consistent with what I've seen in my very large

421
0:41:32 --> 0:41:44
volume of skeptical cellographic practice. So, as I suggested before, this is also, golly,

422
0:41:46 --> 0:41:51
a slide that's difficult to look at, but I don't expect you to read all these things,

423
0:41:51 --> 0:41:57
but I would expect you to be overwhelmed by the amount of independent sources that

424
0:41:58 --> 0:42:03
totally corroborate various data. So, the problem is that

425
0:42:05 --> 0:42:12
there's been a massive number of professionals, attorneys, legislators,

426
0:42:14 --> 0:42:20
physicians, sowing a seed in preparation for the rollout of the pandemic.

427
0:42:21 --> 0:42:29
And I know that sounds a little conspiratorial, but facts are facts. When you have a patent

428
0:42:30 --> 0:42:36
on a COVID-19 vaccination that dates back to the turn of the century, that doesn't quite add up.

429
0:42:37 --> 0:42:40
When you have all the internal communications, which Dr. Peter Bregan

430
0:42:41 --> 0:42:49
has so well illustrated in his book with his beautiful bride, Ginger Bregan, this book is

431
0:42:50 --> 0:42:57
there's 600 pages. It's extraordinarily well referenced with 1100 references. It's a massive

432
0:42:58 --> 0:43:04
goldmine, and buy one and keep it, because they're erasing the data from the internet

433
0:43:05 --> 0:43:15
every single day. And there are a accumulation of irreconcilable, irrefutable, undeniable facts

434
0:43:16 --> 0:43:26
that show that this was set up. This was a plan. We will execute the drugs in the medical literature

435
0:43:26 --> 0:43:32
by the medical industrial complex that we know to be effective against SARS-CoV. And that was done

436
0:43:32 --> 0:43:41
before the SARS-CoV outbreak. Example, hydroxychloroquine, extraordinarily effective.

437
0:43:41 --> 0:43:50
I've used it for 40 years in pregnancy. I know it to be safe. Africans have used it for longer.

438
0:43:51 --> 0:43:56
I used it in pregnancy in the first trimester in patients with autoimmune disease. I knew that was

439
0:43:56 --> 0:44:10
safe, but yet the UN and the WHO and Fauci slandered it and in essence, villainized it

440
0:44:10 --> 0:44:21
in publication in the Lancet Journal. Look it up. Dr. Mandeep, M-A-N-D-E-E-P, M-E-H-R-A,

441
0:44:22 --> 0:44:30
chief cardiovascular surgeon at Boston, Brigham and Winmans. This article, I suspect, was ghost

442
0:44:30 --> 0:44:39
written as well. Now he went a little bit further. They completely falsified the data. They didn't

443
0:44:39 --> 0:44:44
change it around like Shimabukuro did. They completely falsified the data. They did the same

444
0:44:44 --> 0:44:55
thing with ivermectin. The science is in, and Charles, excuse the expression. I know you don't

445
0:44:55 --> 0:45:01
like this expression, but the verdict is out. The science is in. Early treatment of COVID-19

446
0:45:01 --> 0:45:08
is extraordinarily effective, as in 99.99 percent, according to Dr. Ben Marl, who has personally

447
0:45:08 --> 0:45:16
treated 275,000 patients with his early treatment regimen. These are all safe nutraceuticals and

448
0:45:16 --> 0:45:24
vitamins, including ivermectin and hydroxychloroquine. They had to remove that. They had to get that out

449
0:45:24 --> 0:45:28
of the way, otherwise they couldn't be making trillions of dollars. It would have been illegal

450
0:45:28 --> 0:45:35
to move towards an emergency use authorization if those drugs were left on the table, because it

451
0:45:35 --> 0:45:42
would be illegal by the CDC and our government. It would be illegal. So they have manipulated a lot

452
0:45:42 --> 0:45:50
of laws, a lot of doubt, a lot of falsified information, and a lot of new laws to protect them

453
0:45:51 --> 0:46:01
after this plandemic was executed. A lot of those are seeding, sowing doubts of the veracity of the

454
0:46:01 --> 0:46:11
various data. We have funding back in mid 2006, 2007 to upgrade the various data system to the

455
0:46:11 --> 0:46:16
equivalent of that of the DMED database. For those of you who don't know the DMED database,

456
0:46:18 --> 0:46:25
it is the medical epidemiologic database, which is the most sophisticated database

457
0:46:26 --> 0:46:32
in the world. I have the audacity to say that. It is. We were going to do that. We have funding to

458
0:46:32 --> 0:46:41
do that with electronic medical records. In other words, it's not a passive system that's actively

459
0:46:41 --> 0:46:47
taken up from medical records of physicians documenting on the chart. That was put on hold

460
0:46:47 --> 0:46:56
by the FDA and CDC and by the pharmaceutical company. Why? Why do you think? I believe so

461
0:46:56 --> 0:47:03
that they could continue to manipulate and do these shenanigans. The DMED database, they had to go

462
0:47:03 --> 0:47:12
back. The whistleblowers called whistle, blew the whistle on the DMED database. They were crucified.

463
0:47:12 --> 0:47:20
The only thing they could say was, oh, you know, gosh, we didn't see this before, but there's been

464
0:47:20 --> 0:47:26
five years of data error in DMED database. So none of the findings that the whistleblowers find were

465
0:47:26 --> 0:47:35
real. The most accurate database in the country, these flight surgeons and physicians and

466
0:47:35 --> 0:47:40
cardiologists in the military are seeing pilots and active duty people drop like flies.

467
0:47:41 --> 0:47:47
And yet, and they call them out on it and they get threatened. And then the only excuse they had is,

468
0:47:47 --> 0:47:52
oh, well, there was a corruption in the database for five years. No, I don't think so. But they

469
0:47:52 --> 0:47:58
sowed a lot of seeds in the verbiage of bears on the CDC website. Oh, it's association. That's not

470
0:47:58 --> 0:48:04
causal. Well, of course, there's never been. It's very difficult to determine causality.

471
0:48:05 --> 0:48:11
But anyways, just go through the UK government themselves. And I'll show you this on a subsequent

472
0:48:11 --> 0:48:18
slide. Of all things, the UK data, and I just found this out, the UK government website

473
0:48:19 --> 0:48:26
strongly advocates against the use of the COVID-19 vaccine in pregnancy and breastfeeding mothers.

474
0:48:27 --> 0:48:32
I can prove it to you. I'll show it to you. I didn't believe it. I just discovered it a month ago.

475
0:48:32 --> 0:48:40
It's a classic maneuver by the medical industrial complex and by the pharmaceutical companies

476
0:48:40 --> 0:48:46
that put a lot of, you know, 100 pages of trash, nonsense, worthless information. And then at the

477
0:48:46 --> 0:48:53
end of them, that section will drop a nugget, which they did in this one. So why did they do that?

478
0:48:53 --> 0:49:00
It's very easy because they have plausible deniability. When the House of Cards drop,

479
0:49:00 --> 0:49:10
like it has in 75 countries, and you got the government in Austria blaming you, the physicians,

480
0:49:10 --> 0:49:17
because you, physician, did not get informed consent. It's your fault, physician. It's not

481
0:49:17 --> 0:49:22
our fault because we didn't recommend it. It's right in our website. Isn't that the perfect?

482
0:49:22 --> 0:49:30
There's no way the UK government can get sued. So that's what I think. The UK yellow card

483
0:49:30 --> 0:49:37
system, it's the exact same as various is worse. The European Medicines Agency,

484
0:49:37 --> 0:49:46
you drew a big vigilance. It's the exact same as various worse. The WHO, World Health Organization's

485
0:49:46 --> 0:49:53
you drew vigilance. It's the same nonsense, horrible outcomes. You got Edward Dowd

486
0:49:54 --> 0:50:03
documenting 61,000 dead millennials just in six months of last year. Let that soak in.

487
0:50:05 --> 0:50:14
61,000 dead, healthy, young, beautiful, millennial human beings dead in six months.

488
0:50:16 --> 0:50:23
They all died from fentanyl? No. They all died from suicide? No. They all died from COVID-19?

489
0:50:23 --> 0:50:26
No, they did not. These are young, healthy individuals.

490
0:50:29 --> 0:50:35
When I was a millennial, I was 24 years old with my brother, Kent Thorpe, and my research partner,

491
0:50:36 --> 0:50:41
my mentor, and we went to medical school at Wayne State University School of Medicine.

492
0:50:41 --> 0:50:52
In 1976, the influenza vaccine, the swine flu vaccine caused 26 deaths.

493
0:50:52 --> 0:51:00
It was immediately ripped out of the market. But when we were back then, it took 15 years to kill

494
0:51:02 --> 0:51:10
58,500 of my contemporaries at the time who were millennials through the Vietnam War. That's

495
0:51:10 --> 0:51:21
15 years of death and destruction of a war to kill 58,500 of my contemporaries when I was a millennial.

496
0:51:22 --> 0:51:32
Let that sink in. 61,000 dead millennials in six months. Same with One America Insurance Company.

497
0:51:32 --> 0:51:38
One America Insurance Company is one of the largest insurance companies, and the CEO, Mr.

498
0:51:38 --> 0:51:44
Davis, in Indianapolis, Indiana, shows an all-cause mortality rate up 40%.

499
0:51:47 --> 0:51:55
Now, let's put that into context. A 10% increase in all-cause mortality is a black swan 200-year

500
0:51:55 --> 0:52:04
event of three sigma. It's a three sigma, three standard deviation event above what is expected,

501
0:52:05 --> 0:52:16
and it's a major catastrophic death now for the insurance payouts. That's 10%. This was a 40%,

502
0:52:16 --> 0:52:22
so we're looking at 12 sigma event. It's the same thing with Lincoln Insurance Company.

503
0:52:23 --> 0:52:32
It's the same thing with there's 32, 33 young, beautiful, dead Canadian physicians.

504
0:52:32 --> 0:52:39
That's unprecedented. We have longevity data on this. This has never occurred in the history of Canada.

505
0:52:43 --> 0:52:53
They're from the vaccine. You have 1,354 dead or severely affected athletes,

506
0:52:53 --> 0:53:05
922 of whom were dead. This is unprecedented. These are young, healthy human beings at the peak,

507
0:53:05 --> 0:53:12
the pinnacle of their physical health, and they're dead. They're no longer with us.

508
0:53:15 --> 0:53:19
All-cause mortality by anybody's, every government's

509
0:53:19 --> 0:53:29
reconnaissance is way up in every single country. Funeral directors worldwide note a massive increase.

510
0:53:30 --> 0:53:38
Child newborn casket producers, they've never had to produce so many in their entire history.

511
0:53:39 --> 0:53:49
Dr. Palmer's and Dr. Bobke, unequivocal, 93% of the people dying from the vaccine are proven to be

512
0:53:49 --> 0:54:00
dead and killed by the vaccine by massive spike protein endothelitis in nearly every organ system

513
0:54:00 --> 0:54:08
in the body. Dr. Arne Burkhart of Germany, the pathologist, exactly the same. Alexandra

514
0:54:08 --> 0:54:14
Sasha Latipova, I think she's been on this forum. She has procured, she's a whistleblower from the

515
0:54:14 --> 0:54:23
pharmaceutical industry, and I've met with her. She has showed documents showing irrefutably

516
0:54:23 --> 0:54:31
that the toxicology, the reproductive toxicology studies in animals were completely altered and

517
0:54:31 --> 0:54:39
fabricated with the deletion of severe birth defects in the animal dams in the fetuses,

518
0:54:39 --> 0:54:45
and I'll show you some of those. You've got Richard Hirschman, the embalmer. I don't know

519
0:54:45 --> 0:54:49
any of those, any of you all that were tuned in yesterday. He had a brilliant presentation

520
0:54:49 --> 0:54:56
at the Idaho legislature. I was on the panel as well, and he's brilliant, and his story is

521
0:54:56 --> 0:55:03
brilliant. If you get a copy of that, maybe he could visit with us. Albert Bennett V-Days,

522
0:55:03 --> 0:55:10
he needs no introduction. Dr. Daniel Magas of Canada, he and I are in contact. He's a

523
0:55:10 --> 0:55:17
brilliant emergency doctor. We've done a lot of work together. We are correlating all the adverse

524
0:55:17 --> 0:55:23
and skeptical outcomes from Canada, which has just been unbelievable. The massive number of fetal

525
0:55:23 --> 0:55:29
deaths still birthed just in Waterloo area in Ontario. I mean, these are documented. They're

526
0:55:29 --> 0:55:35
unprecedented. Of course, Dr. Peter McCullough has a massive amount of data. The DMEB,

527
0:55:35 --> 0:55:41
U.S. Military Database, World Council for Health has a massive amount of data. They're calling for

528
0:55:41 --> 0:55:51
complete ban of all COVID-19 vaccination. And then you have our publication from April

529
0:55:52 --> 0:56:02
that is COVID-19 and the corruption of medical science. And that's part three, which was published

530
0:56:02 --> 0:56:13
in March. I studied, reviewed, and outlined in a Word document 1,366 peer-reviewed publications.

531
0:56:13 --> 0:56:18
I wrote them all. I studied them all. And I documented them all. And I published them all.

532
0:56:19 --> 0:56:24
The journal, the Gazette of Medical Sciences, was so impressed that I delayed all these,

533
0:56:24 --> 0:56:30
that they published an appendix to the actual publication with every single one of these

534
0:56:30 --> 0:56:38
references published on it. And I formatted them in a table so you can look up the subject of the

535
0:56:38 --> 0:56:45
adverse event or the death, my subject. And going back to those two babies that died after

536
0:56:45 --> 0:56:51
breastfeeding, they're dead, they're no longer with us. They were caused by thrombotic thrombocytopenic

537
0:56:51 --> 0:56:58
perfora and also by autoimmune disease. Those are the huge lion's share of those complications

538
0:56:58 --> 0:57:07
that I documented were from those two causes. Huge numbers. It's not safe. And focusing on

539
0:57:07 --> 0:57:14
the 1,366, that was bad publications, all peer-reviewed, all in the medical literature,

540
0:57:15 --> 0:57:22
it's stunning. Now there's over, and we're doing numbers, we're up to over 2,000 now.

541
0:57:23 --> 0:57:31
Imagine that. I go back for a whole century, a whole century looking at all other vaccines.

542
0:57:33 --> 0:57:40
There's hardly any. You cannot come anywhere close to even 1% of those.

543
0:57:40 --> 0:57:43
It's stunning. This in of itself

544
0:57:47 --> 0:57:51
proves that this is a very dangerous vaccination.

545
0:57:53 --> 0:57:59
Multiple countries have now, over 75 countries have banned the use of the vaccine,

546
0:57:59 --> 0:58:05
either totally or in certain segments of their population, never mind banning all the ridiculous

547
0:58:05 --> 0:58:14
stringency, social distancing and masks and travel. And by the way, in the process of doing

548
0:58:14 --> 0:58:21
another study at this time, outlining the effects of all those. Costa Rica, all the Scandinavian

549
0:58:21 --> 0:58:28
countries, Uruguay, Germany, Italy, Denmark, 78 other countries, probably more by now.

550
0:58:28 --> 0:58:34
Denmark, 78 other countries, probably more by now. And then you've got the Steve Kirsch

551
0:58:36 --> 0:58:46
formal. And I see my buddy Lenny that is watching, and Lenny's a brilliant investigator.

552
0:58:48 --> 0:58:54
He puts together questionnaires and he's a doctor for the brassica, Steve Kirsch's formal survey

553
0:58:54 --> 0:59:02
data undeniable showing unbelievable risks of the vaccine. And then if you're going to throw out

554
0:59:02 --> 0:59:10
all the 32, probably 40 different references by now, then are you going to believe Pfizer themselves?

555
0:59:10 --> 0:59:15
I've been through that data. Pfizer themselves told you that their vaccine is deadly.

556
0:59:16 --> 0:59:23
You're going to believe them? I would. Here's a, if you don't believe me,

557
0:59:25 --> 0:59:32
I've been going on here about 40 minutes or 45 minutes or so. So Charles just cut me off when

558
0:59:32 --> 0:59:43
you want to, but this is right out of the bloody UK website. Look it up. You can read as well as I.

559
0:59:45 --> 0:59:51
The UK government has never recommended the use. They said, do not take the COVID-19 vaccine in

560
0:59:51 --> 0:59:58
pregnancy. Do not give it to breastfeeding moms. Too bad it was buried. I only discovered this,

561
0:59:58 --> 1:00:01
you know, like a month ago. I couldn't believe it.

562
1:00:04 --> 1:00:11
So James, James on this question, if you go for another 10 minutes, this is, there are so many

563
1:00:11 --> 1:00:17
questions, comments. I'm sure people have, but it's just stunning what you're sharing with us.

564
1:00:17 --> 1:00:21
If you want to go for 15 minutes, that's fine as well, but about 10 minutes and then

565
1:00:21 --> 1:00:26
great opportunities for questions. Gotcha. Okay. It's 3.11 here, central time.

566
1:00:26 --> 1:00:34
Hurricane's not banging on my fanny out here. So excellent. So I'll go to 3.20 or something.

567
1:00:35 --> 1:00:35
Okay.

568
1:00:38 --> 1:00:45
This is Sasha, Sasha Lattie-Bowes. And we did this, she broke this in the ET Times

569
1:00:45 --> 1:00:52
and I commented on it and I reviewed it all and she and I have met formally and I interviewed her.

570
1:00:53 --> 1:00:57
And she's a real deal. She's an extraordinarily brilliant young woman.

571
1:00:58 --> 1:01:06
And there's no question that this caused severe skeletal dysplasia in the rat fetuses.

572
1:01:07 --> 1:01:14
I won't go through all the reproductive toxicology. They hit them. They buried them. They lied about

573
1:01:14 --> 1:01:24
them. Can you imagine? I mean, whoever did this, perpetrated this disaster? I mean,

574
1:01:25 --> 1:01:29
mass killing all over the world by perpetrating fraudulent data,

575
1:01:30 --> 1:01:32
the new MO of the medical industrial complex.

576
1:01:36 --> 1:01:43
This is a lethal skeletal dysplasia on my side of the equation. I don't deliver too many rats,

577
1:01:43 --> 1:01:48
we do ultrasound on too many rats, but this is in essence what it showed was when there's a

578
1:01:48 --> 1:01:53
skeletal dysplasia of which there's over 200 different genetic and various causes.

579
1:01:55 --> 1:02:00
Some of them are lethal and the ones that are lethal are caused by the ribs aren't able to

580
1:02:00 --> 1:02:06
grow so the lungs don't grow. So the fetus can go all the way to turn, but yet as soon as the

581
1:02:06 --> 1:02:14
umbilical cord is cut, babies die because they don't have any lung tissue because the chest

582
1:02:14 --> 1:02:19
can't expand and that's why we call it a bell-shaped chest. See, this is the abdominal

583
1:02:19 --> 1:02:25
circumference or diameter. This is a thoracic diameter. They should be equal and you see a

584
1:02:25 --> 1:02:33
bell-shaped chest. This is a radiograph of a baby after birth and this is the stillbirth. I'm sorry,

585
1:02:33 --> 1:02:39
it was not a stillbirth. This was a newborn baby that died because it couldn't sustain life.

586
1:02:39 --> 1:02:46
So this is an abnormal placenta. This is the pattern that I'm seeing six to eight weeks

587
1:02:47 --> 1:02:54
after Pfizer vaccine and I don't have a lot of time to review this. I've got a few minutes left

588
1:02:54 --> 1:03:00
here, but you see the very dense calcification which is really abnormal and it's around each

589
1:03:00 --> 1:03:06
of the organelles if you will, what we call cata-leadens of the placenta. You see an area

590
1:03:06 --> 1:03:12
here that's infarcted. This is a very abnormal looking placenta. This is what I'm seeing about

591
1:03:12 --> 1:03:21
six to eight weeks after the vaccine is injected. Now fortunately in my practice on the vaccine,

592
1:03:22 --> 1:03:28
if the medical records are accurate in the you know in the discrete peaks that I can look in the

593
1:03:28 --> 1:03:35
clinical side, there's a lot of patients that are not taking the vaccine anymore. So and by the way,

594
1:03:35 --> 1:03:44
kudos to you Charles and to you Stephen because you know there's only five percent of the people,

595
1:03:44 --> 1:03:49
five percent of the kids worldwide that are getting this vaccine and that's because of your

596
1:03:49 --> 1:03:56
truth and that's because of all of us in the world putting the word out. People will not admit it

597
1:03:56 --> 1:04:02
that they're not better than me and their kids. They know better than that. I want to do a shout

598
1:04:02 --> 1:04:10
out to one of the young rising heroes that is fortunate enough to be on my team and her name is

599
1:04:10 --> 1:04:18
Tiffany Carado and she's the CEO and Leonard Murphy is part of his team and many others.

600
1:04:19 --> 1:04:26
You know we have Christiane Northrup, just an incredible physician. Many of you know her and

601
1:04:27 --> 1:04:35
you know we have Dr. Brian Hooker, we have Sue Peters, we have just Warren Geek, so many

602
1:04:35 --> 1:04:46
incredibly brilliant people but Tiffany went and started a survey and I want to say 80 or 100,000

603
1:04:46 --> 1:04:54
whatever respondents were deleted because the purveyors of truth didn't like, they like these

604
1:04:54 --> 1:04:59
victims, they're like throwing them under the bus and taking away their platform. Now with Tiffany,

605
1:05:01 --> 1:05:04
that's not going to work with Tiffany Carado so she started her own website,

606
1:05:05 --> 1:05:11
started her own questionnaire and we got on a protected website mycyclestory.com. We published

607
1:05:11 --> 1:05:18
our first manuscript from this and I don't have time to get into it but you should read it.

608
1:05:19 --> 1:05:30
This here is a decidual cast, this is a relatively rare event. That publication of these over the last

609
1:05:31 --> 1:05:38
century have yielded only about 40 or so, maybe 50 related cases in the medical literature.

610
1:05:38 --> 1:05:48
We found 294 in half a year last year. Something is going on very very wrong. Usually decidual casts,

611
1:05:48 --> 1:05:56
this is kind of get a visual of this, this is a perfect cast if you will of the intrauterine cavity.

612
1:05:56 --> 1:06:03
It's a perfect triangle so all this white tissue is actually an anematrial tissue that decidual cast

613
1:06:03 --> 1:06:09
so all this white tissue is actually an anematrial tissue that decidual base cells

614
1:06:09 --> 1:06:17
that's shut off intact. I don't have time to go through all the mechanisms. I don't have time

615
1:06:17 --> 1:06:24
to go through, this is our most recent publication, COVID-19 energy protein folding and pre-end disease.

616
1:06:25 --> 1:06:33
We postulate, we believe, my partners, research partners and I think others, I think Dr. McCullough

617
1:06:34 --> 1:06:45
I think others believe that part of the collapse is a development in vivo, a massive

618
1:06:45 --> 1:06:55
clot that is mostly protonaceous and it's related to an energy deficit. It's related to the fact that

619
1:06:56 --> 1:07:05
vaccine causes a massive deprivation of energy in the mitochondria, the nuclear, the cytoplasmic,

620
1:07:05 --> 1:07:13
and the cellular level. Where does the energy go? It's being depleted into the production of spike

621
1:07:13 --> 1:07:19
protein so the energy is hijacked and many of you may not know this but it takes an extreme amount

622
1:07:19 --> 1:07:28
of energy for the physiologic folding and unfolding of all biomacromolecules whether it's

623
1:07:28 --> 1:07:36
DNA, it's lipid, it's phospholipids, it's large proteins and our creator designed those so they

624
1:07:36 --> 1:07:42
have a function so that they in certain milieu they have to change to a physiologic function.

625
1:07:42 --> 1:07:49
If they misfold then they aggregate in the glutinous and this is what's happening in vitro.

626
1:07:49 --> 1:07:55
This is where Richard Hirschman is getting these massive clots and all the embalmers are.

627
1:07:56 --> 1:08:02
This is what's killing many patients, the micro and the macro clotting. They form in the vena cava.

628
1:08:02 --> 1:08:08
They form in the vena cava. Look at this, look at these clots. Look at these clots. They've never,

629
1:08:08 --> 1:08:14
the embalmers have never seen this before before the vaccines started going out. These are massive

630
1:08:14 --> 1:08:19
clots. This is, look at this ruler. This is a massive clot next to the corpse.

631
1:08:21 --> 1:08:26
These are not occurring after death. These are pre-mortem clots as a cause of death. They've

632
1:08:26 --> 1:08:35
never seen these before. This is the clots washed off in saline so the red, this is largely very,

633
1:08:35 --> 1:08:41
very different than the standard deep vein thrombosis that we saw pre-pandemic. These are

634
1:08:41 --> 1:08:49
not remedial. They're not cured. They're not fixed by standard therapeutics of heparin and

635
1:08:49 --> 1:08:57
low-moderate weight heparin. It's from a crowd of artery. There's several of them. I can't vouch

636
1:08:57 --> 1:09:03
for the veracity of this clot in the middle. Allegedly, I believe that this is a clot which

637
1:09:03 --> 1:09:09
was taken out in vivo by a cardiothoracic surgeon after cracking the chest.

638
1:09:12 --> 1:09:21
I'm going to stop here. Y'all, I love you all. I'm so honored to be able to present our data to you.

639
1:09:23 --> 1:09:25
Let's get the word out. Let's stop this vaccine.

640
1:09:28 --> 1:09:34
Thank you, David. Thank you. Thank you. Thank you, James.