Metabolic Health Experimentation with Nick Norwitz

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Well, hello ladies and gents.
Robert Sykes Keto savage.com to
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Devgat special guest Nick
Norowitz on the line.
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And we dive deep into all the
experiments he has been
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conducting such as the Oreo
cookie experiment, in which case
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he ate Oreos and hydrostatins
and the Oreos outperformed the
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statins for dropping LDL.
We talked quite a bit about the
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lipid energy model, lean mass,
hyper responders, all that good
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stuff.
We talked about his high calorie
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experiment and what that did to
his LDL markers.
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We talked about the satiety per
calorie model and what his
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thoughts are towards it.
And we talked about how he
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scored a lifetime or a year
supply of eggs rather because of
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his recent egg experiment, which
he was pretty much eating the
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equivalent of 1 egg every single
hour every single day.
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So very interesting stuff.
I got a lot of respect for Nick.
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He is an academic, he is a
researcher, he is a scientist at
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heart.
He's got a ton of curiosity and
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that drives all kinds of awesome
experiments.
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A lot of respect form a lot of
respect for what he's doing and
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the attention he is bringing to
metabolic health and therapies
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within the ketogenic sphere, the
low carb sphere, the carnivores
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sphere.
So happy to get him on the
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podcast.
Happy to die deeper.
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Without further ado, sit back,
relax, enjoy the conversation
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with Nick Norowitz.
We are live, Nick.
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How are you, brother?
Great, happy to be here.
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Happy to have you, man.
I, I met you.
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I don't even know if we actually
physically met, but I, I heard
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of you saw you speak on stage at
the Metabolic Health Summit back
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in what it was January or
February and you were, you were
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just tearing up the stage
alongside Dave Feldman with
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regard to your Oreo cookie
study.
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And since then we've been in
contact and you've just been
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having one amazing experiment
after the other.
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And I'm all for self
experimentation.
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So I definitely want to peel the
curtain back and dive deep into
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all of those and some of your
findings.
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But I love a little intro as to
who, what, what even led to the
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person you are now as far as
you're incredibly witty,
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incredibly intelligent.
You are very polarizing online,
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which I admire because you do so
in a very respectful, tactful
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way, which is hard to do with
social media.
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So I kind of want to get a
little back story on who you
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are, man.
What what gets you into the the
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fitness, nutrition, health space
to begin with?
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Yeah, for sure.
Well, thanks for our lovely
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intro.
I, I mean, I, I fancy myself
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first, you know, an academician.
My background is undergrad.
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I studied cell bio and biochem
at Dartmouth College.
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Then I went to Oxford in the UK
for my PhD and human metabolism
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before coming back to the States
to do my MD at Harvard, which
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I'm finishing up in the last
months of that.
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So you know, along this journey
that a lot of conventional
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training, a lot of normal
academics, publishing papers,
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doing research.
But along the way I got drawn
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into the metabolic health
community.
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I'll call that based on a
personal journey with with
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ulcerative colitis where I was
in a really dark place at the
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end of college and beginning of
grad school with some severe
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inflammatory bowel disease
symptomology, ulcerative colitis
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symptomology and palliative
care, IC level care.
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I mean, my life really had gone
downhill quickly.
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I gone from being a competitive
athlete and top academician to,
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you know, being so physically
depleted at getting up and
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walking to the bathroom took the
literal effort running marathons
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used to.
And I'm I, my mentally wasn't
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there.
I socially wasn't there.
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I was like a shell of the person
I was.
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But you know, through
desperation, you're willing to
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try some crazy things, quote
crazy.
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And I found that a ketogenic
diet was pretty effective for me
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at helping me put my colitis
into remission and helping me
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regain my life and putting it
back on course, finishing up my
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my PhD and then going off to
medical school.
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So a ketogenic diet really
changed my life.
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And I'm not someone to, you
know, get super evangelical
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after just an N = 1 experience.
But it did peak my curiosity
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enough to get me to engage with
more of the literature around
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metabolic health.
And one thing led to another,
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and now we're having this
conversation.
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And you started in the ketogenic
diets, was it like seven years
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ago or something like that?
A little over five years ago.
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Five years ago.
And so at that point, I mean,
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the keto diet it, it's
interesting because I've like
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watch the trends.
I've been doing keto for almost
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10 years now and when I started
doing it, there wasn't really
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much literature on there wasn't
really books or the popularity
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that surrounds it now.
I think it peaked in 2019
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according to Google Trends at
least.
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And now carnivores, kind of a
subsidiary of that that's taken
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the limelight.
But I always enjoy talk with
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people that have been doing the
ketogenic diet for several years
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because it's obvious they're in
it for the right reasons as
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opposed to just following the
trends.
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And especially when it comes
from a place of their own
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personal desire or desperation
to improve health and well-being
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in some sort of an or another.
So hearing that makes me respect
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you all the more.
Yeah, I appreciate it.
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It's been, it's been quite a
journey, an eye opening journey
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in many ways.
I mean, it's funny, looking back
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from where I am now, I realized
there are a lot of stereotypes
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built around keto and carnivore.
I guess is a as one extreme
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therein that, you know, you have
these caricatures and
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stereotypes propagated by
mainstream points of view, which
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if I'm being totally honest with
myself, given the ecosystem in
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which I've grown up and the
training that I've been exposed
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to, I would probably hold those
negative stereotypes if I didn't
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have my own, you know, N = 1
experience.
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So it's a funny thing for me
because my whole life mission
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now is to make metabolic health
mainstream, including advancing
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research on ketogenic diets,
even carnivore diets for that
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matter.
We've had a couple papers on
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carnivore diets and potentially
some more plan because I do find
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it metabolically interesting
with physiological plausibility,
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even though that butts up
against, you know, conventional
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narratives and how to
diplomatically walk the line so
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that I can introduce metabolic
health therapy, ketogenic diet
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therapy, these fringe ideas to
the mainstream who I know will
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be susceptible to them because
they're based on, you know,
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rigorous science and Physiology.
And we're asking some
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provocative questions like,
there's no reason people should
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be closed off to these
approaches.
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However, you put them through
the social media filter and you
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end up with these.
I've used the word, but I'll use
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it again.
Like stereotypes and caricatures
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that are just really hard to
kill and get propagated by the
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fact that, you know, things like
keto bashing are just effective
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ways to get social media points
from the mainstream, be it
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mainstream calorie defending
influencers.
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I know we both know a few or,
you know, legacy media outlets
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who will tear into these
concepts of like there were
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recently a couple papers on red
meat and diabetes.
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And it's like, it's a good click
bait title.
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But then you start to delve into
the literature and it's like,
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you know, I almost am
embarrassed to say I'm in the
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nutrition space.
In fact, my parents, when they
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tell people what I do, they're
like, oh, he's in nutrition
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science.
And I'm always like, no, don't
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tell them that because nutrition
science understandably has this
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like fluffy Halo of a fluff
science because it is such a,
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it's a field filled with so much
crappy research that to dig
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through it and find the diamonds
in the rough is something that
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it's intimidating.
I understand it's intimidating
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for the average person to
understand what to do.
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So my mission now is to try to,
you know, make learning about
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metabolism, which I see is like
a broader umbrella under which
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nutrition and diet fall fun to
learn about.
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So people can actually engage
with hardcore metabolic science
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and not just get the platitudes
of what I used to think was
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healthy.
And I think what a lot of people
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still think is healthy.
What was the initial goal like
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with you taking the academic
path that you have before you
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were playing dwarf with the IBS?
Like what?
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What was the the end goal for
going the academic route that
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that you that you chose?
Like what were you planning to
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do with that as you into?
Your career I mean, imagine me
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as like a kid 5678 like I was
always super, super curious.
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Like, I'd go out into the the
yard to be a dead snake with a,
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you know, lump in its belly.
And even like 5 or 6, I'm like,
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I need to do a dissection.
I'd bring it in and it's like,
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is it pregnant?
Do snakes get pregnant like
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that?
How do snakes get pregnant?
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Because I've never seen a snake
penis.
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Like that was thoughts that went
through my mind at five years
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old.
And then you combine that with
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being, you know, in a medical
household.
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So both my parents are MD, pH,
DS.
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It's like the default.
You match up my level of science
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with living with medical
parents.
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And you know, when you have
parents that are in a certain
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career field, be it medicine or
the military, it's like you just
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you take that on as, you know,
something to aspire to,
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something that's noble.
And so I have had in my mind my
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entire life, I wanted to be a
doctor and I wanted to be a
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Doctor Who did science.
And the deeper you delve on that
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path, the more you get a
clarified picture of what
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respectable looks like.
You know, the professor who's
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gone through the, you know, top
trainings in terms of college,
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medical school, residency,
fellowship.
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You get the right grants, you
get the right, you know, you
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know, research partners,
publications in the right
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journals.
There's a very clear picture of
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what to do this the quote right
way looks like.
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So that was always the
aspiration because I thought
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it's how I could bring good to
the world.
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And even after I had my, my own
health experiences, you know, I
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had this lofty idea of, well,
maybe there's something's wrong
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with Western medicine, but to
change the system, you need to
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work from within the system.
And I have these privileges, you
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know, training at some of the
the oldest and most highly
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regarded by the public
institutions, although some of
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them are doing some not great
things for the legacies maybe,
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but nevertheless, like things
like Oxford and Harvard brands,
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they carry weight.
So I'm in a pretty particular
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position, but I won't get into
the details.
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But what I've realized is that
now, especially in in the twenty
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20s, there's a lot more impact
you can have directly through a
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bottom up grass roots approach
than you know, working from
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within the within the mainstream
with, you know, within the
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system.
I can work from without outside
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the system and get people
information now, get them
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enthused about metabolism,
metabolic health, and empower
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them to take control of their
own metabolic health and
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journey.
Even separate from changing the
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system from within, which is a
separate goal and one that it's
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a difficult thing to communicate
because they're just so much
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wrapped up into it, familial,
personal and academic.
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But like, the idea now of
actually changing the system is
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it didn't sound Herculean before
you know, it it I feel like it's
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next to impossible to truly do
if you don't have some sort of
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muscle from another angle.
So I have really loved getting
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into the public space really
over the last year or so and
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finding ways to reach out to
people, empower people, teach
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people and learn along the way.
It's been a lot of fun.
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Yeah, no, it's awesome.
It's funny because I too came
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from a family that was, you
know, steeped in conventional
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medicine.
My mom has always been in
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healthcare and she's a nurse
practitioner manager, went up
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the ladder within the hospital
setting.
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My dad's APHD biologist.
And you know, my, my upbringing
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it 5 or 6 years old was doing
full blown necropsies on
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different wildlife he harvested
for students at a farm to, you
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know, see the entire digestive
passage to everything.
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So like, that was what I was
subjected to as a kid, which
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brought with a ton of curiosity
and insight and just perspective
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effective.
But it is interesting because
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like, their knowledge of
nutrition is so predicated on
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what they went through.
I mean, it made part in part be
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from a generational standpoint.
Like they didn't grow up with
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social media.
They didn't grow up with people
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questioning the conventional
norms like we are with the
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advent of social media, the
Internet, and just the ease of
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information flow.
But it's funny because, you
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know, I started doing ketogenic
diet long before they were
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accepting of it.
They kind of, you know,
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discredited.
And then my mom started doing
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it.
She had a ton of benefits that
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came as a result.
My dad's still pretty skeptical,
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but I feel like this anecdotal
evidence can't be ignored, and
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then once enough people have
done it, most definitely can't
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be ignored.
So I think bringing or bridging
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the gap between what you're able
to do and how you're able to
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impact people at scale through
social media and just the
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stories you're able to share is
going to make a much more
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profound impact than one could
ever hope to from within the
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conventional system.
You said some things that
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definitely resonated with my own
background, especially with
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regards to your parents, because
as I mentioned, like both my
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00:13:48,120 --> 00:13:52,720
parents were very conventionally
trained and I think have a have
250
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an idea of science that a lot of
people have, which is like, you
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know, it's about the data, which
it is, it truly is.
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But when it comes to personal
decision making, it is really
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about the stories, right?
That's not something that can be
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discounted.
We as humans resonate with
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stories.
So it sounds like your mom
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really responded to your story.
And actually the same with my
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mom.
She's now a keto, and she
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adopted a ketogenic diet after
me because, you know, she saw
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how well it worked for me.
And she's reaped her own
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benefits, although they're
distinct.
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00:14:25,880 --> 00:14:28,400
So it really is the stories that
change people's minds.
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And, you know, that's something
that if you were to talk to me
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three years ago, I would have
discounted a little bit.
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I think the idea of anecdotes
has a, well, I know the term
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anecdotes has negative
connotation, but when we think
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about, you know, just raw data
like that doesn't, or just, you
267
00:14:51,880 --> 00:14:54,880
know, data sets, P values,
statistics, whatever, it doesn't
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resonate with people the same
way that stories do.
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And so I think what you need to
do when you're telling or you're
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teaching science, talking about
data, is you need to find a way
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to tell a story around the data.
Anybody that ever written a
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paper and gotten it published
even knows this, like you need
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to tell a story around the data.
And now that's a tricky thing
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because of course, in telling a
story around the data, you're
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always going to introduce
biases, you know, your
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interpretations based on your
framing.
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Like that's the nature of
things.
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So I think practically speaking,
we just need to acknowledge that
279
00:15:25,360 --> 00:15:32,360
science, while the scientific
method itself is, you know, cold
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00:15:32,360 --> 00:15:36,320
and direct and emotionless, the
body of science that results is
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00:15:36,320 --> 00:15:39,440
a function of humans telling
stories about what the data are
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00:15:39,440 --> 00:15:42,600
showing.
Yeah, and humans are, so it's
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not.
Bad.
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It's something we need to
acknowledge in order to deal
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with the practicalities that
arise, including the narratives
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that get propagated around
things like nutrition.
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00:15:49,720 --> 00:15:51,440
Yeah, 100%.
And nutrition is tricky, man,
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because humans are so we're,
we're so, we're so fickle.
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Like we with any other animal.
There's no debate as to what,
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you know, types of foods they
should consume, but there's such
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00:16:01,320 --> 00:16:04,280
a, you know, societal
standpoint, such an emotional
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00:16:04,280 --> 00:16:09,160
standpoint tie with food and
human consumption that is very
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triggering for people for
whatever reason.
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And it like I'm trying to bridge
the gap as I know you are as
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00:16:15,600 --> 00:16:18,200
well, because I, you know,
having been brought up in the
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scientific community, I do place
a lot of emphasis on quality
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00:16:22,680 --> 00:16:26,680
data, But I'm also trying to,
you know, take stock in the
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00:16:26,680 --> 00:16:29,560
anecdotal evidence and what is
sustainable and what is, you
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know, optimal from a health and
well-being and vitality
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00:16:32,040 --> 00:16:34,240
standpoint.
And oftentimes those don't sync
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00:16:34,240 --> 00:16:35,680
up.
So I'll bring people on the
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00:16:35,680 --> 00:16:39,600
podcast like the Lane Norton's
of the world as I respect their
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00:16:39,600 --> 00:16:43,240
opinion, their viewpoints, and
you know, some of the, the, the
304
00:16:43,400 --> 00:16:47,360
value they bring the table, but
not at the complete exclusion of
305
00:16:47,360 --> 00:16:50,040
this anecdotal evidence.
And I feel like there has to be
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00:16:50,040 --> 00:16:53,640
a way to, to mesh that together
as it, as it, you know, pertains
307
00:16:53,640 --> 00:16:59,360
to human consumption, because we
aren't Lab Rats in a controlled
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00:16:59,360 --> 00:17:00,840
feeding study.
We have all these other
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00:17:00,840 --> 00:17:02,840
variables at play and we have to
be realistic.
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00:17:04,079 --> 00:17:05,560
Yeah.
I think we can talk through now
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a framework of kind of how to do
that, reconcile the anecdotes
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with the data.
And part of that is just
313
00:17:13,240 --> 00:17:15,839
considering what data we have
and what data we don't.
314
00:17:16,359 --> 00:17:20,440
So for example, there are
interventions that have clearly
315
00:17:20,440 --> 00:17:23,839
worked for people or let's say
people report that they clearly
316
00:17:23,839 --> 00:17:26,520
work for people.
I'll use myself as an example.
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00:17:26,839 --> 00:17:29,360
There's no doubt in my mind that
ketogenic diet was highly
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00:17:29,360 --> 00:17:31,440
effective for putting my disease
into remission.
319
00:17:32,040 --> 00:17:34,040
That is my story.
It's the narrative I tell
320
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myself, but it's also backed
with my medical history.
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00:17:38,640 --> 00:17:40,880
I suffered and I suffered and
nothing was working.
322
00:17:40,880 --> 00:17:42,040
I tried a bunch of different
diets.
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00:17:42,040 --> 00:17:43,760
Nothing worked.
And I tried this and it worked.
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00:17:44,120 --> 00:17:46,160
It improved my symptoms.
My inflammatory markers went
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down, and on biopsy there was no
disease.
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So that's my narrative.
But if you look at the
327
00:17:52,320 --> 00:17:55,600
literature, can I say that there
are human randomized trials
328
00:17:55,600 --> 00:17:58,880
showing that my intervention
works for my use case, a
329
00:17:58,880 --> 00:18:00,760
ketogenic diet for inflammatory
bowel disease?
330
00:18:00,760 --> 00:18:04,480
The answer is no.
It doesn't mean it doesn't work.
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It just means we haven't
properly asked the questions and
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investigated it.
So I think sometimes people
333
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confuse absence of evidence with
evidence of absence and say this
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00:18:16,320 --> 00:18:19,880
isn't true because we don't have
data to say it's true when it's
335
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never really been investigated.
And on top of that, there are
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questions we just can't ask with
certain forms of investigation,
337
00:18:29,440 --> 00:18:33,000
say the human randomized control
trial, which is something that I
338
00:18:33,000 --> 00:18:35,280
think a lot of people point to
is the quote gold standard,
339
00:18:35,280 --> 00:18:37,800
right?
But not all investigations lend
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00:18:37,800 --> 00:18:41,120
themselves to human RC TS.
So we really just have to cobble
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00:18:41,120 --> 00:18:46,880
together the data we have access
to be that human RC TS and
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Cochrane reviews or just
biologic possibility in animal
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studies.
And then I think use those to
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00:18:55,520 --> 00:18:58,880
frame the stories we we are
hearing and we are telling each
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other.
And if anecdotes are arising
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00:19:01,160 --> 00:19:06,160
that cut against the data where
there are conflict, I think then
347
00:19:06,160 --> 00:19:09,400
it's appropriate to ask, are
there other things contributing
348
00:19:09,400 --> 00:19:13,760
to this story where, you know,
the the biological reality could
349
00:19:13,760 --> 00:19:15,920
be divergent from the narrative
that a person is telling
350
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themselves?
Or is there something new and
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00:19:19,160 --> 00:19:21,800
unique to learn here?
And at the end of the day, I
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00:19:21,800 --> 00:19:23,560
think we can have all the
discussions about what the
353
00:19:23,560 --> 00:19:28,120
published literature say.
Well, also acknowledging and
354
00:19:28,120 --> 00:19:32,600
celebrating individuals and
their own healthcare journeys.
355
00:19:32,600 --> 00:19:34,720
I mean, like, personally, one of
the reasons I love metabolic
356
00:19:34,720 --> 00:19:36,800
health is the proof is in the
pudding.
357
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Your biomarkers, how you're
doing in terms of your health.
358
00:19:40,200 --> 00:19:43,600
Like if you're doing great, I do
not give a crap how you got
359
00:19:43,600 --> 00:19:44,520
there.
I don't care if it was
360
00:19:44,520 --> 00:19:46,160
carnivore.
I don't care if it was vegan.
361
00:19:46,160 --> 00:19:50,720
I don't care if it was eating
McDonald's patties and Wendy's
362
00:19:50,720 --> 00:19:53,200
Frosties.
I think Wendy's make Frosties,
363
00:19:54,320 --> 00:19:55,920
one of those ice cream milkshake
things.
364
00:19:56,240 --> 00:19:57,840
Point being, I mean, I think
that's unlikely.
365
00:19:57,840 --> 00:20:00,960
But like, if you are doing well,
that's all that really matters.
366
00:20:01,200 --> 00:20:05,160
And all we can do is look at the
literature and kind of inform
367
00:20:05,240 --> 00:20:08,840
best practices and come up with
ideas about how to get people
368
00:20:08,840 --> 00:20:10,680
there.
And it's a fun academic
369
00:20:10,680 --> 00:20:12,280
exercise.
But for the individual, at the
370
00:20:12,280 --> 00:20:15,120
end of the day, all that matters
is their story.
371
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Their n = 1.
Yeah, I completely agree.
372
00:20:17,440 --> 00:20:20,400
And I feel like as more time
passes, we'll have more solid
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data to lean on.
And I feel like there there's so
374
00:20:24,080 --> 00:20:28,520
much that is left, there's so
much lacking in that department,
375
00:20:28,640 --> 00:20:31,000
especially as it pertains to
performance athletes.
376
00:20:31,000 --> 00:20:33,920
I mean, I never, I didn't get
into keto because of some
377
00:20:33,960 --> 00:20:35,720
ailment or disease or anything
like that.
378
00:20:35,720 --> 00:20:38,440
I came to it honestly because I
had a negative relationship with
379
00:20:38,440 --> 00:20:40,280
food, eating high carbohydrate
diets.
380
00:20:40,680 --> 00:20:43,160
But I love the sport of
bodybuilding, which is what led
381
00:20:43,160 --> 00:20:45,760
to the high carbohydrate diet.
So I wanted to find a way to
382
00:20:45,760 --> 00:20:48,720
compete at a competitive level
in the complete absence of
383
00:20:48,720 --> 00:20:50,400
carbs.
And I got a ton of negative push
384
00:20:50,400 --> 00:20:52,880
back there.
And everybody was just, you
385
00:20:52,880 --> 00:20:56,560
know, suggesting that that was
not even feasible in the context
386
00:20:56,560 --> 00:20:59,160
of a kid in doing that.
So I was, you know, I, I love as
387
00:20:59,160 --> 00:21:03,280
you do, proving people wrong.
So that's what I set out to do.
388
00:21:03,280 --> 00:21:06,400
And lo and behold, it worked
beautifully and I've kind of
389
00:21:06,400 --> 00:21:08,840
staked my, you know, flag in the
ground.
390
00:21:08,880 --> 00:21:10,080
And that's the hill that I'm
dying on.
391
00:21:10,080 --> 00:21:14,000
That performance not can only
maintain, but honestly, you
392
00:21:14,000 --> 00:21:16,560
know, outperform those with
carbohydrate dependent approach,
393
00:21:16,560 --> 00:21:20,000
especially in the long term.
Play it because you're looking
394
00:21:20,000 --> 00:21:22,640
at people now that are, you
know, taking in performance
395
00:21:22,640 --> 00:21:24,080
enhancing drugs.
Obviously that's a whole another
396
00:21:24,080 --> 00:21:27,360
world in and of itself, but you
see all these athletes that just
397
00:21:27,360 --> 00:21:30,640
really start to dwindle as time
goes on.
398
00:21:30,640 --> 00:21:33,640
And I'm, I'm excited to see what
I'm performing like when I'm 73
399
00:21:33,640 --> 00:21:36,640
years old, following this way of
eating, you know, indefinitely
400
00:21:36,640 --> 00:21:39,680
until then.
No, no, no, your, your journey
401
00:21:39,680 --> 00:21:42,520
is amazing.
And actually I, I need to ask
402
00:21:42,520 --> 00:21:44,240
and other people have asked me
to ask.
403
00:21:45,560 --> 00:21:48,920
One thing I really like about
you is you.
404
00:21:48,960 --> 00:21:52,240
You post pictures very like
authentically and transparently,
405
00:21:52,240 --> 00:21:57,480
both in like the extreme cutting
and bulking phases, which if
406
00:21:57,480 --> 00:22:00,680
people look at your socials like
there's a huge discrepancy
407
00:22:00,680 --> 00:22:04,160
there.
The, the reason I like that is
408
00:22:04,400 --> 00:22:07,920
one anybody who's been like a
physique athlete or even
409
00:22:07,920 --> 00:22:12,720
recreationally understands that,
like, you know, those optimal
410
00:22:13,320 --> 00:22:17,360
or, you know, based on societal
standards, optimal male physique
411
00:22:17,360 --> 00:22:21,680
photos are a function of like
pristine timing, hydration
412
00:22:21,680 --> 00:22:23,480
status, lighting, all these
things.
413
00:22:25,720 --> 00:22:29,560
And it's phasic.
And so first I want to apply to
414
00:22:29,560 --> 00:22:31,720
you from, you know, posting at
both sides of the spectrum, but
415
00:22:31,720 --> 00:22:36,680
also just ask out of my own
curiosity, what is the time lag
416
00:22:37,360 --> 00:22:41,640
between, say, like if you post a
bulking photo and then your most
417
00:22:41,640 --> 00:22:44,560
cut photo, is that like months
apart, weeks apart?
418
00:22:44,800 --> 00:22:47,600
Is that a function of actual
body fat loss or hydration
419
00:22:47,600 --> 00:22:51,160
status?
Like what does the transition
420
00:22:51,160 --> 00:22:54,680
from like that bulk photo to
that cut photo really look like?
421
00:22:55,160 --> 00:22:58,320
Yeah, great question.
So I honestly do not cut water
422
00:22:58,320 --> 00:23:00,560
like a lot of competitors do.
And I think that's one of the
423
00:23:00,640 --> 00:23:03,800
movies of phonic ketogenic prep
protocol is I don't have to
424
00:23:03,800 --> 00:23:07,160
dehydrate.
So I'm fully hydrated in both an
425
00:23:07,160 --> 00:23:09,360
offseason photo and a
competition photo.
426
00:23:10,000 --> 00:23:12,120
So that's not a variable at play
there.
427
00:23:12,400 --> 00:23:16,520
As far as the time, my last prep
was 33 weeks.
428
00:23:16,520 --> 00:23:21,120
I probably looked my best at 27
weeks, which is when I earned
429
00:23:21,120 --> 00:23:24,440
the pro card on my third of five
shows this past season.
430
00:23:25,200 --> 00:23:28,840
So 27 weeks from peak bulk to
peak cut.
431
00:23:29,440 --> 00:23:33,120
I could have done it faster, but
by going more slowly I preserved
432
00:23:33,120 --> 00:23:36,640
more lean tissue and overall
health and well-being.
433
00:23:37,200 --> 00:23:39,360
So that's about 27 weeks
roughly.
434
00:23:40,040 --> 00:23:41,720
Yeah.
Do you ever get your lipids
435
00:23:41,720 --> 00:23:45,040
tested when you're at a cut
versus bulk?
436
00:23:45,320 --> 00:23:47,240
Yeah, I get all my markers
tested.
437
00:23:47,800 --> 00:23:49,880
I do.
That's usually about every three
438
00:23:49,880 --> 00:23:53,600
months as I'm going through a
building phase, a peak cut and
439
00:23:53,600 --> 00:23:56,480
then back to reverse dieting and
finding that, you know, slight
440
00:23:56,480 --> 00:23:59,480
surplus to operate at for
extended periods of time.
441
00:23:59,480 --> 00:24:01,520
So I'm getting my lipids tested
through, I'm getting my hormones
442
00:24:01,520 --> 00:24:05,600
tested through all Now when you
take like naturally, when you
443
00:24:05,960 --> 00:24:10,440
get that lean testosterone for
instance, is, is very correlated
444
00:24:10,440 --> 00:24:14,520
to overall body fat levels.
So when you drop below 5% body
445
00:24:14,520 --> 00:24:16,920
fat as a male, your testosterone
plummets.
446
00:24:16,920 --> 00:24:21,840
I mean, I think at my leanest of
3.9%, my testosterone was like
447
00:24:22,240 --> 00:24:26,880
89 or something scary low.
Now that's obviously not healthy
448
00:24:26,880 --> 00:24:29,480
or optimal.
So as I put on a healthy amount
449
00:24:29,480 --> 00:24:32,440
of body fat in the building
phase, that returns to a
450
00:24:32,440 --> 00:24:35,760
healthy, normal baseline.
But yeah, all these I try to be
451
00:24:35,760 --> 00:24:38,400
very transparent with both the
build and the cut because I
452
00:24:38,400 --> 00:24:41,600
don't want to glorify just the
cut because being that lean for
453
00:24:41,600 --> 00:24:44,160
that long is not healthy.
I know.
454
00:24:44,400 --> 00:24:46,520
And I think it really effects
young men.
455
00:24:46,520 --> 00:24:49,200
Like I'm really I'm 28.
Remember how old you are?
456
00:24:49,800 --> 00:24:52,240
32 I'll be 33 next month.
Right.
457
00:24:52,240 --> 00:24:55,400
So we're like, we're both on the
younger and where we, I mean,
458
00:24:55,600 --> 00:25:00,680
maybe just missed the access of
social media to like, you know,
459
00:25:01,360 --> 00:25:05,600
preteens.
I just think about how it would
460
00:25:05,600 --> 00:25:08,520
have affected my psyche when I
was going through like puberty
461
00:25:08,960 --> 00:25:11,040
and like the 5th and 6th grade.
I hit people to be a little bit
462
00:25:11,040 --> 00:25:15,840
early to have access to what
kids have access to now.
463
00:25:15,880 --> 00:25:19,920
I mean, people talk a lot about
societal standards for women,
464
00:25:20,080 --> 00:25:23,960
but I think, you know, there's
an effect on on men too.
465
00:25:23,960 --> 00:25:26,840
So I think transparency around
that, especially if people use
466
00:25:26,840 --> 00:25:29,440
like there's some, you know,
people, especially people like
467
00:25:29,440 --> 00:25:32,880
actors, they're prepping for a
role be like Crim's Hems, Chris
468
00:25:32,880 --> 00:25:35,640
Hemsworth or Thor or something
like it clearly use PEDs.
469
00:25:35,640 --> 00:25:37,720
I think that's fine.
It's part of the the journey.
470
00:25:37,720 --> 00:25:41,080
He's preparing for his job.
You're preparing for your sport.
471
00:25:41,080 --> 00:25:45,280
I don't know if you use anything
but there just doesn't seem to
472
00:25:45,280 --> 00:25:47,920
be a lot of transparency in
discussion about like what a
473
00:25:47,920 --> 00:25:51,960
natural male physique is or what
actually feels good because
474
00:25:51,960 --> 00:25:54,800
people see you at that level.
Or like I've been super lean.
475
00:25:55,000 --> 00:25:57,880
I don't know if I've ever run
DEXA at least in 3.9%.
476
00:25:57,880 --> 00:26:01,320
But like I also know that on my
leanest I feel like shit and
477
00:26:01,320 --> 00:26:04,360
usually I'm there incidentally,
not necessarily like willingly
478
00:26:04,360 --> 00:26:07,280
for various reasons and
discussion around that I just
479
00:26:07,280 --> 00:26:09,440
think is valuable.
But that was sidetracked from
480
00:26:09,440 --> 00:26:13,440
the question I wanted to ask
about the the labs lean versus
481
00:26:13,440 --> 00:26:15,240
bolt.
What do your lipids look like if
482
00:26:15,240 --> 00:26:17,720
I may ask?
I would assume your LDL jumps
483
00:26:17,720 --> 00:26:20,520
when you're cutting and drops
when you're bolting.
484
00:26:20,520 --> 00:26:21,600
Is that accurate?
What?
485
00:26:21,640 --> 00:26:22,560
What was that last part?
You.
486
00:26:22,960 --> 00:26:25,720
Assumed your LDL, your LDL
cholesterol, I mean, I mean,
487
00:26:25,720 --> 00:26:27,760
we'll probably talk a little bit
about cholesterol and you know,
488
00:26:27,760 --> 00:26:29,800
a lot of my research around lean
mass hyper responders.
489
00:26:29,800 --> 00:26:31,200
I never asked you about your
lipids.
490
00:26:31,360 --> 00:26:33,840
Yeah, I mean, actually.
LDL jump when you're cutting.
491
00:26:34,440 --> 00:26:38,240
Actually there's like a, it's
like a weird bell curve.
492
00:26:38,240 --> 00:26:41,360
So like when I am in a peak bulk
and I'm really trying to be
493
00:26:41,360 --> 00:26:43,800
aggressive with the surplus, it
is higher.
494
00:26:43,800 --> 00:26:47,000
And then when I'm in a, you
know, deficit with it's
495
00:26:47,000 --> 00:26:50,680
basically on the extremes.
So like as I'm dieting down LDL
496
00:26:50,680 --> 00:26:54,280
drops typically, but you know,
when I'm at that, you know,
497
00:26:54,280 --> 00:26:56,760
peaking moment, it, it can be
all over the place.
498
00:26:56,800 --> 00:26:59,880
And it's very highly dependent
upon what I'm eating then as
499
00:26:59,880 --> 00:27:03,080
well.
Because like I'll have refeed
500
00:27:03,080 --> 00:27:06,120
meals in at that point which are
predominantly higher in fat.
501
00:27:06,680 --> 00:27:09,280
So it just depends on when I get
the labs drawn based off of
502
00:27:09,280 --> 00:27:14,000
where I'm at in the prep cycle.
But my, my standard lipid panels
503
00:27:14,000 --> 00:27:18,240
are typically around shooting
from memory here, like my trigs
504
00:27:18,440 --> 00:27:22,480
will get around 30 or 40.
HDL is like 120.
505
00:27:22,480 --> 00:27:26,040
I believe.
LDL is typically between 120 and
506
00:27:26,040 --> 00:27:30,040
200, give or take.
OK, so you can approach sounds
507
00:27:30,040 --> 00:27:33,240
like clean mass type of
responder Physiology especially
508
00:27:33,240 --> 00:27:36,200
with the HDL at high, I mean do
you remember what it was on a
509
00:27:36,200 --> 00:27:38,400
mixed diet?
I assume it was much lower.
510
00:27:38,800 --> 00:27:42,720
Yeah, the HDL was much lower.
I, I didn't get labs drawn that
511
00:27:42,720 --> 00:27:44,120
frequently when I was on a mixed
diet.
512
00:27:44,120 --> 00:27:46,480
I mean, it was a long time ago
when I was eating carbohydrates,
513
00:27:47,040 --> 00:27:51,040
but this is honestly the best.
Myeliputs have been honestly the
514
00:27:51,040 --> 00:27:52,720
best.
All of my markers have been
515
00:27:52,800 --> 00:27:56,320
since doing a ketogenic diet.
I think it gets better the
516
00:27:56,320 --> 00:27:59,120
longer you're doing it.
I'm kind of like a lot of people
517
00:27:59,120 --> 00:28:02,240
talk about metabolic flexibility
and cycling carbs in, but I've
518
00:28:02,240 --> 00:28:06,760
kind of fallen to the belief
that your body is very
519
00:28:06,760 --> 00:28:07,920
adaptable.
It's going to make the most of
520
00:28:07,920 --> 00:28:10,120
whatever you give it.
And if you're staying strictly
521
00:28:10,120 --> 00:28:13,680
ketogenic, your body's metabolic
pathways up regulate to optimize
522
00:28:13,680 --> 00:28:16,560
around fat metabolism.
And if you do that for long
523
00:28:16,560 --> 00:28:19,400
enough, everything improves for
that function.
524
00:28:19,400 --> 00:28:22,520
So I have no plans to deviate
because my health has never been
525
00:28:22,520 --> 00:28:25,160
better.
Awesome, awesome, awesome.
526
00:28:26,440 --> 00:28:32,280
So 100%, man, I, I've got like a
million different questions upon
527
00:28:32,360 --> 00:28:34,640
the different experiments you've
done because you've done so many
528
00:28:34,640 --> 00:28:35,640
of them.
I've lost track of them all.
529
00:28:35,640 --> 00:28:38,680
But my introduction to, like I
said in the beginning was that
530
00:28:38,680 --> 00:28:42,480
Oreo cookie versus statin study.
But since then you've also, I
531
00:28:42,480 --> 00:28:44,520
mean, you, you sent me a post on
Instagram today about you
532
00:28:44,520 --> 00:28:47,480
getting a year's supply of eggs.
So we can talk about that.
533
00:28:47,720 --> 00:28:52,520
You also made a post that I saw
about the satiety per calorie
534
00:28:52,520 --> 00:28:55,680
model, which I've I've got some
thoughts on as well.
535
00:28:56,440 --> 00:28:58,000
OK, Whatever you want to talk
about man.
536
00:28:58,000 --> 00:29:00,160
Like I want the floor to be used
because I want to talk about
537
00:29:00,160 --> 00:29:02,960
whatever is exciting you at the
moment and where you think you
538
00:29:02,960 --> 00:29:05,160
want to take the conversation.
Sure.
539
00:29:05,160 --> 00:29:08,000
I mean, Oreo versus Staten's
always a fun thing to start with
540
00:29:09,400 --> 00:29:12,880
and we can roll from there.
But so this was a project I did.
541
00:29:12,880 --> 00:29:14,640
A lot of people listening
probably already know about it,
542
00:29:14,640 --> 00:29:18,400
so I'll go through it quickly.
But I want to bring attention.
543
00:29:18,400 --> 00:29:20,520
The purpose was to bring
attention to a lot of work we've
544
00:29:20,520 --> 00:29:22,640
been doing.
We have now 10 published papers
545
00:29:23,240 --> 00:29:27,880
on this lean mass hyper
responder phenotype, which is to
546
00:29:27,880 --> 00:29:32,240
cut the jargon, when lean people
tend to go low carb, they tend
547
00:29:32,240 --> 00:29:35,640
to see these increases in LDL
cholesterol, which some people
548
00:29:35,640 --> 00:29:38,720
call the bad cholesterol, along
with increases in HDL
549
00:29:38,720 --> 00:29:41,280
cholesterol and low
triglycerides, which is a
550
00:29:41,280 --> 00:29:44,280
pattern that appears in and
sounds like in you as well,
551
00:29:44,280 --> 00:29:46,560
especially when you're lean.
The high LDL, the high HDL and
552
00:29:46,560 --> 00:29:49,560
low triglycerides.
This is really important to
553
00:29:49,560 --> 00:29:53,160
study because ketogenic diets
are gaining popularity for a
554
00:29:53,160 --> 00:29:56,360
whole host of conditions,
inflammatory conditions, mental
555
00:29:56,360 --> 00:29:58,080
health conditions, neurological
disorders.
556
00:29:58,520 --> 00:30:02,720
But when it comes to clinical
medicine, a major sticking
557
00:30:02,720 --> 00:30:06,840
point, an obstacle remains
cholesterol, where some people
558
00:30:08,240 --> 00:30:11,120
we'll see increases in LDL and
that scares patients.
559
00:30:11,120 --> 00:30:15,480
It scares doctors because of
what we've been told around LDL
560
00:30:15,480 --> 00:30:18,760
cholesterol and markers like
Applebee for those who are a
561
00:30:18,760 --> 00:30:20,240
little bit more cholesterol
versed.
562
00:30:21,080 --> 00:30:24,400
So it's become important for my
colleagues and I to kind of
563
00:30:24,400 --> 00:30:29,240
figure out why lean people see
the increases in LDL when they
564
00:30:29,240 --> 00:30:31,840
go low carb.
And indeed, it does appear
565
00:30:31,840 --> 00:30:35,440
particularly in lean people.
So we, for example, did one meta
566
00:30:35,440 --> 00:30:37,920
analysis of human randomized
control trials.
567
00:30:37,920 --> 00:30:41,720
This was led by my friend Adrian
and published in the American
568
00:30:41,720 --> 00:30:44,720
Journal of Clinical Nutrition.
And what we found was an inverse
569
00:30:44,720 --> 00:30:48,840
association between LDL and BMI
such that when people went low
570
00:30:48,840 --> 00:30:51,880
carb, the leaner you were, the
higher your BMI went.
571
00:30:52,440 --> 00:30:55,840
I'm sorry, the leaner you were,
the higher LDL ones, lean LDMI,
572
00:30:56,200 --> 00:30:58,640
the leaner you were, the higher
LDL went.
573
00:30:58,640 --> 00:31:01,720
And actually, if you broke up
and did meta analysis by each of
574
00:31:01,720 --> 00:31:06,320
the BMI categories, only lean
people with BMI below 25, only
575
00:31:06,320 --> 00:31:10,080
that group saw increases in LDL
who had overweight or obesity.
576
00:31:10,080 --> 00:31:11,600
Those groups did not see
increases.
577
00:31:11,600 --> 00:31:13,520
Class 2 obesity actually saw
decreases.
578
00:31:14,520 --> 00:31:18,960
So this is starting to, you
know, explain a source of
579
00:31:18,960 --> 00:31:22,440
heterogeneity in the data where
it's like, OK, this is
580
00:31:22,440 --> 00:31:25,680
interesting for the people that
have the big jumps in LDL.
581
00:31:25,680 --> 00:31:29,120
It doesn't appear to be things
like, you know, even genetics or
582
00:31:29,120 --> 00:31:31,880
saturated fat as much it is as
it is being leaned.
583
00:31:31,880 --> 00:31:35,720
And that's odd.
So we have a model to explain
584
00:31:35,720 --> 00:31:37,280
why that is.
It's called a lipid energy
585
00:31:37,280 --> 00:31:39,520
model.
We can get into the nitty gritty
586
00:31:39,520 --> 00:31:42,320
around it, but the lipid energy
model makes certain predictions.
587
00:31:42,320 --> 00:31:46,560
And one of the most rudimentary
predictions of our model is
588
00:31:47,040 --> 00:31:50,960
because it appears that when
lean people go low carb, they
589
00:31:50,960 --> 00:31:57,560
really shift over fat burning.
Well and the fat trafficking
590
00:31:57,560 --> 00:31:59,400
system depends on these
particles.
591
00:31:59,680 --> 00:32:04,440
LDL goes up, but if you
reintroduce carbs, then you
592
00:32:04,440 --> 00:32:09,440
remove the need for this liquid
energy model flywheel to spin
593
00:32:10,120 --> 00:32:14,040
and the phenotype reverts.
And the way to say that is add
594
00:32:14,040 --> 00:32:16,520
back carbs.
LDL goes down if you're a lean
595
00:32:16,520 --> 00:32:19,200
mass hyper responder.
This is interesting Physiology,
596
00:32:19,200 --> 00:32:23,680
but I wanted to get people to
engage with it who might not
597
00:32:24,840 --> 00:32:28,480
otherwise have been aware of it.
And so I kind of had to envision
598
00:32:29,520 --> 00:32:32,320
what was the most provocative
way I could demonstrate a
599
00:32:32,320 --> 00:32:34,960
principle of this model.
And one way to do that would be
600
00:32:34,960 --> 00:32:38,320
to lower my LDL with an
unhealthy food, an unhealthy
601
00:32:38,320 --> 00:32:40,480
food with carbs.
And I chose Oreo cookies because
602
00:32:40,480 --> 00:32:44,160
it's simply I could not come up
with a better branded unhealthy
603
00:32:44,160 --> 00:32:47,600
food that everybody would know.
And I predicted that it would
604
00:32:47,600 --> 00:32:49,920
lower my cholesterol, LDL
cholesterol.
605
00:32:50,480 --> 00:32:53,040
And because I know how to down
my IS and cross my T's as a
606
00:32:53,040 --> 00:32:56,960
researcher, I did it as a
rigorous crossover trial, which
607
00:32:56,960 --> 00:32:59,200
means I did the Oreo
intervention.
608
00:32:59,200 --> 00:33:02,760
But I also had a washout period
where I reverted and got back to
609
00:33:02,760 --> 00:33:08,760
my like, you know, set point for
cholesterol when I'm on keto.
610
00:33:08,760 --> 00:33:13,280
And then I tried a statin, a
high dose, high intensity
611
00:33:13,280 --> 00:33:16,720
statin, which was a 20
milligrams of rosuvastatin,
612
00:33:16,800 --> 00:33:20,960
which is Crestor for six weeks.
And the experiment was, let's
613
00:33:20,960 --> 00:33:25,520
see what does better at lowering
my cholesterol, Oreo cookies or
614
00:33:25,520 --> 00:33:27,800
standard of care high dose
statin therapy.
615
00:33:28,400 --> 00:33:30,840
I went to Harvard's
Institutional Review Board.
616
00:33:31,360 --> 00:33:34,720
Their IRB got an exemption.
I collaborated with
617
00:33:34,720 --> 00:33:38,280
lipidologists and cardiologists
and my primary care provider who
618
00:33:38,280 --> 00:33:40,640
was ordering all my labs.
And the results were that the
619
00:33:40,640 --> 00:33:43,960
Oreo cookies, the Oreo cookie
intervention, which was a pure
620
00:33:43,960 --> 00:33:46,080
addition, I was not reducing my
fat.
621
00:33:46,080 --> 00:33:49,080
In fact, since Oreos have fat
and saturated fat, that's
622
00:33:49,080 --> 00:33:51,760
actually increasing my fat.
But I was adding in carbs.
623
00:33:52,520 --> 00:33:57,560
And what happened was the Oreos
reduced my LDL by 71%, which is
624
00:33:57,600 --> 00:34:00,000
dramatic, more than you could
expect from any medication.
625
00:34:00,000 --> 00:34:04,320
And the statins reduce my LDL by
32.5% over actually three times
626
00:34:04,320 --> 00:34:07,520
longer a time period.
So in the end, the Oreos were
627
00:34:07,520 --> 00:34:11,960
twice as potent as at dropping
my LDL as the statin in one
628
00:34:11,960 --> 00:34:16,159
third time, which was a
metabolic demonstration that was
629
00:34:16,159 --> 00:34:18,800
effective in its purpose,
getting people to have
630
00:34:18,800 --> 00:34:22,080
discussions with us about the
broader literature around Lee
631
00:34:22,080 --> 00:34:24,840
Max cyber responders.
I'm assuming the pharma
632
00:34:24,840 --> 00:34:27,679
companies were probably not
ecstatic about this study.
633
00:34:29,120 --> 00:34:32,120
I mean, they didn't reply.
I, I, I think it made waves.
634
00:34:32,120 --> 00:34:36,040
It did not make waves so big
that Pfizer is coming after me.
635
00:34:37,760 --> 00:34:40,880
So no, I have not gotten any
emails from Pfizer or anything.
636
00:34:40,880 --> 00:34:42,840
I mean, I'm humble in what this
is.
637
00:34:42,840 --> 00:34:44,719
I mean, it wasn't N = 1.
It's not kind of changing
638
00:34:44,719 --> 00:34:46,400
guidelines or anything, and they
know that.
639
00:34:46,719 --> 00:34:50,760
But it did stimulate
conversation, got word of our
640
00:34:50,760 --> 00:34:54,080
work out there, helped us build
more collaborations and gain
641
00:34:54,080 --> 00:34:56,560
more resources to do future
studies that are under way.
642
00:34:57,160 --> 00:34:59,200
Out of curiosity, what were some
or any?
643
00:34:59,200 --> 00:35:01,240
Were there any symptoms that you
had while you were doing the
644
00:35:01,400 --> 00:35:05,520
high dose statin?
Yeah, I had, I mean, myalgias
645
00:35:05,520 --> 00:35:08,200
are very common.
So like muscle pains and cramps
646
00:35:08,200 --> 00:35:11,720
in my lower legs.
This was a high dose.
647
00:35:11,720 --> 00:35:15,080
Generally people would not start
on 20 milligrams of Crestor.
648
00:35:15,080 --> 00:35:19,960
It's pretty high.
And that occurred with some
649
00:35:19,960 --> 00:35:24,560
increase in my CPK, so a marker
of muscle damage.
650
00:35:25,000 --> 00:35:28,760
So there might have been a
little bit of cramps and, you
651
00:35:28,760 --> 00:35:30,280
know, increasing this marker of
muscle damage.
652
00:35:30,280 --> 00:35:33,240
It wasn't very high.
It was it was low enough that
653
00:35:33,240 --> 00:35:34,960
actually we noticed this early
on in the study.
654
00:35:34,960 --> 00:35:36,680
And I talked to a lipidologist
colleague and he's like, look,
655
00:35:37,200 --> 00:35:39,920
this is uncomfortable.
But actually I had a patient on
656
00:35:39,920 --> 00:35:41,160
this.
I don't know that I'd keep him
657
00:35:41,160 --> 00:35:43,040
on it for life at these levels,
but it was safe.
658
00:35:43,040 --> 00:35:46,320
Like it wasn't at risk of going
into rhabdomyolysis or anything
659
00:35:46,320 --> 00:35:48,400
like that.
But I had some, I had some
660
00:35:48,400 --> 00:35:49,800
muscle pains.
It was pretty moderate.
661
00:35:49,840 --> 00:35:51,680
Quite honestly.
The Oreos had worse side
662
00:35:51,680 --> 00:35:53,760
effects.
Like my stomach was just not
663
00:35:53,760 --> 00:35:58,640
happy with me.
But yeah, you know, I think to
664
00:35:58,640 --> 00:36:01,080
kind of put this in a clinical
context, if this were to happen,
665
00:36:01,400 --> 00:36:04,080
a patient were to start on this
high dose of statin therapy and
666
00:36:04,080 --> 00:36:06,680
have these symptoms, what will
probably happen is their
667
00:36:06,680 --> 00:36:10,560
clinician would just decrease
the dose because you can get
668
00:36:11,280 --> 00:36:14,840
most of the effect for LDL
lowering for a statin at lower
669
00:36:14,840 --> 00:36:16,920
doses.
And I just started with a high
670
00:36:16,920 --> 00:36:19,440
dose because I wanted the
highest intensity protocol I
671
00:36:19,440 --> 00:36:23,000
possibly could have because I'm
a harder like you, so.
672
00:36:23,800 --> 00:36:26,080
Totally.
So a lot of people like speaking
673
00:36:26,080 --> 00:36:28,560
from a layperson standpoint,
they're concerned about going
674
00:36:28,560 --> 00:36:31,400
keto for fear of what the
mainstream media has inundated
675
00:36:31,400 --> 00:36:34,600
them with over the years as to,
you know, high fat clogging the
676
00:36:34,600 --> 00:36:37,640
arteries, the need for a statin.
They'll often times notice an
677
00:36:37,640 --> 00:36:40,800
increase in LDL or cholesterol,
total cholesterol, you know,
678
00:36:40,800 --> 00:36:44,240
early on.
And then they'll go to a doctor,
679
00:36:44,360 --> 00:36:46,960
primary care, and they'll
automatically always push them
680
00:36:46,960 --> 00:36:50,120
towards a statin.
So this study just basically
681
00:36:50,480 --> 00:36:54,200
forces them to question the
rationale behind all of this.
682
00:36:55,480 --> 00:36:59,600
You know, I, I don't put in, in
the Orient study any value on
683
00:36:59,600 --> 00:37:02,880
LDL or statics like that is not
the place of this study.
684
00:37:04,160 --> 00:37:09,680
Inevitably people are going to
try to tie that in, and the
685
00:37:09,680 --> 00:37:12,960
reason I think they do so is
because what inevitably is is,
686
00:37:13,160 --> 00:37:17,480
or what's being presented here
is an inevitable and unavoidable
687
00:37:17,480 --> 00:37:20,920
tension where we have what we
all agree, pretty much all agree
688
00:37:21,360 --> 00:37:24,680
is an unhealthy intervention.
Adding Oreo cookies onto your
689
00:37:24,680 --> 00:37:27,040
standard diet is not a healthy
thing.
690
00:37:27,040 --> 00:37:28,880
I don't think anybody believes
it is.
691
00:37:28,880 --> 00:37:32,200
But my LDL cholesterol went
down, which a lot of people
692
00:37:32,200 --> 00:37:33,400
would presume to be a good
thing.
693
00:37:33,400 --> 00:37:38,200
So very, very simply, you have a
bad intervention and a good
694
00:37:38,200 --> 00:37:42,360
outcome, and that creates a
paradox attention, a cognitive
695
00:37:42,360 --> 00:37:45,920
dissonance that a lot of people
are uncomfortable sitting with.
696
00:37:46,600 --> 00:37:50,640
And that's not to put any value
on statins or any value on LVL.
697
00:37:50,760 --> 00:37:53,560
That's just to say, here's
something curious and if it's
698
00:37:53,560 --> 00:37:56,320
curious to you and appears
paradoxical to you, that means
699
00:37:56,320 --> 00:37:59,640
there's something you or we
don't understand.
700
00:38:00,120 --> 00:38:02,280
And I want people to sit with
that curiosity and get
701
00:38:02,280 --> 00:38:05,080
inquisitive and then go down the
rabbit hole of our literature
702
00:38:05,080 --> 00:38:10,160
and start asking the right
questions to speak quickly on,
703
00:38:10,200 --> 00:38:13,040
you know, that that patient
scenario, the doctor patient
704
00:38:13,040 --> 00:38:15,920
scenario patient goes keto and
their LDL goes up and it's all
705
00:38:15,920 --> 00:38:18,400
scary.
What I would say is
706
00:38:18,640 --> 00:38:21,720
reassuringly, we now have
multiple studies showing that if
707
00:38:21,720 --> 00:38:25,040
somebody is using a ketogenic
diet for like type 2 diabetes,
708
00:38:25,040 --> 00:38:29,640
obesity or overweight, they will
tend not to see increases in LDL
709
00:38:30,080 --> 00:38:32,880
and actually tend to see
improvements in overall
710
00:38:32,880 --> 00:38:36,280
cardiovascular risk markers,
including markers like
711
00:38:36,280 --> 00:38:39,960
triglycerides and HDL and LDL
and Apple B.
712
00:38:40,640 --> 00:38:45,360
Sometimes there are transient
blips up in LDL, but typically
713
00:38:45,360 --> 00:38:48,920
the LDL particle count in the
Apple B will actually go down
714
00:38:49,240 --> 00:38:52,280
and risk will overall be reduced
in people who are starting from
715
00:38:52,280 --> 00:38:54,840
a place of metabolic dysfunction
with overweight or obesity,
716
00:38:54,840 --> 00:38:58,920
which is actually most people.
Which is also probably why in
717
00:38:58,920 --> 00:39:01,560
general, if you look at all the
studies, you don't see increases
718
00:39:01,560 --> 00:39:05,840
in LTL on keto diets because
those people have overweight or
719
00:39:05,840 --> 00:39:08,920
obesity.
But you do have this subset who
720
00:39:08,920 --> 00:39:11,240
are basically lean and
metabolically healthy who see
721
00:39:11,240 --> 00:39:15,520
the increases.
Now these people can be adopting
722
00:39:15,520 --> 00:39:18,600
ketogenic diets for a variety of
reasons, focusing on those who
723
00:39:18,600 --> 00:39:21,360
are using for them for medical
purposes, ketogenic diet.
724
00:39:21,360 --> 00:39:24,080
For medical purposes, it could
be mental health conditions,
725
00:39:24,080 --> 00:39:26,200
neurological conditions,
autoimmune or inflammatory
726
00:39:26,200 --> 00:39:28,680
disorders.
And that does create a rock and
727
00:39:28,680 --> 00:39:31,560
a hard place scenario.
If the LDL was up very high like
728
00:39:31,560 --> 00:39:34,200
to 304 hundred 500, which we
definitely see.
729
00:39:34,760 --> 00:39:36,920
But the ketogenic diet
therapeutic for that person, at
730
00:39:36,920 --> 00:39:40,320
that point we have to have a
discussion with the doctor about
731
00:39:40,560 --> 00:39:45,280
what is their risk.
And that is a question we are
732
00:39:45,280 --> 00:39:49,640
openly investigating because the
fact of the matter is we don't
733
00:39:49,640 --> 00:39:52,000
know.
And anybody who tells you we do
734
00:39:52,000 --> 00:39:54,920
know is lying through their
teeth or speaking beyond the
735
00:39:54,920 --> 00:39:58,440
literature because this
phenomenon, this phenotype is
736
00:39:58,440 --> 00:40:00,520
unlike anything we've ever seen
before.
737
00:40:01,040 --> 00:40:04,360
So while you can say the quote
preponderance of evidence, the
738
00:40:04,360 --> 00:40:08,080
body of literature existing
suggests that LDL particles and
739
00:40:08,080 --> 00:40:11,440
Apple V have a causal role in
cardiovascular disease.
740
00:40:12,080 --> 00:40:14,320
When you have an entirely new
population with the new
741
00:40:14,320 --> 00:40:17,120
physiologic driver of this
biomarker, they need to be
742
00:40:17,120 --> 00:40:20,640
studied uniquely in order to
understand the absolute risk
743
00:40:20,640 --> 00:40:22,200
associated with this profile.
So.
744
00:40:23,120 --> 00:40:26,120
We're doing that at the present
time.
745
00:40:26,400 --> 00:40:28,960
We have preliminary evidence,
some of which has been
746
00:40:28,960 --> 00:40:30,480
published, some of which we're
still writing up.
747
00:40:30,520 --> 00:40:34,440
It looks very reassuring that
this does not appear to be a
748
00:40:34,440 --> 00:40:38,080
population in which there's any
rapid progression of black.
749
00:40:39,680 --> 00:40:41,400
It doesn't mean there's zero
risks associated with the
750
00:40:41,400 --> 00:40:44,520
profile, but the data we have
thus far have been reassuring.
751
00:40:44,880 --> 00:40:47,200
We can caveat them, we can say
the preliminary, but the fact of
752
00:40:47,200 --> 00:40:51,000
the matter is right now we're
the only, well, I have a few
753
00:40:51,000 --> 00:40:53,320
teams, but our teams are the
only ones that are actually
754
00:40:53,320 --> 00:40:55,320
investigating this question on
this population.
755
00:40:55,320 --> 00:40:57,880
So you can call the evidence
preliminary, but it's all we
756
00:40:57,880 --> 00:41:00,960
have at this point in time.
Yeah, I had, I had Feldman on a
757
00:41:01,040 --> 00:41:04,120
couple months back, I guess
after Part 1 had been published,
758
00:41:04,120 --> 00:41:07,160
but not Part 2.
And what what was the average
759
00:41:07,360 --> 00:41:10,200
LDL reading from the
participants in in that study?
760
00:41:10,200 --> 00:41:11,880
I mean it was around 2 or 300,
right?
761
00:41:12,760 --> 00:41:16,760
Yeah, the mean LDL was 272
milligrams per desolated for the
762
00:41:16,760 --> 00:41:21,720
lean mass hyper responders 272
is very, very high compared to a
763
00:41:21,720 --> 00:41:24,760
match control which had an LDL
of 123.
764
00:41:26,120 --> 00:41:29,040
So the difference is 149
milligrams per deciliter between
765
00:41:29,040 --> 00:41:30,800
the groups.
And the keto group have been
766
00:41:30,800 --> 00:41:35,000
keto for an average of 4.7 years
and we did not see any increase
767
00:41:35,000 --> 00:41:39,680
in plaque in the keto group as
measured by coronary CT and
768
00:41:39,680 --> 00:41:42,840
geography.
So high resolution scans looks
769
00:41:42,840 --> 00:41:45,680
beyond just calcified plaque,
including non calcified plaque
770
00:41:46,440 --> 00:41:47,800
and we didn't see any increase
in plaque.
771
00:41:47,800 --> 00:41:50,000
In fact, the lean mass hyper
responder group was trending
772
00:41:50,000 --> 00:41:52,920
towards lower increase, not
significant, but trending
773
00:41:52,920 --> 00:41:55,440
towards sorry, not lower
increase, lower plaque levels
774
00:41:55,440 --> 00:41:57,920
than the match control.
And there was also no
775
00:41:58,120 --> 00:42:04,320
association between LDL and
plaque amount in the in the lean
776
00:42:04,320 --> 00:42:06,440
mass hyper responders.
And we've actually now had more
777
00:42:06,440 --> 00:42:07,440
data.
We've also looked at the
778
00:42:07,440 --> 00:42:11,200
correlations between Apple B LDL
particle count, even small dense
779
00:42:11,200 --> 00:42:14,560
LDL particle count and none of
these things appear to predict
780
00:42:14,560 --> 00:42:17,600
the amount of plaque in lean
mass hyper responders for
781
00:42:17,600 --> 00:42:21,320
reasons we are working to
explain.
782
00:42:21,840 --> 00:42:24,960
And now we're working on writing
up the prospective data.
783
00:42:24,960 --> 00:42:30,200
So where we actually monitor the
individuals with multiple scans
784
00:42:30,640 --> 00:42:34,360
over the course of time to see
what is the progression in lean
785
00:42:34,360 --> 00:42:38,600
mass hyper responders of plaque
and if it has any association
786
00:42:38,600 --> 00:42:43,320
with Apple B or if other things
like pre-existing plaque might
787
00:42:43,320 --> 00:42:45,880
be better predictors of Platt
progression.
788
00:42:45,880 --> 00:42:50,120
So I can't pull the curtain back
on the data quite yet as it's
789
00:42:50,120 --> 00:42:54,800
not published, but they're going
to be provocative findings that
790
00:42:54,800 --> 00:42:57,440
turn a lot of heads.
Actually, after this Zoom
791
00:42:57,440 --> 00:43:01,360
meeting, I'm getting on a call
with Dave and Professor Adrian
792
00:43:01,360 --> 00:43:05,040
Sotomoto to discuss some of our
preliminary analysis on this
793
00:43:05,040 --> 00:43:05,960
paper.
We're rounding up in the
794
00:43:05,960 --> 00:43:10,240
meantime.
So you know, it's a, it's a cool
795
00:43:10,240 --> 00:43:14,520
space to watch and I, I want to
emphasize, I absolutely want
796
00:43:14,520 --> 00:43:18,080
people to be cautious and have
open minded discussions with
797
00:43:18,080 --> 00:43:22,080
their physicians.
Contemplate the potential pros
798
00:43:22,080 --> 00:43:25,680
and cons of various
interventions, the risks
799
00:43:25,680 --> 00:43:29,240
involved, the risks involved
with respect to maintaining high
800
00:43:29,240 --> 00:43:33,440
Applebee levels even in lean
mass hyper responders, the risks
801
00:43:33,480 --> 00:43:37,080
of various interventions and
that includes trying your best
802
00:43:37,080 --> 00:43:41,520
to weigh the unknowns in these
equations because there are a
803
00:43:41,520 --> 00:43:45,320
lot of unknowns.
For example, you know we don't
804
00:43:45,320 --> 00:43:48,400
know what the effect of Ilean
mass type of responder phenotype
805
00:43:48,400 --> 00:43:51,200
is over 20 years because we just
don't have those data.
806
00:43:51,240 --> 00:43:54,160
But correspondingly we don't
have great data on the long term
807
00:43:54,160 --> 00:43:58,360
risks associated with say taking
a PCs K9 inhibitor which is one
808
00:43:58,360 --> 00:44:00,840
LDL lowering drug.
And we can talk about data there
809
00:44:00,840 --> 00:44:04,640
that I mean are concerning
enough that I am not on one of
810
00:44:04,640 --> 00:44:08,200
these medications.
So it's like the art of medicine
811
00:44:08,280 --> 00:44:12,240
has to do with trying to make
the best decision you can given
812
00:44:12,240 --> 00:44:16,280
an individual context, given
what you know, acknowledging
813
00:44:16,280 --> 00:44:20,240
that there is a lot of unknowns
and it is a matter of best
814
00:44:20,240 --> 00:44:23,960
guesses and updating your
individual choice at any one
815
00:44:23,960 --> 00:44:25,240
point in time.
So I don't think there's a right
816
00:44:25,240 --> 00:44:28,840
and wrong answer and all we're
trying to do here is advance the
817
00:44:28,840 --> 00:44:34,080
science and have open minded
discussions and speak in a
818
00:44:34,320 --> 00:44:37,200
nuanced manner as best we can
about the data as it's evolving
819
00:44:37,200 --> 00:44:38,840
so people can make their own
informed choices.
820
00:44:39,040 --> 00:44:41,360
Yeah, and I think the more data
we have, the better we'll be
821
00:44:41,360 --> 00:44:44,360
able to put their mind at ease.
But I mean, the, the, the common
822
00:44:44,360 --> 00:44:47,520
story I see unfold is that
people will adopt ketogenic diet
823
00:44:47,520 --> 00:44:50,880
and they'll, you know, depending
on how frequently they've
824
00:44:50,880 --> 00:44:53,640
checked their, their lipid
panels in the past, they may be
825
00:44:53,640 --> 00:44:56,560
slightly alarmed by what their,
their LDL is showing.
826
00:44:56,560 --> 00:44:58,920
But then they'll almost
unanimously say they feel
827
00:44:59,320 --> 00:45:01,840
exponentially better.
They've got more, you know,
828
00:45:01,840 --> 00:45:05,200
enhance cognition.
They don't have any GI distress.
829
00:45:05,240 --> 00:45:10,400
And to me, like as not a
scientist, that just, I mean, I,
830
00:45:10,480 --> 00:45:14,800
I like to let people lean into
how they feel like truly be
831
00:45:14,800 --> 00:45:18,200
observant and what their bodies
biofeedback is telling them.
832
00:45:18,200 --> 00:45:21,600
And if they are empowered enough
to do so and they notice, you
833
00:45:21,600 --> 00:45:24,400
know, benefits across the board,
better sleep quality, better
834
00:45:24,400 --> 00:45:27,560
performance, better recovery,
like that tells me all I need to
835
00:45:27,560 --> 00:45:30,680
know.
Yeah, I, I get that.
836
00:45:31,280 --> 00:45:33,680
I also get that people are going
to make decisions with their gut
837
00:45:33,680 --> 00:45:35,560
and a lot of people have that
mindset.
838
00:45:35,960 --> 00:45:40,160
I will caution that you do not
feel progression of
839
00:45:40,160 --> 00:45:42,960
cardiovascular disease.
It's not something that you can
840
00:45:42,960 --> 00:45:48,120
like, you know, just intuit in
your gut and, you know, the
841
00:45:48,120 --> 00:45:50,800
first sign could be a fatal
heart attack.
842
00:45:50,880 --> 00:45:53,560
That's very possible.
I just want to put that out
843
00:45:53,560 --> 00:45:57,320
there because I do not want to
discount the fact that even if
844
00:45:57,320 --> 00:46:00,640
you feel great, there could be
long term consequences to a
845
00:46:00,640 --> 00:46:03,240
particular lifestyle pattern.
Yeah, I totally agree with that.
846
00:46:03,240 --> 00:46:04,520
Just something to be cognizant
of.
847
00:46:04,840 --> 00:46:07,080
Yeah, 100%.
And I'm, I'm a big advocate for
848
00:46:07,080 --> 00:46:10,000
collecting as much hard data as
possible, which is why I do
849
00:46:10,120 --> 00:46:13,360
like, you know, three monthly.
Like I, I do the lipid test and
850
00:46:13,360 --> 00:46:15,680
the hormone test every three
months when I'm going through my
851
00:46:15,680 --> 00:46:17,800
own self experiments because I
want to know the numbers.
852
00:46:17,800 --> 00:46:19,880
I want to be able to be
objective with that data.
853
00:46:21,280 --> 00:46:24,920
I want people to also, you know,
be able to listen to their body
854
00:46:24,920 --> 00:46:28,760
because so many people seem to
have failed to do that simple
855
00:46:28,760 --> 00:46:33,920
task, which is important.
A nice thing I'll just add is
856
00:46:33,920 --> 00:46:36,080
you're talking about collecting
data like you can collect
857
00:46:36,080 --> 00:46:39,240
functional data on yourself.
So like you don't need, OK,
858
00:46:39,240 --> 00:46:41,680
we're trying to figure out at a
population level the risk
859
00:46:41,680 --> 00:46:44,120
associated with the mass hyper
responders, right?
860
00:46:44,760 --> 00:46:48,080
That is still going to be a a
population average when it comes
861
00:46:48,080 --> 00:46:50,280
to you.
What you should really care
862
00:46:50,280 --> 00:46:52,520
about is, is there plaque in
your arteries?
863
00:46:52,920 --> 00:46:57,400
And you can get scans to look.
So you can go get a coronary CTN
864
00:46:57,400 --> 00:46:58,880
geography and see is there
plaque.
865
00:46:59,200 --> 00:47:01,200
And if there is, I will be
concerned.
866
00:47:01,760 --> 00:47:05,200
If there's not, I will be less
concerned, especially if you've
867
00:47:05,200 --> 00:47:06,800
had high levels for a long
period of time.
868
00:47:06,800 --> 00:47:10,120
I'll use my mom as an example.
She's giving me permission to to
869
00:47:10,560 --> 00:47:14,880
talk about her case in broad
strokes, but she for example,
870
00:47:15,440 --> 00:47:18,000
unlike me at baseline, her LDL
is pretty high.
871
00:47:18,400 --> 00:47:21,200
I think it's always been above
160 and she's about to turn 60.
872
00:47:21,200 --> 00:47:23,160
So that exposure alone is pretty
high exposure.
873
00:47:23,160 --> 00:47:25,480
But on top of that, she will
manifest lean mass
874
00:47:25,480 --> 00:47:28,120
hyperresponder Physiology when
she goes to low carb.
875
00:47:28,120 --> 00:47:32,400
She's very petite, probably
about 100 and 510 lbs and her
876
00:47:32,400 --> 00:47:37,120
LDL will jump to close to 400.
So she has had this massive
877
00:47:37,120 --> 00:47:41,240
exposure lifelong to LDL and
people tend to say, you know,
878
00:47:41,240 --> 00:47:43,800
it's about milligrams per
deciliter a year exposure and
879
00:47:43,800 --> 00:47:46,920
LDL and Applebee, she's had this
enormous exposure and it goes up
880
00:47:46,920 --> 00:47:50,320
when she's keto, but she's been
now for several years.
881
00:47:50,600 --> 00:47:51,880
So we've had a lot of
discussions.
882
00:47:51,880 --> 00:47:53,920
I mean, the last thing I want to
do is gamble my mom's health and
883
00:47:53,920 --> 00:47:57,520
like what she should do, whether
she should take a statin or
884
00:47:57,520 --> 00:48:00,440
ezetimibe or other medication,
she should go off keto or low
885
00:48:00,440 --> 00:48:03,960
carb.
In the end, we got her some
886
00:48:03,960 --> 00:48:07,480
scans, including a CIMT and a
coronary CT angiography.
887
00:48:07,880 --> 00:48:11,040
And lo and behold, her total
plaque score was a flat 0.
888
00:48:12,600 --> 00:48:16,440
No, I'm not going to say this is
going to generalize to all 60
889
00:48:16,440 --> 00:48:18,200
year old women on ketogenic
diets.
890
00:48:18,200 --> 00:48:23,880
But for my mother, it does not
appear she has any plaque given,
891
00:48:24,120 --> 00:48:27,960
even given, and despite very
high LDL for a very long time,
892
00:48:28,280 --> 00:48:33,240
which is sufficient for her.
This is her decision.
893
00:48:33,360 --> 00:48:35,760
She's medically informed and I'm
not pulling the wool over her
894
00:48:35,760 --> 00:48:37,440
eyes.
She's an MD to say she doesn't
895
00:48:37,440 --> 00:48:40,360
want to take a medication at
this time because it's not clear
896
00:48:40,360 --> 00:48:42,560
that there would be any benefit.
She's had a big exposure.
897
00:48:42,560 --> 00:48:44,120
She hasn't had any plaque
accumulate.
898
00:48:44,120 --> 00:48:46,360
That's measurable.
So like, why would she take
899
00:48:46,480 --> 00:48:50,160
therapy?
Again, just going through an N =
900
00:48:50,160 --> 00:48:52,600
1 thought process and the kind
of thing you can do for yourself
901
00:48:52,600 --> 00:48:57,680
if you measure your plaque.
I mean, CAC for calcium score is
902
00:48:57,680 --> 00:49:00,680
a little bit more rudimentary,
but still pretty decent.
903
00:49:01,240 --> 00:49:03,880
And there isn't any plaque.
But that should be reassuring.
904
00:49:03,880 --> 00:49:06,560
And the data shows that's
reassuring even in people with
905
00:49:06,560 --> 00:49:10,160
familial hypercholesterolemia.
You know, if the CAC score is
906
00:49:10,160 --> 00:49:15,360
zero, that is better at
predicting, you know, future
907
00:49:15,360 --> 00:49:17,760
events than an Apple B or an
LVO.
908
00:49:18,120 --> 00:49:20,160
So you can get a scan on
yourself, is the point.
909
00:49:20,200 --> 00:49:22,640
You don't have to guess about
the plaque in your artery.
910
00:49:22,640 --> 00:49:25,880
You can go get it measured.
I think the CAC.
911
00:49:25,880 --> 00:49:29,640
Scan nowadays is it's like less
than 300 bucks in most places
912
00:49:29,640 --> 00:49:30,800
right?
Oh, it's cheap.
913
00:49:30,960 --> 00:49:33,160
Yeah, you can get it cheap.
And I mean, insurance should
914
00:49:33,160 --> 00:49:38,520
cover it if you have, you know,
hypercholesterolemia, which if
915
00:49:38,520 --> 00:49:42,360
you're a Lima cyberresponder,
you will, and also a coronary
916
00:49:42,360 --> 00:49:45,520
CTN geography could be covered
by insurance.
917
00:49:45,880 --> 00:49:50,800
It was for me and I'm in my 20s.
So, you know, these are these
918
00:49:50,800 --> 00:49:53,200
are scans you can talk with your
doctor and and they should be
919
00:49:54,400 --> 00:49:56,040
tools you use to inform your
decision.
920
00:49:56,040 --> 00:49:58,160
So I'll use myself again as an
example.
921
00:49:58,800 --> 00:50:04,600
I got ACA coronary CTN geography
years after I've been keto with
922
00:50:04,600 --> 00:50:06,920
the stipulation that if there
was plaque, I'd go on
923
00:50:06,920 --> 00:50:08,600
pharmacotherapy.
I told my doctor to look, I want
924
00:50:08,600 --> 00:50:10,440
you to order this, and I'm
telling you before the results
925
00:50:10,440 --> 00:50:14,280
come in that I'll take
medications if I have a positive
926
00:50:14,280 --> 00:50:16,880
finding.
Yes, I'm young, but my levels
927
00:50:16,880 --> 00:50:19,560
are exceptionally higher.
They had been exceptionally high
928
00:50:19,560 --> 00:50:22,920
such that my overall exposure
was above 5000 milligrams per
929
00:50:22,920 --> 00:50:25,360
deciliter years, so it was
plausible that they could have
930
00:50:25,360 --> 00:50:26,840
been plaque.
Turns out there wasn't.
931
00:50:27,280 --> 00:50:30,120
I will continue to update my
decisions as I collect more data
932
00:50:30,120 --> 00:50:34,880
on myself, but like you, I am
very attuned to my own data,
933
00:50:34,880 --> 00:50:37,680
always getting lipid tests and
we'll follow up with further
934
00:50:37,680 --> 00:50:43,240
functional measures as as I see
fit and then just update my
935
00:50:43,280 --> 00:50:44,920
decision.
I'm not closed off with things
936
00:50:44,920 --> 00:50:49,520
like medication just for me, it
doesn't make sense.
937
00:50:49,960 --> 00:50:53,040
That's my.
As as far as experiments go, I,
938
00:50:53,040 --> 00:50:56,320
I don't know the context of what
all you were trying to decide or
939
00:50:56,320 --> 00:50:59,760
discover with the calorie
experiment that you were doing.
940
00:50:59,800 --> 00:51:02,080
And I know you were eating a ton
of keto bricks and a ton of
941
00:51:02,080 --> 00:51:03,200
macadamia.
Butter, but what?
942
00:51:03,960 --> 00:51:06,560
Was the.
What was the objective of that
943
00:51:06,560 --> 00:51:09,760
experiment?
So first of all, thank you for
944
00:51:09,760 --> 00:51:12,280
the keto bricks.
They are incredibly delicious
945
00:51:12,280 --> 00:51:14,800
and they were from what made
this experiment feasible because
946
00:51:15,440 --> 00:51:18,160
for people who don't know me,
I'm a pretty petite guy, BMI
947
00:51:18,160 --> 00:51:20,960
around like 21 at about 5 foot
75 foot 8.
948
00:51:20,960 --> 00:51:26,680
So eating I was eating like well
over 6000 calories a day is very
949
00:51:26,680 --> 00:51:32,480
not very easy made possible like
you, but but the purpose of the
950
00:51:32,480 --> 00:51:34,720
experiment was actually to drop
my LVL.
951
00:51:34,720 --> 00:51:38,760
So other people, including for
example, Siobhan Huggins have
952
00:51:38,760 --> 00:51:42,360
able been able to drop their LVL
by just going quote hypercaloric
953
00:51:42,840 --> 00:51:45,800
even while keto, which is
another I love my N equals ones
954
00:51:45,800 --> 00:51:49,080
right.
Another way to demonstrate
955
00:51:49,080 --> 00:51:52,080
principles of lipid energy model
and associated principles.
956
00:51:52,080 --> 00:51:56,880
So basically the idea high level
is if you acutely gain a lot of
957
00:51:56,880 --> 00:51:59,800
fat, which if you eat a crazy
amount in a short period of
958
00:51:59,800 --> 00:52:02,360
time, you shouldn't still be
able to gain a decent amount of
959
00:52:02,360 --> 00:52:05,240
body fat or your fat cells
should grow.
960
00:52:05,960 --> 00:52:08,520
Then the there are a few things
that happen.
961
00:52:08,520 --> 00:52:12,840
One, your insulin will go up
even if you're eating keto and
962
00:52:12,840 --> 00:52:16,440
that will help with that storage
and also the expansion of the
963
00:52:16,440 --> 00:52:21,120
fat cells themself acting as
storage depots will have a
964
00:52:21,120 --> 00:52:23,880
structural demand.
At least this is the thought.
965
00:52:23,880 --> 00:52:27,040
So they will have a structural
demand for LDL particles,
966
00:52:27,040 --> 00:52:29,040
Applebee particles, and that
will drop your Applebee.
967
00:52:29,040 --> 00:52:31,880
So for example, Siobhan has
shown that when she went
968
00:52:31,880 --> 00:52:35,600
hypercaloric, I think it was
like she did A5 day protocol
969
00:52:35,600 --> 00:52:37,800
where part of the day she was
eating 4000 calories.
970
00:52:37,800 --> 00:52:41,440
Then she went up to 6000 and she
was eating like tons of heavy
971
00:52:41,440 --> 00:52:42,840
cream.
I think that was her main source
972
00:52:42,840 --> 00:52:44,920
of calories.
Her LDL plummeted more than it
973
00:52:44,920 --> 00:52:49,240
ever had.
I forget how much you can look
974
00:52:49,240 --> 00:52:53,200
up LDL drop experiment Siobhan
Huggins if you want the the
975
00:52:53,200 --> 00:52:56,040
detailed numbers, but she
dropped hers well over, I think
976
00:52:56,040 --> 00:53:00,560
it was over 150 milligrams per
deciliter with cream.
977
00:53:00,560 --> 00:53:02,920
And I wanted to replicate that.
Other people have actually over
978
00:53:02,920 --> 00:53:08,000
20 other people have shown that
if they go low carb, but they go
979
00:53:08,120 --> 00:53:11,680
like crazy high calorie for a
short period of time, even
980
00:53:11,680 --> 00:53:13,800
eating tons of saturated, the
fact that LDL will go down for
981
00:53:13,800 --> 00:53:15,680
the reasons I explained.
So I wanted to replicate that.
982
00:53:15,680 --> 00:53:18,120
I'd never done it.
So that was the purpose of the
983
00:53:18,120 --> 00:53:22,720
experiment.
The interesting thing was, I was
984
00:53:22,800 --> 00:53:24,760
entirely wrong with that
experiment.
985
00:53:26,040 --> 00:53:28,400
What ended up happening is my
LDL didn't change much.
986
00:53:28,400 --> 00:53:32,880
It actually went up a tiny bit,
which was fascinating to me
987
00:53:33,000 --> 00:53:37,840
because that was an n = 1 that
contradicted the findings of 20
988
00:53:37,840 --> 00:53:41,280
other people.
And what was even more
989
00:53:41,280 --> 00:53:44,360
fascinating is to think about
why the results were what they
990
00:53:44,360 --> 00:53:47,880
were in my circumstance.
And so I was measuring a lot of
991
00:53:47,880 --> 00:53:49,960
things along the way.
And what happened to me quite
992
00:53:49,960 --> 00:53:55,480
uniquely is my body temperature
when I was feeding at this level
993
00:53:55,480 --> 00:53:58,640
went up quite a bit.
My heart rate jumped a lot.
994
00:53:58,840 --> 00:54:02,960
And graph this out you can see
in the video and you know my
995
00:54:03,520 --> 00:54:06,880
subjective needs non exercise
activity thermogenesis went up a
996
00:54:06,880 --> 00:54:08,880
lot.
So I was bouncing all around and
997
00:54:08,880 --> 00:54:11,320
actually didn't end up gaining
much weight at all.
998
00:54:11,920 --> 00:54:15,680
And so the way I explained the
results and the LDL not changing
999
00:54:15,680 --> 00:54:17,920
or even going up, which are
totally consistent with our
1000
00:54:17,920 --> 00:54:21,520
model is some people are heart
gainers, some people are easy
1001
00:54:21,520 --> 00:54:22,760
gainers.
I'm a hard gainer.
1002
00:54:22,760 --> 00:54:25,200
And when I over feed and it's
been shown in the literature,
1003
00:54:25,200 --> 00:54:27,320
different people have different
responses to over feeding.
1004
00:54:27,640 --> 00:54:30,600
My body just wants to burn that
energy off.
1005
00:54:30,920 --> 00:54:33,240
So it increases my body
temperature, it increases my
1006
00:54:33,240 --> 00:54:34,960
heart rate, I'm bouncing around
all the time.
1007
00:54:34,960 --> 00:54:38,880
And as a result, my fat cells
didn't end up growing that much.
1008
00:54:38,960 --> 00:54:40,400
So there wasn't a structural
demand.
1009
00:54:40,400 --> 00:54:43,840
And in addition to that, my
energy demands went up.
1010
00:54:44,520 --> 00:54:48,240
And what happens when you're
lean and low carb and your
1011
00:54:48,240 --> 00:54:51,800
energy demand goes up?
All things being equal, the
1012
00:54:51,800 --> 00:54:55,200
lipid energy model has to spin a
little bit faster to get you the
1013
00:54:55,200 --> 00:54:58,800
energy you need.
And that predicts an increase in
1014
00:54:58,800 --> 00:55:00,520
LDL, which is exactly what
happened.
1015
00:55:00,520 --> 00:55:04,360
So it was a really cool
experiment for me because it was
1016
00:55:04,360 --> 00:55:09,440
one where I was, I was, I'm not,
you know, feigning humility
1017
00:55:09,440 --> 00:55:11,600
here.
I was actually wrong, but in
1018
00:55:11,600 --> 00:55:16,000
being wrong, the results still
perfectly fit the model.
1019
00:55:16,200 --> 00:55:21,720
And not only that, but the model
explained an idiosyncratic
1020
00:55:21,720 --> 00:55:26,480
individual response in me while
also explaining results in other
1021
00:55:26,480 --> 00:55:28,800
people.
So it was an individualized
1022
00:55:28,800 --> 00:55:30,640
application of the model, which
was really cool.
1023
00:55:30,840 --> 00:55:32,760
People can see the video if
that's going over their head.
1024
00:55:33,160 --> 00:55:36,320
But that was that experiment.
And it was one of those moments
1025
00:55:36,320 --> 00:55:39,400
where, yeah, did not turn out as
I expected.
1026
00:55:39,680 --> 00:55:43,960
And so I needed to look back to
the data and explain or evolve
1027
00:55:43,960 --> 00:55:49,040
the model and reinterpret, you
know, the data and and see what
1028
00:55:49,120 --> 00:55:51,480
we could learn together.
So I love my Anxious 1 and that
1029
00:55:51,480 --> 00:55:53,200
was a fun one.
No, that's super interesting.
1030
00:55:53,200 --> 00:55:54,960
So are you familiar with Brad
Marshall?
1031
00:55:57,480 --> 00:56:00,680
He's the fire in a bottle.
Yeah, yeah.
1032
00:56:00,680 --> 00:56:03,200
So I don't, and this is
definitely his wheelhouse and
1033
00:56:03,200 --> 00:56:09,640
not mine, but he is hypothesized
that the stearic acid is going
1034
00:56:09,640 --> 00:56:12,520
to make the actual adipocyte
themselves more insulin
1035
00:56:12,520 --> 00:56:15,480
resistant.
And with you consuming such a
1036
00:56:15,480 --> 00:56:18,640
high percentage of your calories
from Ketobrix, which are
1037
00:56:19,080 --> 00:56:21,880
primarily cacao butter, the
highest source of stearic acid,
1038
00:56:21,880 --> 00:56:27,680
I wonder if that could have been
a reason as to why you didn't
1039
00:56:27,680 --> 00:56:30,040
have any growth in the fat cells
themselves.
1040
00:56:31,280 --> 00:56:33,600
And I don't think the stearic
acid was, I mean, I was eating
1041
00:56:33,600 --> 00:56:35,680
other things.
I was eating a ton of macadamia
1042
00:56:35,680 --> 00:56:39,480
butter and macadamia oil, which
is mostly monounsaturated fat.
1043
00:56:40,720 --> 00:56:44,040
You know, I could replicate this
with other fat sources to see if
1044
00:56:44,080 --> 00:56:45,560
it would have a similar
response.
1045
00:56:45,960 --> 00:56:48,000
I have looked at some of Brad
Marshall's stuff.
1046
00:56:48,000 --> 00:56:56,280
I'm not so sold myself on that
model, so I don't know if I have
1047
00:56:56,280 --> 00:56:58,840
any further commentary.
I do not know like that.
1048
00:56:58,840 --> 00:57:01,080
Like I said, that's not my
wheelhouse by any means, but I
1049
00:57:01,080 --> 00:57:04,320
am curious to see how the
different types of fats impact
1050
00:57:04,320 --> 00:57:06,400
fat cells, so I'd be curious to
learn more on that as well.
1051
00:57:07,200 --> 00:57:10,840
Yeah, I think a lot of those
things might be a function of
1052
00:57:10,840 --> 00:57:14,240
more chronic effects.
This was a a short term study.
1053
00:57:15,560 --> 00:57:19,480
And so for things like, you
know, saturated versus
1054
00:57:19,480 --> 00:57:23,640
unsaturated, let's even get more
granular, different types of
1055
00:57:25,000 --> 00:57:28,680
fatty acids in the diet, be it
linoleic acid or stearic acid or
1056
00:57:28,680 --> 00:57:33,440
Omega threes, Omega sevens, in
order to I think affect
1057
00:57:33,440 --> 00:57:37,800
Physiology long term, it
requires a more chronic time
1058
00:57:37,800 --> 00:57:39,600
scale.
Yeah, that would be my high
1059
00:57:39,600 --> 00:57:42,280
level suggestion.
Yeah, no, I agree.
1060
00:57:42,400 --> 00:57:45,520
I agree.
What about satiety per calorie?
1061
00:57:45,520 --> 00:57:47,200
You want to dabble into that
conversation.
1062
00:57:48,480 --> 00:57:51,720
We can, I'm, I'm going to try to
refrain.
1063
00:57:51,720 --> 00:57:54,880
So there have been some, let's
say, strong words exchange
1064
00:57:54,880 --> 00:57:57,840
between me and the proponents of
society versus calorie.
1065
00:57:57,840 --> 00:58:02,760
I'm going to try to keep that in
check because I think, let's say
1066
00:58:02,800 --> 00:58:04,280
we've both been aggressive
towards each other.
1067
00:58:04,440 --> 00:58:05,800
I definitely think I'm on the
right.
1068
00:58:05,800 --> 00:58:07,120
I'm sure they think they're on
the right.
1069
00:58:07,120 --> 00:58:12,600
But we can keep this high level
and discuss it at a academic and
1070
00:58:12,600 --> 00:58:18,440
intellectual perspective.
I will start by letting you give
1071
00:58:18,440 --> 00:58:22,600
your two cents.
I, I've had both on the podcast,
1072
00:58:23,480 --> 00:58:27,520
you know, Ted Naman obviously is
a proponent of his PE formula,
1073
00:58:27,840 --> 00:58:30,160
which a lot of the satiety per
calorie is based on.
1074
00:58:30,600 --> 00:58:35,120
And a lot of that is honestly
very similar to what I started
1075
00:58:35,120 --> 00:58:39,080
doing with my traditional
bodybuilding, you know, dietary
1076
00:58:39,080 --> 00:58:41,800
protocol.
I mean very high fiber, higher
1077
00:58:41,800 --> 00:58:49,080
protein, relatively lower, you
know fat model and from just my
1078
00:58:49,080 --> 00:58:52,480
anecdotal experience, I did not
experience more satiety with
1079
00:58:52,480 --> 00:58:55,480
that.
What I've noticed is that when I
1080
00:58:55,480 --> 00:58:59,600
have higher like if a calories
are equated form and I'm
1081
00:58:59,600 --> 00:59:03,280
following a ketogenic approach
with higher fat, moderate
1082
00:59:03,280 --> 00:59:05,640
protein, very minimal
carbohydrate versus a calorie
1083
00:59:05,640 --> 00:59:09,840
equated model with higher fiber,
higher protein, lower fat, lower
1084
00:59:09,840 --> 00:59:12,840
carbs, I experienced much more
satiety with the ketogenic
1085
00:59:12,840 --> 00:59:15,400
approach.
Even with calories equated, I'll
1086
00:59:15,400 --> 00:59:18,360
have fewer meals, I'll have less
feeding frequency.
1087
00:59:18,600 --> 00:59:20,760
Some of that may be
psychological, some that may be
1088
00:59:21,120 --> 00:59:23,400
sephalic phase of insulin
response, not sure.
1089
00:59:23,400 --> 00:59:26,240
But what I've noticed and what
I've theorized is that if I'm
1090
00:59:26,240 --> 00:59:31,080
consuming less fiber, that's not
going to hinder absorption of
1091
00:59:31,080 --> 00:59:32,960
the nutrition that I am
consuming, especially in the
1092
00:59:32,960 --> 00:59:35,880
context of a caloric deficit as
I'm in when I'm in a prep.
1093
00:59:36,320 --> 00:59:40,520
And if I consume fewer meal
frequencies with really high
1094
00:59:40,520 --> 00:59:45,680
quality, highly bio bioavailable
food, that seems to be the most
1095
00:59:45,680 --> 00:59:49,560
satiant, you know, satiating
form of consumption for me and
1096
00:59:49,560 --> 00:59:51,720
that they replicate that amongst
my clientele.
1097
00:59:51,720 --> 00:59:55,640
So that is in stark contrast to
the satiety per calorie model.
1098
00:59:56,160 --> 00:59:57,720
But that's just been my personal
experience.
1099
00:59:58,480 --> 01:00:02,240
Yeah.
What I'll say is first and
1100
01:00:02,240 --> 01:00:07,800
foremost, as I said earlier, I'm
for whatever tools and
1101
01:00:07,800 --> 01:00:10,320
heuristics people want to use
that serve them.
1102
01:00:10,720 --> 01:00:14,160
That's fine.
And I think the levers of the
1103
01:00:14,160 --> 01:00:18,200
Society for Calorie model, which
are things like hedonic factor,
1104
01:00:18,280 --> 01:00:20,800
a little pseudoscientific there,
but you know, how much of food
1105
01:00:20,800 --> 01:00:24,560
gives you pleasure, the hedonic
factor, the percent protein and
1106
01:00:24,560 --> 01:00:27,280
the fiber content.
Each can be modeling, you know,
1107
01:00:27,280 --> 01:00:30,840
levers people can reflect on
and, you know, toggle as they
1108
01:00:30,840 --> 01:00:32,960
see fit and as is useful for
them.
1109
01:00:34,000 --> 01:00:36,960
That's fine.
You know, it's similar to you
1110
01:00:36,960 --> 01:00:40,440
mentioned Ted Naman's PE model,
Like PE is not a scientific
1111
01:00:40,440 --> 01:00:42,720
model.
It's just a ratio.
1112
01:00:43,000 --> 01:00:46,800
But if it's a ratio that helps
people make more intelligent
1113
01:00:46,880 --> 01:00:48,840
choices for themselves, I'm
totally cool with that.
1114
01:00:49,240 --> 01:00:51,880
And I think there are people who
have benefited from using APE
1115
01:00:52,040 --> 01:00:54,160
mindset.
I've never said that wasn't the
1116
01:00:54,160 --> 01:00:57,800
case.
Might take issue and maybe this
1117
01:00:57,800 --> 01:01:01,200
is just me being a Snooty
academic and overly
1118
01:01:01,200 --> 01:01:04,560
intellectualizing things, but a
lot of the claims that have been
1119
01:01:04,560 --> 01:01:09,720
made around satiety per calorie
are just speaking beyond the
1120
01:01:09,720 --> 01:01:13,000
data, arrogant and pseudo
scientific.
1121
01:01:13,600 --> 01:01:17,320
And those sound like aggressive
terms, but they're actually very
1122
01:01:17,320 --> 01:01:21,000
accurate descriptors.
Which is why, I mean, this can
1123
01:01:21,000 --> 01:01:24,280
be demonstrated by the results
that are output from the satiety
1124
01:01:24,280 --> 01:01:28,160
per calorie model, which the
proponents themselves like to,
1125
01:01:29,680 --> 01:01:32,000
well, let's say speak strongly
about.
1126
01:01:34,160 --> 01:01:37,040
And it's always a slew of
ridiculous things like, you
1127
01:01:37,040 --> 01:01:39,760
know, the claims and this, these
are claims that they will make
1128
01:01:39,760 --> 01:01:42,560
about like things like, you
know, what is the most
1129
01:01:42,560 --> 01:01:45,920
metabolically healthy ice cream?
And they'll give a score to like
1130
01:01:45,920 --> 01:01:48,520
Halo Top ice cream in like the
high 50s or the mid.
1131
01:01:48,520 --> 01:01:50,320
Actually it was like 53.
So not high 50s.
1132
01:01:50,320 --> 01:01:54,280
Something like that would be 52
regardless, which scores better
1133
01:01:54,280 --> 01:01:56,480
than like things like avocados,
egg yolks.
1134
01:01:56,480 --> 01:02:01,480
So they're making direct claims
or very strongly implicit claims
1135
01:02:01,480 --> 01:02:04,800
about the metabolic health value
of something like junk food Halo
1136
01:02:04,800 --> 01:02:09,600
Top ice cream versus cheeses and
egg yolks and avocado and higher
1137
01:02:09,600 --> 01:02:12,600
fat foods that are actually more
nutrient dense.
1138
01:02:12,600 --> 01:02:14,840
And overall, I think the
literature would show better
1139
01:02:14,840 --> 01:02:18,160
from metabolic health and
devaluing things based on their
1140
01:02:18,160 --> 01:02:21,560
caloric density, wrapping it all
around this calorie centric
1141
01:02:21,560 --> 01:02:23,480
mindset since calories are in
the denominator.
1142
01:02:23,480 --> 01:02:28,240
So foods like macadamia nuts,
which they like to tease me
1143
01:02:28,240 --> 01:02:29,480
about because I like macadamia
nuts.
1144
01:02:29,480 --> 01:02:32,840
So that's become a a poking
point for them get downgraded.
1145
01:02:32,840 --> 01:02:35,840
And yet, when you look at the
literature, there actually is at
1146
01:02:35,840 --> 01:02:38,240
least one interventional trial
where just adding macadamia nuts
1147
01:02:38,240 --> 01:02:48,200
to the diet cause weight loss.
And their model, their model is
1148
01:02:48,200 --> 01:02:51,040
a tool, It's a toy, it's a
heuristic.
1149
01:02:51,040 --> 01:02:54,120
And that's fine if you present
it as such.
1150
01:02:54,680 --> 01:02:57,560
But what they try to do is
pretend that it's solid science
1151
01:02:57,560 --> 01:02:59,680
when it's not.
It's not validated.
1152
01:02:59,960 --> 01:03:04,200
It's not even sensible.
Because when you accumulate all
1153
01:03:04,200 --> 01:03:06,880
these factors, some of which
don't even really have real
1154
01:03:06,880 --> 01:03:08,960
science behind them, like a
donic factor, then you weight
1155
01:03:08,960 --> 01:03:13,000
them arbitrarily, which they do.
The intended is fully admitted.
1156
01:03:13,000 --> 01:03:14,440
The weighting is entirely
arbitrary.
1157
01:03:14,960 --> 01:03:17,480
You end up with a scoring system
where you're trying to quantify
1158
01:03:17,480 --> 01:03:20,120
different foods directly,
compare them on a one to 100
1159
01:03:20,120 --> 01:03:26,160
scale, and the science behind it
is completely shoddy, which is
1160
01:03:26,160 --> 01:03:29,480
why you always end up getting
some ridiculous results.
1161
01:03:29,480 --> 01:03:32,320
And it's not even necessarily
ridiculous results biased
1162
01:03:32,320 --> 01:03:35,480
against low carb all the time.
They've also had scores like,
1163
01:03:35,920 --> 01:03:41,280
you know, protein Berry ice
cream is better than salmon or
1164
01:03:41,280 --> 01:03:43,960
pizza is better than watermelon
for weight loss.
1165
01:03:43,960 --> 01:03:45,160
And it's like, these things are
ridiculous.
1166
01:03:45,160 --> 01:03:47,560
And then what inevitably happens
is they'll just go toggle the
1167
01:03:47,560 --> 01:03:50,200
score because they can't,
because it's arbitrary.
1168
01:03:50,520 --> 01:03:54,960
So they can just behind their,
you know, curtain change the
1169
01:03:54,960 --> 01:03:58,440
algorithm and then have a new
score that appeases people and
1170
01:03:58,440 --> 01:04:01,480
sell the product.
And honestly, if it was just
1171
01:04:01,480 --> 01:04:04,480
that, it would be fine.
It's just the arrogance of
1172
01:04:04,480 --> 01:04:09,240
claims like satiety per calorie
explains all dietary phenomena
1173
01:04:09,600 --> 01:04:12,280
in the diet space, period, end
of story, Which Ted has said,
1174
01:04:12,760 --> 01:04:15,800
And I'm like, man, this is a
falsifiable statement.
1175
01:04:15,800 --> 01:04:17,640
For one.
He's asked me to falsify it.
1176
01:04:17,640 --> 01:04:18,800
I've falsified it multiple
times.
1177
01:04:19,440 --> 01:04:24,520
And it's just intellectually
dishonest.
1178
01:04:24,840 --> 01:04:27,760
And I have quite honestly been,
and I'll speak directly to them
1179
01:04:27,760 --> 01:04:30,160
if they're listening.
Like I've just been profoundly
1180
01:04:30,160 --> 01:04:33,240
disappointed.
And their lack of intellectual
1181
01:04:33,240 --> 01:04:35,640
rigor, for one, and the
dishonesty with which they
1182
01:04:35,640 --> 01:04:38,480
market the product.
I mean, like the whole thing
1183
01:04:38,480 --> 01:04:43,640
with me was I was engaged with
them very early on and helping
1184
01:04:43,640 --> 01:04:45,960
them or, or I offered to help
them.
1185
01:04:45,960 --> 01:04:48,760
They did not accept the help.
It's kind of formulate this in a
1186
01:04:48,760 --> 01:04:50,880
way that I thought will be
marketing it in an
1187
01:04:50,880 --> 01:04:53,080
intellectually honest manner
because I thought it was an idea
1188
01:04:53,080 --> 01:04:57,240
that initially had legs, but
they chose not to validate it.
1189
01:04:57,240 --> 01:05:01,040
They chose not to be transparent
about their methodology or the
1190
01:05:01,040 --> 01:05:03,000
studies they were citing as a
conglomerate.
1191
01:05:04,120 --> 01:05:07,680
They went on making these, you
know, absurd grandiose claims,
1192
01:05:08,200 --> 01:05:11,840
cherry picking data and and then
just honestly, like I tried to
1193
01:05:11,840 --> 01:05:13,240
disengage, they kept poking at
me.
1194
01:05:13,240 --> 01:05:15,000
So what happened?
That is this response video.
1195
01:05:15,000 --> 01:05:16,720
You can look it up in my channel
if you want.
1196
01:05:16,720 --> 01:05:19,280
It is strongly worded something
like satiety per calorie is a
1197
01:05:19,280 --> 01:05:24,000
scam.
And I go through the flaws.
1198
01:05:24,000 --> 01:05:26,440
I systematically go through the
flaws and also their marketing
1199
01:05:26,440 --> 01:05:30,080
playbook because I think it is a
great case study of where you
1200
01:05:30,160 --> 01:05:33,560
actually had what was a
potentially good idea that was
1201
01:05:33,560 --> 01:05:37,960
poorly executed for business
purposes at the expense of
1202
01:05:37,960 --> 01:05:41,320
people.
And quite honestly, since then,
1203
01:05:41,320 --> 01:05:43,920
they've just been, it's, it's
been disappointing.
1204
01:05:43,920 --> 01:05:45,960
I, I don't put most of it on
Ted.
1205
01:05:45,960 --> 01:05:47,680
I think he's just kind of
following along.
1206
01:05:47,680 --> 01:05:50,440
But one thing they did, for
example, recently, I didn't even
1207
01:05:50,440 --> 01:05:51,560
respond because it wasn't worth
it.
1208
01:05:51,560 --> 01:05:52,760
It was so pathetic and
desperate.
1209
01:05:52,760 --> 01:05:57,400
But they took a clip from me for
a short about I was talking
1210
01:05:57,400 --> 01:06:00,960
about a randomized control trial
on Super Lola Sweetener
1211
01:06:00,960 --> 01:06:03,760
conducted out of Yale.
And they took it out of context
1212
01:06:04,080 --> 01:06:08,720
and misrepresented it and the
literature really around it and
1213
01:06:10,120 --> 01:06:11,800
to try to make some extreme
point.
1214
01:06:11,800 --> 01:06:14,200
And in fact, the tweet they put
out was something about oatmeal.
1215
01:06:14,200 --> 01:06:16,440
I hadn't talked about oatmeal.
They were just trying to go for
1216
01:06:16,440 --> 01:06:20,160
quick bait.
And it was just like, I've
1217
01:06:20,160 --> 01:06:22,080
offered them many opportunities
to talk to me.
1218
01:06:22,120 --> 01:06:25,400
I've debated Ted once.
It was did not go well for him
1219
01:06:26,760 --> 01:06:30,280
and, and and they're at the
point where like I've tried to
1220
01:06:30,280 --> 01:06:32,960
disengage now they're poking me
and misinterpreting randomized
1221
01:06:32,960 --> 01:06:35,880
control trial literature either
intentionally or because I just
1222
01:06:35,880 --> 01:06:37,200
generally don't understand the
data.
1223
01:06:37,560 --> 01:06:39,960
It's become a little bit of a, a
shoot show, to be honest.
1224
01:06:39,960 --> 01:06:45,080
And I don't really hold grudges.
I just, I've just been really,
1225
01:06:45,080 --> 01:06:48,040
really disappointed in that
marketing model.
1226
01:06:48,760 --> 01:06:54,120
OK, heuristic, terribly,
terribly executed with really
1227
01:06:54,120 --> 01:06:58,200
weak scientific basis.
And so I, I'm sad for the people
1228
01:06:58,200 --> 01:07:02,160
that feel betrayed because it's
spun off of Diet Doctor, which a
1229
01:07:02,160 --> 01:07:04,120
lot of people went to as a go to
source.
1230
01:07:04,120 --> 01:07:09,800
And a lot of people were hurt by
the pivot to kind of, you know,
1231
01:07:09,800 --> 01:07:14,080
reach and pander to a new
audience while giving up
1232
01:07:14,080 --> 01:07:16,520
scientific integrity.
And so I think that's why a lot
1233
01:07:16,520 --> 01:07:19,520
of people flocked away.
Probably why Brett Scherr left,
1234
01:07:19,520 --> 01:07:21,560
who I thought was like the heart
and soul of Diet Doctor.
1235
01:07:22,080 --> 01:07:25,800
And ever since then, I think
it's just been a down spiral of
1236
01:07:25,800 --> 01:07:28,520
virtue signaling and I've just
been disappointed.
1237
01:07:28,520 --> 01:07:30,480
I'm trying to disengage because
I honestly think it's killing
1238
01:07:30,480 --> 01:07:32,560
itself.
But they have a, a tendency.
1239
01:07:32,560 --> 01:07:33,840
I don't know if you've noticed
this on Twitter.
1240
01:07:33,840 --> 01:07:35,840
I don't know if you're on
Twitter much, but they love to
1241
01:07:35,840 --> 01:07:37,840
tag me into things.
I have them both muted, but like
1242
01:07:38,160 --> 01:07:42,200
they will tag me incessantly to
a point that it just appears
1243
01:07:42,200 --> 01:07:45,520
desperate and kind of pitiful.
So I don't know I.
1244
01:07:45,640 --> 01:07:47,920
I I'm sad.
I'm sad for people.
1245
01:07:48,360 --> 01:07:52,080
Yeah, perfectly honest.
It's it's unfortunate I haven't,
1246
01:07:52,200 --> 01:07:55,440
I've seen Dr. E speak.
We were at a conference
1247
01:07:55,440 --> 01:07:57,520
together.
I've had Ted on the podcast,
1248
01:07:57,520 --> 01:07:59,120
I've had Brett Shore on the
podcast.
1249
01:08:00,200 --> 01:08:03,240
And you know, my experience with
with Ted when I had him on was
1250
01:08:03,240 --> 01:08:07,040
it was, it was mostly this was
all pre satiety per calories.
1251
01:08:07,040 --> 01:08:09,040
We're talking about his PE
approach and I, you know,
1252
01:08:09,040 --> 01:08:10,640
appreciated the nuance he
brought there.
1253
01:08:10,640 --> 01:08:15,240
But I feel like as a coach, I
see people, I see clientele, I
1254
01:08:15,240 --> 01:08:17,640
see, you know, people that are
wanting to just simply improve
1255
01:08:17,640 --> 01:08:18,680
their health.
Not all of my clients are
1256
01:08:18,680 --> 01:08:23,479
competitors by any means.
And people tend to flock to
1257
01:08:24,279 --> 01:08:29,200
absolutes and absolutes are very
hard thing to convey a nutrition
1258
01:08:29,200 --> 01:08:33,640
for humans.
And when you're scoring foods
1259
01:08:34,000 --> 01:08:38,359
with an absolute score and you
have people justifying the
1260
01:08:38,359 --> 01:08:43,279
consumption of, you know, XY or
Z because of its, you know, our
1261
01:08:43,319 --> 01:08:46,359
arbitrary score like that just
never really tends to go over
1262
01:08:46,359 --> 01:08:47,600
well.
And I think that's been the
1263
01:08:47,600 --> 01:08:49,479
model.
I'm not sure of the marketing.
1264
01:08:49,479 --> 01:08:51,760
I don't have the, the app, I
don't even know what the app is
1265
01:08:51,760 --> 01:08:56,279
called.
But I, I see people gravitating
1266
01:08:56,279 --> 01:08:58,160
to that and then being LED
astray.
1267
01:08:58,160 --> 01:09:00,720
And then I've got to help them
pick up the pieces.
1268
01:09:00,720 --> 01:09:04,439
And that's my frustration.
Yeah, it's, it is just, I think,
1269
01:09:04,439 --> 01:09:07,720
you know, Andres is a very
astute businessman, maybe Ted to
1270
01:09:07,720 --> 01:09:10,640
some extent too.
And So what I, what I saw in
1271
01:09:10,640 --> 01:09:13,520
their, their marketing, which
plays very well in short form is
1272
01:09:13,520 --> 01:09:20,359
very characteristic business tax
that sell well in short form.
1273
01:09:20,359 --> 01:09:26,359
Things like changing the burden
of proof from you on to the
1274
01:09:26,359 --> 01:09:28,880
person who's taking the question
even when it's in a very pseudo
1275
01:09:28,880 --> 01:09:31,880
scientific manner.
So I go through I think 5 of
1276
01:09:31,880 --> 01:09:36,520
their playbook approaches in my
video and people can look at it.
1277
01:09:36,520 --> 01:09:38,720
I think it is, you know, it
generalizes beyond society per
1278
01:09:38,720 --> 01:09:40,920
calorie where it was just an
example of like I see this
1279
01:09:40,920 --> 01:09:44,800
pattern again and again and
media marketing around nutrition
1280
01:09:44,800 --> 01:09:49,200
where people use these tax for
great engagement and probably
1281
01:09:49,200 --> 01:09:53,399
great business results.
But it's used to stand up a
1282
01:09:53,399 --> 01:09:57,920
complete absence of science.
And if they were serious, they
1283
01:09:57,920 --> 01:10:00,840
would be transparent, fully
transparent about their
1284
01:10:00,840 --> 01:10:03,520
methodology, what literature,
all of it, what they're citing,
1285
01:10:03,520 --> 01:10:05,320
how they're determining how to
weigh things.
1286
01:10:05,560 --> 01:10:08,440
They would even go about trying
to validate it or even just
1287
01:10:08,440 --> 01:10:11,160
simply write a perspectives
piece on their approach, citing
1288
01:10:11,160 --> 01:10:12,560
literature, which they failed to
do.
1289
01:10:12,560 --> 01:10:14,320
Even when I've offered that
opportunity to them.
1290
01:10:14,320 --> 01:10:16,920
I don't think either of them has
published any papers before, You
1291
01:10:16,920 --> 01:10:18,440
know, not to per SE knock on
that.
1292
01:10:18,440 --> 01:10:23,480
But if you're going to claim,
for example, as Ted has, that
1293
01:10:23,680 --> 01:10:27,160
he's the most unbiased
scientific mind in the low carb
1294
01:10:27,160 --> 01:10:30,720
community who's read the
studies, you probably should
1295
01:10:30,720 --> 01:10:33,280
have some degree of scientific
background and not continuously
1296
01:10:33,280 --> 01:10:37,360
make claims that are directly
falsifiable, which you're right,
1297
01:10:37,360 --> 01:10:39,480
people love absolutes.
I don't know if Ted was on your,
1298
01:10:39,480 --> 01:10:42,160
when Ted was on your podcast, if
he, you know, said anything
1299
01:10:42,160 --> 01:10:46,880
like, like I mentioned earlier,
where the PE model or society
1300
01:10:46,880 --> 01:10:49,120
per calorie explains every
phenomenon on the diet space.
1301
01:10:49,120 --> 01:10:51,480
But like when you say that when
you're an MD and you say it with
1302
01:10:51,480 --> 01:10:52,960
confidence, people take you
seriously.
1303
01:10:52,960 --> 01:10:55,640
It takes someone who's actually
read the literature to be like,
1304
01:10:55,720 --> 01:10:58,440
that's false.
Here are data that contradict
1305
01:10:58,440 --> 01:11:00,200
it.
And he's done that several
1306
01:11:00,200 --> 01:11:04,400
times, including in, in like we
had a debate where he'd said
1307
01:11:04,400 --> 01:11:06,720
something about the carbohydrate
insulin model and said, well,
1308
01:11:06,720 --> 01:11:08,800
here's why it's wrong and these
data don't exist.
1309
01:11:08,800 --> 01:11:10,240
And I'm like, you sure you want
to double down on that?
1310
01:11:10,240 --> 01:11:12,800
And he said, yes, kind of like,
well, here the data are, here's
1311
01:11:12,800 --> 01:11:15,160
a human randomized control trial
that you just didn't look at,
1312
01:11:15,160 --> 01:11:16,960
you haven't read, you weren't
aware of it.
1313
01:11:17,360 --> 01:11:20,280
So you can make absolutes and
people will believe you, but
1314
01:11:20,320 --> 01:11:22,360
quite frankly, it's incorrect
and dishonest.
1315
01:11:23,080 --> 01:11:27,320
So my hang up is, again, not
with the heuristic in the
1316
01:11:27,320 --> 01:11:30,040
approach.
It's about how it's being sold
1317
01:11:30,480 --> 01:11:34,120
and the absolutism around it and
what I think are some dishonest
1318
01:11:34,160 --> 01:11:37,640
marketing tactics.
But again, if people use the
1319
01:11:37,640 --> 01:11:40,640
tool and it works for them,
great.
1320
01:11:41,200 --> 01:11:42,800
I, I just want people to be
better.
1321
01:11:43,960 --> 01:11:46,600
So there there's the conflict
between, you know, the, the
1322
01:11:47,160 --> 01:11:50,240
coach in me and then the, the
academic and intellectual,
1323
01:11:50,240 --> 01:11:55,360
which, you know, in fairness to
them, playing devil's advocate
1324
01:11:55,360 --> 01:11:57,760
best I can.
Like, I don't think that they're
1325
01:11:57,760 --> 01:12:01,640
trying to be academics.
And I don't think everybody
1326
01:12:01,640 --> 01:12:03,560
always wants an academic
message.
1327
01:12:03,640 --> 01:12:08,440
So sometimes maybe confidence
and absolutism, even when it
1328
01:12:08,440 --> 01:12:11,080
bucks the data, maybe it's
functional for some people.
1329
01:12:12,760 --> 01:12:14,120
It's the best argument I can
make for them.
1330
01:12:15,440 --> 01:12:19,320
But anyway I just.
Think transparency is, you know,
1331
01:12:19,320 --> 01:12:21,800
first and foremost, So like
whichever path they're taking,
1332
01:12:21,800 --> 01:12:24,520
as long as they're doing so with
a transparent road map like that
1333
01:12:24,600 --> 01:12:26,040
needs to give people a level
playing field.
1334
01:12:26,800 --> 01:12:29,240
Yeah, yeah.
Anyway, we can move on.
1335
01:12:29,240 --> 01:12:31,240
I'm I'm trying not to become
hung up on that.
1336
01:12:31,240 --> 01:12:34,200
That's just something that's a
sore point of disappointment.
1337
01:12:34,240 --> 01:12:36,040
It's just because I like I, it
was one of these things, you
1338
01:12:36,040 --> 01:12:38,160
know, when you like, you really
want to give something the
1339
01:12:38,160 --> 01:12:40,240
benefit of the doubt and then
you really try to help and then
1340
01:12:40,240 --> 01:12:42,200
it just like completely goes
leftwards.
1341
01:12:42,960 --> 01:12:46,480
And that's how things feel now.
So I think it's something to, as
1342
01:12:46,480 --> 01:12:50,840
best I can cut my losses on.
And you know, if I'm accurate in
1343
01:12:50,840 --> 01:12:54,400
my weed and their incessant
poke, incessant poking at me at
1344
01:12:54,400 --> 01:12:56,080
this point in time is just a
sign of desperation.
1345
01:12:56,080 --> 01:12:57,680
I think they're probably sinking
themselves.
1346
01:12:58,240 --> 01:13:02,240
Just let the sinking ship sink.
OK, man, I want to be respectful
1347
01:13:02,240 --> 01:13:04,160
of your time, but I do want to
figure out what's going on with
1348
01:13:04,160 --> 01:13:06,400
these year supply of eggs, man,
What, what, what?
1349
01:13:06,680 --> 01:13:10,160
Oh yeah, that was unexpected.
So I done, I've done a lot of
1350
01:13:10,160 --> 01:13:15,200
Enacles ones and a recent one
was I ate 720 eggs in a month,
1351
01:13:15,600 --> 01:13:18,640
which you probably could match,
but it was on average 1 egg per
1352
01:13:18,640 --> 01:13:22,600
hour every hour for a month.
And it was again, just lipid
1353
01:13:22,600 --> 01:13:25,920
energy model type stuff, but
really was meant to be a hook
1354
01:13:25,920 --> 01:13:30,920
for some new data on how
cholesterol metabolism is, is
1355
01:13:30,920 --> 01:13:34,440
regulated or how cholesterol is
regulated in the body when you
1356
01:13:34,440 --> 01:13:35,720
can take more dietary
cholesterol.
1357
01:13:35,720 --> 01:13:37,320
So there's a new hormone that
was discovered.
1358
01:13:37,320 --> 01:13:38,480
You can see the video about
that.
1359
01:13:38,480 --> 01:13:42,040
It's called colecin.
But that aside, I basically
1360
01:13:42,040 --> 01:13:45,120
showed that eating a lot of eggs
didn't increase my cholesterol.
1361
01:13:45,120 --> 01:13:47,520
And as a lean mass hyper
responder, if I added carbs to
1362
01:13:47,520 --> 01:13:50,400
the mix while eating an absurd
amount of cholesterol in the
1363
01:13:50,400 --> 01:13:54,680
form of something like, you
know, 133,200 milligrams of
1364
01:13:54,680 --> 01:13:58,040
cholesterol in that month, my
cholesterol option went down.
1365
01:13:58,040 --> 01:13:59,560
So it was a metabolic
demonstration.
1366
01:14:00,120 --> 01:14:02,440
It had a pretty juicy hook for a
YouTube video.
1367
01:14:02,440 --> 01:14:05,200
I had, like, all these eggs laid
out on my queen bed.
1368
01:14:05,200 --> 01:14:08,640
So the queen bed was literally
like hovered in egg cartoons
1369
01:14:08,640 --> 01:14:12,320
from Vital Farms.
The video went off beautifully.
1370
01:14:13,040 --> 01:14:15,760
It's been less than a week.
It has on YouTube well over
1371
01:14:15,760 --> 01:14:19,440
110,000 views.
And then on Instagram, the Reel
1372
01:14:19,440 --> 01:14:24,960
has something like 2 million and
Vital Farms, the company that
1373
01:14:24,960 --> 01:14:27,360
made the eggs, saw it and
they're like, this is awesome.
1374
01:14:27,560 --> 01:14:30,160
And we're going to award you a
year's free supply of eggs.
1375
01:14:30,160 --> 01:14:33,640
So that was unexpected.
But yeah, now I am.
1376
01:14:33,760 --> 01:14:35,840
I'm going to get free eggs for
years that probably amount to
1377
01:14:35,840 --> 01:14:38,040
something like 8000 free eggs
from Vital Farms.
1378
01:14:38,040 --> 01:14:41,400
So people can say for the next
year that I'm bought by the big
1379
01:14:41,400 --> 01:14:44,200
egg if they want.
Although the video was created
1380
01:14:44,320 --> 01:14:46,480
without a conflict of interest
because I totally did not expect
1381
01:14:46,480 --> 01:14:48,200
that.
But somebody knocks on my door
1382
01:14:48,200 --> 01:14:50,160
and says I'm going to give you
free eggs for a year, man, I'm
1383
01:14:50,160 --> 01:14:52,000
taking that.
Heck yeah man, we we've got
1384
01:14:52,000 --> 01:14:54,640
chickens for that very reason.
I routinely eat between a dozen
1385
01:14:54,640 --> 01:14:57,400
or two dozen eggs a day, so I am
glad to hear that I'm not the
1386
01:14:57,400 --> 01:14:58,760
only one eating absurd amount of
eggs.
1387
01:14:59,640 --> 01:15:00,680
I love it.
I love it.
1388
01:15:00,680 --> 01:15:01,480
Well.
What?
1389
01:15:01,480 --> 01:15:03,120
What's the next experiment you
get at Cooking man?
1390
01:15:03,120 --> 01:15:06,960
What's on the pipeline for you?
Well, I'd already replicated.
1391
01:15:06,960 --> 01:15:09,640
I've done a few experiments on
that were similar to the egg
1392
01:15:09,640 --> 01:15:13,320
one.
The one I have upcoming is 600
1393
01:15:13,320 --> 01:15:19,040
strips of bacon per day.
I've already done it and quite
1394
01:15:19,040 --> 01:15:20,240
honestly, it's a social
experiment.
1395
01:15:20,240 --> 01:15:24,560
I'll just be very transparent.
I was very intrigued by how well
1396
01:15:24,560 --> 01:15:29,240
the egg video went off.
And I, as someone that's new to
1397
01:15:29,240 --> 01:15:32,240
social media and kind of
finagling with the YouTube
1398
01:15:32,240 --> 01:15:36,400
algorithm, I want to see what
common factors, including with,
1399
01:15:37,200 --> 01:15:41,080
you know, thumbnail title hooks
really play well.
1400
01:15:41,280 --> 01:15:43,120
So it's almost like a carbon
copy.
1401
01:15:43,320 --> 01:15:45,880
I'm not a carbon copy, but like
a very similar replica to the
1402
01:15:45,880 --> 01:15:49,760
egg video with some twists.
And I just want to see as a
1403
01:15:49,760 --> 01:15:53,000
social experiment if the
audience response is the same.
1404
01:15:53,600 --> 01:15:57,720
So that one will be coming out
in due time And I, we'll see if
1405
01:15:57,720 --> 01:16:00,040
people have fun with it.
But yeah, more of a social
1406
01:16:00,040 --> 01:16:04,040
experiment to me in in the in
the I try to be transparent
1407
01:16:04,040 --> 01:16:05,360
about what I'm doing at any
given time.
1408
01:16:05,360 --> 01:16:09,840
But like, you know, I'd love to
communicate nuance and talk
1409
01:16:09,840 --> 01:16:13,040
about data breakdown cells,
science, nature papers and
1410
01:16:13,040 --> 01:16:14,800
videos.
But like that has a cap.
1411
01:16:15,520 --> 01:16:19,720
It's a very niche area.
So how to, you know, expand the
1412
01:16:19,760 --> 01:16:22,480
audience to get people talking
more about metabolic health?
1413
01:16:22,880 --> 01:16:28,440
You know, maybe n = 1 video
might be part of the story.
1414
01:16:28,440 --> 01:16:31,000
So playing with that.
In the meantime, we'll see how
1415
01:16:31,000 --> 01:16:35,400
audience audience replies.
But yeah, hopefully I'll be
1416
01:16:36,040 --> 01:16:39,200
well, actually, I'll just leave
it that and people can we can
1417
01:16:39,200 --> 01:16:40,400
wait and see.
Love it man.
1418
01:16:40,400 --> 01:16:43,040
And if that goes viral and you
score a year's supply of bacon,
1419
01:16:43,040 --> 01:16:44,720
then you're really set.
Bacon and egg.
1420
01:16:45,000 --> 01:16:46,520
Then I just have figured it out,
right?
1421
01:16:46,520 --> 01:16:48,920
I just get free with life.
I just need to do N = 1
1422
01:16:48,920 --> 01:16:50,880
experiments with the right.
So I just choose my favorite
1423
01:16:50,880 --> 01:16:54,200
foods, do N = 1 experiments, and
I'm totally supplied and my
1424
01:16:54,200 --> 01:16:56,040
grocery budget goes to zero.
I love it.
1425
01:16:56,040 --> 01:17:00,480
That is actually the total plan.
Total plan for 2025.
1426
01:17:00,840 --> 01:17:02,080
Hey man, I can totally get
behind that.
1427
01:17:02,080 --> 01:17:06,400
I do love how how you've been
able to just rock this, the
1428
01:17:06,400 --> 01:17:09,080
content, man, like the YouTube
content, the Instagram content,
1429
01:17:09,080 --> 01:17:10,920
like you're tapping into a whole
new audience.
1430
01:17:10,920 --> 01:17:12,600
And it's, it's awesome stuff,
man.
1431
01:17:12,600 --> 01:17:15,920
The, the level of detail you
bring the table as a scientist,
1432
01:17:15,920 --> 01:17:18,840
as an academic, as a researcher
is just unmatched.
1433
01:17:18,880 --> 01:17:21,520
So by all means, keep doing it.
I appreciate it.
1434
01:17:21,520 --> 01:17:24,880
It's been it's been a fun thing
and not a lot of thing medical
1435
01:17:24,880 --> 01:17:28,360
students get to do, but it
definitely is growing quickly.
1436
01:17:28,600 --> 01:17:34,360
The YouTube's grown from like
basically nil to 70,000 Subs in
1437
01:17:34,800 --> 01:17:37,880
nine months or something.
So it's a fun thing to play
1438
01:17:37,880 --> 01:17:39,000
with.
I have to be honest.
1439
01:17:39,000 --> 01:17:44,960
And it's, it's a good outlet to
talk and learn and, and develop
1440
01:17:44,960 --> 01:17:47,760
myself as a communicator.
So anyway, I appreciate your
1441
01:17:47,760 --> 01:17:49,320
time.
Always nice to have a
1442
01:17:49,320 --> 01:17:50,840
discussion.
Always, Manuel, if there's
1443
01:17:50,840 --> 01:17:52,720
everything I can do for you,
Nick, you just let me know and
1444
01:17:52,720 --> 01:17:54,400
I'm there.
Hope to see the conference here
1445
01:17:54,400 --> 01:17:56,400
soon.
And where do you want to direct
1446
01:17:56,400 --> 01:17:58,000
people to to dive deeper into
your world?
1447
01:17:58,720 --> 01:18:02,000
Yeah, sure.
So look up Nick Norwitz,
1448
01:18:02,000 --> 01:18:06,640
NICKNORWITZ on any of your
favorite social platforms.
1449
01:18:06,640 --> 01:18:09,800
My biggest right now are Twitter
and YouTube.
1450
01:18:10,080 --> 01:18:14,760
I'm now on Instagram as well,
Threads, Facebook, LinkedIn, and
1451
01:18:14,760 --> 01:18:18,920
you can go to nicknorwitz.com.
Again, NICKNORWITZ is a kind of
1452
01:18:18,920 --> 01:18:22,840
a hub with links towards my
papers and my various socials.
1453
01:18:22,840 --> 01:18:25,600
But the nice thing about having
my name is I don't think there
1454
01:18:25,600 --> 01:18:27,320
are any other Nick Norwitz in
the world.
1455
01:18:27,320 --> 01:18:30,480
So I'm super easy to find.
You're the only one I know so
1456
01:18:30,760 --> 01:18:33,640
keep killing it man.
I'm enjoying my conversation.
1457
01:18:33,800 --> 01:18:35,800
Pleasure to know you and I look
forward to seeing you soon.
1458
01:18:36,600 --> 01:18:37,800
I appreciate it.
See you brother.
1459
01:18:37,920 --> 01:18:38,920
Bye.
Yeah.