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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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00:12:58,000 --> 00:13:01,520
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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00:13:15,920 --> 00:13:20,360
but I feel like this anecdotal 
evidence can't be ignored, and 

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00:13:20,360 --> 00:13:23,560
then once enough people have 
done it, most definitely can't 

241
00:13:23,560 --> 00:13:26,280
be ignored. 
So I think bringing or bridging 

242
00:13:26,280 --> 00:13:28,440
the gap between what you're able
to do and how you're able to 

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00:13:28,440 --> 00:13:31,880
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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00:13:37,760 --> 00:13:40,960
conventional system. 
You said some things that 

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00:13:40,960 --> 00:13:44,680
definitely resonated with my own
background, especially with 

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00:13:44,680 --> 00:13:48,120
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
00:13:52,720 --> 00:13:55,920
an idea of science that a lot of
people have, which is like, you 

251
00:13:55,920 --> 00:13:59,400
know, it's about the data, which
it is, it truly is. 

252
00:13:59,720 --> 00:14:04,520
But when it comes to personal 
decision making, it is really 

253
00:14:04,520 --> 00:14:06,920
about the stories, right? 
That's not something that can be

254
00:14:06,920 --> 00:14:08,600
discounted. 
We as humans resonate with 

255
00:14:08,600 --> 00:14:11,440
stories. 
So it sounds like your mom 

256
00:14:11,440 --> 00:14:14,560
really responded to your story. 
And actually the same with my 

257
00:14:14,560 --> 00:14:17,400
mom. 
She's now a keto, and she 

258
00:14:17,400 --> 00:14:21,400
adopted a ketogenic diet after 
me because, you know, she saw 

259
00:14:21,400 --> 00:14:23,200
how well it worked for me. 
And she's reaped her own 

260
00:14:23,200 --> 00:14:24,800
benefits, although they're 
distinct. 

261
00:14:25,880 --> 00:14:28,400
So it really is the stories that
change people's minds. 

262
00:14:28,400 --> 00:14:33,320
And, you know, that's something 
that if you were to talk to me 

263
00:14:33,320 --> 00:14:36,800
three years ago, I would have 
discounted a little bit. 

264
00:14:36,800 --> 00:14:40,640
I think the idea of anecdotes 
has a, well, I know the term 

265
00:14:40,640 --> 00:14:46,040
anecdotes has negative 
connotation, but when we think 

266
00:14:46,040 --> 00:14:51,880
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

268
00:14:54,880 --> 00:14:57,200
resonate with people the same 
way that stories do. 

269
00:14:57,600 --> 00:15:00,520
And so I think what you need to 
do when you're telling or you're

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00:15:00,520 --> 00:15:02,960
teaching science, talking about 
data, is you need to find a way 

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00:15:02,960 --> 00:15:06,400
to tell a story around the data.
Anybody that ever written a 

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00:15:06,400 --> 00:15:08,600
paper and gotten it published 
even knows this, like you need 

273
00:15:08,600 --> 00:15:11,560
to tell a story around the data.
And now that's a tricky thing 

274
00:15:11,560 --> 00:15:13,880
because of course, in telling a 
story around the data, you're 

275
00:15:13,880 --> 00:15:16,960
always going to introduce 
biases, you know, your 

276
00:15:16,960 --> 00:15:18,520
interpretations based on your 
framing. 

277
00:15:18,520 --> 00:15:19,840
Like that's the nature of 
things. 

278
00:15:19,840 --> 00:15:24,880
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

280
00:15:32,360 --> 00:15:36,320
and direct and emotionless, the 
body of science that results is 

281
00:15:36,320 --> 00:15:39,440
a function of humans telling 
stories about what the data are 

282
00:15:39,440 --> 00:15:42,600
showing. 
Yeah, and humans are, so it's 

283
00:15:42,600 --> 00:15:43,240
not. 
Bad. 

284
00:15:43,240 --> 00:15:45,040
It's something we need to 
acknowledge in order to deal 

285
00:15:45,040 --> 00:15:47,560
with the practicalities that 
arise, including the narratives 

286
00:15:47,560 --> 00:15:49,360
that get propagated around 
things like nutrition. 

287
00:15:49,720 --> 00:15:51,440
Yeah, 100%. 
And nutrition is tricky, man, 

288
00:15:51,440 --> 00:15:55,080
because humans are so we're, 
we're so, we're so fickle. 

289
00:15:55,080 --> 00:15:58,000
Like we with any other animal. 
There's no debate as to what, 

290
00:15:58,640 --> 00:16:01,320
you know, types of foods they 
should consume, but there's such

291
00:16:01,320 --> 00:16:04,280
a, you know, societal 
standpoint, such an emotional 

292
00:16:04,280 --> 00:16:09,160
standpoint tie with food and 
human consumption that is very 

293
00:16:09,160 --> 00:16:11,640
triggering for people for 
whatever reason. 

294
00:16:11,640 --> 00:16:15,600
And it like I'm trying to bridge
the gap as I know you are as 

295
00:16:15,600 --> 00:16:18,200
well, because I, you know, 
having been brought up in the 

296
00:16:18,200 --> 00:16:22,680
scientific community, I do place
a lot of emphasis on quality 

297
00:16:22,680 --> 00:16:26,680
data, But I'm also trying to, 
you know, take stock in the 

298
00:16:26,680 --> 00:16:29,560
anecdotal evidence and what is 
sustainable and what is, you 

299
00:16:29,560 --> 00:16:32,040
know, optimal from a health and 
well-being and vitality 

300
00:16:32,040 --> 00:16:34,240
standpoint. 
And oftentimes those don't sync 

301
00:16:34,240 --> 00:16:35,680
up. 
So I'll bring people on the 

302
00:16:35,680 --> 00:16:39,600
podcast like the Lane Norton's 
of the world as I respect their 

303
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 

306
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 

308
00:16:59,360 --> 00:17:00,840
feeding study. 
We have all these other 

309
00:17:00,840 --> 00:17:02,840
variables at play and we have to
be realistic. 

310
00:17:04,079 --> 00:17:05,560
Yeah. 
I think we can talk through now 

311
00:17:05,560 --> 00:17:08,599
a framework of kind of how to do
that, reconcile the anecdotes 

312
00:17:08,599 --> 00:17:13,240
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. 

317
00:17:26,839 --> 00:17:29,360
There's no doubt in my mind that
ketogenic diet was highly 

318
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
00:17:34,040 --> 00:17:38,600
myself, but it's also backed 
with my medical history. 

321
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. 

323
00:17:42,040 --> 00:17:43,760
Nothing worked. 
And I tried this and it worked. 

324
00:17:44,120 --> 00:17:46,160
It improved my symptoms. 
My inflammatory markers went 

325
00:17:46,160 --> 00:17:48,240
down, and on biopsy there was no
disease. 

326
00:17:48,960 --> 00:17:52,320
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.

331
00:18:04,520 --> 00:18:06,880
It just means we haven't 
properly asked the questions and

332
00:18:06,880 --> 00:18:09,480
investigated it. 
So I think sometimes people 

333
00:18:09,480 --> 00:18:15,040
confuse absence of evidence with
evidence of absence and say this

334
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
00:18:19,880 --> 00:18:23,760
never really been investigated. 
And on top of that, there are 

336
00:18:23,760 --> 00:18:29,440
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 

340
00:18:37,800 --> 00:18:41,120
themselves to human RC TS. 
So we really just have to cobble

341
00:18:41,120 --> 00:18:46,880
together the data we have access
to be that human RC TS and 

342
00:18:46,880 --> 00:18:51,320
Cochrane reviews or just 
biologic possibility in animal 

343
00:18:51,320 --> 00:18:55,520
studies. 
And then I think use those to 

344
00:18:55,520 --> 00:18:58,880
frame the stories we we are 
hearing and we are telling each 

345
00:18:58,880 --> 00:19:01,160
other. 
And if anecdotes are arising 

346
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
00:19:15,920 --> 00:19:19,160
themselves? 
Or is there something new and 

351
00:19:19,160 --> 00:19:21,800
unique to learn here? 
And at the end of the day, I 

352
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
00:19:36,800 --> 00:19:39,560
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
00:20:15,120 --> 00:20:17,440
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 

373
00:20:20,400 --> 00:20:24,080
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.