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 Welcome to the VP Life Podcast, the show

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 where we bring you actionable health

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 advice from leading minds.

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 I'm your host, Rob.

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 My guest today is Joel Green, author of

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 The Immunity Code and the Way, and a

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 pioneer of immune-centric nutrition whose

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 work has completely reframed how many of

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 us think about metabolism,

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 aging, and the gut immune access.

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 Expect to learn why excess iron and the

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 Fenton reaction may be the hidden driver

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 of oxidative stress,

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 ferroptosis, and accelerated aging.

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 How lactoferrin, food-first strategies,

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 and the smart use of tools like IP6 and

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 phlebotomy can help control iron while

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 supporting gut and immune health.

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 And Joel's latest thinking on metabolism,

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 muscle gain, sugar diets, and how his

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 deep range fits into the bigger picture

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 of long-term health and performance.

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 Now, on to the

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 conversation with Joel Green.

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 Good morning, John.

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 Thank you for being here

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 and joining us on the podcast.

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 I know it's early there, so yeah, thank

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 you for being flexible.

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 Like I mentioned, or fair, this is a

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 conversation I've been pretty sacked out

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 for a while now, so yeah, like I said,

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 bit fanboyish, but what can I say?

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 So I suppose I first heard

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 about you, learned about you,

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 when a lot of people did back when you

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 first appeared on Ben Green's Perfels

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 podcast, or was that kind of circuit

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 2020, 2021, somewhere around there.

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 In any case, yeah, like I said, you

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 pretty much framed, reframed everything I

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 sort of understood about sort of biology,

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 and especially as it

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 pertains to nutrition.

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 And again, sort of, I spent five years in

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 textbooks, and then sort of took a long,

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 deep sort of soul searching, looked at

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 everything and thought, why?

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 Anyway, that's me, of course.

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 And I know that while there are many on

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 our audience who are likely familiar with

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 you and your story, there

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 are probably those who aren't.

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 So yeah, just your backstory, we have

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 plenty of time for the details.

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 Over to you.

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 Yeah, well, first of all,

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 thank you for having me.

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 It's a pleasure, and

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 looking forward to the condo.

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 Just kind of briefly, my backstory,

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 I just, my mother was, my mother was just

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 a failed competitive athlete, I think, in

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 the sense that she never really competed,

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 but she was hyper competitive.

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 And so she always encouraged us or me.

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 And so just from the time I was five, you

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 know, fitness was part of my life.

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 Growing up watching Jacqueline, and then

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 I was kind of my family's personal

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 trainer, like, you know, trying to get

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 him to do calisthenics at age seven, and

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 then get them to run around the block.

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 And I got into weightlifting about fourth

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 grade, where I just took apart a hammock.

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 And I just started kind of because my

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 brother used to beat me up all the time.

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 So I thought maybe if I could do this,

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 you know, I could, so I started just

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 doing curls, whatever I

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 could figure out with these bars.

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 And I actually started gaining a little

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 bit of muscle oddly, you

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 know, like in the fourth grade.

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 So and then I wanted to

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 be fast in the fifth grade.

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 And so I started going to the blacktop

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 during the summers and sprinting, because

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 I really wasn't very fast.

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 And the running craze kind of blew.

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 So this is way back.

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 This is like way back during the 70s.

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 So the running craze kind of bloomed, and

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 I got into running, and I could see that

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 my quads were coming out as a kid.

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 I didn't really

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 understand like what that was.

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 I just thought it was cool.

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 So I was always into it.

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 I was always tracking bodybuilding really

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 kind of just, I would just say you're

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 prototypical consumer, like if you could

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 just stamp like, you know, like sycophant

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 consumer, that was me.

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 And so I was lucky enough to go to high

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 school in San Jose, California, where at

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 that time during the, I guess it was the

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 mid 70s, late 70s, early 80s.

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 But a treasure trove of Olympic athletes

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 trained at this local junior college, you

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 had the gold medalist in the discus, Mack

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 Wilkins, you had Bruce Jenner, you had

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 you know, all these

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 Olympic athletes training there.

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 And there was a spillover to my high

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 school because my high school coach was

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 himself an Olympic level pole halter, who

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 was pretty renowned in the

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 area as the best vault coach.

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 And so all the Olympic athletes would

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 come over to train there.

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 So we had quite the quite the advanced

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 weight training program.

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 I mean, it was it wasn't bodybuilding.

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 It was it was Soviet style power, Soviet

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 style training, like like cleaning jerks,

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 and you know, stuff like that.

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 So and my big thing was, yeah,

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 yeah, exactly.

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 Yeah.

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 My big thing was I had a growth spurt

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 right about one of us right about age 12.

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 And I shot up to six

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 to by the time I was 12.

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 And I was 160 pounds.

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 So I was so skinny.

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 I was I was I was I was embarrassed to go

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 to school, like because I was so skinny.

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 So I always wear long sleeve shirts,

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 because I didn't want

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 anybody see how skinny I was.

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 And so I just started going to the gym

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 every night and just doing

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 what the power lifters were doing.

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 So I was just doing cleaning jerks, you

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 know, like, like nonstop.

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 And it just became part of my life.

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 So I became your

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 prototypical bodybuilding.

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 Sick of fan.

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 Yeah.

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 And I was just I would devour everything

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 and anything in the magazines.

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 And, you know, starting in the early 80s,

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 when Tom Platts exploded, and, you know,

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 just I just tracked everything.

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 And back then, the interesting thing was,

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 the way that information was

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 disseminated, you didn't have

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 influencers, which you

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 had was the magazines.

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 And then the magazines kind of promoted

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 who they wanted to be stars.

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 And so you had this

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 controlled information source.

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 And so you had this this thing of like,

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 you know, well, how do

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 I get to look like you?

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 What do I have to do?

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 I'll do whatever you do.

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 And of course, it was

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 all a giant deception.

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 It was, you know, the huge scam, because

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 all these guys were on steroids.

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 And they just lied their butts off about

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 it, like literally everybody.

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 And so the thing was like, you could

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 never actually look like that.

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 Okay, you might get close, you might look

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 pretty good if you're genetically gifted,

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 but you're never gonna be like that,

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 because they're there, they've got a

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 secret you don't have.

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 So I went down that track as a consumer.

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 And because I was so voracious as a

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 reader, whatever came

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 out, I would jump on.

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 So like, I remember, I think it was 86,

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 there was a supplement that

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 came out called hot stuff.

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 And the marketing was

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 very different back then.

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 Like back then, the marketing was they'd

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 write an entire page, and

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 you would read the whole page.

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 You would go long from copy.

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 Yeah.

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 And just get sucked into it, you know,

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 and so out came this supplement with

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 boron and, you know, wild game and you

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 know, all of these things that a lot of

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 them actually worked like yo and vine.

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 And stuff.

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 And I just started whatever came out, I

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 would just use so that led into that led

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 into MCTs kind of in the late 80s, when I

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 was in college at UCI.

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 And then in the early 90s, the big big

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 thing for me was the

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 meal replacement craze.

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 So metrics came out.

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 And I didn't,

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 I wasn't that was the the original sort

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 of meal replacement in the same space,

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 wasn't it just about

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 well, it was it was the first

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 that really thought about it.

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 So that so prior to that, what it did was

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 it changed the category.

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 So prior to metrics, they were called

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 metabolic optimizers.

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 And the leader was champion nutrition,

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 and other guys that were

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 sticking MCTs in theirs.

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 And then Dr.

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 Scott Conley came out.

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 And he really thought his thing through

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 and he really knew

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 what he was talking about.

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 So his big thing was he stuck in

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 glutamine and lactoferrin in metrics.

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 And that was light years and I had a few

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 conversations with him actually, because

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 he owned a gym right where I lived.

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 And so and he would work the front desk,

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 like an MD working

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 the front desk at a gym.

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 So I just I would go in and after

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 training, just kind of ask

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 him like, Hey, does this work?

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 And he would just he would go down the

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 bio babble role, and I would just kind of

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 sit there kind of glazed over like maybe

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 picking up every hundredth

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 word he was talking about.

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 But so that led me down this road of a

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 lifetime of doing that stuff.

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 Which is ironic, because today where I

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 sit is I you know, I go to the gym once

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 or twice a week, I do that

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 stuff once or twice a week.

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 But it's not the main thing I do.

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 And it's certainly not the thing that I

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 think keeps you young.

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 I think it does the reverse, I think it

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 destroys the body over time.

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 But the irony of that was that now that's

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 where all the doctors are.

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 So they've all adopted meat headology.

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 They've all adopted the the

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 the pattern of of, you know,

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 they call they don't call it 70s

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 bodybuilding, they

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 call it strength training.

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 Oh, no, you got to do strength training.

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 Yeah, it's a Gabriel lines of the world

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 that sort of approach.

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 Yeah, when you break down what they're

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 talking about what to do, well, what is

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 it I should be doing?

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 Well, strength

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 training, what's that look like?

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 Oh, well, see, here's a lat row.

274
00:09:17,500 --> 00:09:19,833
 Oh, the thing we were doing in the 70s.

275
00:09:19,833 --> 00:09:20,000
 Yeah.

276
00:09:20,291 --> 00:09:21,750
 Okay, here's a behind the neck press.

277
00:09:22,166 --> 00:09:23,166
 Yeah, yeah, that one too.

278
00:09:23,708 --> 00:09:24,125
 What else?

279
00:09:24,125 --> 00:09:25,291
 What else you got a T bar row?

280
00:09:25,291 --> 00:09:27,250
 Yeah, yeah, that was in the 70s too.

281
00:09:27,250 --> 00:09:27,833
 So bodybuilding.

282
00:09:28,041 --> 00:09:29,458
 So the answer is bodybuilding.

283
00:09:29,666 --> 00:09:30,541
 No, no, it's not because I

284
00:09:30,541 --> 00:09:31,166
 tell you, I've been there.

285
00:09:31,166 --> 00:09:31,458
 It's not.

286
00:09:33,208 --> 00:09:36,958
 So about 2006, I kind of culminated for

287
00:09:36,958 --> 00:09:40,250
 me, I was, I was running a company, we

288
00:09:40,250 --> 00:09:42,666
 had our revenue had just shot up to like

289
00:09:42,666 --> 00:09:45,375
 25 million in just

290
00:09:45,375 --> 00:09:46,375
 two years from nothing.

291
00:09:47,041 --> 00:09:48,000
 And it's not bad.

292
00:09:48,708 --> 00:09:49,083
 Yeah.

293
00:09:49,416 --> 00:09:52,875
 And, and like a lot of entrepreneurs, I

294
00:09:52,875 --> 00:09:55,916
 was working crazy hours of crazy stress.

295
00:09:56,916 --> 00:09:59,750
 And for me, the kind of hands on

296
00:09:59,750 --> 00:10:03,333
 discovery was that that stuff only works

297
00:10:03,333 --> 00:10:04,750
 when you're in the fitness bubble.

298
00:10:05,250 --> 00:10:08,541
 Yeah, if you get out of that bubble, and

299
00:10:08,541 --> 00:10:10,916
 it doesn't work that great.

300
00:10:11,416 --> 00:10:13,708
 And I just I got really well, the

301
00:10:13,708 --> 00:10:16,083
 interesting thing is, um, I was training.

302
00:10:16,458 --> 00:10:17,458
 So I was huge.

303
00:10:17,958 --> 00:10:20,041
 I mean, I was, I was just big, I was

304
00:10:20,041 --> 00:10:21,708
 about 260 pounds, I was fat.

305
00:10:22,250 --> 00:10:23,625
 So I was both hugely

306
00:10:23,625 --> 00:10:25,541
 muscular and fat at the same time.

307
00:10:26,416 --> 00:10:29,333
 Super strong muscles, like but fat.

308
00:10:30,500 --> 00:10:32,166
 And so I kind of came out of that,

309
00:10:32,166 --> 00:10:34,125
 rethinking things and that led to where

310
00:10:34,125 --> 00:10:35,458
 I'm at today, basically.

311
00:10:36,666 --> 00:10:37,791
 Thank you for that.

312
00:10:37,791 --> 00:10:39,500
 That was, that was an amazing story and

313
00:10:39,541 --> 00:10:40,500
 one I've heard before.

314
00:10:41,083 --> 00:10:43,541
 And yeah, just speaks volumes to what

315
00:10:43,541 --> 00:10:45,166
 you've been able to sort of develop over

316
00:10:45,166 --> 00:10:46,333
 the years consequently, because I know

317
00:10:46,333 --> 00:10:48,500
 you've fundamentally just worked all of

318
00:10:48,500 --> 00:10:50,750
 this out, sort of on the back end of

319
00:10:50,750 --> 00:10:51,625
 different life

320
00:10:51,625 --> 00:10:53,333
 experiences that you've had.

321
00:10:53,333 --> 00:10:55,958
 And I know you've obviously talked about

322
00:10:55,958 --> 00:10:58,291
 this a lot on various podcasts, including

323
00:10:58,291 --> 00:11:01,041
 Mark Bell's one, I believe, when you

324
00:11:01,041 --> 00:11:03,041
 originally, I think was a Daisy Carter

325
00:11:03,041 --> 00:11:05,208
 protocol that you originally did, and

326
00:11:05,208 --> 00:11:07,958
 then you sort of got down to what was it,

327
00:11:07,958 --> 00:11:09,416
 single digital body fat, and he was

328
00:11:09,416 --> 00:11:13,208
 completely sort of just in disbelief of

329
00:11:13,208 --> 00:11:14,166
 this fact at the time.

330
00:11:14,166 --> 00:11:15,166
 Is that more or less correct?

331
00:11:15,708 --> 00:11:15,916
 Yeah.

332
00:11:16,041 --> 00:11:19,000
 So basically it was, it was 2007.

333
00:11:19,625 --> 00:11:21,666
 I had been, I had been at it for about a

334
00:11:21,666 --> 00:11:24,166
 year, just whittling down all the fat I'd

335
00:11:24,166 --> 00:11:26,791
 gained during that period, working.

336
00:11:27,583 --> 00:11:32,333
 And I was about 229 and pretty, pretty

337
00:11:32,333 --> 00:11:33,958
 muscular, you know, but,

338
00:11:33,958 --> 00:11:35,458
 but still kind of not peeled.

339
00:11:36,500 --> 00:11:37,500
 And then I did the, I

340
00:11:37,500 --> 00:11:38,250
 did the Daisy Carter.

341
00:11:38,916 --> 00:11:41,458
 And that was probably for me, the single

342
00:11:41,458 --> 00:11:45,666
 most shocking body fat thing in my entire

343
00:11:45,666 --> 00:11:47,541
 life ever still to this day, because I

344
00:11:47,541 --> 00:11:50,250
 went from 229 to 212 in seven days.

345
00:11:50,250 --> 00:11:54,708
 And then I went into a local place that

346
00:11:54,708 --> 00:11:56,125
 measures your body fat in water.

347
00:11:56,916 --> 00:12:01,500
 And it was, it was either between six and

348
00:12:01,500 --> 00:12:02,458
 seven, it was pretty low.

349
00:12:02,708 --> 00:12:05,125
 And that was, that was after, that was

350
00:12:05,125 --> 00:12:07,750
 after pigging out, like for several days

351
00:12:07,750 --> 00:12:09,125
 coming off the day because the Daisy

352
00:12:09,125 --> 00:12:10,083
 Carter will make you insane.

353
00:12:11,500 --> 00:12:12,416
 So coming off that I was just eating

354
00:12:12,416 --> 00:12:13,625
 pizza or whatever I get.

355
00:12:13,625 --> 00:12:14,625
 So I'm sure I was probably lower.

356
00:12:15,291 --> 00:12:17,541
 And then there was just a, I was in a

357
00:12:17,541 --> 00:12:20,500
 tech stream with Mark Bell and quest

358
00:12:20,500 --> 00:12:23,458
 owner Ron Pena and Carl Carlin or and

359
00:12:23,458 --> 00:12:25,375
 Mark, I was telling about that and Mark's

360
00:12:25,375 --> 00:12:26,458
 like, I don't believe you prove it.

361
00:12:26,458 --> 00:12:28,166
 So I just, I just sent him the, the PDF,

362
00:12:28,166 --> 00:12:30,541
 I called the place up and said, Hey, I,

363
00:12:30,625 --> 00:12:32,458
 you know, can you give me the PDF?

364
00:12:32,458 --> 00:12:33,125
 And they sent it to me

365
00:12:33,125 --> 00:12:34,125
 and I just sent it to Mark.

366
00:12:34,125 --> 00:12:35,583
 And so fair.

367
00:12:35,958 --> 00:12:36,791
 Anyway, perfect.

368
00:12:37,750 --> 00:12:38,041
 Okay.

369
00:12:38,041 --> 00:12:39,375
 So what I really want to do

370
00:12:39,375 --> 00:12:40,916
 today is to dig into iron.

371
00:12:40,916 --> 00:12:41,916
 I know that people are always

372
00:12:41,916 --> 00:12:44,083
 interested in the sugar diet.

373
00:12:45,125 --> 00:12:46,958
 And to be honest, that excites me about

374
00:12:46,958 --> 00:12:48,125
 as much as watching paint dry.

375
00:12:48,833 --> 00:12:50,791
 We'll keep the, we'll, we'll

376
00:12:50,791 --> 00:12:52,000
 aim to keep the people happy.

377
00:12:52,000 --> 00:12:52,625
 And maybe we can chat

378
00:12:52,625 --> 00:12:53,958
 about that a little later on.

379
00:12:53,958 --> 00:12:56,458
 To start with, I think it would be, maybe

380
00:12:56,458 --> 00:12:57,875
 it would be best if we just step back a

381
00:12:57,875 --> 00:12:59,041
 little to discuss the

382
00:12:59,041 --> 00:13:00,041
 immune system as a whole.

383
00:13:00,041 --> 00:13:01,500
 I know that's fundamentally the lens

384
00:13:01,500 --> 00:13:04,000
 through which you sort of view metabolism

385
00:13:04,000 --> 00:13:06,000
 and health in general, and just to

386
00:13:06,000 --> 00:13:07,333
 provide some context, maybe

387
00:13:07,333 --> 00:13:08,333
 the rest of the conversation.

388
00:13:08,958 --> 00:13:12,291
 Now, obviously, I started off with with

389
00:13:12,291 --> 00:13:14,208
 the immunity code, your first book, which

390
00:13:14,208 --> 00:13:15,500
 for anyone who's not read

391
00:13:15,500 --> 00:13:17,250
 it is, is absolute gold.

392
00:13:17,583 --> 00:13:18,708
 So yeah, get a copy.

393
00:13:20,000 --> 00:13:21,875
 Now, of course, I know from here, we

394
00:13:21,875 --> 00:13:23,333
 could go into 30 different directions,

395
00:13:23,333 --> 00:13:24,583
 all of which are fundamentally going to

396
00:13:24,583 --> 00:13:26,166
 be come back to the fact that by

397
00:13:26,166 --> 00:13:27,666
 regulating the immune system of the gut,

398
00:13:28,500 --> 00:13:31,416
 you can make a dent in a lot of health

399
00:13:31,416 --> 00:13:33,541
 conditions and challenges.

400
00:13:34,083 --> 00:13:36,083
 So yeah, I'll ask the lazy question,

401
00:13:36,333 --> 00:13:39,041
 which is, what problems were you trying

402
00:13:39,041 --> 00:13:40,541
 to solve with the immunity code, and

403
00:13:40,541 --> 00:13:43,958
 subsequently, your follow up the way?

404
00:13:44,416 --> 00:13:48,375
 The primary problem is really the problem

405
00:13:48,416 --> 00:13:52,666
 everybody runs into, which is, there's a

406
00:13:52,666 --> 00:13:56,125
 force pushing against you over time.

407
00:13:56,958 --> 00:13:58,750
 Loosely, we could describe that as aging.

408
00:13:59,875 --> 00:14:01,791
 But the big picture of that is that it

409
00:14:01,791 --> 00:14:04,541
 has multiple pathways for dysregulation.

410
00:14:05,250 --> 00:14:07,125
 So, you know, one is that body fat is

411
00:14:07,125 --> 00:14:09,458
 going up, senescent cells are going up,

412
00:14:09,458 --> 00:14:10,791
 inflammation is going up,

413
00:14:11,875 --> 00:14:13,250
 mitochondrial density is going down,

414
00:14:13,500 --> 00:14:15,791
 muscle is going down, body fat

415
00:14:15,791 --> 00:14:18,250
 characteristics are shifting into a

416
00:14:18,250 --> 00:14:19,916
 pro-inflammatory pattern, all kinds of

417
00:14:19,916 --> 00:14:20,625
 all kinds of things are

418
00:14:20,625 --> 00:14:21,666
 happening all at once.

419
00:14:22,500 --> 00:14:24,291
 And everybody faces these problems

420
00:14:24,291 --> 00:14:25,583
 collectively, they haven't really been

421
00:14:25,583 --> 00:14:28,833
 well defined as a group to say, okay,

422
00:14:28,833 --> 00:14:30,666
 well, let's make a list and let's start

423
00:14:30,666 --> 00:14:32,041
 with number one and go down the list.

424
00:14:32,041 --> 00:14:32,541
 Let's do that.

425
00:14:33,750 --> 00:14:35,791
 And even if they were made into a list,

426
00:14:36,041 --> 00:14:37,500
 the problem you're still going

427
00:14:37,500 --> 00:14:39,250
 to have is the issue of time.

428
00:14:40,041 --> 00:14:43,458
 The average person, so the big secret in

429
00:14:43,458 --> 00:14:44,375
 the fitness bubble is

430
00:14:44,375 --> 00:14:45,333
 just two hours a day.

431
00:14:45,833 --> 00:14:46,333
 I mean, no one's ever

432
00:14:46,333 --> 00:14:47,125
 going to tell you that.

433
00:14:47,125 --> 00:14:49,125
 But that is the C, if you were to follow

434
00:14:49,125 --> 00:14:50,833
 anybody around, you're going to see

435
00:14:50,833 --> 00:14:51,958
 they're putting into it.

436
00:14:51,958 --> 00:14:53,166
 That's like two hours a day.

437
00:14:53,166 --> 00:14:55,083
 That's like, who has that?

438
00:14:55,666 --> 00:14:57,333
 Who has two hours a day?

439
00:14:57,583 --> 00:14:57,791
 Yeah.

440
00:14:58,291 --> 00:14:59,125
 So that's the problem.

441
00:14:59,583 --> 00:15:01,916
 The problem is you've got

442
00:15:01,916 --> 00:15:04,041
 this problem of decline.

443
00:15:04,708 --> 00:15:07,250
 And then the only solution that you've

444
00:15:07,250 --> 00:15:08,750
 been given to solve it is, oh, that's no

445
00:15:08,750 --> 00:15:10,000
 problem, just increase time.

446
00:15:10,500 --> 00:15:12,125
 Just increase time, that'll solve it.

447
00:15:12,500 --> 00:15:13,875
 That doesn't work for most people.

448
00:15:14,666 --> 00:15:16,500
 So for me, the issue really was just

449
00:15:16,500 --> 00:15:19,583
 coming down to economy and looking at,

450
00:15:19,583 --> 00:15:22,416
 well, if we only had a couple of minutes

451
00:15:22,416 --> 00:15:24,500
 a day, what would be the most important

452
00:15:24,500 --> 00:15:25,833
 things that we could hit

453
00:15:25,833 --> 00:15:27,125
 in a couple of minutes?

454
00:15:27,791 --> 00:15:29,000
 What would be the 80-20?

455
00:15:30,041 --> 00:15:33,166
 It wouldn't be doing barbell curls.

456
00:15:33,166 --> 00:15:34,375
 That wouldn't really be the thing.

457
00:15:34,375 --> 00:15:34,916
 What would it be?

458
00:15:35,791 --> 00:15:37,583
 And when you begin to go down that road,

459
00:15:37,583 --> 00:15:40,208
 where you're going to wind up at is the

460
00:15:40,208 --> 00:15:42,291
 intersection between the immune system

461
00:15:42,291 --> 00:15:45,958
 and several different organ sets and

462
00:15:45,958 --> 00:15:47,125
 systems in the body.

463
00:15:47,583 --> 00:15:48,250
 One way or another,

464
00:15:48,250 --> 00:15:49,583
 you're going to run into that.

465
00:15:49,750 --> 00:15:50,500
 So fundamentally,

466
00:15:51,250 --> 00:15:52,541
 let's start with oxygen.

467
00:15:53,666 --> 00:15:55,541
 Just getting oxygen into the body.

468
00:15:56,375 --> 00:15:58,041
 What's happening with most people with

469
00:15:58,041 --> 00:16:00,666
 age is that the

470
00:16:00,666 --> 00:16:02,041
 airway begins to collapse.

471
00:16:03,333 --> 00:16:05,750
 The tissue at the back of the throat

472
00:16:05,750 --> 00:16:06,916
 begins to push into

473
00:16:06,916 --> 00:16:07,708
 the back of the throat.

474
00:16:08,083 --> 00:16:09,375
 So you're getting apnea

475
00:16:09,375 --> 00:16:10,416
 events during sleeping.

476
00:16:10,416 --> 00:16:11,958
 You're getting desats during sleeping.

477
00:16:12,625 --> 00:16:13,500
 You're getting stabilized

478
00:16:13,500 --> 00:16:15,000
 hypoxia as a result of that.

479
00:16:15,333 --> 00:16:17,458
 And that alone will sink the whole ship.

480
00:16:18,125 --> 00:16:19,958
 That alone will kill you.

481
00:16:20,791 --> 00:16:21,375
 Just that.

482
00:16:21,666 --> 00:16:22,625
 Hypronorpha levels, right?

483
00:16:23,250 --> 00:16:23,458
 Yeah.

484
00:16:23,833 --> 00:16:26,041
 That alone will sink the entire ship.

485
00:16:26,041 --> 00:16:27,125
 We don't even need to look any farther

486
00:16:27,125 --> 00:16:28,625
 than that if you were going to just start

487
00:16:28,625 --> 00:16:29,708
 with, well, what's number one?

488
00:16:30,125 --> 00:16:31,083
 That's number one,

489
00:16:31,083 --> 00:16:32,291
 really, if you think about it.

490
00:16:32,291 --> 00:16:34,250
 And that converges on a key mechanism

491
00:16:34,250 --> 00:16:38,000
 that essentially is a switch, helping the

492
00:16:38,000 --> 00:16:40,625
 body flip its metabolic state between

493
00:16:40,625 --> 00:16:41,916
 oxidative respiration

494
00:16:41,916 --> 00:16:43,541
 and then glycolysis.

495
00:16:45,208 --> 00:16:46,666
 When you look at that, and

496
00:16:46,666 --> 00:16:49,000
 that master switch is HIF-1,

497
00:16:50,125 --> 00:16:52,541
 hypoxia-inducible factor one, it

498
00:16:52,541 --> 00:16:56,375
 regulates not just the general switching

499
00:16:56,375 --> 00:16:58,958
 between metabolic states, but

500
00:16:58,958 --> 00:17:00,708
 tissue-specific and cell-specific.

501
00:17:01,041 --> 00:17:03,458
 And when you get cell-specific, it gets

502
00:17:03,458 --> 00:17:05,208
 very, very interesting and compelling.

503
00:17:05,791 --> 00:17:07,625
 So when you begin to look at the effect

504
00:17:07,625 --> 00:17:10,291
 of that on immune cells, it can be

505
00:17:10,291 --> 00:17:12,166
 massively beneficial or

506
00:17:12,166 --> 00:17:13,958
 catastrophically disastrous.

507
00:17:14,541 --> 00:17:16,625
 It just depends on the tissue and what.

508
00:17:17,458 --> 00:17:20,333
 But in terms of our coming back out of

509
00:17:20,333 --> 00:17:22,666
 the deep dive into what's our simple fix,

510
00:17:23,500 --> 00:17:24,708
 it's let's fix that first.

511
00:17:25,083 --> 00:17:25,916
 Why don't we fix that?

512
00:17:26,166 --> 00:17:27,750
 And that converges on the immune system.

513
00:17:27,750 --> 00:17:28,916
 And so that whole line of thinking, that

514
00:17:28,916 --> 00:17:31,375
 way of thinking led me down this road.

515
00:17:32,416 --> 00:17:32,583
 Okay.

516
00:17:32,583 --> 00:17:32,833
 Fair enough.

517
00:17:33,333 --> 00:17:35,416
 And then just specifically, what about it

518
00:17:35,416 --> 00:17:37,916
 is, I suppose, just to maybe elaborate

519
00:17:38,166 --> 00:17:40,833
 that a bit more for the audience, how

520
00:17:40,833 --> 00:17:43,208
 does the immune system then regulate and

521
00:17:43,208 --> 00:17:45,333
 govern the subsequent inflammatory

522
00:17:45,333 --> 00:17:47,958
 responses in the body that then drive so

523
00:17:47,958 --> 00:17:50,500
 much of this dysfunction at a level?

524
00:17:51,666 --> 00:17:55,000
 So it's a big question.

525
00:17:57,166 --> 00:18:00,291
 One of the key functions of the immune

526
00:18:00,291 --> 00:18:05,500
 system is to sort of allocate when to use

527
00:18:05,500 --> 00:18:07,083
 what we would call weapons.

528
00:18:08,000 --> 00:18:08,208
 Okay.

529
00:18:08,500 --> 00:18:10,416
 One of the weapons the immune system has

530
00:18:10,416 --> 00:18:12,375
 is to induce an inflammatory state.

531
00:18:13,000 --> 00:18:15,041
 Now that can be massively beneficial in

532
00:18:15,041 --> 00:18:17,000
 the case of an infection, because you

533
00:18:17,000 --> 00:18:18,041
 want to kill the infection.

534
00:18:18,041 --> 00:18:19,708
 So the immune system can ramp up and it

535
00:18:19,708 --> 00:18:21,458
 can produce free radicals and shoot

536
00:18:21,458 --> 00:18:23,666
 superoxide through immune cells and

537
00:18:23,666 --> 00:18:25,250
 pathogens and invaders.

538
00:18:25,250 --> 00:18:26,083
 And that's a good thing.

539
00:18:27,708 --> 00:18:29,833
 That's not such a good thing when you

540
00:18:29,833 --> 00:18:31,916
 have billions of cells that have

541
00:18:31,916 --> 00:18:35,083
 stabilized into a senescent state and are

542
00:18:35,083 --> 00:18:38,166
 essentially trafficking out signals to

543
00:18:38,166 --> 00:18:39,416
 recruit the immune system.

544
00:18:39,875 --> 00:18:41,916
 That's not such a good thing at all.

545
00:18:41,916 --> 00:18:43,250
 Because then what happens is the immune

546
00:18:43,250 --> 00:18:44,875
 system sort of acts like an echo chamber.

547
00:18:45,625 --> 00:18:47,875
 And it propagates these signals across

548
00:18:47,875 --> 00:18:50,500
 the entire body and recruits more and

549
00:18:50,500 --> 00:18:53,041
 more and more resources into dealing with

550
00:18:53,041 --> 00:18:56,666
 this problem that it thinks is an injury,

551
00:18:56,666 --> 00:18:57,958
 but it really it's just getting old.

552
00:18:58,333 --> 00:19:00,500
 So what it is, would that be a case where

553
00:19:00,500 --> 00:19:02,000
 maybe somewhere like excess fasting could

554
00:19:02,000 --> 00:19:03,666
 actually be an issue,

555
00:19:03,666 --> 00:19:04,416
 an actual detriment?

556
00:19:05,416 --> 00:19:05,625
 Yes.

557
00:19:06,708 --> 00:19:11,166
 Yes, because this gets to the

558
00:19:11,166 --> 00:19:13,125
 body needs to balance itself.

559
00:19:13,125 --> 00:19:15,458
 It needs a balance between growth

560
00:19:15,458 --> 00:19:19,166
 pathways and degradation pathways or

561
00:19:19,166 --> 00:19:20,958
 however you want to put it, you know, the

562
00:19:20,958 --> 00:19:23,041
 body's autophagic pathways.

563
00:19:23,541 --> 00:19:24,250
 There needs to be a

564
00:19:24,250 --> 00:19:25,291
 balance between the two.

565
00:19:25,916 --> 00:19:27,625
 And when you see an excess of either one,

566
00:19:28,291 --> 00:19:29,125
 you're going to see some kind of

567
00:19:29,125 --> 00:19:30,500
 pathology either way.

568
00:19:30,791 --> 00:19:32,291
 So if you see too much growth, you're

569
00:19:32,291 --> 00:19:33,416
 probably going to see cancer.

570
00:19:33,416 --> 00:19:34,958
 If you see too much, too

571
00:19:34,958 --> 00:19:36,791
 much autophagy, too much

572
00:19:38,500 --> 00:19:40,583
 action with respect to protein

573
00:19:40,583 --> 00:19:41,458
 degradation, then

574
00:19:41,458 --> 00:19:42,916
 you're going to see issues.

575
00:19:44,083 --> 00:19:44,125
 So

576
00:19:45,500 --> 00:19:46,708
 that's just homeostasis.

577
00:19:47,583 --> 00:19:48,958
 So that's an interesting thing.

578
00:19:48,958 --> 00:19:49,416
 I don't want to spend

579
00:19:49,416 --> 00:19:49,916
 too much time on this.

580
00:19:49,958 --> 00:19:56,125
 But homeostasis is such a simple concept.

581
00:19:56,583 --> 00:19:58,000
 It's so simple to get this.

582
00:19:58,000 --> 00:19:59,333
 It's just simply

583
00:20:00,541 --> 00:20:01,000
 balance.

584
00:20:01,583 --> 00:20:04,500
 Like the thing needs to be balanced.

585
00:20:04,708 --> 00:20:07,083
 You can't be too much on either side.

586
00:20:07,750 --> 00:20:07,958
 Okay.

587
00:20:08,375 --> 00:20:09,208
 That's so simple.

588
00:20:09,916 --> 00:20:12,708
 And you wouldn't know it, listening to

589
00:20:12,708 --> 00:20:14,250
 the world of influencers nowadays,

590
00:20:14,625 --> 00:20:16,833
 because it's all polarized thinking.

591
00:20:17,375 --> 00:20:19,291
 It's all, "Oh yeah, fasting's only good.

592
00:20:22,000 --> 00:20:23,083
 Meat is only good.

593
00:20:23,333 --> 00:20:25,041
 Saturated fats is only good.

594
00:20:25,333 --> 00:20:26,291
 Carbs are only bad."

595
00:20:26,708 --> 00:20:28,041
 You know, there's this polarity of

596
00:20:28,041 --> 00:20:30,500
 thought that to me reflects a bigger

597
00:20:30,500 --> 00:20:32,000
 problem, a problem of thought.

598
00:20:32,875 --> 00:20:35,416
 But the fact that such a simple concept

599
00:20:35,416 --> 00:20:38,000
 is missing from the picture and it's

600
00:20:38,000 --> 00:20:40,708
 essential just blows my mind.

601
00:20:41,333 --> 00:20:43,208
 Yeah, I know it is interesting that you

602
00:20:43,208 --> 00:20:44,041
 mentioned that actually.

603
00:20:44,541 --> 00:20:46,625
 I mean, there are sort of, and I'll just

604
00:20:46,625 --> 00:20:48,291
 use it in the literal sense, sort of very

605
00:20:48,291 --> 00:20:50,833
 left and far and right leaning

606
00:20:50,833 --> 00:20:52,666
 individuals just sort of on

607
00:20:52,666 --> 00:20:54,833
 the vegan and the carnival side.

608
00:20:54,833 --> 00:20:56,541
 And it's interesting just watching your

609
00:20:56,541 --> 00:20:58,166
 poor saladinas and such over the world

610
00:20:58,166 --> 00:20:59,458
 with these sort of extreme views.

611
00:21:00,000 --> 00:21:01,958
 And what I've just found over the years

612
00:21:01,958 --> 00:21:03,541
 is that a lot of these people with these

613
00:21:03,541 --> 00:21:06,208
 extreme views on nutrition generally tend

614
00:21:06,208 --> 00:21:07,916
 to fall back to the middle, whether it's

615
00:21:07,916 --> 00:21:09,625
 reintroducing honey or carbohydrates, or

616
00:21:09,625 --> 00:21:11,541
 what have you, or reintroducing meat.

617
00:21:13,500 --> 00:21:16,750
 So many, yeah, just to sort of maybe sort

618
00:21:16,750 --> 00:21:17,875
 of build on your point.

619
00:21:20,041 --> 00:21:21,625
 Balance is key and it's just interesting

620
00:21:21,625 --> 00:21:24,166
 to note that people with sort of extreme

621
00:21:24,166 --> 00:21:27,000
 views ultimately do come back to sort of

622
00:21:27,000 --> 00:21:28,500
 this fairly centered state.

623
00:21:30,708 --> 00:21:32,291
 And Joel, I'd like to sort of maybe take

624
00:21:32,291 --> 00:21:34,333
 a little bit more into that, into the gut

625
00:21:34,333 --> 00:21:36,583
 side of it quickly before we carry on.

626
00:21:36,875 --> 00:21:40,041
 Now, I know obviously sort of the gut

627
00:21:40,041 --> 00:21:42,208
 being sort of the hub of the immune

628
00:21:42,208 --> 00:21:43,458
 system to an extent anyway.

629
00:21:44,000 --> 00:21:47,250
 A lot of your work sort of that you've

630
00:21:47,250 --> 00:21:49,458
 put out there revolves heavily around

631
00:21:49,458 --> 00:21:51,625
 sort of rebuilding the gut and that you

632
00:21:51,625 --> 00:21:53,625
 aren't generally speaking a fan of

633
00:21:53,625 --> 00:21:54,833
 prebiotics and that you would,

634
00:21:55,583 --> 00:21:57,416
 probiotics, excuse me, that you generally

635
00:21:57,416 --> 00:22:00,250
 sort of prefer prebiotics as a whole.

636
00:22:00,708 --> 00:22:03,666
 Obviously, again, within the industry and

637
00:22:03,666 --> 00:22:06,000
 there's always been a

638
00:22:06,000 --> 00:22:07,166
 push for probiotics.

639
00:22:07,416 --> 00:22:10,458
 And I'm in two months about that.

640
00:22:11,083 --> 00:22:13,000
 I deeply admire the work of Dr.

641
00:22:13,000 --> 00:22:15,166
 Mark Ruschow, who you might know of, and

642
00:22:15,166 --> 00:22:17,291
 he is a very sort of probiotic

643
00:22:17,291 --> 00:22:21,541
 forward-facing and he's very adamant that

644
00:22:21,541 --> 00:22:23,750
 they are effective at helping

645
00:22:23,750 --> 00:22:25,541
 to modulate the immune system.

646
00:22:26,500 --> 00:22:29,041
 I know at least having listened to other

647
00:22:29,041 --> 00:22:31,041
 podcasts you've done that you share,

648
00:22:31,750 --> 00:22:33,041
 maybe someone to have a

649
00:22:33,041 --> 00:22:34,041
 different take on that.

650
00:22:34,041 --> 00:22:36,416
 Could you sort of just guard us through

651
00:22:36,416 --> 00:22:37,916
 your thoughts on probiotics versus

652
00:22:37,916 --> 00:22:40,250
 prebiotics in general as it pertains to

653
00:22:40,250 --> 00:22:41,083
 the gut and maybe the

654
00:22:41,083 --> 00:22:42,041
 immune system more broadly?

655
00:22:42,958 --> 00:22:45,166
 Well, the merger point

656
00:22:45,166 --> 00:22:47,125
 in the road is bacteria.

657
00:22:47,541 --> 00:22:50,291
 That's all we're talking about is taxa

658
00:22:50,291 --> 00:22:52,125
 and representation of species.

659
00:22:52,416 --> 00:22:53,250
 That's what we're talking about.

660
00:22:53,250 --> 00:22:54,583
 The question is, how do we get there?

661
00:22:54,833 --> 00:22:55,416
 That's the only thing

662
00:22:55,416 --> 00:22:56,291
 we're talking about.

663
00:22:56,833 --> 00:22:59,625
 So to say that probiotics work is to say

664
00:22:59,625 --> 00:23:01,500
 that certain taxa can

665
00:23:01,500 --> 00:23:02,750
 exert beneficial effects.

666
00:23:03,583 --> 00:23:03,791
 Duh.

667
00:23:04,000 --> 00:23:04,916
 I mean, we all know that.

668
00:23:04,916 --> 00:23:05,916
 Everybody knows that, right?

669
00:23:05,916 --> 00:23:07,125
 So it's just how do we get there?

670
00:23:07,125 --> 00:23:08,791
 What's the optimal way to get there?

671
00:23:09,625 --> 00:23:10,625
 Keeping in mind not the

672
00:23:10,625 --> 00:23:11,958
 short term, but the long term.

673
00:23:12,625 --> 00:23:14,000
 And that's a problem.

674
00:23:14,791 --> 00:23:16,291
 That's a big problem though, because

675
00:23:16,291 --> 00:23:17,375
 we're in an industry

676
00:23:17,375 --> 00:23:22,083
 that equates results to...

677
00:23:23,333 --> 00:23:27,500
 We're in an industry that has no regard

678
00:23:27,500 --> 00:23:29,625
 for the impact of the most important

679
00:23:29,625 --> 00:23:30,916
 variable, which is time.

680
00:23:31,291 --> 00:23:32,041
 It doesn't exist.

681
00:23:32,750 --> 00:23:33,708
 Time does not exist.

682
00:23:34,458 --> 00:23:36,458
 You listen to the most high level

683
00:23:36,458 --> 00:23:40,541
 influencers and they'll talk as if the

684
00:23:40,541 --> 00:23:42,875
 outcome we get now is going to be the

685
00:23:42,875 --> 00:23:43,708
 outcome we're always going

686
00:23:43,708 --> 00:23:44,833
 to get because we got it now.

687
00:23:45,750 --> 00:23:47,166
 And again, that's going back to this

688
00:23:47,166 --> 00:23:48,541
 paucity or poverty of

689
00:23:48,541 --> 00:23:50,291
 thinking that is just...

690
00:23:50,875 --> 00:23:52,833
 It's similar to homeostasis.

691
00:23:53,083 --> 00:23:55,416
 When you begin to inventory, why aren't

692
00:23:55,416 --> 00:23:56,500
 you taking this into account?

693
00:23:57,041 --> 00:23:58,000
 There's no good reason.

694
00:23:58,583 --> 00:23:59,666
 There's no good reason.

695
00:23:59,666 --> 00:24:00,333
 Only stupidity.

696
00:24:01,458 --> 00:24:03,333
 So the issue becomes,

697
00:24:04,375 --> 00:24:08,541
 okay, so there seems to be sort of a

698
00:24:08,541 --> 00:24:12,500
 youthful profile that more or less seems

699
00:24:12,500 --> 00:24:14,625
 to be consistent among young people.

700
00:24:14,625 --> 00:24:16,958
 And you see a lot of Bifidobacteria,

701
00:24:17,750 --> 00:24:18,958
 healthy representations

702
00:24:18,958 --> 00:24:20,000
 kind of in this respect.

703
00:24:21,041 --> 00:24:23,583
 And it's quantifiable to some degree.

704
00:24:25,500 --> 00:24:26,125
 So the question is, how

705
00:24:26,125 --> 00:24:27,958
 can we proximate that?

706
00:24:27,958 --> 00:24:28,750
 How can we get there?

707
00:24:29,916 --> 00:24:32,625
 I'm not against probiotics at all.

708
00:24:32,875 --> 00:24:33,500
 I think that they can

709
00:24:33,500 --> 00:24:34,666
 be incredibly helpful.

710
00:24:34,666 --> 00:24:36,833
 I'm just against their indiscriminate

711
00:24:36,833 --> 00:24:39,041
 use, particularly among consumers,

712
00:24:39,041 --> 00:24:40,375
 because as soon as you tell consumers,

713
00:24:41,375 --> 00:24:45,125
 hey, our clinical results showed an

714
00:24:45,125 --> 00:24:46,541
 improvement of blah, blah, blah, blah,

715
00:24:46,791 --> 00:24:48,125
 blah, taking our probiotic.

716
00:24:48,125 --> 00:24:48,583
 First, they're probiotic.

717
00:24:48,791 --> 00:24:49,041
 Yeah.

718
00:24:49,958 --> 00:24:52,750
 Well, then they become chiclets.

719
00:24:53,000 --> 00:24:54,166
 They become like M&Ms

720
00:24:55,208 --> 00:24:56,541
 or just gummies.

721
00:24:56,833 --> 00:24:58,000
 They become like just candy.

722
00:24:58,958 --> 00:25:01,000
 And the net result of that, once we

723
00:25:01,000 --> 00:25:02,541
 insert the variable of time, is that

724
00:25:02,541 --> 00:25:03,583
 you're probably going to do more harm

725
00:25:03,583 --> 00:25:04,333
 than good long-term.

726
00:25:04,666 --> 00:25:08,791
 A lot of SIBO problems now are the result

727
00:25:08,791 --> 00:25:13,208
 of a lot of probiotic usage going back.

728
00:25:13,500 --> 00:25:17,125
 And so the question becomes, what's the

729
00:25:17,125 --> 00:25:18,541
 optimal way to get what we want?

730
00:25:19,000 --> 00:25:19,958
 And the really

731
00:25:20,958 --> 00:25:23,791
 surprising thing is how powerful food is,

732
00:25:24,291 --> 00:25:28,208
 to completely, completely retune the gut

733
00:25:28,208 --> 00:25:29,791
 in very short periods.

734
00:25:29,791 --> 00:25:31,708
 And this is empirical in its nature.

735
00:25:31,708 --> 00:25:33,416
 Going back to 2009, there are studies

736
00:25:33,416 --> 00:25:36,750
 that show that you can rapidly recolonize

737
00:25:36,750 --> 00:25:39,125
 the gut in just a few days with food.

738
00:25:39,958 --> 00:25:41,000
 So with that in mind,

739
00:25:42,208 --> 00:25:45,708
 as a generality, if food is so powerful,

740
00:25:46,583 --> 00:25:48,125
 where do we need probiotics?

741
00:25:48,541 --> 00:25:49,625
 And that becomes a

742
00:25:49,625 --> 00:25:50,958
 medical issue then, I think.

743
00:25:51,666 --> 00:25:54,791
 And I do believe the rightful home of

744
00:25:54,791 --> 00:25:59,041
 probiotic strain usage is probably with

745
00:25:59,041 --> 00:26:02,416
 practitioners who can look at something,

746
00:26:02,416 --> 00:26:04,291
 look at a GI map and say, "It seems like

747
00:26:04,291 --> 00:26:05,500
 maybe if we added this

748
00:26:05,500 --> 00:26:06,791
 strain for a few weeks."

749
00:26:06,791 --> 00:26:08,375
 Now that, to me, is really intelligent.

750
00:26:08,375 --> 00:26:09,041
 That's really smart.

751
00:26:09,916 --> 00:26:10,458
 And I think that's kind

752
00:26:10,458 --> 00:26:11,541
 of the right way to do it.

753
00:26:12,083 --> 00:26:14,875
 It's just really a question of what's

754
00:26:14,875 --> 00:26:15,875
 going to do more harm than good.

755
00:26:15,875 --> 00:26:16,541
 And it's probably the

756
00:26:16,541 --> 00:26:18,083
 indiscriminate use of probiotics.

757
00:26:18,875 --> 00:26:19,166
 Fair enough.

758
00:26:19,541 --> 00:26:20,791
 Just speaking of those tests quickly,

759
00:26:22,166 --> 00:26:22,875
 there are a bunch of them

760
00:26:22,875 --> 00:26:24,083
 out there, various labs.

761
00:26:26,958 --> 00:26:27,708
 Well, as you

762
00:26:27,708 --> 00:26:29,083
 mentioned, there's the GI map.

763
00:26:29,125 --> 00:26:31,250
 There are a bunch of them.

764
00:26:32,041 --> 00:26:33,541
 What do you think about their validity

765
00:26:33,541 --> 00:26:34,708
 and their specificity?

766
00:26:36,083 --> 00:26:37,833
 Again, now that we're just on this track,

767
00:26:37,833 --> 00:26:38,333
 I'd just love to get

768
00:26:38,333 --> 00:26:39,125
 your thoughts on this.

769
00:26:39,791 --> 00:26:41,541
 You often hear practitioners on podcasts

770
00:26:41,541 --> 00:26:43,000
 talk about the fact that they sent off

771
00:26:43,000 --> 00:26:48,083
 two samples of the same piece of stool to

772
00:26:48,083 --> 00:26:50,958
 the same company, and they would have got

773
00:26:50,958 --> 00:26:53,125
 back completely different results on

774
00:26:53,125 --> 00:26:54,833
 their GI map or their whatever.

775
00:26:56,125 --> 00:26:57,333
 I mean, the gut is your

776
00:26:57,333 --> 00:26:58,250
 game, let's be honest.

777
00:26:58,916 --> 00:26:59,750
 Do you have any thoughts

778
00:26:59,750 --> 00:27:01,416
 on GI testing in general?

779
00:27:01,416 --> 00:27:02,791
 Do you think it's there yet?

780
00:27:02,791 --> 00:27:05,375
 Or is it still a bit of a north star

781
00:27:05,375 --> 00:27:06,083
 we're trying to get to?

782
00:27:06,791 --> 00:27:07,833
 I think it could be useful.

783
00:27:08,500 --> 00:27:09,500
 I think it could be useful.

784
00:27:09,500 --> 00:27:12,625
 I think the mistake is to see it as

785
00:27:14,166 --> 00:27:14,666
 the gospel.

786
00:27:15,291 --> 00:27:17,541
 I think it's a mistake to

787
00:27:17,541 --> 00:27:19,916
 calcify it into like, "Oh, ha!

788
00:27:20,416 --> 00:27:21,500
 Well, this is me.

789
00:27:21,750 --> 00:27:22,291
 That's it.

790
00:27:22,333 --> 00:27:24,083
 Nothing more to know."

791
00:27:25,500 --> 00:27:29,541
 What I never hear are seldom, very

792
00:27:29,541 --> 00:27:32,375
 seldom, what you'll hear is a breakdown

793
00:27:32,500 --> 00:27:33,791
 of mechanistically,

794
00:27:34,125 --> 00:27:34,958
 "How'd you get that answer?"

795
00:27:36,125 --> 00:27:38,416
 When you begin to ask,

796
00:27:39,125 --> 00:27:41,125
 you'll get crickets because

797
00:27:42,333 --> 00:27:43,166
 I've found a lot of

798
00:27:43,166 --> 00:27:44,083
 practitioners don't know.

799
00:27:44,291 --> 00:27:45,208
 They actually don't know

800
00:27:45,208 --> 00:27:46,708
 how they wrote that answer.

801
00:27:47,666 --> 00:27:49,500
 When you begin to break that down, what

802
00:27:49,500 --> 00:27:50,708
 you find is that many of

803
00:27:50,708 --> 00:27:52,583
 those tests rely on a single gene.

804
00:27:53,416 --> 00:27:57,000
 They're looking for one gene, the 16RS

805
00:27:57,000 --> 00:28:00,916
 ribosomal RNA, and they have a database

806
00:28:00,916 --> 00:28:01,541
 that they're matching

807
00:28:01,541 --> 00:28:02,541
 that gene up against.

808
00:28:03,083 --> 00:28:04,791
 The outcome you're getting is only as

809
00:28:04,791 --> 00:28:05,625
 good as your database.

810
00:28:06,875 --> 00:28:07,875
 Then there are several

811
00:28:07,875 --> 00:28:09,041
 problems within that.

812
00:28:10,041 --> 00:28:12,625
 We could list what those problems are,

813
00:28:12,625 --> 00:28:17,041
 but just suffice to say that a good

814
00:28:17,041 --> 00:28:18,041
 example is acromancia.

815
00:28:18,625 --> 00:28:20,791
 I think in the last couple years, there

816
00:28:20,791 --> 00:28:21,791
 have been several new

817
00:28:21,791 --> 00:28:23,500
 strains discovered of acromancia.

818
00:28:24,458 --> 00:28:26,500
 One of the most common things that I hear

819
00:28:26,500 --> 00:28:28,583
 is, "Oh, I did a GI map

820
00:28:28,583 --> 00:28:30,291
 test and I have no acromancia."

821
00:28:30,291 --> 00:28:31,041
 My response to that

822
00:28:31,041 --> 00:28:31,875
 usually is, "Yeah, you do.

823
00:28:32,500 --> 00:28:33,750
 They just can't test for it."

824
00:28:34,416 --> 00:28:35,208
 "No, how do you know that?"

825
00:28:35,208 --> 00:28:35,791
 "Because you'd be dead,

826
00:28:35,791 --> 00:28:36,750
 probably, if you didn't."

827
00:28:36,750 --> 00:28:38,416
 Yeah, it's more than just

828
00:28:38,416 --> 00:28:40,000
 meanest failure in existence.

829
00:28:40,833 --> 00:28:44,958
 The truth is there's probably dozens of

830
00:28:44,958 --> 00:28:46,083
 strains we haven't yet found.

831
00:28:46,875 --> 00:28:48,291
 To get a GI map test back, and it says,

832
00:28:48,291 --> 00:28:49,875
 "Oh my gosh, I have no acromancia.

833
00:28:49,875 --> 00:28:50,916
 I better go start taking

834
00:28:50,916 --> 00:28:53,375
 pendulum or some tool like that."

835
00:28:54,041 --> 00:28:56,041
 Well, again, it's like,

836
00:28:56,041 --> 00:28:57,291
 "Mm, yeah, you probably do."

837
00:28:57,291 --> 00:28:57,958
 It's just the tests

838
00:28:57,958 --> 00:28:59,541
 don't have that in there.

839
00:28:59,541 --> 00:29:01,291
 They don't have these undiscovered

840
00:29:01,291 --> 00:29:02,416
 strains in the database.

841
00:29:02,416 --> 00:29:03,041
 That's the answer.

842
00:29:03,916 --> 00:29:04,250
 Fair enough.

843
00:29:04,625 --> 00:29:08,666
 I often think that this is a sort of

844
00:29:08,666 --> 00:29:09,500
 wildlife-ure approach.

845
00:29:09,916 --> 00:29:14,375
 It reduces it to the bare basics and then

846
00:29:14,375 --> 00:29:16,041
 just sort of builds upon that instead of

847
00:29:16,041 --> 00:29:18,125
 trying to sort of isolate variables that

848
00:29:18,125 --> 00:29:21,625
 we don't have access to.

849
00:29:22,500 --> 00:29:28,000
 I really like the way you frame and

850
00:29:28,000 --> 00:29:28,958
 conceptualize things.

851
00:29:29,250 --> 00:29:30,875
 To be honest, I'm not very bright.

852
00:29:32,083 --> 00:29:33,875
 I doubt that.

853
00:29:34,333 --> 00:29:35,291
 I seriously doubt that.

854
00:29:35,583 --> 00:29:38,375
 I tend to just look towards using

855
00:29:38,375 --> 00:29:40,833
 frameworks to try and understand complex

856
00:29:40,833 --> 00:29:42,000
 topics and data sets.

857
00:29:42,916 --> 00:29:45,583
 Then, yeah, maybe it's just a result of

858
00:29:45,583 --> 00:29:47,333
 looking at information from that point of

859
00:29:47,333 --> 00:29:50,333
 view, but I always end up trying to find

860
00:29:50,333 --> 00:29:52,083
 flaws in a given model, a

861
00:29:52,083 --> 00:29:53,333
 stress test the best I can.

862
00:29:54,416 --> 00:29:57,750
 Well, to me, I can then form an opinion.

863
00:29:58,791 --> 00:30:00,541
 I can then try and find

864
00:30:00,541 --> 00:30:05,041
 limitations based on that

865
00:30:06,541 --> 00:30:08,291
 opinion relative to that model.

866
00:30:08,291 --> 00:30:09,583
 I can then sort of make cross-reference

867
00:30:09,583 --> 00:30:12,708
 things and try and come to some sort of

868
00:30:12,708 --> 00:30:13,666
 logical conclusion,

869
00:30:13,666 --> 00:30:15,125
 whether it's correct or not.

870
00:30:16,416 --> 00:30:19,166
 I know that's a fairly convoluted, but

871
00:30:19,166 --> 00:30:21,208
 it's kind of served me well.

872
00:30:22,458 --> 00:30:24,250
 Of course, it doesn't mean I'm right.

873
00:30:24,250 --> 00:30:25,500
 It's just the way I think through things.

874
00:30:26,416 --> 00:30:28,291
 I'd love to sort of explore the way you

875
00:30:28,291 --> 00:30:30,958
 think through things and whether you

876
00:30:30,958 --> 00:30:32,458
 think there are any sort of limitations

877
00:30:32,458 --> 00:30:35,166
 to the model that you've put forward when

878
00:30:35,166 --> 00:30:38,666
 it comes to helping people work through

879
00:30:38,666 --> 00:30:39,541
 various health challenges.

880
00:30:40,166 --> 00:30:42,375
 I'm sorry, that was probably 10 questions

881
00:30:42,375 --> 00:30:44,458
 in one and very convoluted, but I'm sure

882
00:30:44,458 --> 00:30:45,750
 you follow the logic.

883
00:30:46,375 --> 00:30:47,083
 Yeah, no, I like it.

884
00:30:47,083 --> 00:30:47,416
 I like it.

885
00:30:48,250 --> 00:30:51,416
 I kind of approach things

886
00:30:51,416 --> 00:30:54,875
 from a macro perspective in that

887
00:30:56,875 --> 00:30:58,666
 there's a bit of a dichotomy with respect

888
00:30:58,666 --> 00:31:01,250
 to how do we get the answer?

889
00:31:01,250 --> 00:31:02,041
 People always want to

890
00:31:02,041 --> 00:31:03,458
 know, what's the answer?

891
00:31:03,708 --> 00:31:04,291
 What's the answer?

892
00:31:06,041 --> 00:31:09,458
 We're led to think that the

893
00:31:09,458 --> 00:31:11,625
 individualized factors just are the

894
00:31:11,625 --> 00:31:14,166
 answer, that they're so overpowering that

895
00:31:14,166 --> 00:31:17,000
 the only way that I can know me is I got

896
00:31:17,000 --> 00:31:18,750
 to go do all these tests that tell me me.

897
00:31:20,166 --> 00:31:22,625
 Just in my experience, what I have found

898
00:31:22,625 --> 00:31:23,791
 is it's the generalities

899
00:31:23,791 --> 00:31:25,000
 where all the horsepower is.

900
00:31:25,583 --> 00:31:28,791
 If you take five massive generalities,

901
00:31:29,125 --> 00:31:31,291
 like let's take vitamin D levels, let's

902
00:31:31,291 --> 00:31:36,500
 take hypoxia, let's take the microbiome,

903
00:31:37,291 --> 00:31:39,083
 and you see where I'm going with this.

904
00:31:39,083 --> 00:31:40,875
 You can just kind of go down this road of

905
00:31:40,875 --> 00:31:42,500
 things that are just generalities.

906
00:31:42,958 --> 00:31:45,208
 Then you take someone who their metabolic

907
00:31:45,208 --> 00:31:46,583
 state is and optimal

908
00:31:46,583 --> 00:31:47,500
 isn't what they want it to be.

909
00:31:47,500 --> 00:31:48,250
 We just apply the

910
00:31:48,250 --> 00:31:50,625
 generalities to them consistently.

911
00:31:50,958 --> 00:31:52,958
 What you will see are these massive

912
00:31:52,958 --> 00:31:55,041
 game-changing improvements

913
00:31:56,083 --> 00:31:58,458
 that are life-changing.

914
00:31:59,750 --> 00:32:02,333
 That's not getting to the level of like,

915
00:32:02,333 --> 00:32:03,000
 "Well, I see you're

916
00:32:03,000 --> 00:32:04,625
 missing a genetic snip for it."

917
00:32:04,625 --> 00:32:05,708
 It's not getting to that level.

918
00:32:05,708 --> 00:32:06,833
 It's just taking the generalities.

919
00:32:07,666 --> 00:32:09,833
 So I generally tend to approach things

920
00:32:09,833 --> 00:32:12,791
 like, "Let's fix the low-hanging fruit.

921
00:32:13,458 --> 00:32:14,833
 Let's go after that and

922
00:32:14,833 --> 00:32:15,875
 then see where we're at."

923
00:32:16,583 --> 00:32:17,500
 Then usually with what's

924
00:32:17,500 --> 00:32:18,708
 left, that's called medicine.

925
00:32:20,208 --> 00:32:22,625
 Usually with what's left, now we're

926
00:32:22,625 --> 00:32:25,208
 talking about things that don't fit the

927
00:32:25,208 --> 00:32:28,541
 generalities, things that require very

928
00:32:28,541 --> 00:32:29,875
 types of specific tests.

929
00:32:29,875 --> 00:32:31,333
 That's really for doctors to do.

930
00:32:31,750 --> 00:32:32,708
 I think that's great.

931
00:32:33,125 --> 00:32:34,416
 I think that's where it should be.

932
00:32:35,750 --> 00:32:37,833
 But all that to say, it's that what we're

933
00:32:37,833 --> 00:32:39,625
 missing here is that in the simple

934
00:32:39,625 --> 00:32:42,500
 things, the big things, the generalities,

935
00:32:42,500 --> 00:32:44,583
 there's so much horsepower, so much power

936
00:32:44,583 --> 00:32:49,416
 for change that you should really,

937
00:32:50,250 --> 00:32:53,208
 collectively, it makes sense to take a

938
00:32:53,208 --> 00:32:54,333
 look at those things first

939
00:32:54,333 --> 00:32:55,958
 and then see where we're at.

940
00:32:55,958 --> 00:32:57,500
 That's just how I approach things.

941
00:32:58,333 --> 00:32:59,208
 The other piece of the

942
00:32:59,208 --> 00:33:00,458
 equation for me is math.

943
00:33:02,125 --> 00:33:03,833
 I've just found historically that

944
00:33:03,833 --> 00:33:05,125
 everything boils down to math.

945
00:33:06,583 --> 00:33:07,625
 Everything boils down to

946
00:33:07,625 --> 00:33:08,583
 the law of large numbers.

947
00:33:08,916 --> 00:33:10,541
 Everything boils down to

948
00:33:10,541 --> 00:33:11,791
 percentages and probabilities.

949
00:33:12,583 --> 00:33:13,833
 That lends me to think in a couple

950
00:33:13,833 --> 00:33:14,625
 different directions.

951
00:33:14,625 --> 00:33:16,708
 One is that it's very difficult to know

952
00:33:16,708 --> 00:33:17,708
 anything with certainty.

953
00:33:18,875 --> 00:33:21,041
 It's just very difficult to know it, but

954
00:33:21,041 --> 00:33:22,166
 the mind loves certainty.

955
00:33:22,416 --> 00:33:23,333
 The mind loves,

956
00:33:24,416 --> 00:33:26,291
 "Ah, yes, this is it."

957
00:33:28,833 --> 00:33:33,708
 You really see that in the social media

958
00:33:33,708 --> 00:33:36,833
 sphere where you have influencers that

959
00:33:36,833 --> 00:33:40,541
 speak with salesman-like certainty on

960
00:33:40,541 --> 00:33:42,291
 topics they don't actually understand.

961
00:33:43,208 --> 00:33:44,500
 Then a few years down the road,

962
00:33:44,500 --> 00:33:46,291
 completely revise their stance.

963
00:33:47,166 --> 00:33:48,833
 That's called a learning curve.

964
00:33:51,083 --> 00:33:53,041
 What would serve them and everybody else

965
00:33:53,041 --> 00:33:56,666
 better is to just begin to introduce some

966
00:33:56,666 --> 00:33:59,291
 maybes in there and some mightbees and

967
00:33:59,291 --> 00:34:00,916
 possibilities rather than

968
00:34:00,916 --> 00:34:02,541
 speaking with abject certainty.

969
00:34:03,291 --> 00:34:10,375
 We're always up against degrees of

970
00:34:10,375 --> 00:34:13,458
 probabilities, probabilistic space.

971
00:34:13,916 --> 00:34:17,416
 We can begin to say things like, "Well,

972
00:34:17,416 --> 00:34:19,541
 we're creating very strong probabilities

973
00:34:19,541 --> 00:34:20,750
 that we might get the

974
00:34:20,750 --> 00:34:21,833
 outcome that we want."

975
00:34:22,458 --> 00:34:24,500
 I'm just really just cloaking math talk

976
00:34:24,500 --> 00:34:26,916
 by talking like that, but

977
00:34:26,916 --> 00:34:27,833
 that's how I approach things.

978
00:34:28,708 --> 00:34:29,875
 Okay, perfect.

979
00:34:29,875 --> 00:34:30,583
 Thank you very much.

980
00:34:30,583 --> 00:34:31,625
 I just had to ask.

981
00:34:32,375 --> 00:34:35,416
 I love the way you build on

982
00:34:36,416 --> 00:34:38,541
 the data that you've always gotten.

983
00:34:39,041 --> 00:34:42,625
 It's just so elegant the way you are able

984
00:34:42,625 --> 00:34:46,833
 to frame and construct relationships.

985
00:34:47,333 --> 00:34:48,958
 A bit of a selfish question, but anyway.

986
00:34:50,583 --> 00:34:52,875
 I recently had the chance to chat to Dr.

987
00:34:52,916 --> 00:34:53,833
 Thomas Seafreet.

988
00:34:53,833 --> 00:34:56,416
 I'm sure you're familiar with, and for

989
00:34:56,416 --> 00:34:57,958
 those in the audience who aren't or maybe

990
00:34:57,958 --> 00:35:00,083
 haven't listened to that podcast, he's

991
00:35:00,083 --> 00:35:01,750
 currently championing the idea that

992
00:35:01,750 --> 00:35:05,083
 cancer is fundamentally a metabolic and

993
00:35:05,083 --> 00:35:06,208
 mitochondrial disease.

994
00:35:06,458 --> 00:35:10,125
 That's by regulating glucose metabolism

995
00:35:10,125 --> 00:35:12,250
 in some way, shape, or form, you can

996
00:35:12,250 --> 00:35:14,125
 essentially starve cancer cells

997
00:35:14,125 --> 00:35:17,041
 selectively and reduce the need to some

998
00:35:17,041 --> 00:35:19,291
 extent for additional or

999
00:35:19,291 --> 00:35:20,625
 adunctive cancer therapies.

1000
00:35:21,791 --> 00:35:23,083
 Obviously, his work is based in the

1001
00:35:23,083 --> 00:35:25,125
 backbone of what Otto Warburg did, I

1002
00:35:25,125 --> 00:35:27,041
 think probably around a century ago now.

1003
00:35:29,125 --> 00:35:31,291
 In any case, he's obviously a big

1004
00:35:31,291 --> 00:35:32,000
 proponent of

1005
00:35:32,000 --> 00:35:34,833
 carbohydrate reduction in general.

1006
00:35:35,291 --> 00:35:37,208
 Unfortunately, we ran out of time.

1007
00:35:37,666 --> 00:35:39,833
 I wasn't really able to ask him about his

1008
00:35:39,833 --> 00:35:42,041
 thoughts on how different types of fatty

1009
00:35:42,041 --> 00:35:44,500
 acids, polyunsaturated fatty acids,

1010
00:35:44,833 --> 00:35:45,791
 saturated fats, et

1011
00:35:45,791 --> 00:35:49,208
 cetera, might affect his model.

1012
00:35:50,375 --> 00:35:52,708
 I'm not a cancer biologist.

1013
00:35:53,541 --> 00:35:55,583
 I'm strictly the imagination, but when

1014
00:35:55,583 --> 00:35:59,041
 you look at his glucose ketone index,

1015
00:36:00,041 --> 00:36:02,833
 which I know he's now making more

1016
00:36:02,833 --> 00:36:04,291
 publicly available for people to

1017
00:36:04,291 --> 00:36:05,625
 understand their own metabolic health,

1018
00:36:06,041 --> 00:36:06,833
 it's very much

1019
00:36:06,833 --> 00:36:08,958
 focused on the macro level.

1020
00:36:09,166 --> 00:36:10,833
 It doesn't seem to really

1021
00:36:10,833 --> 00:36:13,375
 focus on the fatty acids.

1022
00:36:13,375 --> 00:36:14,875
 I know this goes into the order of

1023
00:36:14,875 --> 00:36:16,541
 operations side of it as well.

1024
00:36:17,666 --> 00:36:19,750
 But what do you generally think about

1025
00:36:19,750 --> 00:36:22,208
 when you start talking about fatty acids

1026
00:36:22,208 --> 00:36:24,375
 in particular and the

1027
00:36:24,375 --> 00:36:25,541
 immune system in the gut?

1028
00:36:26,458 --> 00:36:28,000
 What do you think about

1029
00:36:28,000 --> 00:36:30,625
 this approach in general about

1030
00:36:31,833 --> 00:36:34,750
 removing one macronutrient, be it

1031
00:36:34,750 --> 00:36:36,333
 carbohydrates, to

1032
00:36:36,333 --> 00:36:38,208
 improve the health of a system?

1033
00:36:38,250 --> 00:36:40,916
 And then, yeah, if you've got any

1034
00:36:40,916 --> 00:36:46,166
 thoughts on maybe how we overly rely on,

1035
00:36:46,500 --> 00:36:47,875
 I suppose that's the C to all debate.

1036
00:36:48,208 --> 00:36:50,291
 Let's leave that if you, yeah, the first

1037
00:36:50,291 --> 00:36:51,041
 part would be great.

1038
00:36:52,500 --> 00:36:53,500
 Again,

1039
00:36:55,083 --> 00:36:56,333
 the variable that's missing

1040
00:36:56,333 --> 00:36:59,750
 in my opinion would be time.

1041
00:37:00,541 --> 00:37:02,958
 So you could inject that question in

1042
00:37:02,958 --> 00:37:06,208
 under the eugis of the variable of time

1043
00:37:06,208 --> 00:37:07,750
 and say, "Hey, what about for a little

1044
00:37:07,750 --> 00:37:08,750
 bit of time if we

1045
00:37:08,750 --> 00:37:10,541
 restrict this macronutrient?"

1046
00:37:11,083 --> 00:37:12,333
 We might see some very significant

1047
00:37:12,333 --> 00:37:13,500
 improvements depending on

1048
00:37:13,500 --> 00:37:14,375
 what we're talking about.

1049
00:37:15,500 --> 00:37:18,125
 However, when you begin to look at the

1050
00:37:18,125 --> 00:37:19,041
 long term, which is what

1051
00:37:19,041 --> 00:37:20,291
 we always have to look at,

1052
00:37:22,291 --> 00:37:26,458
 there are a couple of magnetars that are

1053
00:37:26,458 --> 00:37:27,250
 always pulling at us.

1054
00:37:27,916 --> 00:37:31,791
 Okay, one of them is insulin.

1055
00:37:33,083 --> 00:37:37,083
 And it's very difficult to obtain real

1056
00:37:37,083 --> 00:37:39,041
 and lasting health without insulin

1057
00:37:39,041 --> 00:37:40,416
 functioning optimally.

1058
00:37:41,208 --> 00:37:42,500
 Really, you're not going to.

1059
00:37:42,500 --> 00:37:43,166
 That's just the answer,

1060
00:37:43,500 --> 00:37:44,791
 unless insulin's functioning.

1061
00:37:44,791 --> 00:37:46,458
 Because it's so pleiotropic in its

1062
00:37:46,458 --> 00:37:47,833
 nature, it affects so many things.

1063
00:37:49,250 --> 00:37:51,708
 So the problem you get into with that is

1064
00:37:51,708 --> 00:37:55,916
 that in order to properly stimulate

1065
00:37:55,916 --> 00:38:00,791
 insulin, there's an inventory or a suite

1066
00:38:00,791 --> 00:38:03,041
 of hormones that need regular stimulation

1067
00:38:03,041 --> 00:38:05,166
 through foods, through macronutrients.

1068
00:38:06,125 --> 00:38:07,208
 And they oppose each other.

1069
00:38:08,083 --> 00:38:11,458
 So I've spoken quite a bit about the

1070
00:38:11,458 --> 00:38:12,375
 example of glucagon

1071
00:38:12,375 --> 00:38:13,541
 because it's kind of in our face.

1072
00:38:14,541 --> 00:38:17,250
 But it's a fun one to pick on because

1073
00:38:17,250 --> 00:38:19,083
 glucagon has been the

1074
00:38:19,083 --> 00:38:20,458
 hero of a low carb movement.

1075
00:38:20,875 --> 00:38:22,625
 And if you go down that road far enough,

1076
00:38:22,625 --> 00:38:23,916
 what you'll see is that actually by

1077
00:38:23,916 --> 00:38:26,791
 overstimulating that, and by not

1078
00:38:26,791 --> 00:38:29,458
 stimulating other hormones, particularly

1079
00:38:29,458 --> 00:38:31,583
 insulin now to connect in through key

1080
00:38:31,583 --> 00:38:33,416
 types of carbohydrates, you

1081
00:38:33,416 --> 00:38:34,583
 actually get insulin resistance.

1082
00:38:35,000 --> 00:38:35,791
 And then the result of

1083
00:38:35,791 --> 00:38:37,375
 that is hyperinsulinemia.

1084
00:38:37,375 --> 00:38:38,916
 So sort of briefly in the muscles, one

1085
00:38:38,916 --> 00:38:42,625
 might argue though, that the macular

1086
00:38:42,625 --> 00:38:43,958
 glucose bearing effect,

1087
00:38:45,125 --> 00:38:47,208
 what would you say to that, that long

1088
00:38:47,208 --> 00:38:50,500
 term ketosis drives this peripheral

1089
00:38:50,500 --> 00:38:52,083
 insulin resistance, but it's typically

1090
00:38:52,083 --> 00:38:53,250
 just within the muscle.

1091
00:38:53,500 --> 00:38:55,208
 Yeah, I would say that probably doesn't

1092
00:38:55,208 --> 00:38:56,291
 hold up to scrutiny for

1093
00:38:56,291 --> 00:38:57,333
 some very good reasons.

1094
00:38:57,791 --> 00:38:58,750
 One is that

1095
00:39:01,041 --> 00:39:01,583
 in order...

1096
00:39:02,250 --> 00:39:04,041
 So I did a debate with

1097
00:39:04,041 --> 00:39:05,333
 Sean Baker that never aired.

1098
00:39:05,791 --> 00:39:06,625
 And I really...

1099
00:39:06,625 --> 00:39:08,166
 I was going to ask about that.

1100
00:39:08,708 --> 00:39:08,916
 Yeah.

1101
00:39:09,333 --> 00:39:11,708
 I really crushed this particular aspect

1102
00:39:11,708 --> 00:39:14,041
 of it, which was to look at like, is

1103
00:39:14,041 --> 00:39:15,625
 long-term ketosis really even something

1104
00:39:15,625 --> 00:39:16,541
 we'd want to consider?

1105
00:39:17,500 --> 00:39:19,125
 And I don't know how deep you want to go

1106
00:39:19,125 --> 00:39:20,541
 down this road because it's quite

1107
00:39:20,541 --> 00:39:25,541
 complex, but I would offer no for lots of

1108
00:39:25,541 --> 00:39:27,333
 reasons that nobody's talking about, but

1109
00:39:27,333 --> 00:39:29,375
 just to kind of sum it up.

1110
00:39:29,375 --> 00:39:33,875
 So long-term ketosis, we're going to need

1111
00:39:33,875 --> 00:39:34,958
 a fuel source for that,

1112
00:39:34,958 --> 00:39:36,375
 which is oxaloacetate.

1113
00:39:36,375 --> 00:39:36,791
 So you're going to need

1114
00:39:36,791 --> 00:39:37,958
 that for a subtle CoA.

1115
00:39:38,958 --> 00:39:41,083
 Normally your source for oxaloacetate is

1116
00:39:41,083 --> 00:39:45,791
 glycolysis, but what's going to happen is

1117
00:39:45,791 --> 00:39:49,041
 that when you're doing oxaloacetate for

1118
00:39:49,041 --> 00:39:50,708
 extended periods, you got to switch to

1119
00:39:50,708 --> 00:39:52,000
 the liver to produce it for you.

1120
00:39:52,500 --> 00:39:52,708
 Okay.

1121
00:39:53,458 --> 00:39:55,208
 Well, the issue that you get into there

1122
00:39:55,208 --> 00:39:57,208
 then is you get a mismatch between the

1123
00:39:57,208 --> 00:40:01,083
 TCA cycle and fatty acid oxidation.

1124
00:40:01,708 --> 00:40:04,250
 So you begin to get kind of an incomplete

1125
00:40:04,250 --> 00:40:05,791
 oxidation that happens.

1126
00:40:05,791 --> 00:40:07,500
 And then that incomplete oxidation will

1127
00:40:07,500 --> 00:40:09,458
 lead to a spillover of very specific

1128
00:40:09,458 --> 00:40:11,666
 types of acyl carnitines into the serum.

1129
00:40:13,875 --> 00:40:17,250
 And some of these moieties or very

1130
00:40:17,250 --> 00:40:19,500
 distinctive types of acyl carnitines are

1131
00:40:19,500 --> 00:40:20,000
 going to drive

1132
00:40:20,000 --> 00:40:21,458
 systemic insulin resistance.

1133
00:40:23,125 --> 00:40:27,208
 And it's all a result of basically you're

1134
00:40:27,208 --> 00:40:28,916
 creating this backlog within the

1135
00:40:28,916 --> 00:40:31,000
 mitochondrial membrane of transporter

1136
00:40:31,000 --> 00:40:33,500
 mechanisms that aren't, and then that

1137
00:40:33,500 --> 00:40:34,791
 spills over into the serum.

1138
00:40:35,583 --> 00:40:35,791
 Yeah.

1139
00:40:36,666 --> 00:40:38,708
 And so, and it really gets to

1140
00:40:40,083 --> 00:40:43,375
 is the liver equipped to supply a

1141
00:40:43,375 --> 00:40:45,333
 glycolysis to the entire body on an

1142
00:40:45,333 --> 00:40:47,166
 extended basis, you know,

1143
00:40:47,166 --> 00:40:48,250
 to every cell in the body.

1144
00:40:49,375 --> 00:40:51,166
 And I think we can make a pretty good

1145
00:40:51,166 --> 00:40:54,125
 case that it's not that, that, you know,

1146
00:40:54,125 --> 00:40:56,416
 you begin to see over time, these

1147
00:40:56,416 --> 00:40:59,000
 disparities between fuel sources and

1148
00:40:59,000 --> 00:40:59,958
 things that are

1149
00:40:59,958 --> 00:41:01,791
 required to sustain this state.

1150
00:41:02,250 --> 00:41:03,000
 And then you begin to

1151
00:41:03,000 --> 00:41:04,000
 see a buildup of things.

1152
00:41:04,500 --> 00:41:06,791
 So again, the missing variables time, if

1153
00:41:06,791 --> 00:41:08,833
 we will just insert time as the master

1154
00:41:08,833 --> 00:41:10,875
 framework and then begin to accept the

1155
00:41:10,875 --> 00:41:13,791
 notion that this is a dynamic

1156
00:41:13,791 --> 00:41:15,958
 system, not a static system.

1157
00:41:17,333 --> 00:41:20,333
 And that is the massive logic error in a

1158
00:41:20,333 --> 00:41:21,708
 lot of these arguments is that the

1159
00:41:21,708 --> 00:41:22,333
 assumption is we're

1160
00:41:22,333 --> 00:41:23,583
 dealing with a static system.

1161
00:41:24,291 --> 00:41:25,166
 It isn't.

1162
00:41:25,166 --> 00:41:26,708
 What it is, is it's a system that seeks a

1163
00:41:26,708 --> 00:41:27,708
 dynamic equilibrium.

1164
00:41:28,875 --> 00:41:30,250
 That's what we're talking about here.

1165
00:41:30,250 --> 00:41:31,333
 And so in a system that

1166
00:41:31,333 --> 00:41:32,458
 seeks a dynamic equilibrium,

1167
00:41:33,666 --> 00:41:36,416
 you can get in my book, the way I talk

1168
00:41:36,416 --> 00:41:39,208
 about this, I call it the forces of time.

1169
00:41:39,208 --> 00:41:40,000
 It's accumulation.

1170
00:41:40,375 --> 00:41:41,791
 You can get an accumulation of something.

1171
00:41:41,791 --> 00:41:43,416
 You can get a degradation of something.

1172
00:41:43,708 --> 00:41:45,416
 You can get a compensation of something.

1173
00:41:45,416 --> 00:41:46,833
 You can get attenuation of something.

1174
00:41:47,708 --> 00:41:48,791
 So all of these forces

1175
00:41:48,791 --> 00:41:51,083
 of time begin to play out.

1176
00:41:51,416 --> 00:41:54,250
 And in the case of oxaloacetate,

1177
00:41:54,250 --> 00:41:56,166
 acylcarnitines, and, you know, all of

1178
00:41:56,166 --> 00:41:58,208
 these sort of intermediates required to

1179
00:41:58,208 --> 00:42:00,666
 sustain ketosis over time, you begin to

1180
00:42:00,666 --> 00:42:02,458
 see a buildup of certain things that you

1181
00:42:02,458 --> 00:42:04,000
 can make a very good case will drive

1182
00:42:04,000 --> 00:42:05,250
 systemic insulin resistance.

1183
00:42:05,833 --> 00:42:06,958
 And in some cases,

1184
00:42:06,958 --> 00:42:08,958
 perhaps it's not recoverable.

1185
00:42:09,833 --> 00:42:11,916
 Okay, I'm going to relisten to that,

1186
00:42:11,916 --> 00:42:13,000
 especially that last part.

1187
00:42:13,000 --> 00:42:13,541
 Thank you for that.

1188
00:42:13,750 --> 00:42:17,166
 That's definitely a sort of solidified a

1189
00:42:17,166 --> 00:42:18,250
 few thoughts in my head.

1190
00:42:19,458 --> 00:42:20,125
 Joe, I'd love to talk

1191
00:42:20,125 --> 00:42:21,208
 about metabolism all day.

1192
00:42:21,458 --> 00:42:21,916
 I really would.

1193
00:42:22,833 --> 00:42:27,666
 And maybe I can convince you to join me

1194
00:42:27,666 --> 00:42:28,958
 for another episode at some point.

1195
00:42:29,958 --> 00:42:31,583
 A bit deeper into that.

1196
00:42:31,875 --> 00:42:34,916
 But I think just of the sake of brevity

1197
00:42:34,916 --> 00:42:36,125
 and time, I'd love to

1198
00:42:36,125 --> 00:42:37,000
 sort of jump into iron.

1199
00:42:38,333 --> 00:42:40,750
 Young Gut Ultra, I know that's a new

1200
00:42:40,750 --> 00:42:41,875
 product you've launched.

1201
00:42:41,875 --> 00:42:42,625
 It's exciting.

1202
00:42:43,166 --> 00:42:45,958
 And it looks to solve the problem of sort

1203
00:42:45,958 --> 00:42:47,375
 of excess iron brought up in the body.

1204
00:42:47,875 --> 00:42:48,916
 Now I know there's a

1205
00:42:48,916 --> 00:42:49,875
 lot to dig into here.

1206
00:42:50,333 --> 00:42:54,083
 And maybe we can start with why excess

1207
00:42:54,083 --> 00:42:55,500
 iron is an issue, maybe from the

1208
00:42:55,541 --> 00:42:57,083
 perspective of the Fenton reaction, maybe

1209
00:42:57,083 --> 00:42:58,291
 it's a sort of a decent

1210
00:42:58,291 --> 00:43:00,375
 sort of lens to view it from.

1211
00:43:01,750 --> 00:43:05,625
 But yeah, why did you sort of choose to

1212
00:43:05,625 --> 00:43:09,875
 focus on iron as an issue with developing

1213
00:43:09,875 --> 00:43:10,750
 that product, I suppose?

1214
00:43:11,541 --> 00:43:12,666
 Yeah, it wasn't really so much out of a

1215
00:43:12,666 --> 00:43:13,958
 need to deal with iron.

1216
00:43:13,958 --> 00:43:16,125
 It's more out of a need to deal with very

1217
00:43:16,125 --> 00:43:18,083
 specific problems that are intractable

1218
00:43:18,083 --> 00:43:20,000
 for everyone over time.

1219
00:43:20,791 --> 00:43:23,375
 One of those problems has to do with the

1220
00:43:23,375 --> 00:43:26,375
 impairment and degradation of the

1221
00:43:26,375 --> 00:43:28,250
 peroxisome membrane within the

1222
00:43:28,250 --> 00:43:29,208
 intracellular space.

1223
00:43:29,583 --> 00:43:32,250
 So if you're in the audience and you're

1224
00:43:32,250 --> 00:43:34,291
 not familiar, peroxisomes are an energy

1225
00:43:34,291 --> 00:43:36,458
 organelle within the cell.

1226
00:43:36,458 --> 00:43:37,625
 And they're kind of

1227
00:43:37,625 --> 00:43:39,666
 co-partners with the mitochondria.

1228
00:43:40,500 --> 00:43:42,583
 There's this notion that the mitochondria

1229
00:43:42,583 --> 00:43:44,916
 kind of exist at the top of the hill, you

1230
00:43:44,916 --> 00:43:45,833
 know, by themselves.

1231
00:43:46,250 --> 00:43:47,416
 And it doesn't really

1232
00:43:47,416 --> 00:43:48,208
 hold up to scrutiny.

1233
00:43:49,041 --> 00:43:52,875
 It's more like a co-emperor sort of

1234
00:43:52,875 --> 00:43:54,666
 situation at the top of the hill where

1235
00:43:54,666 --> 00:43:56,750
 the peroxisomes of the mitochondria form

1236
00:43:56,750 --> 00:43:59,041
 a single system and they very much peddle

1237
00:43:59,041 --> 00:43:59,916
 the bicycle together.

1238
00:44:01,000 --> 00:44:03,250
 So the issue you get into with age is

1239
00:44:03,250 --> 00:44:05,625
 that there are these transporter proteins

1240
00:44:05,625 --> 00:44:06,250
 in the mitochondrial

1241
00:44:06,250 --> 00:44:07,500
 membrane called PEX proteins.

1242
00:44:08,166 --> 00:44:09,083
 And they begin to malfunction.

1243
00:44:09,583 --> 00:44:11,625
 And so part of the function of the of the

1244
00:44:11,625 --> 00:44:13,500
 peroxisomes apart from energy production

1245
00:44:13,500 --> 00:44:17,375
 is to basically dismutate hydrogen

1246
00:44:17,375 --> 00:44:18,791
 peroxide down into water.

1247
00:44:20,333 --> 00:44:24,000
 The hydrogen peroxide by itself can be an

1248
00:44:24,000 --> 00:44:25,958
 extremely important signal molecule as a

1249
00:44:25,958 --> 00:44:27,458
 free radical within the cell.

1250
00:44:27,458 --> 00:44:27,958
 It's very much

1251
00:44:27,958 --> 00:44:29,125
 involved in insulin signaling.

1252
00:44:30,583 --> 00:44:33,583
 The problem is that if you get too much

1253
00:44:33,583 --> 00:44:37,666
 of it, it really kind of becomes maybe

1254
00:44:37,666 --> 00:44:40,666
 just by again by virtue of math, by

1255
00:44:40,666 --> 00:44:42,916
 virtue of sheer weight and sheer numbers,

1256
00:44:42,916 --> 00:44:44,375
 possibly the most detrimental free

1257
00:44:44,375 --> 00:44:45,375
 radical in the body.

1258
00:44:46,083 --> 00:44:48,916
 Now on an individual basis, it's not

1259
00:44:48,916 --> 00:44:50,791
 nearly as damaging as something like the

1260
00:44:50,791 --> 00:44:53,500
 hydroxyl radical or superoxide when

1261
00:44:53,500 --> 00:44:55,125
 superoxide goes wonky.

1262
00:44:55,583 --> 00:44:56,916
 But because there's so much

1263
00:44:56,916 --> 00:45:00,125
 of it, it's really a problem.

1264
00:45:00,625 --> 00:45:03,375
 And so what happens with age is that you

1265
00:45:03,375 --> 00:45:04,916
 get a buildup of hydrogen peroxide in the

1266
00:45:04,916 --> 00:45:06,541
 cell and at the same time we tend to

1267
00:45:06,541 --> 00:45:07,666
 build up iron with age.

1268
00:45:08,458 --> 00:45:08,875
 That's bad.

1269
00:45:09,291 --> 00:45:12,625
 That's very bad because hydrogen peroxide

1270
00:45:12,625 --> 00:45:15,833
 can mediate through iron a reaction

1271
00:45:15,833 --> 00:45:17,541
 called the Fenton reaction that produces

1272
00:45:17,541 --> 00:45:20,250
 a very damaging free radical

1273
00:45:20,250 --> 00:45:22,000
 called the hydroxyl radical.

1274
00:45:22,833 --> 00:45:26,291
 And you get a lot of you get a lot of

1275
00:45:26,291 --> 00:45:28,000
 cell damage from this.

1276
00:45:28,375 --> 00:45:30,375
 You could make the whole argument that

1277
00:45:30,375 --> 00:45:31,041
 that's where your

1278
00:45:31,041 --> 00:45:32,000
 gray hair is coming from.

1279
00:45:32,000 --> 00:45:35,375
 Is that it tends to torch the

1280
00:45:35,375 --> 00:45:36,583
 polyunsaturated fats

1281
00:45:36,583 --> 00:45:37,416
 in the cell membrane?

1282
00:45:37,416 --> 00:45:37,750
 Is that right?

1283
00:45:38,875 --> 00:45:39,041
 Yes.

1284
00:45:39,416 --> 00:45:41,666
 In addition to, well, in particular,

1285
00:45:43,458 --> 00:45:44,416
 the mitochondrial membrane

1286
00:45:44,416 --> 00:45:46,083
 takes a lot of damage from that.

1287
00:45:47,375 --> 00:45:50,666
 So that's a huge problem that needs,

1288
00:45:51,666 --> 00:45:52,791
 we're all going to face.

1289
00:45:52,791 --> 00:45:54,166
 And like, let me just make it simple.

1290
00:45:54,166 --> 00:45:54,833
 Everybody wants to

1291
00:45:54,833 --> 00:45:55,875
 fix for their gray hair.

1292
00:45:56,291 --> 00:45:58,708
 What's the fix?

1293
00:45:58,916 --> 00:46:00,541
 We got to fix this problem because it

1294
00:46:00,541 --> 00:46:01,250
 isn't just your gray

1295
00:46:01,250 --> 00:46:02,458
 hair that it's affecting.

1296
00:46:02,458 --> 00:46:04,333
 Your gray hair is just a marker for how

1297
00:46:04,333 --> 00:46:05,833
 fast the damage is progressing.

1298
00:46:06,916 --> 00:46:07,708
 So that's a big problem.

1299
00:46:09,041 --> 00:46:11,208
 And that was the motivation behind it.

1300
00:46:11,208 --> 00:46:13,916
 The other thing was that when I first

1301
00:46:13,916 --> 00:46:18,916
 really laid into this focus of how can we

1302
00:46:18,916 --> 00:46:22,208
 modulate a few switches in the immune

1303
00:46:22,208 --> 00:46:23,791
 system to get massive results?

1304
00:46:25,083 --> 00:46:28,958
 One of the key variables in that is

1305
00:46:28,958 --> 00:46:32,333
 lactoferrin because lactoferrin, I guess

1306
00:46:32,333 --> 00:46:35,791
 the best way to describe it is that it's

1307
00:46:35,791 --> 00:46:37,083
 kind of like the glue

1308
00:46:37,083 --> 00:46:38,458
 of the immune system.

1309
00:46:39,333 --> 00:46:41,291
 It sort of holds the whole thing together

1310
00:46:41,291 --> 00:46:43,458
 and it acts as an intelligent

1311
00:46:43,458 --> 00:46:46,125
 intermediary with the immune system.

1312
00:46:46,416 --> 00:46:47,958
 So it sort of acts as the

1313
00:46:47,958 --> 00:46:49,500
 glue that drives homeostasis.

1314
00:46:50,000 --> 00:46:53,375
 And in my first iteration of this back in

1315
00:46:53,375 --> 00:46:55,708
 the 20 teens, there

1316
00:46:55,708 --> 00:46:58,208
 wasn't really a way to do it.

1317
00:46:59,500 --> 00:47:00,291
 We didn't really have

1318
00:47:00,291 --> 00:47:01,708
 human lactoferrin back then.

1319
00:47:01,958 --> 00:47:03,541
 And so it's going to be my next question.

1320
00:47:03,750 --> 00:47:03,958
 Yeah.

1321
00:47:04,250 --> 00:47:04,541
 Yeah.

1322
00:47:04,541 --> 00:47:05,916
 So the focus was, go ahead.

1323
00:47:06,458 --> 00:47:07,625
 No, I was just going to say the

1324
00:47:07,625 --> 00:47:09,708
 difference there being the difference

1325
00:47:09,708 --> 00:47:11,166
 between human lactoferrin and then

1326
00:47:11,166 --> 00:47:12,166
 obviously bovine and

1327
00:47:12,166 --> 00:47:13,875
 other forms of lactoferrin.

1328
00:47:14,375 --> 00:47:18,583
 Why is lactoferrin coming from bovine

1329
00:47:18,583 --> 00:47:19,666
 sources or other sources?

1330
00:47:20,250 --> 00:47:22,791
 Maybe such an immunological issue.

1331
00:47:23,291 --> 00:47:25,458
 Why is it sort of less preferential than

1332
00:47:25,458 --> 00:47:28,250
 finding the, I think it's Iphira, is that

1333
00:47:28,250 --> 00:47:30,250
 the brand of human lactoferrin?

1334
00:47:31,541 --> 00:47:31,791
 But yeah.

1335
00:47:32,583 --> 00:47:32,791
 Yeah.

1336
00:47:33,375 --> 00:47:34,500
 So bovine and human

1337
00:47:34,500 --> 00:47:35,625
 lactoferrin are very similar.

1338
00:47:35,833 --> 00:47:37,291
 It depends on who you're reading.

1339
00:47:37,291 --> 00:47:37,666
 They're somewhere

1340
00:47:37,666 --> 00:47:41,208
 between 68 to 77% identical.

1341
00:47:41,958 --> 00:47:43,041
 So that's not bad.

1342
00:47:43,041 --> 00:47:43,625
 That's pretty good.

1343
00:47:44,041 --> 00:47:45,333
 The difference is binding sites.

1344
00:47:46,375 --> 00:47:47,416
 So bovine and

1345
00:47:47,416 --> 00:47:49,083
 lactoferrin has five binding sites.

1346
00:47:49,083 --> 00:47:49,958
 Human has three.

1347
00:47:50,791 --> 00:47:53,000
 But the issue you get into really becomes

1348
00:47:53,000 --> 00:47:55,125
 one that it's a foreign protein.

1349
00:47:55,750 --> 00:47:57,208
 So lactoferrin is a glycoprotein.

1350
00:47:58,375 --> 00:48:03,666
 And you run a bit of a risk for an immune

1351
00:48:03,666 --> 00:48:05,000
 reaction like the body would

1352
00:48:05,000 --> 00:48:06,291
 have to any foreign protein.

1353
00:48:06,875 --> 00:48:09,916
 So where lactoferrin, generally speaking,

1354
00:48:09,916 --> 00:48:11,708
 human lactoferrin is meant to be the

1355
00:48:11,708 --> 00:48:13,750
 master regulator of the immune system,

1356
00:48:14,750 --> 00:48:15,583
 bovine lactoferrin can

1357
00:48:15,583 --> 00:48:16,833
 actually trigger the immune system.

1358
00:48:17,541 --> 00:48:19,375
 Now, I want to be fair, that's not true.

1359
00:48:20,000 --> 00:48:22,166
 Probably in a majority of cases.

1360
00:48:22,625 --> 00:48:22,833
 Yeah.

1361
00:48:23,000 --> 00:48:24,083
 Like bovine lactoferrin

1362
00:48:24,083 --> 00:48:27,125
 can be highly beneficial.

1363
00:48:27,708 --> 00:48:29,833
 So I don't want to sit here and just go,

1364
00:48:30,000 --> 00:48:31,708
 "Eh, mine's the only stuff that works."

1365
00:48:32,000 --> 00:48:33,125
 But no, bovine lactoferrin can

1366
00:48:33,125 --> 00:48:34,208
 be highly, highly beneficial.

1367
00:48:35,041 --> 00:48:36,291
 In fact, it's one of the reasons why

1368
00:48:36,291 --> 00:48:39,291
 dairy is really so beneficial in the long

1369
00:48:39,291 --> 00:48:40,541
 term for so many reasons.

1370
00:48:43,166 --> 00:48:43,958
 That just triggered off

1371
00:48:43,958 --> 00:48:45,416
 a firestorm right there.

1372
00:48:45,708 --> 00:48:46,958
 But we'll let that go.

1373
00:48:48,208 --> 00:48:49,666
 I can hear all the anti-dairy

1374
00:48:49,666 --> 00:48:51,000
 crowd just going, "Ah, click."

1375
00:48:52,750 --> 00:48:58,000
 But all that to say that

1376
00:48:58,000 --> 00:49:01,291
 there's a thing called glycosylation.

1377
00:49:01,583 --> 00:49:06,041
 So I'm trying to tailor

1378
00:49:06,041 --> 00:49:07,125
 this to the audience here.

1379
00:49:07,625 --> 00:49:08,208
 I don't want to...

1380
00:49:08,666 --> 00:49:09,708
 Yeah, we've been pretty deep here.

1381
00:49:09,708 --> 00:49:10,458
 So let's just go there.

1382
00:49:11,833 --> 00:49:16,625
 So much of the information and

1383
00:49:16,625 --> 00:49:19,791
 communication in the body happens based

1384
00:49:19,791 --> 00:49:21,166
 on what are called PTMs or

1385
00:49:21,166 --> 00:49:23,166
 post-translational modifications, which

1386
00:49:23,166 --> 00:49:26,916
 are things that happen after

1387
00:49:26,916 --> 00:49:31,375
 transcription, after making proteins.

1388
00:49:31,375 --> 00:49:32,791
 They're modifications to the proteins.

1389
00:49:33,291 --> 00:49:34,708
 One of those modifications is adding

1390
00:49:34,708 --> 00:49:35,875
 sugars to those

1391
00:49:35,875 --> 00:49:37,541
 proteins to form glycoproteins.

1392
00:49:37,541 --> 00:49:39,000
 And then those sugars, depending on their

1393
00:49:39,000 --> 00:49:42,125
 structure, essentially act as a second

1394
00:49:42,125 --> 00:49:43,083
 messenger system or a

1395
00:49:43,083 --> 00:49:44,083
 communication system.

1396
00:49:44,833 --> 00:49:47,916
 So the specific structure of those sugars

1397
00:49:47,916 --> 00:49:49,166
 carries information.

1398
00:49:50,500 --> 00:49:51,750
 And so lactoferrin...

1399
00:49:51,791 --> 00:49:52,708
 Go ahead.

1400
00:49:53,416 --> 00:49:54,875
 Sorry, would that include ATEs as well?

1401
00:49:55,375 --> 00:49:55,958
 Just out of interest?

1402
00:49:57,583 --> 00:50:00,291
 Yeah, all glycosylation related

1403
00:50:00,291 --> 00:50:02,833
 activities are information carriers.

1404
00:50:03,458 --> 00:50:05,833
 So in my first book, this was actually

1405
00:50:05,833 --> 00:50:07,500
 going to be a chapter and I gave up

1406
00:50:07,500 --> 00:50:08,833
 because there was no way to do it.

1407
00:50:09,000 --> 00:50:12,083
 It was a book talking about PTMs.

1408
00:50:12,083 --> 00:50:13,333
 It's just way too much.

1409
00:50:14,000 --> 00:50:17,791
 Suffice to say that apart from DNA,

1410
00:50:18,333 --> 00:50:19,583
 there's a whole information-bearing

1411
00:50:19,583 --> 00:50:21,458
 system in the body based on the structure

1412
00:50:21,458 --> 00:50:24,125
 of sugar proteins, glycoproteins.

1413
00:50:24,708 --> 00:50:26,208
 So anyways, all that to say that

1414
00:50:27,666 --> 00:50:30,250
 bovine lactoferrin and human lactoferrin

1415
00:50:30,250 --> 00:50:31,875
 share a lot with respect to

1416
00:50:31,875 --> 00:50:32,708
 glycosylation, but

1417
00:50:32,708 --> 00:50:33,708
 there's also some differences.

1418
00:50:34,916 --> 00:50:38,416
 And those differences translate into very

1419
00:50:38,416 --> 00:50:39,375
 practical things like

1420
00:50:39,375 --> 00:50:41,458
 how absorbable is this.

1421
00:50:41,708 --> 00:50:43,958
 And the human lactoferrin just is always

1422
00:50:43,958 --> 00:50:46,125
 going to be more absorbable

1423
00:50:46,125 --> 00:50:47,583
 than the bovine lactoferrin.

1424
00:50:47,791 --> 00:50:49,375
 You're going to need more of the bovine

1425
00:50:49,375 --> 00:50:50,500
 to get the same results.

1426
00:50:50,500 --> 00:50:52,375
 In fact, so in milk,

1427
00:50:53,458 --> 00:50:57,000
 the best estimate so far is that there is

1428
00:50:57,000 --> 00:51:02,791
 1.5 to 2 milligrams per gram of bovine

1429
00:51:02,791 --> 00:51:03,833
 lactoferrin in milk.

1430
00:51:04,208 --> 00:51:07,166
 So at a kilogram level, roughly 150 to

1431
00:51:07,166 --> 00:51:10,833
 200 milligrams of bovine lactoferrin, but

1432
00:51:10,833 --> 00:51:12,208
 then the absorption is not the same.

1433
00:51:12,250 --> 00:51:17,583
 So in other words, like in my young gut

1434
00:51:17,583 --> 00:51:18,916
 ultra product, there's 200

1435
00:51:18,916 --> 00:51:20,875
 milligrams of human lactoferrin.

1436
00:51:21,291 --> 00:51:23,291
 To get that same dose in bovine

1437
00:51:23,291 --> 00:51:24,166
 lactoferrin, you'd need

1438
00:51:24,166 --> 00:51:25,375
 a kilogram and a half.

1439
00:51:26,666 --> 00:51:27,083
 That's a lot.

1440
00:51:27,541 --> 00:51:27,750
 Yeah.

1441
00:51:27,916 --> 00:51:28,750
 So that's a lot.

1442
00:51:29,333 --> 00:51:29,541
 Yeah.

1443
00:51:29,791 --> 00:51:31,500
 And then I'm sorry, I jumped some

1444
00:51:31,500 --> 00:51:33,208
 completely sidetracked here, but then how

1445
00:51:33,208 --> 00:51:34,833
 is lactoferrin, I suppose, sort of

1446
00:51:34,833 --> 00:51:36,000
 solving broadly

1447
00:51:36,000 --> 00:51:37,125
 speaking, the ion problem?

1448
00:51:37,875 --> 00:51:40,291
 So lactoferrin, the interesting thing

1449
00:51:40,291 --> 00:51:42,625
 about lactoferrin is that

1450
00:51:42,625 --> 00:51:46,000
 it drives iron homeostasis.

1451
00:51:46,875 --> 00:51:48,625
 So if you have too little iron or too

1452
00:51:48,625 --> 00:51:51,083
 much iron, it tends to push the pendulum

1453
00:51:51,083 --> 00:51:52,375
 back towards the middle.

1454
00:51:54,666 --> 00:51:56,583
 So lactoferrin, it's a member of the

1455
00:51:56,583 --> 00:51:58,333
 transferrin family, which

1456
00:51:58,333 --> 00:51:59,500
 are iron binding proteins.

1457
00:51:59,791 --> 00:52:02,166
 The thing about lactoferrin is its iron

1458
00:52:02,166 --> 00:52:04,916
 binding capacity is so astoundingly high.

1459
00:52:05,125 --> 00:52:06,083
 It's hundreds of times

1460
00:52:06,083 --> 00:52:08,791
 higher than your ferritin.

1461
00:52:08,791 --> 00:52:12,291
 And so lactoferrin,

1462
00:52:13,791 --> 00:52:14,958
 it's like a sponge.

1463
00:52:15,291 --> 00:52:15,916
 It has this amazing

1464
00:52:15,916 --> 00:52:17,333
 ability to soak up iron.

1465
00:52:20,625 --> 00:52:21,875
 Kind of a simple way to put it.

1466
00:52:22,333 --> 00:52:22,708
 Fair enough.

1467
00:52:22,708 --> 00:52:23,125
 That's perfect.

1468
00:52:23,666 --> 00:52:26,250
 And then, yeah, I suppose there are other

1469
00:52:26,250 --> 00:52:27,958
 few competing molecules out there on the

1470
00:52:27,958 --> 00:52:29,875
 market, things like IP6 phosphate, or I

1471
00:52:29,875 --> 00:52:31,375
 suppose the main mechanism is probably

1472
00:52:31,375 --> 00:52:32,500
 phyto-gasol to some extent

1473
00:52:32,500 --> 00:52:34,083
 binding up iron in the gut.

1474
00:52:34,291 --> 00:52:37,791
 And then obviously, you can go down the

1475
00:52:37,791 --> 00:52:39,166
 copper route to which I know Morley

1476
00:52:39,166 --> 00:52:42,666
 Robbins has done a pretty deep dive on.

1477
00:52:42,666 --> 00:52:44,041
 I mean, I think he's based the latter

1478
00:52:44,041 --> 00:52:45,333
 part of his career around that.

1479
00:52:45,333 --> 00:52:49,041
 And the idea that by regulating coppin,

1480
00:52:49,041 --> 00:52:50,916
 ceruloplasma, you can sort of convert

1481
00:52:50,916 --> 00:52:53,750
 excess ferrous iron, let me get this

1482
00:52:53,750 --> 00:52:55,791
 right, I think, to ferric iron.

1483
00:52:57,000 --> 00:53:00,958
 And then that can then be transported,

1484
00:53:01,458 --> 00:53:04,958
 combined to transferrin and then get

1485
00:53:04,958 --> 00:53:05,750
 yanked out of the bloodstream.

1486
00:53:06,583 --> 00:53:08,291
 What do you think about that as an often

1487
00:53:08,291 --> 00:53:09,708
 not a competing product or competing

1488
00:53:09,708 --> 00:53:12,166
 theory, but as an odd competing mechanism

1489
00:53:12,166 --> 00:53:14,708
 to sort of regulate iron, the idea of

1490
00:53:14,708 --> 00:53:16,625
 just sort of increasing copper intake?

1491
00:53:18,875 --> 00:53:19,041
 Well,

1492
00:53:21,666 --> 00:53:23,708
 first of all, I don't want to do a

1493
00:53:23,708 --> 00:53:24,833
 disservice to his work.

1494
00:53:26,166 --> 00:53:27,708
 Just anecdotally, what I've heard is that

1495
00:53:27,708 --> 00:53:29,125
 he's had some very good outcomes.

1496
00:53:30,500 --> 00:53:33,750
 And I'm not 100% expert in his work, so I

1497
00:53:33,750 --> 00:53:34,541
 don't want to misspeak.

1498
00:53:35,458 --> 00:53:37,625
 As I understand it, which I will say up

1499
00:53:37,625 --> 00:53:39,083
 front has room for error.

1500
00:53:40,125 --> 00:53:41,500
 So please correct me if I'm wrong.

1501
00:53:43,375 --> 00:53:46,791
 So a significant portion of the actual

1502
00:53:46,791 --> 00:53:50,166
 protocol involves dietary modifications.

1503
00:53:51,083 --> 00:53:52,375
 And when I look at those dietary

1504
00:53:52,375 --> 00:53:55,083
 modifications, what the net, which I

1505
00:53:55,083 --> 00:53:56,375
 haven't heard anybody talk about, that

1506
00:53:56,375 --> 00:53:57,500
 they're going to do is you're going to

1507
00:53:57,500 --> 00:54:00,208
 produce a shift in the gut taxa that

1508
00:54:00,208 --> 00:54:02,166
 favors bacteria with

1509
00:54:02,166 --> 00:54:03,250
 iron binding cytoform.

1510
00:54:04,125 --> 00:54:07,625
 So what you're going to get is this

1511
00:54:07,625 --> 00:54:08,666
 variable that doesn't get

1512
00:54:08,666 --> 00:54:10,000
 talked about a lot, which is that,

1513
00:54:11,208 --> 00:54:12,583
 and this gets to the phytic acid thing.

1514
00:54:13,875 --> 00:54:15,916
 As you increase certain taxa in the gut,

1515
00:54:15,916 --> 00:54:16,708
 like the phyto bacteria,

1516
00:54:17,041 --> 00:54:18,791
 they bind iron in the gut.

1517
00:54:20,000 --> 00:54:22,583
 And then in terms of your IP6 problem,

1518
00:54:22,791 --> 00:54:24,375
 that actually prevents that

1519
00:54:24,375 --> 00:54:25,625
 from binding iron in the gut.

1520
00:54:27,166 --> 00:54:30,875
 So shifting the gut taxa can have this

1521
00:54:30,875 --> 00:54:33,500
 tremendous impact with respect to a

1522
00:54:33,500 --> 00:54:37,291
 number of variables that we could kind of

1523
00:54:37,291 --> 00:54:38,625
 anecdotally attribute to

1524
00:54:38,625 --> 00:54:40,041
 quote unquote the protocol.

1525
00:54:40,708 --> 00:54:45,041
 But it's really possibly to some extent

1526
00:54:45,041 --> 00:54:46,000
 has to do with just

1527
00:54:46,000 --> 00:54:47,791
 simply shifting the gut taxa.

1528
00:54:48,208 --> 00:54:49,583
 That's kind of the theory I'd offer on

1529
00:54:49,583 --> 00:54:50,625
 that with respect to copper.

1530
00:54:52,750 --> 00:54:54,000
 The thing is,

1531
00:54:54,291 --> 00:54:56,500
 lactoferrin can also bind copper.

1532
00:54:57,958 --> 00:55:05,000
 And I would just offer that the master

1533
00:55:05,000 --> 00:55:06,750
 regulator of iron naturally

1534
00:55:06,750 --> 00:55:08,333
 in the body is lactoferrin.

1535
00:55:08,666 --> 00:55:10,916
 So if I were to approach the problem, I

1536
00:55:10,916 --> 00:55:12,166
 would kind of start with what exists

1537
00:55:12,166 --> 00:55:14,791
 naturally, which is not to say that maybe

1538
00:55:15,666 --> 00:55:17,541
 he's not having fantastic results too.

1539
00:55:18,083 --> 00:55:22,000
 So I don't claim to have the market

1540
00:55:22,000 --> 00:55:24,041
 cornered on solving the lactoferrin iron

1541
00:55:24,041 --> 00:55:25,375
 problem or the iron problem.

1542
00:55:25,625 --> 00:55:27,000
 So that's what I would say.

1543
00:55:27,583 --> 00:55:28,333
 Yeah, that's perfect.

1544
00:55:28,541 --> 00:55:30,750
 And of course, no disrespect to Molly,

1545
00:55:30,750 --> 00:55:31,833
 though, I'm actually getting more on the

1546
00:55:31,833 --> 00:55:32,791
 podcast in a few weeks.

1547
00:55:33,083 --> 00:55:35,958
 So I'm just always interested in speaking

1548
00:55:35,958 --> 00:55:39,416
 to individuals obviously with opposing

1549
00:55:39,416 --> 00:55:43,625
 but similar sort of understandings of the

1550
00:55:43,625 --> 00:55:45,041
 problem, just looking from a different

1551
00:55:45,041 --> 00:55:47,583
 lens and just trying to

1552
00:55:47,583 --> 00:55:49,625
 get a broader picture of it.

1553
00:55:49,833 --> 00:55:51,416
 I mean, ultimately, all rosary trim.

1554
00:55:51,416 --> 00:55:54,666
 And I suppose one could also just stick a

1555
00:55:54,666 --> 00:55:56,541
 needle in the ROM and just do some sort

1556
00:55:56,541 --> 00:55:57,625
 of venus section as well.

1557
00:55:57,625 --> 00:55:58,833
 I'm sure that is

1558
00:55:58,833 --> 00:56:00,708
 effective as well as anything.

1559
00:56:03,333 --> 00:56:04,000
 But yeah,

1560
00:56:05,208 --> 00:56:06,375
 Joel, you'd be amazing.

1561
00:56:06,875 --> 00:56:07,666
 And I just want to be

1562
00:56:07,666 --> 00:56:08,625
 respectful of your time.

1563
00:56:08,625 --> 00:56:12,208
 But I've got a few rapid-ish fire

1564
00:56:12,208 --> 00:56:13,708
 questions that I'd love to

1565
00:56:13,708 --> 00:56:15,458
 go through if that's okay.

1566
00:56:17,000 --> 00:56:17,208
 Perfect.

1567
00:56:18,000 --> 00:56:18,208
 Okay.

1568
00:56:18,833 --> 00:56:22,750
 To keep the sugar diet crowd happy.

1569
00:56:25,083 --> 00:56:26,000
 I know you've covered this

1570
00:56:26,000 --> 00:56:27,708
 on your Instagram recently.

1571
00:56:28,000 --> 00:56:30,041
 And seemingly, it has more to do with I

1572
00:56:30,041 --> 00:56:32,875
 suppose, one of my other protein

1573
00:56:32,875 --> 00:56:34,625
 restriction, although as we chatted about

1574
00:56:34,625 --> 00:56:37,583
 earlier, if you sort of remove a

1575
00:56:37,583 --> 00:56:43,125
 macronutrient entirely, you're going to

1576
00:56:43,125 --> 00:56:45,041
 get a massive sort of swing in

1577
00:56:45,041 --> 00:56:46,916
 metabolism generally speaking.

1578
00:56:48,541 --> 00:56:51,041
 And I know that there's obviously an

1579
00:56:51,041 --> 00:56:54,958
 issue there with high fat diets sort of

1580
00:56:54,958 --> 00:56:57,500
 triggering an increase in FGF21

1581
00:56:57,500 --> 00:57:00,041
 hepatically, which is why maybe that's

1582
00:57:00,041 --> 00:57:01,041
 not the best way to

1583
00:57:01,041 --> 00:57:02,041
 sort of protein respect.

1584
00:57:02,583 --> 00:57:04,916
 But just overall, I suppose, what's your

1585
00:57:04,916 --> 00:57:06,333
 take on the sugar diet?

1586
00:57:06,625 --> 00:57:08,833
 And do you think it's efficacious?

1587
00:57:08,833 --> 00:57:10,541
 I know time will be available, but yeah.

1588
00:57:13,958 --> 00:57:15,791
 So first question,

1589
00:57:17,208 --> 00:57:21,666
 can quote unquote the sugar diet work to

1590
00:57:21,666 --> 00:57:22,541
 help you lose body fat?

1591
00:57:22,791 --> 00:57:23,541
 Answers, yes, absolutely.

1592
00:57:24,000 --> 00:57:24,208
 Yeah.

1593
00:57:24,750 --> 00:57:25,583
 Is there anything new there?

1594
00:57:25,583 --> 00:57:26,625
 No, nothing.

1595
00:57:27,166 --> 00:57:29,458
 That's been known for decades that just

1596
00:57:29,458 --> 00:57:30,625
 take any macronutrient to

1597
00:57:30,625 --> 00:57:32,291
 zero and you can see fat loss.

1598
00:57:33,375 --> 00:57:33,875
 Mechanistically,

1599
00:57:34,916 --> 00:57:36,791
 personally, I don't think any of the

1600
00:57:36,791 --> 00:57:38,375
 reasons apart from protein restriction

1601
00:57:38,375 --> 00:57:40,000
 are what's going on.

1602
00:57:40,458 --> 00:57:41,208
 The two big reasons

1603
00:57:41,208 --> 00:57:42,291
 nobody's really talked about.

1604
00:57:43,875 --> 00:57:45,000
 Number one is glycolysis.

1605
00:57:46,083 --> 00:57:48,458
 So again, this gets to kind of my

1606
00:57:48,458 --> 00:57:49,500
 worldview, which is math

1607
00:57:49,500 --> 00:57:50,500
 always drives the equation.

1608
00:57:51,666 --> 00:57:54,666
 In a carbohydrate restricted state, you

1609
00:57:54,666 --> 00:57:55,583
 have less substrate

1610
00:57:55,583 --> 00:57:57,000
 available for glycolysis.

1611
00:57:57,333 --> 00:57:58,000
 And so you're going to have less

1612
00:57:58,000 --> 00:57:59,250
 glycolysis in general.

1613
00:58:00,083 --> 00:58:01,916
 When you reintroduce substrate into the

1614
00:58:01,916 --> 00:58:03,583
 equation, remember, we're talking about

1615
00:58:03,583 --> 00:58:04,666
 trillions of cells here.

1616
00:58:04,666 --> 00:58:08,125
 Every one of them can run glycolysis.

1617
00:58:08,666 --> 00:58:10,083
 So when you have more substrate

1618
00:58:10,083 --> 00:58:10,958
 available, you're going

1619
00:58:10,958 --> 00:58:12,083
 to increase glycolysis.

1620
00:58:12,666 --> 00:58:13,958
 Glycolysis will shred you up.

1621
00:58:14,416 --> 00:58:16,666
 That's why sprinting works.

1622
00:58:16,916 --> 00:58:19,833
 That's why high altitude training or high

1623
00:58:19,833 --> 00:58:20,875
 altitude kind of

1624
00:58:20,875 --> 00:58:22,750
 hypoxia works to lean you up.

1625
00:58:22,750 --> 00:58:23,375
 It's been proven.

1626
00:58:24,500 --> 00:58:25,833
 So cancer patients know

1627
00:58:25,833 --> 00:58:27,666
 this glycolysis leans you up.

1628
00:58:28,333 --> 00:58:29,916
 So when you increase glycolysis through

1629
00:58:29,916 --> 00:58:30,875
 increasing substrate,

1630
00:58:31,375 --> 00:58:33,250
 you're going to get lean.

1631
00:58:33,916 --> 00:58:35,166
 The other variable that no one's talking

1632
00:58:35,166 --> 00:58:36,708
 about is just simply that you're

1633
00:58:36,708 --> 00:58:37,625
 recolonizing the gut.

1634
00:58:37,875 --> 00:58:39,000
 And I think it's something that a lot of

1635
00:58:39,000 --> 00:58:41,333
 low carb influencers have stumbled onto

1636
00:58:41,333 --> 00:58:42,583
 and they don't even know it.

1637
00:58:42,583 --> 00:58:43,166
 And it's just simply

1638
00:58:43,166 --> 00:58:44,916
 that I've experienced this.

1639
00:58:45,208 --> 00:58:47,083
 When you recolonize the gut rapidly,

1640
00:58:48,375 --> 00:58:53,416
 there are very specific proteins that are

1641
00:58:53,416 --> 00:58:56,375
 related to fasting and fat loss.

1642
00:58:57,291 --> 00:59:01,750
 One of them is ANGLP4, PT4, or FAFE,

1643
00:59:02,333 --> 00:59:03,833
 fasting induced adipose factor.

1644
00:59:04,708 --> 00:59:08,083
 That is a protein that is secreted during

1645
00:59:08,083 --> 00:59:09,250
 fasting that actually

1646
00:59:09,250 --> 00:59:11,875
 drives fatty acid liberation.

1647
00:59:13,375 --> 00:59:19,083
 And what you will find is that that same

1648
00:59:19,083 --> 00:59:19,875
 protein can be

1649
00:59:19,875 --> 00:59:21,166
 stimulated by the microbiome.

1650
00:59:21,875 --> 00:59:24,791
 So when you increase taxa during a fed

1651
00:59:24,791 --> 00:59:27,250
 state that produce this protein,

1652
00:59:28,375 --> 00:59:29,625
 you drive fat loss.

1653
00:59:30,000 --> 00:59:33,083
 It actually helps prevent fatty acid

1654
00:59:33,083 --> 00:59:36,000
 storage and drive fatty acid release.

1655
00:59:37,041 --> 00:59:39,458
 So you can actually drive fat loss

1656
00:59:39,458 --> 00:59:41,833
 through the microbiome through mimicking

1657
00:59:41,833 --> 00:59:43,125
 fasting through that.

1658
00:59:43,333 --> 00:59:45,000
 So you have glycolysis and you have the

1659
00:59:45,000 --> 00:59:47,958
 recolonization of the microbiome along

1660
00:59:47,958 --> 00:59:48,875
 with protein restriction.

1661
00:59:49,166 --> 00:59:51,458
 So those are three variables that all

1662
00:59:51,458 --> 00:59:52,708
 work together all at once.

1663
00:59:53,000 --> 00:59:55,166
 And so that explains things, I think

1664
00:59:55,166 --> 00:59:57,250
 pretty well, would be my answer.

1665
00:59:58,083 --> 00:59:58,750
 Okay, that's perfect.

1666
00:59:59,000 --> 01:00:02,541
 And do you think maybe a bit more that I

1667
01:00:02,541 --> 01:00:04,708
 spoke not really, it's not like we

1668
01:00:04,708 --> 01:00:06,166
 haven't talked about anything technical

1669
01:00:06,166 --> 01:00:07,083
 to stay listy honest.

1670
01:00:08,083 --> 01:00:10,541
 And when somebody is going through some

1671
01:00:10,541 --> 01:00:12,125
 sort of disease statement, maybe when

1672
01:00:12,125 --> 01:00:13,708
 there's some impaired match or conjugal

1673
01:00:13,708 --> 01:00:15,291
 function, there's an elevated sort of

1674
01:00:15,291 --> 01:00:16,791
 cell dangerous responses at work.

1675
01:00:17,750 --> 01:00:20,000
 There's obviously in those states is

1676
01:00:20,000 --> 01:00:22,250
 going to be impaired oxfoss down

1677
01:00:22,250 --> 01:00:23,791
 regulated use of fatty acids.

1678
01:00:24,416 --> 01:00:27,083
 Do you envisage that being maybe a

1679
01:00:27,083 --> 01:00:29,166
 potentially effective strategy for people

1680
01:00:29,166 --> 01:00:31,291
 who do have some sort of matcha conjugal

1681
01:00:31,291 --> 01:00:34,375
 impairment to sort of bypass that block

1682
01:00:34,375 --> 01:00:36,625
 in energy production, it'd be in the

1683
01:00:36,625 --> 01:00:37,875
 short term while you're dealing with

1684
01:00:37,875 --> 01:00:39,166
 maybe the underlying issues.

1685
01:00:39,791 --> 01:00:40,666
 Yeah, I certainly think so.

1686
01:00:40,666 --> 01:00:41,958
 I think it could be.

1687
01:00:42,750 --> 01:00:43,625
 I would just say it's

1688
01:00:43,625 --> 01:00:44,708
 certainly something to try.

1689
01:00:45,541 --> 01:00:46,041
 Fair enough.

1690
01:00:46,291 --> 01:00:46,500
 Perfect.

1691
01:00:46,958 --> 01:00:47,166
 Okay.

1692
01:00:48,750 --> 01:00:50,833
 Last one, and then I'll let you go.

1693
01:00:52,125 --> 01:00:53,541
 Any new molecules you're particularly

1694
01:00:53,541 --> 01:00:56,333
 excited about, just generally speaking,

1695
01:00:56,583 --> 01:00:57,458
 not giving away any

1696
01:00:57,458 --> 01:00:58,750
 trade secrets or IPF course.

1697
01:00:59,541 --> 01:01:00,041
 Yeah, there's...

1698
01:01:01,166 --> 01:01:04,416
 So we're in the burgeoning era of

1699
01:01:04,416 --> 01:01:05,208
 precision fermentation.

1700
01:01:06,708 --> 01:01:08,583
 Basically, we can get bacteria to make

1701
01:01:08,583 --> 01:01:11,916
 very specific immunoglobulins or proteins

1702
01:01:11,916 --> 01:01:13,666
 or different things we want it to make.

1703
01:01:14,666 --> 01:01:16,416
 And where this gets really interesting is

1704
01:01:16,416 --> 01:01:18,125
 in the replication of milk proteins.

1705
01:01:19,083 --> 01:01:20,416
 So lactoferrin is kind of the most

1706
01:01:20,416 --> 01:01:22,250
 conspicuous example, but there are other

1707
01:01:22,250 --> 01:01:24,750
 ones that are blowing up.

1708
01:01:25,291 --> 01:01:25,875
 They're not blowing up.

1709
01:01:26,666 --> 01:01:27,375
 You're going to see...

1710
01:01:28,458 --> 01:01:30,833
 What you're going to see is the

1711
01:01:30,833 --> 01:01:35,000
 introduction of additional co-factors of

1712
01:01:35,000 --> 01:01:36,916
 unique things that are present in

1713
01:01:36,916 --> 01:01:40,583
 mother's milk that are additive with

1714
01:01:40,583 --> 01:01:42,916
 respect to the equation of

1715
01:01:42,916 --> 01:01:44,500
 optimizing the metabolism.

1716
01:01:44,875 --> 01:01:45,625
 And it gets back to

1717
01:01:47,500 --> 01:01:50,625
 mother's milk is growth serum and it

1718
01:01:50,625 --> 01:01:52,625
 triggers all the right things in all the

1719
01:01:52,625 --> 01:01:53,583
 right way when you're young.

1720
01:01:54,458 --> 01:01:56,833
 And it makes sense that there could be

1721
01:01:56,833 --> 01:01:58,416
 some significant benefits to

1722
01:01:58,416 --> 01:02:00,333
 replicating aspects of that.

1723
01:02:00,750 --> 01:02:03,208
 And through precision fermentation now,

1724
01:02:03,208 --> 01:02:04,666
 we're seeing kind of a release of that.

1725
01:02:05,583 --> 01:02:05,916
 Okay.

1726
01:02:05,916 --> 01:02:06,541
 Perfect answer.

1727
01:02:06,791 --> 01:02:07,083
 Thank you.

1728
01:02:07,666 --> 01:02:09,291
 Cheryl, like I said, you've been a star.

1729
01:02:09,291 --> 01:02:10,583
 This is a conversation I've been wanting

1730
01:02:10,583 --> 01:02:11,333
 to have for a while.

1731
01:02:11,583 --> 01:02:12,291
 So thank you.

1732
01:02:12,291 --> 01:02:14,125
 I appreciate your time and hopefully

1733
01:02:14,125 --> 01:02:16,166
 we'll be able to do this again soon.

1734
01:02:17,125 --> 01:02:18,000
 Just to finish off,

1735
01:02:18,000 --> 01:02:19,125
 where can people find you?

1736
01:02:19,125 --> 01:02:20,458
 Should they wish to connect, learn more

1737
01:02:20,458 --> 01:02:22,166
 about what it is you do, your work, your

1738
01:02:22,166 --> 01:02:23,750
 company, Veep, et cetera?

1739
01:02:24,250 --> 01:02:25,166
 Yeah, probably the best

1740
01:02:25,166 --> 01:02:26,500
 place is my Instagram.

1741
01:02:27,500 --> 01:02:28,583
 So that's real Joel Green.

1742
01:02:29,083 --> 01:02:31,291
 And then my link tree has

1743
01:02:31,291 --> 01:02:32,458
 all those goodies in it.

1744
01:02:32,458 --> 01:02:33,375
 And then I'm trying to

1745
01:02:33,375 --> 01:02:34,875
 grow my ex, my Twitter.

1746
01:02:35,750 --> 01:02:37,625
 I just don't post often enough, but if

1747
01:02:37,625 --> 01:02:38,375
 you want to follow me,

1748
01:02:38,666 --> 01:02:39,541
 same thing, real Joel Green.

1749
01:02:40,208 --> 01:02:44,166
 And then our URL is a veepnutrition.com.

1750
01:02:44,833 --> 01:02:45,041
 Perfect.

1751
01:02:45,708 --> 01:02:47,083
 Joel, thank you so much for your time.

1752
01:02:47,625 --> 01:02:48,291
 Thank you, Rob.

1753
01:02:48,291 --> 01:02:49,375
 I really enjoyed the convo.

1754
01:02:49,375 --> 01:02:49,666
 Really great.