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Speaker 1: So a'n Stevens. Welcome to the podcast.

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Speaker 2: Doctor Paul, great to see you.

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Speaker 3: How are things And Matt, thanks for going very very

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Speaker 3: well here in Australia.

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Speaker 1: And I can see that well. I know that you're

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Speaker 1: in Aspen, Colorado.

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Speaker 3: You've got a rather nice background there, so I love

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Speaker 3: you being in Aspen, Colorado.

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Speaker 2: You know, I was born here in Colorado, so born

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Speaker 2: in these mountains and then raised in northern California, a

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Speaker 2: little town south of San Francisco. So spent a lot

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Speaker 2: of time here just growing up. And then I just

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Speaker 2: moved back pre pandemic about twenty fifteen. In the pandemic

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Speaker 2: hit and I was still going back and forth with California,

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Speaker 2: and I basically said I would absolutely never go back

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Speaker 2: to California.

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Speaker 1: So I moved back to.

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Speaker 2: Colorado full time and found myself here in the mountains.

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Speaker 1: And Jesus, a lot of active people around there, isn't.

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Speaker 2: There Incredibly Yeah, it doesn't matter how active you are,

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Speaker 2: there's always someone more active. Like, yeah, we're a little maniacal,

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Speaker 2: but in good ways.

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Speaker 1: Yeah, not very cold. I mean, you are a scientist,

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Speaker 1: data visionary.

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Speaker 3: You're also a keynote speaker, and you kind of play

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Speaker 3: in the space of human behavior biology and also the

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Speaker 3: intersection with AI and so just give people a bit

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Speaker 3: of a sense of your background and how you ended

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Speaker 3: up where you are right now.

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Speaker 1: Professor.

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Speaker 2: Yeah, So education wise, I was I studied biotechnology and

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Speaker 2: then molecular biology. You were my skills when I was

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Speaker 2: in the lab. So I worked in small molecule drug

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Speaker 2: therapeutics in biotech for really the first third of my

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Speaker 2: career and it was an amazing time. We sequence the

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Speaker 2: human genome and it's like, wait, what's next. You know,

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Speaker 2: the division back then was knowing the genome would help

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Speaker 2: unlock you know, really the future of meta but that

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Speaker 2: wasn't quite the case. You know, we didn't really take

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Speaker 2: into account. You know, you have the genem over here,

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Speaker 2: you have the protium over here, but in between you

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Speaker 2: have you know, essentially the gene regulation. So epigenetics, epigenomics, transcriptome, metabolam,

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Speaker 2: all those pieces. So it's been quite fun though over

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Speaker 2: these last number of years. My research then went into

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Speaker 2: data science, so really focusing on user measurement and optimization.

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Speaker 2: That was in my twenties, and then further I began

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Speaker 2: doing trathlons and iron man distances, and it was through

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Speaker 2: those experiences I really began to optimize my data, my

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Speaker 2: biology using data basically, and you know that idea that

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Speaker 2: when you have wearable data, really any type of data,

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Speaker 2: you know, ultimately you can start to synthesize and understand

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Speaker 2: how that can impact your body. And so it really

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Speaker 2: began using protocols at scale to optimize my biology for racing,

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Speaker 2: and that ultimately led me to my current area of research.

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Speaker 3: Ah okay, so your interest was in performance initially.

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Speaker 2: Performance consciousness, you know, kind of spanning a spectrum. But yeah, absolutely,

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Speaker 2: without being too obsessive about it. You know, I think

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Speaker 2: there's people who get absolutely obsessive about, you know, the

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Speaker 2: measurement side. I guess I would say.

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Speaker 1: So Brian Johnson springing to mind, Yeah, I.

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Speaker 2: Mean he's he's he's over here, you know, relative to measurement.

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Speaker 2: I mean most humans are over here. You know, we're

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Speaker 2: probably over here is but certainly not all the way over.

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Speaker 2: So I think it's important to have a solid regimen

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Speaker 2: and routine and what we call protocols, but also live

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Speaker 2: your life, you know as well.

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Speaker 3: And in terms of measurement and and and measurement devices,

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Speaker 3: what what sort of things do you think are useful

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Speaker 3: for people and what sort of what sort of measures

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Speaker 3: should they be looking at.

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Speaker 2: Yeah, so we spend a lot of time thinking about

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Speaker 2: longevity protocols, helped protocols, and we've analyzed tens of thousands

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Speaker 2: at this stage. And you know, we look at the

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Speaker 2: dominant themes. So you have nutrition, exercise, sleep, stress, you know,

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Speaker 2: metabolic regulation of some kind connection you know as well.

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Speaker 2: Those usually like the six areas we really you know,

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Speaker 2: think about routinely, and so generally starting with like sleep.

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Speaker 2: You know, every person we know has an issue with

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Speaker 2: sleeping or you know, maybe their gut microbiome. So sleep

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Speaker 2: as an example. There's a number of wearables that I've

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Speaker 2: used over the years. My favorite is an Aura ring

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Speaker 2: because it's really the least invasive, the least amount of EMF.

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Speaker 2: You can even turn the bluetooth off, and it's you know,

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Speaker 2: very small essentially, and so that's one of my favorite

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Speaker 2: for sleep relative to accuracy. When I'm training and doing

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Speaker 2: iron Man's or you know, trail running, I usually wear

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Speaker 2: a garment and then I also have a loop and

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Speaker 2: a fit bit, and so we test all of these

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Speaker 2: wearables on the day to day so I think, you know,

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Speaker 2: they're all generally good, some better than others. Apple Watch

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Speaker 2: is great for a normal human just you know, doing

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Speaker 2: the day to day. So it really just depends on

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Speaker 2: you know, what your applications are.

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Speaker 3: Yeah, it's interesting because recently, I so I've been I've

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Speaker 3: been wearing an Apple Watch for a number of years, and

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Speaker 3: then recently I was also worrying a garment because of

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Speaker 3: an intervention we're doing with the military guys over here

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Speaker 3: who all have Garman watches and and and the HRV

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Speaker 3: is is a little bit different on both of those devices, right,

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Speaker 3: And I think this is what people don't understand is

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Speaker 3: that whilst they're all reasonably accurate, they do vary, right,

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Speaker 3: And that my understanding is that Garman is probably a

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Speaker 3: bit more accurate when it comes to HRV because I

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Speaker 3: think they bought first Beat a number of years ago,

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Speaker 3: and Apple uses a slightly different measurement technique. I think

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Speaker 3: most of them use our MSSD.

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Speaker 1: Right, So.

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Speaker 3: You have you have to you can't go from device

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Speaker 3: to device in order for tracking your trends accurate, right.

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Speaker 2: Yeah, as long as you stick with one one device

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Speaker 2: and you look at the trends holistically, you'll be fine, right,

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Speaker 2: I mean, ninety five percent of humans would be fine.

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Speaker 2: You know, there is there's no standard algorithm for HRV measurement,

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Speaker 2: you know, so again it absolutely varies between different devices.

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Speaker 2: We actually got IRB approval to do a research study

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Speaker 2: on exactly that, so looking at the variants of HRV.

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Speaker 2: And then to your point, the the Apple Watch is

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Speaker 2: also it's a different definition, it's not rms SD and

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Speaker 2: then they also I think sample so you know, honestly,

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Speaker 2: I think Apple Watch is one of the less accurate

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Speaker 2: of all of them. But you know, again it's good

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Speaker 2: for the normal US and human for you know, just

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Speaker 2: the typical trends.

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Speaker 3: Yeah, well that's the thing, isn't it. It's more the

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Speaker 3: trend over time rather than the absolute number.

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Speaker 1: With this sort of.

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Speaker 2: Number doesn't really matter, you know, I mean, it's important,

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Speaker 2: but yeah, it's all relative.

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Speaker 3: So yeah, last year numbers consistently in the no chains

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Speaker 3: or something like that.

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Speaker 2: What is what is your HRV?

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Speaker 3: You know on an Apple Watch it kicks around fifty,

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Speaker 3: sort of bounces around that.

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Speaker 1: Number a little bit lower on a garment, right.

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Speaker 3: Which is which was interesting. But the garment also told

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Speaker 3: me that it once three weeks of data before it

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Speaker 3: really gets accurate. And I quite like that, right, I'm like, yeah,

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Speaker 3: okay to celebrate.

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Speaker 1: Yeah, no, very cool.

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Speaker 3: So the guy have a There's a research people that

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Speaker 3: I often talk about when I'm presenting to Comforts, and

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Speaker 3: it's the the similarities between overtraining syndrome.

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Speaker 1: In athletes and corporate burnout.

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Speaker 3: Right, So, and I often talk about this type upe

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Speaker 3: that people walk, whether there are an elite athlete or

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Speaker 3: a corporate there's this very thin line between ultimate peak

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Speaker 3: performance on one side of the line and then on

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Speaker 3: the other side of the line over training syndrome or burnout.

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Speaker 1: And I know that you play in this space.

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Speaker 3: So how could people balance whether they're an athlete or

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Speaker 3: whether they are a corporate How do they make sure

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Speaker 3: that they stay on the right side of that type rope?

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Speaker 2: Yeah, one hundred percent. I mean I would. I'd love

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Speaker 2: to read the paper you're referencing, but I would. I

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Speaker 2: would assume that recovery and autonomic regulation is identical part

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Speaker 2: of that, right, And we were just talking about HRV

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Speaker 2: as an example, so you know, I would assume that

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Speaker 2: there would be a connection, you know, between those two,

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Speaker 2: whether it's you know, overtraining or corporate burnout. So recovery.

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Speaker 2: You know, everyone's looking for this longevity cure. You know,

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Speaker 2: what do you do to stay young? And they want

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Speaker 2: to do a pill and peptides and stem cells. And

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Speaker 2: it starts with sleep. You know, if you're getting quality

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Speaker 2: sleep that you can ideally measure, you don't have to,

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Speaker 2: you know, but again I'm a big fan of measurement

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Speaker 2: because it allows you to then optimize. But that's it. Know,

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Speaker 2: you really start with sleep. And so from that perspective again,

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Speaker 2: autonomic you know, HRV resting heart rate, you know, it's

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Speaker 2: kind of the inverse correlation. Yeah, all critically.

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Speaker 3: Important and and and athletes years ago, before HRV measurement

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Speaker 3: became a thing, athletes used to measure their waking heart

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Speaker 3: rate as soon as they woke up, right, and if

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Speaker 3: they're for resting it, yeah, for resting heart rate and

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Speaker 3: if they're they're waking, resting heart rate had gone either up.

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Speaker 1: Or down by three or four beats. That was a sign.

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Speaker 1: You know, that was the early.

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Speaker 3: Indicator of the the current HRV status. Right, And I

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Speaker 3: am I completely align with you in terms of recovery.

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Speaker 3: I mean, when we think about an athlete, and you know,

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Speaker 3: they're constantly manipulating or their their their trainers are manipulating volume, intensity, duration,

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Speaker 3: and and you know, one of the key things of

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Speaker 3: athlete training is you do not increase volume and intensity

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Speaker 3: for a long period of time or you're heading towards burnout.

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Speaker 1: Right, So they'll manipulate all those variables.

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Speaker 3: But I think for the corporate who's listening to us,

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Speaker 3: they're not really in control of volume and intensity.

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Speaker 2: You know.

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Speaker 3: Sometimes they're just in a heavy period at work. And

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Speaker 3: as I say to them, the one lever that you

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Speaker 3: have to pull is recovery.

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Speaker 1: If you're a corporate, right, I think you'd be honored with.

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Speaker 2: That hundred percent. Yeah, you know, and some of the

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Speaker 2: stuff I mean again, I'm a big fan of like

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Speaker 2: cold plunging for autonomic relations. Yes, here in Colorado we

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Speaker 2: go in the rivers right now, all the snows starting

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Speaker 2: to melt, so they're pretty chilly, probably you know, high

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Speaker 2: thirties or so, you know, depending and but yeah, I

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Speaker 2: mean like that as an example. Breathwork would be another.

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Speaker 2: So we call these micro habits in our world. You know,

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Speaker 2: microrabits build a protocol, and so there are protocols to

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Speaker 2: help with recovery. Those protocols to help with anxiety, I

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Speaker 2: mean that's another one just stress in general. You know,

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Speaker 2: what are you doing to manage the stress? Of course

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Speaker 2: the two are obviously connected. So and then for there,

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Speaker 2: you know, what are you putting into your body, what's

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Speaker 2: your you know, your nutritional regimen, what's your exercise regimen,

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Speaker 2: all those pieces, and I find you know, when I

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Speaker 2: was iron main training, we used to do what are

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Speaker 2: called bricks, you know, and essentially like move your training

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Speaker 2: up and then two to three weeks before the race,

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Speaker 2: depending on the distance, you know, you would start to

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Speaker 2: taper yea to really fortify your muscles and then do

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Speaker 2: the race, you know. So there's different strategies there. That

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Speaker 2: makes a lot of sense.

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Speaker 3: Yeah, And I like to talk to people about micro

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Speaker 3: and macro recovery, which.

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Speaker 1: You've essentially you've essentially mentioned, right, So.

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Speaker 3: Your macro recovery is your sleep, and your micro recovery

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Speaker 3: are little bits of recovery you can do throughout the day,

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Speaker 3: like just a little bit of get off your arson, move,

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Speaker 3: drink some water, do some do some slow controlled breathe.

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Speaker 3: That that autonomic regulation. So a lot of people don't

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Speaker 3: realize like one of the most powerful ways to switch

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Speaker 3: on your parasympathetic nervous system and dampen your sympathetic nervous

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Speaker 3: system is through the breath. Do you have a fevered

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Speaker 3: recovery breathing protocol, because there's lots of different ones.

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Speaker 1: Is there anything?

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Speaker 2: No, But I mean I've done so many different kinds,

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Speaker 2: from yoga, nidra to box breathing, you know, everything in between.

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Speaker 2: But if you have a protocol, we'd love to take

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Speaker 2: a look and we can put it on the platform

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Speaker 2: and have people you know, ultimately use it.

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Speaker 3: So yeah, yeah, Look, I mean I generally say to

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Speaker 3: people any type of slow control breathing is going to

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Speaker 3: switch on your vegas nerve from the bottom up. I

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Speaker 3: have personally have a slight bent for resonant frequency breathing

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Speaker 3: because the research shows that that can affect your heart

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Speaker 3: rate variability more than others. But I think I think

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Speaker 3: they e is just to slow down the breath. And

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Speaker 3: another really good protocol that people can use. Actually, my

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Speaker 3: PhD supervisor had told me this one is the your

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Speaker 3: lowest comfortable breathing rate where people can try, where you

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Speaker 3: you just take a normal breath in and then you

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Speaker 3: breathe out through per slips as slow as you possibly

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Speaker 3: can and squeeze everything out of your diaphragm. But what

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Speaker 3: comes really interesting is at the end of that the inhalation,

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Speaker 3: you don't have to actively inhaliate because your lungs will

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Speaker 3: just fill up automatically because of the pressure vacuum that

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Speaker 3: you've created.

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Speaker 1: And it's really quite interesting.

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Speaker 3: But yeah, I highly recommend that people play with a

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Speaker 3: number of different things in terms of recovery, because as

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Speaker 3: you as you rightly said eighties, it's the one thing

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Speaker 3: that's going to determine what side of that type rope

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Speaker 3: that you actually are on them. What what are some

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Speaker 3: early warning signs and symptoms that people would see in

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Speaker 3: their own data or feel that would suggest that A

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Speaker 3: there are an athlete that's overtraining or b there corporate

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Speaker 3: that's starting to get on the wrong side of the

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Speaker 3: type rope.

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Speaker 2: Yeah, one hundred percent. Honestly, I think it's the ones

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Speaker 2: we already mentioned, you know, HRV, resting heart rate. I mean,

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Speaker 2: I look at HRV, the two of them, really but

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Speaker 2: those are my go to and I know, you know,

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Speaker 2: if I'm on the high side, I'm in my HV

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Speaker 2: can be a size one hundred. I'd say average about

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Speaker 2: sixty to seventy with a whoop. And you know, I

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Speaker 2: know if I am really overtraining overtired, it's in like

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Speaker 2: the thirties. So you know, HRV for me is and

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Speaker 2: of course you have again resting heart rate is almost

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Speaker 2: like an inverse correlation.

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Speaker 1: Yea.

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Speaker 2: So those are the two that I go to. You know,

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Speaker 2: there's also sleep scores you can get out of the

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Speaker 2: or ring or readiness is what they call it. You know,

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Speaker 2: both of those are great. It gives you an example

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Speaker 2: or a you know, a specific number relative to your

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Speaker 2: sleep and how you can improve in similar with just

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Speaker 2: your daily readiness. So I think those are all great

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Speaker 2: metrics to use.

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Speaker 3: Yeah, the ones that they frustrate me a little bit

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Speaker 3: as a as a researcher. So when we were looking

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Speaker 3: at doing this this intervention we're doing with the military currently,

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Speaker 3: you know, we were looking at the different devices and

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Speaker 3: looking at HRV and wanting to get the raw data

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Speaker 3: right and a lot of them won't share the raw data.

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Speaker 3: You know, they'll they'll give you a they'll give you

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Speaker 3: a score or a body battery or a readiness score

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Speaker 3: where they don't publish the algorithm, and I get why

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Speaker 3: they don't because that's their IP, right, and it's probably

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Speaker 3: some combination of your sleep and your HRV that they're

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Speaker 3: they're integrating to give you your readiness score. Right, just

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Speaker 3: just my my annoyance as a researchers they don't give

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Speaker 3: you the algorithm so that you can then really accurately

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Speaker 3: work out our people are trending. But but I guess

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Speaker 3: for the individual, it doesn't really matter, right, So.

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Speaker 2: Yeah, exactly for the individual doesn't matter. But actually we

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Speaker 2: might have a partner I could recommend to you who

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Speaker 2: can support you their you know, relative to the HRV measurement.

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Speaker 2: One of our partners, I mean they actually measure each

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Speaker 2: of you through four different modalities, you know when they're

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Speaker 2: doing a session. It's a group that we work.

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Speaker 1: At out of LA.

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Speaker 2: So yeah, but happy to chat and it might have

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Speaker 2: someone for you there.

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Speaker 1: Yeah, okay, cool.

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Speaker 3: And so you talk about similar to me, You talk

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Speaker 3: that that the next frontier is not just lifespan, right,

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Speaker 3: life span is one thing, but health span and mind

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Speaker 3: span or other things. So quickly, I mean most people

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Speaker 3: will be familiar between health span and lifespan, but but

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Speaker 3: just to give the definition or the differentiation between those

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Speaker 3: and also this idea of mind span a lot of

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Speaker 3: people won't be familiar with.

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Speaker 2: Yep, so lifespan. You know, basically, if you were to

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Speaker 2: look at a graph, it's like, what is the quality

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Speaker 2: of your life through really the later you know stages essentially,

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Speaker 2: and then you know, relative to that quality of life,

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Speaker 2: can you improve that? Essentially? So if you look at

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Speaker 2: your life, you know, people really start slowing down in

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Speaker 2: your seventies and eighties, you know, can you basically normalize

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Speaker 2: and have a better you know life quality of life?

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Speaker 2: I come back to, you know, in those later later

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Speaker 2: periods basically, so you're extending those last years. I think

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Speaker 2: of mind span as a reflection of your This is

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Speaker 2: my personal definition. But you know, I would almost throw

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Speaker 2: in consciousness as well as brain and cognition. You know,

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Speaker 2: generally we spend a lot of time just thinking about

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Speaker 2: brain optimization, but you know consciousness as part of that

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Speaker 2: as well. That could include spirituality, conclude connection, you know,

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Speaker 2: any of those pieces. So that's also been in there

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Speaker 2: of my research over the years.

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Speaker 3: Yeah, cool, and Hi is ai either helping in this

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Speaker 3: area or helping to ship some of the thinking in

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Speaker 3: this area.

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Speaker 2: Yeah, I mean, I think there's positives and negatives of everything.

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Speaker 2: You know, it's a spectrum, So I believe there are

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Speaker 2: some very strong positives. An example right now is one

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Speaker 2: of our lead scientists. His name's doctor Galen Buckwalter. Galen

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Speaker 2: had a tragic accident when he was seventeen, jumped off

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Speaker 2: a bridge, hit a rock, and is a quadriplegic. And

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Speaker 2: he has he qualified for a clinical trial at Caltech

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Speaker 2: and he has six neural implants in his brain, and

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Speaker 2: so I've been with him at cal Tech before. It's

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Speaker 2: an amazing clinical trial. He comes in and they screw

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Speaker 2: on essentially these they're called peds essentially interfaces onto his skull,

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Speaker 2: and then they connect his brain to the Internet. And

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Speaker 2: so we are the generation that's seeing the intersection of

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Speaker 2: biology and machines right now. And so in that example,

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Speaker 2: you know, the AI is helping Galen to control a

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Speaker 2: robotic arm and ultimately free him, you know, to some degree.

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Speaker 2: So that's called brain computer interfaces. There's also spinal cord

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Speaker 2: essentially interfaces where they're going directly into the spinal cord,

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Speaker 2: you know, for people who have these tragic injuries and accidents.

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Speaker 2: So I think those are very positive applications of AI.

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Speaker 2: There's also negative ones as well. You know, you see

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Speaker 2: in the workplace, I mean everyone is basically just using

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Speaker 2: an LLM to not think yeah, and so I think

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Speaker 2: that can very much be to the detriment of the

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Speaker 2: human But you know what we found is really it's

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Speaker 2: human in the loop. You know that concept like you

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Speaker 2: should absolutely utilize the AI, but you can't trust it.

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Speaker 2: You know, it's not there yet. And especially you know

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Speaker 2: in our world, Paul, I mean we have many uh

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Speaker 2: you know clients, you know, we hear about this all

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Speaker 2: the time where they're just taking all of their medical

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Speaker 2: information and just uploading it to chat GPT. And the

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Speaker 2: question is why, Well, in the United States are you know,

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Speaker 2: our our physicians are not taught nutrition. You know, they're

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Speaker 2: taught maybe three or four days I think out of

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Speaker 2: their entire tenure.

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Speaker 1: It's pretty much the same over here.

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Speaker 3: I think they get about a week's education or nutri

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Speaker 3: Do not go and see a doctor with for nutritional advice.

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Speaker 2: Right of course? Right well there, and that's that's that's

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Speaker 2: kind of insane, right. I have this quick anecdote. I

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Speaker 2: broke my collarbone here in Colorado, and I went to

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Speaker 2: the number one orthopedic in the country and I was like,

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Speaker 2: what's you know. She's like, it's broken. I was like, okay,

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Speaker 2: what's my recovery protocol? And she threw me a sling

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Speaker 2: and so my recovery protocol was a mobilization. And then

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Speaker 2: I went to my network and I was focusing on nutrition,

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Speaker 2: bone broth, collagen. I did some pemp PMF if you're

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Speaker 2: familiar with that modality, localized electrical stimulation basically, and I

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Speaker 2: went back and she said come back in four weeks.

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Speaker 2: I went back. I'm sorry, she said come back in six.

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Speaker 2: I went back and forth and she did the X

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Speaker 2: ray and she's like, oh my gosh, it's completely healed.

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Speaker 2: What have you been doing? And I was like, doctor,

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Speaker 2: I've been focusing on my nutrition and she's like, we

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Speaker 2: never would have thought of that. And it was one

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Speaker 2: of those moments. Paul. It's like when I started my

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Speaker 2: company is like, okay, we have.

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Speaker 1: To do better.

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Speaker 2: Like if your doctor is not thinking about nutrition, there's

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Speaker 2: an issue, you know, we have to think of the

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Speaker 2: whole human. Another example, my backgroun's in molecular biology. I

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Speaker 2: didn't really cover that. But I spent many years in

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Speaker 2: the lab as a molecular biologist, and you know, from

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Speaker 2: that perspective, you know they're not taught genomics, you know,

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Speaker 2: let alone epigenomics, let alone peptide. So you know, it's

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Speaker 2: it's this fairly terrifying trend. People are now just going

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Speaker 2: to the ms and uploading everything because they can't find

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Speaker 2: what they need from their doctors today. So you know,

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Speaker 2: I again, I try to be an optimist on that front,

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Speaker 2: and that's why we're you know, putting some confines around

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Speaker 2: what we're building. But it's a it's a challenge.

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Speaker 3: It's interesting you mentioned that that whole recovery pace. So

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Speaker 3: so last year, in January last year, I had open

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Speaker 3: heart surgery because I find out by chance that I

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Speaker 3: had a congenital heart defect. I had a bicuspo of

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Speaker 3: a ORTI file rather than try customers.

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Speaker 1: But but anyway, I ended up having open heart surgery

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Speaker 1: and I wanted.

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Speaker 3: To get out of that hospital as quick as I

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Speaker 3: possibly could because number one, the food was shit right

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Speaker 3: that it was so such low protein. And I know

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Speaker 3: that if you just had your chest cut open and

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Speaker 3: cut through bone, you need you need amino acids big time.

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Speaker 3: You need collagen, you need all of those things you need.

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Speaker 3: You need to be looking at the window at nature,

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Speaker 3: I was looking at at a brick wall. I'm like,

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Speaker 3: this place is shocking for my recovery. But I also

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Speaker 3: I used bone broths a lot, I had a lot

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Speaker 3: of protein, and I used red light and near in

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Speaker 3: for real light on the wound, which which was freaking awesome.

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Speaker 1: That like how quickly that wound healed.

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Speaker 3: And now they actually use you know, real light is

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Speaker 3: a standard protocol for burns victim for a very good reason, right.

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Speaker 3: And the and the near infra red stimulates your microchondria.

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Speaker 3: So there's there's so much stuff that we can do

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Speaker 3: in terms of recovery that is just not in the

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Speaker 3: healthcare system. And I think the reason for it is

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Speaker 3: the healthcare system is really the healthcare system. It's the

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Speaker 3: sick curse system, right. It is just interested in can

436
00:23:21,520 --> 00:23:25,520
Speaker 3: we stop or cure this disease and then once we do, boom,

437
00:23:25,600 --> 00:23:30,000
Speaker 3: you're good or fix this thing and then that recovery.

438
00:23:30,160 --> 00:23:34,840
Speaker 3: They are not interested in recovery and optimal health whatsoever. Right,

439
00:23:34,880 --> 00:23:37,679
Speaker 3: So I think it's important for people to understand that

440
00:23:37,840 --> 00:23:39,240
Speaker 3: different or prevention.

441
00:23:39,600 --> 00:23:42,960
Speaker 2: You know, yes, yeah, that's the doctors we work with.

442
00:23:43,560 --> 00:23:45,200
Speaker 2: You know, they're really focused on how do you prevent

443
00:23:45,240 --> 00:23:47,879
Speaker 2: the disease? You know, even gets to the point it's

444
00:23:47,920 --> 00:23:51,840
Speaker 2: an actual disease. Sometimes you can, of course, but you know,

445
00:23:51,920 --> 00:23:54,520
Speaker 2: I think starting there, we're big fans, so we of

446
00:23:54,520 --> 00:23:58,280
Speaker 2: course look at the biomarkers in biometrics, but now pulling

447
00:23:58,320 --> 00:24:00,520
Speaker 2: in you know, the epigenetic data as well well, and

448
00:24:00,600 --> 00:24:02,560
Speaker 2: you can really build this profile of a human and

449
00:24:02,600 --> 00:24:06,080
Speaker 2: really understand you know, their genetic predisposition all around to

450
00:24:06,119 --> 00:24:09,399
Speaker 2: their gene expression and how does that ultimately impact you know,

451
00:24:09,400 --> 00:24:13,119
Speaker 2: their day to day you know. Fascinating fact is, you

452
00:24:13,160 --> 00:24:16,960
Speaker 2: know we control through our behavior and our lifestyle, and

453
00:24:17,040 --> 00:24:18,800
Speaker 2: it depends on the tissue. And it's you know, it's

454
00:24:18,800 --> 00:24:20,399
Speaker 2: a little bit of a controversial number, but you know,

455
00:24:20,480 --> 00:24:22,880
Speaker 2: maybe thirty to fifty sixty percent of our gene expression

456
00:24:22,960 --> 00:24:25,280
Speaker 2: is based on our behavior. It's based on the people

457
00:24:25,280 --> 00:24:28,240
Speaker 2: you surround yourself with. It's based on the conversations, you know,

458
00:24:28,760 --> 00:24:30,680
Speaker 2: the things that you do. How much time do you

459
00:24:30,760 --> 00:24:33,520
Speaker 2: spend in nature? How much time are you behind a desk,

460
00:24:33,600 --> 00:24:35,840
Speaker 2: you know, sitting there hunched over you know, da da

461
00:24:35,880 --> 00:24:38,480
Speaker 2: da so I find it a bit empowering, you know,

462
00:24:38,520 --> 00:24:41,160
Speaker 2: from that perspective, because we do have some control even

463
00:24:41,200 --> 00:24:43,680
Speaker 2: though you have a genetic predisposition, you know, for something

464
00:24:43,680 --> 00:24:46,840
Speaker 2: like Alzheimer's, you know, you can't necessarily stop the onset

465
00:24:46,840 --> 00:24:49,199
Speaker 2: of the disease, but you can help support you know,

466
00:24:49,240 --> 00:24:52,000
Speaker 2: the onset of the condition and the symptoms and so

467
00:24:52,080 --> 00:24:54,959
Speaker 2: forth and similar you know, even with Alzheimer's, as we

468
00:24:54,960 --> 00:24:58,040
Speaker 2: were chatting about earlier, you know, there are protocols that

469
00:24:58,080 --> 00:25:02,080
Speaker 2: outline again behavioral modification changes, things that we can do

470
00:25:03,160 --> 00:25:05,359
Speaker 2: that ultimately can help prevent dementia, you know, so that

471
00:25:05,400 --> 00:25:06,560
Speaker 2: one is more preventable.

472
00:25:07,000 --> 00:25:11,640
Speaker 3: Yeah, absolutely, And and and actually interesting on dementia because

473
00:25:12,400 --> 00:25:17,600
Speaker 3: in Australia and I mean in America and in Australia

474
00:25:17,640 --> 00:25:19,600
Speaker 3: it's always been the UK the biggest killer has been

475
00:25:19,600 --> 00:25:23,919
Speaker 3: cardiovascular disease, and NI for the first time, the biggest

476
00:25:24,000 --> 00:25:25,720
Speaker 3: killer of females is actually dementia.

477
00:25:25,840 --> 00:25:28,040
Speaker 1: It's not cardiovascular disease, right.

478
00:25:28,000 --> 00:25:31,560
Speaker 3: And and and I think there is a there's an

479
00:25:31,600 --> 00:25:35,840
Speaker 3: explosion of dementia just around the court. Well, we're actually

480
00:25:35,840 --> 00:25:39,480
Speaker 3: starting to see it now, you know, with that metabolic

481
00:25:39,560 --> 00:25:42,600
Speaker 3: dysregulation that people have, you know that a lot of

482
00:25:42,600 --> 00:25:46,800
Speaker 3: people are calling it type three diabetes. So and and

483
00:25:47,320 --> 00:25:50,080
Speaker 3: what you mentioned around those protocols there was we just

484
00:25:50,080 --> 00:25:52,879
Speaker 3: talked offer that that Lancet paper that came out that

485
00:25:53,119 --> 00:25:57,439
Speaker 3: identified all of these risk factors for dementia and that

486
00:25:57,440 --> 00:26:02,920
Speaker 3: that by by implementing behavioraliant dimensions, you know, they estimated

487
00:26:03,000 --> 00:26:04,920
Speaker 3: they could reduce I can't remember when it was sixty

488
00:26:05,040 --> 00:26:07,760
Speaker 3: or seventy percent of dementia cases, right, which is pretty think.

489
00:26:07,600 --> 00:26:10,960
Speaker 2: It massive globally, And there's fifty five million you know,

490
00:26:11,080 --> 00:26:12,919
Speaker 2: has of the writing of that paper, So I mean

491
00:26:12,920 --> 00:26:15,840
Speaker 2: we're talking tens of millions of people that could be

492
00:26:15,880 --> 00:26:19,639
Speaker 2: supported through lifestyle and behavior. So yeah, it's definitely a

493
00:26:19,640 --> 00:26:22,600
Speaker 2: mission of ours. We are going to be publishing. You know,

494
00:26:22,640 --> 00:26:24,240
Speaker 2: you can find the paper online, but we put it

495
00:26:24,240 --> 00:26:26,560
Speaker 2: into a protocol. People can follow Paul and we'll be

496
00:26:26,640 --> 00:26:28,560
Speaker 2: giving us away and you know your readers would be

497
00:26:28,880 --> 00:26:31,439
Speaker 2: would have access to that. But that's the concept. And

498
00:26:31,480 --> 00:26:33,600
Speaker 2: imagine giving that to our parents and our grandparents. And

499
00:26:33,640 --> 00:26:35,840
Speaker 2: they shouldn't start in their sixties and seventies. They should

500
00:26:35,880 --> 00:26:36,280
Speaker 2: start now.

501
00:26:36,840 --> 00:26:39,960
Speaker 3: Yeah, that's some of the early research coming out. Nigh

502
00:26:40,119 --> 00:26:43,800
Speaker 3: is saying that that dementia and Alzheimer's are starting in

503
00:26:43,840 --> 00:26:47,600
Speaker 3: your thirties. And it starts with metabolism, right, it starts

504
00:26:47,640 --> 00:26:50,000
Speaker 3: with when you have that high.

505
00:26:49,760 --> 00:26:53,160
Speaker 1: Normal blood sugar, you're on the path. You are on

506
00:26:53,240 --> 00:26:54,120
Speaker 1: the path, right.

507
00:26:54,440 --> 00:26:58,520
Speaker 3: And so we've talked about the protocol, So so let's

508
00:26:58,560 --> 00:27:00,240
Speaker 3: let's talk a little bit about what you do in

509
00:27:00,400 --> 00:27:04,440
Speaker 3: breen one and so just say I'm a typical person

510
00:27:04,440 --> 00:27:08,040
Speaker 3: who comes in through my company or whatever to bring

511
00:27:08,160 --> 00:27:11,360
Speaker 3: one what what what happens?

512
00:27:12,280 --> 00:27:16,399
Speaker 2: Yeah, so we look at the world again based in

513
00:27:16,440 --> 00:27:19,159
Speaker 2: the concept of a protocol. And the protocol is just

514
00:27:19,200 --> 00:27:21,800
Speaker 2: your routine. You know, like Paul, what do you do

515
00:27:21,840 --> 00:27:23,080
Speaker 2: when you get up in the morning. You know, what

516
00:27:23,119 --> 00:27:25,080
Speaker 2: are the ten things you do before you really start

517
00:27:25,119 --> 00:27:29,600
Speaker 2: your day. And so we consider the protocols the framework,

518
00:27:29,640 --> 00:27:31,760
Speaker 2: and then the things that you do or micro habits

519
00:27:31,800 --> 00:27:35,720
Speaker 2: just to oversimplify it. And so we will take a

520
00:27:35,760 --> 00:27:38,439
Speaker 2: scientific paper, we run it through our AI. We generate

521
00:27:38,480 --> 00:27:41,320
Speaker 2: these protocols and then we can tailor them. This concept

522
00:27:41,320 --> 00:27:45,920
Speaker 2: of adaptive AI based on the human based on their demographics,

523
00:27:45,960 --> 00:27:48,760
Speaker 2: based on their genetics, based on their it could be

524
00:27:48,800 --> 00:27:51,560
Speaker 2: a brain scan. We just partnered with an EEG device

525
00:27:51,680 --> 00:27:55,560
Speaker 2: where we can now incorporate EEG data or BCI data

526
00:27:55,600 --> 00:27:58,520
Speaker 2: into these profiles essentially, and then we give them a

527
00:27:58,640 --> 00:28:02,960
Speaker 2: hyper personalized tailor program essentially based on the protocol and

528
00:28:02,960 --> 00:28:05,919
Speaker 2: the micro habits is the concept, and we do that

529
00:28:06,000 --> 00:28:09,720
Speaker 2: on a corporate level. We do it working with concierge doctors.

530
00:28:10,119 --> 00:28:13,959
Speaker 2: That's really been our major focus longevity, you know, that space,

531
00:28:14,000 --> 00:28:17,680
Speaker 2: because it's exploding. We actually just launched peptides dot one,

532
00:28:17,960 --> 00:28:21,320
Speaker 2: which is a offshoot of brain dot one. It's peptides

533
00:28:21,359 --> 00:28:23,560
Speaker 2: with an A S. And you know, the vision there

534
00:28:23,640 --> 00:28:26,760
Speaker 2: is to actually provide information support of people that are

535
00:28:26,800 --> 00:28:31,160
Speaker 2: looking to you know, find quality peptides, which is a challenge.

536
00:28:31,640 --> 00:28:33,359
Speaker 2: You know, we're in this kind of inflection point at

537
00:28:33,440 --> 00:28:36,280
Speaker 2: least here in the States where a lot of these things,

538
00:28:36,320 --> 00:28:38,240
Speaker 2: you know, I've been doing for years as a triathlete.

539
00:28:38,240 --> 00:28:40,920
Speaker 2: I mean, we've been doing peptides for like decades, you know,

540
00:28:41,000 --> 00:28:43,160
Speaker 2: in some cases red light, you know, I've had friends

541
00:28:43,200 --> 00:28:44,920
Speaker 2: that have been doing red light, cold plunging, you know,

542
00:28:44,960 --> 00:28:48,200
Speaker 2: all these things we've used in trathlon for recovery, you know,

543
00:28:48,280 --> 00:28:51,400
Speaker 2: and so forth. But now they're going really mainstream, and

544
00:28:51,440 --> 00:28:53,320
Speaker 2: so that's cool. You know, more and more people have

545
00:28:53,360 --> 00:28:56,360
Speaker 2: access to these awesome tools. But that's kind of just

546
00:28:56,440 --> 00:28:59,360
Speaker 2: the general framework of brain one peptides one is just

547
00:28:59,400 --> 00:29:02,840
Speaker 2: having a essentially a platform for measurement ultimately.

548
00:29:03,160 --> 00:29:06,200
Speaker 3: And well do peptides then I want to come back

549
00:29:06,240 --> 00:29:07,440
Speaker 3: to the to the platform.

550
00:29:07,680 --> 00:29:10,800
Speaker 1: So what what is the what's the status?

551
00:29:10,840 --> 00:29:14,280
Speaker 3: What's the legal status of peptides in the States because

552
00:29:14,840 --> 00:29:17,720
Speaker 3: in Australia, and I think it's pretty similar in the UK,

553
00:29:18,480 --> 00:29:22,200
Speaker 3: and I could go online and I can buy peptides

554
00:29:22,800 --> 00:29:28,040
Speaker 3: for research purposes own, right, I can't a doctor over

555
00:29:28,080 --> 00:29:31,720
Speaker 3: here cannot administer peptides to me because they're they're not

556
00:29:31,800 --> 00:29:36,680
Speaker 3: approved by the TGA. But anecdotally there is a shitload

557
00:29:36,760 --> 00:29:40,200
Speaker 3: of people who are using peptides and it's a bit

558
00:29:40,240 --> 00:29:44,320
Speaker 3: of wild wes, right, because there's no regulation, you don't

559
00:29:44,400 --> 00:29:48,480
Speaker 3: really know like is this is this BPC one five

560
00:29:48,520 --> 00:29:51,440
Speaker 3: seven and I'm buying? Is it actually BPC one five seven?

561
00:29:51,520 --> 00:29:53,840
Speaker 3: Is it quality stuff? Is it not quality stuff?

562
00:29:54,360 --> 00:29:57,520
Speaker 1: So? So what's the what is the landscape in the States,

563
00:29:57,560 --> 00:29:58,720
Speaker 1: Because I know there are.

564
00:29:58,760 --> 00:30:03,320
Speaker 3: Clinics over there so and there's there's doctors who will

565
00:30:03,720 --> 00:30:06,840
Speaker 3: administer them, so it's clearly a bit different over there.

566
00:30:06,880 --> 00:30:10,400
Speaker 3: And I think probably going to be different gain because

567
00:30:10,400 --> 00:30:11,480
Speaker 3: I think JFK is a.

568
00:30:11,400 --> 00:30:14,560
Speaker 1: Big found of peptides, isn't he sore? Where are we

569
00:30:14,600 --> 00:30:16,160
Speaker 1: in terms of the status over there?

570
00:30:16,560 --> 00:30:19,600
Speaker 2: We're in a shift. So when you talk about peptides

571
00:30:19,640 --> 00:30:22,280
Speaker 2: again short chain amino acids, you know, over here you

572
00:30:22,280 --> 00:30:27,320
Speaker 2: have the glps and glps are exploding. I mean it's insane.

573
00:30:28,440 --> 00:30:31,160
Speaker 2: You know the number of humans who are now injecting themselves,

574
00:30:31,160 --> 00:30:34,440
Speaker 2: which I've mixed feelings about. I think there's a time

575
00:30:34,480 --> 00:30:36,520
Speaker 2: and a place for glps. And you know, there's also

576
00:30:36,560 --> 00:30:40,640
Speaker 2: some other areas that the research has shown they're quite efficacious,

577
00:30:40,680 --> 00:30:43,800
Speaker 2: like within women's health PCOS as an example. Actually women

578
00:30:43,920 --> 00:30:46,840
Speaker 2: are on low doos glps. You know, there's some positive

579
00:30:47,480 --> 00:30:51,160
Speaker 2: effects there. But you know, so like they have been,

580
00:30:51,200 --> 00:30:53,800
Speaker 2: I'd say glps have kind of opened the floodgates. So

581
00:30:53,880 --> 00:30:56,520
Speaker 2: now people where again ten years ago, we were doing

582
00:30:56,600 --> 00:31:01,200
Speaker 2: VPC and you know, no one knew GLP one was

583
00:31:01,360 --> 00:31:04,160
Speaker 2: is it? One is? And so now what's happening is

584
00:31:05,080 --> 00:31:08,360
Speaker 2: people are exploring further because they're seeing positive impacts from

585
00:31:08,360 --> 00:31:10,880
Speaker 2: things like glps, and then it's opening, you know, the

586
00:31:10,880 --> 00:31:14,520
Speaker 2: flood gates again of like TV five hundred and BPC

587
00:31:14,880 --> 00:31:18,040
Speaker 2: and the wolverine and you know this. I mean there's

588
00:31:18,360 --> 00:31:20,880
Speaker 2: you know, while there's there's really only about twenty to

589
00:31:20,920 --> 00:31:23,480
Speaker 2: thirty peptides that are like you know, the major players

590
00:31:23,480 --> 00:31:26,000
Speaker 2: in the space, ultimately there's really not that many all

591
00:31:26,040 --> 00:31:28,600
Speaker 2: at all. And so what's happening in the US is

592
00:31:28,640 --> 00:31:32,880
Speaker 2: because of RFK, they're getting reclassified essentially. And I heard

593
00:31:32,920 --> 00:31:37,440
Speaker 2: this week about midweek he will be talking through the

594
00:31:37,480 --> 00:31:40,160
Speaker 2: next five that are going to be reclassified. And if

595
00:31:40,160 --> 00:31:41,480
Speaker 2: I had to guess, it's going to be you know,

596
00:31:41,520 --> 00:31:46,720
Speaker 2: the tv TB five hundred BPC, uh, maybe GHK, you know,

597
00:31:46,800 --> 00:31:50,640
Speaker 2: CEU and so forth. So we're seeing it right now.

598
00:31:50,800 --> 00:31:53,640
Speaker 2: And the good news is that and maybe unlike you

599
00:31:53,680 --> 00:31:57,160
Speaker 2: know in Australia, but you have again these FDA approved

600
00:31:57,240 --> 00:31:58,840
Speaker 2: peptides you can get from your doctor.

601
00:31:59,240 --> 00:32:01,560
Speaker 3: So at least in that is that sorry, is that

602
00:32:01,680 --> 00:32:03,880
Speaker 3: currently you can you can actually.

603
00:32:03,600 --> 00:32:06,640
Speaker 2: Yeah, there's but there's a few you know, of course

604
00:32:06,760 --> 00:32:09,360
Speaker 2: again with like GLP ones, but there's like a handful

605
00:32:09,520 --> 00:32:12,640
Speaker 2: you can get now. And then with this reclassification, you're

606
00:32:12,640 --> 00:32:14,040
Speaker 2: going to be able to get you know, these ones

607
00:32:14,040 --> 00:32:16,760
Speaker 2: that are much more prevalent, like the vpcs and so forth.

608
00:32:16,920 --> 00:32:20,120
Speaker 3: Right, But right now, if somebody wants to in the States,

609
00:32:20,120 --> 00:32:23,880
Speaker 3: if they wanted to get a wolverine stacks, we should

610
00:32:23,880 --> 00:32:25,240
Speaker 3: sort of explain this for people.

611
00:32:25,280 --> 00:32:26,640
Speaker 1: So BPC one.

612
00:32:26,600 --> 00:32:32,040
Speaker 3: Five seven TV five hundred R essentially powerful anti inflammatory

613
00:32:32,040 --> 00:32:35,280
Speaker 3: peptides help wound healing, all of these sorts of things. Right,

614
00:32:35,360 --> 00:32:40,040
Speaker 3: But what so is it similar similar to Australia where

615
00:32:40,080 --> 00:32:41,880
Speaker 3: it's a kind of a gray area where you can

616
00:32:41,920 --> 00:32:45,680
Speaker 3: buy them for research purposes or can you officially go

617
00:32:45,840 --> 00:32:48,320
Speaker 3: to a doctor and get a script now I know

618
00:32:48,360 --> 00:32:51,320
Speaker 3: you can for GPS, but for those other ones?

619
00:32:51,960 --> 00:32:53,360
Speaker 1: Is it a gray area right now?

620
00:32:53,360 --> 00:32:56,440
Speaker 2: It's a gray area right now, it's about to right, Okay,

621
00:32:56,480 --> 00:32:59,960
Speaker 2: So it's quite similar, right, yeah, yeah, it's exactly the same.

622
00:33:00,200 --> 00:33:02,880
Speaker 2: And to your point, you know, further getting them from

623
00:33:02,920 --> 00:33:04,920
Speaker 2: the gray you know, the gray market. You don't know

624
00:33:04,960 --> 00:33:07,320
Speaker 2: where that molecules coming from. You don't know if it's

625
00:33:07,360 --> 00:33:10,480
Speaker 2: been mass spect or run on a mass spectro photometer

626
00:33:10,600 --> 00:33:14,120
Speaker 2: to understand the molecular composition. You don't know the quality,

627
00:33:14,240 --> 00:33:18,520
Speaker 2: if there's contaminants, fungi, you know, biologics. I mean, so

628
00:33:18,600 --> 00:33:20,760
Speaker 2: it's and a lot of these are coming from China

629
00:33:21,280 --> 00:33:24,800
Speaker 2: and most the precursors are absolutely coming from China, So

630
00:33:25,840 --> 00:33:28,400
Speaker 2: you know it's a it is a concern for sure,

631
00:33:28,400 --> 00:33:30,200
Speaker 2: but it's not new. I mean again, having been this

632
00:33:30,680 --> 00:33:33,880
Speaker 2: for many years, it's only gotten i would say exacerbated

633
00:33:33,880 --> 00:33:36,440
Speaker 2: because there's so much more demand. And now we call

634
00:33:36,480 --> 00:33:41,200
Speaker 2: it peptide broification. Uh but uh, you know, like every

635
00:33:41,440 --> 00:33:44,760
Speaker 2: it's like every you know, crypto cannabis bro is now

636
00:33:44,760 --> 00:33:48,800
Speaker 2: going into peptides and it's fairly tough, right, interesting because

637
00:33:48,840 --> 00:33:51,640
Speaker 2: it's such a gold rush. And so you know, back

638
00:33:51,640 --> 00:33:53,560
Speaker 2: to what we do at Brain one Peptides one. We

639
00:33:53,640 --> 00:33:57,120
Speaker 2: provide a framework for people to measure if the peptides work.

640
00:33:57,360 --> 00:33:59,840
Speaker 2: You know, like you can actually see you start taking

641
00:33:59,840 --> 00:34:02,120
Speaker 2: it on a certain day, I'd be considered an intervention.

642
00:34:02,520 --> 00:34:04,400
Speaker 2: You have a baseline of a period of time, it

643
00:34:04,400 --> 00:34:06,880
Speaker 2: could be one week, two weeks depending and then you

644
00:34:07,120 --> 00:34:09,720
Speaker 2: just see, you know, how to your biometrics, biro markers improve.

645
00:34:09,920 --> 00:34:14,640
Speaker 3: Okay, sure, you're people are constantly uploading their data, uploading

646
00:34:14,680 --> 00:34:16,840
Speaker 3: their data from their Apple Watch or whatever it may be,

647
00:34:17,680 --> 00:34:21,439
Speaker 3: getting getting stuff from their doctor, uploading their blood work,

648
00:34:21,719 --> 00:34:24,719
Speaker 3: and you're analyzing all of that in the back end.

649
00:34:24,800 --> 00:34:27,920
Speaker 2: Yeah, correct, Yeah, they just they connect to wearable once

650
00:34:28,280 --> 00:34:30,960
Speaker 2: and then we have different types of scans you can

651
00:34:31,000 --> 00:34:32,600
Speaker 2: do in the app. You can do a voice scan

652
00:34:33,160 --> 00:34:35,560
Speaker 2: and we get fifteen biomarkers from voice.

653
00:34:35,600 --> 00:34:38,319
Speaker 1: We get about four from void from voice from.

654
00:34:38,239 --> 00:34:42,319
Speaker 2: Absolutely absolutely yeah HRV. Honestly I did. We did analysis.

655
00:34:42,320 --> 00:34:45,000
Speaker 2: We saw HRV coming from voice was within five percent

656
00:34:45,040 --> 00:34:45,920
Speaker 2: of what I saw in my.

657
00:34:45,880 --> 00:34:47,560
Speaker 1: Whoop get away.

658
00:34:47,680 --> 00:34:50,640
Speaker 2: Yeah, oh absolutely your voice. You know tension, I mean

659
00:34:50,680 --> 00:34:52,800
Speaker 2: you hear it in someone's voice, you know, in they're tense.

660
00:34:53,160 --> 00:34:54,480
Speaker 2: So even if you just think of it as a

661
00:34:54,480 --> 00:34:59,399
Speaker 2: stress monitor, it's incredible some of the biomarkers that they talk.

662
00:34:59,440 --> 00:35:02,440
Speaker 2: I don't know if I yet, but it's coming, you know. Uh.

663
00:35:02,480 --> 00:35:05,319
Speaker 2: And similar with the face I mean hypertension. HRV have

664
00:35:05,400 --> 00:35:09,080
Speaker 2: also seen it, you know, within within face scans as well.

665
00:35:09,680 --> 00:35:12,520
Speaker 2: So if someone you know, they can they can connect

666
00:35:12,600 --> 00:35:15,680
Speaker 2: their their wearable one time, that's it and then they

667
00:35:15,719 --> 00:35:18,160
Speaker 2: could do these regular you know types of tests and

668
00:35:18,200 --> 00:35:21,520
Speaker 2: then that can also include blood of course, but there's

669
00:35:21,600 --> 00:35:24,279
Speaker 2: challenges with blood as well, you know, relative to when

670
00:35:24,320 --> 00:35:26,719
Speaker 2: you take it, you know, how you take it. You know,

671
00:35:26,840 --> 00:35:30,240
Speaker 2: you get oxidation, you get to naturing of proteins with heat,

672
00:35:30,640 --> 00:35:31,480
Speaker 2: you know, blood.

673
00:35:31,200 --> 00:35:34,920
Speaker 3: Which which lab, which lab has taken it as well,

674
00:35:34,960 --> 00:35:36,200
Speaker 3: because you know, some of.

675
00:35:36,160 --> 00:35:38,480
Speaker 1: The labs are very slightly different.

676
00:35:38,719 --> 00:35:41,360
Speaker 3: I mean to to go back to just just to

677
00:35:41,360 --> 00:35:43,960
Speaker 3: to kind of shine a light on this whole area.

678
00:35:44,120 --> 00:35:47,200
Speaker 3: As you rightly said, like your your blood mark, the

679
00:35:47,239 --> 00:35:50,080
Speaker 3: time that you get it done can be different. Obviously

680
00:35:50,080 --> 00:35:53,920
Speaker 3: everybody knows about fasting versus non fasting, but but that

681
00:35:53,920 --> 00:35:56,720
Speaker 3: that time in your chacidian rhythm, if you're a female,

682
00:35:56,760 --> 00:35:59,239
Speaker 3: where you are in your menstrual cycle, you know you're

683
00:35:59,719 --> 00:36:02,560
Speaker 3: you're sleep last night. They all of these things affected.

684
00:36:02,719 --> 00:36:06,680
Speaker 3: But you know, if we talk about the whole peptide world.

685
00:36:06,760 --> 00:36:09,719
Speaker 3: So JLP's are really interesting, right because they have been

686
00:36:09,760 --> 00:36:13,680
Speaker 3: around for quite some time, right, the early versions of

687
00:36:13,719 --> 00:36:17,600
Speaker 3: the GLP ones were around well over a decade ago.

688
00:36:18,800 --> 00:36:23,080
Speaker 3: But now we are really nih just starting to see

689
00:36:23,360 --> 00:36:26,960
Speaker 3: some of the data come through. And whilst there's very

690
00:36:27,120 --> 00:36:31,200
Speaker 3: very interesting data. Obviously everybody knows around the weight loss,

691
00:36:31,400 --> 00:36:35,040
Speaker 3: but there seems to be early around cardiovascular disease protection,

692
00:36:35,520 --> 00:36:39,279
Speaker 3: potentially something around dementia, some early signals around that.

693
00:36:39,480 --> 00:36:40,800
Speaker 1: But interesting.

694
00:36:40,840 --> 00:36:44,880
Speaker 3: I just read a paper yesterday on people on GLP ones,

695
00:36:45,120 --> 00:36:48,439
Speaker 3: about fifty percent of them have to come off within

696
00:36:48,480 --> 00:36:52,040
Speaker 3: the first year because of the side effects, right, which

697
00:36:52,080 --> 00:36:55,160
Speaker 3: I think they are. The side effects are more prevalent

698
00:36:55,239 --> 00:36:58,640
Speaker 3: than people know. And interesting when you look at the

699
00:36:58,719 --> 00:37:03,800
Speaker 3: biomarkers in a paper, like people were having great bio

700
00:37:03,880 --> 00:37:08,560
Speaker 3: markers when they're on the glps and clear reductions and

701
00:37:08,760 --> 00:37:12,560
Speaker 3: risk factors for a number of different diseases. So looking

702
00:37:12,600 --> 00:37:17,400
Speaker 3: pretty awesome, like liver fat being obliterated, and that's some

703
00:37:17,440 --> 00:37:20,600
Speaker 3: of the stuff on reditory chide and some of the

704
00:37:20,640 --> 00:37:24,479
Speaker 3: stuff around liver fat. But then when people go off

705
00:37:24,600 --> 00:37:30,160
Speaker 3: the golp ones, they put the weight on really really quick,

706
00:37:30,239 --> 00:37:33,960
Speaker 3: like four times as fast as people who've been dieting,

707
00:37:34,760 --> 00:37:38,200
Speaker 3: and all of their markers get.

708
00:37:38,160 --> 00:37:44,040
Speaker 1: Really bad, really really quick. Right, And this is my

709
00:37:44,360 --> 00:37:46,200
Speaker 1: concern with those.

710
00:37:46,480 --> 00:37:49,759
Speaker 3: And then you know, we step into the bigger peptide

711
00:37:49,840 --> 00:37:52,799
Speaker 3: world where you go all those things that we talked

712
00:37:52,800 --> 00:37:55,279
Speaker 3: about before that people are getting on the gray market, Well,

713
00:37:55,920 --> 00:37:58,560
Speaker 3: they haven't had the clinical trials done on them yet.

714
00:37:58,640 --> 00:38:01,160
Speaker 3: And yes, there's lots of onecdotal stuff that you can

715
00:38:01,200 --> 00:38:03,560
Speaker 3: talk to your me. You took PPC and his injury

716
00:38:03,960 --> 00:38:07,319
Speaker 3: got really good, really quick, But again we do not

717
00:38:07,680 --> 00:38:10,440
Speaker 3: know the long term effects yet, right.

718
00:38:11,120 --> 00:38:15,719
Speaker 2: Yeah, truly not I would agree, So, yeah, slightly terrifying

719
00:38:15,760 --> 00:38:21,600
Speaker 2: from from that perspective. Yeah, we where I see a

720
00:38:21,680 --> 00:38:24,560
Speaker 2: market need or just a human need is like the

721
00:38:24,600 --> 00:38:30,719
Speaker 2: concept of microdosing jlps. You know, that's last year. I

722
00:38:30,719 --> 00:38:33,400
Speaker 2: think that makes a lot more sense, depending you know,

723
00:38:33,440 --> 00:38:36,000
Speaker 2: on the on the human and the condition. And then

724
00:38:36,160 --> 00:38:38,719
Speaker 2: just the concept of like tight trading down, you know,

725
00:38:38,840 --> 00:38:41,960
Speaker 2: like how do you go off especially a full jos GLP.

726
00:38:42,200 --> 00:38:44,920
Speaker 2: And then you know, ultimately just to your point going,

727
00:38:45,840 --> 00:38:47,600
Speaker 2: you know, you don't want to go cool turkey on

728
00:38:47,640 --> 00:38:50,320
Speaker 2: these things. So is there a mechanism to tight trade

729
00:38:50,400 --> 00:38:53,400
Speaker 2: you know, essentially down. Finally, like we talked about, you

730
00:38:53,440 --> 00:38:55,759
Speaker 2: know with triathlon training, you're you're tight trading up. You know,

731
00:38:55,800 --> 00:38:59,160
Speaker 2: it's similar. I think there's a sweet spot for people

732
00:38:59,200 --> 00:39:01,399
Speaker 2: that could be very very beneficial, you.

733
00:39:01,360 --> 00:39:03,480
Speaker 1: Know, and oh oh absolutely.

734
00:39:03,560 --> 00:39:06,200
Speaker 3: I mean you look at the research coming out of

735
00:39:06,200 --> 00:39:08,440
Speaker 3: If you're on an antidepressant and you try and go

736
00:39:08,520 --> 00:39:12,200
Speaker 3: cold turkey, Jesus Christ, you're in for a world of

737
00:39:12,320 --> 00:39:15,840
Speaker 3: pee and you've got to really tight trait that dime on.

738
00:39:17,760 --> 00:39:18,720
Speaker 1: Very very slowly.

739
00:39:18,760 --> 00:39:20,520
Speaker 3: And I think I think it's probably the same for

740
00:39:20,640 --> 00:39:24,360
Speaker 3: any drug, right, but particularly the GLPS. I agree and

741
00:39:24,560 --> 00:39:26,480
Speaker 3: Jesus Christ, you've got to be lifting. You've got to

742
00:39:26,520 --> 00:39:28,160
Speaker 3: be doing resistance training when you're on that.

743
00:39:28,200 --> 00:39:31,720
Speaker 2: Well, I was going to say that the muscle loss

744
00:39:31,760 --> 00:39:34,479
Speaker 2: like more than anything. I mean, you know, talk about

745
00:39:34,480 --> 00:39:37,920
Speaker 2: a longevity hack, you know, like it's been tried and true.

746
00:39:38,120 --> 00:39:41,239
Speaker 2: You know, ultimately weights, yeah, you know, into your later

747
00:39:41,280 --> 00:39:43,920
Speaker 2: stages of life, like sixty seventy, keep going. It doesn't

748
00:39:43,920 --> 00:39:46,319
Speaker 2: have to be heavy, but continue doing weights. You know,

749
00:39:46,400 --> 00:39:48,359
Speaker 2: it's like nearly indisputable.

750
00:39:49,160 --> 00:39:52,200
Speaker 3: I actually think, you know, when we look when when

751
00:39:52,239 --> 00:39:56,759
Speaker 3: you look at it, resistance training I think has been

752
00:39:57,080 --> 00:40:00,360
Speaker 3: massively underappreciated over the years. I mean, I've been an

753
00:40:00,360 --> 00:40:06,200
Speaker 3: exercise scientist for thirty years. We've been talking about cardiovascular training,

754
00:40:06,360 --> 00:40:09,920
Speaker 3: and for very good reason, right but I think now

755
00:40:10,360 --> 00:40:15,640
Speaker 3: just seeing the independent and synergistic benefits of resistance training,

756
00:40:15,840 --> 00:40:20,880
Speaker 3: and particularly as we eage as an aging population, I

757
00:40:20,960 --> 00:40:25,719
Speaker 3: actually think that sarcopenia, which is that progressive loss of

758
00:40:25,760 --> 00:40:30,320
Speaker 3: bone and muscle, I actually think it's probably the biggest killer.

759
00:40:30,560 --> 00:40:33,319
Speaker 3: Right now, people go, hold on, what do you mean

760
00:40:33,480 --> 00:40:36,520
Speaker 3: that's ridiculous. Cardiovascular disease is the biggest killer. We're not

761
00:40:36,600 --> 00:40:37,360
Speaker 3: seeing dementia.

762
00:40:37,440 --> 00:40:39,880
Speaker 1: But so if you if.

763
00:40:39,760 --> 00:40:44,960
Speaker 3: You're in your sixties, falls are the seventh biggest killer.

764
00:40:45,280 --> 00:40:48,320
Speaker 3: And the falls generally come because people have lost muscle

765
00:40:48,360 --> 00:40:51,640
Speaker 3: and particularly those fast twitch fibers that you know you're

766
00:40:51,680 --> 00:40:54,879
Speaker 3: reaching out to grab something ere regaining your feet when

767
00:40:54,880 --> 00:40:57,680
Speaker 3: you get into your seventies, falls are the fifth biggest.

768
00:40:57,360 --> 00:40:58,560
Speaker 1: Killer of everybody.

769
00:40:58,680 --> 00:41:03,000
Speaker 3: Right, But if you have low muscle mass, you dramatically

770
00:41:03,000 --> 00:41:06,480
Speaker 3: increase your risk of cardiovascular disease, you dramatically increase your

771
00:41:06,560 --> 00:41:12,200
Speaker 3: risk of dimension your degenerative diseases, and you dramatically increase

772
00:41:12,239 --> 00:41:16,239
Speaker 3: your risk of metabolic diseases like diabetes. So I think

773
00:41:16,239 --> 00:41:19,799
Speaker 3: if we look at not just it on itself, but

774
00:41:19,880 --> 00:41:25,000
Speaker 3: the impact on other things, I actually think low muscle

775
00:41:25,080 --> 00:41:28,040
Speaker 3: mass is one of the biggest killers out there.

776
00:41:28,440 --> 00:41:31,600
Speaker 1: And oh have you got any thinking on that? Yeah?

777
00:41:31,680 --> 00:41:34,319
Speaker 2: No, I mean absolutely. Again, you know, we talk about it.

778
00:41:35,160 --> 00:41:37,520
Speaker 2: A lot of people are interested in these longevity hacks,

779
00:41:37,600 --> 00:41:39,040
Speaker 2: you know, like what can I do? What are the

780
00:41:39,120 --> 00:41:41,560
Speaker 2: quick easy fixes? And so again we really focus on

781
00:41:41,560 --> 00:41:45,600
Speaker 2: the behavioral side. But again, muscle mass is everything, and

782
00:41:45,640 --> 00:41:47,320
Speaker 2: it doesn't you know, you don't have to be ripped,

783
00:41:47,320 --> 00:41:50,520
Speaker 2: but just doing again resistance training any type of weights

784
00:41:50,560 --> 00:41:53,280
Speaker 2: again into your older age like absolutely critical.

785
00:41:53,440 --> 00:41:55,200
Speaker 1: So couldn't agree more.

786
00:41:55,760 --> 00:41:58,960
Speaker 3: And so you talk we need to wind up a

787
00:41:59,000 --> 00:42:03,560
Speaker 3: little bit, but you also talk about behavioral design right,

788
00:42:03,719 --> 00:42:06,560
Speaker 3: which I'm a fan of as well. So so give

789
00:42:06,640 --> 00:42:10,879
Speaker 3: us give our listeners some practical tools that they can

790
00:42:10,920 --> 00:42:16,040
Speaker 3: do around behavioral design to close what what I call

791
00:42:16,120 --> 00:42:18,520
Speaker 3: the knowing doing gap. Are lots of people called it

792
00:42:18,640 --> 00:42:20,279
Speaker 3: right because there's a lot of people listening to this.

793
00:42:20,719 --> 00:42:23,239
Speaker 3: They know what they need to do, but they're not

794
00:42:23,320 --> 00:42:25,640
Speaker 3: quite doing it right. I say, they're waiting for the

795
00:42:25,760 --> 00:42:31,200
Speaker 3: motivation ferry. But what are some little behavioral design hacks

796
00:42:31,280 --> 00:42:33,920
Speaker 3: that that that you have come up with, or that.

797
00:42:33,680 --> 00:42:37,200
Speaker 1: That your system uses people can actually use.

798
00:42:37,600 --> 00:42:40,280
Speaker 2: Yes, so we have thousands of these actually in the system.

799
00:42:40,560 --> 00:42:44,560
Speaker 2: And you know, so for sleep, as an example, you

800
00:42:44,560 --> 00:42:46,880
Speaker 2: want to improve your sleep, well, what can help improve

801
00:42:46,880 --> 00:42:49,399
Speaker 2: your sleep is when you get in the morning, get

802
00:42:49,480 --> 00:42:51,879
Speaker 2: up in the morning. You know your direct sunlight, your

803
00:42:51,920 --> 00:42:56,359
Speaker 2: secedian regulation, and of course cortisol, and you know all

804
00:42:56,400 --> 00:42:58,880
Speaker 2: of these additional stress hormones that actually start in the

805
00:42:58,880 --> 00:43:02,440
Speaker 2: morning but that impact sleep at night. And so you know,

806
00:43:02,520 --> 00:43:05,000
Speaker 2: big fan in the mornings if you can get the

807
00:43:05,040 --> 00:43:07,600
Speaker 2: direct sunlight. I live in a valley here in Colorado.

808
00:43:07,760 --> 00:43:09,879
Speaker 2: So I don't actually get direct sunlight till about nine,

809
00:43:10,520 --> 00:43:13,360
Speaker 2: but as soon as you can do it, it's absolutely

810
00:43:13,400 --> 00:43:16,440
Speaker 2: a beneficial microhabit as we would call it. And you

811
00:43:16,480 --> 00:43:20,000
Speaker 2: can combine that, you know, after breakfast doing a twenty

812
00:43:20,000 --> 00:43:22,279
Speaker 2: minute walk, you know, in the sunshine, and try to

813
00:43:22,280 --> 00:43:24,840
Speaker 2: get you know, both of those things, you know, with hydration,

814
00:43:24,960 --> 00:43:27,120
Speaker 2: which sounds very rudimentary, you know, but people do not

815
00:43:27,200 --> 00:43:30,399
Speaker 2: drink enough water period. Yeah, So you know, those would

816
00:43:30,400 --> 00:43:33,319
Speaker 2: be like three examples of three micro habits. Also, the

817
00:43:33,320 --> 00:43:36,359
Speaker 2: power of connection in community. You know, people who wake

818
00:43:36,440 --> 00:43:39,160
Speaker 2: up in the morning and feel a connection to something.

819
00:43:39,360 --> 00:43:41,280
Speaker 2: You can call it God, you can call it yourself,

820
00:43:41,280 --> 00:43:43,640
Speaker 2: you can call it nature. It doesn't really matter. But

821
00:43:43,760 --> 00:43:47,520
Speaker 2: having that connection that purpose your life expectancy can go up,

822
00:43:47,520 --> 00:43:50,600
Speaker 2: you know, ten plus years just by having that connection.

823
00:43:51,640 --> 00:43:53,919
Speaker 2: An extension that could be community, the people you surround

824
00:43:53,960 --> 00:43:56,360
Speaker 2: yourself with, the things that you do, could be a

825
00:43:56,360 --> 00:43:59,319
Speaker 2: book club, could be you know, bingo. I mean, it

826
00:43:59,360 --> 00:44:02,640
Speaker 2: doesn't really matter as long as you're with people and

827
00:44:02,840 --> 00:44:05,200
Speaker 2: you know, keeping that connection up. So you know, as

828
00:44:05,239 --> 00:44:07,560
Speaker 2: a data scientists and maleculobologist, I'm always looking at the

829
00:44:07,640 --> 00:44:09,759
Speaker 2: data and like trying to see you know, like how

830
00:44:09,760 --> 00:44:12,640
Speaker 2: do we measure this thing? But like community as an example,

831
00:44:12,719 --> 00:44:14,799
Speaker 2: you know, it's it's a very tried and true there's

832
00:44:14,880 --> 00:44:16,920
Speaker 2: enough papers around this. You know, people who have strong

833
00:44:17,000 --> 00:44:20,239
Speaker 2: senses of community live longer. People who are in isolation

834
00:44:20,400 --> 00:44:23,200
Speaker 2: that have things like hearing loss or traumatic brain injury,

835
00:44:23,520 --> 00:44:26,439
Speaker 2: you know, they live shorter lives ultimately. And the good

836
00:44:26,440 --> 00:44:28,080
Speaker 2: news is that again, these are things that we can

837
00:44:28,120 --> 00:44:31,440
Speaker 2: improve once you're cognizant of them and just come up

838
00:44:31,480 --> 00:44:33,880
Speaker 2: with the framework. We call it a protocol. It's literally

839
00:44:33,920 --> 00:44:36,040
Speaker 2: just a routine or a list, you know, and you

840
00:44:36,080 --> 00:44:37,560
Speaker 2: try to do the best you can, and you don't

841
00:44:37,560 --> 00:44:39,799
Speaker 2: beat yourself up, and you start small. You start with

842
00:44:39,920 --> 00:44:42,920
Speaker 2: one or two of these behavioral changes and then they

843
00:44:42,960 --> 00:44:45,000
Speaker 2: grow incrementally. But if you try to do it all

844
00:44:45,040 --> 00:44:47,520
Speaker 2: at once, it's like the people that diet after the

845
00:44:47,560 --> 00:44:51,920
Speaker 2: New Year, you're going to fail. So small micro habits

846
00:44:51,960 --> 00:44:55,000
Speaker 2: that have you know, compounding interest essentially over time.

847
00:44:56,280 --> 00:45:00,560
Speaker 3: And you then are helping people with Brehamong, are helping

848
00:45:00,600 --> 00:45:06,759
Speaker 3: them to measure their progress. And do you suggest or

849
00:45:06,800 --> 00:45:10,279
Speaker 3: does the AI suggest behavioral tweaks that people.

850
00:45:10,040 --> 00:45:13,560
Speaker 2: Can do based that's correct. Yeah, that's when we call

851
00:45:13,600 --> 00:45:16,759
Speaker 2: that adaptive AI. It's that concept. You know. We could

852
00:45:16,800 --> 00:45:19,600
Speaker 2: upload our data right now, Paul, and you know it

853
00:45:19,800 --> 00:45:23,480
Speaker 2: give us a blueprint, and then we can upload our biometrics.

854
00:45:23,840 --> 00:45:26,160
Speaker 2: We could have biomarkers, and that would be a snapshot

855
00:45:26,160 --> 00:45:28,200
Speaker 2: at this moment in time. But it changes, you know,

856
00:45:28,239 --> 00:45:30,560
Speaker 2: your biology changes. I mean that's the thing with blood.

857
00:45:30,600 --> 00:45:32,760
Speaker 2: You know, you can fast, but at the day before

858
00:45:33,280 --> 00:45:35,680
Speaker 2: you have a high carbohydrate or a high protein you

859
00:45:35,680 --> 00:45:38,080
Speaker 2: know day you know that might impact your blood work.

860
00:45:38,239 --> 00:45:40,799
Speaker 2: So we really look at things, you know, similar to

861
00:45:40,840 --> 00:45:43,400
Speaker 2: the whole HRV conversation. You know, it's really important to

862
00:45:43,400 --> 00:45:45,719
Speaker 2: look at the trends over time, and that's what we

863
00:45:45,800 --> 00:45:46,520
Speaker 2: help provide.

864
00:45:47,080 --> 00:45:50,400
Speaker 3: Yeah, and I think this species is really starting to

865
00:45:50,440 --> 00:45:54,200
Speaker 3: get quite interesting. I mean, you take somebody who's wearing

866
00:45:54,200 --> 00:45:58,399
Speaker 3: a continuous glucose monitor, right, and that if you can

867
00:45:58,560 --> 00:45:59,799
Speaker 3: feed that data up.

868
00:46:00,000 --> 00:46:03,200
Speaker 1: I mean, I have here right here is a continuous

869
00:46:03,280 --> 00:46:06,040
Speaker 1: key tone monitor which is just being.

870
00:46:05,920 --> 00:46:10,360
Speaker 3: Released, right, and I know that there are some early

871
00:46:10,520 --> 00:46:15,799
Speaker 3: research versions of a continuous cortisol monitor, right, which for

872
00:46:15,840 --> 00:46:18,319
Speaker 3: me is a bit of a game changer. Right, if

873
00:46:18,360 --> 00:46:24,520
Speaker 3: you are just constantly measuring these things, and particularly your

874
00:46:24,520 --> 00:46:28,760
Speaker 3: glucose in your cortisol right like and getting that real

875
00:46:28,920 --> 00:46:32,920
Speaker 3: time information like geeze, that upens up a whole new world.

876
00:46:33,080 --> 00:46:36,439
Speaker 3: And I think, you know, we're probably twenty years away

877
00:46:36,480 --> 00:46:40,719
Speaker 3: from people having a chip inserted under their skin that

878
00:46:40,920 --> 00:46:46,160
Speaker 3: is just uploading all of this data into AI, that

879
00:46:46,400 --> 00:46:50,320
Speaker 3: is just you know, just making decisions or tweaks on

880
00:46:50,360 --> 00:46:52,239
Speaker 3: the fly. And this whole idea of a digital twin.

881
00:46:53,080 --> 00:46:55,359
Speaker 3: How far away do you think we are from that?

882
00:46:55,520 --> 00:46:56,239
Speaker 1: In reality?

883
00:46:56,600 --> 00:46:58,920
Speaker 2: I think we're pretty close because again we're seeing it

884
00:46:59,000 --> 00:47:01,600
Speaker 2: right now. I mean I mentioned doctor Galen book Walter earlier.

885
00:47:01,640 --> 00:47:03,640
Speaker 2: You know, he has six of these chips literally on

886
00:47:03,719 --> 00:47:07,000
Speaker 2: his brain on his neural tissue, five in the neo,

887
00:47:07,080 --> 00:47:10,760
Speaker 2: one in the prefrontal. It's right now. So to upload

888
00:47:10,800 --> 00:47:13,440
Speaker 2: information that is different. You know. You can't like you know,

889
00:47:13,600 --> 00:47:16,520
Speaker 2: upload or download jiu jitsu and no jiu jitsu yet,

890
00:47:16,560 --> 00:47:19,920
Speaker 2: you know, like in the matrix. But but the ability

891
00:47:19,960 --> 00:47:23,520
Speaker 2: to measure first, you know, we've made massive progressions there

892
00:47:23,560 --> 00:47:26,800
Speaker 2: down to the single neuron basis, and in the future

893
00:47:26,840 --> 00:47:28,719
Speaker 2: there could be a two way communication for that. So

894
00:47:29,960 --> 00:47:31,880
Speaker 2: it's it's all happening quite quickly.

895
00:47:32,400 --> 00:47:35,200
Speaker 3: It's a it's a very interesting space and the word

896
00:47:35,239 --> 00:47:39,040
Speaker 3: that our kids inhabit is going to be very very interesting. Date,

897
00:47:40,239 --> 00:47:43,479
Speaker 3: So where can people go to find out more about you,

898
00:47:43,520 --> 00:47:44,879
Speaker 3: to find out about.

899
00:47:44,600 --> 00:47:49,360
Speaker 1: Brian one and and these? Brian one available.

900
00:47:48,800 --> 00:47:52,040
Speaker 3: For individuals yet and if not yet, what are you

901
00:47:52,239 --> 00:47:53,000
Speaker 3: planning it?

902
00:47:53,000 --> 00:47:55,879
Speaker 2: It will be this summer, so we'll be opening it up.

903
00:47:55,920 --> 00:48:00,480
Speaker 2: Our goal is to give away a million dementia prevention calls,

904
00:48:01,160 --> 00:48:04,359
Speaker 2: so it'll be completely open. We'll make sure you and

905
00:48:04,400 --> 00:48:08,919
Speaker 2: your listeners are aware. And yeah, right now we're working

906
00:48:08,960 --> 00:48:13,240
Speaker 2: primarily with primarily with longevity clinics, concierge doctors and pepti

907
00:48:13,320 --> 00:48:16,759
Speaker 2: companies and so forth. But later the summer.

908
00:48:16,960 --> 00:48:17,560
Speaker 1: Okay, cool?

909
00:48:17,600 --> 00:48:21,040
Speaker 3: And where can people go to register find out more

910
00:48:21,080 --> 00:48:21,680
Speaker 3: about things?

911
00:48:21,680 --> 00:48:23,000
Speaker 1: Where do we send them?

912
00:48:23,080 --> 00:48:28,000
Speaker 2: So it's brain dot one uh and also peptides dot

913
00:48:28,040 --> 00:48:31,520
Speaker 2: o any one. Yeah, they can find us there and

914
00:48:31,880 --> 00:48:34,239
Speaker 2: happily mentioned your name and we'll put them to the

915
00:48:34,239 --> 00:48:34,879
Speaker 2: front of the list.

916
00:48:35,680 --> 00:48:39,560
Speaker 3: Awesome, great stuff, darnth many thanks and go and enjoy

917
00:48:39,560 --> 00:48:41,000
Speaker 3: your day in Colorado.

918
00:48:41,560 --> 00:48:44,360
Speaker 2: Thank you into nature. Such cheers.

919
00:48:44,680 --> 00:48:45,120
Speaker 1: Good month.