- The Huberman Lab Podcast is hosting its first Journal Club episode with Dr. Peter Atiyah.
- A journal club is a practice where students discuss and critique scientific papers.
- Dr. Atiyah will discuss a paper on metformin and its potential role in longevity.
- Dr. Huberman will present a paper on the placebo effect, specifically related to nicotine.
- The episode aims to inform listeners about the discussed papers and how scientists and clinicians analyze research.
- The podcast is separate from Stanford University and aims to provide free science-related information to the public.
- The podcast is sponsored by Helix Sleep and Levels, offering mattress customization and real-time feedback on health, respectively.
- Dr. Atiyah and Dr. Huberman are excited to share their findings and help listeners develop critical thinking skills.

- The speaker discusses their experience with drinking yerba mate and its health benefits
- They talk about a transformative dream they had and the preparation involved
- The speaker then introduces a paper titled "Reassessing the Evidence of a Survival Advantage in Type 2 Diabetics Treated with Metformin Compared with Controls Without Diabetes, a Retrospective Cohort Study"
- They explain the importance of the paper and provide information about metformin and its mechanism of action
- The speaker clarifies the role of metformin in reducing hepatic glucose output in type 2 diabetes
- They provide a simplified explanation of the biochemistry of energy production and metformin's effect on glucose metabolism
- The speaker briefly mentions the failed product Olestero and its side effects.

- Insulin resistance in the muscles is the primary insult in type 2 diabetes.
- Insulin binds to the insulin receptor on muscle cells, triggering a chemical reaction that allows glucose to enter the cell.
- Insulin resistance occurs when intramuscular fat increases, requiring more insulin to trigger glucose transport into the cell.
- Insulin resistance is marked by an increase in insulin levels, not glucose levels.
- Type 2 diabetes progresses to a point where the body becomes resistant to insulin and glucose levels become elevated.
- Accumulation of fat in the muscle, liver, and pancreas exacerbates insulin resistance.
- Metformin is a first-line drug for type 2 diabetes that addresses glucose disposal and hepatic glucose output.
- Other drugs for type 2 diabetes aim to increase insulin production or sensitivity.
- Inactivity, sleep deprivation, hypercortisolemia, and energy imbalance can contribute to insulin resistance.
- Geroprotective agents like metformin target the hallmarks of aging to protect against age-related diseases.

- The study examined the effects of metformin on patients with type 2 diabetes
- It used a registry to match patients on metformin with controls
- Informative censoring was used to exclude certain patients from the study
- The study found a 15% reduction in all-cause mortality in the metformin group
- The results suggest that metformin may have benefits beyond lowering blood glucose levels
- The study has been considered the best evidence for the benefits of metformin

- Keyes and colleagues are redoing the banister analysis due to the high interest in the topic and the upcoming TAME trial.
- They used a larger sample of half a million people from a Danish health registry.
- They created two groups to study: one with people with and without diabetes and another with discordant twins.
- The medication list was not matched between the groups, which is a limitation of the study.
- The study looked at crude mortality rates per thousand person years.
- Adjusting for age, the crude death rate for those on metformin was almost identical between the non-twin and twin groups.

- The study compares death rates between people with diabetes and those without
- The death rate is higher in people with diabetes, even after age adjustment
- The study uses Kaplan-Meier curves to show mortality rates over time
- The curves show that people with diabetes taking metformin have a higher death rate compared to controls
- The shaded areas represent 95% confidence intervals
- Overlapping confidence intervals would indicate no significant difference
- Statistical power is important for determining sample size and detecting significant differences
- Increasing sample size reduces variability in the data set.

- Increasing sample size decreases variation in measurements
- Epidemiological studies rely on large sample sizes to compensate for biases and limitations
- Randomized prospective experiments are expensive and have limitations
- The hazard ratio is a measure of relative risk in studies
- Metformin use in diabetes patients may increase the risk of death
- Adjustments for medications, education, and marital status did not significantly change the results
- Censoring data did not undo the benefits seen in previous studies
- The study suggests that metformin may not fully offset the disadvantages of diabetes

- The Huberman Lab Podcast is hosting a Journal Club episode with Dr. Peter Atiyah.
- Dr. Atiyah will discuss a paper on metformin and its potential role in longevity.
- Dr. Huberman will present a paper on the placebo effect, specifically related to nicotine.
- The episode aims to inform listeners about the discussed papers and how scientists and clinicians analyze research.
- The podcast is separate from Stanford University and provides free science-related information to the public.
- The podcast is sponsored by Helix Sleep and Levels.
- Dr. Atiyah and Dr. Huberman are excited to share their findings and help listeners develop critical thinking skills.
- The speaker discusses their experience with drinking yerba mate and its health benefits.
- They introduce a paper on the effects of metformin on patients with type 2 diabetes.
- Metformin is a first-line drug for type 2 diabetes that addresses glucose disposal and hepatic glucose output.
- The study found a 15% reduction in all-cause mortality in the metformin group.
- Keyes and colleagues are redoing the analysis due to high interest and the upcoming TAME trial.
- The study compared death rates between people with diabetes taking metformin and controls.
- The study suggests that metformin may not fully offset the disadvantages of diabetes.

- The speaker discusses the difficulty of determining the contribution of metformin to health outcomes in sick individuals on multiple medications.
- They mention the challenge of isolating the effects of metformin from other medications and variables.
- The speaker highlights the limitations of epidemiological studies in controlling for all variables and intangible differences.
- They compare the findings of a study on metformin to a previous study on meat consumption.
- The speaker mentions the lack of randomized control trials for metformin and discusses the success of other drugs in animal studies.
- They explain why they stopped taking metformin due to high lactate levels and weak mitochondrial function.
- The speaker briefly discusses their use of berberine as a substitute for metformin.

- Berberine, a supplement similar to metformin, helped buffer blood glucose and reduce feelings of sickness after consuming high-calorie foods
- Berberine caused headaches if not followed by a significant amount of carbohydrates
- Carbose is another glucose disposal agent that prevents glucose absorption and has shown potential health benefits in studies
- Lowering blood glucose may have potential benefits for conditions like dementia
- Regular exercise is the best way to maintain blood glucose levels, but glucose disposal agents can be used as tools
- SGLT2 inhibitors are a class of drugs that have shown promise in managing blood glucose levels and have potential benefits for non-diabetics
- Caloric restriction may not offer a significant survival advantage for humans and is not a practical approach for most people
- Energy balance and overall nutrition may play a greater role in glucose homeostasis than specific macronutrients
- Metformin may have benefits for insulin-resistant individuals, but may not be as effective for insulin-sensitive individuals who exercise regularly
- Short periods of caloric restriction may not have significant longevity benefits, and longer durations may be necessary for any potential benefits

- The speaker discusses the duration and benefits of fasting, mentioning that they used to do 7 days of water-only fasting per quarter.
- They highlight the potential downside of fasting, which is muscle mass loss.
- The speaker emphasizes the lack of biomarkers for measuring the effects of interventions like fasting, which hinders research progress.
- They suggest that more research funding should be allocated to developing biomarkers for aging.
- The speaker shares their approach to reading scientific papers, which involves asking four key questions: the general and specific question being asked, the approach used, the findings, and the conclusion.
- They mention the importance of looking up unfamiliar terms and acronyms when reading papers.
- The speaker discusses the format of papers and the inclusion of supplemental information.
- They express excitement about a particular experimental paper that they discuss, but note that it is not yet published and may undergo changes.

- The paper discusses how our beliefs about drugs can impact their effects on us at a biological level
- Belief effects are different from placebo effects and can shift psychology and physiology
- Examples of belief effects include how stress affects performance and how beliefs about food can impact hunger levels
- The study focuses on belief effects of nicotine, which is known to improve cognitive performance
- Nicotine enhances signal-to-noise ratio in the brain, increases dopamine release, and improves attention and focus

- Stimulant drugs can enhance the function of the ventromedial prefrontal cortex circuit in children with ADD and ADHD
- Other methods, such as nutrition and playtime, can also help improve symptoms without drugs
- Nicotine can enhance focus in the brain and provide muscle relaxation in the body
- A study used fMRI to measure brain activity in smokers who vaped different doses of nicotine
- Participants were unaware that they all received the same low amount of nicotine
- Subjective feelings matched what participants were told about the nicotine dose
- Activation of the thalamus and other regions involved in attention were observed during a task
- The study provides insights into the impact of nicotine on brain function.

- The study examined how beliefs about nicotine strength affect brain activation and performance on a task.
- Activation in attention-related areas of the brain scaled with the perceived nicotine strength.
- The belief effect changed the way the brain responded to nicotine.
- The connection between the thalamus and ventral medial prefrontal cortex showed a dose-dependent response based on belief.
- The study is the first to look at dose dependence of belief effects.
- The study did not include a control group with no nicotine.
- The study found that beliefs about nicotine strength did not modulate the reward response in the brain.
- The sample size of the study was relatively small.
- The findings suggest that beliefs about nicotine strength can impact physiological responses to nicotine.

- Difficulty of determining metformin's contribution to health outcomes in sick individuals on multiple medications
- Challenge of isolating metformin's effects from other medications and variables
- Limitations of epidemiological studies in controlling for all variables
- Comparison of metformin study to previous meat consumption study
- Lack of randomized control trials for metformin and success of other drugs in animal studies
- Speaker's personal experience with metformin and use of berberine as a substitute
- Benefits and drawbacks of berberine and carbose as glucose disposal agents
- Potential benefits of lowering blood glucose for conditions like dementia
- Importance of exercise in maintaining blood glucose levels
- Potential benefits of SGLT2 inhibitors for managing blood glucose levels
- Lack of significant survival advantage with caloric restriction
- Role of energy balance and overall nutrition in glucose homeostasis
- Effectiveness of metformin for insulin-resistant individuals but not insulin-sensitive individuals who exercise regularly
- Potential benefits of fasting and downside of muscle mass loss
- Need for biomarkers to measure effects of interventions like fasting
- Importance of asking key questions when reading scientific papers
- Impact of beliefs on drug effects at a biological level
- Examples of belief effects on stress, food, and nicotine
- Nicotine's effects on cognitive performance and brain function
- Study on belief effects of nicotine and its impact on brain activation and performance on a task
- Dose dependence of belief effects on brain activation and connection between thalamus and ventral medial prefrontal cortex
- Lack of control group and small sample size in the study
- Impact of beliefs about nicotine strength on physiological responses to nicotine.

- The belief in the amount of nicotine consumed can impact the reward pathways in the brain
- The study was conducted on smokers, who were constantly coughing during the fMRI scans
- Naive individuals may be more susceptible to the belief system regarding the effects of nicotine
- The experiment has implications for drugs, behavioral interventions, vaccines, and psychoactive drugs
- Beliefs about the effects of a drug can impact the brain's reaction to it
- GLP-1 agonists may have a central impact on appetite reduction, but belief is necessary for it to be effective
- Belief effects can also impact the perception of side effects and the effectiveness of a drug
- Medical students may develop symptoms of the diseases they learn about, leading to a warped sense of prevalence
- The study highlights the importance of belief in the effects of drugs and medical conditions.

- The speaker enjoys learning from the person across the table
- They plan to meet again in Austin
- The speaker asks the audience to subscribe to their YouTube channel and podcast on Spotify and Apple
- They mention the sponsors of the podcast
- They discuss the benefits of supplements and mention their partnership with Momentus Supplements
- They promote their Neural Network newsletter and social media accounts
- They thank the audience for their interest in science.

- Belief in the amount of nicotine consumed affects reward pathways in the brain
- Study conducted on smokers experiencing coughing during fMRI scans
- Naive individuals more susceptible to belief system about nicotine effects
- Experiment has implications for drugs, interventions, vaccines, and psychoactive drugs
- Beliefs about drug effects impact brain's reaction
- GLP-1 agonists for appetite reduction require belief for effectiveness
- Belief affects perception of side effects and drug effectiveness
- Medical students may develop symptoms of diseases they learn about
- Importance of belief in drug effects and medical conditions highlighted
- Speaker enjoys learning from person across table
- Plan to meet again in Austin
- Audience asked to subscribe to YouTube channel and podcast on Spotify and Apple
- Sponsors of podcast mentioned
- Benefits of supplements discussed, partnership with Momentus Supplements mentioned
- Promotion of Neural Network newsletter and social media accounts
- Audience thanked for interest in science.

In this journal club episode, my guest is Stanford and Johns Hopkins-trained physician, Dr. Peter Attia, M.D., who is also the host of The Drive podcast and the author of the bestselling book "Outlive: The Science & Art of Longevity."
We each present a scientific paper and discuss the findings' strengths, weaknesses and actionable takeaways.
First, we discuss an article that addresses whether taking the drug metformin can enhance longevity. Then, we discuss an article on belief effects (similar to placebo effects), showing how the effects of a drug on the brain and cognition depend on one's belief about the dose of the drug taken, not the actual dose.
Our conversation also highlights how to read, interpret and critique scientific studies. This episode ought to be of interest to those curious about health and longevity, medicine and psychology and for anyone seeking to better understand how to read and digest scientific findings.
For the full show notes, including articles, books, and other resources, visit hubermanlab.com.
Thank you to our sponsors
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Timestamps
00:00:00 Dr. Peter Attia, Journal Club
00:03:27 Sponsors: Helix Sleep & Levels
00:06:11 Dreams
00:12:36 Article #1, Metformin, Mitochondria, Blood Glucose
00:19:47 Type 2 Diabetes & Causes, Insulin Resistance
00:25:30 Type 2 Diabetes Medications, Metformin, Geroprotection, Bannister Study
00:36:19 Sponsor: AG1
00:37:15 TAME Trial; Demographics, Twin Cohort
00:44:27 Metformin & Mortality Rate
00:51:28 Kaplan-Meier Mortality Curve, Error Bars & Significance, Statistical Power
01:01:17 Sponsor: InsideTracker
01:02:23 Hazard Ratios, Censoring
01:09:00 Metformin Advantage?, Variables, Interventions Testing Program
01:16:02 Berberine, Acarbose, SGLT2 Inhibitors
01:23:48 Blood Glucose & Energy Balance; Caloric Restriction, Aging Biomarkers
01:32:22 Tool: Reading Journal Articles, 4 Questions, Supplemental Information
01:38:10 Article #2, Belief Effects vs. Placebo Effect
01:45:22 Nicotine Effects
01:51:07 Nicotine Doses & Belief Effects, fMRI Scan
02:00:07 Biological Effects, Dose-Dependent Response & Belief Effects
02:05:14 Biology & Beliefs, Significance, Dopamine Response, Non-Smokers
02:10:57 Dose-Dependence & Beliefs, Side Effects, Nocebo Effect
02:19:06 Zero-Cost Support, YouTube Feedback, Spotify & Apple Reviews, Sponsors, Momentous, Neural Network Newsletter, Social Media
Title Card Photo Credit: Mike Blabac
Disclaimer

A study from the UK Biobank or from half a million Danish citizens, like for instance in this study, those are enormous sample sizes.

So even though this is not an experimental study, it's an epidemiological observational study, there's tremendous power by way of the enormous number of subjects in this study.

And that's the way that epidemiology will make up for its deficit.

So you could never do a randomized assignment study on half a million people.

So epidemiology makes up for its biggest limitation, which is it can never compensate for inherent biases by saying we can do infinite duration if we want.

We could survey people over the course of their lives, and we can have the biggest sample size possible.

The cost of actually doing an experiment where you have tens of thousands of people is prohibitive.

If you look at the Women's Health Initiative, which was a five-year study on, I don't know, what was it, 50, 000 women.

So this is the balancing act between epidemiology and randomized prospective experiments.

And so they both offer something, but You just have to know the blind spots of each 1.

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I mean, I think, let's just go to table 4, which I think is the most important table in here, which now lays out the final results in terms of the hazard ratio.

So this is the way we want to really be thinking about this.

So again, hazard ratios, these are important things to understand.

And you always subtract 1 from the hazard ratio.

And that tells you, if it's a positive number, if it's a number, sorry, if it's a number greater than 1, you subtract 1, and that tells you the relative harm.

So if the hazard ratio is 1.5, you subtract 1.5 is a 50% increase in risk.

If the number is negative, you may recall, on the Bannister paper, the hazard ratio was

So that means it's a 15% reduction in relative risk.

And here, you can see all the hazard ratios are positive.

So what it's telling you here is and I'm gonna walk through this because it's there's a lot of information packed here You've got singletons.

They're showing you 3 different ways that they do it They do an unadjusted model if you just look at the singletons with and without metformin and you make no adjustments, the hazard ratio is 1.48, meaning that people on metformin had a 48% greater chance of dying in any given year than their non-diabetic counterpart.

The only reason I'm smiling, it's not because I enjoy people dying, quite to the contrary, is that this is novel for me.

And I've read some epidemiological studies before, but it's not normally where I spend the majority of my time.

But up until now, I was thinking, okay, people taking metformin are dying more than those that aren't.

I just, and I, I'm just relieved to know that I wasn't looking at all this backwards.

So they're dying more, but of course we don't have a group that's taking metformin who doesn't have diabetes and we don't have a group who has diabetes and you know, is taking metformin plus something else.

So again, we're, we're only dealing with these constrained.

Now there's other arm to this study that I'm not getting into cause it adds more complexity, which is they also have another group that's got diabetes, takes metformin and takes sulfonylureas, which is a bigger drug.

So which, again, speaks to the point, right?

The more you need these medications, They're never able to erase the effect of diabetes

But in this case, it seems that they might be accelerating Possibly accelerating death due to diabetes possibly

we could never know that from this because we don't see We would need to see diabetics who don't take metformin who take nothing and I would bet that they would do even worse So my intuition is that the metformin is helping but not helping Nearly as much as we thought before so my point is they make another set of adjustments They say okay.

Well look in the first 1 in the unadjusted model.

What if we adjust for the medications they're on, the cardiovascular, psychiatric, pulmonary, dementia, meds, and marital status?

I don't know why they threw marital status in there, but they did.

Maybe being married or unmarried can accelerate.

I'm sure it can, but it just seems like a random thing to throw in with all their meds.

I would have personally done that adjustment higher up.

But nevertheless, if you do that, all of a sudden the hazard ratio drops from 1.48 to 1.32, which means, yep, you still have a 32% greater chance of dying in any given year.

All right, what if we also adjust for the highest level of education along with any of the other covariates.

Well, that doesn't really change it at all.

It ends up at 1.33 or a 33% chance increase in death.

I always knew that more school wasn't going to save

If you do the twin study, which you could argue is a slightly purer study because you at least have 1 genetic and environmental thing that you've attached.

These are Twins who in theory are the same in every way except 1 has diabetes and 1 doesn't and the 1 with diabetes on metformin still has 115 percent greater chance of dying than the non-diabetic co-twin When you make that first adjustment of all the meds and marital status you bring it down to a 70% increase in risk.

And when you throw education in, it goes up to an 80% chance of risk.

Now they did this really cool thing, which was they did the analysis on with and without censoring.

So everything I just said here was based on no censoring.

Censoring is when you stop counting the metformin people who have died.

So in the singleton group, when you unadjust it, and the reason I'm doing the unadjusted is that's where they did the sensitivity analysis I don't think it really matters that much.

It's you just have to draw a line in the sand somewhere you'll recall that that was a 48 percent chance of Increased mortality all-cause mortality if you stop counting if you if you pardon me if you don't censor Meaning if you include everybody including when people on metformin with diabetes die.

In other words, this is a very important finding, it did not undo the benefits that we saw in the Bannister study.

Bannister saw a 15 percent reduction in mortality when they censored.

When Keys censored, it got better, but not that much better.

In the twins, it went from 115 percent down to only 97 percent.

So in some ways, this presents a little bit of an enigma because it's not entirely clear to me having read these papers many times exactly why Bannister found such an outlined it like such a different response there's another risk there's another technical detail of this paper Which is they you can see on the right side of table 4.

They did something called a nested case control But you'll see and I was going to go into a long explanation of what nested case controls are.

It's another pretty elegant way to do case control studies where you sample by year and you sort of normalize, you don't count all the cases at the end, you count them 1 by 1.

I don't think it's worth getting into, Andrew, because it doesn't change the answer.

You can see it changes it just slightly, but it doesn't change the point.

The point here is the Keys paper Makes it undeniably clear that in that population there was no advantage Offered by metformin that undid the disadvantage of having type 2 diabetes This does not mean that metformin wasn't helping them because we don't know what these people would have been like without metformin.

It could be that this bought them a 50% reduction in relative mortality to where they'd been.

But what it says is, in a way, this is what you would have expected.

This is what you would have expected 10 years ago before the Bannister paper came out.

Or maybe even before metformin was used, because in some ways it's saying, what is the likelihood that sick people who are on a lot of medication are going to die compared to not sick people who aren't on a lot of medication.

It's not quite that simple in the sense that, as you said, there are ways to try and isolate the metformin contribution somewhat because they're on a bunch of other meds.

And presumably that was done and analyzed in other figures where they can sort of try and They can never attach the results specifically to metformin, right?

But there must be some way of weighting the Percentage that are on psychiatric meds or not on psychiatric meds as some way to tease out whether or not there's actually some contribution in metformin to this result?

Well, that's what they're doing in the partial adjustment is they're actually doing their best to say.

High blood pressure, non-high blood pressure, smoking, non-smoking, et cetera.

the way they would do that, presumably, is by saying, okay, married, not married.

So no, no differences jumping out that can be purely explained by these other variables.

Although again, this is a, this is a great opportunity to talk about why no matter how slick you are, no matter how slick your model is, you can't control for everything.

There's a reason that to my knowledge, virtually every study that compares meat eaters to non-meat eaters finds an advantage amongst the non-meat eaters.

Yes, and we can or disease, you know incidence studies and Yeah, it might be tempting to say well therefore eating meat is bad Until you realize that it takes a lot of work to not eat meat That's a very very significant decision that a person for most people that's a very significant decision a person makes.

And for a person to make that decision, they probably have a very high conviction about the benefit of that to their health.

And it is probably the case that they're making other changes with respect to their health as well that are a little more difficult to measure.

Now there's a million other problems with that.

I picked a silly example because the whole meat discussion then gets into, well, you know, when we say eating meat, what do we mean?

that mean- You're not talking about it as like deli meat versus grass fed.

Or a deer that you hunted with your ball.

But my point is, it's very difficult to quantify some of the intangible differences.

And I think that even a study that goes to great lengths, as this 1 does epidemiologically to make these corrections, can never make the corrections.

And so for me, the big takeaway of this study is 1, this makes much more sense to me than the banister paper, which never really made sense to me.

And again, I was first critical of the banister paper in 2018, about 4 years after it came out.

That's about the time I stopped taking metformin, by the way.

I stopped taking it for a different reason, which we can talk about in a sec.

But that was the first time I went back and said, wait a minute, this information, this informative censoring thing is, that's a little fishy.

And I think we weren't looking at a true group of real type 2 diabetics.

In other words, maybe, and even the Keys paper doesn't tell us that metformin wouldn't be beneficial, because it could be that those people, if they were on nothing, as their matched cohorts were on nothing would have been dying at you know a hazard ratio of 3 and this brought it down to 1.5 in which case you would say there is some Jiro protection there.

It is putting the brakes on this process All of this is to say absent a randomized control trial.

Has there been a randomized control trial

not a lot of knowledge Not when it comes to a hard outcome.

So the Interventions testing program, which is kind of the gold standard for animal studies, which is run out of 3 labs.

So it's an NIH-funded program that's run out of 3 labs.

They basically test molecules for geroprotection.

The ITP was the first study that really put rapamycin on the map in 2009.

That was the study that's fortuitously demonstrated that even when rapamycin was given very, very late in life, it was given to 60-month-old mice, it still afforded them a

I mean, it's hard to, I mean, you can't really control with rapamycin.

But when the ITP studied metformin, it did not succeed.

So the, There have not been that many drugs that have worked in the ITP.

It is done concurrently in 3 labs with very large sample sizing.

And so When something works in the ITP, it's pretty exciting.

Rapamycin has been studied several times.

Another 1 we should talk about it in subsequent time is 17-alpha estradiol.

This continues to work in male mice, and it produces comparable effects to rapamycin.

So this is 17-alpha estradiol, not beta estradiol, which is the estradiol that is bioavailable in all

And just as a brief aside, I think you and I basically agree that unless it's a problem, males, we're talking post-puberty, should try and have their estrogen as high as possible without having negative symptomology because of the importance of estrogen for libido, for brain function, tissue, health, bone health.

This idea of crushing estrogen and raising testosterone is just silly, right?

There's not, let's just leave raising testosterone out of it, but many of the approaches to raising testosterone that are pharmacologic in nature also raise estrogen.

A lot of people try and push down on estrogen.

And that is just, again, unless people are getting hyper estrogenic effects like gynecomastia or other issues, is the exact wrong direction to go.

Estrogen is a very important hormone for men and women.

Canagaflozin, an SGLT2 inhibitor, also very successful in the ITP.

But again, interestingly, rapamyc, metformin not.

And the reason I stopped and this will be the last thing before we move on.

Well, because you couldn't go to the Dairy Queen at the buffet.

No, finally, the nausea went away after a few weeks or a month maybe.

But once I got really into lactate testing, I noticed how high my lactate was at rest.

So a resting fasted lactate should be in a healthy person should be below 1 like somewhere between 0.3 0.6 millimole and Only when you start to exercise should lactate go up and in 2018 was when I started Blood testing for my zone 2.

So previously when I was doing zone 2 testing I was just going off my power meter and heart rate But this is when this is after I met in you go San Milan and I started like wanting to use the lactate threshold of 2 millimole as my as my determinant of where to put my wattage on the bike.

And I'm like doing finger pricks before I start, and I'm like 1.6 millimole.

is if you ran a flight of stairs up the back of the Empire State Building.

Well, no, that would put me a lot higher, right?

No, but that's when I started doing a little digging and realized, oh, you know what?

You're gonna shunt more glucose into pyruvate and more pyruvate into lactate.

And then my zone 2 numbers just seemed off.

Because maybe now I'll just briefly describe.

I, during the period of maybe somewhere in the 2012 to 2015 stretch, I don't recall.

So I, I was and I still am a big fan of Tim Ferriss's slow carbohydrate diet.

Because I like to eat meat and vegetables and starches, I'm an omnivore.

And I found that it worked very quickly, got me very lean, I could exercise, I could think, I could sleep.

You know, A lot of my rationale for following 1 eating regimen or another, what I eat is to enjoy myself, but also have mental energy.

Because if I can't sleep at night, I'm not going to replenish.

don't replenish, I'm going to feel like garbage.

So I found the slow carb diet to be, which was in the 4 hour body, to be a very good plan for me.

You don't drink calories, except after a resistance training session, etc.

But 1 day a week, you have this so-called cheat day.

And so I would eat, you know, 8 croissants and then I'd alternate to sweet stuff and then I'd go to a piece.

And by the end of the day, you don't wanna look at an item of food at all.

So the only modification I made to the slow carb diet for our body thing was the day after the cheat day, I wouldn't eat, I would just fast.

And I had no problem doing that because it was just basically, well, since you said, what was it, anal?

Yeah, anal seepage, I did not have that, but since you said that, I won't up the ante here, but I'll at least match your anal seepage comment by saying I had, let's just call it profound gastric distress after eating like that the next day.

So the last thing you want to do is eat any food.

I would just hydrate and oftentimes to try and get some exercise.

What I read was that berberine, poor man's metformin, could buffer blood glucose and in some ways make me feel less sick when ingesting all these calories and in many cases spiking my blood sugar and insulin because you're having ice cream and you know, et cetera.

So if I took berberine and I don't recall the milligram count, and then I ate, you know, 12 donuts, I felt fine.

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Journal Club with Dr. Peter Attia | Metformin for Longevity & The Power of Belief Effects