Category Archives: Science

The Decline and Fall of Peter Attia

Over the years Dr. Peter Attia built a reputation as an influential voice in popular longevity medicine. He’s been pervasive online. And recently he was hired by CBS News based on his credibility. So, he’s big time. His podcast draws millions of listeners, and his book became a bestseller. People trust him with their health decisions. I was an active follower until about 2018 when his arrogance finally got the best of me and I just got tired of him. It wasn’t much of a loss for me to dump him because there are plenty of other excellent people in the field who question the established medical paradigm. But Attia kept going and getting rich in the process, which is common among the top tier people in the field. But apparently, he got himself in way over his head. Hopefully, he’ll come crashing down as fast as he rose. It’s unlikely. But I can still hope.

Check out this report about Attia from Joseph Everett — Hidden Data: How the Top Longevity Doctor tricked us all — that reveals a pattern of overconfidence, selective data presentation, and dismissiveness toward ideas that challenge his worldview. In the video, Everett analyzes Attia’s claims and public statements and does several on-camera interviews with Dave Feldman, Dr. Nick Norwitz, and Dr. Chris Masterjohn to provide some scientific context and to counter some of Attia’s most confident assertions. Here’s a review of Everett’s report. 

The Epstein Connection

I never thought Attia would fall based on his association with Jeffrey Epstein because until last week no one even knew he was hanging out with that crowd. But that’s where we are. The Epstein files revealed more than 1,700 PDFs mentioning Attia. The emails show a close relationship that continued even after Jeffrey Epstein’s crimes were publicly known. Attia met Epstein in 2015 through Epstein’s ex-girlfriend. He called Epstein “literally one of the most interesting people I’ve ever met.” He expressed interest in visiting Epstein’s island, and he stayed at Epstein’s apartments. He attended dinner parties with Epstein and his so-called famous friends. 

Attia’s timeline with Epstein is particularly striking. According to Attia’s own book, on July 11, 2017, his wife rushed their one-month-old infant to the hospital because the baby had stopped breathing and his heart had stopped beating. His wife stayed in the hospital for four days, pleading with Attia to come home. He said he couldn’t because he was in New York with “important work.” The next day, July 12, Attia emailed Epstein confirming he could meet him. That’s difficult for any parent to imagine. But it provides a view into the dark space in which Attia lives so freely.

When the Miami Herald published its piece on Epstein in November 2018, Attia claimed he was “repulsed and nauseated.” Yet he stayed in touch with Epstein for at least four more months. In December 2018, he asked Epstein about the “fallout from recent story.” In February 2019, he was still emailing with the subject line “Where are you these days?” There are many other disgusting exchanges between the two in those files. Read them if you want.

The connection to Epstein itself might not be damning. Time will tell. Plenty of people got caught up in Epstein’s orbit but haven’t been implicated with crimes. But the same overconfidence that led Attia to maintain this relationship shows up repeatedly in his health claims.

The VO2 Max Problem

Attia built much of his longevity framework around VO2 max. He called it “perhaps the single most powerful marker for longevity.” He was emphatic. He brought it up on podcasts constantly. The claim appeared on 60 Minutes. It’s in his book. He says everyone should know their VO2 max and track it.

But there’s a problem. The studies he cites to support this claim never actually measured VO2 max. In Everett’s video, Chris Masterjohn, PhD, points out that you can search some of these papers for the word “oxygen” and find nothing. What the studies measured was how long people lasted on a progressively harder treadmill test. That’s not the same thing. I remember people online questioning Attia on this issue and many other issues. Attia generally ignored them. My impression was that Attia grew to be connected and protected. Or at least he was acting that way. 

And when Attia made a table for his blog showing VO2 max levels, he simply relabeled data from a paper that measured something else entirely. The table made it into his book. He tells people they should spend $200 annually to have their VO2 max measured at an exercise science lab, when all you actually need is a treadmill, according to Masterjohn. 

Masterjohn explains that most people in the general population can’t even reach their VO2 max during these tests. They give up because of heart palpitations, leg pain, or feeling like they’ll throw up. They’re never hitting their actual maximum oxygen consumption. But Attia presents this metric as if it’s the single most important thing you can measure. It shows how Attia grew to become totally disconnected from regular people just trying to get healthy. It’s clear in retrospect that Attia was focused on other clients who could pay him millions. Everett points out in his video that Attia would show up on video podcasts wearing several different $300,000 watches. 

The real problem is that focusing so intensely on VO2 max could lead people to spend hours doing one repetitive motion instead of diversifying their training. As Masterjohn says, gymnasts and pole vaulters have eight years on the general population for lifespan. That’s a testament to the breadth of functional training, not endless cardio optimization.

Hiding Inconvenient Data

Now let’s move to cholesterol and statins. When a major study in Cell Metabolism showed that atorvastatin (the most profitable drug in history) slashed GLP-1 levels while worsening glycemic markers and insulin resistance, Dr. Nick Norwitz (MD, Ph.D.) started discussing the issue online. Two weeks later, Attia published a newsletter that appeared to be responding to Norwitz’s analysis. That seems like Attia’s back handed style. 

But Norwitz noticed something strange. Attia’s newsletter tried to discredit the study, but it completely ignored the most relevant graph. As Norwitz puts it in Everett’s report, “There’s one graph of relevance. An 8-year-old can tell you what’s going on. There’s a big red line. It goes down.” Attia showed the figure that contained this graph but clipped out the specific panel that showed the problem. It’s hard to think that wasn’t intentional, Norwitz says. 

Nick Norwitz and the New Generation

Norwitz himself represents exactly the kind of rigorous, open-minded research Attia claims to support. At age 30, Norwitz has already published 54 peer-reviewed papers. His scientific impact score is higher than Thomas Dayspring, the lipidologist Attia regularly cites as his go-to cholesterol expert. And Dayspring is 50 years older. Norwitz is prolific online, too, but he embraces the conversation with both technical and non-technical people — unlike Attia. 

Norwitz recently gave some credibility to another researcher, Dave Feldman, who is a popular software engineer who has been researching LDL cholesterol for years now. Feldman developed an alternative cholesterol model by conducting his own personal experiments and publishing the results online and in scientific papers. Norwitz tested some of Feldman’s views and lowered his LDL cholesterol from 384 to 111 by eating Oreo cookies for 16 days. When he tried statins for 6 weeks, he only managed to lower his LDL from 421 to 284. The Oreos worked better than the drugs. Why the Oreos worked at all is interesting.

The point isn’t that people should eat Oreos instead of taking statins. The point is that our understanding of cholesterol metabolism is more complex than Attia presents it. And when young researchers like Norwitz demonstrate this complexity, Attia either ignores them or dismisses their work outright.

Dismissing Dissent

Perhaps the most revealing episodes with Attia involve Dave Feldman. When Feldman appeared on Attia’s podcast in 2018, the exchange revealed something troubling about how Attia pushes his influence and bullies people. He interrupted Feldman a staggering 66 times, according to Everett’s count. He called Feldman’s investigation “brain damage.” His treatment was arrogant and dismissive to say the very least. He told people interested in cholesterol questions to “sit down, shut up for a minute, and pay attention.” I remember listening to that episode. It was infuriating. And it was clear that it was actually Attia who was out of his league — not Feldman. I mean, when a software engineer goes up against an MD you’d expect the engineer to lose in a fair fight. But Feldman more than held his own in the match. In fact, he was really impressive. Ultimately, though, when some so-called “expert” reacts like Attia did, it’s likely an indication that they have been exposed. I was mostly done with Attia at that point, at least on the cholesterol issue.

The irony is that Feldman’s questions were reasonable and backed up with some excellent, albeit early, data. According to Feldman and Everett, Most research showing that LDL cholesterol is dangerous comes from studies of metabolically unhealthy people. But what happens to people who have high LDL and also have high HDL and low triglycerides, which are both markers of good metabolic health? Do they still die early? What about the many other biomarkers that demonstrate good health in these people? These questions were totally dismissed by Attia.

Attia further said that this line of inquiry was pointless. He challenged Feldman to crowdfund research if he thought his ideas had merit. Feldman, always up for a good challenge, did exactly that. He raised $350,000 for the Lean Mass Hyper-Responder study. The results showed that metabolically healthy people on a keto diet with sky-high LDL didn’t develop more arterial plaque in their hearts. Imagine that. Attia’s response? Silence. And when invited to co-author a journal editorial about the findings by his own former head of research, Bob Kaplan, Attia declined and said there were people “far more reputable” to discuss it with. 

Meanwhile, Feldman went on to publish eight peer-reviewed papers on the subject and continues to work closely with Norwitz on cholesterol research.

The Real Issue

The pattern is clear. Attia presents himself as committed to open-minded scientific inquiry and he strongly lectures people about that. Yet his own behavior says otherwise. He once stated we should “go back to our original ideals: open minds, the courage to throw out yesterday’s ideas when they don’t appear to be working, and the understanding that scientific truth isn’t final.” But when faced with obvious data that challenges his positions, Attia either ignores it or attacks the messenger, many times in childish, unscientific ways. You can see him online repeatedly rolling his eyes, smirking, shaking his head, raising his voice, and using harsh language when he’s simply questioned by anyone. From his powerful platform, he still maintains extreme confidence in his claims, which seem more shaky than ever. That’s not science. That’s ego. And it’s the same attitude that kept him emailing Jeffrey Epstein months after the world knew what Epstein had done.

I wonder how many online health gurus who called him a friend will come out publicly and question Attia now. So far, too many are silent. I wonder, do these people think we’ll not notice?

Make Protein the Priority

Dr. Donald Layman on Building Muscle, Losing Fat, and Reducing the Metabolic Decline of Aging

Dr. Donald Layman has spent decades studying protein and amino acids. He’s a Professor Emeritus at the University of Illinois, and he’s published more than 120 peer-reviewed papers. His work has transformed how we think about dietary protein. And unlike many scientific experts promoting their views online, Layman’s research cuts cleanly through the confusion about how much protein we need, when to eat it, and why quality matters more than most people realize. 

This post is based on eight interviews with Layman in the last few years, and it’s focused exclusively on his insights and recommendations about protein metabolism, muscle health, and optimal nutrition. All quotes are Layman’s. See the resource list below.

The Muscle-Centric Philosophy

Layman developed what he calls a muscle-centric approach to nutrition. He explains that nutrition comes down to two critical tissues: the brain and skeletal muscle. Everything else in the body adapts and regulates, but these two tissues must be supported well because they determine our quality of life. Layman says, “If you keep muscle healthy, you’ve got a good shot at avoiding obesity, avoiding diabetes, avoiding cancer as you age.”

This focus makes sense when you understand what muscle does. It serves as our largest reservoir for glucose, holding about 75 to 80 percent of our total glucose storage capacity. When muscle health declines, however, we lose this metabolic buffer. Then fat droplets accumulate in muscle cells, and over time this creates insulin resistance and makes it harder for muscles to accept carbohydrates. This cascade leads to hyperglycemia in the blood and eventually diabetes.

But muscle does more than manage glucose. Layman says, “Whether you’re 16 or whether you’re 65, you have to build 250 to 300 grams of new protein [every day] just to replace and repair what you already have.” This constant daily turnover happens regardless of age. The difference is efficiency. Young people enjoy hormonal protection that makes protein synthesis easier. But older people must work harder on both diet and exercise to maintain the same results. The difference is significant. 

The body operates in a constant state of protein flux. Every protein in your body gets broken down and rebuilt in a continuous cycle. Layman says that we replace the equivalent of every protein in our bodies about four times per year. This metabolic demand never stops. The liver must produce proteins 24 hours a day to maintain blood protein levels, manufacture enzymes, and support immune function. When dietary protein falls short, the body simply pulls amino acids from muscle tissue to keep these essential processes running. If dietary protein continues to decline over many years, people loose a significant amount of muscle mass. Sometimes this loss is hidden when people gain weight, but when they lost that weight the muscle loss becomes obvious. 

Children require only about five grams of net new protein per day for growth. Adults need none for growth, but they require vastly more protein for maintenance and repair. The adult body must synthesize 250 to 300 grams of protein daily just to stay even. This remarkable fact challenges the common assumption that children need more protein than adults. The opposite is true. In reality, adults face a more demanding protein requirement because the efficiency of their protein metabolism declines as they age. Also, adults are not as active as children and so their muscles don’t receive the signal from exercise to grow. 

The RDA Problem

The Recommended Dietary Allowance for protein in the United State sits at 0.8 grams per kilogram of body weight. Layman has spent years explaining why this number falls way short. The history is important. The RDA came from nitrogen balance studies conducted decades ago using conscientious objectors during World War II. Researchers put these men in special suits to collect nitrogen leaving their bodies. They lowered protein intake to zero, then gradually increased it until nitrogen inputs matched outputs. This became the basis for protein requirements.

There are big problems with this early research, however. “The RDA is the average requirement. By definition, that’s only the average. Half of the people are above average.” The RDA represents a minimum for survival, not optimal health. Also, nitrogen balance studies carry inherent flaws. All amino acids contain different amounts of nitrogen and plant proteins have more non-essential amino acids than animal proteins. When researchers use nitrogen analysis, they consistently overestimate the actual protein content.

Layman now argues for a fundamental shift in how we think about dietary requirements. He says we should stop talking about protein as a requirement and start talking about essential amino acid requirements. Layman says, “We actually don’t need protein in the diet. We need nutrients and the nutrients are essential amino acids.”

Based on dietary surveys, about 45 percent of Americans consume protein below recommended amounts. That’s an incredible statistic given that RDA is the minimum requirement. Women face particular challenges, especially those over 60 and between 18 and 22. Older women prefer carbohydrates to protein in their diets during a time when their bodies are aging and require fewer total calories to function. Their resting metabolism literally drops about 100 calories per decade naturally. However, younger women often intentionally restrict protein for appearance or moral reasons when many of them adopt extreme diets like veganism. Only women in the middle age range are getting the minimum amount of protein.

How Much Protein Do We Actually Need?

Remember that the American RDA for protein is  0.8 grams per kilogram of body weight. However, Layman recommends that most adults should consume between 1.2 and 1.8 grams of protein per kilogram of body weight. For practical purposes, this translates to roughly 0.5 to 0.8 grams per pound. The exact amount depends on several factors including age, activity level, and metabolic health. Layman’s recommendation isn’t unreasonable, although it may sound shocking to some people since it’s substantially higher than what the U.S. government has been saying for decades. Many others in the protein field go even higher to 1.0 – 1.2 grams of protein per kilogram of body weight just to account for those days when it’s impossible to get the minimum. Life is variable so people have to account for things like travel, schedules, emergencies, etc. 

When determining your dietary protein target, Layman says that you should use your ideal body weight rather than your current weight if you carry excess fat, which is at this point most Americans. He explains that adipose (fat) tissue does not require protein maintenance the way muscle does. For someone who weighs 200 pounds but should weigh 170, calculate protein needs based on 170.

The upper limit matters less than most people think, and Layman is actually somewhat conservative in his recommendations. He says that his research supports a protein intake of up to 1.8 grams per kilogram without concerns. “I don’t think the data really supports going above 1.8 g per kg,” but he emphasizes this comes from lack of research rather than evidence of harm. Studies on protein intake from 0.8 grams per kilogram up to 3 grams per kilogram show that protein appears totally safe across this entire range. Note that most professional and amateur athletes who are knowledgable about protein exceed Layman’s recommendations. Yet Layman sticks to his levels because that’s what his data demonstrates. Actually, Layman rarely talks about professional athletes. Instead, his focus and expertise is on the biochemistry and health of the general population through their entire lifespan. 

Protein Quality Makes the Difference

Not all protein delivers equal benefits. Layman focuses on three key amino acids: leucine, lysine, and methionine. Leucine especially triggers muscle protein synthesis through the mTOR pathway. Animal protein foods deliver about 8 to 10 percent leucine, while plant proteins typically contain only 6 to 7 percent. This presents a problem for vegans as they age. Smart vegans supplement. But if people who have adopted vegan diets don’t supplement, they generally find that over time they lose muscle mass and overall lean tissue as they age. You can clearly see this with the naked eye in vegan populations that aren’t overweight. 

This difference compounds when you consider digestibility. Animal proteins offer about 95 percent digestibility. Plant proteins drop to 60 to 75 percent, and that varies also with different cooking techniques. When you eat beans, for example, your body cannot access nearly half the protein on the label. “The idea that beans are a substitute for beef is a really dumb idea,” Layman says. Strong language like that is rare from Layman, yet he has decades of research to back up his claims. 

The distinction matters most as we age. “Under 30 it doesn’t matter when you eat your protein. It doesn’t matter very much the quality of the protein. But once you cross 30, now the efficiency of how you put it all together makes a big difference in how you’re going to repair or remodel your protein for healthy aging.”

Americans who shift toward plant-based diets, with the extreme being pure veganism, typically increase their grain consumption substantially rather than eating more beans, chickpeas, and almonds. “Americans get 80% of their plant-based protein from wheat. And wheat is a very poor quality protein.” When people eat primarily grains at the RDA level, they become deficient in two or three essential amino acids.

The wheat problem is deeper than most people realize. About 60 percent of American protein comes from animal sources such as fish, eggs, milk, and meats. The remaining 40 percent, though, comes from plants, and 80 percent of that plant protein comes from wheat. That’s a problem because it makes it challenging to get all the required amino acids in their proper proportions. Wheat is deficient in lysine, tryptophan, threonine, and leucine. When people shift toward more plant-based eating by simply consuming more wheat products, they create multiple amino acid deficiencies. These shortfalls affect everything from metabolic signaling to fat burning to brain function through tryptophan and serotonin production. Remember that the body must have all the essential amino acids in specific ratios, so if you don’t consume them the body will simply take them from storage — the muscles. 

Layman emphasizes that although relatively few Americans are vegans the general population is already largely eating a plant-based diet. Over 70 percent of our calories come from plants, but more than 80 percent of those plant calories come from added sugars, oils, hydrogenated fats, and highly refined carbohydrates. Junk food, basically. The number one plant in the American diet is french fries, followed by tomato sauce on pizza and lettuce. “We don’t need a more plant-based diet. We need a better one.” Here Layman distinguishes himself from the current carnivore trend. He’s perfectly ok with an omnivore diet as long as the non-meat portions are based on healthy, properly prepared, food. 

The body requires 20 different amino acids to build protein tissue. Nine of these amino acids are essential, which means that the body cannot manufacture them and must obtain them from food. The remaining 11 are non-essential. But that term can be misleading because the body still needs them. The difference is production capability, not importance. When you lack essential amino acids, protein synthesis stops completely. The body cannot substitute one amino acid for another or skip amino acids in a protein chain. So the body has no choice but to tap the stocks and get those amino acids. Where does it go to find those amino acids? To the muscles. 

Leucine stands out among essential amino acids for its unique signaling role. Beyond serving as a building block, leucine activates the mTOR pathway that initiates muscle protein synthesis. You need approximately 2.5 to 3 grams of leucine per meal to trigger this response. Animal proteins deliver this amount in modest portions, while plant proteins require much larger servings to reach the same threshold. This is one reason why people on plant-based diets must consume more total calories because the body is always hungry and looking for those required amino acids. 

Lysine becomes particularly important when evaluating plant proteins. Grains contain very little lysine, which creates a major limitation in grain-based diets. This shortage explains the traditional practice of combining beans with rice or corn in cultures relying heavily on plant foods. The combination provides complementary amino acid profiles that neither food delivers alone. Experienced vegetarians and vegans know this issue well and monitor it carefully when they eat. It’s not a full proof method to acquire all the essential amino acids, but at least it’s an attempt to recognize the issue.

Methionine supports glutathione production, one of the body’s master antioxidants. Layman’s research shows that when protein intake drops toward the RDA level, glutathione levels decline. To maximize glutathione levels in older adults, protein intake needs to reach at least 1.2 grams per kilogram. This requirement is 50 percent higher than the RDA, revealing how the minimum standard fails to support optimal metabolic function. There is more than enough research on protein now. One wonders why the RDA remains so low. 

Timing and Distribution

The first meal after waking is most importance. Layman consistently emphasizes getting at least 30 to 35 grams of high-quality protein within an hour of rising. This first protein bolus stops the catabolic overnight fasting state that builds during sleep and triggers muscle protein synthesis. 

After that initial meal, distribution throughout the day becomes more flexible. In weight loss studies, Layman found success with 35 grams of protein at breakfast, 35 at lunch, and about 50 at dinner. But he allows variation based on individual preference. “The reality is we have really good data about the protein at breakfast. We have pretty good data about protein at dinner and we have zero data about protein at lunch.”

Layman’s own diet reflects this understanding. He typically consumes 40 to 45 grams at breakfast, 15 to 20 at lunch, and 50 to 60 at dinner. He finds that large midday meals make him sleepy and less alert. Everyone’s different. People just have to experiment to see what fits them best as long as they are getting what they need in any given day. But it’s important to hit that minimum effective dose per meal of around 30 grams of high-quality protein. This amount provides about 2.5 to 3 grams of leucine, enough to trigger muscle protein synthesis. Younger people need less. But older people need higher amounts and sometimes require 40 to 50 grams to achieve the same anabolic response.

The Fasting Dilemma

Time-restricted eating has grown in popularity recently, but Layman urges caution for anyone over 40. In fact, he’s emphatic on the issue. “I don’t think anybody over the age of 50 should ever fast.” The muscle mass lost during extended fasting becomes permanent without aggressive resistance training during the recovery period, and very few people realize this until they directly experience the process themselves. I certainly have. And it’s shocking.

But Layman distinguishes between proper time-restricted feeding and true fasting. Eating within an eight or ten hour window can work if you maintain adequate protein intake. But going 36 hours or longer without food creates a catabolic crisis that strips away lean tissue. Remember, the body must absolutely have all 9 essential amino acids at all times not only to build and maintain muscle but also for hundreds of regular biochemical processes just to maintain health. 

The problem intensifies with some popular one-meal-a-day approaches advocated by some people online. Protein synthesis can process only so much protein at once, typically maxing out around 40 to 50 grams. When you try to consume 100 or more grams in a single meal, your body cannot use all the amino acids for building tissue. You miss opportunities to stimulate synthesis multiple times throughout the day. You see these people online. Their bodies transform quickly. They tend to look shredded but also gaunt. They don’t look healthy at all. 

Research on protein synthesis shows effects lasting four to five hours after a protein-rich meal. This window suggests that we should space our protein intake every four to five hours to optimize results. Cramming all protein into one meal wastes the stimulatory potential of well-timed protein distribution throughout the day. 

Protein and Weight Loss

Layman conducted extensive weight loss research demonstrating protein’s protective effects on lean tissue. He found that typical weight loss results in about 50 percent muscle loss and 50 percent fat loss. This composition change proves devastating, especially for older people who clearly struggle to rebuild lost muscle. But a higher protein intake can change this situation dramatically. “We can make the weight loss 95% fat 5% muscle,” Layman says. The key lies in maintaining at least 100 grams of protein per day for women during caloric restriction combined with resistance exercise. Men need proportionally more protein based on their larger size.

Layman taught his research subjects a simple a visual method to make implementation much easier than counting grams. He says that protein and carbohydrates should look equal in size on the plate. Four ounces of meat appears roughly equivalent to half a cup of rice. This one-to-one visual balance creates roughly the right macronutrient ratio for a meal. 

Higher protein intake during weight loss provides additional advantages beyond muscle preservation. Protein carries a higher thermogenic effect than carbohydrates or fat, which means you burn more calories digesting and processing protein. Protein also provides superior satiety, reduces hunger, and makes caloric restriction more tolerable.

The metabolic advantage of protein extends beyond the thermic effect of food. When you maintain muscle mass during weight loss, you preserve your metabolic rate. Each pound of muscle burns more calories at rest than a pound of fat. But losing muscle during dieting creates a vicious cycle where your metabolism slows down and makes further weight loss harder and weight regain more likely.

Layman’s research reveals that people using skim milk during weight reduction lost the advantage of both protein quality and satiety. The fat naturally present in dairy products serves important functions. He recommends reduced fat products rather than fat-free versions, allowing people to control total fat intake while maintaining the benefits of naturally occurring dairy fat.

The body’s overall composition during weight loss matters far more than the number on the scale. A 60-year-old who loses 30 pounds but half of that comes from muscle ends up metabolically similar to an unhealthy 80-year-old. And visually, these people look obviously gaunt. The muscle loss accelerates the aging process and reduces functional capacity. In contrast, losing mostly fat while preserving muscle keeps you metabolically younger and maintains strength and mobility, both of which are critical to maintaining health as you age. If you think that strength isn’t a factor over time, just observe any elderly person after a few falls and hospital stays. Their bodies dramatically reduce in size as their health rapidly declines. 

GLP-1 medications also present particular challenges during this time. Sure, people lose weight rapidly on these drugs. But without adequate protein and resistance exercise, about 50 percent of the weight loss comes from lean tissue. Layman warns — strongly — that this muscle loss becomes especially problematic because these people often struggle to rebuild what they lost after they discontinue the medication. 

Exercise and Protein Work Together

Resistance training and protein operate synergistically. Layman estimates that building muscle comes down to about 75 percent resistance training and 25 percent protein intake. That may seem anti intuitive given his research on the biochemistry of protein synthesis. However, you cannot compensate for lack of exercise with more protein. The protein intake is the foundational requirement to enable people to maximizes the benefits of training. 

But as you age you don’t have to go crazy in the gym. The definition of resistance training is broader than most people assume. Layman says that gradual stretching and low impact workouts represent a major part of resistance exercise. His weight loss studies with middle-aged women used Nautilus machines without adding weights. The women simply moved through the full range of motion, which emphasizes the eccentric or stretching process. This protocol produced significant improvements in body composition and demonstrates that even a minimal level of moment is beneficial. 

For people intimidated by gyms, Layman recommends yoga, Pilates, or rubber band stretches and movements at home. He says, “The best exercise is the one you’ll do consistently!” The critical factor lies in creating mechanical stimulus that tells muscles they need to maintain or grow their mass. And while muscles are moving under even mild stress they signal other lean tissue to grow, such as bones, ligaments, and tendons. Movement is critical to health. 

Timing protein around exercise matters less than most people think. Layman’s research shows that resistance exercise in a fasted state can trigger protein synthesis mechanisms. But without adequate amino acids available, the signal cannot translate into actual tissue building. Layman says you can “trigger those processes” with exercise or leucine alone, “but you need the complete amino acid mix.” Here Layman emphasizes the interdependence of proper nutrition and proper exercise. 

The Kidney Myth

Concerns about protein harming kidney function persist despite evidence to the contrary. Layman explains that higher protein intake actually increases kidney size and improves the body’s glomerular filtration rate. The kidney adapts to increased protein load by becoming more efficient at clearing urea and creatinine from blood.

Research comparing 0.8 grams per kilogram of protein with 1.6 grams per kilogram shows accelerated clearance rates at higher intake levels. Layman says that “the rate of creatinine clearance, the rate of urea clearance, actually accelerates. GFR becomes more efficient.”

But protein restriction produces the opposite effect. When people consume low protein diets below or even at the RDA level, their kidneys actually shrink and clearance capacity decreases. For healthy people, protein intake up to one gram per pound appears completely safe for the kidneys. Some markers of kidney function improve simply with better hydration because protein requires more water for processing.

Practical Protein Sources

Eggs, dairy, fish, and meat provide the most complete amino acid profiles with the highest digestibility. Whey protein stands out as particularly effective due to its rapid digestion and high leucine content. Layman himself often mixes whey protein powder with Greek yogurt to combine the fast-acting whey with the slower-digesting casein found in yogurt.

For budget-constrained people, eggs and ground beef offer an excellent value. Layman says that when people shift from junk food and quick-service meals to protein-focused diets, they often actually spend less money despite buying better quality food. Various cuts of meat, fish, chicken, ham, cheese, and milk all qualify as functional protein sources since you don’t have to worry about getting all nine essential amino acids. Milk provides one of the easiest ways to fine-tune protein intake. Layman says, “Milk is one gram per ounce. I like milk. So if I need nine more grams at my meal, I just have nine ounces of milk.”

For plant-based eaters, though, the protein challenge intensifies. Beans have to be combined with grains to provide complete amino acid profiles, but even then, digestibility problems persist. Layman suggests that vegetarians and vegans should consider supplementing with essential amino acids to ensure adequate an intake of leucine, lysine, and methionine.

The dairy industry transformed itself based on Layman’s research. In 2003, he addressed 250 research and development professionals from dairy companies. He told them their yogurts contained nothing but sugar and urged them to develop Greek yogurt with higher protein content. Chobani launched within a year, and the entire yogurt market shifted toward protein-rich products. The proliferation of protein shakes and high-protein foods in stores today traces back to this research that shows the importance of protein quality and quantity. Or you could just eat a a traditional diet based on whatever culture you are from since they all generally contain enough protein without having to always think about reading labels and supplementing. 

Greek yogurt also offers advantages over regular yogurt because the straining process concentrates protein while removing excess liquid and sugar. However, Greek yogurt contains more casein than whey. Layman addresses this by adding whey protein powder to Greek yogurt, which creates an ideal blend of fast and slow-digesting proteins.

Whey digests rapidly and floods the bloodstream with amino acids within an hour. This quick availability makes whey excellent for stimulating muscle protein synthesis. Casein, however, digests more slowly and provides a steady release of amino acids over several hours. The combination delivers both immediate stimulus and sustained amino acid availability.

Cheaper protein sources work perfectly well for most people too. Ground beef provides complete protein at lower cost than premium steaks. Chicken thighs cost less than breasts and often taste better due to higher fat content over breasts. Whole eggs deliver superior nutrition compared to egg whites despite containing fat and cholesterol. The key lies in choosing real animal foods rather than processed protein products that promise convenience but deliver inferior amino acid profiles.

Layman conducted weight loss studies specifically examining low-income populations. These studies revealed that shifting to a protein-focused diet actually costs less than the typical American diet heavy in processed foods, chips, candy, and fast service restaurant meals. The perception that healthy eating costs more often reflects comparison of premium organic products with budget processed foods rather than realistic and simple alternatives. Learn to cook. And don’t forget to consider the cost of disease that results from decades of eating poor quality food.

The Carbohydrate Question

Layman takes a balanced approach to carbohydrates that focuses on individual needs and activity levels. He says that the brain and red blood cells require at least 100 grams of carbohydrates per day. If you fail to eat this minimum, your body converts protein into glucose through gluconeogenesis. This process wastes dietary protein that could otherwise build and repair tissues, which is critical as we age. 

Also, exercise intensity determines carbohydrate needs above this baseline. Activities below 65 percent of maximum heart rate primarily burn fat for fuel. Walking, cycling, and low-intensity exercise fall into this category and require minimal carbohydrates beyond the 100-gram minimum. Once intensity crosses the 65 percent threshold into moderate and high-intensity work, the body shifts toward carbohydrate metabolism. Resistance training, running, competitive sports, and high-intensity interval training all demand immediate carbohydrate fuel.

Layman practices what he preaches. He plays tennis and exercises intensely, so he includes carbohydrates in his diet. He says he needs adequate carbs to feel good and compete well during exercise. Without sufficient carbohydrates, he says his performance suffers because he operates above the threshold where fat alone can meet energy demands.

Layman’s one-to-one visual ratio of protein to carbohydrates on the plate creates an effective and visual framework for most people. This approach naturally limits carbohydrate intake while ensuring adequate protein. For someone eating 30 to 40 grams of protein per meal, the equal volume of carbohydrates translates to roughly 30 to 40 grams of carbs, creating a moderate overall carbohydrate intake. The key is to focus on real food carbs, not junk food. That may sound obvious, but in modern society most people have lost the knowledge of basic nutrition to the point that they don’t even know how to search out and prepare real food. 

Also, individual carbohydrate tolerance varies significantly based on genetics, activity level, and metabolic health. Someone with insulin resistance needs to restrict carbohydrates more than a metabolically healthy athlete. The key here lies in matching carbohydrate intake to actual metabolic demand rather than following arbitrary rules about high-carb or low-carb diets.

Protein as an Absolute Number

One of Layman’s most important insights concerns how we think about protein intake. Layman says that protein should be treated as an absolute number, not as a percentage of total calories. “Protein’s an absolute number. I want 150 grams per day or 120. You pick that and then you pick carbohydrates and fat relative to your energy needs.” In other words, he’s advocating that we optimize for protein first, which makes a complex issue much easier to understand. 

This approach changes everything. Most diet plans express protein as a percentage of calories, typically 15 to 30 percent. But that method creates problems. For example, if someone reduces total calories while keeping protein at a fixed percentage, their absolute protein intake will drop too low. During weight loss or caloric restriction, this percentage-based approach guarantees muscle loss.

Instead, Layman recommends choosing your protein target first based on your body weight and activity level. Lock in that absolute number as your top priority. Then adjust carbohydrates and fats based on your individual needs, preferences, and metabolic health. Someone who loves carbohydrates and exercises intensely can probably eat 300 grams per day. Someone managing diabetes may need to restrict carbohydrates significantly. A person following a ketogenic approach can increase dietary fat. The critical factor lies in maintaining adequate protein regardless of how you adjust the other macronutrients. There are only three macronutrients (fat, protein, carbohydrates) and the ratio between the three matters. 

This framework supports personalized nutrition. Layman says the future of nutrition must be personal with people having a clear understanding of protein as the foundation. “It’s the single most important nutrition decision we make. Everything else revolves around it, and if you make the wrong decision there you’re really behind the eight ball to make everything else work.”

The Future of Protein Research

Layman advocates for putting amino acid profiles on nutrition labels. Current labeling tells people how many grams of protein a food contains but provides no information about which amino acids those grams contain. This oversight leaves people unable to make informed decisions about protein quality, which is the most important aspect of protein nutrition. Food labels really should just list the amino acids along with the other nutrients. 

Testing technology exists to analyze amino acids quickly and affordably. For example, mass spectrometry with fluorescence detection can process 400 foods in a day. With 15,000 new food products released in the United States annually, consumers need better tools to evaluate their choices. Looking at eight protein bars on a shelf, you cannot determine which provides superior amino acid composition without detailed analysis.

The resistance to implementing this change comes not from technical barriers but from political and economic forces, which are substantial in the nutrition industry and throughout the scientific community. Adding amino acid profiles to labels would reveal the inferior quality of many plant-based products currently marketed as protein sources. Layman has worked with various organizations and government agencies to push for these changes, but unfortunately progress is coming very slowly.

A Message for Healthy Aging

Layman returns repeatedly to the idea that protein requirements actually increase with age because the human body’s efficiency decreases. The transition begins between 30 and 40 and accelerates dramatically after age 50. Hormonal changes, particularly in women during perimenopause and menopause, make adequate protein intake even more critical.

Beyond muscle, protein affects bone health, immune function, and metabolic regulation. Layman says, “Bone is first and foremost a protein matrix.” Osteoporosis reflects not just calcium deficiency but inadequate protein to maintain the structural foundation of bone tissue. Sarcopenia, the age-related loss of muscle mass and function, threatens independence and quality of life more than most people realize until it’s too late. This wasting process is difficult to see when you are overweight. But lose the fat and it becomes obvious. 

Falls and fractures represent one of the major health problems for people over 65. Layman notes that 300,000 hip fractures occur annually in the United States, which is an utterly massive number of injuries that are not necessary. And it gets worse because one-third of those people never leave the hospital! So, maintaining muscle strength and bone density through adequate protein intake and resistance training provides one of the most effective strategies for preventing these catastrophic medical events.

But this protein issue goes beyond muscle development. The amino acids in protein are necessary for neurotransmitter synthesis and affect mood and cognitive function. Methionine supports glutathione production, one of the body’s primary antioxidant systems. Threonine maintains gut health through mucin production. Tryptophan influences serotonin levels and sleep quality. These metabolic roles require amino acid intake significantly above the RDA. Protein is everywhere in the body, and no substance comes close to protein in terms of overall nutritional requirements. 

The Bottom Line

Layman summarizes his philosophy simply — start all dietary decisions with protein first. Whether you choose to eat vegetarian or carnivore, high-fat or high-carb, everything else should follow from first ensuring adequate high-quality protein first. “Your first choice about what you should eat should always be about a protein decision.”

The science supports consuming significantly more protein than the RDA suggests. Most adults benefit from 1.2 to 1.8 grams per kilogram of body weight, with the first meal of the day containing at least 30 to 35 grams. Animal sources provide superior quality and digestibility compared to plant sources. Resistance training amplifies protein’s benefits but cannot compensate for inadequate protein intake. As a practical matter, the sequence he’s suggesting is pretty simple. 

After decades of research and hundreds of publications, Layman has shown that protein affects nearly every aspect of health from muscle and bone to metabolism and disease prevention. His work has helped reshape the food industry, promoting the development of Greek yogurt and other high-protein products. But Layman’s his most important contribution lies in teaching people that the RDA represents a minimum for survival rather than a target for thriving. Note the use of the term survival. Too few people realize how important protein is to their health. 

And finally, as we age, protein becomes more important and essential for maintaining independence, mobility, and quality of life. “Every year you replace the equivalent of every protein in your body about four times and how well you do that determines a lot about how you age.”

References

Is AI Conscious? 

I’ve been following Cal Newport for years for his work on cognitive issues and deep work to improve career opportunities. But that’s his side job. He’s actually a serious computer scientist and recently he challenged some obvious misconceptions (here, here) about artificial intelligence (AI), especially claims made by biologist Bret Weinstein on the Joe Rogan podcast and earlier in his own podcast. Generally, Weinstein’s great but he can be abstract and long-winded and sometimes difficult to understand in his effort to explore deeper levels of thought. But with AI, he breaks down. In his conversation with Rogan, Weinstein seemed to imply that ChatGPT and similar large language models (LLMs) might be conscious or even manipulating people right now. Conscious? Not even close. And it didn’t take much for Newport to wreck Weinstein’s view by simply explaining in detail how LLM systems actually work at present. 

Newport played some audio clips from the Rogan podcast where Weinstein said that these current LLMs may be functioning like a child’s brain, running experiments and learning what they want. But Newport explains why this comparison fundamentally misunderstands the technology. “Language models don’t run experiments in the way a human mind might,” Newport says. “LLMs certainly don’t want anything to happen. They have no values or drives like a human brain does.”

It’s reasonable to ask why Weinstein doesn’t recognize that he’s out of his field here. He sounds like a guy on the street talking about something he knows nothing about. Newport and others have clearly stated that these LLMs are limited compared to a fully thinking human being, and if we wanted to build something like a conscious human brain, we’d have quite a long way to go.  

Newport says that language models operate through complicated but static tables of numbers processed sequentially through multiplication algorithms. “Once one of these networks is trained, that vast table of numbers is fixed. It’s static. It does not change.” When you query ChatGPT, nothing is being updated or learned. The same fixed numbers produce words through straightforward matrix multiplication spread across thousands of GPU chips.

Newport compares language models to isolating just the language processing center of a human brain. That neural cluster does sophisticated work to understand words and concepts, but we would never call it conscious or alive on its own. Weinstein asks in one of his Joe Rogan clips, “Is the AI conscious? I don’t know. If it’s not now, it will be.” Really? How does he know that? At this point, Weinstein goes over the top, which only undermines his credibility on the subject and helps promote fear. The technology around AI and other forms of computer automation has been progressing for many decades, but only now we’re finally afraid?

Newport responds to Weinstein immediately and emphatically: “I can answer your question. Is the AI conscious? No, it is not conscious.” Newport sounds almost surprised and frustrated. He explains that when we understand the mechanical process of how language models work, “this has a fraction of the types of operations and behaviors you would need to even imagine something like consciousness.”

Newport also addresses why AI pioneer Geoffrey Hinton sounds similar alarms despite knowing how these systems work since he did much of the initial research to enable the technology. Newport clarifies a crucial but obvious distinction totally missed by Weinstein: Hinton worries about hypothetical future AI systems we haven’t built yet, not the current language models in use today. “Weinstein’s talking about language models,” Newport says. “Hinton’s talking about AI artificial brains that we haven’t built yet, but he’s now more confident than he was before that they are buildable. That’s different.” How long away these systems are Newport doesn’t speculate.

Newport also identifies a pattern in how people commonly misunderstand AI: “When a non-technical critic like Weinstein looks at language models, here’s what I think they’re doing instead. They’re observing from the outside the things that the model is doing. They then write a story about what’s happening inside the model that matches what they observed.” This represents what he calls “an ancient animist religion approach to understanding the world” rather than scientific analysis. That’s a heck of a criticism to project at a scientists like Weinstein. But that’s science, right? You debate data. You discuss different perspectives. And sharp criticism among researchers is normal.

Regarding truly dangerous artificial intelligence, Newport says that we would need breakthroughs in multiple separate technologies: world modeling, simulation and planning systems, policy networks for values and drives, memory systems, and real-time learning capabilities. Current AI agents remain limited because language models lack these crucial capabilities.

Newport says that instead of focusing on apocalyptic narratives, we should instead direct our attention toward AI’s potential present day harms. “AI presents many problems, but most of them are happening right now, not in the future,” he says. These concerns include how AI degrades our thinking abilities when we outsource cognitive work, how it erodes our capacity to distinguish truth from fiction, how it floods us with low-quality generated content, and the environmental and economic costs of the global AI arms race. By understanding the actual mechanics of how AI systems work right now, we might be able to avoid both the unfounded fears as well as the overconfidence in their current capabilities.

Zoopharmacognosy

Here are two articles I wrote way back in 1992-1993. Ages ago.

But the topic still lives and is more relevant than ever. As long as there’s advanced life on Earth this topic will be important. The life bit is the catch, though. It’s zoopharmacognosy. It’s how wild animals when they are sick seek out and use medicinal plants to heal themselves. It’s really wild stuff. 

The first piece below I did as an intern at Animals Magazine while going to Northeastern University at night. Animals Magazine was published by the Massachusetts Society for the Prevention of Cruelty to Animals (MSPCA), which is also the home to the famous Angell Animal Medical Center in Boston. The article was part of my final project at school, too. It only took three drafts, but I like the edit very much and the piece really resonated with people. So it worked well. It also led to a fund-raising promotional campaign at the magazine, it helped me get hired on staff as a full time employee, it peaked the interest of an editor at MIT’s Technology Review, it generated many letters to the editor, and it was also cited as a source in a letter to the editor in the British Medical Journal (Can animals teach us medicine? Page 1, Page 2). I never thought I’d see my name in such a prestigious medical publication but there it is. Pretty cool. I just tripped over the reference while doing some research for another article, actually. A happy catch for sure. But the larger point is the subject matter. It’s really critically important and wildly unique. Almost unbelievable. And that’s what really drove all the attention.

Looking back at this article now after all these years, I think it holds up pretty well. I’d only change a few bits, but then again I rarely have the desire to re-write stuff. I’m just not that critical. But I do remember at the time arguing with the editors for another page of space because I had so much material. But this particular issue in the magazine was already full. And I was too junior to get an extra page of that prime real estate — remember this was a time when magazines were designed via paste up boards and printed on real paper. So I had to cut. It’s always painful to cut your own work. That’s why we have editors, I suppose. But cutting is a seriously good skill to develop.

Anyway, I said earlier that the article in Animals Magazine caught the attention of an editor at Technology Review. That’s the second piece below. That was a big surprise. It was a tough thousand words to craft on such an insane deadline — which was immediately. I had to cut so much material that I struggled to make it all hang together. For skilled science writers this article would be just a straightforward little news piece. But for me at the time it was a very big deal. I had mountains of research and very little experience hacking it all down to just one page, basically. But with a little help from the editor I made the deadline. And just like the Animals Magazine article, this one in Technology Review got a lot of attention at the time. It made it into the San Francisco Chronicle and about 10 other daily newspapers around the United States. I was pretty happy, I must say.

The topic of how endangered wild animals seek out and use rare medicinal plants to heal themselves fascinated me back then and it still does today. Back then it was an emerging field in science that could have dramatic implications for human health and the global environment well into the future. Imagine wild animals teaching domesticated humans how to cure some of our nastiest diseases. Could we be humble enough to engage in such a learning exercise? Unlikely. Just look at how the world has matured in the last three decades regarding natural treatments to diseases. Just look at how we treat the wild animals and wild habitats generally. I guess it’s too much to ask to stop killing the animals and their medicinal plants and also the habitats in which both live. Modern humans and the complex cultures we’ve constructed are almost totally detached from nature — and from reality as well. Not to fear, though. We’ll be saved with virtual reality. Coming soon.

Nevertheless, back 30 years ago I started my writing career with two nice pieces here. And then I became depressed. But when I figured out all the time invested in thinking, researching, interviewing, writing, editing, and iterating, I made under $1 an hour. I knew right then that my writing career would have to be killed as soon as possible. I just didn’t have the time to grind it all out earning pennies as I grew my skills and contacts. This was a second career for me because the first one ended in a long hospital stay and five years out of work with no insurance (you gotta love the American medical system, eh?). I simply owed too much money and had no method to pay it all back. And I needed to eat too. It’s really that simple. It took a few years to dump the second career and move on to the third (btw: I’m now on my fourth) but it was necessary. So I guess I shouldn’t judge too harshly all of humanity as I just did in the paragraph above. The irony isn’t lost on me, I can assure you.

See both articles below. Click on the images for pdfs for reading or download.

Zoopharmacognosy
Animals Magazine: September/October 1992: Fur-Bearing Pharmacists
Zoopharmacognosy
MIT’s Technology Review: August/September 1993: The Monkey’s Medicine Chest

Here are some old links related to the two articles above:

Here are some recent links unrelated to the two articles above but related to zoopharmacognosy generally:

More Protein, Please

Here’s a bit on protein based on the views of Dr. Rhonda Patrick as she appeared with Dr. Peter Attia. There’s been a lot of discussion about protein in recent years because it’s now obvious we’re not eating nearly enough. Personally, I think that’s the intention from policy makers, but Attia and Patrick don’t go there.

UPDATE: Before we start, though, please note that I utterly despise Attia. I stopped listening to him around 2018 when he refused to evolve on the LDL cholesterol issue, but on protein he seems largely in line with current trends. I can’t explain that but it’s consistent with what I’ve experienced with other powerful people who may have hidden interests, hold inconsistent views, and over time become closed minded when presented with new data. That’s Attia. And then there’s his overt love affair with Jeffrey Epstein, which came as a surprise to everyone and is obviously unforgivable. Hopefully, he gets what’s coming to him. However, when I listened to this podcast on protein with Rhonda Patrick last year I didn’t notice Attia being his usual obnoxious self so I thought I’d go with it. I’ve been following Patrick for years too. I don’t agree with everything she says, but she’s largely open minded and she qualifies her statements regularly. Plus, I really only care about protein at this point, and I’ve learned to not accept everything everyone says just because I agree with part of what they say.

So, here’s my bit on the Patrick/Attia discussion.

#369 ‒ Rethinking protein needs for performance, muscle preservation, and longevity, and the mental and physical benefits of creatine supplementation and sauna use | Rhonda Patrick, Ph.D.

Everyone knows that the current dietary guidelines in the United States is trash and should be ignored entirely if you want to be healthy. The protein reference range is dangerously inadequate for maintaining muscle mass, preventing frailty, and supporting long-term health. And it’s a shame that even in innovative conversations like this with Attia and Patrick they still have to refer back to the official guidelines to compare what they are recommending. I’d much prefer that they and others just delete the guidelines completely and start fresh with their own assertions based on their own research. Hopefully, RFK, JR will help move that needle. But back to Attia and Patrick on their latest findings on protein.

The Foundation Is Flawed

The current U.S. Recommended Daily Allowance for protein is a pathetic 0.8 grams per kilogram of body weight per day. This number has guided nutritional advice for decades. The number appears on food labels and in dietary guidelines worldwide, as well, because many countries blindly follow the American scientific establishment. But according to Dr. Rhonda Patrick, a scientist whose work explores nutrition, aging, and disease prevention, this recommendation rests on fundamentally flawed research. Honestly, listening to Patrick on protein, I can’t help think that this foundation of “flawed research” sounds just like the history of fat and sugar as we’ve discovered in recent years.

“What you will learn is that a lot of the studies that were done to determine this RDA were flawed,” Patrick says. “They were called nitrogen balance studies, and for many reasons they’re flawed.”

The nitrogen balance method attempted to measure protein needs by tracking nitrogen excretion in urine after protein metabolism. The logic may have seemed sound on its face. Measure what goes in, measure what comes out, and calculate what the body needs. But the execution was problematic.

Different protein sources have varying nitrogen to protein ratios. Urine collection was incomplete. And critically, we lose nitrogen through pathways other than urine. So, the signal to noise ratio in these studies was simply too low to produce reliable results. The whole process today just looks sophomoric now.

“Ultimately, what countless experts have now agreed upon is that the protein for the RDA has been underestimated because of those reasons,” Patrick says. I’d go further. Those early studies were silly.

The New Science Tells a Different Story

Modern research using stable isotope studies has provided far more accurate measurements. These studies use L-1,13-carbon labeled phenylalanine as a tracer, allowing researchers to measure protein metabolism through breath rather than relying on incomplete urine collection. The results are striking.

Multiple isotope tracer studies now show that adults need between 1.2 and 1.6 grams of protein per kilogram of body weight daily to prevent negative protein balance. This represents a 50% increase over the current RDA. It is a massive difference with serious implications for public health.

Attia emphasizes the critical importance of this finding by explaining what makes protein unique among macronutrients.

“We can store fat in unlimited quantities,” Attia says. “We can store carbohydrates. Now, we can’t store them quite as much because we only have so much glycogen we can store in the muscle and in the liver. But when we break down fat, we keep making the substrate to actually make glucose. The only place that an amino acid sits in residence in our body is in the muscle.”

This distinction is critical. When we fall short on protein intake, we have no buffer zone. We have no reserve tank to draw from. We immediately begin breaking down muscle tissue to access the amino acids our bodies need for countless essential functions.

“There is not really a single scenario I can think of that is clinically relevant where it would be desirable to give up muscle mass,” Attia says emphatically. “Giving up muscle mass because we are falling short on our protein intake would be a strategic error and an unforced error.”

The Reality on the Ground

The gap between what people need and what they actually consume is alarming. Nutritional surveys reveal that most adults consume approximately 0.9 grams of protein per kilogram of body weight daily. Men average about 0.9 grams per kilogram, while women consume even less at 0.8 grams per kilogram. They are barely meeting the inadequate RDA.

This means the majority of adults are walking around in a state of negative protein balance, slowly losing muscle mass year after year. For short term and long term health, this creates a compounding problem that becomes increasingly difficult to reverse with age. Don’t believe it? Ask any 60 year old who easy it is to build muscle. Then ask a 20 year old. It’s a distinction with a very big difference.

The Anabolic Resistance Factor

The protein problem intensifies as we age, but not necessarily for the reasons we might think. Patrick says that a phenomenon called anabolic resistance makes muscle tissue less responsive to amino acids. When researchers give the same protein dose to younger adults and older adults, younger people show twice as much muscle protein synthesis. For older adults to achieve the same benefit, they need to double their protein intake. Double!

But here is where the research gets interesting. Attia shares findings from Dr. Luc van Loon demonstrating that inactivity, more than aging itself, drives anabolic resistance.

In one experiment, researchers placed casts on one leg of young subjects while leaving the other leg free to exercise. After the cast period ended, stable isotope studies revealed significant anabolic resistance in the immobilized leg compared to the active leg. This was in the same young person.

“That’s the clearest demonstration that inactivity is the main culprit,” Attia says. “There’s probably an all things equal age related component as well, but I suspect that inactivity is playing a larger role than aging per se.”

Patrick agrees completely and adds that older adults who engage in resistance training show the same anabolic response to protein as younger adults. The activity itself makes up for age related changes.

“If there’s a public health message in this episode, it really is you should be training,” Patrick says. “That’s the most important thing.” She’s obviously advocating training at adequate levels while also eating sufficient levels of protein.

The Frailty Timeline

The consequences of inadequate protein intake combined with inactivity follow a predictable but often overlooked pattern. Patrick describes how muscle loss typically occurs not as a smooth decline but through discrete events.

“Maybe there’s a fall or maybe there’s just a surgery, a planned surgery or a hip replacement or a knee replacement, and your parents or your grandparents are inactive for many weeks and they lose a lot of muscle mass,” she says. “When this is a younger person, it’s much easier to gain back that muscle mass. It’s not the same with an older adult. Even if you’re engaging in resistance training after, you’re not going to get the same amount of muscle mass back as you’ve lost.” I’ve experienced this personally multiple times based on multiple long hospital stays throughout my lifetime. It’s amazing how fast your body simply digests itself and you shrink. It’s shocking, actually.

These events compound over time. A surgery here, a bout with the flu there, another fall, another period of immobility. Eventually, people reach what Patrick calls a “disability threshold” where mobility becomes severely compromised.

“I think people kind of just don’t follow the timeline where it’s like they see what’s leading up to it and before this sort of catabolic crisis occurs where then they reach this point now where they’ve just lost so much muscle mass from these several events that have occurred where they’re just not mobile,” Patrick says.

Attia connects this to quality of life in powerful terms. While frailty and sarcopenia may not be the leading causes of death compared to cardiovascular disease, cancer, and neurodegenerative diseases, they profoundly impact the quality of our final years. Yet, it’s still considered “normal” aging. It’s not.

“When you think about quality of life, which most people care about at least as much, if not slightly more than length of life, I think frailty just kind of wins the day,” Attia says. “Along with cognitive health, frailty is the thing that seems to determine the quality of your final decade on this earth.”

Despite witnessing frailty in parents and grandparents, people somehow fail to prepare for what is essentially inevitable and preventable. “We’ve been to the movie over and over and over again. We see how it goes. And yet somehow we either don’t think it’s going to happen to us or it somehow still seems abstract because it’s so many years off,” Attia says with frustration. Why? Decades of pervasive and ignorant propaganda coming from our so-called official health and medical authorities who control the funding of science worldwide. Think that’s an overstatement? Right. Visit Okinawa and talk to the 100 year old apple farmer who climbs trees every day to get the apples. Ask him if he watches CNN all day long. Ask him what he eats. Ask him how active he is all day every day.

Finding the Optimal Dose

Moving beyond the inadequate 0.8 grams per kilogram minimum, the question becomes what’s optimal?

Patrick points to a meta-analysis by Dr. Stuart Phillips, who examined 49 controlled trials of adults undergoing resistance training with and without supplemental protein. The findings were striking. People consuming 1.6 grams of protein per kilogram of body weight gained 27% more lean body mass and 10% more muscle strength compared to training alone with lower protein intake.

“That’s supply and demand,” Patrick says. “When you’re training, you’re breaking down muscle. You need protein to support the repair of that muscle and the rebuilding of it.”

Above 1.6 grams per kilogram, benefits continue but at a diminishing rate. Patrick uses an analogy from Phillips: “If you have like a wet washcloth and you squeeze it to get all the water out, most of that water is coming out at 1.6 grams per kilogram body weight. But you can keep squeezing a little and you’re still getting some water out. It’s just sort of marginal.”

For most people training regularly, 1.6 grams per kilogram represents the sweet spot. For high level athletes or those banking muscle mass aggressively, doses up to 2.2 grams per kilogram may provide additional marginal benefits.

The Real World Target: Aim Higher

This is where Attia makes a critical practical point that separates clinical medicine from theoretical guidelines. He recommends his patients target 2 grams of protein per kilogram of body weight daily, but he acknowledges that 1.6 grams is probably sufficient for most people training regularly.

His reasoning is brilliant for its simplicity — real life is messy.

“My patients unfortunately don’t live in labs,” Attia says. “My patients live in this place. It’s called the real world. And in the real world, you can’t always hit your targets. Some days you do, some days you don’t. Some days you’re traveling, some days you’re not.”

If someone aims for 1.6 grams and hits it some days but falls short to 1.2 grams on others, they will average around 1.6 grams. But half their days will be below the optimal threshold. The downside of those low days is asymmetric compared to the upside of high days. You cannot make up for insufficient protein intake the previous day by eating more protein today.

“What I’d really like to do is shift the range so that your low day is 1.6 and your high day is maybe 2.2,” Attia says. “And then guess what? You don’t have days where you are ever amino acid restricted.”

Patrick strongly agrees, adding from personal experience: “I have a hard time hitting my goals too. I’m busy. I miss meals. Sometimes we just have a low protein meal. It’s very difficult if you don’t have a chef preparing your every meal to hit these targets every day.”

The recommendation stands: aim for 2 grams per kilogram daily, knowing that on the inevitable days you fall short, you will still meet the minimum threshold for muscle protein synthesis.

Special Populations

Protein needs vary across different life stages and conditions. During pregnancy and adolescence, requirements increase to support growth. Patrick says that essential amino acids activate IGF-1 and growth hormone, which are both critical for development. Studies in infants and toddlers show that protein sources with more essential amino acids support better growth outcomes.

For adolescents approaching adult body size who are physically active, Patrick says that at least 1.2 to 1.6 grams per kilogram, though she acknowledges the data is less specific for this age group. Attia says that given typical activity levels in kids, they should probably aim toward the higher end of that range.

For people trying to lose fat while maintaining or gaining muscle (an increasingly common goal) protein needs climb even higher, potentially to 2.2 grams per kilogram or more. In an energy deficit, the body is constantly battling the pull toward catabolism, making adequate protein intake crucial for preserving muscle mass.

Attia shares his own experience with body recomposition, describing how he consumed protein shakes outside his eating window during a period of intermittent fasting. He was in a caloric deficit but maintained an amino acid excess, which enabled him to lose fat while preserving muscle. “You can actually do that with liquid protein pretty easily because basically all you’re getting is relatively few calories because you’re just consuming whey protein,” he explains. Weight lifters have know this for decades.

This approach becomes especially important for people using GLP-1 receptor agonists like tirzepatide for weight loss. These medications induce significant appetite suppression, which makes it challenging to consume adequate protein. Patrick and Attia discuss how easy to digest protein sources, particularly liquid shakes, become essential for these patients to prevent the muscle loss that plagued early users of these drugs. The very last thing you want is to lose too much lean mass while trying to lose overall body weight. When finally lose the weight, too many people are left with a rail thin body. That’s not the goal of oftentimes that’s the result from using these drugs.

One critical calculation is that for people who are overweight or obese, protein needs should be calculated based on target body weight, not current weight. Otherwise, the numbers become unrealistically high and are driven by fat mass rather than metabolic needs. It’s important to understand this and to give some time for the body to adjust to the new diet.

Addressing the mTOR Controversy

No discussion of protein would be complete without addressing the elephant in the room — concerns about mTOR activation and its relationship to aging and disease.

Patrick acknowledges this stems partly from aging research showing benefits from protein restriction in laboratory animals. But she is quick to point out the profound differences between lab mice and humans. Humans aren’t mice and that’s important to realize because so much drug research is done on mice and then applied to humans.

“These mice are in a small cage. They are not physically active. They’re not under threat. They’re being fed ad libitum. They’re in a perfectly thermoregulated environment. They’re not being exposed to influenza or COVID or whatever viruses, anything that’s going to take them out for a period of a couple of weeks,” Patrick says. “People are not mice. As we get older, we’re being exposed to infectious diseases, things are going to make us immobile for a period of weeks and that is devastating to us.”

The critical distinction is where mTOR activation occurs. When you exercise and consume protein, leucine and other branched chain amino acids are preferentially taken up by skeletal muscle, where mTOR activation drives muscle protein synthesis. This is exactly what you want.

“You want mTOR active in your skeletal muscle,” Patrick says. “You don’t necessarily always want it active systemically.”

Attia draws a parallel with inflammation. “A constant on state of the inflammatory system would be bad. But of course if you had no inflammatory response that would be also bad. So the ideal state is inflammation when you need it otherwise off.”

The same principle applies to mTOR. “We want mTOR on when it has a job to do and we want it relatively silent when we don’t,” Attia says.

Patrick points to compelling human data that contradicts concerns about protein intake, such as in elite athletes, including Olympic athletes and professional athletes in major sports leagues, where they consume at least 2 grams of protein per kilogram daily. They live on average five years longer than the general population.

“Clearly protein isn’t killing them,” Patrick says. “In fact, they’re living longer than the general population. It comes down to supporting exercise. Exercise is the king. Exercise is the most important thing, but you need protein to support that physical activity.”

Creatine: Supplement for Brain and Muscle

Aside from total protein and getting all the essential amino acids in their proper rations, Attia and Patrick also discussed at length the need for creatine. Patrick’s journey with creatine began not in a laboratory, but in her own training regimen. After realizing she had neglected resistance training in favor of endurance work, she hired a personal trainer and increased her strength training from 30 minutes per week to three hours. That’s when creatine entered the picture.

“I finally realized that I wasn’t doing enough training, resistance training,” Patrick says. “And so I got a trainer. I have a personal trainer now. I’m doing resistance type training. I do like a CrossFit type training for at least three hours a week.”

What makes creatine particularly interesting is its research pedigree. Attia says from his own experience, creatine has been studied extensively for decades. He recalls that even 35 to 40 years ago, teenage athletes were consuming creatine based on advice from bodybuilding magazines and supplement store employees. The difference today is that we have a much more sophisticated understanding of how it works and what doses are actually effective.

How Creatine Works in Muscle

Most people know creatine is stored in skeletal muscle as creatine phosphate, where it serves a critical function to rapidly recycle ATP, the major energy currency in cells. This allows for quicker energy production, which becomes relevant during high intensity interval training, resistance training, and even endurance training because it decreases recovery time. And that’s critical as we age because recovery time skyrockets over time after workouts. Remember when you were 20 and you recovered in a day or so from a stressful workout? Try that at 60. You may need a week.

We make creatine endogenously. Our livers produce about one to two grams per day. We can also obtain it from diet, primarily from meat, with beef being the richest source. Vegetarians rely entirely on their endogenous production of one to two grams daily, which is why they tend to be the population that benefits most from creatine supplementation.

The traditional recommendation has been five grams per day, which is enough to saturate muscle tissue over about three to four weeks even for large body builders. This is where the old “loading phase” recommendations came from. Athletes wanting immediate saturation would take much higher doses (like the 30 grams Attia recalls from his youth), but Patrick says this is unnecessary unless you’re competing imminently.

“Most people don’t have to do that,” Patrick says. “The problem is unless you’re doing some competition and you need it right then and there, generally speaking, it’s just not necessary and you really just increase the risk of GI distress.” Thirty grams a day can be a challenge unless the doses are spread out substantially. Otherwise, you’ll get gas and gut pain.

The Exercise Performance Evidence

The data on creatine for exercise performance is extensive and consistent. Patrick explains that creatine essentially improves your exercise performance by allowing you to do one to two more reps or increase your training volume because you’re recycling energy quicker.

“It’s not like the creatine itself is acting like protein,” Patrick says. “It’s not increasing muscle protein synthesis if you’re just a couch potato. You have to do the work.” Again back to exercise, which is the basis of so many recommendations. The human body was designed to move. So, move. A lot.

The reason people increase muscle mass and strength when supplementing with creatine is because they’re able to do more work. For Patrick’s CrossFit training, with its explosive leg movements and high intensity intervals, the effect was noticeable. She acknowledges there’s probably some placebo effect mixed in, but the research is clear enough that she’s confident in the real benefits. It’ll be interesting to see as this research matures whether it’ll be acknowledged by the medical authorities. I predict it wont. Not for a very, very long time. I’m not waiting. Are you?

Creatine for the Brain: The Emerging Frontier

While the muscle benefits are well established, Patrick recently has become increasingly fascinated with creatine’s effects on the brain. This represents a newer area of research, and it’s where the dosing recommendations change significantly.

The brain makes a small amount of creatine on its own, somewhere between one to three grams daily. But here’s the challenge: muscles are very greedy. When you consume creatine, your muscles consume it immediately, especially if you’re training. A German study using isotope labeling found that you need to double the standard dose to get creatine into the brain effectively.

“The 10 grams was where creatine was now not rate limited,” Patrick says.

This finding fundamentally changes the supplementation strategy for cognitive benefits. At five grams per day, you might saturate your muscles, but you’re not getting meaningful amounts into your brain. At 10 grams per day, you cross that threshold.

When Creatine Shines for Cognition

Patrick emphasizes a critical point: creatine for the brain works best in the background of stress. And who doesn’t have stress! This isn’t about taking creatine and suddenly becoming smarter. It’s about resilience under challenging conditions, which for most people is pretty much normal life.

“What I mean by stress is sleep deprivation, psychological stress, like you have an exam, marital stress, emotional stress, sleep deprivation is a big one, neurodegenerative disease or anything that’s compromising brain function,” she says. “That’s where creatine really shines in terms of cognitive function.”

The brain consumes 20% of our total caloric intake despite weighing less than 2% of body weight. It’s one energy hungry organ! Giving your brain extra creatine, which can recycle energy quicker, makes sense particularly when you’re using more of that energy under stress conditions.

Studies on creatine and cognitive function typically look at processing speed and memory, using standard batteries of tests. The results show benefits, but almost always in the context of some form of stress. Sleep deprivation studies are particularly compelling.

“There’s been a few studies that have shown people that are sleep deprived, if you give them (this was on a per kilogram body weight basis, so I think total it was like 20 to 25 grams of creatine) if they were sleep deprived and given that creatine, not only did the cognitive deficits that usually occur when you’re sleep deprived not occur, but their cognitive processing speed was improved more than baseline,” Patrick says.

She’s quick to acknowledge these are small studies and we can’t hang our hats on them alone so more research is needed. But the pattern is consistent across multiple studies. Older adults seem to benefit from creatine supplementation, with aging itself representing a form of stress on the brain.

Even preliminary research in Alzheimer’s disease patients shows promise. A pilot study gave patients with Alzheimer’s 20 grams of creatine and found improvements in cognitive function compared to placebo. When those same patients exercised, they also improved strength and lean body mass.

Attia frames the most interesting question perfectly. It’s prevention. While helping people who already have Alzheimer’s is valuable, the real opportunity lies in using creatine consistently 10 or 20 years earlier in people susceptible to metabolic pathways that may lead toward dementia.

“When you take that individual who is most susceptible to the metabolic path towards dementia and 10 years earlier or 20 years earlier, you’re giving them a substrate that is augmenting ATP creation, I get it,” Attia observes. “That’s the hardest thing to study. That’s also the single most important question in my mind.”

Patrick’s Personal Protocol

Patrick’s current regimen reflects her confidence in the brain benefits. She takes 10 grams per day, split into two five gram doses, mostly before noon. She’s noticed that she no longer experiences afternoon sleepiness when she maintains this dose. When she only gets five grams, the sleepiness returns. She recognizes that this is anecdotal so more research is needed.

“Now again it could be complete bias and who cares if it’s not, because it’s physiologic,” she says. “It’s a biological mechanism that’s working for me.”

When dealing with extreme stress like jet lag from international travel, she increases to 15 to 20 grams per day. She takes the doses in water or tea, finding this easier on her digestive system than taking larger amounts at once. I’ve taken 20 grams and found it difficult on my gut, so it’s makes sense to spread out the doses and increase slowly to find out if you body is able to digest these higher amounts. Attia agrees with the practical approach of splitting doses, noting that 10 to 20 grams in one sitting would probably cause GI issues for many people.

Dosing for Different Populations

For adults training regularly and interested in both muscle and cognitive benefits, Patrick recommends 10 grams per day as the baseline. This ensures muscle saturation while also getting creatine into the brain across the blood brain barrier.

For children and adolescents, the research shows benefits for agility and speed. Patrick gives her sons approximately 2.5 grams daily, based on a recommendation of about 0.1 grams per kilogram of body weight for younger individuals.

When Attia asks about his 17 year old daughter who trains hard with cross country, track, and weight room work, Patrick doesn’t hesitate. “If it were me, I would do 10,” she says. The combination of intense studying and athletic training creates exactly the kind of stress conditions where creatine provides benefits.

Choosing Quality Products

Patrick’s primary concern when selecting creatine is NSF certification, which involves rigorous testing to ensure there’s no lead contamination or heavy metals that can hitchhike on supplements. While Creapure (a particularly pure form of creatine monohydrate) is good, NSF certification provides additional assurance.

The form matters too. Stick with creatine monohydrate, which has the most research behind it. And avoid gummies entirely. A member of Attia’s team discovered through third party testing that 95% of creatine gummy products contained essentially no creatine monohydrate despite label claims.

“Gummies, yeah, unless you can find a third party tested gummy that actually has the amount of creatine monohydrate in it that’s labeled that says on the nutrition facts label I would avoid a gummy,” Patrick says.

And capsules present a different problem. You’ll need to take so many capsules to reach 10 grams. The powder form remains the most practical option.

Debunking the Kidney Myth

One persistent concern about creatine has been kidney health. This stems from confusion between creatine supplementation and creatinine levels in blood tests. When you supplement with creatine, creatinine levels can increase, which some physicians interpret as kidney problems.

Attia provides a simple solution for physicians: use cystatin C instead of creatinine to estimate glomerular filtration rate (GFR). “Cystatin C is a far more accurate way to measure and estimate GFR and you don’t have this problem of getting the confounded creatine levels increased,” he says.

Patrick agrees, noting that the claimed kidney problems from creatine are unfounded. You just need to inform your physician that you’re supplementing so they can interpret lab results correctly or use the more appropriate test. A personal note: Good luck educating your physician on any of this. Unless they are schooled on this research, they’ll balk every time because most doctors just follow the government’s guidelines. Give it a try, though. It’s fun to argue with doctors. Most of them get pissed jet quick when you show up with some expertise. This is especially true in the United States given their education.

The Bottom Line on Creatine

Patrick summarizes her position clearly: “I think that there’s really no downside to doing 10 grams a day.”

The evidence for muscle benefits is solid after decades of research. The evidence for brain benefits is emerging and compelling, particularly for resilience under stress, sleep deprivation, and aging. The safety profile is excellent. And the cost is minimal.

“I’m all in on the creatine,” Patrick says. “My creatine budget literally the household creatine budget just went up 4x,” Attia says, after deciding to give it to his entire family.

For a supplement that has been studied for 40 years with consistent benefits and no identified harms, creatine represents one of the rare cases where the science actually supports the hype, yet the authorities remain silent about these benefits. The key is understanding the proper dosing. Five grams daily for muscle saturation, but 10 grams daily if you want the cognitive benefits as well.

As Patrick experienced firsthand in her training and Attia witnessed in decades of research, sometimes the old supplements really do work. We just understand them better now.

Finally

The evidence is clear and converging from multiple lines of research. The current protein recommendations are too low for maintaining muscle mass, preventing frailty, and supporting optimal health across the lifespan.

For total protein, Attia and Patrick recommend that the minimum should be raised from 0.8 to 1.2 grams per kilogram of body weight. For people who are training regularly (and everyone should be training regularly) the target should be bumped to 1.6 grams per kilogram. And for practical purposes in the real world where consistency is challenging, aiming for 2 grams per kilogram provides a buffer that ensures you never fall below the threshold where muscle protein synthesis is compromised.

As Attia says, “If new data emerge, I’m always happy to change my mind. I’ve changed my mind about so many things over the past 10 years. But I’m going to stand by my recommendation. Two grams per kilogram per day.” That’s more than people think. You really have to pay attention to every meal to make sure you’re getting enough.

Beyond total protein, consider adding creatine to your regimen as well. The science here is equally compelling. Five grams daily will saturate your muscles and improve training performance. Ten grams daily appears necessary to get meaningful amounts into your brain for cognitive benefits, particularly under conditions of stress, sleep deprivation, or aging. After 40 years of research, creatine remains one of the safest and most effective supplements available. Patrick’s conclusion is simple: “I think that there’s really no downside to doing 10 grams a day.”

This entire discussion on protein is serious. Muscle mass is not just about aesthetics or athletic performance. It’s about being strong, maintaining independence, preventing disability, preserving cognitive function, and ensuring the quality of your final decades. Building and maintaining muscle is one of the most important investments you can make in your future self. Say it again: “Building and maintaining muscle is one of the most important investments you can make.” If you dispute this, visit any elderly person in any hospital in any country in the world. What you will see isn’t “normal” aging. It’s sarcopenia. And it’s largely preventable.

“You must steal yourself for what is coming,” Attia says. “You must build up as much muscle mass and strength and cardiovascular fitness as you can muster because the longer you can ride it out, the better you’re going to be.” He’s directly commenting about your elderly years here.

This is really simple. Train consistently, eat optimal levels of protein at every meal, add creatine supplementation for both physical and cognitive benefits, build your physiological reserve of muscle immediately and consciously, and don’t stop. The rainy day is coming. The only question is whether you’ll be prepared. And finally, always question “the science” that says otherwise. Do your own research. Prove yourself right or wrong. Science isn’t something to be followed. It’s to be questioned. To not know this simple principle is to not have a functioning brain.

Six Strategies for Better Learning

The pace of change today demands constant learning, whether for career advancement, upskilling in fast-moving fields, or mastering new personal interests. Many of us wonder if there is a right way to learn so knowledge truly sticks. Recent research points to clear answers.

A interesting paper called Teaching the Science of Learning by Yana Weinstein, Christopher Madan, and Megan Sumeracki, published in Cognitive Research: Principles and Implications, offers a science-based roadmap for effective lifelong learning. Decades of cognitive science and educational research support the strategies they recommend, and their guidance extends well beyond the classroom.

Why Evidence-Based Learning Strategies Matter

Traditional methods like cramming, rote memorization, or repeated review provide an illusion of mastery, but often result in rapid forgetting. Real learning means building a durable, flexible knowledge base that can be called upon in real situations, whether at work or in life.

Weinstein and colleagues highlight six strategies that consistently improve retention and transfer: spaced practice, interleaving, retrieval practice, elaboration, using concrete examples, and dual coding. Below, you’ll find each described along with actions any professional or self-directed learner can apply.

1. Spaced Practice: Distribute Review Over Time

Spaced practice involves spreading study or review sessions over time, rather than massing them together. Research shows knowledge reviewed at intervals is remembered longer with less total effort.

Why it works:

Spaced practice allows memory “retrieval strength” to wane before boosting it again, which leads to better storage in long-term memory.

Actions:

  • Build recurring review into your workflow. Use calendar reminders to revisit topics or skills (e.g., first after one day, then three, then a week).
  • Mark when you learn something new, and schedule check-ins to revisit it later.
  • Use tracking tools (digital or print) to log what you’ve reviewed and when.
  • Leverage digital flashcard systems with spaced repetition (e.g., Anki, SuperMemo) for knowledge that builds on itself, but verify compliance with your organization’s security and privacy policies if using external apps.
  • Blend current tasks or cases with samples from prior projects to reinforce older knowledge.

2. Interleaving: Mix Related Skills and Concepts

Interleaving means alternating practice or review between related skills, concepts, or problem types instead of focusing on one at a time.

Why it works:

Switching between related topics sharpens your ability to discriminate between them and select the proper approach for each, boosting adaptable expertise.

Actions:

  • Alternate work tasks that use related skills (e.g., switch between the analysis and writing phases of a report instead of batching all analysis first).
  • If practicing technical skills, intermingle exercises on different but related techniques in one session.
  • In training, mix case studies or scenarios from multiple categories rather than working through each category in sequence.
  • For language or communication, alternate between different types of correspondence or customer scenarios.
  • Use professional e-learning platforms or in-house tools that automatically vary topics or assessment items across reviews.

3. Retrieval Practice: Actively Recall Information

Retrieval practice is the act of recalling information from memory, not just rereading or reviewing it passively. This dramatically boosts retention.

Why it works:

Retrieval strengthens neural pathways and makes the information more accessible in the future. Low-pressure recall exercises reduce stress and encourage active engagement.

Actions:

  • After a meeting or training, jot down key points and action items from memory before referencing any notes.
  • Create end-of-week or end-of-project knowledge checks, summarizing recent learnings without your materials in front of you.
  • Use flashcards or “quiz yourself” routines as part of continuing professional development.
  • Practice describing complex procedures, explaining them as if to a colleague, without referring to a manual.
  • Set up peer Q&A sessions where team members challenge each other to recall key facts or principles relevant to your organization.
  • Experiment with AI tools to generate personalized quizzes.

4. Elaboration: Link New Knowledge with What You Know

Elaboration refers to the process of connecting new information to prior knowledge and making it personally meaningful.

Why it works:

By asking yourself “how” and “why” questions and drawing analogies to familiar concepts or real scenarios, you deepen your understanding, making it easier to retrieve and apply knowledge later.

Actions:

  • After learning a new tool or concept, write or speak out loud about how it integrates with what you already know.
  • When presented with a new procedure, compare it to previous processes and note similarities or differences.
  • Keep a reflective learning journal: After completing new coursework or reading, sum up the day’s biggest learning in your own words and relate it to past experience.
  • In project debriefs, explicitly link lessons learned to prior projects.
  • When facing a challenging problem, articulate the potential causes and solutions aloud or in writing, referencing knowledge from other fields or prior roles.

5. Concrete Examples: Anchor Ideas in Real Situations

Using concrete examples — specific, real-world cases or analogies — makes abstract concepts memorable and easier to understand.

Why it works:

Concrete information is more readily assimilated and retained. Comparing multiple examples enhances the ability to apply an idea in new situations.

Actions:

  • Illustrate complex principles or models by referencing actual projects, known workplace situations, or well-defined industry scenarios.
  • When learning new regulations or policies, anchor them in relevant, concrete events from your organization’s history.
  • Create job aids or reference sheets using one or more vivid, context-appropriate examples for each key concept.
  • During presentations or training, pair abstract slides with brief case summaries to reinforce understanding.
  • Whenever possible, develop alternate examples that differ on the surface but share the same underlying structure.

6. Dual Coding: Combine Verbal and Visual Information

Dual coding is about presenting material using both words and visuals (charts, diagrams, infographics, sketches) to reinforce learning.

Why it works:

Engaging both verbal and visual channels supports deeper learning and increases recall, provided both representations are clear and meaningfully related.

Actions:

  • Supplement written reports with diagrams, flowcharts, or annotated screenshots to illustrate key points.
  • During meetings or presentations, support spoken points with slide visuals — charts, figures, or concept maps.
  • Capture processes or workflows visually (e.g., draw swimlane diagrams, mind maps) while also describing them in text or speech.
  • After reading a policy or technical manual, attempt to sketch the process or concept with labels and brief annotations.
  • When reviewing digital training, pause to create your own diagrams depicting major processes or relationships.

Combining Strategies for Maximum Effect

Research shows these strategies interact synergistically, so use them together to leverage results. Retrieval practice spaced over time solidifies knowledge. Interleaving concepts keeps skills flexible. Concrete examples and dual coding together make complex information more accessible and memorable. Elaboration will help you transfer abstract theories into daily practice.

Experiment with integrating these techniques in your study sessions, work meetings, or professional development routines. Share your approaches with peers and teams or even online. Evidence-based learning is for everyone. And as these principles spread, organizations and individuals will find it easier to learn, adapt, and excel in an ever changing world.

UnVoxxed Hawaii (LavaOne) January 2019.
UnVoxxed Hawaii (LavaOne) January 2019.

Exploring Six Degrees of Separation

I’ve always been fascinated by how connected we are. I’ve met some famous people in totally random situations, like Mike Love from the Beach Boys at a hotel in Washington, DC, and George Shultz, who was Reagan’s Secretary of State, in an elevator in San Francisco. Also, one day while running along The Charles River in Boston I had a conversation with a homeless man who was from Bari, Italy, where my grandparents were from. On business trips around the world, I’ve met random people on trains and planes who grew up near me in New York. 

When I moved to Sun Microsystems in 2000 in Silicon Valley, that’s when I really learned about the scale of massive human networks via my work on Free and Open Source Software Communities (FOSS). That experience hooked me. So when I watched Derek Muller’s Veritasium video, “Something Strange Happens When You Trace How Connected We Are,” it really hit home. This is not just math. It’s the invisible webs linking people, ideas, diseases, and behaviors. With simulations and real-world examples, Muller unpacks the six degrees of separation concept, showing why our world sometimes feels small despite eight billion people. It’s a deep dive into network science that reshapes how I view communities, opportunities, and my own connections. As someone who’s spent decades building FOSS communities, I see parallels in how software developers form networks. Here’s my take.

The Classic Hook: Six Degrees Explained

The video opens with a striking story from 1999. A German newspaper, Die Zeit, challenges a falafel salesman and former theater director, Salah ben Ghaly, to connect to his favorite actor, Marlon Brando. Through a chain of friends, family, and acquaintances, all on a first-name basis, they do it in six steps. Ben Ghaly’s California friend works with a woman’s boyfriend, who’s linked to a sorority sister of the daughter of the producer of Don Juan DeMarco, starring Brando. Six hops. Muller’s point is clear. This is not a one-off. In a world of eight billion, any two people can likely connect in six steps or fewer. But how does this work? And what does it mean for us?

Muller frames it as a puzzle. If connections were random, say each of us with 100 friends worldwide, the math checks out. One person’s 100 friends, times their 100, and by step five, you’re at 10 billion, overshooting Earth’s population. Straightforward. But real life is not random. We cluster geographically. Most friends live closely nearby and know each other personally. Picture eight billion people in a circle, each linked to 50 neighbors on either side. Connecting opposites takes 40 million steps on average. Six steps? No, you’re nowhere. Yet the world feels small. That’s the mystery.

Network Scientists and Shortcuts

Muller introduces Duncan Watts and Steven Strogatz, network scientists who tackled this in the mid-1990s with their small-world model. They start with a regular network with nodes in a circle tied to nearby neighbors, which mimics real social clusters. Then they add shortcuts, which are random links to distant nodes. In a 1,000-node simulation, rewiring just one percent of links drops separation from 50 to 10. Scale to eight billion? Only three shortcuts per 10,000 friendships bring it to six degrees. Clustering stays high, but the world shrinks jet quick.

Strogatz sums it up. The question is not why the world is small, it’s how could it be otherwise? I’ve felt this myself. A random meetup or conference chat creates a shortcut, putting me one step from a developer in Amsterdam or a startup founder in Tokyo. The video connects this to a concept in sociology called the strength of weak ties. Jobs often come from acquaintances, not close friends since weak links bridge distant networks. Muller suggests attending random events to boost these connections. I’ve landed opportunities this way, showing up to a meetup where I knew no one, only to meet someone who opened new doors. However, randomness matters. I got my job at Sun Microsystems by applying blindly to HR! I didn’t know anyone at Sun at the time. You never know what happens when you move in one direction or another. 

Proving the Small World

Watts and Strogatz tested their model on real data. In 1996, with no Google, they analyzed the nematode Caenorhabditis elegans worm’s neural network, which has 282 neurons with an average of 14 connections. Arranged linearly, it would take 14 steps to connect extremes. In reality? Just 2.65 degrees. Hollywood’s 200,000 actors average under four degrees, cue that old Kevin Bacon game. U.S. power grids also exhibit small-world properties, with key substations acting as connectors. Their 1998 Nature paper became a sensation, now with 58,000 citations, outpacing landmark works on the Higgs boson or DNA. The irony? It seems that a paper on networks does indeed spread like wildfire.

Muller and Strogatz explore unexpected applications of their small-world model, which reveals its reach beyond theoretical networks. For instance, they recount a surprising call from the FBI, which sought Strogatz’s expertise to apply network science to forensic criminology. The agency was investigating “hair and fiber” networks to calculate probabilities of secondary transfers in cases where, say, a fiber from a suspect’s clothing might end up on a bus seat, then transfer to another person, which can complicate crime scene analysis. By modeling these connections as a network, investigators could better estimate the likelihood of such transfers and refine their approach to evidence. Another example touches on epidemiology, where small-world principles help trace contact networks in disease outbreaks, which helps researchers identify key individuals who might unknowingly spread pathogens. These examples highlight how our interconnected world, while powerful, can amplify both solutions and problems.

Hubs and the Dark Side of Connectivity

The video shifts to disease spread. Simulations show a regular network takes 73 steps to infect 100 nodes. Add 10 percent shortcuts? It’s 26 steps. Fully random? 25. For billions, though, less than one percent shortcuts suffice. This echoes global pandemics with air travelcreating shortcuts that push spreading viruses fast.

Albert-László Barabási enters the discussion, drawing from his groundbreaking work on the internet in 1998. At that time, the web had around 800 million pages, yet any two could be connected in just 19 clicks on average. This was puzzling because it didn’t align perfectly with Watts and Strogatz’s small-world model, which focused on ordered networks with random shortcuts. Instead, Barabási identified a different structure: scale-free networks. These connections don’t follow a normal bell curve distribution, where most nodes have roughly the same number of links, like people’s heights clustering around an average. Rather, the web exhibits a power-law distribution — a steep initial drop followed by a long tail. This means most pages have few links, but a small number of super-connected “hubs,” like Yahoo or early search engines. They link to thousands or even millions of others. These hubs make the entire network navigable in so few steps and turn vast systems into small worlds not through random shortcuts alone, but through unequal connectivity.

Barabási explains how this emerges: through two key principles — growth and preferential attachment. Networks don’t appear fully formed. They expand over time. The web started small in the early 1990s and grew to trillions of nodes one page at a time. When a new node joins, it doesn’t connect randomly. It’s biased toward popular nodes. You’re more likely to link to a well-known site like Wikipedia than an obscure blog because it’s visible and useful. This “rich get richer” effect, called preferential attachment, naturally creates large hubs. In simulations with his colleague Réka Albert, they start with a few connected nodes and add new ones that preferentially link to those with more connections. Over time, a few nodes become massively dominant, mirroring real networks.

This scale-free property isn’t unique to the web; it’s universal in complex systems, from social media follows to airline routes.

Real-world hubs are everywhere. Take Chicago’s O’Hare airport, with over 200 direct flights. It’s a massive travel hub. But when storms hit in August 2025, 280 flights were canceled, impacting six other American airports. Ecosystems rely on keystone species like Atlantic cod. Remove them, and food webs collapse. In cells, ATP hubs drive reactions. In brains, the prefrontal cortex links functions. Barabási notes that once hubs are there, they fundamentally change the system. They’re efficient but fragile, useful for drugs targeting bacteria hubs but disastrous for pandemics.

Thailand’s 1990s HIV crisis shows hub power. Broad public health campaigns failed, but when officials targeted brothels as hubs and mandated condoms that cut infections by over 50 percent in military recruits, which prevented five million cases by 2013. Smart strategyto target the inherent weakness of large hubs. 

Behavior in the Net: Cooperation vs Chaos

The video also delves into how networks influence human behavior, using the Prisoner’s Dilemma, a cornerstone of game theory, to illustrate this. Imagine two players, each deciding whether to cooperate or defect in a scenario involving coins as rewards. If both cooperate, they each earn a moderate reward, say 3 coins. If both defect, they get less, maybe 1 coin each. But if one cooperates while the other defects, the defector scores big with 5 coins, and the cooperator gets nothing. From a purely rational, one-time perspective, defecting seems like the best choice — you either win big or minimize your loss. Yet, this leads to both players defecting, earning less than if they had cooperated. This paradox highlights a tension in human interactions: individual gain versus collective benefit.

The dynamics shift when the game is played repeatedly, simulating ongoing relationships like those in social or professional networks. Here, a strategy called “tit for tat” emerges as powerful and effective. In this approach, you start by cooperating and then mirror your opponent’s previous move — cooperating if they cooperated, defecting if they defected. This simple rule fosters trust and punishes betrayal, which encourages long-term cooperation. Political scientist Robert Axelrod ran famous computer tournaments in the 1980s, pitting various strategies against each other in repeated Prisoner’s Dilemma games. His findings, detailed in his book The Evolution of Cooperation, showed that “nice” strategies like tit for tat consistently outperformed selfish ones. Why? Because cooperative strategies build trust over time, especially in clustered networks where players interact repeatedly with the same neighbors. These clusters, like tight-knit communities, create environments where cooperation can thrive, as defectors are gradually outcompeted or isolated.

Watts and Strogatz simulated this on a network. In a regular setup, cooperation spreads from clusters. Add shortcuts? Defectors dominate. A critical threshold exists, more shortcuts, zero cooperation. Strogatz explains that clumps foster trust, global nets amplify toxicity. This mirrors the phenomenon of online keyboard warriors as the internet erases community pockets and fuels negativity. Social media connects but often divides and spreads harm. It seems humans compete and cooperate depending on the situation. This is a key lesson for people who build large communities for a living. 

Watts’ real-world experiments puzzled him. Network structure seemed neutral at first with cooperation as likely in clustered or random setups. But digging deeper, he found that clustered networks amplify copying. If someone cooperates by chance, others follow, but defection spreads just as easily. Over many games, these balance out. Allow players to choose connections? Cooperation surges. Muller’s takeaway. Curate your network, avoid negativity. These insights resonate with my own experiences.

My Take: Power in the Weave

This video is an eye-opener. We’re constantly shaping our networks through shortcuts, hubs, and choices. One action can tip the system. Steve Jobs said those crazy enough to think they can change the world do. This video shows how. Simulations, linked in the video, let you explore disease spread and hub growth to illustrate these concepts. 

In my work building FOSS communities, like through Duke’s Corner Java Podcast, I see these principles in action. Software communities are networks. Hubs like the Java Champions and Java User Groups or OpenJDK contributors connect thousands of developers. Shortcuts? A student’s pull request on GitHub links them to a global project. JCrete’s unconference gatherings and hacking sessions fosters life-changing career connections since such high value developers participate. I’ve interviewed hundreds of developers, from user group leaders to enterprise architects, and their stories echo this video. Collaboration, contribution, and shared purpose drive vibrant ecosystems, whether a local meetup or a global project spanning dozens of countries.

But there’s a flip side. Online toxicity, like flame wars in project issues, thrives in unclustered, chaotic nets. The fix is intentional community building. Encourage participation, foster leadership, ensure transparency, just as Watts’ experiments showed choice promotes cooperation. Every developer can shape the network. A single commit or meetup talk can spark a movement, connecting you to mentors, peers, and opportunities. As I’ve learned from 20 years in FOSS, contributing to communities like Java’s is not just coding. It’s building networks that fuel innovation and careers. Next random invite? Take it! Contribute to a project, join a user group, share your story. It might shrink your world or spark something big. Watch the video and rethink your connections. Communities are networks, and we all have a role in weaving them stronger.

Fukushima nuclear protests in Tokyo in 2011.
Fukushima nuclear protests in Tokyo in 2011.

Redefining Aging: Wisdom Wins

The Myth of Cognitive Decline: Non-Linear Dynamics of Lifelong Learning
Michael Ramscar, Peter Hendrix, Cyrus Shaoul, Petar Milin, Harald Baayen

I’ve always had a hunch about this. Back in my 20s, I was jet quick. Answers came fast. Decisions snapped into place. Now I’m slower, no doubt, but my brain’s juggling a ton more info. Massively more! And my memory is so much more comprehensive now. I also notice I’m not just reacting these days. I’m sifting through years of experience, global connections, interesting new ideas, and some really painful lessons learned since birth. And that takes some time.

I see this process everywhere now. Kids fly through problems with fresh, uncluttered minds. Young adults start to layer on complexity and options and slow down just a bit. Older people, though, like my parents or my older mentors, pause much longer but drop insights that blow me away with their depth. How do they know that? Where did that come from? These patterns are obvious when you watch people wrestle with intellectual challenges, whether coding a complex algorithm, debating philosophy in a little local cafe, arguing over sports teams, or solving intractable real world geopolitical problems.

I stumbled on the article above while digging into learning techniques for some projects on developer training, networking, and memory. It confirms what I’ve felt for years. This isn’t just some theory. It’s a wake up call. And no one talks about it!

A New Spin on Aging

The article flips the script on how we think about our aging brains. Everyone assumes we just fall apart mentally as we get older, right? Wrong. The authors tackle the aging as decline myth head on, pulling from the Greek story of Tithonus, who was immortal but stuck without youth, to slam the idea that growing older means mental breakdown. And they’re not messing around:

“Many of the assumptions scientists currently make about ‘cognitive decline’ are seriously flawed and, for the most part, formally invalid.”

They say slower reaction times or shaky test scores don’t mean your brain’s failing. They’re the natural result of continually laying knowledge over a lifetime. It’s not decline. It’s just your brain working overtime parsing all that wisdom.

With 72 million Americans hitting 65 by 2030, we need to get this right. The authors say buying into the decline myth wastes human potential:

“The myth of cognitive decline is leading to an absurd waste of human potential and human capital.”

I love that assertion in the face of the media scaring us with “your brain’s doomed!” stories. These guys are pushing back hard, saying we need to rethink how we support older people. Aging isn’t the problem. Our misconceptions are.

Breaking the Decline Myth

The core idea here is that your brain doesn’t just stay the same forever. Psychometric tests, those standard measures of cognitive ability, miss the mark because they ignore how experience shapes us over time. Learning tunes out useless noise and crams your head with more info, which takes longer to parse. Language is a big deal here. Words follow a long tail pattern, where common ones rule but rare ones pile up over time. Traditional tests miss this growth, so older people seem slower. Of course the are. They’re processing more!

Could it be that simple? The authors point out that current tests miss how our knowledge grows over time, and that mainstream aging researchers, whatever theories of learning they’ve drawn on elsewhere, haven’t controlled for the sheer amount of information an older brain has to search through. That gap is what’s kept the science off for so long.

And the authors clearly nail the paradox of this experience:

“Learning is a discriminative process that serves to locally reduce the information processing demands associated with specific forms of knowledge and skill… [but] age and experience will inevitably increase the overall range of knowledge and skills any individual possesses, increasing the amount information in (and complexity of) his or her cognitive systems.”

Translation? Your brain’s sharper but busier. They sum it up late in the paper:

“The results reported here indicate that older and younger adults’ performance in psychometric testing are the product of the same cognitive mechanisms processing different quantities of information: Older adults’ performance reflects increased knowledge, not cognitive decline.”

To me that’s a nice big fat middle finger to decades of so-called settled science. No. The science is never settled. You gotta question it, like these authors do with some serious attitude.

Simulations and Real Life

The authors use an interesting data collection tool, the Naive Discriminative Reader, to simulate how brains handle tasks like picking out words. Models with more data, mimicking a lifetime of experience, get pickier with rare words and vary more, just like older people in studies. Same deal with non lexical tasks like letter classification. Slower times come from bigger mental databases, not a broken brain. Paired associate learning, where you link words like baby and cries, shows older adults deeper knowledge makes hard pairs trickier, not memory loss.

Name recall? That’s a mess because names got crazier since the 1880s. American first name complexity jumped from 100 to over 2,000 options. Simulations say it takes half a second longer to recognize names over a lifetime. The authors throw a curveball:

“Confounding name recall problems with cognitive decline is akin to asking older adults to accept personal responsibility for a social problem.”

Ouch! Even tasks like the COWAT FAS test, where older people often shine, support their point. Experience helps you nail word retrieval despite proper noun chaos.

On brain science, the authors are bold:

“Except in the case of neurological diseases where there is evidence of pathology, there is no neurobiological evidence for any declines in the processing capacities of healthy older adults.”

So, without models tying brain changes to behavior, those decline claims seem shaky.

Why This Matters

This article’s a wake up call. Meta analyses often flop because small sample sizes mess up their conclusions.

There’s one more bit worth knowing about because it answers the obvious skeptical question. If cognitive decline isn’t real, why does it show up in study after study? The authors dug into a meta-analysis of 134 studies using the FAS fluency test and found something they hadn’t expected. The size of the study mattered more than anyone realized. In small samples, the kind they call “artisanal,” performance barely changed with age at all. Thirty-five-year-olds and sixty-five-year-olds scored about the same. It was only in the larger studies that the familiar decline showed up, and it grew steadily as the samples got bigger. That’s a strange thing for a real biological decline to do. It suggests some of what we call cognitive decline might be an artifact of how psychology studies are run, not a fact about how brains age normally.

Same deal with retirement: less variety in daily life can jumble memory, not because your brain’s failing, but because learning and memory thrive on context. The authors want us to dump the myths that waste talent and build models to tap lifelong intelligence. Remember this blunt statement from earlier in the article:

“The myth of cognitive decline is leading to an absurd waste of human potential and human capital.”

That’s a paradigm shift, not just for better science, but for creating spaces where wisdom shines. Understanding learning’s ups and downs can help people manage memories better. So, next time someone says aging means decline, tell ‘em to read this research from the authors above. Knowledge acquired from years of experience isn’t the problem. It’s the superpower.

And always question science. Question everything. Even this research that questions the previous research should be questioned. The science is never settled.

Jim Grisanzio at Jfokus in Stockholm in April 2022.
Jim Grisanzio at Jfokus in Stockholm in April 2022.

Boys Building Rockets

Here Kary Mullis explains how little boys build rockets. Loved every word!

Imagine how different our lives would be now had he not died in August 2019 at 74. Such a loss for science. Such a loss for all of us around the world. Mullis was fearless. He would have engaged Gates and Fauci actively and directly regarding COVID — especially regarding PCR, which was his invention that earned him the Nobel Prize for Chemistry.

An Empty Kansai Airport in 2022

Japan didn’t really open until mid 2023.

I took four international trips in 2022. This is what it looked like at the Kansai International Airport in April and July 2022. Totally empty. But at least I had plenty of space on the bus to the airport! Since the international terminal was still closed in Osaka, I couldn’t leave the country from there but instead had to walk downstairs to the domestic terminal and fly locally up to Tokyo. Then I could leave Japan from there. The international terminal in Tokyo looked pretty much the same, btw. Domestic in Tokyo was full, though. You know, because science.

Also, returning to Japan during this time was a nightmare. Most of Tokyo’s Haneda International Terminal was closed. It was eerie. It took 5 hours from landing to getting out of the airport with all the COVID processing going on. Heck it took an hour just to get out of the damn plane itself! So much for Japanese efficiency and their scary bright red “Green Pass” app, eh? Everything was broken. So much science going on, my goodness.

In April 2022 in the terminal there were white tents, people walking around in space suits, yellow signs, roped off areas, and plexiglass panels all over the place. Even the lighted areas seemed intentionally dimmed with only a few bulbs burning overhead. It’s almost as if they set the scene that way on purpose just for effect. Scary virus! Everyone was tightly masked with many sporting full face shields over their N95s. It wasn’t as insane a few months later in July so I decided to test the mask thing and took mine off. Turns out they couldn’t force the mask. One airport official gently reminded me about my missing mask and I sharply waved my hand in front of my nose and walked away. That means no. July was faster, too. They got their processing down to about 2 hours but the terminal was still largely closed.

Anyway, Japan didn’t really open until mid 2023. That’s also when they cancelled the never ending “waves” of “cases” that crashed ashore and swept the country for years. We were on wave 7 or 8 at the time and then, poof, everything just went to zero. Overnight. Such an epic victory for science.