Irresistible attraction, insatiable consumption: the obesity epidemic was inevitable - hyperpalatable food just makes it worse

So incredibly delicious, you can't stay away, can't stop. Buy more now!  It's so much better than reading about why it's true!

(This is an abridged version of an essay that was posted on Medium.)

Three years ago in September of 2021 in a blog post titled "Is obesity research too hard?", I observed how difficult obesity research is, and suggested that it might be too difficult for the scientific methods available in the early twenty-first century.  It's even harder than that: here's one set of reasons. [Sorry about the malfunctioning link; the post is on page two, and Blogger's HTML anchors don't recognize that it's not on the front page.]

Most animals obtain their energy supplies by eating food - it's essential for survival. Most of the time, animals find themselves in resource-constrained environments, and feeding systems that work by "eat as much as you can, whenever you can" without any upper limits, work just fine at keeping obesity from becoming a problem.

But after eons of biological evolution and technological development, human civilization achieved prosperity, and invented refrigeration and transportation that made more than enough food available all the time.  According to the US Bureau of Labor Statistics, in 1901 Americans used 42.5% of their expenditures for food., while by 2002 those expenses had declined to 13.1%., and by 2022 all the way to 6.7%, a reduction of 84%. For North Americans, food is an unlimited resource year round, and we have only ourselves to rely on to keep from getting fat. Our evolutionary history has never before needed to cope with this situation. Without the evolution of new forms of food intake regulation, obesity epidemics are inevitable.

Managing food intake to match energy consumption has two major components: appetite, that is obtaining and ingesting food, and satiation, stopping ingestion when enough has been consumed. These have to balance over the long term.

Then, achieving the balance between appetite and satiation are, at a minimum, five interacting behavior-physiological subsystems. Driving appetite are foraging, which I blogged about earlier, which gets the organism close enough to the food to trigger eating behavior.  Eating is closely followed by ingestion, which is succeeded by digestion, which creates circulating nutrients processed by the organism's metabolism.

Each of these stages sends signals to the others to drive or inhibit their activity.  One of those feedback loops goes between foraging, eating, and ingestion. This makes the very acts of finding and consuming food become ends in themselves. Chefs know that the presentation of the food is an important part of the dining experience -- diners simply enjoy looking at a well-composed arrangement of artfully shaped and colored edibles on a plate.

Food producers and processors, whose mission is to sell more of their product without regard for the welfare of their customers, have learned how to make their foods hyperpalatable, exploiting the positive sensory properties and flavors to keep eaters eating, and buying more.  The salty snacks industry has been most successful at this takeover of the food consumption behavior system, whose adaptive value is enormous when the organism is in a nourishment scarcity environment.  Grilled and smoked meats come in second for hyperpalatability, but their producers have been less successful at creating a mass-distributed product.  In a nourishment rich environment, eating for the sake of eating acquires more negative effects than positive ones. This takeover reached what may be its ultimate expression in the slogans that promoted Lay's potato chips: "Bet you can't eat just one," and reaching the end of the bag of chips: "Don't worry, we'll make more."  The clear message is to keep eating, and don't stop, ever.

The result of these interactions is that people will eat even when they're not hungry, and keep eating even beyond the point of satiation. Their tissue mass will accumulate faster than it is depleted and their weight will go up, regardless of any steady state energy balance levels.

Medical researchers and pharmaceutical companies have searched for decades for drugs that can affect the weight regulation system. And they've found them: Wikipedia lists 38 different drugs with appetite suppressant effects. Each of them has many effects in addition to appetite suppression,  Which effect is a primary one and which is a side effect inevitably depends on the user's goals and perspectives.

The latest example of this rainbow of capabilities is the family of drugs called GLP-1 receptor agonists. Originally discovered by studying the causes of the remarkable metabolic capabilities of the Gila monster, a lizard found in the deserts of the Western US, they turn out to be "not only effective in metabolic diseases [such as type 2 diabetes and obesity] but also play a role in non-metabolic disorders, affecting multiple systems including the musculoskeletal, nervous, cardiovascular, and digestive systems, and can even have implications in oncological diseases."

Drug companies are spending major resources promoting GLP-1 receptor agonists as a panacea, of course. In a tour de force of marketing, one of them, Novo Nordisk, is distributing the single drug semaglutide under three different names: injectable Wegovy for obesity, injectable Ozempic for type-2 diabetes, and oral Rybelsus for type-2 diabetes.  It can do this by exploiting the US drug regulation framework, which gives them a set of patents on semaglutide formulation that will expire over years ranging from 2026 to 2041, and allow them to monopolistically charge prices that may be more than 250 times its cost to make..

Marketers and enthusiasts will avoid telling you about the side effects of weight loss drugs, which are serious enough that most people who started taking anti-obesity medications stopped using them within a year.  People trying Wegovy were best at staying with the program, but only 44% of them lasted a year.

If you're an American reading this, it's more likely than not that you're overweight.  Lots of organizations are happy that you're that way, and few have incentives to help you manage your weight effectively.  Food producers want you to eat more of their products, regardless of your weight condition. They're working hard to develop ever more hyperpalatable foods to keep your binge eating bouts going. Drug manufacturers are happy to have more overweight patients who will pay high prices for their weight reduction drugs. Purveyors of diet plans want you to use their plan and avoid other plans, regardless of whether it's the right one for you.

Healthcare providers have lost what benign incentives they ever had.  For a brief period in the 1970s researchers had discovered that "health management organizations" (HMOs) that focused on improving health for their clients had less expenses and better patient outcomes than fee-for-service insurance systems.  But then HMO managers discovered that care denial strategies were even more profitable than complicated health promotion programs, and now HMOs are just another, more restrictive, insurance offering.

Against these powerful economic forces, individuals who want to reverse their weight increases have a tough road ahead.  The idea that there's no royal road to weight loss, and that each person needs to find a path that works for them and may be different from everyone else's is a revolutionary one. Biology may be destiny, but controlling your own biology without the necessary data and personalizable systems analysis tools that have not yet been devised, must be done by trial and error.  Keep trying, and don't give up until you find a method that works for you.  Good luck! 

Post-modern origin of species

In the 1860s we had Charles Darwin's ideas.  Then in the 1940s we had a "modern synthesis" of genetics and population biology.  And in the 1970s and 1980s this was tied to molecular genetics. Now we have attempts to describe speciation in even more fundamental terms.  Forty years later -- t's about time.

Recently two papers have appeared in Nature and PNAS that attempt to show how to identify when natural selection is occurring in an abstract sense that could help to understand how living systems arise from non-biological systems - abiogenesis. They're not quite successful.  In fact, they're so abstract that people are having trouble figuring out even what these theories are trying to do.

An article in Ars Technica is an example of this confusion.  From the perspective of "publish or perish", this is a good thing, since it means that there are plenty of opportunities for easy papers explaining and correcting.

From my perspective, the problem is that they're phenomenological, showing how to recognize species, but not explaining why distinct species should even exist, or how they come about.  They both assume that species come about via natural selection, although there are other mechanisms that can preferentially increase the population of some kinds of objects within a broader spectrum of varieties.  When objects are created and destroyed via some inaccurate replication process, some varieties will take less energy to create, and some will last longer once they're created.  These are called "thermodynamically preferred" varieties, and the laws of non-equilibrium thermodynamics (which are mathematical laws, not physical ones) will determine how fast the populations of these varieties grow and decline.

Then in chemical systems, you'll find that at some varieties have catalytic properties that amplify the rates of creation of other varieties, and, rarely, autocatalytic properties that amplify the rates of creation of themselves. The autocatalytic property may be distributed across a loop or network of reactions in a hypercycle.  Neither paper provides a way to recognize or measure the existence or power of the autocatalytic advantage, although the PNAS paper would ascribe a "function" to it, once it's recognized.

That paper tries to focus on "function", but the focus doesn't really achieve the needed sharpness, because the word is ambiguous.  Human brains are hardwired to see goal-oriented phenomena in as many places as possible. But for most of the history of life, goals didn't exist, and things happened because they followed inevitably from the way they were in the past, rather than happening in order to change the future by approaching an internally represented target state.  In attempting to create an objective definition for function, the paper almost escapes this teleological trap, but you can tell from the uses of the term in other places that the authors hearts haven't really accepted the concept.  Many of the comments to the Ars Technica story attribute this to a conflict of interest with quasi-religious goals of the foundation that funded much of the authors' work.

That's too bad.  The slogan "It goes by itself" needs to become as much of everyone's way of thinking as Galileo's "Nevertheless, it moves" did 400 years ago.

Foraging as a unifying strategy for neurobehavioral research programs

I follow a few computational and behavioral neuroscientists, and have noticed that they sometimes mention foraging in their research summaries.  I've recently been realizing the brilliance of foraging as a coordinating framework for a research program in those areas.  Foraging provides both evolutionary support and ecological validity to link lab studies with animals' situations in nature, over a vast range of capabilities.  Here's an outline of how that works:

Consider the notation "-->" to mean "provides an evolutionary base for the emergence of".  Then...

Note: the sequence below is not a strict hierarchy; related hierarchies evolve independently in parallel

• passive foraging (e.g. corals) --> gradient following foraging (jellyfish, mosquitos)
• gradient following foraging --> path creation foraging (ants, herbivores)
• path creation foraging --> goal-oriented foraging
• goal oriented foraging --> route planning
• route planning --> global optimization of route traversal resources
• route planning with limited resources --> "mental" route planning
• mental route planning with limited cognitive resources --> cognitive load management
• cognitive load management --> mental introspection
• mental introspection --> consciousness

The perceptual aspects of foraging are multi-factorial, and their evolution is even less strictly hierarchical than foraging as a whole.  Key perceptual transitions include:

• open field, and path network foraging --> localization of self in an "allocentric" environmental landscape
• allocentric maps --> distinction between self and other
• objects with complex properties --> indirect "signs" of foraging goals
• bounded perceptual processing abilities --> attention
• attention --> endogenous control of perceptual salience
• endogenous attentional control --> signification overshoot
• signification overshoot --> the "hard problem" of consciousness

If you want a career in neuroscience that provides a way to get from hardcore neurosynaptic mapping all the way to the most psychological of mental phenomena short of social interactions, picking foraging as a central topic can give you a wide open field full of tasty topics to work on.

Thinking about the evolutionary transitions driven by the basic need for energy that leads to foraging for food sources in this framework illuminates the long, complex path that it will take to fill in the gaps in the quest to understand how the operations of neurons give rise to mental phenomena.  

It's no wonder that philosophers speak of an "explanatory gap" between the brain and the mind, when there are something like nine levels of abstraction between the two.  It will take much detail work by scientists to fill in the intermediate levels before the concepts become sufficiently "common knowledge" that philosophers can comprehend them and recognize the absence of any magic supernatural connection between them, or even any scientistic faith in some unknown kind of materialist connection.  But then, replacement of thought-stopping mystery by knowledge-driven awe at the complexity of nature has always been the role of scientists.

Pricing monoclonal antibody treatments

The FDA has approved another treatment for early-stage Alzheimer's Disease that targets the amyloid plaques that are a hallmark of its effects on the brain.  The treatment—lecanemab, brand-name Leqembi, made by pharmaceutical companies Eisai and Biogen—is an intravenous monoclonal antibody that targets amyloid-beta proteins, which accumulate in plaques in the brains of people with Alzheimer's. Researchers have not yet conclusively determined if amyloid plaques are a root cause of the disease.  There are many things that go wrong in the brains of Alzheimer's patients, and it may be wishful thinking to look for a "silver bullet" single treatment..

Like aducanumab, side effects of lecanemab can be severe, even life-threatening, and like acucanumab, Medicare will pay for the treatment only in the context of an ongoing clinical study.  As of this writing, no studies are planned, which means that only wealthy people will actually get the treatment.

Eisai and Biogen have priced lecanemab at $26,500 for a year's supply. To many people who only see drug prices for over-the-counter products, that seems like a lot of money.  But is it really?

It's a basic principle of price identification in capitalism for sellers to charge "all that the market will bear", and let competition between sellers exist in order to generate a functioning market. Patents for things like drugs prohibit the market-based pricing mechanism from existing, and all we're left with is monopolistic pricing, where the "competition" is the willingness of the buyer to do without the product. When the buyer's alternative is death, this mechanism doesn't work well.

Putting a price on a long, slow decline to death isn't easy, but that doesn't stop people. According to a press release from the company, Eisai has devised a mathematical formula to compute the lifespan quality of life alleviated by their product given its measured effectiveness, and priced it substantially below that. If you believe their formula and the results of their clinical trials, it's a good deal.

Like aducanumab/Aduhelm, lecanemab is a monoclonal antibody, so its pricing can be compared to monoclonal antibodies used as treatments for other diseases. The 42 monoclonal antibody treatments listed by pharmacy discounter GoodRx have a median price per dose of $5275, ranging from the government-set $3/dose for some Covid-19 treatments to $239,020/dose for a chemotherapy treatment.

The Alzheimer's treatment from Eisai is given 24 times a year, making its price $1104/dose. Compared to other monoclonal antibody treatments for other diseases, 80% cheaper per dose coud be considered to be pretty low priced.

Who are official directives to wear face masks protecting? Not you.

Two years into the Covid-19 pandemic, the landscape of the risk and what to do about it has changed.  But the response of public health officials and experts and random people with opinions has not.  The data on what's happening is still bad, so even the most thoughtful of expert assessment isn't as good as it really needs to be.  And the politicization of the response has created a situation where public statements have to be phrased in a way that impels people to do the right thing even if it's for the wrong reasons and supported by inappropriate facts.

The general population can't distinguish between the virus (SARS-Cov-2) and the disease (Covid-19).  The public health surveillance data for the virus is much better than the data for the disease.  This means that even experts who should know better talk about them as if they were the same.  They end up fighting the virus, not the disease.  Journalists who need a hot, grabby story are motivated to find the most severe way to write or talk about the pandemic.

Here's how to think about the situation if you want to react in a more sophisticated way than by following guidance that is oversimplified so that it can motivate the entire population, even those parts of the population that need super-simple instructions or are skeptical of or even opposed to official directives.

Basic principles

• Reduce exposure to the virus
• Stay away from confined areas with poor ventilation
• If you have to go into risky areas, with lots of people who may be infectious, protect yourself - wear a good mask.
• Reduce your susceptibility to the disease by getting vaccinated and boosted

Rules to protect yourself

• Vaccination is better than masking
• Boosters make vaccination even more effective
• Any mask is better than no mask
• Wearing a mask while being vaccinated is better than either one alone
• Cloth or surgical masks protect the people around you more than they protect you
• To protect yourself, wear a standard rated mask
• There are lots of standards: N95, KN95, FFP2, KF94, and more.  It took a bit of searching to find a thorough survey of most of the important ones.
• A rated mask with a valve protects you, but it doesn't protect people around you.  So use a mask without a valve.  If you are infectious but still feel OK (asymptomatic), don't infect others inadvertantly. Even that article misses this point.

Ventilation is an important defense against all airborne risks, but it's complicated to understand and assess, and can be expensive to improve.  It would be nice if some entrepreneur could figure out how to make good ventilation something worth buying.

Too much planning to survive can reduce survival

It's a long, strange path that our ancestors have taken to get to our level of cognitive processing.  It's understandable, but not forgivable, that many philosophers don't bother tracking it all the way through from microbial beginning to the latest cultural edifices.

Everyone knows that evolution works by "survival of the fittest".  Which is almost a tautology since "fitness" is defined in terms of number of descendants who survive to reproduce themselves.

Less well understood is how species with complex individual members come about.  It occurs because there is always variation in complexity, and some variants acquire increased fitness by virtue of some aspects of their complexity.  Because "there is always room at the top", there's a general trend towards ecosystems hosting populations with greater complexity.

Then at some point in the evolution of greater and greater complexity, the ability of individuals to make plans can appear.  This can take a long time, but nature can take as much time as it needs; it's not on any particular schedule.

Among the things that planning can do, is make plans to survive.  An organism that can make plans intended to enhance its survival in certain situations (and then execute those plans) will have a greater likelihood of surviving those situations than an organism that just reacts to the immediate aspects of them.

However, the process of planning consumes cognitive resources and attention.  Computational and game-theoretic analyses of the planning process have shown that comprehensive planning involves a search through a space of all possible sequences of actions that grows exponentially in the size of the problem space, or equivalently in the depth of search traversed before a particular plan of action is abandoned in favor of an alternative.  The game of chess is the classic example of planning in a situation whose solution is beyond the capability of any human or computer yet built.

Cognitive resources used by planning might be more effective in enhancing survival if they were applied to reacting quickly and precisely to situations, rather than focusing on planning.  The stereotype of the "absent-minded professor" is an example of this kind of misallocation of resources.

Thus, the most effective kind of planning is resource-bounded, making  heuristic estimates rather than carrying the planning through to a conclusion.  This creates an inverted-U shaped function of the effectiveness of planning in enhancing survival vs the amount of resources applied to planning.  

Maximizing survival involves finding the sweet spot between planning and action.  Finding and maintaining planning activities at this sweet spot requires identifying and controlling the depth and comprehensiveness of planning.  Ability to exercise this kind of control provides its own survival advantages, with its own inverted-U properties.  

Higher order control of planning is one of the cognitive processes involved in consciousness.  Recognizing this provides part of the answer to the questions of the usefulness of consciousness, and to the evolutionary origin of consciousness.

Is obesity research too hard?

The M3 theory of weight regulation, or, no silver bullet for weight loss.

Sometimes ideas that have been floating around in your mind suddenly fall together.  This seems to be one of those cases.  The trigger might have been a recent report by Herman Pontzer and 83 others, who studied 6421 people and found that metabolism peaks at ages 2-5, plateaus during adulthood, and then slowly declines after about age 60.

What makes a model too complex?

M3 stands for "multifactor, multimodal, metabolic".  Weight management is under the control of a multitude of different factors; it's a complex system that can be purturbed in a large number of ways, and the elements of the system are linked by an equally large number of feedback control factors that make predicting the magnitude of the ultimate effect of any single purturbation is very complex.

It's obvious that complex systems like this cannot be communicated in the simple concepts and language that popular journalists are obligated to use if they intend to engage successfully with a large audience. It's less obvious, but still likely, that public health officials, who wish to issue guidance that can be followed by most people, but who attempt to base their guidance on the best scientific knowledge, cannot effectively synthesize that knowledge in consumable form, even if they had an adequate scientific model.

Today's insight is that an adequate scientific model may be impossible to obtain, because the technology currently used to manage scientific knowledge isn't up to the job.  Scientific knowledge advances one publication at a time.  But it's cumulative only in the way that termite mound or beehive is the result of myriads of individual contributions from individual termites or bees.  The mound does not respond to external stimuli on the same time scale as the stimuli themselves.  When new scientific knowledge about a complex model appears, it does not update the model until a new textbook is written that includes the new or revised item.  Figures and equations in textbooks are not executable models, they're representations that allow readers to build executable models in their heads or in computers.  

And it takes executing the model to determine whether any proposed intervention will result in a desired outcome.  If the model is too complex to be operated in your own head or on your own computer, it's not a useful model for managing the system, even though it may be true.  The best that can be done is to measure how accurately the usable models work at each timescale, and to track how they improve as more compute power is applied to them, and whether they're improving over the years.  Tracking improvements in forecasting accuracy is done in meteorology, and practically nowhere else.

The simple model

Every time a discussion of a new "breakthrough" in weight management is announced, someone inevitably pipes up with "it's easy: calories in minus calories out.  It just takes will power, you lazy wimps."  Not only is this insulting, but it's wrong.  Calories are a measure of energy, they don't convert to mass except in high energy particle accelerators.  The weight management fundamentalists should be talking about grams of carbon, not calories.  And they need to talk about rate of carbon in minus rate of carbon out.

The same bathtub analogy that is used for climate warming works for weight management.  Suppose we have a bathtub with a drain that can't be shut off completely, but can be opened up to allow more flow beyond that basic level.  That basic flow represents the body's base metabolism used for simply keeping you alive, and the rest of the flow is what's consumed by other daily activities.  The bathtub also has a faucet whose flow represents the contents of the food that is eaten every day.  We want to regulate the amount of water in the tub, so that it doesn't overflow or get so heavy that it falls through the floor.  

This model is already difficult to manage, since we can easily measure only the weight of the tub and the rate of flow into it.

Calories are a very imperfect measure, since they are an imperfect proxy for carbon. Calories are measured by burning a substance and measuring the amount of heat produced in excess of the amount of heat needed to ignite it.  Since food is made of carbohydrates and proteins that contain both carbon and hydrogen, some of that heat comes from burning the hydrogen, and the amount from carbon that we're interested in must be estimated from a chemical analysis of the food.  And because some of the measured calories come from sources that are not well digested, such as fiber, calorie measurements overestimate the amount of carbon that becomes bodily tissues to contribute to obesity even more.

The M3 model components

If it's too complex for all of science to deal with, it's too complex to describe in detail here.  We can just give a top level outline of its key components.  We can't even list all the linkages between them.  All the components and their linkages form a graph structure, and computer modeling systems that convert graph structure descriptions into executed model runs don't exist, as far as I know.  So anyway, here's a short list:

• Inputs
• Carbs
• glycemic index
  
• protein
• fiber
  
• Input controls
• Appetite - external sensory
• Mouth feel
  
• crispy
• crunchy
• chewy
• temperature
  
• Flavor
  
• salty
• sweet
• savory (umami, MSG)
• smell - hundreds of qualities
• associative learning
• appearance
• smell
  
• Hunger - internal sensory
  
• blood sugar
• stomach fullness
• internal processing
• digestion efficiency
• microbiome spectrum
  
• glucose production
• glucose consumption
• insulin-controlled conversion rate
  
•  tisue targets
• white fat
• brown fat
• muscle
  
• Outputs
• breathing - CO2
• base rate
• exercising rate
• exercise level
  
• excretion
  

A better list would attach to each item and link a citation to the scientific literature that provides evidence for its properties.

 New frontiers in weight control

The silver bullet would be to identify a single item in the list above that is both measurable and controllable, so that you could manage your weight by controlling that item. But this is impossible, because there are always at least two paths between input and output at any stage of control and processing.  Calories are a single measurement, but because the nutrients that provide calories (and their associated carbon) have different rates of utilization (glycemic index) and bioavailability (fiber does not get converted to energy or weight), it's an incredibly unreliable measurement.

Any combination of measurements and controls is even harder to manage and analyze.  What we ideally need is an artificial intelligence system that tracks a bunch of nutritional properties and identifies an optimal combination of them to maximize flavor while maintaining a target weight.  And it needs to be frictionless and transparent at the same time, quietly looking over your shoulder whenever you attempt to eat anything, computing how it will affect your weight management plan, and gently suggesting alternatives.  Alas, this is well beyond the state of the art in AI technology.  Training the machine learning part of such a system would take not 6000 participants, but 600,000 of them or more, each tracking every meal and a host of metabolic indicators.

The latest trend in public health interventions to manage an obese population is dietary sugar, and in particular sugary drinks.  Sugar is a powerful contributor to weight gain since it's both calorie dense and is metabolized very rapidly. It makes a big contribution to the rate of carbon input to a person's mass flow balance.  So regulating sugar input by public health officials might have some impact.

Focusing on the appetite component of the M3 model offers additional possible opportunities for management.  One of appetite's most dangerous properties is that it's insatiable.  It's not for nothing that Lay's Potato Chips once had a slogan "Bet you can't eat just one."  Eating something that's crispy, crunchy and salty doesn't satiate, it increases the desire to eat more.  

How this works is very unclear, and may be beyond the capability of current neurophilosophical thinking to clarify.  Super-appetizing foods have biased, if not overridden, the free will of a large fraction of the human population.  Philosophers arguing over whether free will exists amazingly fail to take facts like this into account. A will that is partially free and can be biased or overridden is incompatible with the content and methods of these arguments. Simply saying that these foods have been engineered to be addictive, as many writers assert, merely assigns blame without explaining the phenomenon.

But if you can't control the desire for salty snacks, you can at least improve the food value of them.  Instead of starchy chips and puffs that are metabolized vary rapidly, you can choose snacks with more protein that is metabolized more slowly, such as pork chicharrones, and ones that contain more fiber that is not metabolized at all.  It's something to look for in the grocery store.

How to understand biology

Computer experts are continually trying to understand biology in computer science or computer programming terms, and continually failing miserably.  The editors of Slashdot are giving it yet another try.

Biology is 100% parallel, stochastic, and intrinsically asynchronous.  Computer science gave up on those concepts ages ago.  I can’t think of a programming language that deals with them as anything but library afterthoughts.

Here are the foundational principles of biology that real biologists feel in their bones.  Journalists and popularizers ignore them routinely.

1. Nothing in biology makes sense except in the context of evolution
2. Evolution operates by naturally selected replication of the organismic consequences of random genetic variation.  There are no goals, and nobody/nothing is in charge.
3. Organisms function by translation of DNA into proteins that act as catalysts for all the other chemical processes in them, including control of DNA replication and regulation of the catalytic efficiency of all those enzymes.

Reference facts: (almost) every human cell contains 3 billion DNA bases, which make up about 30,000 genes.  There are more than 1000 billion cells in an adult body, and you carry around another 1000 billion non-human cells in your microbiome.

All the gosh-wow factoids in a popular book can’t bring these concepts into your head with any force.  You have to live with the details before it starts to really fall together.

Every one of them knew that as time went by they'd get a little bit older and a little bit slower

Why does endurance go down as people get older?  Part of the reason is that mitochondria, components of cells that play a key part in the conversion of glucose into energy for cellular functions like contraction of muscle cells, gets less efficient with age.  If the mitochondria can't deliver as much energy to your muscle cells, your muscles don't work as well or as fast, and you get tired sooner as well.

There is more research into longevity going on than I can keep track of, but a recent study was published in Cell Reports by Jianfeng Lan and 5 others that got a lot of public attention.  It was titled Translational regulation of non-autonomous mitochondrial stress response promotes longevity.  They have traced control of mitochondrial activity six layers upstream, and then found that combining the effects of changing the regulation of two different genes increases longevity by more than twice as much as altering either one alone.

It's all part of a program of "translational research" that goes beyond the pure science goal of understanding thoroughly how mitochondrial function affects aging, and aims to identify places in the almost incomprehensibly complex control network within cells.  But "amost incomprehensible" doesn't mean "will never be understood well enough to permit us to make useful alterations in the way the network operates."  This report identifies a promising set of links to try to affect using drug therapy.  It suggests that fixing this aspect of aging may not be a single-drug pill, but rather a combo pill.

Stephen Dubner's Freakonomics Radio show recently rebroadcast and episode on the effects of exercise on health and longevity, titled The zero-minute workout, which discosses some of the other aspects of mitochondrial function, and what might be done to keep it working well.

Mitochondria and aging are an important line of research that is worth keeping an eye on.