Isegoria

Lauren and Simon Freeman, oceanographers with the US Naval Undersea Warfare Center in Rhode Island, noticed strange pings in the Hawaiian Islands:

They perceived that the soundscape of healthy, protected reefs was dominated by low-frequency sounds (the kind typically made by fish and other large animals), while degraded reefs were noticeably higher pitched.

“We were told the sound was from snapping shrimp, end of story,” says Simon. “[But] there seemed to be a correlation between the sound and the proportion of algae covering the seafloor.”

Determined to dig deeper, the Freemans and their colleagues housed red algae in tanks devoid of clamorous crustaceans or other animals. The sounds they picked up matched the high-frequency sounds of struggling reefs.

[...]

Like the plants that help us breathe, algae also photosynthesize. Underwater, that process of converting sunlight and carbon dioxide into energy and oxygen sends tiny bubbles spiraling toward the surface. And according to new research, when each bubble detaches from the seaweed, it goes ping. The scientists behind the discovery suggest that, like a heartbeat heard through a stethoscope, measuring that unique sound could be a new way to monitor the health of a coral reef.

Evolutionary psychology is famous for having lots of stories that make sense but are hard to test, Scott Alexander says, and psychiatry is famous for having mountains of experimental data but no idea what’s going on:

Maybe if you added them together, they might make one healthy scientific field? Enter Evolutionary Psychopathology: A Unified Approach by psychology professor Marco del Giudice. It starts by presenting the theory of “life history strategies”. Then it uses the theory — along with a toolbox of evolutionary and genetic ideas — to shed new light on psychiatric conditions.

Some organisms have lots of low-effort offspring. Others have a few high-effort offspring. This was the basis of the old r/k selection theory. Although the details of that theory have come under challenge, the basic insight remains. A fish will lay 10,000 eggs, then go off and do something else. 9,990 will get eaten by sharks, but that still leaves enough for there to be plenty of fish in the sea. But an elephant will spend two years pregnant, three years nursing, and ten years doing at least some level of parenting, all to produce a single big, well-socialized, and high-prospect-of-life-success calf. These are two different ways of doing reproduction. In keeping with the usual evolutionary practice, del Giudice calls the fish strategy “fast” and the elephant strategy “slow”.

The following is not a figure from Del Giudice’s book, he says, but maybe it should be:

Psychiatry is hard to analyze from an evolutionary perspective, he argues:

From an evolutionary perspective, it shouldn’t even exist. Most psychiatric disorders are at least somewhat genetic, and most psychiatric disorders decrease reproductive fitness. Biologists have equations that can calculate how likely it is that maladaptive genes can stay in the population for certain amounts of time, and these equations say, all else being equal, that psychiatric disorders should not be possible. Apparently all else isn’t equal, but people have had a lot of trouble figuring out exactly what that means. A good example of this kind of thing is Greg Cochran’s theory that homosexuality must be caused by some kind of infection; he does not see another way it could remain a human behavior without being selected into oblivion.

Del Giudice does the best he can within this framework. He tries to sort psychiatric conditions into a few categories based on possible evolutionary mechanisms.

First, there are conditions that are plausibly good evolutionary strategies, and people just don’t like them. For example, nymphomania is unfortunate from a personal and societal perspective, but one can imagine the evolutionary logic checks out.

Second, there are conditions which might be adaptive in some situations, but don’t work now. For example, antisocial traits might be well-suited to environments with minimal law enforcement and poor reputational mechanisms for keeping people in check; now they will just land you in jail.

Third, there are conditions which are extreme levels of traits which it’s good to have a little of. For example, a little anxiety is certainly useful to prevent people from poking lions with sticks just to see what will happen. Imagine (as a really silly toy model) that two genes A and B determine anxiety, and the optimal anxiety level is 10. Alice has gene A = 8 and gene B = 2. Bob has gene A = 2 and gene B = 8. Both of them are happy well-adjusted individuals who engage in the locally optimal level of lion-poking. But if they reproduce, their child may inherit gene A = 8 and gene B = 8 for a total of 16, much more anxious than is optimal. This child might get diagnosed with an anxiety disorder, but it’s just a natural consequence of having genes for various levels of anxiety floating around in the population.

Fourth, there are conditions which are the failure modes of traits which it’s good to have a little of. For example, psychiatrists have long categorized certain common traits into “schizotypy”, a cluster of characteristics more common in the relatives of schizophrenics and in people at risk of developing schizophrenia themselves. These traits are not psychotic in and of themselves and do not decrease fitness, nor is schizophrenia necessarily just the far end of this distribution. But schizotypal traits are one necessary ingredient of getting schizophrenia; schizophrenia is some kind of failure mode only possible with enough schizotypy. If schizotypal traits do some other good thing, they can stick around in the population, and this will look a lot like “schizophrenia is genetic”.

How can we determine which of these categories any given psychiatric disorder falls into?

One way is through what is called taxometrics — the study of to what degree mental disorders are just the far end of a normal distribution of traits. Some disorders are clearly this way; for example, if you quantify and graph everybody’s anxiety levels, they will form a bell curve, and the people diagnosed with anxiety disorders will just be the ones on the far right tail. Are any disorders not this way? This is a hard question, though schizophrenia is a promising candidate.

Another way is through measuring the correlation of disorders with mutational load. Some people end up with more mutations (and so a generically less functional genome) than others. The most common cause of this is being the child of an older father, since that gives mutations more time to accumulate in sperm cells. Other people seem to have higher mutational load for other, unclear reasons, which can be measured through facial asymmetry and the presence of minor physical abnormalities (like weirdly-shaped ears). If a particular psychiatric disorder is more common in people with increased mutational load, that suggests it isn’t just a functional adaptation but some kind of failure mode of something or other. Schizophrenia and low-functioning autism are both linked to higher mutational load.

Another way is by trying to figure out what aspect of evolutionary strategy matches the occurrence of the disorder. Developmental psychologists talk about various life stages, each of which brings new challenges. For example, adrenache (age 6-8) marks “the transition from early to middle childhood”, when “behavioral plasticity and heightened social learning go hand in hand with the expression of new genetic influences on psychological traits such as agression, prosocial behavior, and cognitive skills” and children receive social feedback “about their attractiveness and competitive ability”. More obviously, puberty marks the expression of still other genetic influences and the time at which young people start seriously thinking about sex. So if various evolutionary adaptations to deal with mating suddenly become active around puberty, and some mental disorder always starts at puberty, that provides some evidence that the mental disorder might be related to an evolutionary adaptation for dealing with mating. Or, since a staple of evo psych is that men and women pursue different reproductive strategies, if some psychiatric disease is twice as common in women (eg depression) or five times as common in men (eg autism), then that suggests it’s correlated with some strategy or trait that one sex uses more than the other.

This is where Del Giudice ties in the life history framework. If some psychiatric disease is more common in people who otherwise seem to be pursuing some life strategy, then maybe it’s related to that strategy. Either it’s another name for that strategy, or it’s another name for an extreme version of that strategy, or it’s a failure mode of that strategy, or it’s associated with some trait or adaptation which that strategy uses more than others do. By determining the association of disorders with certain life strategies, we can figure out what adaptive trait they’re piggybacking on, and from there we can reverse engineer them and try to figure out what went wrong.

This is a much more well-thought-out and orderly way of thinking about psychiatric disease than anything I’ve ever seen anyone else try. How does it work?

Unclear. Psychiatric disorders really resist being put into this framework. For example, some psychiatric disorders have a u-shaped curve regarding childhood quality — they are more common both in people with unusually deprived childhoods and people with unusually good childhoods. Many anorexics are remarkably high-functioning, so much so that even the average clinical psychiatrist takes note, but others are kind of a mess. Autism is classically associated with very low IQ and with bodily asymmetries that indicate high mutational load, but a lot of autistics have higher-than-normal IQ and minimal bodily asymmetry. Schizophrenia often starts in a very specific window between ages 18 and 25, which sounds promising for a developmental link, but a few cases will start at age 5, or age 50, or pretty much whenever. Everything is like this. What is a rational, order-loving evolutionary psychologist supposed to do?

Del Giudice bites the bullet and says that most of our diagnostic categories conflate different conditions. The unusually high-functioning anorexics have a different disease than the unusually low-functioning ones. Low IQ autism with bodily asymmetries has a different evolutionary explanation than high IQ autism without. In some cases, he is able to marshal a lot of evidence for distinct clinical entities. For example, most cases of OCD start in adulthood, but one-third begin in early childhood instead. These early OCD cases are much more likely to be male, more likely to have high conscientiousness, more likely to co-occur with autistic traits, and have a different set of obsessions focusing on symmetry, order, and religion (my own OCD started in very early childhood and I feel called out by this description). Del Giudice says these are two different conditions, one of which is associated with pathogen defense and one of which is associated with a slow life strategy.

[...]

There is a part of me that thinks this book is a beautiful example of what solving a complicated field would look like. You take all the complications, and you explain by layering of a bunch of different simple and reasonable things on top of one another. The psychiatry parts of Evolutionary Psychopathology: A Unified Approach do this. I don’t know if it’s all just epicycles, but it’s a heck of a good try.

The New York Times explains how to survive a flu epidemic:

“Avoid crowds,” says Stephen C. Redd, director of the Center for Preparedness and Response at the C.D.C. If the flu strain is particularly virulent, you may be advised to keep a distance of at least three feet from other people. Research shows that virus transmission rates can fall by nearly 40 percent with mandatory social-distancing measures like closing schools and day cares. You may also be directed to isolate yourself and your family inside your home, a practice known among emergency-preparedness experts as “shelter in place.” Cache at least two weeks of food, medicine and water.

A global flu pandemic begins when a virus circulating in animals — like birds or pigs — mutates to infect humans, allowing it to spread quickly. In 1918, such an influenza sickened an estimated one-third of the world’s population, killing as many as 50 million people. During the next pandemic, practice cough etiquette (into a tissue or your inner elbow, not your palm); wash your hands regularly (20 seconds with soap and water); avoid touching your eyes, nose and mouth. If someone in your home falls ill, minimize close contact. Designate a sick room. You may want to wear a mask; one of the most effective types for filtering floating flu particles is known as an N95. Consider buying N95 masks before an outbreak. “In a severe pandemic, there will be a global shortage,” says Redd, who served as the C.D.C.’s incident commander during the last flu pandemic, the H1N1 outbreak in 2009.

Producing a vaccine for a new influenza strain could take months; when one becomes available, get it as soon as you can, knowing that it will be distributed first to those most at risk. Beware rumors and fake news. “Misinformation online will be a big challenge,” Redd says. Get to know your neighbors and your community now: You’ll need one another’s help. Don’t let fear erode empathy. In 1918, the sick starved to death, not for lack of food but because people were too afraid to get close enough to feed them. “You can bring a meal to a neighbor who is coughing without having face-to-face contact,” Redd says.

I suppose we should all be thankful not to be living in the worst year in historys, AD 538:

Analysis of atmospheric pollutants trapped in ice extracted from a glacier in the Swiss-Italian Alps suggests that this was the start of a cataclysmic run of global misfortune. “It was the beginning of one of the worst periods to be alive, if not the worst year,” Professor Michael McCormick of Harvard University said in the journal Science.

The analysis suggests that early in 536 a volcanic eruption in Iceland spread ash across the northern hemisphere. Europe, the Middle East and parts of Asia fell into darkness. “For the sun gave forth its light without brightness, like the moon, during the whole year,” wrote the historian Procopius.

Crops failed from Scandinavia to Mesopotamia. “It would have made places very cold very quickly and would have been most felt in Britain and northwestern Europe,” said Professor Christopher Loveluck of the University of Nottingham. This was only the start.

Two more climate-cooling eruptions followed, in 540 and 547. In 541 an outbreak of bubonic plague, known as the Plague of Justinian, emerged in the port of Pelusium in Egypt and went on to kill as much as half of the population of the Byzantine — or Eastern Roman — Empire, according to Dr Kyle Harper of the University of Oklahoma. The Western Roman Empire had fallen less than a century earlier. “In Britain the cities, the administrative support, they come apart,” he said. “It was the first Brexit and it was not entirely peaceful.”

This blend of volcanoes, pestilence and climate change helps to explain a century of economic stagnation. The malaise appears to end in about 640. The ice then shows a spike of airborne lead, signalling large-scale silver smelting and rising hopes of prosperity.

Researchers have adapted a third technique, commonly used to chart much larger proteins, to determine the precise shape of small organic molecules:

The gold standard for determining chemical structures has long been x-ray crystallography. A beam of x-rays is fired at a pure crystal containing millions of copies of a molecule lined up in a single orientation. By tracking how the x-rays bounce off atoms in the crystal, researchers can work out the position of every atom in the molecule. Crystallography can pinpoint atomic positions down to less than 0.1 nanometers, about the size of a sulfur atom. But the technique works best with fairly large crystals, which can be hard to make. “The real lag time is just getting a crystal,” says Brian Stoltz, an organic chemist at the California Institute of Technology (Caltech) in Pasadena. “That can take weeks to months to years.”

The second approach, known as nuclear magnetic resonance (NMR) spectroscopy, doesn’t require crystals. It infers structures by perturbing the magnetic behavior of atoms in molecules and then tracking their behavior, which changes depending on their atomic neighbors. But NMR also requires a fair amount of starting material. And it’s indirect, which can lead to mapping mistakes with larger druglike molecules.

The new approach builds on a technique called electron diffraction, which sends an electron beam through a crystal and, as in x-ray crystallography, determines structure from diffraction patterns. It has been particularly useful in solving the structure of a class of proteins lodged in cell membranes. In this case, researchers first form tiny 2D sheetlike crystals of multiple copies of a protein wedged in a membrane.

But in many cases, efforts to grow the protein crystals go awry. Instead of getting single-membrane sheets, researchers end up with numerous sheets stacked atop one another, which can’t be analyzed by conventional electron diffraction. And the crystals can be too small for x-ray diffraction. “We didn’t know what to do with all these crystals,” says Tamir Gonen, an electron crystallography expert at the University of California, Los Angeles (UCLA). So, his team varied the technique: Instead of firing their electron beam from one direction at a static crystal, they rotated the crystal and tracked how the diffraction pattern changed. Instead of a single image, they got what was more like molecular computerized tomography scan. That enabled them to get structures from crystals one-billionth the size of those needed for x-ray crystallography.

Gonen says because his interest was in proteins, he never thought much about trying his technique on anything else. But earlier this year, Gonen moved from the Howard Hughes Medical Institute’s Janelia Research Campus in Ashburn, Virginia, to UCLA. There, he teamed up with colleagues, along with Stoltz at Caltech, who wanted to see whether the same approach would work not just with proteins, but with smaller organic molecules. The short answer is it did. On the chemistry preprint server ChemRxiv, the California team reported on Wednesday that when they tried the approach with numerous samples, it worked nearly every time, delivering a resolution on par with x-ray crystallography. The team could even get structures from mixtures of compounds and from materials that had never formally been crystallized and were just scraped off a chemistry purification column. These results all came after just a few minutes of sample preparation and data collection. What’s more, a collaboration of German and Swiss groups independently published similar results using essentially the same technique this week.