Revealing the Origin of Eukaryotes

Tracing the breadcrumbs of deep phylogeny through gene duplications. 

Last week, we discussed the jamboree of mutation that is the MHC locus in animals. One part of that story was the persistent duplication and pseudogene-i-zation (which is to say, the birth and death) of genes in that locus through primate evolution, another consequence of the never-ending arms race with our pathogens. Gene duplication has much deeper significance, however, as it has given rise to new genes throughout biological evolution, as it is merely an accident of DNA (or RNA) replication, thus operationally rather frequent. Significant transitions, such as the advent of eukaryotes, and the advent of plants and of angiosperms, all feature rapid gene duplication, even whole-genome duplication, which provide grist for new functions, refinement of old functions, and speciation.

A recent paper did a deep dive into the origin of eukaryotes, perhaps the watershed event in the history of life, second only to the origin of life itself on the early Earth. It is very difficult to reconstruct what happened during these extremely early events, which these authors put as long as three billion years ago. There has been so much mutational churn in our molecules, and no fossil record to speak of, that, again like the origin of life itself, we do not have a great deal to go on. Thankfully, the discovery of the kingdom of archaea, and its especially eukaryotic-like class, the Asgard archaea, has provided a much better platform for speculating about what the originating organisms might have been like.

Eukaryotes differ from bacteria and archaea by numerous characteristics, implying extensive development/evolution before the last common ancestor from which we can trace all the extant descendants. These include the eponymous nucleus, an internal system of membranes and membrane-bound organelles, a complex cytoskeleton of both actin and microtubules, a mitochondrion, meiosis, a microtubule spindle-driven division system, and many other, more obscure molecular differences. The lack of intermediate forms is certainly frustrating from a scientific perspective, making it difficult to go through the catalog of life today to identify the steps involved in this transition. It also implies that the process ended with an evolutionary bang that in essence caused the final iteration to wipe out all the preceding forms, a bit like humans vs the many other Australopithecines and their descendants. 

These differences are enormous and momentous, making eukaryotic cells far larger, energetically capable, and complex than their antecedents. Another key characteristic is a prevalence of gene duplication and specialization, leading to much larger genomes along with all the other complexity. It has long been theorized that it was the union of the proto-mitochondrion, which was a bacterium, with the archaeal founding cell, that set the whole process off, particularly providing the massive amount of energy required for all this rise in complexity. 

However, the current authors claim that this definitively is not the case- that the mitochondrial symbiosis was a rather late event, coincident with the oxygenation of the atmosphere about two billion years ago. They argue that, since gene duplication and specialization is in any case a clear characteristic of eukaryotes, using molecular clocks to time these many gene duplications can give us relatively specific and data-rich insight into the epochs at which each of the processes that they participate in first developed. 

The authors present estimated times of origin for key duplications involved in RNA synthesis. The RNA polymerases I, II, and III were duplicated from one polymerase in archaea, and are composed of numerous gene products, as well as ancillary regulatory proteins. While some subunits are still shared, the ones that duplicated did so in the range of 2.3 to 2.8 billion years ago, before the symbiosis with the mitochondrial precursor, timed at "mFECA", or the mitochondrial first eukaryotic common ancestor, about 2.2 billion years ago. "nFECA" is nuclear first eukaryotic common ancestor, while "LECA" is last eukaryotic common ancestor. The axis at the top is time before present, in giga-years ago, or Ga.

For example, eukaryotes all have three RNA polymerases, while bacteria and archaea only have one. These RNA polymerases specialize on mRNA synthesis (RNA pol II), ribosomal RNA synthesis (RNA pol I), and tRNA, 5S RNA and U6 snRNA (RNA pol III). Why this specialization exists remains a bit mysterious, though once it started there was no going back. In any case, it happened and is totally characteristic of eukaryotes, so these duplications (which involve the duplication of numerous genes encoding proteins of the polymerase complex itself and its regulators and way-finding helpers) can be used to date eukaryogenesis, using a very carefully calibrated and species-sampled molecular clock. And what they find is that all of these duplications, given as ranges in the graphs above, with green dots at the likeliest time points, all lie prior to the point of "mFECA", which is the mitochondrial first eukaryotic common ancestor, at roughly 2.2 billion years ago. Tabulated over studies of almost a hundred other genes that are similarly duplicated and characteristic of eukaryotes, the authors place the "nFECA", or nuclear eukaryotic common ancestor way back at almost 3 billion years ago. 

That is a very long time! It is a very long time ago that the characteristics of eukaryotes started to come together, and it is also a very long time (well over a billion years) over which that development spanned before culminating in the last common ancestor of all extant eukaryotes, which the authors put at about 1.7 billion years ago. And note that that still comes a billion years before the Cambrian explosion of animal life. We are talking about really deep time here. 

If mitochondrial symbiosis came later, (causing another bout of genomic change as hundreds of bacterial genes moved from the symbiont to the nucleus), just as the atmosphere was getting oxygenated, what was going on in the preceding billion years? One can speculate that these evolving proto-eukaryotes were the top predators of their world, a bit like eukaryotic protists in microbial environments today. The competition would as always have been intense, but there were no higher life forms (i.e. animals or protists) to worry about. Size was not a problem, but rather an advantage. The focus was on quality and effectiveness in finding, disabling, and digesting prey. Thus there was little downside to complexity, unlike the constraints on prey species, which had to optimize for rapid growth and reproduction under both nutrient and predation constraints. New and costly systems for protein secretion, for prey digestion, and intelligent, responsive regulation of all cell processes might have been consistently advantageous.

I take this work as being definitive, at least in terms of settling the debate about early vs late symbiosis. It benefits from a clear theoretical basis and new, voluminous sequence data from appropriately related species in its molecular comparisons. I recommend it highly, as I can only scratch the surface of its analysis here. The advent of mitochondria was then a later step change in complexity, but brought incredible metabolic productivity that, at least in oxygen-rich environments, would have definitively superseded all the prior forms of the proto-eukaryote, and (unfortunately for us) erased that record of evolution. A later innovation, placed between mFECA and the last eukaryotic common ancestor "LECA" was sexual meiosis, another fascinating and characteristic innovation of eukaryotes. These authors thus provide a true revolution in our understanding of eukaryogenesis, extending it across well over a billion years.

One more sample from the author's presentation of molecular duplications that help time eukaryogenesis. Here, DNA repair proteins are emphasized, including some involved in meiosis (light blue dots, see legend). Some of these duplications involve genes from the mitochondrial endosymbiont, (MSH4), and some (such as EME1/2 and MUS81) come from older repair processes, but later specialized for meiosis. 

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MHC Through Evolution: Breaking All the Rules

The immunologically critical MHC gene cluster plays by its own rules through the arms race of life.

Last week, I discussed the very general landscape of variation in the human genome, specifically the tradeoff between prevalence in the population and effect size. Given that the vast majority of variants are deleterious, those that affect our phenotypic traits are more heavily selected against the greater effect they have. The result is that at a gross level, most genes and most traits share the same general distribution of lots of variants (alleles) with minor effects, and far fewer with large effects. And those with minor effects also turn out to be tangential for biologists, rarely informative about the nature of the traits they (sort-of) affect.

This week, another paper and another view of evolution, though the eyes of one the more critical genes of the immune system, the major histocompatibility complex, or MHC group of genes. While our adaptive immune system has developed the extraordinary and powerful ability (though semi-controlled DNA recombination of the antibody and TCR genes) to recognize practically any antigen, foreign or domestic, that system requires stringent controls. One of those controls on T cells, which carry the antigen-recognizing TCR receptor, is that it can only see antigens that are "presented" on MHC molecules. MHC proteins have a surface cleft that gets loaded with and holds small peptides (8 to 12 amino acids long) that are cleaved from other proteins, either from pathogens or from the cell itself. The MHC+peptide complex then sits on the surface of the cell, announcing either that 1) I am healthy, full of normal cell proteins, going about their business, nevermind, or 2) I have some other proteins inside, either from a viral infection (class I MHC) or from some bacterium I have just phagocytosed to deal with an infection (class II MHC). In the second case, T cells carrying the TCR receptor lock onto the MHC+peptide complex, and start up the process of killing that cell. 

MHC proteins (beige, pink) present an antigen (red) from one cell, and dock to a T-cell which recognizes the antigen+MHC complex by shape, using the TCR receptor. The additional CD8 or CD4 receptors help to verify the proper binding. While class I MHC are present on all cells, class II MHC are on phagocytosing cells like dendritic cells and macrophages that commonly ingest, reprocess, and re-display bits of encountered pathogens.  

Given that the TCR gene recombination process is unbiassed and produces a galaxy of random binding specificities, how do these cells distinguish self from non-self antigens? This is a deep question that is not fully resolved. But one major mechanism is thymic selection, which is what gives T cells their name. Special cells in the thymus display a wide range of self-antigens, and T cells, which are obliged to pass through the thymus during their maturation, are induced to commit suicide if they react to any of them. A paper from 2018 fascinatingly discussed how it is possible to create a T cell population that knows the "language" of foreign vs domestic after what is known to be a rather haphazard selection process, which displays only a partial range of self-antigens, and leaves quite a few self-reactive T cells around.

At any rate, the MHC proteins do not benefit from hyper-variation provided by genetic recombination. Yet it turns out that variation is beneficial here as well. The way foreign antigen peptides nestle in the MHC groove can be varied by mutations in the MHC molecule, providing a rich field of variation in antigen recognition and thus disease resistance. So, our MHC genes have not just a few alleles in the population, not just a few dozen, but over six thousand alleles. For each individual MHC protein, each person has only two, but over the population, there myriads with different properties. MHC was first recognized for its role in self vs non-self recognition and transplant rejection, (thus the "compatibility" in its name), and it quickly became evident that people vary tremendously in their MHC complement. And this variation plays a big role in keeping us (and all other animals) going as populations, in the face of pathogens that evolve a lot faster than we do. 

A recent paper provided a phylogenetic history of MHC molecules in monkeys, covering the last sixty million years of evolution in our lineage. It is a festival of gene birth, death, and duplication, quite apart from the smaller mutations that are constantly accumulating and cycling through the population. The MHC region carries about 200 related genes, most of which have minor roles, and only six of which (three MHC class I, and three MHC class II) follow the high-mutation pattern because they encode the main antigen presenting proteins. These genes are subject to, quite obviously, unique selective forces. 

How the MHC gene cluster looks, when aligned and identified by gene, over the primates. Note the deep divergence between the new- and old-world primates. Genes A, B, and C are the major MHC class I genes, which vary the most over this time. Note also how some of these genes have gone through extensive duplication in some old-world monkey lineages.

The first force is balancing selection. As soon as one allele becomes common, pathogens evolve to evade its presentation skills, rendering it less effective and less desirable. This results in a population full of minor variants. Indeed, for any individual person, having two MHC molecules that are the same would be bad. Being heterozygous at these genes is highly advantageous, thus enforcing both the retention of minor alleles, and an observed behavior in mating to favor partners with different MHC complements. Apparently, our MHC makeup is reflected in our personal aroma! 

A second force, conversely, is the retention of ancient alleles. It turns out that, across the old-world monkeys, many MHC alleles are preserved and cluster more closely in sequence comparisons with each other than they do with other alleles in the same species. That is, despite the general speed of MHC evolution and constant accumulation of new alleles, old alleles are preserved in all monkey populations as well, due to their distinct capabilities, under balancing selection. This is part of what makes population bottlenecks so damaging to near-extinction species. They lose critically valuable genetic resources (in the form of rare MHC alleles) that represent millions of years of accumulated variation. 

Incidentally, the trees shown here again reinforce the history of primate evolution, with new world monkeys splitting off from the old-world monkeys quite early on and developing a very distinct set of MHC molecules.

So, while virtually every other gene in the genome is being relentlessly optimized, sticking to its knitting, doing one thing and being beaten down whenever any mutation steers it from its optimized path, the MHC genes follow quite a different path, at least in portions of their sequence that provide variation in antigen binding and presentation. These genes revel in endless diversity, throw off pseudogenes at a high rate, wink out of existence and come back in other forms. Natural selection is the motor in each case, but meets the challenge of survival in different ways.

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How Do Complex Human Traits Add Up?

Notes on the genetics, traits, and evolution.

Everything about us is a trait. Not everything about our traits is genetic, though. The conundrum of nature vs nurture, of genes vs environment, and the structure and meaning of genetics goes to the heart of biology. A few traits, like eye color, are simple enough. But they are the exception, by far. Body mass index is influenced by practically every gene we have. And autism has, by this point, hundreds of contributing genes. Both traits are highly heritable, in the sense that inheritance/genes are the dominant influence, vs environment (as seen in twins) when most conditions are equal. But environment can easily be dominant over BMI when conditions change and starvation sets in. 

A puzzle that came out of the early human genome studies was how unhelpful it was to do genome-wide association studies (GWAS) to approach some of these questions- that is, studies of what variants in the population at large contribute to particular traits, especially to serious diseases. Study after study was done, and disappointment mounted that what were found were genes with minor effects, in tangential biological processes. This was supposed to be the holy grail- the payoff for sequencing the human genome- and what came up was dud after dud.

A recent paper plows over this ground again with a new mathematical synthesis of genetic structure of human traits, genetic alleles, and selection. What it finds is sort of obvious, but there are some intriguing observations along the way. It is critical to note at the outset that evolution as Darwin understood and described, and natural selection in particular, is absolutely at the heart of this or any contemporary analysis of genetics. While Darwin's understanding was revolutionary and broad, subsequent decades of work have brought these concepts to a very concrete, operational, indeed mathematical, level. 

Let's start with the concept of allele frequency, also called minor allele frequency, of MAF. Over any individual genome, there will be millions of "variants", which are coding differences from the reference genome. Which does not have any special status... it is just the genome of some guy from Buffalo. Variants (or alleles) are bases in the genome that differ from the reference. With three billion positions and four possible bases per position, that means that there are nine billion possible variants. How common is a particular variant in a population? That is its allele frequency. For GWAS and related studies, the threshold is commonly set at variants seen in the population at over one percent frequency, while minor alleles are seen under that frequency. A variant that causes some devastating disease is typically one that sprang up recently, and is heavily selected against. That is why it must have an exceedingly low allele frequency. On the other hand, a variant may have no discernable effect at all, not being selected for or against, thus just drifts along in the genome, not subject to natural selection. Such alleles may, over long periods of time, drift to higher or lower frequency by random chance.

However, the focus of GWAS association studies are variants between these extremes. These are variants that have some effect on a trait (or may be physically close to others that do, thus get "carried" along over time). At the same time, they are also common in the population, at least common enough to be discernable in an association study. Such a study needs some statistical correlation between the occurrence of the variant, and the occurrence of the trait. That means that the variant can not just appear once, but must appear many times over a large population. At the same time, a study that focuses on a trait like, say, high blood pressure, will be seeing variants that are, by definition, deleterious. That means that any allele with a large effect will be subject to strong selection, and driven out of the population. Only alleles with more modest effects will be able to survive at all, and even then, at low frequencies. So a GWAS focuses on medium-to-low prevalence variants, hunting for alleles on the loose in a large population that have typically modest effects on a given disease or other trait. Such alleles will have typically survived for tens or even hundreds of thousands of years, so they will have some complex relationship to natural selection. 

In contrast to all this is the family study, which focuses on a dramatic variant that causes some terrible disease. Such studies have been remarkably productive, because they deal with extremely rare, high-effect variants, which are as a rule very informative about the genesis of that disease. Such variants, as mentioned above, would be heavily selected against, thus disappear rapidly. But mutation is always happening, so all sorts of mutations arise in large enough populations. Assuming that, as biologists, we are interested in the core ten or fewer genes that most influence a given trait or condition, the hundreds or thousands of significant, but low-effect variants that come out of GWAS are almost by definition guaranteed to be tangential and minor. It turns out that most traits are complex, in the sense of being influenced in various minor ways by hundreds of genes.

So, what is the typical genetic structure of complex traits? That is- what this paper set out to answer. "Structure" in this case means ... what is the normal distribution of selective target / effect size versus frequency/prevalence in the population of variants that, in combination, add up to a complex trait? The assumption (as discussed above) is that the core armature of such traits does not have variants at all, due to strong selection, while the available variants in the population all have minor effects that in sum form the genetic variation seen in the trait in the population. 

While other researchers have attempted to fit the variation distribution of complex traits to typical formulas like the normal distribution, these authors found that a natural selection-informed approach gave a clear and simple result. All traits follow the same general scaling, with only two parameters- the mutational target size of the trait (that is, the proportion of the genome capable of appearing as relevant variants), and the effect that each site has on the given trait, termed (very poorly) the site's "heritability". It is important to note that every site in the genome is equally and fully heritable. The term refers to the trait, and the size of the effect from variations of that site on that trait. Summed over all sites in the genome and all variations in the population, this heritability ultimately equates to the overall variation of the trait that is genetically caused.

A comparison of two traits, and how they might look in a genetic variation study. In blue is a trait skewed towards small effect variants, with weak selection and consequently variants with higher frequency. In red is a different trait that partakes more from stronger effect variants. On the whole, this kind of difference is not common among complex traits that arise from thousands of loci. MAF = minor allele frequency; Z-score is the score in a GWAS study indicating how statistically significant the variant's effect on the trait is. Note how lower Z-score correlates with more variants at the higher MAF frequencies. At the same time, the GWAS method overall has some skew to higher MAF frequencies, since only those provide sufficient statistical power to get any results at all. Log(s) is the strength of selection; L is the genetic target size for the whole trait, and h*2 is the heritability, or proportion of the trait effect due to the causal variant.

The model they come up with accounts for the selective effect of trait effects (the larger the effect of the variation on traits, the lower its frequency in the population). It also accounts for the fact that variants that affect one trait often affect other traits as well, so the selective effect needs to be considered over all affected traits, most of which are probably unknown, but can be inferred. And conversely, most traits are composed of contributions from many genes and their alleles, sometimes thousands- they are genetically complex traits. 

The model the researchers come up with can normalize among the huge population of variants that affect a single trait, in this case blood pressure. Left shows the effect sizes of individual variants, and right shows the scaled (normalized) version from the paper's model, showing that all these variants follow the same overall rule / logic, using the custom parameters of h*2 and L- trait heritability and mutational target size. All this is to say that the lower effect variants (skewed to left) are assumed to have higher selection coefficients.

The researchers go on to show that various traits do look different under this analysis. Some differ mostly by target size, accounting for more or fewer variants, but having a similar spread of effect sizes over the population. Others differ by the scale of effects that each variant contributes, thus skewing toward higher or lower allele frequencies overall. Interestingly, they add an analysis of the age of these low-frequency, low-effect variants that are the grist for GWAS, finding that they are on average 137,000 years old. That compares with an average age of 600,000 years for variants that are neutral, thus would not come up in GWAS or be under selection. This is fascinating in its implications both for human population genetics in general, and for the fact that most human variation- even that under modest selection- predates the divergence between African and non-African populations. 

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Performing Search, as a Transcription Regulator

Billions of years have created some weird tricks in DNA search.

Search is all around us, as we increasingly rely on search engines to find everything we need on the internet, want to watch, or want to buy. Search looks into databases, which hold the sought-after information. All our accounts, all the domain names, all the products... everything is held in databases of one kind or another, and those databases are indexed in clever ways to provide virtually instant pointers from the question we ask to the answer held online. AI merely puts a linguistic gloss on this, and most people are still encountering AI first as a feature of search, such as the top of current Google search results.

Well, our genomes are databases as well- rich and ancient storehouses of jewels that encode the body and its doings. How does search work there, and what is search even for? At any moment, each cell of the body has certain needs, stresses, and goals, as expressed in its DNA programming. The tools available are proteins and RNAs, which carry out the cell's functions. The needs may arise from signals coming from previously expressed receptors, say, for insulin, which may trigger and tell the cell to take up glucose from the blood. The receptor turns on a kinase, which may turn on another kinase, which turns on a transcription regulator, which goes into the nucleus and ... does a search. This regulator is searching for places (specific sequences) in the genomic DNA where it can bind, after which it helps to turn on (or off) the nearby gene, executing the desired function / tool. 

General introduction to transcription regulators (or "factors") and their role in gene activation and the whole process of gene expression.

Obviously a very different kind of search than what Google does on our behalf across documents, but there are similarities. Internet search depends on patterns, matching the user's input with the vast corpus of the internet also held as text symbols. Transcription regulators match patterns, in this case patterns of DNA that they like to bind, which may occur only once in the genome, or occur tens of thousands of times. The pattern here is a complementary physical/electrochemical shape, rather than an abstract same-symbol match. The genome is, to a protein, truly vast. Our three billion-base genome is forty million times larger than an average regulatory protein of, say, fifty kilodaltons (kDa). Search is also, here, a difficult problem, which researchers have been wondering about for decades. Several recent papers discuss different aspects of the problem and shed some modern light on it.

We have roughly 1600 transcription regulators in our genomes, so there is something going on all the time. DNA is always being queried. And what it replies with is RNA- a transcript issued/copied from a gene, which either goes off to instruct creation of a protein, or is itself functional in some way. So, how do proteins bind to DNA, executing their search? It was transformative when the first atomic structures of such proteins were solved. They were clearly complementary with their DNA targets, with nicely positioned positive charges to mate with the backbone of the DNA and amino acid fingers reaching into the helix to feel the shapes of the nucleotides they wanted to bind. All very neat, and paradigmatic for bacteria whose genomes are quite small. But there is more to the story. Binding sites in human genes tend to be quite short- five to seven bases. That really isn't enough to be very specific, across a vast genome. Eukaryotes have developed several weird tricks, as it were, to encourage efficient search over much larger genomes and at the same time increase precision while maintaining evolvability and flexibility.

Eukaryotes have nucleosomes, chromatin, and packaging. The DNA is not just splayed out randomly, but wound up on protein spools. One would think that this would impair search by regulators. But paradoxically, there is a fine balance between hunting around on a given piece of DNA for a preferred site (one-dimensional search, 1D), and jumping off, letting go, and trying somewhere else (by diffusion; three-dimensional search, 3D). The compaction of genomic DNA into nucleosomes that wind up most of the DNA while leaving linking DNA in between free appears to provide a nice balance of landing spots that allow searching regulators to jump very long distances (in linear DNA terms) while not going very far in absolute terms. Regulators vary in how aggressively they can plow through nucleosomes to try out their internal DNA sites, but many (called pioneer factors) can do so.

Secondly, transcription regulators cooperate with other proteins to create longer, more complex DNA sites for precise gene identification and higher binding affinity. As biologists have characterized the enhancers and promoters of important developmental genes, they have found that DNA binding sites occur in bunches, and have much weaker effects when broken down and separated. Sometimes there is direct side-to-side cooperation between two regulators that bind the DNA. At other times, they combine with other non-DNA-binding proteins to create complexes at such sites. The DNA recognition sequences of these combinatorial sites can be changed significantly, even beyond (our) recognition, by the addition of cooperative proteins. This is something that makes prediction of where a given regulator binds particularly perilous. 

Thirdly, many regulators contain not only DNA binding domains, but also extra disordered domains that facilitate DNA search and binding. This has been a recent realization that accounts for some of the speed and flexibility of regulator search and DNA interaction in eukaryotes. The stable crystal structures of paradigmatic bacterial regulators are not the whole story, and indeed are insufficient to explain what is happening in the much larger setting of our own cells. The authors note that eighty percent of human gene regulators have large disordered domains, (called IDRs, for intrinsically disordered region), upwards of 500 amino acids long. These never showed up in crystal structures, naturally. Being disordered, they are also poorly conserved. So, they have been difficult to study. 

Comparison of binding by one regulator, MSN2, which has a large IDR, to its genomic sites. At top is its native binding pattern, across a whole genome. At bottom are mapped its core motif occurrences on that DNA. Second from top is the MSN2 protein mutated to contain only its core motif-binding domain, and third from top is the MSN2 protein mutated to remove that domain and retain everything else. Note how different the patterns of binding by each of these proteins are, though how each approximates to some degree the wild-type pattern.

In related work, researchers have divided up such proteins into the core binding site part and the IDR part. They find that both parts work partially, directing binding to some of the native sites around the genome. In fact, the IDR part does a more statistically accurate job than the core DNA binding motif. This is fascinating, showing that in eukaryotes, a new search mechanism arose, supplementing discrete and precise binding with a floppy / fuzzy code in the IDR and its binding sites. It turns out that regions of hundreds of bases around core target sites (which in one case amount to only the motif AGGGG) are preferentially bound by the respective IDR protein domain, with multiple weak interactions that remain structurally uncharacterized. In fact, neither the protein structures responsible, nor the DNA sites they bind are known yet, though deletion studies through IDR domains show that binding is distributed throughout.

Relationship between IDR binding site size, and the ratio of 1D vs 3D search time, by simulation. The bottom axis is size of the IDR binding region, the Y axis is time taken for search. Time spent in total (yellow) goes down to minimum at an optimum between 1D search that is slowed by longer IDR-binding regions, while 3D search is strongly accelerated by longer IDR-binding regions.

The combination of core binding and loosely unstructured binding in one regulatory / search protein provides powerful benefits. In dimensionality terms, if the effective landing site is expanded from five to five hundred bases, then the time required for 3D search through the space of the nucleus is dramatically shortened. Secondly, loose binding by the IDR then promotes an "octopus"-like 1D search along the local DNA, resulting in efficient settling on the core binding site to get ultimately precise positioning. The ultimate affinity of the regulator with the local DNA is also enhanced compared to what it could manage over a five base pair site. The researchers conclude that with these domains, the search problem is, in net terms, reduced by one dimension, from 3D to 2D. The surrounding areas of DNA that have marginal affinity for the IDR domain are called "antenna" regions, and the author's simulations show how they alter search behavior.

Schematic explanation of the current work, describing how IDR domains help to speed up the transition from 3D search through space, to 1D search across the DNA. And then also to facilitate 1D search by preventing full detachment from the DNA while the core binding motif continues to search by diffusion for its binding site (yellow).

For computers and databases, search is a huge problem that has led to technical innovation, as well as large drains on resources. Every search engine combs the internet, gobbling up all available information, creating indexes, and updating them constantly in order to give us the instant access we want. This infrastructure has been raised to a new level by AI, which transforms search into a new form, combining it with language translation and prediction methods that allow a search for corkscrew to bring back results for wine. Whether it understands anything is unlikely, but the desire to upgrade search from a simply determinative process to one that is more fuzzy and richly interpretive, and thus more useful, is not a new phenomenon.

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Only Little People Pay Taxes

Review of "The Second Estate", by Ray Madoff, about how the rich have excused themselves from paying taxes.

"A system that requires someone who earns $100,000 to pay almost 30 percent in payroll and income taxes while giving another person who inherits $10 million a free pass is indefensible."

As we head into the nation's birthday, we should take stock of how we are fulfilling its founding propositions and promises. There have been good and bad times, and one has to say that the current time, while generally prosperous, is extremely fraught. A psychopathic (and rich) demagogue is President, and the good will and respect we have spent these centuries building around the world is being rapidly squandered. Internally, the Republic is being gnawed by any number of ills, but one of the deepest is extreme inequality. Paul Krugman has commented on this a bit, comparing our current moment unfavorably with the Gilded Age. Despite the Occupy movement and glimmerings of democratic socialism, the rich are lording it over the rest of us more blatantly and destructively than ever.

Everybody loves money, but the rich have a special, and frankly dysfunctional, relationship. There is never enough, and always too much in taxes. When they are in power, tax cuts and cuts to the IRS. When they are out of power, complaints about the "death tax", and heavy political spending by cloaked groups to get back into power. And all the time, they invest prodigiously in the "wealth management" industry, whose job is mostly to cheat the government and avoid taxes. This is not civically enlightened, nor edifying, behavior. But since the rich have the levers of power, (being the first funding filter for all political candidates of either party), they have been successful getting what they want. As Madoff explains, the rich have by this point almost entirely excused themselves from federal taxation, putting the whole burden on labor income. As the saying goes, what is criminal is not what is illegal, but what is legal.

The first step was setting the capital gains tax rate to roughly half of the labor income tax rate, with a max of 15% for long term gains. This is excused in many ways. Much of investment gains come from inflation. Corporate profits are already taxed, thus this is "double" taxation. Or, that capital investment is just great and deserves lower taxation to drive economic growth. Or, that they raise taxes eventually, after they supercharge economic growth! Etc., etc. Obviously, these are all excuses, disingenuous at best. For the recipient of capital gains, they are income in the form of money, pure and simple, and they are gains on top of whatever they had originally invested. And these gains are unearned, in the sense that no work/labor was done- merely waiting. How that makes it somehow more deserving of love from the tax system is hard to understand. There should be a uniform tax rate for it all. 

The next step is inheritance, which is currently tax-free, as the estate tax is more or less a dead letter. It applies only to very large estates, and only to those dumb enough to not evade them through trusts, etc. This takes unearned income to a whole new level. No work was done here at all, other than being born to the right people. Nothing is earned or contributed to the country or economy. Inheritances should be taxed at the normal income tax rate, period. Not only are inheritances free, but their cost basis is stepped up to the time of death, so that redemption is now pain-free for the heirs, in terms of capital gains taxes. One could hardly imagine a less equitable arrangement.

Madoff then describes one unholy intersection of investment and inheritance, as the borrow-and-die technique. Rich people can let their investments sit untouched till death, so that their heirs get the whole amount, tax-free. In the meantime, they can take out loans from banks (having plenty of collateral) to live from. Such income does not apparently count to the IRS as income, and thus they can leave the debt to their heirs, who can pay it back with easy money when the time comes. All tax-free.

Additionally, Madoff goes on a lengthy discussion of charitable giving, which in the hands of our current rich has been degraded into a font of power and control, with very little giving. While the money given can not be taken back, (generating enormous tax deductions), there few rules about how rapidly, or how beneficially, the money needs to be given out. The rich now routinely set up donor-advised funds (DAF), which allow them to exercise ongoing control over investments, over the "charity", and over rate of disbursement. Not only that, but control can pass to heirs, establishing an aristocracy of putatively charitable pots of money, in addition to the non-charitable pots they are already getting. These points are all separate from the routine, and perhaps purposeful futility of most philanthropic giving, and the trend of cloaking political organizations (frequently dedicated to further reductions in taxes) in charitable garb. 

Thus the current tax system makes a mockery of this country's founding principles, and creates the mortal danger of an unbridled and perpetual aristocracy of wealth, increasingly influential over the political system. What is the solution? Bring all income under the same progressive income tax system- inheritances, capital gains, lottery winnings, wages, winnings, ... everything. And apply payroll taxes (that is, the funding streams for Social Security and Medicare) to everything as well. 

The US deficit is getting into dangerous territory. Social Security and Medicare are not fully funded past the next decade. What this book makes clear is that there is plenty of money to fund everything. What we are lacking is proper knowledge about the true state of play, and the courage to tax everyone equally from the income that they receive. The idea that, as cited at the top, income earned by the sweat of one's brow should be split with the government, while income that floats down unearned from a will should not be, is insulting to every working person and to the very idea of work. 

For, to take a step back, what is the point of having a society and an economy? It is not to enshrine an undeserved hierarchy of unjust power in hereditary perpetuity. It is to motivate everyone to work towards the common good. There are many kinds of work, but evasion of taxes and political corruption are probably not what count, to most people, or to our founders. It takes unstinting work to make a great society, and if the culture and rules don't foster that work, decline is inevitable.

• A fellow crank agrees with me.
• Let's kill Social Security!
• Let's make America ungreat!
• A new vampire squid.
• "Certainly we do the opposite of what Biden did"

From Icebox to Hothouse, and Back Again

Better modeling, by including the biosphere, retrodicts more of Earth's dynamic climate history.

Climate change, while ignored by the current administration, is not ignoring us. The Earth is warming well past where it has been for millions of years. But before that? While the planet has generally had stable climates, they have varied substantially through time, and have gone through occasional catastrophes. There was a little ice age, in the middle of the last millennium, thought to have been caused in part by the depopulation of the Americas due to European diseases. The ensuing regrowth of forests covering the Americas drew down CO2 from the atmosphere and cooled the climate. But more to the point, there have been far more severe episodes, both of heat (the end-Permian extinction event) and cold (the Sturtian glaciation of the Precambrian). All of these arise from CO2 levels, as CO2 is the master controller of heat in the atmosphere, thanks to the greenhouse effect. (As it is on Venus as well.) 

For example, the end-Permian extinction is thought to have been caused by unusual volcanism in what is now Siberia. Over a mere 100,000 years, this poured an estimated 26,000 petagrams of CO2 into the atmosphere, causing its concentration to shoot up to about 2500 ppm (parts per million) and temperatures to shoot up as well, killing off 90% of all species. What we are doing now is much faster, though admittedly in early days. We are pouring roughly 11 petagrams of CO2 into the atmosphere yearly, which has raised CO2 concentrations from a preindustrial 280 ppm to 427 ppm today. It would take us another one to two thousand years to cause a 90% extinction event!

A bedrock of our climate thermostat is the silicate cycle. Since the vast majority of carbon on earth is locked up in rocks, (carbonates of silicon, magnesium, and calcium), not in the biosphere, it is rocks that have a dominant effect. Volcanoes belch out CO2 in huge amounts. That CO2 slowly eats away at rocks that are exposed, re-forming carbonate compounds that are weathered off and back into the ocean. Where these compounds (with those built by shelled animals of all kinds) are gradually deposited on the sea floor and subducted back into the Earth's crust. Some of those carbonates are reduced at depth and brought forth again by volcanic activity. The more CO2 there is in the atmosphere, and the warmer it is, the more weathering happens and thus the faster CO2 levels are brought back down. That is the elegant thermostat that has kept Earth at mostly mild temperatures through its long history. 

However, this is a slow thermostat, taking hundreds of thousands of years to equilibrate. Unusual events, like an asteroid impact, prodigious volcanism, or the advent of human ingenuity, can make a mess of things way faster than the silicate cycle can deal with in its slow, grinding way. Many subtler influences can also come into play, like cycles in the tilt of the Earth towards the Sun, or continental arrangements that lead to particular patterns of ocean circulation, can create variations such as ice ages. A recent paper brought out peculiar influences from the biosphere that can also affect, and even destabilize, the thermostat on longer time horizons

The oceans are responsible for roughly half of photosynthetic productivity, and they are also where the carbonate minerals get buried. So how they react to changes in the atmosphere are very influential in the whole cycle. These authors ran half-million-year simulations of climate perturbations while including not only the silicate cycle, but also reactions by the biosphere and especially the phosphorous cycle, which has a strong influence on biological productivity. It turns out that when the atmosphere has lower levels of oxygen than we do today, (as was the case during the Precambrian epoch), high CO2 levels cause long-term rises in biosphere productivity and also in phosphate recycling out of the ocean floor. The extra phosphate increases biological productivity even more, and thus causes CO2 drawdown to persist past where the silicate cycle would level out for the long term. The result can be a rebounding ice age after a hot phase. 

Model results over 500,000 years, showing rebound from an injection of high CO2 at year 10,000. A shows concentrations of CO2 over time, B shows O2 concentration, and C shows sea ice, which goes to zero at first, the rebounds sharply, especially under the blue condition of 0.6 times current oxygen concentration in the atmosphere. It shows how exquisitely sensitive the climate is to CO2.

These models make some sense of the Precambrian climate cycles, which had a few dramatic swings that went through so-called snowball Earth phases where the entire surface of the planet seems to have iced over. The silicate cycle naturally came to the rescue eventually, spewing enough CO2 from volcanoes to overcome the snow / albedo effects of all the ice and cause a rebound hot phase. Between the rising oxygen levels and the extreme climatic swings, the stage was somehow set for the rise of animal life, leading the so-called Cambrian explosion, though there was a fair amount of simpler precursor animal live in the Precambrian.dd

https://www.science.org/doi/10.1126/science.adh7730

A schematic of the proposed cycle, with CO2 coming in from vulcanism (red) and being disposed of by various means, first and foremost the silicate cycle (blue). OC = organic carbon, P = phosphorous/phosphate, OCpetro = organic carbon weathered out of sediments, coal, limestone, and other geologic formations. Thus, the brown color shows this paper's additions to the classical silicate cycle.

While it is just a modeling paper, models are what we think and do in science. It is nice to have laboratory confirmation for areas of science (like molecular biology) that permit it, but historical sciences, especially those pertaining to whole planets as systems, have to be more forensic and speculative. This new model is a refinement on the basic silicate cycle, and thus seems a strong improvement on what has heretofore been a science of more or less back-of-the-envelope estimation. And judging from this new model, the authors propose that the next ice age is not being put off indefinitely by our profligate emissions, but rather that organic burial feedbacks will bring it closer (than 400k years away) with additional overcooling thereafter!

• Medicine is toast. "MIRA outperformed physicians in diagnostic accuracy and made guideline-concordant, medication-safe and appropriate admission decisions."
• A death sentence for US science.
• Revaluing trash.
• Apparently, fungi in the ocean are a thing.

Vindman on Russia and Ukraine

Not enough appeasement, or not enough deterrence?

I have been watching the Harry Potter series of films, a decade or two after first reading the books. Aside from being extremely entertaining, they show Rowling to have been weirdly prescient about the moral dilemmas only developing as she was writing, and now flourishing in grotesque fashion. How large sectors of supposedly civilized populations can be attracted to blatant racism. How cruelty, destruction, and contemptuous corruption can likewise become an attractive political brand. How corrupt powers corrupt the truth first, and then replace merit with lickspittle devotion among their followers, with predictable consequences. What seemed comically phantasmagoric has now turned into our day-to-day reality, with phones taking the place of wands.

It is not only relevant to US political scene, but also internationally, in the turn taken by Russia from a struggling post-Soviet democracy or at least quasi-democracy, back to an imperial emperorship under Vladimir Putin. After sending clouds of misinformation into the West, he started attacking Georgia and Ukraine with dementors, trying, without success so far, to squeeze the soul out of his "little brother". 

Alexander Vindman has something to say about the matter, in his new book, "The Folly of Realism". Vindman came to fame through his testimony against Voldemort, -er, Trump- during the first impeachment hearing, which revolved around corrupt conditioning of aid to Ukraine to get false political testimony against his foes. Vindman was on the NSC, and had participated extensively in Defense department and White House policy development around the changing conditions in Ukraine and Russia. His book recounts the long historical road that led to the current Ukraine war, and the many missteps by the US that are now part of that history.

The question is about US policy around the catastrophe in Ukraine- what was the US role in it? What should our policy have been, and what should it be now? The "realism" in Vindman's title refers to the foreign policy school that foreswears idealism. It says that we should ignore any sympathetic feelings about democracy or independence for Ukraine and recognize that Ukraine was always going to be in Russia's sphere of influence and not get tangled up in its defense. Under this reading, our policy mistake was to lure Ukraine towards the West with empty promises of joining NATO and the EU, while our paramount interest was actually in maintaining a stable relationship with Russia so that no one starts World War 3. 

On the other hand would be a more values-based, idealistic approach. Under this reading, our promises were not wrong, only our unwillingness to back them up. It is patently obvious that neither Russia nor anyone else is going to use nuclear weapons in these kinds of conflicts- that would be self-defeating when the aim is to gain territory and population (or even to defend one's own population, when pitted against other nuclear powers). In all honesty, having nuclear weapons is more of a prestige thing at this point than a real factor of military strategy, let alone tactics. But to give Putin his due, he used them with consummate skill, rattling the nuclear saber at critical times to cow the West and particularly the US from intervening in Ukraine, much to our shame.

Idealism posits that our interests are inextricably linked to our values. There are no durable and dependable international relationships without shared values, and we should be extremely grateful that, at least up to the current administration, the liberal West has had a solid core of shared values that undergird our entire collective security structure. Thinking that we can pursue "interests" that conflict with those values is chimerical and tends, as we are seeing in the current administration, to sell out and destroy exactly what is most valuable to us on the international stage. 

But perhaps even worse than the philosophical differences within the US policy establishment that led to the schizophrenic and catastrophic approach to Ukraine was the inattentive way we sleepwalked into it. Emblematic of this is Obama's "reset" with Russia. Even after Putin had declared that the loss of the Soviet empire was the most catastrophic event in the last century, even after Russia attacked and set up a simmering conflict with Georgia for trending democratic, even after Russia had spent years pumping offensive and destabilizing propaganda into its enemies in the West, Obama was anxious to get Russia off his plate and initiated the reset. This was a policy of turning a blind eye to all the geopolitical trends that clearly showed that Russia was not going to be a democratic partner to the West, but was, on the contrary, heading rapidly in the opposite direction, despite the window dressing of Dmitri Medvedev. More specifically, it failed to recognize that Ukraine was in mortal peril from these trends. The prior president Bush had declared that his ultimate goal was to bring Ukraine into NATO. But no plan was offered, no timeline or support was given, even while Russia's apoplexy over the prospect was, to those who were paying attention, growing by the year. 

Current status of NATO. Whatever the rhetoric, the new eastern European members of NATO are members in order to defend themselves against Russia. The whole point of NATO is to unite Europe defensively against Russia. Naturally, Russia takes this as an insult, but the history is self-explanatory, as is the same historical reasoning in case of Ukraine. As long as Russia takes no responsibility for its many past crimes, and its current lies, offensive behavior, and ongoing crimes, there can be no question of reversing this fundamental relationship.

The reset ignored all this and assumed, as we all did, that a new war in Europe was inconceivable- whatever complaints Russia had would be raised in some appropriate forum. During this time, Russia was carefully playing its cards for Ukraine, using Paul Manafort to dress up its proxy, Viktor Yanukovych, electing him president, and getting him to cancel progress towards joining the EU. Unfortunately, in 2014, the Ukrainian people wised up to the direction all this was going, and ousted Yanukovych in a popular uprising, sending him fleeing to Russia. Immediately thereafter, Russia extracted its pound of flesh, invading and taking over Crimea, and for good measure starting a war in Eastern Ukraine, to be kept on the simmer. 

All this should have been foreseen by US policy makers. But instead, they had their reset, with a few temporary benefits weighing against the disastrous direction portended by Russia's actual policies and intentions. If the US model for Ukraine was the same as for Belarus, we should have been honest about that and not promised any future relationship or alliance such as NATO. We should have clarified that Ukraine was in Russia's sphere, and tough luck.. they would have to deal with the neighbor that nature had dealt them. On the other hand, if we truly valued the independence of Ukraine and its civilized aspirations, in light of its being in its own right a very large country, both in area and in population, then we would have put more effort into deterring Russia rather than appeasing it. 

Ukraine was not ready for NATO membership- that much was understood. We can see by the example of Hungary how dangerous it is to have backsliding, regressive and frankly traitorous countries within the alliance. Ukraine's democracy was by no means ready for full membership. In light of that, the US should have offered a direct security relationship, as the Georgia war played out, to put teeth behind our desire for Ukraine to remain independent and work out its own relationship with democracy and with Europe. The point was not to influence the government or people of Ukraine, but simply to deter Russian meddling. For by this time, the truth was visible- that Russia wanted to rebuild its empire / sphere of influence, whether its neighbors wanted to be assimilated or not. The race was on, between the gathering strength and determination of Russia to recover "its" former possessions, and its neighbors' growing sovereignty and ties to Europe. 

One might ask.. how is this model different from Vietnam? Wouldn't this have tied us to a corrupt government that would have been fatally impaired, politically speaking, by taking assistance from the US? Wouldn't Ukraine have come to rely on our security crutch, while thumbing its nose at Russia and miring itself ever deeper in corruption and dysfunction? I think the differences are significant. Firstly, the Ukraine war had not happened yet. We would be deterring, not trying to repel, an attack. Secondly, the ultimate prize of European integration remained as a more significant goal, quite beyond any bilateral relationship with the US. It is clear that the people of Ukraine were quite strongly motivated in that direction, and part of that was gaining a functioning liberal political system.

As a Ukrainian by birth, Vindman was and is appalled by the path to war, some of it paved by the US. He is casting about for historical counterfactuals and alternative paths, and, given the dysfunctions of our own political system, those are hard to come by. Perhaps preventing the first election of Donald Trump would have been significantly more productive than any policy adjustments farther back in time.  But I have to agree that our split-the-difference approach to Ukraine, which was initiated in the Bush administration, was fundamentally in error, and was a temporizing solution (which the Obama administration fatally continued) to a problem that turned out to be far more urgent than was anticipated. Though it should have been anticipated.

• Are we second-rate yet?
• There's something about postmodernism... 
• War is now IT.

Strides in Cancer Treatment

A new paper shows that CART therapies can be unleashed against solid tumors.

We are finally in the payoff period in the decades-long war on cancer. Slowly, painfully, precision approaches are being developed to treat specific molecular lesions in ways that are superior to the old blunderbuss kill-everything approaches. At first, these treatments had only marginal effects, at astounding costs. But increasingly, the effects are lengthening and cures are in sight in some forms of cancer. One unexpected area of revolutionary progress has been immunotherapies, which in various ways help our immune systems attack cancers. It turns out that many cancers have tricks to hide from the immune system, and once those tricky dampening molecules are circumvented, dramatic reductions are possible. One paper recently described an anticancer vaccine made up of a witch's brew of targeting molecules, cancer antigens, and adjuvants, that achieves strong anti-melanoma action.

Another one of these immunotherapies is CART, or chimeric antigen receptor T-cell therapy. T cells have a receptor repertoire, just as B-cells do, which target things to be attacked- foreign pathogens, diseased states, etc. at molecules called antigens. One problem in cancer is that the cells are, originally at least, our own, so they mostly evade immune detection by having few "foreign" antigens. But there are nevertheless some antigens, comprised of normal molecules that are out of place (such as DNA found outside the cell) and "neoantigens" that are proteins expressed from the mutations in cancer cells. Additionally, as mentioned above, cancer cells express additional molecules (PD-L1) that can dampen even the immune response that does get generated by these few cancer antigens. So, the chimeric part of CART is taking the patient's own T-cells and engineering some of them to express new anti-antigen receptors that are relevant to the patient's cancer. Perhaps there is a mutant fusion protein that the cancer depends on. Perhaps the cancer displays an unusual surface molecule. Perhaps the tables need to be turned and PD-L1 targeted. There are many possible targets. 

CART therapies have, to date, been mostly directed at blood tumors. Solid tumors have extra protection in their micro-environments, and have not been good targets, though they necessarily have blood supplies and thus exposure to systemic T-cells. A recent paper blows open this field by revealing a magic molecule that plays a very significant role in the structure of solid tumors- the urokinase receptor. The urokinase plasminogen activator receptor (uPAR) is heavily expressed on senescent cells and many solid tumors, but rarely expressed elsewhere. Indeed, its expression correlates with tumor aggressiveness. Plasminogen is a protease that is sort of a cleanup crew for the circulatory system and body generally. It breaks up blood clots, and digests follicle tissues allowing ovulation. It encourages wound healing and discourages fibrosis- the buildup of scar tissue. However, in the cancer setting, the same activity seems to encourage fibrosis in a sort of constant wound healing state. Reviews in this field are rather confused about the direction of action. But one thing is clear- uPAR has myriad signaling activities relevant to tissue repair and immune activation that are not all dependent on the uPA (plasminogen activator) and plasmin activation system. Indeed, it is expressed not just in cancers, but in many other fibrotic settings.

A wide array of proteins are assessed here for their expression in a cancer tissue sample. uPAR is in red at the upper left. The matrix on the right shows the correlation of expression in a wide variety of cell types and tissues, like cancer-associated fibroblasts (CAFs), monocytes/macrophages (Mo/Mac), and with the protein fibroblast activation protein alpha (FAP).

The authors sought to target CART cells against uPAR, principally as a targeting device, since this marks many solid tumors and correlates with metastasis and rapid cancer progression, in addition to inflammation and fibrosis. While only tested in mice, the results were remarkable. 

"CAR T cells targeting the D2-D3 domain of uPAR display broad antitumor activity in xenograft, syngeneic, and patient-derived models, including in adjuvant and combination settings, supporting the concept that targeting conserved malignant cell states can enable therapeutic strategies that transcend tumor type. ... our prior work shows that uPAR CAR T cells targeting senescent cells remodel fibrotic tissues, and, as shown herein, this remodeling is associated with CAR T cell infiltration and cytotoxic activity. Similarly, parallel work demonstrates that uPAR CAR T cells exhibit potent efficacy in glioblastoma models and can co-target supportive stromal cells."

This is to say that these CART cells target not only tumor cells, but the surrounding solid tissues (stromal cells) that they rely on. That is the key to defeating solid tumors. It also indicates that other autoimmune and fibrotic conditions may be addressable with this therapy as well. 

Treatment effects from the CART therapy in mice, against several tumors. The red graphs are controls, and the blue graphs are treatments. Top is the tumor volume over time, while at bottom is survival of the mice over time.  Lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), high-grade serous ovarian carcinoma (HGSOC), and pancreatic ductal adenocarcinoma (PDAC).

The results of treatment of xenografted human ovarian tumors into susceptible mice, at 3 weeks, bottom. On the left is the control, while the other two sets were treated with CART cells against uPAR.

The authors note that relapses were seen occasionally, but that in these cases, the uPAR target was still highly expressed. That suggests firstly that it is difficult for tumors of these targeted types to do without uPAR, and secondly that something else went wrong with the tailored CART therapy, other than that its target went away. Perhaps future work can enhance its penetration or activity. The researchers also strained to make their model systems as human-relevant as possible, using cancer tissue transplanted (xenografted) from human cell lines, human CART cells, and mice with transplanted immune systems from humans. This work is thus not only a scientific breakthrough of the highest order, but is a technical tour de force as well. It also ends up with a variety of patent declarations and commercial ties, indicating that this breakthrough is being fully milked by its inventors and commercialized at breakneck speed.

One major problem with this mode of therapy is that CART cells require a great deal of engineering. First, antibodies against uPAR were developed in mice or other species. Then the genes from those immune systems were recovered from those mice, to get the precisely recombined gene that expressed the antibody with highest binding activity against uPAR. Then that gene, hooked up to new transmembrane and intracellular domains, (specially selected to activate the T cell they will be put into), was introduced into a transformation vector and put into the T cells collected from the diseased mice. In humans, this treatment routinely runs a half a million dollars. It is incredibly ornate, and one expects that gene therapy will someday allow the patient's T cells to be directly modified in the body, without all the collection and laboratory work, (which takes months), given a high-quality gene encoding the antibody fragment that is generally applicable- not tailored to a specific patient.

• The example of Spain.
• AI does insurance... as you would expect!
• AI is not what it is cracked up to be. And way more expensive than it has to be.
• Japan is surprisingly willing to keep importing fossil fuels, despite exchange rate degradation.
• Renewables and batteries have stabilized California's grid and made electricity cheaper.
• Map of where electricity has gotten more expensive in the last year.
• How other animals deal with inequality.
• What economic warfare looks like.
• Can we survive the internet?
• Electric cars are good for everyone.

What is the Matter With the Labor Market?

Labor's share of the economy has rarely been lower- what is going on?

We will start with a graph of share of income, to labor, vs capital. Note that labor here includes all the highly paid executives- all those fat salaries. The share has been going down for decades, while the profit and capital share has been going up. The seventies were the high-water mark, when unions reached their apogee, and after which the Reagan revolution put business and management back in the driver's seat. 

Labor's share of national income is at an all-time low.

The neoclassical theory of labor is that businesses will hire as many employees out of a perfectly liquid labor market until the last hire is exactly as productive as her labor cost. Every worker would be hired into their most productive possible job, with the commensurate pay. Over the economy as whole, this mechanism would mean that everyone who can be productive will be employed, and that every company produces as much as it can sell. And also that wages grossly equal the productive capacity of the workers, as judged by what buyers are willing to part with. 

In a very rough sense, there is logic to this model, which at least has the virtue of generally equating what is being spent by buyers with what companies are making as revenue and paying out for their inputs, including labor. But there are a lot of problems when you get into the details, making the whole topic of labor market operation and wage-setting far more complicated, and far less fair, than capitalists and their favorite economists envision. It is a bit like the market for medical care, which has grievous flaws. One wouldn't want to go to a Stalinist system of state job assignment and wage-setting, but that doesn't mean the market mechanisms are operating fairly and efficiently.

One would have thought that the internet, enabling rapid and nation-wide job posting and hunting, would have fundamentally changed the job market, in favor of workers. But the graph above disagrees- things have gotten worse instead of better. One thing that internet job boards do not mention is pay. That remains a closely held secret, never discussed with workers or with prospects, until the moment when they have already been reeled in and gone through numerous interviews, and the low-ball is offered. There are many other structural asymmetries and power dynamics. Productivity is extremely hard to gauge, and ends up being whatever one's manager gets into her or his head. The whole job-finding process is extremely averse, full of humiliation, uncertainty, and pain, enforcing inertia in current employees, and thus power for employers. 

For example, a paper from a few years back shows that, when women enter a profession and change its composition, the pay across that profession goes down. The scholarly language is restrained, but the lesson is obvious. Pay is set by intuition and power relations, not by an analysis of productivity, or the magical workings of a fair labor market. The 80's started the greed-is-good movement in American business, as executives were empowered to take pieces of the business for themselves. Before, managers were employees, often well paid. Now, their pay became increasingly an expression of power rather than productivity- how much they could extract from the business as rent. Naturally, the more money from the business (whether via salary, stock, or other benefits) went into executive's pockets, the less was left over for workers. Similarly, the whole theory of business underwent a change as well, from an organization with multiple stakeholders and purposes, including civic ones, to a singular focus on profit and rewarding investors. Labor ceased to be involved as a stakeholder, but was demoted to an input, to be paid as little as possible. 

One additional influence is the idea of the sufficient wage. Most people are most keenly interested in having income sufficient to live on, in some style considered in their social sphere to be decent. When wages across society fall below this level, revolutions occur. But do wages ever rise above it? Employers are sensitive to these dynamics, and as part of their wage setting know what workers will put up with, regardless of productivity, fairness, revenue, etc. This is particularly relevant with the addition of women to the workforce. What used to be regarded as a decent wage, in that it supported a family, now only has to support half a family, since most families have two earners. The perverse effect of women entering the workforce is thus, on this admittedly vague social theory, not only to subject them to outright socially based discrimination, but to lower the general level of wages, insofar as employers can get away with that without generating an insurrection. 

The value of the federal minimum wage over time.

Now we are at a dramatic point, where a soaring stock market rides on ever-higher profits taken by US businesses, while a vibe-cession and plunging consumer sentiment show that most Americans are struggling, unhappy, and underpaid. Billionaires are sprouting like mushrooms, each of whose dollars is taken from the hands of labor. So what is fair, and what do workers deserve? We need to take a whole-society view here, rather than confining ourselves to what pure capitalism sees as an ideal. Much of income inequality comes from a minimum wage that simply has not kept up, not even with inflation, let alone with worker productivity. A recent book outlines much of the evidence, but it is well known that raising minimum wages is hugely positive, increasing economic activity and helping low-power workers get a fairer deal out of the system, at very little cost to job creation or profits. The authors suggest (very modestly, one must say) generally keeping minimum wages at sixty percent of the median wage, which is currently 64,000 per year, thus would work out to about $18.50 per hour. Lower pay than that generally reflects power dynamics of oppression, and feeds into bad working conditions and the maintenance of low-value industries.

At the upper end, a new social contract needs to be drawn up to re-orient the corporation to a more socially positive role. Competition, which is the most important discipline on businesses, needs to be fostered. Taxation needs to be raised and made fairer, removing escape hatches, offshore shelters, conduits, etc. Capital needs to be taxed at least equivalently with labor, not less, as is shamefully done now. The chances of any of this taking place in the corrupt environment of the current administration and congress is nil, obviously, but if they won't do it, then the workers they are so blatantly betraying have the votes to forge a new path.

Notice that these are not technical issues, but social ones. The growth of inequality and loss of labor's wage share is a story of lost social cohesion, self-serving ideologies, and political corruption. Hopefully we do not need a crisis on the scale of World War 2 or the Civil War to recover some degree of care for each other, but the current environment would need a dramatic reversal to even begin going in that direction.

• More on the debt.
• How can this staggering loss be sold?
• When labor gets out of hand.
• When companies become tax cheats. We all should have a Carribean subsidiary!