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Sony’s new 1440p OLED gaming monitor seems a lot better than its first
Same great, low-profile design, updated specs.
Dr. Baker Presents Midwestern University's Vision for the Future of Healthcare Education
Executive profile in The CEO Magazine focuses on Midwestern's commitment to One Health and cutting edge education
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NFL Draft Profile: Michigan Football DL Tre Williams
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Argentine bishop offers advice to young people who wish to enter politics
Bishop Juan Liébana of Chascomús, Argentina, describes the ideal profile of a politician: a person of great virtue and integrity intent on building a better society.
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Follow the spark, choosing new Nashville artists to profile
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Chris Bell NFL Draft Profile
Doug watches the college film to assess Chris Bell's strengths and weaknesses as well as what it likely means for his NFL future.
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“AI polls” are fake polls
A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.
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Viewpoint: FP10 should remain open, excellent and secure
Europe is right to worry about research security. Foreign interference is real. So is the misuse of sensitive knowledge. Universities working in sensitive areas such as AI, quantum, semiconductors and advanced materials cannot afford to ignore the geopolitical environment around them.But Europe is in danger of drawing the wrong conclusion, one that would increase, not reduce, its strategic vulnerabilities.If the EU applies an “EU preference” logic to the next Framework Programme for research and innovation (FP10), it will weaken one of its greatest strategic assets: a research system built on openness, excellence and international collaboration. In the name of security, Europe could end up advancing science more slowly, innovating less effectively and making itself less attractive to global talent and partners in advanced science and technology.That would be a serious mistake.The EU preference included in Article 10 of the proposed European Competitiveness Fund may make sense in some industrial or deployment contexts, but is far harder to justify when applied to collaborative research in advanced science and technology, where excellence and global connectivity are crucial. Research is not procurement. It does not thrive when isolated. It advances through access to the best ideas, the best people, the best facilities and the best data, wherever they are found. This is why FP10 should not simply absorb industrial policy logic by default. Doing so would risk importing instruments that are ill-suited to research and that ultimately increase vulnerability rather than resilience.For universities of science and technology, the issue is especially acute. These institutions sit at the frontier of knowledge and technology creation in the very fields Europe sees as critical for its future competitiveness and resilience. They know better than most that security risks are real. But they also know that openness and security are not opposites. In practice, they have to be made to work together. Research security is not about closing doors. It is about building resilience through collective responsibility, trust, proportionate safeguards and better governance. That is a fundamentally different approach from default restriction.The risks of non-collaborationThe real danger in the current debate is that Europe talks too much about the risks of collaboration and not enough about the risks of non-collaboration. Those risks are strategic too. Cut researchers off from international networks and Europe loses access to knowledge, data, infrastructures and talent. Slow down global collaboration in critical technologies and Europe slows down its own progress on cutting-edge science. Make participation rules unpredictable and Europe weakens its attractiveness to researchers and investors alike.In other words, over-restricting collaboration will create strategic vulnerabilities, particularly in advanced science and technologies.This point is often underestimated in policy discussions that frame openness mainly as a value to be defended. Europe’s scientific strength, technological development and long-term competitiveness depend on remaining connected to the best research ecosystems in the world. For a continent that wants to accelerate deep tech, strengthen industrial capacity and reduce strategic dependencies, weakening the excellence base would be self-defeating. That does not mean ignoring risk. Quite the opposite. Universities are already strengthening due diligence, internal governance, awareness-raising, screening procedures and compliance support. Across Europe, institutions are working to manage risks linked to foreign interference, sanctions, export controls and the misuse of research. The right response is not complacency. It is better risk management. But that means targeted, evidence-based and proportionate measures, not blunt top-down restrictions with wide spillover effects. In the daily reality of universities, openness and restriction often coexist. The real challenge is how to apply safeguards without sliding into securitisation that damages academic freedom, open science and international cooperation. Restrict partners, not nationsMore restrictive treatment of collaborators from European Economic Area members Iceland, Liechtenstein and Norway, or from Switzerland and the UK, is strategically very difficult to justify. These are deeply embedded partners in Europe’s research and innovation ecosystem. Beyond that, Europe should still resist default exclusion and instead rely on case-by-case assessment. The relevant question is not nationality in the abstract. It is the actual risk profile of a collaboration: the institution, the affiliations, the field, the knowledge involved, the intended use and the safeguards available. Screening should focus on institutions and affiliations rather than nationality alone. Related articlesParliament ‘misreads’ link between Horizon Europe and ECF, Commission official saysFrustration grows at governance gap in next Horizon EuropeIf EU preference logic is imported into research without careful calibration, the likely result is a chilling effect. Researchers may step back from legitimate and beneficial collaboration, even where risks are manageable. International partners may see Europe as less predictable. And Europe may end up undermining the very excellence base it needs to compete, scale up and lead in strategic technologies, thereby increasing its dependence on others.FP10 should do the opposite. It should remain open by default, with restrictions used only exceptionally, and then on the basis of clear evidence. It should integrate research security into open science and research integrity frameworks, not set them against each other. And it should recognise that academic freedom, scientific excellence and responsible international collaboration are not obstacles to Europe’s security, they are part of it. Europe needs stronger tools to protect itself. But it also needs the discipline to avoid measures that would weaken it and increase its strategic vulnerabilities in the process. In FP10, that means staying open, excellent and secure.Louise Drogoul is senior advisor for innovation and sustainability at the Cesaer university association.
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GMB Management Software for Multi Location Business
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Migration can influence cardiovascular risk profiles, study shows
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OC Insider: Food, Sports & Entertainment - Orange County Business Journal
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Jonah Coleman Analytical Draft Profile
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Scientists Stunned: Colossal Eggs Discovered 3,500 Meters Beneath an Active Volcano
Beneath an active seafloor volcano off Vancouver Island, researchers have documented a congregation of giant eggs at roughly 3,500 meters, a discovery that reframes how life can flourish under extreme conditions. The eggs belong to the Pacific white skate, an elusive deep‑sea species adapted to cold, crushing pressure and perpetual darkness. What seemed an unlikely nursery is actually a geothermally warmed refuge, where subtle heat helps embryos survive a marathon incubation. The finding links volcanic energy to a quiet engine of biodiversity, turning a hostile landscape into an incubator. A living volcano, a hidden nursery The seamount long assumed dormant now exhales mineral‑rich, shimmering plumes, proof of hydrothermal life at depth. Expedition cameras swept across black basalt and pale bacterial mats, revealing vents that pulse with warmth. That warmth, though modest by human standards, alters the physics of development for cold‑adapted embryos. In a realm where metabolism creeps, even a few degrees can mean faster growth and higher survival. The volcano is not only active; it is ecologically formative, drafting a blueprint for a thriving oasis. Giant eggs and a skate built for the abyss The Pacific white skate, Bathyraja spinosissima, is built for the abyss: broad wings, armored spines, and a life history that trades speed for endurance. Females lay outsized, rectangular “mermaid’s purses,” often 46–50 centimeters long, packed with rich yolk to fuel years of growth. In the frigid deep, embryos can require around four years to hatch, a timeline that magnifies every energetic advantage. The scale is striking—large eggs, large adults, and a textbook case of deep‑sea gigantism. The volcano’s gentle heat may literally shave months or years from the wait. Why heat matters at the bottom of the sea Hydrothermal circulation delivers low‑level warmth without the turbulence that would scatter fragile egg‑cases. Slightly elevated temperatures accelerate enzyme kinetics, nudging development along while keeping embryos within a safe range. Mineral‑laden fluids likely shape local microbiomes, which, in turn, can influence biofilms on egg surfaces. The environment acts like a slow, steady incubator, countering the deep sea’s tyrannies of cold and scarcity. For a species with long maturation and few offspring, every incremental boost compounds across generations. An ecosystem sculpted by fire and water Seafloor volcanoes create steep environmental gradients, stitching together hot vents, cool eddies, and mineral gardens into mosaic habitats. Microbes harvest chemical energy, seeding food webs that support crustaceans, fishes, and skates. Cameras documented egg‑cases nestled among rocky ledges, near communities nourished by vent‑driven chemistry. These islands of productivity behave like deep‑sea oases, sustaining life far beyond the vent orifice’s flickering light. The nursery’s success underscores how geological forces engineer biological opportunity. “Finding a cradle of life tucked beneath a breathing volcano reminds us that the planet’s harshest places can be profoundly generous.” What the discovery could change The nursery reframes conservation priorities in regions where volcanism quietly underwrites reproduction. Protecting hydrothermal corridors could safeguard entire lifecycles, not just charismatic adults spotted during occasional surveys. It also sharpens questions about how climate‑driven shifts in ocean circulation might influence vent activity, temperature fields, and embryo survival. With methodical mapping, time‑series cameras, and environmental DNA, scientists can track whether nurseries remain stable or drift with geologic rhythms. Key implications include: Enhanced understanding of deep‑sea reproduction at hydrothermal sites. New conservation targets centered on geothermal nurseries. Comparative studies with other volcanic regions, from the Galápagos to rift zones. Biotechnological insights from organisms adapted to long, cold development. Better models of how seafloor heat shapes regional biodiversity. Methods behind the revelation Remotely operated vehicles threaded through chimney fields, gathering video, temperatures, and mineral signatures. High‑definition imagery captured the distinctive, horned egg cases, their edges dusted with fine volcanic silt. Geochemical profiles mapped how heat and chemicals disperse, outlining the “thermal lanes” where eggs most cluster. Combined, these datasets reveal a nursery organized by geothermal topography, with egg‑cases concentrated in pockets of gentle, sustained warmth. A fragile boon in a changing ocean Deep‑sea environments feel remote, yet they intersect with global pressures: mining proposals, cable routes, and shifting oxygen levels. The nursery’s resilience hinges on stable heat flow, intact substrates, and minimal disturbance from noise or sediment. Safeguarding such places is not just about protecting novelty; it preserves a slow, ancient strategy that lets large, long‑lived animals endure in the coldest reaches of the Pacific. Where geology and biology meet, the planet’s deep time still writes living stories. This volcano‑warmed nursery adds a vital chapter to that story, revealing how subtle thermal gifts can tip the scales toward life in the abyss. With each dive, researchers trace the contours of an unseen world, where fire feeds water, and water—against all odds—feeds the future.
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The Razer Blade 16 has Intel's latest Core Ultra 9 chips and up to 64GB of LPDDR5X-9600 RAM.
Glyphosate: A story of science, risk, and nuance
In the summer of 2014, a California groundskeeper named Dewayne Johnson started noticing patches of raw, weeping skin spreading across his body. He had spent years applying Roundup, Monsanto’s glyphosate-based herbicide, for a school district, sometimes drenched in it when equipment malfunctioned. By 2014, he had a diagnosis: non-Hodgkin’s lymphoma. In 2018, a jury awarded him $289 million in damages, later reduced on appeal. Tens of thousands of lawsuits followed. The story hasn’t quieted down. It’s all over the internet, swinging between “this will kill you, buy organic” and “relax, you’re fear-mongering.” Some of that recent chatter stems from an Executive Order protecting glyphosate and its production, which set off intense infighting within the MAHA movement. Some of it reflects a deeper truth: Americans genuinely care about harmful chemicals in their environment (see poll below). And the conversation isn’t going anywhere, with a Supreme Court case involving Monsanto set for this April. Glyphosate (the active ingredient in Roundup) is one of the most widely used herbicides in the world. But does glyphosate cause cancer? And how much exposure is actually risky? With so much mistrust in institutions and corporations (and some genuine conflicts of interest), making sense of the actual scientific evidence is genuinely hard. Here is a translation of what the scientific evidence actually says. Does glyphosate cause harm? Glyphosate is an herbicide that kills most plants it contacts rather than targeting specific species. It works by blocking an enzyme pathway (EPSPS) that plants and many microorganisms need to produce essential amino acids. Without those amino acids, the plant can’t grow and dies. Glyphosate was first developed by Monsanto in the 1970s and became ubiquitous after the company introduced “Roundup Ready” crops in the 1990s. In 2024, Bayer removed glyphosate from residential Roundup-branded products due to litigation pressure. But today it is still the most widely used herbicide in the world. Farmers also discovered they could spray it directly on crops like oats, lentils, beans, and peas just before harvest to dry them out faster and make harvesting easier. Because of its widespread use, it’s obviously really important to understand if it’s harmful to humans. The key principle: The dose makes the poison The most important concept in toxicology is that “the dose makes the poison.” Sixteenth-century physician Paracelsus articulated what remains the foundational principle of toxicology: sola dosis facit venenum. Water will kill you if you drink enough of it. Aspirin saves lives at 81 milligrams and causes internal bleeding at higher chronic doses. So, at what dose is glyphosate poisonous? The LD50 in rats (the dose that kills half the test animals) is around 5,600 mg/kg body weight. Table salt is roughly 3,000 mg/kg. By that classic measure, glyphosate is less acutely toxic than salt. But some people are exposed to a lot of glyphosate through their work. And among the general public, there are many questions about low-dose, cumulative exposure from multiple sources over long periods. Does glyphosate cause health problems? Cancer Correlation maps are striking, with one analysis finding that 60% of counties that spray the most glyphosate have non-Hodgkin’s lymphoma rates above the national average. But correlation alone doesn’t establish cause, which is why animal and human studies matter. In animals: Rat studies are typically what most fear is rooted in, but most people don’t know the study details on the dosage given to rats. A pooled analysis of the 13 most rigorous rat studies found evidence that very high doses, around 55,000 times greater than typical food residue exposure, can cause certain cancers. In humans: One of the strongest studies followed 55,000 herbicide users over 20 years and found no overall increased cancer risk. There was one signal: among those with the highest use, rates of acute myeloid leukemia (AML) appeared elevated. A broader meta-analysis of 18 human studies also found no overall cancer risk, though a separate meta-analysis focused specifically on non-Hodgkin lymphoma found that people with high cumulative glyphosate exposure faced a 41% higher relative risk compared to those with low or no exposure. These human studies are observational studies (randomized controlled trials would be unethical), and meta-analyses are only as reliable as the studies they pool. But the story seems consistent: at very high exposure levels, there may be some cancer risk. But that’s about as far as the science currently takes us. Emerging research: gut and reproductive health Gut: Because glyphosate targets a pathway that exists in some gut bacteria, scientists have questioned whether it could affect the microbiome. In mice, a 2023 University of Iowa study found that glyphosate altered gut bacterial composition and raised markers of intestinal inflammation. A 2024 systematic review found similar patterns: disrupted gut bacteria and problems with the mucus layer that protects the intestinal wall in mice. Whether this translates to humans is an open question. The human gut is highly variable and resistant, and we don't yet have strong studies confirming the same effects in people. Reproductive health: Animal studies have found that glyphosate-based herbicides can interfere with reproductive hormones, including disrupting egg cell development in mice and reducing the number of eggs available in sheep’s ovaries. However, the doses used in these experiments were high, so it’s not yet clear whether the same effects would occur in humans. On the human side, a 2021 pilot study led by Mount Sinai researchers tested urine samples from pregnant women across the U.S. and found glyphosate in 95% of them. The study also found a possible connection between higher glyphosate exposure during pregnancy and a subtle physical difference measured in female newborns. That said, some connections weren’t statistically reliable and this was a small study. The researchers themselves said more and larger studies are needed before drawing firm conclusions. What do regulators say about glyphosate safety? In 2015, the International Agency for Research on Cancer (IARC), part of the World Health Organization, classified glyphosate as "probably carcinogenic to humans" (Group 2A). The classification is worth taking seriously. But, there’s an important distinction: IARC classifies hazard, meaning the potential to cause harm under some conditions. It does not assess risk, which accounts for actual exposure levels and the real-world probability of harm. The U.S. EPA, the European Food Safety Authority, Health Canada, and regulatory agencies in Australia and Japan have all concluded that glyphosate is “unlikely to be carcinogenic to humans” at realistic exposure levels. They’re asking a different question: given how much of this people actually encounter, what is the probability of harm? Your actual exposure is what determines your actual risk. What does glyphosate mean for your daily life? At the grocery store: Food residues are small. The EPA’s acceptable daily intake is 1.75 mg/kg of body weight per day. To hit that threshold from oatmeal alone, a 150-pound adult would need to eat roughly 50 pounds of oats every day. But this calculation addresses only one pathway (food), and we don’t yet have robust tools to measure people’s actual total exposure. If reducing exposure matters to you, organic certification prohibits synthetic herbicides, and organic oat products generally test at lower or undetectable levels. Either way, a diet rich in whole grains, conventional or organic, is far better for your health than one that omits them out of fear of residues. On the farm: Occupational exposure is orders of magnitude higher than consumer exposure. Farmers and farm workers who mix, load, and apply glyphosate-based herbicides, especially without protective equipment, face meaningfully different risk profiles. Proper PPE isn’t optional. Integrated weed management strategies that rotate chemical modes of action are also worth taking seriously, both for health and for long-term effectiveness. If you live near a farm: Spray drift is real. Concentrations near field edges can spike during and after application, particularly on windy days. This is an area where I think public health could really step up and empower rural communities with buffer zones, rather than placing the onus on individuals. But for now, knowing your local agricultural calendar and keeping windows closed during application are the first steps. Bottom line Dewayne Johnson was exposed to glyphosate at levels most people will never encounter, and a jury decided he deserved compensation. That outcome is not evidence that the oatmeal in your pantry is dangerous. But it is a reminder that the dose, the context, and the person doing the exposing all matter enormously. Glyphosate is a chemical tool with benefits, trade-offs, and genuine open scientific questions. Learning to hold that complexity without collapsing into panic or dismissal is, honestly, one of the most useful and hardest things to do in navigating modern health science. Love, YLE Your Local Epidemiologist (YLE) is founded and operated by Dr. Katelyn Jetelina, MPH PhD—an epidemiologist, wife, and mom of two little girls. Hannah Totte, MPH, is an epidemiologist and YLE Community Manager. YLE reaches more than 425,000 people in over 132 countries with one goal: “Translate” the ever-evolving public health science so that people will be well-equipped to make evidence-based decisions. This newsletter is free to everyone, thanks to the generous support of fellow YLE community members. To support the effort, subscribe or upgrade below: Subscribe
ICE agents have been deployed to airports. Are the polls next?
The high-profile deployment of Immigration and Customs Enforcement agents to airports has renewed support on the right and fear on the left about the possibility of ICE going to the polls in November.
Accelerating Innovative and Effective Pediatric Health Care Delivery Systems: Interventions and Value-Based Care Models for Children with Chronic Health Conditions and Complex Social Needs
Children, youth, and families have unique health needs, which set the foundation for health across the life course; chronic conditions now affect nearly one in three U.S. children, with disproportionate prevalence in those enrolled in Medicaid and CHIP.
Marathon has sold 1.2M copies across Steam, PS5, and Xbox
Alinea Analytics estimates show that Marathon has generated gross revenues of $55M via 1.2M copies sold on Steam, PS5, and Xbox: Looking at the split between Steam, PS5, and Xbox, Steam is clearly the main platform for Marathon, accounting for a little under 70% of the audience (800K copies sold). Meanwhile, PS5 takes about 19% (217K) and Xbox (including console, PC, and cloud) accounts for a bit over 11% or 133K. Marathon is technically a first-party Sony title, so seeing the home console struggle to break 20% of the volume is a notable data point for the ongoing platform-agnostic debate. PlayStation Studios online games will almost certainly continue being multiplatform (despite Sony reportedly pulling back on PC releases). Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe As for Marathon, the consensus among hardcore players who pushed through the awkward onboarding phase – myself included – is that it’s fantastic. The gunplay, aesthetic, and presentation are among the best in the shooter genre. A great game doesn’t always equal an immediate hit, though, as shown by our estimates. Things are looking lukewarm right now. But this might be one of those marathon-not-a-sprint situations. Had to, didn’t I? Why wasn’t Marathon a hit on the same level as Arc Raiders? One topic that came up in a lot of conversations at GDC this year was why Marathon hasn’t hit the same stratosphere as Arc Raiders. On paper, they’re both extraction shooters, and Marathon has the Bungie pedigree – the house that built the gold standard for gunplay in Halo and Destiny. Marathon’s neon-futuristic aesthetic also distinguishes itself from the gritty realism of Tarkov or the post-apocalyptic hope of ARC Raiders. But vibes can only get you so far for first impressions if the onboarding feels like a brick wall. Marathon is a sweaty PvP-focused experience with a first-time user experience and UI that I can only describe as dreadful. Players are dropped into a complex ecosystem where the UI, though visually striking, is functionally uninformative, forcing users to manually hover over nondescript, identical icons just to identify basic gear or weapon mods. This lack of clarity is compounded by punishing mechanics like a severe heat gauge for movement and a scarcity of vital resources, all without a clear tutorial or a low-stakes mode to learn the ropes. Most people – even top streamers and veteran shooter players – have no idea what’s going on in Marathon at first. Arc is on the complete other end of the spectrum. As we covered here and here, Arc Raiders offers a more collaborative, approachable loop where players often work together toward shared goals. And the objectives are instantly clear. To many players, this contrast only emphasised Marathon’s issues, especially during the testing period. Players understand the Arc Raiders loop within 30 minutes, while Marathon acts as a massive filter, chewing up newcomers and spitting them out before they can experience the depth of Bungie’s signature gunplay. What I’m getting at here is that the poor first-time user experience of Marathon’s Server Slam likely stifled launch sales, while the opposite was true for Arc. Let’s look at the pre-launch copies sold for each game during their respective Server Slams (launch-aligned) : Looking at the trajectory: Arc Raiders saw a massive 80% jump in copies sold during its three-day Server Slam (day -13 to -11). Players jumped in, realised the water was fine, and immediately opened their wallets. Marathon, meanwhile, saw a 49% increase in the four days following its Slam (Day -7 to -3). At the time of each game’s respective launch, Arc Raiders had nearly double the Steam footprint of Marathon – and word of mouth only continued to grow. Bungie could have had more time to fix the onboarding process had the beta happened earlier. But Marathon launched three days after the beta finished. These factors limited the launch sales quite a bit, I reckon. Marathon has found a niche audience, though Despite the friction-heavy start, the data suggests that those who survived Marathon’s onboarding are loving life. We’ve been tracking cross-platform DAUs, and while there’s the expected post-launch leakage, many players are sticking with it. After peaking at 478K total DAUs on its first Saturday, Marathon has settled into a respectable rhythm, holding 345K DAUs as of yesterday and averaging 380K DAUs across the weekend. Steam continues to do the heavy lifting here, consistently accounting for the lion’s share of the daily players. Players have been putting in the hours, too: On Steam, Marathon’s average playtime has climbed to 27.8 hours, significantly outpacing the console averages on PS5 (16.5h) and Xbox (17.3h). Even more telling than the averages: 22% of the Steam audience has surged past the 50-hour mark, and nearly 7% have already logged over 100 hours. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe This data suggests that once the Bungie magic clicks, it hooks players deeper than the average extraction shooter. There’s also started to be a shift in the game’s discourse. Marathon launched as one of those games that’s cool to hate. But as Marathon’s 100-hour club grows, we’re seeing conversations around its mechanical merit outweigh the negativity. Several high-profile creators, who were initially vocal critics, have spent the last week coming around on the mechanical depth of the endgame. It’s a subtle but positive signal; the hate train is losing steam, and a new narrative about the game is emerging. Bungie faithfuls unite Another interesting metric in Marathon’s first few weeks is who, exactly, is playing. Bungie leans heavily on its prestige as the “makers of Halo and Destiny,” in its marketing, and that message has clearly hit the mark. On Steam, the gravity (hammer) of Bungie’s previous work is unavoidable. A staggering 78.2% of Marathon players also played Destiny 2. The trend carries across other platforms, with 74.2% of PS5 players and 82.7% of Xbox players also having played Destiny 2. The Halo legacy lives on, it seems. More on that in a bit. While Destiny 2 went free to play, these numbers still represent a high-intent migration of a fanbase that trusts Bungie’s specific brand of kinetic gunplay and cryptic world-building. The Xbox data adds another layer of legacy. About 85.7% of Marathon players on Xbox have played Halo Infinite, while over half of the Steam audience has spent time in Halo Infinite and 36.1% in the Master Chief Collection (a paid collection of the old Bungie-made legacy games). Interestingly, we see a 55.9% overlap with ARC Raiders on Steam. Overlap is even higher there on PlayStation (60.5%) and Xbox (66.5%). And there’s also significant crossover with Helldivers 2 on all platforms, too. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe Bungie has found some of its fans with Marathon, and the challenge now is keeping this engaged in a high-stakes PvP environment when they’ve spent the last decade primarily enjoying the power fantasies of PvE. On that note… Go the full 26 miles? Or cut and run? Time for some could’ve, should’ve, would’ve. These things would have improved Marathon’s performance at launch: A more robust onboarding process, perhaps in the form of a short single-player/PvE campaign. We know Bungie fans love this stuff. A traditional arena-based mode akin to Destiny’s Crucible could have been a bridge for the cautious players who’d have been otherwise deterred by the Server Slam. It’s also a great palate cleanser after getting merked. Introducing a dedicated PvE environment would have similarly diversified the conversation and lowered the barrier for the Bungie faithful who found the pure PvP extraction loop too abrasive. PvE is safer than PvP these days. There’s an argument that a thin PvE mode would have just felt like a budget Destiny, potentially hurting the brand more. But given how dire the FTUE is, I think it would have been a net positive. Any kind of tutorialised loop that demystifies the stakes, really. While there is merit in a studio sticking firmly to a singular creative vision, and going all in on the hardcore extraction loop. Less forgiving is the technical reality is that the user interface and first-time user experience (FTUE) were not at a commercial standard for launch. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe In a landscape where player time is oversaturated and the most contested currency, a flawed FTUE is a critical failure point. But it’s not all doom and gloom, as Marathon has an incredible, unique gameplay loop, suggesting that financial success is still attainable if Bungie can pivot effectively. Bungie and PlayStation now face a difficult strategic crossroads, though – one within a challenging games market. They could: Double down on Marathon with a long-term Rainbow Six Siege- or No Man’s Sky-style recovery plan, which is something I heard Last Stand Media’s Chris Maldonado mention last week. While this could be a sunk-cost fallacy in action, it could eventually yield the audience the game’s mechanical depth deserves. Shift focus toward the inevitable Destiny 3 or another project, mitigating the escalating opportunity cost and cutting their losses, so to speak. Doing both is an expensive proposition, given the high overhead and burn rate of operating out of Bellevue, Washington. With Sony recently demonstrating a lower threshold for underperforming studios and projects, the margin for error has vanished. Whatever happens, the next six months will determine whether Marathon becomes a cornerstone of Sony’s live-service portfolio or a cautionary tale of vision exceeding accessibility. I’m hoping it’s the former, because Marathon rocks. As always, hit subscribe to get updates on Marathon and other relevant games. Subscribe Want to get your hands on our data for yourself – for free? We’re offering a free trial of our platform for games companies. Send us a message here, or reply to this email, and we’ll set you up. The last word Reply to this email – or reach out here – if you have any feedback for the newsletter – or want to request a game for us to cover. [Alinea Analytics boasts the most accurate PC and console estimates in the business. Game makers use our platform to understand their audience, keep an eye on the competition, monitor sales trends, and spot new opportunities. We equip game studios and financial institutions with accurate data and the confidence to make smarter, data-driven decisions. Want to talk about all things games market data? We’d love to chat!]
Alliant Private Client Strengthens Entertainment Practice with Addition of Michelle Quintero
IRVINE, Calif., March 24, 2026--Michelle Quintero has joined Alliant Insurance Services as Executive Vice President with Alliant Private Client. Based on the West Coast and recognized by Risk & Insurance® as a 2026 Entertainment, Hospitality & Gaming Power Broker®, Quintero brings more than 25 years of technical acumen and delivers tailored solutions to high-profile and celebrated individuals in music, film, and live events.
A DNA test ruled him out. He was convicted of murder anyway.
Forensics has its share of high-profile problems. There’s phony “junk science,” like bogus bite-mark and blood spatter analyses that have sent innocent people to jail. And there’s the steady drumbeat of lab scandals, where analysts make up results. But there’s a subtler and more pervasive problem at work in many cases: lab analysts and lawyers who take perfectly legitimate science and twist it. Globe Opinion is exploring these distortions with a series we’re calling “Twisted Science.” And there may be no better place to start than with the case of Terrel Barros.
Your Thymus and Your Healthspan
Our thymus gland plays a central role in the development or our immune system, specifically for supporting T cell development (how these cells got their name, maturation and differentiation in the thymus) and discriminating between self and foreign, non-self antigen proteins with production of dendritic cells. As we age, our thymus gland shrinks—the process known as involution—with progressive change from spongy to fatty tissue, with loss of functionality. But this process, with respect to timeline and extent, markedly varies from one person to the next. And to make things even more complicated, our thymus gland anatomy and precise location in the chest also is highly variable. So the famous Frank Netter diagrams from the 1960s (such as at left below) don’t capture the remarkable heterogeneity that a random set of 12 chest CT scans (below at right). What I consider as 2 landmark papers in Nature this week (here and here) used AI to quantify health of the thymus in 2 large cohorts, and then correlate the metric to a broad array of health outcomes. In this edition of Ground Truths, I’m going to cover three questions: (1) How was thymus health determined by AI?; (2) How is thymus health linked to key clinical outcomes? and (3) Are there ways we can promote a healthy (aka rejuvenate) thymus gland in our later years? Subscribe 1. How was thymus health determined by AI? This was accomplished by extensive work developing and validating an AI pipeline for 2 stages, the first for localization and segmentation of the thymus bed, and the second to quantify a digital marker, termed the thymic health score. There’s a lot to this algorithmic development, so I won’t go into all the details, but just provide a rudimentary outline of what was done. The 1st stage used supervised learning with 2 radiologists reviewing 2,461 chest CT scans. That work trained a 3D U-Net model to automatically identify the thymic bed’s 3D cropped region using center of mass coordinates, which reached 99.8% accuracy. The 2nd stage used a foundation model that was pre-trained with SwAV (which stands for Swapping Assignment between multiple Views), a self-supervised model, that generated a high-dimensional thymus representation of 4,096 features. That compares to the radiology reductionist and subjective scoring of 0 to 3 where 0 means the thymus is fully degenerated and fatty, and 3 is considered dense, intact glandular soft tissue. Notably, the self-supervised learning (SSL) performance was superior to supervised (AUC ~0.75 vs 0.55, respectively) reflecting the shallowness of the 0-3 classifier vs SSL’s holistic, self-taught AI. The thymic health score ranged from 0 to 100, with the highest number indexed to fully preserved thymic health. The algorithmic work extended to explainability with both Shapely value distribution, meaning the model was holistic not relying on any “magic” pixel, and occlusion sensitivity, demonstrating the model’s performance was not affected by ribs, sternum, lung tissue, but rather focused on the thymic bed directly. Below are a few saliency maps from the occlusion sensitivity that indicate the thymic bed focus, not affected by neighboring structures, using the jet color scale. Now the AI was ready for processing ~25,000 CT scans, each over 30 MB files, from the 2 large participant cohorts to provide a thymic health score, it did so in less than 14 hours, which is less than 2 seconds per scan! Share 2. How is thymus health linked to key clinical outcomes? The two cohorts were the National Lung Screening Trial, NLST (N=25,031) and the Framingham Heart Study, FHS (N=2,581) each with baseline demographics and long term follow up of >12 years for health outcomes. From the NSLT, you can see below that increased age and body-mass index were correlated to reduced thymic health. And, overall, men had reduced thymic health scores compared with women. There are a lot of graphs in the paper for outcomes, for both the NLST and FHS cohorts. To simplify the major outcomes, below is a composite Figure with striking reduction of all-cause mortality and for the different causes of death. The results were consistent between the 2 cohorts. For example, the cardiovascular mortality hazard ratio average was 0.57 in NLST and 0.38 in FHS (weighted to be 0.53 for the aggregate). The reduction of mortality also extended to digestive diseases and pulmonary disease (data not shown below). Lung cancer incidence was reduced by 36% for high vs low thymic health (Figure below, with a panel -incidence and b panel-mortality, adjusted for age, sex, BMI, smoking status). Notably, there was a smoker’s paradox: lower incidence and improved survival for lung cancer in smokers who had a high thymus health score. Smoking was associated with lower thymic scores whereas alcohol was not. Higher thymic health was linked to higher HDL cholesterol, lower triglycerides, lower fasting blood glucose, and lower systolic and diastolic blood pressure. Inflammation biomarkers, such as C-reactive protein and interleukin-6, were elevated in the people with lower thymic health scores. In their second paper, the same team looked at the relationship between thymic score and outcomes for 3,476 patients receiving cancer immunotherapy. The non-small cell lung cancer progression-free survival was reduced in patients with low thymic health score. A parallel relationship for survival was seen for other types of cancer including melanoma, breast, and kidney with a 44% lower risk among high thymic scores (Figure). A similar pattern was seen with different immune checkpoint inhibitors. The thymus health score outperformed programmed death ligand-1 (PD-L1)and tumor mutation burden (TMB) assay of the tumor and was an independent prognostic marker of progression-free survival. In this dataset, a direct connect with thymus score and adaptive immune function was noted with a correlation before cancer treatment for both T-cell diversity and thymus T-cell production (a metric known as T cell receptor excision circles). Thymus Removal Study There is a highly relevant citation about thymus function before moving onto ways to rejuvenate it. In 2023, a very important study of thymus removal during cardiothoracic surgery was published, with 1146 patients undergoing thymus removal vs 1146 matched controls (mean age 55 years). The adverse outcomes for thymus removal were striking, with a 2.9 higher risk of all-cause mortality and doubling of cancer incidence, 1.5 fold increase in cancer mortality, and 1.5-fold increase in autoimmune diseases. The immune function showed marked compromise after thymus removal, as reflected by CD4+ and CD8+ T cells (Figure below) Share Ground Truths 3. Are there ways we can promote a healthy (aka rejuvenate) thymus gland in our later years? In recent months we’ve learned a lot about the process of thymus involution and the pathways by which this may be modulated. Thymus involution is primarily due to loss to thymus epithelial cells (TECs) and there are 2 subtypes with different functions: the cortical, responsible for positive selection of T cells, and the medullary, for negative selection. When adipose tissue infiltrates the thymus, thymic adipocytes are pro-inflammatory, knocking out T-cell output. Likewise, systemic inflammation, or “inflammaging,” from smoking, obesity, and chronic stress promote thymic adipocytes. Now, from preclinical studies, we know about key pathways that account for these processes. Historically, back in 2014, FOXN1 was recognized as a single master transcription factor essential for TEC function, with studies in mice with forced FOXN1 upregulation leading to thymus regeneration. That laid the foundation for potential regrowth of quiescent thymus cells. It took awhile to find pathways to accomplish this goal and to even refute its role as the master regulator. The Liver-Thymus Axis Feng Zhang and his team recently showed that injection of an mRNA vaccine to the liver encoding DLL1, IL-7 and FLT3-L in combination, factors known to support thymopoiesis (Figure), successfully enhanced immune function in aged mice. However, the effect was transient. The FGF21 Story Two reports in 2025 addressed the thymus gland’s production of FGF21, a growth factor (fibroblast growth factor 21) and its control of thymus involution. This growth factor is also produced by the liver, but it doesn’t have impact on the thymus in aged rodent models. In contrast, The liver’s hepatocyte growth factor (HGF) has been shown to reverse senescent TEC structural changes. Growth hormone stimulates production of insulin growth factor-1 (IGF-1) in the liver and the thymus. Two small studies in human participants (TRIIM, for Thymus Regeneration, Immunorestoration, and Insulin Mitigation) of 6 and 50 people, respectively, treated with combined human growth hormone, metformin and DHEA, suggested the potential of slowing epigenetic aging and improving thymus mass and function. But the combination of drugs, small sample, and lack of controls make conclusions murky. Increased thymus FGF21 led to increased CD8 T cells in old mice and extended healthspan and improved physical performance. Building on the previous FOXN1 data, ablation of β-klotho, the obligatory co-receptor for FOXN1, accelerated thymic aging. The benefit to FGF21 was confirmed in a companion paper using an FGF21 knock-in mouse model showing thymus enlargement and increased TECs throughout the lifespan. (schematic Figure below). The accompanying editorial for these 2 papers speculated: “The proposed link between age-associated thymus involution and organismal aging is intriguing, and suggests we might seek to achieve systemic rejuvenation by counteracting thymic involution.” Other Factors Lessons from the Axolotl (Mexican Salamander) In an elegant set of experiments of the axolotl (Figure), known for its complete thymus regeneration after total surgical removal, mediators were identified. Surprisingly FOXN1 was dispensable. But midkine, a growth factor, appeared to be the driver, the initiator of thymus cell growth, survival, and repair. Other components that contributed were Postn+ (periostin-expressing mesenchymal niches) and Ccl19, a chemokine protein from the bloodstream. RANK and RANKL RANK (receptor activator of nuclear factor κB its ligand (RANKL) have been considered key regulators of medullary TECs. In a study of both aged mice and human thymus cell cultures, their key role was confirmed, with multiple benefits of resorting TEC function, recruitment of progenitor cells, and T cell development. Subscribe Summing Up This body of work strongly supports the health of the thymus gland as a critical regulator of human healthspan, not just a correlate or link. The new landmark studies are reinforced by the regenerative biology experimental models that have shown, via an array of mediators, that healthspan of aged mice is at least in part dependent on thymus gland function and its critical role for maintaining adaptive immunity. It sure seems that we’d be better off having an immune reservoir of naive T cells instead of a profile in older adults of exhausted, low quality, memory T cells, with a senescent phenotype. It is striking that we ignored the importance of the thymus gland for many decades. A wake-up call was the results of the thymectomy matched control study reviewed here, with the opposite of high thymic health score improved health outcomes. The convergence of AI and healthspan here is notable. The exceptional and laborious work for developing and validating (no less explaining) the AI to quantify thymus health set the foundation for probing the connect the major health outcomes in two cohorts with extensive follow-up. We’ve never had a way to meaningfully quantify the thymus gland before, so this represents important leverage of supervised, self-supervised, and transformer models. The study wouldn’t have been possible without AI. And it begs the question as to whether there are ways we can maintain our thymus at a high health score. But it’s not so simple to rejuvenate our thymus. There are multiple risks including the induction of autoimmunity, increasing the risk of cancer, and inducing a pro-inflammatory state. For example, factors that increase TEC proliferation could compromise the medulllary negative selection process and leak out auto-reactive (self-attacking) T cells. Thymic cells could be induced to proliferate, but we know, for example, that growth hormone and IGF-1 are associated with an increase risk of cancer. If thymus rejuvenation doesn’t clear out the accumulated senescent cells in older adults, then inflammation within the gland could block the production of TECs. Keeping these risks in mind, we now have identified many ways to keep our thymus healthy as we age that undoubtedly will be tested in clinical trials going forward. Ultimately, the benefit-to-risk tradeoffs will be defined. In the meantime, we have desperately needed an immunome. As I’ve stressed in multiple prior Ground Truths, we have no test in the clinic to assess a patient’s immune status! It was very encouraging for me to get an email from Hugo Aerts, the senior author of the landmark papers in the days after they were published: “I also wanted to say that your Substack on “Why We Need an Immunome” was inspiring for this work. We found it a very compelling perspective and greatly enjoyed reading it.” Just having an assessment of a person’s immune status via a chest CT scan, with millions of these performed per year, might help in guiding the right immunotherapy for cancer (e.g. more intensive, combinations for those with low thymic health scores) and help define people who are increased risk for age-related diseases of cancer, cardiovascular, and neurodegenerative. The main theme of Super Agers is that we now have many layers of data (genetics, proteins, biomarkers, organ clocks that can be integrated via multimodal AI) for us to define a person’s specific risk decades before one of these age-related diseases leads to symptoms, enabling prevention. From the new studies this week, we can add thymus health score as yet another way to understand a person’s risk, a window into their adaptive immune system and healthspan. And perhaps someday we will be able to safely rejuvenate the thymus, or maintain its health through one’s life, and use the thymus health score to monitor. NB: I wrote this post (No A.I.) A Quick Poll Loading... ********************************************************************* Thanks to Ground Truths subscribers (now > 200,000) from every US state and 212 countries. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. Please join! If you found this interesting PLEASE share it! Share Ground Truths Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Please don’t hesitate to post comments and give me feedback. Let me know topics that you would like to see covered. Leave a comment Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. It enabled us to accept and support 47 summer interns in 2025! We aim to accept even more of the several thousand who will apply for summer 2026.
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Partisanship and science
I recently participated in a symposium of the Denver-based Institute for Science & Policy, during which I had a “fireside chat” with Tony Mills of the American Enterprise Institute. Mills has written extensively on the politicization of science, and the two of us had a very enjoyable hour-long conversation on the topic. You can watch it below. The main questions we dealt with are why there is such a vast partisan gap in trust of science, and to what extent this is a unique moment. Mills helpfully brings a good deal of data to the discussion, as he did in this useful piece at Issues in Science & Technology. Tusk depends on reader support. To support this work, please become a paid subscriber. Subscribe Note this graph, drawing on a range of survey data to demonstrate partisan attitudes toward science since 1970s. As it demonstrates, there’s been a very sharp partisan divergence in confidence in science during the Trump Era, starting prior to the Covid pandemic. At least in part, we can attribute this to a rise in populist anti-science rhetoric embraced by Trump, his appointees, and those in his media orbit. But as the graph also shows, the partisan divide has existed in the past, and it’s not always in the same direction. The largest divergence in party views toward science prior to 2016 was in the 1970s, when liberals equated scientific achievement with the military-industrial complex and thus trusted it less. That era of scientific mistrust is often overlooked. Indeed, as Mills notes, the Moon landings (1969-72), which today are considered one of the last great moments of national unity, were experienced nothing like that at the time. There was sharp debate back then over whether the Apollo missions were worth the vast expenditures when the country had so much else to deal with. It’s outside the dataset, and we don’t have the partisanship lens for it, but the 1950s was another deeply anti-science decade, with critics of intellectuals and college professors alleging their ties to communism and their lack of commitment to basic American moral beliefs. This was the subject of Richard Hofstadter’s 1962 book Anti-Intellectualism in American Life, in which he quotes religious leaders like Franklin Graham: [In place of the Bible] we substituted reason, rationalism, mind culture, science worship, the working power of government, Freudianism, naturalism, humanism, behaviorism, positivism, materialism, and idealism. [This is the work of] so-called intellectuals. Thousands of these “intellectuals” have publicly stated that morality is relative—that there is no norm or absolute standard.… This fervor was heavily whipped up by Sen. Joe McCarthy (R-Wisconsin), although it’s clear that not all his fellow Republicans were on board with his red-baiting. What ended that era? The simple answer is the 1957 launch of Sputnik. Americans became afraid that they were losing to Soviet scientists, and suddenly university researchers and government projects were awash with funding. In our conversation, I asked Mills about the possibility of us having a Sputnik moment again that would rally the American public in favor of science today. Mills argued that the COVID-19 pandemic was essentially a Sputnik moment — a terrifying threat to all Americans that required scientific advances to address. But thanks in part to political polarization and the populist and conspiratorial leanings of Donald Trump, we got the opposite of a unifying moment. Many Americans turned against science, despite science actually stepping up in that moment. As we discussed in the chat, it’s not clear what scientists could or should be doing in this moment to increase faith in their work. As Mills notes, one of the chief complaints against scientists and professors is that they’ve become too political; scholars becoming even more political might not help them achieve their goals. This (mainly Republican-driven) anti-science era will end, of course, but it’s not clear what event will bring that about. Share
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