Frequency shaping of tactile perception via transcutaneous interferential electrical stimulation: a simulation study

Electrotactile feedback via transcutaneous interferential electrical stimulation generates temporally modulated stimulation fields and enables frequency-domain adjustment with carrier and beat frequencies. To systematically characterize these effects, we present a simulation framework that integrates tissue-scale electrical potential simulation with the finite element method and axon-scale dynamics using the axon cable equation, which incorporates cable theory and the Hodgkin–Huxley model, to predict axon activation and tactile perceptual metrics. We simulated a simplified glabrous skin model with three orthogonally oriented axons. Results show that the carrier frequency in the range of 1–4 kHz determines the upper bounds of the perceived field size, reaching up to 1.6 mm and exceeding the 1 mm electrode diameter, and perceived intensity, whereas the beat frequency in the range of 0–100 Hz adjusts these quantities within these bounds. Furthermore, axons oriented perpendicular to the skin surface exhibit lower activation thresholds than those oriented parallel. Unlike the conventional approaches of transcutaneous electrical stimulation, our results suggest that transcutaneous interferential electrical stimulation can shape the perceived field and perceived intensity without electrode reconfiguration or amplitude modulation. These findings clarify the distinct roles of carrier and beat frequency in tactile perception. This paper provides a theoretical foundation for frequency-domain adjustment of electrotactile interfaces and points toward compact, programmable systems. Quantitative validation through psychophysical experiments will further test and refine these predictions.

Targeting the microbiota-gut-brain axis in post-stroke insomnia: a phase-dependent therapeutic framework

Post-stroke insomnia (PSI) is a critical biological barrier to neurorehabilitation afflicting over half of all stroke survivors. Traditional sedatives often force clinicians into a therapeutic dilemma between sleep efficacy and cognitive suppression. The microbiota-gut-brain (MGB) axis has recently emerged as a transformative target to resolve this impasse. Acute stroke triggers profound autonomic dysfunction, causing immediate intestinal barrier collapse. This “leaky gut” facilitates the systemic translocation of lipopolysaccharides (LPS) and activates the NLRP3 inflammasome. The resulting inflammatory storm hijacks central tryptophan metabolism via the indoleamine 2,3-dioxygenase (IDO) enzyme. This “tryptophan steal” diverts serotonin precursors toward neurotoxic kynurenine pathways, driving severe cortical hyperarousal. Sleep fragmentation then prevents the glymphatic system from clearing metabolic waste, further exacerbating neuroinflammation. To break this vicious cycle of neurotoxicity, we propose a phase-dependent therapeutic framework. During the highly vulnerable acute phase, interventions must prioritize gut barrier protection using postbiotics to mitigate infection risks under CNS injury-induced immunodepression (CIDS), often discussed as stroke-induced immunosuppression. As patients enter the chronic phase, therapy shifts toward metabolic restoration using live therapeutics, such as washed microbiota transplantation (WMT) and next-generation psychobiotics like Akkermansia muciniphila. Targeting the MGB axis offers a mechanism-based strategy to achieve precision sleep medicine, restoring the biological foundation necessary for optimal neuroplasticity and recovery.

Is fake grass a bad idea? The AstroTurf wars are far from over.

A rare warm spell in January melted enough snow to uncover Cornell University’s newest athletic field, built for field hockey. Months before, it was a meadow teeming with birds and bugs; now it’s more than an acre of synthetic turf roughly the color of the felt on a pool table, almost digital in its saturation. The day I walked up the hill from a nearby creek to take a look, the metal fence around the field was locked, but someone had left a hallway-size piece of the new simulated grass outside the perimeter. It was bristly and tough, but springy and squeaky under my booted feet. I could imagine running around on it, but it would definitely take some getting used to.

My companion on this walk seemed even less favorably disposed to the thought. Yayoi Koizumi, a local environmental advocate, has been fighting synthetic-turf projects at Cornell since 2023. A petite woman dressed that day in a faded plum coat over a teal vest, with a scarf the colors of salmon, slate, and sunflowers, Koizumi compulsively picked up plastic trash as we walked: a red Solo cup, a polyethylene Dunkin’ container, a five-foot vinyl panel. She couldn’t bear to leave this stuff behind to fragment into microplastic bits—as she believes the new field will. “They’ve covered the living ground in plastic,” she said. “It’s really maddening.” 

The new pitch is one part of a $70 million plan to build more recreational space at the university. As of this spring, Cornell plans to install something like a quarter million square feet of synthetic grass—what people have colloquially called “astroturf” since the middle of the last century. University PR says it will be an important part of a “health-promoting campus” that is “supportive of holistic individual, social, and ecological well-being.” Koizumi runs an anti-plastic environmental group called Zero Waste Ithaca, which says that’s mostly nonsense.

This fight is more than just the usual town-versus-gown tension. Synthetic turf used to be the stuff of professional sports arenas and maybe a suburban yard or two; today communities across the United States are debating whether to lay it down on playgrounds, parks, and dog runs. Proponents say it’s cheaper and hardier than grass, requiring less water, fertilizer, and maintenance—and that it offers a uniform surface for more hours and more days of the year than grass fields, a competitive advantage for athletes and schools hoping for a more robust athletic program.

But while new generations of synthetic turf look and feel better than that mid-century stuff, it’s still just plastic. Some evidence suggests it sheds bits that endanger users and the environment, and that it contains PFAS “forever chemicals”—per- and polyfluoroalkyl substances, which are linked to a host of health issues. The padding within the plastic grass is usually made from shredded tires, which might also pose health risks. And plastic fields need to be replaced about once a decade, creating lots of waste.

Yet people are buying a lot of the stuff. In 2001, Americans installed just over 7 million square meters of synthetic turf, just shy of 11,000 metric tons. By 2024, that number was 79 million square meters—enough to carpet all of Manhattan and then some, almost 120,000 metric tons. Synthetic turf covers 20,000 athletic fields and tens of thousands of parks, playgrounds, and backyards. And the US is just 20% of the global market. 

Where real estate is limited and demand for athletic facilities is high, artificial turf is tempting. “It all comes down to land and demand.”

Frank Rossi, professor of turf science, Cornell

Those increases worry folks who study microplastics and environmental pollution. Any actual risk is hard to parse; the plastic-making industry insists that synthetic fields are safe if properly installed, but lots of researchers think that isn’t so. “They’re very expensive, they contain toxic chemicals, and they put kids at unnecessary risk,” says Philip Landrigan, a Boston College epidemiologist who has studied environmental toxins like lead and microplastics.

But at Cornell, where real estate is limited and demand for athletic facilities is high, synthetic turf was a tempting option. As Frank Rossi, a professor of turf science at Cornell, told me: “It all comes down to land and demand.”


In 1965, Houston’s new, domed base­ball stadium was an icon of space-age design. But the Astrodome had a problem: the sun. Deep in the heart of Texas, it shined brightly through the Astrodome’s skylights—so much so that players kept missing fly balls. So the club painted over the skylights. Denied sunlight, the grass in the outfield withered and died.

A replacement was already in the works. In the late 1950s a Ford Foundation–funded educational laboratory determined that a soft, grasslike surface material would give city kids more places to play outside and had prevailed upon the Monsanto corporation to invent one. The result was clipped blades of nylon stuck to a rubber base, which the company called ChemGrass. Down it went into Houston’s outfield, where it got a new, buzzier name: AstroTurf.

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Workers lay artificial turf at the Astrodome in Houston on July 13, 1966. Developed by Monsanto, the material was originally known as ChemGrass but was later renamed AstroTurf after the stadium.
AP PHOTO/ED KOLENOVSKY, FILE

That first generation of simulated lawn was brittle and hard, but quality has improved. Today, there are a few competing products, but they’re all made by extruding a petroleum-based polymer—that’s plastic—through tiny holes and then stitching or fusing the resulting fibers to a carpetlike bottom. That gets attached to some kind of padding, also plastic. In the 1970s the industry started layering that over infill, usually sand; by the 1990s, “third generation” synthetic turf had switched to softer fibers made of polyethylene. Beneath that, they added infill that combined sand and a soft, cheap shredded rubber made from discarded automobile tires, which pile up by the hundreds of millions every year. This “crumb rubber” provides padding and fills spaces between the blades and the backing.

In the early 1980s, nearly half the professional baseball and football fields in the US had synthetic turf. But many players didn’t like it. It got hotter than real grass, gave the ball different action, and seemed to be increasing the rate of injuries among athletes. Since the 1990s, most pro sports have shifted back toward grass—water and maintenance costs pale in comparison to the importance of keeping players happy or sparing them the risk of injury. 

But at the same time, more universities and high schools are buying the artificial stuff. The advantages are clear, especially in places where it rains either too much or not enough. A natural-grass field is usable for a little more than 800 hours a year at the most, spread across just eight months in the cooler, wetter northern US. An artificial-turf field can see 3,000 hours of activity per year. For sports like lacrosse, which begins in late winter, this makes artificial turf more appealing. Most lacrosse pitches are now synthetic. So are almost all field hockey pitches; players like the way the even, springy turf makes the ball bounce.

Furthermore, supporters say synthetic turf needs less maintenance than grass, saving money and resources. That’s not always true; workers still have to decompact the playing surface and hose it off to remove bird poop or cool it down. Sometimes the infill needs topping up. But real grass allows less playing time, and because grass athletic fields often need to be rotated to avoid damage, synthetic ground cover can require less space. Hence the market’s explosive growth in the 21st century.


The city and town of Ithaca—two separate political entities with overlapping jurisdiction over Cornell construction projects—held multiple public meetings about the university’s new synthetic fields: the field hockey pitch and a complex called the Meinig Fieldhouse. Koizumi’s group turned up in force, and a few folks who worked at Cornell came to oppose the idea too—submitting pages of citations and studies on the risks of synthetic grass.

At two of those meetings, dozens of Cornell athletes turned out to support the turf. Representatives of the university and the athletic department declined to speak with me for this story, citing an ongoing lawsuit from Zero Waste Ithaca. But before that, Nicki Moore, Cornell’s director of athletics, told a local newspaper that demand from campus groups and sports teams meant the fields were constantly overcrowded. “Activities get bumped later and later, and sometimes varsity teams won’t start practicing until 10 at night, you know?” Moore told the paper. “Availability of all-weather space should normalize scheduling a great deal.”

That argument wasn’t universally convincing. “It’s a bad idea, but that’s from the environmental perspective,” says Marianne Krasny, director of Cornell’s Civic Ecology Lab and one of the speakers at those hearings. “Obviously the athletic department thinks it’s a great idea.”

square patch of artificial turf

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Members of Cornell on Fire, a climate action group with members from both the university and the town, joined in opposing the use of artificial turf, citing the fossil-fuel origins of the stuff. They described the nominal support of the project from student athletes as inauthentic, representing not grassroots support but, yes, an astroturf campaign. 

Sorting out the actual science here isn’t simple. Over time, the plastic that synthetic turf is made of sheds bits of itself into the environment. In one study, published in 2023 in the journal Environmental Pollution, researchers found that 15% of the medium-­size and microplastic particles in a river and the Mediterranean Sea outside Barcelona, Spain, came from artificial turf, mostly in the form of tiny green fibers. Back in 2020, the European Chemicals Agency estimated that infill material from artificial-­turf fields in the European Union was contributing 16,000 metric tons of microplastics to the environment each year—38% of all annual microplastic pollution. Most of that came from the crumb rubber infill, which Europe now plans to ban by 2031. 

This pollution worries the Cornell activists. Ithaca is famous for scenic gorges and waterways. The new field hockey pitch is uphill from a local creek that empties into Cayuga Lake, the longest of the Finger Lakes and the source of drinking water for over 40,000 people.

And it’s not just the plastic bits. When newer generations of synthetic turf switched to durable high-density polyethylene, the new material gunked up the extruders used in the manufacturing process. So turf makers started adding fluorinated polymers—a type of PFAS. Some of these environmentally persistent “forever chemicals” cause cancer, disrupt the endocrine system, or lead to other health problems. Research in several different labs has found PFAS in many types of plastic grass.

But the key to assessing the threat here is exposure. Heather Whitehead, an analytical chemist then at the University of Notre Dame, found PFAS in synthetic turf at levels around five parts per billion—but estimated it’d be in water running off the fields at three parts per trillion; for context, the US Environmental Protection Agency’s legal drinking-water limit on one of the most widespread and dangerous PFAS chemicals is four parts per trillion. “These chemicals will wash off in small amounts for long periods of time,” says Graham Peaslee, Whitehead’s advisor and an emeritus nuclear physicist who studies PFAS concentrations. “I think it’s reason enough not to have artificial turf.”

This gets confusing, though. There are over 16,000 different types of PFAS, few have been well studied, and different ­companies use different manufacturing techniques. Companies represented by the Synthetic Turf Council now “use zero intentionally added PFAS,” says Melanie Taylor, the group’s president. “This means that as the field rolls off the assembly line, there are zero PFAS-formulated materials present.”

Some researchers are skeptical of the industry’s assurances. They’re hard to confirm, especially because there are a lot of ways to test for PFAS. The type of synthetic turf going onto the new field hockey pitch at Cornell is called GreenFields TX; the university had a sample tested using an EPA method that looks for 40 different PFAS compounds. It came back negative for all of them. The local activists countered that the test doesn’t detect the specific types they’re most concerned about, and in 2025 they paid for three more tests on newly purchased synthetic turf. Two clearly found fluorine—the F in “PFAS”—and one identified two distinct PFAS compounds. (The company that makes GreenFields TX, TenCate, declined to comment, citing ongoing litigation.)

PFAS isn’t the only potential problem. There’s also the crumb rubber made from tires. A billion tires get thrown out every year worldwide, and if they aren’t recycled they sit in giant piles that make great habitats for rats and mosquitoes; they also occasionally catch fire. Lots of the tires that go into turf are made of styrene-­butadiene rubber, or SBR. In bulk, that’s bad. Butadiene is a carcinogen that causes leukemia, and fumes from styrene can cause nervous system damage. SBR also contains high levels of lead.

But how much of that comes out of synthetic-­turf infill? Again, that’s hotly debated. Researchers around the world have published suggestive studies finding potentially dangerous levels of heavy metals like zinc and lead in synthetic turf, with possible health risks to people using the fields. But a review of many of the relevant studies on turf and crumb rubber from Canada’s National Collaborating Centre for Environmental Health determined that most well-conducted health risk assessments over the last decade found exposures below levels of concern for cancer and certain other diseases. A 2017 report by the European Chemicals Agency—the same people who found all those microplastics in the environment—“found no reason to advise people against playing sports on synthetic turf containing recycled rubber granules as infill material.” And a multiyear study from the EPA, published in 2024, found much the same thing—although the researchers said that levels of certain synthetic chemicals were elevated inside places that used indoor artificial turf. They also stressed that the paper was not a risk assessment. 

The problem is, the kinds of cancers these chemicals can cause may take decades to show up. Long-term studies haven’t been done yet. All the evidence available so far is anecdotal—like a series for the Philadelphia Inquirer that linked the deaths of six former Phillies players from a rare type of brain cancer called glioblastoma to years spent playing on PFAS-containing artificial turf. That’d be about three times the usual rate of glioblastoma among adult men, but the report comes with a lot of cautions—small sample size, lots of other potential causes, no way to establish causation.

Synthetic turf has one negative that no one really disputes: It gets very hot in the sun—as hot as 150 °F (66 °C). This can actually burn players, so they often want to avoid using a field on very hot days.

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A field hockey player from Cornell University passes the ball during a game played on artificial turf at Bryant University in 2025. Cornell’s own turf field will be ready for the 2026 season.
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Athletes playing on artificial turf also have a higher rate of foot and ankle injuries, and elite-level football players seem to be more predisposed to knee injuries on those surfaces. But other studies have found rates of knee and hip injury to be roughly comparable on artificial and natural turf—a point the landscape architect working on the Cornell project made in the information packet the university sent to the city. Athletic departments and city parks departments say that the material’s upsides make it worthwhile, given that there’s no conclusive proof of harm.

Back in Ithaca, Cornell hired an environmental consulting firm called Haley & Aldrich to assess the evidence. The company concluded that none of the university’s proposed installations of artificial turf would have a negative environmental impact. People from Cornell on Fire and Zero Waste Ithaca told me they didn’t trust the firm’s findings; representatives from Haley & Aldrich declined to comment.

Longtime activists say that as global consumption of fossil fuels declines, petrochemical companies are desperate to find other markets. That means plastics. “There’s a big push to shift more petrochemicals into plastic products for an end market,” says Jeff Gearhart, a consumer product researcher at the Ecology Center. “Industry people, with a vested interest in petrochemicals, are looking to expand and build out alternative markets for this stuff.”

All that and more went before the decision-­makers in Ithaca. In September 2024, the City of Ithaca Planning Board unanimously issued a judgment that the Meinig Fieldhouse would not have a significant environmental impact and thus would not need to complete a full environmental impact assessment. Six months later, the town made the same determination for the field hockey pitch.

Zero Waste Ithaca sued in New York’s supreme court, which ruled against the group. Koizumi and lawyers from Pace University’s Environmental Litigation Clinic have appealed. She says she’s still hopeful the court might agree that Ithaca authorities made a mistake by not requiring an environmental impact statement from the college. “We have the science on our side,” she says.


Ithaca is a pretty rarefied place, an Ivy League university town. But these same tensions—potential long-term environmental and public health consequences versus the financial and maintenance concerns of the now—are pitting worried citizens against their representatives and city agencies around the country. 

New York City has 286 municipal synthetic-­turf fields, with more under construction. In Inwood, the northernmost neighborhood in Manhattan, two fields were approved via Zoom meetings during the pandemic, and Massimo Strino, a local artist who makes kaleidoscopes, says he found out only when he saw signs announcing the work on one of his daily walks in Inwood Hill Park, along the Hudson River. He joined a campaign against the plan, gathering more than 4,300 signatures. “I was canvassing every weekend,” Strino says. “You can count on one hand, literally, the number of people who said they were in favor.” 

But that doesn’t include the group that pushed for one of those fields in the first place: Uptown Soccer, which offers free and low-cost lessons and games to 1,000 kids a year, mostly from underserved immigrant families. “It was turning an unused community space into a usable space,” says David Sykes, the group’s executive director. “That trumped the sort of abstract concerns about the environmental impacts. I’m not an expert in artificial turf, but the parks department assured me that there was no risk of health effects.”

Artificial turf doesn’t go away. “You’re going to be paying to get rid of it. Somebody will have to take it to a dump, where it will sit for a thousand years.”

Graham Peaslee, emeritus nuclear physicist studying PFAS concentrations, University of Notre Dame

New York City councilmember Christopher Marte disagrees. He has introduced a bill to ban new artificial turf from being installed in parks, and he hopes the proposal will be taken up by the Parks Committee this spring. Last session, the bill had 10 cosponsors—that’s a lot. Marte says he expects resistance from lobbyists, but there’s precedent. The city of Boston banned artificial turf in 2022.  

Upstate, in a Rochester suburb called Brighton, the school district included synthetic-­turf baseball and softball diamonds in a wide-ranging February 2024 capital improvement proposition. The measure passed. In a public meeting in November 2025, the school board acknowledged the intent to use synthetic grass—or, as concerned parents had it, “to rip up a quarter ­million square feet of this open space and replace it with artificial turf,” says David Masur, executive director of the environmental group PennEnvironment, whose kids attend school in Brighton. Parents and community members mobilized against the plan, further angered when contractors also cut down a beloved 200-year-old tree. School superintendent Kevin McGowan says it’s too late to change course. Masur has been working to oppose the plan nevertheless—he says school boards are making consequential decisions about turf without sharing information or getting input, even though these fields can cost millions of dollars of taxpayer money.

In short, the fights can get tense. On Martha’s Vineyard, in Massachusetts, a meeting about plans to install an artificial field at a local high school had to be ended early amid verbal abuse. A staffer for the local board of health who voiced concern about PFAS in the turf quit the board after discovering bullet casings in her tote bag, she said, which she perceived as a death threat. After an eight-year fight, the board eventually banned artificial turf altogether. 


What happens next? Well, outdoor artificial turf lasts only eight to 12 years before it needs to be taken up and replaced. The Synthetic Turf Council says it’s at least partially recyclable and cites a company called BestPLUS Plastic Lumber as a purveyor of products made from recycled turf. The company says one of its products, a liner called GreenBoard that artificial turf can be nailed into, is at least 40% recycled from fake grass. Joseph Sadlier, vice president and general manager of plastics recycling at BestPLUS, says the company recycles over 10 million pounds annually. 

Yet the material is piling up. In 2021, a Danish company called Re-Match announced plans to open a recycling plant in Pennsylvania and began amassing thousands of tons of used plastic turf in three locations. The company filed for bankruptcy in 2025.

In Ithaca, university representatives told planning boards that it would be possible to recycle the old artificial turf they ripped out to make way for the Meinig Fieldhouse. That didn’t happen. An anonymous local activist tracked the old rolls to a hauling company a half-hour’s drive south of campus and shared pictures of them sitting on the lot, where they stayed for months. It’s unclear what their ultimate fate will be.

That’s the real problem: Artificial turf just doesn’t go away. “You’re going to be paying to get rid of it,” says Peaslee, the PFAS expert. “Somebody will have to take it to a dump, where it will sit for a thousand years.” At minimum, real grass is a net carbon sink, even including installation and maintenance. Synthetic turf releases greenhouse gases. One life-­cycle analysis of a 2.2-acre synthetic field in Toronto determined that it would emit 55 metric tons of carbon dioxide over a decade. Plastic fields need less water to maintain, but it takes water to make plastic, and natural grass lets rainwater seep into the ground. Synthetic turf sends most of it away as runoff.

It’s a boggling set of issues to factor into a decision. Rossi, the Cornell turf scientist, says he can understand why a school in the northern United States might go plastic, even when it cares about its students’ health. “It was the best bad option,” he says. Concerns about microplastics and PFAS are “significant issues we have not fully addressed.” And they need to be. 

Douglas Main is a journalist and former senior editor and writer at National Geographic.

Continuous attractor dynamics in spatial navigation: from population geometry to flexible computation

A central computational problem in spatial navigation is how spatial representations remain stable under noise and uncertainty, and update reliable estimations of continuous variables such as head-direction and position, which respectively rely on the head-direction system and the grid-cells system in the entorhinal cortex. The two systems demonstrate strong population-level dynamics, suggesting a potential framework to explain the critical problem of spatial representations. Currently, the framework involves continuous attractor networks and the neural field theories as an unified perspective, from which the population activity can be described as evolving of continuous variables on a low-dimensional attractor manifold, together with the selective instantiation of these dynamics across symmetry-related or context-dependent subspaces. From this viewpoint, a key question is how different sources of information, such as self-motion, sensory cues and environmental structure, interact with attractor dynamics to regulate the evolution and stability of population states. Specifically, external inputs can stabilize attractor states by anchoring them to landmarks; intrinsic network connectivity, symmetry, and multi-timescale dynamics determine whether an attractor is stable and whether it supports continuous motion; environmental boundaries and geometric constraints can systematically shape the local geometry of spatial activity patterns; direction- or context-dependent signals may selectively recruit neuronal subpopulations with specific tuning preferences; and cross-level organization of attractor dynamics, enabling a unified representational and control framework from individual decision-making to collective behavioral organization. Through the joint action of these mechanistic dimensions, continuous attractor representations are able to support the core computations required for navigation. More broadly, this perspective provides a theoretical foundation for understanding how continuous spatial representations are computed, read out, and flexibly manipulated to support planning and behavioral control.

STAT+: Everyone agrees AI scribes are increasing health care costs. No one agrees what to do about it

To hear health systems tell the story, artificial intelligence tools like ambient scribes are helping not only reduce doctor burnout, but also increasing payments from insurers that haven’t been compensating them properly. But on insurer earnings calls, the payers position themselves as white knights sounding the alarm on providers using AI to raise health care costs to an unsustainable level.

However, at least behind closed doors, both sides appear to agree that AI scribes are driving up health care costs. 

“The investors, the health plans, and the providers, in private, were like, ‘OK, well, it’s quite clear scribes are increasing coding intensity. One hundred percent,’” said Caroline Pearson, executive director at the Peterson Health Technology Institute, describing a roundtable PHTI held earlier this year. The nonprofit institute, founded in 2023, evaluates the impact of new technologies on health care costs and quality.

Continue to STAT+ to read the full story…

The Digital Path to AI in Cancer Care

David West
David West
CEO, Proscia

As cancer care becomes data-driven, artificial intelligence (AI) will play an increasingly central role across the treatment continuum, from biomarker identification and drug development to clinical trial recruitment and diagnostics. In this corner of healthcare, the ability of AI to interpret and annotate tumor sample slides that have been digitized is taking center stage. While the promise is great, and AI interpretation is already influencing some clinical care, it has not yet reached critical mass.

“There’s something like a billion slides created every year for diagnostic purposes, and today most of those, about 85%, are still read by a pathologist with a microscope on physical glass slides,” said David West, CEO and co-founder of digital pathology company Proscia. In practice, that means pathologists manually examine slides, identify cancer, grade tumors, and dictate reports in a traditional approach to diagnosing cancer that has seen little change in decades.

Mohamed Omar
Mohamed Omar, MD
Associate Professor
Cedars-Sinai Medical Center

But that foundation is now shifting. Advances in slide scanning, cloud storage, and AI are turning digital pathology images into data that can be analyzed at scale. At Memorial Sloan Kettering Cancer Center, large archives of digitized slides helped launch Paige AI, one of the earliest companies to train deep learning systems on pathology images linked to clinical and genomic outcomes. This yielded the first U.S. Food and Drug Administration (FDA)-approved diagnostic using AI and digital pathology: Paige Prostate Detect. The company, which was acquired last year by AI-enabled precision medicine company Tempus, now combines Paige’s digital pathology-based AI with Tempus’s broad genomic sequencing data platform.

Researchers in the field say the implications of AI in digital pathology extend beyond image analysis. Mohamed Omar, MD, an associate professor of computational biology at Cedars-Sinai Medical Center, Los Angeles, noted that large language models can help clinicians navigate a research landscape that produces “hundreds of papers every single day” to inform ongoing cancer research. Multimodal AI tools promise to unlock even more insights from digital pathology data by combining it with genomic, radiomic, and clinical data to build powerful new models of both common and rare cancers for diagnosis, drug development, and clinical trial enrollment.

Razik Yousfi
Razik Yousfi
SVP and GM, Tempus

While adoption is in its early stages, the advent of faster and less expensive scanners is bringing digital pathology within reach of both regional and rural hospitals. Razik Yousfi, senior vice president and general manager of AI products at Tempus, and a co-founder of Paige, predicts that within the next 10 years, the majority of pathology workflows will be digital. The ultimate goal of the application of AI here is not to replace human pathologists, but to empower them with a capable assistant while spreading adoption beyond major medical centers.

Building the foundations

As the field of applying AI to digital pathology progresses, it needs to build the groundwork for a wider range of potential applications that could address rare cancers and other areas without an abundance of data. One such project is called Atlas, a collaboration between researchers in Korea, Germany, and the United States to build a foundation model trained using 1.2 million histopathology whole-slide images from 490,000 cases sourced from the Mayo Clinic and Charité – Universitätsmedizin Berlin.

Foundation models like Atlas allow large-scale pre-training of data to develop numerical representations called embeddings that capture both the structural and contextual features of slides in the dataset. Atlas incorporates a diversity of diseases, staining types, and scanners, and uses multiple image magnifications during training. This broad approach confers power and utility. It allows the digitized representations of the histology to be adapted, queried, or fine-tuned to very specific downstream tasks using much less data than would be needed to build a one-off model.

As such, a foundation model provides a reusable digitized computational backbone that can be tapped across a wide range of uses, like tumor classification, detection of morphologic structures, biomarker quantification, and outcome prediction. In short, foundational models make the process of querying digital pathology images more efficient compared with past approaches.

Andrew P. Norgan
Andrew P. Norgan, MD, PhD
CMO, Mayo Clinic

“In the case of pathology, the successful AI models developed using ‘conventional’ neural network approaches before the advent of FMs (foundation models) typically required huge amounts of training data to achieve high performance and generalizability—the ability to work across datasets distinct from the training data,” said lead Atlas researcher Andrew P. Norgan, MD, PhD, CMO of Mayo Clinic Digital Pathology and assistant professor of laboratory medicine and pathology. “We think of FMs as [an] enabler that allows model development in pathology … to move from artisanal or craft processes to more scalable and reproducible processes that should allow for the rapid development of high-quality models to address problems in pathology.”

At Paige AI, the company’s early work resulted in the first FDA-approved AI diagnostic, Paige Prostate Detect. Its algorithm was built using a technique called multiple instance learning instead of traditional supervised neural network techniques that require detailed human annotation of slides, a time-consuming and expensive method that could expose the learning to human error. The difference between the two methods is that traditional neural networks expose AI to a slide with cancer and tell it that there is cancer present. In multiple instance learning, the model is shown unannotated slides and is tasked with finding the cancer.

Even this approach, however, required a very large dataset. It became apparent to company leaders that the heavy lifting required to get Paige Prostate Detect to work wasn’t scalable.

“We had kind of cracked this recipe,” said Yousfi. “We know how to use a lot of GPU (graphics processing unit) compute, and if we get a ton of data and a lot of compute, we can build anything. But GPU infrastructure is very expensive, and it takes a lot of time to train a very large system.”

Perhaps the most important factor moving Paige away from this model is that it will not work when there is only a small amount of data available. This blocks the ability to train AI to recognize rare cancers for which sample counts are low. The company needed a different approach.

“We had this idea [for] a new system that was basically trained on all of the images we had access to, independent of the organ and indication and tissue and task,” Yousfi said. “Back then, we didn’t know what that thing was called. But ultimately, that became what everyone is calling today a foundation model.”

Originally trained on 200,000 slides, Paige’s new model now includes 3.5 million images and roughly two billion parameters, making it the backbone for other downstream applications the company builds today. This ability to use foundation models as the AI and data encyclopedia for smaller applications will ultimately propel the field of digital pathology forward by widening the playing field.

Going multimodal

To address more complex predictive problems, additional data types can be integrated. Clinical, radiologic, or genomic data can be combined with morphologic embeddings or used during training to help the model learn which tissue features carry a signal of disease or identify a biomarker. These approaches aim to support precision oncology by making morphologic data computable and aligning slide-derived features with other cancer-focused datasets. “These approaches can surface subtle or ‘latent’ patterns in pathology slides and align them with other data sources,” Norgan said. Pathologist and oncology care teams can then evaluate and interpret the features identified by the models within the clinical and biological context.

“In this way, pathologists and oncology teams use these outputs as decision-support tools, while clinical judgment remains central to diagnostic interpretation and therapeutic decision making,” Norgan added.

Atlas has now been succeeded by Atlas2, which was trained on 5.5 million pathology images and is now a two billion-parameter model, making it one of the largest pathology foundation models to date. The team has explored distilling methods to create smaller, more efficient, and targeted versions of the model that retain performance, with an eye toward finding a balance between scale and deployability.

Proscia is embarking on a different multimodal approach that combines vision models with language models, with the intent of creating methods to query the morphology of digitized slides. Their efforts in vision-language models (VLMs) combine textual data with visual data and allow the model to describe the morphology of a slide, answer questions about what it contains, find images in a database based on a text query, and even follow multimodal instructions such as “circle the tumor area on this image.”

In short, a VLM can be engaged in the same way you can engage a human. “I could go ask a pathologist to point out all the areas of tumor-infiltrating lymphocytes,” West said. “Now, because language-vision models are encoding language and images in the same space, they can do that, too. You can ask the model to describe what is happening in an image, and it will tell you exactly what it sees.”

At Cedars-Sinai, Omar’s work with large language models takes a less direct route of leveraging queries to gather information from research studies or even images. “Basically, you could go to the tool, ask questions, and the tool will provide you with pieces of code,” he explained. “These pieces of code are what you use on the slide to get more information.”

Atlas provides a similar function at the Mayo Clinic, Norgan noted. Because the model-generated embeddings in the digitized slide also encode semantic information, the Atlas team is now building a slide search function, which would allow researchers or clinicians to identify and access slides, or regions of slides, with related features.

Democratizing care

Although it will take time to disseminate the tools needed for AI-enabled digitized models of cancer care to smaller health systems, the future is now at Moffitt Cancer Center, where the research hospital is engaged in a top-to-bottom digitization of its system.

Marilyn Bui
Marilyn Bui, MD, PhD
Senior Member
Moffitt Cancer Center

According to Marilyn Bui, MD, PhD, senior member of the departments of pathology and machine learning, the comprehensive cancer center plans for full digital adoption across clinical and research labs by 2027. Last August, it entered a multi-year collaboration with integrated AI and digital pathology company PathAI to deploy its cloud-based digital pathology image management system for both research and clinical applications.

Within the pathology department, the transition will mean that all glass slides will be scanned and reviewed digitally, providing the basis for applying AI computational tools to assist pathologists. Bui said that the cancer center is accelerating its move toward clinical AI adoption: “Just today I received an email asking which AI algorithms we plan to incorporate for clinical utility—prostate cancer, breast cancer, general tumor detection,” she said. “For us, it’s no longer just research.”

Moffitt is taking a hybrid approach to algorithm development and deployment within the system. Some AI tools will come from commercial vendors and will be validated internally, while others will be developed by investigators through the center’s translational pathology work. Taking this approach will allow it to apply AI to both common cancers and the rare tumor types Moffitt frequently encounters.

While the digital initiative will be transformational, Bui emphasized that the goal is not to replace pathologists but to enhance their capabilities. She prefers to refer to AI as augmented intelligence to reflect this. “Artificial intelligence suggests a robot replacing us,” she said. “But what we mean is augmented intelligence—tools that assist and enhance our ability to make clinical decisions.”

Further, Moffitt intends to integrate digitized slide data with genomic, proteomic, and clinical outcome data to build a multimodal data environment that could advance precision oncology. “Digital pathology and AI will allow us to extract far more information from tissue samples,” Bui said, “making our diagnoses more actionable for the clinical team and ultimately improving patient care.”

The promise of AI in oncology isn’t just better algorithms, it’s broader access. The maturation of computational pathology and its dissemination from large cancer centers like Moffitt to regional and rural health systems has the potential to provide levels of care typically only available at large research hospitals in community settings as well.

“It’s about democratizing access to care,” said Omar. “For a person in Maine or Wisconsin or another place to have access to the same high-quality care that you would get from a larger academic medical center in LA or New York, slides have to be digitized.”

Over the next 10 years, there could be a compelling business case for hospitals to embrace digital pathology. As the cost of scanners comes down and a broad range of diagnostic tools becomes available, digitizing routine H&E slides could become common.

While genetic cancer testing can cost hundreds of dollars, Omar pointed out that pathology slides “cost $5 [and] they are available universally, in all patients with cancer.” As AI models increasingly identify genomic-level insights directly from those inexpensive images, it represents a “huge win for accessibility, making AI work for patients who cannot afford genetic tests,” Omar said. If there is broad adoption of digital pathology “it is very easy to roll out any kind of AI models and computational tools across the board, across situations and locations that don’t have access to care.”

“At the end of the day, all slides will be digitized,” he concluded. “It’s just a matter of time.”

 

Chris Anderson, a Maine native, has been a B2B editor for more than 25 years. He was the founding editor of Security Systems News and Drug Discovery News, and led the print launch and expanded coverage as editor in chief of Clinical OMICs, now named Inside Precision Medicine.

The post The Digital Path to AI in Cancer Care appeared first on Inside Precision Medicine.

The Most Effective OCD Treatment Reaches Almost No One: Here’s What We Can Do About It

– Rebecca Deusser, MS, MBA and Sanjaya Saxena, MD

“It took me years to find out that what I was dealing with was OCD!”

This is a phrase all too often repeated by people living with obsessive compulsive disorder. Currently, individuals live with OCD for an average of 7 years (Dell’Osso et al, 2019) before they even receive a diagnosis, all while symptoms may intensify and daily life often becomes increasingly constrained. 

Clinicians, researchers, and advocates have long raised this concern. What has been missing is clear data behind how many people with OCD in the U.S. are missed in clinical settings or are not receiving the most effective treatment.

When the International OCD Foundation undertook this analysis, the scale of the problem became unmistakable. Millions of people in America are currently struggling with OCD without the most effective treatment.

The challenges we detail in our new white paper, America’s OCD Care Crisis: National Findings on the Failure of Effective OCD Treatment to Reach Patients, are significant, but fixable. They are symptoms of structural oversights that can be changed. Effective, evidence-based treatment for OCD exists, and through intentional action, we can dramatically change these unacceptable outcomes for people with OCD.

Where People With OCD Fall Through the Cracks

Well established prevalence rates for OCD indicate that nearly 10 million people in America — roughly 3% (Ruscio et al, 2010; Stein et al,2025; Ringeisen et al, 2025) — will have OCD at some point in their lives. Yet our findings suggest that 75% of them are never even identified, and up to 95% aren’t receiving the most effective treatment for the disorder.

In our analysis, we discovered significant systemic breakdowns at several key points of a patient’s journey: screening, diagnosis, referral, and treatment.

  • Screening and Diagnosis: Receiving a clinical diagnosis is an important step toward recovery as it promotes understanding and opens paths to effective treatment. Yet our findings suggest that this crucial initial step is missing for many millions of people. Of the 10.4 million patient records reviewed in our analysis, only 0.51% received a formal OCD diagnosis, far below the 3% expected prevalence rate. 
  • Referral to appropriate care: After a diagnosis is obtained, a handoff to appropriate care is needed to keep the patient from falling out of the treatment pathway. Here, too, we found an alarming gap within our sample: more than 72% of patients identified as having OCD did not receive a referral for cognitive-behavioral therapy (CBT), the most effective treatment for OCD.
  • Effective Treatment: Decades of research has established Exposure and Response Prevention (ERP) therapy, a specific form of CBT, as the most effective, first-line therapy for OCD. Yet, an astounding 95-98% of people with OCD had not received ERP treatment. Even when people seek help — and even when they are diagnosed — the vast majority never reach the treatment most likely to help them recover.

What We Can Do About It

The breakdowns seen in each step of the care pathway reinforce the focus of IOCDF’s Vision 2030, our five-year strategy to address the systemic barriers that keep effective OCD treatment out of reach.

While the findings are stark, they illuminate many opportunities for change:

  • Identify symptoms earlier by implementing routine OCD screening in primary healthcare and mental health settings.
  • Support clinicians in better understanding and treating OCD by expanding training in assessment, diagnosis, and evidence-based treatment modalities.
  • Help people receive care that works by strengthening adherence to existing professional treatment guidelines.
  • Increase the number of people with OCD who receive effective treatment  by supporting affordable access to ERP and other evidence-based therapies.
  • Let people know they’re not alone by raising accurate public awareness of what OCD really is — and that it is treatable.

Vision 2030 outlines how the IOCDF is committing its resources, partnerships, and expertise toward advancing these priorities — by increasing awareness and community, expanding access to effective treatment, and advancing research. Together, these efforts are designed to work in concert, improving clinical training, implementing screening for early identification, strengthening pathways from diagnosis to care, and increasing the likelihood that people receive evidence-based treatment.

At the same time, the scale of the problem revealed in this report makes clear that progress depends on collective action across the field. Clinicians, health systems, educators, researchers, policymakers, advocates, and people with lived experience all have a role to play. Together, these efforts can help ensure that people with OCD reach effective treatment sooner, reducing years of unnecessary confusion and distress. 

How You Can Help

Join us in building better access to effective treatment for people with OCD:

The current state of treatment for OCD in the U.S. is sobering, but it is not the end of the story. OCD is treatable, recovery is possible, and change can happen as awareness grows and access expands. With continued effort, the gap between how many are struggling and how many receive effective care can begin to close. A brighter future is possible — and we can build it together.

References

  1. Dell’Osso, B., Benatti, B., Grancini, B., Vismara, M., De Carlo, V., Cirnigliaro, G., Albert, U., & Viganò, C. (2019). Investigating duration of illness and duration of untreated illness in obsessive compulsive disorder reveals patients remain at length pharmacologically untreated. International Journal of Psychiatry in Clinical Practice, 23(4), 311–313. https://doi.org/10.1080/13651501.2019.1621348
  2. Ruscio, A. M., Stein, D. J., Chiu, W. T., & Kessler, R. C. (2010). The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication. Molecular Psychiatry, 15(1), 53-63. https://doi.org/10.1038/mp.2008.94
  3. Stein, D. J., Ruscio, A. M., Altwaijri, Y., Chiu, W. T., Sampson, N. A., Aguilar-Gaxiola, S., Al-Hamzawi, A., Alonso, J., Chardoul, S., Gureje, O., Hu, C., Karam, E. G., McGrath, J. J., Navarro-Mateu, F., Scott, K. M., Stagnaro, J. C., Torres, Y., Vladescu, C., Wciórka, J., Xavier, M., … Kessler, R. C. (2025). Obsessive-compulsive disorder in the World Mental Health surveys. Research Square, rs.3.rs-6090427. https://doi.org/10.21203/rs.3.rs-6090427/v1
  4. Ringeisen, H., Edlund, M., Guyer, H., Dever, J., Carpenter, L., Olfson, M., First, M., Geiger, P., Liao, D., Peytchev, A., Carr, C., Chwastiak, L., Dixon, L. B., Monroe-Devita, M., Scott Stroup, T., Swanson, J., Swartz, M., Gibbons, R., Stambaugh, L., Bareis, N., … Mental Health and Substance Use Disorders Prevalence Study Consortium (2025). Prevalence of past-year mental and substance use disorders, 2021-2022. Psychiatric Services (Washington, D.C.), 76(8), 720–728. https://doi.org/10.1176/appi.ps.20240329

IOCDF Training & Resources for Clinicians

When clinicians have easier access to best practices in OCD diagnosis and treatment, more people can receive effective care. The IOCDF’s Training Institute offers evidence-based programs for clinicians at every stage of practice, including:

  • A robust, on-demand webinar catalog (CE-eligible!) covering fundamentals, modalities, related disorders, and comorbidities. The catalog includes access to the free webinar, OCD Basics. 
  • IOCDF’s Training Institute offers intensive workshops and events, consultation groups, and more for clinicians of every level.
  • Professional Members at the IOCDF join a nationwide network of committed professionals, are eligible for listing on our Resource Directory, and have access to special pricing for Training Institute offerings.

The post The Most Effective OCD Treatment Reaches Almost No One: Here’s What We Can Do About It appeared first on International OCD Foundation.

The Unspoken Toll: Why Exam Pressure Must Be Part of the Youth Mental Health Discussion

A Conversation with Tatum Redmond and Amanda van der Vyver-Anderson from Community Keepers, South Africa


By Mai El Shoush, Partnerships Campaign Manager, Stavros Niarchos Foundation (SNF) Global Center for Child and Adolescent Mental Health at the Child Mind Institute


Community Keepers is an award-winning organization based in Stellenbosch, South Africa, which works to improve the social and emotional well-being of learners and their caregivers. The SNF Global Center at the Child Mind Institute works with the organization to further advance the comprehensive mission of transforming schools into safe spaces where student well-being is prioritized alongside academic achievement. This includes strengthening the workforce to expand evidence-based support and brief interventions through low-intensity psychological therapy approaches.

While addressing the workforce gaps, the partnership has yielded valuable insight into the essential competencies front line workers require to effectively support young people experiencing mental health challenges. Together with other NGOs, Community Keepers has also been instrumental in strengthening the process of developing context-sensitive and culturally appropriate training materials scheduled for pilot implementation in South Africa later this year – representing an important step towards strengthening mental health care systems for underserved communities. The partnership also extends beyond training development, as the SNF Global Center at the Child Mind Institute continues to collaborate closely with Community Keepers on an upcoming randomized control trial (RCT). The scientific evaluation will assess both the feasibility of establishing a virtual clinic for young people and the effectiveness of remotely delivered cognitive behavioral therapy (CBT) interventions via video consultations. The research is intended to expand access to equitable and quality mental health care for young people across South Africa. Tatum Redmond has been a care facilitator in one of the Community Keepers’ high school-based offices, while Amanda van der Vyver-Anderson is an educational psychologist and heads the training and development of Mental Health First Aiders for internal and external staff.

Amanda van der Vyver-Anderson

How important is it to approach issues such as academic pressure within the wider conversation around youth mental health in South Africa, and beyond?

It is critical to integrate discussions of exam stress into the broader dialogue surrounding youth mental health, both here in South Africa and internationally. We see countless students under immense pressure to not only pass, but also secure their future prospects and meet family expectations. This is unfortunately often dismissed as “just school” or a “normal” experience. However, it impacts a substantial number of young people, often more severely than we acknowledge. And the level of support available is not equitable across the board. Addressing this is crucial because of the detrimental effects on core cognitive functions — and ultimately, academic performance — as well as the significant toll on mental health. This can manifest as anxiety, burnout, and even depression.

In what ways can exam-related stress connect to broader mental health challenges?

While a certain level of stress can serve as a beneficial motivator, severe distress can lead to cognitive shutdown. This specifically impacts the executive functions — planning, organizing, prioritizing, working memory, focus, and concentration — that are fundamental to preparing for exams. This shutdown can then create a detrimental, ongoing cycle of heightened stress about exams or the future, coupled with a decline in the ability to take effective action.

It’s vital to recognize that exam stress does not merely stay in the exam room — it can be a gateway to larger mental health challenges. Constant stress regarding school performance, marks, or the fear of failure can escalate into conditions like anxiety, chronic overwhelm, or depression. Students may experience sleep disruption, poor nutrition, and feelings of inadequacy. And these symptoms often persist long after the test is over. Compounding this is the reluctance of most students to seek help because they believe their feelings are normal or fear appearing weak. Yet, if left unaddressed, sustained pressure along with these symptoms can profoundly affect their psychological well-being.

Tatum Redmond

What role do community-focused organizations such as Community Keepers play in linking academic stress to systematic youth mental health support and improvement?

Organizations like Community Keepers play a truly pivotal role — not merely as emergency responders but as an integrated support system within educational institutions as well. Crucially, they move beyond immediate crisis response by collaborating with schools to develop long-term support and to provide safe spaces to engage in dialogue. They offer genuine attention and care when learners are struggling with school demands, exams, and family pressures.

The approach is not just “addressing stress today” but asking, “How can we create an enduring environment where young people feel safe, supported, and connected?” Doing this requires collaboration with the learners themselves, educators and school staff, as well as parents, caregivers, and community leaders.

What factors make schools uniquely positioned to be safe and supportive spaces?
Schools are exceptionally well-positioned to serve as safe and supportive spaces for students for several key reasons:

  • Learners spend a substantial portion of their day at school, making it a primary setting where adults can observe signs of distress, anxiety, or coping difficulties.
  • Schools have the opportunity to house critical personnel — teachers, counselors, and external partners like Community Keepers — who are on hand to offer support or a listening ear.
  • The curriculum can extend beyond academic skills and learning. It can include mental health and emotional literacy, stress management, and peer support.
  • When a school actively fosters an environment of safety, respect, and validation, it fundamentally alters how learners navigate pressure, stress, or complex personal problems. Having a guaranteed safe space at school is deeply stabilizing for the mind.

How can the goal of securing mental health support as a pillar of education be reached?
Achieving the goal of establishing mental health support as a solid, non-negotiable pillar of education requires several strategic commitments:

  • Schools must actively allocate resources for it, ensuring adequate numbers of support staff, rather than relying on minimal provision. Teachers need training to recognize signs of distress and respond helpfully and appropriately.
  • Mental health literacy must be integrated into the curriculum. Instead of only focusing on academic subjects, topics like stress management, emotional intelligence, and maintaining healthy relationships should be covered.
  • The government must demonstrate a serious commitment, including mental health support in education budgets, developing clear policies, and ensuring rigorous follow-through.

How have your practices and initiatives in promoting and supporting schools as safe spaces made meaningful change?
We’ve observed tangible change in the learners’ attitudes; those who feel comfortable expressing their emotions are generally happier and more resilient because they have established a safe, non-judgmental space where trust is built.

What role can teachers and school leadership play as partners in creating an evidence-based supportive learning environment? Where are the gaps in building capacity and how can they be better supported?
Educators and school leadership are essential partners in establishing an environment that successfully supports learner mental health and cultivates a culture of well-being. They can do so by:

  • Prioritizing both the physical space and curriculum time necessary for learners to engage with support services.
  • Serving as role models who embody and encourage emotional regulation and actively normalize help-seeking behaviour.
  • Remaining deeply cognisant of factors that contribute to learner distress so as to not inadvertently exacerbate it.

Investing in staff wellness and support, capacity building, and policy reform is not merely beneficial, but a foundational requirement to capacitate educators effectively. This allows them to sustainably support the mental health of their entire school community.

The SNF Global Center’s work in South Africa is carried out through the Child and Adolescent Mental Health Initiative (CAMHI South Africa). We are proud to expand the partnership with Community Keepers and value their collaboration towards co-creating scalable, school-centered mental health approaches that authentically respond to the diverse lived-experiences of young people.

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