Astronomers using NASA’s James Webb Space Telescope have discovered water molecules inside the enormous envelope of gas and dust surrounding IRS 3, an aging star located remarkably close to the supermassive black hole at the centre of the Milky Way. The finding challenges the long-held assumption that the intense radiation and gravitational turbulence around Sagittarius A, commonly known as Sgr A, would prevent molecules from surviving in such a hostile environment.

IRS 3 lies about 0.6 light-years from Sgr A*, a distance equivalent to roughly 42,000 times the separation between Earth and the Sun. In everyday terms, that is an immense distance. On the scale of the Galactic Centre, however, it places the star in the immediate neighbourhood of a black hole containing approximately four million times the mass of the Sun. The region is crowded with stars, powerful magnetic fields, energetic particles and rapidly changing radiation, making IRS 3 an exceptional natural laboratory for studying how stars evolve under extreme conditions.

The observations were conducted with the Mid-Infrared Instrument, or MIRI, aboard the James Webb Space Telescope. Mid-infrared light is particularly useful for investigating cool dust and molecules that absorb and re-emit radiation at characteristic wavelengths. By analysing the infrared spectrum of IRS 3, researchers led by PD Dr Florian Peißker of the University of Cologne identified the chemical and physical properties of the material surrounding the star with far greater detail than previous observations allowed.

What makes IRS 3 especially striking is the scale of its circumstellar envelope. The structure extends to a radius of approximately 10,000 astronomical units, where one astronomical unit is the average distance between Earth and the Sun. Such envelopes are common around mature, evolved stars, but IRS 3 appears to be unusually isolated in the immediate vicinity of Sgr A*. Its enormous shell of material therefore stands out against a dense background containing millions of other stars.

The new observations indicate that IRS 3 is undergoing a phase known as a superwind. This is a brief but dramatic stage in the late evolution of certain stars, particularly asymptotic giant branch stars. During this phase, powerful stellar winds carry gas and newly formed dust away from the star at extremely high rates. Over periods of only a few centuries, the star can lose a substantial fraction of its outer layers, transforming its surroundings into a thick, expanding envelope that will eventually disperse into interstellar space.

According to the research team, IRS 3 is losing material at a rate equivalent to the mass of Earth every 18 days. Although the comparison makes the scale easier to imagine, the total outflow is far more significant when considered over astronomical timescales. The steady loss of gas and dust explains why the envelope is both unusually large and dense. It also provides the raw material in which molecules can form, shielded within cooler regions of the expanding stellar outflow.

The detection of water is the most surprising aspect of the study. Near Sgr A*, ultraviolet radiation, X-rays and high-energy particles are expected to break apart fragile molecules. Water molecules can be destroyed when energetic photons dissociate them into their constituent atoms, particularly in exposed regions close to powerful sources of radiation. Yet the MIRI observations show that water exists within the envelope of IRS 3, suggesting that the dense outflow from the star creates protected pockets where molecular chemistry can proceed.

This discovery does not mean that the Galactic Centre is a calm or hospitable environment. Instead, it demonstrates that stellar mass loss can temporarily create its own chemical refuge. The material expelled by IRS 3 increases the density of gas and dust around the star, allowing some regions of the envelope to absorb damaging radiation. Within these shielded zones, atoms can combine on dust grains or in the gas phase, producing molecules that would otherwise be rapidly destroyed. The finding offers a new view of how evolved stars may enrich even the most violent regions of a galaxy.

The researchers say that IRS 3 may be actively supplying the area around Sgr A* with elements and molecules that later become part of the broader interstellar medium. Water itself is not evidence of life, but it is a crucial ingredient in planetary formation and a central component of the chemistry that precedes biology. As the envelope expands, some of its contents will eventually mix with surrounding gas, potentially influencing the composition of future stars, planets and smaller bodies formed in the Galactic Centre.

The study, published in Astronomy & Astrophysics, also highlights the scientific value of observing the Milky Way’s centre at infrared wavelengths. Visible light is heavily obscured by dust along the line of sight, while infrared radiation can pass through much of that material and reveal otherwise hidden structures. Future observations with METIS, a next-generation mid-infrared instrument being developed for the Extremely Large Telescope in Chile, could provide sharper views of IRS 3’s envelope, measure its winds in greater detail and determine how its molecular content changes over time. For now, the star’s unexpected water-rich cocoon is offering astronomers a rare glimpse of stellar chemistry unfolding beside one of the most extreme objects in the universe.

Subject of Research: Not applicable

Article Title: Dust production in the harsh environment of Sgr A* – MIRI/JWST observation of the O-rich asymptotic giant branch star IRS 3

News Publication Date: 11-Aug-2026

Web References: https://doi.org/10.1051/0004-6361/202660243

References: Astronomy & Astrophysics

Image Credits: ESO/F. Peissker

Keywords

James Webb Space Telescope, JWST, MIRI, IRS 3, Sagittarius A, Sgr A, Milky Way, Galactic Centre, water molecules, superwind, asymptotic giant branch star, stellar evolution, circumstellar envelope, dust production, black hole, infrared astronomy, Extremely Large Telescope

A new research project at the New Jersey Institute of Technology is taking a closer look at a strange but important behavior in rubber-like materials: their properties can depend on what happened to them before. With a $125,000 New Directions grant from the American Chemical Society Petroleum Research Fund, chemical and materials engineering professor Gennady Gor and his students will investigate how petroleum-derived polymers absorb fluids, swell, contract and change their elasticity over time. The work could improve predictions of how elastomers perform in everything from industrial seals to oil and gas equipment.

Elastomers are polymers capable of undergoing large, reversible deformations. Silicone, neoprene and natural or synthetic rubber are familiar examples. Their molecular chains can stretch, rearrange and return toward their original configuration, giving these materials their characteristic flexibility. Yet exposure to liquids or vapors can dramatically alter that behavior. Hydrocarbon molecules may enter the polymer network, pushing molecular chains apart and causing the material to expand. At the same time, the absorbed fluid can change the polymer’s stiffness, strength and ability to recover its original shape.

Gor’s project focuses on a phenomenon known as hysteresis, in which a material’s current state depends not only on its present conditions but also on the path it took to reach them. For an elastomer, that means the material may respond differently when it is swelling than when it is shrinking, even if its size and surrounding environment are identical. The difference can arise from molecular rearrangements, delayed relaxation or changes in the interactions between polymer chains and absorbed molecules. Such path-dependent behavior is central to understanding why materials sometimes fail to return fully to their previous mechanical state.

The question is especially relevant for petroleum-related technologies. Elastomers are widely used as O-rings, gaskets and seals because they can deform to fill microscopic gaps and maintain a hermetic barrier. In oil and gas environments, however, these components may encounter complex mixtures of hydrocarbons under pressure and at elevated temperatures. If a seal swells excessively, softens or loses its ability to recover after repeated exposure, it can become unreliable. A better understanding of hysteresis could help engineers select materials and operating conditions that reduce leakage and extend component lifetimes.

The new study represents a shift for Gor’s Laboratory for Materials Interfaces. His previous research has largely examined porous adsorbent materials, which collect molecules on their internal surfaces. Elastomers are different: they do not need pores to take up substantial amounts of fluid. Instead, molecules diffuse into the polymer matrix and interact with its flexible chains. The resulting process is more like a sponge absorbing liquid, although the molecular mechanisms are governed by diffusion, thermodynamics and the elasticity of the polymer network.

Günel Nabiyeva, a fourth-year doctoral student, will lead much of the experimental effort with undergraduate chemical engineering student Elitsa Mileva and second-year doctoral student Supun Rangana. The team has already begun collecting data on how rubber deforms in the presence of liquids and vapors. For Mileva, who has spent considerable time reviewing the scientific literature, the grant will provide an opportunity to move deeper into laboratory work. Nabiyeva describes the project as a new system for the research group because the laboratory has not previously studied elastomers in this way.

The researchers will expose polymer samples to controlled concentrations of hydrocarbon vapors and track how the materials respond. Their measurements will combine swelling, fluid uptake and elasticity rather than treating these properties separately. This approach is essential because a polymer can gain mass and volume while simultaneously becoming softer or, under some conditions, displaying a more complicated mechanical response. Different hydrocarbons may produce different results because their molecular size, chemical structure and compatibility with the polymer influence how quickly they enter the material and how strongly they interact with its chains.

Rangana will contribute expertise in ultrasonic sensing, which can measure subtle changes without physically contacting or damaging the sample. Ultrasonic waves travel through a material in ways that depend on its density, structure and mechanical properties. By analyzing changes in wave transmission or reflection, scientists can detect variations in stiffness and internal condition with high precision. Coupling these measurements to vapor exposure could reveal how quickly elasticity changes as molecules enter the polymer and whether the material follows the same path during desorption as it did during absorption.

The team hopes its results will fill a gap in the fundamental understanding of polymer hysteresis. Although hysteresis is well known in many areas of physics and engineering, relatively few studies have examined how history-dependent elasticity develops in swollen elastomers. The new measurements may help distinguish reversible molecular motions from more persistent structural changes and improve models used to predict polymer performance. Ultimately, the researchers aim to make elastomer behavior less mysterious and more reliable, helping engineers design seals and flexible components that remain dependable across repeated cycles of chemical exposure, swelling and recovery.

Subject of Research: Elastomers, petroleum-derived polymers, polymer swelling, elasticity and hysteresis

Article Title: Ultrasonic Experiments Aim to Reveal Why Rubber Remembers Its History

Web References: Gennady Gor’s NJIT profile; NJIT Laboratory for Materials Interfaces

Image Credits: Courtesy of New Jersey Institute of Technology

Keywords

Elastomers, polymers, hysteresis, rubber, polymer swelling, ultrasonic sensors, materials science, chemical engineering, petroleum research, NJIT

Animal testing has shaped modern drug development for decades, but its limitations become especially visible when scientists evaluate cancer immunotherapies. These treatments are designed to stimulate the immune system to recognize and destroy malignant cells, yet the same powerful immune activation can trigger life-threatening complications in patients. Researchers at the University of Rochester are developing a human-cell-based alternative: miniature tissue models known as organs-on-a-chip that could help predict these toxicities before experimental medicines reach clinical trials.

The work is being led through the university’s Translational Center for Barrier Microphysiological Systems, or TraCe-bMPS. The center is building drug-development tools around modular µSiM tissue chips, devices that contain ultrathin membranes populated with human cells. Unlike conventional laboratory cultures, these systems are engineered to reproduce key features of biological barriers, including the physical separation between tissues, controlled exposure to drugs, and measurable inflammatory responses. Their modular construction also allows the devices to be manufactured in large quantities with consistent dimensions and materials.

The platform is based primarily on acrylic components and incorporates membranes designed to mimic interfaces found in the human body. Such barriers regulate the movement of molecules and immune cells between compartments, making them central to drug absorption, toxicity, and inflammation. By assembling reproducible chips with human cells, researchers can study how a therapy affects a tissue under conditions that more closely approximate human biology than many animal models. The design also makes it possible to modify individual components for different organs or disease settings.

A major feature of the Rochester system is the integration of sensors directly into the chips. Developed in part through the work of biomedical engineering professor Benjamin Miller, these sensors can track barrier function and inflammatory signaling in real time. Instead of waiting until the end of an experiment to examine damaged cells, researchers can observe how a tissue responds as a drug is introduced. Changes in electrical or molecular signals may reveal that a barrier is becoming more permeable or that inflammatory pathways are being activated, providing an early warning of toxicity.

The immediate focus is on two severe complications associated with some cancer immunotherapies. Cytokine release syndrome, commonly called CRS, occurs when activated immune cells release large quantities of signaling proteins known as cytokines. The resulting systemic inflammation can cause fever, low blood pressure, breathing difficulties, and, in the most serious cases, organ failure. Immune effector cell-associated neurotoxicity syndrome, or ICANS, can affect the nervous system, producing confusion, seizures, impaired speech, or other neurological symptoms. Both conditions are difficult to predict reliably with animal testing because species differ in immune signaling networks and cell-surface receptors.

“The goal is to predict these toxicities from human cells on a chip, before a drug ever reaches a patient, and to do it without relying on animal models that have repeatedly failed to predict CRS in people,” says James McGrath, director of TraCe-bMPS and the William R. Kenan Jr. Professor of Biomedical Engineering. The approach does not simply attempt to reproduce a whole human body in miniature. Instead, it focuses on specific biological barriers and immune interactions that are directly relevant to the safety question being studied.

The project has now reached an important regulatory stage. The team was accepted into the US Food and Drug Administration’s Innovative Science and Technology Approaches for New Drugs, or ISTAND, pilot program. ISTAND is intended to help evaluate emerging methods that could improve drug development and eventually support regulatory decisions. Acceptance does not mean that the tissue-chip platform has already been approved for routine use, but it creates a formal pathway for the researchers to work with the FDA on defining the evidence needed for qualification.

The Rochester group is preparing a detailed qualification plan that will describe clinical considerations, timelines, data-sharing procedures, and statistical methods for evaluating the technology. If the platform ultimately receives FDA qualification, pharmaceutical companies could use its results as part of the evidence submitted in support of new drug applications. Such recognition would represent a significant step for organs-on-a-chip research, which has expanded rapidly but has only rarely progressed into formal regulatory programs.

The effort comes as US regulators seek alternatives to animal testing in preclinical safety studies. The FDA Modernization Act 2.0, enacted in 2022, opened the door for non-animal methods, while the agency’s 2025 roadmap outlined further efforts to reduce reliance on animal models. Researchers say pharmaceutical companies are showing strong interest because many immunotherapies are already in clinical development and carry risks of CRS or ICANS. The Rochester team collaborated with Graham Marsh of the Critical Path Institute and consulted with scientists at Pfizer about how the tool could fit into real-world drug development. If successful, the technology could give researchers a more human-relevant way to identify dangerous immune reactions early, helping developers eliminate unsafe candidates and refine promising treatments before patients are exposed.

Subject of Research: Human-cell tissue chips for predicting cancer immunotherapy toxicities.

Web References: University of Rochester; Translational Center for Barrier Microphysiological Systems; University of Rochester Biomedical Engineering; FDA ISTAND pilot program; FDA Modernization Act 2.0.

Image Credits: URochester photo / J. Adam Fenster.

Keywords: Drug discovery, tissue chips, organs-on-a-chip, cancer immunotherapy, cytokine release syndrome, CRS, ICANS, neurotoxicity, animal testing alternatives, biomedical engineering, microphysiological systems, human-cell models.

A tiny microscope weighing just five grams could give neuroscientists an unprecedented view of how individual brain cells control behavior while animals move naturally. Researchers at the University of Colorado Anschutz Medical Campus and the University of Colorado Boulder have developed a head-mounted device that can both record neural activity and selectively activate individual neurons during movement. The technology could help scientists investigate how brain circuits generate behavior and how those circuits become disrupted in conditions such as Alzheimer’s disease, Parkinson’s disease and epilepsy.

The device, called Opto2P-FCM, combines two powerful techniques that have traditionally been difficult to use together in a freely moving animal. Two-photon microscopy provides detailed images of living brain tissue at cellular resolution, while optogenetics uses light-sensitive proteins to control selected neurons. By integrating both capabilities into a miniature instrument, the researchers can observe specific cells as they become active and then stimulate chosen neurons to test how they influence the surrounding network.

“These miniature microscopes have been increasingly used to study the neural basis of behavior in freely moving animals,” said Emily Gibson, PhD, associate professor of biomedical engineering at CU Anschutz and the study’s senior author. “This new microscope allows deeper penetration and higher resolution images in the brain. Importantly, it can also excite select neurons using optogenetics.”

For decades, conventional two-photon microscopes have been regarded as the gold standard for imaging neurons in living brains. These systems use infrared laser light to produce high-resolution images deep within tissue, allowing researchers to track calcium signals and other indicators of neural activity. However, conventional microscopes are generally large, stationary instruments. Animals must often remain immobilized beneath the objective, making it difficult to study brain activity during walking, exploration, social interaction or other natural behaviors.

Miniature microscopes have helped overcome that limitation by moving the imaging system onto the animal’s head. Yet reducing the size and weight of the equipment has often required compromises. Some compact systems provide lower-resolution images, while others can record neural activity but cannot stimulate precisely selected cells. The Colorado team designed Opto2P-FCM to address both problems through a dual-path optical architecture that separates imaging from stimulation.

In the imaging pathway, infrared light is directed through the brain to generate two-photon signals from fluorescent markers inside neurons. These markers can report changes in calcium concentration, which occur when neurons fire. The resulting signals are collected to create detailed images of neural activity at the level of individual cells. A separate optical pathway delivers patterned light for optogenetic stimulation, allowing researchers to activate specific neurons without disrupting the imaging beam or overwhelming the detectors.

This separation is technically important because imaging and stimulation place different demands on an optical system. High-resolution imaging requires precise focusing, efficient light collection and minimal optical distortion. Optogenetic activation, by contrast, requires intense, accurately positioned light capable of reaching the light-sensitive proteins expressed by selected neurons. Designing both functions into a device small enough to be carried by an animal required careful control of the alignment, geometry and weight of every optical component.

“This microscope is a game changer,” said Juliet Gopinath, PhD, professor of electrical, computer and energy engineering and physics at CU Boulder and a study co-author. “Being able to demonstrate a state-of-the-art instrument for both read-out and photo-stimulation of neurons is amazing.” The research team included engineers, physicists and neuroscientists who worked together to solve problems involving miniature lenses, mechanical tolerances, optical alignment and three-dimensional fabrication.

The device weighs approximately five grams, but its small size made construction unusually demanding. Mo Zohrabi, PhD, a senior research scientist at CU Boulder and co-first author, said the team initially thought such an instrument might be impossible to build because of the tight tolerances required by the optics and available 3D-printing technology. Gregory Futia, PhD, a senior research associate at CU Anschutz and co-first author, said that every component had to be designed and accounted for with extreme precision. Even slight misalignment could reduce image quality or prevent the stimulation beam from reaching the intended cells.

The researchers believe the platform could transform experiments designed to distinguish correlation from causation in the brain. Recording a neuron’s activity can show that it is associated with a behavior, but it does not prove that the cell helps produce that behavior. With optogenetic stimulation, scientists can activate a selected population and observe whether movement, decision-making or other actions change. At the same time, the microscope can record how neighboring neurons respond, providing a view of how local circuits coordinate activity.

The current Opto2P-FCM system is a prototype, and the researchers are working on future versions that could be smaller, lighter and faster. They also hope to expand the field of view so that more neurons can be monitored at once. Such improvements could make it possible to track larger networks over longer periods while animals engage in increasingly complex behaviors. By combining cellular-resolution observation with targeted manipulation in a freely moving subject, the technology may help reveal how healthy neural circuits operate and how neurological disease changes the communication between them.

Subject of Research: Miniature two-photon microscopy, optogenetics, neural circuits and brain activity during natural movement

Article Title: New Miniature Microscope Allows Scientists to Watch and Control Brain Cells During Natural Movement

News Publication Date: Aug. 11, 2026

Web References: University of Colorado Anschutz Medical Campus; University of Colorado Boulder; Optica study

References: Optica, “New Miniature Microscope Allows Scientists to Watch and Control Brain Cells During Natural Movement,” article publication date: Aug. 7, 2026

Keywords

Miniature microscope, two-photon microscopy, optogenetics, neuroscience, brain imaging, neural circuits, freely moving animals, biomedical engineering, applied physics, neurological disease, brain research

The Marcus Foundation has awarded $28.7 million to Chuck Murry, MD, PhD, director of the USC Stem Cell Center, to support a clinical trial testing a stem cell-based therapy intended to regenerate heart muscle damaged by a severe heart attack. The award, the largest the foundation has given to the University of Southern California and one of its largest contributions to academic medicine, will fund both the planned human study and a parallel research program examining how the immune system responds to transplanted cardiac cells.

The trial is scheduled to begin in 2027 at Keck Hospital of USC in partnership with the USC Cardiac and Vascular Institute. A second clinical site will be established at the University of Washington, where elements of the technology were originally developed. The first phase will enroll approximately 18 patients who have experienced extensive myocardial infarction, the medical term for a heart attack that destroys part of the heart’s muscular wall.

Patients in the study will receive stem-cell-derived heart muscle cells delivered into regions damaged by the infarction. The primary goals will be to evaluate safety and determine whether the procedure is feasible in people with severe cardiac injury. Investigators will also monitor early biological signals, including whether the transplanted cells remain active, integrate with the injured tissue and produce measurable changes in cardiac performance during recovery and long-term follow-up.

A heart attack occurs when blood flow through a coronary artery is blocked, depriving cardiac muscle of oxygen. Within minutes, cells in the affected region begin to die, and the resulting scar tissue lacks the contractile properties of healthy myocardium. Unlike tissues such as skin or blood, adult human heart muscle has only a limited capacity for self-repair. As a result, a large infarction can weaken the heart’s pumping function, increase the risk of heart failure and leave survivors unable to perform ordinary activities without fatigue or breathlessness.

Current cardiovascular treatments can reopen blocked arteries, limit further injury and help the remaining heart muscle work more efficiently. They cannot, however, routinely replace the cardiomyocytes that have already been lost. Murry’s research program is aimed at addressing that biological gap by producing replacement heart muscle cells in the laboratory and delivering them directly to damaged tissue. The strategy represents a shift from supporting a failing heart to attempting to rebuild part of its contractile apparatus.

The transplanted cells are being developed as a form of cellular therapy, in which living cells act as the therapeutic agent rather than serving merely as a vehicle for a drug. According to Murry, the cells are intended to become active within the injured heart, contribute to repair and synchronize with surrounding muscle. Achieving that outcome requires more than placing new cells into scarred tissue: the cells must survive, connect functionally with the host myocardium and avoid creating dangerous electrical disturbances or abnormal rhythms. The initial trial is therefore designed principally to establish safety before testing therapeutic effectiveness in larger patient groups.

The foundation’s funding will also support research into the immune response triggered by cell transplantation. Even cells created from stem cells can be recognized as foreign by the recipient’s immune system, potentially leading to inflammation or destruction of the transplanted population. Patients who receive cellular grafts may consequently require immunosuppressive drugs, which can increase susceptibility to infection and produce other long-term complications. Researchers will study how immune cells interact with the implanted cardiac cells and investigate methods that could reduce or eventually eliminate the need for chronic immunosuppression.

The work builds on approximately three decades of research by Murry and his collaborators to move regenerative cardiology from laboratory experiments toward clinical treatment. The program includes gene-edited cellular technology, intended to improve the compatibility or performance of therapeutic cells in the human body. The precise effectiveness of the approach will not be known until it is tested in patients, and the small 2027 cohort will not be large enough to determine whether the therapy improves survival or prevents heart failure. Those questions would require subsequent trials involving substantially more participants and longer observation.

The Marcus Foundation described the project as a potential turning point for regenerative medicine, while USC leaders said the investment could create a platform for developing additional cellular therapies. The immediate scientific challenge is to determine whether transplanted heart muscle cells can be delivered safely and function meaningfully within severely damaged human hearts. If the trial meets its safety and feasibility objectives, it could provide the clinical evidence needed to advance a new generation of treatments for myocardial infarction—therapies designed not only to help patients live with damaged cardiac tissue, but to restore some of the function that conventional medicine cannot yet replace.

Subject of Research: Stem cell-based regenerative therapy for heart muscle damaged by myocardial infarction

Article Title: $28.7 Million Award Supports USC Trial of Stem Cell Therapy to Regenerate Heart Muscle After Heart Attack

Web References: The Marcus Foundation: https://marcusfoundation.org/; USC Stem Cell Center: https://stemcell.keck.usc.edu/; Chuck Murry Lab: https://murrylab.usc.edu/charles-chuck-murry-md-phd/; USC Cardiac and Vascular Institute: https://www.keckmedicine.org/services/cardiovascular/; Keck School of Medicine of USC: https://keck.usc.edu/

Image Credits: Steve Cohn

Keywords: Heart disease, myocardial infarction, heart attack, heart muscle, stem cell research, stem cell therapy, cell therapy, regenerative medicine, cardiovascular disorders, heart failure, clinical trial, cardiac regeneration

Scientists in Arkansas have developed a machine-learning approach that can identify potentially disease-causing strains of a poultry bacterium by analyzing not only which genes are present, but also how those genes are arranged across the genome. The method focuses on the “genetic neighborhoods” surrounding genes, offering a new way to distinguish harmful strains of Enterococcus cecorum from closely related strains that do not cause disease.

E. cecorum is commonly found in poultry environments, and many of its strains are harmless. However, pathogenic strains can cause arthritis, bone infections and lameness, creating serious animal-welfare problems and economic losses for poultry producers. Because pathogenic and nonpathogenic strains can share many of the same genes, identifying the genetic features associated with disease has been challenging.

The research team, led by Aranyak Goswami of the Arkansas Agricultural Experiment Station’s Center for Agricultural Data Analytics, examined the organization of genes within genomic islands. These are segments of DNA that bacteria often acquire from other microorganisms through horizontal gene transfer. Genomic islands can carry genes involved in antibiotic resistance, bacterial survival, movement of DNA and virulence, making them important regions for understanding how pathogens emerge.

Rather than treating the bacterial genome as a simple list of genetic components, the researchers analyzed it as a structured map. They investigated which genes occurred near one another, the order in which they appeared and the way groups of neighboring genes formed recurring units known as genomic-island cassettes. This architecture provided information that could be missed when genes are examined individually.

“The machine-learning model recognizes patterns in gene order much like it recognizes patterns in language,” Goswami said. In the same way that a language model can learn that certain words frequently appear together, the computational system learned that particular combinations and arrangements of bacterial genes were associated with pathogenic strains. The approach therefore captures relationships among genes rather than relying only on the presence or absence of individual DNA sequences.

For the proof-of-concept study, the researchers analyzed the genomes of 145 E. cecorum strains isolated from poultry. The dataset included 95 nonpathogenic strains and 50 pathogenic strains capable of causing illness. The analysis found that disease-associated strains were more likely to contain genomic islands enriched in genes linked to antimicrobial resistance and the transfer of genetic material between bacteria.

Those findings do not mean that every bacterium carrying such genes will necessarily cause disease. Instead, the researchers describe the system as an exploratory classification and research tool. It identifies patterns that may help scientists investigate why some bacterial lineages become harmful, while also providing clues about how resistance and virulence traits move through bacterial populations.

Current monitoring methods for E. cecorum often depend on culturing the bacterium or screening for specific genes. Such techniques remain valuable, but they may overlook broader genomic relationships. The new pipeline could complement these approaches by evaluating the wider context in which genes occur. Additional testing with larger and more geographically diverse datasets will be necessary before the method can be used for routine flock surveillance or diagnostic decision-making.

The researchers believe the strategy could eventually be adapted to other bacterial species affecting animals, humans, wildlife and plants. Goswami’s team is beginning to examine Enterococcus faecalis, a close relative of E. cecorum and a frequent cause of hospital-acquired infections in humans. They also plan to apply the pipeline to Escherichia coli and other bacteria to study how nonpathogenic lineages acquire the genomic configurations associated with disease. The study, published in Frontiers in Microbiology, demonstrates how machine learning and comparative genomics can reveal hidden signals in bacterial DNA and may help researchers track the evolution of emerging pathogens.

Subject of Research: Animals

Article Title: Genomic-island cassette architecture provides interpretable signal for exploratory classification of poultry-associated Enterococcus cecorum lineages

News Publication Date: 7-Jul-2026

Web References: https://doi.org/10.3389/fmicb.2026.1882753

References: Frontiers in Microbiology, DOI: 10.3389/fmicb.2026.1882753

Image Credits: UA University Relations photo by Chieko Hara

Keywords: artificial intelligence, machine learning, deep learning, computational biology, bacterial pathogens, Enterococcus cecorum, genomic islands, genomic architecture, antibiotic resistance, poultry disease, pathogen surveillance, comparative genomics

Around 11,000 years ago, communities in southwest Asia began one of the most consequential experiments in human history: growing their own food. Wild cereals, legumes and fruit-bearing plants were gradually brought under human management, setting in motion the transition from mobile hunter-gatherer lifeways to farming societies. For decades, archaeologists have assumed that one of the earliest signs of this transformation was an increase in cereal grain size. A new study, however, suggests that some of the biggest grains found at the dawn of agriculture may not have been genetically altered at all. They may simply have grown in wetter conditions.

The findings, published in the Proceedings of the National Academy of Sciences, challenge a central assumption about how cereal domestication began. Researchers studying charred barley and emmer wheat grains from the Early Neolithic sites of el-Hemmeh and Sharara in the southern Levant found that the plants still possessed fully wild characteristics during the earliest phases of the Pre-Pottery Neolithic. Their ears had brittle rachises, the structures that naturally break apart when mature, allowing seeds to disperse in the wild. There was no evidence of the tough, non-shattering rachis that later became one of the defining features of domesticated cereals.

The absence of non-shattering forms is significant because a tough rachis makes harvesting far more efficient. In wild cereals, the rachis fractures as the plant ripens, scattering seeds before people can collect them. A mutation that keeps the grains attached would have offered major advantages to human harvesters and could then have spread through repeated cultivation and replanting. Researchers have therefore often treated the appearance of non-shattering cereals as a key marker of domestication. Grain size, by contrast, has frequently been interpreted as an earlier signal that people were already selecting plants through cultivation.

At el-Hemmeh and Sharara, however, grain size told a more complicated story. Barley and emmer wheat remained morphologically wild, yet their grains varied dramatically. Some were as small as typical wild cereals, while others fell within the size range commonly associated with domesticated plants. If large grains were the product of genetic selection caused by systematic tillage, the researchers expected to find other evidence of intensive cultivation. Instead, the ecological evidence pointed toward relatively low-disturbance environments.

The team examined the weed species preserved alongside the cereal remains. Weeds are valuable archaeological indicators because different plants thrive under different environmental conditions. Species associated with heavily tilled or frequently disturbed soils were not dominant in the assemblages from these early sites. This weakened the argument that repeated ploughing or intensive soil preparation had already created strong selection for larger seeds. The researchers began looking for another explanation for the striking variation in grain size.

Their answer came from stable carbon isotope analysis. Carbon exists in several naturally occurring forms, or isotopes, and plants incorporate these isotopes in ways that are influenced by their growing conditions. In cereals, the stable carbon isotopic composition of a grain can reflect the balance between carbon uptake and water loss during photosynthesis. When plants experience water stress, changes in gas exchange through their leaves alter the carbon isotope signal recorded in their tissues. By measuring this signal in ancient grains, scientists can reconstruct aspects of the moisture conditions under which the plants grew.

The results showed a strong relationship between grain size and water availability. Barley grains that reached domestic-sized dimensions had carbon isotope values indicating that they developed under wetter conditions. Smaller, wild-sized grains carried signatures consistent with considerably drier growth environments. The difference suggests that environmental moisture, rather than inherited genetic change, was responsible for much of the early increase in cereal grain size. In other words, the same wild plant population could produce grains of very different sizes depending on the conditions it experienced during development.

This phenomenon is known as developmental plasticity: the ability of a single genotype to produce different physical traits in response to the environment. It is widespread in plants and can affect characteristics such as height, leaf area, flowering time and seed production. In the Early Holocene southern Levant, developmental plasticity may have created the visual impression that cereals were already becoming domesticated. People collecting and replanting the largest grains might eventually have generated genetic selection, but the initial size increase itself appears to have been ecological rather than evolutionary.

“Environmental conditions provided a much better explanation for the observed variation in grain size than genetic selection under tillage,” said Dr Jade Whitlam of the University of Oxford, who led the study. The researchers propose that genetic selection for larger grains may have occurred later than previously thought, perhaps after selection for non-shattering rachises had already begun. This reverses the sequence often assumed in models of domestication and places greater emphasis on the complex interaction between climate, plant biology and human harvesting practices.

The study also reframes the origins of agriculture as a gradual process of niche construction rather than a sudden decision to domesticate plants. Early communities altered their relationship with wild vegetation through harvesting, protection, transport and repeated use of particular landscapes. These practices may have changed plant populations long before crops displayed unmistakable domestication traits. By combining archaeobotany, weed ecology and stable isotope evidence, the researchers argue that the first steps toward agriculture were not necessarily driven by deliberate genetic engineering of crops, but by prolonged human management operating within a variable environment. The result is a more nuanced picture of farming’s origins—one in which climate could temporarily make wild cereals look domesticated before their genomes caught up.

Subject of Research: The environmental and biological processes that influenced cereal grain size and plant domestication in the Early Holocene southern Levant.

Article Title: Developmental plasticity under human management shaped cereal evolution prior to domestication in the Early Holocene southern Levant

News Publication Date: 4-Aug-2026

Web References: https://www.eurekalert.org/multimedia/1146086

References: Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.2535274123

Image Credits: Jerome Poulalier, www.jerome-poulalier-photography.com

Keywords: Archaeology, archaeobotany, cereal domestication, agriculture, Neolithic, Early Holocene, southern Levant, barley, emmer wheat, stable carbon isotopes, developmental plasticity, plant evolution, climate, hunter-gatherers

The University of Houston has launched UH Health, a cross-disciplinary academic health enterprise intended to reshape how healthcare professionals are educated, how medical research is conducted and how care reaches communities across Texas. The initiative brings together medicine, nursing, pharmacy, optometry, psychology, social work, population health, biomedical research and health systems science under a single interprofessional framework. University leaders say the model is designed to confront a rapidly intensifying combination of population growth, healthcare worker shortages, chronic disease and unequal access to medical services.

Rather than treating healthcare disciplines as separate academic and clinical systems, UH Health is built around team-based care. In this approach, physicians, nurses, pharmacists, optometrists, behavioral health specialists, social workers and public health experts contribute to a shared understanding of each patient’s needs. The model reflects the growing recognition that health outcomes are shaped not only by disease biology, but also by mental health, housing, income, nutrition, transportation and access to preventive services. By training students to work across professional boundaries, the University hopes to prepare graduates for a healthcare system increasingly focused on coordinated and personalized care.

“Healthcare is no longer delivered in isolation, and complex health challenges require coordinated solutions,” said Jonathan McCullers, vice president for health affairs at UH and dean of the Tilman J. Fertitta Family College of Medicine. The university’s academic health strategy is intended to place students in an environment where clinical reasoning, behavioral science, population health and scientific discovery interact. Such integration can help future clinicians identify the underlying drivers of illness, select more appropriate interventions and communicate more effectively with specialists and community organizations.

The launch comes as Texas faces a widening gap between healthcare demand and workforce capacity. Rapid population growth, an aging population and shortages of trained professionals have placed pressure on hospitals and clinics throughout the state. The Texas Hospital Association has reported that 64% of hospitals were operating with fewer beds or reduced services because of staffing shortages. UH Health aims to expand the pipeline of physicians, nurses, pharmacists, optometrists, social workers and other professionals while emphasizing workforce readiness, collaborative practice and the ability to manage complex cases.

UH’s location near the Texas Medical Center gives the initiative access to one of the world’s largest concentrations of hospitals, research institutes and specialized clinical programs. Partnerships with organizations including HCA Healthcare, Memorial Hermann Hospital, Baylor College of Medicine and MD Anderson Cancer Center are expected to provide students and researchers with expanded opportunities for clinical training, translational research and collaboration. Translational research—the process of moving discoveries from laboratories into diagnostics, treatments and public health programs—depends heavily on this type of interaction between universities, hospitals and industry.

The university is also positioning UH Health as a platform for research that reaches beyond traditional medical departments. Scientists in chemistry, physics and biomedical engineering are working alongside health researchers on problems ranging from cancer and infectious disease to substance-use disorders and neurodegeneration. UH researchers have received more than $11 million from the Cancer Prevention and Research Institute of Texas for work involving cancer prevention, diagnosis and treatment. A fentanyl vaccine developed at the university is advancing toward human trials, although its clinical effectiveness and safety will need to be established through carefully controlled studies.

Brain health is another major focus. Texas ranks fourth nationally in the number of Alzheimer’s cases and second in Alzheimer’s-related deaths, according to the Texas Department of State Health Services. More than 100 faculty members across 12 of UH’s 16 colleges are involved in research related to prevention, early detection, caregiving and treatment, supported by $62.5 million in active grants. Their work may involve diverse technologies and methods, including biological markers, computational analysis, behavioral interventions, biomedical engineering and the study of social factors that influence cognitive decline and caregiver health.

To strengthen this research ecosystem, UH is investing $77 million in a new 55,000-square-foot medical research building. The facility is expected to support interdisciplinary laboratories and shared scientific infrastructure, allowing investigators from different fields to exchange data, equipment and expertise more efficiently. In modern biomedical science, discoveries often emerge at the boundaries between disciplines—for example, when engineering approaches are applied to drug delivery, physical sciences are used to study disease mechanisms or data science improves early diagnosis.

UH Health’s community programs are intended to connect these academic and research activities with practical healthcare needs. The UH Health Family Care Center provides primary care and mental health services to the university and surrounding communities, including Third Ward, East End and South Houston. The Household-Centered Care program gives students experience through home visits with community caregivers, while the 3rd Ward Place of Wellness offers screenings, preventive services and health education. The College of Optometry extends access to vision care through community clinics and outreach programs serving children and families.

The enterprise is also expanding beyond Houston through a partnership with DHR Health in the Rio Grande Valley, a rapidly growing region that continues to face significant medical access challenges. University officials say the collaboration could support healthcare education, workforce development and research tailored to local needs. By linking professional training, scientific discovery and community partnerships, UH Health is presenting an academic health model designed for a state where medical demands are growing faster than conventional systems can respond.

Subject of Research: Academic healthcare education, biomedical research, healthcare workforce development and community health access

Article Title: University of Houston Launches UH Health to Integrate Education, Research and Community Care

Web References: https://mediasvc.eurekalert.org/Api/v1/Multimedia/ed42117d-36c9-45cf-b2e3-443e4e08b680/Rendition/low-res/Content/Public

References: Texas Hospital Association; Texas Department of State Health Services; University of Houston

Image Credits: University of Houston and UH Health

Keywords: UH Health, University of Houston, healthcare workforce shortage, academic health, team-based care, biomedical research, cancer research, fentanyl vaccine, Alzheimer’s disease, community healthcare, nursing, optometry, pharmacy, medical education, Texas Medical Center

A climate shock that unfolded about 304 million years ago is offering scientists a dramatic warning about how quickly Earth’s climate system can amplify an initial temperature rise. During the Late Paleozoic Ice Age, a relatively modest increase in global temperatures appears to have triggered a much larger episode of warming, as methane released from thawing permafrost intensified the greenhouse effect. Researchers say the ancient event provides a powerful geological parallel for the climate changes occurring today.

The study, led by Le Yao of the Nanjing Institute of Geology and Paleontology with contributions from University of Cincinnati geosciences professor Thomas Algeo and international colleagues, examined a short-lived warming episode during Earth’s penultimate ice age. Their findings suggest that global sea surface temperatures eventually increased by more than 7 degrees Celsius, or approximately 12 degrees Fahrenheit. The rise was not necessarily caused by one enormous initial pulse of carbon. Instead, it may have developed through a chain reaction in which warming activated additional natural sources of greenhouse gases.

The Late Paleozoic Ice Age extended across a vast span of geological time, when large ice sheets covered parts of the supercontinent Gondwana. Although the planet was in an “icehouse” state, atmospheric carbon dioxide and methane still had the power to destabilize the climate. The newly analyzed warming event is particularly significant because it occurred under ice-age conditions rather than during an already warm greenhouse world. That makes it a valuable analog for the modern Earth, which still contains continent-scale ice masses in Greenland and Antarctica.

According to the researchers, the initial climate disturbance may have been linked to volcanic activity. Volcanic emissions can inject carbon dioxide and other gases into the atmosphere, where they absorb outgoing infrared radiation and prevent some heat from escaping into space. The warming may also have been assisted by changes in Earth’s orbit. Over long cycles, variations in orbital shape alter the distribution of sunlight across the planet, influencing the growth and retreat of ice sheets and changing the seasonal balance of solar energy.

At first, the additional carbon may have produced only a limited temperature increase. But once warming crossed a critical threshold, frozen ground in high-latitude regions began to thaw. Permafrost contains large quantities of organic carbon preserved in frozen soils. When that material becomes available to microbes, decomposition can release carbon dioxide and methane. Methane is especially powerful over shorter atmospheric timescales because, molecule for molecule, it absorbs considerably more infrared radiation than carbon dioxide, even though it remains in the atmosphere for less time.

This process can create a positive climate feedback. An initial warming causes permafrost to thaw, thawing releases greenhouse gases, and the additional gases produce further warming. That extra heat can accelerate more thawing, allowing the cycle to reinforce itself. The researchers describe the ancient event as a transient global warming episode in which a comparatively modest carbon release appears to have crossed a climatic tipping point and initiated much more extensive carbon emissions from natural reservoirs.

The geological timescale of the ancient warming is also central to the study’s relevance. Algeo said the temperature change unfolded over tens of thousands of years, with warming occurring at an average rate of roughly one-tenth of a degree Celsius per 1,000 years. Modern warming is progressing far more rapidly. Researchers have observed an increase of nearly 1 degree Celsius in global sea surface temperature over approximately the past century, a rate many times faster than the average change reconstructed for the ancient event.

The comparison does not mean that Earth is destined to repeat the precise conditions of 304 million years ago. Continents, ecosystems, atmospheric composition and ice-sheet geometry were all different in the Late Paleozoic. However, the physics of greenhouse warming and the existence of carbon feedbacks remain relevant. Ancient climate records reveal how a system that appears stable can respond nonlinearly when warming activates processes capable of releasing additional greenhouse gases.

The findings also place human history in a broader planetary context. All recorded human civilization has developed during the most recent ice age, despite the fact that the term can sound incompatible with today’s climate. In scientific usage, Earth remains in an ice age because substantial permanent ice sheets still exist in Greenland and Antarctica. The ancient warming episode matters precisely because it demonstrates that an ice age does not guarantee a permanently cold or stable climate. Even within an icehouse world, a small disturbance can trigger rapid and substantial changes when reinforcing feedbacks are engaged.

The research, published in the Proceedings of the National Academy of Sciences, underscores why scientists closely monitor permafrost, polar ice and other climate-sensitive carbon stores. The ancient record cannot provide an exact forecast of future warming, but it shows that Earth’s climate has repeatedly responded to carbon disturbances with amplifying feedbacks. As modern emissions continue to raise temperatures at an exceptional rate, the geological evidence offers a clear message: the danger lies not only in the carbon released directly by human activity, but also in the natural carbon sources that warming can unlock.

Subject of Research: Ancient global warming, permafrost methane feedbacks, and climate tipping points during the Late Paleozoic Ice Age

Article Title: A transient global warming event during Earth’s penultimate icehouse

Web References: https://doi.org/10.1073/pnas.2601643123

References: Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.2601643123

Image Credits: Andrew Higley, University of Cincinnati

Keywords: climate change, global warming, ice age, Late Paleozoic Ice Age, permafrost, methane, climate feedback, tipping point, paleoclimate, geology, volcanic activity, Earth’s climate history

A multidisciplinary team from Baylor College of Medicine, Rice University and the University of Texas School of Public Health has received the inaugural Climate + Health Excellence award from the Burroughs Wellcome Fund. The five-year, $10 million award will support FORECAST, an ambitious program designed to investigate how climate change, extreme weather and environmental disruption influence the emergence and spread of infectious diseases. Led by infectious disease researcher Dr. Anthony Maresso, the project will combine wastewater surveillance, metagenomic sequencing, climate science, epidemiology and public education to create an early-warning system for pathogen activity across Texas.

FORECAST will build on Texas’s expanding wastewater-monitoring infrastructure, including the Texas Wastewater Environmental Biomonitoring Network, or TexWEB. The statewide network samples sewage from 15 Texas cities and analyzes biological material shed by communities. Unlike clinical surveillance, which depends on people seeking medical care and receiving diagnostic tests, wastewater epidemiology captures population-level signals from entire communities. Viral genetic fragments, bacterial DNA and other biological markers can appear in sewage before hospitals and clinics register a rise in patients, providing public health officials with valuable time to investigate and respond.

The program will use metagenomic surveillance, a technique that examines genetic material recovered from environmental samples rather than searching only for a predetermined pathogen. In conventional testing, laboratories typically use targeted molecular assays designed to detect a known virus or bacterium. Metagenomic sequencing can survey a much broader range of organisms, including variants and potentially unfamiliar pathogens. Researchers can then compare these signals with clinical data, geographic information and environmental measurements to determine whether changes in temperature, rainfall, flooding, drought or other conditions are associated with shifts in infectious disease activity.

The scientific goal is not simply to identify pathogens after they appear, but to uncover relationships between microbes and the environmental conditions that help them enter or circulate within human populations. Climate change can influence disease transmission through several pathways. Warmer temperatures may expand the geographic range or seasonal activity of mosquitoes and other vectors. Heavy rainfall and flooding can overwhelm sanitation systems and redistribute contaminants, while drought can alter water use and concentrate biological material. Changes in human behavior, animal movement and ecosystems may create additional opportunities for pathogens to cross species boundaries.

Maresso and his colleagues demonstrated during the COVID-19 pandemic that SARS-CoV-2 signals in wastewater could precede increases in clinically diagnosed infections. Viral RNA released in feces entered sewage systems, where researchers tracked changes in concentration over time. Although wastewater measurements cannot determine which individuals are infected, they can reveal whether pathogen activity is increasing or declining within a catchment area. The approach has since been extended to a wider range of targets, including avian influenza, measles, HIV and viruses associated with cancer. FORECAST aims to develop this surveillance capacity into a predictive climate-health platform.

Rice University climate scientist Dr. Sylvia Dee will help connect pathogen observations with weather and climate data. The team plans to examine whether specific environmental patterns consistently occur before increases in particular infectious agents. Such models could eventually function like a public health weather report, indicating when conditions are becoming more favorable for disease transmission. The researchers emphasize that predictive systems will require careful validation because the presence of pathogen genetic material does not necessarily indicate infectious virus, active transmission or a future outbreak. Interpreting the signal will require laboratory studies, clinical evidence and knowledge of local infrastructure.

The project will also investigate diseases transmitted by vectors such as mosquitoes. Dr. Peter Hotez and colleagues at the National School of Tropical Medicine will focus on vector-borne pathogen transmission and the growing health risks associated with changing climate conditions. Texas is particularly relevant for this work because it contains diverse ecological regions and experiences heat waves, hurricanes, flooding and rapid urban growth. These factors can affect mosquito habitats, human exposure and the movement of pathogens across communities. Integrating wastewater findings with vector surveillance could help reveal connections that would remain hidden if either system were used alone.

Education and public communication will form a central part of FORECAST. The team plans to create a “Middle to Medical” climate-health education track extending from middle school through medical training and professional development. Dr. Nancy Moreno, who developed Baylor’s BioEd online program, will lead educational efforts with Rice University’s Dr. Joseph Campana, director of the university’s Center for Environmental Studies and EcoStudio. The curriculum will explain how pathogens spread, how climate conditions alter disease risk and how scientific evidence can guide decisions by students, clinicians, policymakers and communities.

The award is particularly significant because FORECAST was selected as the sole funded project from 161 applications submitted to the new CHEX program. The initiative is intended to strengthen research, education and public engagement at the intersection of climate change and human health. Dr. Eric Boerwinkle, dean of the UT School of Public Health and a project co-investigator, will contribute access to large clinical datasets that can be used to evaluate wastewater and environmental signals against reported illnesses. The investigators say the work could improve outbreak preparedness while advancing the still-developing field of wastewater science.

By combining environmental sequencing with climate modeling and health education, FORECAST seeks to shift infectious disease surveillance from a largely reactive system toward earlier detection and prevention. Its findings may help officials recognize emerging threats before they produce widespread clinical disease, while also clarifying how environmental changes shape viral evolution, transmission and geographic spread. The researchers describe wastewater as an unusually candid public health resource: it aggregates biological information from a population without requiring individual testing. As climate pressures intensify, they argue, that collective signal could become an essential tool for protecting communities and preparing the next generation of scientists.

Subject of Research:
Climate-driven infectious disease emergence, wastewater epidemiology, metagenomic pathogen surveillance and climate-health education.

Article Title:
Texas Researchers Launch FORECAST Program to Link Climate Change With Emerging Viral Threats

Web References:
Baylor College of Medicine; Rice University; University of Texas School of Public Health; Burroughs Wellcome Fund; Texas Wastewater Environmental Biomonitoring Network (TexWEB).

References:
Information provided in the source news release concerning the FORECAST project, the Climate + Health Excellence award and TexWEB wastewater surveillance activities.

Keywords:
Wastewater epidemiology, viral surveillance, metagenomic sequencing, climate change, infectious diseases, pathogen emergence, public health, Texas, SARS-CoV-2, avian influenza, measles, vector-borne disease, climate health, epidemiology, wastewater science

A research team in Japan has won a US$1 million Milestone 2 award in the XPRIZE Healthspan competition for developing engineered “super exosomes,” microscopic biological delivery vehicles designed to target aging and damaged cells. Led by Professor Keisuke Goda of Tohoku University’s SiRIUS Institute of Medical Research and Graduate School of Medicine, in collaboration with researchers from the University of Tokyo’s Department of Chemistry, the team was selected from more than 600 competitors worldwide.

XPRIZE Healthspan is a seven-year international competition focused on extending the period of life people spend in good health. Participating teams are challenged to develop treatments capable of restoring muscle, cognitive, and immune function in adults between 50 and 90 years old. The competition sets a minimum target of reversing at least 10 years of biological decline, while the most ambitious goal is a 20-year improvement within one year or less of treatment. Goda’s team is now moving forward after receiving recognition for results obtained in aged animal studies.

At the center of the research are exosomes, naturally occurring nanoparticles released by cells. These membrane-bound vesicles normally transport proteins, lipids, messenger RNA, and other molecular signals between cells, functioning as part of the body’s communication network. Because exosomes can carry biological cargo and interact with specific tissues, scientists have been investigating them as potential alternatives to synthetic drug-delivery systems. However, naturally produced exosomes often lack sufficient targeting precision, limiting their ability to reach the cells most relevant to a disease or aging process.

The Tohoku-led group attempted to solve that problem by chemically modifying the surface of exosomes with lanthanide ions. Lanthanides are a family of metallic elements with distinctive electronic and chemical properties. According to the researchers, attaching these ions changes the surface behavior of the exosomes and substantially improves their ability to recognize and bind to senescent cells. The resulting particles have been named “super exosomes,” a term that reflects their enhanced targeting and delivery capabilities rather than a new biological category.

Cellular senescence is one of the major biological processes associated with aging. Senescent cells have generally stopped dividing because of accumulated damage or stress, but they do not necessarily disappear. Instead, some remain metabolically active and release inflammatory molecules, growth regulators, and other signals that can disrupt nearby tissues. This collection of secreted factors, often called the senescence-associated secretory phenotype, can contribute to chronic inflammation, impaired tissue repair, and the deterioration of organs. Precisely influencing these cells has therefore become a major objective in longevity research.

The proposed super-exosome platform is designed to deliver regenerative molecular cargo directly to aging tissues after attaching to senescent cells. Potential cargoes include growth factors, messenger RNA, and other genetic materials capable of altering cellular behavior. Rather than distributing such molecules broadly throughout the body, a targeted exosome could concentrate them near damaged or dysfunctional tissue. In theory, this approach could promote repair while reducing unwanted effects in healthy cells, although the degree of targeting and the durability of the response will need to be confirmed in human studies.

In preclinical experiments involving several groups of aged mice, the researchers reported statistically significant improvements in frailty, physical performance, and multiple functional measures associated with aging. They also described the treatment’s safety profile as excellent in the studies conducted so far. The team says the overall benefit corresponds to more than 15 additional healthy human years when estimated using cross-species lifespan scaling. Such calculations can help compare biological effects between species, but they are not evidence that a mouse treatment will extend human life by a specific number of years. Human biology, dosing, immune responses, and long-term risks could differ substantially.

The award will support the next stage of development: clinical studies planned in collaboration with Tohoku University Hospital and the Tohoku University Healthspan Research Center. These studies will need to establish how the particles behave in humans, how efficiently they reach senescent cells, what cargoes are most effective, and whether the treatment produces measurable improvements in strength, cognition, immunity, or other healthspan indicators. Researchers will also have to monitor possible immune reactions, unintended effects on healthy tissues, changes in tumor risk, and the persistence of engineered exosomes in the body. These questions are essential before claims of age reversal can move beyond the laboratory.

The platform could eventually be investigated for conditions involving muscle decline, cognitive impairment, immune dysfunction, hair loss, skin aging, and reproductive health. The team plans to commercialize the technology through NanoTitan, with the aim of developing scalable manufacturing and international distribution for exosome-based therapeutics produced in Japan. “Advancing to the XPRIZE Healthspan finals is an important milestone, but our ultimate goal is to translate this technology into therapies that allow people to lead healthy, independent, and active lives longer,” Goda said. The research now enters its most demanding phase: determining whether an impressive result in aged mice can become a safe, reproducible, and clinically meaningful treatment for people.

Subject of Research: Engineered “super exosomes” designed to target senescent cells and deliver regenerative molecular cargo for healthy aging.

Article Title: Japanese Research Team Wins US$1 Million XPRIZE Award for “Super Exosome” Aging Technology

Web References: https://mediasvc.eurekalert.org/Api/v1/Multimedia/673c8fb3-268a-4a90-93b4-a0d531624a52/Rendition/low-res/Content/Public

Image Credits: Goda Lab

Keywords: Super exosomes, exosomes, cellular senescence, healthy aging, longevity research, XPRIZE Healthspan, regenerative medicine, Tohoku University, lanthanide ions, aged mice, healthspan, nanomedicine

PHILADELPHIA — Public resistance to new data centers has risen sharply across the United States, even as Americans’ overall views of artificial intelligence remain largely unchanged, according to a nationally representative survey from the Annenberg Public Policy Center at the University of Pennsylvania. The findings reveal a growing divide between public attitudes toward AI as a technology and attitudes toward the physical infrastructure required to operate it. While many people continue to see potential benefits from AI, particularly in medical research, opposition increases substantially when the technology is associated with a large industrial facility being built near their homes.

The survey found that 61% of U.S. adults somewhat or strongly oppose the construction of new data centers in their communities. That figure is 12 percentage points higher than the 49% recorded in an earlier APPC survey conducted in February and March. Support fell during the same period, from 21% to 14%. The change comes as communities across the country debate the environmental, economic, and social consequences of rapidly expanding computing infrastructure used to train and operate advanced AI systems.

Data centers are specialized facilities filled with servers, networking equipment, cooling systems, backup power supplies, and security infrastructure. AI applications can require enormous amounts of computational power because they process vast datasets and perform calculations across billions of model parameters. Training a large AI model may require thousands of processors operating simultaneously, while everyday use also depends on data centers to generate responses, analyze images, translate languages, and carry out other tasks. These facilities can consume substantial amounts of electricity and water, making their construction a highly visible local issue even when the software they support is used remotely.

Opposition to local data centers crosses political boundaries. Majorities of Democrats, Republicans, and independents said they opposed new facilities in their areas, although the proportions differed: 69% of Democrats, 54% of Republicans, and 53% of independents expressed opposition. Resistance was strongest among adults younger than 30, reaching 70%, and declined to 57% among people 65 and older. The pattern is notable because younger adults are often assumed to be more comfortable with emerging technologies and are more likely to use AI-powered services in education, work, entertainment, and communication.

Despite the shift in views about local infrastructure, broader opinions about AI have remained stable. Thirty-nine percent of respondents said they expected AI’s impact on the United States over the next decade to be somewhat or very negative, compared with 18% who expected a positive impact. The result was statistically unchanged from the spring survey. In addition, 68% said the federal government has done “too little” to regulate AI, a view shared by majorities of Democrats, Republicans, and independents. The results suggest that concerns about AI regulation have become persistent rather than being driven solely by short-term news events.

Respondents distinguished sharply between areas where AI might produce public benefits and areas where it could create risks. Among 13 sectors examined, medical research and scientific discovery was the only category receiving a net-positive assessment, with anticipated benefits exceeding expected harms by 41 percentage points. AI systems are increasingly being used to identify patterns in biological data, predict molecular structures, assist with medical imaging, and help researchers screen potential treatments. These applications may accelerate work that would otherwise require years of laboratory experiments, although they still depend on human validation and carefully controlled clinical studies.

The most negative assessments involved personal privacy and data security, which registered a net score of minus 63 points. Children’s online safety followed at minus 50 points, while employment and jobs reached minus 46 points. These concerns reflect the technical and social consequences of deploying AI at scale. Models may be trained on or exposed to sensitive information, automated systems can make decisions that are difficult to explain, and workplace applications may alter or eliminate certain tasks. The survey does not measure whether these risks will materialize in specific industries, but it indicates that many Americans view them as more immediate than AI’s possible benefits outside medicine.

Personal experience with AI was associated with more favorable opinions about its national impact. Among respondents who said they had never used AI during the previous month, 54% expected its effect on the country to be negative. That proportion fell to 40% among light users and to 29% among those who used AI many times or almost every day. However, frequent use did not make people more supportive of data centers. Opposition to building new facilities near respondents’ homes remained essentially flat across different levels of AI use. This distinction suggests that familiarity may influence perceptions of digital tools, while concerns about electricity demand, water consumption, noise, traffic, land use, and local utility costs may remain regardless of personal experience with AI software.

“The people who use AI the most are the most optimistic about what it will do for the country, and that has been consistent across our surveys,” said Matt Levendusky, a University of Pennsylvania political science professor and the Stephen and Mary Baran Chair in the Institutions of Democracy at APPC. He said that optimism had clear limits, particularly when questions involved privacy, employment, or the construction of a data center nearby. The survey was conducted by SSRS for APPC’s Institutions of Democracy division among 1,320 U.S. adult citizens from June 16 through July 19, 2026. Respondents were surveyed primarily online, with a small telephone sample, and weighted to match population benchmarks. The margin of error for the full sample was plus or minus 3.5 percentage points, with larger margins for subgroups. Together, the findings indicate that the next phase of the AI debate may be shaped less by abstract promises about intelligent software than by negotiations over the highly physical systems that make it possible.

Subject of Research: People

Article Title: Opposition to Local Data Centers Rises Sharply as Views on AI Hold Steady

Web References: Annenberg Public Policy Center news release; Reuters; The New York Times; Associated Press

References: Annenberg Public Policy Center Institutions of Democracy national survey, June 16–July 19, 2026; APPC AI topline survey data; APPC survey methodology

Image Credits: Annenberg Public Policy Center

Keywords: Artificial intelligence, data centers, public opinion, AI regulation, medical research, privacy, data security, employment, social surveys, political science

Pulmonary arterial hypertension (PAH) is being redefined by molecular biology. Once viewed mainly as a disorder of excessive blood-vessel constriction, the disease is now understood as a progressive process involving vascular remodeling, immune activation, metabolic disruption, and inherited susceptibility. A review published online on June 17, 2026, in the Chinese Medical Journal describes how these interacting mechanisms are reshaping PAH research and opening the door to treatments designed not only to relieve symptoms, but also to alter the disease itself.

PAH is a rare and potentially fatal condition in which the small arteries carrying blood through the lungs become narrowed and structurally damaged. As resistance within the pulmonary circulation rises, the right side of the heart must pump harder to maintain blood flow. Over time, the right ventricle can enlarge, weaken, and fail. Current therapies have improved survival, but many patients continue to experience progressive disease, limited exercise capacity, and an uncertain long-term outlook. The new review was conducted by Dr. Taeil Yang of Gil Medical Center at Gachon University College of Medicine and Professor Wook-Jin Chung of the Gachon Cardiovascular Research Institute in the Republic of Korea.

The authors explain that PAH develops through a complex interaction among several types of cells in the pulmonary circulation. Endothelial cells, which form the inner lining of blood vessels, normally regulate vessel diameter, blood flow, clotting, and repair. In PAH, these cells become dysfunctional and can produce excessive vasoconstrictors while reducing protective signals such as nitric oxide and prostacyclin. Endothelial injury also promotes the recruitment of inflammatory cells and stimulates neighboring smooth-muscle cells and fibroblasts to multiply. The resulting changes thicken the vessel wall and progressively reduce the space available for blood flow.

Inflammation is another central feature of this transformation. T cells, B cells, macrophages, and other immune cells can accumulate around pulmonary arteries, releasing cytokines and growth factors that sustain vascular injury. Rather than being a temporary response to damage, this immune activity may become chronic, reinforcing the abnormal behavior of vascular cells. The review emphasizes that immune signaling is closely connected to endothelial dysfunction and tissue remodeling, suggesting that PAH cannot be fully understood by studying blood-vessel tone alone.

The metabolism of pulmonary vascular cells also changes as the disease advances. Under normal conditions, mitochondria generate much of the energy required for cellular function through oxidative phosphorylation. In PAH, endothelial and smooth-muscle cells may shift toward glycolysis, a pattern resembling the “Warburg effect” observed in cancer. This metabolic reprogramming allows cells to generate energy rapidly while supporting biosynthesis and proliferation. It can also increase resistance to programmed cell death, enabling abnormal cells to persist within the vessel wall. These changes help explain why pulmonary arteries can continue remodeling even when vasoconstriction is medically controlled.

Genetic research has provided some of the strongest evidence that PAH is driven by specific biological pathways. Variants in BMPR2, the gene most commonly associated with heritable PAH, can impair signaling involved in vascular growth, repair, and cell survival. Other genes linked to PAH include SOX17, TBX4, and KCNK3. Several of these genes influence the bone morphogenetic protein, or BMP, pathway and its relationship with transforming growth factor beta, known as TGF-β. When this signaling network is disrupted, the balance between controlled growth and abnormal proliferation can shift, increasing susceptibility to pulmonary vascular disease. Genetic risk, however, is not destiny: environmental exposures, inflammation, infections, hormonal influences, and other biological triggers may determine whether disease develops and how rapidly it progresses.

These discoveries are already influencing treatment strategies. Traditional PAH medicines primarily target pathways that regulate vascular constriction, including endothelin, nitric oxide, and prostacyclin signaling. Newer approaches aim deeper at the mechanisms driving vascular remodeling. Sotatercept has attracted particular attention because it acts on signaling within the BMP/TGF-β superfamily and is designed to restore a healthier balance between growth-promoting and growth-inhibiting signals. By targeting the biology of vessel-wall remodeling rather than simply dilating arteries, the therapy represents a shift toward disease modification. Researchers are also studying seralutinib, which targets growth-factor and platelet-derived growth-factor signaling, as well as immune-directed treatments such as tocilizumab and rituximab. Metabolism-focused therapies remain another active area of investigation.

The review also highlights the growing importance of multi-omics research. Genomics can reveal inherited variants, while transcriptomics shows which genes are active in diseased tissue. Proteomics measures changes in proteins and signaling molecules, and metabolomics captures the chemical products of altered cellular pathways. Combining these layers may reveal why patients with apparently similar clinical diagnoses can have very different disease trajectories or responses to therapy. Such information could eventually help physicians classify patients according to molecular subtypes, identify biomarkers before irreversible vascular damage occurs, and select treatments according to the dominant mechanism in each individual.

Professor Chung argues that the most promising future for PAH depends on connecting laboratory discoveries with carefully designed translational studies and clinical trials. That challenge is substantial because the disease involves multiple interacting cell types and pathways, and because tissue samples from the pulmonary circulation are difficult to obtain. Nevertheless, the expanding molecular framework is changing the goals of treatment. Instead of focusing exclusively on lowering pulmonary artery pressure, researchers are seeking ways to repair endothelial dysfunction, restrain immune activity, normalize cellular metabolism, and reverse pathological remodeling. The field is moving toward precision medicine in which genetic and molecular information may guide therapy, offering patients the possibility of longer-lasting control and, ultimately, recovery of healthier pulmonary vascular function.

Subject of Research: Pulmonary arterial hypertension and its molecular mechanisms and emerging treatments

Article Title: Pulmonary arterial hypertension from a translational perspective: Bridging pathophysiology and treatment

News Publication Date: 17-Jun-2026

Web References: https://doi.org/10.1097/CM9.0000000000004137

References: Chinese Medical Journal, DOI: 10.1097/CM9.0000000000004137

Image Credits: Chinese Medical Journal

Keywords: Pulmonary arterial hypertension; PAH; BMPR2; SOX17; TBX4; KCNK3; BMP signaling; TGF-β; vascular remodeling; endothelial dysfunction; inflammation; metabolic reprogramming; sotatercept; seralutinib; precision medicine

Cities may soon be able to identify their hottest walking routes with the same precision used to map traffic or public transport. HeiGIT, the Heidelberg Institute for Geoinformation Technology, has added a tree-shade indicator to its free Climate Action Navigator, a digital platform designed to help municipalities and civil society organizations understand how urban environments affect everyday life. The new tool provides a street-level view of where pedestrian paths are protected by tree canopies and where people are exposed to direct sunlight, offering planners a detailed basis for decisions about urban greening, heat adaptation and safer walking routes.

The need for such information is becoming increasingly urgent as cities experience more frequent and intense heat waves. A citywide estimate of tree cover can suggest that an urban area is relatively green while concealing major differences between neighborhoods. In one district, a large park or wooded hillside may raise the average, even though the streets used daily by residents remain almost entirely unshaded. The Climate Action Navigator is designed to reveal these local contrasts by measuring shade along pedestrian routes rather than relying only on broad land-cover statistics.

In Innsbruck, Austria, tree cover extends across approximately 30 percent of the city’s relevant areas, but the distribution is far from even. Much of the shaded pedestrian network lies outside the central urban area, while heavily used streets in the city center can remain exposed to full sun. This distinction matters because people experience heat at the scale of individual journeys: walking to school, commuting to work, visiting shops or reaching public transport. Two routes separated by only a few streets may therefore offer very different levels of thermal comfort and protection from solar radiation.

The indicator is also intended to connect physical infrastructure with human behavior and well-being. Shaded paths can make walking more attractive during hot weather, potentially influencing whether people choose to travel on foot, wait for public transport or avoid certain destinations altogether. Claudia Schmiedeberg of the GLEN Study said that understanding the social effects of climate change requires examining how local surroundings shape daily decisions over time. Combining the tree-shade data with longitudinal survey information could help researchers investigate whether residents in greener neighborhoods adapt differently to heat, and whether unequal access to shade contributes to wider social disparities.

Technically, the tool identifies pedestrian walkways that directly overlap with tree canopies at least two meters high. The height threshold is designed to distinguish trees capable of producing meaningful overhead shade from low shrubs, grass and ground vegetation. The analysis uses high-resolution global canopy datasets and applies the same processing method across different cities. This allows a small town, a regional center and a major capital to be compared using a consistent measure rather than relying on incompatible local mapping systems.

The calculation also models a high-noon scenario, when the sun is strongest and shadows are generally shortest. By estimating shade under these demanding conditions, the indicator focuses on a daily period when heat exposure may be especially severe. It measures the availability of shade at what the developers describe as the weakest point of the day, creating a conservative benchmark for planning. The result is not a complete simulation of human thermal comfort, which also depends on air temperature, humidity, wind, pavement materials and building geometry, but it provides a clear spatial signal of where tree canopy is present above pedestrian infrastructure.

Early comparisons show how sharply shade levels can differ between cities. In the historic city of Maribor, Slovenia, approximately 35 percent of the pedestrian network is covered by trees. In Tempe, Arizona, a university city located in a hot and generally arid region, the corresponding figure is just above 7 percent. Such numbers do not by themselves determine whether a city is comfortable or unsafe, but they provide a comparable starting point for identifying exposure. When combined with information about schools, care facilities, public transport stops or tourist destinations, the data can show which groups and routes may require priority attention.

Urban planners could use the indicator to decide where new trees would provide the greatest benefit, while also recognizing streets where existing canopy already supports walking during hot periods. Linking shade maps with school catchment areas, for example, could reveal whether children have protected routes to school or must travel through long stretches of direct sunlight. Tourism agencies and local authorities could also use the information to recommend cooler walking routes to major attractions. In this way, the platform is intended not only to document an environmental problem but also to support targeted interventions, from tree planting and maintenance to short-term route guidance.

Jim Walker of the Walk21 Foundation said the indicator offers comparable, street-by-street evidence that can help administrations prioritize infrastructure investment during the hottest months. Its developers argue that global canopy datasets make it possible to overcome the local data shortages that often prevent smaller municipalities from conducting detailed climate assessments. Dr. Kirsten von Elverfeldt, community engagement manager at HeiGIT, said the goal was to make granular diagnostic information freely available so that greening initiatives can be directed toward the places where they are most needed.

The Climate Action Navigator is open to the public, allowing users to explore how their municipality performs and compare different urban areas. The platform’s tree-shade indicator does not replace on-the-ground assessments, but it can help transform an abstract climate challenge into a visible pattern of shaded and exposed streets. As heat increasingly shapes how people move through cities, that ability to see the difference at walking level could make urban climate planning more precise, more equitable and more immediately actionable.

Subject of Research: Not applicable

Article Title: New Global Tool Maps Tree Shade Street by Street to Reveal Cities’ Heat Exposure

News Publication Date: August 11, 2026

Web References: Climate Action Navigator: https://heigit.org/ ; Tree shade indicator video: https://www.youtube.com/watch?v=vAQxEnAgM44 ; Innsbruck example: plugin/hiwalk?share-id=f50386c3-4ea6-45b8-946a-6fedfae38dc8 ; Maribor example: plugin/hiwalk?share-id=f675a5bd-f15f-429c-81f4-80cac6c7051a ; Tempe example: plugin/hiwalk?share-id=31880ebb-1c6d-40e1-89cf-ffac9bceb607

Image Credits: Climate Action Navigator

Keywords: urban heat, tree shade, climate adaptation, pedestrian routes, urban planning, tree canopy, heat exposure, Climate Action Navigator, HeiGIT, sustainable cities

Lipid nanoparticles (LNPs) have become one of the most important delivery technologies in modern medicine, helping transport messenger RNA into cells for vaccines, protein replacement therapies and experimental treatments. Yet a formulation that performs well in mice can behave very differently in humans. This species gap makes nonhuman primate studies an important step in drug development, but conventional methods for comparing multiple nanoparticles often require euthanasia and extensive tissue collection. A new study reports a way to measure the functional activity of several LNPs in the same animal using only a small blood sample.

Published in Nature Biotechnology, the work introduces a non-invasive nanoparticle barcoding platform called snapCodes. The method is designed to determine which LNP formulation successfully delivers its mRNA cargo and prompts cells to produce the encoded protein. Rather than relying on tissue harvesting, the researchers identify delivery events through DNA barcodes that can be recovered from serum and analyzed by sequencing. The approach could allow scientists to compare many candidate nanoparticles in a single nonhuman primate while reducing both animal use and the logistical burden of downstream analysis.

The central challenge addressed by the study is that nanoparticle delivery is not adequately described by measuring where an LNP travels. An LNP may reach an organ or circulate in the bloodstream without releasing its mRNA in a form that cells can translate. The new system instead records functional mRNA delivery. Each nanoparticle is associated with a distinctive DNA sequence, and the mRNA cargo is engineered to encode a fusion protein containing nanoluciferase and a SNAP-tag. Nanoluciferase is a compact enzyme that produces light in the presence of its substrate, while the SNAP-tag is a protein module capable of forming a covalent bond with specific chemical groups.

For the barcode to become a permanent molecular record of delivery, the researchers modified the DNA tags with benzylguanine. When a cell receives an mRNA molecule encoding the nanoluciferase–SNAP-tag fusion, the resulting protein can react with a benzylguanine-bearing snapCode. This creates a stable DNA–protein complex. The complexes are then exported from cells into the circulation, where they can be isolated from a small serum sample. Sequencing the recovered DNA reveals which barcoded LNPs produced the fusion protein and therefore achieved functional mRNA delivery.

The design turns transient protein expression into a measurable signal that can be collected without sacrificing the animal. This is particularly valuable in studies involving nonhuman primates, where tissue-based nanoparticle profiling can require euthanasia and can limit the number of formulations tested in each subject. A blood-based assay also makes it possible to monitor delivery over time, potentially showing how the activity of a formulation changes after dosing. The study used just 30 microliters of serum, a volume small enough to support repeated sampling and longitudinal measurements.

Before comparing nanoparticle performance, the researchers validated the molecular components of the system, including the activity of the snapCode chemistry and the ability of the fusion protein to participate in the intended covalent reaction. These steps were necessary to establish that the barcode signal reflected genuine expression of the delivered mRNA rather than nonspecific interactions. Once the platform had been characterized, the team used it to evaluate multiple chemically distinct LNPs in living animals.

The investigators intravenously administered six snapCoded LNP formulations to mice and nonhuman primates. Each formulation carried its own molecular identity, allowing all six candidates to be assessed in parallel. Serum collected after administration was analyzed for the DNA–fusion protein complexes, and sequencing was used to quantify the relative delivery activity associated with each barcode. By testing the same barcoded set across species, the researchers could directly examine whether patterns observed in mice were reproduced in nonhuman primates.

Such cross-species comparisons are crucial because LNP composition strongly influences biological behavior. Changes in ionizable lipids, helper lipids, cholesterol, polyethylene glycol-lipid components or particle structure can affect stability, organ distribution, cellular uptake and endosomal escape. These properties may differ substantially between rodents and primates because of differences in blood proteins, immune responses, tissue physiology and cellular trafficking. A method that measures expression from several formulations in the same animal may therefore reveal species-specific delivery patterns more efficiently than traditional one-formulation-per-animal experiments.

The snapCode strategy does not replace every form of nanoparticle analysis. It reports successful expression of a particular engineered mRNA and depends on the recovery and sequencing of the associated molecular complexes. It does not, by itself, provide a complete map of tissue distribution, long-term safety or therapeutic efficacy. Nevertheless, it adds a functional layer to LNP evaluation: scientists can ask not only where particles go, but which particles actually release mRNA that cells translate. In early development, that distinction can help prioritize candidates before more resource-intensive studies begin.

By combining multiplexed dosing with low-volume serum sampling, the researchers aim to make nonhuman primate testing more informative while using fewer animals. The platform could be adapted for screening delivery systems designed for different organs or therapeutic proteins, provided that the encoded reporter and barcode chemistry remain compatible with the intended experiment. As mRNA medicines expand beyond vaccines into gene editing, immunotherapy and protein replacement, tools that connect nanoparticle chemistry to real biological output may become increasingly important. Non-invasive barcoding offers a way to track those differences in living subjects and could help narrow the path from promising LNP design to clinically relevant drug candidate.

Subject of Research: A non-invasive method for comparing functional mRNA delivery by multiple lipid nanoparticles in mice and nonhuman primates using serum-based DNA barcodes.

Article Title: Non-invasive nanoparticle barcoding in nonhuman primates

Article References: Jang, B., Zenhausern, R., Lian, L. et al. Non-invasive nanoparticle barcoding in nonhuman primates. Nat Biotechnol (2026). https://doi.org/10.1038/s41587-026-03262-6

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41587-026-03262-6

Keywords: lipid nanoparticles, mRNA delivery, nanoparticle barcoding, snapCodes, SNAP-tag, nanoluciferase, nonhuman primates, serum sequencing, drug delivery, RNA therapeutics

A new study has brought scientists closer to observing how inflammation during pregnancy may alter the earliest stages of human brain development. Using three-dimensional tissue models made from human fetal brain samples, researchers modeled maternal immune activation and identified the signaling molecule interleukin-17A, or IL-17A, as a major driver of abnormal cortical development. The findings, published in Nature Neuroscience, offer a human-based experimental system for investigating how immune signals outside the brain can influence the formation of neural circuits before birth.

Maternal immune activation refers to the biological response triggered when a pregnant individual experiences infection or significant inflammation. Epidemiological studies have associated certain prenatal inflammatory exposures with an increased likelihood of neurodevelopmental conditions, including autism spectrum disorder, schizophrenia, and intellectual disability. Yet the mechanisms behind these associations have remained difficult to study. Animal models have provided important clues, but differences between species can limit their ability to reproduce the timing, cellular organization, and molecular environment of the developing human cortex.

The researchers addressed this challenge with “brain cerebroids,” three-dimensional, ex vivo models that preserve features of developing human fetal brain tissue. Unlike simplified cultures composed of a single cell type, these structures retain a more complex arrangement of neural progenitors, immature neurons, and supporting cells. Their three-dimensional architecture allows cells to communicate and organize in ways that more closely resemble the fetal cortex, including the production and movement of neurons that ultimately establish the layered structure of the brain’s outer region.

To recreate aspects of maternal immune activation, the team exposed the fetal brain cerebroids to inflammatory conditions associated with immune signaling during pregnancy. The central focus was IL-17A, a cytokine produced primarily by activated immune cells, particularly a subset of T cells known as T helper 17 cells. Cytokines are small signaling proteins that coordinate immune responses, but they can also affect tissues beyond the immune system. In the developing brain, inappropriate or excessive exposure to such signals may influence cell proliferation, migration, differentiation, and the formation of connections between neurons.

The study found that IL-17A exposure was linked to disruptions in cortical development within the human cerebroids. These effects are described as “IL-17A-driven,” indicating that the cytokine was not merely associated with the developmental changes but played a functionally important role in producing them. The disturbances affected the organization and behavior of developing neural cells, processes that are essential for building the cortex. During normal development, neural progenitor cells generate new neurons in tightly regulated sequences, while young neurons migrate to their appropriate positions. Interference with either process can alter the structure and connectivity of later-forming brain tissue.

The results are especially significant because they were observed in human fetal brain material rather than inferred only from animal studies. Previous research in mice has implicated maternal immune activation and IL-17A in changes to cortical organization and behavior in offspring. However, the human cerebroid model provides an opportunity to examine whether similar immune mechanisms operate in human tissue, where the timing of neurogenesis, cell-type composition, and cortical architecture differ from those of rodents. The approach may also help reveal human-specific responses that conventional laboratory animals cannot capture.

The findings do not mean that IL-17A exposure during pregnancy inevitably causes a neurodevelopmental condition, nor do they establish that prenatal inflammation is a single explanation for such conditions. Brain development is shaped by a combination of genetic factors, immune signals, environmental influences, and developmental timing. The experiments also took place in an ex vivo model, outside the full physiological environment of a living pregnancy. Cerebroids cannot reproduce the placenta, maternal circulation, hormonal changes, or the complete immune system, all of which influence how inflammatory signals reach the fetus and how long they remain active.

Nevertheless, the model could become a powerful platform for testing mechanisms and potential interventions. Researchers may use it to determine how IL-17A changes gene activity in neural progenitors, whether it alters communication between neurons and glial cells, and which molecular pathways make some developing cells more vulnerable than others. Because the tissue is human and three-dimensional, it may also support studies of patient-specific genetic risk, allowing investigators to compare how different backgrounds respond to the same inflammatory signal.

The work also highlights a broader shift in neuroscience toward experimental systems that combine human tissue with controlled laboratory manipulation. Understanding prenatal inflammation is difficult in clinical studies because immune exposure cannot be ethically assigned or precisely timed in pregnant people. Brain cerebroids offer a way to isolate individual components of that complex biology while preserving more of the developing tissue’s natural organization than conventional two-dimensional cell cultures. As these models improve, they may help distinguish temporary developmental changes from persistent alterations in cortical circuitry and identify when immune signaling is most consequential.

By showing that IL-17A can disrupt human cortical development in a three-dimensional ex vivo system, the study gives researchers a clearer biological target in the search for links between prenatal inflammation and later neurodevelopment. Its most immediate contribution is not a new diagnosis or treatment, but a more precise experimental framework: one that connects maternal immune signaling to cellular events in the developing human cortex. That connection could guide future work on prevention, therapeutic timing, and the complex origins of developmental differences long before the first symptoms become visible.

Subject of Research: Maternal immune activation and IL-17A-driven disruption of human fetal cortical development in 3D ex vivo brain cerebroids.

Article Title: Modeling maternal immune activation in 3D ex vivo human fetal brain cerebroids reveals IL-17A-driven disruption of cortical development.

Article References: Assir, M.Z.K., Yanakiev, M., Gim, D.H. et al. Modeling maternal immune activation in 3D ex vivo human fetal brain cerebroids reveals IL-17A-driven disruption of cortical development. Nature Neuroscience (2026). https://doi.org/10.1038/s41593-026-02400-2

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41593-026-02400-2

Keywords: maternal immune activation, IL-17A, fetal brain development, cortical development, brain cerebroids, neurodevelopment, prenatal inflammation, human brain models, cytokines, neuroscience

A new study is drawing attention to a hidden problem in mental-health research: scientists may be using the same words to describe first episode psychosis (FEP) while measuring entirely different things. In an analysis published in Schizophrenia, researchers Seiber, Sridhar, Hasenstab and colleagues examine how U.S. insurance claims data are used to estimate the incidence of FEP—the number of new cases appearing in a population over a defined period—and argue that greater standardization is urgently needed.

First episode psychosis refers to the point at which a person experiences psychotic symptoms for the first time in their life. These symptoms can include hallucinations, delusions, disorganized thinking or major changes in behavior and functioning. FEP is not a single diagnosis. It can occur in schizophrenia-spectrum disorders, bipolar disorder, severe depression and several medical or substance-related conditions. Because early treatment is linked to better long-term outcomes, knowing how often FEP occurs is essential for planning specialized clinics, staffing early-intervention programs and directing public-health resources.

The researchers focus on U.S. claims data, enormous digital records generated when patients receive medical care and providers submit bills to insurers. These databases can include diagnostic codes, procedure codes, prescription information, dates of service and details about emergency, inpatient and outpatient treatment. Unlike traditional epidemiological surveys, claims datasets can cover millions of people and make it possible to study patterns across large geographic areas. Their scale, however, does not automatically make their estimates precise.

The central challenge is that a billing code is not the same as a clinical assessment. A code for psychosis may indicate a confirmed diagnosis, a suspected condition, a historical problem or a provisional label assigned during an emergency evaluation. Claims data also rarely contain the complete clinical narrative needed to determine whether symptoms truly represent a person’s first psychotic episode. A patient may have received care in another health system, paid out of pocket, changed insurers or carried an earlier diagnosis that is invisible in the database being studied.

Even the definition of “incidence” can vary. Some researchers count a first-ever psychosis-related diagnosis, while others count a first hospitalization, a first emergency-department visit or the first appearance of a relevant code after a period without documented care. These approaches can produce different numbers from the same underlying population. A study requiring a long “clean period”—a span of time with no previous psychosis-related claims—may reduce the likelihood of counting established cases as new, but it can also exclude people whose earlier treatment occurred outside the available records.

Age, sex, insurance type and geography can further influence the apparent rate of FEP. Young adults may be more likely to encounter emergency services, while people in rural areas may face limited access to psychiatrists and specialized programs. Differences in insurance coverage can determine which services generate observable claims. If researchers compare estimates without accounting for these factors, they may mistake variations in detection or access for genuine differences in disease occurrence.

The study’s call for standardization points toward a more consistent technical framework. Researchers need to specify which diagnostic codes qualify as psychosis, whether substance-induced and medically caused episodes are included, how long a person must remain free of prior claims to be considered a new case, and which healthcare settings are examined. They also need to define the population denominator—the number of people considered at risk—and explain how individuals with incomplete enrollment or interrupted insurance coverage are handled.

Validation is another crucial step. Claims-based algorithms should be compared with detailed chart reviews, clinical registries or structured assessments to determine how accurately they identify genuine FEP. Two statistical measures are especially important: sensitivity, or the ability to capture true cases, and positive predictive value, or the proportion of algorithm-identified cases that are confirmed after review. An algorithm with high sensitivity may find more possible cases but also produce more false positives; one with high specificity may miss people who received vague or inconsistent coding.

Standardized methods could make FEP estimates more comparable across states, insurers and research teams. That would help scientists detect real trends rather than methodological noise and could reveal whether early psychosis services are reaching the populations most in need. More reliable estimates could also strengthen efforts to investigate racial, socioeconomic and regional disparities, provided that claims data are interpreted carefully and not treated as a complete substitute for clinical information.

The message from the research is not that U.S. claims databases are unusable. On the contrary, their breadth makes them one of the most powerful tools available for studying mental-health care at scale. But their value depends on transparent definitions, validated case-finding methods and clear reporting standards. As health systems increasingly rely on administrative data and automated analytics, agreeing on what counts as a new case of psychosis may be the difference between a map that reveals a public-health crisis and one that merely reflects the quirks of the billing system.

Subject of Research: Estimating first episode psychosis incidence rates using U.S. claims data

Article Title: Estimating first episode psychosis (FEP) incidence rates using U.S. claims data: a need for standardization

Article References: Seiber, E.E., Sridhar, S., Hasenstab, K.A. et al. “Estimating first episode psychosis (FEP) incidence rates using U.S. claims data: a need for standardization.” Schizophrenia (2026). https://doi.org/10.1038/s41537-026-00793-4

Image Credits: AI Generated

DOI: 10.1038/s41537-026-00793-4

Keywords: First episode psychosis, FEP, incidence rates, U.S. claims data, schizophrenia, mental health, epidemiology, healthcare data, standardization

The price of saving a newborn’s life can extend far beyond the hospital walls. A new analysis published in the Journal of Perinatology is drawing attention to a largely invisible consequence of neonatal intensive care: the direct medical out-of-pocket costs paid by families. The study, led by researchers Gorka, Profit and Phibbs, examines who carries the greatest financial burden during a neonatal intensive care unit admission and investigates how structural conditions may shape those costs.

Neonatal intensive care is among the most technologically advanced forms of medicine. Infants in NICUs may require mechanical ventilation, incubators that regulate temperature and humidity, continuous heart and oxygen monitoring, intravenous nutrition, specialized medications and repeated laboratory testing. These interventions can be lifesaving, particularly for babies born extremely prematurely or with serious medical complications. Yet the financial consequences of receiving this care are not experienced equally by every household, even when families receive treatment in the same health-care system.

The researchers’ focus is direct medical out-of-pocket spending: the money families must pay themselves for medical services connected to a NICU admission. This can include deductibles, copayments, coinsurance and other forms of cost sharing that remain after insurance has paid its portion. Unlike the total hospital charge or the amount reimbursed by an insurer, out-of-pocket cost reflects the portion that reaches a family’s own budget. For households already coping with an unexpected high-risk birth, even relatively small individual charges can accumulate rapidly.

The study is designed not only to document these expenses, but also to explore the structural forces behind differences in cost burden. In health economics, structural contributions refer to the way institutions and systems distribute risk and resources. Insurance design, employment-linked coverage, household income, geographic location, hospital characteristics and access to public assistance can all affect how much a family ultimately pays. Two infants with similar clinical needs may therefore generate very different financial experiences for their parents, depending on the architecture of coverage surrounding them.

That distinction matters because the effects of a NICU admission are not limited to the newborn’s medical condition. Parents may need to travel long distances to reach a specialized hospital, arrange accommodation near the facility, pay for transportation or meals, and take unpaid leave from work. These expenses may not always appear in estimates of direct medical out-of-pocket costs, but they can intensify the economic shock associated with a prolonged admission. The medical bill is only one component of the broader financial strain that can accompany neonatal illness.

A central question raised by the analysis is whether the families with the fewest financial resources are also the ones most exposed to high cost sharing. A payment that is manageable for a high-income household may consume a substantial share of a lower-income family’s monthly budget. Economists often describe this pattern as a disproportionate cost burden: the absolute amount paid may not be the highest, yet the payment represents a greater fraction of household resources. This distinction can reveal inequities that remain hidden when researchers look only at average dollar amounts.

The findings are expected to be relevant to health-policy debates about medical debt, insurance protection and the financial consequences of premature birth. If structural factors account for meaningful differences in family payments, reducing inequality may require more than improving clinical care. Potential responses could include limits on neonatal cost sharing, stronger protections against unexpected bills, expanded eligibility for public coverage and assistance with transportation or family support services. The analysis may also help hospitals and policymakers identify families at risk of financial hardship while an infant is still receiving care.

The issue has significance beyond individual hospitalizations because NICU care can influence a family’s financial stability long after discharge. Parents may face follow-up appointments, medications, developmental assessments and specialist care for children who experienced complications of prematurity or serious illness. Medical expenses can overlap with reduced work hours, job loss or the need for one parent to become a full-time caregiver. A short period of intensive treatment can therefore produce a long economic aftershock, particularly when families lack savings or paid leave.

By placing family payments at the center of neonatal research, Gorka, Profit and Phibbs emphasize a dimension of NICU care that is often absent from clinical success measures. Survival, complications and length of stay remain essential indicators, but they do not fully describe the experience of families navigating intensive care. Understanding who pays the most, why they pay it and how those payments relate to broader social structures could help redefine quality in neonatal medicine. The study’s message is potentially viral because it connects cutting-edge life-saving technology with a simple but consequential question: when medicine saves a baby, how much of the cost is left for the family to survive?

Subject of Research: Direct medical out-of-pocket costs of neonatal intensive care admissions and structural factors contributing to differences in financial burden among NICU families.

Article Title: Who pays the most for neonatal intensive care? An analysis of the out-of-pocket cost burden borne by NICU families

Article References: Gorka, N., Profit, J. & Phibbs, C.S. “Who pays the most for neonatal intensive care? An analysis of the out-of-pocket cost burden borne by NICU families.” Journal of Perinatology (2026). https://doi.org/10.1038/s41372-026-02869-6

Image Credits: AI Generated

DOI: 10.1038/s41372-026-02869-6

Keywords: neonatal intensive care, NICU, out-of-pocket costs, medical expenses, health-care inequality, premature birth, financial burden, insurance, neonatal health, health policy

Expansion microscopy has spent the past decade changing the rules of super-resolution imaging. Instead of relying solely on increasingly sophisticated optics, the technique physically enlarges biological specimens so that molecules separated by nanometers become easier to distinguish with ordinary fluorescence microscopes. Now, researchers have introduced a method designed to push that concept toward one of the most difficult goals in microscopy: seeing the shapes of individual proteins directly.

The approach, described by Ahmed H. Shaib, Mahmoud M. Alawieh and Stefan O. Rizzoli in Nature Protocols, combines one-step nanoscale expansion microscopy with fluctuation-based super-resolution analysis. The resulting workflow, called ONE microscopy, is intended to make molecular-scale imaging more accessible to laboratories that do not have access to cryo-electron microscopes or specialized high-end optical systems.

Traditional light microscopy is limited by diffraction, a physical effect that causes light from two nearby objects to blur together when they are too close. Even modern super-resolution methods can require complex instruments, intense labeling strategies or extensive computational processing. Expansion microscopy takes a different route. Researchers anchor biological molecules within a swellable polymer network and then expand the material, increasing the physical distance between fluorescent labels.

The expansion step does not automatically reveal every molecular detail. A protein’s structure can still be represented by only a small number of fluorescent signals, and conventional images may contain noise, background fluorescence and motion-related fluctuations. ONE microscopy addresses these limitations by analyzing changes in fluorescence intensity over time. These fluctuations contain information about the presence, position and behavior of labeled molecules that may not be obvious in a single frame.

In practical terms, the method links chemical preparation, physical enlargement and computational analysis into a single workflow. Samples are embedded in a polymer gel, labeled to identify the proteins of interest and then expanded. After expansion, researchers acquire image sequences using conventional fluorescence equipment. Specialized software analyzes the temporal variation in the recorded signals, extracting spatial information beyond what a standard diffraction-limited image would provide.

This combination is significant because it shifts the focus from simply locating a protein to examining its overall shape. For many biological questions, knowing that a protein is present is not enough. Its size, orientation and structural organization can determine how it interacts with membranes, vesicles, organelles or neighboring proteins. Directly observing those features could help researchers investigate molecular machines in their native cellular environments rather than relying exclusively on purified samples or averaged structural models.

The protocol is designed to work across a broad range of biological materials, including purified proteins, cultured cells and tissues. That flexibility could make the technique useful for researchers studying protein organization at multiple scales. A purified protein might provide a controlled test of shape reconstruction, while cells and tissues could reveal how the same protein is arranged amid the crowded and complex environment of living biology.

A major part of the reported advance is the accompanying software package. Fluctuation-based imaging can be powerful, but its usefulness depends on reliable data processing, and computational analysis has often been a barrier for non-specialist users. The authors present the software as stable and user-friendly, with the goal of making the analysis more efficient, reproducible and practical for laboratories using standard fluorescence microscopes.

ONE microscopy does not replace cryo-electron microscopy, which remains capable of resolving structures at atomic or near-atomic scales under appropriate conditions. Nor does it eliminate the challenges associated with labeling, gel chemistry, image quality and sample preparation. Expansion can introduce distortions, and successful imaging depends on preserving the relationship between the fluorescent labels and the underlying structures. Nevertheless, the method offers a complementary strategy: rather than averaging thousands or millions of molecules, it aims to examine individual protein shapes through expanded, fluorescence-labeled specimens.

The researchers describe the workflow as a practical framework for protein imaging on conventional equipment. By combining physical separation of fluorophores with information extracted from fluorescence fluctuations, the method brings nanoscale structural analysis closer to routine biological imaging. Its broader impact may come not from replacing existing forms of super-resolution, but from making a previously specialized capability more reproducible and attainable for laboratories investigating how individual proteins operate inside cells and tissues.

Subject of Research: One-step nanoscale expansion microscopy for visualizing individual protein shapes using conventional fluorescence microscopes.

Article Title: ONE microscopy.

Article References: Shaib, A.H., Alawieh, M.M. & Rizzoli, S.O. ONE microscopy. Nature Protocols (2026). https://doi.org/10.1038/s41596-026-01399-x

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41596-026-01399-x

Keywords: expansion microscopy, ExM, nanoscale imaging, super-resolution microscopy, fluctuation-based analysis, protein structure, fluorescence microscopy, single-protein imaging, cryo-electron microscopy, biological imaging

Foundation models are promising to become the “universal translators” of biomedical data—but a new perspective argues that medicine should resist treating them as all-knowing digital doctors. In a review published in Nature Biomedical Engineering, researchers describe how large, adaptable artificial intelligence systems are reshaping biomedical imaging while warning that impressive benchmark scores can conceal serious weaknesses in clinical environments. Their central message is direct: foundation models are most likely to improve healthcare by augmenting specialists, not replacing them.

Foundation models are designed to learn broad representations from enormous and diverse datasets before being adapted to specific tasks. In biomedical imaging, those data may include magnetic resonance imaging, computed tomography, X-rays, ultrasound, digital pathology slides and ophthalmic images. The same underlying model could theoretically identify tumors, segment organs, estimate disease risk, retrieve similar cases and generate clinical reports. The vision becomes even broader when imaging is combined with pathology, electronic health records and genomic information, creating a composite system intended to analyze a patient across multiple biological scales.

That ambition reflects a major change from traditional medical AI. Earlier systems were generally built for one narrowly defined task, such as detecting pneumonia on chest radiographs or outlining a brain lesion on MRI scans. Foundation models instead attempt to create a reusable backbone that can be transferred across diseases, hospitals and imaging technologies. Technically, they learn statistical patterns in high-dimensional data, often through self-supervised training in which the system predicts missing, transformed or associated information. Afterward, developers fine-tune or prompt the model for particular clinical applications.

But biomedical imaging is not a single, uniform world. Images differ according to scanner manufacturer, acquisition protocol, patient population, disease prevalence and local clinical practice. A model trained primarily on data from large academic hospitals may perform very differently in community clinics, rural settings or countries with limited equipment. This problem, known as domain shift, can occur even when images appear visually similar. Small changes in image quality, contrast, hardware or patient demographics may alter the statistical distribution learned by the model and undermine its predictions.

The authors introduce a framework called real-world evaluation and assessment of foundation models, or REAL-FM, to examine whether these systems are ready for practical use. Rather than focusing only on accuracy scores, REAL-FM considers several dimensions at once, including the quality and representativeness of training data, technical readiness, clinical value, integration into existing workflows and responsible artificial intelligence. The framework is intended to help clinicians interpret claims about new models and to push developers toward evaluations that resemble actual medical practice.

One of the sharpest distinctions in the perspective is between pattern recognition and causal reasoning. Foundation models can become extraordinarily skilled at recognizing visual associations—for example, linking a particular texture or anatomical feature with a diagnosis present in their training data. Yet association is not the same as understanding why a disease occurs, how it will progress or whether a treatment will benefit an individual patient. A model may identify a correlation that is valid in one hospital but reflects a hidden confounder, such as a scanner type, reporting convention or patient-selection pattern, rather than a biological signal.

This limitation becomes especially dangerous when models are moved beyond simplified benchmarks. Many benchmark datasets provide carefully curated images, clear labels and narrowly defined tasks. Clinical care is messier: scans can be incomplete, diagnoses can be uncertain, records may contain contradictory information and several conditions may coexist. The perspective highlights a lack of verified generalization across such conditions, along with a shortage of prospective, outcome-based validation. In a prospective study, an AI system would be evaluated while care is actually being delivered, with researchers measuring whether it improves diagnostic accuracy, treatment decisions, patient outcomes or workflow efficiency.

Data scarcity is another obstacle. The largest foundation models require vast quantities of data, but medical information is difficult to collect, standardize and share. Patient records are fragmented across institutions, imaging data may lack reliable annotations and rare diseases are inherently underrepresented. Privacy regulations and governance requirements further complicate the creation of centralized datasets. As a result, a model may appear broadly capable while remaining poorly tested in the populations and clinical circumstances where errors could have the greatest consequences.

The researchers argue that human oversight therefore remains indispensable. In practical terms, foundation models may be most useful as clinical assistants that prioritize images for review, highlight suspicious regions, summarize longitudinal records or offer a second opinion that specialists can interrogate. Safe deployment will require transparent reporting of uncertainty, monitoring for performance drift, mechanisms for correcting errors and clear accountability when recommendations influence care. The future envisioned by the authors is not a single monolithic medical oracle, but a coordinated ecosystem of specialized AI systems, each evaluated for a defined clinical role and connected to expert-led workflows.

The perspective arrives as the biomedical AI field races toward increasingly general-purpose systems. Its warning is not that foundation models lack value, but that technical scale alone cannot establish clinical reliability. Before these models can be trusted with consequential decisions, they must demonstrate robustness across domains, usefulness in real workflows, safety under unexpected conditions and measurable benefits for patients. The proposed REAL-FM framework offers a way to separate viral demonstrations from durable medical progress—by asking not only what a model can recognize, but where it works, why it works and whether it makes care better.

Subject of Research: Foundation models and their real-world evaluation in biomedical imaging and clinical medicine.

Article Title: Foundation models in biomedical imaging: turning hype into reality

Article References: Muneer, A., Zhang, K., Hamdi, I. et al. Foundation models in biomedical imaging: turning hype into reality. Nature Biomedical Engineering 10, 1557–1575 (2026). https://doi.org/10.1038/s41551-026-01762-z

Image Credits: AI Generated

DOI: 10.1038/s41551-026-01762-z

Keywords: foundation models, biomedical imaging, medical artificial intelligence, clinical AI, multimodal AI, domain shift, causal reasoning, clinical validation, responsible AI, REAL-FM