A million-person study points to repeated heat injury in the oesophagus.NASA has selected 12 new investigations to help support human explorers in space. Six will help advance the ability to produce food off-planet, while another six advance the understanding of how unique conditions associated with space exploration can impact the health and physiology of astronauts.
The six food-focused investigations, supported by the agency’s Space Crops grants, advance NASA’s goal of harnessing the power of plants to enhance quality of life for humans in space, as well as to enable lunar and Mars exploration. Four of the space crops proposals focus on studies of edible plants and how their growth, physiology, and associated microbial communities are affected by environmental conditions in space or on other planetary bodies.
Another proposal involves understanding mechanisms by which certain plant species, called resurrection plants, can withstand extreme, dry conditions. The last space crops proposal builds on previous studies on the International Space Station to uncover functions of algal genes, segments of DNA controlling algae survival, whose expression is modified by spaceflight. Such studies can help scientists integrate biological-based solutions into space life-support systems.
The second set of six proposals fall under the agency’s Biological and Physical Sciences Division’s focus on precision health, which seeks to unravel the mechanisms by which space exploration affects health and well-being. One proposal studies how lunar dust exposure impacts respiratory, immune, and inflammation responses. A second proposal identifies repurposed drugs that can mitigate the effects space travel has on health and physiology.
Two more of the research proposals look at how radiation combined with other stressors affects age-relevant characteristics seen in various organ and physiological systems. The final two proposals assess molecular and cellular changes induced by stressors in space that can alter gene expression or protein function. The research will identify ways to mitigate health issues and develop early-warning detection systems to notify crew of potential concerns.
The principal investigators who conduct the space biology studies come from 10 institutions across eight states. Nine of the awards are for investigators who are receiving funding from the Space Biology Program for the first time.
When fully implemented, more than $7 million in grant money will be awarded throughout fiscal years 2026-2030. These awards were made in response to research proposals submitted to ROSES-2024: Program Element E.9: Space Biology Research Studies (NNH24ZDA001N-SBR).
To learn more about NASA’s biological and physical research in space, visit: https://science.nasa.gov/biological-physical/
NASA’s Biological and Physical Sciences Division pioneers scientific discovery and enables exploration by using space environments to conduct investigations not possible on Earth. Studying biological and physical phenomenon under extreme conditions allows researchers to advance the fundamental scientific knowledge required to go farther and stay longer in space, while also benefitting life on Earth.
Scientists in Brazil have demonstrated that a combination of three non-destructive imaging techniques, visible-spectrum (RGB) photography, X-ray radiography, and three-dimensional magnetic resonance imaging (MRI), can detect and characterize hidden damage in soybean seeds that conventional quality tests frequently miss. The study, published in Smart Agricultural Technology, comes at a critical moment: Brazil is the world’s largest soybean producer and exporter, with an estimated harvest of 166 million tons for the 2024/2025 growing season, and seed quality is increasingly under threat from the very climate extremes that help drive the country’s agricultural productivity.
The research, led by Rafael Mateus Alves and colleagues at institutions including the Seed Technology Center of Embrapa Soybean and the University of São Paulo, was funded by the São Paulo Research Foundation (FAPESP). Its central premise is deceptively simple: because seed quality is largely determined in the field, before harvest even begins, researchers and seed companies need tools that can look inside a seed without killing it. Destructive assays such as the tetrazolium viability test, which stains metabolically active tissue red, are the industry standard, but they end the life of the sample. That is a particular problem for breeding programs, where each seed represents a unique genetic combination that must survive analysis if it is to be planted.
The seed itself is a small miracle of engineering. A protective coat, derived from the ovule integuments and marked by a scar called the hilum, regulates water uptake and shields the embryo within. The embryo contains the plumule, which gives rise to the plant’s first true leaves; the apical meristem, precursor of the aerial plant; and the hypocotyl–radicle axis, which breaks through the soil and forms the primary root. Flanking this axis are the cotyledons, storage organs packed with macromolecules that are metabolized and shipped to the growing axis during germination. Damage to any of these structures, from insects, fungi, drought, heat, or rough handling during harvest, can silently reduce a seed lot’s vigor, the capacity for rapid, uniform germination that underpins successful crop establishment.
To interrogate this architecture non-invasively, the team assembled ten representative seeds from production fields, commercial lots, and storage samples, each embodying a distinct damage category: stink bug injury, purple seed stain caused by fungi, green seeds from incomplete maturation, wrinkled seeds from heat and drought stress, weathering-related coat ruptures, severe structural failure, mechanical harvest damage, and internal galleries bored by the cigarette beetle (Lasioderma serricorne) during storage. Every seed was imaged sequentially with each of the three modalities and then subjected to the tetrazolium test as a qualitative reference standard.
The technical pipeline was meticulously standardized. For visible-light imaging, seeds were mounted on acetate sheets and photographed with a Leica DMLB microscope equipped with a DFC 310FX digital camera, oriented in four standardized positions with the hilum consistently to the right. X-ray radiographs were acquired on a Faxitron MX-20 DC-12 system operating at 34 kilovolts, with a nine-second exposure and an object-to-source distance of 11.4 centimeters; uniform contrast settings were applied to all images to make damaged tissues directly comparable. The MRI work used a horizontal 2 Tesla superconducting magnet coupled to a Bruker Avance III spectrometer operating at 85.24 megahertz for proton nuclei. Before scanning, seeds were conditioned to raise their moisture content from roughly 8–10 percent (wet basis) by incubation on moistened germination paper for three hours at 25 °C, a step that ensured sufficient hydrogen signal for imaging. A three-dimensional FLASH pulse sequence, with a 3-millisecond echo time and 75-millisecond repetition time, collected data on a 128×128×128 matrix over a 12.8-millimeter field of view, yielding isotropic voxels of 100 micrometers per side. Datasets were zero-padded to 256³ before Fourier transformation and rendered in three dimensions using ImageJ with the 3Dscript plugin.
The resulting image galleries are striking. On seeds punctured by stink bugs, the dominant pest of Brazilian soybean fields, RGB images revealed darkened patches on the cotyledons and near the plumule, the visible legacy of insect feeding that lacerates tissue and injects yeasts that degrade it from within. X-ray images flagged zones of reduced radiation absorption in the same darkened regions, while MRI cross-sections exposed the depth of tissue destruction with unusual clarity, precisely because degraded tissue no longer absorbs water and therefore produces no magnetic resonance signal. The tetrazolium test confirmed that these zones lacked respiratory activity, meaning they were metabolically dead.
Not every symptom tells the same story, however, and the multimodal approach proved especially powerful at distinguishing superficial from structural damage. Seeds with purple seed stain, caused by Cercospora fungi that secrete the toxin cercosporin, showed internal structures that appeared entirely normal in both X-ray and MRI. Yet the tetrazolium test produced an unusually intense red coloration at the stained coat, indicating that fungal activity had compromised the seed coat’s ability to regulate water uptake, allowing the staining solution to penetrate more deeply into the embryo. Similarly, green seeds, which retain chlorophyll because heat and drought interrupted maturation, showed no structural anomalies under X-ray or MRI, but their membranes proved unusually permeable to the tetrazolium solution, hinting at the physiological deterioration typical of immature tissue.
Where MRI truly distinguished itself was in detecting damage invisible to every other method. One seed that appeared flawless in visible light and radiographically normal in X-ray images revealed, in its three-dimensional MRI reconstruction, internal ruptures running through the central cotyledons, the likely consequence of rapid, uneven drying that forces differential cellular expansion and eventual tissue collapse. In mechanically damaged seeds, the X-ray images showed a crack in the hypocotyl–radicle axis that the camera could not see, but MRI went further, revealing the full extent of the fissure and the displacement of the axis relative to the cotyledons. The team also documented a dramatic structural failure nicknamed the “popcorn effect,” in which alternating wetting and rapid drying cycles tear the seed coat and force the cotyledons apart, a phenomenon increasingly reported in Brazilian seed lots as late-season weather grows more erratic.
To move beyond qualitative observation, the researchers extracted grayscale histograms from each X-ray image, normalizing pixel frequencies across the full 0–255 intensity range. Two statistical descriptors, mean gray level and Shannon entropy, were then compared across damage categories using one-way ANOVA followed by Tukey’s honest significance test. The analysis yielded clear separation: undamaged seeds showed the narrowest distributions with peaks at high grayscale values, while beetle-infested seeds and wrinkled seeds displayed the broadest distributions with heavy weight in the lower gray ranges, reflecting hollowed-out tissues and sparse, deformed structures. Mean gray level differed significantly across categories, peaking in undamaged seeds and bottoming out in wrinkled ones, while Shannon entropy, a measure of histogram complexity, was highest in beetle-damaged seeds and lowest in healthy ones. Because each damage category produced a characteristic radiographic fingerprint, the authors suggest these histogram metrics could support automated, quantitative screening in commercial seed laboratories.
Each modality, the authors stress, occupies a distinct niche. RGB imaging is fast, cheap, and ideal for surface screening but blind to anything beneath the coat. X-ray radiography, already a mainstay of seed testing labs, reveals internal voids, malformations, and cavities rapidly and non-destructively, though it cannot report on metabolic viability and demands careful standardization. MRI, with its superb soft-tissue contrast and genuine three-dimensional resolution, excels at detecting subtle physiological and structural alterations, latent mechanical injury, hydration-induced ruptures, and moisture redistribution, but its cost and acquisition time currently confine it to research settings. The tetrazolium test remains valuable as a reference but is destructive and subject to interpreter bias.
The authors argue the techniques should be viewed as complementary rather than competing, and they sketch a future in which RGB and X-ray screening handle high-throughput commercial quality control while MRI resolves ambiguous or high-stakes cases, such as breeding lines and seed physiology studies. Advances in imaging hardware, automation, and artificial intelligence-based analysis, they note, could eventually fuse these modalities into scalable phenotyping workflows. For now, the message is clear: in an era when a single season of heat, drought, and hungry insects can undermine an entire seed lot, the ability to see damage in all three dimensions, without sacrificing the seed itself, may prove as transformative for agriculture as it has been for medicine.
Article Title: When damage goes deep: a multi-technique approach including 3D for soybean seed damage assessment
Article References: Alves, R. M., Teixeira, J. M., Marassi, A. G., Henning, F. A., Umburanas, R. C., Gomes-Junior, F. G., & Tannús, A. (2026). When damage goes deep: a multi-technique approach including 3D for soybean seed damage assessment. Smart Agricultural Technology, 15, Article 102523. https://doi.org/10.1016/j.atech.2026.102523
Image Credits: AI Generated
DOI: 10.1016/j.atech.2026.102523
Keywords: soybean seeds, seed quality, MRI, X-ray imaging, RGB imaging, seed vigor, multimodal imaging, stink bug damage, tetrazolium test, non-destructive testing, seed coat rupture, cigarette beetle
The ocean has quietly absorbed billions of tons of humanity’s carbon emissions over the past two centuries, but scientists and companies racing to supercharge that natural service have long been hampered by a stubborn and costly engineering problem. Now researchers at Stony Brook University, working with the Research Foundation for the State University of New York, have unveiled a method for electrochemical ocean alkalinity enhancement that they say can dramatically lower the cost of ocean-based carbon dioxide removal by eliminating one of the most expensive steps in the entire process: the pretreatment of seawater before it enters an electrochemical reactor. The innovation, now available for licensing through SUNY TechConnect, promises high-quality carbon offsets at a substantially reduced cost while simultaneously helping to counteract the acidification that threatens marine ecosystems worldwide.
At the heart of the challenge is a delicate chemical balancing act. As atmospheric carbon dioxide dissolves into seawater, it forms carbonic acid, which lowers the ocean’s pH and erodes the carbonate chemistry that corals, shellfish and other calcifying organisms depend upon. Ocean carbon dioxide capture exploits a simple principle: if the ocean becomes more alkaline, it can absorb more CO2 from the air and lock it away safely as bicarbonate, one of the most stable and abundant forms of inorganic carbon on Earth. This process, known as ocean alkalinity enhancement, effectively turns the surface ocean into a vast, distributed carbon sink. But adding alkalinity to seawater is not trivial, and doing it in a way that is energy-efficient, scalable and safe has become one of the central engineering puzzles of the emerging carbon removal industry.
One of the most promising approaches relies on electrochemistry, specifically a technique called bipolar membrane electrodialysis. In this system, ion-selective membranes are stacked between two end electrodes, and the arrangement allows operators to split ordinary saltwater into its constituent acid and base. When brine containing sodium chloride flows through the stack, the process generates hydrochloric acid on one side and sodium hydroxide, a strong base, on the other. The elegance of the scheme lies in its product handling: if the hydrochloric acid is kept on land, where it can be stored, neutralized or put to industrial use, and only the sodium hydroxide along with the treated seawater is returned to the ocean, the receiving waters gain a net infusion of alkalinity. That added alkalinity shifts the carbonate equilibrium, allowing the ocean to draw down carbon dioxide from the atmosphere and convert it into dissolved bicarbonate that remains stable for millennia.
This electrochemical pathway has attracted serious commercial interest precisely because it produces what carbon markets call negative emissions, meaning carbon dioxide is durably removed from the atmosphere rather than merely avoided. Companies pursuing net-zero targets increasingly rely on such carbon removal credits to offset their residual emissions, and ocean alkalinity enhancement is widely regarded as one of the largest-capacity avenues available, given the sheer scale of the world’s oceans. Yet the technology has been held back by a deceptively mundane problem: what flows into the reactor matters just as much as what flows out.
Seawater, and many other brine streams that might feed these systems, contains divalent cations, most notably calcium and magnesium ions, alongside the sodium and chloride that the process is designed to split. When these divalent ions encounter the high-pH conditions created at the base-producing side of a bipolar membrane stack, they precipitate as solid calcium and magnesium compounds that coat the membranes in a crust known as scale. The consequences are cascading. Scaled membranes lose their ion-selective efficiency, forcing the system to push harder and consume more electricity to achieve the same output. Over time, the deposits shorten membrane lifetime, increasing maintenance frequency and replacement costs. The conventional answer has been water softening pretreatment, in which the incoming seawater is stripped of calcium and magnesium before it ever reaches the electrodialysis unit. While effective, such pretreatment adds significant capital and operating expense, undermining the economic case for the entire carbon removal operation and eroding the value proposition of the resulting carbon credits.
The Stony Brook researchers behind the new method have essentially designed around this bottleneck. Their technology enables electrochemical enhancement of ocean alkalinity without any pretreatment of the incoming seawater at all. By rethinking how the electrochemical system handles brine streams laden with divalent cations, the researchers have created a process that tolerates raw seawater directly, sidestepping the water softening infrastructure that previous designs demanded. According to the announcement from the Research Foundation for SUNY, the result is a system that produces negative emission carbon offsets of very high quality at a substantially reduced cost, simply because the most expensive upstream step has been engineered out of existence. The advantages claimed for the approach are straightforward and commercially significant: it is cheaper, more energy efficient, and requires no expensive water softening pretreatment.
The implications ripple across both the carbon markets and the broader climate technology landscape. Carbon offset buyers, including corporations striving to meet net-zero commitments, place a premium on removal credits that are durable, verifiable and cost-competitive. Ocean alkalinity enhancement already offers exceptional permanence, since bicarbonate dissolved in seawater represents one of the most long-lived forms of carbon storage known. By cutting costs at the front end, the Stony Brook method could help push the price of these high-quality ocean-based offsets toward levels that make them viable at gigatonne scale, a threshold that analysts consider essential if carbon removal is to play a meaningful role in stabilizing the global climate. Cheaper alkalinity generation also strengthens the second major application of the technology: mitigating ocean acidification directly, without necessarily framing it as a carbon market product at all.
Ocean acidification itself is a mounting crisis. Since the industrial revolution, the average surface ocean pH has dropped measurably as the sea has absorbed roughly a quarter to a third of anthropogenic CO2 emissions. The consequences have been documented across coral reefs, oyster hatcheries, pteropods and other calcifying organisms whose shells and skeletons become harder to build in increasingly acidic waters. A technology that adds alkalinity to coastal waters and open ocean regions simultaneously addresses this chemical stress and harvests the carbon removal benefit, a dual function that distinguishes ocean alkalinity enhancement from many other carbon removal approaches. In regions where fisheries, aquaculture and reef ecosystems are economically vital, localized deployment of alkalinity-enhancing electrochemical systems could offer both environmental resilience and revenue through carbon credit sales.
The scientific pedigree of the work reflects the growing maturity of the carbon removal field. Stony Brook University, a flagship research institution within the SUNY system, has become an active hub for climate and energy innovation, and the new method is protected under intellectual property identified in the licensing announcement. The Research Foundation for the State University of New York, the nation’s largest research foundation supporting the nation’s largest public university system, is actively seeking development partners, commercial partners and licensees to translate the laboratory advance into deployed systems. The foundation describes a broad portfolio of SUNY-led research spanning artificial intelligence for the public good, quantum technologies, next-generation semiconductors, biotechnology and medicine, and energy and climate solutions, with system-wide research expenditures approaching 1.5 billion dollars in fiscal year 2025.
For the carbon removal industry, the timing of the announcement is notable. As voluntary and compliance carbon markets mature, buyers are demanding higher fidelity in the offsets they purchase, favoring durable removal over avoidance-based credits. Electrochemical ocean alkalinity enhancement, with its well-understood chemistry and measurable inputs and outputs, is well positioned to meet rigorous monitoring, reporting and verification standards. The obstacle has always been cost, and the pretreatment bottleneck has been a substantial contributor. If the Stony Brook design performs as described at industrial scale, it could remove one of the largest cost wedges standing between laboratory demonstration and commercial deployment, accelerating a technology class that many climate analysts view as indispensable to achieving deep decarbonization.
The broader lesson of the advance may be as important as the technology itself. In the race to scale carbon removal, progress often comes not from exotic new chemistry but from eliminating the hidden costs and fragilities that make promising concepts uneconomic in practice. Water softening pretreatment is exactly the kind of unglamorous engineering detail that determines whether a climate technology remains a paper exercise or becomes infrastructure. By designing a bipolar membrane electrodialysis system that thrives on untreated seawater, the Stony Brook researchers have addressed one of those decisive details. The ocean, meanwhile, stands ready. Every unit of alkalinity added is an invitation for the sea to take up more carbon dioxide and, in doing so, to heal a little of the acidification that a warming world has inflicted upon it. What remains now is the work of scaling, partnering and commercializing, and the SUNY licensing announcement signals that the researchers and their institution intend to see this chemistry leave the laboratory and reach the sea.
Article Title: Method for electrochemical ocean alkalinity enhancement
Article References: Method for electrochemical ocean alkalinity enhancement. Research Foundation for the State University of New York, via EurekAlert! News by Subject: Tech & Engineering. Available at: SUNY TechConnect (https://suny.technologypublisher.com/) Original publication
Image Credits: AI Generated
DOI: Not provided
Keywords: ocean alkalinity enhancement, carbon dioxide removal, bipolar membrane electrodialysis, ocean acidification mitigation, carbon offsets, Stony Brook University, negative emissions, seawater pretreatment, net-zero goals, electrochemistry, Research Foundation for SUNY
A OpenAI anunciou recentemente uma série de novidades para o ChatGPT, incluindo uma atualização muito bem-vinda para usuários do ChatGPT Voice.
Agora, o assistente pode usar os modelos GPT-5.6 ou GPT-6 Astra quando precisa pesquisar ou raciocinar sobre questões mais difíceis — e o usuário pode escolher qual usar com um seletor.
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Além disso, a empresa também simplificou os limites de uso diários do GPT-Live:
Com essas mudanças, os planos Plus e Pro não mudam mais para o GPT-Live-1 mini depois de atingir o limite de uso do Voice. Além disso, os níveis separados de inteligência do Voice (Instant, Medium e High) foram descontinuados.
A OpenAI anunciou também que a Deep Research está agora disponível no ChatGPT Work e no Codex para os planos Plus, Pro, Business, Enterprise e Edu. Basta ao usuário digitar @Deep Research ou pedir explicitamente para usá-la no comando.
Outra novidade chegando aos dois recursos é o plugin Data, que ajuda a analisar dados de negócios conectados. É possível fazer uma pergunta sobre um negócio, investigar mudanças ou até mesmo criar um dashboard interativo sobre o conteúdo analisado.
Now everyone can put data to work.
— ChatGPT (@ChatGPT) September 10, 2026
We’re introducing a new Data agent in ChatGPT Work so you can turn your company’s data into answers, interactive dashboards, and action—just by asking.
Just add the Data Plugin in ChatGPT Work, connect to the data sources and context you… pic.twitter.com/R7N3I2NFCN
Agora também é possível compartilhar arquivos e pastas no ChatGPT pela Biblioteca. É possível compartilhar com pessoas específicas ou com integrantes do workspace, com opções de gerenciamento de acesso e uma visualização dos conteúdos compartilhados.
Por fim, a Biblioteca também suporta agora o Box, o Dropbox e o SharePoint, que se juntam ao Google Drive para permitir que o usuário pesquise com facilidade por arquivos e pastas disponíveis nessas plataformas e os usem como contexto em conversas.
Thirty years after a small group of European professors of geriatric medicine first warned that the continent’s fastest-growing population was being cared for by physicians who had never been formally trained to care for them, the program they created to fix the problem is marking its anniversary with a scientific milestone of its own. A new special article published in European Geriatric Medicine documents the research output of the most recent graduating cohort of the European Academy for Medicine of Ageing, or EAMA, and in doing so offers a rare longitudinal measure of how a structured, pan-European leadership program in geriatric medicine translates into scholarly productivity, professional advancement and, ultimately, better care for older people.
The new paper, titled “‘Highlights of latest EAMA’: generation research outputs of the 30-year anniversary cohort,” was authored by Thomas Münzer of the Geriatric Clinic St. Gallen in Switzerland, Hannes B. Stähelin of Basel, and Barbara van Munster of the University of Groningen Medical School in the Netherlands, writing on behalf of the EAMA Board. It arrives at a moment when the demographic arithmetic of Europe has made the question of geriatric capacity more urgent than ever: the proportion of people over 65 continues to climb, multimorbidity, frailty and polypharmacy have become the daily reality of hospital medicine, and health systems across the continent still struggle to recruit and retain physicians trained specifically in the medicine of ageing. The article’s premise is simple but rarely examined with this degree of rigor — if you invest systematically in the education of mid-career geriatricians, what do you get back?
To understand the significance of the anniversary cohort’s research output, one has to go back to the early 1990s, when the group of European Professors in Medical Gerontology published a stark assessment in the journal Age and Ageing. Writing in 1994, Stähelin and colleagues documented that medical gerontology was taught unevenly, and in many countries not at all, in European medical schools. Geriatric medicine, despite being one of the few specialties whose patient population was guaranteed to expand every single year, was frequently a subordinate unit within internal medicine, staffed by physicians who had acquired their expertise on the job rather than through dedicated training. The professors’ conclusion was that Europe needed not merely more geriatricians but a new cadre of academic leaders — clinicians who could teach, publish, shape curricula and advocate for the specialty within their national health systems.
That diagnosis led, in 1995, to the founding of the European Academy for Medicine of Ageing, an intensive postgraduate program deliberately modeled on leadership academies rather than conventional continuing medical education. EAMA’s structure has remained remarkably stable across its three decades: a small, competitively selected cohort of physicians, typically already experienced clinicians, is brought together for a series of residential courses spread over roughly two years, interspersed with mentored projects that require participants to produce original scholarly work. The curriculum spans the full breadth of the medicine of ageing — from the biology of ageing and the physiology of frailty, through geriatric syndromes such as falls, delirium, incontinence and sarcopenia, to the organizational science of acute geriatric units, nursing home medicine, rehabilitation and end-of-life care. Crucially, faculty are drawn from across Europe, exposing participants to radically different national models of geriatric care and building a professional network that persists long after the formal courses end.
The “reloaded” reform of the program, described in a 2018 paper by Roller-Wirnsberger and colleagues in European Geriatric Medicine, formalized what three decades of experience had taught the academy’s faculty. That paper set out explicit competencies and standards for a European leadership program in geriatric medicine, defining what a graduate of EAMA should be able to do: not just diagnose and treat, but design services, lead multidisciplinary teams, mentor juniors, conduct and critique research, and represent the specialty at institutional and governmental levels. The competency framework aligned the academy with modern medical-education theory, in which learning objectives are specified in advance and assessed rather than assumed. It is against this framework that the anniversary cohort’s performance, as documented in the new article, can be read as an evaluation of the program itself.
The central finding of the new special article is that the latest cohort of EAMA graduates has generated a substantial body of research output — the “generation research outputs” of the title — spanning peer-reviewed publications, presentations and ongoing projects in geriatric medicine. Each participant in the program is expected to develop a scholarly project under faculty mentorship, moving from a research question through protocol design, data collection and analysis to presentation and, ideally, publication. For the 30-year anniversary cohort, the academy compiled and highlighted these outputs, creating what the authors describe as the “Highlights of latest EAMA” — a curated snapshot of what a single generation of emerging European geriatric leaders produced during and immediately after their training.
Why does this matter beyond the individual careers involved? The technical answer lies in how research capacity compounds. A single published paper changes one evidence base marginally; a cohort of trained researchers who continue publishing changes the trajectory of an entire specialty. Geriatric medicine has historically been under-represented in high-impact clinical research relative to the burden of disease it manages. Conditions such as delirium, frailty and multimorbidity were for decades excluded from major trials or treated as confounders rather than outcomes, precisely because the specialty lacked enough investigator-trained clinicians to insist on their inclusion. Programs like EAMA attack that bottleneck at its root: every graduate who learns to design a study, secure a mentor and navigate the publication pipeline becomes a node through which clinical questions from the bedside can flow into the literature and back.
The pedagogical machinery behind that outcome is worth examining, because it explains why the anniversary cohort’s productivity is treated by the authors as more than a curiosity. EAMA’s residential courses are built around case-based, small-group learning in which participants bring real clinical and organizational problems from their home institutions and work them through with international faculty. The mentored projects between courses impose deadlines and accountability — the two ingredients that, as anyone who has supervised doctoral students knows, most reliably convert good intentions into submitted manuscripts. The academy also functions as a peer-review incubator: draft papers are critiqued by senior European geriatricians before submission, giving participants exposure to the standards of international journals at a stage of their careers when feedback is most formative.
The anniversary article also carries a personal and institutional poignancy. Hannes B. Stähelin, one of the co-authors, is identified in the publication as deceased; he was among the founding professors whose 1994 analysis launched the academy, and his presence on the author line of a paper published in 2026 spans the full thirty-year arc of the program. The continuity from the GEPMG position paper through the 2002 retrospective review of the academy’s first years, published in Gerontology, through the 2018 competency framework, and now to this documentation of cohort research output, constitutes something rare in medical education: a thirty-year, multi-generation audit trail of a single intervention in specialty training, documented by the people who built it.
For health systems, the implications are concrete. Europe’s national models of geriatric care differ enormously — from the fully established departments of the United Kingdom and the Netherlands to countries where geriatrics is still fighting for recognition as an independent specialty. EAMA’s cohorts deliberately mix these national traditions, so that a geriatrician from a country without an acute geriatric unit model trains alongside colleagues who run such units daily. The research outputs of the anniversary cohort, the authors suggest, function as a form of technology transfer: projects conceived in one system are published in international journals and become adaptable blueprints for colleagues elsewhere. In an era when the European Union explicitly tracks health-workforce capacity, an academy that reliably produces clinicians who can lead services and generate evidence is a strategic asset, not a professional courtesy.
The article is also, implicitly, an argument about how educational interventions should be evaluated. Medical education research is notoriously dominated by satisfaction surveys and self-reported confidence measures, which correlate weakly with actual performance change. Research output — publications generated, projects completed, academic positions attained — is a harder, more objective endpoint, and the EAMA Board’s decision to compile and publish the anniversary cohort’s outputs signals a commitment to accountability by measurable results. It is a methodology other postgraduate leadership programs in medicine, from palliative care to rural health, could plausibly adopt: define the competencies, train against them, and then report what the trainees actually produced.
The publication timeline of the article itself — received in December 2025, revised in April 2026, accepted in June and published on 6 July 2026 in European Geriatric Medicine, the journal of the European Geriatric Medicine Society — places it squarely in the anniversary year it commemorates. As Europe’s population ages at a pace with no historical precedent, the question the founding professors asked in 1994 — who will teach the teachers, and who will lead the specialty? — has an answer that can now be pointed to in print: thirty years of EAMA cohorts, and a newest generation whose scholarly work is documented, highlighted and, the academy clearly hopes, replicated by the cohorts to come.
Article Title: “Highlights of latest EAMA”: generation research outputs of the 30-year anniversary cohort
Article References: Münzer, T., Stähelin, H. B., van Munster, B., & the European Academy for Medicine of Ageing (EAMA) Board (2026). “Highlights of latest EAMA”: generation research outputs of the 30-year anniversary cohort. European Geriatric Medicine. https://doi.org/10.1007/s41999-026-01536-5
Image Credits: AI Generated
DOI: 10.1007/s41999-026-01536-5
Keywords: European Academy for Medicine of Ageing, EAMA, geriatric medicine, medical education, research output, leadership program, ageing, Europe, geriatric care, anniversary cohort, lifelong learning
In a finding that could reshape the search for new treatments against one of the deadliest gynecologic malignancies, researchers in Shanghai have identified the approved lung cancer drug tepotinib as a potent inhibitor of ovarian cancer growth, acting through an unexpected molecular target known as LY75. The study, published in the Journal of Ovarian Research, combines large-scale computational screening, structural biology, and preclinical testing to make a case for repurposing an existing medicine against a disease that urgently needs new options.
Ovarian cancer remains one of the most lethal cancers affecting women, largely because it is often diagnosed at an advanced stage and because resistance to platinum-based chemotherapy and PARP inhibitors eventually develops in most patients. High-grade serous ovarian cancer, the most common and aggressive subtype, has proven particularly stubborn, and survival rates have improved only marginally over recent decades. Against this backdrop, the idea of finding new uses for drugs that have already passed safety testing in humans, a strategy known as drug repurposing, has gained considerable traction. The new study demonstrates how modern computational tools can accelerate that process dramatically.
The research team, led by Yang Xiao, Wei Xia, and Yanan Song of Pudong Gongli Hospital and the Shanghai University of Medicine and Health Sciences, began by focusing on LY75, also known as CD205 or DEC205, a C-type lectin receptor best known for its role in antigen uptake by dendritic cells. Mining data from The Cancer Genome Atlas and the Human Protein Atlas, the investigators found that LY75 was significantly upregulated in ovarian cancer tissues compared with healthy tissue. More importantly, elevated LY75 expression correlated with shorter progression-free survival, marking the protein as both a potential biomarker of aggressive disease and an attractive therapeutic target.
With the target in hand, the team turned to structure-based virtual screening. Rather than testing thousands of compounds in the laboratory, they used the published crystal structure of the LY75 protein, deposited in the Protein Data Bank under the identifier 8K8H, as a template to computationally dock molecules from the TargetMol compound library. Docking predicts how well a small molecule fits into a binding pocket on a protein, but the researchers went considerably further. They applied MM/GBSA calculations, a method that estimates binding free energy by combining molecular mechanics forces with implicit solvent models, to rescore candidate poses. They also employed protein-ligand interaction fingerprints, or PLIF analysis, to compare the binding patterns of candidates against known interaction motifs, and ran ADMET predictions to filter out compounds likely to fail on absorption, metabolism, or toxicity grounds before any experiment was performed.
From this computational funnel, tepotinib emerged as the leading candidate. Tepotinib is an orally available small molecule approved in several countries for the treatment of non-small cell lung cancer harboring MET exon 14 skipping mutations, where it acts as a MET kinase inhibitor. Its appearance as a strong LY75 binder raised an obvious question: was any anti-cancer effect simply a consequence of MET inhibition? The team anticipated this concern and designed their study around it, measuring c-MET expression in their cell models, examining MET–LY75 co-expression patterns, and running parallel pharmacological controls with capmatinib, another selective MET inhibitor, to disentangle the two mechanisms.
The laboratory experiments delivered striking results. Tepotinib preferentially inhibited ovarian cancer cell lines with high LY75 expression, achieving half-maximal inhibitory concentrations, or IC₅₀ values, of 16.31 micromolar in SKOV3 cells and 18.91 micromolar in OVCAR-8 cells. In contrast, the drug showed markedly weaker activity against HO8910 cells, which express low levels of LY75, a dose-response pattern consistent with LY75 serving as the drug’s relevant target rather than an incidental one. To confirm a direct physical interaction, the researchers turned to surface plasmon resonance, a label-free optical technique that measures real-time binding between molecules immobilized on a sensor surface. The experiments confirmed that tepotinib binds LY75 directly, with a kinetic dissociation constant of 2.52 micromolar and a steady-state K_D of 3.74 micromolar, values indicating a specific and measurable interaction.
Perhaps the most intriguing mechanistic finding concerns what tepotinib does to the LY75 protein once bound. Treatment with the drug induced apoptosis in the sensitive cell lines, suppressed their migratory capacity, a process closely tied to metastatic spread, and downregulated LY75 protein levels. When the team probed how this downregulation occurred, they found that tepotinib accelerated LY75 degradation through a pathway that does not depend on the ubiquitin-proteasome system, the cell’s standard machinery for tagging unwanted proteins for destruction. Cycloheximide chase experiments, which block new protein synthesis and allow the decay rate of existing proteins to be measured, supported this conclusion. The identity of the alternative degradation route remains an open question, but the observation suggests tepotinib may engage lysosomal or autophagic pathways, a hypothesis that will require further work to confirm.
The in vivo evidence proved even more compelling. In mouse xenograft models implanted with SKOV3 ovarian cancer cells, oral administration of tepotinib markedly suppressed tumor growth, achieving a tumor inhibition rate of 79.6 percent. Analysis of the excised tumors showed reduced LY75 expression in the treated animals, consistent with the drug engaging its target in living tissue. All animal procedures were approved by the Institutional Animal Care and Use Committee of Shanghai Health Medical College and conducted in accordance with the ARRIVE guidelines for reporting animal research.
Crucially, the MET controls strengthened rather than weakened the case for LY75 as the operative target. Capmatinib, a structurally distinct MET inhibitor, failed to reproduce the full anti-tumor activity of tepotinib in the ovarian cancer models, and analyses of c-MET expression and MET–LY75 co-expression in patient datasets suggested that MET inhibition alone could not account for the magnitude of benefit observed. The authors therefore conclude that tepotinib’s effect in ovarian cancer reflects a genuine dual pharmacology, with LY75 binding and subsequent LY75 protein downregulation contributing substantially to its activity.
The implications of the study extend in several directions. First, it elevates LY75 from an immunological curiosity to a candidate therapeutic target in ovarian cancer, a protein whose abundance in tumors and association with poor prognosis make it a marker worth tracking clinically. LY75 has already attracted attention in oncology as a target for antibody-drug conjugates, given its presence on the surface of certain tumor cells and its efficient internalization, and the new findings add a small-molecule dimension to that conversation. Second, the work offers a template for computational drug repurposing: crystal-structure-guided docking, energy-based rescoring, interaction fingerprinting, and ADMET filtering followed by rigorous biochemical and in vivo validation. The approach identifies candidates in silico in a fraction of the time and cost of conventional screening campaigns.
Third, and most immediately, the results argue for clinical exploration of tepotinib in ovarian cancer, particularly in patients whose tumors express high levels of LY75. Because the drug is already approved and its safety profile in humans is documented, the path from laboratory finding to clinical trial is potentially shorter than for a de novo compound. The micromolar potencies observed in cell culture are modest by the standards of modern targeted therapy, and patients would likely require careful dosing studies, biomarker-based selection, and possibly drug combinations to translate the xenograft results into human benefit. Questions also remain about whether the ubiquitin-proteasome-independent degradation mechanism operates identically in human tumors and about the precise structural features of the tepotinib–LY75 interaction that could be optimized in next-generation analogs.
The study is not without limitations, as its authors acknowledge. The work relies on cell lines and xenografts rather than patient-derived models, and the correlation between LY75 expression and drug sensitivity, while suggestive, has been established across only a handful of cell lines. Prospective validation in patient-derived xenografts and organoids, ideally stratified by LY75 expression, would sharpen the biomarker hypothesis considerably. Nonetheless, the convergence of computational prediction, biochemical confirmation, mechanistic insight, and animal efficacy data makes this one of the more complete preclinical repurposing cases published for ovarian cancer in recent memory.
For a disease in which the therapeutic arsenal has expanded slowly and resistance is nearly universal, the prospect that a drug already sitting on pharmacy shelves could be redirected against a newly validated molecular target is the kind of story that resonates far beyond the laboratory. If follow-up studies and early-phase trials bear out these findings, tepotinib’s second act may prove more consequential than its first, and LY75 may take its place among the actionable targets of precision oncology.
Article Title: Discovery of tepotinib as a novel LY75-targeting small-molecule inhibitor with anti-tumor activity in ovarian cancer via virtual screening
Article References: Xiao, Y., Han, Y., Kong, W., Cheng, J., Xia, W., & Song, Y. (2026). Discovery of tepotinib as a novel LY75-targeting small-molecule inhibitor with anti-tumor activity in ovarian cancer via virtual screening. Journal of Ovarian Research. https://doi.org/10.1186/s13048-026-02230-7
Image Credits: AI Generated
DOI: 10.1186/s13048-026-02230-7
Keywords: Ovarian cancer, LY75, Tepotinib, Virtual screening, Drug repurposing, Molecular targeted therapy, Surface plasmon resonance, Tumor biomarkers
Every spring, Europe’s forests are showered with far more than rain. Wind-pollinated trees release staggering quantities of pollen into the atmosphere, and much of it eventually settles on leaves, branches and the forest floor. New research now shows that this pollen is not merely biological debris — it is a measurable, taxon-specific driver of nutrient fluxes in the water that drips through forest canopies, a flow scientists call throughfall. The findings, published in Environmental Monitoring and Assessment, provide the first continental-scale evidence directly linking pollen deposition to forest water chemistry, and they suggest that decades of forest monitoring may have been quietly misattributing a slice of nutrient input to other sources.
The study was carried out by a large international team led by Elena Gottardini of the Fondazione Edmund Mach in Italy, working within the ICP Forests programme, a pan-European network that monitors air pollution effects on forests. The researchers analysed throughfall samples collected in 2018 from 60 intensive monitoring plots — known as Level II plots — across eight countries: Belgium, Finland, France, Germany, Italy, Norway, Switzerland and the United Kingdom. The plots ranged in altitude from 14 to 1,900 metres above sea level and were dominated by six tree genera: Abies, Fagus, Larix, Picea, Pinus and Quercus. In total, 196 throughfall samples were collected between February and July, covering the early vegetative season when most European trees flower.
The innovation of the study lies in its methodology. Rather than inferring pollen inputs from nearby aerobiological samplers, the team examined the very same water samples that were being chemically analysed. A known quantity of water from each sample was filtered through a 5-micrometre cellulose nitrate mesh, and a calibrated number of 10-micrometre polystyrene-divinylbenzene microspheres — roughly 155,000 per sample — were added as a counting standard. The filters were then dissolved in acetone, centrifuged, and the resulting pellet embedded in fuchsin jelly on microscope slides. Trained analysts identified and counted pollen grains under 400-times magnification, stopping when about 1 percent of the added microspheres had been counted. From these counts, the team calculated pollen deposition rates in grains per square metre per day, correcting for filtered volume, throughfall quantity and sampling duration.
The results were striking. Fifty-three pollen taxa were identified across the samples, with woody species accounting for 98 percent of all grains. Four genera — Pinus, Picea, Fagus and Quercus — together made up 91.4 percent of the total. Pine pollen alone represented more than half of everything collected, a dominance the researchers attribute to the buoyant air sacs on pine grains, which allow them to travel enormous distances from both local and distant sources. In beech, spruce and pine stands, the pollen of the dominant genus itself prevailed, making up 49.7, 59.1 and 84.3 percent of the local pollen spectrum respectively. In oak stands, oak pollen ranked second at 26.9 percent, behind pine. Data from fir and larch stands were excluded because sampling there did not align with those genera’s flowering periods.
By combining the measured pollen curves with published flowering phenology, the team defined main pollen seasons for each genus. Beech and oak flowering spanned April and May, with beech peaking in the last week of April and oak showing a double peak at weeks 19 and 23, likely reflecting multiple oak species flowering at slightly different times across the wide latitudinal and altitudinal spread of plots. Spruce pollen peaked around weeks 19 to 20, while pine peaked at week 19 with a secondary pulse at week 22. Overall, 57 percent of the throughfall samples fell within their stand’s flowering period for at least half of their collection window, providing a robust temporal overlap between pollen deposition and water chemistry measurements.
The chemical analysis, conducted at the Research Institute for Nature and Forest laboratory in Belgium, quantified major ions including potassium, calcium, magnesium, sodium, chloride, phosphate, sulphate, nitrate, nitrite and ammonium using ion chromatography, alongside total dissolved nitrogen and non-purgeable organic carbon measured on a TOC/TN analyser. Linear mixed-effects models then tested whether pollen deposition rates could predict the flux of these compounds, with plot identity included as a random effect and autocorrelation between repeated samples explicitly modelled.
The answer was a clear yes. Every statistically significant association between pollen and throughfall chemistry was positive, meaning more pollen corresponded to more nutrients reaching the forest floor. Potassium emerged as the star player: its flux was significantly explained by pollen from all four main genera, with pollen accounting for an average of 33 percent of the variance. This makes biochemical sense, because potassium is one of the predominant ions in pollen grains, and pollen washed from flowers and crowns by rain or deposited dry is a direct source of the ion during the flowering season — an idea first proposed decades ago but never confirmed at this scale. The strongest single relationships involved oak pollen, which explained 77.8 percent of the variance in ammonium fluxes and 55 percent in total dissolved nitrogen.
Broadleaved and coniferous pollen left different chemical fingerprints. Beech and oak pollen together significantly explained fluxes of non-purgeable organic carbon, dissolved organic nitrogen, total dissolved nitrogen, ammonium and magnesium, while the combined pollen of pine and spruce was linked with every measured compound except phosphate. Intriguingly, broadleaved pollen showed a weak negative association with nitrate fluxes. The authors urge caution in interpreting this pattern, since several non-exclusive mechanisms could be at play. Laboratory experiments have shown that pollen and its associated microbiota can transform extracellular nitrate into nitrite and nitrous oxide, an effect pronounced in beech and oak but weak or absent in pine and spruce. Canopy uptake of nitrogen and coincidentally lower atmospheric deposition during broadleaf flowering are also possible explanations that this single-year study cannot disentangle.
The dissolved organic carbon carried in throughfall also differed by forest type. Specific ultraviolet absorbance at 254 nanometres, a proxy for aromatic and recalcitrant carbon, was highest in spruce stands, whose needles release lignin derivatives and tannins. The humification index was significantly higher in oak throughfall, reflecting more decomposed, humic organic matter. Most revealing was the fluorescence index, which distinguishes microbial from plant-derived organic matter: beech and oak samples had significantly higher values, with medians near 1.9, than pine and spruce samples, which sat near 1.7. Values above 1.9 typically indicate microbially processed carbon, and the elevated readings under broadleaves suggest microbes play a larger role in transforming pollen-derived carbon in those forests — hinting that pollen inputs feed not just trees but entire soil microbial food webs.
For the authors, the implications reach well beyond academic curiosity. Routine throughfall monitoring has historically ignored pollen as a variable, meaning that chemical enrichment previously attributed solely to canopy leaching or atmospheric deposition may in fact be partly pollenic. As climate change pushes flowering earlier and increases airborne pollen amounts across arboreal taxa, these hidden inputs could grow. Masting behaviour in beech and oak — the episodic, synchronized production of enormous seed and pollen crops — introduces strong year-to-year variability that any nutrient budget must now reckon with.
The researchers acknowledge the limitations of a one-year, correlative dataset and call for multi-year studies incorporating canopy architecture, stand age, phenology and insect infestations, as well as stable isotope tracing or controlled exclusion experiments to nail down mechanisms. Still, the message is clear: pollen is not just about reproduction, or even allergies. It is a seasonal fertiliser delivered from the sky, and forests have been banking on it all along. Incorporating pollen surveys into long-term forest observation networks, the team argues, will be essential for accurate nutrient budgets in a changing climate.
Article Title: Deposited pollen from dominant tree genera drives nutrient composition of throughfall in European forests
Article References: Gottardini, E., Cristofolini, F., Cristofori, A., Vanguelova, E., Thimonier, A., Clarke, N., Wachtveitl, L., Ukonmaanaho, L., Lindroos, A.-J., Nicolas, M., Limić, I., Boeckx, P., Bodé, S., Bauters, M., & Verstraeten, A. (2026). Deposited pollen from dominant tree genera drives nutrient composition of throughfall in European forests. Environmental Monitoring and Assessment, 198(10), Article 1053. https://doi.org/10.1007/s10661-026-15883-0
Image Credits: AI Generated
DOI: 10.1007/s10661-026-15883-0
Keywords: Tree pollen deposition, Throughfall chemistry, Atmospheric deposition, Forest nutrient cycle, Potassium fluxes, Dissolved organic carbon, ICP Forests, Flowering phenology, Nitrogen cycling, European forests
GPS collars reveal hyenas retreating while male lions repeatedly close the distance.In a development that could reshape how scientists study the mechanics of human movement, a team of biomedical engineers and computer scientists has unveiled an open-source software tool capable of tracking the tiny, intricate bones of the wrist as they glide and rotate during motion. The new tool, called Hierarchical 3D Registration, or 3DH, is a module within the SlicerAutoscoperM extension of the widely used 3DSlicer computing environment. Described in a study published in BioMedical Engineering OnLine, the software was validated against previously established methods using both sequential three-dimensional computed tomography, or 3DCT, scans of living participants performing thumb tasks and dynamic four-dimensional CT, or 4DCT, images of cadaveric wrists moving through flexion and extension. The results demonstrate that the open-source approach can match the accuracy of independent, previously published methodologies while offering researchers everywhere a free and reproducible path to quantifying skeletal kinematics.
The wrist has long been one of the most challenging joints for biomechanists to study. It contains eight small carpal bones, including the scaphoid and lunate, along with the radius of the forearm and the metacarpal bones of the hand, all articulating in a tightly packed arrangement that allows the remarkable range of motion humans rely on every day. Understanding how these bones move relative to one another, a field of study known as arthrokinematics, is essential for unraveling the causes of wrist instability, osteoarthritis, ligament injuries and the long-term outcomes of surgical repairs. Yet measuring those movements in living, moving joints has historically required either invasive techniques, labor-intensive manual analysis or proprietary software that few laboratories can access or verify.
Quantitative tracking of skeletal structures in vivo, with both efficiency and high temporal resolution, matters to a wide range of questions in biomechanical research, and the authors of the new study argue that the field has been held back by a shortage of accessible, semi-automated registration tools. Image registration, the computational process of aligning one three-dimensional image volume to another, lies at the heart of motion tracking from CT data. When a bone moves between two scans, its position and orientation change, and a registration algorithm must find the transformation that best overlays the bone’s image from one time point onto the next. Done well, this yields precise measurements of rotation and translation. Done poorly or inconsistently, it introduces errors that can swamp the small movements of carpal bones, which may shift by only a few millimeters and a few degrees during normal function.
The new 3DH module addresses this problem with a hierarchical strategy for registering bones across sequences of image volumes. The researchers presented and evaluated the software using two distinct classes of data drawn from previous studies. The first consisted of sequential 3DCT datasets of human participants performing various thumb tasks, in which the radius, the first metacarpal and the trapezium were the target bones. The second consisted of dynamic 4DCT datasets capturing simulated flexion-extension motion in cadaveric wrists, providing time-resolved, three-dimensional image volumes of the scaphoid and lunate in motion. By testing the tool on both static sequential scans and true dynamic imaging, the team was able to demonstrate that 3DH is not limited to a single imaging paradigm but can serve as a unified tracking solution across modalities.
To determine whether the new open-source tool could be trusted, the investigators compared the arthrokinematics computed with 3DH against values that had been previously calculated using independent approaches for the same 3DCT and 4DCT datasets. The statistical framework for this comparison was the Bland-Altman analysis, a standard method for assessing agreement between two measurement techniques. Rather than simply correlating the two sets of results, Bland-Altman analysis quantifies the mean bias, the systematic difference between methods, and the 95 percent limits of agreement, the range within which most individual differences between the methods are expected to fall. This approach is particularly well suited to method-comparison studies because it reveals whether a new technique introduces systematic error and how widely individual measurements might deviate from those of the established gold standard.
The performance figures reported in the study are striking. For the 3DCT data, in which the radius, first metacarpal and trapezium were tracked, the mean bias for the helical angle, a single-axis description of three-dimensional rotation, was just minus 0.06 degrees, with 95 percent limits of agreement ranging between minus 1.87 degrees and 1.74 degrees. Translation measurements fared nearly as well: the mean bias was 0.12 millimeters, with limits of agreement spanning from minus 2.23 millimeters to 2.00 millimeters. In practical terms, the open-source tool reproduced the rotational and translational measurements of the earlier methods to within roughly two degrees and two millimeters at the extremes, differences small enough to preserve the biological signal in most wrist kinematics experiments.
The dynamic 4DCT results told a similar story for the carpal bones. Tracking the scaphoid and lunate through simulated flexion-extension, 3DH produced mean biases of the Euler angle rotations, which decompose three-dimensional rotation into three orthogonal components, of less than 0.77 degrees about any direction. The widest 95 percent limits of agreement ranged between minus 7.11 degrees and 8.65 degrees. For translations, mean biases were less than 0.5 millimeters in any direction, with the widest limits of agreement ranging between minus 2.36 millimeters and 1.43 millimeters. The wider limits of agreement for rotations in the dynamic data likely reflect the added challenges of time-resolved imaging, including motion blur and the smaller, more complexly shaped carpal bones, but the near-zero mean biases indicate that the tool does not systematically drift away from established values.
Crucially, all target bones were successfully tracked in both the 3DCT and 4DCT datasets, meaning the hierarchical registration algorithm converged on correct solutions in every case tested. This robustness matters because registration algorithms can occasionally fail, locking onto incorrect alignments or diverging entirely, and such failures typically demand time-consuming manual intervention. A semi-automated tool that reliably succeeds across diverse bones, motion tasks and imaging protocols removes a significant bottleneck. Manual bone tracking in CT volume sequences can take hours per bone per trial, and the labor multiplies rapidly in studies involving multiple participants, multiple bones and dozens of motion cycles. By automating this process within a validated framework, 3DH promises to accelerate the pace at which wrist biomechanics data can be collected and analyzed.
The choice to build the module inside 3DSlicer, and specifically within the SlicerAutoscoperM extension, is a deliberate strategic decision with implications well beyond the wrist. 3DSlicer is a free, open-source platform for medical image computing and visualization with a large international user base spanning research, clinical and educational communities. By embedding 3DH in this ecosystem, the developers have made the tool immediately available to any laboratory already working with 3DSlicer, complete with the platform’s established infrastructure for loading DICOM data, segmenting anatomical structures and visualizing results. The authors note that the ability to track bones from both 3DCT and 4DCT data sources, with agreement to prior methodologies, demonstrates that the 3DH approach is a capable tool that could promote collaboration and consistency of results through open-source software.
Consistency is a quietly urgent issue in biomechanics. When different laboratories use different proprietary tools with undisclosed algorithms, it becomes difficult to distinguish true biological differences between study populations from mere methodological discrepancies. Open-source registration changes that calculus: the code can be inspected, verified, extended and reused, and results from different institutions become directly comparable because they are produced by identical algorithms. This transparency also lowers the barrier to entry for research groups in settings that cannot afford commercial licenses, potentially broadening the global community capable of conducting rigorous skeletal kinematics research.
The study itself emerged from a collaboration spanning several institutions. The team included Joseph J. Crisco, Amy M. Morton and John D. Holtgrewe of the Department of Orthopedics at The Warren Alpert Medical School of Brown University and Rhode Island Hospital; Cesar Lopez, Andrew Thoreson and Kristin D. Zhao of the Assistive and Restorative Technology Laboratory and the Department of Physical Medicine and Rehabilitation at the Mayo Clinic in Rochester, Minnesota; and Jean-Christophe Fillion-Robin and Beatriz Paniagua of Kitware Inc. in Clifton Park, New York. The involvement of Kitware, a company known for its leadership in open-source scientific computing, underscores the blend of academic rigor and software engineering expertise required to produce a research tool robust enough for widespread distribution. Funding was provided by the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under award numbers AR059185, AR078924 and AR071338.
The implications of this work extend naturally to the future of musculoskeletal imaging. As newer CT technologies, including photon-counting detector systems, deliver ever-finer spatial resolution and as dynamic 4DCT becomes more widely available, the volume of image data available for kinematic analysis will grow dramatically. Tools like 3DH, which are fast, semi-automated and validated across modalities, will be essential for converting that imaging bounty into quantitative biomechanical knowledge. For patients with wrist disorders, the downstream promise is equally tangible: better measurements of how carpal bones actually move in living joints can inform more accurate diagnoses, improved surgical planning, more realistic computational models of joint loading and ultimately better-designed treatments for conditions ranging from scapholunate instability to thumb-base arthritis. With the tool now openly available in the 3DSlicer environment, researchers around the world can begin putting it to work.
Article Title: Kinematic tracking of the small bones of the wrist in sequential 3DCT and dynamic 4DCT volume images using open-source Hierarchical 3D Registration, a module within SlicerAutoscoperM
Article References: Crisco, J. J., Morton, A. M., Lopez, C., Thoreson, A., Zhao, K. D., Holtgrewe, J. D., Fillion-Robin, J.-C., & Paniagua, B. (2026). Kinematic tracking of the small bones of the wrist in sequential 3DCT and dynamic 4DCT volume images using open-source Hierarchical 3D Registration, a module within SlicerAutoscoperM. BioMedical Engineering OnLine. https://doi.org/10.1186/s12938-026-01601-x
Image Credits: AI Generated
DOI: 10.1186/s12938-026-01601-x
Keywords: Computed tomography, 3DCT, 4DCT, Bone tracking, 3DH, 3DSlicer, Image registration, Wrist kinematics, Arthrokinematics, Open-source software, SlicerAutoscoperM, Bland-Altman analysis
Long-term exposure to common air pollutants may significantly raise the risk of developing substance use disorders, while living surrounded by greenery appears to offer a measure of protection, according to a large new population-based study drawing on nearly a quarter of a million participants from the UK Biobank.
The research, published in BMC Psychiatry, analyzed data from 247,138 UK Biobank participants who were free of substance use disorders at baseline, tracking them over a median follow-up period of 10.9 years. During that time, 4,982 participants went on to develop a substance use disorder, providing the researchers with a robust dataset to examine the relationship between environmental exposures and mental health outcomes.
The study, led by Huan Liu and Bolun Cheng of Xi’an Jiaotong University in China, along with colleagues including Feng Zhang, represents one of the most comprehensive investigations to date into how the air people breathe and the greenness of their neighborhoods may influence vulnerability to addiction. The findings arrive at a moment when urban planners and public health officials are increasingly recognizing that the built and natural environments shape health in ways that extend well beyond respiratory and cardiovascular disease.
To assess air pollution exposure, the team employed Land Use Regression modeling to estimate concentrations of five pollutants at each participant’s residential address: fine particulate matter known as PM2.5, coarse particulate matter classified as PM2.5−10, the larger particulate fraction PM10, nitrogen dioxide (NO2), and nitrogen oxides (NOX). These pollutants, produced primarily by traffic, industry, and combustion sources, have long been associated with a range of physical health problems, but their role in psychiatric and behavioral conditions has remained far less certain.
For residential greenness, the researchers turned to the 2005–2007 Land Cover Map, measuring three distinct aspects of the environment within a 300-meter buffer around each home: the proportion of green space, the presence of a domestic garden, and the extent of natural environment. This tripartite approach allowed the investigators to distinguish between different types of vegetation and their potentially different effects on health.
Using Cox proportional hazards models, the team calculated hazard ratios with 95 percent confidence intervals to quantify the association between each exposure and the risk of developing a substance use disorder. The results were striking in their consistency. All five air pollutants were positively associated with incident SUD in fully adjusted models that controlled for a wide range of potential confounders.
Fine particulate matter, or PM2.5, showed the strongest effect, with a hazard ratio of 1.111 (95 percent CI: 1.081–1.142), followed by PM10 with a hazard ratio of 1.070 (95 percent CI: 1.054–1.086). These figures indicate that higher exposure to particulate pollution was associated with a measurable increase in the likelihood of developing a substance use disorder over the follow-up period, even after accounting for demographic, socioeconomic, and behavioral factors.
On the protective side of the ledger, two of the three greenness measures emerged as significant. Green space was inversely associated with SUD risk, showing a hazard ratio of 0.997 (95 percent CI: 0.996–0.998), and the natural environment measure produced an identical finding, with a hazard ratio of 0.997 (95 percent CI: 0.995–0.998). While these effect sizes appear modest on a per-unit basis, they represent population-level signals across a very large cohort, suggesting that even incremental increases in neighborhood greenness may contribute to reduced vulnerability.
Perhaps the most intriguing finding of the study concerns the interaction between pollution and greenery. The researchers tested whether residential greenness modified the association between air pollutants and SUD risk by introducing cross-product terms into their models and evaluating them with likelihood-ratio tests. The results pointed to a buffering role for domestic gardens specifically. Among participants in the high-exposure subgroup, the presence of a domestic garden attenuated the positive associations between pollutants and SUD, with cross-product terms of 0.979 (95 percent CI: 0.963–0.996) for PM2.5 and 0.987 (95 percent CI: 0.980–0.995) for PM10.
In practical terms, this suggests that having access to a private garden may partially offset some of the harm associated with living in areas of elevated particulate pollution, offering a form of environmental resilience that public health advocates have long hypothesized but rarely demonstrated with prospective cohort data.
The associations were not uniform across the population. The positive relationships between air pollution and substance use disorder risk were most pronounced among males, participants aged 65 and older, and individuals with a history of smoking. These findings highlight the importance of considering demographic and behavioral modifiers when assessing the health consequences of environmental exposures, and they suggest that certain subgroups may benefit disproportionately from interventions aimed at reducing pollution or increasing green cover.
To ensure the robustness of their findings, the team conducted a series of sensitivity analyses. These included restricting the sample to long-term residents to minimize exposure misclassification from relocation, using alternative outcome definitions based on ICD-10 codes F10-F19 and F11-F19 to capture different ranges of substance-related diagnoses, and recomputing greenness measures at a wider 1000-meter buffer around each residence. The core conclusions held across these variations, strengthening confidence in the results.
The study was performed in accordance with the ethical principles of the Declaration of Helsinki and was registered with the UK Biobank under application number 46478. Ethical approval for the UK Biobank was granted by the North West Multi-centre Research Ethics Committee under approval reference 11/NW/0382. All participants provided written informed consent before any study-related procedures were initiated.
The work was supported by the China Postdoctoral Science Foundation, the Natural Science Basic Research Plan in Shaanxi Province of China, and the Fundamental Research Funds for the Central Universities. Corresponding authors are Bolun Cheng and Feng Zhang, both affiliated with Xi’an Jiaotong University, with Zhang also holding a position in the Department of Psychiatry at the First Affiliated Hospital of Xi’an Jiaotong University.
The findings come amid growing scientific interest in the neurological and psychiatric consequences of air pollution. Particulate matter, particularly PM2.5, is small enough to cross the blood-brain barrier and has been implicated in neuroinflammation, oxidative stress, and alterations in brain structure and function. These biological mechanisms could plausibly influence reward processing, impulse control, and stress reactivity, all of which are central to the development and perpetuation of substance use disorders.
Conversely, greenness has been associated with stress reduction, improved mental well-being, greater opportunities for physical activity and social interaction, and lower levels of psychological distress, each of which may buffer against the onset of addictive behaviors. The current study adds a significant piece of evidence to this emerging picture by demonstrating the relationship prospectively in one of the world’s largest and most deeply phenotyped biobanks.
The authors conclude that long-term exposure to ambient air pollutants was associated with a higher risk of incident substance use disorders and that residential greenness showed protective associations, with the most pronounced patterns observed among older males and individuals with a smoking history. They argue that the findings support integrating greenness exposure into environmental frameworks for the prevention of substance use disorders, a recommendation that carries implications for urban design, housing policy, and environmental regulation.
As cities around the world continue to grapple with the twin challenges of air quality and mental health, studies of this scale provide an evidence base for interventions that address both simultaneously. The prospect that something as tangible as a garden could offer measurable protection against the psychiatric consequences of polluted air adds a compelling dimension to ongoing debates about how the environments we build shape the minds that inhabit them.
The article is published open access under a Creative Commons Attribution 4.0 International License, permitting broad sharing and adaptation with appropriate credit to the original authors and source. It was received on 08 December 2025, accepted on 28 August 2026, and published on 09 September 2026.
Article Title: Various ambient air pollutants, residential greenness, and risk of substance use disorders: a population-based cohort study
Article References: Liu, H., Cheng, B., Wei, W., Qin, L., & Zhang, F. (2026). Various ambient air pollutants, residential greenness, and risk of substance use disorders: a population-based cohort study. BMC Psychiatry. https://doi.org/10.1186/s12888-026-08588-8
Image Credits: AI Generated
DOI: 10.1186/s12888-026-08588-8
Keywords: air pollution, residential greenness, substance use disorders, PM2.5, PM10, nitrogen dioxide, UK Biobank, prospective cohort, environmental health, domestic garden, mental health
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