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arXiv:2609.18282v1 Announce Type: new Abstract: Large language models are increasingly used to generate and evaluate online content, yet it remains unclear whether the qualities they associate with higher engagement match what real users respond to. We study this question using 1.17 million answers to 25,978 questions from Zhihu, Quora, and Reddit, comparing real platform answers and AI-generated answers across four within-question engagement levels. We introduce Ontological Preference Measurement, which represents answers along three dimensions: logic, affect, and expression. We find a systematic gap between AI preference and real user engagement: as target engagement increases, LLMs add more explicit logical structure, while real user engagement is more strongly associated with affective and expressive salience. We call this tendency logic overbinding. Based on this diagnosis, we propose Ontology-Masked Reasoning Autoencoding (OMRA), a controlled intervention that masks and

arXiv:2609.18134v1 Announce Type: new Abstract: Methodological progress in artificial intelligence (AI) for electronic health records (EHRs) depends on our ability to determine which algorithms work better, and under which conditions. However, such progress is thought to be hindered by difficulties in reproducibility and in defining clinically meaningful evaluation tasks. We empirically study these barriers by re-implementing 12 historical and recent algorithms within a shared evaluation framework and evaluating them on two clinical datasets, MIMIC-IV and NWICU. We compare two complementary task families: expert-authored clinically meaningful tasks and generated tasks defined from randomly sampled event codes and prediction horizons. We ask whether relative algorithms comparisons transfer across task families and datasets, whether residual task heterogeneity contains useful methodological structure, and what a controlled comparison reveals about progress over the last decade. We find

arXiv:2609.17710v1 Announce Type: new Abstract: Community health workers (CHWs) in the Global South increasingly encounter AI-powered tools, yet the counseling work central to their role remains largely unsupported. We study communication practices among Accredited Social Health Activists (ASHAs) in rural Rajasthan, India, through simulated family-planning calls, semi-structured interviews, and an LLM chatbot roleplay design-probe with 20 participants. In calls, ASHAs often responded to social or material concerns by shifting to health-risk information, denying concerns, promising unspecified help, or listing medical solutions with limited explanation. A smaller set of responses instead engaged concerns, sought permission before involving family members, or left decisions with beneficiaries. We interpret these patterns through Motivational Interviewing, emphasizing restraint from correcting, persuading, or over-solving. Drawing across observed calls, interviews, and probe reactions,

In Switzerland, around 2,400 children are born as twins every year. When the fetuses share a placenta, they are connected to one another via blood vessels.

Incorporating a free smartphone app featuring AI-driven health coaching, blood pressure monitoring, and behavioral incentives into a hospital's existing clinical workflows helps patients make meaningful reductions in blood pressure, findings that suggest that digital apps may offer an effective means of extending care beyond the clinic when incorporated into treatment plans.

iOS 27.2 Beta Previews New Apple Intelligence Health App  MacRumorsThe Apple Watch 'Always-Listening' Features Should Worry Every Lawyer, Expert Says  Law.comApple Watch Ultra 4 vs. Apple Watch Ultra 3: Apple's premium smartwatch  AppleInsiderHere's Why a New Apple Watch Charging Puck Was Just Released  MacRumorsHow to turn off the new 'always listening' feature on Apple Watches  USA Today

iOS 27.2 Beta Previews New Apple Intelligence Health App  MacRumorsThe Apple Watch 'Always-Listening' Features Should Worry Every Lawyer, Expert Says  Law.comApple Watch Ultra 4 vs. Apple Watch Ultra 3: Apple's premium smartwatch  AppleInsiderHere's Why a New Apple Watch Charging Puck Was Just Released  MacRumorsHow to turn off the new 'always listening' feature on Apple Watches  USA Today

More than 100,000 people in the country are over 100 years old

Artificial intelligence is rapidly becoming part of how people seek, interpret and act on health information. Yet the technology is advancing faster than the evidence needed to determine whether these systems actually help people understand what matters, make informed health decisions and know what to do next.

Human brain cells transplanted into mice in ‘most extensive’ integration ever  NatureDevelopmental xenocortication using human-derived organoids in mice  NatureStanford Grows Human Brain Tissue Inside Mice in Science Breakthrough  YahooPart-human part-mouse brain developed in science breakthrough  BBCScientists Fuse Human Neurons Into the Brains of Mice  The New York Times

Human brain cells transplanted into mice in ‘most extensive’ integration ever  NatureDevelopmental xenocortication using human-derived organoids in mice  NatureStanford Grows Human Brain Tissue Inside Mice in Science Breakthrough  YahooPart-human part-mouse brain developed in science breakthrough  BBCScientists Fuse Human Neurons Into the Brains of Mice  The New York Times

A new genome-editing method, prime assembly, precisely inserts long DNA sequences into targeted genomic locations, potentially enabling mutation-agnostic gene therapies for diverse genetic diseases with fewer individualized edits. The post Prime Assembly Expands Genome Editing with Precise, Large-Scale DNA Integration appeared first on GEN - Genetic Engineering and Biotechnology News.

Somewhere in the world, a woman over 50 will have fractured a bone by the time you finish reading this sentence due to osteoporosis, a silent bone disease that can weaken the structural integrity of the skeletal system and a person's quality of life. The disease weakens bones and makes them more likely to break because of reduced bone mineral density and bone mass, and it affects an estimated 75 million people across Europe, the USA, and Japan.

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The latest news and headlines from Yahoo! News. Get breaking news stories and in-depth coverage with videos and photos.

Today, the American Association for Cancer Research (AACR) released the 16th edition of its annual Cancer Progress Report.

The number of people aged 100 or older in Japan surpassed a record 100,000 this year, the latest government figures show, underscoring the country’s rapidly aging and declining population. The Health and Welfare Ministry statistics show Japan now has 107,677 centenarians, up 7,914 from the previous year and exceeding the 100,000 mark for the first […] The post Centenarians living in Japan exceed 100,000 for the first time appeared first on Egyptian Gazette.

Less than a second. That’s how long it takes for an emerging AI tool to detect signs of endometriosis through one simple scan. It’s a much faster process than the current seven-year wait for surgery and less invasive.

Artificial intelligence (AI) scribes can reduce the time physicians spend documenting patient visits by 69.1% during simulated primary care appointments, according to research led by University of Toronto Ph.D. student LaShawn Murray.

Records released by EFF show vendors in Medicare's AI-assisted WISeR prior authorization pilot often missed a 72-hour goal, with one request unanswered for 83 days.

The number of people aged 100 or older in Japan surpassed a record 100,000 this year, the latest government figures show, underscoring the country’s rapidly aging and declining population. The Health and Welfare Ministry statistics show Japan now has 107,677 centenarians, up 7,914 from the previous year and exceeding the 100,000 mark for the first […] The post Centenarians living in Japan exceed 100,000 for the first time appeared first on Egyptian Gazette.

The FDA granted de novo authorization to Queen of Hearts, an AI EKG model for heart attack triage. What the evidence shows and what patients should know.

arXiv:2609.17338v1 Announce Type: new Abstract: Software clones are fragments of code that are similar or functionally equivalent to each other. They pose significant challenges for maintenance, refactoring, and bug detection. Detecting Type-IV clones, which are semantically equivalent but may differ syntactically, is particularly difficult for traditional token- or syntax-based methods. Recent machine learning approaches rely on contrastive learning, which requires careful negative sampling and can introduce bias. In this paper, we propose LWVIC4Code, a non-contrastive representation learning approach specifically designed for Type-IV clone detection. Building on the Variance-Invariance-Covariance Regularization (VICReg) framework and prior layer-wise VICReg training, LWVIC4Code introduces cross-layer consistency regularization and depth-dependent layer weighting to progressively refine semantic information across transformer layers, producing robust and discriminative code

arXiv:2609.17223v1 Announce Type: new Abstract: Medical AI models hold immense potential to improve patient outcomes, but they are also known to unintentionally memorise individual records from their training datasets. While such memorisation has been linked to targeted privacy attacks, its consequences for clinical deployment, where patients may be assessed by a model that saw their historical data during training, remain poorly understood. Here we show that predictions on a patient's unseen future data can change significantly if a model observed that same patient's anonymised historical data during training, a phenomenon we term "memorisation bias". We demonstrate that this bias exists across diverse data modalities and model architectures, and over prolonged time spans: in some cases, memorisation bias persists on future records acquired decades after the historical records used for training. Moreover, in simulated prospective deployment, memorisation bias has asymmetric effects

Public comments have closed on Medicare's proposed Software as a Medical Service category. Some algorithm-based lab analyses could incur patient copays.

ByteDance closed a $290M funding round for Anew Labs, its newly spun-off AI drug discovery unit, at a $1.5B valuation, Reuters reports, citing two sources familiar with the matter. Moreover, the company that owns TikTok will retain 56% of the business after this round, according to the same sources.  According to the same reporting, HSG, […] This story continues at The Next Web

Tokyo, Japan —  Japan has been gripped by a declining population for decades, but one age group is adding new members and there are more of them than ever. For the first time in Japan, the number of people aged 100 or older has surpassed more than 100,000 – a new record in the country known … The post For the first time, Japan has more than 100,000 centenarians appeared first on Egypt Independent.

Streptococcus pneumoniae is a bacterial pathogen that causes life-threatening infections, including pneumonia and meningitis. These infections are commonly treated with antibiotics, but antibiotics are becoming less effective against S. pneumoniae over time because of changes in the pathogen that cause drug resistance. This phenomenon, called antimicrobial resistance, is resulting in significant health care costs and deaths around the world. In a new study published by Wiley in Advanced Science, researchers used artificial intelligence (AI) to identify approved drugs that may be effective against S. pneumoniae.

Kane Wu / Reuters: Sources: Shanghai-based Anew Labs, a ByteDance spinoff using AI for drug discovery, raised $290M from HSG, IDG Capital, and others at a $1.5B valuation  —  Chinese social media and internet company ByteDance has completed a $290 million fundraising for its AI drugmaking unit after spinning …

Consumers have placed their personal physicians above all health care touchpoints in their lives when it comes to trust stewards of and for health care information and data protection. More consumers have adopted the use of AI in every day life across many life flows, including their health care. The latest riff from the annual Edelman Trust Barometer 2026 highlights a look into health and trust in concert with the Yale School of Public Health. And they found that among AI users, one-half think AI can address their health concerns at least as well as doctors can.             To gain global health citizens’ perspectives on trust, health, and AI, the Edelman team polled 12,998 adults in 13 countries between late February and mid-March 2026. Countries covered included Australia, Brazil, Canada, France, Germany, India, Indonesia, Japan, Mexico, S. Africa, S. Korea, the UK and the United States. The first chart reveals that 1-in-2 AI users’ views on

A new 3D-structure of a cancer-linked protein bound to its cellular partner reveals details of how the protein binds to chromosomes and could offer insights for future disease treatments.

AI agents could reliably support diagnoses and clinical decision-making in the future—provided sensitive health data are protected and clinicians can assess the reliability of individual AI-generated results. Researchers at the Else Kröner Fresenius Center (EKFZ) for Digital Health at TU Dresden and Dresden University Hospital have developed an on-premises medical AI system that addresses both challenges. Their findings have been published in the journal Nature Medicine.

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Teens' AI use becomes problematic when a chatbot replaces a trusted adult or peer, according to psychiatrists.

After an injury, DNA not only alters its activity but also the way it is organized spatially within the cell nucleus.

A few species of hydra are immortal in their normal environmental conditions, meaning that function does not decline over time and mortality risk does not increase over time. Researchers spent a good deal of time taking care of hundreds of hydra some years ago to demonstrate that this is the case. Hydra are lower animals, essentially a bundle of stem cells capable of regenerating and replacing any part of their bodies, somewhat analogous to an ambulatory embryo. It is an open question as to whether anything we can learn from their biochemistry can be useful in human medicine. In today's open access paper, researchers report on the employment of telomerase by hydra. Telomeres are repeated sequences at the end of chromosomes that shorten with each […]

The biologic drug interferon-alpha can benefit patients with blood cancers called myeloproliferative neoplasms by forcing mutant blood stem cells to become shorter-lived white blood cells, according to a study by Weill Cornell Medicine investigators. Because the broad activity of interferon-alpha can induce significant side effects, developing more focused strategies based on these mechanistic findings could meet an important need in cancer therapy.

During transplantation, blood flow to the donor liver must stop as it's moved to the recipient. Once transplanted, oxygen-rich blood is restored, yet doing so can cause what is called ischemia-reperfusion injury. To protect transplanted livers from this tissue damage, researchers at The Hospital for Sick Children (SickKids) have discovered a way to protect dying cells from rupturing and affecting the surrounding area.

Targeting the gut microbiome with fecal microbiota transplantation (FMT) may help cancer patients with immunotherapy-related colitis avoid the need for steroids and other immunosuppressive treatments, according to researchers at The University of Texas MD Anderson Cancer Center.

Insilico Medicine, a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, today announced Longevity Vaccines, a research initiative developing treatments that direct a patient's own immune cells to eliminate the earliest cellular drivers of age-related disease.

Preeclampsia is one of the leading causes of pregnancy-related death. Even after a healthy delivery, mother and baby can go home only to show signs of a postpartum hypertensive disorder days or weeks later.

A National Institutes of Health (NIH)-funded scientific team has shown that a new brain-computer interface (BCI) can allow people with vocal tract and bodily paralysis to convey both speech and upper-body gestures simultaneously.

Stockholm-based Tandem Health has raised $100m in a Series B round led by the Scaleup Europe Fund, which EQT manages. The company announced the round on 14 September. Existing investors Kinnevik, Northzone, Amino Collective, and Visionaries also took part. Tandem said the deal is the fund’s first investment in healthcare. The round follows a $50m […] This story continues at The Next Web

The company anticipates its two pumps will work with a next-generation insulin dosing algorithm.

Cells become senescent constantly throughout life in response to various forms of damage and stress, ceasing replication and generating a potent mix of inflammatory signals. In youth, these cells are promptly cleared by the immune system, but with advancing age they begin to linger and accumulate. The inflammatory signaling becomes disruptive to tissue structure and function when sustained over the long term, and this is an important contribution to degenerative aging. Here, researchers show that macrophage cells in the kidney express increasing amounts of the P2RX7 receptor on the cell surface as they progress towards becoming senescent, and blocking this receptor with a suitable antagonist small molecule reduces macrophage senescence and improves kidney function. Macrophage senescence is a pathological feature in aging or diseased kidneys. […]

TIGRa, half CRISPR’s size, fits in viral vectors to boost protective genes. Its compact design could enable gene

arXiv:2609.13322v1 Announce Type: new Abstract: Research on cellular senescence and the senescence-associated secretory phenotype (SASP) draws on independently curated gene resources that differ in scope, identifiers, and update cycles, making cross-resource integration error-prone. We unified four widely used resources, CellAge, GenAge, the SenMayo signature, and the Reactome Cellular Senescence pathway, onto a single canonical identifier (the Ensembl gene ID) and enriched every gene with three annotation layers absent from all four inputs: cross-species conservation, tissue and cell-type expression, and high-confidence protein-protein interactions. Unification collapsed 1,460 summed source entries into 1,250 unique genes (210 redundant entries removed, 14.4%) while preserving full source provenance: 173 genes are corroborated by two or more resources and two (IL6, JUN) by all four. The three annotation layers reach 95.8%, 97.9%, and 93.0% of genes, with 89.4% annotated across all

arXiv:2609.15638v1 Announce Type: new Abstract: This study explores the use of deep learning and explainable artificial intelligence to diagnose hepatocellular carcinoma (HCC) and define effective biomarkers across five different stages of disease development using a transcriptomic biomarker HCC dataset constructed via semi-supervised learning from three source datasets. Several deep learning experiments were conducted with different feature extraction techniques and gene sets to identify the most effective features for training high-accuracy models with minimal loss. The best-performing model, using 15 selected genes with the SelectKBest algorithm, achieved 90.74% accuracy, while the model with the lowest recorded loss of 0.3187 was obtained using 20 selected genes. To address the issue of class imbalance in the dataset, a weighted training approach was conducted, and for model transparency and interpretability a SHAP-based XAI analysis provided insights into the model's

arXiv:2609.15225v1 Announce Type: new Abstract: Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requiring coronal plane reconstruction, and to evaluate its clinical applicability. Methods: CUA-Net was built on 3D ResNet-18, equipped with a dynamic data resampling strategy to mitigate the data imbalance issue and a hard sample mining technique to fully learn from the difficult cases by loss adjustment. We further proposed the self-supervised reconstruction to comprehensively explore the volumes and the online data augmentation to refine the wrong predictions and enhance the model's generalization. We compared the CUA-Net with different deep-learning methods and junior/senior sonographers in the testing set. The evaluation metrics included accuracy, precision, recall, F1-score, micro-AUC, and macro-AUC. Results: The proposed CUA-Net exhibited satisfactory performance in both internal and

arXiv:2609.15184v1 Announce Type: new Abstract: Zero-shot text-to-speech (TTS) can clone a speaker's voice from a short audio prompt, yet most TTS systems still require the audio prompt transcript during inference. This dependency prevents cross-lingual voice cloning when the audio prompt transcript is unavailable, particularly for unseen languages. Cross-Lingual F5-TTS removes this dependency and enables transcript-free cross-lingual voice cloning, but it prepares its training data with forced alignment. Forced alignment is sensitive to boundary errors, and its cost grows as more languages are covered. Its speaking rate predictor is also unreliable at estimating duration when the audio prompt begins or ends with silence. In this paper, we present Cross-Lingual F5-TTS 2, a simplified framework for transcript-free cross-lingual voice cloning without forced alignment. Instead of using forced alignment to segment real utterances, we build same-speaker prompt and target pairs using a

arXiv:2609.15046v1 Announce Type: new Abstract: Personal health interfaces present wellbeing data through standardized dashboards that rarely fit how people interpret or act on it. Personalizing them to what people would like to see for themselves often requires design and technical expertise, a barrier that generative AI may potentially lower. Therefore, we ask what designs emerge and how it enables and constrains the design process. We conducted a co-design study where 14 participants redesigned Google and Apple Health interfaces using Figma Make. Participants reimagined interfaces that supported personal context, future planning, and interactive experiences, yet conversational AI designs converged around chat-window conventions. AI helped materialize loosely articulated ideas, but model defaults and generation latency shaped iteration. The process more readily operationalized interpretability and accountability than privacy, trust, and emotional safety. Generative co-design let

arXiv:2609.14886v1 Announce Type: new Abstract: Online mental health communities thrive on peer support, yet those who volunteer to help often lack formal training and may struggle to articulate supportive responses. AI co-writing could lower this barrier; however, peer support derives much of its value from being perceived as personal, raising questions around authorship, ownership, and trust. We built PeerPen, a writing assistance tool embedded within a Reddit-like interface, supporting two main features: draft generation and revision of user-written responses. Through semi-structured interviews with 15 participants, we find that PeerPen reduced the burden of composing responses and increased confidence in offering support. Participants wanted AI to assist their writing without taking over authorship and anticipated tensions around authenticity and trust. Such assistance could make authorship uncertain even for responses written without it, weakening trust across the community. We

Machine learning enables computers to learn from data and use that knowledge to make predictions or decisions. In health care, machine learning supports tasks such as disease diagnosis, predicting disease progression, treatment planning and patient monitoring.

Nostradamus's ambiguous 16th-century verse is being linked to artificial intelligence, but the interpretation reflects modern fears rather than evidence of a specific prediction about machines.

After an injury, DNA not only changes its activity but also the way it is organized spatially within the cell nucleus. In this process, certain regions of DNA establish new physical contacts through chromatin loops that act as bridges, bringing together sequences that are far apart in the genome's linear sequence. Now, a study has identified—in an animal model—the formation of these loops as an essential step in tissue regeneration after an injury.

Dr. Chi Kyung (CK) Kim of the Department of Neurology at Korea University Guro Hospital and his research team successfully conducted a multinational validation of AI technology that precisely detects large vessel occlusion (LVO) in acute stroke patients using only standard brain CT (non-contrast CT) without contrast agents. The findings are published in the Journal of NeuroInterventional Surgery. The team includes research Dr. Kim Beom-joon of the Department of Neurology, Dr. Jun Sun-woo of the Department of Radiology at Seoul National University Bundang Hospital, and CMO Ryu Wi-sun of JLK.

Moderna and Merck's Phase 3 melanoma vaccine trial showed positive results, but full data and FDA approval are still pending for the mRNA therapy.

InvestorPlace - Stock Market News, Stock Advice & Trading Tips During these busy times, it pays to stay on top of the latest profit opportunities. And today’s blog post should be a great place to start. The post Intel Upgraded, CVS Health Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

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John Reynolds / Tech.eu: Stockholm-based Tandem Health, which offers clinicians an AI copilot that generates medical notes during patient consultations, raised a $100M Series B  —  The funding will be used for European expansion, driving up its customer base, and expanding to “an AI-native clinic operating system”.

A familiar diabetes pill could hold the power to slow the biological forces that leave the body increasingly vulnerable to disease as it ages. What if a drug already prescribed to millions of people could do more than control blood sugar? For years, researchers have wondered whether metformin, one of the world’s most widely used [...]

A scientific team has shown that a new brain-computer interface (BCI) can allow people with vocal tract and bodily paralysis to convey both speech and upper-body gestures simultaneously. While BCIs have facilitated one or the other in the past, this new system is the first to enable both modes of communication at once, more closely replicating natural expression.

Internal documents show contractor readiness concerns, decision delays, and high non-affirmation rates, while providers report patients waiting for care and payment problems.

Qingyu Chen, PhD, and his team set out to study how artificial intelligence language models are adapted for medicine and found that what these models memorize can be both useful and risky. A model may retain valuable medical knowledge, but in a controlled study using real hospital records, the same fine-tuning—the added training that adapts a model to a specific task—that improved diagnostic performance also made it more likely to reproduce material it had seen during training, including sensitive patient information.

arXiv:2609.12650v1 Announce Type: new Abstract: Multi-electrode Arrays (MEAs) enable tissue-level electrophysiological studies of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) by recording extracellular field potentials. Recent computational models have improved MEA simulations by coupling detailed electrode descriptions with the Bidomain framework, a parabolic-elliptic system of nonlinear PDEs coupled with a stiff ionic model. The standard numerical strategy relies on operator splitting techniques that decouple the PDE and ODE components. In most implementations, the ionic subsystem is treated explicitly while the diffusive operator is handled implicitly, resulting in a first-order implicit-explicit (IMEX) time discretization. Although computationally convenient, this approach limits temporal accuracy and may reduce efficiency in large-scale simulations. In this work, we investigate higher-order IMEX Runge-Kutta schemes within a Strang-based operator

arXiv:2609.12822v1 Announce Type: new Abstract: Blinded physician evaluation has been considered by many to be the gold standard for assessing clinical reasoning in large language models (LLMs). This is difficult to scale; thus, prior studies typically rely on small physician panels, often from a single institution or specialty, which both limits the scientific questions investigated and makes it unclear whether findings would be reproduced with a different set of evaluators. To more rigorously and scalably study clinical reasoning in AI models, here we introduce PrecepTron, an LLM fine-tuned for physician-level evaluation of open-ended responses. PrecepTron was trained using low-rank adaptation (LoRA) of a 32-billion-parameter model on a small number of physician examples. We also release GRAND-ROUNDS, a new large-scale physician-annotated benchmark of 9,217 scores by 11 physicians across seven studies. We show that frontier LLMs in typical "LLM-as-a-judge" approaches often disagree

arXiv:2609.12718v1 Announce Type: new Abstract: Hallucinations can undermine clinician trust in LLMs, making it important that evaluation methods capture clinically relevant errors. Rubric-based evaluation has become the leading approach for assessing LLMs in medicine, but it is unclear whether rubric scores reflect such errors. We first study this in a controlled setting using MedHallu, finding that more specific rubrics better distinguish correct from hallucinated responses. To test this systematically, we develop a taxonomy of medical hallucination types and a clinician-validated error-injection pipeline that creates matched correct and error-injected responses. Across HealthBench, HealthBench Professional, and LiveMedBench, our clinically relevant hallucinations are missed by rubrics, often leaving scores unchanged. We find that rubrics are most effective when explicitly checking facts, and are less effective for additional or unexpected errors they do not anticipate. A

arXiv:2609.12650v1 Announce Type: new Abstract: Multi-electrode Arrays (MEAs) enable tissue-level electrophysiological studies of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) by recording extracellular field potentials. Recent computational models have improved MEA simulations by coupling detailed electrode descriptions with the Bidomain framework, a parabolic-elliptic system of nonlinear PDEs coupled with a stiff ionic model. The standard numerical strategy relies on operator splitting techniques that decouple the PDE and ODE components. In most implementations, the ionic subsystem is treated explicitly while the diffusive operator is handled implicitly, resulting in a first-order implicit-explicit (IMEX) time discretization. Although computationally convenient, this approach limits temporal accuracy and may reduce efficiency in large-scale simulations. In this work, we investigate higher-order IMEX Runge-Kutta schemes within a Strang-based operator

arXiv:2609.12298v1 Announce Type: new Abstract: Finger-level motor decoding is important for naturalistic brain-computer interface (BCI) control, yet individual-finger decoding from scalp electroencephalography (EEG) remains challenging because finger representations are spatially close in the sensorimotor cortex and blurred by volume conduction. Leveraging the high spatial resolution of functional MRI (fMRI), we introduce fMRI Representation-Informed Shared-Space Training (FRIST), a two-stage EEG decoding framework that first learns fMRI-informed spectral projections from simultaneous EEG-fMRI recordings and then uses fMRI-derived class geometry to guide residual refinement of EEG predictions. FRIST transfers information across recordings through shared finger labels without requiring paired trials and uses only EEG at inference. We evaluated 12 able-bodied participants during movement execution (ME) and motor imagery (MI) under two-class and three-class chronological

In the world of paediatric medicine, haematopoietic stem cell transplantation is often the last and best hope for children with leukaemia, inherited immune deficiencies, bone marrow failure syndromes and a range of other life-threatening disorders. The procedure replaces a child’s faulty blood-forming and immune system with healthy donor stem cells, offering the possibility of a […]

Gene editing has long promised a revolution in cancer medicine, yet the promise has remained stubbornly out of reach for one deceptively simple reason: getting the CRISPR-Cas9 machinery into tumor cells, and only tumor cells, is extraordinarily difficult. A new comprehensive review published in Advanced Composites and Hybrid Materials argues that the missing piece of […]

Artificial intelligence has become an increasingly powerful tool in the search for new medicines, but a persistent problem has haunted the field: neural networks that invent molecules are remarkably creative yet notoriously unreliable. They can propose chemical structures that look plausible on paper but violate basic principles of chemistry or pharmacology, forcing medicinal chemists to […]

A blood test that could help clinicians diagnose autism spectrum disorder in toddlers has moved a significant step closer to real-world use, thanks to a new translational study published in the Annals of Biomedical Engineering. Researchers led by Juergen Hahn of Rensselaer Polytechnic Institute, working with clinical partners in Arizona, Tennessee, and the biotechnology company […]

Chronic kidney disease is one of the world’s most burdensome chronic conditions, a slow and often silent deterioration of renal function that affects hundreds of millions of people and frequently goes undetected until the damage is advanced. Staging the disease correctly is central to everything that follows: it determines how aggressively clinicians manage blood pressure […]

Peppers are among the world’s most valuable vegetable crops, prized for their culinary versatility, vibrant pigments, and nutritional content, yet they remain dangerously vulnerable to cold. Even brief exposure to chilling temperatures can disrupt membrane integrity, suppress photosynthesis, and throw cellular redox balance into disarray, slashing both yield and fruit quality. Now, a comprehensive review […]

Treating inherited diseases is one of the greatest challenges in modern medicine. In the future, targeted gene corrections at the earliest stages of embryonic development could help prevent certain inherited diseases from developing and being passed on to future generations. However, the safety of such approaches depends on how human embryos repair the DNA damage caused during gene editing and on the limitations of available technologies. These questions are addressed in a study published in the journal Nature, led by first author Štěpán Jeřábek, who is affiliated with both Columbia University and IOCB Prague. The research also involved two other IOCB Prague scientists, Iva Pichová and Michal Doležal.

Oesophageal adenocarcinoma is one of the most stubborn cancers in modern oncology. Diagnosed at a stage where the tumour has often already invaded the wall of the gullet or spread beyond it, it carries some of the bleakest long-term survival figures of any major cancer type. Even as chemotherapy, radiotherapy, targeted drugs and, more recently, […]

Artificial intelligence has taken another step into the exam room, and this time the target is one of the most quietly common conditions in women’s health: cystocele, the herniation of the bladder into the front wall of the vagina that affects a large share of women who have given birth. In a study published in […]

Deep learning models can now spot malaria parasites in blood smears, grade diabetic retinopathy from retinal photographs, and detect the earliest structural signatures of Alzheimer’s disease on brain MRI scans, often matching the performance of experienced clinicians. Yet a persistent problem has kept many of these systems out of routine clinical use: they deliver confident-looking […]

Living to 100 may benefit more than one generation. Children of centenarians tend to live longer while delaying major threats to heart health. A study published in JAMA Network Open found that adults with at least one parent who lived to 100 had substantially lower risks of death, cardiovascular disease, and hypertension than people whose [...]

For nearly a century, scientists have known that cutting calories can extend lifespan in laboratory animals, from yeast to mice. Whether the same holds true for humans has been far harder to establish, largely because the tools for measuring human aging are still maturing. A new study published in GeroScience offers some of the strongest […]

Every few seconds inside a scanning suite, a quiet race unfolds between two forces that pull a medical image apart. On one side is the patient, whose breathing, heartbeat and small involuntary shifts blur the geometry of each frame. On the other is the contrast agent itself, flooding through vessels and tissues, brightening some regions […]

A one-year-old boy with a rare mitochondrial disorder that had pushed both of his heart ventricles to the brink of collapse has survived to receive a new heart, thanks to an unconventional sequence of mechanical circulatory support decisions described by cardiac surgeons at the University of Osaka. The case, published in the Journal of Artificial […]

Maize is the backbone of global agriculture, cultivated on more than 200 million hectares and feeding billions of people as food, animal feed, and bioenergy feedstock. Yet the crop that sustains so much of the world is increasingly under siege. Erratic rainfall, scorching heat waves, soil degradation, and emerging pests and diseases are steadily eroding […]