Researchers have identified two brain receptors that help the brain clear away amyloid beta, a hallmark of Alzheimer’s disease. By stimulating these receptors in mice, scientists increased levels of a natural amyloid-breaking enzyme, reduced buildup in the brain, and improved memory-related behavior. Because these receptors are common drug targets, the findings could open the door to affordable pill-based treatments with fewer side effects.
Researchers have identified two brain receptors that help the brain clear away amyloid beta, a hallmark of Alzheimer’s disease. By stimulating these receptors in mice, scientists increased levels of a natural amyloid-breaking enzyme, reduced buildup in the brain, and improved memory-related behavior. Because these receptors are common drug targets, the findings could open the door to affordable pill-based treatments with fewer side effects.
arXiv:2602.15019v1 Announce Type: new
Abstract: Bio-pharmaceutical innovation has shifted: many new drug assets now originate outside the United States and are disclosed primarily via regional, non-English channels. Recent data suggests >85% of patent filings originate outside the U.S., with China accounting for nearly half of the global total; a growing share of scholarly output is also non-U.S. Industry estimates put China at ~30% of global drug development, spanning 1,200+ novel candidate
arXiv:2602.15019v1 Announce Type: new
Abstract: Bio-pharmaceutical innovation has shifted: many new drug assets now originate outside the United States and are disclosed primarily via regional, non-English channels. Recent data suggests >85% of patent filings originate outside the U.S., with China accounting for nearly half of the global total; a growing share of scholarly output is also non-U.S. Industry estimates put China at ~30% of global drug development, spanning 1,200+ novel candidates. In this high-stakes environment, failing to surface "under-the-radar" assets creates multi-billion-dollar risk for investors and business development teams, making asset scouting a coverage-critical competition where speed and completeness drive value. Yet today's Deep Research AI agents still lag human experts in achieving high-recall discovery across heterogeneous, multilingual sources without hallucinations.
We propose a benchmarking methodology for drug asset scouting and a tuned, tree-based self-learning Bioptic Agent aimed at complete, non-hallucinated scouting. We construct a challenging completeness benchmark using a multilingual multi-agent pipeline: complex user queries paired with ground-truth assets that are largely outside U.S.-centric radar. To reflect real deal complexity, we collected screening queries from expert investors, BD, and VC professionals and used them as priors to conditionally generate benchmark queries. For grading, we use LLM-as-judge evaluation calibrated to expert opinions. We compare Bioptic Agent against Claude Opus 4.6, OpenAI GPT-5.2 Pro, Perplexity Deep Research, Gemini 3 Pro + Deep Research, and Exa Websets. Bioptic Agent achieves 79.7% F1 versus 56.2% (Claude Opus 4.6), 50.6% (Gemini 3 Pro + Deep Research), 46.6% (GPT-5.2 Pro), 44.2% (Perplexity Deep Research), and 26.9% (Exa Websets). Performance improves steeply with additional compute, supporting the view that more compute yields better results.
arXiv:2602.13332v1 Announce Type: cross
Abstract: Long-form clinical videos are central to visual evidence-based decision-making, with growing importance for applications such as surgical robotics and related settings. However, current multimodal large language models typically process videos with passive sampling or weakly grounded inspection, which limits their ability to iteratively locate, verify, and justify predictions with temporally targeted evidence. To close this gap, we propose MedSc
arXiv:2602.13332v1 Announce Type: cross
Abstract: Long-form clinical videos are central to visual evidence-based decision-making, with growing importance for applications such as surgical robotics and related settings. However, current multimodal large language models typically process videos with passive sampling or weakly grounded inspection, which limits their ability to iteratively locate, verify, and justify predictions with temporally targeted evidence. To close this gap, we propose MedScope, a tool-using clinical video reasoning model that performs coarse-to-fine evidence seeking over long-form procedures. By interleaving intermediate reasoning with targeted tool calls and verification on retrieved observations, MedScope produces more accurate and trustworthy predictions that are explicitly grounded in temporally localized visual evidence. To address the lack of high-fidelity supervision, we build ClinVideoSuite, an evidence-centric, fine-grained clinical video suite. We then optimize MedScope with Grounding-Aware Group Relative Policy Optimization (GA-GRPO), which directly reinforces tool use with grounding-aligned rewards and evidence-weighted advantages. On full and fine-grained video understanding benchmarks, MedScope achieves state-of-the-art performance in both in-domain and out-of-domain evaluations. Our approach illuminates a path toward medical AI agents that can genuinely "think with videos" through tool-integrated reasoning. We will release our code, models, and data.
npj Digital Medicine, Published online: 17 February 2026; doi:10.1038/s41746-026-02438-3Empowering genetic discoveries and cardiovascular risk assessment by predicting electrocardiograms from genotype
(MedPage Today) -- Use of a best practice alert in the electronic health record (EHR) combined with a clinician education component was associated with a higher likelihood of early human papillomavirus (HPV) vaccination, a retrospective quality...
(MedPage Today) -- Use of a best practice alert in the electronic health record (EHR) combined with a clinician education component was associated with a higher likelihood of early human papillomavirus (HPV) vaccination, a retrospective quality...
npj Digital Medicine, Published online: 16 February 2026; doi:10.1038/s41746-026-02437-4Randomized-controlled trial of skills-based vr vs. distraction vr vs. sham VR for chronic low back pain
Researchers tracked more than 400 toddlers to see whether mRNA COVID-19 vaccination during or just before pregnancy was linked to autism or developmental delays. After detailed assessments of speech, motor skills, behavior, and social development, they found no meaningful differences between vaccinated and unvaccinated groups. Experts say the results provide strong reassurance about vaccine safety in pregnancy.
Researchers tracked more than 400 toddlers to see whether mRNA COVID-19 vaccination during or just before pregnancy was linked to autism or developmental delays. After detailed assessments of speech, motor skills, behavior, and social development, they found no meaningful differences between vaccinated and unvaccinated groups. Experts say the results provide strong reassurance about vaccine safety in pregnancy.
An operational AI forecasting model developed by Hertfordshire University researchers aims to improve resource efficiency within healthcare.
Public sector organisations often hold large archives of historical data that do not inform forward-looking decisions. A partnership between the University of Hertfordshire and regional NHS health bodies addresses this issue by applying machine learning to operational planning. The project analyses healthcare demand to assist managers with decisions rega
An operational AI forecasting model developed by Hertfordshire University researchers aims to improve resource efficiency within healthcare.
Public sector organisations often hold large archives of historical data that do not inform forward-looking decisions. A partnership between the University of Hertfordshire and regional NHS health bodies addresses this issue by applying machine learning to operational planning. The project analyses healthcare demand to assist managers with decisions regarding staffing, patient care, and resources.
Most AI initiatives in healthcare focus on individual diagnostics or patient-level interventions. The project team notes that this tool targets system-wide operational management instead. This distinction matters for leaders evaluating where to deploy automated analysis within their own infrastructure.
The model uses five years of historical data to build its projections. It integrates metrics such as admissions, treatments, re-admissions, bed capacity, and infrastructure pressures. The system also accounts for workforce availability and local demographic factors including age, gender, ethnicity, and deprivation.
Iosif Mporas, Professor of Signal Processing and Machine Learning at the University of Hertfordshire, leads the project. The team includes two full-time postdoctoral researchers and will continue development through 2026.
“By working together with the NHS, we are creating tools that can forecast what will happen if no action is taken and quantify the impact of a changing regional demographic on NHS resources,” said Professor Mporas.
Using AI for forecasting in healthcare operations
The model produces forecasts showing how healthcare demand is likely to change. It models the impact of these changes in the short-, medium-, and long-term. This capability allows leadership to move beyond reactive management.
Charlotte Mullins, Strategic Programme Manager for NHS Herts and West Essex, commented: “The strategic modelling of demand can affect everything from patient outcomes including the increased number of patients living with chronic conditions.
“Used properly, this tool could enable NHS leaders to take more proactive decisions and enable delivery of the 10-year plan articulated within the Central East Integrated Care Board as our strategy document.”
The University of Hertfordshire Integrated Care System partnership funds the work, which began last year. Testing of the AI model tailored for healthcare operations is currently underway in hospital settings. The project roadmap includes extending the model to community services and care homes.
This expansion aligns with structural changes in the region. The Hertfordshire and West Essex Integrated Care Board serves 1.6 million residents and is preparing to merge with two neighbouring boards. This merger will create the Central East Integrated Care Board. The next phase of development will incorporate data from this wider population to improve the predictive accuracy of the model.
The initiative demonstrates how legacy data can drive cost efficiencies and shows that predictive models can inform “do nothing” assessments and resource allocation in complex service environments like the NHS. The project highlights the necessity of integrating varied data sources – from workforce numbers to population health trends – to create a unified view for decision-making.
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Int J Mol Sci. 2026 Feb 6;27(3):1597. doi: 10.3390/ijms27031597.ABSTRACTAmpullary carcinoma (AC) is a rare gastrointestinal malignancy with dual intestinal and pancreatobiliary differentiation, complicating diagnosis, staging, and treatment. This review synthesizes current epidemiology, pathology, and multi-omic data to outline a pragmatic care pathway: lineage-first at presentation, mutation-fast at progression. Histology remains the primary classifier: the intestinal subtype generally aligns w
Int J Mol Sci. 2026 Feb 6;27(3):1597. doi: 10.3390/ijms27031597.
ABSTRACT
Ampullary carcinoma (AC) is a rare gastrointestinal malignancy with dual intestinal and pancreatobiliary differentiation, complicating diagnosis, staging, and treatment. This review synthesizes current epidemiology, pathology, and multi-omic data to outline a pragmatic care pathway: lineage-first at presentation, mutation-fast at progression. Histology remains the primary classifier: the intestinal subtype generally aligns with colorectal regimens, whereas pancreatobiliary and mixed subtypes favor pancreaticobiliary therapy. In selected fit patients, modified FOLFIRINOX may address mixed phenotypes. Next-generation sequencing adds precision by identifying therapeutically relevant alterations, including ERBB2/HER2 amplifications, MSI-high/dMMR, BRAF V600E, and rare NTRK or RET fusions, while KRAS mutations are enriched in pancreatobiliary tumors. We recommend early application of a rapid-core panel (KRAS/BRAF, MSI/dMMR, ERBB2/HER2, RNA-based fusions) to capture high-impact targets, followed by comprehensive profiling at first progression. Liquid biopsy, plasma circulating tumor DNA (ctDNA), or bile-derived DNA may complement tissue and help identify the dominant lineage. Research priorities include ampulla-enriched umbrella trials, explicit AC subcohorts in tissue-agnostic studies, and ctDNA-informed endpoints. This lineage-first, mutation-fast paradigm supports precision care and evidence generation in AC.
Nature, Published online: 13 February 2026; doi:10.1038/d41586-026-00412-3Symptoms and organ damage abated in young children and teenagers whose conditions had resisted other treatments.
Publication date: May 2026Source: Artificial Intelligence in Medicine, Volume 175Author(s): Marina del Barrio, Kazim Laos, María José Vilchez Lara, Carlos Goicoechea García, Hector D. Menendez
(MedPage Today) -- The FDA approved a tumor treating fields (TTFields) device for locally advanced pancreatic cancer, the first therapy approved in this setting in nearly 30 years.
Dubbed Optune Pax, the wearable device delivers alternating electric...
(MedPage Today) -- The FDA approved a tumor treating fields (TTFields) device for locally advanced pancreatic cancer, the first therapy approved in this setting in nearly 30 years.
Dubbed Optune Pax, the wearable device delivers alternating electric...
The Food and Drug Administration’s refusal to review Moderna’s flu vaccine this month has renewed fears that Trump administration policies could paralyze the vaccine industry, dissuading companies from developing new shots in the U.S. and leaving the country flat-footed in the event of future pandemics.
“I consider it an unprecedented action that really violates the basic principles of a data-driven regulatory agency and the fundamentals of public health, and it’s that simple,” said Gary Nab
The Food and Drug Administration’s refusal to review Moderna’s flu vaccine this month has renewed fears that Trump administration policies could paralyze the vaccine industry, dissuading companies from developing new shots in the U.S. and leaving the country flat-footed in the event of future pandemics.
“I consider it an unprecedented action that really violates the basic principles of a data-driven regulatory agency and the fundamentals of public health, and it’s that simple,” said Gary Nabel, former head of the National Institutes of Health’s Vaccine Research Center and chief scientist at Sanofi, who now runs a vaccine and cancer startup. “It’s a destructive precedent that will undermine the future of vaccine development and the preeminence of American research.”
OpenAI described how it scaled PostgreSQL to support ChatGPT and its API platform, handling millions of queries per second for hundreds of millions of users. By running a single-primary PostgreSQL deployment on Azure with nearly 50 read replicas, optimizing query patterns, and offloading write-heavy workloads to sharded systems, OpenAI maintained low-latency reads while managing write pressure. By Leela Kumili
OpenAI described how it scaled PostgreSQL to support ChatGPT and its API platform, handling millions of queries per second for hundreds of millions of users. By running a single-primary PostgreSQL deployment on Azure with nearly 50 read replicas, optimizing query patterns, and offloading write-heavy workloads to sharded systems, OpenAI maintained low-latency reads while managing write pressure.
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Today, we’ve got a ton of updates including news about venture capital funding, telehealth policy, the government’s progress on information blocking, and research into the accuracy of Apple’s new hypertension feature.Continue to STAT+ to read the full story…
You’re reading the web edition of STAT’s Health Tech newsletter, our guide to how technology is transforming the life sciences. Sign up to get it delivered in your inbox every Tuesday and Thursday.
Good morning health tech readers!
Today, we’ve got a ton of updates including news about venture capital funding, telehealth policy, the government’s progress on information blocking, and research into the accuracy of Apple’s new hypertension feature.
Transl Cancer Res. 2026 Jan 31;15(1):43. doi: 10.21037/tcr-2025-1499. Epub 2026 Jan 27.ABSTRACTBACKGROUND: Osteoglycin (OGN), an extracellular matrix protein, has emerging but poorly characterized roles in cancer. This study presents the first pan-cancer investigation of OGN's expression patterns, clinical significance, immune interactions, and functional mechanisms.METHODS: Multi-omics data from Genotype Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TC
Transl Cancer Res. 2026 Jan 31;15(1):43. doi: 10.21037/tcr-2025-1499. Epub 2026 Jan 27.
ABSTRACT
BACKGROUND: Osteoglycin (OGN), an extracellular matrix protein, has emerging but poorly characterized roles in cancer. This study presents the first pan-cancer investigation of OGN's expression patterns, clinical significance, immune interactions, and functional mechanisms.
METHODS: Multi-omics data from Genotype Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), and Human Protein Atlas (HPA) databases were integrated. Differential expression was analyzed in normal tissues and tumor samples. Diagnostic utility was evaluated using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Prognostic value was assessed via Kaplan-Meier [overall survival (OS); disease-specific survival (DSS); disease free interval (DFI); progression-free interval (PFI)] and Cox regression analyses. Immune microenvironment correlations were quantified using ESTIMATE, CIBERSORT, and gene set enrichment. Functional pathways were explored through gene set enrichment analysis (GSEA) and correlation with hallmark cancer signatures.
RESULTS: OGN was broadly expressed in normal tissues (brain, liver, kidney) but significantly downregulated in most tumor types (P<0.05, TCGA; validated at protein level, HPA). OGN demonstrated high diagnostic accuracy in pan-cancer (AUC: 0.703-0.990), achieving near-perfect performance in colon adenocarcinoma (COAD) (AUC: 0.966) and thyroid cancer (THCA) (AUC: 0.920). High OGN expression correlated with improved survival outcomes in thymoma (THYM) (OS/DSS) and cholangiocarcinoma (CHOL) (PFI/DFI), but worse prognosis in lung adenocarcinoma/liver hepatocellular carcinoma (LUAD/LIHC), indicating cancer-type specificity. OGN expression strongly associated with immune cell infiltration (macrophages, natural killer cells, T cells), chemokine signaling, programmed death-ligand 1 (PD-L1) levels, microsatellite instability (MSI), and tumor mutation burden (TMB). GSEA revealed enrichment of OGN-linked genes in epithelial-mesenchymal transition (EMT), angiogenesis, JAK-STAT, and PI3K pathways across cancers.
CONCLUSIONS: Our pan-cancer analysis highlights OGN as a context-dependent regulator linking extracellular matrix (ECM) remodeling with immune and angiogenic signaling. Its pan-cancer dysregulation, diagnostic/prognostic value, and crosstalk with immune evasion mechanisms nominate OGN as a promising multi-functional biomarker and therapeutic target.
AI‑generated code creates implicit architectural decisions, forcing teams to rely on experimentation to validate quality attributes. To get useful results from AI, teams must clearly express trade‑offs and reasoning so the model can generate solutions aligned with desired QARs. By Pierre Pureur, Kurt Bittner
AI‑generated code creates implicit architectural decisions, forcing teams to rely on experimentation to validate quality attributes. To get useful results from AI, teams must clearly express trade‑offs and reasoning so the model can generate solutions aligned with desired QARs.
Nature, Published online: 12 February 2026; doi:10.1038/d41586-026-00250-3Densely packed arrays of electrical components called capacitors can form a high-fidelity vibration sensor that can be worn on the skin.
Oncogene. 2026 Feb 11. doi: 10.1038/s41388-026-03679-y. Online ahead of print.ABSTRACTNon-small cell lung cancer (NSCLC) with spinal metastasis represents a clinical challenge due to its aggressive nature, limited treatment options, and profound impact on patient quality of life. Here, we report the development of an innovative upconversion mesoporous silica nanoparticle (UCMS) platform co-loaded with celecoxib and rose bengal (UCMS@CXB/RB), engineered to synergistically combine photodynamic the
Oncogene. 2026 Feb 11. doi: 10.1038/s41388-026-03679-y. Online ahead of print.
ABSTRACT
Non-small cell lung cancer (NSCLC) with spinal metastasis represents a clinical challenge due to its aggressive nature, limited treatment options, and profound impact on patient quality of life. Here, we report the development of an innovative upconversion mesoporous silica nanoparticle (UCMS) platform co-loaded with celecoxib and rose bengal (UCMS@CXB/RB), engineered to synergistically combine photodynamic therapy (PDT) and cyclooxygenase-2 (COX-2) inhibition. Upon near-infrared (NIR) irradiation, UCMS@CXB/RB generated abundant reactive oxygen species, triggered immunogenic cell death, and significantly suppressed prostaglandin E2 signaling, leading to reduced angiogenesis and improved antitumor immunity. In vitro and in vivo studies confirmed that this nanoplatform effectively remodeled the tumor microenvironment, inhibited tumor growth, and alleviated cancer-induced spinal dysfunction. Single-cell multi-omics analysis further revealed dynamic crosstalk among immune cells, tumor cells, and endothelial populations, providing mechanistic insights into the multifaceted therapeutic effects of UCMS@CXB/RB. Our results underscore the clinical potential of integrating PDT with targeted COX-2 blockade to address the complex pathophysiology of NSCLC spinal metastasis. This study presents a promising minimally invasive therapeutic strategy with strong translational relevance for managing metastatic NSCLC and improving patient outcomes.
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(MedPage Today) -- Use of a best practice alert in the electronic health record (EHR) combined with a clinician education component was associated with a higher likelihood of early human papillomavirus (HPV) vaccination, a retrospective quality...
