Background: The widespread adoption of electronic health records (EHRs) has generated large-scale repositories of highly sensitive clinical information, emphasizing the need for robust anonymization strategies to enable secondary use for research while safeguarding patient privacy. Conventional rule-based and machine learning approaches for deidentifying medical text face limitations with the linguistic complexity, variability, and context dependence inherent to clinical documentation. Recent advances in large language models (LLMs), combined with emerging quantum computing paradigms, present novel opportunities to enhance the accuracy, scalability, and resilience of health care data anonymization. Objective: This study aims to evaluate the efficacy of LLM-based and quantum-enhanced hybrid architectures for medical text anonymization, assessing the effectiveness and computational efficiency across multiple entity types in Portuguese clinical notes. Methods: We constructed a gold-standard corpus of 1000 Portuguese outpatient clinical notes, manually annotated by 5 trained researchers for 5 protected-entity categories: patient names, dates, identifiers, organizations, and geographic locations. Four anonymization strategies were evaluated: 2 stand-alone LLMs (Llama-3.1-8B-instruct and Llama-3.3-70B-instruct) and 2 quantum-enhanced hybrid models (Dynex-QML with 8B and 70B base models) incorporating quantum optimization via Quadratic Unconstrained Binary Optimization (QUBO) formulations. The quantum-enhanced approach transforms the final attention layer of the LLM into a global constraint satisfaction problem solved via neuromorphic quantum annealing. Model performance was measured on a held-out test set of 500 notes using precision, recall, and -score metrics. Computational efficiency was quantified through end-to-end processing time. Results: The quantum-enhanced Dynex-QML-70B model achieved the highest overall performance with a macro-score of 0.855 (95% CI 0.823‐0.880), outperforming the stand-alone Llama-3.3-70B (0.726, 95% CI 0.704‐0.747), Dynex-QML-8B (0.733, 95% CI 0.709‐0.756), and Llama-3.1-8B (0.602, 95% CI 0.588‐0.615). Compared with Llama 3.3 70B, Dynex-QML (Llama 70B) improved macro-score by 0.128 (95% CI 0.091‐0.163; empirical 2-sided bootstrap

npj Digital Medicine, Published online: 14 September 2026; doi:10.1038/s41746-026-03240-x

Publisher Correction: A scoping review on the mental health harms of LLM-based chatbots

npj Digital Medicine, Published online: 14 September 2026; doi:10.1038/s41746-026-03225-w

Data-driven identification of repurposable drugs for ALS

Nature Cancer, Published online: 14 September 2026; doi:10.1038/s43018-026-01237-9

Marsoni et al. evaluated the feasibility of a dynamic circulating tumor DNA-guided adjuvant and postadjuvant treatment strategy in patients with resected microsatellite-stable, high-risk stage II or III colon cancer in the phase 2 PEGASUS trial.

Nature Medicine, Published online: 14 September 2026; doi:10.1038/s41591-026-04622-0

In this Comment, we argue for a global health system that recognizes and supports countries as the primary agents of action, oriented around global public goods and collective action, and served by a leaner set of global and regional institutions. We present a potential vision for the functions and distribution of labor in the system to inform ongoing reform discussions and draw critique, dissent and amendment.

Nature Medicine, Published online: 11 September 2026; doi:10.1038/s41591-026-04642-w

In the randomized phase 2 ImmunoPRISM trial, patients with high-risk smoldering multiple myeloma (MM) showed higher rates of complete clinical responses in response to treatment with teclistamab compared with lenalidomide–dexamethasone, although longer follow-up is required to determine durable prevention of progression to MM.

Science, Ahead of Print.

Background: Large language models (LLMs) are increasingly being deployed in health care, but their use and deployment in many real-world hospital environments pose significant challenges and concerns. In particular, state-of-the-art commercial models store or process data externally, which is often in conflict with ensuring patient data protection. At the same time, using LLMs locally is limited by the lack of available computing infrastructure. Small open-source LLMs that do not require substantial computing resources could offer a practical way to resolve these tensions, but their medical utility in real-world local contexts, especially in non-English languages, has not been sufficiently evaluated. Objective: This study aimed to evaluate the feasibility of small, locally deployable open-source LLMs for clinically relevant tasks in a resource-constrained hospital setting and to propose a reproducible framework for institution-specific evaluation before deployment. Methods: We evaluated 6 open-source LLMs ranging from 8B to 24B parameters (from the Mistral, Phi4, Falcon3, Llama3.1, and Meditron3 families) in a zero-shot setting across 7 tasks covering 4 clinical use cases: information extraction, medical text translation, text generation, and clinical decision support. We used deidentified French clinical data from a Swiss tertiary hospital, including discharge letters, clinical notes, and structured electronic health records. Performance was assessed using task-specific metrics, such as precision, recall, F₁-score, embedding-based semantic similarity, recall-oriented understudy for gisting evaluation (ROUGE) score, readability indices, and human review by clinicians. Results: Model performance varied substantially between tasks. In the simplest retrieval task (needle-in-the-haystack), several models performed strongly, with Llama3.1 achieving an F₁-score of 99.81% and Mistral-small achieving 99.71%. In contrast, performance was poor in more complex tasks. For detecting protected health information, the best-performing LLMs achieved only modest overall macro–F₁-scores (0.33-0.34), substantially below a fine-tuned Robustly Optimized BERT Pretraining Approach (RoBERTa) baseline (0.94). In the task of extracting immune-related adverse events from discharge notes, the highest overall macro–F₁-score was 0.35 with Phi4. For medical text translation, Phi4 ranked highest in embedding-based evaluation, whereas Meditron3-Phi4 performed the worst, with clinician reviews identifying hallucinations in 55% of its outputs. In the task of summarizing discharge letters, quality was low across all models, with the best penalized ROUGE score reaching only 0.169 with Llama3.1. In the tasks of generating patient-friendly discharge note summaries and clinical decision support, clinician ratings generally ranged from dissatisfied to neutral, and no model achieved consistently satisfactory performance. Conclusions: Small open-source LLMs appear feasible for simple retrieval-oriented tasks in local hospital deployments but are currently inadequate for more complex applications, such as clinical decision support, deidentification, extraction of adverse events, and medical summarization. These findings highlight the importance of locally grounded evaluation tailored to specific use cases and the need for robust institutional evaluation frameworks to ensure safe and reliable deployment. Trial Registration:

Nature, Published online: 09 September 2026; doi:10.1038/s41586-026-11025-1

A generative committor-guided path-sampling framework reconstructs rare biomolecular transition pathways and reveals the underlying thermodynamics and kinetics without using predefined collective variables or brute-force sampling, at an acceptable computational cost.

Nature, Published online: 09 September 2026; doi:10.1038/s41586-026-10876-y

In mice, a sparse population of sleep-active long-range inhibitory neurons in the neocortex promote widespread cortical synchronization and sleep, revealing a cortical mechanism that contributes to the regulation of sleep.

Nature, Published online: 09 September 2026; doi:10.1038/s41586-026-10997-4

Evidence from Bianfu Cave shows specialized hunting, expedient stone-tool production and extensive bone use of Denisovans, providing new insights into their ecology, behaviour and cultural legacy in eastern Asia.

Nature, Published online: 09 September 2026; doi:10.1038/s41586-026-10468-w

Eight integrated mutational footprints collectively explain the mutational processes in 85% of primary prostate cancer genomes.

Nature, Published online: 09 September 2026; doi:10.1038/s41586-026-11003-7

A proximity-mapping atlas defines tumour-associated proximity antigens, revealing disease-associated membrane spatial communities, and identifies EGFR–CDCP1 as a co-target pair that enhances tumour killing by multispecific therapeutics.

Nature Medicine, Published online: 09 September 2026; doi:10.1038/s41591-026-04615-z

In a phase 2 randomized clinical trial, treatment with the myeloperoxidase (MPO) inhibitor mitiperstat, intended to target the neutrophil–MPO inflammatory pathway, did not improve symptoms or exercise function in individuals with heart failure with preserved or mildly reduced ejection fraction.

npj Digital Medicine, Published online: 09 September 2026; doi:10.1038/s41746-026-03111-5

Impact of LLM assistance on physician decision-making: a multi-country randomized controlled trial

Background: New HIV cases among Malaysian men who have sex with men continue to rise, with young men who have sex with men (YMSM) accounting for 44% of new infections and experiencing high rates of comorbidities. Mobile health (mHealth) apps offer a promising approach to addressing these challenges by providing discreet access to health information, screening tools, and linkage to services. Given the near-universal smartphone ownership among Malaysian YMSM and high levels of mobile gaming engagement, gamified mHealth apps may be particularly effective in sustaining engagement and promoting HIV prevention behaviors and comorbidity management. However, realizing their full potential requires identifying the features and design principles that are most important to Malaysian YMSM and that can support sustained engagement and improve health outcomes in this vulnerable population. Objective: This study used an interdisciplinary expert panel approach to identify the key features, design principles, and gamification elements to be incorporated into MY-Hero, a gamified mHealth app designed to support HIV prevention, comorbidity management, and overall well-being among Malaysian YMSM. Methods: Guided by the integrated behavioral model (IBM), we conducted an interdisciplinary expert panel comprising experts in health, technology, and design sciences, as well as health care professionals with expertise in the Malaysian YMSM population, along with local lesbian, gay, bisexual, transgender, queer, and others (LGBTQ+) community leaders. Through a structured series of discussions and thematic analysis, we identified culturally appropriate design principles and key features for MY-Hero that align with the health needs and sociocultural context of Malaysian YMSM. Results: Three expert panel sessions were conducted with 9 experts. Several key themes emerged: (1) the importance of establishing clinical affiliation and facilitating linkage to HIV testing, pre-exposure prophylaxis (PrEP), and related services, including harm reduction services; (2) the need to enhance user interface (UI) and user experience (UX) by optimizing usability, interactivity, and engagement to maintain user interest; (3) the incorporation of customizable health content to tailor interventions based on individual characteristics and preferences; (4) the use of gamification mechanisms, such as reward systems and progression tracking to promote adoption and sustained engagement with health services; and (5) the importance of privacy and data security as critical design considerations for ensuring user safety, confidentiality, and trust. Conclusions: The findings highlight the importance of user-centered design, contextualized health content, and gamification mechanisms in mHealth tools for Malaysian YMSM. These insights provide practical guidance for developing culturally appropriate gamified mHealth interventions for vulnerable populations by informing strategies to enhance user engagement, reduce HIV prevention fatigue, and support the well-being of YMSM in stigmatized contexts.

Nature, Published online: 07 September 2026; doi:10.1038/s41586-026-11103-4

Author Correction: AhR inhibition promotes axon regeneration via a stress–growth switch

The Drosophila whole male central nervous system connectome enables end-to-end analysis of sensorimotor circuits. Comparison with existing female datasets shows that brain-wide wiring differences between the sexes are concentrated in higher centers.

Nature Cancer, Published online: 01 September 2026; doi:10.1038/s43018-026-01243-x

Publisher Correction: Adjuvant personalized multivalent neoantigen DNA vaccination for MGMT unmethylated glioblastoma: a phase 1 trial

Oncogene, Published online: 01 September 2026; doi:10.1038/s41388-026-03969-5

Neuromedin U ‘innervation’ reprograms myeloid immunosuppression in neuroendocrine prostate cancer