Playing more and more, struggling to cut back, or continuing to game despite its negative impact on everyday life can all be signs of gaming disorder. But what about women who play video games and may be overlooked by conventional diagnostic tools? A study by the University of Geneva (UNIGE) sheds light on why female gamers can remain under the radar and highlights the distinctive features of their gaming experiences. The study found that participants tended to favour immersive games over competitive ones and were less likely to identify with the traditional image of a gamer. These findings, published in European Psychiatry, could help inform more tailored approaches to the prevention and treatment of gaming disorder.

A study examines how Shanghai's college admission reform has reshaped school practices, student motivation, and learning behaviors. Drawing on classroom observations and interviews with teachers and students, the research shows that expanded subject choices and broader evaluation criteria have created new opportunities for students to explore interests, connect learning with future aspirations, and develop more active approaches to learning. The study also highlights the importance of continued support in helping students make meaningful choices within a more flexible education system.

Researchers at Fudan University, in collaboration with Zhejiang Cancer Hospital (Hangzhou Institute of Medicine, Chinese Academy of Sciences) and Washington University in St. Louis, have released bacNeo, the first comprehensive computational toolkit dedicated to identifying bacteria-derived neoantigens in human cancers. The framework combines three modules, BACC for bacterial component classification, BACH for HLA allele typing, and BACP for bacterial peptide prioritization, into a single one-stop pipeline that accommodates metagenomic, metatranscriptomic, bulk and single-cell sequencing, and mass spectrometry data. A novel scoring system, SPARK (Score for Peptide Antigenicity Recognition and Kinetics), weights TAP transport efficiency against HLA-peptide binding affinity and reaches an area under the ROC curve of 0.81 on experimentally validated peptide-HLA datasets. The work, published in iMetaMed, provides a reproducible and modular foundation for systematic bacterial neoantigen discovery and supports the design of therapeutic vaccines, chimeric antigen receptor (CAR) T-cell therapies, and immune checkpoint blockade strategies across diverse cancer types.

Precision oncology is evolving from a predictive paradigm towards adaptive decision-making. This review presents a forward-looking conceptual framework for a Closed-Loop Intelligent Oncology System (CIOS), which aims to support iterative evaluation of candidate treatment strategies by updating a patient-specific digital twin.

With rapid advances in synthetic biology and genetic engineering, genetically engineered bacteria (GEB) have emerged as a promising platform for biological therapy, addressing key limitations of conventional drug delivery systems and demonstrating significant clinical potential. By leveraging a modular design framework, GEB exhibits high biocompatibility and programmability, enabling precise genetic modifications for targeted delivery, dynamic responsiveness, and sustained therapeutic effects. This review systematically examines the therapeutic development of GEB, focusing on its pivotal roles in tumor therapy, inflammatory bowel disease (IBD), metabolic disorders, and the treatment of complex infections. It outlines key design strategies—including sensing, payload release, and biocontainment modules—as well as evaluation frameworks and mechanisms of action. We also discuss major challenges to clinical translation, such as the limited availability of clinically validated chassis strains, the balance between bacterial fitness and therapeutic load, and persistent biosafety concerns. Future progress will depend on advancements in high-precision genome editing, intelligent responsive systems, and interdisciplinary collaboration to bridge the gap between preclinical promise and clinical application. This review aims to provide an up-to-date reference to facilitate the translation of GEB from laboratory discoveries to viable clinical applications in precision medicine.

In this study, researchers profiled the human skin microbiome through an integrated analysis of public datasets, revealing high diversity and distinct co‐occurrence patterns that enabled classification into several modules. Key host and environmental factors were assessed for associations with microbiome composition, with lifestyle habits such as alcohol intake and physical activity emerging as particularly impactful. These findings were subsequently validated in a local cohort, showing strong consistency. Using machine learning, the team further identified potential microbial biomarkers and demonstrated accurate bidirectional prediction between skin microbiome profiles and alcohol intake.