Ahead of World Mental Health Day on October 10, attention is turning to the question of what causes psychological strain at work. A study by Bielefeld University shows that inappropriate tasks are not the only factor associated with exhaustion. Changes in day-to-day work can also leave employees feeling exhausted, even when the number of burdensome tasks decreases. Perceived uncertainty plays an important role.

Microplastics and nanoplastics are increasingly detected in the environment and human biological samples, raising concerns about their potential health effects. A new review published in Med Research highlights particle size as a key factor determining how these plastic particles interact with biological barriers and organs. Nanoplastics can more readily enter cells and subcellular structures, where they are associated with mitochondrial dysfunction, oxidative stress, ferroptosis, and inflammatory signaling. Larger microplastics, in contrast, primarily cause mechanical barrier disruption and persistent immune activation. The review compares these size-dependent effects across the intestine, liver, kidney, lung, and brain and discusses emerging intervention strategies and major gaps in translating experimental findings to human health.

OmicsGWAS is a comprehensive post-GWAS analysis platform that provides an automated workflow from data preprocessing to result visualization. It supports standardized conversion of GWAS summary statistics and integrates multi-omics datasets, including eQTL, pQTL, and mQTL data. By incorporating methods such as Mendelian randomization, colocalization analysis, and SMR, the platform enables systematic exploration of genotype–phenotype relationships, comorbidity mechanisms, and potential drug targets. OmicsGWAS improves the efficiency, standardization, and reproducibility of post-GWAS studies and facilitates precision medicine research.

Mendelian randomization leverages genetic variants to mitigate confounding bias in causal inference. This paper systematically reviews the methodological evolution of Mendelian randomization, elaborates on its expanding applications in epidemiology and drug target validation, and identifies future research directions to address existing biases via dynamic analysis, multi-omics integration, and trans-ethnic data harmonization.

Four decades after the 1986 nuclear disaster, researchers at Leibniz University Hannover and the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) examined six tiny, highly radioactive fragments that were released from the destroyed reactor in Ukraine in the wake of the incident. Analyses show that these “hot particles” are far more stable than had previously been assumed. The findings could allow for more precise assessments of the health risks posed by such radioactive particles (DOI: 10.1016/j.jhazmat.2026.141533).

Surgical telemedicine includes proactive, data-driven preoperative screening and risk stratification beyond traditional reactive consultation; intraoperative telepresence enhanced by robotics that enables collaboration to meet established technical thresholds; and postoperative pathways that clearly distinguish safety-oriented surveillance from function-oriented tele-rehabilitation.

It mitigates regional imbalances in medical resources, overcomes geographical limitations, and forms a health-centered, workflow-oriented full-cycle paradigm.

Its large-scale application is constrained by technical, economic, regulatory and ethical barriers.

This review integrates the heterogeneous mechanisms of diabetic peripheral neuropathy (DPN) into a three-stage framework: metabolic dysregulation, chronic inflammation, and overt neuronal damage. Within this framework, six representative DPN subtypes are mapped to disease progression and linked through redox disequilibrium as a central mechanistic hub. The review further summarizes genetic, epigenetic, and metabolic risk factors, evaluates current stage-aligned therapeutic strategies, and discusses cold atmospheric plasma (CAP) as an emerging redox-modulating intervention that warrants further preclinical and clinical evaluation.

Skin cancer is a global health challenge, with nearly 1.5 million new cases diagnosed in 2024 according to World Health Organization (WHO) data. In response, the University of Alicante (UA) and the Sant Joan d’Alacant University Hospital have collaborated to launch MEL-IA (MobilE skin Lesion dIAgnosis), an artificial intelligence system designed to automate the classification of skin lesions. The MEL-IA system achieves an overall accuracy of 86 %.