This exposure assessment measured outdoor micro-environment RF-EMF levels in daily-life settings across urban and suburban locations in Japan using a portable device (50 MHz–6 GHz) with GPS. Reported exposure levels were higher in urban areas, with railway stations showing the highest levels among the environments measured. The authors emphasize the need for further comprehensive studies and frame prolonged RF-EMF exposure as an ongoing public health concern.

This in vitro study used LC-MS metabolomics to assess how continuous versus intermittent RF-EMF irradiation affects mouse Leydig (TM3) and spermatogonia (GC-1) cells. The authors report stronger metabolic disturbances in TM3 cells under continuous exposure, including changes in amino acid and glutathione-related pathways, while intermittent exposure mainly affected fatty acyl and purine-related metabolism. GC-1 cells were reported to be less sensitive, and ADP changes were proposed as a potential metabolic signature. The authors interpret these metabolic disturbances as suggesting potential reproductive health risks.

This animal study used metabolomics to assess metabolic changes in male Drosophila melanogaster exposed to 3.5 GHz RF-EMF at 0.1, 1, and 10 W/m². It reports disruptions in four metabolic pathways and 34 differential metabolites, with significant decreases in several metabolites including GABA, glucose-6-phosphate, and AMP. The authors interpret the findings as suggesting RF-EMF-related metabolic disturbance, while noting no clear dose-dependent pattern.

This exposure assessment measured personal RF electric field strength in multiple indoor and outdoor micro-environments in Malaysia using an ExpoM-RF 4 meter and modeled exposure with machine learning (FCNN, XG Boost) and linear regression. Reported exposures were usually below the stated public limit (61.4 V/m), but maximum values in dense urban areas with many base stations were reported to approach 56.7365 V/m. The authors frame near-threshold maxima in high-density areas as a potential health risk and recommend caution and monitoring.

This ecological analysis used a public health database of myocardial infarction admissions in São José dos Campos, Brazil (1998–2005) and categorized geomagnetic activity using the planetary Kp index. The abstract reports a higher relative frequency of MI admissions during disturbed geomagnetic conditions compared with quiet periods, with a stronger association in women. Unsupervised k-means clustering reportedly supported the sex-specific pattern.

This review/overview argues that ultrafine particulate matter and industrial nanoparticles can reach the brain and accumulate in sleep and arousal regulatory regions, including orexinergic neuron hubs. It reports that ferromagnetic particles in these regions show motion responsive to low-intensity electromagnetic fields (30–50 μT) and describes links to sleep disturbances and neurodegenerative disease markers in young urban residents. The authors frame combined air pollution nanoparticle exposure and low-level EMF as a significant threat and call for monitoring and protective strategies.

This analytical study evaluated machine learning models (SVM and Random Forest) to predict health symptoms in adults living near mobile phone base stations. The SVM model reportedly achieved high predictive performance for headache, sleep disturbance, dizziness, vertigo, and fatigue, and outperformed Random Forest and prior models. The abstract concludes that proximity to base stations is connected with increased prevalence of several symptoms and emphasizes distance, age, and duration of residence as key predictors.