RF Safe promotes its QuantaCase™ (also called TruthCase™) as the “best anti-radiation phone case,” citing a review of 2025 market options, expert analyses, and user feedback from platforms like Reddit and Amazon. The post argues that while no case provides 100% protection, QuantaCase’s approach is more credible than “fake” anti-radiation cases and should be paired with exposure-reduction behaviors (e.g., distance and wired tech). It also references a claimed WHO 2025 position on animal cancer certainty, but provides no verifiable details in the excerpt.

This numerical study modeled RF exposure from WiFi/5G-type antennas near a 3D brain model with implanted brain pacemakers relevant to Parkinson’s disease. SAR and temperature increases were reported to remain below ICNIRP 2020 limits across modeled conditions, with maxima at a 90° antenna-to-brain angle. Despite compliance with SAR/temperature limits, the authors report modeled thermal strain and tissue displacement that could affect postoperative efficacy, leading them to recommend caution and increased distance from phones.

This animal study exposed zebrafish embryos to static electromagnetic fields for 63 days post-hatching across aquariums positioned 30–99 cm from the source, with an EMF-free control. The abstract reports strong shifts in sex distribution (including 100% female at the closest distance), markedly reduced survival in exposed groups, and histological liver and gonadal damage. The authors frame the findings as evidence of potential ecological risk via disrupted sex ratios and compromised health.

This study tested magnetic fields from tablets, laptops, smartphones, and household/leisure magnets against 13 cardiac implantable electronic device (CIED) models to assess magnet mode activation. It reports that these consumer devices can trigger magnet mode when in close proximity, with median activation distances of 5–6.5 mm for phones/tablets/laptops and mainly contact-level activation for household/leisure magnets. None of the tested devices activated magnet mode at distances of 20 mm or more, and the authors emphasize patient awareness of proximity-related risk.

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.