Near‐Infrared Lifetime Nanothermometry Detects Microwave‐Induced Brain Heating
Bibliographic record
Abstract
Abstract In modern environments, the brain is continuously exposed to numerous external stimuli, including the microwave radiation used in telecommunication technologies. It has been suggested that the absorption of this radiation by brain tissue can induce local heating. Because brain temperature influences neural activity, metabolism, and overall brain function, microwave‐induced heating raises concerns over the safety of such technologies. Proper evaluation of the risks associated with microwave‐based technologies thus requires accurate quantification of heating in deep organs without disrupting their physiology. This study, demonstrates that microwave‐induced brain heating can be remotely monitored in vivo via luminescence thermometry using near‐infrared luminescent silver sulfide (Ag 2 S) nanoparticles. Their temperature‐dependent luminescence lifetime is a reliable thermometric parameter for the measurement of absolute brain temperature. The in vivo results offer direct, real‐time evidence of brain heating (up to 4 °C) under telecom exposure conditions (3 GHz). Moreover, they establish lifetime thermometry as a reliable, minimally invasive approach for investigating thermoregulation in deep tissues even under external electromagnetic stimulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".