Prevention of melatonin suppression by nocturnal lighting: relevance to cancer
Bibliographic record
Abstract
The decreased melatonin production in humans and animals caused by environmental lighting, especially short wavelength lighting (between 470 and 525 nm) has been shown to be associated with an increased risk of cancer. The purpose of this study was to investigate whether blocking light in this wavelength range under bright light may prevent the suppression of melatonin, which could help to prevent cancer. Optical filter lenses were designed, allowing selective exclusion of all wavelengths below 530 nm. Salivary melatonin levels were measured under dim light (<5 lux), bright light (800 lux) and filtered light (800 lux) at hourly intervals between 2000 and 0800 h in 11 healthy young male participants (mean age 23.5+/-1.5 years). The measurements were taken during three nonconsecutive nights over a 2-week period. The Dim Light Melatonin Onset test was used as a marker of circadian phase. Nine of the 11 participants demonstrated preserved melatonin levels in filtered light similar to their dim light secretion profile. With filtered light, the participants had a mean relative amount of melatonin of 91.2 (P>0.05 between dim light and experimental condition). Unfiltered bright light drastically suppressed melatonin production with a mean relative amount of melatonin of 25.4 (P<0.05 between dim light and experimental condition). Preventing melatonin deficiencies using lenses that block light of low wavelength from reaching the retina presents a cost-effective, practical solution to the problem of increased malignancy rates in shift workers.
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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) | 0.000 | 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".