Melatonin supplementation and oxidative DNA damage repair capacity among night shift workers: a randomised placebo-controlled trial
Bibliographic record
Abstract
OBJECTIVES: A decreased ability to repair oxidative DNA damage, due to melatonin suppression, is a compelling mechanism by which night shift workers are at an increased risk of cancer. We sought to determine if melatonin supplementation would improve oxidative DNA damage repair among night shift workers. METHODS: We conducted a parallel-arm randomised placebo-controlled trial of melatonin supplementation among 40 night shift workers. Supplements were consumed before engaging in day sleep over a 4-week period. All urine excreted during a representative day sleep and night work period before and during the intervention period was collected for measurement of creatinine-adjusted 8-hydroxy-2'-deoxyguanosine (8-OH-dG) as an indicator of oxidative DNA damage repair capacity, with higher concentrations indicating better repair. Linear regression models were used to analyse the association between ln-transformed 8-OH-dG concentration and intervention status during day sleep and night work. RESULTS: The melatonin intervention was associated with a borderline statistically significant 1.8-fold increase in urinary 8-OH-dG excretion during day sleep (95% CI 1.0, 3.2, p=0.06). No statistically significant difference in 8-OH-dG excretion was observed during the subsequent night shift (melatonin vs placebo excretion ratio=0.9; 95% CI 0.6, 1.5; p=0.7). CONCLUSIONS: Our results suggest that melatonin supplementation improves oxidative DNA damage repair capacity among night shift workers. Future larger-scale trials are needed to evaluate the impact of varying doses of melatonin supplements and examine the impacts of longer-term use of melatonin supplements by night 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".