A randomized clinical trial of the impact of melatonin on influenza vaccine: Outcomes from the melatonin and vaccine response immunity and chronobiology study (MAVRICS)
Bibliographic record
Abstract
Vaccine immunogenicity is affected by a variety of factors. Melatonin has been reported to affect immune responses to vaccines and infection. This was a randomized open-label trial – in which adults scheduled to receive the influenza vaccine were randomized to 5 mg melatonin or control to evaluate the effect of post-vaccination melatonin on humoral (hemagglutination-inhibition assays, HAI) and cellular (FluoroSpot) vaccine-specific cytokine responses 14–21 days post-vaccination. A total of 108 participants (melatonin treatment group: 53; control group: 55) completed the study. The groups were similar in baseline characteristics, including sleep as measured by the Pittsburgh Sleep Quality Index. Seroconversion rates or geometric mean fold rises (GMFR) in HAI titers did not vary by treatment group. There were also no statistically significant differences between pre- and post-vaccination levels of interferon gamma (IFN-γ) or granzyme B (GzB) by treatment; however, there was a significantly higher fold rise in the double secretor (IFN-γ + GzB) peripheral blood mononuclear cells for influenza vaccine in subjects taking daily melatonin (GMFR 1.7; 95% CI 1.3, 2.3) compared to those who did not (GMFR 0.9; 95% CI 0.7, 1.1) (p < .001). Daily melatonin for 14 days post-influenza vaccination significantly increased the cellular co-expression of IFN-γ + GzB; however, there were no other differences in the cellular or humoral responses. Future studies of the potential utility of melatonin for enhancing vaccine response with larger sample sizes may help elucidate candidate mechanisms for these limited effects, including any interactions with the circadian system.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".