Blunted Nocturnal Salivary Melatonin Secretion Profiles in Military-Related Posttraumatic Stress Disorder
Bibliographic record
Abstract
Background: Although sleep disturbances are a hallmark of posttraumatic stress disorder (PTSD), few studies have evaluated the role of dysregulated endogenous melatonin secretion in this condition. Methods: This study compared the sleep quality and nocturnal salivary melatonin profiles of Canadian Armed Forces (CAF) personnel diagnosed with PTSD, using the Clinician Administered PTSD Scale (CAPS score ≥50), with two healthy CAF control groups; comprising, a ‘light control’ (LC) group with standardized evening light exposure and ‘normal control’ (NC) group without restriction. Participants were monitored for 1-week using wrist actigraphy to assess sleep quality, and 24-h salivary melatonin levels were measured by immunoassay (sampling every 2 h) on the penultimate day in a dim-light (<5 lux) laboratory environment. Results: A repeated measures design showed that nocturnal (mean ± SEM) melatonin concentrations for LC were higher than both HC (p=.03) and PTSD (p=.001) with no difference between PTSD and HC. Relative to PTSD, HC had significantly higher melatonin levels over a 4-h period (01 h to 05 h), whereas the LC group had higher melatonin levels over an 8-h period (23h to 07 h). Actigraphic sleep quality parameters were not significantly different between healthy controls and PTSD patients, likely because the PTSD patients were taking sleeping medications. Conclusions: Blunted nocturnal melatonin secretion in military PTSD in association with sleep disturbances was consistent with previous findings showing lower melatonin after exposure to trauma and suggestive of severe chronodisruption. Future studies targeting the melatonergic system for therapeutic intervention may be beneficial for treatment resistant PTSD.
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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 | 0.001 |
| 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".