Measurement of melatonin in body fluids: Standards, protocols and procedures
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The circadian rhythm of melatonin in saliva or plasma, or of the melatonin metabolite 6-sulfatoxymelatonin (a6MTs) in urine, is a defining feature of suprachiasmatic nucleus (SCN) function, the body's endogenous oscillatory pacemaker. The primary objective of this review is to ascertain the clinical benefits and limitations of current methodologies employed for detection and quantification of melatonin in biological fluids and tissues. DATA IDENTIFICATION: A search of the English-language literature (Medline) and a systematic review of published articles were carried out. STUDY SELECTION: Articles that specified both the methodology for quantifying melatonin and indicated the clinical purpose were chosen for inclusion in the review. DATA EXTRACTION: The authors critically evaluated the methodological issues associated with various tools and techniques (e.g. standards, protocols, and procedures). RESULTS OF DATA SYNTHESIS: Melatonin measurements are useful for evaluating problems related to the onset or offset of sleep and for assessing phase delays or advances of rhythms in entrained individuals. They have also become an important tool for psychiatric diagnosis, their use being recommended for phase typing in patients suffering from sleep and mood disorders. Additionally, there has been a continuous interest in the use of melatonin as a marker for neoplasms of the pineal region. Melatonin decreases such as found with aging are or post pinealectomy can cause alterations in the sleep/wake cycle. The development of sensitive and selective methods for the precise detection of melatonin in tissues and fluids has increasingly been shown to have direct relevance for clinical decision making. CONCLUSIONS: Due to melatonin's low concentration, as well as the coexistence of numerous other compounds in the blood, the routine determination of melatonin has been an analytical challenge. The available evidence indicates however that these challenges can be overcome and consequently that evaluation of melatonin's presence and activity can be an accessible and useful tool for clinical diagnosis.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".