Decreased urinary level of melatonin as a marker of disease severity in patients with multiple sclerosis.
Bibliographic record
Abstract
Melatonin has both pro-inflammatory and anti-inflammatory properties depending on the stage of inflammation. Despite its therapeutic effect in alleviation of some symptoms of multiple sclerosis; the precise role of melatonin in MS pathogenesis remains a topic of debate. The aim of this study was to measure the urine level of one of melatonin products which is an index of serum melatonin level, in MS patients in the acute phase of relapse and control patients. We also analyzed different clinical and cognitive indices in order to find any correlation with melatonin level. Twenty eight patients who were diagnosed as relapsing-remitting MS, according to the revised McDonald criteria, along with 10 age- and sex-matched control subjects were recruited in our study. Here we showed that urine 6-sulphatoxymelatonin levels (aMT6s; the major metabolite of melatonin) were significantly lower in MS patients compared to control group. Interestingly, urine aMT6s levels significantly correlated with MS Functional Composite score, but not Expanded Disability Severity Score. Based on above findings, there might be new hope in developing a quantitative and objective measure to assess the MS severity especially in neurodegenerative diseases. However, our results should be analyzed cautiously. We didn't evaluate simultaneous level of 25-OH Vitamin D. It has been recently reported that there is a negative correlation between melatonin and vitamin D levels. Further studies are needed to confirm this hypothesis.
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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 | 0.001 | 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".