Correlation Between Salivary, Platelet and Central Serotonin Levels in Children
Bibliographic record
Abstract
BACKGROUND: Serotonin (5-HT) is a neurotransmitter synthesized in both the central nervous system (CNS) and in enterochromaffin cells of the gut. 5-HT biosynthesis is separate between the periphery and the CNS. Any observed correlations between centrally and peripherally measured 5-HT remain to be elucidated. Previous efforts have looked for a noninvasive marker of central serotonin, including serotonin in whole blood, plasma, platelets, saliva, and urine; however, results are conflicting. AIM: Finding a noninvasive marker for central serotonin turnover that can be used for diagnosis and therapeutic monitoring in patients with primary neurotransmitter deficiencies. METHODS: Inclusion criterion was all children presenting with neurological symptoms whose clinical investigations included lumbar puncture (LP) for cerebrospinal fluid (CSF) collection and neurotransmitter metabolite analysis, were recruited. For central serotonin turnover, the serotonin metabolite 5-hydroxyindoleacetic acid (5HIAA) was used. Bivariate correlation between the serotonin levels in CSF (5HIAA), platelets, and saliva was calculated. RESULTS: Twenty-six patients (aged 6 months to 15 years) with various neurologic presentations had LP for CSF collection and neurotransmitter metabolite analysis as part of their clinical care. An additional salivary and blood sample was obtained at the same time. Eighteen patients had suitable samples for quantitative measure of serotonin. There was no correlation between platelet serotonin and CSF 5HIAA levels (Pearson's coefficient of correlation - PCC: 0.010) or between salivary serotonin and CSF 5HIAA (PCC: 0.258). There was a strong negative correlation between salivary and platelet serotonin (PCC: -0.679). CONCLUSION: Our findings suggest that salivary serotonin measurement is not a suitable noninvasive marker for measuring central serotonin turnover.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".