New Spectrofluorimetric Method for Determining Serotonin: Application to Human Urine
Bibliographic record
Abstract
In this present paper, we investigate the development of simple, rapid, accurate, reproducible and sensitive methods for the determination of serotonin (5-HT) in urine. For this purpose stationary fluorescence was used as method. With regard to the analysis of serotonin, the liquid-liquid extraction (LLE) solid phase extraction (SPE) and standard addition procedures were used. Several physicochemical factors affecting the sensitivity of the fluorescence intensity of serotonin were optimized, including the system of solvent (organic, micellar), the pH and the salts. The study of the analytical performances of the method led to very low limits of detection (LOD) varying between 0.1 and 3 ng/mL and to limits of quantification (LOQ) ranging between 0.4 and 10 ng/mL. This confirms the sensitivity of the method. Thus the low values of standard deviations (DRS) (between 0.3 and 6.6%) testify the good reproducibility of the measurements with satisfactory covering rate (89 to 111%). Accordingly, our results show that the spectrofluorimetric method is simple, fast and sensitive and can be applied to the routine analysis and does not require expensive equipment nor tiresome chemical pretreatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".