Analysis of tolvaptan and its metabolites in sports drug testing by high‐performance liquid chromatography coupled to tandem mass spectrometry
Bibliographic record
Abstract
Tolvaptan is prohibited by the World Anti-doping Agency (WADA) under class S5 - Diuretics and masking agents. Less than 1% of the administrated dose is excreted by humans in urine. Knowledge concerning the metabolism in humans, and especially the excretion of metabolites in human urine, is limited. An analysis method based on the dilute-and-shoot approach using high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) for detection was developed and validated. Ion transitions, which are part of this method, can easily be included in already existing screening methods used in routine doping analysis for the detection of diuretics. After administration of a single dose of tolvaptan to one male subject, low concentrations of the drug itself could be detected in urine samples over a time period of 24 h. In addition, hydroxyl metabolites of tolvaptan and one carboxyl metabolite with a cleaved benzazepine ring system were identified. These metabolites showed detection times of up to 150 h. An inclusion of these metabolites in the methods used in doping control analysis seems therefore to be of value. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".