Enantioselective disposition of (R)‐salmeterol and (S)‐salmeterol in urine following inhaled dosing and application to doping control
Bibliographic record
Abstract
Salmeterol (USAN, INN, BAN) is a long-acting beta2-adrenoceptor agonist (LABA) widely used in the treatment of airways disease. Although salmeterol is permitted via inhalation by athletes and supratherapeutic dosing may enhance performance, no urine threshold has been established by the World Anti-Doping Agency (WADA). Salmeterol is a chiral compound consisting of (R)- and (S)-enantiomers, normally administered as racemic (rac-) mixture via inhalation. Levels of rac-salmeterol in urine are often below detectable levels and there is surprisingly little information regarding the enantioselectivity of salmeterol pharmacokinetics. In this study, subjects inhaled either 50 (n = 6) or 200 µg (n = 4; generally regarded as maximum therapeutic dose) of salmeterol and urine was then collected for 24 h and analyzed by enantioselective ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Maximum rac-salmeterol urine concentrations were obtained at 2 h for both doses with medians of 0.084 ng/mL after the 50 µg dose and 2.1 ng/mL after the 200 µg dose, with an individual maximum of 5.7 ng/mL. Levels were detectable at 24 h for both doses. Salmeterol displayed enantioselective pharmacokinetics, with a mean ± SD log (S):(R) = 0.055 ± 0.025 (P < 0.0001) equivalent to (S):(R) of 1.13. In conclusion, rac-salmeterol by inhalation exhibits modest enantioselectivity in urine following single dose administration and can be detected following a single 50 µg dose for up to 24 h after inhalation. The present findings are of relevance if a urine threshold limit is to be introduced for salmeterol on the list of prohibited substances. The application of an enantiomer ratio analysis may offer improved discriminatory detection capability for doping control analysis applications. 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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".