Quantitation of Formoterol, Salbutamol, and Salbutamol-4′-O-Sulfate in Human Urine and Serum via UHPLC-MS/MS
Bibliographic record
Abstract
The adrenergic beta-2 agonists formoterol and salbutamol are used for the treatment of asthma and COPD but are also misused in sports competitions. Therefore, they are included in WADA regulations. Both drugs are mainly excreted in urine after administration via inhalation. A four-armed, double-blind cross-over clinical trial was conducted involving endurance-trained participants (12 females and 12 males). Inhalation dosages of 36 μg formoterol, 1200 μg salbutamol, a combination of both, or a placebo were administered before exercise. Serum and urine were collected after exercise and 3 and 24 h after administration. Here, we show the successful quantitation of formoterol, salbutamol, and its phase II metabolite salbutamol-4′-O-sulfate in all urine and serum samples using ultra-high performance liquid chromatography–tandem mass spectrometry. In the serum analysis, results of up to 14.2 pg/mL formoterol, 10.0 ng/mL salbutamol, and 21.4 ng/mL salbutamol-4′-O-sulfate (calculated as salbutamol equivalent) were found. In urine, maximum concentrations (after deglucuronidation) were 17.2 ng/mL formoterol, 948.5 ng/mL salbutamol, and 2738.5 ng/mL salbutamol-4′-O-sulfate. Sex-specific differences in serum concentrations as well as in urinary excretion were observed. The results pronounce the importance of the implementation and elucidation of phase II metabolites to quantitation methods in antidoping.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".