Comparison of analytical approaches for the detection of oral testosterone undecanoate administration in men
Bibliographic record
Abstract
For antidoping laboratories, the determination of an illicit testosterone (T) administration in urine samples remains a difficult process as it requires the determination of the exogenous origin by carbon isotope ratios (CIRs) of testosterone and its metabolites. As a complement to the urinary analysis, targeting testosterone esters (e.g. testosterone undecanoate [TU]) in serum samples by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) could represent a simpler approach compared with isotope ratio mass spectrometry (IRMS). These two approaches both lead to the direct detection of the administration of exogenous T but with a difference in effort and complexity of the analysis. To compare the detection window obtained with the two strategies, serum and the corresponding urine samples collected from an administration study with oral TU were analysed. Results showed that, at all timepoints where the intact TU was detected in serum, the CIRs of urinary steroids were also not in agreement with an endogenous origin. IRMS analysis required more effort but resulted in slightly longer detection windows than the ester analysis. Finally, this comparison study showed that, in the presence of a suspicious urinary steroid profile, the LC-MS/MS steroid esters analysis in the corresponding serum samples can be very helpful. If steroid esters are not detected, the IRMS analysis can then be conducted on the urine sample afterwards. Overall, the combination of matrices might facilitate the detection of prohibited T administration in sports, especially for athletes with naturally low T/E ratios.
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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 | 0.001 |
| 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) | 0.000 | 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".