Evaluation of endogenous steroid sulfates and glucuronides in urine after oral and transdermal administration of testosterone. Part I: Male participants
Bibliographic record
Abstract
The detection of the performance-enhancing drug testosterone (T) remains a significant challenge in doping control analysis. Longitudinal monitoring through the steroidal Athlete Biological Passport (ABP) is a valuable tool for T detection, but further research is needed to enhance its efficacy. Phase II metabolites of endogenous anabolic androgenic steroids (EAAS), including glucuronides and sulfates, have gained increasing interest as potential new biomarkers for the steroidal ABP. Notably, sulfate metabolites have demonstrated higher sensitivity to oral, transdermal, and intramuscular T administration, with extended detection windows compared to traditional biomarkers. However, before incorporating these promising biomarkers into urinary steroid profiling, it is essential to address the metabolic variations associated with different T administration methods, as well as differences related to ethnicity and sex. In this part of the study, we investigate the effects of oral and transdermal T administration on conventional biomarkers and phase II EAAS metabolites in male participants. Sulfate ratios indicated higher sensitivity to multiple administrations of testosterone undecanoate (TU) tablets and T gel, significantly prolonging detection times compared to conventional steroid profile biomarkers. Specifically, sulfate ratios such as androsterone sulfate (AS)/testosterone sulfate (TS) and epiandrosterone sulfate (EpiAS)/TS enabled detection for an average of 20 days following the last oral TU dose and at least 16 days after the last transdermal T application. These findings provide further evidence that incorporating sulfate EAAS metabolites into steroid profiling enhances detection capabilities. For advanced T doping detection, sulfate metabolites should be considered essential biomarkers in the steroid profile.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".