Influence of Indomethacin on Steroid Metabolism: Endocrine Disruption and Confounding Effects in Urinary Steroid Profiling of Anti-Doping Analyses
Bibliographic record
Abstract
Anabolic androgenic steroids (AAS) are prohibited as doping substances in sports by the World Anti-Doping Agency. Concentrations and concentration ratios of endogenous AAS (steroid profile markers) in urine samples collected from athletes are used to detect their administration. Certain (non-prohibited) drugs have been shown to influence the steroid profile and thereby sophisticate anti-doping analysis. It was shown in vitro that the non-steroidal anti-inflammatory drug (NSAID) indomethacin inhibits selected steroid-biotransformations catalyzed by the aldo-keto reductase (AKR) 1C3, which plays a key role in the endogenous steroid metabolism. Kinetic parameters for the indomethacin-mediated inhibition of the AKR1C3 catalyzed reduction in etiocholanolone were determined in vitro using two comparing methods. As NSAIDs are very frequently used (not only) by athletes, the inhibitory impact of indomethacin intake on the steroid metabolism was evaluated, and steroid profile alterations were detected in vivo (one male and one female volunteer). Significant differences between samples collected before, during or after the intake of indomethacin for selected steroid profile markers were observed. The presented results are of relevance for the interpretation of results from doping control analysis. Additionally, the administration of NSAIDs should be carefully reconsidered due to their potential as endocrine disruptors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.000 |
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".