Genotype‐dependent metabolism of exogenous testosterone – new biomarkers result in prolonged detectability
Bibliographic record
Abstract
Testosterone (T) misuse still represents a major problem in sports drug testing. Many strategies have been developed and applied to routine doping controls in recent years to enable both to identify suspicious samples in initial testing procedures and to confirm the exogenous origin of urinary T by means of carbon isotope ratio (CIR) determinations. Depending on the tested individual's genotype of UGT2B17, significantly different amounts of T are glucuronidated and excreted, which results in unaffected T/epitestosterone ratios after T misuse in those subjects with the deletion/deletion polymorphism (del/del). The aim of this study was to investigate differences in metabolic pathways of orally administered T between persons of del/del and insertion/insertion (ins/ins) genetic polymorphism. Therefore, a recently established method using hydrogen isotope ratios together with high-resolution and high-accuracy mass spectrometry was applied after administration of deuterated T to n = 4 subjects including both genotypes. Participants collected urine specimens directly before and for up to 8 days after the application. Urine aliquots were prepared to yield unconjugated, glucuronidated, and sulphoconjugated fractions of urinary steroids. Besides the significant difference in the excretion of T-glucuronide, all measured metabolites varied rather on an individual basis than due to a genotype difference. New T metabolites (both methylated and de-methylated) were detected and investigated regarding their potential to enhance the screening for T misuse. Sulphoconjugated epiandrosterone was further identified as the biomarker allowing for a prolonged retrospective detection of T misuse by means of CIR determinations for up to 5 days compared to 1 day if currently applied sports drug testing procedures were used. 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
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".