Development of mass spectrometry‐based methods for the detection of 11‐ketotestosterone and 11‐ketodihydrotestosterone
Bibliographic record
Abstract
The anabolic properties of 11-hydroxyandrostenedione (OHA4) and its physiologically active metabolites 11-ketotestosterone (KT) and 11-ketodihydrotestosterone (KDHT) have been discussed in several recent publications. Especially KT has become readily available via internet-based providers. No doping control methods for the detection of KT or KDHT exist, neither on the initial testing procedure level nor as confirmatory assay. Probing for the misuse of adrenosterone, the prohormone of OHA4, has already been addressed, and the suggested marker for its misuse was mainly the urinary concentration of 11-hydroxyandrosterone (OHA). In addition, for confirmation purposes, the carbon isotope ratios (CIR) were taken into consideration. The urinary concentration of OHA is highly variable, and the endogenous dilution after exogenous administration may therefore be considerable; hence, described approaches resulted in short detection times. In this study, the human metabolism of KT was investigated in order to provide additional means for the detection of KT and its prohormone OHA4. Two volunteers (one female and one male) orally administered 20 mg of KT each, and urine samples were collected for 5 days. Urinary concentrations of KT and its metabolites were investigated, and a reference population encompassing 220 male and female athletes was investigated in order to elucidate preliminary thresholds. As confirmation procedure, an isotope ratio mass spectrometry-based method was developed in order to determine the CIR of KT and relevant metabolites. The developed methods enabled the detection of exogenous KT for more than 20 h after a single oral administration, which is comparable to a single oral testosterone administration.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".