Detection of Synthetic Testosterone Use by Novel Comprehensive Two-Dimensional Gas Chromatography Combustion–Isotope Ratio Mass Spectrometry
Bibliographic record
Abstract
We report the first demonstration of comprehensive two-dimensional gas chromatography combustion-isotope ratio mass spectrometry (GC×GCC-IRMS) for the analysis of urinary steroids to detect illicit synthetic testosterone use, of interest in sport doping. GC coupled to IRMS (GCC-IRMS) is currently used to measure the carbon isotope ratios (CIRs, δ(13)C) of urinary steroids in antidoping efforts; however, extensive cleanup of urine extracts is required prior to analysis to enable baseline separation of target steroids. With its greater separation capabilities, GC×GC has the potential to reduce sample preparation requirements and enable CIR analysis of minimally processed urine extracts. Challenges addressed include online reactors with minimized dimensions to retain narrow peak shapes, baseline separation of peaks in some cases, and reconstruction of isotopic information from sliced steroid chromatographic peaks. Difficulties remaining include long-term robustness of online reactors and urine matrix effects that preclude baseline separation and isotopic analysis of low-concentration and trace components. In this work, steroids were extracted, acetylated, and analyzed using a refined, home-built GC×GCC-IRMS system. 11-Hydroxyandrosterone and 11-ketoetiocolanolone were chosen as endogenous reference compounds because of their satisfactory signal intensity, and their CIR was compared to target compounds androsterone and etiocholanolone. Separately, a GC×GC-quadrupole MS system was used to measure testosterone (T)/epitestosterone (EpiT) concentration ratios. Urinary extracts of urine pooled from professional athletes and urine from one individual that received testosterone gel (T-gel) and one individual that received testosterone injections (T-shots) were analyzed. The average precisions of δ(13)C and Δδ(13)C measurements were SD(δ(13)C) approximately ±1‰ (n = 11). The T-shot sample resulted in a positive for T use with a T/EpiT ratio of >9 and CIR measurements of Δδ(13)C > 5‰, both fulfilling World Anti-Doping Agency criteria. These data show for the first time that synthetic steroid use is detectable by GC×GCC-IRMS without the need for extensive urine cleanup.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".