Investigations on changes in <sup>13</sup>C/<sup>12</sup>C ratios of endogenous urinary steroids after pregnenolone administration
Bibliographic record
Abstract
For the detection of possible misuse of naturally occurring anabolic androgenic steroids like testosterone (T), anti-doping laboratories use a combination of two techniques. One is molecular steroid profiling to evaluate urinary steroid concentrations and normal diagnostic ratios. The other is isotope ratio mass spectrometry (IRMS), in which the ¹³C/¹²C ratios of target analytes like T are compared to the ¹³C/¹²C ratios of endogenous reference compounds (ERCs). The ¹³C/¹²C of the most commonly used ERC, pregnanediol (5β-pregnane-3α,20α-diol, PD), can be influenced by administration of pregnenolone (3β-hydroxy-pregn-5-en-20-one, PREG). Therefore PREG administration bears the potential to circumvent IRMS testing for doping control samples. In order to investigate the influence of PREG on PD and on other urinary excreted steroids, administration studies with oral and transdermal application of PREG were carried out. The influence of PREG administration on concentrations and ¹³C/¹²C ratios of all investigated target analytes was negligible. Only PD and 5β-pregnan-3α-ol-20-one (3aP) showed significant depletion in both their glucuronidated and sulfated steroids. The results suggest that appropriate alternative ERCs are: 11β-hydroxy-androsterone/etiocholanolone, 5β-pregnane-3α,17,20α-triol, pregn-5-ene-3β,17,20α-triol and cholesterol. Due to its properties to disguise the misuse of anabolic steroids by influencing the ¹³C/¹²C ratio of PD, PREG should be considered to be added to the World Anti-Doping Agency (WADA) list of prohibited substances as a masking agent.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".