Carbon isotope ratio analysis of endogenous glucocorticoid urinary metabolites after cortisone acetate and adrenosterone administration for doping control
Bibliographic record
Abstract
Glucocorticoids are listed on the World Anti-Doping Agency (WADA) Prohibited List of substances. The detection of the administration of hydrocortisone and cortisone is complicated by the fact that the human body also produces these steroids naturally. Gas chromatography-combustion-isotope ratio mass spectrometry can be utilized to determine the use of endogenous glucocorticoids by measuring the carbon isotope ratio (CIR) of their resulting metabolites in human urine samples. A comprehensive sample preparation protocol for the analysis of endogenous glucocorticoid urinary metabolites was developed and validated, incorporating the use of high performance liquid chromatography (HPLC) for purification and chemical oxidation for derivatisation. Target compounds were tetrahydrocortisol and tetrahydrocortisone, and 11β-hydroxyetiocholanolone, 11-oxoetiocholanolone and 11β-hydroxyandrosterone, while pregnanediol functioned as the endogenous reference compound. Urine samples from a population of 50 volunteers were analyzed to determine CIR reference limits. Excretion studies of the endogenous glucocorticoid preparation cortisone acetate (25 mg oral) and the dietary supplement adrenosterone (75 mg oral) were conducted with six male individuals. Variable changes in steroid metabolite isotopic composition were found across subjects after administration. The study also revealed that CIR analysis of the major glucocorticoid metabolites tetrahydrocortisol and tetrahydrocortisone is necessary to unambiguously distinguish administration of cortisone and adrenosterone, the former officially restricted to out-of-competition use by athletes, the latter not being restricted at the current time. Moreover, this study reaffirms that CIR methods for the doping control of endogenous steroids should not rely upon a single ERC, as the administration of an appropriate precursor to that ERC could cause complications during analysis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".