Isotope ratio mass spectrometry in antidoping analysis: The use of endogenous reference compounds
Bibliographic record
Abstract
Rationale Isotope ratio mass spectrometry (IRMS) is an analytical technique required by the World Antidoping Agency (WADA) before releasing of an adverse finding for the abuse of pseudoendogenous steroids (i.e. testosterone). For every single individual, the delta 13 C values (‰) of the selected target compounds (TCs, i.e. testosterone and/or its precursors/metabolites) are compared with those of endogenous reference compounds (ERCs). The aim of this work is to investigate the individual variation in the delta values of four different commonly used ERCs to establish the maximum acceptable variation, in order to detect potential outliers. Methods Routine urine samples collected for antidoping purposes were submitted to IRMS confirmation. After a specific liquid chromatographic purification of the analytes of interest, the final extracts were analyzed by gas chromatography/combustion (GC/C)‐IRMS. The selected ERCs monitored were pregnanediol, pregnanetriol, 11‐keto‐etiocholanolone and 11β‐hydroxyandrosterone. The obtained 13 C delta values were statistically analyzed to evaluate their inter‐ and intra‐individual distribution. Results The delta values of the ERCs studied showed a normal distribution and no major differences among genders were observed. As expected, there are differences depending on the geographical origin of the samples, reflecting different dietary habits and food sources. The intra‐individual dispersion, expressed as the standard deviation (SD) of the values of the studied ERCs, did not greatly exceed the instrumental error (0.5‰), demonstrating the good preservation of the delta values along the metabolic pathway. Conclusions For the selected ERCs of non‐sporting volunteers and the urinary specimens from more than 1000 sportsmen, we can propose a maximum SD of 0.54‰ and range of 1.2‰ for delta 13 C values as acceptance criteria to detect potential outliers. These cases can be caused by the external masking effect of the administration of a substance modifying the delta values or outliers due to unforeseen procedural artifacts.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".