Zeranol: doping offence or mycotoxin? A case‐related study
Bibliographic record
Abstract
Zeranol ((7R,11S)-7,15,17-trihydroxy-11-methyl-12-oxabicyclo[12.4.0]octadeca-1(14),15,17-trien-13-one, also referred to as 7α-zearalanol, Ralone®, Frideron®, Ralgro®, etc.) is a semi-synthetic estrogenic veterinary drug with growth-promoting properties. Its use regarding animal husbandry has been prohibited in the European Union since 1981 and, due to its anabolic effects, it is further recognized as a banned substance in sport. Numerous studies were conducted concerning the identification of the illicit application of zeranol to domestic livestock. These studies also considered the natural occurrence of zeranol as a metabolite of the mycotoxin zearalenone and the issue of differentiating both scenarios, i.e. illegal use or unintended contamination. Human sports drug testing authorities are facing comparable challenges since the deliberate misuse of the (for human application non-approved) drug should be discriminated from adverse analytical findings resulting from the biotransformation of the mycotoxin zearalenone possibly ingested with contaminated food. The active drug (zeranol), its major human metabolites (zearalanone, 7β-zearalanol) and the mycotoxin (zearalenone) plus its major and unique metabolic products (α-zearalenol, β-zearalenol) have been monitored in routine doping controls by means of validated gas chromatography-(tandem) mass spectrometry (GC-(MS/)MS) methods since 1996, and between 2005 and 2010 four samples providing suspicious signals were detected. In agreement with literature data, in vitro metabolism studies demonstrated the metabolic pathway from zearalenone towards zeranol (and common metabolites). In contrast, an administration study urine sample (collected after oral application of 20 mg of zeranol) yielded only ultra-trace amounts of zearalenone and its characteristic metabolites, which supported the assumption that a mycotoxin contamination caused the finding of zeranol in the doping control specimens rather than a misuse of the anabolic 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".