Targeting the Administration of Ecdysterone in Doping Control Samples
Bibliographic record
Abstract
Abstract Purpose The phytosteroid ecdysterone was recently reported to enhance performance in sports and may thus be considered as a substance of relevance in anti-doping control. To trace back an administration of ecdysterone from urine samples analytical properties have been investigated to assess its integration into initial testing procedures (ITP) in doping control laboratories. Methods Analytical properties of ecdysterone were evaluated using GC-QTOF-MS and LC-QTOF-MS. Its metabolism and elimination in human were studied using urines collected after administration. Results The detectability of ecdysterone by GC-MS (after derivatization) and/or LC-MS(/MS) has been demonstrated and sample preparation methods were evaluated. Dilute-and-inject for LC-MS(/MS) or SPE using Oasis HLB for GC-MS or LC-MS were found most suitable, while liquid-liquid extraction was hampered by the high polarity of ecdysteroids. Most abundantly, ecdysterone was detected in the post administration urines as parent compound besides the metabolite desoxy-ecdysterone. Additionally desoxy-poststerone was tentatively assigned as minor metabolite, however further investigations are needed. Conclusion An administration of ecdysterone can be targeted using existing procedures of anti-doping laboratories. Ecdysterone and desoxy-ecdysterone appeared as suitable candidates for integration in ITP. Using dilute-and-inject a detection of the parent compound was possible for more than two days after the administration of a single dose of ~50 mg.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".