Bibliographic record
Abstract
The possible performance-enhancing effects and medical benefits of ecdysterone (ECDY) have been discussed several times throughout the last decades. In 2020, the World Anti-Doping Agency include ECDY in their monitoring programme and continued this prevalence study until now. Only little is known about the human metabolism of ECDY besides the first study performed on human subjects in the field of sports drug testing that was already conducted in 2001. Aim of this study was the in-depth investigation on human ECDY metabolism to improve its detectability and to support the decision-making processes as to how ECDY can be implemented most effectively into sports drug testing regulations. In a first trial, one male volunteer was administered with threefold deuterated ECDY to enable the detection and potential identification of all urinary metabolites still comprising the deuterium label by employing hydrogen isotope ratio mass spectrometry and high-resolution/high-accuracy mass spectrometry. Samples were collected for up to 14 days, and metabolites excreted unconjugated, glucuronidated, and sulphated were investigated. The detected deuterated metabolites were confirmed in a second administration trial encompassing two male and one female volunteers. After the administration of 50 mg of unlabelled ECDY, urine samples were collected for up to 7 days. Besides the already described urinary metabolites of ECDY, more than 20 new metabolites were detected encompassing all expected metabolic conversions including side chain cleavage at C21. A large interindividual variation in the amounts of excreted metabolites was visible, and considerable differences in abundances of early- and late-excretion phase metabolites were observed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".