Specific characterization of non‐steroidal selective androgen peceptor modulators using supercritical fluid chromatography coupled to ion‐mobility mass spectrometry: application to the detection of enobosarm in bovine urine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently under development for therapeutic purposes in human medicine, non‐steroidal selective androgen receptor modulators (non‐steroidal SARMs) are also known to impact growth associated pathways. As such, they present a potential for abuse in sports and food‐producing animals as interesting alternative anabolic substances. Forbidden since 2008 by the World Anti‐Doping Agency (WADA) these compounds are however easily available and could be (mis)used in livestock production as growth promoters. To prevent such practices, dedicated analytical strategies have to be developed for specific and sensitive detection of these compounds in biological matrices. Using an innovative analytical platform constituted of supercritical fluid chromatography coupled to ion mobility‐mass spectrometry, the present study enabled efficient separation and identification in urine of 4 of these drugs (andarine, bicalutamide, hydroxyflutamide, and enobosarm) in accordance with European Union criteria (Commission Decision 2002/657/EC). Besides providing information about compounds structure and behaviour in gas phase, such a coupling enabled reaching low limits of detection (LOD < 0.05 ng.mL −1 for andarine and limits of detection < 0.005 ng.mL −1 for the three others) in urine with good repeatability (CV < 21 %). The workflow has been applied to quantitative determination of enobosarm elimination in urine of treated bovine (200 mg, oral). Copyright © 2016 John Wiley & Sons, Ltd.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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 it