Doping control analysis of emerging drugs in human plasma – identification of GW501516, S‐107, JTV‐519, and S‐40503
Bibliographic record
Abstract
An important aspect of preventive doping research is the rapid implementation of tests for emerging drugs with potential for misuse into routine doping control assays. New therapeutics of different classes such as PPARdelta-agonists (e.g. GW501516), ryanodine-calstabin-complex stabilizers (e.g. S-107 and JTV-519), and selective androgen receptor modulators (SARMs, e.g. S-40503) are currently used for the treatment of particular medical conditions such as metabolic syndrome, cardiac arrhythmia, debilitating diseases and osteoporosis, respectively. Due to their being at an early stage of clinical trials and the limited availability of data on the metabolism and possible renal elimination of the active drugs, the development of protocols for doping control analyses of plasma specimens could be an option for the detection of the circulating agents. The mass spectrometric fragmentation of four emerging drug candidates (GW501516, S-107, JTV-519, and S-40503) was elucidated by positive electrospray ionization and collision-induced dissociation using a high resolution/high accuracy mass spectrometer. A screening and confirmation procedure was established based on liquid chromatography/tandem mass spectrometry requiring a volume of 100 microL of plasma. Proteins were precipitated using acetonitrile, the specimens were centrifuged and the supernatant analyzed using a triple-quadrupole mass spectrometer employing multiple reaction monitoring of diagnostic ion transitions. The method was validated with regard to specificity, limits of detection (0.4-8.3 ng/mL), recoveries (72-98%), intraday and interday precisions (12-21%), and ion suppression/enhancement effects.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".