Screening for the synthetic cannabinoid JWH‐018 and its major metabolites in human doping controls
Bibliographic record
Abstract
Referred to as 'spice', several new drugs, advertised as herbal blends, have appeared on the market in the last few years, in which the synthetic cannabinoids JWH-018 and a C(8) homologue of CP 47,497 were identified as major active ingredients. Due to their reported cannabis-like effects, many European countries have banned these substances. The World Anti-Doping Agency has also explicitly prohibited synthetic cannabinoids in elite sport in-competition. Since urine specimens have been the preferred doping control samples, the elucidation of the metabolic pathways of these substances is of particular importance to implement them in sports drug testing programmes. In a recent report, an in vitro phase-I metabolism study of JWH-018 was presented yielding mainly hydroxylated and N-dealkylated metabolites. Due to these findings, a urine sample of a healthy man declaring to have smoked a 'spice' product was screened for potential phase-I and -II metabolites by high-resolution/high-accuracy mass spectrometry in the present report. The majority of the phase-I metabolites observed in earlier in vitro studies of JWH-018 were detected in this urine specimen and furthermore most of their respective monoglucuronides. As no intact JWH-018 was detectable, the monohydroxylated metabolite being the most abundant one was chosen as a target analyte for sports drug testing purposes; a detection method was subsequently developed and validated in accordance to conventional screening protocols based on enzymatic hydrolysis, liquid-liquid extraction, and liquid chromatography/electrospray tandem mass spectrometry analysis. The method was applied to approximately 7500 urine doping control samples yielding two JWH-018 findings and demonstrated its capability for a sensitive and selective identification of JWH-018 and its metabolites in human urine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".