Development of a qualitative liquid chromatography/tandem mass spectrometric method for the detection of narcotics in urine relevant to doping analysis
Bibliographic record
Abstract
A new screening procedure for 18 narcotics in urine for anti-doping purposes has been developed using liquid chromatography/triple quadrupole mass spectrometry (LC/MS). Electrospray ionization (ESI) was used as interface. Infusion experiments were performed for all substances to investigate their mass spectrometric behaviour in terms of selecting product specific ions. These product ions were then used to develop a tandem mass spectrometric method using selected reaction monitoring (SRM). For the LC/MS analysis, chromatography was performed on an octadecylsilane column. The total run time of the chromatographic method was 5.5 min. For the sample preparation prior to LC/MS analysis, the urine samples were liquid-liquid extracted at pH 9.5 after overnight enzymatic hydrolysis. Two extraction solvents were evaluated: dichloromethane/methanol 9/1 (v/v), which is currently used for the extraction of narcotics, and diethyl ether, used for the extraction of steroids. With diethyl ether the detection limits for all compounds ranged between 0.5 and 20 ng/mL and with the mixture containing dichloromethane the detection limits ranged between 0.5 and 10 ng/mL. Taking into account the minimum required performance limits of the World Anti-Doping Agency of 200 ng/mL for narcotics, diethyl ether can also be considered as extraction solvent for narcotics. Finally, the described method was applied to the analysis of urine samples previously found to contain narcotics by our routine gas chromatography/mass spectrometry (GC/MS) method.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.013 |
| 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".