LC–MS/MS determination of the novel fentanyl analog, ortho-methylfentanyl, in drug-related toxicity casework: concentrations in ligated femoral blood
Bibliographic record
Abstract
The purpose of this study was to develop and validate an analytical method to chromatographically separate, identify, and quantify ortho-methylfentanyl (o-methylfentanyl) in postmortem blood. A combination of simple protein precipitation with liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to facilitate chromatographic separation of similar fentanyl analogs, including both meta (m-) and para (p-) methylfentanyl. The analytical range was 1 to 200 ng/mL; the method was validated in accordance with ANSI/ASB Standard 036. In addition to providing details of the validated analytical method, this study details the results of the analysis of 112 case samples (101 postmortem case samples and 11 antemortem case samples) from drug-toxicity related death investigations completed by the toxicology laboratory of the Office of the Chief Medical Examiner, Edmonton, Alberta, Canada. Analytical data is presented which compares concentrations of ortho-methylfentanyl in paired postmortem blood collected from both a visualized, ligated femoral vein together with postmortem blood collected directly from the heart, that is, visualized. Median blood ortho-methylfentanyl concentrations were found to be 5.94 ng/mL (femoral) and 8.04 ng/mL (cardiac). The median cardiac-to-femoral blood concentration ratio across the entire data set was 1.19. The study highlights the varied distribution in the body based on the median concentration of these drugs in postmortem blood.
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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 | 0.000 | 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 | 0.001 |
| 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".