Characterization of xylazine metabolism in rat liver microsomes using liquid chromatography–hybrid triple quadrupole–linear ion trap–mass spectrometry
Bibliographic record
Abstract
Xylazine is an α2 -adrenoceptor agonist and it is widely used in veterinary anesthesia in combination with ketamine. There is limited information on the metabolism of xylazine. A quantitative method for the determination of xylazine by HPLC-ESI/MS/MS was developed. The method consisted of a protein precipitation extraction followed by analysis using liquid chromatography electrospray tandem mass spectrometry. The chromatographic separation was achieved using a Thermo Betasil Phenyl 100 × 2 mm column combined with an isocratic mobile phase composed of acetonitrile, methanol, water and formic acid (60:20:20:0.4) at a flow rate of 300 μL/min. The mass spectrometer was operating in selected reaction monitoring mode and the analytical range was set at 0.05-50 μm. The precision (%CV) and accuracy (%NOM) observed were 2.3-7.2 and 88.2-96.4%. In vitro metabolism studies were performed in rat liver microsomes and results showed moderate cytochrome P450 affinity (Km = 10.1 μm) and a low metabolic stability of xylazine with a half-life of 4.1 min in rat liver microsomes. Five phase 1 metabolites were observed. The main metabolite observed was an oxidation of the thiazine moiety at m/z 235 and, to a lesser extent, we observed the formation of N-(2,6-dimethylphenyl)thiourea at m/z 181 and three distinctive hydroxylated metabolites at m/z 237. Further experiments with ketamine and ketoconazole strongly supported that the metabolism of xylazine to its main metabolite is mediated by CYP3A in rat liver microsomes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".