Characterization of xylazine metabolism in rat liver microsomes using liquid chromatography–hybrid triple quadrupole–linear ion trap–mass spectrometry
Why this work is in the frame
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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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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it