<i>In vitro</i> ketamine CYP3A‐mediated metabolism study using mammalian liver S9 fractions, cDNA expressed enzymes and liquid chromatography tandem mass spectrometry
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Bibliographic record
Abstract
Ketamine is widely used in medicine in combination with several benzodiazepines, including midazolam. The objectives of this study were to develop a novel HPLC-MS/selected reaction monitoring (SRM) method capable of quantifying ketamine and norketamine using an isotopic dilution strategy in biological matrices and study the formation of norketamine, the principal metabolite of ketamine with and without the presence of midazolam, a well-known CYP3A substrate. 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 3.9-7.8 and 95.9-111.1% respectively. The initial rate of formation of norketamine was determined using various ketamine concentrations and Km values of 18.4, 13.8 and 30.8 μm for rat, dog and human liver S9 fractions were observed, respectively. The metabolic stability of ketamine on liver S9 fractions was significantly higher in human (T1/2 = 159.4 min) compared with rat (T1/2 = 12.6 min) and dog (T1/2 = 7.3 min) liver S9 fractions. Moreover significantly lower IC50 and Ki values observed in human compared with rat and dog liver S9 fractions. Experiments with cDNA expressed CYP3A enzymes showed that the formation of norketamine is mediated by CYP3A but results suggest an important contribution from other isoenzymes, most likely CYP2C particularly in rat.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it