<i>In vitro</i> metabolism of specific CYP2D and CYP3A opioid substrates using rat liver S9 fractions and mass spectrometry reveal a severe metabolic impairment with increasing age
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Codeine and oxycodone are opioids used to alleviate pain. The outcome of the treatment is ultimately related to their metabolism by Cytochromes P450 (CYPs). Depending on the drugs used, alterations in the metabolism of drugs by CYPs can lead to severe consequences including alterations in their efficacy, safety and toxicity. The objectives of this study were to develop a novel HPLC–MS/MS method capable of quantifying codeine and oxycodone along with specific metabolites using an isotopic dilution strategy and study the rate of formation of morphine (CYP2D), norcodeine (CYP3A), oxymorphone (CYP2D) and noroxycodone (CYP3A). The chromatographic separation was achieved using a Biobasic C 18 100 × 1 mm column combined with an isocratic mobile phase composed of methanol and 10 m m ammonium acetate (40:60) at a flow rate of 75 μL/min. The mass spectrometer was operating in scan mode MS/MS and the analytical range was set at 10–10 000 n m . The precision (RSD) and accuracy (RE) observed were 4.4–11.5 and −9.1–6.1% respectively. Liver S9 fractions from 3‐, 6‐, 12‐ and 18‐month‐old male Sprague–Dawley rats were prepared and Michaelis–Menten parameters were determined. The derived maximum enzyme velocity suggested a rapid saturation of the CYP2D and CYP3A active sites in the liver S9 fractions of 18‐month‐old rats. Moreover, metabolic stabilities of codeine and oxycodone in rat liver S9 fractions were significantly greater for the 18‐month‐old rats. This study suggests that there is an impairment of CYP2D and CYP3A metabolism in aging rats.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it