Influence of experimental diabetes and insulin treatment on the enantioselective pharmacokinetics of mexiletine and its metabolites
Bibliographic record
Abstract
This study evaluates the influence of streptozotocin-induced diabetes on the kinetic disposition and metabolism of mexiletine (MEX) enantiomers in rats. Animals in the control (n = 6 for each blood collection time), diabetic (single intravenous dosage of 45 mg·(kg body mass)(-1) of streptozotocin), and insulin-treated groups (diabetic rats treated daily with 2 IU insulin) received by gavage a single dose of 10 mg·(kg body mass)(-1) racemic MEX. MEX enantiomers and the metabolites hydroxymethylmexiletine (HMM) and p-hydroxymexiletine PHM) were analyzed by LC-MS/MS. Statistical analysis was based on a serial sacrifice design, and parameter estimation was performed using a Bayesian modeling procedure. Area under the curve (AUC) for the (-)-(R) enantiomers of MEX, HMM, and PHM did not differ between the control and diabetic groups. However, AUC for (+)-(S)-MEX and (+)-(S)-HMM were lower in the diabetic than in the control group. Insulin treatment recovered glucose levels to normal and the (+)-(S)-MEX AUC and (+)-(S)-HMM AUC became similar to the AUCs observed in the nondiabetic animals.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.000 |
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".