Comparing pharmacokinetics and metabolism of diltiazem in normotensive Sprague Dawley and Wistar Kyoto rats vs. spontaneously hypertensive rats in vivo
Bibliographic record
Abstract
BACKGROUND: In order to identify a suitable rodent model for preclinical study of calcium antagonists, the pharmacokinetics and metabolism of one of the prototypes diltiazem (DTZ) in normotensive Sprague Dawley (SDR) was compared with Wistar Kyoto (WKY) rats and spontaneously hypertensive rats (SHR) following 5 mg/kg twice daily for five doses given by subcutaneous injection. METHODS: Pharmacokinetic data were analyzed by standard procedures assuming a one-compartment model with first-order input using Rstrips(®), and differences between the groups were considered significant when p<0.05. RESULTS: Plasma concentrations of DTZ were higher in the SHR than the normotensive SDR and WKY rats, although the differences did not reach statistical significance (p>0.05). Plasma concentrations of the active metabolites N-desmethyl DTZ (MA), deacetyl DTZ (M1) and deacetyl N-desmethyl DTZ (M2) were significantly higher in the SHR and WKY rats than the SDR, which was attributed to higher DTZ concentrations and also genetic factors. CONCLUSIONS: Although the differences were mainly quantitative and very small, the study has shown for the first time that the metabolism profiles of DTZ in SHR and WKY rats were closer to humans than SDR, and they may be more preferable rat models to study pharmacokinetic and metabolism studies of DTZ or similar agents.
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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 | 0.000 |
| 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".