Effects of angiotensin II blockade on inflammation‐induced alterations of pharmacokinetics and pharmacodynamics of calcium channel blockers
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Inflammation elevates plasma verapamil concentrations but diminishes pharmacological response. Angiotensin II is a pro-inflammatory mediator. We examined the effect of angiotensin II receptor blockade on the pharmacokinetics and pharmacodynamics of verapamil, as well as the binding properties and amounts of its target protein in calcium channels, in a rat model of inflammation. EXPERIMENTAL APPROACH: We used 4 groups of male Sprague-Dawley rats (220-280 g): inflamed-placebo, inflamed-treated, control-placebo and control-treated. Inflammation as pre-adjuvant arthritis was induced by injecting Mycobacterium butyricum on day 0. From day 6 to 12, 30 mg kg(-1) oral valsartan or placebo was administered twice daily. On day 12, a single oral dose of 25 mg kg(-1) verapamil was administered and prolongation of the PR interval measured and plasma samples collected for verapamil and nor-verapamil analysis. The amounts of the target protein Ca(v)1.2 subunit of L-type calcium channels in heart was measured by Western blotting and ligand binding with (3)H-nitrendipine. KEY RESULTS: Inflammation reduced effects of verapamil, although plasma drug concentrations were increased. This was associated with a reduction in ligand binding capacity and amount of the calcium channel target protein in heart extracts. Valsartan significantly reversed the down-regulating effect of inflammation on verapamil's effects on the PR interval, and the lower level of protein binding and the decreased target protein. CONCLUSIONS AND IMPLICATIONS: Reduced responses to calcium channel blockers in inflammatory conditions appeared to be due to a reduced amount of target protein that was reversed by the angiotensin II antagonist, valsartan.
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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".