The Effect of Infliximab on Hepatic Cytochrome P450 and Pharmacokinetics of Verapamil in Rats with Pre-Adjuvant Arthritis: A Drug-Disease and Drug-Drug Interaction
Bibliographic record
Abstract
Inflammatory conditions result in increased concentration but reduced potency of some cardiovascular drugs. This is associated with increased levels of pro-inflammatory mediators. Infliximab reduces pro-inflammatory mediators and reverses the diminishing effect of inflammation on response in the rat. We suggested that infliximab treatment would also reverse the effects of inflammation on drug metabolism and clearance. We examined hepatic cytochrome P450 content and the pharmacokinetics of verapamil in pre-adjuvant arthritic rats treated with infliximab. Pre-adjuvant arthritis was induced in male Sprague-Dawley rats with a tail base injection of Mycobacterium butyricum. Animals were monitored for symptoms of arthritis, serum nitrite and C-reactive protein. On day 6, rats were administered with single s.c. doses of infliximab (10 mg/kg). On day 14, a single i.v. dose of racemic verapamil (2 mg/kg) was administered, and S- and R-verapamil concentrations were determined by high performance liquid chromatography. Hepatic cytochrome P450 content and verapamil protein binding were also measured. Serum nitrite levels were significantly elevated in pre-adjuvant arthritis. Infliximab did not affect mean nitrite concentrations but there was a significant correlation between nitrite and S-verapamil concentrations as well as cytochrome P450, CYP3A, and CYP1A contents. Infliximab increased cytochrome P450 enzymes content that had been diminished by pre-adjuvant arthritis but had no significant effect on verapamil protein binding. Infliximab partially restores hepatic cytochrome P450 enzyme contents. The effect of infliximab on the mean verapamil clearance was not significantly affected due, likely, to the lack of effect on plasma protein binding.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".