Inflammatory reactions and drug response: importance of cytochrome P450 and membrane transporters
Bibliographic record
Abstract
Inflammatory reactions (IRs), both infectious and aseptic, downregulate numerous enzymes of cytochrome P450 (CYP) and ATP-binding cassette transporters. The mechanism involves proinflammatory cytokines and activation of transcription factors, nuclear factor-κB, CCAAT-enhancer-binding protein-β and c-myc, which bind to negative regulatory elements and/or impede the binding of nuclear receptors to promoter elements. Downregulation of CYP enzymes and transporters modulates the kinetics of a drug, resulting in increased plasma and tissue concentrations of the drug and enhanced effect and/or toxicity. Clinical trials have shown that IRs increase the risk of myocardial infarction and stroke. In this article, we speculate that IRs downregulate cardiac and vascular CYP enzymes (CYP2C8/9 and CYP2J2) responsible for the formation of vasorelaxant products. Patients with IRs should be advised that the risk of drug adverse effects and of cardiovascular diseases is increased; therefore, the benefit-risk ratio and use of drugs with narrow therapeutic index should be revaluated, as well as the conditions precipitating cardiovascular events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".