Role of NF-κB in the Regulation of Cytochrome P450 Enzymes
Bibliographic record
Abstract
Nuclear factor kappa B (NF-kappaB) is an important transcription factor that regulates a wide spectrum of genes including cytochrome P450 (CYP), the most important family of drug metabolizing enzymes. Therefore, in this review, we addressed the potential role of NF-kappaB in CYP regulation. We proposed three mechanisms by which NF-kappaB can regulate CYP expression and activity. First, NF-kappaB can directly regulate the expression of CYP1A1, CYP2B1/2, CYP2C11, CYP2D5, CYP2E1, CYP3A7, and CYP27B1 through binding to the promoter region of these genes. Second, NF-kappaB indirectly regulates the transcription of CYP genes through mutual repression with some nuclear receptors that are involved in CYP regulation such as AhR, CAR, GR, PXR, RXR, PPAR, FXR, and LXR. Finally, NF-kappaB can regulate CYP activity at post-transcriptional level by inducing heme oxygenase or by affecting the CYP protein stability. In addition, increased inflammatory mediators, oxidative stress, and subsequent NF-kappaB activation have been demonstrated in many conditions such as inflammatory bowel diseases, rheumatoid arthritis, psychological stress, diabetes, aging, cancer, renal diseases, and congestive heart failure. Meanwhile, there is a significant alteration of CYP expression and activity in these diseases. Therefore, we propose that NF-kappaB could be one of the links between inflammation, oxidative stress, and CYP regulation in these diseases. In conclusion, NF-kappaB plays a crucial role in the regulation of CYP through several mechanisms and this role can explain the altered CYP regulation in many conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".