Induction of Cytochrome P450 1A1 by Ketoconazole and Itraconazole but not Fluconazole in Murine and Human Hepatoma Cell Lines
Bibliographic record
Abstract
Azole antifungal agents are widely prescribed drugs for the treatment of systemic fungal infections; however, since their introduction into the market, increasing evidences of hepatotoxicity have been reported. Therefore, we examined here the ability of three structurally different antifungal drugs, ketoconazole (KTZ), itraconazole (ITZ), and fluconazole (FLZ) to induce the CYP1A1, an enzyme known to play an important role in chemical activation of xenobiotics to toxic metabolites. KTZ and ITZ, but not FLZ, induced the CYP1A1 in murine Hepa 1c1c7 and human HepG2 hepatoma cells at the mRNA, protein and activity levels in a concentration- and time-dependent manner. The increases in Cyp1a1 mRNA levels mediated by KTZ and ITZ were completely blocked by the RNA synthesis inhibitor, actinomycin D, whereas the level of existing mRNA was not altered, implying a requirement of de novo RNA synthesis through a transcriptional mechanism. The ability of these drugs to directly activate the aryl hydrocarbon receptor (AhR) transformation and hence xenobiotic responsive element's binding was strongly correlated with their abilities to induce luciferase activity. Inhibition studies showed that KTZ and ITZ, in addition to being CYP1A1 inducers, are substrates and competitive inhibitors. This study provides the first evidence for the ability of KTZ and ITZ to induce the CYP1A1 gene expression through an AhR-dependent mechanism, and suggests a novel mechanism of the KTZ- and ITZ-mediated toxicities.
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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) | 0.002 | 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".