Usefulness and limitations of mRNA measurement in HepaRG cells for evaluation of cytochrome P450 induction
Bibliographic record
Abstract
Cytochrome P450s (CYPs) are involved in the metabolism of various drugs, and may generate toxic metabolites or intermediates that result in drug-induced liver injury (DILI). Consequently, inducers of CYPs may promote DILI. In a draft test guideline, the Organisation for Economic Co-operation and Development (OECD) recommends measurement of the metabolic activity of CYP as an index for assessing CYP-inducing activity. However, change of mRNA level has also been used as a simple parameter to evaluate CYP induction. In this study, therefore, we examined the usefulness and limitations of mRNA expression measurement for evaluation of the induction of CYP1A2, CYP2B6, and CYP3A4 by omeprazole, phenobarbital, and rifampicin (RIF), respectively, in HepaRG cells, a well-established cell line derived from human hepatocellular carcinoma. The results of mRNA measurement correlated well with the results of metabolic activity measurement in the lower concentration ranges for all inducers, even though we observed significant decreases in albumin and urea secretion in the presence of 10 µM RIF, reflecting its known hepatotoxicity. Our results indicate that mRNA measurements and metabolic activity measurements in HepaRG cells generally give comparable results for fold-induction of CYPs.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".