Effects of species of origin and mode of induction of microsomes on carbamazepine-induced cell toxicity
Bibliographic record
Abstract
Standardization and validation of in vitro drug metabolism is essential for pre-clinical drug development as well as for in vitro toxicity assays including the lymphocyte toxicity assay (LTA) and the in vitro platelet toxicity assay (iPTA). Use of isolated liver microsomes (MIC) in in vitro testing has been utilized for a long time; however, the effect of species of origin and induction agents on the metabolic capacities of MIC is not adequately evaluated. In this study we investigated the impact of species of origin and induction agent on the capacity of MICs to bioactivate carbamazepine (CBZ) using cytotoxicity as a gross endpoint to measure the levels of cytotoxic metabolites generated by each type of MICs. Jurkat E6.1 cell line was used and MICs from human, rat, mouse, minipig and rabbit origin as well as rat MICs that is either non-induced or induced by phenobarbitone (PHB), dexamethasone (DEXA), 3-methylcholanthrene (3MC), clofibrate (CLOF) and isoniazid (INH) were investigated. MICs from minipig and rat MICs induced with 3MC exhibited the highest capacity to produce cytotoxic metabolites of CBZ. These findings will help optimize and standardize in vitro toxicity assays and provide guidance to pre-clinical investigation of drugs.
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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 | 0.001 |
| 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) | 0.001 | 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".