Molecular cytotoxic mechanisms of chlorpromazine in isolated rat hepatocytes
Bibliographic record
Abstract
Chlorpromazine (CPZ), a member of the largest class of first-generation antipsychotic agents, is known to cause hepatotoxicity in the form of cholestasis and hepatocellular necrosis in some patients. The mechanism of CPZ hepatotoxicity is unclear, but is thought to result from reactive metabolite formation. The goal of this research was to assess potential cytotoxic mechanisms of CPZ using the accelerated cytotoxicity mechanism screening (ACMS) technique with freshly isolated rat hepatocytes. This study identified CPZ cytotoxicity and inhibition of mitochondrial membrane potential (MMP) to be concentration-dependent. Furthermore, inhibition of cytochrome P450s (CYPs), including CYP2D1 and 1A2, delayed CPZ cytotoxicity, suggesting a role for CYP activation of CPZ to a toxic metabolite(s) in this model. Metabolism studies also demonstrated glucuronide and glutathione (GSH) requirement for CPZ detoxification in hepatocytes. Inactivating the 2-electron reduction pathway, NAD(P)H quinone oxidoreductase (NQO1), caused a significant increase in hepatocyte susceptibility to CPZ, indicating quinoneimine contribution to CPZ cytotoxicity. Nontoxic concentrations of peroxidase/H(2)O(2) (inflammatory model) increased cytotoxicity in CPZ-treated hepatocytes and caused additional mitochondrial toxicity. Inflammation further depleted GSH and increased oxidized glutathione (GSSG) levels. Results suggest activation of CPZ to reactive metabolites by 2 pathways in hepatocytes: (i) a CYP-catalyzed quinoneimine pathway, and (ii) a peroxidase-catalyzed oxidation of CPZ to CPZ radicals.
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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 | 0.000 |
| 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".