Methotrexate induced mitochondrial injury and cytochrome c release in rat liver hepatocytes
Bibliographic record
Abstract
Methotrexate (MTX) is a folic acid antagonist that is widely used to treat a variety of diseases. One of the most serious side effects of MTX therapy is hepatotoxicity. The potential molecular cytotoxic mechanisms of MTX toward isolated rat hepatocytes were investigated using Accelerated Cytotoxicity Mechanism Screening (ACMS) techniques. A concentration and time dependent increase in cytotoxicity and reactive oxygen species (ROS) formation and a decrease in mitochondrial membrane potential (MMP) were observed with MTX. Furthermore, a significant increase in MTX (300 μM)-induced cytotoxicity and ROS formation were observed when glutathione (GSH)-depleted hepatocytes were used whereas addition of N-acetylcysteine (a GSH precursor) decreased cytotoxicity. Catalase inactivation also increased MTX-induced cytotoxicity, while the direct addition of catalase to the hepatocytes decreased cytotoxicity. MTX treatment in isolated rat mitochondria caused swelling and significantly decreased adenosine triphosphate (ATP) and GSH content, and cytochrome c release. Potent antioxidants such as mesna, resveratrol and Trolox decreased MTX-induced cytotoxicity and ROS formation and increased MMP. This study suggests that MTX-induced cytotoxicity caused by ROS formation and GSH oxidation leads to oxidative stress and mitochondrial injury in rat hepatocytes.
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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".