Evaluation of Azathioprine-Induced Cytotoxicity in an<i>In Vitro</i>Rat Hepatocyte System
Bibliographic record
Abstract
Azathioprine (AZA) is widely used in clinical practice for preventing graft rejection in organ transplantations and various autoimmune and dermatological diseases with documented unpredictable hepatotoxicity. The potential molecular cytotoxic mechanisms of AZA towards isolated rat hepatocytes were investigated in this study using "Accelerated Cytotoxicity Mechanism Screening" techniques. The concentration of AZA required to cause 50% cytotoxicity in 2 hrs at 37°C was found to be 400 μM. A significant increase in AZA-induced cytotoxicity and reactive oxygen species (ROS) formation was observed when glutathione- (GSH-) depleted hepatocytes were used. The addition of N-acetylcysteine decreased cytotoxicity and ROS formation. Xanthine oxidase inhibition by allopurinol decreased AZA-induced cytotoxicity, ROS, and hydrogen peroxide (H2O2) formation and increased % mitochondrial membrane potential (MMP). Addition of N-acetylcysteine and allopurinol together caused nearly complete cytoprotection against AZA-induced hepatocyte death. TEMPOL (4-hydroxy-2,2,6,6-tetramethylpiperidin-1-oxyl), a known ROS scavenger and a superoxide dismutase mimic, and antioxidants, like DPPD (N,N'-diphenyl-p-phenylenediamine), Trolox (a water soluble vitamin E analogue), and mesna (2-mercaptoethanesulfonate), also decreased hepatocyte death and ROS formation. Results from this study suggest that AZA-induced cytotoxicity in isolated rat hepatocytes may be partly due to ROS formation and GSH depletion that resulted in oxidative stress and mitochondrial injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".