Exploring an animal model of amodiaquine-induced liver injury in rats and mice
Bibliographic record
Abstract
Amodiaquine (AQ) is associated with a relatively high incidence of idiosyncratic drug-induced liver injury (IDILI) and agranulocytosis. A previous study reported that a combination of high dose AQ and glutathione (GSH) depletion led to liver injury. However, the characteristics of this toxicity were very different from AQ-induced liver injury in humans. We developed a model of AQ-induced liver injury with characteristics similar to the injury in humans by treating mice with lower doses of AQ for several weeks. In this study we found that not only did GSH depletion not increase AQ covalent binding to hepatic proteins at this lower dose, but also it paradoxically prevented the liver injury. We extended the model to rats and found AQ treatment led to a mild delayed onset liver injury that resolved despite continued treatment with AQ. Immunohistochemistry indicated the presence of Kupffer cell activation, apoptosis and hepatocyte proliferation in the liver. There was also an increase in serum IL-2, IL-5, IL-9, IL-12, MCP-1 and TGFβ, but a decrease in leptin. Coincident with the elevated serum ALT, the number of liver CD4(+) T-cells, IL-17 secreting cells and TH17/Treg cells increased at Week 3 and decreased during continued treatment. Increases in NK1.1+ cells and activated M2 macrophages were also observed during liver injury. These results suggest that the outcome of the liver injury was determined by the balance between effector and regulatory cells. Co-treatment with cyclosporin prevented AQ-induced liver injury, which supports an immune mechanism. Retinoic acid (RA), which has been reported to enhance natural killer (NK) cell activity, exacerbated AQ-induced liver injury. These results suggest that AQ-induced IDILI is immune mediated and the subsequent adaptation appears to represent immune tolerance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".