The Role of CD8 T Cells in Amodiaquine-Induced Liver Injury in PD1–/– Mice Cotreated with Anti-CTLA-4
Bibliographic record
Abstract
The mechanism of idiosyncratic drug-induced liver injury (IDILI) remains poorly understood, in part due to the lack of a valid animal model. Clinical evidence suggests that most IDILI is immune mediated, and the major factor preventing liver injury in most patients is immune tolerance. Many attempts have been made in the past to develop an animal model of IDILI, but none had characteristics similar to those of IDILI in humans, and presumably they involved a different mechanism. Recently our laboratory reported a model of amodiaquine (AQ)-induced IDILI using PD1-/- mice and an anti-CTLA4 antibody. This may be the first valid animal model of IDILI because it mimics the characteristics of IDILI in humans. The current study extended the duration of AQ treatment to see if this model would lead to liver failure and to further characterize the associated immune response. Although AQ treatment was extended to 10 weeks and total bilirubin levels were significantly elevated compared to control, there was no further increase from weeks 7 to 10, and the animals did not develop overt liver failure. Mice treated with AQ and anti-CTLA4 had a significant increase in percentage of hepatic CD4, CD8, Th17, and Treg cells after 10 weeks of AQ treatment, as well as significantly decreased NK cells. CD8 T cells have been implicated in several serious idiosyncratic drug reactions, and we used an anti-CD8 antibody to deplete CD8 T cells to study their involvement in this liver injury. We found that depletion of CD8 T cells protected mice from AQ-induced liver injury in this model, which strongly suggests that they are responsible for the liver damage. This is consistent with the finding of CD8 T cells in liver biopsies of human IDILI and may lead the way to an effective treatment for serious IDILI.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".