Liver Injury Caused by Green Tea Extract in PD-1<sup>–/–</sup> Mice: An Impaired Immune Tolerance Model for Idiosyncratic Drug-Induced Liver Injury
Bibliographic record
Abstract
Idiosyncratic drug-induced liver injury (IDILI) is an idiosyncratic drug reaction that is specific to an individual and can lead to liver failure and even death. The mechanism of IDILI remains poorly understood, but most IDILI appears to be immune-mediated. We have developed the first validated animal model by using a PD-1–/– mouse model in combination with anti-CTLA-4 to block immune checkpoints and impair immune tolerance. Treatment of these mice with drugs that cause IDILI in humans led to delayed-onset liver injury with characteristics similar to IDILI in humans. The current study investigates the effects of green tea extract, a weight-loss dietary supplement that has been reported to cause IDILI in humans. Green tea extracts contain a highly variable content of catechins including (−)-epigallocatechin gallate, the major catechin in green tea formulations. If the liver injury caused by green tea extract in humans is immune-mediated, it may occur in our impaired immune tolerance model. Female PD-1–/– mice treated with anti-CTLA-4 antibody and green tea extract (500 mg/kg), a dose that is considered a no-observed-adverse-effect level for liver in rodents, produced a delayed onset increase in serum alanine transaminase levels and an increase in hepatic CD8+ T cells. In contrast, the response in male PD-1–/– mice was less pronounced, and there was no evidence of liver injury in wild-type mice. These findings are consistent with the hypothesis that the IDILI caused by green tea extract is immune-mediated and is similar to IDILI caused by medications that are associated with IDILI.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".