The mechanism underlying acetaminophen-induced hepatotoxicity in humans and mice involves mitochondrial damage and nuclear DNA fragmentation
Bibliographic record
Abstract
Acetaminophen (APAP) overdose is the predominant cause of acute liver failure in the United States. Toxicity begins with a reactive metabolite that binds to proteins. In rodents, this leads to mitochondrial dysfunction and nuclear DNA fragmentation, resulting in necrotic cell death. While APAP metabolism is similar in humans, the later events resulting in toxicity have not been investigated in patients. In this study, levels of biomarkers of mitochondrial damage (glutamate dehydrogenase [GDH] and mitochondrial DNA [mtDNA]) and nuclear DNA fragments were measured in plasma from APAP-overdose patients. Overdose patients with no or minimal hepatic injury who had normal liver function tests (LTs) (referred to herein as the normal LT group) and healthy volunteers served as controls. Peak GDH activity and mtDNA concentration were increased in plasma from patients with abnormal LT. Peak nuclear DNA fragmentation in the abnormal LT cohort was also increased over that of controls. Parallel studies in mice revealed that these plasma biomarkers correlated well with tissue injury. Caspase-3 activity and cleaved caspase-3 were not detectable in plasma from overdose patients or mice, but were elevated after TNF-induced apoptosis, indicating that APAP overdose does not cause apoptosis. Thus, our results suggest that mitochondrial damage and nuclear DNA fragmentation are likely to be critical events in APAP hepatotoxicity in humans, resulting in necrotic cell death.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".