Loss of BOK Has a Minor Impact on Acetaminophen Overdose-Induced Liver Damage in Mice
Bibliographic record
Abstract
Acetaminophen (APAP) is one of the most commonly used analgesic and anti-pyretic drugs, and APAP intoxication is one of the main reasons for liver transplantation following liver failure in the Western world. While APAP poisoning ultimately leads to liver necrosis, various programmed cell death modalities have been implicated, including ER stress-triggered apoptosis. The BCL-2 family member BOK (BCL-2-related ovarian killer) has been described to modulate the unfolded protein response and to promote chemical-induced liver injury. We therefore investigated the impact of the loss of BOK following APAP overdosing in mice. Surprisingly, we observed sex-dependent differences in the activation of the unfolded protein response (UPR) in both wildtype (WT) and Bok-/- mice, with increased activation of JNK in females compared with males. Loss of BOK led to a decrease in JNK activation and a reduced percentage of centrilobular necrosis in both sexes after APAP treatment; however, this protection was more pronounced in Bok-/- females. Nevertheless, serum ALT and AST levels of Bok-/- and WT mice were comparable, indicating that there was no major difference in the overall outcome of liver injury. We conclude that after APAP overdosing, loss of BOK affects initiating signaling steps linked to ER stress, but has a more minor impact on the outcome of liver necrosis. Furthermore, we observed sex-dependent differences that might be worthwhile to investigate.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".