Downregulation of RIP3 Improves the Protective Effect of ATF6 in an Acute Liver Injury Model
Bibliographic record
Abstract
Background . Activating transcription factor 6 (ATF6) and receptor‐interacting protein 3 (RIP3) are important signaling proteins in endoplasmic reticulum (ER) stress and necroptosis, respectively. However, their regulatory relationship and clinical significance are unknown. We investigate the impact of ATF6 on RIP3 expression, and its role in hepatocyte necroptosis in an acute liver injury model. Methods . In vivo and in vitro experiments were carried out. LO2 cells were treated with thapsigargin (TG). In vivo , male BALB/c mice were treated with carbon tetrachloride (CCl 4 , 1 mL/kg) or tunicamycin (TM, 2 mg/kg). Then, the impact of ATF6 or RIP3 silencing on liver injury, hepatocyte necroptosis, and ER stress‐related protein expression was examined. Results . TG induced ER stress and necroptosis and ATF6 and RIP3 expression in LO2 cells. The knockdown of ATF6 significantly decreased RIP3 expression ( p < 0.05) and increased ER stress and necroptosis. The downregulation of RIP3 significantly reduced necroptosis and ER stress ( p < 0.05). Similar results were observed in CCl 4 or the TM‐induced mouse model. The knockdown of ATF6 significantly decreased CCl 4 ‐induced RIP3 expression and increased liver injury, necroptosis, and ER stress in mice livers ( p < 0.05). In contrast, the downregulation of RIP3 significantly reduced liver injury, hepatocyte necroptosis, and ER stress. Conclusions . Hepatocyte ATF6 has multiple roles in acute liver injury. It reduces hepatocyte necroptosis via negative feedback regulation of ER stress. In addition, ATF6 can upregulate the expression of RIP3, which is not helpful to the recovery process. However, downregulating RIP3 reduces hepatocyte necroptosis by promoting the alleviation of ER stress. The findings suggest that RIP3 could be a plausible target for the treatment of liver injury.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".