SVIP alleviates CCl4-induced liver fibrosis via activating autophagy and protecting hepatocytes
Bibliographic record
Abstract
Abstract Prolonged parenchymal cell death leads to activation of fibrogenic cells and extracellular matrix accumulation and eventually liver fibrosis. Autophagy, a major catabolic process of intracellular degradation and recycling, participates in hepatic fibrosis. However, the precise role of autophagy in the pathogenesis of hepatic fibrosis is controversial. The present study aims to investigate the key role of small VCP/p97 interacting protein (SVIP) against CCl 4 -induced hepatic fibrosis via activating autophagy. Autophagy could be activated by SVIP in HepG2 cells, but starvation cannot increase SVIP expression in vitro and in vivo. Moreover, SVIP expression, in agreement with autophagic activity and the volume of lipid droplets, first increases and then decreases during the progression of liver fibrosis with CCl 4 treatment in vivo and in vivo. Further, overexpression of SVIP can protect HepG2 cells from the toxicity of CCl 4 , which could be enhanced by starvation. Finally, starvation keeps SVIP and autophagy at such high levels in the rat livers that markedly delays the progress of hepatic fibrosis. Probably, the protective effect of SVIP is associated with stabilizing nuclear factor (erythroid-derived 2)-related factor 2 (Nrf2) and transcription factor EB (TFEB). The current study provides insight into the biological role of SVIP and autophagy in regulating hepatic fibrosis, targeting SVIP might be a novel therapeutic strategy in the future.
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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".