New role and molecular mechanism of Gadd45a in hepatic fibrosis
Bibliographic record
Abstract
AIM: To investigate the role of Gadd45a in hepatic fibrosis and the transforming growth factor (TGF)-β/Smad signaling pathway. METHODS: Wild-type male BALB/c mice were treated with CCl4 to induce a model of chronic liver injury. Hepatic stellate cells (HSCs) were isolated from the liver of BALB/c mice and were treated with small interfering RNAs (siRNAs) targeting Gadd45a or the pcDNA3.1-Gadd45a recombinant plasmid. Cellular α-smooth muscle actin (α-SMA), β-actin, type I collagen, phospho-Smad2, phospho-Smad3, Smad2, Smad3, and Smad4 were detected by Western blots. The mRNA levels of α-SMA, β-actin, and type I collagen were determined by quantitative real-time (qRT)-PCR analyses. Reactive oxygen species production was monitored by flow cytometry using 2,7-dichlorodihydrofluorescein diacetate. Gadd45a, Gadd45b, anti-Gadd45g, type I collagen, and SMA local expression in liver tissue were measured by histologic and immunohistochemical analyses. RESULTS: Significant downregulation of Gadd45a, but not Gadd45b or Gadd45g, accompanied by activation of the TGF-β/Smad signaling pathways was detected in fibrotic liver tissues of mice and isolated HSCs with chronic liver injury induced by CCl4 treatment. Overexpression of Gadd45a reduced the expression of extracellular matrix proteins and α-SMA in HSCs, whereas transient knockdown of Gadd45a with siRNA reversed this process. Gadd45a inhibited the activity of a plasminogen activator inhibitor-1 promoter construct and (CAGA)9 MLP-Luc, an artificial Smad3/4-specific reporter, as well as reduced the phosphorylation and nuclear translocation of Smad3. Gadd45a showed protective effects by scavenging reactive oxygen species and upregulating antioxidant enzymes. CONCLUSION: Gadd45a may counteract hepatic fibrosis by regulating the activation of HSCs via the inhibition of TGF-β/Smad signaling.
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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".