Regulation of Transforming Growth Factor-β1–driven Lung Fibrosis by Galectin-3
Bibliographic record
Abstract
RATIONALE: Idiopathic pulmonary fibrosis (IPF) is a chronic dysregulated response to alveolar epithelial injury with differentiation of epithelial cells and fibroblasts into matrix-secreting myofibroblasts resulting in lung scaring. The prognosis is poor and there are no effective therapies or reliable biomarkers. Galectin-3 is a β-galactoside binding lectin that is highly expressed in fibrotic tissue of diverse etiologies. OBJECTIVES: To examine the role of galectin-3 in pulmonary fibrosis. METHODS: We used genetic deletion and pharmacologic inhibition in well-characterized murine models of lung fibrosis. Further mechanistic studies were performed in vitro and on samples from patients with IPF. MEASUREMENTS AND MAIN RESULTS: Transforming growth factor (TGF)-β and bleomycin-induced lung fibrosis was dramatically reduced in mice deficient in galectin-3, manifest by reduced TGF-β1-induced EMT and myofibroblast activation and collagen production. Galectin-3 reduced phosphorylation and nuclear translocation of β-catenin but had no effect on Smad2/3 phosphorylation. A novel inhibitor of galectin-3, TD139, blocked TGF-β-induced β-catenin activation in vitro and in vivo and attenuated the late-stage progression of lung fibrosis after bleomycin. There was increased expression of galectin-3 in the bronchoalveolar lavage fluid and serum from patients with stable IPF compared with nonspecific interstitial pneumonitis and controls, which rose sharply during an acute exacerbation suggesting that galectin-3 may be a marker of active fibrosis in IPF and that strategies that block galectin-3 may be effective in treating acute fibrotic exacerbations of IPF. CONCLUSIONS: This study identifies galectin-3 as an important regulator of lung fibrosis and provides a proof of principle for galectin-3 inhibition as a potential novel therapeutic strategy for IPF.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".