Early activation of pro-fibrotic WNT5A in sepsis-induced acute lung injury
Bibliographic record
Abstract
INTRODUCTION: The mechanisms of lung repair and fibrosis in the acute respiratory distress syndrome (ARDS) are poorly known. Since the role of WNT/β-catenin signaling appears to be central to lung healing and fibrosis, we hypothesized that this pathway is activated very early in the lungs after sepsis. METHODS: We tested our hypothesis using a three-step experimental design: (1) in vitro lung cell injury model with human bronchial epithelial BEAS-2B and lung fibroblasts (MRC-5) cells exposed to endotoxin for 18 hours; (2) an animal model of sepsis-induced ARDS induced by cecal ligation and perforation, and (3) lung biopsies from patients who died within the first 24 hours of septic ARDS. We examined changes in protein levels of target genes involved in the Wnt pathway, including WNT5A, non-phospho (Ser33/37/Thr41) β-catenin, matrix metalloproteinase-7 (MMP7), cyclin D1, and vascular endothelial growth factor (VEGF) by Western blotting and immunohistochemistry. Finally, we validated the main gene targets of this pathway in experimental animals and human lungs. RESULTS: Protein levels of WNT5A, non-phospho (Ser33/37/Thr41) β-catenin, total β-catenin, MMP7, cyclin D1, and VEGF increased after endotoxin stimulation in BEAS-2B and MRC-5 cells. Lungs from septic animals and from septic humans demonstrated acute lung inflammation, collagen deposition, and marked increase of WNT5A and MMP7 protein levels. CONCLUSIONS: Our findings suggest that the WNT/β-catenin signaling pathway is activated very early in sepsis-induced ARDS and could play an important role in lung repair and fibrosis. Modulation of this pathway might represent a potential target for treatment for septic and ARDS patients.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".