FGF19 is Downregulated in Idiopathic Pulmonary Fibrosis and Inhibits Lung Fibrosis in Mice
Bibliographic record
Abstract
Abstract Idiopathic pulmonary fibrosis (IPF) is a devastating lung disease with limited therapeutic possibilities. FGF19 (fibroblast growth factor 19), an endocrine FGF, was recently shown to decrease liver fibrosis. To ask whether FGF19 had antifibrotic properties in the lung and decipher its effects on common features associated with lung fibrogenesis, we assessed, by ELISA, FGF19 concentrations in plasma and BAL fluids obtained from control subjects and patients with IPF. In vivo, using an intravenously administered adeno11-associated virus, we overexpressed FGF19 at the fibrotic phase of two experimental models of murine lung fibrosis and assessed its effect on lung morphology, lung collagen content, fibrosis markers, and profibrotic mediator expression at mRNA and protein levels. In vitro, we investigated whether FGF19 could modulate the TGF-β–induced differentiation of primary human lung fibroblasts into myofibroblasts and the apoptosis of murine alveolar type II cells. Although FGF19 was not detected in BAL fluid, FGF19 concentration was decreased in the plasma of patients with IPF compared with control subjects. In vivo, the overexpression of FGF19 was associated with a marked decrease of lung fibrosis and fibrosis markers, with a decrease of profibrotic mediator expression and lung collagen content. In vitro, FGF19 decreased alveolar type 2 epithelial cell apoptosis through the decrease of the proapoptotic BIM protein expression and prevented TGF-β–induced myofibroblast differentiation through the inhibition of JNK phosphorylation. Altogether, these data identify FGF19 as an antifibrotic molecule with potential therapeutic interest in fibrotic lung disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".