Negative Transpulmonary Pressure Disrupts Airway Morphogenesis by Suppressing Fgf10
Bibliographic record
Abstract
Mechanical forces are increasingly recognized as important determinants of cell and tissue phenotype and also appear to play a critical role in organ development. During the fetal stages of lung morphogenesis, the pressure of the fluid within the lumen of the airways is higher than that within the chest cavity, resulting in a positive transpulmonary pressure. Several congenital defects decrease or reverse transpulmonary pressure across the developing airways and are associated with a reduced number of branches and a correspondingly underdeveloped lung that is insufficient for gas exchange after birth. The small size of the early pseudoglandular stage lung and its relative inaccessibility in utero have precluded experimental investigation of the effects of transpulmonary pressure on early branching morphogenesis. Here, we present a simple culture model to explore the effects of negative transpulmonary pressure on development of the embryonic airways. We found that negative transpulmonary pressure decreases branching, and that it does so in part by altering the expression of fibroblast growth factor 10 (Fgf10). The morphogenesis of lungs maintained under negative transpulmonary pressure can be rescued by supplementing the culture medium with exogenous FGF10. These data suggest that Fgf10 expression is regulated by mechanical stress in the developing airways. Understanding the mechanical signaling pathways that connect transpulmonary pressure to FGF10 can lead to the establishment of novel non-surgical approaches for ameliorating congenital lung defects.
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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) | 0.002 | 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".