Defective mesenchymal Bmpr1a-mediated BMP signaling causes congenital pulmonary cysts
Bibliographic record
Abstract
Abnormal lung development can cause congenital pulmonary cysts, the mechanisms of which remain largely unknown. Although the cystic lesions are believed to result directly from disrupted airway epithelial cell growth, the extent to which developmental defects in lung mesenchymal cells contribute to abnormal airway epithelial cell growth and subsequent cystic lesions has not been thoroughly examined. In the present study using genetic mouse models, we dissected the roles of bone morphogenetic protein (BMP) receptor 1a (Bmpr1a)-mediated BMP signaling in lung mesenchyme during prenatal lung development and discovered that abrogation of mesenchymal Bmpr1a disrupted normal lung branching morphogenesis, leading to the formation of prenatal pulmonary cystic lesions. Severe deficiency of airway smooth muscle cells and subepithelial elastin fibers were found in the cystic airways of the mesenchymal Bmpr1a knockout lungs. In addition, ectopic mesenchymal expression of BMP ligands and airway epithelial perturbation of the Sox2-Sox9 proximal-distal axis were detected in the mesenchymal Bmpr1a knockout lungs. However, deletion of Smad1/5, two major BMP signaling downstream effectors, from the lung mesenchyme did not phenocopy the cystic abnormalities observed in the mesenchymal Bmpr1a knockout lungs, suggesting that a Smad-independent mechanism contributes to prenatal pulmonary cystic lesions. These findings reveal for the first time the role of mesenchymal BMP signaling in lung development and a potential pathogenic mechanism underlying congenital pulmonary cysts.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".