Airway epithelial compression promotes airway smooth muscle proliferation and contraction
Bibliographic record
Abstract
During acute bronchoconstriction, the airway epithelium becomes mechanically compressed, as airway smooth muscle contracts and the airway narrows. This mechanical compression activates airway epithelium to promote asthmatic airway remodeling. However, whether compressed airway epithelium can feed back on the cause of bronchoconstriction has remained an open question. Here we examine the potential for epithelial compression to augment proliferation and contraction of airway smooth muscle, and thus potentiate further bronchoconstriction and epithelial compression. Well-differentiated primary human bronchial epithelial (HBE) cells maintained in air-liquid interface culture were mechanically compressed to mimic the effect of bronchoconstriction. Primary human airway smooth muscle (HASM) cells were incubated with conditioned media collected from mechanically compressed HBE cells to examine the effect of epithelial-derived mediators on HASM cell proliferation using an EdU assay and HASM cell contraction using traction microscopy. An endothelin receptor antagonist, PD-145065, was employed to probe the role of HBE cell-derived endothelin-1 on the proliferation and contraction of HASM cells. Conditioned media from compressed HBE cells increased HASM cell proliferation, independent of the endothelin-1 signaling pathway. However, conditioned media from compressed HBE cells significantly increased HASM cell basal contraction and histamine-induced contraction, both of which depended on the endothelin-1 signaling pathway. Our data demonstrate that mechanical compression of bronchial epithelial cells contributes to proliferation and basal contraction of airway smooth muscle cells and that augmented contraction depends on epithelial cell-derived endothelin-1. By means of both airway smooth muscle remodeling and contractility, our findings suggest a causal role of epithelial compression on asthma pathogenesis.
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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".