Caveolin-1 Controls Airway Epithelial Barrier Function. Implications for Asthma
Bibliographic record
Abstract
The molecular basis for airway epithelial fragility in asthma has remained unclear. We investigated whether the loss of caveolin-1, the major component of caveolae and a known stabilizer of adherens junctions, contributes to epithelial barrier dysfunction in asthma. We studied the expression of caveolin-1 and adhesion molecules E-cadherin and β-catenin in airway sections, and we cultured bronchial epithelial cells from patients with asthma and from healthy control subjects. To determine the functional role of caveolin-1, we investigated the effects of caveolin-1 up-regulation and down-regulation on E-cadherin expression, barrier function, and proallergic activity in the human bronchial epithelial cell lines 16HBE and BEAS-2B. The membrane expression of caveolin-1 was significantly lower in airway epithelia from patients with asthma than from subjects without asthma, and this lower expression was maintained in vitro upon air-liquid interface and submerged culturing. Importantly, reduced caveolin-1 expression was accompanied by a loss of junctional E-cadherin and β-catenin expression, disrupted epithelial barrier function, and increased levels of the proallergic cytokine thymic stromal lymphopoietin (TSLP). Furthermore, E-cadherin redistribution upon exposure to epidermal growth factor or house dust mite was paralleled by the internalization of caveolin-1 in 16HBE cells. These effects appear to be causally related, because the short, interfering RNA down-regulation of caveolin-1 resulted in the delocalization of E-cadherin and barrier dysfunction in 16HBE cells. Moreover, caveolin-1 overexpression improved barrier function and reduced TSLP expression in BEAS-2B cells. Together, our data demonstrate a crucial role for caveolin-1 in epithelial cell-cell adhesion, with important consequences for epithelial barrier function and the promotion of Th2 responses in asthma.
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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) | 0.001 | 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".