The role of caveolin-1 in pulmonary matrix remodeling and mechanical properties
Bibliographic record
Abstract
Caveolin-1 (cav1) is a 22-kDa membrane protein essential to the formation of small invaginations in the plasma membrane, called caveolae. The cav1 gene is expressed primarily in adherent cells such as endothelial and smooth muscle cells and fibroblasts. Caveolae contain a variety of signaling receptors, and cav1 notably downregulates transforming growth factor (TGF)-beta signal transduction. In pulmonary pathologies such as interstitial fibrosis or emphysema, altered mechanical properties of the lungs are often associated with abnormal ECM deposition. In this study, we examined the physiological functions and the deposition of ECM in cav1(-/-) mice at various ages (1-12 mo). Cav1(-/-) mice lack caveolae and by 3 mo of age have significant reduced lung compliance and increased elastance and airway resistance. Pulmonary extravasation of fluid, as part of the cav1(-/-) mouse phenotype, probably contributed to the alteration of compliance, which was compounded by a progressive increase in deposition of collagen fibrils in airways and parenchyma. We also found that the increased elastance was caused by abundant elastic fiber deposition primarily around airways in cav1(-/-) mice at least 3 mo old. These observed changes in the ECM composition probably also contribute to the increased airway resistance. The higher deposition of collagen and elastic fibers was associated with increased tropoelastin and col1alpha2 and col3alpha1 gene expression in lung tissues, which correlated tightly with increased TGF-beta/Smad signal transduction. Our study illustrates that perturbation of cav1 function may contribute to several pulmonary pathologies as the result of the important role played by cav1, as part of the TGF-beta signaling pathway, in the regulation of the pulmonary ECM.
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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) | 0.000 | 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".