MicroRNA-19b Mediates Lung Epithelial-Mesenchymal Transition via Phosphatidylinositol-3,4,5-Trisphosphate 3-Phosphatase in Response to Mechanical Stretch
Bibliographic record
Abstract
Lung epithelial-mesenchymal transition (EMT) plays an important role in ventilation-associated lung fibrosis, which may contribute to the poor outcome of patients with acute respiratory distress syndrome. Because microRNAs control and modulate normal physiological and pathophysiological processes, we investigated the role of microRNAs in the development of acute respiratory distress syndrome-associated EMT in response to mechanical stress. In the current study, primary human alveolar epithelial type II (AEII) cells were subjected to cyclic stretch that resulted in EMT profiles with decreased gene expression of cytokeratin-8, E-cadherin, and surfactant protein B, and increased expression of vimentin, α-smooth muscle actin, and N-cadherin. Microarray analysis revealed that the expression of microRNA-19b (miR-19b) was up-regulated in the AEII cells, and real-time polymerase chain reaction showed that the expression of miR-19b increased in both the AEII cells and the primary human small-airway epithelial cells. Overexpression of miR-19b in small-airway epithelial cells promoted the mechanical stretch-induced EMT phenotypes, whereas inhibition of miR-19b attenuated it. The inhibitory effect of miR-19b was attributed to enhanced signaling of phosphatidylinositol-3,4,5-trisphosphate 3-phosphatase (PTEN), leading to inactivation of the AKT pathway. Restoration of PTEN expression or inhibition of AKT phosphorylation suppressed the mechanical stretch-induced EMT phenotypes. We further demonstrated that the mechanical stretch-induced miR19 expression was regulated by the focal adhesion kinase-Rho pathway. In conclusion, we found that miR-19b plays a key role in the development of the EMT phenotype through down-regulation of PTEN in human lung epithelial cells in response to mechanical stretch. The miR-19b-PTEN signaling pathway may serve as a novel therapeutic target in the context of ventilator-associated lung fibrosis.
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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) | 0.001 | 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".