Epithelial–mesenchymal transition in the pathophysiology of airway remodelling in asthma
Bibliographic record
Abstract
PURPOSE OF REVIEW: We currently understand little about the mechanisms that lead to airway remodeling in asthma. The origin of the mesenchymal cells that contribute to fibrosis of the airway is poorly understood. However, emerging evidence suggests that the airway epithelium could contribute to airway remodeling through the process of epithelial-mesenchymal transition (EMT) following environmental challenge. In this review, we will discuss the mechanistic features of EMT and highlight recent descriptions of EMT in the airway to further define the role of the airway epithelium in the pathogenesis of asthma. RECENT FINDINGS: Growth factors, inflammatory mediators, and matricellular proteins expressed following exposure to environmental insults are known to induce downregulation of epithelial cell-cell adhesions and promote mesenchymal gene expression programs both in vitro and in vivo. These results demonstrate that the plastic and dynamic airway epithelium may contribute to airway remodeling via EMT in asthma. SUMMARY: It is becoming increasingly clear that the airway epithelium orchestrates inflammatory and remodeling responses of the airway. Understanding the regulatory mechanisms involved in epithelial plasticity will be crucial to determine effective therapies to halt the progression of airway remodeling 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".