Aberrant cell migration contributes to defective airway epithelial repair in childhood wheeze
Bibliographic record
Abstract
Abnormal wound repair has been observed in the airway epithelium of patients with chronic respiratory diseases, including asthma. Therapies focusing on repairing vulnerable airways, particularly in early life, present a potentially novel treatment strategy. We report defective lower airway epithelial cell repair to strongly associate with common pre-school-aged and school-aged wheezing phenotypes, characterized by aberrant migration patterns and reduced integrin α5β1 expression. Next generation sequencing identified the PI3K/Akt pathway as the top upstream transcriptional regulator of integrin α5β1, where Akt activation enhanced repair and integrin α5β1 expression in primary cultures from children with wheeze. Conversely, inhibition of PI3K/Akt signaling in primary cultures from children without wheeze reduced α5β1 expression and attenuated repair. Importantly, the FDA-approved drug celecoxib - and its non-COX2-inhibiting analogue, dimethyl-celecoxib - stimulated the PI3K/Akt-integrin α5β1 axis and restored airway epithelial repair in cells from children with wheeze. When compared with published clinical data sets, the identified transcriptomic signature was also associated with viral-induced wheeze exacerbations highlighting the clinical potential of such therapy. Collectively, these results identify airway epithelial restitution via targeting the PI3K-integrin α5β1 axis as a potentially novel therapeutic avenue for childhood wheeze and asthma. We propose that the next step in the therapeutic development process should be a proof-of-concept clinical trial, since relevant animal models to test the crucial underlying premise are unavailable.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".