Dysregulated Notch Signaling in the Airway Epithelium of Children with Wheeze
Bibliographic record
Abstract
The airway epithelium of children with wheeze is characterized by defective repair that contributes to disease pathobiology. Dysregulation of developmental processes controlled by Notch has been identified in chronic asthma. However, its role in airway epithelial cells of young children with wheeze, particularly during repair, is yet to be determined. We hypothesized that Notch is dysregulated in primary airway epithelial cells (pAEC) of children with wheeze contributing to defective repair. This study investigated transcriptional and protein expression and function of Notch in pAEC isolated from children with and without wheeze. Primary AEC of children with and without wheeze were found to express all known Notch receptors and ligands, although pAEC from children with wheeze expressed significantly lower NOTCH2 (10-fold, p = 0.004) and higher JAG1 (3.5-fold, p = 0.002) mRNA levels. These dysregulations were maintained in vitro and cultures from children with wheeze displayed altered kinetics of both NOTCH2 and JAG1 expression during repair. Following Notch signaling inhibition, pAEC from children without wheeze failed to repair (wound closure rate of 76.9 ± 3.2%). Overexpression of NOTCH2 in pAEC from children with wheeze failed to rescue epithelial repair following wounding. This study illustrates the involvement of the Notch pathway in airway epithelial wound repair in health and disease, where its dysregulation may contribute to asthma development.
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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 | 0.000 |
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".