Blocking Notch3 Signaling Abolishes MUC5AC Production in Airway Epithelial Cells from Individuals with Asthma
Bibliographic record
Abstract
Abstract In asthma, goblet cell numbers are increased within the airway epithelium, perpetuating the production of mucus that is more difficult to clear and results in airway mucus plugging. Notch1, Notch2, or Notch3, or a combination of these has been shown to influence the differentiation of airway epithelial cells. How the expression of specific Notch isoforms differs in fully differentiated adult asthmatic epithelium and whether Notch influences mucin production after differentiation is currently unknown. We aimed to quantify different Notch isoforms in the airway epithelium of individuals with severe asthma and to examine the impact of Notch signaling on mucin MUC5AC. Human lung sections and primary bronchial epithelial cells from individuals with and without asthma were used in this study. Primary bronchial epithelial cells were differentiated at the air–liquid interface for 28 days. Notch isoform expression was analyzed by Taqman quantitative PCR. Immunohistochemistry was used to localize and quantify Notch isoforms in human airway sections. Notch signaling was inhibited in vitro using dibenzazepine or Notch3-specific siRNA, followed by analysis of MUC5AC. NOTCH3 was highly expressed in asthmatic airway epithelium compared with nonasthmatic epithelium. Dibenzazepine significantly reduced MUC5AC production in air–liquid interface cultures of primary bronchial epithelial cells concomitantly with suppression of NOTCH3 intracellular domain protein. Specific knockdown using NOTCH3 siRNA recapitulated the dibenzazepine-induced reduction in MUC5AC. We demonstrate that NOTCH3 is a regulator of MUC5AC production. Increased NOTCH3 signaling in the asthmatic airway epithelium may therefore be an underlying driver of excess MUC5AC production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".