Cigarette smoke activates CFTR through ROS-stimulated cAMP signaling in human bronchial epithelial cells
Bibliographic record
Abstract
Air pollution stimulates airway epithelial secretion through a cholinergic reflex that is unaffected in cystic fibrosis (CF), yet a strong correlation is observed between passive smoke exposure in the home and impaired lung function in CF children. Our aim was to study the effects of low smoke concentrations on cystic fibrosis transmembrane conductance regulator (CFTR) function in vitro. Cigarette smoke extract stimulated robust anion secretion that was transient, mediated by CFTR, and dependent on cAMP-dependent protein kinase activation. Secretion was initiated by reactive oxygen species (ROS) and mediated by at least two distinct pathways: autocrine activation of EP4 prostanoid receptors and stimulation of Ca2+ store-operated cAMP signaling. The response was absent in cells expressing the most common disease-causing mutant F508del-CFTR. In addition to the initial secretion, prolonged exposure of non-CF bronchial epithelial cells to low levels of smoke also caused a gradual decline in CFTR functional expression. F508del-CFTR channels that had been rescued by the CF drug combination VX-809 (lumacaftor) + VX-770 (ivacaftor) were more sensitive to this downregulation than wild-type CFTR. The results suggest that CFTR-mediated secretion during acute cigarette smoke exposure initially protects the airway epithelium while prolonged exposure reduces CFTR functional expression and reduces the efficacy of CF drugs.
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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) | 0.002 | 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".