Deleterious impact of <i>Pseudomonas aeruginosa</i> on cystic fibrosis transmembrane conductance regulator function and rescue in airway epithelial cells
Bibliographic record
Abstract
The epithelial response to bacterial airway infection, a common feature of lung diseases such as chronic obstructive pulmonary disease and cystic fibrosis, has been extensively studied. However, its impact on cystic fibrosis transmembrane conductance regulator (CFTR) channel function is not clearly defined. Our aims were, therefore, to evaluate the effect of Pseudomonas aeruginosa on CFTR function and expression in non-cystic fibrosis airway epithelial cells, and to investigate its impact on ΔF508-CFTR rescue by the VRT-325 corrector in cystic fibrosis cells. CFTR expression/maturation was evaluated by immunoblotting and its function by short-circuit current measurements. A 24-h exposure to P. aeruginosa diffusible material (PsaDM) reduced CFTR currents as well as total and membrane protein expression of the wildtype (wt) CFTR protein in CFBE-wt cells. In CFBE-ΔF508 cells, PsaDM severely reduced CFTR maturation and current rescue induced by VRT-325. We also confirmed a deleterious impact of PsaDM on wt-CFTR currents in non-cystic fibrosis primary airway cells as well as on the rescue of ΔF508-CFTR function induced by VRT-325 in primary cystic fibrosis cells. These findings show that CFTR function could be impaired in non-cystic fibrosis patients infected by P. aeruginosa. Our data also suggest that CFTR corrector efficiency may be affected by infectious components, which should be taken into account in screening assays of correctors.
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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 | 0.001 |
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".