Corticosteroid-resistant inflammatory signalling in<i>Pseudomonas</i>-infected bronchial cells
Bibliographic record
Abstract
Decreasing the inflammatory response that leads to tissue damage during cystic fibrosis (CF) lung disease has been a long-standing goal of CF therapy. While corticosteroids are widely used anti-inflammatory drugs, their efficacy in CF lung disease remains debated. The complex interaction between the colonising bacteria and the host environment may impact corticosteroid responsiveness. In this study, sputum samples from adult CF patients were collected at baseline and during pulmonary exacerbation episodes. Lung function measurements and sputum microbiological analyses were performed. In parallel, the inflammatory response and corticosteroid sensitivity of airway epithelial cells to Pseudomonas -derived exoproducts was investigated. We report that adult CF patients colonised with mucoid Pseudomonas aeruginosa have higher levels of baseline inflammation, more frequent exacerbations and worse lung function compared with patients colonised with nonmucoid P. aeruginosa . Moreover, mucoid P. aeruginosa activates NF-κB via Toll-like receptor (TLR) 2, which acts in an additive manner to TLR5 to drive inflammation in airway epithelial cells. Furthermore, TLR2-mediated intracellular signalling is more resistant to the anti-inflammatory effects of corticosteroid when compared with other TLR signalling pathways. Overall, these results suggest that airway inflammation triggered by mucoid P. aeruginosa is less responsive to the anti-inflammatory action of corticosteroids. Whether this translates into a diminished response of CF patients to corticosteroid therapy should be examined in future clinical studies.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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 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".