LasR-deficient Pseudomonas aeruginosa variants increase airway epithelial mICAM-1 expression and enhance neutrophilic lung inflammation
Bibliographic record
Abstract
Pseudomonas aeruginosa causes chronic airway infections, a major determinant of lung inflammation and damage in cystic fibrosis (CF). Loss-of-function lasR mutants commonly arise during chronic CF infections, are associated with accelerated lung function decline in CF patients and induce exaggerated neutrophilic inflammation in model systems. In this study, we investigated how lasR mutants modulate airway epithelial membrane bound ICAM-1 (mICAM-1), a surface adhesion molecule, and determined its impact on neutrophilic inflammation in vitro and in vivo. We demonstrated that LasR-deficient strains induce increased mICAM-1 levels in airway epithelial cells compared to wild-type strains, an effect attributable to the loss of mICAM-1 degradation by LasR-regulated proteases and associated with enhanced neutrophil adhesion. In a subacute airway infection model, we also observed that lasR mutant-infected mice displayed greater airway epithelial ICAM-1 expression and increased neutrophilic pulmonary inflammation. Our findings provide new insights into the intricate interplay between lasR mutants, LasR-regulated proteases and airway epithelial ICAM-1 expression, and reveal a new mechanism involved in the exaggerated inflammatory response induced by lasR mutants.
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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".