LasR-regulated proteases in acute vs. chronic lung infection: a double-edged sword
Why this work is in the frame
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Bibliographic record
Abstract
Pseudomonas aeruginosa is a gram-negative opportunistic pathogen capable of causing both acute and chronic infections, particularly in individuals with compromised host defenses. The quorum sensing transcriptional activator LasR is widely recognized for its role in regulating the expression of acute virulence factors, notably several secreted proteases which cause direct host damage and subvert host immunity in acute infections. Paradoxically, lung infections caused by LasR-deficient variants, which are found in at least a third of cystic fibrosis (CF) patients with chronic P. aeruginosa infections, are associated with accelerated lung disease and increased markers of inflammation compared to infections caused by strains with a functional LasR system. While the loss of LasR function often (although not always) results in impaired production of LasR-controlled acute virulence factors, the implication of this pathoadaptation on host-pathogen interactions and chronic disease pathology is less well recognized. We recently observed that loss of LasR function in lasR variants, which results in impaired secreted protease production, led to increased expression of the membrane-bound surface adhesion molecule mICAM-1 in the airway epithelium, and increased neutrophilic inflammation. Specifically, human airway epithelial cells stimulated with lasR variants had higher mICAM-1 expression and greater neutrophil binding in vitro compared to stimulation with wild-type P. aeruginosa. In a subacute non-lethal P. aeruginosa lung infection model, lasR variant infection also induced higher mICAM-1 expression in the murine airway epithelium and was associated with increased neutrophilic pulmonary inflammation in vivo. Here, we discuss how (loss of) LasR function and LasR-regulated proteases affect host immunity, inflammation and tissue pathology in acute vs. chronic P. aeruginosa lung infection.
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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) | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| 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 it