Innate Immunity Mediated by TLR5 as a Novel Antiinflammatory Target for Cystic Fibrosis Lung Disease
Bibliographic record
Abstract
Novel therapies to target lung inflammation are predicted to improve the lives of people with cystic fibrosis (CF) but specific antiinflammatory targets have not been identified. The goal of this study was to establish whether TLR5 signaling is the key molecular pathway mediating lung inflammation in CF, and to determine whether strategies to inhibit TLR5 can reduce the damaging inflammatory response. The innate immune responses were analyzed in both airway epithelial cells and primary PBMCs from CF patients and matched controls. Additionally, 151 clinical isolates of Pseudomonas aeruginosa from CF patients were assessed for motility and capacity to activate TLR5. Blood and airway cells from CF patients produced significantly more proinflammatory cytokine than did control cells following exposure to the CF pathogens P. aeruginosa and Burkholderia cepacia complex (p < 0.001). Stimulation with pure TLR ligands demonstrated that TLR signaling appears to mediate the excessive cytokine production occurring in CF. Using complementary approaches involving both neutralizing Ab targeting TLR5 and flagellin-deficient bacteria, we established that inhibition of TLR5 abolished the damaging inflammatory response generated by CF airway cells following exposure to P. aeruginosa (p < 0.01). The potential therapeutic value of TLR5 inhibition was further supported by our demonstration that 75% of clinical isolates of P. aeruginosa retained TLR5 activating capacity during chronic CF lung infection. These studies identify the innate immune receptor TLR5 as a novel antiinflammatory target for reducing damaging lung inflammation in CF.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".