Toll-Like Receptor 2 Represses Nonpilus Adhesin-Induced Signaling in Acute Infections with the <i>Pseudomonas aeruginosa pilA</i> Mutant
Bibliographic record
Abstract
Expression of pili and associated proteins is an important means of host invasion by bacterial pathogens. Recent evidence has suggested that the binding of Pseudomonas aeruginosa through nonpilus adhesins may also be important in respiratory diseases, since adhesins bind mucins. Using wild-type C57BL/6 and TLR2KO mice, we compared the induction levels of the host response to P. aeruginosa that either expressed pili or lacked pilus expression due to a mutation in the structural gene pilA. In C57BL/6 mice, deletion of pili led to a decreased immune response, evidenced by a lower secretion of cytokines and a lack of neutrophil chemotaxis. By contrast, the P. aeruginosa pilA mutant induced a hyperresponsive phenotype in TLR2KO mice. TLR2KO mice showed an increased number of neutrophils in lavage fluid compared to the levels seen when either mouse strain was exposed to wild-type P. aeruginosa. Further analysis indicated that the increased neutrophil influx was associated with an increased expression of calgranulins, possibly through an induction of Toll-like receptor 4 (TLR4) expression. The hyperresponsive phenotype of TLR2KO mice exposed to the P. aeruginosa pilA mutant was associated with TLR4 induction and indicated that nonpilus adhesin-induced signaling was repressed by TLR2 function and, if not blocked by the host, could induce airway hyperresponsiveness.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".