IRF3 is an integral component in the host defense against Pseudomonas aeruginosa lung infection in mice. (45.6)
Bibliographic record
Abstract
Abstract Pseudomonas aeruginosa is a major opportunistic pathogen. Host defense mechanisms involved in P. aeruginosa lung infection remains incompletely defined. Interferon regulatory factor 3 (IRF3) is a transcription factor and is primarily associated with host defense against viral infections. A role of IRF3 in P. aeruginosa infection has not been reported previously. Here we showed that IRF3 deficiency led to impaired clearance of P. aeruginosa from the lung in mice. P. aeruginosa infection induced IRF3 nucleus translocation, activation of ISRE and production of IFNβ, suggesting that P. aeruginosa induces the IRF3-ISRE-IFN pathway activation. In vitro, macrophages from IRF3 deficient mice showed complete inhibition on the production of CCL5 (RANTES) and CCL10 (IP-10), partial inhibition of CXCL1 (KC) and TNF and no effect on CXCL2 (MIP-2) in response to P. aeruginosa stimulation. In vivo, IRF3 deficient mice showed complete inhibition of CCL5 production and partial or no effects on other cytokine and chemokine production in the bronchoalveolar lavage fluids and lung tissues. Profiling of immune cells in the airways revealed that recruitment of neutrophils and macrophages into the airspace was reduced, while B cell, T cell, NK cells and NKT cells infiltrations were unaffected in IRF3 deficient mice in response to P. aeruginosa lung infection. These data suggest that IRF3 regulates a distinct profile of cytokines and chemokines and selectively modulate neutrophil and macrophage recruitment during P. aeruginosa infection. Thus, IRF3 is an integral component in the host defense against P. aeruginosa lung infection.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".