The Development of Early Host Response to Pseudomonas aeruginosa Lung Infection Is Critically Dependent on Myeloid Differentiation Factor 88 in Mice
Bibliographic record
Abstract
Toll-like receptors (TLR) induce distinct patterns of host responses through myeloid differentiation factor 88 (MyD88)-dependent and/or -independent pathways, depending on the nature of the pathogen. Pseudomonas aeruginosa is a cause of serious lung infection in immunocompromised individuals and cystic fibrosis patients. The role of the TLR-MyD88 pathway in P. aeruginosa-induced lung infection in vivo was examined in this study. MyD88-/- mice demonstrated an impaired clearance of P. aeruginosa from the lung. Little or no neutrophil recruitment was observed in the airways of MyD88-/- mice following P. aeruginosa lung infection. This observation was associated with a reduced production of inflammatory mediators that affect neutrophil recruitment, including macrophage-inflammatory protein-2, tumor necrosis factor, and interleukin-1beta in the airways of MyD88-/- mice. Similarly, MyD88-/- mice showed inhibited NF-kappaB activation in the lung following P. aeruginosa infection. Interestingly, P. aeruginosa infection induced a 7.5-fold increase of TLR2 mRNA expression in the lungs of MyD88+/+ mice. Furthermore, host responses to P. aeruginosa lung infection in TLR2-/- and TLR4 mutant mice were partially inhibited compared with the responses of respective control mice. Taken together, our results indicate that the MyD88-dependent pathway is essential for the development of early host responses to P. aeruginosa infection, leading to the clearance of this bacterium, and that TLR2 and TLR4 are involved in this process.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".