Acinetobacter baumannii Infection Inhibits Airway Eosinophilia and Lung Pathology in a Mouse Model of Allergic Asthma
Bibliographic record
Abstract
Allergic asthma is a dysregulation of the immune system which leads to the development of Th2 responses to innocuous antigens (allergens). Some infections and microbial components can re-direct the immune response toward the Th1 response, or induce regulatory T cells to suppress the Th2 response, thereby inhibiting the development of allergic asthma. Since Acinetobacter baumannii infection can modulate lung cellular and cytokine responses, we studied the effect of A. baumannii in modulating airway eosinophilia in a mouse model of allergic asthma. Ovalbumin (OVA)-sensitized mice were treated with live A. baumannii or phosphate buffered saline (PBS), then intranasally challenged with OVA. Compared to PBS, A. baumannii treatment significantly reduced pulmonary Th2 cytokine and chemokine responses to OVA challenge. More importantly, the airway inflammation in A. baumannii-treated mice was strongly suppressed, as seen by the significant reduction of the proportion and the total number of eosinophils in the bronchoalveolar lavage fluid. In addition, A. baumannii-treated mice diminished lung mucus overproduction and pathology. However, A. baumannii treatment did not significantly alter systemic immune responses to OVA. Serum OVA-specific IgE, IgG1 and IgG2a levels were comparable between A. baumannii- and PBS-treated mice, and tracheobronchial lymph node cells from both treatment groups produced similar levels of Th1 and Th2 cytokines in response to in vitro OVA stimulation. Moreover, it appears that TLR-4 and IFN-γ were not directly involved in the A. baumannii-induced suppression of airway eosinophilia. Our results suggest that A. baumannii inhibits allergic airway inflammation by direct suppression of local pulmonary Th2 cytokine responses to the allergen.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".