TNF-α and Macrophages Are Critical for Respiratory Syncytial Virus–Induced Exacerbations in a Mouse Model of Allergic Airways Disease
Bibliographic record
Abstract
Viral respiratory infections trigger severe exacerbations of asthma, worsen disease symptoms, and impair lung function. To investigate the mechanisms underlying viral exacerbation, we established a mouse model of respiratory syncytial virus (RSV)-induced exacerbation after allergen sensitization and challenge. RSV infection of OVA-sensitized/challenged BALB/c mice resulted in significantly increased airway hyperresponsiveness (AHR) and macrophage and neutrophil lung infiltration. Exacerbation was accompanied by increased levels of inflammatory cytokines (including TNF-α, MCP-1, and keratinocyte-derived protein chemokine [KC]) compared with uninfected OVA-treated mice or OVA-treated mice exposed to UV-inactivated RSV. Dexamethasone treatment completely inhibited all features of allergic disease, including AHR and eosinophil infiltration, in uninfected OVA-sensitized/challenged mice. Conversely, dexamethasone treatment following RSV-induced exacerbation only partially suppressed AHR and failed to dampen macrophage and neutrophil infiltration or inflammatory cytokine production (TNF-α, MCP-1, and KC). This mimics clinical observations in patients with exacerbations, which is associated with increased neutrophils and often poorly responds to corticosteroid therapy. Interestingly, we also observed increased TNF-α levels in sputum samples from patients with neutrophilic asthma. Although RSV-induced exacerbation was resistant to steroid treatment, inhibition of TNF-α and MCP-1 function or depletion of macrophages suppressed features of disease, including AHR and macrophage and neutrophil infiltration. Our findings highlight critical roles for macrophages and inflammatory cytokines (including TNF-α and MCP-1) in viral-induced exacerbation of asthma and suggest examination of these pathways as novel therapeutic approaches for disease management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| 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".