Treating Viral Exacerbations of Chronic Obstructive Pulmonary Disease: Insights from a Mouse Model of Cigarette Smoke and H1N1 Influenza Infection
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease is a progressive lung disease that is punctuated by periods of exacerbations (worsening of symptoms) that are attributable to viral infections. While rhinoviruses are most commonly isolated viruses during episodes of exacerbation, influenza viruses have the potential to become even more problematic with the increased likelihood of an epidemic. METHODOLOGY AND PRINCIPAL FINDINGS: This study examined the impact of current and potential pharmacological targets namely the systemic corticosteroid dexamethasone and the peroxisome proliferator-activated receptor-gamma agonist pioglitazone on the outcome of infection in smoke-exposed mice. C57BL/6 mice were exposed to room air or cigarette smoke for 4 days and subsequently inoculated with an H1N1 influenza A virus. Interventions were delivered daily during the course of infection. We show that smoke-exposed mice have an exacerbated inflammatory response following infection. While smoke exposure did not compromise viral clearance, precision cut lung slices from smoke-exposed mice showed greater expression of CC (MCP-1, -3), and CXC (KC, MIP-2, GCP-2) chemokines compared to controls when stimulated with a viral mimic or influenza A virus. While dexamethasone treatment partially attenuated the inflammatory response in the broncho-alveolar lavage of smoke-exposed, virally-infected animals, viral-induced neutrophilia was steroid insensitive. In contrast to controls, dexamethasone-treated smoke-exposed influenza-infected mice had a worsened health status. Pioglitazone treatment of virally-infected smoke-exposed mice proved more efficacious than the steroid intervention. Further mechanistic evaluation revealed that a deficiency in CCR2 did not improve the inflammatory outcome in smoke-exposed, virally-infected animals. CONCLUSIONS AND SIGNIFICANCE: This animal model of cigarette smoke and H1N1 influenza infection demonstrates that smoke-exposed animals are differentially primed to respond to viral insult. While providing a platform to test pharmacological interventions, this model demonstrates that treating viral exacerbations with alternative anti-inflammatory drugs, such as PPAR-gamma agonists should be further explored since they showed greater efficacy than systemic corticosteroids.
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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 | 0.001 |
| 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".