Targeting PI3K-p110α Suppresses Influenza Virus Infection in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: Chronic obstructive pulmonary disease (COPD) and influenza virus infections are major global health issues. Patients with COPD are more susceptible to infection, which exacerbates their condition and increases morbidity and mortality. The mechanisms of increased susceptibility remain poorly understood, and current preventions and treatments have substantial limitations. OBJECTIVES: To characterize the mechanisms of increased susceptibility to influenza virus infection in COPD and the potential for therapeutic targeting. METHODS: We used a combination of primary bronchial epithelial cells (pBECs) from COPD and healthy control subjects, a mouse model of cigarette smoke-induced experimental COPD, and influenza infection. The role of the phosphoinositide-3-kinase (PI3K) pathway was characterized using molecular methods, and its potential for targeting assessed using inhibitors. MEASUREMENTS AND MAIN RESULTS: COPD pBECs were susceptible to increased viral entry and replication. Infected mice with experimental COPD also had more severe infection (increased viral titer and pulmonary inflammation, and compromised lung function). These processes were associated with impaired antiviral immunity, reduced retinoic acid-inducible gene-I, and IFN/cytokine and chemokine responses. Increased PI3K-p110α levels and activity in COPD pBECs and/or mice were responsible for increased infection and reduced antiviral responses. Global PI3K, specific therapeutic p110α inhibitors, or exogenous IFN-β restored protective antiviral responses, suppressed infection, and improved lung function. CONCLUSIONS: The increased susceptibility of individuals with COPD to influenza likely results from impaired antiviral responses, which are mediated by increased PI3K-p110α activity. This pathway may be targeted therapeutically in COPD, or in healthy individuals, during seasonal or pandemic outbreaks to prevent and/or treat influenza.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".