The Prostanoid 15-Deoxy-Δ12,14-Prostaglandin-J2 Reduces Lung Inflammation and Protects Mice Against Lethal Influenza Infection
Bibliographic record
Abstract
BACKGROUND: Growing evidence indicates that influenza pathogenicity relates to altered immune responses and hypercytokinemia. Therefore, dampening the excessive inflammatory response induced after infection might reduce influenza morbidity and mortality. METHODS: Considering this, we investigated the effect of the anti-inflammatory molecule 15-deoxy-Δ(12,14)-prostaglandin J(2) (15d-PGJ(2)) in a mouse model of lethal influenza infection. RESULTS: Administration of 15d-PGJ(2) on day 1 after infection, but not on day 0, protected 79% of mice against lethal influenza infection. In addition, this treatment considerably reduced the morbidity associated with severe influenza infection. Our results also showed that treatment with 15d-PGJ(2) decreased influenza-induced lung inflammation, as shown by the diminished gene expression of several proinflammatory cytokines and chemokines. Unexpectedly, 15d-PGJ(2) also markedly reduced the viral load in the lungs of infected mice. This could be attributed to maintained type I interferon gene expression levels after treatment. Interestingly, pretreatment of mice with a peroxisome proliferator-activated receptor gamma (PPARγ) antagonist before 15d-PGJ(2) administration completely abrogated its protective effect against influenza infection. CONCLUSIONS: Our results demonstrate for the first time that treatment of mice with 15d-PGJ(2) reduces influenza morbidity and mortality through activation of the PPARγ pathway. PPARγ agonists could thus represent a potential therapeutic avenue for influenza infections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".