Lipoxygenase-derived lipid mediators effectively regulate influenza-induced immunopathology.
Bibliographic record
Abstract
Abstract Despite the worldwide application of vaccination and other antiviral interventions, influenza A virus (IAV) infection still remains a serious threat to humans. The success of IAV infection is linked to its ability to cause lower airways infections, which activates alveolar macrophages and often leads to a cytokine storm, pneumonia and respiratory failure. At this stage, uncontrolled host inflammatory response is the major cause of death. Therefore, understanding the mechanisms of immune regulation during IAV infection is critical in preventing IAV-induced immunopathology and mortality. Although cytokines have been extensively studied in immunity to IAV infection, little is known about the role of eicosanoids. We have recently demonstrated that cyclooxygenase-derived PGE2 plays a deleterious role in protection against IAV infection by inhibiting antiviral type I interferon (IFN). Herein, we aimed to investigate the potential contribution of lipoxygenase (LOX)-derived lipid mediators in IAV-immunity using the 5-LOX (Alox5 −/−) deficient mice. Our data indicate that despite reduced pulmonary IAV titers, Alox5 −/− mice are more susceptible to infection and exogenous administration of stable lipoxin A4 restore protection to IAV in Alox5 −/− mice. This increased susceptibility was coupled with enhanced immunopathology and decreased pulmonary function. Remarkably, the production of type I IFN and IL-10 were significantly reduced in the lungs of IAV-infected Alox5 −/− mice as well as IAV-infected Alox5 −/− macrophages. Collectively these findings identified a protective role of the LOX-derived lipids against IAV-induced immunopathology and may pave the way for novel anti-influenza treatments using stable bioactive lipids.
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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".