The Tie2-agonist Vasculotide rescues mice from influenza virus infection
Bibliographic record
Abstract
Seasonal influenza virus infections cause hundreds of thousands of deaths annually while viral mutation raises the threat of a novel pandemic strain. Antiviral drugs exhibit limited efficacy unless administered early and may induce viral resistance. Thus, targeting the host response directly has been proposed as a novel therapeutic strategy with the added potential benefit of not eliciting viral resistance. Severe influenza virus infections are complicated by respiratory failure due to the development of lung microvascular leak and acute lung injury. We hypothesized that enhancing lung endothelial barrier integrity could improve the outcome. Here we demonstrate that the Tie2-agonist tetrameric peptide Vasculotide improves survival in murine models of severe influenza, even if administered as late as 72 hours after infection; the benefit was observed using three strains of the virus and two strains of mice. The effect required Tie2, was independent of viral replication and did not impair lung neutrophil recruitment. Administration of the drug decreased lung edema, arterial hypoxemia and lung endothelial apoptosis; importantly, Vasculotide is inexpensive to produce, is chemically stable and is unrelated to any Tie2 ligands. Thus, Vasculotide may represent a novel and practical therapy for severe infections with 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".