Myxomavirus-Derived Serpin Prolongs Survival and Reduces Inflammation and Hemorrhage in an Unrelated Lethal Mouse Viral Infection
Bibliographic record
Abstract
Lethal viral infections produce widespread inflammation with vascular leak, clotting, and bleeding (disseminated intravascular coagulation [DIC]), organ failure, and high mortality. Serine proteases in clot-forming (thrombotic) and clot-dissolving (thrombolytic) cascades are activated by an inflammatory cytokine storm and also can induce systemic inflammation with loss of normal serine protease inhibitor (serpin) regulation. Myxomavirus secretes a potent anti-inflammatory serpin, Serp-1, that inhibits clotting factor X (fX) and thrombolytic tissue- and urokinase-type plasminogen activators (tPA and uPA) with anti-inflammatory activity in multiple animal models. Purified serpin significantly improved survival in a murine gammaherpesvirus 68 (MHV68) infection in gamma interferon receptor (IFN-γR) knockout mice, a model for lethal inflammatory vasculitis. Treatment of MHV68-infected mice with neuroserpin, a mammalian serpin that inhibits only tPA and uPA, was ineffective. Serp-1 reduced virus load, lung hemorrhage, and aortic, lung, and colon inflammation in MHV68-infected mice and also reduced virus load. Neuroserpin suppressed a wide range of immune spleen cell responses after MHV68 infection, while Serp-1 selectively increased CD11c(+) splenocytes (macrophage and dendritic cells) and reduced CD11b(+) tissue macrophages. Serp-1 altered gene expression for coagulation and inflammatory responses, whereas neuroserpin did not. Serp-1 treatment was assessed in a second viral infection, mouse-adapted Zaire ebolavirus in wild-type BALB/c mice, with improved survival and reduced tissue necrosis. In summary, treatment with this unique myxomavirus-derived serpin suppresses systemic serine protease and innate immune responses caused by unrelated lethal viral infections (both RNA and DNA viruses), providing a potential new therapeutic approach for treatment of lethal viral sepsis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".