Viral Anti-Inflammatory Proteins Target Diverging Immune Pathways with Converging Effects on Arterial Dilatation, Plaque and Apoptosis
Bibliographic record
Abstract
Abdominal aortic aneurysms are often fatal due to atherosclerosis, thromboembolism, rupture, and hemorrhage, however, treatment is limited to expectant monitoring and surgical intervention. Inflammation is detected in aneurysms and in plaque with associated increased apoptosis, chemokines, cytokines, hemorrhage, and thrombosis. We compared treatment with three different myxomavirus-derived anti-inflammatory proteins targeting apoptosis, thrombosis, and chemokine pathways. The effect of each protein on aortic dilatation and plaque growth was assessed after angioplasty in Apolipoprotein E null mice. Four myxomavirus-derived proteins were studied; Serp-1 a serine protease inhibitor (serpin) targeting thrombotic and thrombolytic proteases, Serp-2 a cross-class serpin inhibiting granzyme B and caspases 1 and 8, M-T7 a broad spectrum C, CC, and CXC chemokine inhibitor, and R171E, an inactive M-T7 mutant. Cell invasion, elastin breaks, plaque progression, and aortic dilatation were significantly reduced by Serp-1, Serp-2, or M-T7 protein treatment, but not by R171E. PCR array analysis detected altered expression of a group of shared 40 apoptotic genes in monocytes after treatment with each active protein, but not R171E. Interference with inflammatory cell responses, through highly divergent inflammatory response pathways, produces similar reductions in monocyte invasion, arterial dilatation, and plaque growth potentially through modified expression of apoptotic genes.
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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) | 0.000 | 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".