Myxoma viral serpin, Serp-1, a unique interceptor of coagulation and innate immune pathways
Bibliographic record
Abstract
Serpins maintain haemostasis through regulation of serine proteinases in the thrombotic and thrombolytic pathways. Viruses encode serpins that can alter thrombotic and thrombolytic responses producing, in some cases, disseminated intravascular coagulation (DIC). However, it has not been precisely defined how viral serpins induce these profound responses. The rabbit myxoma viral serpin, Serp-1 inhibits urokinase- and tissue-type plasminogen activators (uPA and tPA), plasmin and factor Xa in vitro and exhibits remarkable anti-inflammatory activity in various animal models. The effects of Serp-1 on activation of human platelets, endothelial cells, monocytes and T cells that mediate thrombosis and innate immune responses were therefore examined. We found that Serp-1 attenuated platelet and mononuclear cell adhesion to fibronectin and collagen. Serp-1 similarly inhibited monocyte migration into the peritoneum. Serp-1 inhibition of monocyte migration was lost in uPA receptor (uPAR) deficient mice. Serp-1 bound to the plasma membrane surface and altered uPA activation of endothelial cells (p=0.001), thrombin activation of platelets (p=0.021) and phorbol ester activation of endothelial (p=0.047), monocyte (p=0.011) and Jurkat T cells (p=0.012) as measured by intracellular calcium. Modulation of cellular activation was confirmed by membrane fluidity analysis. Microarray analysis of Serp-1 treated endothelial cells revealed alterations in Inositol 1,4,5-triphosphate receptor type II (ITPR2) a calcium-regulating gene. This study demonstrates the unique capacity of a viral serpin, Serp-1 to modify adhesion, activation, gene expression and calcium homeostasis in a wide range of cells that regulate coagulation and inflammation. Endothelial cells potentially represent a pivotal regulatory point for Serp-1 anti-inflammatory activity.
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".