Herpesviruses enhance fibrin clot lysis
Bibliographic record
Abstract
The incorporation of virus- and host-derived procoagulant factors initiates clotting directly on the surface of herpesviruses, which is an explanation for their correlation to vascular disease. The virus exploits the resulting thrombin to enhance infection by modulating the host cell through protease activated receptor (PAR) 1 signalling. Prior reports demonstrated that at least one herpesvirus expresses surface annexin A2 (A2), a cofactor for tissue plasminogen activator (tPA)-dependent activation of plasminogen to plasmin. Since plasmin is both a fibrinolytic protease and PAR agonist, we investigated whether herpesviruses enhance fibrinolysis and the effect of plasmin on cell infection. Herpes simplex virus types 1 (HSV1) and 2, and cytomegalovirus (CMV) purified from various cell lines each accelerated the proteolytic activation of plasminogen to plasmin by tPA. Ligand blots identified A2 as one of several plasminogen binding partners associated with the virus when compared to an A2-deficient virus. This was confirmed with inhibitory A2-antibodies. However, A2 was not required for virus-enhanced plasmin generation. HSV1, HSV2 and CMV accelerated tPA-dependent fibrin clot lysis by up to 2.8-fold. Modest plasmin generation and fibrinolysis was detected independent of exogenous tPA, which was inhibited by plasminogen activator inhibitor type-1 and ε-aminocaproic acid; however, the molecular basis remains speculative. Up to a ~6-fold enhancement of infection was provided by plasmin-mediated cell infection. Inhibitory antibodies revealed that plasmin increased HSV1 infection through a mechanism involving PAR2. Thus, virus-enhanced fibrinolysis may help explain the paradox of the highly procoagulant in vitro herpesvirus surface eliciting only relatively weak independent vascular disease risk.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".