Abstract 363: Thrombin Activatable Fibrinolysis Inhibitor is a Regulator of Angiogenic Potential in Endothelial Cells
Bibliographic record
Abstract
Angiogenesis, the sprouting of new blood vessels from existing vessels, is a process that is fundamental to both normal physiology, as well as disease processes such as atherosclerosis and cancer metastasis. A key regulator of the angiogenesis is the elaboration of pericellular proteolytic activity including plasmin and the matrix metalloproteases (MMPs). Thrombin activatable fibrinolysis inhibitor (TAFI) is a plasma zymogen that can be cleaved by thrombin, plasmin, or thrombin in complex with thrombomodulin (TM) to form activated TAFI (TAFIa). TAFIa cleaves carboxyl terminal lysine and arginine residues from substrates, including plasminogen-binding sites on cell surface receptors. TAFIa is thus a regulator of pericellular plasminogen activation. Plasmin regulates angiogenesis through MMP activation and degradation of the extracellular matrix (ECM). Previous studies have shown that TAFIa downregulates endothelial tube formation in a fibrin matrix, likely through inhibition of fibrin degradation. The current study was undertaken to evaluate if TAFIa is capable of modulating angiogenic responses of endothelial cells in vitro in the context of reconstituted basement membrane. We found that treatment of primary human umbilical vein endothelial cells (HUVECs) with a specific inhibitor of TAFIa, potato tuber carboxypeptidase inhibitor, resulted in an increase in proliferation, invasion, tube formation, and collagen degradation. On the other hand, treatment with a stable variant of TAFIa (TAFIa-CIIYQ) with a 150-fold increased half-life at 37°C resulted in a decrease in HUVEC tube formation and collagen degradation of HUVECs. Furthermore, a mutant soluble form of TM that supports TAFI, but not protein C, activation also had an inhibitory effect on HUVEC tube formation and collagen degradation. Finally, we assessed the effect of TAFIa on plasminogen activation. Treatment of HUVECs with various concentrations of TAFIa resulted in a decrease in uPA-mediated plasminogen activation on the surface of HUVECs. Together these experiments provide direct evidence of an anti-angiogenic effect of TAFIa. Our results suggest that promotion of TAFI activation or TAFIa stability may be viable therapeutic approaches for inhibition of angiogenesis.
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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) | 0.006 | 0.002 |
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".