journal article·2011-06

Sequential co-immobilization of thrombomodulin and endothelial protein C receptor on polyurethane: Activation of protein C

K.E. Kador, T.G. Mamedov, M. Schneider, A. Subramanian

Acta Biomaterialia· Volume 7· Issue 6
Publisher page

Abstract

In an effort to control the surface-mediated activation of thrombin and clot formation, proteins and molecules which mimic the anticoagulant properties of the vascular endothelial lining were immobilized on material surfaces. When immobilized on biomaterial surfaces, thrombomodulin (TM), an endothelial glycoprotein that binds thrombin and activates protein C (PC), was shown to generate activated PC (APC) and delay clot formation. However, TM-mediated activation of PC on biomaterial surfaces was shown to be limited by the transport of PC to the surface, with maximum activation obtained at a surface density of ∼40 fmole TM cm(-2). This work investigates surface immobilized with TM and endothelial protein C receptor (EPCR), a natural cofactor to TM which increases the rate of activation of PC on the native endothelium. A sequential and ordered immobilization of TM and EPCR on polyurethane at an enzymatically relevant distance (<10 nm) resulted in higher amounts of APC compared with surfaces with immobilized TM or with TM and EPCR immobilized randomly and at TM surface densities (1400 fmole cm(-2)) which were previously shown to be transport limited. Ordered TM and EPCR samples also showed increased time to clot formation in experiments with platelet-poor plasma, as measured by thromboelastography. Surfaces immobilized with TM and its natural cofactor EPCR at an enzymatically relevant distance are able to overcome transport limitations, increasing anticoagulant activation and time to clot formation.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Blood Coagulation and Thrombosis Mechanisms · Atrial Fibrillation Management and Outcomes · Hemostasis and retained surgical items

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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