Blood Systems Biology

 描述(申请人提供)：针对PAR-12-138，这项建议侧重于对人类血液进行综合和高通量的功能表型分析，并辅之以系统生物学和生物工程方法，用于针对患者特定的计算机模型进行培训，以确定和量化对凝血触发因素或药理制剂的反应。宾夕法尼亚大学和加州大学伯克利分校的生物工程师、计算科学家、放射科医生和血液学家组成的多人研究团队将在复杂血流动力学条件下的凝血分级背景下研究人类血小板遗传学和信号、凝血蛋白水解酶和血液生化。四个具体目标是：目标1探索从调节止血到血栓形成再到栓塞的转变，重点是血小板收缩力量、纤维蛋白形成和von Willebrand因子的展开。实验和模型构建将包括与体外诊断相关的接触通路激活及其触发因素 以及潜在的抗血栓治疗。计算机模拟集中在分子、细胞和局部冠状动脉规模，包括使用来自健康个体的血液参数得出的数据驱动模型。目的2将使用患者特有的血小板/凝血模型和通过CT血管成像获得的患者自身完整的冠状动脉解剖来模拟急性心肌梗死(AMI)。然后，将创建一个大量的矽肺患者队列，以对急性心肌梗死严重程度进行评分，以确定多维风险因素和药物疗效。AIM 3将利用动脉血栓的小鼠动脉激光损伤模型来创建批次内运输和反应的n个活体数据集，从而为测试系统生物学预测提供在体环境。体内工作将强调使用专门为这项研究开发的新型荧光传感器。总体而言，这些方法代表了血小板信号模型与现实的、分级的血流动力学/质量运输模拟的完全集成，这些模拟调节粘附性结合功能和血浆蛋白酶网络。更好地阐明和定量测量血液动力学条件下的血液反应和血小板信号通路，旨在满足血栓形成风险评估、更安全和更有针对性的抗凝剂或抗血小板治疗以及中风研究的临床需求。

 DESCRIPTION (provided by applicant): In response to PAR-12-138, this proposal focuses on the integrative and high throughput functional phenotyping of human blood, matched by Systems Biology and Bioengineering approaches for patient-specific training of computer models to identify and quantify responses to clotting triggers or pharmacological agents. A multi-investigator team of bioengineers, computational scientists, radiologists, and hematologists at the University of Pennsylvania and UC-Berkeley will investigate human platelet genetics and signaling, blood coagulation proteases, and blood biochemistry in the hierarchical context of clotting under complex hemodynamic conditions. Four specific aims are: Aim 1 explores the transition from regulated hemostasis to thrombosis to embolism with emphasis on platelet contractile forces, fibrin formation, and von Willebrand Factor unfolding. Experiments and model building will include contact pathway activation and its triggers, relevant to in vitro diagnostics and potentially anti-thrombotic therapies. Computer simulations are focused at the molecular, cellular, and local coronary artery scale, including data-driven models derived using blood parameters derived from healthy individuals. Aim 2 will focus on simulation of acute myocardial infarction (aMI) using patient-specific platelet/coagulation models and the patient's own complete coronary anatomy obtained by CT-angiography. Then, a large in silico patient cohort will be created to score aMI severity metrics to identify multidimensional risk factors and drug efficacy. Aim 3 will utilize an arterial mouse laser injury model of arterial thrombosis to create n vivo data sets of intraclot transport and reaction, thus providing an in vivo setting for testing Systems Biology predictions. The in vivo work will emphasize the use of novel fluorescent sensors developed specifically for this research. Overall, these approaches represent the full integration of platelet signaling models with realistic and hierarchical hemodynamic/mass transport simulations that regulate adhesive bond function and plasma protease networks. Better elucidation and quantitative measurement of blood reactions and platelet signaling pathways under hemodynamic conditions are directed at clinical needs in thrombotic risk assessment, safer and more focused anti-coagulant or anti-platelet therapies, and stroke research.