Blood Systems Biology

 描述（由申请人提供）：为响应PAR-12-138，本提案重点关注人血液的综合和高通量功能表型分析，与系统生物学和生物工程方法相匹配，用于计算机模型的患者特定培训，以识别和量化对凝血触发物或药理学试剂的反应。一个由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小组将在复杂血液动力学条件下的凝血层次背景下研究人类血小板遗传学和信号传导、凝血蛋白酶和血液生化。四个具体目标是：目的1探讨从调节性止血到血栓形成再到栓塞的转变，重点是血小板收缩力、纤维蛋白形成和血管性血友病因子解折叠。实验和模型构建将包括接触途径激活及其触发，与体外诊断相关 和潜在的抗血栓治疗。计算机模拟集中在分子，细胞和局部冠状动脉尺度，包括使用来自健康个体的血液参数导出的数据驱动模型。目标2将侧重于使用患者特定的血小板/凝血模型和通过CT血管造影术获得的患者自身的完整冠状动脉解剖结构模拟急性心肌梗死（aMI）。然后，将创建一个大型计算机模拟患者队列，对aMI严重程度指标进行评分，以确定多维风险因素和药物疗效。目标3将利用动脉血栓形成的动脉小鼠激光损伤模型来创建批内转运和反应的体内数据集，从而为测试系统生物学预测提供体内设置。体内工作将强调使用专门为此研究开发的新型荧光传感器。总的来说，这些方法代表了血小板信号模型与调节粘附功能和血浆蛋白酶网络的现实和分层血流动力学/传质模拟的完全整合。在血液动力学条件下更好地阐明和定量测量血液反应和血小板信号传导途径，是针对血栓形成风险评估、更安全和更集中的抗凝剂或抗血小板治疗以及卒中研究的临床需求。

 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.