Blood Systems Biology

血液系统生物学

基本信息

批准号：
7934185
负责人：
SCOTT L DIAMOND
金额：
$ 77.19万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-01 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7934185
关键词：
Adhesions Adhesives Age Aging Agonist Algorithms Antibodies Antiplatelet Drugs Biological Assay Biological Neural Networks Biology Biomedical Engineering Blood Blood Clot Blood Platelets Blood coagulation Blood specimen Calcium Calibration Clinical Coagulation Process Code Collagen Complex Computer Simulation Convection Cytoplasmic Granules Data Data Set Databases Defect Deposition Development Diamond Diffusion Disease Epoprostenol Epoprostenol Receptors Ethnic Origin Ethnic group Event F2R gene Feedback Female Flow Cytometry Gender Role Genomics Growth Hematocrit procedure Hemorrhage Human In Vitro Individual Integrins Kinetics Laser injury Liquid substance Maps Measurement Measures Metabolic Pathway Metabolism Microfluidic Microchips Microfluidics Modeling Monitor Mus Mutation Neural Network Simulation Operative Surgical Procedures P-Selectin PAWR gene Pathway interactions Patients Peptide Hydrolases Phenotype Phosphatidylserines Plasma Platelet Activation Probability Production Reaction Research Risk Assessment Scanning Signal Pathway Signal Transduction Simulate Staging Stenosis Surface Systems Biology Testing Thrombin Thromboplastin Thrombosis Thrombus Time TimeLine Tracer Training Transgenic Mice VWF gene Validation Venous brass clinically relevant combinatorial experience hemodynamics in vivo inhibitor/antagonist loss of function mutation male mouse model public health relevance receptor release of sequestered calcium ion into cytoplasm research study response simulation stroke therapy synergism vector web site

项目摘要

DESCRIPTION (provided by applicant): 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. High throughput phenotyping of individual blood samples will be used to train bottom-up and top-down models of blood clotting under static, venous, and arterial hemodynamic conditions. Specific Aims are: Aim 1: Use high throughput intracellular calcium measurements to train neural network models to predict patient-specific response to combinatorial and sequential stimulation, thus testing the milieu that platelets actually experience during thrombosis. Furthermore, high throughput measures of inside-out signaling will be implemented for the development of large scale computational simulation of platelet metabolic pathways. Aim 2: Along with platelet phenotyping, we will use validated high throughput blood thrombin phenotyping to identify pathways and synergisms that are defective in patients with existing but undefined defects. These approaches then allow the development of a full platelet-plasma computer simulation of coagulation. Aim 3: Using validated tissue factor microarray-flow chambers and microfluidic chambers, we will functionally phenotype thrombus production and clot stability for normal donors and patients under hemodynamic conditions and pharmacological modulation. Aim 4: In vivo studies using a mouse laser injury model to follow evolving intrathrombic spatial gradients. The flow studies are supported by advanced multiscale Lattice Kinetic Monte Carlo (LKMC) simulation of clotting under flow using data from all three specific aims. These approaches represent the first 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 thrombosis risk assessment, anti-coagulation therapy during surgery, platelet targeted therapies, and stroke research. PUBLIC HEALTH RELEVANCE: Blood is ideal for Systems Biology research since it is easily obtained from donors or patients, amenable to high throughput liquid handling experiments, and clinically relevant. Clotting and bleeding diseases of aging are seldom due to acquired mutations and this drives the need for advanced functional phenotyping in concert with Systems Biology and other sequencing/genomic approaches.

描述（由申请人提供）：该提案侧重于人类血液的综合和高通量功能表型分析，并与系统生物学和生物工程方法相匹配，用于针对患者的计算机模型训练，以识别和量化对凝血触发因素或药物的反应。个体血液样本的高通量表型分析将用于训练静态、静脉和动脉血流动力学条件下自下而上和自上而下的凝血模型。具体目标是：目标 1：使用高通量细胞内钙测量来训练神经网络模型，以预测患者对组合和顺序刺激的特异性反应，从而测试血小板在血栓形成过程中实际经历的环境。此外，将实施由内而外信号传导的高通量测量，以开发血小板代谢途径的大规模计算模拟。目标 2：除了血小板表型分析之外，我们将使用经过验证的高通量血液凝血酶表型分析来识别存在但未明确缺陷的患者中存在缺陷的途径和协同作用。然后，这些方法可以开发完整的血小板-血浆凝血计算机模拟。目标 3：使用经过验证的组织因子微阵列流室和微流体室，我们将对正常供体和患者在血流动力学条件和药理调节下的血栓产生和凝块稳定性进行功能表型分析。目标 4：使用小鼠激光损伤模型来跟踪不断变化的血栓内空间梯度的体内研究。流动研究得到先进的多尺度晶格动力学蒙特卡罗 (LKMC) 模拟的支持，该模拟使用来自所有三个特定目标的数据进行流动下的凝血。这些方法代表了血小板信号传导模型与调节粘合功能和血浆蛋白酶网络的真实且分层的血流动力学/质量传输模拟的首次完全集成。更好地阐明和定量测量血流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、手术期间抗凝治疗、血小板靶向治疗和中风研究的临床需求。公共卫生相关性：血液是系统生物学研究的理想选择，因为它很容易从捐赠者或患者那里获得，适合高通量液体处理实验，并且具有临床相关性。衰老引起的凝血和出血疾病很少是由获得性突变引起的，这推动了对与系统生物学和其他测序/基因组方法相结合的高级功能表型分析的需求。