CAREER: Mathematical Modeling to Identify New Regulatory Mechanisms of Blood Clotting

职业：通过数学模型确定新的凝血调节机制

• 批准号: 2341362
• 负责人: Karin Leiderman
• 金额: $ 51万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2341362&HistoricalAwards=false
• 关键词: CAREER; Mathematical; Modeling; Identify; New

This CAREER project will develop new mathematical models and numerical methods for simulating blood clotting and identifying regulatory mechanisms within the blood clotting system. In response to vessel injuries, blood will clot to prevent bleeding. The clotting response is complex and involves numerous biochemical and biophysical components working together under the influence of flow. Certain diseases or drugs may cause clots to form improperly, resulting in life-threatening bleeding or pathological clot growth with vessel occlusion. Due to the intricate biochemical and biophysical aspects of the clotting system, predicting its responses and identifying the regulatory mechanisms underlying these responses is difficult. Mathematical models of blood clotting provide powerful tools for designing new drugs, experiments, and patient-specific therapies, but there are still great challenges in formulating such models. This research focuses on developing new mathematical models of essential biochemical players and their involvement in complex biophysical processes. These models will be used to test hypotheses related to regulation of blood clotting and optimal drug design. Additionally, graduate students will be trained in interdisciplinary research and help to organize summer workshops in mathematical biology. The workshops will be offered to local community college students, with the goal being their recruitment and retention into four-year programs by offering active learning, faculty and graduate student mentoring, peer networking, and timely advising. This research will build a comprehensive modeling framework coupling the biochemistry, biophysics, and biomechanics of blood clotting. It will address mechanistic questions about regulating the generation and sequestration of thrombin, the most important enzyme in the clotting process. Specifically, the research will focus on (1) development of a mathematical model that accurately describes thrombin's binding to fibrin (the polymer that stabilizes growing blood clots) and explains the extended periods of time that thrombin has been observed to stay bound to fibrin under flow, (2) development of a mathematical model that incorporates a new, platelet-dependent mechanism to inhibit thrombin generation and explains observed inhibition under flow, and (3) development of a new numerical method to model platelets as discrete objects immersed in a fluid, interacting elastically, responding to molecules in the surrounding fluid, and carrying information via molecules bound to their surfaces.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该职业项目将开发新的数学模型和数值方法，用于模拟血液凝固并识别血液凝固系统内的调节机制。为了应对血管损伤，血液会凝结以防止出血。凝血反应很复杂，涉及许多生化和生物物理成分在血流的影响下协同工作。某些疾病或药物可能会导致血栓形成不当，导致危及生命的出血或病理性血栓生长并导致血管闭塞。由于凝血系统复杂的生化和生物物理方面，预测其反应并确定这些反应背后的调节机制是很困难的。血液凝固的数学模型为设计新药、实验和患者特异性疗法提供了强大的工具，但制定此类模型仍面临巨大挑战。这项研究的重点是开发重要生化参与者及其参与复杂生物物理过程的新数学模型。这些模型将用于测试与凝血调节和最佳药物设计相关的假设。此外，研究生将接受跨学科研究培训，并帮助组织数学生物学夏季研讨会。这些研讨会将向当地社区学院的学生提供，目的是通过提供主动学习、教师和研究生指导、同伴网络和及时建议来招募和保留他们进入四年制课程。这项研究将建立一个耦合血液凝固的生物化学、生物物理学和生物力学的综合建模框架。它将解决有关调节凝血酶（凝血过程中最重要的酶）的产生和隔离的机制问题。具体来说，该研究将集中于 (1) 开发一个数学模型，该模型准确描述凝血酶与纤维蛋白（稳定生长血栓的聚合物）的结合，并解释观察到凝血酶在流动下与纤维蛋白保持结合的较长时间，（2）开发了一种数学模型，该模型结合了一种新的血小板依赖性机制来抑制凝血酶生成并解释了在流动下观察到的抑制，以及（3）开发了一种新的数值方法，将血小板建模为浸入水中的离散物体一种流体，弹性相互作用，对周围流体中的分子做出反应，并通过与其表面结合的分子携带信息。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。