EAGER: Modeling Multiscale Control of Liver Regeneration

EAGER：肝脏再生的多尺度控制建模

• 批准号: 1747917
• 负责人: Rajanikanth Vadigepalli
• 金额: $ 5万
• 依托单位: Thomas Jefferson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1747917&HistoricalAwards=false
• 关键词: EAGER; Modeling; Multiscale; Control; Liver

Liver disease affects millions of individuals each year. Treatment for liver disease often requires a liver transplant due to the inability of damaged liver tissue to regenerate in many cases. A better understanding how liver tissue is renewed and repaired will improve the ability to develop future interventions. Understanding tissue physiology is often complicated by the fact that cells next to each other do not necessarily respond the same manner. Emerging technologies and analysis methods aimed at high-throughput molecular assays of hundreds-to-thousands of single cells have enabled an unprecedented view of the heterogeneity, hierarchy and complexity of cellular functional states. Multiscale modeling is one tool that can aid in understanding the variation in observable cellular behavior, so this research project is developing a novel multiscale modeling framework that takes advantage of the in-depth information on cellular function that can be obtained from these single cell data sets. This modeling framework bridges from the molecular scale to the tissue scale to enhance knowledge gained about physiology and pathophysiology. While the outputs from this model will support improved understanding and manipulation of tissue response to injury in the liver, it will likely be applicable to understanding other tissues as well. The research team is integrating students of all levels, from high school through graduate school, in this project in order to excite them about scientific research and to provide them with professional development opportunities. The central innovative idea of this project is to realize the full potential of the novel single cell data sets by developing models of cellular functional states and state transitions to bridge the molecular and tissue scales. The team is developing the proposed multiscale modeling framework in the context of understanding the control principles governing the coordinated tissue response to injury. This approach involves explicit accounting of cellular functional states of immune, stromal, endothelial and epithelial cells, and putative molecular processes driving the state transitions, with broad applicability to multiple tissue repair scenarios. The team is focusing on the process of liver regeneration as an enabling testbed in order to fully develop, fine tune and illustrate the multiscale modeling approach for broader application and utility.

肝病每年影响数百万人。肝脏疾病的治疗通常需要肝脏移植，因为在许多情况下受损的肝脏组织无法再生。更好地了解肝脏组织是如何更新和修复的，将提高开发未来干预措施的能力。 理解组织生理学通常是复杂的，因为相邻的细胞不一定以相同的方式反应。针对数百至数千个单细胞的高通量分子测定的新兴技术和分析方法使细胞功能状态的异质性，层次结构和复杂性成为前所未有的观点。多尺度建模是一种可以帮助理解可观察细胞行为变化的工具，因此本研究项目正在开发一种新的多尺度建模框架，该框架利用了可以从这些单细胞数据集获得的细胞功能的深入信息。这个建模框架从分子尺度到组织尺度的桥梁，以增强有关生理学和病理生理学的知识。虽然该模型的输出将支持改善对肝脏损伤的组织反应的理解和操作，但它也可能适用于理解其他组织。研究小组正在将从高中到研究生院的各级学生纳入该项目，以激发他们对科学研究的兴趣，并为他们提供专业发展机会。该项目的核心创新思想是通过开发细胞功能状态和状态转换的模型来实现新的单细胞数据集的全部潜力，以桥接分子和组织尺度。该团队正在开发拟议的多尺度建模框架，以了解协调组织对损伤反应的控制原则。这种方法涉及明确说明免疫，基质，内皮和上皮细胞的细胞功能状态，以及推定的分子过程驱动的状态转换，具有广泛的适用性，以多种组织修复的情况。该团队专注于肝再生过程，作为一个使能的试验平台，以充分开发，微调和说明多尺度建模方法，以获得更广泛的应用和效用。