Understanding the Role of Mechanical Boundary Conditions on Tissue Assembly and Repair in 3D Fibrous Microtissues
Understanding the Role of Mechanical Boundary Conditions on Tissue Assembly and Repair in 3D Fibrous Microtissues
批准号:
2311640
负责人:
Emma Lejeune
金额:
$63.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2026-07-31
中文摘要
该奖项将支持将产生关于生物组织组装和修复的新知识的研究。 这项工作既能促进科学进步,又能促进国民健康。组织组装和修复是伤口愈合的基本机制。已知机械力控制组织组装。 然而,力调节新组织形成及其组织的机制仍然知之甚少。从本质上讲,改变组织上的机械力可以促进或抑制伤口愈合。然而,机械力和伤口愈合结果之间的直接关系在很大程度上是未知的。该奖项支持基础研究,以提供有关机械力如何在严格控制的实验室环境中影响组织组装和修复的知识。通过建立一个组合的实验和计算平台来测量机械、化学和生物线索之间的相互作用,这项研究将直接推进工程设备和治疗方法的设计,以促进伤口愈合。因此,这项研究的结果将有利于美国国家健康,经济和社会,因为受损的伤口愈合是一个重要的医学问题。最后,这项工作将包括在中学水平的社区推广,以教育学生关于机械生物学的令人兴奋的领域。这个项目的目标是了解域边界条件(即,控制紧急ECM对准和组织几何形状的边界约束)控制局部组织修复(即,通过基质收缩性和基质沉积的愈合)通过诱导的空间不均匀的机械微环境(即,自组装纤维对准、组织应变和组织应力)。这项工作紧密结合了体外实验和计算建模,其中体外实验建立在先前开发的组织组装和修复的三维体外仿生间隙闭合模型上。本研究将首先建立一个力学计算模型来预测不同微桩结构周围微组织的非均匀应力和应变。然后,将机械计算模型与基于时间推移图像的实验数据相结合,形成一个组合的机械和数据驱动的框架来预测差距闭合过程。最后,该框架将用于定义该体外实验系统的“间隙闭合”和“间隙闭合失败”之间的过渡状态。除了获得有关生物组织组装和修复的知识外,这项工作还将建立一种通用的方法,用于整合机械生物学系统的机械和数据驱动的计算模型。该奖项反映了NSF的法定使命,并被认为值得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来支持。
英文摘要
This award will support research that will generate new knowledge about biological tissue assembly and repair. This work will both promote the progress of science and advance national health. Tissue assembly and repair are the fundamental mechanisms that underly wound healing. It is known that mechanical forces control tissue assembly. However, the mechanisms by which forces regulate new tissue formation and its organization remain poorly understood. Essentially, changing the mechanical forces on a tissue can either promote or suppress wound healing. However, the direct relationship between mechanical forces and wound healing outcomes are largely unknown. This award supports the fundamental research to provide knowledge about how mechanical forces will influence tissue assembly and repair in a tightly controlled laboratory setting. Through establishing a combined experimental and computational platform for measuring the interplay between mechanical, chemical, and biological cues, this research will directly advance the design of engineered devices and therapeutics to promote would healing. Thus, results from this research will benefit the U.S. national health, economy, and society as impaired wound healing is a significant medical problem. Finally, this work will include community outreach at the middle school level to educate students about the exciting field of mechanobiology.The objective of this project is to understand how domain boundary conditions (i.e., the boundary restraints that control emergent ECM alignment and tissue geometry) control local tissue repair (i.e., healing through matrix contractility and matrix deposition) via the induced spatially heterogeneous mechanical microenvironment (i.e., self-assembled fiber alignment, tissue strain, and tissue stress). This work tightly integrates in vitro experiments and computational modeling, where the in vitro experiments build on a previously developed three-dimensional in vitro biomimetic gap closure model of tissue assembly and repair. This work will first establish a mechanistic computational model to predict the heterogeneous stresses and strains of microtissue formed around different micropost configurations. Then, it will integrate the mechanistic computational model with timelapse image based experimental data to form a combined mechanistic and data-driven framework to predict the gap closure process. Finally, this framework will be used to define the transition regime between “gap closure” and “gap closure failure” for this in vitro experimental system. In addition to the knowledge gained about biological tissue assembly and repair, this work will establish a generalizable methodology for integrating mechanistic and data driven computational models for mechanobiological systems.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.
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