Manipulating Fluid Flow in Mechanoadaptation of Bone

骨机械适应中的流体流动控制

• 批准号: 2010010
• 负责人: Sandra Shefelbine
• 金额: $ 65.37万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2010010&HistoricalAwards=false
• 关键词: Manipulating; Fluid; Flow; Mechanoadaptation; Bone

Bone is sensitive to mechanical loads, or “mechano-sensitive”. It responds to increased loading by making more bone and to decreased loading by taking away bone. This project will study how mechanical signals are translated into a biological response using analysis at the tissue, cellular, and molecular level. Investigations will reveal how to optimize the mechanical signal by adjusting the speed and magnitude of a load applied to the tibia bone of a living mouse. Evaluation of where new bone is made in response to the loading will be made by imaging methods. These include high resolution 3D x-ray tomography and fluorescent labeling that can indicate where new bone has formed. The in-flux of calcium signaling into bone cells in a mouse tibia will also be measured under different mechanical loading conditions. These measurements will indicate how the cell-level response changes with different loading protocols. A molecular imaging technique will be used to determine what proteins are being made by the bone cells in response to loading. Bones from old mice and younger mice will be compared to see how the response changes with age. This work will provide insight about how to optimize mechanical loading to cause bone formation, which can help to inform exercise and rehabilitation therapies to keep bone healthy.This project will use the in vivo murine tibial loading model to explore two potential fluid based stimuli: peak fluid velocity and fluid signal (integral of fluid velocity over time). By exploring the effects of loading profiles in a computational poroelastic finite element models, loading profiles will be designed to optimize each stimuli separately as well as both together in mature and aged bone. The effects of the loading profile on the tissue level will be observed by measuring the amount of bone formation. Cellular signaling during mechanical loading will be determined by using in vivo multi-photon imaging of calcium reporter osteocytes. This will indicate if cells are sensitive to peak fluid velocity or fluid signal (the amount of time there is fluid-induced shear stress). Fluorescence in situ hybridization (FISH) will be used to quantitatively assess intracellular signaling of genes involved in mechanoadaptation (mechano-RNA). This study will not only provide a mechanistic understanding of adaptation to load but will also advance imaging and assessment techniques for exploring mechanoadaptation at the cellular and molecular level. This work is co-funded by the Biomechanics & Mechanobiology and the Physiological Mechanisms & Biomechanics programs.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.

骨骼对机械载荷敏感，或“机械敏感”。 它通过制造更多的骨来响应增加的负荷，通过带走骨来响应减少的负荷。该项目将研究机械信号如何通过组织、细胞和分子水平的分析转化为生物反应。 研究将揭示如何通过调整施加到活体小鼠胫骨的负载的速度和大小来优化机械信号。 将通过成像方法评价在哪里形成新骨以响应载荷。 这些包括高分辨率3D X射线断层扫描和荧光标记，可以指示新骨形成的位置。还将在不同的机械负荷条件下测量钙信号传导到小鼠胫骨中的骨细胞中的流入。 这些测量将指示小区级响应如何随不同加载协议而变化。 分子成像技术将用于确定骨细胞对负荷的反应是什么蛋白质。 老年小鼠和年轻小鼠的骨骼将进行比较，以了解反应如何随年龄变化。这项工作将提供关于如何优化机械负荷以引起骨形成的见解，这可以帮助指导运动和康复治疗以保持骨骼健康。本项目将使用体内小鼠胫骨负荷模型来探索两种潜在的基于流体的刺激：峰值流体速度和流体信号（流体速度随时间的积分）。 通过在计算多孔弹性有限元模型中探索载荷分布的影响，载荷分布将被设计为在成熟骨和老化骨中分别优化每种刺激以及一起优化每种刺激。 将通过测量骨形成量来观察载荷分布对组织水平的影响。 将通过使用钙报告骨细胞的体内多光子成像来确定机械负荷期间的细胞信号传导。 这将指示细胞是否对峰值流体速度或流体信号（存在流体诱导的剪切应力的时间量）敏感。 荧光原位杂交（FISH）将用于定量评估参与机械适应（mechano-RNA）的基因的细胞内信号传导。这项研究不仅将提供一个适应负荷的机械理解，但也将推进成像和评估技术，探索机械适应在细胞和分子水平。 这项工作由生物力学机械生物学和生理机制生物力学计划共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。