Manipulating Fluid Flow in Mechanoadaptation of Bone

骨骼对机械负荷很敏感，或者说“机械敏感”。它通过制造更多的骨头来应对增加的负荷，通过带走骨头来应对减少的负荷。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在活体小鼠胫骨上的负荷的速度和大小来优化机械信号。通过成像方法评估新骨在载荷作用下的位置。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。在不同的机械负荷条件下，还将测量钙信号进入小鼠胫骨骨细胞的通量。这些测量将表明细胞水平的响应如何随不同的加载方案而变化。一种分子成像技术将被用来确定骨细胞在对负荷作出反应时产生了什么蛋白质。老年老鼠和年轻老鼠的骨头将被比较，看看反应是如何随着年龄的变化而变化的。这项工作将提供关于如何优化机械负荷导致骨形成的见解，这可以帮助告知运动和康复疗法，以保持骨骼健康。本项目将使用小鼠体内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）。通过在计算孔隙弹性有限元模型中探索加载剖面的影响，将设计加载剖面来优化每种刺激分别以及成熟和衰老骨骼中的加载剖面。加载剖面对组织水平的影响将通过测量骨形成量来观察。机械负荷期间的细胞信号将通过钙报告骨细胞的体内多光子成像来确定。这将表明单元格是否对峰值流体速度或流体信号（流体引起的剪切应力存在的时间）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对负荷适应的机制理解，而且将推动成像和评估技术在细胞和分子水平上探索机械适应。这项工作是由生物力学与生物力学和生理机制与生物力学项目共同资助的。该奖项反映了美国国家科学基金会的法定使命，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。

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.