Manipulating Fluid Flow in Mechanoadaptation of Bone

骨骼对机械载荷很敏感，或者说“机械敏感”。它通过制造更多的骨骼来应对增加的负荷，通过移除骨骼来应对减少的负荷。这个项目将利用组织、细胞和分子水平的分析，研究机械信号如何转化为生物反应。研究将揭示如何通过调整施加在活老鼠胫骨上的载荷的速度和大小来优化机械信号。将通过成像方法来评估新骨在哪里对负荷做出反应。其中包括高分辨率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，还将测量小鼠胫骨中钙信号进入骨细胞的内流。这些测量将指示细胞级别的响应如何随不同的加载协议而变化。分子成像技术将被用来确定骨细胞对负荷做出反应时产生了什么蛋白质。老年小鼠和年轻小鼠的骨骼将进行比较，看看这种反应如何随着年龄的变化而变化。这项工作将提供有关如何优化机械负荷以导致骨形成的见解，这将有助于为运动和康复治疗提供信息，以保持骨健康。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：液体峰值速度和液体信号(液体速度随时间的积分)。通过探索计算孔弹性有限元模型中载荷分布的影响，将设计载荷分布以分别优化成熟骨和老年骨中的每个刺激以及同时优化每个刺激。载荷分布对组织水平的影响将通过测量骨形成量来观察。机械负荷过程中的细胞信号将通过体内钙报告骨细胞的多光子成像来确定。这将表明细胞是否对流体峰值速度或流体信号(存在流体诱导剪应力的时间量)敏感。荧光原位杂交(FISH)将被用来定量评估与机械适应相关的基因的细胞内信号(MANHO-RNA)。这项研究不仅将提供对负荷适应的机械性理解，还将促进在细胞和分子水平上探索机械适应的成像和评估技术。这项工作由生物力学与机械生物学和生理机制与生物力学项目共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.