Implicit Learning in Osteocyte Network under Mechanical Loading

描述(由申请人提供)：本申请涉及广泛的挑战领域(15)“翻译科学”和特定的挑战主题“15-AR-104骨骼和神经系统”。骨适应需要骨细胞在原位检测机械信号，并将骨细胞网络中的信号整合到骨细胞系统中的适当活动中。据推测，骨细胞网络模拟了一个简单的神经系统，可以通过习惯化和敏感化等基本内隐学习形式获得对体内生物力学刺激的短期记忆。然而，这些行为都没有在骨细胞网络中得到实验证实，关于骨细胞作为神经元网络的行为也知之甚少。骨细胞网络被认为是骨重建过程中的主要力学传感器，是调节骨记忆功能的最有能力的候选者。在这项研究中，我们假设“基本形态的可塑性变化对机械刺激的反应能力是骨细胞网络固有的和基本的特性，而骨细胞网络中的短期记忆可以通过三种基本形式的内隐学习来实现：习惯化、敏感化和经典条件化”。根据我们建立的新的体外骨细胞网络模型和骨细胞钙信号研究的经验，本研究的目的是：(1)通过记录和分析细胞网络中实时传播的[Ca~(2+)]i波，研究骨细胞网络对流体剪切刺激的习惯化、敏化和经典的条件反射行为，并确定骨细胞网络内隐学习过程中的良性和有害的机械刺激；(2)通过使用药物抑制剂或基于siRNA的基因敲除3种蛋白中的一种，研究CaMK通路、缝隙连接细胞间通讯和P2Y2受体在骨细胞网络对机械刺激的习惯性、敏化和经典条件作用中的作用。如果能够克服与骨细胞网络中记忆存储相关的重大挑战，我们将有机会在骨力学转导和基本生理系统的行为研究中开创一个新的范式。这些知识将为寻找治疗骨质疏松症的策略和新药带来深远的好处。骨质疏松症影响着数百万人，经济负担超过100亿美元。这个RC1应用程序提出了一个新的假设，即在机械负荷下，骨细胞网络中存在内隐记忆。我们将分析在不同流体流动刺激模式下的实时细胞内钙波，以研究在体外骨细胞网络中内隐学习的三种基本形式，即习惯化、敏感化和经典条件化。力学传导机制对于了解骨质疏松症的病因和防止太空中的骨丢失具有重要意义。

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (15) "Translational Science" and specific Challenge Topic "15-AR-104 Bone and the Nervous System". Bone adaptation requires osteocytes to detect mechanical signals in situ and integrate the signals in the osteocytic network into appropriate activities in the bone cell system. It is conjectured that a bone cell network mimics a simple neuronal system and can acquire short-term memory to in vivo biomechanical stimuli through the elementary forms of implicit learning, e.g., habituation and sensitization. However, none of these behaviors have been confirmed experimentally in bone cell networks, and little is known about how bone cells behave as a neuronal network. The osteocytic network, recognized as the major mechanical sensor in the bone remodeling process, is the most capable candidate to accommodate the memory function in bone. In this study, we hypothesize that "the ability for elementary forms of plastic change in response to mechanical stimulation is an inherent and fundamental property of the osteocytic network, and the short-term memory in osteocytic networks can be achieved by three elementary forms of implicit learning: habituation, sensitization, and classical conditioning". In the light of our novel in vitro osteocytic network model and experience in calcium signaling research of bone cells, the goals of this study are to: (1) investigate the habituation, sensitization, and classical conditioning behaviors of osteocytic networks to fluid shear stimuli by recording and analyzing the real-time [Ca2+]i wave propagation inside the cell network and to determine the benign and noxious mechanical stimuli in the implicit learning process of osteocytic networks; and (2) investigate the roles of CaMK pathway, gap junction intercellular communication, and P2Y2 receptor in the habituation, sensitization, and classical conditioning of osteocytic networks to mechanical stimuli by using pharmacological inhibitors or siRNA-based knockdown of one of the 3 proteins. If the significant challenges associated with the memory storage in osteocytic network can be overcome, we will have an opportunity to initiate a new paradigm in research of bone mechanotransduction and behavior studies of fundamental physiological systems. The knowledge will profoundly benefit the hunt for strategies and new drugs for the treatment of osteoporosis, which affects millions of people with more than a $10 billion financial burden. This RC1 application proposes to test a novel hypothesis that the implicit memory exists in osteocyte networks under mechanical loading. The real-time intracellular calcium waves in response to various patterns of fluid flow stimulation will be analyzed to study the three elementary forms of implicit learning, i.e., habituation, sensitization, and classical conditioning, in in vitro osteocytic networks. The mechanotransduction mechanisms have a great importance in understanding the etiology of osteoporosis and preventing bone loss in space.