Automated Analysis of Skeletal Muscle Fiber Cross-sectional Area and Metabolic Ty

描述(由申请人提供)：骨骼肌形态的准确量化在多种医学领域都是必需的，如肌肉再生、肌营养不良、运动生理学和营养。对于这样的研究，骨骼肌通常是固定的，切片的，标记的，以直观地显示肌肉纤维的边界，并进行数字摄影。然后，研究人员使用费时费力的技术来描绘肌肉纤维的轮廓，以计算横截面面积(CSA)。研究人员还标记肌肉组织以确定某些肌球蛋白亚型的表达，但目前的试剂在小鼠身上效果不佳，小鼠是应用最广泛的实验动物。在这个STTR项目的第一阶段，开发了一种算法，并将其纳入Vala的CyteSeer(R)细胞图像分析程序，以实现CSA的快速计算和肌肉中单一肌球蛋白亚型的定量。对于第二阶段，我们建议：1)开发用于识别小鼠肌球蛋白亚型(Slow、IIa、IIb和IIx)、层粘连蛋白和OXPAT的单抗，并用有机荧光团或纳米晶体(也称为量子点)标记单抗，用于直接免疫细胞荧光程序；2)使CyteSeer(R)能够执行多通道分析，用于分析多种肌球蛋白亚型，分析纤维内细胞核的分布(对检测再生纤维或炎症很重要)，或分析与肥胖有关的肌细胞内脂肪和蛋白质，以及3)提高CyteSeer(R)鉴定健康和受损肌肉中纤维的能力，特别是在肌肉营养不良方面。这项研究将开发试剂和软件，大大提高骨骼肌分析的准确性和速度，这是一个在各种健康背景下非常重要的课题。

DESCRIPTION (provided by applicant): The accurate quantification of skeletal muscle morphology is desired in a wide variety of medical areas such as muscle regeneration, muscular dystrophy, exercise physiology, and nutrition. For such studies, skeletal muscle is often fixed, sectioned, and labeled to visualize the borders of the muscle fibers, and digitally photographed. Investigators then use laborious time- consuming techniques to trace the outline of muscle fibers to calculate the cross-sectional area (CSA). Investigators also label muscle tissues to identify the expression of certain myosin subtypes, but current reagents do not work well in the mouse, the most widely utilized experimental animal. In Phase I of this STTR project, an algorithm was developed and incorporated into Vala's CyteSeer(R) cell image analysis program, to enable rapid calculation of CSA, and quantification of a single myosin isoform within the muscle. For Phase II, we propose: 1) to develop monoclonal antibodies (MAbs) for identification of myosin subtypes (slow, IIa, IIb, and IIx), laminin, and OXPAT in the mouse, and to label the MAbs with organic fluorophores or nanocrystals (aka quantum dots) for use in direct immunocytofluorescence procedures, 2) to enable CyteSeer(R) to perform multichannel analysis for the analysis of multiple myosin isoforms, the analyze of distribution of nuclei within the fibers (important to detect regenerating fibers or inflammation), or analysis of intramyocellular lipids and proteins associated with obesity, and 3) to improve the ability of CyteSeer(R) to characterize fibers in healthy and damaged muscle, especially with regard to muscular dystrophy. The research will develop reagents and software which will greatly increase the accuracy and speed with which skeletal muscle can be analyzed a subject of great importance in a variety of health contexts.