A Novel Technique for Imaging and Analysis of Hair Cells in the Organ of Corti Using Modified Sca/eS and Machine Learning
A Novel Technique for Imaging and Analysis of Hair Cells in the Organ of Corti Using Modified Sca/eS and Machine Learning
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DOI：
10.21769/bioprotoc.3342
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发表时间：
2019-08-20
期刊：
影响因子：
0.8
通讯作者：
Yamasoba, Tatsuya
中科院分区：
文献类型：
--
作者：
Urata, Shinji;Iida, Tadatsune;Yamasoba, Tatsuya
在这里，我们描述了一种基于胆固醇的光学清除方法，称为修改后的Sca/eS，可用于成像小鼠耳蜗中的所有毛细胞（HC）。Sca/eS的这种修饰由三个步骤定义：脱钙、脱脂和折射率匹配，这些步骤都可以在72小时内完成。此外，我们建立了自动分析程序，执行基于机器学习的模式识别。这些程序生成1）HC的线性化图像，2）HC的坐标，3）全息耳蜗图，以及4）HC损失的集群。总之，一种新的方法，整合了修改后的Sca/eS和基于机器学习的程序，有利于定量和全面分析所有HC的生理和病理特性。
Here, we describe a sorbitol-based optical clearing method, called modified Sca/eS that can be used to image all hair cells (HCs) in the mouse cochlea. This modification of Sca/eS is defined by three steps: decalcification, de-lipidation, and refractive index matching, which can all be completed within 72 h. Furthermore, we established automated analysis programs that perform machine learning-based pattern recognition. These programs generate 1) a linearized image of HCs, 2) the coordinates of HCs, 3) a holocochleogram, and 4) clusters of HC loss. In summary, a novel approach that integrates modified Sca/eS and programs based on machine learning facilitates quantitative and comprehensive analysis of the physiological and pathological properties of all HCs.