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视神经轴突数量的高效测定:一种体视学方法。

Efficient determination of axon number in the optic nerve: A stereological approach.

机构信息

Institute of Human Anatomy and Embryology, University of Regensburg, Regensburg, Germany.

Institute of Human Anatomy and Embryology, University of Regensburg, Regensburg, Germany.

出版信息

Exp Eye Res. 2019 Sep;186:107710. doi: 10.1016/j.exer.2019.107710. Epub 2019 Jun 27.

DOI:10.1016/j.exer.2019.107710
PMID:31254512
Abstract

Quantifying the number of axons in the optic nerve is of interest in many research questions. Here, we show that a stereological method allows simple, efficient, precise and unbiased determination of the total axon number in the murine optic nerve. Axons in semi-thin optic nerve cross sections from untreated eyes (n = 21) and eyes subjected to retinal damage by intravitreous NMDA injections (n = 32) or PBS controls (n = 5) were manually identified, counted and digitally labeled by hand. A stereological procedure was empirically tested with systematic combinations of different sampling methods (simple random sampling without replacement, systematic uniform random sampling, stratified random sampling) and sampling parameters. Extensive numerical Monte Carlo experiments were performed to evaluate their large-sample properties. Our results demonstrate reliable determination of total axon number and superior performance compared to other methods at a small fraction of the time required for a full manual count. We specify suitable sampling parameters for the adoption of an efficient stereological sampling scheme, give empirical estimates of the additionally introduced sampling variance to facilitate experimental planning, and offer AxonCounter, an easy-to-use plugin implementing these stereological methods for the multi-platform image processing application NIH ImageJ.

摘要

定量视神经中的轴突数量在许多研究问题中都很重要。在这里,我们展示了一种立体学法,可简单、高效、精确且无偏地确定小鼠视神经中的总轴突数量。在未经处理的眼睛(n=21)和接受玻璃体内 NMDA 注射(n=32)或 PBS 对照(n=5)的视网膜损伤的眼睛的半薄视神经横切片中,手动识别、计数和数字化标记轴突。通过系统组合不同的抽样方法(无替换的简单随机抽样、系统均匀随机抽样、分层随机抽样)和抽样参数,对立体学法进行了经验测试。进行了广泛的数值蒙特卡罗实验,以评估其大样本特性。我们的结果表明,与其他方法相比,该方法可在一小部分时间内可靠地确定总轴突数量,并具有优越的性能。我们为采用有效的立体学法指定了合适的抽样参数,提供了额外引入的抽样方差的经验估计值,以方便实验规划,并提供了 AxonCounter,这是一个易于使用的插件,可用于 NIH ImageJ 等多平台图像处理应用程序实现这些立体学法。

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