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首页> 外文期刊>Journal of Neuroscience Methods >Automated measurement of nerve fiber density using line intensity scan analysis
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Automated measurement of nerve fiber density using line intensity scan analysis

机译：使用线强度扫描分析自动测量神经纤维密度

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摘要

Quantification of nerve fibers in peripheral and central nervous systems is important for the understanding of neuronal function, organization and pathological changes. However, current methods to quantify nerve fibers are resource-intensive and often provide an indirect measurement of nerve fiber density. Here, we describe an automated and efficient method for nerve fiber quantification, which we developed by making use of widely available software and analytical techniques, including Hessian-based feature extraction in NIH ImageJ and line intensity scan analysis. The combined use of these analytical tools through an automated routine enables reliable detection and quantification of nerve fibers from low magnification, non-uniformly labeled epifluorescence images. This allows for time-efficient determination of nerve density and also comparative analysis in large brain structures, such as hippocampus or between various regions of neural circuitry. Using this method, we have obtained accurate measurements of cholinergic fiber density in hippocampus and a large area of cortex in mouse brain sections immunolabeled with an antibody against the vesicular acetylcholine transporter (VAChT). The density values are comparable among animals tested, showing a high degree of reproducibility. Because our method can be performed at relatively low cost and in large tissue sections where nerve fibers can be labeled by various antibodies or visualized by expression of reporter proteins, such as green fluorescent protein in transgenic mice, we expect our method to be broadly useful in both research and clinical investigation. To our knowledge, this is the first method to reliably quantify nerve fibers through a rapid and automated protocol.
机译：量化周围和中枢神经系统中的神经纤维对于理解神经元功能，组织和病理变化非常重要。然而，当前定量神经纤维的方法是资源密集的，并且经常提供神经纤维密度的间接测量。在这里，我们描述了一种自动有效的神经纤维定量方法，该方法是我们利用广泛可用的软件和分析技术开发的，包括NIH ImageJ中基于Hessian的特征提取和线强度扫描分析。通过自动化程序将这些分析工具结合使用，可以从低倍放大，标记不均匀的落射荧光图像可靠地检测和定量神经纤维。这样可以高效地确定神经密度，并可以在大型大脑结构（例如海马体）或神经回路的各个区域之间进行比较分析。使用这种方法，我们获得了精确测量的海马胆碱能纤维密度，并用抗水泡乙酰胆碱转运蛋白（VAChT）抗体免疫标记的小鼠大脑切片大面积皮质。在测试的动物之间，密度值是可比的，显示出高度的再现性。因为我们的方法可以在相对较低的成本下进行，并且可以在较大的组织切片中进行，其中神经纤维可以用各种抗体标记或通过报道蛋白（例如转基因小鼠中的绿色荧光蛋白）的表达而可视化，所以我们希望我们的方法在以下方面具有广泛的用途：研究和临床研究。据我们所知，这是通过快速，自动化的方案可靠地定量神经纤维的第一种方法。

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