期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 286, 期 -, 页码 31-37出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2017.05.018
关键词
Immungold quantification; Electron microscopy; Aquaporin-4
资金
- South-East Health Region of Norway [2016070]
- Letten Foundation
Background: Immunogold cytochemistry is the method of choice for precise localization of antigens on a subcellular scale. The process of immunogold quantification in electron micrographs is laborious, especially for proteins with a dense distribution pattern. New methods: Here I present a MATLAB based toolbox that is optimized for a typical immunogold analysis workflow. It combines automatic detection of gold particles through a multi-threshold algorithm with manual segmentation of cell membranes and regions of interests. Results: The automated particle detection algorithm was applied to a typical immunogold dataset of neural tissue, and was able to detect particles with a high degree of precision. Without manual correction, the algorithm detected 97% of all gold particles, with merely a 0.1% false-positive rate. Comparisons with existing method(s): To my knowledge, this is the first free and publicly available software custom made for immunogold analyses. The proposed particle detection method compares favorably to previously published algorithms. Conclusions: The software presented here will be valuable tool for researchers in neuroscience working with immunogold cytochemistry. (C) 2017 The Author(s). Published by Elsevier B.V.
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