High-Resolution Single-Neuron Reconstruction Analysis in Golgi-Stained Brain Tissues

Qiaowei Tang , Binfu Fan , Xiaoqing Cai , Zhiming Shen , Jichao Zhang , Jun Hu , Jiang Li , Ying Zhu

Cell Proliferation ›› 2026, Vol. 59 ›› Issue (2) : e70092

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Cell Proliferation ›› 2026, Vol. 59 ›› Issue (2) :e70092 DOI: 10.1111/cpr.70092
ORIGINAL ARTICLE
High-Resolution Single-Neuron Reconstruction Analysis in Golgi-Stained Brain Tissues
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Abstract

Understanding the structural and functional organisation of brain networks is a fundamental objective in neuroscience, with three-dimensional (3D) reconstruction of single-neuron morphology serving as a critical foundation. The Golgi staining method, which enables random neuronal labeling and provides high-contrast signals in both optical and X-ray microscopy, remains a valuable tool for morphological analysis. However, its widespread application in large-scale neuronal reconstructions is hindered by signal discontinuities in neuronal branches, high-density labeling, and complex background interference. While automated reconstruction methods perform well in sparsely labelled and morphologically simple neuronal populations, their effectiveness is limited in Golgi-stained samples. Here we develop a semi-automated single-neuron reconstruction method for Golgi-stained mouse brain neurons (SNR-Golgi). By integrating three key technical modules—background denoising, single-neuron extraction, and branch repair—SNR-Golgi significantly enhances the accuracy and completeness of neuronal reconstruction. In fluorescence micro-optical sectioning tomography (fMOST) datasets, SNR-Golgi demonstrated superior performance in neuronal reconstruction within the mouse somatosensory cortex, achieving a 30% increase in reconstructed branch count, a 76% improvement in total branch length, and a 3.7-fold increase in axonal length. Additionally, in synchrotron-based X-ray imaging datasets, SNR-Golgi enabled submicron-resolution 3D reconstruction of single neurons. These results demonstrate that SNR-Golgi effectively addresses the complexity of Golgi-stained samples and provides robust technical support for the structural analysis of brain neurons across various imaging modalities.

Keywords

3D reconstruction / fluorescence micro-optical sectioning tomography (fMOST) / Golgi / high-fidelity / single neuron / synchrotron-based X-ray microscopy

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Qiaowei Tang, Binfu Fan, Xiaoqing Cai, Zhiming Shen, Jichao Zhang, Jun Hu, Jiang Li, Ying Zhu. High-Resolution Single-Neuron Reconstruction Analysis in Golgi-Stained Brain Tissues. Cell Proliferation, 2026, 59 (2) : e70092 DOI:10.1111/cpr.70092

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2025 The Author(s). Cell Proliferation published by Beijing Institute for Stem Cell and Regenerative Medicine and John Wiley & Sons Ltd.

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