Near‐Freezing‐Temperature Golgi Neuronal Staining for X‐ray Imaging of Human Brain

Achieving detailed neuronal structural information in large-volume brain tissue has been a longstanding challenge in human brain imaging. A key obstacle arises from the trade-off between staining efficiency and tissue autolysis. Traditional Golgi staining, typically conducted at room temperature or 37 °C to optimize staining efficiency, leads to rapid autolysis of brain tissue, resulting in the loss of fine structural details. Here, a near-freezing temperature (NFT) staining strategy in post-mortem frozen (PMF) human brain samples are presented, using a mercury chloride-based method under ice-water bath conditions. In contrast to the 37 °C Golgi staining, this NFT-based method significantly reduces tissue autolysis, preserving fine neuronal structures. Notably, neuronal counts in the same field of view increased by 5.5-fold, and dendritic spine density increases by 22-fold. Using this approach, uniform staining of millimeter-thick is achieved, centimeter-scale human brain slices and integrated it with synchrotron-based X-ray microscopy to perform micrometer resolution 3D reconstructions of the cerebellum and frontal lobe. This novel technique offers a powerful tool for the fine-structural imaging of large-volume brain tissue, providing new insights into the intricate organization of neural networks.

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Publication Details

Journal
Advanced Science
Published
2025-05-28
DOI
https://doi.org/10.1002/advs.202504468
Citations
3
Primary Topic
Advanced Electron Microscopy Techniques and Applications
Type
article
Field-Weighted Citation Impact
7.65

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article

Near‐Freezing‐Temperature Golgi Neuronal Staining for X‐ray Imaging of Human Brain

Chunhai Fan, Feng Zhou, Jun Hu, Jichao Zhang et al.
3 citations
Advanced Science
Advanced Electron Microscopy Techniques and Applications
7.65
article

Near‐Freezing‐Temperature Golgi Neuronal Staining for X‐ray Imaging of Human Brain

Chunhai Fan, Feng Zhou, Jun Hu, Jichao Zhang, Li Jiang, Xiaoqing Cai, Lin‐Fa Wang, Qian Li, Yu Zhang, Qiaowei Tang, Chao Ma, Xin Yan, Ying Zhu
article en
3 citations

Abstract

Achieving detailed neuronal structural information in large-volume brain tissue has been a longstanding challenge in human brain imaging. A key obstacle arises from the trade-off between staining efficiency and tissue autolysis. Traditional Golgi staining, typically conducted at room temperature or 37 °C to optimize staining efficiency, leads to rapid autolysis of brain tissue, resulting in the loss of fine structural details. Here, a near-freezing temperature (NFT) staining strategy in post-mortem frozen (PMF) human brain samples are presented, using a mercury chloride-based method under ice-water bath conditions. In contrast to the 37 °C Golgi staining, this NFT-based method significantly reduces tissue autolysis, preserving fine neuronal structures. Notably, neuronal counts in the same field of view increased by 5.5-fold, and dendritic spine density increases by 22-fold. Using this approach, uniform staining of millimeter-thick is achieved, centimeter-scale human brain slices and integrated it with synchrotron-based X-ray microscopy to perform micrometer resolution 3D reconstructions of the cerebellum and frontal lobe. This novel technique offers a powerful tool for the fine-structural imaging of large-volume brain tissue, providing new insights into the intricate organization of neural networks.

Advanced ScienceVol. 12(30)
Shanghai University (CN), Shanghai Jiao Tong University (CN), Chinese Academy of Sciences (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Shanghai Advanced Research Institute (CN), Shanghai Institute of Applied Physics (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Fudan University, Chinese Academy of Medical Sciences, Peking Union Medical College, National Key Research and Development Program of China
Clean water and sanitation
Openalex Percentile: Top 4%
Advanced Electron Microscopy Techniques and Applications
7.65
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