Evidence map›Paper›PMID 40924310›Full record

ReviewDiscover nano2025

Immunoelectron microscopy: a comprehensive guide from sample preparation to high-resolution imaging.

Jinsai Wu, Bo Su, Leiyan Gu, Jie Zhang, Qiuxiao Shi, Danrong Hu

Abstract readReview
In one paragraph

Review in Discover nano, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jinsai WuHistology and Imaging Platform, Core Facilities of West China Hospital, Chengdu, 610041, People's Republic of China.
Bo SuHistology and Imaging Platform, Core Facilities of West China Hospital, Chengdu, 610041, People's Republic of China.
Leiyan GuDepartment of Pathophysiology, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
Jie ZhangHistology and Imaging Platform, Core Facilities of West China Hospital, Chengdu, 610041, People's Republic of China.
Qiuxiao ShiHistology and Imaging Platform, Core Facilities of West China Hospital, Chengdu, 610041, People's Republic of China. shiqiuxiao@wchscu.cn.
Danrong HuDepartment of Rehabilitation Medicine, Rehabilitation Medical Center, Key Laboratory of Rehabilitation Medicine in Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China. hudanrong@sina.com.

Funding

The Higher Education Teaching Reform Project of Sichuan University SCU11260
6 · The paper itself

Abstract

Immunoelectron Microscopy (IEM) is a technique that combines specific immunolabeling with high-resolution electron microscopic imaging to achieve precise spatial localization of biomolecules at the subcellular scale (< 10 nm) by using high-electron-density markers such as colloidal gold and quantum dots. As a core tool for analyzing the distribution of proteins, organelle interactions, and localization of disease pathology markers, it has irreplaceable value, especially in synapse research, pathogen-host interaction mechanism, and tumor microenvironment analysis. According to the differences in labeling sequence and sample processing, the IEM technology system can be divided into two categories: the first is pre-embedding labeling, which optimizes the labeling efficiency through the pre-exposure of antigenic epitopes and is especially suitable for the detection of low-abundance and sensitive antigens; the second is post-embedding labeling, which relies on the low-temperature resin embedding (e.g., LR White, Lowicryl) or the Tokuyasu frozen ultrathin sectioning technology, which can improve the deep-end labeling while maintaining the ultrastructural integrity of the tissue. The accessibility of deep antigens is enhanced while maintaining ultrastructural integrity. The two techniques have significant complementarities: the former has high labeling efficiency but limited cellular structure preservation, while the latter has better tissue structure preservation but needs to balance the problems of resin penetration and antigenic epitope masking. This article provides a systematic analysis of the entire IEM workflow, focusing on the synergistic strategies for fixation and dehydration, experimental method selection, and specific application cases. It also introduces a quantitative analysis framework based on systematic random sampling (SUR) and deep learning algorithms (such as Gold Digger), including FIB-SEM 3D reconstruction (with isotropic resolution reaching 5 nm) and correlative light and electron microscopy (CLEM) multimodal integration strategies for functional-structural co-localization. Through technological innovation and cross-platform integration, IEM is driving the advancement of ultrastructural pathology diagnostics and precision nanomedicine to new heights.

Indexed as

Immunoelectron microscopyPost-embeddingPre-embeddingQuantitationTokuyasu

Identifiers

PMID40924310
PMCPMC12420552

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.