Principles of deep immunohistochemistry for 3D histology.

Cell Rep Methods

Department of Psychiatry, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.

Published: May 2023

AI Article Synopsis

  • Deep immunohistochemistry (IHC) is an emerging technique in 3D histology that aims to improve staining of tissues for detailed visualization of biological structures and molecules.
  • Although it holds great promise for understanding biological relationships and aiding clinical diagnostics, the complexity of the methods can limit its accessibility to users.
  • The authors propose a comprehensive framework for deep IHC that includes theoretical insights, method principles, standardized benchmarks, and future research directions to help researchers effectively implement and adapt these techniques.

Article Abstract

Deep immunohistochemistry (IHC) is a nascent field in three-dimensional (3D) histology that seeks to achieve thorough, homogeneous, and specific staining of intact tissues for visualization of microscopic architectures and molecular compositions at large spatial scales. Despite the tremendous potential of deep IHC in revealing molecule-structure-function relationships in biology and establishing diagnostic and prognostic features for pathological samples in clinical practice, the complexities and variations in methodologies may hinder its use by interested users. We provide a unified framework of deep immunostaining techniques by discussing the theoretical considerations of the physicochemical processes involved, summarizing the principles applied in contemporary methods, advocating a standardized benchmarking scheme, and highlighting unaddressed issues and future directions. By providing the essential information to guide investigators in customizing immunolabeling pipelines, we also seek to facilitate the adoption of deep IHC for researchers to address a wide range of research questions.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10261851PMC
http://dx.doi.org/10.1016/j.crmeth.2023.100458DOI Listing

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