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Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features

The estimation of the number or density of neurons and types of glial cells and their relative proportions in different brain areas are at the core of rigorous quantitative neuroanatomical studies. Unfortunately, the lack of detailed, updated, systematic and well-illustrated descriptions of the cyto...

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Autores principales: García-Cabezas, Miguel Á., John, Yohan J., Barbas, Helen, Zikopoulos, Basilis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5088408/
https://www.ncbi.nlm.nih.gov/pubmed/27847469
http://dx.doi.org/10.3389/fnana.2016.00107
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author García-Cabezas, Miguel Á.
John, Yohan J.
Barbas, Helen
Zikopoulos, Basilis
author_facet García-Cabezas, Miguel Á.
John, Yohan J.
Barbas, Helen
Zikopoulos, Basilis
author_sort García-Cabezas, Miguel Á.
collection PubMed
description The estimation of the number or density of neurons and types of glial cells and their relative proportions in different brain areas are at the core of rigorous quantitative neuroanatomical studies. Unfortunately, the lack of detailed, updated, systematic and well-illustrated descriptions of the cytology of neurons and glial cell types, especially in the primate brain, makes such studies especially demanding, often limiting their scope and broad use. Here, following an extensive analysis of histological materials and the review of current and classical literature, we compile a list of precise morphological criteria that can facilitate and standardize identification of cells in stained sections examined under the microscope. We describe systematically and in detail the cytological features of neurons and glial cell types in the cerebral cortex of the macaque monkey and the human using semithin and thick sections stained for Nissl. We used this classical staining technique because it labels all cells in the brain in distinct ways. In addition, we corroborate key distinguishing characteristics of different cell types in sections immunolabeled for specific markers counterstained for Nissl and in ultrathin sections processed for electron microscopy. Finally, we summarize the core features that distinguish each cell type in easy-to-use tables and sketches, and structure these key features in an algorithm that can be used to systematically distinguish cellular types in the cerebral cortex. Moreover, we report high inter-observer algorithm reliability, which is a crucial test for obtaining consistent and reproducible cell counts in unbiased stereological studies. This protocol establishes a consistent framework that can be used to reliably identify and quantify cells in the cerebral cortex of primates as well as other mammalian species in health and disease.
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spelling pubmed-50884082016-11-15 Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features García-Cabezas, Miguel Á. John, Yohan J. Barbas, Helen Zikopoulos, Basilis Front Neuroanat Neuroscience The estimation of the number or density of neurons and types of glial cells and their relative proportions in different brain areas are at the core of rigorous quantitative neuroanatomical studies. Unfortunately, the lack of detailed, updated, systematic and well-illustrated descriptions of the cytology of neurons and glial cell types, especially in the primate brain, makes such studies especially demanding, often limiting their scope and broad use. Here, following an extensive analysis of histological materials and the review of current and classical literature, we compile a list of precise morphological criteria that can facilitate and standardize identification of cells in stained sections examined under the microscope. We describe systematically and in detail the cytological features of neurons and glial cell types in the cerebral cortex of the macaque monkey and the human using semithin and thick sections stained for Nissl. We used this classical staining technique because it labels all cells in the brain in distinct ways. In addition, we corroborate key distinguishing characteristics of different cell types in sections immunolabeled for specific markers counterstained for Nissl and in ultrathin sections processed for electron microscopy. Finally, we summarize the core features that distinguish each cell type in easy-to-use tables and sketches, and structure these key features in an algorithm that can be used to systematically distinguish cellular types in the cerebral cortex. Moreover, we report high inter-observer algorithm reliability, which is a crucial test for obtaining consistent and reproducible cell counts in unbiased stereological studies. This protocol establishes a consistent framework that can be used to reliably identify and quantify cells in the cerebral cortex of primates as well as other mammalian species in health and disease. Frontiers Media S.A. 2016-11-01 /pmc/articles/PMC5088408/ /pubmed/27847469 http://dx.doi.org/10.3389/fnana.2016.00107 Text en Copyright © 2016 García-Cabezas, John, Barbas and Zikopoulos. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
García-Cabezas, Miguel Á.
John, Yohan J.
Barbas, Helen
Zikopoulos, Basilis
Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features
title Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features
title_full Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features
title_fullStr Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features
title_full_unstemmed Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features
title_short Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features
title_sort distinction of neurons, glia and endothelial cells in the cerebral cortex: an algorithm based on cytological features
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5088408/
https://www.ncbi.nlm.nih.gov/pubmed/27847469
http://dx.doi.org/10.3389/fnana.2016.00107
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