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The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations

Estimation of total number of a population of cells that are sparsely distributed in an organ or anatomically-defined region of interest represents a challenge for conventional stereological methods. In these situations, classic fractionator approaches that rely on systematic uniform random sampling...

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Autores principales: Boyce, Rogely W., Gundersen, Hans J. G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871675/
https://www.ncbi.nlm.nih.gov/pubmed/29618974
http://dx.doi.org/10.3389/fnana.2018.00019
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author Boyce, Rogely W.
Gundersen, Hans J. G.
author_facet Boyce, Rogely W.
Gundersen, Hans J. G.
author_sort Boyce, Rogely W.
collection PubMed
description Estimation of total number of a population of cells that are sparsely distributed in an organ or anatomically-defined region of interest represents a challenge for conventional stereological methods. In these situations, classic fractionator approaches that rely on systematic uniform random sampling are highly inefficient and, in many cases, impractical due to the intense sampling of the organ and tissue sections that is required to obtain sufficient counts for an acceptable level of precision. The proportionator, an estimator based on non-uniform sampling theory, marries automated image analysis with stereological principles and is the only estimator that provides a highly efficient and precise method to address these challenging quantification problems. In this paper, the practical considerations of the proportionator estimator and its implementation with Proportionator™ software and digital slide imaging are reviewed. The power of the proportionator as a stereological tool is illustrated in its application to the estimation of the total number of a very rare (~50/vertebrae) and sparsely distributed population of osteoprogenitor cells in mouse vertebral body. The proportionator offers a solution to neuroscientists interested in quantifying total cell number of sparse cell populations in the central and peripheral nervous system where systematic uniform random sampling-based stereological estimators are impractical.
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spelling pubmed-58716752018-04-04 The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations Boyce, Rogely W. Gundersen, Hans J. G. Front Neuroanat Neuroscience Estimation of total number of a population of cells that are sparsely distributed in an organ or anatomically-defined region of interest represents a challenge for conventional stereological methods. In these situations, classic fractionator approaches that rely on systematic uniform random sampling are highly inefficient and, in many cases, impractical due to the intense sampling of the organ and tissue sections that is required to obtain sufficient counts for an acceptable level of precision. The proportionator, an estimator based on non-uniform sampling theory, marries automated image analysis with stereological principles and is the only estimator that provides a highly efficient and precise method to address these challenging quantification problems. In this paper, the practical considerations of the proportionator estimator and its implementation with Proportionator™ software and digital slide imaging are reviewed. The power of the proportionator as a stereological tool is illustrated in its application to the estimation of the total number of a very rare (~50/vertebrae) and sparsely distributed population of osteoprogenitor cells in mouse vertebral body. The proportionator offers a solution to neuroscientists interested in quantifying total cell number of sparse cell populations in the central and peripheral nervous system where systematic uniform random sampling-based stereological estimators are impractical. Frontiers Media S.A. 2018-03-21 /pmc/articles/PMC5871675/ /pubmed/29618974 http://dx.doi.org/10.3389/fnana.2018.00019 Text en Copyright © 2018 Boyce and Gundersen. 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 or reproduction in other forums is permitted, provided the original author(s) and the copyright owner 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
Boyce, Rogely W.
Gundersen, Hans J. G.
The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations
title The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations
title_full The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations
title_fullStr The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations
title_full_unstemmed The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations
title_short The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations
title_sort automatic proportionator estimator is highly efficient for estimation of total number of sparse cell populations
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871675/
https://www.ncbi.nlm.nih.gov/pubmed/29618974
http://dx.doi.org/10.3389/fnana.2018.00019
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