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A novel unbiased counting method for the quantification of synapses in the mouse brain
BACKGROUND: The numerical density of synapses and their ultrastructural features are best assessed with electron microscopy. Counting is done within counting frames placed on a pair of sections (disector technique). But this requires that the thin sections are taken from comparable brain regions and...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier/North-Holland Biomedical Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4282307/ https://www.ncbi.nlm.nih.gov/pubmed/25445248 http://dx.doi.org/10.1016/j.jneumeth.2014.10.020 |
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author | Reichmann, Florian Painsipp, Evelin Holzer, Peter Kummer, Daniel Bock, Elisabeth Leitinger, Gerd |
author_facet | Reichmann, Florian Painsipp, Evelin Holzer, Peter Kummer, Daniel Bock, Elisabeth Leitinger, Gerd |
author_sort | Reichmann, Florian |
collection | PubMed |
description | BACKGROUND: The numerical density of synapses and their ultrastructural features are best assessed with electron microscopy. Counting is done within counting frames placed on a pair of sections (disector technique). But this requires that the thin sections are taken from comparable brain regions and the disectors are placed in a uniform random fashion. Small brain areas like the polymorph layer of the mouse dentate gyrus are difficult to encounter, and manually moving the microscope stage for placing the micrographs seems arbitrary. NEW METHOD: Here the polymorph layer was approximated with 20 μm thin, Nissl-stained vibratome sections. The subsequent vibratome section was processed for electron microscopy and serially thin sectioned. The microscope stage was moved using a random number generator, placing at least 20 disectors onto a pair of sections. The numerical synapse density, the numerical density of dense-core vesicles, and other ultrastructural features were compared between mice that had been kept in an enriched environment and mice kept under standard housing conditions. RESULTS: Environmental enrichment significantly decreased the numerical density of dense-core vesicles and synaptic cleft widths within the polymorph layer, associated with behavioral improvement in the Morris water maze, a hippocampus-dependent task of spatial learning and memory. COMPARISON WITH EXISTING METHODS: This procedure was easy to handle and enabled us to produce thin sections in small, defined brain areas. Furthermore, placing the disectors with random numbers excluded observer bias. CONCLUSIONS: Our procedure provides an uncomplicated way of assessing numerical densities in small brain areas in an unbiased manner. |
format | Online Article Text |
id | pubmed-4282307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier/North-Holland Biomedical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-42823072015-01-30 A novel unbiased counting method for the quantification of synapses in the mouse brain Reichmann, Florian Painsipp, Evelin Holzer, Peter Kummer, Daniel Bock, Elisabeth Leitinger, Gerd J Neurosci Methods Basic Neuroscience BACKGROUND: The numerical density of synapses and their ultrastructural features are best assessed with electron microscopy. Counting is done within counting frames placed on a pair of sections (disector technique). But this requires that the thin sections are taken from comparable brain regions and the disectors are placed in a uniform random fashion. Small brain areas like the polymorph layer of the mouse dentate gyrus are difficult to encounter, and manually moving the microscope stage for placing the micrographs seems arbitrary. NEW METHOD: Here the polymorph layer was approximated with 20 μm thin, Nissl-stained vibratome sections. The subsequent vibratome section was processed for electron microscopy and serially thin sectioned. The microscope stage was moved using a random number generator, placing at least 20 disectors onto a pair of sections. The numerical synapse density, the numerical density of dense-core vesicles, and other ultrastructural features were compared between mice that had been kept in an enriched environment and mice kept under standard housing conditions. RESULTS: Environmental enrichment significantly decreased the numerical density of dense-core vesicles and synaptic cleft widths within the polymorph layer, associated with behavioral improvement in the Morris water maze, a hippocampus-dependent task of spatial learning and memory. COMPARISON WITH EXISTING METHODS: This procedure was easy to handle and enabled us to produce thin sections in small, defined brain areas. Furthermore, placing the disectors with random numbers excluded observer bias. CONCLUSIONS: Our procedure provides an uncomplicated way of assessing numerical densities in small brain areas in an unbiased manner. Elsevier/North-Holland Biomedical Press 2015-01-30 /pmc/articles/PMC4282307/ /pubmed/25445248 http://dx.doi.org/10.1016/j.jneumeth.2014.10.020 Text en © 2014 The Authors http://creativecommons.org/licenses/by/3.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Basic Neuroscience Reichmann, Florian Painsipp, Evelin Holzer, Peter Kummer, Daniel Bock, Elisabeth Leitinger, Gerd A novel unbiased counting method for the quantification of synapses in the mouse brain |
title | A novel unbiased counting method for the quantification of synapses in the mouse brain |
title_full | A novel unbiased counting method for the quantification of synapses in the mouse brain |
title_fullStr | A novel unbiased counting method for the quantification of synapses in the mouse brain |
title_full_unstemmed | A novel unbiased counting method for the quantification of synapses in the mouse brain |
title_short | A novel unbiased counting method for the quantification of synapses in the mouse brain |
title_sort | novel unbiased counting method for the quantification of synapses in the mouse brain |
topic | Basic Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4282307/ https://www.ncbi.nlm.nih.gov/pubmed/25445248 http://dx.doi.org/10.1016/j.jneumeth.2014.10.020 |
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