Chapter title |
Neuronal Cell Morphology in Primary Cerebellar Granule Cells Using High-Content Analysis
|
---|---|
Chapter number | 17 |
Book title |
Neurotrophic Factors
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7571-6_17 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7570-9, 978-1-4939-7571-6
|
Authors |
Nicholas Radio, Steven Frank, Radio, Nicholas, Frank, Steven |
Abstract |
Neurite outgrowth, one of the underlying cellular processes that defines the development and functionality of the mammalian nervous system, is also a sensitive indicator of neuronal cell health. From screening libraries of putative neurotherapeutic compounds to analyzing the millions of environmental pollutants for which we have inadequate neurotoxicity safety data, the large volume of chemical compounds that require evaluation is a major obstacle for manual imaging and analysis methods. In this context, high-content analysis (HCA) has emerged as a sensitive and accurate method for detecting changes in neuronal cell morphology within a format applicable to screening large chemical libraries. Advances in HCA technologies have enabled the automated imaging and quantitative analysis of neurite outgrowth morphology within a 96-well plate in less than 5 min. Traditionally, neurite outgrowth assessment has been conducted on immortalized cell lines such as pheochromocytoma (PC-12) cells that differentiate into neuron-like cells upon culture with nerve growth factor. Unfortunately, they do not retain all the in vivo characteristics of physiological neuronal tissue, including lack of synapse formation. As researchers refine neurite outgrowth quantitative analysis using HCA, an emerging question is how to quantify this biology in more complex models that more faithfully recapitulate in vivo environments. Primary neurons provide several benefits relative to neuronal cell lines, including the elaboration of axons from secondary dendrites and formation of both pre- and postsynaptic junctions. This chapter reviews techniques for evaluating neurite outgrowth using the ArrayScan HCA platform within a model system of primary cultures of rodent cerebellar granule cells. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Professor > Associate Professor | 2 | 25% |
Librarian | 1 | 13% |
Student > Bachelor | 1 | 13% |
Student > Doctoral Student | 1 | 13% |
Researcher | 1 | 13% |
Other | 1 | 13% |
Unknown | 1 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 2 | 25% |
Engineering | 2 | 25% |
Business, Management and Accounting | 1 | 13% |
Neuroscience | 1 | 13% |
Biochemistry, Genetics and Molecular Biology | 1 | 13% |
Other | 0 | 0% |
Unknown | 1 | 13% |