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Cell Viability Assays

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Cover of 'Cell Viability Assays'

Table of Contents

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    Book Overview
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    Chapter 1 Basic Colorimetric Proliferation Assays: MTT, WST, and Resazurin
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    Chapter 2 Assaying Cellular Viability Using the Neutral Red Uptake Assay
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    Chapter 3 Assessment of Cell Viability with Single-, Dual-, and Multi-Staining Methods Using Image Cytometry
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    Chapter 4 High-Throughput Spheroid Screens Using Volume, Resazurin Reduction, and Acid Phosphatase Activity
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    Chapter 5 A Protocol for In Vitro High-Throughput Chemical Susceptibility Screening in Differentiating NT2 Stem Cells
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    Chapter 6 Ferroptosis and Cell Death Analysis by Flow Cytometry
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    Chapter 7 Assaying Mitochondrial Respiration as an Indicator of Cellular Metabolism and Fitness
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    Chapter 8 An ATP-Based Luciferase Viability Assay for Animal African Trypanosomes Using a 96-Well Plate
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    Chapter 9 SYBR® Green I-Based Fluorescence Assay to Assess Cell Viability of Malaria Parasites for Routine Use in Compound Screening
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    Chapter 10 Screening Applications to Test Cellular Fitness in Transwell® Models After Nanoparticle Treatment
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    Chapter 11 Assays for Analyzing the Role of Transport Proteins in the Uptake and the Vectorial Transport of Substances Affecting Cell Viability
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    Chapter 12 Metabolite Profiling of Mammalian Cell Culture Processes to Evaluate Cellular Viability
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    Chapter 13 Assaying Spontaneous Network Activity and Cellular Viability Using Multi-well Microelectrode Arrays
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    Chapter 14 Quantitative Ratiometric Ca2+ Imaging to Assess Cell Viability
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    Chapter 15 Functional Viability: Measurement of Synaptic Vesicle Pool Sizes
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    Chapter 16 Phenotyping Cellular Viability by Functional Analysis of Ion Channels: GlyR-Targeted Screening in NT2-N Cells
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    Chapter 17 Systematic Cell-Based Phenotyping of Missense Alleles
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    Chapter 18 Second Harmonic Generation Microscopy of Muscle Cell Morphology and Dynamics
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    Chapter 19 Assessment of Population and ECM Production Using Multiphoton Microscopy as an Indicator of Cell Viability
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    Chapter 20 Average Rheological Quantities of Cells in Monolayers
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    Chapter 21 Measurement of Cellular Behavior by Electrochemical Impedance Sensing
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    Chapter 22 Nano-QSAR Model for Predicting Cell Viability of Human Embryonic Kidney Cells
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    Chapter 23 Erratum to: Functional Viability: Measurement of Synaptic Vesicle Pool Sizes
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    Chapter 24 Erratum to: Phenotyping Cellular Viability by Functional Analysis of Ion Channels: GlyR-Targeted Screening in NT2-N Cells
Attention for Chapter 12: Metabolite Profiling of Mammalian Cell Culture Processes to Evaluate Cellular Viability
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Chapter title
Metabolite Profiling of Mammalian Cell Culture Processes to Evaluate Cellular Viability
Chapter number 12
Book title
Cell Viability Assays
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6960-9_12
Pubmed ID
Book ISBNs
978-1-4939-6959-3, 978-1-4939-6960-9
Authors

Isobelle M. Evie, Alan J. Dickson, Mark Elvin

Editors

Daniel F. Gilbert, Oliver Friedrich

Abstract

Metabolite profiling allows for the identification of metabolites that become limiting during cell culture and/or for finding bottlenecks in metabolic pathways that limit culture growth and proliferation. Here we describe one protocol with two different sampling methodologies for GC-MS-based metabolite profiling. We also highlight an example of the types of datasets that are attainable and how such datasets can be evaluated to identify factors related to cell viability. We also demonstrate, via the same methodology, the accurate quantification of a number of metabolites of interest.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 38%
Student > Ph. D. Student 2 25%
Student > Postgraduate 1 13%
Student > Bachelor 1 13%
Unknown 1 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 38%
Chemical Engineering 1 13%
Neuroscience 1 13%
Engineering 1 13%
Unknown 2 25%