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Cellular Heterogeneity

Overview of attention for book
Cellular Heterogeneity
Humana Press, New York, NY

Table of Contents

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    Book Overview
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    Chapter 1 Heterogeneity of Metazoan Cells and Beyond: To Integrative Analysis of Cellular Populations at Single-Cell Level
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    Chapter 2 Integrating Analysis of Cellular Heterogeneity in High-Content Dose-Response Studies
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    Chapter 3 Image-Based Tracking of Heterogeneous Single-Cell Phenotypes
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    Chapter 4 Broad Immune Monitoring and Profiling of T Cell Subsets with Mass Cytometry
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    Chapter 5 Spectral and Imaging Flow Cytometry in Phytoplankton Research
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    Chapter 6 X-Ray Fluorescence-Detected Flow Cytometry
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    Chapter 7 Multiparametric Analysis of Myeloid Populations by Flow Cytometry
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    Chapter 8 Quantitation of IRF3 Nuclear Translocation in Heterogeneous Cellular Populations from Cervical Tissue Using Imaging Flow Cytometry
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    Chapter 9 Methods of Study of Neuron Structural Heterogeneity: Flow Cytometry vs. Laser Interferometry
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    Chapter 10 Usage of Multiparameter Flow Cytometry to Study Microglia and Macrophage Heterogeneity in the Central Nervous System During Neuroinflammation and Neurodegeneration
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    Chapter 11 Analysis of Microtubule Dynamics Heterogeneity in Cell Culture
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    Chapter 12 Heterogeneity of Focal Adhesions and Focal Contacts in Motile Fibroblasts
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    Chapter 13 Laser Tweezers Raman Microspectroscopy of Single Cells and Biological Particles
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    Chapter 14 Quantification of the Metabolic Heterogeneity in Mycobacterial Cells Through the Measurement of the NADH/NAD+ Ratio Using a Genetically Encoded Sensor
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    Chapter 15 Characterizing Cell Heterogeneity Using PCR Fingerprinting of Surface Multigene Families in Protozoan Parasites
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    Chapter 16 Assessing Carbon Source-Dependent Phenotypic Variability in Pseudomonas putida
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    Chapter 17 The Retinal Pigment Epithelial Cell Line (ARPE-19) Displays Mosaic Structural Chromosomal Aberrations
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    Chapter 18 FACS Isolation of Viable Cells in Different Cell Cycle Stages from Asynchronous Culture for RNA Sequencing
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    Chapter 19 Measuring Nanoscale Chromatin Heterogeneity with Partial Wave Spectroscopic Microscopy
Attention for Chapter 4: Broad Immune Monitoring and Profiling of T Cell Subsets with Mass Cytometry
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Chapter title
Broad Immune Monitoring and Profiling of T Cell Subsets with Mass Cytometry
Chapter number 4
Book title
Cellular Heterogeneity
Published by
Humana Press, New York, NY, February 2018
DOI 10.1007/978-1-4939-7680-5_4
Pubmed ID
Book ISBNs
978-1-4939-7679-9, 978-1-4939-7680-5
Authors

Tess Melinda Brodie, Vinko Tosevski

Abstract

Mass cytometry (cytometry by time-of-flight, CyTOF) is a high-dimensional single-cell analytical technology that allows for highly multiplexed measurements of protein or nucleic acid abundances by bringing together the detection capacity of atomic mass spectroscopy and the sample preparation workflow typical of regular flow cytometry. In 2014 the mass cytometer was adapted for the acquisition of samples from microscopy slides (termed imaging mass cytometry), greatly increasing the applicability of this technology with the inclusion of spatial information. By using antibodies (or other probes) labeled with purified metal isotopes, mass cytometers are currently able to detect more than 50 different parameters at a single-cell level, exceeding the dimensionality of any other flow cytometry methodology currently on the market. This capability licenses unprecedented possibilities in many areas dealing with complex cellular mixtures (immunology, cell biology, and beyond), improving biomarker discovery and moving us closer to affordable personalized medicine than before.

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 33%
Student > Bachelor 4 19%
Professor 1 5%
Student > Ph. D. Student 1 5%
Professor > Associate Professor 1 5%
Other 0 0%
Unknown 7 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 29%
Medicine and Dentistry 3 14%
Biochemistry, Genetics and Molecular Biology 2 10%
Computer Science 1 5%
Immunology and Microbiology 1 5%
Other 1 5%
Unknown 7 33%