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B Cell Receptor Signaling

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Cover of 'B Cell Receptor Signaling'

Table of Contents

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    Book Overview
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    Chapter 1 Activation-Induced Cytidine Deaminase Aided In Vitro Antibody Evolution
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    Chapter 2 Analyzing Mouse B Cell Responses Specific to LCMV Infection
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    Chapter 3 Expression of Exogenous Genes in Murine Primary B Cells and B Cell Lines Using Retroviral Vectors
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    Chapter 4 Biophysical Techniques to Study B Cell Activation: Single-Molecule Imaging and Force Measurements
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    Chapter 5 DNA-Based Probes for Measuring Mechanical Forces in Cell-Cell Contacts: Application to B Cell Antigen Extraction from Immune Synapses
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    Chapter 6 Deriving Quantitative Cell Biological Information from Dye-Dilution Lymphocyte Proliferation Experiments
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    Chapter 7 Flow Cytometry Analysis of mTOR Signaling in Antigen-Specific B Cells
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    Chapter 8 Ex Vivo Culture Assay to Measure Human Follicular Helper T (Tfh) Cell-Mediated Human B Cell Proliferation and Differentiation
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    Chapter 9 B Cell Receptor Signaling and Compartmentalization by Confocal Microscopy
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    Chapter 10 Imaging the Interactions Between B Cells and Antigen-Presenting Cells
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    Chapter 11 In Vivo Tracking of Particulate Antigen Localization and Recognition by B Lymphocytes at Lymph Nodes
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    Chapter 12 Study B Cell Antigen Receptor Nano-Scale Organization by In Situ Fab Proximity Ligation Assay
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    Chapter 13 Single-Particle Tracking of Cell Surface Proteins
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    Chapter 14 The Use of Intravital Two-Photon and Thick Section Confocal Imaging to Analyze B Lymphocyte Trafficking in Lymph Nodes and Spleen
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    Chapter 15 Time-Lapse Förster Resonance Energy Transfer Imaging by Confocal Laser Scanning Microscopy for Analyzing Dynamic Molecular Interactions in the Plasma Membrane of B Cells
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    Chapter 16 Understanding of B Cell Receptor Signaling Through a Photo-Activatable Antigen Presentation System
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    Chapter 17 Use of Streptolysin O-Induced Membrane Damage as a Method of Studying the Function of Lipid Rafts During B Cell Activation
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    Chapter 18 Visualization and Quantitative Analysis of the Actin Cytoskeleton Upon B Cell Activation
Attention for Chapter 6: Deriving Quantitative Cell Biological Information from Dye-Dilution Lymphocyte Proliferation Experiments
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Chapter title
Deriving Quantitative Cell Biological Information from Dye-Dilution Lymphocyte Proliferation Experiments
Chapter number 6
Book title
B Cell Receptor Signaling
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7474-0_6
Pubmed ID
Book ISBNs
978-1-4939-7473-3, 978-1-4939-7474-0
Authors

Koushik Roy, Maxim Nikolaievich Shokhirev, Simon Mitchell, Alexander Hoffmann, Roy, Koushik, Shokhirev, Maxim Nikolaievich, Mitchell, Simon, Hoffmann, Alexander

Abstract

The dye-dilution assay is a powerful tool to study lymphocyte expansion dynamics. By combining time course dye-dilution experiments with computational analysis, quantitative information about cell biological parameters, such as percentage of cells dividing, time of division, and time of death, can be produced. Here, we describe the method to generate quantitative cell biological insights from dye-dilution experiments. We describe experimental methods for generating dye-dilution data with murine lymphocytes and then describe the computational data analysis workflow using a recently developed software package called FlowMax. The aim is to interpret the dye-dilution data quantitatively and objectively, such that cell biological parameters can be reported with an appropriate measure of confidence, which in turn depends on the quality and quantity of available data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 20%
Student > Bachelor 1 20%
Student > Postgraduate 1 20%
Other 1 20%
Unknown 1 20%
Readers by discipline Count As %
Immunology and Microbiology 2 40%
Environmental Science 1 20%
Neuroscience 1 20%
Unknown 1 20%