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Patient-Specific Induced Pluripotent Stem Cell Models

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Cover of 'Patient-Specific Induced Pluripotent Stem Cell Models'

Table of Contents

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    Book Overview
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    Chapter 157 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 165 Patient-Specific Induced Pluripotent Stem Cell Models: Characterization of iPS Cell-Derived Cardiomyocytes.
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    Chapter 166 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 167 Modeling Axonal Phenotypes with Human Pluripotent Stem Cells.
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    Chapter 168 In Vitro Modeling of Alcohol-Induced Liver Injury Using Human-Induced Pluripotent Stem Cells.
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    Chapter 169 Modeling Genomic Imprinting Disorders Using Induced Pluripotent Stem Cells.
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    Chapter 170 Generation of Patient-Specific induced Pluripotent Stem Cell from Peripheral Blood Mononuclear Cells by Sendai Reprogramming Vectors.
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    Chapter 171 Using Human Induced Pluripotent Stem Cells to Model Skeletal Diseases
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    Chapter 172 Patient-Specific Induced Pluripotent Stem Cell Models: Generation and Characterization of Cardiac Cells.
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    Chapter 173 Generation of Cardiomyocytes from Pluripotent Stem Cells.
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    Chapter 178 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 179 A Doxycycline-Inducible System for Genetic Correction of iPSC Disease Models.
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    Chapter 194 Multisystemic Disease Modeling of Liver-Derived Protein Folding Disorders Using Induced Pluripotent Stem Cells (iPSCs).
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    Chapter 195 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 196 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 204 Generation of Integration-Free Patient Specific iPS Cells Using Episomal Plasmids Under Feeder Free Conditions.
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    Chapter 205 Generation of Human Induced Pluripotent Stem Cells Using RNA-Based Sendai Virus System and Pluripotency Validation of the Resulting Cell Population.
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    Chapter 225 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 257 Directed Myogenic Differentiation of Human Induced Pluripotent Stem Cells.
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    Chapter 258 Generation and Characterization of Induced Pluripotent Stem Cells from Patients with mtDNA Mutations.
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    Chapter 267 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 273 Generation and Characterization of Patient-Specific iPSC Model for Cardiovascular Disease.
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    Chapter 278 Transgene-Free Disease-Specific iPSC Generation from Fibroblasts and Peripheral Blood Mononuclear Cells.
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Chapter title
Patient-Specific Induced Pluripotent Stem Cell Models
Chapter number 267
Book title
Patient-Specific Induced Pluripotent Stem Cell Models
Published in
Methods in molecular biology, May 2015
DOI 10.1007/7651_2015_267
Pubmed ID
Book ISBNs
978-1-4939-3033-3, 978-1-4939-3034-0
Authors

Walter, Anna, Šarić, Tomo, Hescheler, Jürgen, Papadopoulos, Symeon, Anna Walter, Tomo Šarić, Jürgen Hescheler, Symeon Papadopoulos

Editors

Andras Nagy, Kursad Turksen

Abstract

The possibility to generate cardiomyocytes (CMs) from disease-specific induced pluripotent stem cells (iPSCs) is a powerful tool for the investigation of various cardiac diseases in vitro. The pathological course of various cardiac conditions, causatively heterogeneous, often converges into disturbed cellular Ca(2+) cycling. The gigantic Ca(2+) channel of the intracellular Ca(2+) store of CMs, the ryanodine receptor type 2 (RyR2), controls Ca(2+) release and therefore plays a crucial role in Ca(2+) cycling of CMs. In the present protocol we describe ways to measure and analyze global as well as local cellular Ca(2+) release events in CMs derived from a patient carrying a CPVT-causing RyR2 mutation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 14%
Student > Doctoral Student 4 14%
Student > Master 3 11%
Student > Ph. D. Student 3 11%
Professor 2 7%
Other 4 14%
Unknown 8 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 32%
Engineering 3 11%
Agricultural and Biological Sciences 2 7%
Medicine and Dentistry 2 7%
Neuroscience 1 4%
Other 1 4%
Unknown 10 36%