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Cardiac Gene Therapy

Overview of attention for book
Cover of 'Cardiac Gene Therapy'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Current Methods in Cardiac Gene Therapy: Overview.
  3. Altmetric Badge
    Chapter 2 Silencing Genes in the Heart.
  4. Altmetric Badge
    Chapter 3 Generation of Efficient miRNA Inhibitors Using Tough Decoy Constructs.
  5. Altmetric Badge
    Chapter 4 Cardiac Gene Therapy
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    Chapter 5 Direct Cardiac Reprogramming as a Novel Therapeutic Strategy for Treatment of Myocardial Infarction.
  7. Altmetric Badge
    Chapter 6 Production and Characterization of Vectors Based on the Cardiotropic AAV Serotype 9.
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    Chapter 7 Cell-Based Measurement of Neutralizing Antibodies Against Adeno-Associated Virus (AAV).
  9. Altmetric Badge
    Chapter 8 Synthesis of Modified mRNA for Myocardial Delivery.
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    Chapter 9 Exosomes-Based Gene Therapy for MicroRNA Delivery.
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    Chapter 10 Lipidoid mRNA Nanoparticles for Myocardial Delivery in Rodents.
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    Chapter 11 Gene Transfer in Isolated Adult Cardiomyocytes.
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    Chapter 12 Gene Transfer in Cardiomyocytes Derived from ES and iPS Cells.
  14. Altmetric Badge
    Chapter 13 Gene Transfer to Rodent Hearts In Vivo.
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    Chapter 14 Ultrasound-Targeted Microbubble Destruction for Cardiac Gene Delivery.
  16. Altmetric Badge
    Chapter 15 A Needleless Liquid Jet Injection Delivery Approach for Cardiac Gene Therapy.
  17. Altmetric Badge
    Chapter 16 Cardiac Gene Delivery in Large Animal Models: Antegrade Techniques.
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    Chapter 17 Direct Myocardial Injection of Vectors.
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    Chapter 18 Selective Pressure-Regulated Retroinfusion for Gene Therapy Application in Ischemic Heart Disease.
  20. Altmetric Badge
    Chapter 19 Cardiac Gene Delivery Using Recirculating Devices.
  21. Altmetric Badge
    Chapter 20 Molecular Cardiac Surgery with Recirculating Delivery (MCARD): Procedure and Vector Transfer.
  22. Altmetric Badge
    Chapter 21 Gene Delivery for the Generation of Bioartificial Pacemaker.
  23. Altmetric Badge
    Chapter 22 Gene Therapy for Post-infarction Ventricular Tachycardia.
  24. Altmetric Badge
    Chapter 23 MicroRNA Delivery Strategies to the Lung in a Model of Pulmonary Hypertension.
  25. Altmetric Badge
    Chapter 24 Inhaled Gene Transfer for Pulmonary Circulation.
Attention for Chapter 3: Generation of Efficient miRNA Inhibitors Using Tough Decoy Constructs.
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Chapter title
Generation of Efficient miRNA Inhibitors Using Tough Decoy Constructs.
Chapter number 3
Book title
Cardiac Gene Therapy
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6588-5_3
Pubmed ID
Book ISBNs
978-1-4939-6586-1, 978-1-4939-6588-5
Authors

Jimeen Yoo, Roger J. Hajjar, Dongtak Jeong Ph.D., Dongtak Jeong

Editors

Kiyotake Ishikawa

Abstract

Over the last decade a previously unappreciated mechanism of gene regulation has been uncovered that is mediated by a large class of small noncoding RNAs known as microRNAs (miRNAs), and this mechanism is utilized by organisms ranging from plants to humans. MiRNAs are important downregulators of gene expression and are seen to be dysregulated in disease development. Thus inhibition of aberrantly upregulated miRNAs as a therapeutic approach has become a promising field.Many models of miRNA inhibitors currently exist, with decoy models being the most successful in current research. A promising inhibition model is the tough decoy (TuD) RNAs inhibitor, which uses antisense sequences to bind to target miRNAs, preventing them from binding to their endogenous targets. Since the TuD inhibitors have the ability to be successfully used in vitro and in vivo studies, this is a covetable inhibition method. In this chapter, we introduce how to design and generate miRNA tough decoy inhibitors with an adeno-associated viral construct. TuD inhibitors will have two miRNA binding sites. The TuD will include stem sequences, a miRNA binding site, and linkers. In vitro validation experiments to confirm the effectiveness of the TuD to inhibit miRNA are described. We also propose some practical approaches for making a TuD for miRNA of interest. We hope this chapter facilitates readers to create a simpler method to generate TuD that can be used for miRNA loss of function studies.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 17%
Other 3 13%
Student > Doctoral Student 3 13%
Student > Bachelor 2 8%
Unspecified 1 4%
Other 2 8%
Unknown 9 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 29%
Agricultural and Biological Sciences 2 8%
Medicine and Dentistry 2 8%
Unspecified 1 4%
Computer Science 1 4%
Other 3 13%
Unknown 8 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 January 2018.
All research outputs
#17,832,285
of 22,908,162 outputs
Outputs from Methods in molecular biology
#7,247
of 13,131 outputs
Outputs of similar age
#293,492
of 420,477 outputs
Outputs of similar age from Methods in molecular biology
#639
of 1,074 outputs
Altmetric has tracked 22,908,162 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,131 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 420,477 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.