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Huntington’s Disease

Overview of attention for book
Huntington’s Disease
Springer New York

Table of Contents

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    Book Overview
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    Chapter 1 Stereological Methods to Quantify Cell Loss in the Huntington’s Disease Human Brain
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    Chapter 2 Assessing Autophagic Activity and Aggregate Formation of Mutant Huntingtin in Mammalian Cells
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    Chapter 3 A Filter Retardation Assay Facilitates the Detection and Quantification of Heat-Stable, Amyloidogenic Mutant Huntingtin Aggregates in Complex Biosamples
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    Chapter 4 Cellular Models: HD Patient-Derived Pluripotent Stem Cells
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    Chapter 6 Mouse Models of Huntington’s Disease
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    Chapter 8 Automated Operant Assessments of Huntington’s Disease Mouse Models
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    Chapter 10 Murine Models of Huntington’s Disease for Evaluating Therapeutics
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    Chapter 11 Generating Excitotoxic Lesion Models of Huntington’s Disease
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    Chapter 12 Large-Brained Animal Models of Huntington’s Disease: Sheep
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    Chapter 14 Nonhuman Primate Models of Huntington’s Disease and Their Application in Translational Research
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    Chapter 15 In Vivo Multidimensional Brain Imaging in Huntington’s Disease Animal Models
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    Chapter 16 Magnetic Resonance Imaging in Huntington’s Disease
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    Chapter 17 Biofluid Biomarkers in Huntington’s Disease
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    Chapter 18 Assessing and Modulating Kynurenine Pathway Dynamics in Huntington’s Disease: Focus on Kynurenine 3-Monooxygenase
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    Chapter 20 Using Genomic Data to Find Disease-Modifying Loci in Huntington’s Disease (HD)
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    Chapter 22 Methods for Assessing DNA Repair and Repeat Expansion in Huntington’s Disease
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    Chapter 23 Translating Antisense Technology into a Treatment for Huntington’s Disease
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    Chapter 26 Dissection and Preparation of Human Primary Fetal Ganglionic Eminence Tissue for Research and Clinical Applications
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    Chapter 28 Quality Assessment and Production of Human Cells for Clinical Use
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    Chapter 29 Erratum to: Large-Brained Animal Models of Huntington’s Disease: Sheep
Attention for Chapter: Methods to Quantify Cell Signaling and GPCR Receptor Ligand Bias: Characterization of Drugs that Target the Endocannabinoid Receptors in Huntington’s Disease
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Chapter title
Methods to Quantify Cell Signaling and GPCR Receptor Ligand Bias: Characterization of Drugs that Target the Endocannabinoid Receptors in Huntington’s Disease
Book title
Huntington’s Disease
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7825-0_25
Pubmed ID
Book ISBNs
978-1-4939-7824-3, 978-1-4939-7825-0
Authors

Amina M. Bagher, Robert B. Laprairie, Melanie E. M. Kelly, Eileen M. Denovan-Wright

Abstract

G protein-coupled receptors (GPCRs) interact with multiple intracellular effector proteins such that different ligands may preferentially activate one signal pathway over others, a phenomenon known as signaling bias. Signaling bias can be quantified to optimize drug selection for preclinical research. Here, we describe moderate-throughput methods to quantify signaling bias of known and novel compounds. In the example provided, we describe a method to define cannabinoid-signaling bias in a cell culture model of Huntington's disease (HD). Decreasing type 1 cannabinoid receptor (CB1) levels is correlated with chorea and cognitive deficits in HD. There is evidence that elevating CB1 levels and/or signaling may be beneficial for HD patients while decreasing CB1 levels and/or signaling may be detrimental. Recent studies have found that Gαi/o-biased CB1 agonists activate extracellular signal-regulated kinase (ERK), increase CB1 protein levels, and improve viability of cells expressing mutant huntingtin. In contrast, CB1 agonists that are β-arrestin1-biased were found to reduce CB1 protein levels and cell viability. Measuring agonist bias of known and novel CB1 agonists will provide important data that predict CB1-specific agonists that might be beneficial in animal models of HD and, following animal testing, in HD patients. This method can also be applied to study signaling bias for other GPCRs.

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The data shown below were collected from the profile of 1 X user 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 16%
Student > Bachelor 3 12%
Researcher 3 12%
Professor 2 8%
Student > Doctoral Student 2 8%
Other 2 8%
Unknown 9 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 12%
Medicine and Dentistry 3 12%
Neuroscience 2 8%
Psychology 2 8%
Agricultural and Biological Sciences 1 4%
Other 3 12%
Unknown 11 44%
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 04 June 2018.
All research outputs
#18,635,458
of 23,085,832 outputs
Outputs from Methods in molecular biology
#7,986
of 13,204 outputs
Outputs of similar age
#330,843
of 442,628 outputs
Outputs of similar age from Methods in molecular biology
#950
of 1,499 outputs
Altmetric has tracked 23,085,832 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,204 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.