Huntington’s Disease
Springer New York
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Mendeley readers
Attention Score in Context
| Chapter title |
Cellular Models: HD Patient-Derived Pluripotent Stem Cells
|
|---|---|
| Chapter number | 4 |
| Book title |
Huntington’s Disease
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7825-0_4 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7824-3, 978-1-4939-7825-0
|
| Authors |
Charlene Geater, Sarah Hernandez, Leslie Thompson, Virginia B. Mattis, Geater, Charlene, Hernandez, Sarah, Thompson, Leslie, Mattis, Virginia B. |
| Abstract |
Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by expanded polyglutamine (polyQ)-encoding repeats in the Huntingtin (HTT) gene. Traditionally, HD cellular models consisted of either patient cells not affected by disease or rodent neurons expressing expanded polyQ repeats in HTT. As these models can be limited in their disease manifestation or proper genetic context, respectively, human HD pluripotent stem cells (PSCs) are currently under investigation as a way to model disease in patient-derived neurons and other neural cell types. This chapter reviews embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) models of disease, including published differentiation paradigms for neurons and their associated phenotypes, as well as current challenges to the field such as validation of the PSCs and PSC-derived cells. Highlighted are potential future technical advances to HD PSC modeling, including transdifferentiation, complex in vitro multiorgan/system reconstruction, and personalized medicine. Using a human HD patient model of the central nervous system, hopefully one day researchers can tease out the consequences of mutant HTT (mHTT) expression on specific cell types within the brain in order to identify and test novel therapies for disease. |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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 % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 17% |
| Researcher | 4 | 17% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Bachelor | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 1 | 4% |
| Unknown | 8 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 7 | 29% |
| Agricultural and Biological Sciences | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Mathematics | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 8 | 33% |
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 02 June 2018.
All research outputs
#15,532,144
of 23,083,773 outputs
Outputs from Methods in molecular biology
#5,409
of 13,205 outputs
Outputs of similar age
#270,117
of 442,605 outputs
Outputs of similar age from Methods in molecular biology
#596
of 1,499 outputs
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So far Altmetric has tracked 13,205 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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