↓ Skip to main content

Dove Medical Press

Article Metrics

Transgenic animal models for study of the pathogenesis of Huntington’s disease and therapy

Overview of attention for article published in Drug Design, Development and Therapy, April 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
1 news outlet
twitter
1 tweeter

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
138 Mendeley
Title
Transgenic animal models for study of the pathogenesis of Huntington’s disease and therapy
Published in
Drug Design, Development and Therapy, April 2015
DOI 10.2147/dddt.s58470
Pubmed ID
Authors

Xiao-Jiang Li, Rengbao Chang, Xudong Liu, Shihua Li

Abstract

Huntington's disease (HD) is caused by a genetic mutation that results in polyglutamine expansion in the N-terminal regions of huntingtin. As a result, this polyQ expansion leads to the misfolding and aggregation of mutant huntingtin as well as age-dependent neurodegeneration. The genetic mutation in HD allows for generating a variety of animal models that express different forms of mutant huntingtin and show differential pathology. Studies of these animal models have provided an important insight into the pathogenesis of HD. Mouse models of HD include transgenic mice, which express N-terminal or full-length mutant huntingtin ubiquitously or selectively in different cell types, and knock-in mice that express full-length mutant Htt at the endogenous level. Large animals, such as pig, sheep, and monkeys, have also been used to generate animal HD models. This review focuses on the different features of commonly used transgenic HD mouse models as well as transgenic large animal models of HD, and also discusses how to use them to identify potential therapeutics. Since HD shares many pathological features with other neurodegenerative diseases, identification of therapies for HD would also help to develop effective treatment for different neurodegenerative diseases that are also caused by protein misfolding and occur in an age-dependent manner.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
China 1 <1%
Unknown 135 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 32 23%
Researcher 21 15%
Student > Ph. D. Student 20 14%
Student > Master 19 14%
Student > Doctoral Student 6 4%
Other 16 12%
Unknown 24 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 25%
Neuroscience 27 20%
Biochemistry, Genetics and Molecular Biology 22 16%
Medicine and Dentistry 14 10%
Nursing and Health Professions 3 2%
Other 13 9%
Unknown 25 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 15 May 2015.
All research outputs
#3,195,800
of 22,805,349 outputs
Outputs from Drug Design, Development and Therapy
#177
of 2,083 outputs
Outputs of similar age
#43,646
of 264,662 outputs
Outputs of similar age from Drug Design, Development and Therapy
#9
of 82 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,083 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 90% of its peers.
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 264,662 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.