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Modeling Alexander disease with patient iPSCs reveals cellular and molecular pathology of astrocytes

Overview of attention for article published in Acta Neuropathologica Communications, July 2016
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3 tweeters

Citations

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56 Mendeley
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Title
Modeling Alexander disease with patient iPSCs reveals cellular and molecular pathology of astrocytes
Published in
Acta Neuropathologica Communications, July 2016
DOI 10.1186/s40478-016-0337-0
Pubmed ID
Authors

Takayuki Kondo, Misato Funayama, Michiyo Miyake, Kayoko Tsukita, Takumi Era, Hitoshi Osaka, Takashi Ayaki, Ryosuke Takahashi, Haruhisa Inoue

Abstract

Alexander disease is a fatal neurological illness characterized by white-matter degeneration and formation of Rosenthal fibers, which contain glial fibrillary acidic protein as astrocytic inclusion. Alexander disease is mainly caused by a gene mutation encoding glial fibrillary acidic protein, although the underlying pathomechanism remains unclear. We established induced pluripotent stem cells from Alexander disease patients, and differentiated induced pluripotent stem cells into astrocytes. Alexander disease patient astrocytes exhibited Rosenthal fiber-like structures, a key Alexander disease pathology, and increased inflammatory cytokine release compared to healthy control. These results suggested that Alexander disease astrocytes contribute to leukodystrophy and a variety of symptoms as an inflammatory source in the Alexander disease patient brain. Astrocytes, differentiated from induced pluripotent stem cells of Alexander disease, could be a cellular model for future translational medicine.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 30%
Student > Ph. D. Student 8 14%
Student > Master 5 9%
Student > Doctoral Student 4 7%
Other 4 7%
Other 8 14%
Unknown 10 18%
Readers by discipline Count As %
Neuroscience 15 27%
Agricultural and Biological Sciences 12 21%
Medicine and Dentistry 9 16%
Biochemistry, Genetics and Molecular Biology 6 11%
Computer Science 1 2%
Other 2 4%
Unknown 11 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 December 2017.
All research outputs
#7,938,092
of 13,785,324 outputs
Outputs from Acta Neuropathologica Communications
#474
of 723 outputs
Outputs of similar age
#120,611
of 258,403 outputs
Outputs of similar age from Acta Neuropathologica Communications
#1
of 1 outputs
Altmetric has tracked 13,785,324 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 723 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one is in the 30th percentile – i.e., 30% 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 258,403 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them