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Induced pluripotent stem cell-based modeling of neurodegenerative diseases: a focus on autophagy

Overview of attention for article published in Journal of Molecular Medicine, June 2017
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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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

news
1 news outlet
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3 X users

Citations

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19 Dimensions

Readers on

mendeley
91 Mendeley
Title
Induced pluripotent stem cell-based modeling of neurodegenerative diseases: a focus on autophagy
Published in
Journal of Molecular Medicine, June 2017
DOI 10.1007/s00109-017-1533-5
Pubmed ID
Authors

Johannes Jungverdorben, Andreas Till, Oliver Brüstle

Abstract

The advent of cell reprogramming has enabled the generation of induced pluripotent stem cells (iPSCs) from patient skin fibroblasts or blood cells and their subsequent differentiation into tissue-specific cells, including neurons and glia. This approach can be used to recapitulate disease-specific phenotypes in classical cell culture paradigms and thus represents an invaluable asset for disease modeling and drug validation in the framework of personalized medicine. The autophagy pathway is a ubiquitous eukaryotic degradation and recycling system, which relies on lysosomal degradation of unwanted and potentially cytotoxic components. The relevance of autophagy in the pathogenesis of neurodegenerative diseases is underlined by the observation that disease-linked genetic variants of susceptibility factors frequently result in dysregulation of autophagic-lysosomal pathways. In particular, disrupted autophagy is implied in the accumulation of potentially neurotoxic products such as protein aggregates and their precursors and defective turnover of dysfunctional mitochondria. Here, we review the current state of iPSC-based assessment of autophagic dysfunction in the context of neurodegenerative disease modeling. The collected data show that iPSC technology is capable to reveal even subtle alterations in subcellular homeostatic processes, which form the molecular basis for disease manifestation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Belgium 1 1%
Unknown 89 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 25%
Student > Bachelor 14 15%
Student > Master 11 12%
Researcher 10 11%
Student > Doctoral Student 5 5%
Other 10 11%
Unknown 18 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 25%
Neuroscience 18 20%
Biochemistry, Genetics and Molecular Biology 13 14%
Medicine and Dentistry 7 8%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Other 6 7%
Unknown 21 23%
Attention Score in Context

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 March 2018.
All research outputs
#2,967,403
of 22,979,862 outputs
Outputs from Journal of Molecular Medicine
#106
of 1,554 outputs
Outputs of similar age
#57,073
of 317,348 outputs
Outputs of similar age from Journal of Molecular Medicine
#4
of 23 outputs
Altmetric has tracked 22,979,862 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,554 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 92% 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 317,348 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 81% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.