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Protein misfolding in neurodegenerative diseases: implications and strategies

Overview of attention for article published in Translational Neurodegeneration, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#44 of 243)
  • High Attention Score compared to outputs of the same age (84th percentile)

Mentioned by

news
1 news outlet
twitter
9 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
243 Dimensions

Readers on

mendeley
531 Mendeley
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Title
Protein misfolding in neurodegenerative diseases: implications and strategies
Published in
Translational Neurodegeneration, March 2017
DOI 10.1186/s40035-017-0077-5
Pubmed ID
Authors

Patrick Sweeney, Hyunsun Park, Marc Baumann, John Dunlop, Judith Frydman, Ron Kopito, Alexander McCampbell, Gabrielle Leblanc, Anjli Venkateswaran, Antti Nurmi, Robert Hodgson

Abstract

A hallmark of neurodegenerative proteinopathies is the formation of misfolded protein aggregates that cause cellular toxicity and contribute to cellular proteostatic collapse. Therapeutic options are currently being explored that target different steps in the production and processing of proteins implicated in neurodegenerative disease, including synthesis, chaperone-assisted folding and trafficking, and degradation via the proteasome and autophagy pathways. Other therapies, like mTOR inhibitors and activators of the heat shock response, can rebalance the entire proteostatic network. However, there are major challenges that impact the development of novel therapies, including incomplete knowledge of druggable disease targets and their mechanism of action as well as a lack of biomarkers to monitor disease progression and therapeutic response. A notable development is the creation of collaborative ecosystems that include patients, clinicians, basic and translational researchers, foundations and regulatory agencies to promote scientific rigor and clinical data to accelerate the development of therapies that prevent, reverse or delay the progression of neurodegenerative proteinopathies.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 531 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
United Kingdom 1 <1%
Finland 1 <1%
Netherlands 1 <1%
Unknown 526 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 124 23%
Student > Bachelor 100 19%
Student > Master 74 14%
Researcher 53 10%
Student > Doctoral Student 26 5%
Other 55 10%
Unknown 99 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 169 32%
Neuroscience 61 11%
Agricultural and Biological Sciences 44 8%
Chemistry 40 8%
Medicine and Dentistry 26 5%
Other 73 14%
Unknown 118 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 23 September 2020.
All research outputs
#1,846,701
of 18,942,198 outputs
Outputs from Translational Neurodegeneration
#44
of 243 outputs
Outputs of similar age
#40,942
of 274,031 outputs
Outputs of similar age from Translational Neurodegeneration
#1
of 1 outputs
Altmetric has tracked 18,942,198 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 243 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has done well, scoring higher than 81% 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 274,031 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 84% 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