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Targeted therapies to improve CFTR function in cystic fibrosis

Overview of attention for article published in Genome Medicine, September 2015
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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 (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

news
1 news outlet
policy
1 policy source
twitter
7 tweeters
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
229 Mendeley
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Title
Targeted therapies to improve CFTR function in cystic fibrosis
Published in
Genome Medicine, September 2015
DOI 10.1186/s13073-015-0223-6
Pubmed ID
Authors

Malcolm Brodlie, Iram J. Haq, Katie Roberts, J. Stuart Elborn

Abstract

Cystic fibrosis is the most common genetically determined, life-limiting disorder in populations of European ancestry. The genetic basis of cystic fibrosis is well established to be mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene that codes for an apical membrane chloride channel principally expressed by epithelial cells. Conventional approaches to cystic fibrosis care involve a heavy daily burden of supportive treatments to combat lung infection, help clear airway secretions and maintain nutritional status. In 2012, a new era of precision medicine in cystic fibrosis therapeutics began with the licensing of a small molecule, ivacaftor, which successfully targets the underlying defect and improves CFTR function in a subgroup of patients in a genotype-specific manner. Here, we review the three main targeted approaches that have been adopted to improve CFTR function: potentiators, which recover the function of CFTR at the apical surface of epithelial cells that is disrupted in class III and IV genetic mutations; correctors, which improve intracellular processing of CFTR, increasing surface expression, in class II mutations; and production correctors or read-through agents, which promote transcription of CFTR in class I mutations. The further development of such approaches offers great promise for future therapeutic strategies in cystic fibrosis.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 229 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Brazil 1 <1%
Unknown 226 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 71 31%
Student > Master 36 16%
Student > Ph. D. Student 19 8%
Researcher 18 8%
Student > Postgraduate 17 7%
Other 31 14%
Unknown 37 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 49 21%
Medicine and Dentistry 47 21%
Agricultural and Biological Sciences 36 16%
Pharmacology, Toxicology and Pharmaceutical Science 19 8%
Nursing and Health Professions 9 4%
Other 28 12%
Unknown 41 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 25 April 2019.
All research outputs
#948,994
of 14,830,199 outputs
Outputs from Genome Medicine
#230
of 1,032 outputs
Outputs of similar age
#21,419
of 247,878 outputs
Outputs of similar age from Genome Medicine
#2
of 6 outputs
Altmetric has tracked 14,830,199 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,032 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.7. This one has done well, scoring higher than 77% 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 247,878 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.