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The therapeutic landscape of HIV-1 via genome editing

Overview of attention for article published in AIDS Research and Therapy, July 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 (#38 of 556)
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

blogs
1 blog
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9 X users
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2 Facebook pages

Readers on

mendeley
102 Mendeley
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Title
The therapeutic landscape of HIV-1 via genome editing
Published in
AIDS Research and Therapy, July 2017
DOI 10.1186/s12981-017-0157-8
Pubmed ID
Authors

Alexander Kwarteng, Samuel Terkper Ahuno, Godwin Kwakye-Nuako

Abstract

Current treatment for HIV-1 largely relies on chemotherapy through the administration of antiretroviral drugs. While the search for anti-HIV-1 vaccine remain elusive, the use of highly active antiretroviral therapies (HAART) have been far-reaching and has changed HIV-1 into a manageable chronic infection. There is compelling evidence, including several side-effects of ARTs, suggesting that eradication of HIV-1 cannot depend solely on antiretrovirals. Gene therapy, an expanding treatment strategy, using RNA interference (RNAi) and programmable nucleases such as meganuclease, zinc finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeats/CRISPR-associated proteins (CRISPR-Cas9) are transforming the therapeutic landscape of HIV-1. TALENS and ZFNS are structurally similar modular systems, which consist of a FokI endonuclease fused to custom-designed effector proteins but have been largely limited, particularly ZFNs, due to their complexity and cost of protein engineering. However, the newly developed CRISPR-Cas9 system, consists of a single guide RNA (sgRNA), which directs a Cas9 endonuclease to complementary target sites, and serves as a superior alternative to the previous protein-based systems. The techniques have been successfully applied to the development of better HIV-1 models, generation of protective mutations in endogenous/host cells, disruption of HIV-1 genomes and even reactivating latent viruses for better detection and clearance by host immune response. Here, we focus on gene editing-based HIV-1 treatment and research in addition to providing  perspectives for refining these techniques.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 30 29%
Student > Master 15 15%
Student > Ph. D. Student 12 12%
Researcher 9 9%
Other 7 7%
Other 8 8%
Unknown 21 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 27%
Medicine and Dentistry 15 15%
Agricultural and Biological Sciences 14 14%
Immunology and Microbiology 9 9%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Other 12 12%
Unknown 21 21%
Attention Score in Context

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 28 February 2019.
All research outputs
#2,348,695
of 22,988,380 outputs
Outputs from AIDS Research and Therapy
#38
of 556 outputs
Outputs of similar age
#46,512
of 312,506 outputs
Outputs of similar age from AIDS Research and Therapy
#1
of 8 outputs
Altmetric has tracked 22,988,380 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 556 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 93% 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 312,506 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 85% of its contemporaries.
We're also able to compare this research output to 8 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