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Degradable lipid nanoparticles with predictable in vivo siRNA delivery activity

Overview of attention for article published in Nature Communications, June 2014
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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 (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
10 tweeters
patent
7 patents
weibo
3 weibo users

Citations

dimensions_citation
286 Dimensions

Readers on

mendeley
361 Mendeley
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Title
Degradable lipid nanoparticles with predictable in vivo siRNA delivery activity
Published in
Nature Communications, June 2014
DOI 10.1038/ncomms5277
Pubmed ID
Authors

Kathryn A. Whitehead, J. Robert Dorkin, Arturo J. Vegas, Philip H. Chang, Omid Veiseh, Jonathan Matthews, Owen S. Fenton, Yunlong Zhang, Karsten T. Olejnik, Volkan Yesilyurt, Delai Chen, Scott Barros, Boris Klebanov, Tatiana Novobrantseva, Robert Langer, Daniel G. Anderson

Abstract

One of the most significant challenges in the development of clinically viable delivery systems for RNA interference therapeutics is to understand how molecular structures influence delivery efficacy. Here, we have synthesized 1,400 degradable lipidoids and evaluate their transfection ability and structure-function activity. We show that lipidoid nanoparticles mediate potent gene knockdown in hepatocytes and immune cell populations on IV administration to mice (siRNA EC50 values as low as 0.01 mg kg(-1)). We identify four necessary and sufficient structural and pKa criteria that robustly predict the ability of nanoparticles to mediate greater than 95% protein silencing in vivo. Because these efficacy criteria can be dictated through chemical design, this discovery could eliminate our dependence on time-consuming and expensive cell culture assays and animal testing. Herein, we identify promising degradable lipidoids and describe new design criteria that reliably predict in vivo siRNA delivery efficacy without any prior biological testing.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 361 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Germany 2 <1%
Canada 2 <1%
Unknown 354 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 116 32%
Researcher 50 14%
Student > Master 39 11%
Student > Bachelor 30 8%
Other 23 6%
Other 49 14%
Unknown 54 15%
Readers by discipline Count As %
Chemistry 57 16%
Biochemistry, Genetics and Molecular Biology 47 13%
Engineering 47 13%
Agricultural and Biological Sciences 44 12%
Pharmacology, Toxicology and Pharmaceutical Science 31 9%
Other 65 18%
Unknown 70 19%

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 30 June 2020.
All research outputs
#1,833,702
of 18,057,469 outputs
Outputs from Nature Communications
#19,191
of 36,034 outputs
Outputs of similar age
#21,442
of 196,233 outputs
Outputs of similar age from Nature Communications
#33
of 76 outputs
Altmetric has tracked 18,057,469 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 36,034 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 52.8. This one is in the 46th percentile – i.e., 46% 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 196,233 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 89% of its contemporaries.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.