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Porous Silicon Nanoparticle Delivery of Tandem Peptide Anti-Infectives for the Treatment of Pseudomonas aeruginosa Lung Infections

Overview of attention for article published in Advanced Materials, July 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
13 news outlets
blogs
2 blogs
twitter
2 tweeters
facebook
1 Facebook page
reddit
1 Redditor
video
1 video uploader

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
55 Mendeley
citeulike
1 CiteULike
Title
Porous Silicon Nanoparticle Delivery of Tandem Peptide Anti-Infectives for the Treatment of Pseudomonas aeruginosa Lung Infections
Published in
Advanced Materials, July 2017
DOI 10.1002/adma.201701527
Pubmed ID
Authors

Ester J. Kwon, Matthew Skalak, Alessandro Bertucci, Gary Braun, Francesco Ricci, Erkki Ruoslahti, Michael J. Sailor, Sangeeta N. Bhatia

Abstract

There is an urgent need for new materials to treat bacterial infections. In order to improve antibacterial delivery, an anti-infective nanomaterial is developed that utilizes two strategies for localization: i) a biodegradable nanoparticle carrier to localize therapeutics within the tissue, and ii) a novel tandem peptide cargo to localize payload to bacterial membranes. First, a library of antibacterial peptides is screened that combines a membrane-localizing peptide with a toxic peptide cargo and discovers a tandem peptide that displays synergy between the two domains and is able to kill Pseudomonas aeruginosa at sub-micromolar concentrations. To apply this material to the lung, the tandem peptide is loaded into porous silicon nanoparticles (pSiNPs). Charged peptide payloads are loaded into the pores of the pSiNP at ≈30% mass loading and ≈90% loading efficiency using phosphonate surface chemistry. When delivered to the lungs of mice, this anti-infective nanomaterial exhibits improved safety profiles over free peptides. Moreover, treatment of a lung infection of P. aeruginosa results in a large reduction in bacterial numbers and markedly improves survival compared to untreated mice. Collectively, this study presents the selection of a bifunctional peptide-based anti-infective agent and its delivery via biodegradable nanoparticles for application to an animal model of lung infection.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 25%
Unspecified 11 20%
Researcher 10 18%
Student > Bachelor 7 13%
Student > Master 4 7%
Other 9 16%
Readers by discipline Count As %
Engineering 14 25%
Unspecified 14 25%
Chemistry 8 15%
Materials Science 7 13%
Agricultural and Biological Sciences 5 9%
Other 7 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 113. 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 07 August 2017.
All research outputs
#112,569
of 12,183,081 outputs
Outputs from Advanced Materials
#120
of 8,987 outputs
Outputs of similar age
#6,029
of 262,470 outputs
Outputs of similar age from Advanced Materials
#9
of 257 outputs
Altmetric has tracked 12,183,081 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,987 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one has done particularly well, scoring higher than 98% 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 262,470 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 97% of its contemporaries.
We're also able to compare this research output to 257 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.