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Design and engineering of a transmissible antiviral defense

Overview of attention for article published in Journal of Biological Engineering, October 2016
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Title
Design and engineering of a transmissible antiviral defense
Published in
Journal of Biological Engineering, October 2016
DOI 10.1186/s13036-016-0033-4
Pubmed ID
Authors

Matthew L. Paff, Scott L. Nuismer, Andrew D. Ellington, Ian J. Molineux, Ryan H. May, James J. Bull

Abstract

We propose, model, and implement a novel system of population-level intervention against a virus. One context is a treatment against a chronic infection such as HIV. The underlying principle is a form of virus 'wars' in which a benign, transmissible agent is engineered to protect against infection by and spread of a lethal virus. In our specific case, the protective agent consists of two entities, a benign virus and a gene therapy vector mobilized by the benign virus. Numerical analysis of a mathematical model identified parameter ranges in which adequate, population-wide protection is achieved. The protective system was implemented and tested using E. coli, bacteriophage M13 and a phagemid vector mobilized by M13 to block infection by the lethal phage T5. Engineering of M13 profoundly improved its dynamical properties for facilitating spread of the gene therapy vector. However, the gene therapy vector converts the host cell to resist T5 too slowly for protection on a time scale appropriate for T5. Overall, there is a reasonable marriage between the mathematical model and the empirical system, suggesting that such models can be useful guides to the design of such systems even before the models incorporate most of the relevant biological details.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 24%
Researcher 2 12%
Student > Bachelor 1 6%
Unspecified 1 6%
Professor 1 6%
Other 1 6%
Unknown 7 41%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 18%
Biochemistry, Genetics and Molecular Biology 3 18%
Unspecified 1 6%
Nursing and Health Professions 1 6%
Immunology and Microbiology 1 6%
Other 0 0%
Unknown 8 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 13 October 2016.
All research outputs
#15,387,502
of 22,893,031 outputs
Outputs from Journal of Biological Engineering
#183
of 261 outputs
Outputs of similar age
#201,578
of 319,855 outputs
Outputs of similar age from Journal of Biological Engineering
#3
of 6 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 261 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 22nd percentile – i.e., 22% 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 319,855 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
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 3 of them.