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A theoretical model of the West Nile Virus survival data

Overview of attention for article published in BMC Immunology, June 2017
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Title
A theoretical model of the West Nile Virus survival data
Published in
BMC Immunology, June 2017
DOI 10.1186/s12865-017-0206-z
Pubmed ID
28681706
Authors

James K. Peterson, Alison M. Kesson, Nicholas J. C. King

Abstract

In this work, we develop a theoretical model that explains the survival data in West Nile Virus infection. We build a model based on three cell populations in an infected host; the collateral damage cells, the infected dividing cell, and the infected non-dividing cells. T cell-mediated lysis of each of these populations is dependent on the level of MHC-1 upregulation, which is different in the two infected cell populations, interferon-gamma and free virus levels. The model allows us to plot a measure of host health versus time for a range of initial viral doses and from that infer the dependence of minimal health versus viral dose. This inferred functional relationship between the minimal host health and viral dose is very similar to the data that has been collected for WNV survival curves under experimental conditions.

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Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 25%
Researcher 2 25%
Student > Bachelor 1 13%
Other 1 13%
Student > Doctoral Student 1 13%
Other 1 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 25%
Immunology and Microbiology 2 25%
Computer Science 1 13%
Veterinary Science and Veterinary Medicine 1 13%
Economics, Econometrics and Finance 1 13%
Other 1 13%

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 23 June 2017.
All research outputs
#9,127,392
of 11,403,395 outputs
Outputs from BMC Immunology
#297
of 387 outputs
Outputs of similar age
#190,563
of 263,321 outputs
Outputs of similar age from BMC Immunology
#16
of 19 outputs
Altmetric has tracked 11,403,395 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 387 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 10th percentile – i.e., 10% 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 263,321 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.

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