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Modeling rejection immunity

Overview of attention for article published in Theoretical Biology and Medical Modelling, May 2012
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Mentioned by

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1 tweeter

Citations

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1 Dimensions

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9 Mendeley
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Title
Modeling rejection immunity
Published in
Theoretical Biology and Medical Modelling, May 2012
DOI 10.1186/1742-4682-9-18
Pubmed ID
Authors

AndreaDe Gaetano, Alice Matone, Annamaria Agnes, Pasquale Palumbo, Francesco Ria, Sabina Magalini

Abstract

Transplantation is often the only way to treat a number of diseases leading to organ failure. To overcome rejection towards the transplanted organ (graft), immunosuppression therapies are used, which have considerable side-effects and expose patients to opportunistic infections. The development of a model to complement the physician's experience in specifying therapeutic regimens is therefore desirable. The present work proposes an Ordinary Differential Equations model accounting for immune cell proliferation in response to the sudden entry of graft antigens, through different activation mechanisms. The model considers the effect of a single immunosuppressive medication (e.g. cyclosporine), subject to first-order linear kinetics and acting by modifying, in a saturable concentration-dependent fashion, the proliferation coefficient. The latter has been determined experimentally. All other model parameter values have been set so as to reproduce reported state variable time-courses, and to maintain consistency with one another and with the experimentally derived proliferation coefficient.

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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 44%
Researcher 3 33%
Student > Master 2 22%
Readers by discipline Count As %
Computer Science 3 33%
Agricultural and Biological Sciences 2 22%
Medicine and Dentistry 2 22%
Mathematics 1 11%
Engineering 1 11%
Other 0 0%

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 May 2012.
All research outputs
#7,804,665
of 12,440,173 outputs
Outputs from Theoretical Biology and Medical Modelling
#121
of 225 outputs
Outputs of similar age
#66,297
of 119,138 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#5
of 7 outputs
Altmetric has tracked 12,440,173 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 225 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 32nd percentile – i.e., 32% 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 119,138 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.