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Mathematical Modeling of Early Cellular Innate and Adaptive Immune Responses to Ischemia/Reperfusion Injury and Solid Organ Allotransplantation

Overview of attention for article published in Frontiers in immunology, September 2015
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Title
Mathematical Modeling of Early Cellular Innate and Adaptive Immune Responses to Ischemia/Reperfusion Injury and Solid Organ Allotransplantation
Published in
Frontiers in immunology, September 2015
DOI 10.3389/fimmu.2015.00484
Pubmed ID
Authors

Judy D. Day, Diana M. Metes, Yoram Vodovotz

Abstract

A mathematical model of the early inflammatory response in transplantation is formulated with ordinary differential equations. We first consider the inflammatory events associated only with the initial surgical procedure and the subsequent ischemia/reperfusion (I/R) events that cause tissue damage to the host as well as the donor graft. These events release damage-associated molecular pattern molecules (DAMPs), thereby initiating an acute inflammatory response. In simulations of this model, resolution of inflammation depends on the severity of the tissue damage caused by these events and the patient's (co)-morbidities. We augment a portion of a previously published mathematical model of acute inflammation with the inflammatory effects of T cells in the absence of antigenic allograft mismatch (but with DAMP release proportional to the degree of graft damage prior to transplant). Finally, we include the antigenic mismatch of the graft, which leads to the stimulation of potent memory T cell responses, leading to further DAMP release from the graft and concomitant increase in allograft damage. Regulatory mechanisms are also included at the final stage. Our simulations suggest that surgical injury and I/R-induced graft damage can be well-tolerated by the recipient when each is present alone, but that their combination (along with antigenic mismatch) may lead to acute rejection, as seen clinically in a subset of patients. An emergent phenomenon from our simulations is that low-level DAMP release can tolerize the recipient to a mismatched allograft, whereas different restimulation regimens resulted in an exaggerated rejection response, in agreement with published studies. We suggest that mechanistic mathematical models might serve as an adjunct for patient- or sub-group-specific predictions, simulated clinical studies, and rational design of immunosuppression.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Student > Master 6 17%
Researcher 5 14%
Other 2 6%
Student > Postgraduate 2 6%
Other 5 14%
Unknown 7 20%
Readers by discipline Count As %
Medicine and Dentistry 9 26%
Biochemistry, Genetics and Molecular Biology 5 14%
Agricultural and Biological Sciences 5 14%
Computer Science 2 6%
Mathematics 1 3%
Other 5 14%
Unknown 8 23%
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 07 October 2015.
All research outputs
#20,824,878
of 25,584,565 outputs
Outputs from Frontiers in immunology
#25,074
of 32,016 outputs
Outputs of similar age
#210,201
of 286,688 outputs
Outputs of similar age from Frontiers in immunology
#123
of 161 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 32,016 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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