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Integrated Model of Metabolism and Autoimmune Response in β-Cell Death and Progression to Type 1 Diabetes

Overview of attention for article published in PLOS ONE, December 2012
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Title
Integrated Model of Metabolism and Autoimmune Response in β-Cell Death and Progression to Type 1 Diabetes
Published in
PLOS ONE, December 2012
DOI 10.1371/journal.pone.0051909
Pubmed ID
Authors

Tijana Marinković, Marko Sysi-Aho, Matej Orešič

Abstract

Progression to type 1 diabetes is characterized by complex interactions of environmental, metabolic and immune system factors, involving both degenerative pathways leading to loss of pancreatic β-cells as well as protective pathways. The interplay between the degenerative and protective pathways may hold the key to disease outcomes, but no models have so far captured the two together. Here we propose a mathematical framework, an ordinary differential equation (ODE) model, which integrates metabolism and the immune system in early stages of disease process. We hypothesize that depending on the degree of regulation, autoimmunity may also play a protective role in the initial response to stressors. We assume that β-cell destruction follows two paths of loss: degenerative and autoimmune-induced loss. The two paths are mutually competing, leading to termination of the degenerative loss and further to elimination of the stress signal and the autoimmune response, and ultimately stopping the β-cell loss. The model describes well our observations from clinical and non-clinical studies and allows exploration of how the rate of β-cell loss depends on the amplitude and duration of autoimmune response.

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 > Master 5 29%
Lecturer 1 6%
Student > Bachelor 1 6%
Other 1 6%
Student > Ph. D. Student 1 6%
Other 3 18%
Unknown 5 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 12%
Medicine and Dentistry 2 12%
Engineering 2 12%
Mathematics 1 6%
Business, Management and Accounting 1 6%
Other 4 24%
Unknown 5 29%