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Publication year
2017Source
Journal of Theoretical Biology, 419, (2017), pp. 333-342ISSN
Publication type
Article / Letter to editor

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Organization
Internal Medicine
Journal title
Journal of Theoretical Biology
Volume
vol. 419
Page start
p. 333
Page end
p. 342
Subject
Radboudumc 6: Metabolic Disorders RIMLS: Radboud Institute for Molecular Life SciencesAbstract
Glucose plasma measurements for diabetes patients are generally presented as a glucose concentration-time profile with 15-60min time scale intervals. This limited resolution obscures detailed dynamic events of glucose appearance and metabolism. Measurement intervals of 15min or more could contribute to imperfections in present diabetes treatment. High resolution data from mixed meal tolerance tests (MMTT) for 24 type 1 and type 2 diabetes patients were used in our present modeling. We introduce a model based on the physiological properties of transport, storage and utilization. This logistic approach follows the principles of electrical network analysis and signal processing theory. The method mimics the physiological equivalent of the glucose homeostasis comprising the meal ingestion, absorption via the gastrointestinal tract (GIT) to the endocrine nexus between the liver, pancreatic alpha and beta cells. This model demystifies the metabolic 'black box' by enabling in silico simulations and fitting of individual responses to clinical data. Five-minute intervals MMTT data measured from diabetic subjects result in two independent model parameters that characterize the complete glucose system response at a personalized level. From the individual data measurements, we obtain a model which can be analyzed with a standard electrical network simulator for diagnostics and treatment optimization. The insulin dosing time scale can be accurately adjusted to match the individual requirements of characterized diabetic patients without the physical burden of treatment.
This item appears in the following Collection(s)
- Academic publications [229097]
- Electronic publications [111496]
- Faculty of Medical Sciences [87745]
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