title: A stochastic mathematical model to study the autoimmune progression towards type 1 diabetes.
abstract: BACKGROUND
  The integrity of the interactions and the 3D architecture among beta cell populations in pancreatic islets is critical for proper biosynthesis, storage and release of insulin. The aim of this study was to evaluate the effect on electrophysiological signalling of beta cells that is produced by progressive lymphocytic islet cell infiltration (insulitis), by modelling the disruption of pancreatic islet anatomy as a consequence of insulitis and altered glucose concentrations.
  
  
  METHODS
  On the basis of histopathological images of murine islets from non-obese diabetic mice, we simulated the electrophysiological dynamics of a 3D cluster of mouse beta cells via a stochastic model. Progressive damage was modelled at different glucose concentrations, representing the different glycaemic states in the autoimmune progression towards type 1 diabetes.
  
  
  RESULTS
  At 31% of dead beta cells (normoglycaemia) and 69% (hyperglycaemia), the system appeared to be biologically robust to maintain regular Ca(2+) ion oscillations guaranteeing an effective insulin release. Simulations at 84%, 94% and 98% grades (severe hyperglycemia) showed that intracellular calcium oscillations were absent. In such conditions, insulin pulsatility is not expected to occur.
  
  
  CONCLUSIONS
  Our results suggest that the islet tissue is biophysically robust enough to compensate for high rates of beta cell loss. These predictions can be experimentally tested in vitro by quantifying space and time electrophysiological dynamics of animal islets kept at different glucose gradients. The model indicates the necessity of maintaining glycaemia within the physiological range as soon as possible after diabetes onset to avoid a dramatic interruption of Ca(2+) pulsatility and the consequent drop of insulin release.
authors.affiliation: Department of Endocrinology and Diabetes, University Campus Bio-Medico, Rome, Italy.
authors.forename: R
authors.initials: R
authors.lastname: Portuesi
authors.forename: C
authors.initials: C
authors.lastname: Cherubini
authors.forename: A
authors.initials: A
authors.lastname: Gizzi
authors.forename: R
authors.initials: R
authors.lastname: Buzzetti
authors.forename: P
authors.initials: P
authors.lastname: Pozzilli
authors.forename: S
authors.initials: S
authors.lastname: Filippi
mesh_terms: D000200:Action Potentials; D000818:Animals; D001786:Blood Glucose / Q000378:metabolism; D002118:Calcium / Q000378:metabolism; D003922:Diabetes Mellitus, Type 1 / Q000209:etiology* / Q000276:immunology*; D050417:Insulin-Secreting Cells / Q000276:immunology / Q000473:pathology / Q000502:physiology*; D051379:Mice; D008954:Models, Biological; D013269:Stochastic Processes
chemical_list: D001786:Blood Glucose; D002118:Calcium