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Functional identification of islet cell types by electrophysiological fingerprinting

Journal article
Authors L. J. B. Briant
Q. Zhang
E. Vergari
J. A. Kellard
B. Rodriguez
Frances M. Ashcroft
Patrik Rorsman
Published in Journal of the Royal Society Interface
Volume 14
Issue 128
ISSN 1742-5689
Publication year 2017
Published at Institute of Neuroscience and Physiology, Department of Physiology
Language en
Links 10.1098/rsif.2016.0999
Keywords islet electrophysiology, logistic regression, alpha-cell, beta-cell, gamma-cell, conductance-based, pancreatic alpha-cells, k-atp channels, inhibits glucagon-secretion, gated ion channels, beta-cells, insulin-secretion, delta-cells, potassium channels, endocrine pancreas, b-cells, ci l, 1982, diabetes, v31, p538
Subject categories Internal medicine


The alpha-, beta- and delta-cells of the pancreatic islet exhibit different electrophysiological features. We used a large dataset of whole- cell patch- clamp recordings from cells in intactmouse islets (N = 288 recordings) to investigatewhether it is possible to reliably identify cell type (alpha,beta or gamma) based on their electrophysiological characteristics. We quantified 15 electrophysiological variables in each recorded cell. Individually, none of the variables could reliably distinguish the cell types. We therefore constructed a logistic regressionmodel that included all quantified variables, to determine whether they could together identify cell type. The model identified cell typewith 94% accuracy. Thismodelwas applied to a dataset of cells recorded from hyperglycaemic bV59M mice; it correctly identified cell type in all cells and was able to distinguish cells that co-expressed insulin and glucagon. Based on this revised functional identification, we were able to improve conductance-based models of the electrical activity in alpha-cells and generate a model of gamma-cell electrical activity. These new models could faithfully emulate alpha- and gamma-cell electrical activity recorded experimentally.

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