Cited by 59Pancreatic function and diabetesNeural dynamics and brain functionIon channel regulation and function

Functional identification of islet cell types by electrophysiological fingerprinting

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Briant, Linford J. B., Zhang, Quan, Vergari, Elisa, Kellard, Joely A., Rodriguez, Blanca, Ashcroft, Frances M., Rorsman, Patrik·2017·Journal of The Royal Society Interface

Abstract

The α-, β- and δ-cells of the pancreatic islet exhibit different electrophysiological features. We used a large dataset of whole-cell patch-clamp recordings from cells in intact mouse islets (N= 288 recordings) to investigate whether it is possible to reliably identify cell type (α, β or δ) 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 regression model that included all quantified variables, to determine whether they could together identify cell type. The model identified cell type with 94% accuracy. This model was applied to a dataset of cells recorded from hyperglycaemic βV59M 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 α-cells and generate a model of δ-cell electrical activity. These new models could faithfully emulate α- and δ-cell electrical activity recorded experimentally.

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Authors
Briant, L. J. B., Zhang, Q., Vergari, E., Kellard, J. A., Rodriguez, B., Ashcroft, F. M., & Rorsman, P.
Affiliations
  • Churchill Hospital (GB)
  • Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK
  • University of Oxford (GB)
Corresponding author
Briant, Linford J. B.
Venue
Journal of The Royal Society Interface
Published
2017-03
Volume
14
Issue
128
Pages
20160999
ISSN
  • 1742-5662 (ISSN-L)
  • 1742-5689
OpenAlex
W2592904886
Cited by
59
References
89
Citations by year
2026: 3 · 2025: 7 · 2024: 4 · 2023: 2 · 2022: 6 · 2021: 13 · 2020: 9 · 2019: 7 · 2018: 4 · 2017: 4
FWCI
6.72
Type
journal article
Language
en
Open access
Locations
  • Journal of The Royal Society Interface (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Wellcome Trust (089795, 095531, 100246/Z/12/Z, 201325/Z/16/Z, 884655)
  • European Research Council (322620)
  • Engineering and Physical Sciences Research Council (EP/K503769/1)
  • European Commission (675451)
  • Diabetes UK
  • National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/P001076/1)
  • BHF Centre of Research Excellence, Oxford (RE/13/1/30181)
Topics
  • Health Sciences › Medicine › Surgery › Pancreatic function and diabetes
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ion channel regulation and function
Keywords
pancreatic islet cells, alpha cells, pancreatic beta cells, delta cells, cell type annotation, logistic regression, hyperglycemia, conductance-based models
MeSH terms
Animals, Hyperglycemia, Islets of Langerhans, Models, Biological, Mice, Knockout, Mice, Electrophysiological Phenomena

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