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Updated: Jun 13, 2025

Isolated Pancreatic Islet Treatment and Apoptosis Measurement
Published on: May 2, 2025
Tipping-point transition from transient to persistent inflammation in pancreatic islets
Thomas Holst-Hansen1, Pernille Yde Nielsen1,2, Mogens H Jensen3
1Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
Type 2 diabetes involves dual IL-1β responses in pancreatic islets. A balance of feedback loops determines transient beneficial or persistent harmful inflammation, impacting insulin secretion.
Area of Science:
- Immunology
- Endocrinology
- Computational Biology
Background:
- Type 2 diabetes (T2D) is linked to elevated pro-inflammatory cytokine IL-1β.
- Low IL-1β levels transiently benefit insulin secretion and beta-cell proliferation, while prolonged exposure impairs function and causes cell death.
- The local regulation of these opposing IL-1β effects within single pancreatic islets remains unclear.
Purpose of the Study:
- To investigate the dual nature of IL-1β signaling within pancreatic islets.
- To determine if islet-level regulation can explain transient versus persistent IL-1β responses.
- To model the IL-1β regulatory network in pancreatic islets using a quantitative in silico approach.
Main Methods:
- Developed a quantitative in silico model of the IL-1β regulatory network in pancreatic islets.
- Analyzed the network's response to pro-inflammatory and metabolic cues.
- Identified key feedback mechanisms governing IL-1β dynamics.
Main Results:
- The IL-1β regulatory network can generate both transient and persistent IL-1β responses.
- A balance between fast positive feedback (IL-1R/IKK/NF-κB) and slow negative feedback (e.g., A20) determines the response mode.
- Large islets and those with high IL-1β-producing cell density are more susceptible to persistent inflammation.
Conclusions:
- The duality of IL-1β effects is likely regulated at the single islet level.
- Feedback mechanisms involving positive and negative regulation on different timescales explain IL-1β response modes.
- Model predictions offer testable hypotheses for experimental validation and potential clinical applications in T2D.
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