ArticleDiabetologia2025
Beyond the loss of beta cells: a quantitative analysis of islet architecture in adults with and without type 1 diabetes.
Article in Diabetologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Proteomic analysis of pancreatic endocrine cells by mechanistic single-cell isolation identifies membrane pathways.Experimental & molecular medicine · 2026Article
- Deep learning-powered quantification of endocrine cells and CD3Diabetologia · 2026Article
- Zinc-Coordinated Trienzyme Nanogel Cascade Therapy for Accelerated Post-Pancreatectomy Cutaneous Wound Healing.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Effects of a Sodium-Glucose Cotransporter 2 Inhibitor Dapagliflozin on Pancreas in Obese Diabetic Mice.In vivo (Athens, Greece)Article
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Authors and funding
8 authors.
Funding
Abstract
aims/hypothesisThe organisation and cellular architecture of islets of Langerhans are critical to the physiological regulation of hormone secretion but it is debated whether human islets adhere to the characteristic mantle-core (M-C) structure seen in rodents. It is also unclear whether inherent architectural changes contribute to islet dysfunction in type 1 diabetes, aside from the loss of beta cells. Therefore, we have exploited advances in immunostaining, spatial biology and machine learning to undertake a detailed, systematic analysis of adult human islet architecture in health and type 1 diabetes, by a quantitative analysis of a dataset of >250,000 endocrine cells in >3500 islets from ten individuals.
methodsFormalin-fixed paraffin-embedded pancreatic sections (4 μm) from organ donors without diabetes and living donors with recent-onset type 1 diabetes were stained for all five islet hormones and imaged prior to analysis, which employed a novel automated pipeline using QuPath software, capable of running on a standard laptop. Whole-slide image analysis involved segmentation classifiers, cell detection and phenotyping algorithms to identify islets, specific cell types and their locations as (x,y)-coordinates in regions of interest. Each endocrine cell was categorised into binary variables for cell type (i.e. beta or non-beta) and position (mantle or core). A χ
resultsThe χ CONCLUSIONS/
interpretationUsing a novel analysis pipeline, statistical evidence supports the existence of an M-C structure in human adult islets, irrespective of type 1 diabetes status. The methods presented in the current study offer potential applications in spatial biology, islet immunopathology, transplantation and organoid research, and developmental research.
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