Network Physiology is an emerging interdisciplinary field dedicated to uncovering the complexity of physiological interactions across diverse organ systems in health and disease. Submissions to this Research Topic should be framed within the context of Network Physiology.

The endocrine pancreas plays a central role in maintaining metabolic homeostasis. It serves as a paradigmatic example of a complex physiological regulatory system, operating across multiple organizational levels and timescales. Within the pancreas, endocrine cells are organized into micro-organs known as the islets of Langerhans. Among these, insulin-producing beta cells are the most prevalent, working alongside glucagon-secreting α-cells, somatostatin-secreting δ-cells, pancreatic polypeptide-producing PP cells, and other less frequent cell types to form the endocrine compartment.

Insulin synthesis and secretion in beta cells arise from intricate nonlinear intracellular mechanisms and are tightly regulated through interactions with neighboring beta cells and other endocrine cell types. These intercellular interactions occur on various timescales, including fast direct electrical coupling via gap junctions, and slower paracrine, autocrine, and juxtacrine signalling pathways. Proper islet function thus relies on the emergence of collective rhythmic activity, shaped by complex processes operating across hierarchical levels of biological organization.

However, when this delicate intercellular coordination is disrupted – due to genetic, metabolic, or environmental factors – it can lead to pathological desynchronization of hormonal output, impaired insulin release, and ultimately, the development of diabetic states. Understanding how these network-level failures arise, and how they differ across disease stages and phenotypes, is of central importance for advancing both diagnostic and therapeutic approaches for diabetes.

This growing recognition of islets as a dynamic, network-organized system has spurred the development of innovative and interdisciplinary approaches that integrate biological experimentation with computational modelling. Functional multicellular calcium imaging, network analysis, and spatially resolved multicellular models provide a unifying framework for exploring endocrine regulation from a systems-level perspective. These methods enable a deeper understanding of how cellular heterogeneity and connectivity contribute to coordinated islet behavior in both health and disease. Ultimately, we envision that such integrative frameworks in computational physiology will not only improve our ability to describe and interpret the complex organization of pancreatic islets under physiological and pathological conditions but will also help inform the design of targeted clinical interventions aimed at restoring normal endocrine function in diabetes.

The aim of this Research Topic is to highlight recent advances in our understanding of collective rhythmicity in pancreatic islets and how its disruption contributes to diabetes and related metabolic disorders. We are especially interested in interdisciplinary studies that address either intracellular signalling networks or intercellular communication among heterogeneous ensembles of endocrine and/or immune cells. Contributions that combine theoretical and experimental perspectives using tools from complexity science are particularly encouraged. We welcome submissions of original research articles as well as reviews.

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Network-Based Perspectives on Collective Rhythmicity and Dysfunction in the Endocrine Pancreas: From Physiology to Diabetes