In physiological conditions, beta cells constitute approximately 50–70% of the total endocrine cells, followed by alpha cells (20–40%), delta cells (<10%), and a few epsilon and PP cells ( Steiner et al., 2010) however these proportions vary from region to region (e.g., PP cells can reach 80% in the pancreatic head, whereas beta cells are <20% in the same region) or with disease stage ( Rahier et al., 1983 Steiner et al., 2010). The islets of Langerhans, which account for 1–4% of the total pancreatic volume, form the endocrine portion and contain several cell populations (secreting distinct proteins): alpha cells (glucagon), beta cells (insulin), delta cells (somatostatin), epsilon cells (ghrelin), and pancreatic polypeptide cells (PP) ( Dolenšek et al., 2015 Noguchi and Huising, 2019). The pancreas is mainly divided into exocrine and endocrine tissue. The standardization and implementation of these analysis tools is of critical importance to understand disease pathogenesis, and may be informative for the design of new therapies aimed at preserving beta cell function and halting the inflammation caused by the immune attack. Therefore, we present a tool and analysis pipeline that allows for the accurate characterization of the human pancreas, enabling the study of the anatomical and physiological changes underlying pancreatic diseases such as type 1 diabetes. In addition, we show that QuPath can identify immune cell populations in the exocrine tissue and islets of Langerhans, accurately localizing and quantifying immune infiltrates in the pancreas. We demonstrate that QuPath can be adequately used to analyze whole-slide images with the aim of identifying the islets of Langerhans and define their cellular composition as well as other basic morphological characteristics. Here, we described the use of QuPath-an open-source platform for image analysis-for the investigation of human pancreas samples. Nowadays, multiplex immunofluorescence protocols as well as sophisticated image analysis tools can be employed. In addition, the use of new imaging technologies has unraveled many mysteries of the human pancreas not merely in the presence of disease, but also in physiological conditions. Recently, human pancreas samples have become available through several biobanks worldwide, and this has opened numerous opportunities for scientific discovery.
However, intrinsic differences between animals and humans have made clinical translation very challenging. Access to human pancreas samples for research purposes has been historically limited, restricting pathological analyses to animal models. Type 1 diabetes is a chronic disease of the pancreas characterized by the loss of insulin-producing beta cells. 2German Center for Diabetes Research (DZD), Helmholtz Zentrum Munich, Munich, Germany.1Institute of Diabetes Research, Helmholtz Diabetes Center at Helmholtz Zentrum München, Munich, Germany.Apaolaza 1,2 †, Peristera-Ioanna Petropoulou 1,2 † and Teresa Rodriguez-Calvo 1,2*
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