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Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells.

ABSTRACT: Pancreatic β cells secrete the hormone insulin into the bloodstream and are critical in the control of blood glucose concentrations. β cells are clustered in the micro-organs of the islets of Langerhans, which have a rich capillary network. Recent work has highlighted the intimate spatial connections between β cells and these capillaries, which lead to the targeting of insulin secretion to the region where the β cells contact the capillary basement membrane. In addition, β cells orientate with respect to the capillary contact point and many proteins are differentially distributed at the capillary interface compared with the rest of the cell. Here, we set out to develop an automated image analysis approach to identify individual β cells within intact islets and to determine if the distribution of insulin across the cells was polarised. Our results show that a U-Net machine learning algorithm correctly identified β cells and their orientation with respect to the capillaries. Using this information, we then quantified insulin distribution across the β cells to show enrichment at the capillary interface. We conclude that machine learning is a useful analytical tool to interrogate large image datasets and analyse sub-cellular organisation.

SUBMITTER: Cottle L

PROVIDER: S-EPMC8229564 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Effects on insulin release, cyclic AMP content and protein phosphorylation of agents modifying cyclic AMP levels have been tested in intact rat islets of Langerhans. Insulin release induced by glucose was potentiated by dibutyryl cyclic AMP, glucagon, cholera toxin and 3-isobutyl-1-methylxanthine (IBMX); the calmodulin antagonist trifluoperazine reversed these potentiatory effects. Inhibition by trifluoperazine of IBMX-potentiated release was, however, confined to concentrations of IBMX below 50 microM; higher concentrations, up to 1 mM, were resistant to inhibition by trifluoperazine. IBMX-potentiated insulin release was also inhibited by 2-deoxyadenosine, an inhibitor of adenylate cyclase. In the absence of glucose, IBMX at concentrations up to 1 mM did not stimulate insulin release and in the presence of 3.3 mM-glucose IBMX was effective only at a concentration of 1 mM; under the latter conditions trifluoperazine again did not inhibit insulin secretion. The maximum effect on insulin release was achieved with 25 microM-IBMX. Islet [cyclic AMP] was increased by IBMX, with the maximum rise occurring with 100 microM-IBMX. The increase in [cyclic AMP] elicited by IBMX was more rapid than that induced by cholera toxin. Trifluoperazine did not significantly affect islet cyclic AMP levels under any of the conditions tested. When islets were incubated with [32P]Pi, radioactivity was incorporated into islet ATP predominantly in the gamma-position. The rate of equilibration of label was dependent on medium Pi and glucose concentration and at optimal concentrations of these 100% equilibration of internal [32P]ATP with external [32P]Pi required a period of 3h. Radioactivity was incorporated into islet protein and, in response to an increase in islet [cyclic AMP], the major effect was on a protein of Mr 15 000 on sodium dodecyl sulphate/polyacrylamide gels. The extent of phosphorylation of the Mr-15 000 protein was correlated with the level of cyclic AMP: phosphorylation in response to IBMX was inhibited by 2-deoxyadenosine but not by trifluoperazine. Fractionation of islets suggested that the Mr-15 000 protein was of nuclear origin: the protein co-migrated with histone H3 on acetic acid/urea/Triton gels. In the islet cytosol a number of proteins were phosphorylated in response to elevation of islet [cyclic AMP]: the major species had Mr values of 18 000, 25 000, 34 000, 38 000 and 48 000. Culture of islets with IBMX increased the rate of [3H]-thymidine incorporation.(ABSTRACT TRUNCATED AT 400 WORDS)

Dataset Information

Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells.

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