Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells
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 connection...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Metabolites |
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| Online Access: | https://www.mdpi.com/2218-1989/11/6/363 |
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| author | Louise Cottle Ian Gilroy Kylie Deng Thomas Loudovaris Helen E. Thomas Anthony J. Gill Jaswinder S. Samra Melkam A. Kebede Jinman Kim Peter Thorn |
| author_facet | Louise Cottle Ian Gilroy Kylie Deng Thomas Loudovaris Helen E. Thomas Anthony J. Gill Jaswinder S. Samra Melkam A. Kebede Jinman Kim Peter Thorn |
| author_sort | Louise Cottle |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T10:37:57Z |
| format | Article |
| id | doaj.art-4b694be37f45486b8bb8ca0d57b18f07 |
| institution | Directory Open Access Journal |
| issn | 2218-1989 |
| language | English |
| last_indexed | 2024-03-10T10:37:57Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj.art-4b694be37f45486b8bb8ca0d57b18f072023-11-21T23:08:50ZengMDPI AGMetabolites2218-19892021-06-0111636310.3390/metabo11060363Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β CellsLouise Cottle0Ian Gilroy1Kylie Deng2Thomas Loudovaris3Helen E. Thomas4Anthony J. Gill5Jaswinder S. Samra6Melkam A. Kebede7Jinman Kim8Peter Thorn9Charles Perkins Centre, School of Medical Sciences, University of Sydney, Camperdown 2006, AustraliaSchool of Computer Science, University of Sydney, Camperdown 2006, AustraliaCharles Perkins Centre, School of Medical Sciences, University of Sydney, Camperdown 2006, AustraliaSt Vincent’s Institute, Fitzroy 3065, AustraliaSt Vincent’s Institute, Fitzroy 3065, AustraliaNorthern Clinical School, University of Sydney, St Leonards 2065, AustraliaNorthern Clinical School, University of Sydney, St Leonards 2065, AustraliaCharles Perkins Centre, School of Medical Sciences, University of Sydney, Camperdown 2006, AustraliaSchool of Computer Science, University of Sydney, Camperdown 2006, AustraliaCharles Perkins Centre, School of Medical Sciences, University of Sydney, Camperdown 2006, AustraliaPancreatic 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.https://www.mdpi.com/2218-1989/11/6/363insulinbeta cellhumanisletpolarisationmachine learning |
| spellingShingle | Louise Cottle Ian Gilroy Kylie Deng Thomas Loudovaris Helen E. Thomas Anthony J. Gill Jaswinder S. Samra Melkam A. Kebede Jinman Kim Peter Thorn Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells Metabolites insulin beta cell human islet polarisation machine learning |
| title | Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells |
| title_full | Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells |
| title_fullStr | Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells |
| title_full_unstemmed | Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells |
| title_short | Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells |
| title_sort | machine learning algorithms applied to intact islets of langerhans demonstrate significantly enhanced insulin staining at the capillary interface of human pancreatic β cells |
| topic | insulin beta cell human islet polarisation machine learning |
| url | https://www.mdpi.com/2218-1989/11/6/363 |
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