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Automated High-Throughput, High-Content 3D Imaging of Intact Pancreatic Islets

dc.contributor.authorSexton, Jonathan
dc.contributor.authorMcCarty, Sean
dc.contributor.authorClasby, Martin
dc.coverage.spatialUnited States
dc.date.accessioned2024-10-28T18:02:49Z
dc.date.available2024-10-28T18:02:49Z
dc.date.issued2023-10-01
dc.identifier.issn2472-5552
dc.identifier.issn2472-5560
dc.identifier.urihttps://www.ncbi.nlm.nih.gov/pubmed/37527729
dc.identifier.urihttps://hdl.handle.net/2027.42/195368en
dc.description.abstractDiabetes poses a global health crisis affecting individuals across age groups and backgrounds, with a prevalence estimate of 700 million people worldwide by 2045. Current therapeutic strategies primarily rely on insulin therapy or hypoglycemic agents, which fail to address the root cause of the disease - the loss of pancreatic insulin-producing beta-cells. Therefore, bioassays that recapitulate intact islets are needed to enable drug discovery for beta-cell replenishment, protection from beta-cell loss, and islet-cell interactions. Standard cancer insulinoma beta-cell lines MIN6 and INS-1 have been used to interrogate beta-cell metabolic pathways and function but are not suitable for studying proliferative effects. Screening using primary human/rodent intact islets offers a higher level of physiological relevance to enhance diabetes drug discovery and development. However, the 3-dimensionality of intact islets have presented challenges in developing robust, high-throughput assays to detect beta-cell proliferative effects. Established methods rely on either dissociated islet cells plated in 2D monolayer cultures for imaging or reconstituted pseudo-islets formed in round bottom plates to achieve homogeneity. These approaches have significant limitations due to the islet cell dispersion process. To address these limitations, we have developed a robust, intact ex vivo pancreatic islet bioassay in 384-well format that is capable of detecting diabetes-relevant endpoints including beta-cell proliferation, chemoprotection, and islet spatial morphometrics.
dc.format.mediumPrint-Electronic
dc.languageeng
dc.publisherElsevier
dc.rightsLicence for published version: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectdrug discovery
dc.subjecttype-II diabetes
dc.titleAutomated High-Throughput, High-Content 3D Imaging of Intact Pancreatic Islets
dc.typeArticle
dc.identifier.pmid37527729
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/195368/2/1-s2.0-S2472555223000527-main.pdf
dc.identifier.doi10.1016/j.slasd.2023.07.003
dc.identifier.doihttps://dx.doi.org/10.7302/24563
dc.identifier.sourceSLAS Discovery
dc.description.versionAccepted version
dc.date.updated2024-10-28T18:02:47Z
dc.identifier.orcid0000-0002-9244-5888
dc.identifier.volume28
dc.identifier.issue7
dc.identifier.startpage316
dc.identifier.endpage324
dc.identifier.name-orcidSexton, Jonathan; 0000-0002-9244-5888
dc.identifier.name-orcidMcCarty, Sean
dc.identifier.name-orcidClasby, Martin
dc.working.doi10.7302/24563en
dc.owningcollnameInternal Medicine, Department of


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Licence for published version: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
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