{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sethia N"],"funding":["NIDDK NIH HHS","Khalifa Bin Zayed Al Nahyan Foundation","Stephen and Barbara Slaggie Family","National Institutes of Health","J.W. Kieckhefer Foundation","National Science Foundation"],"pagination":["3453-3462"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10883307"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["40(7)"],"pubmed_abstract":["There is a critical need for sorting complex materials, such as pancreatic islets of Langerhans, exocrine acinar tissues, and embryoid bodies. These materials are cell clusters, which have highly heterogeneous physical properties (such as size, shape, morphology, and deformability). Selecting such materials on the basis of specific properties can improve clinical outcomes and help advance biomedical research. In this work, we focused on sorting one such complex material, human stem cell-derived β cell clusters (SC-β cell clusters), by size. For this purpose, we developed a microfluidic device in which an image detection system was coupled to an actuation mechanism based on traveling surface acoustic waves (TSAWs). SC-β cell clusters of varying size (∼100-500 μm in diameter) were passed thr"],"journal":["Langmuir : the ACS journal of surfaces and colloids"],"pubmed_title":["On Chip Sorting of Stem Cell-Derived β Cell Clusters Using Traveling Surface Acoustic Waves."],"pmcid":["PMC10883307"],"funding_grant_id":["ECCS-2025124","R01DK131209","EEC 1941543","R01 DK131209"],"pubmed_authors":["Finger EB","Bischof JC","Schornack AMR","Peterson QP","Etheridge ML","Khashim Z","Rao JS","Dutcher CS","Sethia N"],"additional_accession":[]},"is_claimable":false,"name":"On Chip Sorting of Stem Cell-Derived β Cell Clusters Using Traveling Surface Acoustic Waves.","description":"There is a critical need for sorting complex materials, such as pancreatic islets of Langerhans, exocrine acinar tissues, and embryoid bodies. These materials are cell clusters, which have highly heterogeneous physical properties (such as size, shape, morphology, and deformability). Selecting such materials on the basis of specific properties can improve clinical outcomes and help advance biomedical research. In this work, we focused on sorting one such complex material, human stem cell-derived β cell clusters (SC-β cell clusters), by size. For this purpose, we developed a microfluidic device in which an image detection system was coupled to an actuation mechanism based on traveling surface acoustic waves (TSAWs). SC-β cell clusters of varying size (∼100-500 μm in diameter) were passed thr","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Feb","modification":"2025-04-18T12:58:53.29Z","creation":"2025-04-06T22:27:08.258Z"},"accession":"S-EPMC10883307","cross_references":{"pubmed":["38318799"],"doi":["10.1021/acs.langmuir.3c02934"]}}