02570nas a2200433   4500000000100000000000100001008004100002260001200043653003000055653001900085653001400104653001200118653001100130653002400141653001200165653002500177653003900202653002300241653002600264653001600290653001300306653004100319653001800360653001800378653002200396100002100418700002100439700002000460700002400480700001900504700002100523700002300544700001700567245012500584300001300709490000600722520139400728022001402122       2020                            d  c2020-0310aDiabetes Mellitus, Type 210aDrug Discovery10aExenatide10aGlucose10aHumans10aHypoglycemic Agents10aInsulin10aIslets of Langerhans10aMicrofluidic Analytical Techniques10aModels, Biological10aTissue Array Analysis10aTolbutamide10aDiabetes10aglucose-stimulated insulin secretion10ahanging-drops10aorgan on chip10apancreatic islets1 aPatrick M. Misun1 aBurçak Yesildag1 aFelix Forschler1 aAparna Neelakandhan1 aNassim Rousset1 aAdelinn Biernath1 aAndreas Hierlemann1 aOlivier Frey00aIn Vitro Platform for Studying Human Insulin Release Dynamics of Single Pancreatic Islet Microtissues at High Resolution  ae19002910 v43 aInsulin is released from pancreatic islets in a biphasic and pulsatile manner in response to elevated glucose levels. This highly dynamic insulin release can be studied in vitro with islet perifusion assays. Herein, a novel platform to perform glucose-stimulated insulin secretion (GSIS) assays with single islets is presented for studying the dynamics of insulin release at high temporal resolution. A standardized human islet model is developed and a microfluidic hanging-drop-based perifusion system is engineered, which facilitates rapid glucose switching, minimal sample dilution, low analyte dispersion, and short sampling intervals. Human islet microtissues feature robust and long-term glucose responsiveness and demonstrate reproducible dynamic GSIS with a prominent first phase and a sustained, pulsatile second phase. Perifusion of single islet microtissues produces a higher peak secretion rate, higher secretion during the first and second phases of insulin release, as well as more defined pulsations during the second phase in comparison to perifusion of pooled islets. The developed platform enables to study compound effects on both phases of insulin secretion as shown with two classes of insulin secretagogs. It provides a new tool for studying physiologically relevant dynamic insulin secretion at comparably low sample-to-sample variation and high temporal resolution.  a2366-7478