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dc.contributor.authorPapas, Klearchos K.
dc.contributor.authorBellin, Melena D.
dc.contributor.authorSutherland, David E. R.
dc.contributor.authorSuszynski, Thomas M.
dc.contributor.authorKitzmann, Jennifer P.
dc.contributor.authorAvgoustiniatos, Efstathios S.
dc.contributor.authorGruessner, Angelika C.
dc.contributor.authorMueller, Kathryn R.
dc.contributor.authorBeilman, Gregory J.
dc.contributor.authorBalamurugan, Appakalai N.
dc.contributor.authorLoganathan, Gopalakrishnan
dc.contributor.authorColton, Clark K.
dc.contributor.authorKoulmanda, Maria
dc.contributor.authorWeir, Gordon C.
dc.contributor.authorWilhelm, Josh J.
dc.contributor.authorQian, Dajun
dc.contributor.authorNiland, Joyce C.
dc.contributor.authorHering, Bernhard J.
dc.date.accessioned2015-08-20T18:51:27Z
dc.date.available2015-08-20T18:51:27Z
dc.date.issued2015-08
dc.date.submitted2015-07
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1721.1/98167
dc.description.abstractBackground Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR) in predicting clinical islet autotransplant (IAT) insulin independence (II). IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding factors such as immune rejection and immunosuppressant toxicity. Methods Membrane integrity staining (FDA/PI), OCR normalized to DNA (OCR/DNA), islet equivalent (IE) and OCR (viable IE) normalized to recipient body weight (IE dose and OCR dose), and OCR/DNA normalized to islet size index (ISI) were used to characterize autoislet preparations (n = 35). Correlation between pre-IAT islet product characteristics and II was determined using receiver operating characteristic analysis. Results Preparations that resulted in II had significantly higher OCR dose and IE dose (p<0.001). These islet characterization methods were highly correlated with II at 6–12 months post-IAT (area-under-the-curve (AUC) = 0.94 for IE dose and 0.96 for OCR dose). FDA/PI (AUC = 0.49) and OCR/DNA (AUC = 0.58) did not correlate with II. OCR/DNA/ISI may have some utility in predicting outcome (AUC = 0.72). Conclusions Commonly used assays to determine whether a clinical islet preparation is of high quality prior to transplantation are greatly lacking in sensitivity and specificity. While IE dose is highly predictive, it does not take into account islet cell quality. OCR dose, which takes into consideration both islet cell quality and quantity, may enable a more accurate and prospective evaluation of clinical islet preparations.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Clinical Islet Transplantation Consortium Grant)en_US
dc.description.sponsorshipIscel Cell Resources (Grant)en_US
dc.description.sponsorshipCarol Olson Memorial Diabetes Research Funden_US
dc.description.sponsorshipSchott Foundationen_US
dc.description.sponsorshipIacocca Foundationen_US
dc.description.sponsorshipNational Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (K23 DK084315)en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0134428en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePublic Library of Scienceen_US
dc.titleIslet Oxygen Consumption Rate (OCR) Dose Predicts Insulin Independence in Clinical Islet Autotransplantationen_US
dc.typeArticleen_US
dc.identifier.citationPapas, Klearchos K., Melena D. Bellin, David E. R. Sutherland, Thomas M. Suszynski, Jennifer P. Kitzmann, Efstathios S. Avgoustiniatos, Angelika C. Gruessner, et al. “Islet Oxygen Consumption Rate (OCR) Dose Predicts Insulin Independence in Clinical Islet Autotransplantation.” Edited by Matthias G von Herrath. PLoS ONE 10, no. 8 (August 10, 2015): e0134428.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.contributor.mitauthorColton, Clark K.en_US
dc.relation.journalPLOS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPapas, Klearchos K.; Bellin, Melena D.; Sutherland, David E. R.; Suszynski, Thomas M.; Kitzmann, Jennifer P.; Avgoustiniatos, Efstathios S.; Gruessner, Angelika C.; Mueller, Kathryn R.; Beilman, Gregory J.; Balamurugan, Appakalai N.; Loganathan, Gopalakrishnan; Colton, Clark K.; Koulmanda, Maria; Weir, Gordon C.; Wilhelm, Josh J.; Qian, Dajun; Niland, Joyce C.; Hering, Bernhard J.en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-8777-9632
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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