A Multiparametric Assessment of Human Islets Predicts Transplant Outcomes in Diabetic Mice.

Prior to transplantation into individuals with type 1 diabetes, in vitro assays are used to evaluate the quality, function and survival of isolated human islets. In addition to the assessments of these parameters in islet, they can be evaluated by multiparametric morphological scoring (0-10 points) and grading (A, B, C, D, and F) based on islet characteristics (shape, border, integrity, single cells, and diameter). However, correlation between the multiparametric assessment and transplantation outcome has not been fully elucidated. In this study, 55 human islet isolations were scored using this multiparametric assessment. The results were correlated with outcomes after transplantation into immunodeficient diabetic mice. In addition, the multiparametric assessment was compared with oxygen consumption rate of isolated islets as a potential prediction factor for successful transplantations. All islet batches were assessed and found to score: 9 points (n = 18, Grade A), 8 points (n = 19, Grade B), and 7 points (n = 18, Grade B). Islets that scored 9 (Grade A), scored 8 (Grade B) and scored 7 (Grade B) were transplanted into NOD/SCID mice and reversed diabetes in 81.2%, 59.4%, and 33.3% of animals, respectively (P < 0.0001). Islet scoring and grading correlated well with glycemic control post-transplantation (P < 0.0001) and reversal rate of diabetes (P < 0.05). Notably, islet scoring and grading showed stronger correlation with transplantation outcome compared to oxygen consumption rate. Taken together, a multiparametric assessment of isolated human islets was highly predictive of transplantation outcome in diabetic mice.

Quantitative assessment of ß-cell apoptosis and cell composition of isolated, undisrupted human islets by laser scanning cytometry.

BACKGROUND: Assays for assessing human islet cell quality, which provide results before transplantation, would be beneficial to improve the outcomes for islet transplantation therapy. Parameters such as percent ß-cell apoptosis and cell composition are found to vary markedly between different islet preparations and may serve as markers of islet quality. We have developed fluorescence-based assays using laser scanning cytometry for assessing ß-cell apoptosis and islet cell composition on serial sections of intact isolated islets. METHODS: Isolated human islets were fixed in formalin and embedded in paraffin. Serial sections were immunostained for the pancreatic hormones and acinar and ductal cell markers. DNA fragmentation was used to label apoptotic cells. Stained cells were quantified using an iCys laser scanning cytometer. RESULTS: Islet preparations from 102 human pancreatic islet isolations were analyzed. For the whole set of islet preparations, we found a mean islet cell composition of 54.5%±1.2% insulin-positive, 33.9%±1.2% glucagon, 12.1%±0.7% somatostatin, and 1.5%±0.2% pancreatic polypeptide-positive cells. The apoptotic ß cells were 2.85%±0.4% with a range of 0.27% to 18.3%. The percentage of apoptotic ß cells correlated well (P<0.0001, n=59) with results obtained in vivo by transplantation of the corresponding islets in diabetic NODscid mice. CONCLUSIONS: The analysis of whole, nondissociated islets for cell composition and ß-cell apoptosis using laser scanning cytometry gives reliable and reproducible results and could be performed both before islet transplantation and on preserved cell blocks at any time in future. Thus, they can be a powerful tool for islet quality assessment.

PFA: program for the quantitative assessment of cell metabolism by spectral data analysis.

Assessment of mitochondrial oxidative metabolism has wide-ranging importance, from pharmacokinetic analysis to studies in cell viability and apoptosis. Here we present the Perfusion File Analyzer (PFA) application for the real-time analysis of spectral data to measure cytochrome c reduction, cytochrome a3 reduction, and other parameters important to cellular metabolism, which are collected during tissue perfusion experiments. Our current efforts are focused on quantitating changes in mitochondrial function by normalizing baseline drift of spectral data while addressing two major challenges: (1) a lack of real-time feedback from the system when aiming is compromised, and (2) an inability to adjust calculated data in the event of spectral shift. PFA has been developed to address these issues, and is currently used for quality assessment of human islets prior to clinical transplantation.