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Publications (2)4 Total impact

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    Article: Antibody-based proteomics for discovery and exploration of proteins expressed in pancreatic islets.
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    ABSTRACT: Abnormal glucose tolerance and deviant blood glucose levels are late stage clinical parameters that signify diabetes mellitus. To be able to diagnose the disease at an earlier stage and develop new tools for beta cell imaging, new molecular markers are needed. In the present study, five proteins highly expressed in pancreatic islets with no expression in the surrounding exocrine glandular cells of pancreas, and one protein with the opposite expression pattern, were identified by searches in the Human Protein Atlas (www.proteinatlas.org). The proteins were analyzed immunohistochemically on a specially designed tissue microarray, containing isolated human islets and pancreatic tissues with different characteristics, and compared to the expression of previously known markers of endocrine and exocrine pancreatic cells. Of the five novel endocrine markers, tetraspanin-7 was identified as a membrane-bound protein with exclusive positivity in islet cells. Also beta-2-microglobulin and ubiquitin carboxyl-terminal hydrolase isozyme L1 were expressed in a majority of islet cells, whereas sad1/unc-84 domain-containing protein 1 and beta-1,3-glucuronyltransferase 1 were positive in a smaller subset of islet cells. The potential exocrine marker galectin-2 was expressed in both exocrine acinary cells and pancreatic ductal cells, with no or low positivity in islet cells. In conclusion, antibody-based proteomics and specially designed tissue microarrays enable identification and exploration of novel proteins with differential expression in pancreatic islets. Here we describe 5 candidate proteins for further investigation of their physiological role and potential involvement in the pathogenesis of diabetes. One of these proteins, tetraspanin-7, is expressed on the cell membrane and could thus be a potential candidate for future development of tracers for beta cell imaging.
    Discovery medicine 06/2010; 9(49):565-78.
  • Article: Refinement of the automated method for human islet isolation and presentation of a closed system for in vitro islet culture.
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    ABSTRACT: The procedure of human islet isolation needs further optimization and standardization. Here, we describe techniques to enhance enzymatic digestion and minimize mechanical forces during the digestion process. The isolation protocol has also been modified to meet current GMP (cGMP) standards. Moreover, the impact of donor- and process-related factors was correlated to the use of islets for clinical transplantation. One hundred twelve standardized consecutive islet isolations were evaluated. Metyltioninklorid and indermil (topical tissue adhesive) were applied to detect leakage of collagenase injected and to repair the damaged pancreatic glands. The effects of dye and glue were evaluated in terms of islet yield, islet function using the perifusion assay, and success rate of the isolation. To analyze key factors for successful isolations, both univariate and multivariate regression analysis were performed. Both Metyltioninklorid and Indermil were effective to prevent leakage of enzyme solutions from the pancreatic glands. Both islet yield and success rate were higher when these tools were applied (4,516.1+/-543.0 vs. 3,447.7+/-323.5, P=0.02; 50.0% vs. 21.3%, P=0.02, respectively). No adverse effects on islet function or collagenase activity were observed. Multivariate regression analysis identified the maximal recorded amylase >100 U/L (P=0.026), BMI (P=0.03), and the use of catecholamine (P=0.04) as crucial donor-related factors. In addition, cold ischemia time (P=0.005), the dissection procedure using whole glands with duodenum (P=0.02), and the local procurement team (P=0.03) were identified as crucial isolation-related variables. A standardized technique of islet isolation is presented applying novel means to improve enzymatic digestion and to meet cGMP standards.
    Transplantation 11/2004; 78(9):1367-75. · 4.00 Impact Factor