Extended survival versus accelerated rejection of nonhuman primate islet allografts: Effect of mesenchymal stem cell source and timing.

Mesenchymal stem cells (MSC) have been shown to be immunomodulatory, tissue regenerative, and graft promoting; however, several questions remain with regard to ideal MSC source and timing of administration. In this study, we utilized a rigorous preclinical model of allogeneic islet cell transplantation, incorporating reduced immune suppression and near to complete mismatch of major histocompatibility antigens between the diabetic cynomolgus monkey recipient and the islet donor, to evaluate both the graft promoting impact of MSC source, that is, derived from the islet recipient, the islet donor or an unrelated third party as well as the impact of timing. Co-transplant of MSC and islets on post-operative day 0, followed by additional IV MSC infusions in the first posttransplant month, resulted in prolongation of rejection free and overall islet survival and superior metabolic control for animals treated with recipient as compared to donor or third-party MSC. Immunological analyses demonstrated that infusion of MSC from either source did not prevent alloantibody formation to the islet or MSC donor; however, treatment with recipient MSC resulted in significant downregulation of memory T cells, decreased anti-donor T cell proliferation, and a trend toward increased Tregulatory:Tconventional ratios.

Using Hidden Markov Models to Determine Changes in Subject Data over Time, Studying the Immunoregulatory effect of Mesenchymal Stem Cells.

A novel application of Hidden Markov Models is used to help research intended to test the immunuregulatory effects of mesenchymal stem cells in a cynomolgus monkey model of islet transplantation. The Hidden Markov Model, an unsupervised learning data mining technique, is used to automatically determine the postoperative day (POD) corresponding to a decrease of graft function, a possible sign of transplant rejection, on nonhuman primates after isolated islet cell transplant. Currently, decrease of graft function is being determined solely on experts' judgment. Further, information gathered from the evaluation of construted Hidden Markov Models is used as part of a clustering method to aggregate the nonhuman subjects into groups or clusters with the objective of finding similarities that could potentially help predict the health outcome of subjects undergoing postoperative care. Results on expert labeled data show the HMM to be accurate 60% of the time. Clusters based on the HMMs further suggest a possible correspondence between donor haplotypes matching and loss of function outcomes.