The Banner University Medical Center's (BUMC) renal transplant program relies on the LifePort Kidney Transporter to optimize marginal kidney organs via hypothermic machine perfusion (HMP) prior to transplantation. Hemodynamic parameters produced by the device followed over the duration of support, combined with clinical experience, guide decisions in determining the acceptability of a donor kidney for implantation. Thus far, statistical evidence supporting ideal parameters remain undefined. The purpose of this study is to create a logistic model that will ascertain the post-implant sustainability of LifePort® supported kidneys and predict clinical outcomes. My hypothesis is that the statistical models constructed based on retrospective LifePort® parameters and clinical outcome data will successfully predict donor organ vascular health for transplantation and the optimal support duration. A successful model will contribute to increased efficiencies in the kidney transplant process as well as improved patient outcomes. An overview of the institution’s success was weighed using a survival analysis, with delayed graft function (DGF) as the endpoint. A logistic regression model and forecast model were built to predict the outcome for rejecting or accepting the organ for transplant, as well as to predict the hemodynamic parameters hours after the start of infusion. Results concluded a flow greater than 80 mL/min had a 90% probability of transplantation. The forecast model was capable of predicting flow for up to five hours. The calculated flow was in a 10 mL/min range of the actual flow, when up to one hour parameters were entered into the model. The study concluded practicality in the clinical setting, in kidney transplantation.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-08-25T20:54:16Z No. of bitstreams: 1 MalekChouchane_TESE.pdf: 3043835 bytes, checksum: b90ef34a2d4072ef5abda48d216aebb4 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-08-26T21:40:31Z (GMT) No. of bitstreams: 1 MalekChouchane_TESE.pdf: 3043835 bytes, checksum: b90ef34a2d4072ef5abda48d216aebb4 (MD5) / Made available in DSpace on 2016-08-26T21:40:31Z (GMT). No. of bitstreams: 1 MalekChouchane_TESE.pdf: 3043835 bytes, checksum: b90ef34a2d4072ef5abda48d216aebb4 (MD5) Previous issue date: 2016-02-29 / Recently, the field of cellular reprogramming has been revolutionized by works showing the potential to directly lineage-reprogram somatic cells into neurons upon overexpression of specific transcription factors. This technique offers a promising strategy to study the molecular mechanisms of neuronal specification, identify potential therapeutic targets for neurological diseases and eventually repair the central nervous system damaged by neurological conditions. Notably, studies with cortical astroglia revealed the high potential of these cells to reprogram into neurons using a single neuronal transcription factor. However, it remains unknown whether astroglia isolated from different regions of the central nervous system have the same neurogenic potential and generate induced neurons (iN) with similar phenotypes. Similarly, little is known about the fate that iNs could adopt after transplantation in the brain of host animals. In this study we compare the potential to reprogram astroglial cells isolated from the postnatal cerebral cortex and cerebellum into iNs both in vitro and in vivo using the proneural transcription factors Neurogenin-2 (Neurog2) and Achaete scute homolog-1 (Ascl1). Our results indicate cerebellar astroglia can be reprogrammed into induced neurons (iNs) with similar efficiencies to cerebral cortex astroglia. Notably however, while iNs in vitro adopt fates reminiscent of cortical or cerebellar neurons depending on the astroglial population used for reprogramming, in situ, after transplantation in the postnatal and adult mouse brain, iNs adopt fates compatible with the region of integration. Thus, our data suggest that the origin of the astroglial population used for lineage-reprogramming affects the fate of iNs in vitro, but this imprinting can be overridden by environmental cues after grafting.