Investigating the Diabetic Brain: The Effects of Pioglitazone and Insulin on the Cellular Processes and Pathology of Alzheimer's Disease

Alzheimer’s disease (AD) is the sixth leading cause of death in the US. Some researchers refer to AD as “Type III Diabetes” because of reported glucose metabolism dysfunction. Preclinical studies suggest increasing insulin decreases AD pathology, although the mechanism remains unclear. To sensitize insulin signaling, this study activated Peroxisome Proliferator-Activated Receptor Gamma using intranasal co-administration of pioglitazone (PGZ) and insulin. This method targeted the site of action to reduce peripheral effects and to maximize impact in transgenic mice expressing AD pathology. Data from GC-MS fluxomics analysis suggested that PGZ+Insulin increased glucose metabolism in the brain. Immunohistochemistry with relevant antibodies was used to identify AD pathological markers in the subiculum, indicating that PGZ+Insulin decreased pathology compared to Insulin and Saline. This suggests that increasing glucose uptake in the brain alleviated AD pathology, further clarifying the role of insulin signaling in AD pathology.Gemstone

DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS

Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.