Translational Medical Research Commons^™

The Role Of Perivascular Fibrosis In Post-Stroke Glymphatic Impairment And Cerebral Amyloid Angiopathy, Matthew D. Howe

Dissertations & Theses (Open Access)

In healthy brain tissue, toxic amyloid-β (Aβ) proteins are transported by the pulsatile flow of cerebrospinal fluid (CSF) along perivascular drainage pathways. Ischemic stroke may disrupt this process, leading to a perivascular build-up of Aβ, termed cerebral amyloid angiopathy (CAA). I hypothesize that an abnormal pattern of extracellular matrix deposition within the vascular basement membrane, termed fibrosis, impairs Aβ drainage from the aged brain after stroke. I further hypothesize that inhibition of astrocytic transforming growth factor-β (TGF-β) signaling can reverse these phenotypes. Finally, I also hypothesize that serum biomarkers of perivascular fibrosis can be used to diagnose CAA following intracerebral …

Ischemic Stroke Damage Is Reduced By Inhibition Of Il-6 Signaling With Tocilizumab, Jacob Hudobenko

Dissertations & Theses (Open Access)

Introduction:

Stroke is the leading cause of serious long-term disability and is the 5^th leading cause of death causing approximately 130,000 deaths in the United States every year {1}. Stroke is also the 2^nd leading cause of death in American women {2}. Women are 33% more likely to require nursing home care then men, have a higher lifetime risk of stroke and are 13% less likely to receive thrombolytic (clot busting) treatment than men {2}. Interleukin 6 (IL-6) is a pro-inflammatory cytokine involved in the regulation of the immune system in multiple disease states such as rheumatoid …

Characterization Of Theranostic Peptides For Glioblastoma Multiforme, Aaron Mellesmoen

All NMU Master's Theses

Glioblastoma multiforme (GBM) is a type of primary CNS tumor in which viable treatment options do not exist. Standard of care including tumor resection, chemotherapy, and radiation does little to extend the 5-year survival expectancy past 5.1%. Herein, two small-peptide molecules with inherent antitumor activity, blood-brain barrier permeability, and capability for tumor-specific drug deliverance and intraoperative visualization (termed theranostic) were of focus. Confocal microscopy was employed to characterize in vitro specificity of chlorotoxin, a 4 kDa scorpion venom peptide, and rBSG, the recombinant 25 kDa non-glycosylated extracellular domain of extracellular matrix metalloproteinase inducer (EMMPRIN; Basigin) isoform …

Transcriptomics Of Learning, Pablo Iturralde

Theses

Learning is a basic and important component of behavior yet we have very little empirical information about the interaction between mechanisms of learning and evolution. In our work, we are testing hypotheses about the neurogenetic mechanisms through which animal learning abilities evolve. We are able to test this directly by using experimentally evolved populations of flies, which differ in learning ability. These populations were previously evolved within the lab by creating worlds with different patterns of change following theoretically predicted effects on which enhanced learning will evolve. How has evolution acted to modulate genes and gene expression in the brain …

Muc4 Based Immunotherapy For Pancreatic Cancer, Kasturi Banerjee

Theses & Dissertations

Pancreatic Cancer (PC) is a lethal disease claiming approximately 45000 lives in the US in 2018, and it establishes an elaborate immunosuppressive tumor microenvironment that aids in disease pathogenesis. Immunotherapy has emerged as a strategy to target tumor cells by reprogramming patient’s immune system. Challenges present in PC immunotherapy are: i) identifying a tumor-associated antigen that could be targeted, ii) identifying adjuvants that could efficiently deliver antigens, iii) eliciting robust anti-tumor responses and iv) overcoming peripheral tolerance and immunosuppression elicited by the tumor.

Firstly, we detected circulating autoantibodies to MUC4 present in PC patients and observed that IgM autoantibodies to …

Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones

Theses and Dissertations--Computer Science

In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …