Viruses are known to be associated with 20% of human cancers. Epstein Barr virus (EBV) in particular is the first virus associated with human cancers. Here, we computationally detect EBV and explore the effects of this virus across cancers by taking advantage of the fact that EBV microRNAs (miRNAs) and Epstein Barr virus small RNAs (EBERs) are expressed at all viral latencies. We identify and characterize two sub-populations of EBV positive tumors: those with high levels of EBV miRNA and EBERS expression and those with medium levels of expression. Based on principal component analysis (PCA) and hierarchical clustering of viral miRNAs across all samples we observe a pattern of expression for these EBV miRNAs which is correlated with both the tumor cell type (B cell versus epithelial cell) and with the overall levels of expression of these miRNAs. We further investigated the effect of the levels of EBV miRNAs with the overall survival of patients across cancers. Through Kaplan Meier survival analysis we observe a significant correlation with levels of EBV miRNAs and lower survival in adult AML patients. We also designed a machine learning model for risk assessment of EBV in association with adult AML and other clinical factors. Our next aim was to identify targets of EBV miRNAs, hence, we used a combination of previously known methodologies for miRNA target detection in addition to a multivariable regression approach to identify targets of these viral miRNAs in stomach cancer. Finally, we investigate the variations across EBV subtype specific EBNA3C gene which interacts with the host immune system. Preliminary data suggests potential regional variations plus higher pathogenicity of subtype 1 in comparison to subtype 2 EBV. Overall, these studies further our understanding of how EBV manipulates the tumor microenvironment across cancer subtypes.

No description available.

Functional vasodilation in arterioles is impaired with chronic ischemia. We sought to examine the impact of chronic ischemia and age on skeletal muscle resistance artery function. To examine the impact of chronic ischemia, the femoral artery was resected from young (2-3mo) and adult (6-7mo) mice and the profunda femoris artery diameter was measured at rest and following gracilis muscle contraction 14 days later using intravital microscopy. Functional vasodilation was significantly impaired in ischemic mice (14.4±4.6% vs. 137.8±14.3%, p<0.0001 n=8) and non-ischemic adult mice (103.0±9.4% vs. 137.8±14.3%, p=0.05 n=10). In order to analyze the cellular mechanisms of the impairment, a protocol was developed to apply pharmacological agents to the experimental preparation while maintaining tissue homeostasis. Endothelial and smooth muscle dependent vasodilation were impaired with ischemia, 39.6 ± 13.6% vs. 80.5 ± 11.4% and 43.0 ± 11.7% vs. 85.1 ± 10.5%, respectively. From this data, it can be supported that smooth muscle dysfunction is the reason for the observed impairment in arterial vasodilation.

To increase capacity for monitoring and surveillance of tick-borne diseases, publicly available tick distribution and climate change datasets are required to create accurate predictive distribution models. It is difficult, however, to assess model accuracy and utility when using incomplete datasets.  The more recent development of comprehensive tick databases for Europe and availability of climate change scenarios from multiple IPCC Assessment Reports allows for improved modeling efforts. Multiple tick datasets were combined and three climate change projections were compared by predicting current and future distributions of Ixodes ricinus ticks in Europe using the MaxEnt species distribution model. Overall, much of Europe contains suitable habitat for the Ixodes ricinus tick, both now and under future climate change projections.  Contraction of habitable areas is predicted to occur at lower latitudes and altitudes, while expansion is predicted to occur at higher altitudes in mountainous regions and the higher latitudes, primarily in northern Scandinavia.

<p>Regardless of their origin or pathology, many, if not all, diseases have long been regarded as complex. Yet, despite the progression in the understanding of complexity and the development of systems biology, the majority of biomedical research has been derived from qualitative principles. In comparison to the ethical, temporal and logistical limitations of human experimentation, <em>in vivo</em> animal models have served to provide a more advantageous means to elucidate the underlying disease mechanisms. However, given the additional limitations presented by such models, <em>in silico </em>models have emerged as an effective complement, and, in some cases, a replacement for <em>in vivo</em> experimentation. The <em>in silico </em>models presented in this thesis were developed using mathematical and computational methods to investigate the evolution of two complex, diverse diseases from a systems biology perspective: allergic asthma and cancer.</p> <p>We generated two novel <em>in silico</em> models of allergic asthma aimed at clarifying some dynamic aspects of allergic responses. Experimentally, we utilized an <em>in vivo</em> murine model of chronic exposure to the most pervasive aeroallergen worldwide, house dust mite (HDM), for up to 20 weeks, equivalent to at least 20 human years. Using a range of HDM concentrations, experimental data were collected to study local and systemic effects. The first model applied empirical mathematical techniques to establish equations for airway inflammation and HDM-specific immunoglobulins using an iterative approach of experimentation and validation. Using the equations generated, we showed that the model was able to accurately predict and simulate data. The model also demonstrated the non-linear relationship between HDM exposure and both airway inflammation and allergic sensitization and identified system thresholds.</p> <p>The second model used mechanistic mathematical techniques to investigate the trafficking of eosinophils as they migrated from bone marrow to the blood and, ultimately, to the lungs. Making use of a limited data set, the model determined the effect of individual processes on the system. We identified eosinophil production, survival and death as having the greatest impacts, while migration played a relatively minor role. Furthermore, the model was used to simulate knockout models and the use of antibodies <em>in silico</em>.</p> <p>In the context of cancer growth and metastasis, we developed a theoretical model demonstrating the spatio-temporal development of a tumour in two-dimensions. The model was encoded to create a computer graphic simulation program, which simulated the effects of various parameters on the size and shape of a tumour. Through simulations, we demonstrated the importance of the diffusion process in cancer growth and metastasis.</p> <p>Ultimately, we believe the greatest benefit of each <em>in silico</em> model is the ability to provide an understanding of each respective disease recognized as dynamic and formally complex, but predominantly studied in reductionist, static or un-integrated approaches.</p> / Doctor of Philosophy (Medical Science)

<p>Obstructive lung diseases limit airflow and gas exchange and have a major impact on a patient’s long-term health. Asthma and chronic obstructive pulmonary disease (COPD) are the most prevalent obstructive lung diseases and represent a major burden on healthcare systems worldwide. It is now accepted that the pathologies associated with these diseases are heterogeneous in nature, and as the function of the lung is determined by its three-dimensional structure, methods to volumetrically evaluate the lung are important tools in furthering the study of these pathologies.</p> <p>Three-dimensional imaging methodologies, such as computed tomography (CT) and single photon emission computed tomography (SPECT), are used clinically in the diagnosis of lung disease, but results are not commonly quantified. In addition, asthma and COPD develop slowly over time and diagnosis normally takes place after the underlying pathologies are well established. Experimental models in small animals, such as rats and mice, allow for the study of disease pathogenesis in a controlled setting and development of quantitative imaging practices for these models provides translational tools for relating results back to the clinic.</p> <p>In this thesis, CT densitometry and ventilation/perfusion (V/Q) SPECT are explored as methods to investigate models of asthma and COPD. CT densitometry is shown to be capable of quantifying allergic inflammation in an asthma model but is of less use in a model of COPD, predominantly due to the relative amounts of inflammation present. However, V/Q imaging is shown to be quite sensitive to the effects of cigarette smoke in a model of COPD and has been used to better understand how pathologies associated with COPD contribute to gas exchange limitation in the lung.</p> <p>The models, imaging techniques, and analysis methods described in this work provide insight into chronic obstructive lung disease and allow for future investigations into how pathologies effect gas exchange. Further, the characterization of the models described in this thesis allows for drug efficacy studies to be performed, both on established and novel treatments. Future research into asthma and COPD will benefit further from the use of threedimensional imaging methodologies because they provide volumetric information on structure and function and can act as a translational bridge between clinical disease and preclinical animal models.</p> / Doctor of Philosophy (Medical Science)

Diabetes is a major risk factor for the development of cataract [3,14,20,22]. In this thesis, we create a model that allows us to understand the incidence of one disease in the context of another; in particular, cataract in the presence of diabetes. The World Health Organization's Vision 2020 blindness-prevention initiative administers surgeries to remove cataracts, the leading cause of blindness worldwide [24]. One of the geographic areas most impacted by cataract-related blindness is Sub-Saharan Africa. In order to plan the number of surgeries to administer, the World Health Organization uses data on cataract prevalence. However, an estimation of the incidence of cataract is more useful than prevalence data for the purpose of resource planning. In 2012, Dray and Williams developed a method for estimating incidence based on prevalence data [5]. Incidence estimates can be further refined by considering associated risk factors such as diabetes. We therefore extend the Dray and Williams model to include diabetes prevalence when calculating cataract incidence estimates. We explore two possible approaches to our model construction, one a detailed extension, and the other, a simplification of that extension. We provide a discussion comparing the two approaches.

No description available.

<p>Food allergies are immune system-driven diseases that lead to reproducible adverse reactions which can be fatal. These severe systemic reactions are primary mediated by immunoglobulin E (IgE) that is derived from B cells which have been activated by T helper type 2 (Th2) cells. While much work has advanced the clinical and pharmacological management of patients with allergic diseases, much remains to be elucidated about how individuals initially acquire allergy. This Thesis details a mechanism linking initial gastrointestinal exposure to peanut (PN) allergen, to the generation of Th2 cells: PN allergen activates epithelial cell secretion of interleukin (IL)-33 and eosinophil degranulation of eosinophil peroxidase, which causes CD103+ dendritic cell (DC) activation and migration to mesenteric lymph nodes where DC OX40L engages naïve T cells to secrete IL-4 in an autocrine/paracrine manner to promote and consolidate Th2 cell differentiation. These events are followed by B cell activation and PN-specific IgE production, which sensitizes mast cells to be hypersensitive to PN re-exposure by causing immediate allergic reactions including anaphylaxis. This is later followed by eosinophilic inflammation that is partially mediated by innate lymphoid cells. As food allergy also serves as a unique model to better understand mechanisms of adaptive immunity, especially Th2 immunobiology, both basic science and clinical implications are discussed in this Thesis. Major themes include Th2 and disease heterogeneity, identification of ‘the original source of IL-4’, an unprecedented <em>in vivo </em>requirement for eosinophils in priming adaptive immune responses, and the need to weigh basic science findings against the human disease <em>in natura </em>litmus test. Looking forward, many questions remain to be answered in the field of food allergy research, but the findings of this Thesis may be one step towards the prevention, management or cure of a disease with growing public concern, potentially fatal consequences, and an unmet need in understanding its pathogenesis.</p> / Doctor of Philosophy (Medical Science)

Background & Aims: Despite advances in surgical care and chemotherapeutic regimens, the five-year survival rate for Stage IV Hepatoblastoma (HB), the predominant pediatric liver tumor, remains at 27%. YAP1 and β-Catenin co-activation occurs in 80% of children’s HB; however, a lack of conditional genetic models precludes exploration of tumor maintenance and therapeutic targets. Thus, the clinical need for a targeted therapy remains unmet. Given the predominance of YAP1 and β-catenin activation in children’s tumors, I sought to evaluate YAP1 as a therapeutic target in HB. Approach & Results: Herein, I engineered the first conditional murine model of HB using hydrodynamic injection to deliver transposon plasmids encoding inducible YAP1S127A, constitutive β-CateninDelN90, and a luciferase reporter to murine liver. Tumor regression was evaluated using in vivo bioluminescent imaging, and tumor landscape characterized using RNA sequencing, ATAC sequencing and DNA foot-printing. Here I show that YAP1 withdrawal in mice mediates >90% tumor regression with survival for 230+ days. Mechanistically, YAP1 withdrawal promotes apoptosis in a subset of tumor cells and in remaining cells induces a cell fate switch driving therapeutic differentiation of HB tumors into Ki-67 negative “hbHep cells.” hbHep cells have hepatocyte-like morphology and partially restored mature hepatocyte gene expression. YAP1 withdrawal drives formation of hbHeps by modulating liver differentiation transcription factor (TF) occupancy. Indeed, tumor-derived hbHeps, consistent with their reprogrammed transcriptional landscape, regain partial hepatocyte function and can rescue liver damage in mice. Conclusions: YAP1 withdrawal, without modulation of oncogenic β-Catenin, significantly regresses hepatoblastoma, providing the first in vivo data to support YAP1 as a therapeutic target for HB. Modulating YAP1 expression alone is sufficient to drive long-term regression in hepatoblastoma because it promotes cell death in a subset of tumor cells and modulates transcription factor occupancy to reverse the fate of residual tumor cells to mimic functional hepatocytes.