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Skip to Search Results- 1Ametaj, Burim (Agricultural, Food and Nutritional Science)
- 1Davis, Faith (School of Public Health)
- 1Dixon, Roger A (Psychology)
- 1Dr. Christopher Power, Department of Neurology and Department of Psychiatry
- 1Dr. Glen B. Baker, Department of Psychiatry
- 1Le, Chris (Laboratory Medicine and Pathology)
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A Study of Potential Plasma Biomarkers of Disease Conversion and Progression in Multiple Sclerosis
DownloadFall 2020
Multiple sclerosis (MS) is a complex and heterogeneous disease of the central nervous system (CNS) characterized by leukocyte infiltration, myelin damage, local gliosis, and axonal injury. Relapsing-remitting MS (RRMS) is the most common disease course. Although the pathogenesis remains unclear,...
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Blood and Urinary Metabotyping Reveals Potential Predictive Biomarkers for Identifying Dairy Cows at Risk of Subclinical Mastitis During the Dry-Off Period
DownloadFall 2021
Subclinical mastitis (SCM) remains one of the most important infectious diseases of dairy cows as it is associated with considerable losses in milk production and financial revenue. Currently, most SCM research and practices focus on diagnosing this intramammary infection (IMI) by counting...
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Characterization of Urinary Arsenic Metabolites for Use as Biomarkers of Susceptibility to Arsenic Toxicity
DownloadSpring 2021
Arsenic is naturally occurring in the environment, and can be found in rocks, soil, water, and air. One main route of human exposure to arsenic is through drinking water from groundwater sources. Chronic exposure to arsenic is associated with cardiovascular, neurological, skin, and cancer-...
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CNS Tumours: Exploring Barriers to Registration and Feasibility of Extracting Molecular Characteristics
DownloadFall 2018
Two concerns regarding the collection of data for brain and other central nervous system (CNS) tumours in Canada are under-reporting of non-malignant tumours and the need for improved reporting of clinically relevant molecular information. The first part of our study, addressing under-reporting,...
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Data-Driven Approaches to Modeling Heterogeneity and Variability Across Asymptomatic Brain and Cognitive Aging, Mild Cognitive Impairment, and Alzheimer’s disease
DownloadSpring 2024
Objective We apply data-driven approaches to identify predictors of heterogeneous trajectories across normal aging, Mild Cognitive Impairment (MCI), and Alzheimer’s disease (AD). In Study 1, we investigated predictors of left and right hippocampal (HC) volume trajectory classes. In Study 2, we...