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Description
Several debilitating neurological disorders, such as Alzheimer's disease, stroke, and spinal cord injury, are characterized by the damage or loss of neuronal cell types in the central nervous system (CNS). Human neural progenitor cells (hNPCs) derived from human pluripotent stem cells (hPSCs) can proliferate extensively and differentiate into the various

Several debilitating neurological disorders, such as Alzheimer's disease, stroke, and spinal cord injury, are characterized by the damage or loss of neuronal cell types in the central nervous system (CNS). Human neural progenitor cells (hNPCs) derived from human pluripotent stem cells (hPSCs) can proliferate extensively and differentiate into the various neuronal subtypes and supporting cells that comprise the CNS. As such, hNPCs have tremendous potential for disease modeling, drug screening, and regenerative medicine applications. However, the use hNPCs for the study and treatment of neurological diseases requires the development of defined, robust, and scalable methods for their expansion and neuronal differentiation. To that end a rational design process was used to develop a vitronectin-derived peptide (VDP)-based substrate to support the growth and neuronal differentiation of hNPCs in conventional two-dimensional (2-D) culture and large-scale microcarrier (MC)-based suspension culture. Compared to hNPCs cultured on ECMP-based substrates, hNPCs grown on VDP-coated surfaces displayed similar morphologies, growth rates, and high expression levels of hNPC multipotency markers. Furthermore, VDP surfaces supported the directed differentiation of hNPCs to neurons at similar levels to cells differentiated on ECMP substrates. Here it has been demonstrated that VDP is a robust growth and differentiation matrix, as demonstrated by its ability to support the expansions and neuronal differentiation of hNPCs derived from three hESC (H9, HUES9, and HSF4) and one hiPSC (RiPSC) cell lines. Finally, it has been shown that VDP allows for the expansion or neuronal differentiation of hNPCs to quantities (>1010) necessary for drug screening or regenerative medicine purposes. In the future, the use of VDP as a defined culture substrate will significantly advance the clinical application of hNPCs and their derivatives as it will enable the large-scale expansion and neuronal differentiation of hNPCs in quantities necessary for disease modeling, drug screening, and regenerative medicine applications.
ContributorsVarun, Divya (Author) / Brafman, David (Thesis advisor) / Nikkhah, Mehdi (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2016
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Description
It is hypothesized that changes in brain tissue microstructure, particularly degradation of neurites (i.e,. axons and dendrites) and synapses, are early drivers of Alzheimer's disease (AD) pathogenesis. Quantitative magnetic resonance imaging (MRI) tools like diffusion tensor imaging (DTI) have long been used to study AD pathogenesis. Using DTI metrics, structural

It is hypothesized that changes in brain tissue microstructure, particularly degradation of neurites (i.e,. axons and dendrites) and synapses, are early drivers of Alzheimer's disease (AD) pathogenesis. Quantitative magnetic resonance imaging (MRI) tools like diffusion tensor imaging (DTI) have long been used to study AD pathogenesis. Using DTI metrics, structural insights of neuro tissue can be inferred but not directly measured. DTI has proven to be an effective tool indicating fractional anisotrophy (FA) differences between groups of varying AD risk factor, but it does not explicitly quantify pathophysiologically-relevant features like neurite density and complexity. This study aims to develop and validate an advanced diffusion MRI acquisition and biophysical modeling platform that can be used to explicitly quantify changes to brain tissue microstructure, specifically neurite density and complexity. Ultimately, this platform will be used to study the pathogenic mechanisms that drive AD in the pre-clinical and clinical setting.
ContributorsYamada, Nelson Garr (Author) / Beeman, Scott (Thesis advisor) / Schaefer, Sydney (Committee member) / Su, Yi (Committee member) / Arizona State University (Publisher)
Created2023