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You searched for +publisher:"Vanderbilt University" +contributor:("Daniel O. Claassen"). Showing records 1 – 3 of 3 total matches.

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Vanderbilt University

1. Kumar, Kevin Krishan. Investigation of Neuronal Manganese Regulation in Physiology and Disease Using High Throughput Screening, Induced Pluripotent Stem Cells, and Chemical Biology Approaches.

Degree: PhD, Neuroscience, 2014, Vanderbilt University

Manganese (Mn) is both an essential biological cofactor and neurotoxicant. Disruption of Mn biology in the basal ganglia has been implicated in the pathogenesis of neurodegenerative disorders, such as parkinsonism and Huntington’s disease (HD). However, beyond several non-selective transporters, little is known about the intracellular processes regulating neuronal Mn homeostasis. We hypothesized that small molecules that modulate intracellular Mn could provide insight into cell-level Mn regulatory mechanisms. We performed a high throughput screen of 40,167 small molecules for modifiers of cellular Mn content. Utilizing the identified small molecules, we tested for differential regulation of Mn handling in human floor-plate lineage dopaminergic neurons, a lineage especially vulnerable to environmental Mn exposure. We report differential Mn accumulation between developmental stages and stage-specific differences in the Mn-altering activity of individual small molecules, demonstrating cell-level regulation of Mn content across neuronal differentiation. In a parallel study, we sought to reveal any cellular metabolic phenotypes influenced by Mn exposure and/or the mutant HD genotype using an unbiased metabolomics approach. Our analysis revealed metabolic evidence of an interaction between the HD genotype and environmentally relevant Mn exposures in a striatal neural lineage. The metabolic phenotypes detected support existing hypotheses that changes in energetic processes underlie the pathogenesis of both HD and Mn neurotoxicity. Advisors/Committee Members: Aaron B. Bowman (committee member), Joseph S. Neimat (committee member), Michael Aschner (committee member), C. David Weaver (committee member), Daniel O. Claassen (committee member), Kevin C. Ess (Committee Chair).

Subjects/Keywords: High Throughput Screening; Manganese; Neurodegenerative diseases; Human Induced Pluripotent Stem Cells; Metabolomics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kumar, K. K. (2014). Investigation of Neuronal Manganese Regulation in Physiology and Disease Using High Throughput Screening, Induced Pluripotent Stem Cells, and Chemical Biology Approaches. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14021

Chicago Manual of Style (16th Edition):

Kumar, Kevin Krishan. “Investigation of Neuronal Manganese Regulation in Physiology and Disease Using High Throughput Screening, Induced Pluripotent Stem Cells, and Chemical Biology Approaches.” 2014. Doctoral Dissertation, Vanderbilt University. Accessed January 15, 2021. http://hdl.handle.net/1803/14021.

MLA Handbook (7th Edition):

Kumar, Kevin Krishan. “Investigation of Neuronal Manganese Regulation in Physiology and Disease Using High Throughput Screening, Induced Pluripotent Stem Cells, and Chemical Biology Approaches.” 2014. Web. 15 Jan 2021.

Vancouver:

Kumar KK. Investigation of Neuronal Manganese Regulation in Physiology and Disease Using High Throughput Screening, Induced Pluripotent Stem Cells, and Chemical Biology Approaches. [Internet] [Doctoral dissertation]. Vanderbilt University; 2014. [cited 2021 Jan 15]. Available from: http://hdl.handle.net/1803/14021.

Council of Science Editors:

Kumar KK. Investigation of Neuronal Manganese Regulation in Physiology and Disease Using High Throughput Screening, Induced Pluripotent Stem Cells, and Chemical Biology Approaches. [Doctoral Dissertation]. Vanderbilt University; 2014. Available from: http://hdl.handle.net/1803/14021


Vanderbilt University

2. Petersen, Kalen John. Novel Assays of Brain Networks and Applications to Neurodegeneration.

Degree: PhD, Chemical and Physical Biology, 2019, Vanderbilt University

The human brain is comprised of spatially separable, functionally discrete networks which can be mapped in vivo using multimodal magnetic resonance imaging (MRI). MRI permits interrogation of both the neuroanatomy of healthy brain circuits and identification of neuropathological dysfunction. The dentato-rubro-thalamic tract, the major efferent cerebellar white matter pathway, has an ipsilateral branch of unknown function. Tractographic analysis demonstrates that this branch is characterized by a more medial-posterior connectivity profile in the thalamus than the classical pathway, implying partial divergence. Resting-state functional connectivity reveals bilateral correlation between activity in the cerebellar dentate and thalamus, suggesting a functional role for ipsilateral connections. This network is degenerative in neurological disorders of movement and cognition such as progressive supranuclear palsy. While cortico-cerebellar loops mediate numerous motor and non-motor processes, frontal networks are critical for behavioral self-regulation. The limbic network is characterized by feedback projections involving the ventral striatum and cortical regions including the orbitofrontal cortex and anterior cingulate gyrus, critical regulators of reward-motivated activity. The dopamine-sensitive ventral striatum is functionally altered by administration of dopamine agonists as pharmacological therapy for Parkinson’s disease. Resting-state functional connectivity is elevated in mesocorticolimbic networks centered on the ventral striatum in patients who develop aberrant impulsive and compulsive behaviors as a side effect of dopamine replacement therapy. This altered pattern is associated with enhanced reward-learning proficiency. However, portions of the limbic network have poor signal in traditional functional MRI due to susceptibility and distortion in the ventral frontal lobe. As an alternative modality, perfusion-weighted arterial spin labeling (ASL) can recapitulate brain networks generally identified with the blood oxygenation level-dependent (BOLD) signal. However, optimized image pre-processing is necessary for consistent connectivity mapping. Surround subtraction, component-based noise correction, and spatial smoothing improve matching of ASL- and BOLD-derived networks. ASL-based functional connectivity is applied to the organization of the orbitofrontal cortex, and a previously hypothesized medial-lateral division is confirmed. Medial and lateral sub-regions are shown to have different functional and structural connectivity profiles; the latter is highly connected with the salience network and thus a potential mediator of impulsivity. Advisors/Committee Members: Victoria L. Morgan (committee member), Kevin D. Niswender (committee member), Daniel O. Claassen (committee member), Manus J. Donahue (committee member), Seth A. Smith (Committee Chair).

Subjects/Keywords: orbitofrontal cortex; tractography; functional connectivity; Parkinsons disease; impulsivity; brain connectivity; magnetic resonance imaging

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Petersen, K. J. (2019). Novel Assays of Brain Networks and Applications to Neurodegeneration. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/12253

Chicago Manual of Style (16th Edition):

Petersen, Kalen John. “Novel Assays of Brain Networks and Applications to Neurodegeneration.” 2019. Doctoral Dissertation, Vanderbilt University. Accessed January 15, 2021. http://hdl.handle.net/1803/12253.

MLA Handbook (7th Edition):

Petersen, Kalen John. “Novel Assays of Brain Networks and Applications to Neurodegeneration.” 2019. Web. 15 Jan 2021.

Vancouver:

Petersen KJ. Novel Assays of Brain Networks and Applications to Neurodegeneration. [Internet] [Doctoral dissertation]. Vanderbilt University; 2019. [cited 2021 Jan 15]. Available from: http://hdl.handle.net/1803/12253.

Council of Science Editors:

Petersen KJ. Novel Assays of Brain Networks and Applications to Neurodegeneration. [Doctoral Dissertation]. Vanderbilt University; 2019. Available from: http://hdl.handle.net/1803/12253


Vanderbilt University

3. Plassard, Andrew John. Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease.

Degree: PhD, Computer Science, 2017, Vanderbilt University

Improved segmentation of magnetic resonance imaging is necessary to provide quantitative and anatomical information for current and future radiological understanding of Parkinson’s disease and progression. Image segmentation is a common task, accomplished by a family of approaches, for calculation of volumetric and structural biomarkers in medical images. In Parkinson’s there is a focus on understanding subcortical grey matter, in particular as localization for deep brain stimulation surgery. In this work, we propose the following contributions on the multi-atlas segmentation framework. First, we propose an expansion of the statistical label fusion generative models to incorporate atlases of multiple labeling protocols. Second, we propose a multi-atlas segmentation framework to account for variability in imaging sequences. Third, we present a segmentation approach for efficient segmentation of the hippocampus and amygdala in the presence of a large atlas population. Fourth, we present a segmentation approach for automated segmentation of anatomical structures with highly variable anatomies, in particular the cerebellar lobules. Fifth, we present an evaluation of multi-modal segmentation of the subcortical grey matter. Sixth, we present an improved approach for assessment of segmentation accuracy and determination of the number of atlases needed for a given segmentation task. Together, this work expands and characterizes multi-atlas segmentation for use in Parkinson’s disease. These contributions improve our understanding of segmentation with varying labeling protocols and imaging sequences, our methods for evaluating segmentation results, and our methods for segmenting particular structures of interest. Advisors/Committee Members: Benoit M Dawant (committee member), Daniel O Claassen (committee member), Maureen K McHugo (committee member), Aniruddha S Gokhale (committee member), Bennett A Landman (Committee Chair).

Subjects/Keywords: Medical Image Segmentation; Parkinson's disease

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Plassard, A. J. (2017). Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14512

Chicago Manual of Style (16th Edition):

Plassard, Andrew John. “Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed January 15, 2021. http://hdl.handle.net/1803/14512.

MLA Handbook (7th Edition):

Plassard, Andrew John. “Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease.” 2017. Web. 15 Jan 2021.

Vancouver:

Plassard AJ. Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2021 Jan 15]. Available from: http://hdl.handle.net/1803/14512.

Council of Science Editors:

Plassard AJ. Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/14512

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