Matching Items (7)
Description
Parkinson's disease, the most prevalent movement disorder of the central nervous system, is a chronic condition that affects more than 1000,000 U.S. residents and about 3% of the population over the age of 65. The characteristic symptoms include tremors, bradykinesia, rigidity and impaired postural stability. Current therapy based on augmentation or replacement of dopamine is designed to improve patients' motor performance but often leads to levodopa-induced complications, such as dyskinesia and motor fluctuation. With the disease progress, clinicians must closely monitor patients' progress in order to identify any complications or decline in motor function as soon as possible in PD management. Unfortunately, current clinical assessment for Parkinson's is subjective and mostly influenced by brief observations during patient visits. Thus improvement or decline in patients' motor function in between visits is extremely difficult to assess. This may hamper clinicians while making informed decisions about the course of therapy for Parkinson's patients and could negatively impact clinical care. In this study we explored new approaches for PD assessment that aim to provide home-based PD assessment and monitoring. By extending the disease assessment to home, the healthcare burden on patients and their family can be reduced, and the disease progress can be more closely monitored by physicians. To achieve these aims, two novel approaches have been designed, developed and validated. The first approach is a questionnaire based self-evaluation metric, which estimate the PD severity through using self-evaluation score on pre-designed questions. Based on the results of the first approach, a smart phone based approach was invented. The approach takes advantage of the mobile computing technology and clinical decision support approach to evaluate the motor performance of patient daily activity and provide the longitudinal disease assessment and monitoring. Both approaches have been validated on recruited PD patients at the movement disorder program of Barrow Neurological Clinic (BNC) at St Joseph's Hospital and Medical Center. The results of validation tests showed favorable accuracy on detecting and assessing critical symptoms of PD, and shed light on promising future of implementing mobile platform based PD evaluation and monitoring tools to facilitate PD management.
ContributorsPan, Di (Author) / Petitti, Diana (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Dhall, Rohit (Committee member) / Arizona State University (Publisher)
Created2013
Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012
Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Viral protein U (Vpu) is a type-III integral membrane protein encoded by Human Immunodeficiency Virus-1 (HIV- 1). It is expressed in infected host cells and plays several roles in viral progeny escape from infected cells, including down-regulation of CD4 receptors. But key structure/function questions remain regarding the mechanisms by which the Vpu protein contributes to HIV-1 pathogenesis. Here we describe expression of Vpu in bacteria, its purification and characterization. We report the successful expression of PelB-Vpu in Escherichia coli using the leader peptide pectate lyase B (PelB) from Erwinia carotovora. The protein was detergent extractable and could be isolated in a very pure form. We demonstrate that the PelB signal peptide successfully targets Vpu to the cell membranes and inserts it as a type I membrane protein. PelB-Vpu was biophysically characterized by circular dichroism and dynamic light scattering experiments and was shown to be an excellent candidate for elucidating structural models.
ContributorsDeb, Arpan (Author) / Johnson, William (Author) / Kline, Alexander (Author) / Scott, Boston (Author) / Meador, Lydia (Author) / Srinivas, Dustin (Author) / Martin Garcia, Jose Manuel (Author) / Dorner, Katerina (Author) / Borges, Chad (Author) / Misra, Rajeev (Author) / Hogue, Brenda (Author) / Fromme, Petra (Author) / Mor, Tsafrir (Author) / ASU Biodesign Center Immunotherapy, Vaccines and Virotherapy (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Biodesign Institute (Contributor) / School of Molecular Sciences (Contributor) / Applied Structural Discovery (Contributor) / Personalized Diagnostics (Contributor)
Created2017-02-22
Description
Accurate quantitative information of tumor/lesion volume plays a critical role
in diagnosis and treatment assessment. The current clinical practice emphasizes on efficiency, but sacrifices accuracy (bias and precision). In the other hand, many computational algorithms focus on improving the accuracy, but are often time consuming and cumbersome to use. Not to mention that most of them lack validation studies on real clinical data. All of these hinder the translation of these advanced methods from benchside to bedside.
In this dissertation, I present a user interactive image application to rapidly extract accurate quantitative information of abnormalities (tumor/lesion) from multi-spectral medical images, such as measuring brain tumor volume from MRI. This is enabled by a GPU level set method, an intelligent algorithm to learn image features from user inputs, and a simple and intuitive graphical user interface with 2D/3D visualization. In addition, a comprehensive workflow is presented to validate image quantitative methods for clinical studies.
This application has been evaluated and validated in multiple cases, including quantifying healthy brain white matter volume from MRI and brain lesion volume from CT or MRI. The evaluation studies show that this application has been able to achieve comparable results to the state-of-the-art computer algorithms. More importantly, the retrospective validation study on measuring intracerebral hemorrhage volume from CT scans demonstrates that not only the measurement attributes are superior to the current practice method in terms of bias and precision but also it is achieved without a significant delay in acquisition time. In other words, it could be useful to the clinical trials and clinical practice, especially when intervention and prognostication rely upon accurate baseline lesion volume or upon detecting change in serial lesion volumetric measurements. Obviously, this application is useful to biomedical research areas which desire an accurate quantitative information of anatomies from medical images. In addition, the morphological information is retained also. This is useful to researches which require an accurate delineation of anatomic structures, such as surgery simulation and planning.
in diagnosis and treatment assessment. The current clinical practice emphasizes on efficiency, but sacrifices accuracy (bias and precision). In the other hand, many computational algorithms focus on improving the accuracy, but are often time consuming and cumbersome to use. Not to mention that most of them lack validation studies on real clinical data. All of these hinder the translation of these advanced methods from benchside to bedside.
In this dissertation, I present a user interactive image application to rapidly extract accurate quantitative information of abnormalities (tumor/lesion) from multi-spectral medical images, such as measuring brain tumor volume from MRI. This is enabled by a GPU level set method, an intelligent algorithm to learn image features from user inputs, and a simple and intuitive graphical user interface with 2D/3D visualization. In addition, a comprehensive workflow is presented to validate image quantitative methods for clinical studies.
This application has been evaluated and validated in multiple cases, including quantifying healthy brain white matter volume from MRI and brain lesion volume from CT or MRI. The evaluation studies show that this application has been able to achieve comparable results to the state-of-the-art computer algorithms. More importantly, the retrospective validation study on measuring intracerebral hemorrhage volume from CT scans demonstrates that not only the measurement attributes are superior to the current practice method in terms of bias and precision but also it is achieved without a significant delay in acquisition time. In other words, it could be useful to the clinical trials and clinical practice, especially when intervention and prognostication rely upon accurate baseline lesion volume or upon detecting change in serial lesion volumetric measurements. Obviously, this application is useful to biomedical research areas which desire an accurate quantitative information of anatomies from medical images. In addition, the morphological information is retained also. This is useful to researches which require an accurate delineation of anatomic structures, such as surgery simulation and planning.
ContributorsXue, Wenzhe (Author) / Kaufman, David (Thesis advisor) / Mitchell, J. Ross (Thesis advisor) / Johnson, William (Committee member) / Scotch, Matthew (Committee member) / Arizona State University (Publisher)
Created2016
Description
Viral protein U (Vpu) is a type-III integral membrane protein encoded by the Human Immunodeficiency Virus-1 (HIV- 1). It is expressed in infected host cells and plays vital roles in down-regulation of CD4 receptors in T cells and also in the budding of virions. But, there remain key structure/function questions regarding the mechanisms by which the Vpu protein contributes to HIV-1 pathogenesis and thus, it makes for an attractive target to study the structural attributes of this protein by elucidating a structural model with X-ray crystallography. This study describes a multi-pronged approach of heterologous over-expression of Vpu. The strategies of purification and biophysical/ biochemical characterization of the different versions of the protein to evaluate their potential for crystallization are also detailed. Furthermore, various strategies employed for the crystallization of Vpu by both in surfo and in cubo techniques, and the challenges faced towards the structural studies of this membrane protein by characterization with solution Nuclear magnetic resonance (NMR) spectroscopy are also described.
ContributorsDeb, Arpan (Author) / Leket-Mor, Tsafrir S (Thesis advisor) / Fromme, Petra (Committee member) / Mason, Hugh (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2016
Description
CTB-MPR is a fusion protein between the B subunit of cholera toxin (CTB) and the membrane-proximal region of gp41 (MPR), the transmembrane envelope protein of Human immunodeficiency virus 1 (HIV-1), and has previously been shown to induce the production of anti-HIV-1 antibodies with antiviral functions. To further improve the design of this candidate vaccine, X-ray crystallography experiments were performed to obtain structural information about this fusion protein. Several variants of CTB-MPR were designed, constructed and recombinantly expressed in Escherichia coli. The first variant contained a flexible GPGP linker between CTB and MPR, and yielded crystals that diffracted to a resolution of 2.3 Å, but only the CTB region was detected in the electron-density map. A second variant, in which the CTB was directly attached to MPR, was shown to destabilize pentamer formation. A third construct containing a polyalanine linker between CTB and MPR proved to stabilize the pentameric form of the protein during purification. The purification procedure was shown to produce a homogeneously pure and monodisperse sample for crystallization. Initial crystallization experiments led to pseudo-crystals which were ordered in only two dimensions and were disordered in the third dimension. Nanocrystals obtained using the same precipitant showed promising X-ray diffraction to 5 Å resolution in femtosecond nanocrystallography experiments at the Linac Coherent Light Source at the SLAC National Accelerator Laboratory. The results demonstrate the utility of femtosecond X-ray crystallography to enable structural analysis based on nano/microcrystals of a protein for which no macroscopic crystals ordered in three dimensions have been observed before.
ContributorsLee, Ho-Hsien (Author) / Cherni, Irene (Author) / Yu, HongQi (Author) / Fromme, Raimund (Author) / Doran, Jeffrey (Author) / Grotjohann, Ingo (Author) / Mittman, Michele (Author) / Basu, Shibom (Author) / Deb, Arpan (Author) / Dorner, Katerina (Author) / Aquila, Andrew (Author) / Barty, Anton (Author) / Boutet, Sebastien (Author) / Chapman, Henry N. (Author) / Doak, R. Bruce (Author) / Hunter, Mark (Author) / James, Daniel (Author) / Kirian, Richard (Author) / Kupitz, Christopher (Author) / Lawrence, Robert (Author) / Liu, Haiguang (Author) / Nass, Karol (Author) / Schlichting, Ilme (Author) / Schmidt, Kevin (Author) / Seibert, M. Marvin (Author) / Shoeman, Robert L. (Author) / Spence, John (Author) / Stellato, Francesco (Author) / Weierstall, Uwe (Author) / Williams, Garth J. (Author) / Yoon, Chun Hong (Author) / Wang, Dingjie (Author) / Zatsepin, Nadia (Author) / Hogue, Brenda (Author) / Matoba, Nobuyuki (Author) / Fromme, Petra (Author) / Mor, Tsafrir (Author) / ASU Biodesign Center Immunotherapy, Vaccines and Virotherapy (Contributor) / Department of Chemistry and Biochemistry (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Biodesign Institute (Contributor) / Infectious Diseases and Vaccinology (Contributor) / Department of Physics (Contributor)
Created2014-08-20