Matching Items (94)
Description
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier.
ContributorsBuddi, Sai (Author) / Taylor, Thomas (Thesis advisor) / Cochran, Douglas (Thesis advisor) / Nelson, Randall (Committee member) / Duman, Tolga (Committee member) / Arizona State University (Publisher)
Created2012
Description
Cancer claims hundreds of thousands of lives every year in US alone. Finding ways for early detection of cancer onset is crucial for better management and treatment of cancer. Thus, biomarkers especially protein biomarkers, being the functional units which reflect dynamic physiological changes, need to be discovered. Though important, there are only a few approved protein cancer biomarkers till date. To accelerate this process, fast, comprehensive and affordable assays are required which can be applied to large population studies. For this, these assays should be able to comprehensively characterize and explore the molecular diversity of nominally "single" proteins across populations. This information is usually unavailable with commonly used immunoassays such as ELISA (enzyme linked immunosorbent assay) which either ignore protein microheterogeneity, or are confounded by it. To this end, mass spectrometric immuno assays (MSIA) for three different human plasma proteins have been developed. These proteins viz. IGF-1, hemopexin and tetranectin have been found in reported literature to show correlations with many diseases along with several carcinomas. Developed assays were used to extract entire proteins from plasma samples and subsequently analyzed on mass spectrometric platforms. Matrix assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) mass spectrometric techniques where used due to their availability and suitability for the analysis. This resulted in visibility of different structural forms of these proteins showing their structural micro-heterogeneity which is invisible to commonly used immunoassays. These assays are fast, comprehensive and can be applied in large sample studies to analyze proteins for biomarker discovery.
ContributorsRai, Samita (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Borges, Chad (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
The purpose of this study is to first investigate the role of political socialization on young men and women and what motivates them to become politically active and make the ultimate decision to run for elected office. These effects include parental attitudes, exposure to political shows and news sources, participation in voluntary organizations, and overall community involvement. After understanding these direct and indirect effects of political socialization, I can attempt to explain the causes for the gender gap in political ambition \u2014 meaning that significantly more men are running for elected office compared to women.
ContributorsOsgood, Shannon Marie (Author) / Woodall, Gina (Thesis director) / Herrera, Richard (Committee member) / Barrett, The Honors College (Contributor) / College of Public Service and Community Solutions (Contributor) / School of Public Affairs (Contributor) / School of Politics and Global Studies (Contributor)
Created2015-05
Description
The Undoing Project is an ongoing educational feminist YouTube channel that serves as an introduction to feminism and feminist theory. The objective for this project is to present feminist theory and feminist ideology in an accessible and entertaining way. Through this project I sought to accomplish three goals: to challenge the negative image of feminism, bridge the gap between the language of academia and the public, and to acknowledge and unlearn ingrained prejudices. The videos focus on theory, history, legislation, current events, and pop culture. The initial project consists of ten videos addressing the feminist wave models, a brief history of the feminist movement, and discussions of concepts like hegemony, intersectionality, masculinity, femininity, and race.
ContributorsBuchholtz, Kaylee Marie (Author) / Brian, Jennifer (Thesis director) / Grzanka, Patrick (Committee member) / Brouwer, Dan (Committee member) / Barrett, The Honors College (Contributor) / College of Public Service and Community Solutions (Contributor) / School of Social Transformation (Contributor) / Department of English (Contributor)
Created2015-05
Description
Along with the number of technologies that have been introduced over a few years ago, gesture-based human-computer interactions are becoming the new phase in encompassing the creativity and abilities for users to communicate and interact with devices. Because of how the nature of defining free-space gestures influence user's preference and the length of usability of gesture-driven devices, defined low-stress and intuitive gestures for users to interact with gesture recognition systems are necessary to consider. To measure stress, a Galvanic Skin Response instrument was used as a primary indicator, which provided evidence of the relationship between stress and intuitive gestures, as well as user preferences towards certain tasks and gestures during performance. Fifteen participants engaged in creating and performing their own gestures for specified tasks that would be required during the use of free-space gesture-driven devices. The tasks include "activation of the display," scroll, page, selection, undo, and "return to main menu." They were also asked to repeat their gestures for around ten seconds each, which would give them time and further insight of how their gestures would be appropriate or not for them and any given task. Surveys were given at different time to the users: one after they had defined their gestures and another after they had repeated their gestures. In the surveys, they ranked their gestures based on comfort, intuition, and the ease of communication. Out of those user-ranked gestures, health-efficient gestures, given that the participants' rankings were based on comfort and intuition, were chosen in regards to the highest ranked gestures.
ContributorsLam, Christine (Author) / Walker, Erin (Thesis director) / Danielescu, Andreea (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor) / School of Arts, Media and Engineering (Contributor) / Department of English (Contributor) / Computing and Informatics Program (Contributor)
Created2015-05
Description
Previous research has found improvements in motor and cognitive measures following Assisted Cycle Therapy (AC) in adolescence with Down syndrome (DS). Our study investigated whether we would find improvements in older adults with DS on measures of leisure physical activity (GLTEQ) and sleep, which are early indicators of Alzheimer's disease (AD) in persons with Down syndrome. This study consisted of eight participants with Down syndrome between 31 and 51 years old that cycled for 30 minutes 3 x/week for eight weeks either at their voluntary cycling rate (VC) or approximately 35% faster with the help of a mechanical motor (AC). We predicted that, based on pilot data (Gomez, 2015), GLTEQ would either maintain or improve after AC, but would decrease after VC and would stay the same after NC. We predicted that the sleep score may improve after both VC or AC or it may improve more after VC than AC based on pilot data related to leisure activity. Our results were consistent with our prediction that GLTEQ will either maintain or improve after AC but will decrease after VC. Our results were not consistent with our prediction that sleep may improve after both VC or AC or it may improve more after VC than AC, possibly because we did not pre-screen for sleep disorders. Future research should focus on recruiting more participants and using both objective and subjective measures of sleep and physical activity to improve the efficacy of the study.
ContributorsParker, Lucas Maury (Author) / Ringenbach, Shannon (Thesis director) / Buman, Matthew (Committee member) / Holzapfel, Simon (Committee member) / School of Social and Behavioral Sciences (Contributor) / School of Nutrition and Health Promotion (Contributor) / College of Public Service and Community Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
G3Box's 2013 Marketing Plan outlines a strategic plan and short term operational strategies for the company. The document includes a discussion of the company's decision to enter the market for healthcare facilities in developing counties, and a situation assessment of the market conditions. G3Box is targeting small and large NGOs that currently provide healthcare facilities in developing countries. The market size for healthcare aid in developing countries is estimated to be $1.7 billion. The plan also analyses the customer's value chain and buying cycle by using voice of the customer data. The strategic position analysis profiles G3Box's competition and discusses the company's differential advantage versus other options for healthcare facilities in developing countries. Next the document discusses G3Box's market strategy and implementation, along with outlining a value proposition for the company. G3Box has two objectives for 2013: 1) Increase sales revenue to $1.3 million and 2) increase market presence to 25%. In order to reach these objectives, G3Box has developed a primary and secondary strategic focus for each objective. The primary strategies are relationship selling and online marketing. The secondary strategies are developing additional value-added activities and public relations.
ContributorsWalters, John (Author) / Denning, Michael (Thesis director) / Ostrom, Lonnie (Committee member) / Carroll, James (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
Description
The majority of the 52 photovoltaic installations at ASU are governed by power purchase agreements (PPA) that set a fixed per kilowatt-hour rate at which ASU buys power from the system owner over the period of 15-20 years. PPAs require accurate predictions of the system output to determine the financial viability of the system installations as well as the purchase price. The research was conducted using PPAs and historical solar power production data from the ASU's Energy Information System (EIS). The results indicate that most PPAs slightly underestimate the annual energy yield. However, the modeled power output from PVsyst indicates that higher energy outputs are possible with better system monitoring.
ContributorsVulic, Natasa (Author) / Bowden, Stuart (Thesis director) / Bryan, Harvey (Committee member) / Sharma, Vivek (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
Description
The 21st century engineer will face a diverse set of challenges spread out along a broad spectrum of disciplines. Among others, the fields of energy, healthcare, cyberspace, virtual reality, and neuroscience require monumental efforts by the new generation of engineers to meet the demands of a growing society. However the most important, and likely the most under recognized, challenge lies in developing advanced personalized learning. It is the core foundation from which the rest of the challenges can be accomplished. Without an effective method of teaching engineering students how to realize these grand challenges, the knowledge pool from which to draw new innovations and discoveries will be greatly diminished. This paper introduces the Inventors Workshop (IW), a hands-on, passion-based approach to personalized learning. It is intended to serve as a manual that will inform the next generation of student leaders and inventioneers about the core concepts the Inventors Workshop was built upon, and how to continue improvement into the future. Due to the inherent complexities in the grand challenge of personalized learning, the IW has developed a multifaceted solution that is difficult to explain in a single phrase. To enable comprehension of the IW's full vision, the process undergone to date of establishing and expanding the IW is described. In addition, research has been conducted to determine a variety of paths the Inventors Workshop may utilize in future expansion. Each of these options is explored and related to the core foundations of the IW to assist future leaders and partners in effectively improving personalized learning at ASU and beyond.
ContributorsEngelhoven, V. Logan (Author) / Burleson, Winslow (Thesis director) / Peck, Sidnee (Committee member) / Fortun, A. L. Cecil (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12