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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
The research presented here aims to explore the perceived Quality of Life (QoL) and perceived accessibility among varying demographic and socioeconomic groups in the Phoenix Metropolitan Area. A relationship between perceived QoL and perceived accessibility was further investigated. The data was collected through the Phoenix Area Social Survey (PASS), which sent randomized surveys to 496 people in the Phoenix region. The survey’s response rate varied, from a low of 22.2% in one of the lowest-income neighborhoods and a high of 55.6% for a middle-income neighborhood. Results were obtained through statistical analyses, such as correlations, chi-squared tests, and t-tests. Results for income, gender and ethnicity indicated similar and comparable perceived QoL and perceived accessibility in the Phoenix area. The data did not reveal a relationship between perceived QoL and perceived accessibility; however, accessibility did increase with increasing income. A striking finding revolved around disparities in access to walkability and transit across all income, genders and ethnicities. This presents implications for built environment and resource allocation planning in order to enhance the lives of residents in the Valley. Future research and investigation into the objective indicators of QoL and impacts of culture on QoL should be pursued.
ContributorsOmar, Hafsa (Author) / Pfeiffer, Deirdre (Thesis director) / Ehlenz, Meagan (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Planners are often involved in the development of 'visions' for specific projects or larger plans. These visions often serve as guideposts for more specific plans or projects and the visioning process is important for involving community members into the planning process. This paper provides a review of the recent literature published about visioning and is intended to provide guidance for visioning activities in planning projects. I use the general term "vision" in reference to a desirable state in the future. The body of academic literature on visioning in planning has been growing over the last decade. However, the planning literature on visioning is diverse and dispersed, posing various challenges to researchers and planners seeking guidance for their own planning (research) activities. For one, relevant articles on visioning are scattered over different strands of literature ranging from traditional planning literature (Journal of the American Planning Association, Planning Practice and Research, etc.) to less traditional and intuitive sources (Futures, Journal of Cross-Cultural Psychology). Further, some of them not easily identifiable and may not be openly accessible via the Internet. Thus, our review intends to help collect and synthesize this literature and begin to provide guidance for the future of visioning in the field of planning. I do this by compiling visioning literature from different strands of the planning literature, synthesizing key insights into visioning in (urban) planning, undertaking exemplary appraisals of visioning approaches in planning against quality criteria, and deriving conclusions for visioning research and practice. From this review, I highlight areas of opportunity and ways forward in order to make visioning more effective and more influential for the future of communities throughout the world.
ContributorsMinowitz, Amy (Author) / Golub, Aaron (Thesis advisor) / Wiek, Arnim (Committee member) / Pfeiffer, Deirdre (Committee member) / Arizona State University (Publisher)
Created2013
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
Mixed-income housing policy has been an approach to address the problem of concentrated poverty since the 1990s. The idea of income mix in housing is founded on the proposition that economic opportunities of the poor can be expanded through the increasing of their social capital. The current in-depth case study of Vineyard Estates, a mixed-income housing development in Phoenix, AZ tests a hypothesis that low-income people improve their chances of upward social mobility by building ties with more affluent residents within the development. This study combines qualitative and quantitative methods to collect and analyze information including analysis of demographic data, resident survey and in-depth semi-structured interviews with residents, as well as direct observations. It focuses on examining the role of social networks established within the housing development in generating positive economic outcomes of the poor. It also analyzes the role of factors influencing interactions across income groups and barriers to upward social mobility. Study findings do not support that living in mixed-income housing facilitates residents' upward social mobility. The study concludes that chances of upward social mobility are restrained by structural factors and indicates a need to rethink the effectiveness of mixed-income housing as an approach for alleviating poverty.
ContributorsDurova, Aleksandra (Author) / Kamel, Nabil (Committee member) / Pfeiffer, Deirdre (Committee member) / Lucio, Joanna (Committee member) / Arizona State University (Publisher)
Created2013
Description
Over the last two decades programs and mandates to encourage and foster sustainable urban development have arisen throughout the world, as cities have emerged as key opportunity sites for sustainable development due to the compactness and localization of services and resources. In order to recognize this potential, scholars and practitioners have turned to the practice of visioning as a way to motivate actions and decision making toward a sustainable future. A "vision" is defined as desirable state in the future and scholars believe that the creation of a shared, motivational vision is the best starting point to catalyze positive and sustainable change. However, recent studies on city visions indicate that they do not offer substantive sustainability content, and methods or processes to evaluate the sustainability content of the resulting vision (sustainability appraisal or assessment) are often absent from the visioning process. Thus, this paper explores methods for sustainability appraisal and their potential contributions to (and in) visioning. The goal is to uncover the elements of a robust sustainability appraisal and integrate them into the visioning process. I propose an integrated sustainability appraisal procedure based on sustainability criteria, indicators, and targets as part of a visioning methodology that was developed by a team of researchers at Arizona State University (ASU) of which I was a part. I demonstrate the applicability of the appraisal method in a case study of visioning in Phoenix, Arizona. The proposed method allows for early and frequent consideration and evaluation of sustainability objectives for urban development throughout the visioning process and will result in more sustainability-oriented visions. Further, it can allow for better measurement and monitoring of progress towards sustainability goals, which can make the goals more tangible and lead to more accountability for making progress towards the development of more sustainable cities in the future.
ContributorsMinowitz, Amy (Author) / Wiek, Arnim (Thesis advisor) / Golub, Aaron (Committee member) / Pfeiffer, Deirdre (Committee member) / Arizona State University (Publisher)
Created2013
Description
Salmonella enterica is a gastrointestinal (GI) pathogen that can cause systemic diseases. It invades the host through the GI tract and can induce powerful immune responses in addition to disease. Thus, it is considered as a promising candidate to use as oral live vaccine vectors. Scientists have been making great efforts to get a properly attenuated Salmonella vaccine strain for a long time, but could not achieve a balance between attenuation and immunogenicity. So the regulated delayed attenuation/lysis Salmonella vaccine vectors were proposed as a design to seek this balance. The research work is progressing steadily, but more improvements need to be made. As one of the possible improvements, the cyclic adenosine monophosphate (cAMP) -independent cAMP receptor protein (Crp*) is expected to protect the Crp-dependent crucial regulator, araC PBAD, in these vaccine designs from interference by glucose, which decreases synthesis of cAMP, and enhance the colonizing ability by and immunogenicity of the vaccine strains. In this study, the cAMP-independent crp gene mutation, crp-70, with or without araC PBAD promoter cassette, was introduced into existing Salmonella vaccine strains. Then the plasmid stability, growth rate, resistance to catabolite repression, colonizing ability, immunogenicity and protection to challenge of these new strains were compared with wild-type crp or araC PBAD crp strains using western blots, enzyme-linked immunosorbent assays (ELISA) and animal studies, so as to evaluate the effects of the crp-70 mutation on the vaccine strains. The performances of the crp-70 strains in some aspects were closed to or even exceeded the crp+ strains, but generally they did not exhibit the expected advantages compared to their wild-type parents. Crp-70 rescued the expression of araC PBAD fur from catabolite repression. The strain harboring araC PBAD crp-70 was severely affected by its slow growth, and its colonizing ability and immunogenicity was much weaker than the other strains. The Pcrp crp-70 strain showed relatively good ability in colonization and immune stimulation. Both the araC PBAD crp-70 and the Pcrp crp-70 strains could provide certain levels of protection against the challenge with virulent pneumococci, which were a little lower than for the crp+ strains.
ContributorsShao, Shihuan (Author) / Curtiss, Roy (Thesis advisor) / 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
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
DescriptionThis paper explores if there is a relationship between neighborhoods foreclosures and future social mobility in Maricopa County. Using data from various sources, we constructed a statistical model, multiple regression analysis, and maps to demonstrate patterns across Maricopa County, Arizona.
ContributorsO'Connell, Jennifer (Author) / Connor, Dylan (Thesis director) / Pfeiffer, Deirdre (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2022-12