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- Genre: Academic theses
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
Knowing that disorder is related to crime, it has become essential for criminologists to understand how and why certain individuals perceive disorder. Using data from the Perceptions of Neighborhood Disorder and Interpersonal Conflict Project, this study uses a fixed photograph of a neighborhood, to assess whether individuals "see" disorder cues. A final sample size of n=815 respondents were asked to indicate if they saw particular disorder cues in the photograph. The results show that certain personal characteristics do predict whether an individual sees disorder. Because of the experimental design, results are a product of the individual's personal characteristics, not of the respondent's neighborhood. These findings suggest that the perception of disorder is not as clear cut as once thought. Future research should explore what about these personal characteristics foster the perception of disorder when it is not present, as well as, how to fight disorder in neighborhoods when perception plays such a substantial role.
ContributorsScott, Christopher (Author) / Wallace, Danielle (Thesis advisor) / Katz, Charles (Committee member) / Ready, Justin (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
Criminologists have directed significant theoretical and empirical attention toward the institution of marriage over the past two decades. Importantly, the momentum guiding this line of research has increased despite the fact that people are getting married far less often and much later in the life course than in any point in American history. The aim of this dissertation is to address this disconnect by focusing attention to nonmarital romantic relationships and their instability during emerging adulthood. To do so, it uses data from the Pathways to Desistance Study, a longitudinal study of 1,354 at-risk males and females who were adjudicated from the juvenile and adult systems in Phoenix and Philadelphia between 2000 and 2003. The project focuses attention to the following issues: (1) the effect of romantic dissolution on aggressive and income-based offenses; (2) the extent to which strain
egative emotionality and peer influence/exposure account for the effect of romantic dissolution on crime; and (3) the extent to which certain relationship and individual circumstances moderate the effect of romantic dissolution. The models reveal a few key findings. First, romantic dissolution is strongly related to an increase in both aggressive and income-based crime, but is more strongly related to income-based crime. Second, the effect of romantic dissolution is reduced when measures of strain
egative emotionality and peer influence/exposure measures are added to models, but the peer influence/exposure measures account for the strongest reduction. Finally, romantic dissolution does not serve as a positive life event among these at-risk youth, but its effect is exacerbated under a number of contexts (e.g. when an individual is unemployed). This study closes with a summary of these findings as well as its key limitations, and offers insight into potential policy implications and avenues of future research.
egative emotionality and peer influence/exposure account for the effect of romantic dissolution on crime; and (3) the extent to which certain relationship and individual circumstances moderate the effect of romantic dissolution. The models reveal a few key findings. First, romantic dissolution is strongly related to an increase in both aggressive and income-based crime, but is more strongly related to income-based crime. Second, the effect of romantic dissolution is reduced when measures of strain
egative emotionality and peer influence/exposure measures are added to models, but the peer influence/exposure measures account for the strongest reduction. Finally, romantic dissolution does not serve as a positive life event among these at-risk youth, but its effect is exacerbated under a number of contexts (e.g. when an individual is unemployed). This study closes with a summary of these findings as well as its key limitations, and offers insight into potential policy implications and avenues of future research.
ContributorsLarson, Matthew Joseph (Author) / Sweeten, Gary (Thesis advisor) / Piquero, Alex (Committee member) / Spohn, Cassia (Committee member) / Wallace, Danielle (Committee member) / Arizona State University (Publisher)
Created2013
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
Effectiveness and efficiency of the police have been contentious topics from the public perspective. Police departments have developed policies to help better their patrol officers' effectiveness on the streets in both quality and timeliness. Although there have been few recent studies about the response time of officers to calls for service, this is a subject that should not go overlooked. As an important aspect to the patrol officer's repertoire, response time can have effects on the community and its perception on the police. This study uses a multi-level modeling approach to examine the effects of incident and neighborhood factors on police response time within a medium size Southwest city. Police departments use a scale to determine the priority of a call for service, commonly referred to as the PRI. This index scale was found to have the most effect on the response times, while a few cyclical patterns were obtained of level 1 variables. Neighborhood characteristics showed significant effects, measuring structural disadvantage, however, caution should be used in generalizing these findings to other public jurisdictions.
ContributorsSullivan, Eamon (Author) / Ready, Justin (Thesis advisor) / Wallace, Danielle (Committee member) / Katz, Charles (Committee member) / Arizona State University (Publisher)
Created2012
Description
Meditation app usage is associated with decreases in stress, anxiety, and depression symptoms. Many meditation app subscribers, however, quickly abandon or reduce their app usage. This dissertation presents three manuscripts which 1) determined the behavioral, demographic, and socioeconomic factors associated with the abandonment of a meditation app, Calm, during the COVID-19 pandemic, 2) determined which participant characteristics predicted meditation app usage in the first eight weeks after subscribing, and 3) determined if changes in stress, anxiety, and depressive symptoms from baseline to Week 8 predicted meditation app usage from Weeks 8-16. In Manuscript 1, a survey was distributed to Calm subscribers in March 2020 that assessed meditation app behavior and meditation habit strength, and demographic information. Cox proportional hazards regression models were estimated to assess time to app abandonment. In Manuscript 2, new Calm subscribers completed a baseline survey on participants’ demographic and baseline mental health information and app usage data were collected over 8 weeks. In Manuscript 3, new Calm subscribers completed a baseline and Week 8 survey on demographic and mental health information. App usage data were collected over 16 weeks. Regression models were used to assess app usage for Manuscripts 2 and 3. Findings from Manuscript 1 suggest meditating after an existing routine decreased risk of app abandonment for pre-pandemic subscribers and for pandemic subscribers. Additionally, meditating “whenever I can” decreased risk of abandonment among pandemic subscribers. No behavioral factors were significant predictors of app abandonment among the long-term subscribers. Findings from Manuscript 2 suggest men had more days of meditation than women. Mental health diagnosis increased average daily meditation minutes. Intrinsic motivation for meditation increased the likelihood of completing any meditation session, more days with meditation sessions, and more average daily meditation minutes. Findings from Manuscript 3 suggest improvements in stress increased average daily meditation minutes. Improvements in depressive symptoms decreased daily meditation minutes. Evidence from this three-manuscript dissertation suggests meditation cue, time of day, motivation, symptom changes, and demographic and socioeconomic variables may be used to predict meditation app usage.
ContributorsSullivan, Mariah (Author) / Stecher, Chad (Thesis advisor) / Huberty, Jennifer (Committee member) / Buman, Matthew (Committee member) / Larkey, Linda (Committee member) / Chung, Yunro (Committee member) / Arizona State University (Publisher)
Created2022
Description
ABSTRACT
The legalization of marijuana is increasing in the United States. With more dispensaries opening, it is essential to look at these businesses' impacts on neighborhood crime rates. Alcohol outlets are known as crime attractors/crime generators, and their presence in a neighborhood is also significant to look at when investigating violent crime rates. It is crucial then to take both marijuana and alcohol outlets together to determine the effects these facilities have on aggravated assault and robbery in a neighborhood. To assess the impact of marijuana outlets, on-premises alcohol outlets, and off-premises alcohol outlets in Los Angeles, California, on aggravated assaults and robberies, this thesis uses Los Angeles business, crime, and census data. The study addresses the following research questions: (1) Does an additional marijuana outlet in a neighborhood increase aggravated assaults and robberies? (2) Does the presence of on- and off-premises alcohol outlets increase aggravated assault and robbery? (3) Does the presence of multiple types of risky businesses increase violent crime? The current study finds an increase in aggravated assaults and robberies when marijuana outlets and on- and off-premises outlets are located in a neighborhood. The only non-significant finding is when all three outlet types were present; marijuana outlets are the only outlet type not associated with an increase in robbery. These findings suggest that limits should be placed on the number of risky retailers in a neighborhood and provides policy implications directed toward reducing violent crime near marijuana and alcohol outlets.
KEYWORDS alcohol outlets, marijuana outlets, aggravated assault, robbery
ContributorsStowell, Sierra (Author) / Chamberlain, Alyssa (Thesis advisor) / Wallace, Danielle (Committee member) / Arizona State University (Publisher)
Created2022
Description
Young adult collegiate women, particularly students with adverse childhood experiences (ACEs) and who have experienced intimate partner violence (IPV) victimization, report a myriad of adverse mental health and academic difficulties. Practicing yoga has demonstrated promising findings among adults as a healing modality in the aftermath of interpersonal violence victimization and traumatization. Less known are the associations between collegiate women’s yoga participation and their mental health, body connection, and academic well-being examined through a yoga feminist- trauma conceptual framework. Among young adult collegiate women, this study examined (1) associations amongst socio-demographics, mental health service use, IPV types, and yoga participation (2) the strength and direction of associations on measures of ACEs, mental health, body connection, and academic well-being, (3) whether yoga participation predicted students’ mental health, body connection, and academic well-being after controlling for confounding variables, including ACEs and IPV victimization, and (4) whether socio-demographics, mental health service use, ACEs, and IPV types predicted yoga participation. This study was observational, cross-sectional, and gathered self-report quantitative data. Eligible participants were current collegiate women enrolled at an urban, public university in the southwestern United States who were 18 to 24 years of age. The main sub-sample (n = 93) included students who were ever in an intimate relationship and practiced yoga within the past year. IRB approval was obtained. Findings demonstrated that yoga participation was not a significant predictor of students’ mental health, body connection, or academic well-being. Socio-demographics, mental health service use, ACEs, and IPV did not predict yoga participation. However, women with greater ACEs fared worse on measures of mental health (i.e., depression and post-traumatic stress disorder symptoms), and women with experiences of IPV harassment reported greater post-traumatic stress disorder symptoms. Further, employed women reported fewer depression symptoms and were less likely to experience emotional IPV. Lastly, students with greater body connection (more awareness) fared better academically. This research supports prior literature on the adverse mental health outcomes among young adult collegiate women with histories of interpersonal violence. Further examination is warranted into employment and body connection, particularly related to yoga, as protective factors of students' health, safety, and academic well-being.
ContributorsKappas Mazzio, Andrea Alexa (Author) / Messing, Jill T (Thesis advisor) / Mendoza, Natasha (Committee member) / Huberty, Jennifer (Committee member) / Arizona State University (Publisher)
Created2022
Description
The purpose of this study is to examine how sex influences the physical demandof weapons used in homicide. The study focuses on two research questions using data
from Newark, New Jersey: (1) Does sex influence the use of a weapon that is more or
less physically demanding to commit homicide? and (2) Does the sex dyad of the
offender and victim influence using a weapon that is more or less physically demanding?
The descriptive analysis shows significant relationships between the sex dyad of the
offender and victim in homicide and the level of physical demand used to perpetrate
homicide. The logistic multinomial regression analysis shows suspect sex and suspect
and victim sex dyads significantly predict the physical demand of the weapons used to
perpetrate homicide compared to those who utilized weapons of low physical demand.
The results support the need to challenge traditional perspectives regarding the role of sex
in criminal decision-making and seek to integrate more intersectional and gendered
explanations into neoclassical theories of criminal behavior. Theoretical implications and
future avenues of research are also discussed.
ContributorsAlvarez, Gabriel (Author) / Pizarro, Jesenia M. (Thesis advisor) / Messing, Jill T. (Committee member) / Wallace, Danielle (Committee member) / Arizona State University (Publisher)
Created2022