Matching Items (80)
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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

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
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Description
Purpose: To examine: (1) whether Non-Hispanic Blacks (NHB) and Non-Hispanic Whites (NHW) with diagnosed arthritis differed in self-reported physical activity (PA) levels, (2) if NHB and NHW with arthritis differed on potential correlates of PA based on the Social Ecological Model (Mcleroy et al., 1988), and (3) if PA participation

Purpose: To examine: (1) whether Non-Hispanic Blacks (NHB) and Non-Hispanic Whites (NHW) with diagnosed arthritis differed in self-reported physical activity (PA) levels, (2) if NHB and NHW with arthritis differed on potential correlates of PA based on the Social Ecological Model (Mcleroy et al., 1988), and (3) if PA participation varied by race/ethnicity after controlling for age, gender, education, and BMI. Methods: This study was a secondary data analysis of data collected from 2006-2008 in Chicago, IL as part of the Midwest Roybal Center for Health Promotion. Bivariate analyses were used to assess potential differences between race in meeting either ACR or ACSM PA guidelines. Comparisons by race between potential socio-demographic correlates and meeting physical activity guidelines were assessed using Chi-squares. Potential differences by race in psychosocial, arthritis, and health-related and environmental correlates were assessed using T-tests. Finally, logistic regression analyses were used to examine if race was still associated with PA after controlling for socio-demographic characteristics. Results: A greater proportion of NHW (68.1% and 35.3%) than NHB (46.5% and 20.9%) met both the arthritis-specific and the American College of Sports Medicine (ACSM) recommendations for physical activity, respectively. NHB had significantly lower self-efficacy for exercise and reported greater impairments in physical function compared to NHW. Likewise, NHB reported more crime and less aesthetics within their neighborhood. NHW were 2.56 times more likely to meet arthritis-specific PA guidelines than NHB after controlling for age, gender, education, marital status, and BMI. In contrast, after controlling for sociodemographic characteristics, age and gender were the only significant predictors of meeting ACSM PA guidelines. Discussion: There were significant differences between NHB and NHW individuals with arthritis in meeting PA guidelines. After controlling for age, gender, education, and BMI non-Hispanic White individuals were still significantly more likely to meet PA guidelines. Interventions aimed at promoting higher levels of physical activity among individuals with arthritis need to consider neighborhood aesthetics and crime when designing programs. More arthritis-specific programs are needed in close proximity to neighborhoods in an effort to promote physical activity.
ContributorsChuran, Christopher (Author) / Der Ananian, Cheryl (Thesis advisor) / Adams, Marc (Committee member) / Campbell, Kathryn (Committee member) / Arizona State University (Publisher)
Created2013
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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

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
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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

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
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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

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
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Description
With an excessive amount of resources in the United States healthcare system being spent on the treatment of diseases that are largely preventable through lifestyle change, the need for successful physical activity interventions is apparent. Unfortunately an individual's physical activity and health goals are often not supported by the social

With an excessive amount of resources in the United States healthcare system being spent on the treatment of diseases that are largely preventable through lifestyle change, the need for successful physical activity interventions is apparent. Unfortunately an individual's physical activity and health goals are often not supported by the social context of their daily lives. This single-case design study, Walking Intervention through Text messaging for CoHabiting individuals (WalkIT CoHab), looks at the efficacy of a text based adaptive physical activity intervention to promote walking over a three month period and the effects of social support in intervention performance in three pairs of cohabiting pairs of individuals (n=6). Mean step increase from baseline to intervention ranged from 1300 to 3000 steps per day for all individuals, an average 45.87% increase in physical activity. Goal attainment during the intervention ranged from 43.96% to 71.43%, meaning all participants exceeded the 40% success rate predicted by 60th percentile goals. Social support scores for study partners, unlike social support scores for family and friends, were often in the high social support range and had a moderate increase from pre to post visits for most participants. Although there was variation amongst participants, there was a high correlation in physical activity trends and successful goal attainment in each pair of participants. Less ambitious percentile goals and more personalized motivational text messages might be beneficial to some participants. An extended intervention, something the majority of participants expressed interest in, would further support the efficacy of this behavioral intervention and allow for possible long term benefits of social support in the intervention to be investigated.
ContributorsFernandez, Jacqueline Alyssa (Author) / Adams, Marc (Thesis director) / Angadi, Siddhartha (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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An increasingly sedentary population in the United States, specifically with adolescents, is putting youth at risk of future health related trauma and disease. This single-case design study, Walking Intervention Through Text Messaging for Adolescents (WalkIT-A), was used to intervene with a 12-year old, physically inactive male, in an attempt to

An increasingly sedentary population in the United States, specifically with adolescents, is putting youth at risk of future health related trauma and disease. This single-case design study, Walking Intervention Through Text Messaging for Adolescents (WalkIT-A), was used to intervene with a 12-year old, physically inactive male, in an attempt to test the efficacy of a 12-week physical activity program that may help reduce health risks by increasing number of steps walked per day. The components of the intervention consisted of a FitBit Zip pedometer, physical activity education, text messages, monetary incentives, and goal setting that adapted personally to the participant. Mean step count increased by 30% from baseline (mean = 3603 [sd = 1983]) to intervention (mean = 4693 [sd = 2112]); then increased slightly by 6.7% from intervention to withdrawal (mean = 5009 [sd = 2152]). Mean "very active minutes" increased by 45% from baseline (mean = 8.8 [sd = 8.9]) to intervention (mean = 12.8 [sd = 9.6]); then increased by 61.7% from intervention to withdrawal (mean = 20.7 [sd = 8.4]). Weight, BMI, and blood pressure all increased modestly from pre to post. Cardiovascular fitness (estimated VO2 max) improved by 12.5% from pre (25.5ml*kg-1*min-1) to post (28.7ml*kg-1*min-1). The intervention appeared to have a delayed and residual effect on the participant's daily steps and very active minutes. Although the idealistic ABA pattern did not occur, and the participant did not meet the target of 11,500 daily steps, a positive trend toward that target behavior in the latter 1/3rd of the intervention was observed. Results suggest the need for an extended intervention over a longer period of time and customized even further to the participant.
ContributorsLamb, Nicholas Reid (Author) / Adams, Marc (Thesis director) / Ainsworth, Barbara (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2014-12
DescriptionA novel and unconventional approach for delivering a eukaryotic apoptosis factor, TNF-related apoptosis-inducing ligand (TRAIL), to cancer cells within and around necrotizing tumors by utilizing a S. Typhimurium purine requiring auxotroph as a biological vector to develop two anticancer therapies with multiple modality and broad economic feasibility.
ContributorsKoons, Andrew (Author) / Curtiss, Roy (Thesis director) / Lake, Douglas (Committee member) / Janthakahalli, Nagaraj Vinay (Committee member) / Barrett, The Honors College (Contributor)
Created2013-12
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The WalkIT Study is a mobile health study examining the efficacy of a four month text message-based intervention for increasing physical activity among 96 overweight adults. The purpose of this thesis is to examine the potency of the different types of motivational prompt-to-action text messages used in the WalkIT Study

The WalkIT Study is a mobile health study examining the efficacy of a four month text message-based intervention for increasing physical activity among 96 overweight adults. The purpose of this thesis is to examine the potency of the different types of motivational prompt-to-action text messages used in the WalkIT Study for increasing steps per day by examining the individual messages, creating qualitative themes and comparing themed groups, and evaluating the interaction between demographic subgroups and themed groups. A total of nine themes was created. The results found that Message 13, “It doesn't matter how old you are – it's never too early or too late to become physically active so start today; only then will you start to see results!”, had the highest median step count (7129 steps) and Message 71, “It's ok if you can't reach your goal today. Just push yourself more tomorrow.”, had the lowest median step count (5054 steps). For themes, the highest median step count (6640 steps) was found in Theme 6, Challenges, and the lowest median step count (5450 steps) was found in Theme 9, Unconditional Feedback. Theme 6 (Challenges) had the highest median step count for females, Theme 7 (Everyday Tips) had the highest median step count for males, Theme 4 (Nutrition) had the highest median step count for the 18-42 group, Theme 6 (Challenges) had the highest median step count for the 43-61 group, and Theme 9 (Unconditional Feedback) had the lowest median step count for both genders and both age groups. The results suggest the usefulness of analyzing the effectiveness of individual motivational text messages, themes, and the interaction between demographic groups and themes in physical activity interventions.
ContributorsBhuiyan, Nishat Anjum (Author) / Adams, Marc (Thesis director) / Ainsworth, Barbara (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05
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The SARS-CoV-2 (Covid-19) virus has had severe impacts on college students' ways of life. To examine how students were coping and perceiving the Covid-19 pandemic, a secondary analysis of an online survey across the three Arizona public universities investigated students’ knowledge about Covid-19, engagement with preventive strategies, pandemic preparedness and

The SARS-CoV-2 (Covid-19) virus has had severe impacts on college students' ways of life. To examine how students were coping and perceiving the Covid-19 pandemic, a secondary analysis of an online survey across the three Arizona public universities investigated students’ knowledge about Covid-19, engagement with preventive strategies, pandemic preparedness and gauged their risk perception. Results from our analysis indicate that the students were knowledgeable about Covid-19 and were changing their habits and engaging with preventive measures. Results further suggest that students were prepared for the pandemic in terms of resources and were exhibiting high-risk perceptions. The data also revealed that students who were being cautious and engaging with preventive behaviors had a higher risk-perception than individuals who were not. As for individuals who were prepared for the pandemic in terms of supplies, their risk perception was similar to those who did not have supplies. Individuals who were prepared and capable of providing a single caretaker to tend to their sick household members and isolate them in a separate room had a higher risk perception than those who could not. These results can help describe how college students will react to a future significant event, what resources students may be in need of, and how universities can take additional steps to keep their students safe and healthy. The results from this study and recommendations will provide for a stronger and more understanding campus community during times of distress and can improve upon already established university protocols for health crises and even natural disasters.

ContributorsNaqvi, Avina Itrat (Co-author) / Shaikh, Sara (Co-author) / Jehn, Megan (Thesis director) / Adams, Marc (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05