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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
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
Breast cancer is one of the leading causes of cancer-related deaths among women in the United States. Uninsured women are less likely to receive breast cancer screenings, more likely to be diagnosed at an advanced stage, and more likely to have poorer outcomes following a breast cancer diagnosis (Abdelsattar et al., 2016; Akinlotan et al., 2021; Ko et al., 2020; & Ntiri et al., 2018). Women in underserved communities often experience socioeconomic barriers which impact obtaining preventative screenings, such as mammograms. Lack of patient navigation, transportation, and financial concerns interfere with obtaining breast cancer screening (Akinlotan et al., 2021 & Miller et al., 2019). Through the intervention of mobile mammography, uninsured women in underserved communities can be reached and access to screening mammograms can be achieved (Stanley et al., 2017 & Vang et al., 2018). Two mobile mammography events were hosted at the project site which provided 35 women with screening mammograms. All scheduled mammogram time slots at the events were filled and completed. Offering mobile mammography to this population has the potential to increase breast cancer surveillance.
ContributorsGlessner-Vallee, Paula (Author) / Santerre, Jennifer (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-26
Description
Introduction: The objective of this study is to emphasize the significance of exclusive breastfeeding (EB) and investigate methods to encourage and sustain it within a hospital environment. Using the self-efficacy theory, the study seeks to improve the current support system for breastfeeding mothers and their families. Methods: The project was approved by the university IRB and facility IRB; guidelines were maintained. The project takes place in a non-profit organization in the southwestern United States. Education was conducted at a required staff meeting for Women and Infant Services (WIS) floor about supporting breastfeeding mothers. A pre- and post-education Breastfeeding Knowledge Scale (BKS) survey was performed, effectiveness was measured using a two-tailed t-test. The reliability of the BKS scale is 0.83 and the validity of the scale is reported to be strong. The hospital measures the EB rates of patients that are greater than 37 weeks gestation without need for neonatal intensive unit care and the mom requests to breastfeed. Results: The goal was 42% rate of EB in the first 48 hours after birth. After education the average rate of EB was 39.6%, lower than the goal but higher than the 33.7% rate before education. A two-tailed paired sample t-test (n=27) was used for BKS and the results were significant based on an alpha value; thus, showing significant knowledge gain. Conclusion: Consistent staff education improves breastfeeding support for moms in the hospital, leading to successful exclusive breastfeeding. This project benefits various settings, such as pediatric, postpartum, labor and delivery, and pediatric offices.
ContributorsHudson, Jennifer (Author) / Esperas, Amanda (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-26
Description
Introduction: Depression screening in the pediatric setting is a crucial part of the adolescent's examination. A standardized screening tool and protocol streamlines the process of assessing adolescents and minimizes the chances of serious mental health disorders going undetected and untreated. Evaluation of current evidence demonstrates the use of a standardized tool improves detection, diagnosis, and management of depression and other mental health illnesses.
Method: The Patient Health Questionnaire—modified for adolescents (PHQ9-A) was administered to all eligible adolescents, ages 12-18, during an annual well visit for a period of 6 weeks. Lewin's Change Theory guided a system change in the electronic health record, and the questionnaire results were documented and provided to the pediatric provider at the time of the appointment. A chart review was conducted to determine whether all eligible patients were administered the questionnaire and if a depression diagnosis or mental health referral had been made.
Results: Out of 76 eligible well visits, 65 (86%) patients completed the PHQ9-A. The average score was 5.29 (SD = 6.49) with a maximum score of 25. Out of those that completed screening, 11 (17%) had a positive PHQ9-A score resulting in 8 referrals to mental health services and 2 mental health diagnoses in the clinic.
ContributorsCoomer, Meagan (Author) / Rauton, Monica (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-27
Description
Background: There is growing evidence that persistent exposure to the adverse effects of stressful work conditions, abuse, and re-traumatization without proper intervention leads to compassion fatigue (CF) and reduced compassion satisfaction (CS). Without appropriate intervention, the outcome of CF affects the patient, staff, and the organization. Despite proposed self-care measures, mental health (MH) workers continue to struggle with CF and lack the resources to combat the issue.
Objectives: Ongoing awareness on the implications of trauma and its impact on one's behavior, supports the use of Trauma-informed care (TIC) skills in creating a conducive work environment. This quality improvement project examines the efficacy of TIC education as an intervention for CF pre/post-one-hour education session among MH workers.
Methods: MH nurses (n=8) from diverse backgrounds in a Phoenix inpatient psychiatric hospital gave consent for the study. Participation was sought via flyers and entailed attending the one-hour education session, filling out a demographic, and pre/post-professional quality of life (ProQol) surveys. The ProQol standardized tool measures CF, CS, and burnout with reliability >0.70. Expected outcomes include a reduction in CF and an improvement in CS. Data analysis using intellectus software involved descriptive analysis and paired t-tests to compare outcomes.
Results: Pre/post data analysis was statistically significant, P = 0.003, which shows a reduction in CF and an improvement in CS.
Conclusion: TIC as an intervention for CF looks promising. MH nurses can manage their stress symptoms and that of their patients using TIC skills.
ContributorsOnyia, Nneka (Author) / Guthery, Ann (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-29
Description
Substance use disorder has been increasing in the United States year after year. Modern treatments fail as often as they succeed. The current standards of practice fail to provide patients with the ability to harness thoughts and control anxiety. Mindfulness practices are currently being adapted as a therapeutic technique to address some of these concerns. An exhaustive literature review was conducted to investigate how various mindfulness techniques impact substance use disorder. Ten high-quality studies were retained and synthesized to show current understandings of the effectiveness of a mindfulness therapeutic technique. An evidence-based intervention is suggested for implementing mindfulness-based relapse prevention into a residential treatment facility. The intervention created incorporates the self-efficacy theory and an adapted health-belief model. Adults in a residential treatment facility for substance use disorder were given eight mindfulness sessions over the course of four weeks. Participants were given pre- and post-intervention screenings for mindful attention and anxiety. The data analysis after two-tailed paired T-tests showed that anxiety significantly decreased (α=.05, p<.001) and mindful attention increased significantly (α=.05, p=.015). Overall, mindfulness shows promise in its potential to reduce substance abuse.
ContributorsWandler, Ryan (Author) / Nunez, Diane (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-27
Description
An alarming number of youth have mental health concerns, but of those who are diagnosed, only half receive treatment. Using Bandera's social cognitive theory, one can achieve behavioral changes through self-efficacy and control their actions by self-regulation. Mindfulness activities, when implemented early, can decrease stress, and improve well-being in youth.
Methods:
This project was implemented among students attending an alternative high school in Arizona. Nine students participated in four different mindfulness, hands-on activities during two classes- 1 hour each. Participants completed a pre and a post-test with the 10-item questionnaire Perceived Stress Scale (PSS), and a 3-question survey to evaluate the program at the end of the second week.
Results: Among the 9 participants (mean age = 16 SD=2.06), the stress levels were considered low to moderate in the pretest (mean=16.56) and the post-test (mean=15.89). Stress level scores were reduced after the education although the difference was not statistically significant. Furthermore, all participants agreed that the content and activities were appropriate, 88.9% agreed they had a "better understanding of how to reduce stress," and 77.8% stated their "knowledge of stress has improved."
Discussion/Conclusion:
This project aimed to help reduce vulnerable adolescents' stress level through mindfulness activities. Mental health education like this may help adolescents better manage stress and consequently promote their overall well-being. Future projects should recruit a larger sample and implement a longer time for larger and longer effects.
ContributorsQualman, Stephanie (Author) / Chen, Angela (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-05-10
Description
Mental health challenges are becoming a significant public health issue for adolescents/teenagers, and primary interventions have been focused on mental health education. Because adolescents spend most of their time in school, primary mental health interventions should be prioritized in this setting. A PICOT question was developed to determine if mental health literacy (MHL) in adolescents would improve while decreasing stigma and improving help-seeking behaviors after a program of enhanced mental health education. Partnering with a large Arizona suburban school district social work department, a teen Mental Health First Aid (tMHFA) pilot program was implemented for a class of nine (n = 9) adolescent students (aged 17-18 years) old during the school day. tMHFA was delivered in three 90-minute class days. Using the Mental Health Literacy questionnaire (MHLq), a pre and post-test design revealed a significant (p value=less than 0.05) increase in the students' MHL, help-seeking behaviors, and decreased stigma after delivery. This quality improvement project was IRB approved, and all human subjects' rights were protected. In conclusion, there is strong evidence that enhanced mental health programming, such as tMHFA, effectively educates adolescents about mental health challenges and, perhaps, could promote behavioral changes in future generations.
ContributorsJones, M. Christina (Author) / Schiller, Zita (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-05-15