Matching Items (102)
Description
Fluoroquinolone antibiotics have been known to cause severe, multisystem adverse side effects, termed fluoroquinolone toxicity (FQT). This toxicity syndrome can present with adverse effects that vary from individual to individual, including effects on the musculoskeletal and nervous systems, among others. The mechanism behind FQT in mammals is not known, although various possibilities have been investigated. Among the hypothesized FQT mechanisms, those that could potentially explain multisystem toxicity include off-target mammalian topoisomerase interactions, increased production of reactive oxygen species, oxidative stress, and oxidative damage, as well as metal chelating properties of FQs. This review presents relevant information on fluoroquinolone antibiotics and FQT and explores the mechanisms that have been proposed. A fluoroquinolone-induced increase in reactive oxygen species and subsequent oxidative stress and damage presents the strongest evidence to explain this multisystem toxicity syndrome. Understanding the mechanism of FQT in mammals is important to aid in the prevention and treatment of this condition.
ContributorsHall, Brooke Ashlyn (Author) / Redding, Kevin (Thesis director) / Wideman, Jeremy (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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
Accumulating evidence implicates exposure to adverse childhood experiences in the development of hypocortisolism in the long-term, and researchers are increasingly examining individual-level mechanisms that may underlie, exacerbate or attenuate this relation among at-risk populations. The current study takes a developmentally and theoretically informed approach to examining episodic childhood stressors, inherent and voluntary self-regulation, and physiological reactivity among a longitudinal sample of youth who experienced parental divorce. Participants were drawn from a larger randomized controlled trial of a preventive intervention for children of divorce between the ages of 9 and 12. The current sample included 159 young adults (mean age = 25.5 years; 53% male; 94% Caucasian) who participated in six waves of data collection, including a 15-year follow-up study. Participants reported on exposure to negative life events (four times over a 9-month period) during childhood, and mothers rated child temperament. Six years later, youth reported on the use of active and avoidant coping strategies, and 15 years later, they participated in a standardized psychosocial stress task and provided salivary cortisol samples prior to and following the task. Path analyses within a structural equation framework revealed that a multiple mediation model best fit the data. It was found that children with better mother-rated self-regulation (i.e. low impulsivity, low negative emotionality, and high attentional focus) exhibited lower total cortisol output 15 years later. In addition, greater self-regulation in childhood predicted greater use of active coping in adolescence, whereas a greater number of negative life events predicted increased use of avoidant coping in adolescence. Finally, a greater number of negative events in childhood predicted marginally lower total cortisol output, and higher levels of active coping in adolescence were associated with greater total cortisol output in young adulthood. Findings suggest that children of divorce who exhibit better self-regulation evidence lower cortisol output during a standardized psychosocial stress task relative to those who have higher impulsivity, lower attentional focus, and/or higher negative emotionality. The conceptual significance of the current findings, including the lack of evidence for hypothesized relations, methodological issues that arose, and issues in need of future research are discussed.
ContributorsHagan, Melissa (Author) / Luecken, Linda (Thesis advisor) / MacKinnon, David (Committee member) / Wolchik, Sharlene (Committee member) / Doane, Leah (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
In order to analyze data from an instrument administered at multiple time points it is a common practice to form composites of the items at each wave and to fit a longitudinal model to the composites. The advantage of using composites of items is that smaller sample sizes are required in contrast to second order models that include the measurement and the structural relationships among the variables. However, the use of composites assumes that longitudinal measurement invariance holds; that is, it is assumed that that the relationships among the items and the latent variables remain constant over time. Previous studies conducted on latent growth models (LGM) have shown that when longitudinal metric invariance is violated, the parameter estimates are biased and that mistaken conclusions about growth can be made. The purpose of the current study was to examine the impact of non-invariant loadings and non-invariant intercepts on two longitudinal models: the LGM and the autoregressive quasi-simplex model (AR quasi-simplex). A second purpose was to determine if there are conditions in which researchers can reach adequate conclusions about stability and growth even in the presence of violations of invariance. A Monte Carlo simulation study was conducted to achieve the purposes. The method consisted of generating items under a linear curve of factors model (COFM) or under the AR quasi-simplex. Composites of the items were formed at each time point and analyzed with a linear LGM or an AR quasi-simplex model. The results showed that AR quasi-simplex model yielded biased path coefficients only in the conditions with large violations of invariance. The fit of the AR quasi-simplex was not affected by violations of invariance. In general, the growth parameter estimates of the LGM were biased under violations of invariance. Further, in the presence of non-invariant loadings the rejection rates of the hypothesis of linear growth increased as the proportion of non-invariant items and as the magnitude of violations of invariance increased. A discussion of the results and limitations of the study are provided as well as general recommendations.
ContributorsOlivera-Aguilar, Margarita (Author) / Millsap, Roger E. (Thesis advisor) / Levy, Roy (Committee member) / MacKinnon, David (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Research shows that general parenting practices (e.g., support and discipline), influence adolescent substance use. However, socialization theory suggests that parental socialization occurs not only through general parenting practices, but also through parents' attempts to influence specific behaviors and values. A growing literature supports links between substance-specific parenting and adolescent substance use. For adolescent alcohol use, there are considerable limitations and gaps within this literature. To address these limitations, the present study examined the factor structure of alcohol-specific parenting, investigated the determinants of alcohol-specific parenting, and explored its association with nondrinking adolescents' attitudes about alcohol use. Using a high-risk sample of nondrinking adolescents and their parents, the current study found three dimensions of alcohol-specific parenting using both adolescent and parent reports, but also found evidence of non-invariance across reporters. Results also revealed complex roles of parental alcohol use disorder (AUD; including recovered and current AUD), family history of AUD, and current drinking as determinants of the three dimensions of anti-alcohol parenting behaviors. Moreover, the current study showed that the effects of these determinants varied by the reporter of the parenting behavior. Finally, the current study found the dimensions of alcohol-specific parenting to be unique and significant predictors of nondrinking adolescents' attitudes about alcohol, over and above general parenting practices, parent AUD, and parent current drinking. Given its demonstrated distinctness from general parenting practices, its link with adolescent alcohol attitudes, and its potential malleability, alcohol-specific parenting may be an important complement to interventions targeting parents of adolescents.
ContributorsHandley, Elizabeth D (Author) / Chassin, Laurie (Thesis advisor) / MacKinnon, David (Committee member) / Crnic, Keith (Committee member) / Sandler, Irwin (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
Bacteria play a vital role in the world ecosystem, more importantly human health and disease. The capability to differentiate and identify these microorganisms serves as an important research objective. In past years, separations-based approaches have served as a way to observe and identify bacteria based on their characteristics. Gradient insulator dielectrophoresis (g-iDEP) provides benefits in identifying serotypes of a single species with precise separation. Separation of Staphylococcus epidermidis in a single g-iDEP microchannel is conducted exploiting their electrophoretic and electrokinetic properties. The cells were captured and concentrated at gates with interacting forces within the microchannel to clearly distinguish between the two strains. These results provide support for g-iDEP serving as a separating method and, furthermore, future clinical applications.
ContributorsDavis, Paige Elizabeth (Author) / Hayes, Mark (Thesis director) / Borges, Chad (Committee member) / Jones, Paul (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor)
Created2015-05
Description
Background: High risk types of human papillomavirus (HPV) are known to cause cancer, including cervical (99%) and oropharyngeal cancer (70%). HPV type 16 is the most common subtype. Three antigens that are critical for integration or tumor progression are E2, E6 and E7. In this study, we developed a systematic approach to identify naturally-processed HPV16-derived HLA class I epitopes for immunotherapy development. Methods: K562 cells, which lack HLA expression, were transduced with each HPV16 antigen using lentivirus and supertransfected with HLA-A2 by nucleofection. Stable cell lines expressing each antigen were selected for and maintained throughout the investigation. In order to establish a Gateway-compatible vector for robust transient gene expression, a Gateway recombination expression cloning cassette was inserted into the commercial Lonza pMAX GFP backbone, which has been experimentally shown to display high transfection expression efficiency. GFP was cloned into the vector and plain K562 cells were transfected with the plasmid by nucleofection. Results: Expression of K562-A2 was tested at various time points by flow cytometry and A2 expression was confirmed. Protein expression was shown for the transduced K562 E7 by Western blot analysis. High transfection efficiency of the pMAX_GFP_Dest vector (up to 97% GFP+ cells) was obtained 48 hours post transfection, comparable to the commercial GFP-plasmid. Conclusion: We have established a rapid system for target viral antigen co-expression with single HLA molecules for analysis of antigen presentation. Using HPV as a model system, our goal is to identify specific antigenic peptide sequences to develop immunotherapeutic treatments for HPV-associated cancers.
ContributorsVarda, Bianca Marie (Author) / Anderson, Karen (Thesis director) / Borges, Chad (Committee member) / Krishna, Sri (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Protein AMPylation is a recently discovered and relatively unstudied post-translational modification (PTM). AMPylation has previously been shown to play an important role in metabolic regulation and host pathogenesis in bacteria, but the recent identification of potential AMPylators across many species in every domain of life has supported the possibility that AMPylation could be a more fundamental and physiologically significant regulatory PTM. For the first time, we characterized the auto-AMPylation capability of the human protein SOS1 through in vitro AMPylation experiments using full-length protein and whole-domain truncation mutants. We found that SOS1 can become AMPylated at a tyrosine residue possibly within the Cdc25 domain of the protein, the Dbl homology domain is vital for efficient auto-AMPylation activity, and the C-terminal proline-rich domain exhibits a complex regulatory function. The proline-rich domain alone also appears to be capable of catalyzing a separate, unidentified covalent self-modification using a fluorescent ATP analogue. Finally, SOS1 was shown to be capable of catalyzing the AMPylation of two endogenous human protein substrates: a ubiquitous, unidentified protein of ~49kDa and another breast-cancer specific, unidentified protein of ~28kDa.
ContributorsOber-Reynolds, Benjamin John (Author) / LaBaer, Joshua (Thesis director) / Borges, Chad (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2014-05