Matching Items (49)
Description
Blood donations today undergo extensive screening for transfusion transmitted infections (TTI) since the discovery of the first infectious agent in the early 1900s. Nucleic Acid Testing (NAT) is a serological test used widely in disease detection. NAT is known to rapidly and effectively detect pathogenic genomic material in blood by reducing the "window period" of infection. However, NAT produces false negative results for disease positive samples posing a risk of disease transmission. Therefore, NAT is used in conjunction with the Enzyme-Linked Immunosorbent Assay (ELISA) to mitigate these risks. However, the ELISA assay also poses the same risk as NAT. This study proposes immunosignaturing as an alternative serological test that may combat this risk and investigates whether it would be more effective than other standardized serological tests in disease detection. Immunosignaturing detects antibodies by utilizing a microarray of randomized peptide sequences. Immunosignaturing provides information about an individual's immune health from the pattern of reactivity of antibody-peptide binding. Unlike ELISA and NAT, immunosignaturing can be programmed to detect any disease and detect multiple diseases simultaneously. Using ELISA, NAT, and immunosignaturing, immune profiles of asymptomatic patients were constructed for 10 different classes of blood borne diseases. A pattern of infection was identified for each disease and the sensitivity and specificity of these assays were assessed relative to each other. Results indicate that immunosignaturing can be a viable diagnostic tool in blood testing. Immunosignatures demonstrated increased sensitivity and specificity compared to ELISA and NAT in discerning disease positive and negative samples within and across different classes of disease.
ContributorsSharma, Megumi (Author) / McFadden, Grant (Thesis director) / Nickerson, Cheryl (Committee member) / Green, Alex (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Mycobacterial infections, as represented by leprosy and tuberculosis, have persisted as human pathogens for millennia. Their environmental counterparts, nontuberculous mycobacteria (NTM), are commodious infectious agents endowed with extensive innate and acquired antimicrobial resistance. The current drug development process selects for antibiotics with high specificity for definitive targets within bacterial metabolic and replication pathways. Because these compounds demonstrate limited efficacy against mycobacteria, novel antimycobacterial agents with unconventional mechanisms of action were identified. Two highly resistant NTMs, Mycobacterium abscessus (Mabs) a rapid-growing respiratory, skin, and soft tissue pathogen, and Mycobacterium ulcerans (MU), the causative agent of Buruli ulcer, were selected as targets. Compounds that indicated antimicrobial activity against other highly resistant pathogens were selected for initial screening. Antimicrobial peptides (AMPs) have demonstrated activity against a variety of bacterial pathogens, including mycobacterial species. Designed antimicrobial peptides (dAMPs), rationally-designed and synthetic contingents, combine iterative features of natural AMPs to achieve superior antimicrobial activity in resistant pathogens. Initial screening identified two dAMPs, RP554 and RP557, with bactericidal activity against Mabs. Clay-associated ions have previously demonstrated bactericidal activity against MU. Synthetic and customizable aluminosilicates have also demonstrated adsorption of bacterial cells and toxins. On this basis, two aluminosilicate materials, geopolymers (GP) and ion-exchange nanozeolites (IE-nZeos), were screened for antimicrobial activity against MU and its fast-growing relative, Mycobacterium marinum (Mmar). GPs demonstrated adsorption of MU cells and mycolactone, a secreted, lipophilic toxin, whereas Cu-nZeos and Ag-nZeos demonstrated antibacterial activity against MU and Mmar. Cumulatively, these results indicate that an integrative drug selection process may yield a new generation of antimycobacterial agents.
ContributorsDermody, Roslyn June (Author) / Haydel, Shelley E (Thesis advisor) / Bean, Heather (Committee member) / Nickerson, Cheryl (Committee member) / Stephanopoulos, Nicholas (Committee member) / Arizona State University (Publisher)
Created2022
Description
Psychologists report effect sizes in randomized controlled trials to facilitate interpretation and inform clinical or policy guidance. Since commonly used effect size measures (e.g., standardized mean difference) are not sensitive to heterogeneous treatment effects, methodologists have suggested the use of an alternative effect size δ, a between-subjects causal parameter describing the probability that the outcome of a random participant in the treatment group is better than the outcome of another random participant in the control group. Although this effect size is useful, researchers could mistakenly use δ to describe its within-subject analogue, ψ, the probability that an individual will do better under the treatment than the control. Hand’s paradox describes the situation where ψ and δ are on opposing sides of 0.5: δ may imply most are helped whereas the (unknown) underlying ψ indicates that most are harmed by the treatment. The current study used Monte Carlo simulations to investigate plausible situations under which Hand’s paradox does and does not occur, tracked the magnitude of the discrepancy between ψ and δ, and explored whether the size of the discrepancy could be reduced with a relevant covariate. The findings suggested that although the paradox should not occur under bivariate normal data conditions in the population, there could be sample cases with the paradox. The magnitude of the discrepancy between ψ and δ depended on both the size of the average treatment effect and the underlying correlation between the potential outcomes, ρ. Smaller effects led to larger discrepancies when ρ < 0 and ρ = 1, whereas larger effects led to larger discrepancies when 0 < ρ < 1. It was useful to consider a relevant covariate when calculating ψ and δ. Although ψ and δ were still discrepant within covariate levels, results indicated that conditioning upon relevant covariates is still useful in describing heterogeneous treatment effects.
ContributorsLiu, Xinran (Author) / Anderson, Samantha F (Thesis advisor) / McNeish, Daniel (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2023
Description
Mycobacterium tuberculosis (Mtb), the etiological agent of the tuberculosis disease, is estimated to infect one-fourth of the human population and is responsible for 1.5 million deaths annually. The increased emergence of bacterial resistance to clinical interventions highlights the lack in development of novel antimicrobial therapeutics. Prototypical bacterial two-component systems (TCS) allow for sensing of extracellular stimuli and relay thereof to create a transcriptional response. The prrAB TCS is essential for viability in Mtb, presenting itself as an attractive novel drug target. In Mtb, PrrAB is involved in the adaptation to the intra-macrophage environment and recent work implicates PrrAB in the dosR-dependent hypoxia adaptation. This work defines a direct molecular and regulatory connection between Mtb PrrAB and the dosR-dependent hypoxia response. Using electrophoretic mobility shift assays combined with surface plasmon resonance, the Mtb dosR gene is established as a specific target of PrrA, corroborated by fluorescence reporter assays demonstrating a regulatory relationship. Considering the scarce understanding of prrAB essentiality in nontuberculous mycobacteria and the presence of multiple prrAB orthologs in Mycobacterium smegmatis and Mycobacterium abscessus, CRISPR interference was utilized to evaluate the essentiality of PrrAB beyond Mtb. prrAB was found to be inessential for viability in M. smegmatis yet required for in vitro growth. Conversely, M. abscessus prrAB repression led to enhanced in vitro growth. Diarylthiazole-48 (DAT-48) displayed decreased selectivity against M. abscessus but demonstrated enhanced intrinsic activity upon prrAB repression in M. abscessus. Lastly, to aid in the rapid determination of mycobacterial drug susceptibility and the detection of mycobacterial heteroresistance, the large volume scattering imaging (LVSim) platform was adapted for mycobacteria. Using LVSim, Mtb drug susceptibility was detected phenotypically within 6 hours, and clinically relevant mycobacterial heteroresistance was detected phenotypically within 10 generations. The data generated in these studies provide insight into the essential role of PrrAB in Mtb and its involvement in the dosR-dependent hypoxia adaptation, advance the understanding of mycobacterial PrrAB essentiality and PrrAB-associated mycobacterial growth dependency. These studies further establish molecular and mechanistic connection between PrrAB and DAT-48 in Mtb and M. abscessus and develop a rapid phenotypic drug susceptibility testing platform for mycobacteria.
ContributorsHaller, Yannik Alex (Author) / Haydel, Shelley E (Thesis advisor) / Bean, Heather (Committee member) / Nickerson, Cheryl (Committee member) / Plaisier, Christopher (Committee member) / Acharya, Abhinav (Committee member) / Arizona State University (Publisher)
Created2023
Description
Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers can employ diverse strategies when studying individual differences in multiple mediation pathways, including individual fit measures and analysis of residuals. This dissertation investigates the use of individual residuals and fit measures to identify individual differences in multiple mediation pathways. More specifically, this study focuses on mediation model residuals in a heterogeneous population in which some people experience indirect effects through one mediator and others experience indirect effects through a different mediator. A simulation study investigates 162 conditions defined by effect size and sample size for three proposed methods: residual differences, delta z, and generalized Cook’s distance. Results indicate that analogs of Type 1 error rates are generally acceptable for the method of residual differences, but statistical power is limited. Likewise, neither delta z nor gCd could reliably distinguish between contrasts that had true effects and those that did not. The outcomes of this study reveal the potential for statistical measures of individual mediation. However, limitations related to unequal subpopulation variances, multiple dependent variables, the inherent relationship between direct effects and unestimated indirect effects, and minimal contrast effects require more research to develop a simple method that researchers can use on single data sets.
ContributorsSmyth, Heather Lynn (Author) / MacKinnon, David (Thesis advisor) / Tein, Jenn-Yun (Committee member) / McNeish, Daniel (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2022
Description
One of the identified health risk areas for human spaceflight is infectious disease, particularly involving environmental microorganisms already found on the International Space Station (ISS). In particular, bacteria belonging to the Burkholderia cepacia complex (Bcc) which can cause human disease in those who are immunocompromised, have been identified in the ISS water supply. This present study characterized the effect of spaceflight analog culture conditions on Bcc to certain physiological stresses (acid and thermal as well as intracellular survival in U927 human macrophage cells). The NASA-designed Rotating Wall Vessel (RWV) bioreactor was used as the spaceflight analogue culture system in these studies to grow Bcc bacterial cells under Low Shear Modeled Microgravity (LSMMG) conditions. Results show that LSMMG culture increased the resistance of Bcc to both acid and thermal stressors, but did not alter phagocytic uptake in 2-D monolayers of human monocytes.
ContributorsVu, Christian-Alexander (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05
Description
Food insecurity is an economic and social condition involving limited or uncertain access to food. The problem of food insecurity in communities is influenced by economic conditions, food deserts, and barriers to accessing healthy food. Individuals experiencing food insecurity often endure concurrent problems of financial instability, hunger, and poor mental and physical health. Public and non-profit services in the U.S., such as the federally supported Supplemental Nutrition Assistance Program (SNAP) and community food banks, provide food-related assistance to individuals who are at a high risk of experiencing food insecurity. Unfortunately, many individuals who qualify for these services still experience food insecurity due to barriers preventing them from accessing food, which may include inadequate finances, transportation, skills, and information. Effective approaches for removing barriers that prevent individuals from accessing food are needed to mitigate the increased risk of hunger, nutritional deficiencies, and chronic disease among vulnerable populations. This dissertation tested a novel food insecurity intervention using informational nudges to promote food security through the elimination of information barriers to accessing food. The intervention used in this mixed-methods feasibility study consisted of informational nudges in the form of weekly text messages that were sent to food pantry clients experiencing food insecurity. The study aims were to test the efficacy and acceptability of the intervention by examining whether the informational nudges could enhance food pantry utilization, increase SNAP registration, and promote food security. Quantitative study results showed a lower prevalence of food insecurity in the intervention group than the control group. Qualitative findings revealed how the intervention group found the text messages to be helpful and informative. These study findings can enhance future food insecurity interventions aiming to eliminate barriers that prevent individuals who are food insecure from accessing healthy food.
ContributorsRoyer, Michael F. (Author) / Wharton, Christopher (Thesis advisor) / Buman, Matthew (Committee member) / Der Ananian, Cheryl (Committee member) / MacKinnon, David (Committee member) / Ohri-Vachaspati, Punam (Committee member) / Arizona State University (Publisher)
Created2023
Description
Longitudinal recursive partitioning (LRP) is a tree-based method for longitudinal data. It takes a sample of individuals that were each measured repeatedly across time, and it splits them based on a set of covariates such that individuals with similar trajectories become grouped together into nodes. LRP does this by fitting a mixed-effects model to each node every time that it becomes partitioned and extracting the deviance, which is the measure of node purity. LRP is implemented using the classification and regression tree algorithm, which suffers from a variable selection bias and does not guarantee reaching a global optimum. Additionally, fitting mixed-effects models to each potential split only to extract the deviance and discard the rest of the information is a computationally intensive procedure. Therefore, in this dissertation, I address the high computational demand, variable selection bias, and local optimum solution. I propose three approximation methods that reduce the computational demand of LRP, and at the same time, allow for a straightforward extension to recursive partitioning algorithms that do not have a variable selection bias and can reach the global optimum solution. In the three proposed approximations, a mixed-effects model is fit to the full data, and the growth curve coefficients for each individual are extracted. Then, (1) a principal component analysis is fit to the set of coefficients and the principal component score is extracted for each individual, (2) a one-factor model is fit to the coefficients and the factor score is extracted, or (3) the coefficients are summed. The three methods result in each individual having a single score that represents the growth curve trajectory. Therefore, now that the outcome is a single score for each individual, any tree-based method may be used for partitioning the data and group the individuals together. Once the individuals are assigned to their final nodes, a mixed-effects model is fit to each terminal node with the individuals belonging to it.
I conduct a simulation study, where I show that the approximation methods achieve the goals proposed while maintaining a similar level of out-of-sample prediction accuracy as LRP. I then illustrate and compare the methods using an applied data.
I conduct a simulation study, where I show that the approximation methods achieve the goals proposed while maintaining a similar level of out-of-sample prediction accuracy as LRP. I then illustrate and compare the methods using an applied data.
ContributorsStegmann, Gabriela (Author) / Grimm, Kevin (Thesis advisor) / Edwards, Michael (Committee member) / MacKinnon, David (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
There is a need to reinvent evidence-based interventions (EBIs) for pediatric anxiety problems to better address the demands of real-word service delivery settings and achieve public health impact. The time- and resource-intensive nature of most EBIs for youth anxiety has frequently been noted as a barrier to the utilization of EBIs in community settings, leading to increased attention towards exploring the viability of briefer, more accessible protocols. Principally, this research reports between-group effect sizes from brief-interventions targeting pediatric anxiety and classifies each as well-established, probably efficacious, possibly efficacious, experimental, or questionable. brief interventions yielded an overall mean effect size of 0.19 on pediatric anxiety outcomes from pre to post. Effect sizes varied significantly by level of intervention: Pre to post-intervention effects were strongest for brief-treatments (0.35), followed by brief-targeted prevention (0.22), and weakest for brief-universal prevention (0.09). No participant or other intervention characteristic emerged as significant moderators of effect sizes. In terms of standard of evidence, one brief intervention is well-established, and five are probably efficacious, with most drawing on cognitive and behavioral change procedures and/or family systems models. At this juncture, the minimal intervention needed for clinical change in pediatric anxiety points to in-vivo exposures for specific phobias (~3 hours), cognitive-behavioral therapy (CBT) with social skills training (~3 hours), and CBT based parent training (~6 hours, eight digital modules with clinician support). This research concludes with a discussion on limitations to available brief EBIs, practice guidelines, and future research needed to capitalize on the viability of briefer protocols in enhancing access to, and impact of, evidence-based care in the real-world.
ContributorsStoll, Ryan (Author) / Pina, Armando A. (Thesis advisor) / Gonzales, Nancy (Committee member) / MacKinnon, David (Committee member) / Perez, Marisol (Committee member) / Arizona State University (Publisher)
Created2019
Description
Positive alcohol outcome expectancies (AOEs) are consistent longitudinal predictors of later alcohol use; however, exclusion of solitary drinking contexts in the measurement of AOEs may have resulted in an underestimation of the importance of low arousal positive (LAP) effects. The current study aimed to clarify the literature on the association between AOEs and drinking outcomes by examining the role of drinking context in AOE measurement. Further, exclusion of contextual influences has also limited understanding of the unique effects of AOEs relative to subjective responses (SR) to alcohol. The present study addressed this important question by exploring relations between AOEs and SR when drinking context was held constant across parallel measures of these constructs. Understanding which of these factors drives relations between alcohol effects and drinking behavior has important implications for intervention. After conducting confirmatory factor analysis (CFA) and tests of measurement invariance for the AOE and SR measures, 4 aims collectively examined the role of context in reporting of AOEs (Aims 1 and 2), the extent to which context specific AOEs uniquely relate to drinking outcomes (Aim 3), and the importance of context effects on correspondence between AOEs and SR (Aim 4). Results of Aims 1 and 2 demonstrated that participants are imagining contexts when reporting on measures of AOEs that do not specify the context, and found significant mean differences in high and low arousal positive AOEs across contexts. Contrary to the hypotheses of Aim 3, context-specific AOEs were not significantly associated with drinking behavior. Results of Aim 4 indicated that while LAP AOEs for both unspecified and solitary contexts were associated with LAP SR in a solitary setting, unspecified context AOEs had a stronger relation than the solitary context AOEs. No significant relations between high arousal positive (HAP) AOEs and HAP SR emerged. The findings suggest that further investigation of the relation between context-specific AOEs and drinking outcomes/SR is warranted. Future studies of these hypotheses in samples with a wider range of drinking behavior, or at different stages of alcohol involvement, will elucidate whether mean level differences in context specific AOEs are important in understanding alcohol related outcomes.
ContributorsScott, Caitlin (Author) / Corbin, William (Thesis advisor) / MacKinnon, David (Committee member) / Barrera, Manuel (Committee member) / Chassin, Laurie (Committee member) / Arizona State University (Publisher)
Created2016