Matching Items (110)
Description
Under the direction of Dr. Carolyn Compton, a group of seven Barrett honors students have embarked on a truly unique team thesis project to create a documentary on the process of creating a COVID-19 testing laboratory. This documentary tells the story of the ASU Biodesign Clinical Testing Laboratory (ABCTL), the first lab in the western United States to offer public saliva testing to identify the presence of COVID-19.
ContributorsCura, Joriel (Director, Photographer) / Foote, Hannah (Producer, Sound designer) / Raymond, Julia (Production personnel) / Bardfeld, Sierra (Narrator, Editor) / Dholaria, Nikhil (Writer of added commentary) / Liu, Tara (Writer of added commentary) / Varghese, Mahima (Writer of added commentary) / Compton, Carolyn C. (Interviewee, Project director) / Harris, Valerie (Interviewee) / LaBaer, Joshua (Interviewee) / Miceli, Joseph (Interviewee) / Nelson, Megan (Interviewee) / Ungaro, Brianna (Interviewee)
Created2021
Description
Signal transduction networks comprising protein-protein interactions (PPIs) mediate homeostatic, diseased, and therapeutic cellular responses. Mapping these networks has primarily focused on identifying interactors, but less is known about the interaction affinity, rates of interaction or their regulation. To better understand the extent of the annotated human interactome, I first examined > 2500 protein interactions within the B cell receptor (BCR) signaling pathway using a current, cutting-edge bioluminescence-based platform called “NanoBRET” that is capable of analyzing transient and stable interactions in high throughput. Eighty-three percent (83%) of the detected interactions have not been previously reported, indicating that much of the BCR pathway is still unexplored. Unfortunately, NanoBRET, as with all other high throughput methods, cannot determine binding kinetics or affinities. To address this shortcoming, I developed a hybrid platform that characterizes > 400 PPIs quantitatively and simultaneously in < 1 hour by combining the high throughput and flexible nature of nucleic programmable protein arrays (NAPPA) with the quantitative abilities of surface plasmon resonance imaging (SPRi). NAPPA-SPRi was then used to study the kinetics and affinities of > 12,000 PPIs in the BCR signaling pathway, revealing unique kinetic mechanisms that are employed by proteins, phosphorylation and activation states to regulate PPIs. In one example, activation of the GTPase RAC1 with nonhydrolyzable GTP-γS minimally affected its binding affinities with phosphorylated proteins but increased, on average, its on- and off-rates by 4 orders of magnitude for one-third of its interactions. In contrast, this phenomenon occurred with virtually all unphosphorylated proteins. The majority of the interactions (85%) were novel, sharing 40% of the same interactions as NanoBRET as well as detecting 55% more interactions than NanoBRET. In addition, I further validated four novel interactions identified by NAPPA-SPRi using SDS-PAGE migration and Western blot analyses. In one case, we have the first evidence of a direct enzyme-substrate interaction between two well-known proto-oncogenes that are abnormally regulated in > 30% of cancers, PI3K and MYC. Herein, PI3K is demonstrated to phosphorylate MYC at serine 62, a phosphosite that increases the stability of MYC. This study provides valuable insight into how PPIs, phosphorylation, and GTPase activation regulate the BCR signal transduction pathway. In addition, these methods could be applied toward understanding other signaling pathways, pathogen-host interactions, and the effect of protein mutations on protein interactions.
ContributorsPetritis, Brianne Ogata (Author) / LaBaer, Joshua (Thesis advisor) / Lake, Douglas (Committee member) / Wang, Shaopeng (Committee member) / Arizona State University (Publisher)
Created2018
Description
According to the World Health Organization, cancer is one of the leading causes of death around the world. Although early diagnostics using biomarkers and improved treatments with targeted therapy have reduced the rate of cancer related mortalities, there remain many unknowns regarding the contributions of the tumor microenvironment to cancer progression and therapeutic resistance. The tumor microenvironment plays a significant role by manipulating the progression of cancer cells through biochemical and biophysical signals from the surrounding stromal cells along with the extracellular matrix. As such, there is a critical need to understand how the tumor microenvironment influences the molecular mechanisms underlying cancer metastasis to facilitate the discovery of better therapies. This thesis described the development of microfluidic technologies to study the interplay of cancer cells with their surrounding microenvironment. The microfluidic model was used to assess how exposure to chemoattractant, epidermal growth factor (EGF), impacted 3D breast cancer cell invasion and enhanced cell motility speed was noted in the presence of EGF validating physiological cell behavior. Additionally, breast cancer and patient-derived cancer-associated fibroblast (CAF) cells were co-cultured to study cell-cell crosstalk and how it affected cancer invasion. GPNMB was identified as a novel gene of interest and it was shown that CAFs enhanced breast cancer invasion by up-regulating the expression of GPNMB on breast cancer cells resulting in increased migration speed. Lastly, this thesis described the design, biological validation, and use of this microfluidic platform as a new in vitro 3D organotypic model to study mechanisms of glioma stem cell (GSC) invasion in the context of a vascular niche. It was confirmed that CXCL12-CXCR4 signaling is involved in promoting GSC invasion in a 3D vascular microenvironment, while also demonstrating the effectiveness of the microfluidic as a drug screening assay. Taken together, the broader impacts of the microfluidic model developed in this dissertation include, a possible alternative platform to animal testing that is focused on mimicking human physiology, a potential ex vivo platform using patient-derived cells for studying the interplay of cancer cells with its surrounding microenvironment, and development of future therapeutic strategies tailored toward disrupting key molecular pathways involved in regulatory mechanisms of cancer invasion.
ContributorsTruong, Danh, Ph.D (Author) / Nikkhah, Mehdi (Thesis advisor) / LaBaer, Joshua (Committee member) / Smith, Barbara (Committee member) / Mouneimne, Ghassan (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2018
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
Multicellular organisms use precise gene regulation, executed throughout development, to build and sustain various cell and tissue types. Post-transcriptional gene regulation is essential for metazoan development and acts on mRNA to determine its localization, stability, and translation. MicroRNAs (miRNAs) and RNA binding proteins (RBPs) are the principal effectors of post-transcriptional gene regulation and act by targeting the 3'untranslated regions (3'UTRs) of mRNA. MiRNAs are small non-coding RNAs that have the potential to regulate hundreds to thousands of genes and are dysregulated in many prevalent human diseases such as diabetes, Alzheimer's disease, Duchenne muscular dystrophy, and cancer. However, the precise contribution of miRNAs to the pathology of these diseases is not known.
MiRNA-based gene regulation occurs in a tissue-specific manner and is implemented by an interplay of poorly understood and complex mechanisms, which control both the presence of the miRNAs and their targets. As a consequence, the precise contributions of miRNAs to gene regulation are not well known. The research presented in this thesis systematically explores the targets and effects of miRNA-based gene regulation in cell lines and tissues.
I hypothesize that miRNAs have distinct tissue-specific roles that contribute to the gene expression differences seen across tissues. To address this hypothesis and expand our understanding of miRNA-based gene regulation, 1) I developed the human 3'UTRome v1, a resource for studying post-transcriptional gene regulation. Using this resource, I explored the targets of two cancer-associated miRNAs miR-221 and let-7c. I identified novel targets of both these miRNAs, which present potential mechanisms by which they contribute to cancer. 2) Identified in vivo, tissue-specific targets in the intestine and body muscle of the model organism Caenorhabditis elegans. The results from this study revealed that miRNAs regulate tissue homeostasis, and that alternative polyadenylation and miRNA expression patterns modulate miRNA targeting at the tissue-specific level. 3) Explored the functional relevance of miRNA targeting to tissue-specific gene expression, where I found that miRNAs contribute to the biogenesis of mRNAs, through alternative splicing, by regulating tissue-specific expression of splicing factors. These results expand our understanding of the mechanisms that guide miRNA targeting and its effects on tissue-specific gene expression.
MiRNA-based gene regulation occurs in a tissue-specific manner and is implemented by an interplay of poorly understood and complex mechanisms, which control both the presence of the miRNAs and their targets. As a consequence, the precise contributions of miRNAs to gene regulation are not well known. The research presented in this thesis systematically explores the targets and effects of miRNA-based gene regulation in cell lines and tissues.
I hypothesize that miRNAs have distinct tissue-specific roles that contribute to the gene expression differences seen across tissues. To address this hypothesis and expand our understanding of miRNA-based gene regulation, 1) I developed the human 3'UTRome v1, a resource for studying post-transcriptional gene regulation. Using this resource, I explored the targets of two cancer-associated miRNAs miR-221 and let-7c. I identified novel targets of both these miRNAs, which present potential mechanisms by which they contribute to cancer. 2) Identified in vivo, tissue-specific targets in the intestine and body muscle of the model organism Caenorhabditis elegans. The results from this study revealed that miRNAs regulate tissue homeostasis, and that alternative polyadenylation and miRNA expression patterns modulate miRNA targeting at the tissue-specific level. 3) Explored the functional relevance of miRNA targeting to tissue-specific gene expression, where I found that miRNAs contribute to the biogenesis of mRNAs, through alternative splicing, by regulating tissue-specific expression of splicing factors. These results expand our understanding of the mechanisms that guide miRNA targeting and its effects on tissue-specific gene expression.
ContributorsKotagama, Kasuen Indrajith Bandara (Author) / Mangone, Marco (Thesis advisor) / LaBaer, Joshua (Committee member) / Newbern, Jason (Committee member) / Rawls, Alan (Committee member) / Arizona State University (Publisher)
Created2019
Description
Biomarkers find a wide variety of applications in oncology from risk assessment to diagnosis and predicting and monitoring recurrence and response to therapy. Developing clinically useful biomarkers for cancer is faced with several challenges, including cancer heterogeneity and factors related to assay development and biomarker performance. Circulating biomarkers offer a rapid, cost-effective, and minimally-invasive window to disease and are ideal for population-based screening. Circulating immune biomarkers are stable, measurable, and can betray the underlying antigen when present below detection levels or even no longer present. This dissertation aims to investigate potential circulating immune biomarkers with applications in cancer detection and novel therapies. Over 600,000 cancers each year are attributed to the human papillomavirus (HPV), including cervical, anogenital and oropharyngeal cancers. A key challenge in understanding HPV immunobiology and developing immune biomarkers is the diversity of HPV types and the need for multiplexed display of HPV antigens. In Project 1, nucleic acid programmable protein arrays displaying the proteomes of 12 HPV types were developed and used for serum immunoprofiling of women with cervical lesions or invasive cervical cancer. These arrays provide a valuable high-throughput tool for measuring the breadth, specificity, heterogeneity, and cross-reactivity of the serologic response to HPV. Project 2 investigates potential biomarkers of immunity to the bacterial CRISPR/Cas9 system that is currently in clinical trials for cancer. Pre-existing B cell and T cell immune responses to Cas9 were detected in humans and Cas9 was modified to eliminate immunodominant epitopes while preserving its function and specificity. This dissertation broadens our understanding of the immunobiology of cervical cancer and provides insights into the immune profiles that could serve as biomarkers of various applications in cancer.
ContributorsEwaisha, Radwa Mohamed Emadeldin Mahmoud (Author) / Anderson, Karen S (Thesis advisor) / LaBaer, Joshua (Committee member) / Lake, Douglas F (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2018
Description
Biological fluids, in particular blood plasma, provide a vital source of information on the state of human health. While specific detection of biomarker species can aid in disease diagnostics, the complexity of plasma makes analysis challenging. Despite the challenge of complex sample analysis, biomarker quantification has become a primary interest in biomedical analysis. Due to the extremely specific interaction between antibody and analyte, immunoassays are attractive for the analysis of these samples and have gained popularity since their initial introduction several decades ago. Current limitations to diagnostics through blood testing include long incubation times, interference from non-specific binding, and the requirement for specialized instrumentation and personnel. Optimizing the features of immunoassay for diagnostic testing and biomarker quantification would enable early and accurate detection of disease and afford rapid intervention, potentially improving patient outcomes. Improving the limit of quantitation for immunoassay has been the primary goal of many diverse experimental platforms. While the ability to accurately quantify low abundance species in a complex biological sample is of the utmost importance in diagnostic testing, models illustrating experimental limitations have relied on mathematical fittings, which cannot be directly related to finite analytical limits or fundamental relationships. By creating models based on the law of mass action, it is demonstrated that fundamental limitations are imposed by molecular shot noise, creating a finite statistical limitation to quantitative abilities. Regardless of sample volume, 131 molecules are necessary for quantitation to take place with acceptable levels of uncertainty. Understanding the fundamental limitations of the technique can aid in the design of immunoassay platforms, and assess progress toward the development of optimal diagnostic testing. A sandwich-type immunoassay was developed and tested on three separate human protein targets: myoglobin, heart-type fatty acid binding protein, and cardiac troponin I, achieving superior limits of quantitation approaching ultimate limitations. Furthermore, this approach is compatible with upstream sample separation methods, enabling the isolation of target molecules from a complex biological sample. Isolation of target species prior to analysis allows for the multiplex detection of biomarker panels in a microscale device, making the full optimization of immunoassay techniques possible for clinical diagnostics.
ContributorsWoolley, Christine F (Author) / Hayes, Mark A. (Thesis advisor) / Ros, Alexandra (Committee member) / LaBaer, Joshua (Committee member) / Arizona State University (Publisher)
Created2015
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
Description
Recent advances in hierarchical or multilevel statistical models and causal inference using the potential outcomes framework hold tremendous promise for mock and real jury research. These advances enable researchers to explore how individual jurors can exert a bottom-up effect on the jury’s verdict and how case-level features can exert a top-down effect on a juror’s perception of the parties at trial. This dissertation explains and then applies these technical advances to a pre-existing mock jury dataset to provide worked examples in an effort to spur the adoption of these techniques. In particular, the paper introduces two new cross-level mediated effects and then describes how to conduct ecological validity tests with these mediated effects. The first cross-level mediated effect, the a1b1 mediated effect, is the juror level mediated effect for a jury level manipulation. The second cross-level mediated effect, the a2bc mediated effect, is the unique contextual effect that being in a jury has on the individual the juror. When a mock jury study includes a deliberation versus non-deliberation manipulation, the a1b1 can be compared for the two conditions, enabling a general test of ecological validity. If deliberating in a group generally influences the individual, then the two indirect effects should be significantly different. The a2bc can also be interpreted as a specific test of how much changes in jury level means of this specific mediator effect juror level decision-making.
ContributorsLovis-McMahon, David (Author) / Schweitzer, Nicholas (Thesis advisor) / Saks, Michael (Thesis advisor) / Salerno, Jessica (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2015