Matching Items (453)
Filtering by
- Creators: Harrington Bioengineering Program
- Member of: Theses and Dissertations
- Member of: ASU Electronic Theses and Dissertations
Description
This study explores the ways in which LGBTQ young adults describe the aspects of their identities, and how those identities shape their service needs and experiences. A participatory action research component was explored as a research and service approach that is sensitive to LGBTQ young people living at the intersections of multiple identities. Although it is understood that LGBTQ young people come from a variety of backgrounds, research is limited in its understanding and exploration of how aspects of identity, such as race and class, influence the lives and service needs of this population. The data was collected through an initial set of interviews with fifteen LGBTQ-identified young adults ages 18 to 24. The interviewees were recruited from an LGBTQ youth-serving organization using a purposive sampling approach to reflect racial/ethnic and gender identity diversity. Following the interviews, eight of the participants engaged as co-researchers on a participatory action research (PAR) team for sixteen weeks. The process of this team's work was assessed through a reflective analysis to identify factors that impacted the participants' lives. Analysis of the interviews identified key themes related to identity among the LGBTQ young people. The interviewees experienced a multiplicity of identities that were both socially and individually constructed. These identities were impacted by their immediate and social environments. The young people also identified ways that they used their identities to influence their environments and enhance their own resilience. The service experiences and needs of the LGBTQ young people in this study were directly influenced by their multiple identities. Implications for intersectional approaches to serving this population are explored. Analysis of the PAR process identified four areas in which the young people were most impacted through their work and interactions with one another: relationships, communication, participation, and inclusion. Implications for research and service approaches with LGBTQ young people are discussed.
ContributorsWagaman, M. Alex (Author) / Segal, Elizabeth A. (Thesis advisor) / Adelman, Madelaine (Committee member) / Ayón, Cecilia (Committee member) / Arizona State University (Publisher)
Created2013
Description
Random peptide microarrays are a powerful tool for both the treatment and diagnostics of infectious diseases. On the treatment side, selected random peptides on the microarray have either binding or lytic potency against certain pathogens cells, thus they can be synthesized into new antimicrobial agents, denoted as synbodies (synthetic antibodies). On the diagnostic side, serum containing specific infection-related antibodies create unique and distinct "pathogen-immunosignatures" on the random peptide microarray distinct from the healthy control serum, and this different mode of binding can be used as a more precise measurement than traditional ELISA tests. My thesis project is separated into these two parts: the first part falls into the treatment side and the second one focuses on the diagnostic side. My first chapter shows that a substitution amino acid peptide library helps to improve the activity of a recently reported synthetic antimicrobial peptide selected by the random peptide microarray. By substituting one or two amino acids of the original lead peptide, the new substitutes show changed hemolytic effects against mouse red blood cells and changed potency against two pathogens: Staphylococcus aureus and Pseudomonas aeruginosa. Two new substitutes are then combined together to form the synbody, which shows a significantly antimicrobial potency against Staphylococcus aureus (<0.5uM). In the second chapter, I explore the possibility of using the 10K Ver.2 random peptide microarray to monitor the humoral immune response of dengue. Over 2.5 billion people (40% of the world's population) live in dengue transmitting areas. However, currently there is no efficient dengue treatment or vaccine. Here, with limited dengue patient serum samples, we show that the immunosignature has the potential to not only distinguish the dengue infection from non-infected people, but also the primary dengue infection from the secondary dengue infections, dengue infection from West Nile Virus (WNV) infection, and even between different dengue serotypes. By further bioinformatic analysis, we demonstrate that the significant peptides selected to distinguish dengue infected and normal samples may indicate the epitopes responsible for the immune response.
ContributorsWang, Xiao (Author) / Johnston, Stephen Albert (Thesis advisor) / Blattman, Joseph (Committee member) / Arntzen, Charles (Committee member) / Arizona State University (Publisher)
Created2013
Description
The object of this study is to charac terize the effect of focused ultrasound stimulation (FUS) on the rat ce rvix which has been observed to speed its ripening during pregnancy. Ce rvical ripening is required for successful fetal delivery. Timed-pregnant Sprague-Dawley rats (n=36) were used. On day 14 of gestation, the FUS system was placed on the body surface of the rat over the cervix and ultrasound energy was applied to cervix for variable times up to 1 hour in the control group, the FUS system was placed on rats but no energy was applied. Daily measurement of cervix light-induced florescence (LIF, photon counts of collagen x-bridge fluorescence) were made on days 16 of gestation and daily until spont-aneous delivery (day22) to estimate changes in cervical ripening. We found that pulses of 680 KHz ultrasound at 25 Hertz, 1 millisecond pulse duration at 1W/cm^2 applied for as little as 30 minutes would immediately afterwards show the cervix to hav e ripened to the degree seen just before delivery on day 22. Delivery times, fetal weights and viability were unaffected in the FUS-treated animals.
ContributorsLuo, Daishen (Author) / Towe, Bruce C (Thesis advisor) / Wang, Xiao (Committee member) / Caplan, Michael (Committee member) / Arizona State University (Publisher)
Created2012
Description
Sensitivity is a fundamental challenge for in vivo molecular magnetic resonance imaging (MRI). Here, I improve the sensitivity of metal nanoparticle contrast agents by strategically incorporating pure and doped metal oxides in the nanoparticle core, forming a soluble, monodisperse, contrast agent with adjustable T2 or T1 relaxivity (r2 or r1). I first developed a simplified technique to incorporate iron oxides in apoferritin to form "magnetoferritin" for nM-level detection with T2- and T2* weighting. I then explored whether the crystal could be chemically modified to form a particle with high r1. I first adsorbed Mn2+ ions to metal binding sites in the apoferritin pores. The strategic placement of metal ions near sites of water exchange and within the crystal oxide enhance r1, suggesting a mechanism for increasing relaxivity in porous nanoparticle agents. However, the Mn2+ addition was only possible when the particle was simultaneously filled with an iron oxide, resulting in a particle with a high r1 but also a high r2 and making them undetectable with conventional T1-weighting techniques. To solve this problem and decrease the particle r2 for more sensitive detection, I chemically doped the nanoparticles with tungsten to form a disordered W-Fe oxide composite in the apoferritin core. This configuration formed a particle with a r1 of 4,870mM-1s-1 and r2 of 9,076mM-1s-1. These relaxivities allowed the detection of concentrations ranging from 20nM - 400nM in vivo, both passively injected and targeted to the kidney glomerulus. I further developed an MRI acquisition technique to distinguish particles based on r2/r1, and show that three nanoparticles of similar size can be distinguished in vitro and in vivo with MRI. This work forms the basis for a new, highly flexible inorganic approach to design nanoparticle contrast agents for molecular MRI.
ContributorsClavijo Jordan, Maria Veronica (Author) / Bennett, Kevin M (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Sherry, A Dean (Committee member) / Wang, Xiao (Committee member) / Yarger, Jeffery (Committee member) / Arizona State University (Publisher)
Created2012
Description
For many adolescents, high school is a critical period of self-awareness, peer-influence, and identity construction. During this volatile period, young people explore how to express themselves in ways that range from conformity to non-conformity and transgression. This is particularly true when it comes to young people's understanding and expression of gender identity. For some youth, their personal form(s) of gender expression align neatly with social expectations; for others, it does not. When gender expression does not align with social expectations, students may be vulnerable to bullying or harassment by peers or adults. Often, youth who are policed and regulated by their classmates through bullying (or harassment, depending upon the relevant or implemented policy) are targeted based on their perceived identity, be that racial, ethnic, citizenship, or, most frequently, gender and sexuality. This project advances the need for research done from a critical youth studies perspective (both methodologically and ethically) and provides new insight into the types of language and practices used by youth to express, perform and "do" gender. Utilizing qualitative methodology, including participant observation, focus group and individual interviews, surveys, and the collection and content analysis of school ephemera, this research investigated how high school students navigate gender identity amidst other intersecting identities. This project examined how youth both "do" and "perform" gender in their everyday lives as high school students. Their gender identity is frequently understood amidst other intersecting identities, particularly sexual orientation, religion and race. These youth also pointed to several important influences in how they understand their own gender, and the gender identity of those around them, including media and peer groups. Because this research took place at two charter art schools, the findings also provided a framework for understanding how these two schools, and charter art schools more generally, provide alternative spaces for young people to experiment and play with their identity construction. Findings indicate that youth are forced to navigate and construct their gender identity amidst many conflicting and contradictory ideologies. Schools, media, and peer groups all heavily influence the way young people understand themselves.
ContributorsPrior, Sarah (Author) / Cavender, Gray (Thesis advisor) / Adelman, Madelaine (Thesis advisor) / Swadener, Beth Blue (Committee member) / Katsulis, Yasmina (Committee member) / Arizona State University (Publisher)
Created2012
Description
This study is based on 31 interviews conducted in 2012 with male, female, and transgender sex workers at the St. James Infirmary, a full-spectrum health clinic run by sex workers for sex workers, located in San Francisco, California. My primary goals were, first, to document the lived realities of a diverse range of sex workers who live and work in the San Francisco Bay Area, and, second, to understand the impact of sex work discourse on the facilitation of stigma toward the sex work community and, finally, how that stigma influences the sex worker group identity and individual identity constructions. My primary findings indicate that although sex work discourse has traditionally been constructed within the dominant public sphere and not by sex workers themselves, this discourse has a profound effect on creating and perpetuating the stigma associated with sex work. In turn, this stigma affects both how the group and how individuals construct their identities, often negatively. Alternatively, a benefit of stigma is that it can induce the production of counterpublics which facilitate the emergence of new discourse. However, for this new discourse to gain acceptance into the public sphere, activist organizations must utilize traditional (and sometimes unintentionally marginalizing) strategies that can impact both the identity construction of the group and of individuals within the group. Understanding these complex relationships is therefore essential to understanding how activist organizations, such as the St. James Infirmary, situate themselves within the larger dominant public sphere, their impact on sex work discourse, and their impact on individual sex worker identity construction.
ContributorsRead, Kathleen (Author) / Adams, Karen L (Thesis advisor) / Katsulis, Yasmina (Thesis advisor) / Adelman, Madelaine (Committee member) / Arizona State University (Publisher)
Created2013
Description
Single cell phenotypic heterogeneity studies reveal more information about the pathogenesis process than conventional bulk methods. Furthermore, investigation of the individual cellular response mechanism during rapid environmental changes can only be achieved at single cell level. By enabling the study of cellular morphology, a single cell three-dimensional (3D) imaging system can be used to diagnose fatal diseases, such as cancer, at an early stage. One proven method, CellCT, accomplishes 3D imaging by rotating a single cell around a fixed axis. However, some existing cell rotating mechanisms require either intricate microfabrication, and some fail to provide a suitable environment for living cells. This thesis develops a microvorterx chamber that allows living cells to be rotated by hydrodynamic alone while facilitating imaging access. In this thesis work, 1) the new chamber design was developed through numerical simulation. Simulations revealed that in order to form a microvortex in the side chamber, the ratio of the chamber opening to the channel width must be smaller than one. After comparing different chamber designs, the trapezoidal side chamber was selected because it demonstrated controllable circulation and met the imaging requirements. Microvortex properties were not sensitive to the chambers with interface angles ranging from 0.32 to 0.64. A similar trend was observed when chamber heights were larger than chamber opening. 2) Micro-particle image velocimetry was used to characterize microvortices and validate simulation results. Agreement between experimentation and simulation confirmed that numerical simulation was an effective method for chamber design. 3) Finally, cell rotation experiments were performed in the trapezoidal side chamber. The experimental results demonstrated cell rotational rates ranging from 12 to 29 rpm for regular cells. With a volumetric flow rate of 0.5 µL/s, an irregular cell rotated at a mean rate of 97 ± 3 rpm. Rotational rates can be changed by altering inlet flow rates.
ContributorsZhang, Wenjie (Author) / Frakes, David (Thesis advisor) / Meldrum, Deirdre (Thesis advisor) / Chao, Shih-hui (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation considers how adolescent identity is constructed and represented in commercial musical theatre for youth (e.g. Broadway and Disney Theatrical Group) by examining two commercial productions with adolescents in lead roles--Spring Awakening and Disney's High School Musical. My theoretical framework is intersectionality which creates a foundation for my research within the field of childhood studies, gender studies, and performance studies to illuminate current US American trends in youth oriented art and research. My framework extends into a case study methodology exploring the world of childhood and youth sexuality through a close read of the popular Broadway musical adaptation, Spring Awakening. In addition, a second investigation chronicles the world of Disney's High School Musical through my own intersectional tool, the Disney Industrial Complex. I claim that adolescence, as a constructed identity, exists as a multi-faceted intersectional category composed of multiple and conflicting intersections such as gender, race, sex, ethnicity, and so on. These intersections develop over the course of the period known as "adolescence" and "youth." The goal of this dissertation is to serve as a reference for other theatre educators and their work with young people creating art.
ContributorsBliznik, Sean J (Author) / Etheridge-Woodson, Stephani (Thesis advisor) / Saldana, Johnny (Committee member) / Adelman, Madelaine (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation treats a number of related problems in control and data analysis of complex networks.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
ContributorsWang, Lezhi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Papandreoou-Suppappola, Antonia (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
While techniques for reading DNA in some capacity has been possible for decades,
the ability to accurately edit genomes at scale has remained elusive. Novel techniques
have been introduced recently to aid in the writing of DNA sequences. While writing
DNA is more accessible, it still remains expensive, justifying the increased interest in
in silico predictions of cell behavior. In order to accurately predict the behavior of
cells it is necessary to extensively model the cell environment, including gene-to-gene
interactions as completely as possible.
Significant algorithmic advances have been made for identifying these interactions,
but despite these improvements current techniques fail to infer some edges, and
fail to capture some complexities in the network. Much of this limitation is due to
heavily underdetermined problems, whereby tens of thousands of variables are to be
inferred using datasets with the power to resolve only a small fraction of the variables.
Additionally, failure to correctly resolve gene isoforms using short reads contributes
significantly to noise in gene quantification measures.
This dissertation introduces novel mathematical models, machine learning techniques,
and biological techniques to solve the problems described above. Mathematical
models are proposed for simulation of gene network motifs, and raw read simulation.
Machine learning techniques are shown for DNA sequence matching, and DNA
sequence correction.
Results provide novel insights into the low level functionality of gene networks. Also
shown is the ability to use normalization techniques to aggregate data for gene network
inference leading to larger data sets while minimizing increases in inter-experimental
noise. Results also demonstrate that high error rates experienced by third generation
sequencing are significantly different than previous error profiles, and that these errors can be modeled, simulated, and rectified. Finally, techniques are provided for amending this DNA error that preserve the benefits of third generation sequencing.
the ability to accurately edit genomes at scale has remained elusive. Novel techniques
have been introduced recently to aid in the writing of DNA sequences. While writing
DNA is more accessible, it still remains expensive, justifying the increased interest in
in silico predictions of cell behavior. In order to accurately predict the behavior of
cells it is necessary to extensively model the cell environment, including gene-to-gene
interactions as completely as possible.
Significant algorithmic advances have been made for identifying these interactions,
but despite these improvements current techniques fail to infer some edges, and
fail to capture some complexities in the network. Much of this limitation is due to
heavily underdetermined problems, whereby tens of thousands of variables are to be
inferred using datasets with the power to resolve only a small fraction of the variables.
Additionally, failure to correctly resolve gene isoforms using short reads contributes
significantly to noise in gene quantification measures.
This dissertation introduces novel mathematical models, machine learning techniques,
and biological techniques to solve the problems described above. Mathematical
models are proposed for simulation of gene network motifs, and raw read simulation.
Machine learning techniques are shown for DNA sequence matching, and DNA
sequence correction.
Results provide novel insights into the low level functionality of gene networks. Also
shown is the ability to use normalization techniques to aggregate data for gene network
inference leading to larger data sets while minimizing increases in inter-experimental
noise. Results also demonstrate that high error rates experienced by third generation
sequencing are significantly different than previous error profiles, and that these errors can be modeled, simulated, and rectified. Finally, techniques are provided for amending this DNA error that preserve the benefits of third generation sequencing.
ContributorsFaucon, Philippe Christophe (Author) / Liu, Huan (Thesis advisor) / Wang, Xiao (Committee member) / Crook, Sharon M (Committee member) / Wang, Yalin (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2017