Matching Items (162)
Description
In an effort to address the lack of literature in on-campus active travel, this study aims to investigate the following primary questions:<br/>• What are the modes that students use to travel on campus?<br/>• What are the motivations that underlie the mode choice of students on campus?<br/>My first stage of research involved a series of qualitative investigations. I held one-on-one virtual interviews with students in which I asked them questions about the mode they use and why they feel that their chosen mode works best for them. These interviews served two functions. First, they provided me with insight into the various motivations underlying student mode choice. Second, they provided me with an indication of what explanatory variables should be included in a model of mode choice on campus.<br/>The first half of the research project informed a quantitative survey that was released via the Honors Digest to attract student respondents. Data was gathered on travel behavior as well as relevant explanatory variables.<br/>My analysis involved developing a logit model to predict student mode choice on campus and presenting the model estimation in conjunction with a discussion of student travel motivations based on the qualitative interviews. I use this information to make a recommendation on how campus infrastructure could be modified to better support the needs of the student population.
ContributorsMirtich, Laura Christine (Author) / Salon, Deborah (Thesis director) / Fang, Kevin (Committee member) / School of Public Affairs (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Microfluidic devices represent a growing technology in the world of analytical chemistry. Serial femtosecond crystallography (SFX) utilizes microfluidic devices to generate droplets of an aqueous buffer containing protein crystals, which are then fired out as a jet in the beam of an X-ray free electron laser (XFEL). A crucial part of the device is its method of droplet detection. This project presents a design for a capacitive sensor that uses a unique electrode configuration to detect the difference in capacitance between the aqueous and oil phases. This design was developed using MATLAB and COMSOL Multiphysics simulations and printed using high-resolution 3D printing. Results show that this design can successfully distinguish between the two immiscible liquids, confirming it as a possible detection method in future SFX experiments.
ContributorsCorder, Cameron Dean (Author) / Ros, Alexandra (Thesis director) / Williams, Peter (Committee member) / Hayes, Mark (Committee member) / School of Molecular Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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
Obtaining local electrochemical (EC) information is extremely important for understanding basic surface reactions, and for many applications. Scanning electrochemical microscopy (SECM) can obtain local EC information by scanning a microelectrode across the surface. Although powerful, SECM is slow, the scanning microelectrode may perturb reaction and the measured signal decreases with the size of microelectrode. This thesis demonstrates a new imaging technique based on a principle that is completely different from the conventional EC detection technologies. The technique, referred to as plasmonic-based electrochemical imaging (PECI), images local EC current (both faradaic and non-faradaic) without using a scanning microelectrode. Because PECI response is an optical signal originated from surface plasmon resonance (SPR), PECI is fast and non-invasive and its signal is proportional to incident light intensity, thus does not decrease with the area of interest. A complete theory is developed in this thesis work to describe the relationship between EC current and PECI signal. EC current imaging at various fixed potentials and local cyclic voltammetry methods are developed and demonstrated with real samples. Fast imaging rate (up to 100,000 frames per second) with 0.2×3µm spatial resolution and 0.3 pA detection limit have been achieved. Several PECI applications have been developed to demonstrate the unique strengths of the new imaging technology. For example, trace particles in fingerprint is detected by PECI, a capability that cannot be achieved with the conventional EC technologies. Another example is PECI imaging of EC reaction and interfacial impedance of graphene of different thicknesses. In addition, local square wave voltammetry capability is demonstrated and applied to study local catalytic current of platinum nanoparticle microarray. This thesis also describes a related but different research project that develops a new method to measure surface charge densities of SPR sensor chips, and micro- and nano-particles. A third project of this thesis is to develop a method to expand the conventional SPR detection and imaging technology by including a waveguide mode. This innovation creates a sensitive detection of bulk index of refraction, which overcomes the limitation that the conventional SPR can probe only changes near the sensor surface within ~200 nm.
ContributorsShan, Xiaonan (Author) / Tao, Nongjian (Thesis advisor) / Chae, Junseok (Committee member) / Christen, Jennifer Blain (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2011
Description
X-ray diffraction is the technique of choice to determine the three-dimensional structures of proteins. In this study it has been applied to solve the structure of the survival motor neuron (SMN) proteins, the Fenna-Mathews-Olson (FMO) from Pelodictyon phaeum (Pld. phaeum) protein, and the synthetic ATP binding protein DX. Spinal muscular atrophy (SMA) is an autosomal recessive genetic disease resulting in muscle atrophy and paralysis via degeneration of motor neurons in the spinal cord. In this work, we used X-ray diffraction technique to solve the structures of the three variant of the of SMN protein, namely SMN 1-4, SMN-WT, and SMN-Δ7. The SMN 1-4, SMN-WT, and SMN-Δ7 crystals were diffracted to 2.7 Å, 5.5 Å and 3.0 Å, respectively. The three-dimensional structures of the three SMN proteins have been solved. The FMO protein from Pld. phaeum is a water soluble protein that is embedded in the cytoplasmic membrane and serves as an energy transfer funnel between the chlorosome and the reaction center. The FMO crystal diffracted to 1.99Å resolution and the three-dimensional structure has been solved. In previous studies, double mutant, DX, protein was purified and crystallized in the presence of ATP (Simmons et al., 2010; Smith et al. 2007). DX is a synthetic ATP binding protein which resulting from a random selection of DNA library. In this study, DX protein was purified and crystallized without the presence of ATP to investigate the conformational change in DX structure. The crystals of DX were diffracted to 2.5 Å and the three-dimensional structure of DX has been solved.
ContributorsSeng, Chenda O (Author) / Allen, James P. (Thesis advisor) / Wachter, Rebekka (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2013
Description
Food system and health characteristics were evaluated across the last Waorani hunter-gatherer group in Amazonian Ecuador and a remote neighboring Kichwa indigenous subsistence agriculture community. Hunter-gatherer food systems like the Waorani foragers may not only be nutritionally, but also pharmaceutically beneficial because of high dietary intake of varied plant phytochemical compounds. A modern diet that reduces these dietary plant defense phytochemicals below levels typical in human evolutionary history may leave humans vulnerable to diseases that were controlled through a foraging diet. Few studies consider the health impact of the recent drastic reduction of plant phytochemical content in the modern global food system, which has eliminated essential components of food because they are not considered "nutrients". The antimicrobial and anti-inflammatory nature of the food system may not only regulate infectious pathogens and inflammatory disease, but also support beneficial microbes in human hosts, reducing vulnerability to chronic diseases. Waorani foragers seem immune to certain infections with very low rates of chronic disease. Does returning to certain characteristics of a foraging food system begin to restore the human body microbe balance and inflammatory response to evolutionary norms, and if so, what implication does this have for the treatment of disease? Several years of data on dietary and health differences across the foragers and the farmers was gathered. There were major differences in health outcomes across the board. In the Waorani forager group there were no signs of infection in serious wounds such as 3rd degree burns and spear wounds. The foragers had one-degree lower body temperature than the farmers. The Waorani had an absence of signs of chronic diseases including vision and blood pressure that did not change markedly with age while Kichwa farmers suffered from both chronic diseases and physiological indicators of aging. In the Waorani forager population, there was an absence of many common regional infectious diseases, from helminthes to staphylococcus. Study design helped control for confounders (exercise, environment, genetic factors, non-phytochemical dietary intake). This study provides evidence of the major role total phytochemical dietary intake plays in human health, often not considered by policymakers and nutritional and agricultural scientists.
ContributorsLondon, Douglas (Author) / Tsuda, Takeyuki (Thesis advisor) / Beezhold, Bonnie L (Committee member) / Hruschka, Daniel (Committee member) / Eder, James (Committee member) / Arizona State University (Publisher)
Created2012
Description
Polydimethyl siloxane is a commonly used fabrication material for microfluidic devices. However, its hydrophobic nature and protein adsorption on the surface restricts its use for microfluidic applications. Also, it is critical to control the electroosmotic flow for electrophoretic and dielectrophoretic manipulations. Therefore, surface modification of PDMS is essential to make it well suited for bioanalytical applications. In this project, the role of polyethylene oxide copolymers F108 and PLL-PEG has been investigated to modify the surface properties of PDMS using physisorption method. Measuring electroosmotic flow and adsorption studies tested the quality and the long-term stability of the modified PDMS surface. Static and dynamic coating strategies were used to modify the PDMS surface. In static coating, the PDMS surface was incubated with the coating agent prior to the measurements. For dynamic coating, the coating agent was always present in the solution throughout the experiment. F108 and PLL-PEG were equally effective to prevent the protein adsorption under both strategies. However, dynamic coating was more time saving. Furthermore, effective reduction of EOF was observed with F108 coating agent under dynamic conditions and with PLL-PEG coating agent under static conditions. Moreover, PLL-PEG dynamic coatings exhibited reversal of EOF. These important findings could be used to manipulate EOF and suggest optimal coating agent and strategies for PDMS surface treatment by the physisorption method.
ContributorsManchanda, Shikha (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Liu, Yan (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation describes a novel, low cost strategy of using particle streak (track) images for accurate micro-channel velocity field mapping. It is shown that 2-dimensional, 2-component fields can be efficiently obtained using the spatial variation of particle track lengths in micro-channels. The velocity field is a critical performance feature of many microfluidic devices. Since it is often the case that un-modeled micro-scale physics frustrates principled design methodologies, particle based velocity field estimation is an essential design and validation tool. Current technologies that achieve this goal use particle constellation correlation strategies and rely heavily on costly, high-speed imaging hardware. The proposed image/ video processing based method achieves comparable accuracy for fraction of the cost. In the context of micro-channel velocimetry, the usability of particle streaks has been poorly studied so far. Their use has remained restricted mostly to bulk flow measurements and occasional ad-hoc uses in microfluidics. A second look at the usability of particle streak lengths in this work reveals that they can be efficiently used, after approximately 15 years from their first use for micro-channel velocimetry. Particle tracks in steady, smooth microfluidic flows is mathematically modeled and a framework for using experimentally observed particle track lengths for local velocity field estimation is introduced here, followed by algorithm implementation and quantitative verification. Further, experimental considerations and image processing techniques that can facilitate the proposed methods are also discussed in this dissertation. Unavailability of benchmarked particle track image data motivated the implementation of a simulation framework with the capability to generate exposure time controlled particle track image sequence for velocity vector fields. This dissertation also describes this work and shows that arbitrary velocity fields designed in computational fluid dynamics software tools can be used to obtain such images. Apart from aiding gold-standard data generation, such images would find use for quick microfluidic flow field visualization and help improve device designs.
ContributorsMahanti, Prasun (Author) / Cochran, Douglas (Thesis advisor) / Taylor, Thomas (Thesis advisor) / Hayes, Mark (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation is intended to tie together a body of work which utilizes a variety of methods to study applied mathematical models involving heterogeneity often omitted with classical modeling techniques. I posit three cogent classifications of heterogeneity: physiological, behavioral, and local (specifically connectivity in this work). I consider physiological heterogeneity using the method of transport equations to study heterogeneous susceptibility to diseases in open populations (those with births and deaths). I then present three separate models of behavioral heterogeneity. An SIS/SAS model of gonorrhea transmission in a population of highly active men-who-have-sex-with-men (MSM) is presented to study the impact of safe behavior (prevention and self-awareness) on the prevalence of this endemic disease. Behavior is modeled in this examples via static parameters describing consistent condom use and frequency of STD testing. In an example of behavioral heterogeneity, in the absence of underlying dynamics, I present a generalization to ``test theory without an answer key" (also known as cultural consensus modeling or CCM). CCM is commonly used to study the distribution of cultural knowledge within a population. The generalized framework presented allows for selecting the best model among various extensions of CCM: multiple subcultures, estimating the degree to which individuals guess yes, and making competence homogenous in the population. This permits model selection based on the principle of information criteria. The third behaviorally heterogeneous model studies adaptive behavioral response based on epidemiological-economic theory within an $SIR$ epidemic setting. Theorems used to analyze the stability of such models with a generalized, non-linear incidence structure are adapted and applied to the case of standard incidence and adaptive incidence. As an example of study in spatial heterogeneity I provide an explicit solution to a generalization of the continuous time approximation of the Albert-Barabasi scale-free network algorithm. The solution is found by recursively solving the differential equations via integrating factors, identifying a pattern for the coefficients and then proving this observed pattern is consistent using induction. An application to disease dynamics on such evolving structures is then studied.
ContributorsMorin, Benjamin (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Hiebeler, David (Thesis advisor) / Hruschka, Daniel (Committee member) / Suslov, Sergei (Committee member) / Arizona State University (Publisher)
Created2012