ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Biology
- Creators: Fenichel, Eli
- Creators: Stafford, Phillip
Description
Consideration of both biological and human-use dynamics in coupled social-ecological systems is essential for the success of interventions such as marine reserves. As purely human institutions, marine reserves have no direct effects on ecological systems. Consequently, the success of a marine reserve depends on managers` ability to alter human behavior in the direction and magnitude that supports reserve objectives. Further, a marine reserve is just one component in a larger coupled social-ecological system. The social, economic, political, and biological landscape all determine the social acceptability of a reserve, conflicts that arise, how the reserve interacts with existing fisheries management, accuracy of reserve monitoring, and whether the reserve is ultimately able to meet conservation and fishery enhancement goals. Just as the social-ecological landscape is critical at all stages for marine reserve, from initial establishment to maintenance, the reserve in turn interacts with biological and human use dynamics beyond its borders. Those interactions can lead to the failure of a reserve to meet management goals, or compromise management goals outside the reserve. I use a bio-economic model of a fishery in a spatially patchy environment to demonstrate how the pre-reserve fisheries management strategy determines the pattern of fishing effort displacement once the reserve is established, and discuss the social, political, and biological consequences of different patterns for the reserve and the fishery. Using a stochastic bio-economic model, I demonstrate how biological and human use connectivity can confound the accurate detection of reserve effects by violating assumptions in the quasi-experimental framework. Finally, I examine data on recreational fishing site selection to investigate changes in response to the announcement of enforcement of a marine reserve in the Gulf of California, Mexico. I generate a scale of fines that would fully or partially protect the reserve, providing a data-driven way for managers to balance biological and socio-economic goals. I suggest that natural resource managers consider human use dynamics with the same frequency, rigor, and tools as they do biological stocks.
ContributorsFujitani, Marie (Author) / Abbott, Joshua (Thesis advisor) / Fenichel, Eli (Thesis advisor) / Gerber, Leah (Committee member) / Anderies, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
The advent of new high throughput technology allows for increasingly detailed characterization of the immune system in healthy, disease, and age states. The immune system is composed of two main branches: the innate and adaptive immune system, though the border between these two states is appearing less distinct. The adaptive immune system is further split into two main categories: humoral and cellular immunity. The humoral immune response produces antibodies against specific targets, and these antibodies can be used to learn about disease and normal states. In this document, I use antibodies to characterize the immune system in two ways: 1. I determine the Antibody Status (AbStat) from the data collected from applying sera to an array of non-natural sequence peptides, and demonstrate that this AbStat measure can distinguish between disease, normal, and aged samples as well as produce a single AbStat number for each sample; 2. I search for antigens for use in a cancer vaccine, and this search results in several candidates as well as a new hypothesis. Antibodies provide us with a powerful tool for characterizing the immune system, and this natural tool combined with emerging technologies allows us to learn more about healthy and disease states.
ContributorsWhittemore, Kurt (Author) / Sykes, Kathryn (Thesis advisor) / Johnston, Stephen A. (Committee member) / Jacobs, Bertram (Committee member) / Stafford, Phillip (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2014
Description
The healthcare system in this country is currently unacceptable. New technologies may contribute to reducing cost and improving outcomes. Early diagnosis and treatment represents the least risky option for addressing this issue. Such a technology needs to be inexpensive, highly sensitive, highly specific, and amenable to adoption in a clinic. This thesis explores an immunodiagnostic technology based on highly scalable, non-natural sequence peptide microarrays designed to profile the humoral immune response and address the healthcare problem. The primary aim of this thesis is to explore the ability of these arrays to map continuous (linear) epitopes. I discovered that using a technique termed subsequence analysis where epitopes could be decisively mapped to an eliciting protein with high success rate. This led to the discovery of novel linear epitopes from Plasmodium falciparum (Malaria) and Treponema palladium (Syphilis), as well as validation of previously discovered epitopes in Dengue and monoclonal antibodies. Next, I developed and tested a classification scheme based on Support Vector Machines for development of a Dengue Fever diagnostic, achieving higher sensitivity and specificity than current FDA approved techniques. The software underlying this method is available for download under the BSD license. Following this, I developed a kinetic model for immunosignatures and tested it against existing data driven by previously unexplained phenomena. This model provides a framework and informs ways to optimize the platform for maximum stability and efficiency. I also explored the role of sequence composition in explaining an immunosignature binding profile, determining a strong role for charged residues that seems to have some predictive ability for disease. Finally, I developed a database, software and indexing strategy based on Apache Lucene for searching motif patterns (regular expressions) in large biological databases. These projects as a whole have advanced knowledge of how to approach high throughput immunodiagnostics and provide an example of how technology can be fused with biology in order to affect scientific and health outcomes.
ContributorsRicher, Joshua Amos (Author) / Johnston, Stephen A. (Thesis advisor) / Woodbury, Neal (Committee member) / Stafford, Phillip (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014
Description
African Swine Fever (ASF), endemic in many African countries, is now spreading to other continents. Though ASF is capable of incurring serious economic losses in affected countries, no vaccine exists to provide immunity to animals. Disease control relies largely on rapid diagnosis and the implementation of movement restrictions and strict eradication programs. Developing a scalable, accurate and low cost diagnostic for ASF will be of great help for the current situation. CIM's 10K random peptide microarray is a new high-throughput platform that allows systematic investigations of immune responses associated with disease and shows promise as a diagnostic tool. In this study, this new technology was applied to characterize the immune responses of ASF virus (ASFV) infections and immunizations. Six sets of sera from ASFV antigen immunized pigs, 6 sera from infected pigs and 20 sera samples from unexposed pigs were tested and analyzed statistically. Results show that both ASFV antigen immunized pigs and ASFV viral infected pigs can be distinguished from unexposed pigs. Since it appears that immune responses to other viral infections are also distinguishable on this platform, it holds the potential of being useful in developing a new ASF diagnostic. The ability of this platform to identify specific ASFV antibody epitopes was also explored. A subtle motif was found to be shared among a set of peptides displaying the highest reactivity for an antigen specific antibody. However, this motif does not seem to match with any antibody epitopes predicted by a linear antibody epitope prediction.
ContributorsXiao, Liang (Author) / Sykes, Kathryn (Thesis advisor) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
Many studies over the past two decades examined the link between climate patterns and discharge, but few have attempted to study the effects of the El Niño Southern Oscillation (ENSO) on localized and watershed specific processes such as nutrient loading in the Southwestern United States. The Multivariate ENSO Index (MEI) is used to describe the state of the ENSO, with positive (negative) values referring to an El Niño condition (La Niña condition). This study examined the connection between the MEI and precipitation, discharge, and total nitrogen (TN) and total phosphorus (TP) concentrations in the Upper Salt River Watershed in Arizona. Unrestricted regression models (UMs) and restricted regression models (RMs) were used to investigate the relationship between the discharges in Tonto Creek and the Salt River as functions of the magnitude of the MEI, precipitation, and season (winter/summer). The results suggest that in addition to precipitation, the MEI/season relationship is an important factor for predicting discharge. Additionally, high discharge events were associated with high magnitude ENSO events, both El Niño and La Niña. An UM including discharge and season, and a RM (restricting the seasonal factor to zero), were applied to TN and TP concentrations in the Salt River. Discharge and seasonality were significant factors describing the variability in TN in the Salt River while discharge alone was the significant factor describing TP. TN and TP in Roosevelt Lake were evaluated as functions of both discharge and MEI. Some significant correlations were found but internal nutrient cycling as well as seasonal stratification of the water column of the lake likely masks the true relationships. Based on these results, the MEI is a useful predictor of discharge, as well as nutrient loading in the Salt River Watershed through the Salt River and Tonto Creek. A predictive model investigating the effect of ENSO on nutrient loading through discharge can illustrate the effects of large scale climate patterns on smaller systems.
ContributorsSversvold, Darren (Author) / Neuer, Susanne (Thesis advisor) / Elser, James (Committee member) / Fenichel, Eli (Committee member) / Arizona State University (Publisher)
Created2012
Description
The southwestern willow flycatcher (Empidonax traillii extimus) is listed as an endangered species throughout its range in the southwestern United States. Little is known about its sub-population spatial structure and how this impacts its population viability. In conjunction with being listed as endangered, a recovery plan was produced by the US Fish and Wildlife Service, with recovery units (sub-populations) roughly based on major river drainages. In the interest of examining this configuration of sub-populations and their impact on the measured population viability, I applied a multivariate auto-regressive state-space model to a spatially extensive time series of abundance data for the southwestern willow flycatcher over the period spanning 1995-2010 estimating critical growth parameters, correlation in environmental stochasticity or "synchronicity" between sub-populations (recovery units) and extinction risk of the sub-populations and the whole. The model estimates two parameters, the mean and variance of annual growth rate. Of the models I tested, I found the strongest support for a population model in which three of the recovery units were grouped (the Lower Colorado, Gila Basin, and Rio Grande recovery units) while keeping all others separate. This configuration has 6.6 times more support for the observed data than a configuration assigning each recovery unit to a separate sub-population, which is how they are circumscribed in the recovery plan. Given the best model, the mean growth rate is -0.0234 (CI95 -0.0939, 0.0412) with a variance of 0.0597 (CI95 0.0115, 0.1134). This growth rate is not significantly different from zero and this is reflected in the low potential for quasi-extinction. The cumulative probability of the population experiencing at least an 80% decline from current levels within 15 years for some sub-populations were much higher (range: 0.129-0.396 for an 80% decline). These results suggest that the rangewide population has a low risk of extinction in the next 15 years and that the formal recovery units specified by the original recovery plan do not correspond to proper sub-population units as defined by population synchrony.
ContributorsDockens, Patrick E. T. (Author) / Sabo, John (Thesis advisor) / Stromberg, Juliet (Committee member) / Fenichel, Eli (Committee member) / Arizona State University (Publisher)
Created2012
Description
Immunotherapy has been revitalized with the advent of immune checkpoint blockade
treatments, and neo-antigens are the targets of immune system in cancer patients who
respond to the treatments. The cancer vaccine field is focused on using neo-antigens from
unique point mutations of genomic sequence in the cancer patient for making
personalized cancer vaccines. However, we choose a different path to find frameshift
neo-antigens at the mRNA level and develop broadly effective cancer vaccines based on
frameshift antigens.
In this dissertation, I have summarized and characterized all the potential frameshift
antigens from microsatellite regions in human, dog and mouse. A list of frameshift
antigens was validated by PCR in tumor samples and the mutation rate was calculated for
one candidate – SEC62. I develop a method to screen the antibody response against
frameshift antigens in human and dog cancer patients by using frameshift peptide arrays.
Frameshift antigens selected by positive antibody response in cancer patients or by MHC
predictions show protection in different mouse tumor models. A dog version of the
cancer vaccine based on frameshift antigens was developed and tested in a small safety
trial. The results demonstrate that the vaccine is safe and it can induce strong B and T cell
immune responses. Further, I built the human exon junction frameshift database which
includes all possible frameshift antigens from mis-splicing events in exon junctions, and I
develop a method to find potential frameshift antigens from large cancer
immunosignature dataset with these databases. In addition, I test the idea of ‘early cancer
diagnosis, early treatment’ in a transgenic mouse cancer model. The results show that
ii
early treatment gives significantly better protection than late treatment and the correct
time point for treatment is crucial to give the best clinical benefit. A model for early
treatment is developed with these results.
Frameshift neo-antigens from microsatellite regions and mis-splicing events are
abundant at mRNA level and they are better antigens than neo-antigens from point
mutations in the genomic sequences of cancer patients in terms of high immunogenicity,
low probability to cause autoimmune diseases and low cost to develop a broadly effective
vaccine. This dissertation demonstrates the feasibility of using frameshift antigens for
cancer vaccine development.
treatments, and neo-antigens are the targets of immune system in cancer patients who
respond to the treatments. The cancer vaccine field is focused on using neo-antigens from
unique point mutations of genomic sequence in the cancer patient for making
personalized cancer vaccines. However, we choose a different path to find frameshift
neo-antigens at the mRNA level and develop broadly effective cancer vaccines based on
frameshift antigens.
In this dissertation, I have summarized and characterized all the potential frameshift
antigens from microsatellite regions in human, dog and mouse. A list of frameshift
antigens was validated by PCR in tumor samples and the mutation rate was calculated for
one candidate – SEC62. I develop a method to screen the antibody response against
frameshift antigens in human and dog cancer patients by using frameshift peptide arrays.
Frameshift antigens selected by positive antibody response in cancer patients or by MHC
predictions show protection in different mouse tumor models. A dog version of the
cancer vaccine based on frameshift antigens was developed and tested in a small safety
trial. The results demonstrate that the vaccine is safe and it can induce strong B and T cell
immune responses. Further, I built the human exon junction frameshift database which
includes all possible frameshift antigens from mis-splicing events in exon junctions, and I
develop a method to find potential frameshift antigens from large cancer
immunosignature dataset with these databases. In addition, I test the idea of ‘early cancer
diagnosis, early treatment’ in a transgenic mouse cancer model. The results show that
ii
early treatment gives significantly better protection than late treatment and the correct
time point for treatment is crucial to give the best clinical benefit. A model for early
treatment is developed with these results.
Frameshift neo-antigens from microsatellite regions and mis-splicing events are
abundant at mRNA level and they are better antigens than neo-antigens from point
mutations in the genomic sequences of cancer patients in terms of high immunogenicity,
low probability to cause autoimmune diseases and low cost to develop a broadly effective
vaccine. This dissertation demonstrates the feasibility of using frameshift antigens for
cancer vaccine development.
ContributorsZhang, Jian (Author) / Johnston, Stephen Albert (Thesis advisor) / Chang, Yung (Committee member) / Stafford, Phillip (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2018
Description
The closer integration of the world economy has yielded many positive benefits including the worldwide diffusion of innovative technologies and efficiency gains following the widening of international markets. However, closer integration also has negative consequences. Specifically, I focus on the ecology and economics of the spread of species and pathogens. I approach the problem using theoretical and applied models in ecology and economics. First, I use a multi-species theoretical network model to evaluate the ability of dispersal to maintain system-level biodiversity and productivity. I then extend this analysis to consider the effects of dispersal in a coupled social-ecological system where people derive benefits from species. Finally, I estimate an empirical model of the foot and mouth disease risks of trade. By combining outbreak and trade data I estimate the disease risks associated with the international trade in live animals while controlling for the biosecurity measures in place in importing countries and the presence of wild reservoirs. I find that the risks associated with the spread and dispersal of species may be positive or negative, but that this relationship depends on the ecological and economic components of the system and the interactions between them.
ContributorsShanafelt, David William (Author) / Perrings, Charles (Thesis advisor) / Fenichel, Eli (Committee member) / Richards, Timorthy (Committee member) / Janssen, Marco (Committee member) / Collins, James (Committee member) / Arizona State University (Publisher)
Created2016