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Description
Systemic lupus erytematosus (SLE) is an autoimmune disease where the immune system is reactive to self antigens resulting in manifestations like glomerulonephritis and arthritis. The immune system also affects the central nervous system (known as CNS-SLE) leading to neuropsychiatric manifestations such as depression, cognitive impairment, psychosis and seizures.

Systemic lupus erytematosus (SLE) is an autoimmune disease where the immune system is reactive to self antigens resulting in manifestations like glomerulonephritis and arthritis. The immune system also affects the central nervous system (known as CNS-SLE) leading to neuropsychiatric manifestations such as depression, cognitive impairment, psychosis and seizures. A subset of pathogenic brain-reactive autoantibodies (BRAA) is hypothesized to bind to integral membrane brain proteins, affecting their function, leading to CNS-SLE. I have tested this BRAA hypothesis, using our lupus-mouse model the MRL/lpr mice, and have found it to be a reasonable explanation for some of the manifestations of CNS-SLE. Even when the MRL/lpr had a reduced autoimmune phenotype, their low BRAA sera levels correlated with CNS involvement. The correlation existed between BRAA levels to integral membrane protein and depressive-like behavior. These results were the first to show a correlation between behavioral changes and BRAA levels from brain membrane antigen as oppose to cultured neuronal cells. More accurate means of predicting and diagnosing lupus and CNS-SLE is necessary. Using microarray technology I was able to determine peptide sets that could be predictive and diagnostic of lupus and each specific CNS manifestation. To knowledge no test currently exists that can effectively diagnose lupus and distinguish between each CNS manifestations. Using the peptide sets, I was able to determine possible natural protein biomarkers for each set as well as for five monoclonal BRAA from one MRL/lpr. These biomarkers can provide specific targets for therapy depending on the manifestation. It was necessary to investigate how these BRAA enter the brain. I hypothesized that substance P plays a role in altering the blood-brain barrier (BBB) allowing these BRAA to enter and affect brain function, when bound to its neurokinin-1 receptor (NK-1R). Western blotting results revealed an increase in the levels of NK-1R in the brain of the MRL/lpr compared to the MRL/mp. These MRL/lpr with increased levels of both NK-1R and BRAA displayed CNS dysfunction. Together, these results demonstrate that NK-1R may play a role in CNS manifestations. Overall, the research conducted here, add to the role that BRAA are playing in CNS-lupus.
ContributorsWilliams, Stephanie (Author) / Hoffman, Steven A (Thesis advisor) / Conrad, Cheryl (Committee member) / Chen, Julian (Committee member) / Orchinik, Miles (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Food is an essential driver of animal behavior. For social organisms, the acquisition of food guides interactions with the environment and with group-mates. Studies have focused on how social individuals find and choose food sources, and share both food and information with group-mates. However, it is often not clear how

Food is an essential driver of animal behavior. For social organisms, the acquisition of food guides interactions with the environment and with group-mates. Studies have focused on how social individuals find and choose food sources, and share both food and information with group-mates. However, it is often not clear how experiences throughout an individual's life influence such interactions. The core question of this thesis is how individuals’ experience contributes to within-caste behavioral variation in a social group. I investigate the effects of individual history, including physical injury and food-related experience, on individuals' social food sharing behavior, responses to food-related stimuli, and the associated neural biogenic amine signaling pathways. I use the eusocial honey bee (Apis mellifera) system, one in which individuals exhibit a high degree of plasticity in responses to environmental stimuli and there is a richness of communicatory pathways for food-related information. Foraging exposes honey bees to aversive experiences such as predation, con-specific competition, and environmental toxins. I show that foraging experience changes individuals' response thresholds to sucrose, a main component of adults’ diets, depending on whether foraging conditions are benign or aversive. Bodily injury is demonstrated to reduce individuals' appetitive responses to new, potentially food-predictive odors. Aversive conditions also impact an individual's social food sharing behavior; mouth-to-mouse trophallaxis with particular groupmates is modulated by aversive foraging conditions both for foragers who directly experienced these conditions and non-foragers who were influenced via social contact with foragers. Although the mechanisms underlying these behavioral changes have yet to be resolved, my results implicate biogenic amine signaling pathways as a potential component. Serotonin and octopamine concentrations are shown to undergo long-term change due to distinct foraging experiences. My work serves to highlight the malleability of a social individual's food-related behavior, suggesting that environmental conditions shape how individuals respond to food and share information with group-mates. This thesis contributes to a deeper understanding of inter-individual variation in animal behavior.
ContributorsFinkelstein, Abigail (Author) / Amdam, Gro V (Thesis advisor) / Conrad, Cheryl (Committee member) / Smith, Brian (Committee member) / Neisewander, Janet (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Body size plays a pervasive role in determining physiological and behavioral performance across animals. It is generally thought that smaller animals are limited in performance measures compared to larger animals; yet, the vast majority of animals on earth are small and evolutionary trends like miniaturization occur in every animal clade.

Body size plays a pervasive role in determining physiological and behavioral performance across animals. It is generally thought that smaller animals are limited in performance measures compared to larger animals; yet, the vast majority of animals on earth are small and evolutionary trends like miniaturization occur in every animal clade. Therefore, there must be some evolutionary advantages to being small and/or compensatory mechanisms that allow small animals to compete with larger species. In this dissertation I specifically explore the scaling of flight performance (flight metabolic rate, wing beat frequency, load-carrying capacity) and learning behaviors (visual differentiation visual Y-maze learning) across stingless bee species that vary by three orders of magnitude in body size. I also test whether eye morphology and calculated visual acuity match visual differentiation and learning abilities using honeybees and stingless bees. In order to determine what morphological and physiological factors contribute to scaling of these performance parameters I measure the scaling of head, thorax, and abdomen mass, wing size, brain size, and eye size. I find that small stingless bee species are not limited in visual learning compared to larger species, and even have some energetic advantages in flight. These insights are essential to understanding how small size evolved repeatedly in all animal clades and why it persists. Finally, I test flight performance across stingless bee species while varying temperature in accordance with thermal changes that are predicted with climate change. I find that thermal performance curves varied greatly among species, that smaller species conform closely to air temperature, and that larger bees may be better equipped to cope with rising temperatures due to more frequent exposure to high temperatures. This information may help us predict whether small or large species might fare better in future thermal climate conditions, and which body-size related traits might be expected to evolve.
ContributorsDuell, Meghan (Author) / Harrison, Jon F. (Thesis advisor) / Smith, Brian H. (Thesis advisor) / Rutowski, Ronald (Committee member) / Wcislo, William (Committee member) / Conrad, Cheryl (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Estrogen-containing hormone therapy (HT) is approved for treatment of symptoms associated with menopause by the Food and Drug Administration. A common estrogen used in HT is 17β-estradiol (E2). Rodent models of menopause, and some clinical work as well, suggest a cognitively-beneficial role of E2. However, as of the 2017 statement

Estrogen-containing hormone therapy (HT) is approved for treatment of symptoms associated with menopause by the Food and Drug Administration. A common estrogen used in HT is 17β-estradiol (E2). Rodent models of menopause, and some clinical work as well, suggest a cognitively-beneficial role of E2. However, as of the 2017 statement released by the North American Menopause Society, HT is not currently advised for use as cognitive therapy in healthy, menopausal women, given that the data so far from existing clinical studies are not yet definitive. Indeed, the delivery of E2 treatment can be optimized to yield more consistent results on cognitive function, particularly considering that exogenously administered E2 gets rapidly metabolized and cleared from the body. Further, E2-containing HT must include a progestogen if prescribed to women with a uterus to oppose its undesired uterine stimulating effects, such as increased endometrial hyperplasia and cancer risks. Studies have shown that the addition of a progestogen to E2 treatment can attenuate the effects of E2 on cognition and brain variables associated with cognitive function. Thus, a brain-specific delivery platform of E2 treatment that would minimize the hormone’s effects in the periphery while maintaining the beneficial cognitive effects is desirable. To achieve this goal, my dissertation work bridged two distinct scientific fields – behavioral neuroendocrinology and polymeric drug delivery – with the overarching aim of targeting the delivery of E2 to the brain to achieve maximal cognitively-beneficial effects with minimal undesired uterine stimulation. This aim was addressed via three distinct delivery strategies: 1) combining E2 with a cognitively-beneficial progestogen, 2) encapsulating E2 in polymeric nanoparticles, and 3) solubilizing E2 using cyclodextrins for intranasal administration. Findings revealed that although all E2-containing treatments increased uterine horn weights, a marker of uterine stimulation, in middle-aged ovariectomized rats, some E2 treatment formulations yielded memory improvements, others were neutral in their effects on memory, and some impaired memory. Together, data from this dissertation set the stage for targeted E2 delivery research to optimize the cognitive therapeutic effects of E2 in the context of menopause while minimizing peripheral burden, leading to translationally relevant clinical implications for women’s health.
ContributorsPrakapenka, Alesia (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Conrad, Cheryl (Committee member) / Stabenfeldt, Sarah (Committee member) / Sirianni, Rachael (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The current trend of interconnected devices, or the internet of things (IOT) has led to the popularization of single board computers (SBC). This is primarily due to their form-factor and low price. This has led to unique networks of devices that can have unstable network connections and minimal processing power.

The current trend of interconnected devices, or the internet of things (IOT) has led to the popularization of single board computers (SBC). This is primarily due to their form-factor and low price. This has led to unique networks of devices that can have unstable network connections and minimal processing power. Many parallel program- ming libraries are intended for use in high performance computing (HPC) clusters. Unlike the IOT environment described, HPC clusters will in general look to obtain very consistent network speeds and topologies. There are a significant number of software choices that make up what is referred to as the HPC stack or parallel processing stack. My thesis focused on building an HPC stack that would run on the SCB computer name the Raspberry Pi. The intention in making this Raspberry Pi cluster is to research performance of MPI implementations in an IOT environment, which had an impact on the design choices of the cluster. This thesis is a compilation of my research efforts in creating this cluster as well as an evaluation of the software that was chosen to create the parallel processing stack.
ContributorsO'Meara, Braedon Richard (Author) / Meuth, Ryan (Thesis director) / Dasgupta, Partha (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
This thesis discusses three recent optimization problems that seek to reduce disease spread on arbitrary graphs by deleting edges, and it discusses three approximation algorithms developed for these problems. Important definitions are presented including the Linear Threshold and Triggering Set models and the set function properties of submodularity and monotonicity.

This thesis discusses three recent optimization problems that seek to reduce disease spread on arbitrary graphs by deleting edges, and it discusses three approximation algorithms developed for these problems. Important definitions are presented including the Linear Threshold and Triggering Set models and the set function properties of submodularity and monotonicity. Also, important results regarding the Linear Threshold model and computation of the influence function are presented along with proof sketches. The three main problems are formally presented, and NP-hardness results along with proof sketches are presented where applicable. The first problem seeks to reduce spread of infection over the Linear Threshold process by making use of an efficient tree data structure. The second problem seeks to reduce the spread of infection over the Linear Threshold process while preserving the PageRank distribution of the input graph. The third problem seeks to minimize the spectral radius of the input graph. The algorithms designed for these problems are described in writing and with pseudocode, and their approximation bounds are stated along with time complexities. Discussion of these algorithms considers how these algorithms could see real-world use. Challenges and the ways in which these algorithms do or do not overcome them are noted. Two related works, one which presents an edge-deletion disease spread reduction problem over a deterministic threshold process and the other which considers a graph modification problem aimed at minimizing worst-case disease spread, are compared with the three main works to provide interesting perspectives. Furthermore, a new problem is proposed that could avoid some issues faced by the three main problems described, and directions for future work are suggested.
ContributorsStanton, Andrew Warren (Author) / Richa, Andrea (Thesis director) / Czygrinow, Andrzej (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
In the last few years, billion-dollar companies like Yahoo and Equifax have had data breaches causing millions of people’s personal information to be leaked online. Other billion-dollar companies like Google and Facebook have gotten in trouble for abusing people’s personal information for financial gain as well. In this new age

In the last few years, billion-dollar companies like Yahoo and Equifax have had data breaches causing millions of people’s personal information to be leaked online. Other billion-dollar companies like Google and Facebook have gotten in trouble for abusing people’s personal information for financial gain as well. In this new age of technology where everything is being digitalized and stored online, people all over the world are concerned about what is happening to their personal information and how they can trust it is being kept safe. This paper describes, first, the importance of protecting user data, second, one easy tool that companies and developers can use to help ensure that their user’s information (credit card information specifically) is kept safe, how to implement that tool, and finally, future work and research that needs to be done. The solution I propose is a software tool that will keep credit card data secured. It is only a small step towards achieving a completely secure data anonymized system, but when implemented correctly, it can reduce the risk of credit card data from being exposed to the public. The software tool is a script that can scan every viable file in any given system, server, or other file-structured Linux system and detect if there any visible credit card numbers that should be hidden.
ContributorsPappas, Alexander (Author) / Zhao, Ming (Thesis director) / Kuznetsov, Eugene (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Political polarization is the coalescence of political parties -- and the individuals of which parties are composed -- around opposing ends of the ideological spectrum. Political parties in the United States have always been divided, however, in recent years this division has only intensified. Recently, polarization has also wound its

Political polarization is the coalescence of political parties -- and the individuals of which parties are composed -- around opposing ends of the ideological spectrum. Political parties in the United States have always been divided, however, in recent years this division has only intensified. Recently, polarization has also wound its way to the Supreme Court and the nomination processes of justices to the Court. This paper examines how prevalent polarization in the Supreme Court nomination process has become by looking specifically at the failed nomination of Judge Merrick Garland and the confirmations of now-Justices Neil Gorsuch and Brett Kavanaugh. This is accomplished by comparing the ideologies and qualifications of the three most recent nominees to those of previous nominees, as well as analysing the ideological composition of the Senate at the times of the individual nominations.
ContributorsJoss, Jacob (Author) / Hoekstra, Valerie (Thesis director) / Critchlow, Donald (Committee member) / Computer Science and Engineering Program (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
The original version of Helix, the one I pitched when first deciding to make a video game
for my thesis, is an action-platformer, with the intent of metroidvania-style progression
and an interconnected world map.

The current version of Helix is a turn based role-playing game, with the intent of roguelike
gameplay and a dark

The original version of Helix, the one I pitched when first deciding to make a video game
for my thesis, is an action-platformer, with the intent of metroidvania-style progression
and an interconnected world map.

The current version of Helix is a turn based role-playing game, with the intent of roguelike
gameplay and a dark fantasy theme. We will first be exploring the challenges that came
with programming my own game - not quite from scratch, but also without a prebuilt
engine - then transition into game design and how Helix has evolved from its original form
to what we see today.
ContributorsDiscipulo, Isaiah K (Author) / Meuth, Ryan (Thesis director) / Kobayashi, Yoshihiro (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to

RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to properly dispose of the material. Some searches will show locations of facilities near users that collect certain materials and dispose of the materials properly. This is a full stack software project that explores open source software and APIs, UI/UX design, and iOS development.
ContributorsTran, Nikki (Author) / Ganesh, Tirupalavanam (Thesis director) / Meuth, Ryan (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05