Cancer rates vary between people, between cultures, and between tissue types, driven by clinically relevant distinctions in the risk factors that lead to different cancer types. Despite the importance of cancer location in human health, little is known about tissue-specific cancers in non-human animals. We can gain significant insight into how evolutionary history has shaped mechanisms of cancer suppression by examining how life history traits impact cancer susceptibility across species. Here, we perform multi-level analysis to test how species-level life history strategies are associated with differences in neoplasia prevalence, and apply this to mammary neoplasia within mammals. We propose that the same patterns of cancer prevalence that have been reported across species will be maintained at the tissue-specific level. We used a combination of factor analysis and phylogenetic regression on 13 life history traits across 90 mammalian species to determine the correlation between a life history trait and how it relates to mammary neoplasia prevalence. The factor analysis presented ways to calculate quantifiable underlying factors that contribute to covariance of entangled life history variables. A greater risk of mammary neoplasia was found to be correlated most significantly with shorter gestation length. With this analysis, a framework is provided for how different life history modalities can influence cancer vulnerability. Additionally, statistical methods developed for this project present a framework for future comparative oncology studies and have the potential for many diverse applications.

Hundreds of thousands of people die annually from malaria; a protozoan of the genus Plasmodium is responsible for this mortality. The Plasmodium parasite undergoes several life stages within the mosquito vector, the transition between which require passage across the lumen of the mosquito midgut. It has been observed that in about 15% of parasites that develop ookinetes in the mosquito abdomen, sporozoites never develop in the salivary glands, indicating that passage across the midgut lumen is a significant barrier in parasite development (Gamage-Mendis et al., 1993). We aim to investigate a possible correlation between passage through the midgut lumen and drug-resistance trends in Plasmodium falciparum parasites. This study contains a total of 1024 Anopheles mosquitoes: 187 Anopheles gambiae and 837 Anopheles funestus samples collected in high malaria transmission areas of Mozambique between March and June of 2016. Sanger sequencing will be used to determine the prevalence of known resistance alleles for anti-malarial drugs: chloroquine resistance transporter (pfcrt), multidrug resistance (pfmdr1) gene, dihydropteroate synthase (pfdhps) and dihydrofolate reductase (pfdhfr). We compare prevalence of resistance between abdomen and head/thorax in order to determine whether drug resistant parasites are disproportionately hindered during their passage through the midgut lumen. A statistically significant difference between resistance alleles in the two studied body sections supports the efficacy of new anti-malarial gene surveillance strategies in areas of high malaria transmission.

For our project, we explored the growth of the ASU BioDesign Clinical Testing Laboratory (ABCTL) from a standard university research lab to a COVID-19 testing facility through a business lens. The lab has pioneered the saliva-test in the Western United States. This thesis analyzes the laboratory from various business concepts and aspects. The business agility of the lab and it’s quickness to innovation has allowed the lab to enjoy great success. Looking into the future, the laboratory has a promising future and will need to answer many questions to remain the premier COVID-19 testing institution in Arizona.

One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it necessitates the development of increasingly stronger drugs to combat resistant pathogens. Not only is this strategy costly and time consuming, it is also unsustainable. To contend with this problem, many multi-drug treatment strategies are being explored. Previous studies have shown that resistance to some drug combinations is not possible, for example, resistance to a common antifungal drug, fluconazole, seems impossible in the presence of radicicol. We believe that in order to understand the viability of multi-drug strategies in combating drug resistance, we must understand the full spectrum of resistance mutations that an organism can develop, not just the most common ones. It is possible that rare mutations exist that are resistant to both drugs. Knowing the frequency of such mutations is important for making predictions about how problematic they will be when multi-drug strategies are used to treat human disease. This experiment aims to expand on previous research on the evolution of drug resistance in S. cerevisiae by using molecular barcodes to track ~100,000 evolving lineages simultaneously. The barcoded cells were evolved with serial transfers for seven weeks (200 generations) in three concentrations of the antifungal Fluconazole, three concentrations of the Hsp90 inhibitor Radicicol, and in four combinations of Fluconazole and Radicicol. Sequencing data was used to track barcode frequencies over the course of the evolution, allowing us to observe resistant lineages as they rise and quantify differences in resistance evolution across the different conditions. We were able to successfully observe over 100,000 replicates simultaneously, revealing many adaptive lineages in all conditions. Our results also show clear differences across drug concentrations and combinations, with the highest drug concentrations exhibiting distinct behaviors.

A large section of United States citizens live far away from supermarkets and do not have an easy way to get to one. This portion of the population lives in an area called a food desert. Food deserts are geographic areas in which access to affordable, healthy food, such as fresh produce, is limited or completely nonexistent due to the absence of convenient grocery stores. Individuals living in food deserts are left to rely on convenience store snacks and fast food for their meals because they do not have access to a grocery store with fresh produce in their area. Unhealthy foods also lead to health issues, as people living in food deserts are typically at a higher risk of diet-related conditions, such as obesity, diabetes, and cardiovascular disease. Harvest, a sustainable farming network, is a smartphone application that teaches and guides people living in small spaces through the process of growing fresh, nutritious produce in their own homes. The app will guide users through the entire process of gardening, from seed to harvest. Harvest would give individuals living in food deserts an opportunity to access fresh produce that they currently can’t access. An overwhelming response based on our user discussion and market analysis revealed that our platform was in demand. Development of a target market, brand guide, and full-lifecycle were beneficial during the second semester as Harvest moved forward. Through the development of a website, social media platform, and smartphone application, Harvest grew traction for our platform. Our social media accounts saw a 1700% growth rate, and this wider audience was able to provide helpful feedback.