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.
In this study, the influence of fluid mixing on temperature and geochemistry of hot spring fluids is investigated. Yellowstone National Park (YNP) is home to a diverse range of hot springs with varying temperature and chemistry. The mixing zone of interest in this paper, located in Geyser Creek, YNP, has been a point of interest since at least the 1960’s (Raymahashay, 1968). Two springs, one basic (~pH 7) and one acidic (~pH 3) mix together down an outflow channel. There are visual bands of different photosynthetic pigments which suggests the creation of temperature and chemical gradients due to the fluids mixing. In this study, to determine if fluid mixing is driving these changes of temperature and chemistry in the system, a model that factors in evaporation and cooling was developed and compared to measured temperature and chemical data collected downstream. Comparison of the modeled temperature and chemistry to the measured values at the downstream mixture shows that many of the ions, such as Cl⁻, F⁻, and Li⁺, behave conservatively with respect to mixing. This indicates that the influence of mixing accounts for a large proportion of variation in the chemical composition of the system. However, there are some chemical constituents like CH₄, H₂, and NO₃⁻, that were not conserved, and the concentrations were either depleted or increased in the downstream mixture. Some of these constituents are known to be used by microorganisms. The development of this mixing model can be used as a tool for predicting biological activity as well as building the framework for future geochemical and computational models that can be used to understand the energy availability and the microbial communities that are present.