Acetylcholinesterase (AChE) inhibition by chemical toxicants such as organophosphates, nerve agents, and carbamates can lead to a series of adverse health outcomes including seizures, coma, and death. An adverse outcome pathway (AOP) is a framework that describes a series of biologically measurable key events (KEs) leading from some molecular initiating event (MIE) to an adverse outcome (AO) of regulatory significance, all developed and hosted in the AOP Wiki. A quantitative AOP (qAOP) is a mathematical model that predicts how perturbations in the MIE affect KEs based on the key event relationships (KERs) that define the AOP. The purpose of this thesis was to expand upon the KERs that define the AOP for AChE inhibition leading to neurodegeneration in order to better understand the effects of AChE inhibitors and the risks they pose to ecosystems, wildlife, and human health. In order to reduce the resources and time spent for chemical toxicity testing, a qAOP was developed based on the available quantitative data and models that supported the AOP. A literature review for the collection of qualitative evidence and quantitative data in support of the AOP was performed resulting in further expansion of the relationships between key events (KERs) through construction of additional KER description pages. A model evaluation was performed by comparing the qAOP model predictions with experimental data, with a subsequent sensitivity analysis of unknown parameters. The qAOP model simulates the MIE through its fifth KE (KE 5) and KE 7. Model predictions compared to experimentally measured data either under- or overpredicting multiple KEs warranting additional refinement such as a formal parameter optimization. Overall, more data amenable to qAOP model development are needed. To aid qAOP model development, the presentation of data in the AOPWiki may be improved by presenting the quantitative data in the AOP Wiki in a tabular format and allowing for the hosting of mathematical models or raw data. With these recommendations in mind, and through continued AOP construction in the AOP Wiki, new qAOP models will be developed, ultimately supporting chemical risk assessment and the mitigation of effects upon exposed individuals and wildlife populations.

Fish consumption advisories are important to the protection of human health but are not often widely communicated nor systematically or comprehensively conducted. The objective of this thesis is to explore the strengths and weaknesses of current fish consumption advisory programs in the US and Canada, providing a comparison between the two countries. The US and Canada were chosen because the two countries are relatively similar in socio-economic makeup as well as in their state vs. federal regulatory setup, allowing for easier comparison. At the sub-federal level, Arizona was chosen to serve as a case study for the US, and Nova Scotia as a case study for Canada. To compare each country, fish consumption advisory programs were broadly described across the 50 US states and 13 Canadian provinces and territories to provide a full understanding of the variation in such programs within each country. In addition to comparison across states and provinces, opportunities and challenges for policy correction to strengthen fish consumption advisory programs will be provided, including suggestions on how the US and Canada can learn from each other in creating better environmental policy. Policy is addressed as a means of improving fish consumption advisory programs because without state or federal requirements to monitor fish tissue for contaminants of concern across the US and Canada, there is no guarantee human health and environmental justice will remain protected in either country. Potential global sources of enhanced environmental policy will be provided as examples of further opportunities for the US and Canada to improve fish consumption advisory program policies.

Cellular and molecular biologists often perform cellular assays to obtain a better understanding of how cells work. However, in order to obtain a measurable response by the end of an experiment, the cells must reach an ideal cell confluency. Prior to conducting the cellular assays, range-finding experiments need to be conducted to determine an initial plating density that will result in this ideal confluency, which can be costly. To help alleviate this common issue, a mathematical model was developed that describes the dynamics of the cell population used in these experiments. To develop the model, images of cells from different three-day experiments were analyzed in Photoshop®, giving a measure of cell count and confluency (the percentage of surface area covered by cells). The cell count data were then fitted into an exponential growth model and were correlated to the cell confluency to obtain a relationship between the two. The resulting mathematical model was then evaluated with data from an independent experiment. Overall, the exponential growth model provided a reasonable and robust prediction of the cell confluency, though improvements to the model can be made with a larger dataset. The approach used to develop this model can be adapted to generate similar models of different cell-lines, which will reduce the number of preliminary range-finding experiments. Reducing the number of these preliminary experiments can save valuable time and experimental resources needed to conduct studies using cellular assays.