The Georgia Environmental Protection Division (GA EPD) performs limited water quality monitoring and relies on point source detection to identify sewage spills, which overlooks the complex socioeconomic and political factors that influence urban bacteria pollution. The South River Watershed Alliance is an Atlanta-based community group that conducts regular E. coli monitoring with Georgia State University, as there is a particular need to determine baseline in situ bacteria levels in a region that carries the burden of flooding and sewage overflows due to state disinvestment in infrastructure and failed regulatory frameworks. Georgia has recently adopted the national E. coli standard more than 30 years after the Environmental Protection Agency first recommended the transition from the fecal coliform standard in 1986, but the state is currently utilizing a scientifically flawed strategy in its revisions to the National Pollution Discharge Elimination System (NPDES) permit program that will allow direct conversions between fecal coliform and E. coli values. This bacterial equivalency strategy undermines the purpose of the E. coli standard to protect public health. Given that Georgia environmental law normalizes heightened levels of E. coli in urban streams without further investigation into its driving factors, the latter strategy is one example of several regulatory measures which contribute to what Ruth Wilson Gilmore describes as organized abandonment. My presentation will provide an overview of Georgia water quality policy situated within a critical geography framework to critique the impact of state regulation on the Upper South River watershed.

Collective invasion plays a pivotal role in cancer metastasis, characterized by coordinated movement of leader and follower cells into surrounding tissues. This study presents a continuous mathematical model to investigate the dynamics underlying this process, focusing on leader chemotaxis, cell-cell adhesion, and the conservation of cell numbers. The model incorporates diffusion, chemotaxis, and adhesion terms, governed by parameters for leader-leader ($\alpha_l$), follower-follower ($\alpha_f$), and leader-follower ($\alpha_{fl}$) interactions. Using a nondimensionalized system of partial differential equations solved numerically via the finite element method, we explored invasion dynamics across diverse parameter settings. Preliminary simulations model the leader cells migrating directionally towards a chemoattractant gradient, forming invasion fronts that pull follower cells via strong leader-follower adhesion. Collective invasion is observed when leader-follower adhesion dominated over leader-leader adhesion. Our results aim to provide early insights into the interplay between chemotaxis and adhesion in driving metastatic behavior, and our objective is to further characterize these dynamics based on our model parameters in future work.

Metastasis, the spread of cancer from a primary tumor to distant sites, is driven by coordinated cell behaviors within the tumor microenvironment. A key mechanism underlying metastasis is collective cancer cell migration, which significantly impacts cancer progression and patient outcomes. Experimental studies using spatiotemporal genomic and cellular analysis have uncovered the phenotypic heterogeneity within invading cancer cell populations, distinguishing leader cells—phenotypically stable and highly invasive—from follower cells, which exhibit phenotypic plasticity and limited invasiveness. Despite these advancements, the biophysical properties and interactions governing collective invasion remain poorly understood. To address this knowledge gap, we developed a cell-based computational model based on the cellular Potts model framework to investigate the interplay between leader cell migration, follower cell proliferation, and leader-follower interactions during collective invasion. The model distinguishes between single cell invasion and collective invasion by quantifying invasive area vs. infiltrative invasion area, single vs. clustered cell breakoff, invasive stalk number and height. Our simulations reveal that leader cell migration, leader-follower adhesion, and follower proliferation are critical determinants of collective cancer migration. These findings provide novel insights into the biophysical mechanisms driving collective invasion.

A Compartmentalized Mathematical Model of Hypertrophic Mouse Ventricular Myocytes Dilmini Warnakulasooriya1 and Vladimir E. Bondarenko1,2 1Department of Mathematics and Statistics and 2Neuroscience Institute, Georgia State University, Atlanta, GA, USA Compensated cardiac hypertrophy is considered as an adaptive response of the myocytes to increased workload and develops at early stages of heart failure. Experimentally, cardiac hypertrophy is induced by the procedure called transverse aortic constriction (TAC) during the first week after surgery. It is believed that during the early stage of hypertrophy the heart increases its function without adverse effects. To investigate cardiac hypertrophy, we developed a new comprehensive compartmentalized mathematical model of hypertrophic mouse ventricular myocytes that described the cell geometry, cardiac action potentials, [Ca2+]i transients, and β1- and β2-adrenergic signaling systems. Simulation results obtained with the hypertrophic cell model were compared to those from the normal ventricular myocyte model. Our model simulations revealed the prolongation of the action potential, increased [Ca2+]i transients, lower adenylyl cyclase activity, and generation of pro-arrhythmic events called early afterdepolarizations (EADs) in hypertrophic myocytes as compared to control myocytes. We also explored the mechanisms of EAD for slow stimulation rates (< 1 Hz) upon application of 1 μM of β-adrenergic agonist isoproterenol, which demonstrated a synergistic effect of the late Na+ current INaL, the T-type Ca2+ current ICaT, the L-type Ca2+ current ICaL, and the slow component of the fast Na+ current INa in generation of EADs.