<p> Raccoon rabies in the Northeastern United States rapidly expanded in genetic diversity and spatially from 1977 to 1999 during the Mid-Atlantic outbreak. For a portion this expansion, from 1983 to 1986, the rate of epidemic expansion slowed. This is reflected in a plateau in the effective number of infections and a decrease in the rate of invasion into new areas. I used a mathematical model of rabies dynamics to test alternative hypotheses for the observed reduction in the spread of raccoon rabies. It has been theorized that the geography of the Mid-Atlantic States, particularly the rivers and terrestrial habitat, influenced these changes. I will test ten hypotheses for the slowdown using a spatially explicit model of raccoon rabies dynamics that includes a model of the pathogen&rsquo;s molecular evolution. </p><p> The ten hypotheses were to test if the reduction in rate of spread was caused by 1) a geographic bottleneck created by the Atlantic coast, 2) rivers limiting the movement of raccoons, 3) rivers halting the movement of raccoons, 4) habitat limiting the movement of raccoons 5) a combination of rivers limiting movement, habitat and mountains, 6) a combination of rivers halting movement, habitat and mountains, 7) the Susquehanna River limiting movement, 8) the Susquehanna River halting movement, 9) an unidentified barrier limiting movement and 10) an unidentified barrier halting movement. </p><p> Our model results suggest that the slowdown observed from 1983 to 1987 was caused by a combination of major rivers in the area. The effects of rivers appear to explain the slowdown in the epidemic, but the addition of habitat and mountains is important to explain the sustained high levels of demographic spread in the late stages of the epidemic. In addition, our results indicate that the currently accepted estimate of raccoon dispersal over rivers may be an overestimate.</p>

Prostate cancer is the most commonly diagnosed cancer in men and nearly 30,000 patients will die this year due to complications arising from the disease. Prostate cancer patients are frequently treated with androgen deprivation therapies, but the duration of response is variable, and patients frequently progress to an incurable stage of the disease referred to as castration-resistant prostate cancer (CRPC). Second-generation AR antagonists such as enzalutamide and apalutamide are effective therapies that block androgen receptor (AR) transactivation and signaling in over 50% of CRPC patients. However, an estimated 30% of responders will develop resistance to these therapies within two years. There is another class of AR antagonists which are referred to as pan AR antagonists, that have shown to inhibit the activity of wild-type AR as well as several mutated versions of AR. Currently, there are several pan AR antagonists in preclinical development and approved for the treatment of CRPC in patients harboring pathogenic point mutations in AR. We chose four genetically distinct AR-positive prostate cancer preclinical models to generate enzalutamide, JNJ-pan-AR, or apalutamide resistant cell lines. We then performed transcriptomic and proteomic profiling on the AR antagonist sensitive and resistant cell lines to uncover molecular alterations that may be critical to the maintenance and/ or predictive biomarkers of the resistant phenotype. Global profiling uncovered significant variability in molecular alterations across the AR antagonist resistant cell lines as well as the prostate cancer preclinical models. However, we uncovered upregulation of AKR1C3 protein expression across all three AR antagonist resistant cell lines using the LNCaP and LNCaP/AR preclinical models. Further characterization of the functional significance of AKR1C3 upregulation demonstrated that AKR1C3 protein expression contributes to JNJ-pan-AR resistance. Similar findings have reported the correlation between AKR1C3 expression and changes in drug efficacy across several chemotherapeutic agents approved to CRPC treatment. Collectively the findings from this study support the rationale of AKR1C3 as a target for AR antagonist resistant prostate cancer disease progression.