Most hereditary tumors show aberrations in DNA repair genes or their regulators. In contrast, only a minority of sporadic tumors show alterations in these genes. As a result, genomic instability is currently considered an enhancer of tumorigenesis rather than an obligatory event in this process. However, tumor heterogeneity presents a significant technical challenge for most cancer genomics studies performed at less than 100× mean resolution depth. To address the importance of genomic instability in prostate carcinogenesis and tumor progression, we performed ultrahigh depth exome sequencing of 124 DNA damage repair/response (repairome) genes in 63 tumors and matched normal tissue samples in African Americans and Caucasians. The average sequence depth was 712-fold for DNA isolated from normal tissue and 368-fold for FFPE tumors. We identified 671 somatic mutations in tumors from African Americans and 762 somatic mutations in tumors in Caucasians. The most frequently mutated DNA repairome genes were EXO1,

Chytridiomycosis is an emerging disease caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) that poses a serious threat to frog populations worldwide. Several studies have shown that inoculation of bacterial species Janthinobacterium lividum (Jl) can mitigate the impact of the disease. However, there are many questions regarding this interaction. A mathematical model of a frog population infected with chytridiomycosis is developed to investigate how the inoculation of Jl

The generalized monotone iterative technique for sequential 2 q order Caputo fractional boundary value problems, which is sequential of order q, with mixed boundary conditions have been developed in our earlier paper. We used Green’s function representation form to obtain the linear iterates as well as the existence of the solution of the nonlinear problem. In this work, the numerical simulations for a linear nonhomogeneous sequential Caputo fractional boundary value problem for a few specific nonhomogeneous terms with mixed boundary conditions have been developed. This in turn will be used as a tool to develop the accurate numerical code for the linear nonhomogeneous sequential Caputo fractional boundary value problem for any nonhomogeneous terms with mixed boundary conditions. This numerical result will be essential to solving a nonlinear sequential boundary value problem, which arises from applications of the generalized monotone method.

We study a quasilinear hierarchically size-structured population model presented in [4]. In this model the growth, mortality and reproduction rates are assumed to depend on a function of the population density. In [4] we showed that solutions to this model can become singular (measure-valued) in finite time even if all the individual parameters are smooth. Therefore, in this paper we develop a first order finite difference scheme to compute these measure-valued solutions. Convergence analysis for this method is provided. We also develop a high resolution second order scheme to compute the measure-valued solution of the model and perform a comparative study between the two schemes.

West Nile Virus (WNV), primarily spread by the Culex species of mosquito, accounts for a large percentage of mosquito-borne diseases. In order to investigate the dynamics of WNV, an agent-based model was developed in the NetLogo modeling environment that simulates the transmission of the virus by incorporating temperature, humans, horses, birds, and a mosquito population. This model allows the observer to view simulations between the agents listed and measure the impact of vaccinations on the survival rate of horses infected with WNV. Furthermore, the model integrates and evaluates the impact public health agents have on human WNV dynamics through their education of the general public and containment of mosquito populations. The intention of the simulation results from this model is to help develop a vaccination strategy for horse populations, while also demonstrating the usefulness of public health agents' efforts on the individual agents within the disease dynamics.