Lack of detection of human papillomavirus DNA in prostate carcinomas in patients from northeastern Brazil

Prostate cancer is the second most common cancer among men in western populations, and despite its high mortality, its etiology remains unknown. Inflammatory processes are related to the etiology of various types of tumors, and prostate inflammation, in particular, has been associated with prostate cancer carcinogenesis and progression. Human papillomavirus (HPV) is associated with benign and malignant lesions in the anogenital tract of both females and males. The possible role of HPV in prostate carcinogenesis is a subject of great controversy. In this study, we aimed to examine the prevalence of HPV infections in prostate carcinomas of patients from northeastern Brazil. This study included 104 tissue samples from primary prostate carcinoma cases. HPV DNA was purified and then amplified using MY09/11 and GP5+/GP6+ degenerate primer sets that detect a wide range of HPV types, and with specific PCR primers sets for E6 and E7 HPV regions to detect HPV 16. None of the samples showed amplification products of HPV DNA for primer sets MY09/11 and GP5+/GP6+, or the specific primer set for the E6 and E7 HPV regions. HPV infection, thus, does not seem to be one of the causes of prostate cancer in the population studied.     

Comparative chemical and biological hydrolytic stability of homologous esters and isosteres

Esters are one of the major functional groups present in the structures of prodrugs and bioactive compounds. Their presence is often associated with hydrolytic lability. In this paper, we describe a comparative chemical and biological stability of homologous esters and isosteres in base media as well as in rat plasma and rat liver microsomes. Our results provided evidence for the hydrolytic structure lability relationship and demonstrated that the hydrolytic stability in plasma and liver microsome might depend on carboxylesterase activity. Molecular modelling studies were performed in order to understand the experimental data. Taken together, the data could be useful to design bioactive compounds or prodrugs based on the correct choice of the ester subunit, addressing compounds with higher or lower metabolic lability.     

A Solution to the Challenge of Optimization on 'Golf-Course'-Like Fitness Landscapes

Genetic algorithms (GAs) have been used to find efficient solutions to numerous fundamental and applied problems. While GAs are a robust and flexible approach to solve complex problems, there are some situations under which they perform poorly. Here, we introduce a genetic algorithm approach that is able to solve complex tasks plagued by so-called ''''golf-course''''-like fitness landscapes. Our approach, which we denote variable environment genetic algorithms (VEGAs), is able to find highly efficient solutions by inducing environmental changes that require more complex solutions and thus creating an evolutionary drive. Using the density classification task, a paradigmatic computer science problem, as a case study, we show that more complex rules that preserve information about the solution to simpler tasks can adapt to more challenging environments. Interestingly, we find that conservative strategies, which have a bias toward the current state, evolve naturally as a highly efficient solution to the density classification task under noisy conditions.