Occult hepatitis B infection in a hemodialysis population in Guilan province, northern Iran

Hemodialysis (HD) patients are vulnerable to transfusion-transmitted infections such as hepatitis B virus (HBV). HBV infection with undetectable hepatitis B surface antigens (HBsAg) is described as occult HBV and can lead to serious complications. The aim of this study was to evaluate the prevalence of occult HBV and concomitant factors in HD patients. Using a cross-sectional design, clinical and epidemiological data were obtained from May to September 2009 in 11 different HD units in Guilan province in northern Iran. After serological testing for HBV surface antigens in 514 HD patients using a third-generation enzyme-linked immunosorbent assay kit (Diapro, Milano, Italy), HBsAg-negative patients were tested for HBV DNA using a Qiagen PCR kit (Artus Qiagen GmbH, Hilden, Germany). After omission of seven HBsAg-positive patients, 507 patients were included in the study, 280 (55.2%) of whom were male and 227 (44.8%) were female. Patients ranged in age from 16 to 66 years (mean 53.2 years). No HBV DNA was detected in HBsAg-negative patients. Some 59 patients (11.6%) were anti-hepatitis C virus positive and 32 (6.3%) were hepatitis C virus positive according to polymerase chain reaction. The study results indicate that occult HBV infection is not a significant health problem in HD patients in Guilan province.     

Connectionist approaches for solubility prediction of n-alkanes in supercritical carbon dioxide

Carbon dioxide injection is a known promising and economical technology for improving oil recovery. Despite its immense effect on oil recovery, the application of this technique in modern recovery industry has been limited due to poor solubility of n-alkanes in supercritical CO₂. Therefore, it is very consequential to investigate the solubility of different n-alkanes in supercritical CO₂. Since experimental methods for measuring the solubility of n-alkanes in supercritical CO₂ at different temperatures and pressures are not economical and usually take a long time, feasibility of applying intelligent tools in the solubility prediction of different n-alkanes in supercritical CO₂ at pressures up to 45.9 MPa was conducted in this study. For this purpose, two models including an artificial neural network and an adaptive neuro-fuzzy interference system (ANFIS) both trained with particle swarm optimization (PSO) algorithm were used for simulating this process. Calculated mole fractions of n-alkanes in supercritical CO₂ from ANFIS–PSO model were excellently consistent with actual measured values. Moreover, comparison between these models and Chrastil semiempirical correlation show superiority and accuracy of the proposed ANFIS–PSO approach. Results of this study indicate that ANFIS–PSO method is a powerful technique for predicting solubility of n-alkanes in supercritical CO₂.