Chronic hepatitis C in Swedish subjects receiving opiate substitution therapy-Factors associated with advanced fibrosis.

Background: Opiate substitution therapy (OST) reduces the risk of death from directly drug-related causes in heroin users, allowing other chronic health problems to emerge. People who inject drugs (PWID) are exposed to hepatitis C virus (HCV), with an associated risk of chronic liver disease. We investigated HCV prevalence and liver-related morbidity in a cohort of OST recipients, and analyzed factors associated with significant hepatic fibrosis. Methods: All patients registered on 1 April 2008 in 4 clinics providing OST in the 3 largest cities in Sweden were eligible for inclusion. HCV viremic subjects were evaluated for fibrosis stage by liver biopsy, transient elastometry (TE), and/or a biochemical fibrosis index (Göteborg University Cirrhosis Index; GUCI). Factors associated with severity of fibrosis were determined by logistic regression analysis. Results: Out of 524 eligible patients, 277 consented to enrolment. Two hundred and thirty-six subjects (88%) were anti-HCV-positive, and 162 of these were viremic (69%). Significant liver fibrosis (defined as Ishak stages F3-F6, TE value ≥ 8.85 kPa, or GUCI > 0.33) was found in 69 out of 103 (67%) tested viremic patients, and was associated with alcohol intake (p = 0.03), higher body mass index (BMI; p = 0.04), and the presence of anti-HBc antibodies (indicating exposure to hepatitis B virus (HBV); p = 0.02). Conclusions: Significant liver fibrosis was detected in two-thirds of HCV viremic OST recipients in this cohort, and was associated with alcohol use, high BMI, and exposure to HBV. These findings indicate that the management of HCV and associated risk factors should be emphasized in Swedish OST programs

Protein distance constraints predicted by neural networks and probability density functions

3To whom correspondence should be addressed We predict interatomic Cα distances by two independent data driven methods. The first method uses statistically derived probability distributions of the pairwise distance between two amino acids, whilst the latter method consists of a neural network prediction approach equipped with windows taking the context of the two residues into account. These two methods are used to predict whether distances in independent test sets were above or below given thresholds. We investigate which distance thresholds produce the most information-rich constraints and, in turn, the optimal performance of the two methods. The predictions are based on a data set derived using a new threshold which defines when sequence similarity implies structural similarity. We show that distances in proteins are predicted more accurately by neural networks than by probability density functions. We show that the accuracy of the predictions can be further increased by using sequence profiles. A threading method based on the predicted distances is presented. A homepage with software, predictions and data related to this paper is available a

Treatment for chronic hepatitis C in a cohort of opiate substitution therapy recipients in three Swedish cities - completion rates and efficacy.

Opiate substitution treatment (OST) programs could provide opportunities for management of comorbidities, such as hepatitis C virus (HCV) infection, in people who inject drugs. We aimed to prospectively evaluate the real-life feasibility of interferon/ribavirin-based HCV treatment in OST recipients, with a special focus on psychiatric status and health-related quality of life