A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen

<p>Abstract</p> <p>Background</p> <p>HIV-1 genotypic susceptibility scores (GSSs) were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART) switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed.</p> <p>Methods</p> <p>We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90^thday after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb) and other covariates by means of Cox regression and random survival forests (RSF). Prediction models were validated via the bootstrap and c-index measure.</p> <p>Results</p> <p>The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70), while RSF showed a better performance (c-index≈0.73, p < 0.0001 vs. Cox regression). Variable importance according to RSF was concordant with the Cox hazards.</p> <p>Conclusions</p> <p>GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.</p

Contribution to the Protection of PVG Connected to Three Phase Electrical Network Supply

AbstractIn this paper we propose to investigate, model, optimize and simulate the connection of a 3Kwc domestic photovoltaic generator to the three-phase power network throughout a current-controlled voltage source inverter. The current-controlled voltage source inverter tasks are:•Tracking the PVG maximum power point.•Injecting the maximum power into a three phase electrical network with unit power factor.The totality of the produced energy by the PVG has to be injected in the network, whereas the electricity requirement for domestic use has to be withdrawn from the network supply .This is in order to avoid batteries storage problems .As well as the realization of a decoupling system which can protect the generator from perturbations that can reach the electrical network supply

Advanced Fuzzy MPPT Controller for a Stand-alone PV System

AbstractIn this paper an intelligent method of maximum power point tracking (MPPT) using fuzzy logic control for stand-alone photovoltaic (PV) system has been presented. The PV system is composed of PV solar array, buck DC-DC converter, and MPPT controller. Fuzzy logic controller (FLC) is easy to implement, and does not need knowledge of the exact model of the system. Simulation results compared with those obtained by the conventional perturbation and observation (P&O) technique show the effectiveness of the fuzzy logic controller during steady-state and varying weather conditions

Natural NS5A inhibitor resistance associated substitutions in hepatitis C virus genotype 1 infected patients from Italy

Objectives: Genetic variability in NS5A is associated with different levels of resistance to the currently licensed NS5A inhibitors. The aim of this study was to detect NS5A inhibitor resistance associated substitutions (RASs) in hepatitis C virus (HCV) genotype 1 (GT1) patients who are naive to direct-acting HCV antivirals. Methods: Amplification, Sanger sequencing and phylogenetic analysis of the HCV NS5A region were performed on plasma obtained from 122 consecutive patients with HCV chronic infection attending four different clinics in Italy. Results: NS5A inhibitor RASs were detected in 14/61 (23.0%) HCV GT1b and 3/61 (4.9%) HCV GT1a infected patients (p 0.007). The pan-genotypic RAS Y93H was detected in 1 (1.6%) GT1a and 4 (6.6%) GT1b patients. GT1a sequences clustered into two different clades with RASs detected in 1/34 (2.9%) clade I and 2/27 (7.4%) clade II sequences. Conclusions: Although the impact of naturally occurring NS5A RASs might be limited with upcoming pan-genotypic treatment regimens, this information is still useful to map naturally occurring HCV variants in different geographic areas in the context of current HCV therapy

Naturally occurring hepatitis C virus (HCV) NS3/4A protease inhibitor resistance-related mutations in HCV genotype 1-infected subjects in Italy

To assess the prevalence of hepatitis C virus (HCV) NS3/4A protease inhibitor (PI) resistance mutations in HCV genotype 1-infected PI-naive individuals in Italy