Phase 3 trial of first generation protease inhibitor therapy for hepatitis C virus/human immunodeficiency virus coinfection

AIMTo evaluate efficacy/safety of hepatitis C virus (HCV) protease inhibitor boceprevir with pegylated interferon (PEG-IFN) alfa and weight-based ribavirin (RBV) in a phase 3 trial. METHODSA prospective, multicenter, phase 3, open-label, single-arm study of PEG-IFN alfa, weight-based RBV, and boceprevir, with a PEG-IFN/RBV lead-in phase was performed. The HCV/human immunodeficiency virus coinfected study population included treatment naïve (TN) and treatment experienced (TE) patients. Treatment duration ranged from 28 to 48 wk dependent upon response-guided criteria. All patients had HCV Genotype 1 with a viral load > 10000 IU/mL. Compensated cirrhosis was allowed. Sample size was determined to establish superiority to historical (PEG-IFN plus RBV) rates in sustained viral response (SVR). RESULTSA total of 257 enrolled participants were analyzed (135 TN and 122 TE). In the TN group, 81.5% were male and 54.1% were black. In the TE group, 76.2% were male and 47.5% were white. Overall SVR12 rates (HCV RNA P = 0.002). Among the TN, SVR12 was 42.1% among whites and 27.4% among blacks (P = 0.09). CONCLUSIONThe trial met its hypothesis of improved SVR compared to historical controls but overall SVR rates were low. All-oral HCV treatments will mitigate these difficulties.

Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network

The healthcare industry is in dire need of rapid microbial identification techniques for treating microbial infections.Microbial infections are a major healthcare issue worldwide,as these widespread diseases often develop into deadly symptoms.While studies have shown that an early appropriate antibiotic treatment significantly reduces the mortality of an infection,this effective treatment is difficult to practice.The main obstacle to early appropriate antibiotic treatments is the long turnaround time of the routine microbial identification,which includes time-consuming sample growth.Here,we propose a microscopy-based framework that identifies the pathogen from single to few cells.Our framework obtains and exploits the morphology of the limited sample by incorporating three-dimensional quantitative phase imaging and an artificial neural network.We demonstrate the identification of 19 bacterial species that cause bloodstream infections,achieving an accuracy of 82.5%from an individual bacterial cell or cluster.This performance,comparable to that of the gold standard mass spectroscopy under a sufficient amount of sample,underpins the effectiveness of our framework in clinical applications.Furthermore,our accuracy increases with multiple measurements,reaching 99.9%with seven different measurements of cells or clusters.We believe that our framework can serve as a beneficial advisory tool for clinicians during the initial treatment of infections.

Silver nanoislands on cellulose fibers for chromatographic separation and ultrasensitive detection of small molecules

High-throughput small-molecule assays play essential roles in biomedical diagnosis,drug discovery,environmental analysis,and physiological function research.Nanoplasmonics holds a great potential for the label-free detection of small molecules at extremely low concentrations.Here,we report the development of nanoplasmonic paper(NP-paper)for the rapid separation and ultrasensitive detection of mixed small molecules.NP-paper employs nanogap-rich silver nanoislands on cellulose fibers,which were simply fabricated at the wafer level by using low-temperature solid-state dewetting of a thin silver film.The nanoplasmonic detection allows for the scalable quantification and identification of small molecules over broad concentration ranges.Moreover,the combination of chromatographic separation and nanoplasmonic detection allows both the highly sensitive fluorescence detection of mixed small molecules at the attogram level and the label-free detection at the sub-nanogram level based on surface-enhanced Raman scattering.This novel material provides a new diagnostic platform for the high-throughput,low-cost,and label-free screening of mixed small molecules as an alternative to conventional paper chromatography.