Characterizing Enterovirus 71 and Coxsackievirus A16 Virus-like Particles Production in Insect Cells

Enterovirus 71 (EV71) and Coxsackievirus A16 (CVA16) are two viruses commonly responsible for hand, foot and mouth disease (HFMD) in children. The lack of prophylactic or therapeutic measures against HFMD is a major public health concern. Insect cell-based EV71 and CVA16 virus-like particles (VLPs) are promising vaccine candidates against HFMD and are currently under development. In this paper, the influence of insect cell line, incubation temperature, and serial passaging effect and stability of budded virus (BV) stocks on EV71 and CVA16 VLP production was investigated. Enhanced EV71 and CVA16 VLP production was observed in Sf9 cells compared to High Five (TM) cells. Lowering the incubation temperature from the standard 27 degrees C to 21 degrees C increased the production of both VLPs in Sf9 cells. Serial passaging of CVA16 BV stocks in cell culture had a detrimental effect on the productivity of the structural proteins and the effect was observed with only 5 passages of BV stocks. A 2.7x higher production yield was achieved with EV71 compared to CVA16. High-resolution asymmetric flow field-flow fractionation couple with multi-angle light scattering (AF4-MALS) was used for the first time to characterize EV71 and CVA16 VLPs, displaying an average root mean square radius of 15 +/- 1 nm and 15.3 +/- 5.8 nm respectively. This study highlights the need for different approaches in the design of production process to develop a bivalent EV71 and CVA16 vaccine. (C) 2015 Elsevier Inc. All rights reserved

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

Cog-4 has limited diagnostic test accuracy and validity for cognitive assessment in stroke survivors

Background: Guidelines recommend cognitive screening for all stroke survivors but do not suggest a preferred tool. Certain elements (orientation, executive function, language, and inattention) of the impairment scale, National Institutes of Health Stroke Scale (NIHSS), have been suggested as a short cognitive screening test—Cog-4. We aimed to describe accuracy and validity of Cog-4 against a more detailed cognitive assessment (Montreal Cognitive Assessment [MoCA]). Methods: We assessed consecutive acute stroke unit admissions in 2 hospitals over 3 months. Four independent blinded assessors performed NIHSS and MoCA between days 1 and 4 poststroke. We described test properties of Cog-4 for MoCA-defined cognitive impairment using usual thresholds (Cog-4 ≥ 1 and MoCA &lt; 26 of 30) and described the correlations of individual Cog-4 components with broadly equivalent MoCA domains. Results: We assessed 173 participants; 166 had Cog-4 data and 148 MoCA. MoCA described 84% (n = 124) of assessed participants as having cognitive impairment and the Cog-4, 37% (n = 62). Cog-4 had a sensitivity of .36 (95% confidence interval [CI]: .28-.45) and a specificity of .96 (95% CI: .80-.99) (positive predictive value: .98, negative predictive value: .23) for MoCA-defined cognitive impairment. Individual Cog-4 items correlated with certain MoCA domains, but the strength of association was modest (r = −.44 orientation, −.37 language, −.19 for inattention, and no significant correlation for executive function, P = .72). Conclusions: Our data suggest that many stroke survivors with MoCA-defined cognitive problems would not be detected by Cog-4. Subtest correlations suggest that Cog-4 may not be a valid measure of the cognitive domains that it purports to describe. Other brief cognitive screening tests may be better suited to acute stroke

Engineering hepatitis B virus core particles for targeting HER2 receptors in vitro and in vivo

We acknowledge funding from Biotechnology and Biological Sciences Research Council (BBSRC; (BB/J008656/1)) and the EU FP7-ITN Marie-Curie Network programme RADDEL (290023). NH is a recipient of Graduate School King's Health Partner's scholarship. RK is a Marie-Curie Fellow. S.B. acknowledges funding from the European Research Council under the 7th Framework Program (FP7), ERC Starting Grant No. 335078 COLOURATOMS, and the Integrated Infrastructure Initiative No. 262348European Soft Matter Infrastructure, ESM