Construction and characterization of recombinant flaviviruses bearing insertions between E and NS1 genes

<p>Abstract</p> <p>Background</p> <p>The yellow fever virus, a member of the genus <it>Flavivirus</it>, is an arthropod-borne pathogen causing severe disease in humans. The attenuated yellow fever 17D virus strain has been used for human vaccination for 70 years and has several characteristics that are desirable for the development of new, live attenuated vaccines. We described here a methodology to construct a viable, and immunogenic recombinant yellow fever 17D virus expressing a green fluorescent protein variant (EGFP). This approach took into account the presence of functional motifs and amino acid sequence conservation flanking the E and NS1 intergenic region to duplicate and fuse them to the exogenous gene and thereby allow the correct processing of the viral polyprotein precursor.</p> <p>Results</p> <p>YF 17D EGFP recombinant virus was grew in Vero cells and reached a peak titer of approximately 6.45 ± 0.4 log10 PFU/mL at 96 hours post-infection. Immunoprecipitation and confocal laser scanning microscopy demonstrated the expression of the EGFP, which was retained in the endoplasmic reticulum and not secreted from infected cells. The association with the ER compartment did not interfere with YF assembly, since the recombinant virus was fully competent to replicate and exit the cell. This virus was genetically stable up to the tenth serial passage in Vero cells. The recombinant virus was capable to elicit a neutralizing antibody response to YF and antibodies to EGFP as evidenced by an ELISA test. The applicability of this cloning strategy to clone gene foreign sequences in other flavivirus genomes was demonstrated by the construction of a chimeric recombinant YF 17D/DEN4 virus.</p> <p>Conclusion</p> <p>This system is likely to be useful for a broader live attenuated YF 17D virus-based vaccine development for human diseases. Moreover, insertion of foreign genes into the flavivirus genome may also allow <it>in vivo </it>studies on flavivirus cell and tissue tropism as well as cellular processes related to flavivirus infection.</p

Left atrial volume quantification using cardiac MRI in atrial fibrillation: comparison of the Simpson’s method with biplane area-length, ellipse, and three-dimensional methods

PURPOSELeft atrial volume is an important predictor of future arrhythmias, and it can be assessed by several different methods. Simpson’s method is well accepted as a reference standard, although no standardization exists for cardiac magnetic resonance (CMR). We aimed to compare the estimations of left atrial volumes obtained by the Simpson’s method with three other methods. MATERIALS AND METHODSEighty-one consecutive patients referred for CMR imaging between February 2007 and May 2010 were included in the study (47 males; mean age, 59.4±11.5 years; body mass index, 26.3±3.7 kg/m2). Left atrial volume measurements were performed using the Simpson’s, biplane area-length, ellipse, and three-dimensional methods. Results were correlated using a Bland-Altman plot and linear regression models and compared by two-tailed paired-sample t tests. Reader variability was also calculated. RESULTSLeft atrial volume measurements using the biplane area-length technique showed the best correlation with Simpson’s method (r=0.92; P 0.99). CONCLUSIONThe biplane area-length method can be used for left atrial volume measurement when the Simpson’s method cannot be performed. If these two methods are not feasible, then all methods are highly reproducible and can be used, but should not be used interchangeably for follow-up studies

Enhancing Network Slicing Architectures with Machine Learning, Security, Sustainability and Experimental Networks Integration

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.Comment: 10 pages, 11 figure

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response