The open reading frame 5A of foxtail mosaic virus is expressed in vivo and is dispensable for systemic infection

Infectious transcripts were successfully derived from full-length cDNA clones of foxtail mosaic potexvirus (FoMV). Full-length clones were constructed by RT-PCR whereby 50 and 30 genomic segments of 2.7 and 3.4 kb, respectively, were ligated into Bluescript II KS. The in vitro RNA transcripts were infectious to moncotyledonous (barley) and dicotyledonous (Chenopodium amaranticolor) plant species. Individual mutation studies on clones of each of the five major ORFs confirmed predicted gene function for the polymerase, TGB (triple gene block), and coat protein (CP) genes. Protoplast studies on expression of a unique open reading frame, ORF 5A, which initiates 143 nts upstream of the CP before it “reads through” the CP, revealed that the 5A protein was produced in vivo. Mutation analysis of the 5A ORF indicated, however, that it was not required for either replication or for productive infection of plants. However, the nucleic acid sequences encoding the extended CP segment were shown to be important for CP expression. Additional mutations in 5A had no effect on FoMV replication in protoplasts but rendered the virus noninfectious to plants. A correlation with diminished CP production from both mutant clones implies that synthesis of subgenomic CP mRNA was compromised, and this limited systemic infection

Results of the First Coincident Observations by Two Laser-Interferometric Gravitational Wave Detectors

We report an upper bound on the strain amplitude of gravitational wave bursts in a waveband from around 800Hz to 1.25kHz. In an effective coincident observing period of 62 hours, the prototype laser interferometric gravitational wave detectors of the University of Glasgow and Max Planck Institute for Quantum Optics, have set a limit of 4.9E-16, averaging over wave polarizations and incident directions. This is roughly a factor of 2 worse than the theoretical best limit that the detectors could have set, the excess being due to unmodelled non-Gaussian noise. The experiment has demonstrated the viability of the kind of observations planned for the large-scale interferometers that should be on-line in a few years time.Comment: 11 pages, 2 postscript figure

Aquilegia, Vol. 31 No. 5, Fall 2007, Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1121/thumbnail.jp

MRI findings in men on active surveillance for prostate cancer: does dutasteride make MRI visible lesions less conspicuous? Results from a placebo-controlled, randomised clinical trial

Objectives To investigate changes in the Apparent Diffusion Coefficient (ADC) using diffusion-weighted imaging (DWI) in men on active surveillance for prostate cancer taking dutasteride 0.5 mg or placebo. Methods We analysed 37 men, randomised to 6 months of daily dutasteride (n = 18) or placebo (n = 19), undergoing 3T multi-parametric Magnetic Resonance Imaging (mpMRI) scans at baseline and 6 months. Images were reviewed blind to treatment allocation and clinical information. Mean ADC of peripheral (PZ) and transition (TZ) zones, and MR-suspicious lesions were compared between groups over 6 months. Conspicuity was defined as the PZ divided by tumour ADC, and its change over 6 months was assessed. Results A decrease in mean conspicuity in the dutasteride group (but not the controls) was seen over 6 months (1.54 vs 1.38; p = 0.025). Absolute changes in ADC and conspicuity were significantly different between placebo and dutasteride groups at 6 months: (-0.03 vs 0.08, p = 0.033) and (0.11 vs –0.16, p = 0.012), as were percentage changes in the same parameters: (-2.27% vs 8.56% p = 0.048) and (9.25% vs -9.89% p = 0.013). Conclusions Dutasteride was associated with increased tumour ADC and reduced conspicuity. A lower threshold for triggering biopsy might be considered in men on dutasteride undergoing mpMRI for prostate cancer

Climate impact and adaptation to heat and drought stress of regional and global wheat production

Wheat (Triticum aestivum) is the most widely grown food crop in the world threatened by future climate change. In this study, we simulated climate change impacts and adaptation strategies for wheat globally using new crop genetic traits (CGT), including increased heat tolerance, early vigor to increase early crop water use, late flowering to reverse an earlier anthesis in warmer conditions, and the combined traits with additional nitrogen (N) fertilizer applications, as an option to maximize genetic gains. These simulations were completed using three wheat crop models and five Global Climate Models (GCM) for RCP 8.5 at mid-century. Crop simulations were compared with country, US state, and US county grain yield and production. Wheat yield and production from high-yielding and low-yielding countries were mostly captured by the model ensemble mean. However, US state and county yields and production were often poorly reproduced, with large variability in the models, which is likely due to poor soil and crop management input data at this scale. Climate change is projected to decrease global wheat production by −1.9% by mid-century. However, the most negative impacts are projected to affect developing countries in tropical regions. The model ensemble mean suggests large negative yield impacts for African and Southern Asian countries where food security is already a problem. Yields are predicted to decline by −15% in African countries and −16% in Southern Asian countries by 2050. Introducing CGT as an adaptation to climate change improved wheat yield in many regions, but due to poor nutrient management, many developing countries only benefited from adaptation from CGT when combined with additional N fertilizer. As growing conditions and the impact from climate change on wheat vary across the globe, region-specific adaptation strategies need to be explored to increase the possible benefits of adaptations to climate change in the future.info:eu-repo/semantics/publishedVersio

Pinning of stripes by local structural distortions in cuprate high-Tc superconductors

We study the spin-density wave (stripe) instability in lattices with mixed low-temperature orthorhombic (LTO) and low-temperature tetragonal (LTT) crystal symmetry. Within an explicit mean-field model it is shown how local LTT regions act as pinning centers for static stripe formation. We calculate the modulations in the local density of states near these local stripe regions and find that mainly the coherence peaks and the van Hove singularity (VHS) are spatially modulated. Lastly, we use the real-space approach to simulate recent tunneling data in the overdoped regime where the VHS has been detected by utilizing local normal state regions.Comment: Conference proceedings for Stripes1

Magnetic Field Amplification in Galaxy Clusters and its Simulation

We review the present theoretical and numerical understanding of magnetic field amplification in cosmic large-scale structure, on length scales of galaxy clusters and beyond. Structure formation drives compression and turbulence, which amplify tiny magnetic seed fields to the microGauss values that are observed in the intracluster medium. This process is intimately connected to the properties of turbulence and the microphysics of the intra-cluster medium. Additional roles are played by merger induced shocks that sweep through the intra-cluster medium and motions induced by sloshing cool cores. The accurate simulation of magnetic field amplification in clusters still poses a serious challenge for simulations of cosmological structure formation. We review the current literature on cosmological simulations that include magnetic fields and outline theoretical as well as numerical challenges.Comment: 60 pages, 19 Figure

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Discovery and fine-mapping of glycaemic and obesity-related trait loci using high-density imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated