Severe Acute Respiratory Syndrome Coronavirus nsp9 Dimerization Is Essential for Efficient Viral Growth

The severe acute respiratory syndrome coronavirus (SARS-CoV) devotes a significant portion of its genome to producing nonstructural proteins required for viral replication. SARS-CoV nonstructural protein 9 (nsp9) was identified as an essential protein with RNA/DNA-binding activity, and yet its biological function within the replication complex remains unknown. Nsp9 forms a dimer through the interaction of parallel α-helices containing the protein-protein interaction motif GXXXG. In order to study the role of the nsp9 dimer in viral reproduction, residues G100 and G104 at the helix interface were targeted for mutation. Multi-angle light scattering measurements indicated that G100E, G104E, and G104V mutants are monomeric in solution, thereby disrupting the dimer. However, electrophoretic mobility assays revealed that the mutants bound RNA with similar affinity. Further experiments using fluorescence anisotropy showed a 10-fold reduction in RNA binding in the G100E and G104E mutants, whereas the G104V mutant had only a 4-fold reduction. The structure of G104E nsp9 was determined to 2.6-Å resolution, revealing significant changes at the dimer interface. The nsp9 mutations were introduced into SARS-CoV using a reverse genetics approach, and the G100E and G104E mutations were found to be lethal to the virus. The G104V mutant produced highly debilitated virus and eventually reverted back to the wild-type protein sequence through a codon transversion. Together, these data indicate that dimerization of SARS-CoV nsp9 at the GXXXG motif is not critical for RNA binding but is necessary for viral replication

Euforea treatment algorithm for allergic rhinitis

Non peer reviewe

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or \u27scaffold\u27) of haplotypes across each chromosome. We then phase the sequence data \u27onto\u27 this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds

Geolocation with respect to persona privacy for the Allergy Diary app - a MASK study

Background: Collecting data on the localization of users is a key issue for the MASK (Mobile Airways Sentinel network: the Allergy Diary) App. Data anonymization is a method of sanitization for privacy. The European Commission's Article 29 Working Party stated that geolocation information is personal data. To assess geolocation using the MASK method and to compare two anonymization methods in the MASK database to find an optimal privacy method. Methods: Geolocation was studied for all people who used the Allergy Diary App from December 2015 to November 2017 and who reported medical outcomes. Two different anonymization methods have been evaluated: Noise addition (randomization) and k-anonymity (generalization). Results: Ninety-three thousand one hundred and sixteen days of VAS were collected from 8535 users and 54,500 (58. 5%) were geolocalized, corresponding to 5428 users. Noise addition was found to be less accurate than k-anonymity using MASK data to protect the users' life privacy. Discussion: k-anonymity is an acceptable method for the anonymization of MASK data and results can be used for other databases.Peer reviewe