Statistics of convective cloud turbulence from a comprehensive turbulence retrieval method for radar observations

Turbulent mixing processes are important in determining the evolution of convective clouds,and the production of convective precipitation. However, the exact nature of these impacts remains uncertain due to limited observations. Model simulations show that assumptions made in parametrizing turbulence can have a marked effect on the characteristics of simulated clouds. This leads to significant uncertainty in forecasts from convection‐permitting numerical weather prediction (NWP) models. This contribution presents a comprehensive method to retrieve turbulence using Doppler weather radar to investigate turbulence in observed clouds. This method involves isolating the turbulent component of the Doppler velocity spectrum width, expressing turbulence intensity as an eddy dissipation rate, ϵ. By applying this method throughout large datasets of observations collected over the southern United Kingdom using the (0.28° beam‐width) Chilbolton Advanced Meteorological Radar (CAMRa), statistics of convective cloud turbulence are presented. Two contrasting case days are examined: a shallow “shower” case, and a “deep convection” case, exhibiting stronger and deeper updraughts. In our observations, ϵ generally ranges from 10−3 to 10−1 m2/s3, with the largest values found within, around and above convective updraughts. Vertical profiles of ϵ suggest that turbulence is much stronger in deep convection; 95th percentile values increase with height from 0.03 to 0.1 m2/s3, compared to approximately constant values of 0.02–0.03 m2/s3 throughout the depth of shower cloud. In updraught regions on both days, the 95th percentile of ϵ has significant (p < 10−3) positive correlations with the updraught velocity, and the horizontal shear in the updraught velocity, with weaker positive correlations with updraught dimensions. The ϵ‐retrieval method presented considers a very broad range of conditions, providing a reliable framework for turbulence retrieval using high‐resolution Doppler weather radar. In applying this method across many observations, the derived turbulence statistics will form the basis for evaluating the parametrization of turbulence in NWP models

Patient Awareness and Approval for an Opt-Out Genomic Biorepository

Aim: In this study, we sought to assess patient awareness and perceptions of an opt-out biorepository. Materials & methods: We conducted exit interviews with adult patients and parents of pediatric patients having their blood drawn as part of their clinical care at Vanderbilt University Medical Center (TN, USA). Results: 32.9% of all patients and parents of pediatric patients report having heard of the opt-out biorepository, while 92.4% approve of this research effort based on a brief description. Awareness that leftover blood could be used for research increased among adult patients during the study period, from 34.3 to 50.0%. Conclusion: These findings will inform ongoing assessments of the suitability of opt-out and opt-in methods as alternatives to written informed consent for inclusion in a biorepository

Data to knowledge: how to get meaning from your result

Structural and functional studies require the development of sophisticated `Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB `super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results

Intra-Accumbens Injection of a Dopamine Aptamer Abates MK-801-Induced Cognitive Dysfunction in a Model of Schizophrenia

Systemic administration of the noncompetitive NMDA-receptor antagonist, MK-801, has been proposed to model cognitive deficits similar to those seen in patients with schizophrenia. The present work investigated the ability of a dopamine-binding DNA aptamer to regulate these MK-801-induced cognitive deficits when injected into the nucleus accumbens. Rats were trained to bar press for chocolate pellet rewards then randomly assigned to receive an intra-accumbens injection of a DNA aptamer (200 nM; n = 7), tris buffer (n = 6) or a randomized DNA oligonucleotide (n = 7). Animals were then treated systemically with MK-801 (0.1 mg/kg) and tested for their ability to extinguish their bar pressing response. Two control groups were also included that did not receive MK-801. Data revealed that injection of Tris buffer or the random oligonucleotide sequence into the nucleus accumbens prior to treatment with MK-801 did not reduce the MK-801-induced extinction deficit. Animals continued to press at a high rate over the entire course of the extinction session. Injection of the dopamine aptamer reversed this MK-801-induced elevation in lever pressing to levels as seen in rats not treated with MK-801. Tests for activity showed that the aptamer did not impair locomotor activity. Results demonstrate the in vivo utility of DNA aptamers as tools to investigate neurobiological processes in preclinical animal models of mental health disease

PDBe: improved findability of macromolecularstructure data in the PDB

© 2019 The Authors. Published by OUP. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1093/nar/gkz990The Protein Data Bank in Europe (PDBe), a founding member of the Worldwide Protein Data Bank (wwPDB), actively participates in the deposition, curation, validation, archiving and dissemination of macromolecular structure data. PDBe supports diverse research communities in their use of macromolecular structures by enriching the PDB data and by providing advanced tools and services for effective data access, visualization and analysis. This paper details the enrichment of data at PDBe, including mapping of RNA structures to Rfam, and identification of molecules that act as cofactors. PDBe has developed an advanced search facility with ∼100 data categories and sequence searches. New features have been included in the LiteMol viewer at PDBe, with updated visualization of carbohydrates and nucleic acids. Small molecules are now mapped more extensively to external databases and their visual representation has been enhanced. These advances help users to more easily find and interpret macromolecular structure data in order to solve scientific problems.The Protein Data Bank in Europe is supported by European Molecular Biology Laboratory-European Bioinformatics Institute; Wellcome Trust [104948]; Biotechnology and Biological Sciences Research Council [BB/N019172/1, BB/G022577/1, BB/J007471/1, BB/K016970/1, BB/K020013/1, BB/M013146/1, BB/M011674/1, BB/M020347/1, BB/M020428/1, BB/P024351/1]; European Union [284209]; ELIXIR and Open Targets. Funding for open access charge: EMB

Accurate Protein Structure Annotation through Competitive Diffusion of Enzymatic Functions over a Network of Local Evolutionary Similarities

High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods

The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology

RNA-Seq Mapping and Detection of Gene Fusions with a Suffix Array Algorithm

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions–particularly those expressed with low abundance– is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software. We introduced new features including filter and junction mapping, annotation-aided pairing rescue and accurate mapping quality values. We combined this pipeline with a Suffix Array Spliced Read (SASR) aligner to detect chimeric transcripts. Performing paired-end RNA-Seq of the breast cancer cell line MCF-7 using the SOLiD system, we called 40 gene fusions among over 120,000 splicing junctions. We validated 36 of these 40 fusions with TaqMan assays, of which 25 were expressed in MCF-7 but not the Human Brain Reference. An intra-chromosomal gene fusion involving the estrogen receptor alpha gene ESR1, and another involving the RPS6KB1 (Ribosomal protein S6 kinase beta-1) were recurrently expressed in a number of breast tumor cell lines and a clinical tumor sample