Explore the vast range of titles available.

Most genomic variants associated with phenotypic traits or disease do not fall within gene coding regions, but in regulatory regions, rendering their interpretation difficult. We collected public data on epigenetic marks and transcription factor binding in human cell types and used it to construct an intuitive summary of regulatory regions in the human genome. We verified it against independent assays for sensitivity. The Ensembl Regulatory Build will be progressively enriched when more data is made available. It is freely available on the Ensembl browser, from the Ensembl Regulation MySQL database server and in a dedicated track hub.

Abstract Study Objectives To examine the effects of cognitive behavioral treatments for insomnia (CBT-I) and pain (CBT-P) in patients with comorbid fibromyalgia and insomnia. Methods One hundred thirteen patients (Mage = 53, SD = 10.9) were randomized to eight sessions of CBT-I (n = 39), CBT-P (n = 37), or a waitlist control (WLC, n = 37). Primary (self-reported sleep onset latency [SOL], wake after sleep onset [WASO], sleep efficiency [SE], sleep quality [SQ], and pain ratings) and secondary outcomes (dysfunctional beliefs and attitudes about sleep [DBAS]; actigraphy and polysomnography SOL, WASO, and SE; McGill Pain Questionnaire; Pain Disability Index; depression; and anxiety) were examined at posttreatment and 6 months. Results Mixed effects analyses revealed that both treatments improved self-reported WASO, SE, and SQ relative to control at posttreatment and follow-up, with generally larger effect sizes for CBT-I. DBAS improved in CBT-I only. Pain and mood improvements did not differ by group. Clinical significance analyses revealed the proportion of participants no longer reporting difficulties initiating and maintaining sleep was higher for CBT-I posttreatment and for both treatments at 6 months relative to control. Few participants achieved >50% pain reductions. Proportion achieving pain reductions of >30% (~1/3) was higher for both treatments posttreatment and for CBT-I at 6 months relative to control. Conclusions CBT-I and CBT-P improved self-reported insomnia symptoms. CBT-I prompted improvements of larger magnitude that were maintained. Neither treatment improved pain or mood. However, both prompted clinically meaningful, immediate pain reductions in one third of patients. Improvements persisted for CBT-I, suggesting that CBT-I may provide better long-term pain reduction than CBT-P. Research identifying which patients benefit and mechanisms driving intervention effects is needed. Clinical Trial Sleep and Pain Interventions in Fibromyalgia (SPIN), clinicaltrials.gov, NCT02001077.

Background Much effort is made to ensure Cochrane reviews are based on reliably extracted data. There is a commitment to wide access to these data—for novel processing and/or reuse—but delivering this access is problematic. Aim To describe a proof-of-concept programme to extract, curate and structure data from Cochrane reviews. Methods One student of Applied Sciences (16 weeks full time), access to pre-publication review files and use of ‘Eclipse’ to create an open-access tool (RAPTOR) using the programming language Java. Results The final software batch processes hundreds of reviews in seconds, extracting all study data and automatically tidying and unifying presentation of data for return into the source review, reuse, or export for novel analyses. Conclusions This software, despite being limited, illustrates how the efforts of reviewers meticulously extracting study data can be improved, disseminated and reused with little additional effort.

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.

Background Targeted resequencing has become the most used and cost-effective approach for identifying causative mutations of Mendelian diseases both for diagnostics and research purposes. Due to very rapid technological progress, NGS laboratories are expanding their capabilities to address the increasing number of analyses. Several open source tools are available to build a generic variant calling pipeline, but a tool able to simultaneously execute multiple analyses, organize, and categorize the samples is still missing. Results Here we describe VarGenius, a Linux based command line software able to execute customizable pipelines for the analysis of multiple targeted resequencing data using parallel computing. VarGenius provides a database to store the output of the analysis (calling quality statistics, variant annotations, internal allelic variant frequencies) and sample information (personal data, genotypes, phenotypes). VarGenius can also perform the “joint analysis” of hundreds of samples with a single command, drastically reducing the time for the configuration and execution of the analysis. VarGenius executes the standard pipeline of the Genome Analysis Tool-Kit (GATK) best practices (GBP) for germinal variant calling, annotates the variants using Annovar, and generates a user-friendly output displaying the results through a web page. VarGenius has been tested on a parallel computing cluster with 52 machines with 120GB of RAM each. Under this configuration, a 50 M whole exome sequencing (WES) analysis for a family was executed in about 7 h (trio or quartet); a joint analysis of 30 WES in about 24 h and the parallel analysis of 34 single samples from a 1 M panel in about 2 h. Conclusions We developed VarGenius, a “master” tool that faces the increasing demand of heterogeneous NGS analyses and allows maximum flexibility for downstream analyses. It paves the way to a different kind of analysis, centered on cohorts rather than on singleton. Patient and variant information are stored into the database and any output file can be accessed programmatically. VarGenius can be used for routine analyses by biomedical researchers with basic Linux skills providing additional flexibility for computational biologists to develop their own algorithms for the comparison and analysis of data. The software is freely available at: https://github.com/frankMusacchia/VarGenius

Background The aim of this study was to demonstrate a novel method of assessing data quality for an orthopaedic registry and its effects on data quality metrics. Methods A quality controlled clinical patient registry was implemented, comprising six observational cohorts of shoulder and knee pathologies. Data collection procedures were co-developed with clinicians and administrative staff in accordance with the relevant dataset and organised into the registry database software. Quality metrics included completeness, consistency and validity. Data were extracted at scheduled intervals (3 months) and quality metrics reported to stakeholders of the registry. Results The first patient was enrolled in July 2017 and the data extracted for analysis over 4 quarters, with the last audit in August 2018 ( N  = 189). Auditing revealed registry completeness was 100% after registry deficiencies were addressed. However, cohort completeness was less accurate, ranging from 12 to 13% for height & weight to 90–100% for operative variables such as operating surgeon, consulting surgeon and hospital. Consistency and internal validation improved to 100% after issues in registry processes were rectified. Conclusions A novel method to assess data quality in a clinical orthopaedic registry identified process shortfalls and improved data quality over time. Real-time communication, a comprehensive data framework and an integrated feedback loop were necessary to ensure adequate quality assurance. This model can be replicated in other registries and serve as a useful quality control tool to improve registry quality and ensure applicability of the data to aid clinical decisions, especially in newly implemented registries. Trial registration ACTRN12617001161314 ; registration date 8/08/2017. Retrospectively registered.

E2F transcription factor 3 (E2F3) is oncogenic and dysregulated in various malignancies. Complex networks involving microRNAs (miRNAs) and E2F3 regulate tumorigenesis and progression. However, the potential roles of E2F3 and its target miRNAs in nasopharyngeal carcinoma (NPC) are rarely reported. E2F3 expression was detected in human NPC tissues and cell lines through quantitative real-time PCR. NPC cell proliferation, migration, and invasion were evaluated in vitro by colony forming, cell counting kit-8, wound healing, and Transwell invasion assays. Publicly available database software was used to explore the target miRNAs of E2F3. Dual-luciferase reporter assay was performed to identify the direct relationship. The function of miRNAs in vivo was investigated by using a tumor xenograft model. E2F3 was upregulated in NPC cell lines and tissues, and its exotic expression promoted NPC cell invasion and migration. E2F3 was identified as a target of miR-432, which restrained NPC cell invasion and migration in vitro and in vivo. Further experiments revealed that miR-432 repressed the invasion and migration potential of NPC cells by modulating E2F3 expression. miRNA-432 suppressed the malignant biological behavior of NPC cells by targeting E2F3. This study provided further insights into NPC prognosis and treatment.

Over decades, relational database management systems (RDBMSs) have been the first choice to manage data. Recently, due to the variety properties of big data, graph database management systems (GDBMSs) have emerged as an important complement to RDBMSs. As pointed out in the existing literature, both RDBMSs and GDBMSs are capable of managing graph data and relational data; however, the boundaries of them still remain unclear. For this reason, in this paper, we first extend a unified benchmark for RDBMSs and GDBMSs over the same datasets using the same query workload under the same metrics. We then conduct extensive experiments to evaluate them and make the following findings: (1) RDBMSs outperform GDMBSs by a substantial margin under the workloads which mainly consist of group by, sort, and aggregation operations, and their combinations; (2) GDMBSs show their superiority under the workloads that mainly consist of multi-table join, pattern match, path identification, and their combinations.