Reactome (http://www.reactome.org) is a collaboration among groups at the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University School of Medicine and The European Bioinformatics Institute, to develop an open source curated bioinformatics database of human pathways and reactions. Recently, we developed a new web site with improved tools for pathway browsing and data analysis. The Pathway Browser is an Systems Biology Graphical Notation (SBGN)-based visualization system that supports zooming, scrolling and event highlighting. It exploits PSIQUIC web services to overlay our curated pathways with molecular interaction data from the Reactome Functional Interaction Network and external interaction databases such as IntAct, BioGRID, ChEMBL, iRefIndex, MINT and STRING. Our Pathway and Expression Analysis tools enable ID mapping, pathway assignment and overrepresentation analysis of user-supplied data sets. To support pathway annotation and analysis in other species, we continue to make orthology-based inferences of pathways in non-human species, applying Ensembl Compara to identify orthologs of curated human proteins in each of 20 other species. The resulting inferred pathway sets can be browsed and analyzed with our Species Comparison tool. Collaborations are also underway to create manually curated data sets on the Reactome framework for chicken, Drosophila and rice.

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities. Database URL: http://central.biomart.org.

Delayed gastric conduit emptying (DGCE) after esophagectomy for cancer is associated with adverse outcomes and troubling symptoms. Widely accepted diagnostic criteria and a symptom grading tool for DGCE are missing. This hampers the interpretation and comparison of studies. A modified Delphi process, using repeated web-based questionnaires, combined with live interim group discussions was conducted by 33 experts within the field, from Europe, North America, and Asia. DGCE was divided into early DGCE if present within 14 days of surgery and late if present later than 14 days after surgery. The final criteria for early DGCE, accepted by 25 of 27 (93%) experts, were as follows: >500 mL diurnal nasogastric tube output measured on the morning of postoperative day 5 or later or >100% increased gastric tube width on frontal chest x-ray projection together with the presence of an air–fluid level. The final criteria for late DGCE accepted by 89% of the experts were as follows: the patient should have ‘quite a bit’ or ‘very much’ of at least two of the following symptoms; early satiety/fullness, vomiting, nausea, regurgitation or inability to meet caloric need by oral intake and delayed contrast passage on upper gastrointestinal water-soluble contrast radiogram or on timed barium swallow. A symptom grading tool for late DGCE was constructed grading each symptom as: ‘not at all’, ‘a little’, ‘quite a bit’, or ‘very much’, generating 0, 1, 2, or 3 points, respectively. For the five symptoms retained in the diagnostic criteria for late DGCE, the minimum score would be 0, and the maximum score would be 15. The final symptom grading tool for late DGCE was accepted by 27 of 31 (87%) experts. For the first time, diagnostic criteria for early and late DGCE and a symptom grading tool for late DGCE are available, based on an international expert consensus process.

INTRODUCTION: Non–Helicobacter pylori microbiota might account for some cases with unexplained chronic gastritis that may in a minority eventually progress to gastric cancer through the Correa cascade. We characterized gastric microbiota by describing the normal stomach, compared it with early precancerous lesions and other disease states, and assessed whether H. pylori status affects bacterial diversity. METHODS: In a population-based study of those with and without gastrointestinal symptoms, cytology brush samples were collected during endoscopy from 316 individuals. Mucosal status was classified as normal mucosa (171), nonatrophic H. pylori gastritis (33), atrophic gastritis (12), or antral chemical gastritis (61). The 16S rRNA gene sequencing and analysis were performed to characterize the microbiota. RESULTS: Microbiota in atrophic gastritis and nonatrophic H. pylori gastritis stomachs were dysbiotic and differed from those in the normal stomach (P = 0.001). The normal stomach had the highest microbial diversity, followed by antral chemical gastritis. The atrophic gastritis and chronic H. pylori gastritis groups had the lowest diversity, a difference that was statistically significant (P = 0.01). Besides H. pylori, non–H. pylori bacteria accounted for group differences. Microbial network analysis showed that the normal group network was most highly connected, whereas the H. pylori gastritis group had the lowest connection. We found an increasing positive co-occurrence of oral bacteria in the stomach because samples deviated from the normal network, some of which were pathogens. The H. pylori–negative group had the highest microbial diversity (Shannon index) compared with the H. pylori–positive group (P = 0.001). DISCUSSION: In this low–H. pylori prevalence general population, the gastric mucosal microbiota of the normal stomach differed significantly from those with nonatrophic or atrophic gastritis. There was an increasing abundance of pathogenic bacteria from the normal state to early precancerous states.