Faecal transplantation for IBD management-pitfalls and promises.

BACKGROUND: Faecal microbiota transplantation (FMT) as a potential treatment for inflammatory bowel disease (IBD) is an area of active current research, having been stimulated by the remarkable efficacy of FMT in treatment of Clostridium difficile-associated colitis. SOURCES OF DATA: This review is based on data from numerous case series on FMT in IBD since 1989 and results of four RCTs in ulcerative colitis (UC); three fully published. AREAS OF AGREEMENT: Early signals of short to medium-term efficacy of FMT for UC are promising. AREAS OF CONTROVERSY: Methodology, underlying mechanisms and questions regarding safety of FMT remain controversial. GROWING POINTS: Many trials of FMT in adults and children are currently recruiting. AREAS TIMELY FOR DEVELOPING RESEARCH: Future trials of FMT will likely revisit Crohn's disease and patients undergoing pouch surgery. Advances in microbial culture complementing genetic sequencing and investigations into the virome and mycobiome in IBD will be of great future interest.

DataFoundry: information management for scientific data.

Data warehouses and data marts have been successfully applied to a multitude of commercial business applications. They have proven to be invaluable tools by integrating information from distributed, heterogeneous sources and summarizing this data for use throughout the enterprise. Although the need for information dissemination is as vital in science as in business, working warehouses in this community are scarce because traditional warehousing techniques do not transfer to scientific environments. There are two primary reasons for this difficulty. First, schema integration is more difficult for scientific databases than for business sources, because of the complexity of the concepts and the associated relationships. While this difference has not yet been fully explored, it is an important consideration when determining how to integrate autonomous sources. Second, scientific data sources have highly dynamic data representations (schemata). When a data source participating in a warehouse changes its schema, both the mediator transferring data to the warehouse and the warehouse itself need to be updated to reflect these modifications. The cost of repeatedly performing these updates in a traditional warehouse, as is required in a dynamic environment, is prohibitive. This paper discusses these issues within the context of the DataFoundry project, an ongoing research effort at Lawrence Livermore National Laboratory. DataFoundry utilizes a unique integration strategy to identify corresponding instances while maintaining differences between data from different sources, and a novel architecture and an extensive meta-data infrastructure, which reduce the cost of maintaining a warehouse.