Dynamic environments of fungus-farming termite mounds exert growth-modulating effects on fungal crop parasites.

This study investigated for the first time the impact of the internal mound environment of fungus-growing termites on the growth of fungal crop parasites. Mounds of the termite Odontotermes obesus acted as (i) temperature and relative humidity (RH) 'stabilisers' showing dampened daily variation and (ii) 'extreme environments' exhibiting elevated RH and CO levels, compared to the outside. Yet, internal temperatures exhibited seasonal dynamics as did daily and seasonal CO levels.

Fungus-Farming Termites Selectively Bury Weedy Fungi that Smell Different from Crop Fungi.

Mutualistic associations such as the fungal farms of insects are prone to parasitism and are consequently vulnerable to attack by weeds and pests. Therefore, efficient farm management requires quick detection of weeds for their elimination. Furthermore, if the available weedicides are non-specific, then the ability of insects to discriminate between crop and weeds becomes essential for targeted application of such compounds.

Insight: An ontology-based integrated database and analysis platform for epilepsy self-management research.

We present Insight as an integrated database and analysis platform for epilepsy self-management research as part of the national Managing Epilepsy Well Network. Insight is the only available informatics platform for accessing and analyzing integrated data from multiple epilepsy self-management research studies with several new data management features and user-friendly functionalities. The features of Insight include, (1) use of Common Data Elements defined by members of the research community and an epilepsy domain ontology for data integration and querying, (2) visualization tools to support real time exploration of data distribution across research studies, and (3) an interactive visual query interface for provenance-enabled research cohort identification.

: Semantic Provenance and Analysis Platform for Multi-center Neurology Healthcare Research.

is a Semantic Web technology-based platform to support large-scale secondary analysis of healthcare data for neurology clinical research. features the novel use of: (1) provenance metadata, which describes the history or origin of patient data, in clinical research analysis, and (2) support for patient cohort queries across multiple institutions conducting research in epilepsy, which is the one of the most common neurological disorders affecting 50 million persons worldwide. is being developed as a healthcare informatics infrastructure to support a national network of eight epilepsy research centers across the U.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce.

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy.

Prevalence and associated features of gastroesophageal reflux symptoms in a Caucasian-predominant adolescent school population.

Objective: To determine the prevalence of esophageal symptoms and associated symptoms of gastroesophageal reflux symptoms in 14-18 year-old high school students and the percentage of symptomatic adolescents who saw a physician or received medications.

Design And Setting: A cross-sectional questionnaire administered to students at two high schools.

Participants: 1,286 completed questionnaires were analyzed.