Outdoor spatial mosquito repellents, such as mosquito coils or heating devices, release pyrethroid insecticides into the air to provide protection from mosquitoes within a defined area. This broadcast discharge of pyrethroids into the environment raises concern about the effect on non-target organisms. A previous study found that prallethrin discharged from a heating device did not affect honey bee (Apis mellifera L.
View Article and Find Full Text PDFSummary: Knowledge graphs are being increasingly used in biomedical research to link large amounts of heterogenous data and facilitate reasoning across diverse knowledge sources. Wider adoption and exploration of knowledge graphs in the biomedical research community is limited by requirements to understand the underlying graph structure in terms of entity types and relationships, represented as nodes and edges, respectively, and learn specialized query languages for graph mining and exploration. We have developed a user-friendly interface dubbed ExEmPLAR (Extracting, Exploring, and Embedding Pathways Leading to Actionable Research) to aid reasoning over biomedical knowledge graphs and assist with data-driven research and hypothesis generation.
View Article and Find Full Text PDFBecause nontarget, beneficials, like insect pollinators, may be exposed unintentionally to insecticides, it is important to evaluate the impact of chemical controls on the behaviors performed by insect pollinators in field trials. Here we examine the impact of a portable mosquito repeller, which emits prallethrin, a pyrethroid insecticide, on honey bee foraging and recruitment using a blinded, randomized, paired, parallel group trial. We found no significant effect of the volatilized insecticide on foraging frequency (our primary outcome), waggle dance propensity, waggle dance frequency, and feeder persistency (our secondary outcomes), even though an additional deposition study confirmed that the treatment device was performing appropriately.
View Article and Find Full Text PDFIntroduction: Genome-wide association studies (GWAS) have played a critical role in identifying many thousands of loci associated with complex phenotypes and diseases. This has led to several translations of novel disease susceptibility genes into drug targets and care. This however has not been the case for analyses where sample sizes are small, which suffer from multiple comparisons testing.
View Article and Find Full Text PDF