Grand challenges in entomology: Priorities for action in the coming decades.

Entomology is key to understanding terrestrial and freshwater ecosystems at a time of unprecedented anthropogenic environmental change and offers substantial untapped potential to benefit humanity in a variety of ways, from improving agricultural practices to managing vector-borne diseases and inspiring technological advances.We identified high priority challenges for entomology using an inclusive, open, and democratic four-stage prioritisation approach, conducted among the membership and affiliates (hereafter 'members') of the UK-based Royal Entomological Society (RES).A list of 710 challenges was gathered from 189 RES members.

Target Organ Toxicity in Rats After Subchronic Oral Exposure to Soil Extracts Containing a Complex Mixture of Contaminants.

Complex mixtures of unknown contaminants present a challenge to identify toxicological risks without using large numbers of animals and labor-intensive screens of all organs. This study examined soil extracts from a legacy-contaminated pesticide packaging and blending site. HepG2 cytotoxicity was used as an initial screen of 18 soil samples; then, three extracts (A, B and C) from different locations at the study site were used for testing in animals.

Mapping nectar-rich pollinator floral resources using airborne multispectral imagery.

Wild pollinator numbers are known to be positively associated with amounts of flower-rich habitat at landscape level. Increasing floral resources can be particularly beneficial in relatively nectar-poor agricultural systems and having a baseline understanding of the temporal and spatial availability of resources can allow targeted habitat management. Very high-resolution remote sensing has potential to facilitate accurate mapping of fine-scale, within-habitat pollinator foraging resources, thereby allowing spatial and temporal gaps to be identified and addressed, improving predictions of pollinator numbers, and enabling remote monitoring of pollinator conservation measures.

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

Purpose: To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics.

Methods: Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011.