Eyewitness memory: The impact of a negative mood during encoding and/or retrieval upon recall of a non-emotive event

The police often appeal for eyewitnesses to events that were unlikely to have been emotive when observed. An eyewitness, however, may be in a negative mood whilst encoding or retrieving such events as mood can be influenced by a range of personal, social, and environmental factors. For example, bad weather can induce a negative mood. This experiment compared the impact of negative and neutral moods during encoding and/or retrieval upon eyewitness recall of a non-emotive event. A negative mood during encoding had no impact upon the number of correct details recalled (provided participants were in a neutral mood at retrieval) but a negative mood during retrieval impaired the number of correct details recalled (provided participants were in a neutral mood at encoding). A negative mood at both time points enhanced the number of correct details recalled, demonstrating a mood-dependent memory enhancement. The forensic implications of these findings are discussed

A deep dive into the ecology of Gamay (Botany Bay, Australia): current knowledge and future priorities for this highly modified coastal waterway

Context: Gamay is a coastal waterway of immense social, cultural and ecological value. Since European settlement, it has become a hub for industrialisation and human modification. There is growing desire for ecosystem-level management of urban waterways, but such efforts are often challenged by a lack of integrated knowledge. Aim and methods: We systematically reviewed published literature and traditional ecological knowledge (TEK), and consulted scientists to produce a review of Gamay that synthesises published knowledge of Gamay’s aquatic ecosystem to identify knowledge gaps and future research opportunities. Key results: We found 577 published resources on Gamay, of which over 70% focused on ecology. Intertidal rocky shores were the most studied habitat, focusing on invertebrate communities. Few studies considered multiple habitats or taxa. Studies investigating cumulative human impacts, long-term trends and habitat connectivity are lacking, and the broader ecological role of artificial substrate as habitat in Gamay is poorly understood. TEK of Gamay remains a significant knowledge gap. Habitat restoration has shown promising results and could provide opportunities to improve affected habitats in the future. Conclusion and implications: This review highlights the extensive amount of knowledge that exists for Gamay, but also identifies key gaps that need to be filled for effective management

Updates on radiotherapy-immunotherapy combinations: Proceedings of 6th annual ImmunoRad conference.

Focal radiation therapy (RT) has attracted considerable attention as a combinatorial partner for immunotherapy (IT), largely reflecting a well-defined, predictable safety profile and at least some potential for immunostimulation. However, only a few RT-IT combinations have been tested successfully in patients with cancer, highlighting the urgent need for an improved understanding of the interaction between RT and IT in both preclinical and clinical scenarios. Every year since 2016, ImmunoRad gathers experts working at the interface between RT and IT to provide a forum for education and discussion, with the ultimate goal of fostering progress in the field at both preclinical and clinical levels. Here, we summarize the key concepts and findings presented at the Sixth Annual ImmunoRad conference

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)