Efficient and Robust Europium(III)-Based Hybrid Lanthanide Scintillators for Advanced X-Ray Imaging.

Scintillators that convert ionizing radiation into low-energy photons are essential for medical diagnostics and industrial inspections. Despite advances in X-ray scintillators, challenges remain in achieving high efficiency, environmental compatibility, stability, and flexibility. Here, we present experimental investigations of a new type of europium(III)-based hybrid ternary complex scintillators for improved X-ray detection and imaging.

Coronavirus sampling and surveillance in bats from 1996-2019: a systematic review and meta-analysis.

The emergence of SARS-CoV-2 highlights a need for evidence-based strategies to monitor bat viruses. We performed a systematic review of coronavirus sampling (testing for RNA positivity) in bats globally. We identified 110 studies published between 2005 and 2020 that collectively reported positivity from 89,752 bat samples.

Exploring the Mosquito-Arbovirus Network: A Survey of Vector Competence Experiments.

Arboviruses receive heightened research attention during major outbreaks or when they cause unusual or severe clinical disease, but they are otherwise undercharacterized. Global change is also accelerating the emergence and spread of arboviral diseases, leading to time-sensitive questions about potential interactions between viruses and novel vectors. Vector competence experiments help determine the susceptibility of certain arthropods to a given arbovirus, but these experiments are often conducted in real time during outbreaks, rather than with preparedness in mind.

A minimum data standard for vector competence experiments.

The growing threat of vector-borne diseases, highlighted by recent epidemics, has prompted increased focus on the fundamental biology of vector-virus interactions. To this end, experiments are often the most reliable way to measure vector competence (the potential for arthropod vectors to transmit certain pathogens). Data from these experiments are critical to understand outbreak risk, but - despite having been collected and reported for a large range of vector-pathogen combinations - terminology is inconsistent, records are scattered across studies, and the accompanying publications often share data with insufficient detail for reuse or synthesis.

Optimising predictive models to prioritise viral discovery in zoonotic reservoirs.

Despite the global investment in One Health disease surveillance, it remains difficult and costly to identify and monitor the wildlife reservoirs of novel zoonotic viruses. Statistical models can guide sampling target prioritisation, but the predictions from any given model might be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use the bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of probable reservoir hosts.