Workflow evaluation of environmental contamination with hazardous drugs during compounding and administration in an UK hospital.

Introduction: Exposure of healthcare workers to hazardous drugs may result in adverse health effects underscoring the importance of validating working procedures and safety precautions to minimise the risk. The objective was to monitor environmental contamination caused by the hazardous drug workflow: from drug vials, compounding process, to patient administration.

Methods: Surface wipe samples were collected from potentially contaminated surfaces in the compounding department and in the administration department.

Partial Sequence Analysis of Commercial Peste des Petits Ruminants Vaccines Produced in Africa.

Peste des petits ruminants virus (PPRV), which is the only member of the species and belongs to the genus within the family, causes the highly contagious viral sickness "Peste des petits ruminants (PPR)." PPR is of serious economic significance for small ruminant production, particularly in Africa. Control of this critical disease depends highly on successful vaccination against the PPRV.

Using spaceborne LiDAR to reveal drivers of animal demography.

Remote sensing can provide continuous spatiotemporal information about vegetation to inform wildlife habitat estimates, but these methods are often limited in availability or lack adequate resolution to capture the three-dimensional vegetative details critical for understanding habitat. The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne light detection and ranging system (LiDAR) that has revolutionized the availability of high-quality three-dimensional vegetation measurements of the Earth's temperate and tropical forests. To date, wildlife-related applications of GEDI data or GEDI-fusion products have been limited to estimate species habitat use, distribution, and diversity.

Pharmacogenomic augmented machine learning in electronic health record alerts: A health system-wide usability survey of clinicians.

Pharmacogenomic (PGx) biomarkers integrated using machine learning can be embedded within the electronic health record (EHR) to provide clinicians with individualized predictions of drug treatment outcomes. Currently, however, drug alerts in the EHR are largely generic (not patient-specific) and contribute to increased clinician stress and burnout. Improving the usability of PGx alerts is an urgent need.

A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders.

Unsolved Mendelian cases often lack obvious pathogenic coding variants, suggesting potential non-coding etiologies. Here, we present a single cell multi-omic framework integrating embryonic mouse chromatin accessibility, histone modification, and gene expression assays to discover cranial motor neuron (cMN) cis-regulatory elements and subsequently nominate candidate non-coding variants in the congenital cranial dysinnervation disorders (CCDDs), a set of Mendelian disorders altering cMN development. We generate single cell epigenomic profiles for ~86,000 cMNs and related cell types, identifying ~250,000 accessible regulatory elements with cognate gene predictions for ~145,000 putative enhancers.