Workplace distractions in the digital era – are smartphones a threat to safety or an essential tool?

Anaesthesia is a technology‐dependant specialty. While the impact of total intravenous anaesthesia, video laryngoscopes and ultrasound‐guidance – to name but a few influential recent technologies – have been extensively studied [e.g. 1-4], the professional use of smartphones in anaesthesia remains relatively under‐investigated. This is perhaps an oversight considering that this ubiquitous accessory now reaches into nearly every aspect of our lives, from communication to study, shopping and dining, and indeed – to professional practice. In this issue of Anaesthesia, van Harten et al. report “An observational study of distractions in the operating theatre” [5], which among other findings, highlights the (distracting) role played by smartphones. In this editorial, we consider the utility and methodology of van Harten et al.’s work, reflect on the extent to which smartphones may threaten patient safety in anaesthesia, and ask how this can be balanced against their prominent and increasing role as a professional tool

Rapid Sampling of Molecular Motions with Prior Information Constraints

Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion