Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Towards an inclusive methodology for the measurement of in-house use

Introduces the background to the EQLIPSE (Evaluation and Quality in Library Performance: System for Europe) project and the work done in compiling a core set of performance indicators for evaluating libraries. Describes the collection of in house library use data at the University of Central Lancashire Library test site, where EQLIPSE staff gathered data as part of the data collection exercise to test the feasibility of the indicators and to accumulate data in the EQLIPSE system. Some of the difficulties encountered in the process are noted along with the measures taken to address them. In addition to measuring actual use, attempts were also made to establish whether users habitually reshelve items they consult, both when at the shelf and when working at study spaces. Unobtrusive direct observation eventually formed the mainstay of the methods used to measure this. Results suggest that users consulting items at the shelf would change every 10 minutes on average and that the number of users would fall or rise gradually during the two hours between counts. Future developments to the EQLIPSE methodology are discussed

Membrane protein structure, function, and dynamics: a perspective from experiments and theory

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.JTD, IA, and MR used the computational resources of the Modeling Facility of the Department of Chemistry, University of California Irvine funded by NSF Grant CHE-0840513 for this work. A-NB was supported in part by the Marie Curie International Reintegration Award IRG-26920.TWA was supported by ARC DP120103548, NSF MCB1052477, DE Shaw Anton (PSCA00061P; NRBSC, through NIH RC2GM093307), VLSCI (VR0200), and NCI (dd7). BA and SV acknowledge the support by ERC advanced Grant No. 268888. ZC and PG would like to acknowledge Reference Framework (NSRF) 2011–2013, National Action ‘‘Cooperation,’’ under grant entitled ‘‘Magnetic Nanoparticles for targeted MRI therapy (NANOTHER),’’ with code ‘‘11RYM-1-1799.’’ The program is cofunded by the European Regional Development Fund and national resources. Part of the calculations presented herein were performed using resources of the LinkSCEEM-2 project, funded by the EC under FP7 through Capacities Research Infrastructure, INFRA-2010-1.2.3 Virtual Research Communities, Combination of Collaborative Project and Coordination and Support Actions (CPCSA) under Grant agreement no. RI-261600. GB was supported in part by NSF grant MCB1330728 from the National Science Foundation and Grant PO1GM55876-14A1 from the National Institutes of Health. LD received funding from EU FP7 (PIOF-GA-2012-329534). LD, and MLK used the computational resources of Temple University, supported by the National Science Foundation through major research instrumentation grant number CNS-09-58854. JS acknowledges support from the Instituto de Salud Carlos III FEDER (CP12/03139