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

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

Recent advances in the management of childhood asthma

Journal of the Singapore Paediatric Society361-216-28SPSJ

Oval cell-mediated liver regeneration: Role of cytokines and growth factors

In experimental models, which induce liver damage and simultaneously block hepatocyte proliferation, the recruitment of a hepatic progenitor cell population comprised of oval cells is invariably observed. There is a substantial body of evidence to suggest that oval cells are involved in liver regeneration, as they differentiate into hepatocytes and biliary cells. Recently, bone marrow cells were shown to be a source of a stem cells with the capacity to repopulate the liver. Presently, the relationship between bone marrow cells and oval cells is unclear. Investigations will be greatly assisted by the availability of in vitro models based on a knowledge of cytokines that affect oval cells. While the cytokines, which regulate the different hematopoietic lineages, are well characterized, there is relatively little information regarding those that influence oval cells. This review outlines recent developments in the field of oval cell research and focuses on cytokines and growth factors that have been implicated in regulating oval cell proliferation and differentiation

High-Dimensional Micro-array Data Classification Using Minimum Description Length and Domain Expert Knowledge

This paper reports on three machine learning methods, i.e. Naïve Bayes (NB), Adaptive Bayesian Network (ABN) and Support Vector Machines (SVM) for multi-target classification on micro-array datasets involving a large feature space and very few samples. By adopting the Minimum Description Length criterion for ranking and selecting relevant features, experiments are carried out to investigate the accuracy and effectiveness of the above methods in classifying many targets as well as to study the effects of feature selection on the sensitivity of each classifier. The paper also shows how the knowledge of a domain expert makes it possible to decompose the multi-target classification in a set of binary classifications, one for each target, with a substantial improvement in accuracy. The effectiveness of the MDL criterion to decide on particular feature subsets is asserted by empirical results showing that MDL is comparable with entropy based feature selection methodologies reported by earlier works

Bioinformatics Adventures in Database Research

Informatics has helped launch molecular biology into the genomic era. It appears certain that informatics will remain a major contributor to molecular biology in the post-genome era. We discuss here data integration and datamining in bioinformatics, as well as the role that database theory played in these topics