A general theory for preferential sampling in environmental networks

This is the final version. Available from the Institute of Mathematical Statistics via the DOI in this recordThis paper presents a general model framework for detecting the preferential sampling of environmental monitors recording an environmental process across space and/or time. This is achieved by considering the joint distribution of an environmental process with a site–selection process that considers where and when sites are placed to measure the process. The environmental process may be spatial, temporal or spatio–temporal in nature. By sharing random effects between the two processes, the joint model is able to establish whether site placement was stochastically dependent of the environmental process under study. Furthermore, if stochastic dependence is identified between the two processes, then inferences about the probability distribution of the spatio–temporal process will change, as will predictions made of the process across space and time. The embedding into a spatio–temporal framework also allows for the modelling of the dynamic site—selection process itself. Real–world factors affecting both the size and location of the network can be easily modelled and quantified. Depending upon the choice of population of locations to consider for selection across space and time under the site– selection process, different insights about the precise nature of preferential sampling can be obtained. The general framework developed in the paper is designed to be easily and quickly fit using the R-INLA package. We apply this framework to a case study involving particulate air pollution over the UK where a major reduction in the size of a monitoring network through time occurred. It is demonstrated that a significant response–biased reduction in the air quality monitoring network occurred, namely the relocation of monitoring sites to locations with the highest pollution levels, and the routine removal of sites at locations with the lowest. We also show that the network was consistently unrepresentative of the levels of particulate matter seen across much of GB throughout the operating life of the network. Finally we show that this may have led to a severe over-reporting of the population–average exposure levels experienced across GB. This could have great impacts on estimates of the health effects of black smoke levels.Natural Science and Engineering Research Council of Canad

Stress in nurses : stress-related affect and its determinants examined over the nursing day

Peer reviewedPostprin

Clinical trials in a remote Aboriginal setting: lessons from the BOABS smoking cessation study

Background: There is limited evidence regarding the best approaches to helping Indigenous Australians to stop smoking. The composite analysis of the only two smoking cessation randomised controlled trials (RCTs)investigating this suggests that one-on-one extra support delivered by and provided to Indigenous Australians in a primary health care setting appears to be more effective than usual care in encouraging smoking cessation. This paper describes the lessons learnt from one of these studies, the Be Our Ally Beat Smoking (BOABS) Study, and how to develop and implement an integrated smoking cessation program. Methods: Qualitative study using data collected from multiple documentary sources related to the BOABS Study. As the project neared completion the research team participated in four workshops to review and conduct thematic analyses of these documents. Results: Challenges we encountered during the relatively complex BOABS Study included recruiting sufficient number of participants; managing the project in two distant locations and ensuring high quality work across both sites; providing appropriate training and support to Aboriginal researchers; significant staff absences, staff shortages and high workforce turnover; determining where and how the project fitted in the clinics and consequent siloing of the Aboriginal researchers relating to the requirements of RCTs; resistance to change, and maintaining organisational commitment and priority for the project.The results of this study also demonstrated the importance of local Aboriginal ownership, commitment, participation and control. This included knowledge of local communities, the flexibility to adapt interventions to local settings and circumstances, and taking sufficient time to allow this to occur. Conclusions: The keys to the success of the BOABS Study were local development, ownership and participation, worker professional development and support, and operating within a framework of cultural safety. There were difficulties associated with the BOABS Study being an RCT, and many of these are shared with stand-alone programs. Interventions targeted at particular health problems are best integrated with usual primary health care. Research to investigate complex interventions in Indigenous health should not be limited to randomised clinical trials and funding needs to reflect the additional, but necessary, cost of providing for local control of planning and implementation

Impaired perception of facial motion in autism spectrum disorder

Copyright: © 2014 O’Brien et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article has been made available through the Brunel Open Access Publishing Fund.Facial motion is a special type of biological motion that transmits cues for socio-emotional communication and enables the discrimination of properties such as gender and identity. We used animated average faces to examine the ability of adults with autism spectrum disorders (ASD) to perceive facial motion. Participants completed increasingly difficult tasks involving the discrimination of (1) sequences of facial motion, (2) the identity of individuals based on their facial motion and (3) the gender of individuals. Stimuli were presented in both upright and upside-down orientations to test for the difference in inversion effects often found when comparing ASD with controls in face perception. The ASD group’s performance was impaired relative to the control group in all three tasks and unlike the control group, the individuals with ASD failed to show an inversion effect. These results point to a deficit in facial biological motion processing in people with autism, which we suggest is linked to deficits in lower level motion processing we have previously reported

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance

Label-free cell cycle analysis for high-throughput imaging flow cytometry

Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding effects of fluorescent stains while maximizing available fluorescence channels. The method is effective in cell cycle analysis for mammalian cells, both fixed and live, and accurately assesses the impact of a cell cycle mitotic phase blocking agent. As the same method is effective in predicting the DNA content of fission yeast, it is likely to have a broad application to other cell types

The SNAPSHOT study protocol : SNAcking, Physical activity, Self-regulation, and Heart rate Over Time

Peer reviewedPublisher PD

Optimizing Optical Flow Cytometry for Cell Volume-Based Sorting and Analysis

Cell size is a defining characteristic central to cell function and ultimately to tissue architecture. The ability to sort cell subpopulations of different sizes would facilitate investigation at genomic and proteomic levels of mechanisms by which cells attain and maintain their size. Currently available cell sorters, however, cannot directly measure cell volume electronically, and it would therefore be desirable to know which of the optical measurements that can be made in such instruments provide the best estimate of volume. We investigated several different light scattering and fluorescence measurements in several different cell lines, sorting cell fractions from the high and low end of distributions, and measuring volume electronically to determine which sorting strategy yielded the best separated volume distributions. Since we found that different optical measurements were optimal for different cell lines, we suggest that following this procedure will enable other investigators to optimize their own cell sorters for volume-based separation of the cell types with which they work

Machine Perfusion of Donor Livers for Transplantation: A Proposal for Standardized Nomenclature and Reporting Guidelines.

With increasing demand for donor organs for transplantation, machine perfusion (MP) promises to be a beneficial alternative preservation method for donor livers, particularly those considered to be of suboptimal quality, also known as extended criteria donor livers. Over the last decade, numerous studies researching MP of donor livers have been published and incredible advances have been made in both experimental and clinical research in this area. With numerous research groups working on MP, various techniques are being explored, often applying different nomenclature. The objective of this review is to catalog the differences observed in the nomenclature used in the current literature to denote various MP techniques and the manner in which methodology is reported. From this analysis, we propose a standardization of nomenclature on liver MP to maximize consistency and to enable reliable comparison and meta-analyses of studies. In addition, we propose a standardized set of guidelines for reporting the methodology of future studies on liver MP that will facilitate comparison as well as clinical implementation of liver MP procedures