Heated aquatic microcosms for climate change experiments

Ponds and shallow lakes are likely to be strongly affected by climate change, and by increase in environmental temperature in particular. Hydrological regimes and nutrient cycling may be altered, plant and animal communities may undergo changes in both composition and dynamics, and long-term and difficult to reverse switches between alternative stable equilibria may occur. A thorough understanding of the potential effects of increased temperature on ponds and shallow lakes is desirable because these ecosystems are of immense importance throughout the world as sources of drinking water, and for their amenity and conservation value. This understanding can only come through experimental studies in which the effects of different temperature regimes are compared. This paper reports design details and operating characteristics of a recently constructed experimental facility consisting of 48 aquatic microcosms which mimic the pond and shallow lake environment. Thirty-two of the microcosms can be heated and regulated to simulate climate change scenarios, including those predicted for the UK. The authors also summarise the current and future experimental uses of the microcosms

NiftyNet: a deep-learning platform for medical imaging

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this application requires substantial implementation effort. Thus, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on TensorFlow and supports TensorBoard visualization of 2D and 3D images and computational graphs by default. We present 3 illustrative medical image analysis applications built using NiftyNet: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. NiftyNet enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications.Comment: Wenqi Li and Eli Gibson contributed equally to this work. M. Jorge Cardoso and Tom Vercauteren contributed equally to this work. 26 pages, 6 figures; Update includes additional applications, updated author list and formatting for journal submissio

Knowledge and attitudes of men to prostate cancer

Objective: To ascertain the current level of understanding about prostate cancer (PCa), including treatment options and potential side effects of treatment, among older men. Design and Setting: Questionnaires administered by general practitioners (GPs) in 5 general practices in the Perth metropolitan and regional areas of Western Australia. Participants: Convenience sample of men aged 40-80 years (n=503) with or without prostate cancer presenting for routine consultations. Main outcome measures: Knowledge and attitudes of men to prostate cancer Results: Eighty percent of men did not know the function of the prostate and 48% failed to identify PCa as the most common internal cancer in men. Thirty-five percent had no knowledge of the treatments for PCa and 53% had no knowledge of the side effects of treatments. Asked how they would arrive at a decision about treatment, 70% stated they would ask the GP/specialist for all their options and then decide themselves. Conclusion: This study confirms a deficit in knowledge of the disease among men in the at risk age group. Lack of knowledge encompassed areas which could delay diagnosis and hence treatment. Overall the population preferred some GP/specialist involvement in treatment decision making

The spatial effect of protein deuteration on nitroxide spin-label relaxation:implications for EPR distance measurement

This work was supported by a Wellcome Trust Senior Fellowship (095062) to T.O.-H. The Authors would also like to acknowledge funding from The MRC – United Kingdom, Grant G1100021.Pulsed electron-electron double resonance (PELDOR) coupled with site-directed spin labeling is a powerful technique for the elucidation of protein or nucleic acid, macromolecular structure and interactions. The intrinsic high sensitivity of electron paramagnetic resonance enables measurement on small quantities of bio-macromolecules, however short relaxation times impose a limit on the sensitivity and size of distances that can be measured using this technique. The persistence of the electron spin-echo, in the PELDOR experiment, is one of the most crucial limitations to distance measurement. At a temperature of around 50 K one of the predominant factors affecting persistence of an echo, and as such, the sensitivity and measurable distance between spin labels, is the electron spin echo dephasing time (Tm). It has become normal practice to use deuterated solvents to extend Tm and recently it has been demonstrated that deuteration of the underlying protein significantly extends Tm. Here we examine the spatial effect of segmental deuteration of the underlying protein, and also explore the concentration and temperature dependence of highly deuterated systems.Publisher PDFPeer reviewe

The capability of Acoustic Emission features to monitor diamond-coated burr grinding wear and effectiveness

Within manufacturing there is a growing need for autonomous Tool Condition Monitoring (TCM) systems, with the ability to predict tool wear and failure. This need is increased, when using specialised tools such as Diamond-Coated Burrs (DCBs) for grinding high strength ceramics or glass, in which the random nature of the tool, inconsistent manufacturing methods and high wear rates create large variance in tool life. This unpredictable nature leads to a significant fraction of a DCB tool's life being underutilised due to premature replacement. Workpiece surface damage, increased grinding forces and large-scale diamond grain pullout could all be the result of high levels of runout and in-circularity common within electroplated DCBs. As such it is important to not only monitor the overall tool wear but also tool condition. Acoustic Emission (AE) presents as an indirect on-machine sensing method highly suited to grinding applications. The high frequency range of AE, >20 kHz, prevents machine noise from dominating the acquired signals, isolating the micro-scale machining processes within noises machine environments. AE resulting from the grinding process has the potential to monitor not only tool wear but also runout and circularity. A series of DCB wear tests have been conducted, each consisting of the continuous acquisition of AE during grinding and frequent tool surface measurements. Preliminary results demonstrate AE kurtosis can be seen as an indicator of each tool’s runout, representing the fraction of time the tool and workpiece are in contact during a revolution. As a result, an indirect monitoring system capable of monitoring wear and tool state with AE could be utilised within the manufacturing sector

HIV policy implementation in two health and demographic surveillance sites in Uganda: findings from a national policy review, health facility surveys and key informant interviews.

BACKGROUND: Successful HIV testing, care and treatment policy implementation is essential for realising the reductions in morbidity and mortality those policies are designed to target. While adoption of new HIV policies is rapid, less is known about the facility-level implementation of new policies and the factors influencing this. METHODS: We assessed implementation of national policies about HIV testing, treatment and retention at health facilities serving two health and demographic surveillance sites (HDSS) (10 in Kyamulibwa, 14 in Rakai). Ugandan Ministry of Health HIV policy documents were reviewed in 2013, and pre-determined indicators were extracted relating to the content and nature of guidance on HIV service provision. Facility-level policy implementation was assessed via a structured questionnaire administered to in-charge staff from each health facility. Implementation of policies was classified as wide (?75% facilities), partial (26-74% facilities) or minimal (?25% facilities). Semi-structured interviews were conducted with key informants (policy-makers, implementers, researchers) to identify factors influencing implementation; data were analysed using the Framework Method of thematic analysis. RESULTS: Most policies were widely implemented in both HDSS (free testing, free antiretroviral treatment (ART), WHO first-line regimen as standard, Option B+). Both had notable implementation gaps for policies relating to retention on treatment (availability of nutritional supplements, support groups or isoniazid preventive therapy). Rakai implemented more policies relating to provision of antiretroviral treatment than Kyamulibwa and performed better on quality of care indicators, such as frequency of stock-outs. Factors facilitating implementation were donor investment and support, strong scientific evidence, low policy complexity, phased implementation and effective planning. Limited human resources, infrastructure and health management information systems were perceived as major barriers to effective implementation. CONCLUSIONS: Most HIV policies were widely implemented in the two settings; however, gaps in implementation coverage prevail and the value of ensuring complete coverage of existing policies should be considered against the adoption of new policies in regard to resource needs and health benefits

Prospective review of radiotherapy trials through implementation of standardised multi-centre workflow and IT infrastructure

Objective: We sought to develop a process that would allow us to perform a prospective review of outlining in trials using expert reviewers based in multiple centres. Methods: We implemented a specific information technology infrastructure and workflow that could serve all organizations involved in the radiotherapy quality assurance (RTQA) process. Results: Data were processed and packaged in the computational environment for radiotherapy research (CERR) binary format and securely transmitted to the expert reviewer at the designated remote organization. It was opened and reviewed using the distributed CERR-compiled application, and a standardized report was sent to the respective centre. Centres were expected to correct any unacceptable deviations and resubmit outlining for approval prior to commencing treatment. 75% of reviews were completed and fed back to centres within 3 working days. There were no delays in treatment start date. Conclusion: Our distributed RTQA review approach provides a method of prospective outlining review at multiple centres, without compromising the quality, delaying the start of treatment or the need for significant additional infrastructure resources. Future progress in the area of prospective individual case review will need to be supported by additional resources for clinician time to undertake the reviews. Advances in knowledge: Trial groups around the world have formulated different approaches to address the need for the prospective review of radiotherapy (RT) data with clinical trials, in line with available resources. We report a UK solution that has allowed the workload for outlining review to be distributed across a wider group of volunteer reviewers without the need for any additional infrastructure costs and has already been adopted within the UK RT trials community