'The world is full of big bad wolves': investigating the experimental therapeutic spaces of R.D. Laing and Aaron Esterson

In conjunction with the recent critical assessments of the life and work of R.D. Laing, this paper seeks to demonstrate what is revealed when Laing’s work on families and created spaces of mental health care are examined through a geographical lens. The paper begins with an exploration of Laing’s time at the Tavistock Clinic in London during the 1960s, and of the co-authored text with Aaron Esterson entitled, Sanity, Madness and the Family (1964). The study then seeks to demonstrate the importance Laing and his colleague placed on the time-space situatedness of patients and their worlds. Finally, an account is provided of Laing’s and Esterson’s spatial thinking in relation to their creation of both real and imagined spaces of therapeutic care

AGENT: Alumni growth and engagement across new technologies

The AGENT project aims to use social networking technologies (LinkedIn and Facebook) to support the development of undergraduates’ employability and career development. The focus of the project is on e-mentoring by alumni to provide a ‘bridge’ between individuals whose social ties and connections are weakened by time and distance, whilst at the same time capitalising on the learning opportunities afforded by the widening of social networks. Social networking sites (SNSs) have been shown to provide students with the tools to make connections, build relationships and support personal development. From a social capital perspective, SNSs can support ‘weak ties’ by allowing students to grow a social network from which to draw resources in the form of information, knowledge, advice and expertise that an institution’s alumni can provide. Alumni are a key resource for building professional networking communities that can provide offline as well as online support to students. We report on an on-going JISC project –AGENT (Alumni Growth and Engagement across New Technologies) that explores how Web 2.0 technologies engage alumni, create the sense of belonging, develop more effective and mutually-beneficial alumni-student connections and associated positive social capital outcomes.Joint Information Systems Committee (JISC) 2011-201

Representation of probabilistic scientific knowledge

This article is available through the Brunel Open Access Publishing Fund. Copyright © 2013 Soldatova et al; licensee BioMed Central Ltd.The theory of probability is widely used in biomedical research for data analysis and modelling. In previous work the probabilities of the research hypotheses have been recorded as experimental metadata. The ontology HELO is designed to support probabilistic reasoning, and provides semantic descriptors for reporting on research that involves operations with probabilities. HELO explicitly links research statements such as hypotheses, models, laws, conclusions, etc. to the associated probabilities of these statements being true. HELO enables the explicit semantic representation and accurate recording of probabilities in hypotheses, as well as the inference methods used to generate and update those hypotheses. We demonstrate the utility of HELO on three worked examples: changes in the probability of the hypothesis that sirtuins regulate human life span; changes in the probability of hypotheses about gene functions in the S. cerevisiae aromatic amino acid pathway; and the use of active learning in drug design (quantitative structure activity relation learning), where a strategy for the selection of compounds with the highest probability of improving on the best known compound was used. HELO is open source and available at https://github.com/larisa-soldatova/HELO.This work was partially supported by grant BB/F008228/1 from the UK Biotechnology & Biological Sciences Research Council, from the European Commission under the FP7 Collaborative Programme, UNICELLSYS, KU Leuven GOA/08/008 and ERC Starting Grant 240186

On the use of semi-distributed and fully-distributed urban stormwater models

Urban stormwater models comprise four main components: rainfall, rainfall-runoff, overland flow and sewer flow modules. They can be considered semi-distributed (SD) or fully distributed (FD) according to the rainfall-runoff module definition. SD models are based on sub-catchments units through which rainfall is applied to the model and at which runoff volumes are estimated. In FD models, the runoff volumes are estimated and applied directly on every element of a twodimensional (2D) model of the surface. This poster presents a comparison of SD and FD models based on two case studies: Zona Central catchment at Coimbra, Portugal, and Cranbrook catchment at London, UK. SD and FD modelling results are compared against water depth and flow records in sewers, and photographic records of a flood event. In general, FD models are theoretically more realistic and physically-based, but the results of this study suggest that the implementation of these models requires higher resolution (more detailed) elevation, land use and sewer network data than is normally used in the implementation of SD models. Failing to use higher resolution data for the implementation of FD models could result in poor-performing models. In cases when high resolution data are not available, the use of SD models could be a better choice

Liver transplantation across ABO blood groups

Six hundred seventy-one first, second, and third orthotopic liver allografts in 520 patients were reviewed to determine the effect of donor-recipient mismatches or incompatibility for the ABO blood group on graft survival. A significant advantage for ABO donor-recipient identity was found, especially in adults and for first grafts. However, a surprisingly large number of ABO incompatible grafts were successful. We recommend that nonidentical or incompatible grafts be limited to patients such as small children for whom the supply of available donors is severely limited or for patients in urgent need of transplantation or retransplantation

Quantifying disease activity in fatty-infiltrated skeletal muscle by IDEAL-CPMG in Duchenne muscular dystrophy

The purpose of this study was to explore the use of iterative decomposition of water and fat with echo asymmetry and least-squares estimation Carr-Purcell-Meiboom-Gill (IDEAL-CPMG) to simultaneously measure skeletal muscle apparent fat fraction and water T2 (T2,w) in patients with Duchenne muscular dystrophy (DMD). In twenty healthy volunteer boys and thirteen subjects with DMD, thigh muscle apparent fat fraction was measured by Dixon and IDEAL-CPMG, with the IDEAL-CPMG also providing T2,w as a measure of muscle inflammatory activity. A subset of subjects with DMD was followed up during a 48-week clinical study. The study was in compliance with the Patient Privacy Act and approved by the Institutional Review Board. Apparent fat fraction in the thigh muscles of subjects with DMD was significantly increased compared to healthy volunteer boys (p <0.001). There was a strong correlation between Dixon and IDEAL-CPMG apparent fat fraction. Muscle T2,w measured by IDEAL-CPMG was independent of changes in apparent fat fraction. Muscle T2,w was higher in the biceps femoris and vastus lateralis muscles of subjects with DMD (p <0.05). There was a strong correlation (p <0.004) between apparent fat fraction in all thigh muscles and six-minute walk distance (6MWD) in subjects with DMD. IDEAL-CPMG allowed independent and simultaneous quantification of skeletal muscle fatty degeneration and disease activity in DMD. IDEAL-CPMG apparent fat fraction and T2,w may be useful as biomarkers in clinical trials of DMD as the technique disentangles two competing biological processes