Multiple Biomarkers for the prediction of ischemic stroke: the PRIME study

Objective: To simultaneously evaluate 14 biomarkers from distinct biological pathways for risk prediction of ischemic stroke, including biomarkers of hemostasis, inflammation, and endothelial activation as well as chemokines and adipocytokines.
Methods and Results: The Prospective Epidemiological Study on Myocardial Infarction (PRIME) is a cohort of 9771 healthy men 50 to 59 years of age who were followed up over 10 years. In a nested case–control study, 95 ischemic stroke cases were matched with 190 controls. After multivariable adjustment for traditional risk factors, fibrinogen (odds ratio [OR], 1.53; 95% confidence interval [CI], 1.03–2.28), E-selectin (OR, 1.76; 95% CI, 1.06–2.93), interferon-γ-inducible-protein-10 (OR, 1.72; 95% CI, 1.06–2.78), resistin (OR, 2.86; 95% CI, 1.30–6.27), and total adiponectin (OR, 1.82; 95% CI, 1.04–3.19) were significantly associated with ischemic stroke. Adding E-selectin and resistin to a traditional risk factor model significantly increased the area under the receiver-operating characteristic curve from 0.679 (95% CI, 0.612–0.745) to 0.785 and 0.788, respectively, and yielded a categorical net reclassification improvement of 29.9% (P=0.001) and 28.4% (P=0.002), respectively. Their simultaneous inclusion in the traditional risk factor model increased the area under the receiver-operating characteristic curve to 0.824 (95% CI, 0.770–0.877) and resulted in an net reclassification improvement of 41.4% (P<0.001). Results were confirmed when using continuous net reclassification improvement.
Conclusion: Among multiple biomarkers from distinct biological pathways, E-selectin and resistin provided incremental and additive value to traditional risk factors in predicting ischemic stroke.

Design and Development of a Film-based Intervention about Teenage Men and Unintended Pregnancy: Applying the Medical Research Council Framework in Practice

Following the UK Medical Research Council’s (MRC) guidelines for the development and evaluation of complex interventions, this study aimed to design, develop and optimise an educational intervention about young men and unintended teenage pregnancy based around an interactive film. The process involved identification of the relevant evidence base, development of a theoretical understanding of the phenomenon of unintended teenage pregnancy in relation to young men, and exploratory mixed methods research. The result was an evidence-based, theory-informed, user-endorsed intervention designed to meet the much neglected pregnancy education needs of teenage men and intended to increase both boys’ and girls’ intentions to avoid an unplanned pregnancy during adolescence. In prioritising the development phase, this paper addresses a gap in the literature on the processes of research-informed intervention design. It illustrates the application of the MRC guidelines in practice while offering a critique and additional guidance to programme developers on the MRC prescribed processes of developing interventions. Key lessons learned were: 1) know and engage the target population and engage gatekeepers in addressing contextual complexities; 2) know the targeted behaviours and model a process of change; and 3) look beyond development to evaluation and implementation.

Developing a best practice model for partnership practice between specialist palliative care and intellectual disability services: a mixed methods study

Background: The lack of access to good quality palliative care for people with intellectual disabilities is highlighted in the international literature. In response, more partnership practice in end-of-life care is proposed. 
Aim: This study aimed to develop a best practice model to guide and promote partnership practice between specialist palliative care and intellectual disability services. 
Design: A mixed methods research design involving two phases was used, underpinned by a conceptual model for partnership practice. 
Setting/participants: Phase 1 involved scoping end-of-life care to people with intellectual disability, based on self-completed questionnaires. In all, 47 of 66 (71.2%) services responded. In Phase 2, semi-structured interviews were undertaken with a purposive sample recruited of 30 health and social care professionals working in intellectual disability and palliative care services, who had provided palliative care to someone with intellectual disability. For both phases, data were collected from primary and secondary care in one region of the United Kingdom. 
Results: In Phase 1, examples of good practice were apparent. However, partnership practice was infrequent and unmet educational needs were identified. Four themes emerged from the interviews in Phase 2: challenges and issues in end-of-life care, sharing and learning, supporting and empowering and partnership in practice. 
Conclusion: Joint working and learning between intellectual disability and specialist palliative care were seen as key and fundamental. A framework for partnership practice between both services has been developed which could have international applicability and should be explored with other services in end-of-life care.

Aerofoil Optimisation Using CST Parameterisation in SU2

This paper describes an implementation of the popular method of Class-Shape Transformation for aerofoil design within SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities from the new parameterisation is introduced, enabling the calculation of gradients with respect to new design variables. To assess the accuracy and efficiency of the alternative approach, two transonic optimisation problems are investigated: an inviscid problem with multiple constraints and a viscous problems without any constraints. Results show the new parameterisation obtaining reliable optimums, with similar levels of
performance of the software native parameterisations.

Multiple mycotoxin exposure determined by urinary biomarkers in rural subsistence farmers in the former Transkei, South Africa

Subsistence farmers are exposed to a range of mycotoxins. This study applied novel urinary multi-mycotoxin LC-MS/MS methods to determine multiple exposure biomarkers in the high oesophageal cancer region, Transkei, South Africa. Fifty-three female participants donated part of their maize-based evening meal and first void morning urine, which was analysed both with sample clean-up (single and multi-biomarker) and by a 'dilute-and-shoot' multi-biomarker method. Results were corrected for recovery with LOD for not detected. A single biomarker method detected fumonisin B1 (FB1) (87% incidence; mean±standard deviation 0.342±0.466 ng/mg creatinine) and deoxynivalenol (100%; mean 20.4±49.4 ng/mg creatinine) after hydrolysis with β-glucuronidase. The multi-biomarker 'dilute-and-shoot' method indicated deoxynivalenol-15-glucuronide was predominantly present. A multi-biomarker method with β-glucuronidase and immunoaffinity clean-up determined zearalenone (100%; 0.529±1.60 ng/mg creatinine), FB1 (96%; 1.52±2.17 ng/mg creatinine), α-zearalenol (92%; 0.614±1.91 ng/mg creatinine), deoxynivalenol (87%; 11.3±27.1 ng/mg creatinine), β-zearalenol (75%; 0.702±2.95 ng/mg creatinine) and ochratoxin A (98%; 0.041±0.086 ng/mg creatinine). These demonstrate the value of multi-biomarker methods in measuring exposures in populations exposed to multiple mycotoxins. This is the first finding of urinary deoxynivalenol, zearalenone, their conjugates, ochratoxin A and zearalenols in Transkei.

An Extended Event Reasoning Framework for Decision Support under Uncertainty

To provide in-time reactions to a large volume of surveil- lance data, uncertainty-enabled event reasoning frameworks for CCTV and sensor based intelligent surveillance system have been integrated to model and infer events of interest. However, most of the existing works do not consider decision making under uncertainty which is important for surveillance operators. In this paper, we extend an event reasoning framework for decision support, which enables our framework to predict, rank and alarm threats from multiple heterogeneous sources.

Elements of A New Framework for the principle of Equal Treatment of persons in EC Law

In June and November 2000, the European Parliament and the Council adopted two Directives referring to ‘the principle of equal treatment irrespective of’ in their title, one relating to racial and ethnic origin, the other to disability, age, religion and belief or sexual orientation. A thorough reform of Directive 76/207/EEC on the principle of equal treatment for women and men in employment matters is pending between the European Parliament's second reading and adoption while this is written. Community secondary legislation on equal treatment of persons has thus expanded in scope and number of reasons which must not serve as starting points for differentiation. Does this signify progress in legal protection against personal discrimination? While not providing a ready answer, this article proposes an analytical framework to answer this question, concentrating on conceptions of equality in general and in particular on the problems multi-dimensional discrimination might pose for the law.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Precision Teaching in IV Fluid Prescribing and Patient Safety

OBJECTIVES: Precision Teaching (PT) has been shown to be an effective intervention to assess teaching method effectiveness and evaluate learning outcomes. SAFMEDS (Say All Fast Minute Every Day Shuffled) are a practice/assessment procedure within the PT framework to assist learning and fluency. We explored the effects of a brief intervention with PT, to impart high frequency performance in safe intravenous fluid prescription in a group of final year undergraduate medical students.
METHODS: 133 final year undergraduate medical students completed a multiple choice question (MCQ) test on safe IV fluid prescription at the beginning and end of the study. The control group (n= 76) of students were taught using a current standardized teaching method. Students allocated to the intervention arm of the study were additionally instructed on PT and the use of SAFMEDS. The study group (n = 57) received 50 SAFMEDS cards containing information on the principles of IV fluid prescription scenarios. These students were trained/tested twice per day for 1 minute.
RESULTS: Interim analysis showed that the study group displayed an improvement in fluency and accuracy as the study progressed. There was a statistically significant improvement in MCQ performance for the PT group compared with the control group between the beginning and end of the study (35% vs 15%).
CONCLUSION: These results suggest PT employing SAFMEDS is an effective method for improving fluency, accuracy and patient safety in intravenous fluid prescribing amongst undergraduate medical students.

Modeling relativistic soliton interactions in overdense plasmas: A perturbed nonlinear Schrodinger equation framework

We investigate the dynamics of localized solutions of the relativistic cold-fluid plasma model in the small but finite amplitude limit, for slightly overcritical plasma density. Adopting a multiple scale analysis, we derive a perturbed nonlinear Schrodinger equation that describes the evolution of the envelope of circularly polarized electromagnetic field. Retaining terms up to fifth order in the small perturbation parameter, we derive a self-consistent framework for the description of the plasma response in the presence of localized electromagnetic field. The formalism is applied to standing electromagnetic soliton interactions and the results are validated by simulations of the full cold-fluid model. To lowest order, a cubic nonlinear Schrodinger equation with a focusing nonlinearity is recovered. Classical quasiparticle theory is used to obtain analytical estimates for the collision time and minimum distance of approach between solitons. For larger soliton amplitudes the inclusion of the fifth-order terms is essential for a qualitatively correct description of soliton interactions. The defocusing quintic nonlinearity leads to inelastic soliton collisions, while bound states of solitons do not persist under perturbations in the initial phase or amplitude

An Ambiguity Aversion Framework of Security Game under Ambiguities

Security is a critical concern around the world. Since resources for security are always limited, lots of interest have arisen in using game theory to handle security resource allocation problems. However, most of the existing work does not address adequately how a defender chooses his optimal strategy in a game with absent, inaccurate, uncertain, and even ambiguous strategy profiles' payoffs. To address this issue, we propose a general framework of security games under ambiguities based on Dempster-Shafer theory and the ambiguity aversion principle of minimax regret. Then, we reveal some properties of this framework. Also, we present two methods to reduce the influence of complete ignorance. Our investigation shows that this new framework is better in handling security resource allocation problems under ambiguities.

A new statistical framework for the quantification of covariate associations with species distributions

Identifying processes that shape species geographical ranges is a prerequisite for understanding environmental change. Currently, species distribution modelling methods do not offer credible statistical tests of the relative influence of climate factors and typically ignore other processes (e.g. biotic interactions and dispersal limitation). We use a hierarchical model fitted with Markov Chain Monte Carlo to combine ecologically plausible niche structures using regression splines to describe unimodal but potentially skewed response terms. We apply spatially explicit error terms that account for (and may help identify) missing variables. Using three example distributions of European bird species, we map model results to show sensitivity to change in each covariate. We show that the overall strength of climatic association differs between species and that each species has considerable spatial variation in both the strength of the climatic association and the sensitivity to climate change. Our methods are widely applicable to many species distribution modelling problems and enable accurate assessment of the statistical importance of biotic and abiotic influences on distributions.

Developing management capability within a horizontal supply chain in performance measurement deployment and evolution: A Dynamic Capabilities and Goal Theory perspective

Complex collaboration in rapidly changing business environments create challenges for management capability in Utility Horizontal Supply Chains (UHSCs) involving the deploying and evolving of performance measures. The aim of the study is twofold. First, there is a need to explore how management capability can be developed and used to deploy and evolve Performance Measurement (PM), both across a UHSC and within its constituent organisations, drawing upon a theoretical nexus of Dynamic Capability (DC) theory and complementary Goal Theory. Second, to make a contribution to knowledge by empirically building theory using these constructs to show the management motivations and behaviours within PM-based DCs. The methodology uses an interpretive theory building, multiple case based approach (n=3) as part of a USHC. The data collection methods include, interviews (n=54), focus groups (n=10), document analysis and participant observation (reflective learning logs) over a five-year period giving longitudinal data. The empirical findings lead to the development of a conceptual framework showing that management capabilities in driving PM deployment and evolution can be represented as multilevel renewal and incremental Dynamic Capabilities, which can be further understood in terms of motivation and behaviour by Goal-Theoretic constructs. In addition three interrelated cross cutting themes of management capabilities in consensus building, goal setting and resource change were identified. These management capabilities require carefully planned development and nurturing within the UHSC. 

PICan: An integromics framework for dynamic cancer biomarker discovery

Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.

THE SAAF STUDY: evaluation of the Safeguarding Children Assessment and Analysis Framework (SAAF), compared with management as usual, for improving outcomes for children and young people who have experienced, or are at risk of, maltreatment: study protocol for a randomised controlled trial

Background: Serious case reviews and research studies have indicated weaknesses in risk assessments conducted by child protection social workers. Social workers are adept at gathering information but struggle with analysis and assessment of risk. The Department for Education wants to know if the use of a structured decision-making tool can improve child protection assessments of risk.

Methods/design: This multi-site, cluster-randomised trial will assess the effectiveness of the Safeguarding Children Assessment and Analysis Framework (SAAF). This structured decision-making tool aims to improve social workers' assessments of harm, of future risk and parents' capacity to change. The comparison is management as usual.

Inclusion criteria: Children's Services Departments (CSDs) in England willing to make relevant teams available to be randomised, and willing to meet the trial's training and data collection requirements.

Exclusion criteria: CSDs where there were concerns about performance; where a major organisational restructuring was planned or under way; or where other risk assessment tools were in use.

Six CSDs are participating in this study. Social workers in the experimental arm will receive 2 days training in SAAF together with a range of support materials, and access to limited telephone consultation post-training. The primary outcome is child maltreatment. This will be assessed using data collected nationally on two key performance indicators: the first is the number of children in a year who have been subject to a second Child Protection Plan (CPP); the second is the number of re-referrals of children because of related concerns about maltreatment. Secondary outcomes are: i) the quality of assessments judged against a schedule of quality criteria and ii) the relationship between the three assessments required by the structured decision-making tool (level of harm, risk of (re) abuse and prospects for successful intervention).

Discussion: This is the first study to examine the effectiveness of SAAF. It will contribute to a very limited literature on the contribution that structured decision-making tools can make to improving risk assessment and case planning in child protection and on what is involved in their effective implementation.