Formative assessment of inquiry skills for Responsible Research and Innovation using 3D Virtual Reality Glasses and Face Recognition

This paper examines the experience and views of learners on technological innovations with a novel pedagogical model to enhance formative online assessment of Responsible Research and Innovation (RRI) skills with e-authentication. The authors developed the OER “virtual classroom” app based on the famous “Bletchley Park” and also an activity for learners exploring this museum in pairs with individual assessment. Participants practiced RRI skills and shared their views about their VR experience in an e-assessment activity with e-authentication through the TeSLA face recognition system. Participants were students from the UK and Brazil. Our research questions include whether the 3DVRG activities in pairs in the same physical environment support peer-learning with assessment-in-context. Findings revealed that activities that enabled physical interactions in pairs enriched the virtual interactions in the museum. The combination of authentic scenario, interactive tasks and assessment-in-context helped learners acquire new information and connect with existing knowledge. These interactions enhanced the immersive learning experience, particularly for those who did not experienced sickness with 3DVRG. Three types of interactions with the virtual space, their peer and the topic respectively enabled the virtual, social and cognitive presence

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

CCL2-driven inflammation increases mammary gland stromal density and cancer susceptibility in a transgenic mouse model.

Abstract Background Macrophages play diverse roles in mammary gland development and breast cancer. CC-chemokine ligand 2 (CCL2) is an inflammatory cytokine that recruits macrophages to sites of injury. Although CCL2 has been detected in human and mouse mammary epithelium, its role in regulating mammary gland development and cancer risk has not been explored. Methods Transgenic mice were generated wherein CCL2 is driven by the mammary epithelial cell-specific mouse mammary tumour virus 206 (MMTV) promoter. Estrous cycles were tracked in adult transgenic and non-transgenic FVB mice, and mammary glands collected at the four different stages of the cycle. Dissected mammary glands were assessed for cyclical morphological changes, proliferation and apoptosis of epithelium, macrophage abundance and collagen deposition, and mRNA encoding matrix remodelling enzymes. Another cohort of control and transgenic mice received carcinogen 7,12-Dimethylbenz(a)anthracene (DMBA) and tumour development was monitored weekly. CCL2 protein was also quantified in paired samples of human breast tissue with high and low mammographic density. Results Overexpression of CCL2 in the mammary epithelium resulted in an increased number of macrophages, increased density of stroma and collagen and elevated mRNA encoding matrix remodelling enzymes lysyl oxidase (LOX) and tissue inhibitor of matrix metalloproteinases (TIMP)3 compared to non-transgenic controls. Transgenic mice also exhibited increased susceptibility to development of DMBA-induced mammary tumours. In a paired sample cohort of human breast tissue, abundance of epithelial-cell-associated CCL2 was higher in breast tissue of high mammographic density compared to tissue of low mammographic density. Conclusions Constitutive expression of CCL2 by the mouse mammary epithelium induces a state of low level chronic inflammation that increases stromal density and elevates cancer risk. We propose that CCL2-driven inflammation contributes to the increased risk of breast cancer observed in women with high mammographic density

Resilience Management for Healthy Cities in a Changing Climate

Cities are experiencing multiple impacts from global environmental change, and the degree to which they will need to cope with and adapt to these challenges will continue to increase. We argue that a ‘complex systems and resilience management’ view may significantly help guide future urban development through innovative integration of, for example, grey, blue and green infrastructure embedded in flexible institutions (both formal and informal) for multi-functionality and improved health. For instance, the urban heat island effect will further increase city-centre temperatures during projected more frequent and intense heat waves. The elderly and people with chronic cardiovascular and respiratory diseases are particularly vulnerable to heat. Integrating vegetation and especially trees in the urban infrastructure helps reduce temperatures by shading and evapotranspiration. Great complexity and uncertainty of urban social-ecological systems are behind this heatwave-health nexus, and they need to be addressed in a more comprehensive manner. We argue that a systems perspective can lead to innovative designs of new urban infrastructure and the redesign of existing structures. Particularly to promoting the integration of grey, green and blue infrastructure in urban planning through institutional innovation and structural reorganization of knowledge-action systems may significantly enhance prospects for improved urban health and greater resilience under various scenarios of climate change.info:eu-repo/semantics/publishedVersio

Efficacy of a training intervention on the quality of practitioners' decision support for patients deciding about place of care at the end of life: A randomized control trial: Study protocol

<p>Abstract</p> <p>Background</p> <p>Most people prefer home palliation but die in an institution. Some experience decisional conflict when weighing options regarding place of care. Clinicians can identify patients' decisional needs and provide decision support, yet generally lack skills and confidence in doing so. This study aims to determine whether the quality of clinicians' decision support can be improved with a brief, theory-based, skills-building intervention.</p> <p>Theory</p> <p>The Ottawa Decision Support Framework (ODSF) guides an evidence based, practical approach to assist clinicians in providing high-quality decision support. The ODSF proposes that decisional needs [personal uncertainty, knowledge, values clarity, support, personal characteristics] strongly influence the quality of decisions patients make. Clinicians can improve decision quality by providing decision support to address decisional needs [clarify decisional needs, provide facts and probabilities, clarify values, support/guide deliberation, monitor/facilitate progress].</p> <p>Methods/Design</p> <p>The efficacy of a brief education intervention will be assessed in a two-phase study. In phase one a focused needs assessment will be conducted with key informants. Phase two is a randomized control trial where clinicians will be randomly allocated to an intervention or control group. The intervention, informed by the needs assessment, knowledge transfer best practices and the ODSF, comprises an online tutorial; an interactive skills building workshop; a decision support protocol; performance feedback, and educational outreach. Participants will be assessed: a) at baseline (quality of decision support); b) after the tutorial (knowledge); and c) four weeks after the other interventions (quality of decision support, intention to incorporate decision support into practice and perceived usefulness of intervention components). Between group differences in the primary outcome (quality of decision support scores) will be analyzed using ANOVA.</p> <p>Discussion</p> <p>Few studies have investigated the efficacy of an evidence-based, theory guided intervention aimed at assisting clinicians to strengthen their patient decision support skills. Expanding our understanding of how clinicians can best support palliative patients' decision-making will help to inform best practices in patient-centered palliative care. There is potential transferability of lessons learned to other care situations such as chronic condition management, advance directives and anticipatory care planning. Should the efficacy evaluation reveal clear improvements in the quality of decision support provided by clinicians who received the intervention, a larger scale implementation and effectiveness trial will be considered.</p> <p>Trial registration</p> <p>This study is registered as NCT00614003</p

A reappraisal of the impact of dairy foods and milk fat on cardiovascular disease risk

Background This review provides a reappraisal of the potential effects of dairy foods, including dairy fats, on cardiovascular disease (CVD)/coronary heart disease (CHD) risk. Commodities and foods containing saturated fats are of particular focus as current public dietary recommendations are directed toward reducing the intake of saturated fats as a means to improve the overall health of the population. A conference of scientists from different perspectives of dietary fat and health was convened in order to consider the scientific basis for these recommendations. Aims This review and summary of the conference focus on four key areas related to the biology of dairy foods and fats and their potential impact on human health: (a) the effect of dairy foods on CVD in prospective cohort studies; (b) the impact of dairy fat on plasma lipid risk factors for CVD; (c) the effects of dairy fat on non-lipid risk factors for CVD; and (d) the role of dairy products as essential contributors of micronutrients in reference food patterns for the elderly. Conclusions Despite the contribution of dairy products to the saturated fatty acid composition of the diet, and given the diversity of dairy foods of widely differing composition, there is no clear evidence that dairy food consumption is consistently associated with a higher risk of CVD. Thus, recommendations to reduce dairy food consumption irrespective of the nature of the dairy product should be made with cautionJ. Bruce German, Robert A. Gibson, Ronald M. Krauss, Paul Nestel, Benoît Lamarche, Wija A. van Staveren, Jan M. Steijns, Lisette C. P. G. M. de Groot, Adam L. Lock and Frédéric Destaillat

Recent progress in understanding and predicting Atlantic decadal climate variability

Recent Atlantic climate prediction studies are an exciting new contribution to an extensive body of research on Atlantic decadal variability and predictability that has long emphasized the unique role of the Atlantic Ocean in modulating the surface climate. We present a survey of the foundations and frontiers in our understanding of Atlantic variability mechanisms, the role of the Atlantic Meridional Overturning Circulation (AMOC), and our present capacity for putting that understanding into practice in actual climate prediction systems

predictive precision medicine towards the computational challenge

The emerging fields of predictive and precision medicine are changing the traditional medical approach to disease and patient. Current discoveries in medicine enable to deepen the comprehension of diseases, whereas the adoption of high-quality methods such as novel imaging techniques (e.g. MRI, PET) and computational approaches (i.e. machine learning) to analyse data allows researchers to have meaningful clinical and statistical information. Indeed, applications of radiology techniques and machine learning algorithms rose in the last years to study neurology, cardiology and oncology conditions. In this chapter, we will provide an overview on predictive precision medicine that uses artificial intelligence to analyse medical images to enhance diagnosis, prognosis and treatment of diseases. In particular, the chapter will focus on neurodegenerative disorders that are one of the main fields of application. Despite some critical issues of this new approach, adopting a patient-centred approach could bring remarkable improvement on individual, social and business level