Nottingham Trent University

About: Nottingham Trent University is a education organization based out in Nottingham, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 4702 authors who have published 12862 publications receiving 307430 citations. The organization is also known as: NTU & Trent Polytechnic.

High‐throughput protein expression analysis using tissue microarray technology of a large well‐characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses

Abstract: Recent studies on gene molecular profiling using cDNA microarray in a relatively small series of breast cancer have identified biologically distinct groups with apparent clinical and prognostic relevance. The validation of such new taxonomies should be confirmed on larger series of cases prior to acceptance in clinical practice. The development of tissue microarray (TMA) technology provides methodology for high-throughput concomitant analyses of multiple proteins on large numbers of archival tumour samples. In our study, we have used immunohistochemistry techniques applied to TMA preparations of 1,076 cases of invasive breast cancer to study the combined protein expression profiles of a large panel of well-characterized commercially available biomarkers related to epithelial cell lineage, differentiation, hormone and growth factor receptors and gene products known to be altered in some forms of breast cancer. Using hierarchical clustering methodology, 5 groups with distinct patterns of protein expression were identified. A sixth group of only 4 cases was also identified but deemed too small for further detailed assessment. Further analysis of these clusters was performed using multiple layer perceptron (MLP)-artificial neural network (ANN) with a back propagation algorithm to identify key biomarkers driving the membership of each group. We have identified 2 large groups by their expression of luminal epithelial cell phenotypic characteristics, hormone receptors positivity, absence of basal epithelial phenotype characteristics and lack of c-erbB-2 protein overexpression. Two additional groups were characterized by high c-erbB-2 positivity and negative or weak hormone receptors expression but showed differences in MUC1 and E-cadherin expression. The final group was characterized by strong basal epithelial characteristics, p53 positivity, absent hormone receptors and weak to low luminal epithelial cytokeratin expression. In addition, we have identified significant differences between clusters identified in this series with respect to established prognostic factors including tumour grade, size and histologic tumour type as well as differences in patient outcomes. The different protein expression profiles identified in our study confirm the biologic heterogeneity of breast cancer and demonstrate the clinical relevance of classification in this manner. These observations could form the basis of revision of existing traditional classification systems for breast cancer.

Excessive Computer Game Playing: Evidence for Addiction and Aggression?

Abstract: Computer games have become an ever-increasing part of many adolescents' day-to-day lives. Coupled with this phenomenon, reports of excessive gaming (computer game playing) denominated as "computer/video game addiction" have been discussed in the popular press as well as in recent scientific research. The aim of the present study was the investigation of the addictive potential of gaming as well as the relationship between excessive gaming and aggressive attitudes and behavior. A sample comprising of 7069 gamers answered two questionnaires online. Data revealed that 11.9% of participants (840 gamers) fulfilled diagnostic criteria of addiction concerning their gaming behavior, while there is only weak evidence for the assumption that aggressive behavior is interrelated with excessive gaming in general. Results of this study contribute to the assumption that also playing games without monetary reward meets criteria of addiction. Hence, an addictive potential of gaming should be taken into consideration regarding prevention and intervention.

A Survey on Ambient Intelligence in Healthcare

Abstract: Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive, and anticipatory communications. Such innovative interaction paradigms make AmI technology a suitable candidate for developing various real life solutions, including in the healthcare domain. This survey will discuss the emergence of AmI techniques in the healthcare domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of AmI, such as smart environments and wearable medical devices. We will summarize the state-of-the-art artificial intelligence (AI) methodologies used for developing AmI system in the healthcare domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions), and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.