The development, evaluation and use of freshly isolated renal proxinal tubule systems in the fischer rat

The investigation of renal pathophysiology and toxicology has traditionally been advanced by the development of increasingly defined and refined in vitro preparations. This study has sought to develop and evaluate various methods of producing pure samples of renal proximal tubules (PTs) from the Fischer rat. The introduction summarised the most common in vitro preparations together with the parameters used to monitor viability - particularly with regard to toxic events. The most prevalent isolation methods have involved the use of collagenase to produce dissociation of the cortex. However, the present study has shown that even the mildest collagenase treatment caused significant structural damage which resulted in a longevity of only 3hr in suspension. An alternative mechanical isolation technique has been developed in this study that consists of perfusion loading the renal glomeruli with Fe304 followed by disruption of the cortex by homogenisation and sequential sieving. The glomeruli are removed magnetically and the PTs then harvested by a 64μM sieve. PTs isolated in this way showed a vastly superior structural preservation over their collagenase isolated counterparts; also oxygen consumption and enzyme leakage measurements showed a longevity in excess of 6hr when incubated in a very basic medium. Attempts were then made to measure the cytosolic calcium levels in both mechanical and collagenase isolated PTs using the fluorescent calcium indicator Fura. However results were inconclusive due to significant binding of the Fura to the external PT surfaces. In conclusion, PTs prepared by the present mechanical isolation technique exhibit superior preservation and longevity compared with even the mildest collagenase isolation technique and hence appear to offer potential advantages over collagenase isolation as an in vitro renal system.

Competing for knowledge:creating, connecting and growing

With the buzzwords of knowledge-based economy and knowledge-driven economy, policy-makers, as well as journalists and management consultants, are pushing forward a vision of change that transforms the way advanced economies work. Yet little is understood about how the knowledge-based economy differs from the old, traditional economy. It is generally agreed that the phenomenon has grown out of the branch of economic thought known as new growth theory. Digesting up-to-date thinking in economics, management, innovation studies and economic geography, this significant volume provides an account of these developments and how they have transformed advanced economies.

Connecting a sociology of childhood perspective with the study of child health, illness and wellbeing:introduction

In the last decades we have seen a growing interest in research into children's own experiences and understandings of health and illness. This development, we would argue, is much stimulated by the sociology of childhood which has drawn our attention to how children as a social group are placed and perceived within the structure of society, and within inter-generational relations, as well as how children are social agents and co-constructors of their social world. Drawing on this tradition, we here address some cross-cutting themes that we think are important to further the study of child health: situating children within health policy, drawing attention to practices around children's health and well-being and a focus on children as health actors. The paper contributes to a critical analysis of child health policy and notions of child health and normality, pointing to theoretical and empirical research potential for the sociology of children's health and illness.

Connecting a sociology of childhood perspective with the study of child health, illness and wellbeing:introduction

This chapter focuses on concepts and theoretical points of departure found in child health and wellbeing studies. Firstly, seeing children as a social group draws attention to the ways this group is placed and perceived in the structures of societies. Children as a social group need to be understood in relation to other social groups. Secondly, understanding children as social agents and as co-constructors of their social worlds is fundamental to studying their experiences and ways of dealing with health and wellbeing in everyday life. Thirdly, in recent years, there has been a turn towards seeing children as beings. The chapter discusses the child health issues and concerns in contemporary society. Children are diagnosed with an increasing range of conditions and are subject to more and more elaborate child health and welfare interventions, reflecting a medical perspective on the changing panorama of illness and health risks in the 21st century.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.