Recapitulation of embryological programmes in renal fibrosis - The importance of epithelial cell plasticity and developmental genes

Chronic fibrosis represents the final common pathway in progressive renal disease. Myofibroblasts deposit the constituents of renal scar, thus crippling renal function. It has recently emerged that an important source of these pivotal effector cells is the injured renal epithelium. This review concentrates on the process of epithelial-mesenchymal transition (EMT) and its regulation. The role of the developmental gene, gremlin, which is reactivated in adult renal disease, is the subject of particular focus. This member of the cysteine knot protein superfamily is critical to the process of nephrogenesis but quiescent in normal adult kidney. There is increasing evidence that gremlin expression reactivates in diabetic nephropathy, and in the diseased fibrotic kidney per se. Known to antagonize members of the bone morphogenic protein (BMP) family, gremlin may also act downstream of TGF-beta in induction of EMT. An increased understanding of the extracellular modulation of EMT and, in particular, of the gremlin-BMP axis may result in strategies that can halt or reverse the devastating progression of chronic renal fibrosis. Copyright (c) 2006 S. Karger AG, Basel.

Where there is smoke, there is (the potential for) fire: soft indicators of research and policy impact

There is a growing literature examining the impact of research on informing policy, and of research and policy on practice. Research and policy do not have the same types of impact on practice but can be evaluated using similar approaches. Sometimes the literature provides a platform for methodological debate but mostly it is concerned with how research can link to improvements in the process and outcomes of education, how it can promote innovative policies and practice, and how it may be successfully disseminated. Whether research-informed or research-based, policy and its implementation is often assessed on such 'hard' indicators of impact as changes in the number of students gaining five or more A to C grades in national examinations or a percentage fall in the number of exclusions in inner city schools. Such measures are necessarily crude, with large samples smoothing out errors and disguising instances of significant success or failure. Even when 'measurable' in such a fashion, however, the impact of any educational change or intervention may require a period of years to become observable. This paper considers circumstances in which short-term change may be implausible or difficult to observe. It explores how impact is currently theorized and researched and promotes the concept of 'soft' indicators of impact in circumstances in which the pursuit of conventional quantitative and qualitative evidence is rendered impractical within a reasonable cost and timeframe. Such indicators are characterized by their avowedly subjective, anecdotal and impressionistic provenance and have particular importance in the context of complex community education issues where the assessment of any impact often faces considerable problems of access. These indicators include the testimonies of those on whom the research intervention or policy focuses (for example, students, adult learners), the formative effects that are often reported (for example, by head teachers, community leaders) and media coverage. The collation and convergence of a wide variety of soft indicators (Where there is smoke …) is argued to offer a credible means of identifying subtle processes that are often neglected as evidence of potential and actual impact (… there is fire).

Disaggregating conservative Protestant groups in Northern Ireland: Overlapping categories and the importance of a born-again self-identification

Rather than treating conservative Protestantism as a homogenous phenomenon, recent literature has underlined the importance of disaggregating this group to illuminate important attitudinal and behavioral differences between conservative Protestants. However, the methods used to empirically operationalize conservative Protestantism have not always been able to capture variations within the groupings. Based on analysis of the 2004 Northern Ireland Life and Times Survey, we argue that religious self-identification is a more useful way of analyzing conservative Protestant subgroups than denomination or religious belief. We show that many of these identifications are overlapping, rather than stand-alone, religious group identifications. Moreover, the identification category of born-again has seldom been included in surveys. We find having a born-again identification to be a better predictor than the more frequently asked fundamentalist and evangelical categories of the religious and social beliefs that are seen as indicative of conservative Protestantism.

Escaping the Cage of Ethno-National Conflict in Northern Ireland: The Importance of Transnational Networks

co-author; Cathal McCall

Research with children: methodological issues and innovative techniques

In the past few decades, a growing body of literature examining children’s perspectives on their own lives has developed within a variety of disciplines, such as sociology, psychology, anthropology and geography. This article provides a brief up-to-date examination of methodological and ethical issues that researchers may need to consider when designing research studies involving children; and a review of some of the methods and techniques used to elicit their views. The article aims to encourage researchers to critically reflect on these methodological issues and the techniques they choose to use, since they will have implications for the data produced.

Methodological considerations in reserve system selection: a case study of Malagasy Lemurs.

Although data quality and weighting decisions impact the outputs of reserve selection algorithms, these factors have not been closely studied. We examine these methodological issues in the use of reserve selection algorithms by comparing: (1) quality of input data and (2) use of different weighting methods for prioritizing among species. In 2003, the government of Madagascar, a global biodiversity hotspot, committed to tripling the size of its protected area network to protect 10% of the country’s total land area. We apply the Zonation reserve selection algorithm to distribution data for 52 lemur species to identify priority areas for the expansion of Madagascar’s reserve network. We assess the similarity of the areas selected, as well as the proportions of lemur ranges protected in the resulting areas when different forms of input data were used: extent of occurrence versus refined extent of occurrence. Low overlap between the areas selected suggests that refined extent of occurrence data are highly desirable, and to best protect lemur species, we recommend refining extent of occurrence ranges using habitat and altitude limitations. Reserve areas were also selected for protection based on three different species weighting schemes, resulting in marked variation in proportional representation of species among the IUCN Red List of Threatened Species extinction risk categories. This result demonstrates that assignment of species weights influences whether a reserve network prioritizes maximizing overall species protection or maximizing protection of the most threatened species.

Inferring the conservative causal core of gene regulatory networks

Background
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.

Results
In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.

Conclusions
For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.