Linkages between ecocentric values and action in expert discourse: the case of genetically modified food in the UK

Attitudes towards the environment can be manifest in two broad categories, namely anthropocentric and ecocentric. The former regards nature as of value only insofar as it is useful to humanity, whereas the latter assigns intrinsic value to natural entities. Industrial society can be characterised as being dominated by anthropocentrism, which leads to the assumption that a majority of people hold anthropocentric values. However, research shows the most widely held values are ecocentric, which implies that many people's actions are at variance with their values. Furthermore, policy relating to environmental issues is predominantly anthropocentric, which implies it is failing to take account of the values of the majority. Research among experts involved in policy formulation has shown that their values, often ecocentric, are excluded from the policy process. The genetic modification of food can be categorised as anthropocentric, which implies that the technique is in conflict with widely held ecocentric values. This thesis examines data collected from interviews with individuals who have an influence on the debate surrounding the introduction of genetically modified foods, and can be considered 'experts'. Each interviewee is categorised according to whether their values and actions are ecocentric or anthropocentric, and the linkages between the two and the arguments used to justify their positions are explored. Particular emphasis is placed on interviewees who have ecocentric values but act professionally in an anthropocentric way. Finally, common themes are drawn out, and the features the arguments used by the interviewees have in common are outlined.

Gene delivery of the elastase inhibitor elafin protects macrophages from neutrophil elastase-mediated impairment of apoptotic cell recognition

The resolution of inflammation is dependent on recognition and phagocytic removal of apoptotic cells by macrophages. Receptors for apoptotic cells are sensitive to degradation by human neutrophil elastase (HNE). We show in the present study that HNE cleaves macrophage cell surface CD14 and in so doing, reduces phagocytic recognition of apoptotic lymphocytic cells (Mutu 1). Using an improved method of adenovirus-mediated transfection of macrophages with the HNE inbibitor elafin, we demonstrate that elafin overexpression prevents CD14 cleavage and restores apoptotic cell recognition by macrophages. This approach of genetic modification of macrophages could be used to restore apoptotic cell recognition in inflammatory conditions. (C) 2004 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Representation and parameterisation issues in genetic algorithms

A multi-chromosome GA (Multi-GA) was developed, based upon concepts from the natural world, allowing improved flexibility in a number of areas including representation, genetic operators, their parameter rates and real world multi-dimensional applications. A series of experiments were conducted, comparing the performance of the Multi-GA to a traditional GA on a number of recognised and increasingly complex test optimisation surfaces, with promising results. Further experiments demonstrated the Multi-GA's flexibility through the use of non-binary chromosome representations and its applicability to dynamic parameterisation. A number of alternative and new methods of dynamic parameterisation were investigated, in addition to a new non-binary 'Quotient crossover' mechanism. Finally, the Multi-GA was applied to two real world problems, demonstrating its ability to handle mixed type chromosomes within an individual, the limited use of a chromosome level fitness function, the introduction of new genetic operators for structural self-adaptation and its viability as a serious real world analysis tool. The first problem involved optimum placement of computers within a building, allowing the Multi-GA to use multiple chromosomes with different type representations and different operators in a single individual. The second problem, commonly associated with Geographical Information Systems (GIS), required a spatial analysis location of the optimum number and distribution of retail sites over two different population grids. In applying the Multi-GA, two new genetic operators (addition and deletion) were developed and explored, resulting in the definition of a mechanism for self-modification of genetic material within the Multi-GA structure and a study of this behaviour.