Introduction to the DISRUPT postprandial database: subjects, studies and methodologies

Dysregulation of lipid and glucose metabolism in the postprandial state are recognised as important risk factors for the development of cardiovascular disease and type 2 diabetes. Our objective was to create a comprehensive, standardised database of postprandial studies to provide insights into the physiological factors that influence postprandial lipid and glucose responses. Data were collated from subjects (n = 467) taking part in single and sequential meal postprandial studies conducted by researchers at the University of Reading, to form the DISRUPT (DIetary Studies: Reading Unilever Postprandial Trials) database. Subject attributes including age, gender, genotype, menopausal status, body mass index, blood pressure and a fasting biochemical profile, together with postprandial measurements of triacylglycerol (TAG), non-esterified fatty acids, glucose, insulin and TAG-rich lipoprotein composition are recorded. A particular strength of the studies is the frequency of blood sampling, with on average 10-13 blood samples taken during each postprandial assessment, and the fact that identical test meal protocols were used in a number of studies, allowing pooling of data to increase statistical power. The DISRUPT database is the most comprehensive postprandial metabolism database that exists worldwide and preliminary analysis of the pooled sequential meal postprandial dataset has revealed both confirmatory and novel observations with respect to the impact of gender and age on the postprandial TAG response. Further analysis of the dataset using conventional statistical techniques along with integrated mathematical models and clustering analysis will provide a unique opportunity to greatly expand current knowledge of the aetiology of inter-individual variability in postprandial lipid and glucose responses.

Development of new methodologies for entry to targets of therapeutic interest

This Account provides an overview of strategies that have been reported from our laboratories for the synthesis of targets of therapeutic interest, namely carbohydrates, and prodrugs for the treatment of melanoma. These programmes have involved the development of new synthetic methodologies including the regio- and stereoselective synthesis of specific carbohydrate isomers, and new protecting group methodologies. This review provides an insight into the progress of these research themes, and suggests some applications for the targets that are currently being explored.

Swarm pattern transformation methodologies

The work reported in this paper is motivated by the need for developing swarm pattern transformation methodologies. Two methods, namely a macroscopic method and a mathematical method are investigated for pattern transformation. The first method is based on macroscopic parameters while the second method is based on both microscopic and macroscopic parameters. A formal definition to pattern transformation considering four special cases of transformation is presented. Simulations on a physics simulation engine are used to confirm the feasibility of the proposed transformation methods. A brief comparison between the two methods is also presented.

Typical control curricula and using software for teaching/assessment: a UK perspective

This paper describes some of the preliminary outcomes of a UK project looking at control education. The focus is on two aspects: (i) the most important control concepts and theories for students doing just one or two courses and (ii) the effective use of software to improve student learning and engagement. There is also some discussion of the correct balance between teaching theory and practise. The paper gives examples from numerous UK universities and some industrial comment.

Global oil production: forecasts and methodologies

A range of forecasts of global oil production made between 1956 and the present day are listed. For the majority of these the methodology used to generate the forecast is described. The paper distinguishes between three types of forecast: group 1-quantitative analyses which predict that global oil production will reach a resource-limited peak in the near term, and certainly before the year 2020; group 2-forecasts that use quantitative methods, but which see no production peak within the forecast's time horizon (typically 2020 or 2030); group 3-nonquantitative analyses that rule out a resource-limited oil peak within the foreseeable future. The paper analyses these forecast types and suggests that group 1 forecasts are the most realistic.