Immune correlate study on human Schistosoma japonicum in a well-defined population in Leyte, Philippines: I. Assessment of 'resistance' versus 'susceptibility' to S-japonicum infection

This study describes the categorical classification of 155 individuals living in an endemic village in Macanip, Leyte, Philippines as 'resistant' or 'susceptible' to Schistosoma japonicum infection using available exposure, infection and reinfection data collected from a 3-year water contact (WC) study. Epidemiological parameters including age, sex, and infection intensities in relation to observed reinfection patterns are also described. This classification was used in subsequent immunological studies described in two accompanying papers to identify protective immune mechanisms among resistant individuals induced by defined candidate vaccine molecules for S. japonicum. The study suggests that individuals who were most vulnerable to rapid reinfection were children belonging to the 5-14 age group. A drop in incidence at age group 15-19 and decreased intensity of infection starting at this age group and older (15+) suggests development of immunity. Controlling for the effect of the other variables, a multivariate analysis showed significant association for sex, in that females were more likely to be resistant. This implies that other than acquired immunity to infection, some age-dependent host factors may also play an important role in the overall changes of reinfection patterns seen in schistosomiasis japonica in this population. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Variables affecting the fine grinding of minerals using stirred mills

Base metal resources are becoming more fine-grained and refractory and minerals separation processes require these ores to be milled to increasingly finer sizes. To cope with very fine grinding to below a P-80 of approximately 15 mum stirred milling technology has been adopted from other industries Neither this technology, nor the basic concepts of fine grinding, are well understood by the minerals processing industry. Laboratory studies were therefore carried out in order to investigate fine milling using different types of stirred mills. The variables analysed were stirrer speed, grinding media type and size, slurry solids content as well as the feed and product size. The results of the testwork have shown that all of these variables affect the grinding efficiency. The ratio of media size to material size was found to be of particular significance. The results were also analysed using the stress intensity approach and the optimum stress intensity ranges for the most efficient grinding were determined. Application of the results for process optimisation in the industrial size units is also discussed in this paper. (C) 2003 Elsevier Science Ltd. All rights reserved.

Outcome variables for osteoarthritis clinical trials: the OMERACT-OARSI set of responder criteria

Improvement in analysis and reporting results of osteoarthritis (OA) clinical trials has been recently obtained because of harmonization and standardization of the selection of outcome variables (OMERACT 3 and OARSI). Moreover, OARSI has recently proposed the OARSI responder criteria. This composite index permits presentation of results of symptom modifying clinical trials in OA based on individual patient responses (responder yes/no). The 2 organizations (OMERACT and OARSI) established. a task force aimed at evaluating: (1) the variability of observed placebo and active treatment effects using the OARSI responder criteria; and (2) the possibility of proposing a simplified set of criteria. The conclusions of the task force were presented and discussed during the OMERACT 6 conference, where a simplified set of responder criteria (OMERACT-OARSI set of criteria) was proposed.

The variety of variables in automated real-time refinement

The refinement calculus is a well-established theory for deriving program code from specifications. Recent research has extended the theory to handle timing requirements, as well as functional ones, and we have developed an interactive programming tool based on these extensions. Through a number of case studies completed using the tool, this paper explains how the tool helps the programmer by supporting the many forms of variables needed in the theory. These include simple state variables as in the untimed calculus, trace variables that model the evolution of properties over time, auxiliary variables that exist only to support formal reasoning, subroutine parameters, and variables shared between parallel processes.