A twin study of mathematics disability

Although results obtained from recent twin and adoption studies suggest that individual differences in mathematics performance are due in part to heritable influences, no genetic analysis of mathematics disability (MD) has been previously reported. In this article we present data from the first twin sample ascertained for mathematics deficits (40 identical and 23 same-sex fraternal twin pairs in which at least one member had MD). When mathematics performance data from these twin pairs were subjected to a multiple regression analysis, evidence for a significant genetic etiology was obtained. However, tests for the differential etiology of MD as a function of reading performance level were nonsignificant. Results of this first twin study of MD indicate that the condition is significantly heritable, but data from additional twin pairs will be required to test hypotheses of differential etiology more rigorously.     

Techniques to investigate cellular and molecular interactions in the host response to implanted biomaterials

Evaluation of the host response to implanted materials requires systematic, objective investigations of responses at both the cellular and molecular levels. This article explains the basis behind two technologies: antibody and molecular techniques, which will give valuable information when applied to investigations of cells and molecules involved in the host biomaterial interaction. Such investigations are well underway, and a number of groups are now studying well characterised cell markers or molecules to evaluate the host response to biomaterials. Here we outline current technologies for the development of antibodies as tools to study cell markers or molecules, including those for which reagents are not yet available and DNA based technologies, whose continued application should prove an invaluable adjunct to existing approaches. These technologies may be particularly valuable to investigations focusing on newly characterised cytokines, receptors or cell adhesion molecules and subsequently provide a way forward for the production of advanced biomaterials.     

Drug design by machine learning: support vector machines for pharmaceutical data analysis.

We show that the support vector machine (SVM) classification algorithm, a recent development from the machine learning community, proves its potential for structure-activity relationship analysis. In a benchmark test, the SVM is compared to several machine learning techniques currently used in the field. The classification task involves predicting the inhibition of dihydrofolate reductase by pyrimidines, using data obtained from the UCI machine learning repository. Three artificial neural networks, a radial basis function network, and a C5.0 decision tree are all outperformed by the SVM. The SVM is significantly better than all of these, bar a manually capacity-controlled neural network, which takes considerably longer to train.     

Genetic algorithm based neural classifiers for factor subset extraction

A clear understanding of risk factors is important to develop appropriate prevention and control strategies for infection caused by such pathogens as Salmonella Typhimurium. In this study, there are 91 risk factors that nonlinearly contribute to the Salmonella Typhimurium infection and many of them are not of significance. It is very important to automatically extract a factor subset with those important risk factors. This paper proposes a genetic algorithm for factor subset extraction in conjunction with neural and statistical classifiers to classify case and control status in Salmonella Typhimurium infection. The results show that the proposed approach is able to find an appropriate factor subset and the proposed neural classifiers outperform the traditional statistical classifiers. A statistical analysis is conducted by varying the parameters in the genetic algorithm based neural classifier to minimise the prediction error and determine the optimal system configuration.     

Congenital hypoplasia of portions of both right and left ventricular myocardial walls. Clinical and necropsy observations in two patients with parchment heart syndrome

Clinical and morphologic findings are described in two patients with congenital hypoplasia of portions of both right and left ventricular free walls in the absence of associated coronary or valvular heart disease. One, a 61 year old man who had never had clinical evidence of cardiac dysfunction, died suddenly and unexpectedly. The second, a 55 year old woman, died of progressive, eventually intractable congestive heart failure of 29 months' duration. Although at least 22 necropsy patients have previously been reported to have "parchment-like" thinning of portions of the right ventricular free wall, only one patient has previously been described with such thinning of portions of both right and left ventricular free walls. The spectrum of right or right and left ventricular wall congenital hypoplasia is a broad one, with nearly half of described patients dying of congestive heart failure in the 1st year of life and the other half reaching adulthood with or without manifestations of cardiac dysfunction.