Assessment of the role of genetic polymorphism in venous thrombosis through artificial neural networks.

PURPOSE: To assess the role of genetic polymorphisms in venous thrombosis events (VTE) using Artificial Neural Networks (ANNs), a model for solving non-linear problems frequently associated with complex biological systems, due to interactions between biological, genetic and environmental factors. METHODS: A database was generated from a case-control study of venous thrombosis, using 238 patients and 211 controls. The database of 64 variables included age, gender and a panel of 62 genetic variants. Three different ANNs were compared, with logistic regression for the accuracy of predicting cases and controls. RESULTS: ANNs yielded a better performance than the logistic regression algorithm. Indeed, through ANNs models, the 62 variables related to genetic variants were first reduced to a set of 9, and then of 3 (MTHFR 677 C/T, FV arg506gln, ICAM1 gly214arg). CONCLUSIONS: The findings of this study illustrate the power of ANN in evaluating multifactorial data, and show that the different sensitivities of the models of elaboration are related to the characteristics of the data. This may contribute to a better understanding of the role played by genetic polymorphisms in VTE, and help to define, if possible, a test panel of genetic variants to estimate an individual's probability of developing the disease.

Artificial neural networks for the identification of the differences between "light" and "heavy" alcoholics, starting from five nonlinear biological variables.

This article makes a comparison among three types of evaluation systems based on a set of data composed of "heavy" alcoholics and "light" alcoholics. The three systems are: 1) a system based on genetic algorithms called BEAGLE; b) seven different types of Artificial Neural Networks; c) a metasystem called MetaNet. The technical aim was to compare the classification capability of these three systems in terms of two classes ("heavy" alcoholics and "light" alcoholics). From the results obtained, the MetaNet system stand out. Globally, it has the best result, followed by the two Artificial Neural Networks, Squash and Logicon Projection. The results obtained prove that the advanced elaboration data systems applied in the social and health fields can be employed in prevention programs having an aim to reduce the social impact of certain pathologies correlated with different kinds of dependence.

[Peripheral rheumatoid neuropathy. Description of a clinical case]. / La neuropatia reumatoide periferica. Descrizione di un caso clinico.

After describing peripheral rheumatoid neuropathy and pointing out its increased frequency after the advent of steroid therapy, the Authors describe a case brought to their attention at the Rheumatology Division of the Ospedale San Camillo De Lellis.

[Vertebral hyperostosis and hyperostosis frontalis interna]. / L'hyperostose vertébrale et l'hyperostose frontale interne.

Routine roentgenographic examination of the spine was performed in 690 patients with rheumatologic disorders. Ankylosing hyperostosis was discovered in 124 patients (18 percent). Roentgenograms of the skull revealed hyperostosis frontalis interna in 63 percent of cases, especially in female patients. No common pathogenic mechanism, however, has been discovered in these two disorders.