Activation of the shoulder and arm muscles during axial load exercises on a stable base of support and on a medicine ball

The purpose of this study was to compare SEMG activities during axial load exercises on a stable base of support and on a medicine ball (relatively unstable). Twelve healthy male volunteers were tested (x = 23 +/- 7y). Surface EMG was recorded from the biceps brachii, anterior deltoid, clavicular portion of pectoralis major, upper trapezius and serratus anterior using surface differential electrodes. All SEMG data are reported as percentage of RMS mean values obtained in maximal voluntary contractions for each muscle studied. A 3-way within factor repeated measures analysis of variance was performed to compare RMS normalized values. The RMS normalized values of the deltoid were always greater during the exercises performed on a medicine ball in relation to those performed on a stable base of support. The trapezius showed greater mean electric activation amplitude values on the wall-press exercise on a medicine ball, and the pectoralis major on the push-up. The serratus and biceps did not show significant differences of electric activation amplitude in relation to both tested bases of support. Independent of the base of support, none of the studied muscles showed significant differences of electric activation amplitude during the bench-press exercise. The results contribute to the identification of the levels of muscular activation amplitude during exercises that are common in clinical practice of rehabilitation of the shoulder and the differences in terms of type of base of support used. (C) 2006 Elsevier Ltd. All rights reserved.

Cultural Consonance, a 5HT2A Receptor Polymorphism, and Depressive Symptoms: A Longitudinal Study of Gene x Culture Interaction in Urban Brazil

In this study in urban Brazil we examine, as a predictor of depressive symptoms, the interaction between a single nucleotide polymorphism in the 2A receptor in the serotonin system (-1438G/A) and cultural consonance in family life, a measure of the degree to which an individual perceives her family as corresponding to a widely shared cultural model of the prototypical family. A community sample of 144 adults was followed over a 2-year-period. Cultural consonance in family life was assessed by linking individuals` perceptions of their own families with a shared cultural model of the family derived from cultural consensus analysis. The -1438G/A polymorphism in the 2A serotonin receptor was genotyped using a standard protocol for DNA extracted from leukocytes. Covariates included age, sex, socioeconomic status, and stressful life events. Cultural consonance in family life was prospectively associated with depressive symptoms. In addition, the interaction between genotype and cultural consonance in family life was significant. For individuals with the A/A variant of the -1438G/A polymorphism of the 2A receptor gene, the effect of cultural consonance in family life on depressive symptoms over a 2-year-period was larger (beta = -0.533, P < 0.01) than those effects for individuals with either the G/A (beta = -0.280, P < 0.10) or G/G (beta = -0.272, P < 0.05) variants. These results are consistent with a process in which genotype moderates the effects of culturally meaningful social experience on depressive symptoms. Am. J. Hum. Biol. 21:91-97, 2009. (C) 2008 Wiley-Liss, Inc.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.