Labeling of Baropodometric Analysis Data Using Computer Vision Techniques in Classification of Foot Deformities.

Background and Objectives: Foot deformities are the basis of numerous disorders of the locomotor system. An optimized method of classification of foot deformities would enable an objective identification of the type of deformity since the current assessment methods do not show an optimal level of objectivity and reliability. The acquired results would enable an individual approach to the treatment of patients with foot deformities. Thus, the goal of this research study was the development of a new, objective model for recognizing and classifying foot deformities with the application of machine learning, by labeling baropodometric analysis data using computer vision methods. Materials and Methods: In this work, data from 91 students of the Faculty of Medicine and the Faculty of Sports and Physical Education, University of Novi Sad were used. Measurements were determined by using a baropodometric platform, and the labelling process was carried out in the Python programming language, using functions from the OpenCV library. Segmentation techniques, geometric transformations, contour detection and morphological image processing were performed on the images, in order to calculate the arch index, a parameter that gives information about the type of the foot deformity. Discussion: The foot over which the entire labeling method was applied had an arch index value of 0.27, which indicates the accuracy of the method and is in accordance with the literature. On the other hand, the method presented in our study needs further improvement and optimization, since the results of the segmentation techniques can vary when the images are not consistent. Conclusions: The labeling method presented in this work provides the basis for further optimization and development of a foot deformity classification system.

Interconnection between Mixed-Handedness, Digit Ratios and Hand and Foot Minor Anomalies in Predicting Schizophrenia.

BACKGROUND: According to the neurodevelopmental theory, brain structuring early markers could be seen in different body parts as minor physical anomalies. Alongside minor physical anomalies, handedness and index to ring finger ratio are brain development indicators, specifically brain lateralization. Studies are consentient about the association of these findings with schizophrenia, though there is inconsistency about individual anatomical regions' contribution. We proposed that handedness in combination with morphological indicators of early brain development could be sensitive and specific in predicting schizophrenia status. SUBJECTS AND METHODS: Within the list for the assessment of schizophrenia patients and normal controls of the Caucasian race were seven categorical minor physical anomalies of hand and feet, handedness, and index to ring finger ratio. In this cross-sectional study the examinees were recruited from January 2012 to December 2015. RESULTS: Forced-entry binary logistic regression model correctly classified 86.5% of patients and 99.2% of the comparison subjects with a 92.8% overall accuracy. Mixed-handedness, hyperconvex fingernails, big gap between 1st and 2nd toe, and partial syndactyly of 2nd and 3rd toe made a significant independent contribution to the patient-control prediction group status. Furthermore, these items showed a significant correlation with the predictors of the head from the previous study. CONCLUSION: Briefly, the limb components, assessed independently of other body regions, proved to be worthy as schizophrenia predictors.

Tadalafil in Increasing Doses: The Influence on Coronary Blood Flow and Oxidative Stress in Isolated Rat Hearts.

INTRODUCTION: This study aimed to assess the influence of different doses of tadalafil on coronary flow and oxidative stress in isolated rat hearts. METHODS: The hearts of male Wistar albino rats (n = 48) were retrogradely perfused according to the Langendorff technique at gradually increased constant perfusion pressure (CPP) (40-120 mm Hg). Coronary flow and oxidative stress markers: nitrite oxide (NO) outflow and superoxide anion production in coronary effluent were measured. The experiments were performed during control conditions and in the presence of tadalafil (10, 20, 50, and 200 nM) alone or with Nω-nitro-L-arginine monomethyl ester (L-NAME) (30 µM). RESULTS: Tadalafil administration significantly increased coronary flow at all CPP values at all administered doses. Tadalafil led to an increase in the NO levels, but a statistically significant NO release increase was found only at the highest dose and highest CPP. Tadalafil did not significantly affect the release of O2-. After inhibiting the nitrite oxide synthase system by L-NAME, tadalafil-induced changes in cardiac flow and NO levels were reversed. L-NAME administration had no pronounced effect on the O2- release. CONCLUSION: Tadalafil causes changes in the heart vasculature in a dose-dependent manner. It does not lead to a significant increase in the production of superoxide anion radicals.