Preliminary studies of elemental spatial redistribution in breast tumors

Ponencia presentada en la XXIII Reunião Anual de Usuários do LNLS/CNPEM. Campinas, Brasil, 26 al 27 de febrero de 2013.Synchrotron radiation combined with capillary optics has been used as an optimal x-ray source for microanalysis. It can be used to excite x-ray fluorescence and this approach leads to very low detection limits on micrometric areas on very small samples. Synchrotron microscopic XRF (μ-SRXRF) allows quantitative study of the nature and degree of heterogeneity of inorganic constituents in biological samples. This microbeam method, due to intrinsic characteristics of SR, is able to implement multielemental spectrochemical analysis with spatial resolution on the micrometer scale. It shows high efficiency for element determination and short time of analysis requirements. In the present work, we applied μ-SRXRF to study spatial distribution of elements on normal and cancerous human breast tissue in order to identify possible correlations induced by the desease. Several authors have shown that there is a significant increase of Ca, Cr, Mn, Fe, Cu, Zn and Br in breast tumors compared to normal tissues. Since until now the research were mainly going to macroscopic level, it is interesting to study the spatial distribution of these elements to extend the knowledge to the microscopic scale. In these studies spatial redistribution of trace elements due to biochemical changes in tumors may be observed.Fil: Sosa, Carlos Manuel. Universidad Nacional de Córdoba; Argentina.Fil: Sbarato, Viviana María. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Pérez, Carlos Alberto. Laboratório Nacional de Luz Síncrotron; Brasil.Fil: Bongiovanni, Guillermina Azucena.Consejo Nacional de Investigaciones Cientificas y Técnicas; Argentina.Fil: Sánchez, Héctor Jorge. Universidad Nacional de Córdoba; Argentina.Fil: Pérez, Roberto Daniel. Universidad Nacional de Córdoba; Argentina

La comunicación familiar y la incorporación al proceso de formación académica de los estudiantes de primer año de la carrera de Licenciatura en Psicología de la Universidad de El Salvador, Facultad Multidisciplinaria de Occidente

En la realidad actual, la sociedad tiene diferentes perspectivas de enfoque para el desarrollo de los individuos, pero la exigencia más evidente es que todas las sociedades, concuerdan en que la formación profesional es una necesidad y los medios para lograrlo son la educación superior universitaria o técnica, siendo en este tema la vía universitaria, que usualmente se inicia cuando las personas comienzan la etapa de adultos/as emergente

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts