A interface do ROODA : uma barreira para o aprendizado

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CLASSIFICAÇÃO E TRATAMENTO DE LESÕES DE FURCA

A presença de lesões de furca está relacionada à reabsorção óssea e à perda de inserção no espaço interradicular. Desse modo, dentes multirradiculares com invasão de furca ainda constituem um desafo que pode comprometer o sucesso da  terapia periodontal. O objetivo deste  trabalho é abordar por meio de uma  revisão de  literatura os  fatores etiológicos e predisponentes das lesões de furca, focando na classifcação e nas formas de tratamento. Trata-se de uma pesquisa bibliográfica, com o objetivo de reunir informações científicas publicadas, relacionadas à temática proposta, no qual realizou-se uma busca no banco de dados do Scielo, Bireme, a partir das fontes Medline e Lilacs, bem como livros especializados. Pode-se classifcar as lesões de furca em Classe I, II e III, segundo o envolvimento de furca no sentido horizontal. O diagnóstico é realizado clinicamente através de sondagem da área afetada sendo complementado por exames de imagem. Os tratamentos existentes para  lesões  na região  de  furca  são  divididos  em  conservadores,  ressectivos  e  regeneradores. Tais  tratamentos  têm  como objetivos a manutenção de dentes com lesão de furca, restabelecendo uma anatomia que possibilite a remoção do bioflme dental pelo paciente na área afetada, assim como o controle pelo profssional. Desse modo, torna-se necessário o conhecimento da anatomia radicular, assim como dos fatores etiológicos para eleição de um tratamento adequado e consequentemente o dente tratado tenha um prognóstico favorável.Descritores: Defeitos da Furca. Periodontia. Diagnóstico.AbstractClassifcation and  treatment of  furcation  involviment. The presence of  furcation defects  is  related  to bone resorption and insertion loss in interradicular space. Thus, multirooted teeth with furcation lesions remain a challenge that can compromise the success of periodontal therapy.  The aim of this work was to address by a literature review and etiological and predisposing factors of furcation defects, focusing on classifcation and forms of treatment. This is a bibliographic research, with the aim of gathering published, related to the proposed theme, which was held in a search database SciELO, Bireme from Medline and Lilacs scientifc information sources, as well as specialized books. It was possible to classify furcation defects in Class I, II and III, according to furcation involvement in the horizontal direction. The diagnosis is made clinically by probing the affected area is complemented by imaging. The treatments for lesions in the furcation area are divided into conservatives, resections and regenerators. Such treatments aim keeping teeth with furcation lesion, restoring an anatomy that allows the removal of bioflm by the patient in the affected area, as well as control by the professional. Thus, it becomes necessary to know the root anatomy as well as the etiological factors for the election of an appropriate treatment and consequently the treated tooth has a favorable prognosis.Descriptors: Furcation defects. Periodontology. Diagnosis

Suspected vertical transmission of Chagas disease caused by DTU TcIV in an infection probably transmitted orally, during anoutbreak in the Brazilian Amazo

This study describes difficulties in the monitoring of a child born during an oral outbreak of Chagas disease, in which there are several indications that the transmission occurred through the congenital route: 1. the mother was in the third trimester of pregnancy when she was infected; 2. She presented high parasitemia at the time of delivery; 3. In both, the mother and her daughter, T. cruzi was classified as DTU TcIV. The parasites were not found in the blood at birth and the infection was detected only three months later in an asymptomatic infant. As the mother and her child live in a highly endemic area, vector transmission could not be excluded during this period

Heterogeneidade do desempenho de alunos da Unicamp, do ingresso à conclusão.

O objetivo deste trabalho é propor uma metodologia para avaliar o desempenho dos alunos da Universidade Estadual de Campinas, do ingresso à conclusão do curso. A amostra é composta por todos os ingressantes dessa universidade nos anos de 1997 a 2000, e a população que corresponde ao universo dos alunos ingressantes em todo o período de existência da universidade. O conjunto de dados disponível foi obtido a partir dos questionários socioculturais, aplicados pela Comissão Permanente de Vestibulares na inscrição do vestibular, e de informações acadêmicas fornecidas pela Diretoria Acadêmica da Universidade. É proposta uma metodologia com base na variável denominada "ganho relativo" sugerida por Dachs e Maia (2006). Essa nova metodologia fundamenta-se em medidas de diversidades propostas por Rao (1982) e na utilização de U-estatísticas. Propõem-se testes de homogeneidade para avaliar se existe diferença no desempenho entre alunos segundo alguns agrupamentos

Wavelet statistical analysis in multitemporal SAR images

International audienc

Self-modeling ordinal regression with time invariant covariates – an application to prostate cancer data

CAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORIn a prostate cancer study, the severity of genito-urinary (bladder) toxicity is assessed for patients who were given different doses of radiation. The ordinal responses (severity of side effects) are recorded longitudinally along with the cancer stage of a patient. Differences among the patients due to time-invariant covariates are captured by the parameters. To build up a suitable framework for an analysis of such data, we propose the use of self-modeling ordinal longitudinal model where the conditional cumulative probabilities for a category of an outcome have a relation with shape-invariant model. Since patients suffering from a common disease usually exhibit a similar pattern, it is natural to build up a nonlinear model that is shape invariant. The model is essentially semi-parametric where the population time curve is modeled with penalized regression spline. Monte Carlo expectation maximization technique is used to estimate the parameters of the model. A simulation study is also carried out to justify the methodology used.26521332154CAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORsem informaçã

Wavelet-based estimators for mixture regression

We consider a process that is observed as a mixture of two random distributions, where the mixing probability is an unknown function of time. The setup is built upon a wavelet-based mixture regression. Two linear wavelet estimators are proposed. Furthermore, we consider three regularizing procedures for each of the two wavelet methods. We also discuss regularity conditions under which the consistency of the wavelet methods is attained and derive rates of convergence for the proposed estimators. A Monte Carlo simulation study is conducted to illustrate the performance of the estimators. Various scenarios for the mixing probability function are used in the simulations, in addition to a range of sample sizes and resolution levels. We apply the proposed methods to a data set consisting of array Comparative Genomic Hybridization from glioblastoma cancer studies461215234CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP308439/2014-72013/21273-5; 2013/09035-1; 2013/00506-1The authors thank an associate editor and two referees for the insightful suggestions and comments that led to a considerable improvement of this paper. The first author acknowledges FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) for the visit to the Georgia Institute of Technology (2013/21273‐5) and for his postdoc at the University of Campinas (2013/09035‐1). The second author acknowledges FAPESP (2013/00506‐1) and CNPq (308439/2014‐7). The third author acknowledges support from the National Center for Advancing Translational Sciences of the National Institutes of Health under Award UL1TR000454 and the Giglio Family Award from the Georgia Institute of Technolog