Gestational protein restriction induces CA3 dendritic atrophy in dorsal hippocampal neurons but does not alter learning and memory performance in adult offspring

Studies have demonstrated that nutrient deficiency during pregnancy or in early postnatal life results in structural abnormalities in the offspring hippocampus and in cognitive impairment. In an attempt to analyze whether gestational protein restriction might induce learning and memory impairments associated with structural changes in the hippocampus, we carried out a detailed morphometric analysis of the hippocampus of male adult rats together with the behavioral characterization of these animals in the Morris water maze (MWM). Our results demonstrate that gestational protein restriction leads to a decrease in total basal dendritic length and in the number of intersections of CA3 pyramidal neurons whereas the cytoarchitecture of CA1 and dentate gyrus remained unchanged. Despite presenting significant structural rearrangements, we did not observe impairments in the MWM test. Considering the clear dissociation between the behavioral profile and the hippocampus neuronal changes, the functional significance of dendritic remodeling in fetal processing remains undisclosed. © 2012 ISDN.

O portal do professor e projetos de trabalho: uma proposta de construção de um ambiente de aprendizagem Matemática no ensino fundamental

Pós-graduação em Educação - FCT

A autonomia no processo de ensino-aprendizagem para a formação de professores de língua estrangeira: espanhol

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Educação infantil: percepção de profissionais e familiares sobre inclusão, aprendizagem e desenvolvimento da criança com deficiência, em Maringá/BR e em Guadalajara/ES

Pós-graduação em Educação Escolar - FCLAR

Mensuração de estratégias de estudo e aprendizagem de alunos universitários: learning and study strategies inventory (lassi) adaptação e validação para o Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O processo de (re) construção da prática pedagógica de professores de língua inglesa em formação inicial

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fluazuron-induced morphological changes in Rhipicephalus sanguineus Latreille, 1806 (Acari: Ixodidae) nymphs: An ultra-structural evaluation of the cuticle formation and digestive processes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Enrichment of Tropical Peat with Micronutrients for Agricultural Applications: Evaluation of Adsorption and Desorption Processes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The influence of niche and neutral processes on a neotropical anuran metacommunity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Feedbacks between vegetation and disturbance processes promote long-term persistence of forest-grassland mosaics in south Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Interactive simulations to physics teaching: a case study in brazilian high school

This paper presents the results of a study that investigated the use of simulators to improve physics teaching. The study population consisted of eight classes totaling 205 second year high school students from Brazilian public school. The research methodology adopted compares the average performance of students on tests conducted in the classroom to performance on tests conducted in the laboratory using computer simulators. The results obtained showed that students’ performance on tests improved after the use of simulators. It was found that the students had more homogeneous test results when using the simulator.

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.