Avaliação da resistência à Xylella fastidiosa em germoplasma de tangerina e híbridos introduzidos da Itália e Córsega

A Clorose Variegada dos Citros (CVC), causada pela bactéria Xylella fastidiosa, é atualmente uma das doenças que mais afeta a citricultura brasileira, sendo as variedades de laranja-doce as mais afetadas. Ensaio instalado na Estação Experimental de Bebedouro (EECB), em condições de estufa, teve como objetivo avaliar o comportamento em relação à CVC de germoplasma de citros introduzidos pela EECB, Fundecitrus e Cenargen. Os materiais foram multiplicados sobre diversos porta-enxertos e, quando atingiram o tamanho adequado, inoculados por garfagem lateral de ramo doente. Cada variedade constou de quatro plantas, três das quais foram inoculadas, e a outra sem inocular deixada como padrão. As avaliações consistiram na observação de sintomas, teste de ELISA e PCR. Os primeiros sintomas nos materiais contaminados começaram a surgir 7 meses após a inoculação. Encontraram-se 18 variedades positivas no teste de PCR, o que indica sua suscetibilidade à bactéria Xylella fastidiosa. Entretanto, as variedades que foram detectadas pelo teste ELISA e não pelo PCR não foram contadas como suscetíveis e, sim, como falsos positivos.

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

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

In silico evaluation of the Eucalyptus transcriptome

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

Microcalcification enhancement and classification on mammograms using the wavelet transform

This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency subband it's possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm. © 2008 IEEE.

Heminested reverse-transcriptase polymerase chain reaction (hnRT-PCR) as a tool for rabies virus detection in stored and decomposed samples

Background. The use of methods, both sensitive and specific, for rabies diagnosis are important tools for the control and prophylaxis of the disease. Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR) has been used in rabies diagnosis with good results, even in decomposed materials. Additionally, molecular techniques have been used for epidemiological studies and to gain a better knowledge of viral epidemiology. Findings. The aim of this work was to evaluate the RT-PCR and hnRT-PCR for rabies virus detection in original tissues stored at -20°C for different periods considering their use for rabies virus detection in stored and decomposed samples. RT-PCR and hnRT-PCR were evaluated in 151 brain samples from different animal species, thawed and left at room temperature for 72 hours for decomposition. The RT-PCR and hnRT-PCR results were compared with previous results from Direct Fluorescent Antibody Test and Mouse Inoculation Test. From the 50 positive fresh samples, 26 (52%) were positive for RT-PCR and 45 (90%) for hnRT-PCR. From the 48 positive decomposed samples, 17 (34, 3%) were positive for RT-PCR and 36 (75%) for hnRT-PCR. No false-positives results were found in the negatives samples evaluated to the molecular techniques. Conclusion. These results show that the hnRT-PCR was more sensitive than RT-PCR, and both techniques presented lower sensibility in decomposed samples. The hnRT-PCR demonstrated efficacy in rabies virus detection in stored and decomposed materials suggesting it's application for rabies virus retrospective epidemiological studies. © 2008 Arajo et al; licensee BioMed Central Ltd.

Unsupervised segmentation method for cuboidal cell nuclei in histological prostate images based on minimum cross entropy

This paper presents a novel segmentation method for cuboidal cell nuclei in images of prostate tissue stained with hematoxylin and eosin. The proposed method allows segmenting normal, hyperplastic and cancerous prostate images in three steps: pre-processing, segmentation of cuboidal cell nuclei and post-processing. The pre-processing step consists of applying contrast stretching to the red (R) channel to highlight the contrast of cuboidal cell nuclei. The aim of the second step is to apply global thresholding based on minimum cross entropy to generate a binary image with candidate regions for cuboidal cell nuclei. In the post-processing step, false positives are removed using the connected component method. The proposed segmentation method was applied to an image bank with 105 samples and measures of sensitivity, specificity and accuracy were compared with those provided by other segmentation approaches available in the specialized literature. The results are promising and demonstrate that the proposed method allows the segmentation of cuboidal cell nuclei with a mean accuracy of 97%. © 2013 Elsevier Ltd. All rights reserved.

Simulated annealing for building roof contours identification from lidar data

This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives.

Classificação de sinais acústicos utilizando a transformada wavelet discreta e a decomposição de modo empírico: aplicações na área de alimentos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Resultado reagente próximo ao limiar de reaticidade: uma dificuldade no diagnóstico laboratorial da hepatite C

Pós-graduação em Pesquisa e Desenvolvimento (Biotecnologia Médica) - FMB

Leishmaniose visceral canina-LVC, em Campina Grande-PB/Brasil: avalição epidemiológica e diagnóstica

Pós-graduação em Doenças Tropicais - FMB

Avaliação da reação em cadeia pela polimerase (PCR) para a detecção do vírus rábico em amostras animais armazenadas por diferentes períodos e submetidas à decomposição

Pós-graduação em Medicina Veterinária - FMVZ

Infecção por Leishmania spp. e/ou por Trypanosoma cruzi em cães provenientes de área endêmica e não endêmica para leishmaniose canina

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

Ambiente data cleaning: suporte extensível, semântico e automático para análise e transformação de dados

Pós-graduação em Ciência da Computação - IBILCE

Reconhecimento de fragmentos de impressões digitais baseado em cristas e poros

Pós-graduação em Ciência da Computação - IBILCE

Algorithms for automatic segmentation of bovine embryos produced

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.