19 resultados para Software-based techniques
Resumo:
A population-based cross-sectional study was set up in Sabará country, Southeastern Brazil, to identify asymptomatic human visceral leishmaniasis in an urban area of low disease prevalence. Blood was collected on filter paper (n=1,604 inhabitants) and examined by indirect immunofluorescent test, enzyme-linked immunosorbent assay and immunochromatographic strip test. The prevalence rates of infection ranged from 2.4 to 5.6% depending on the test used. One year later, venous blood was collected in a subset of 226 participants (102 seropositive and 124 seronegative). The tests performed were IFAT, ELISA, rk39-ELISA, polymerase chain reaction and hybridization with Leishmania donovani complex probe. No clinical signs or symptoms of leishmaniasis were observed. Using hybridization as a reference test, the sensitivity and specificity of serology were respectively: 24.8 and 71% (ELISA); 26.3 and 76.3% (rk-39); 30.1 and 63.4% (IFAT). Due to disagreements, different criteria were tested to define the infection and hybridization should be considered in epidemiological studies.
Resumo:
ABSTRACTINTRODUCTION: In the Americas, mucosal leishmaniasis is primarily associated with infection by Leishmania (Viannia) braziliensis. However, Leishmania (Viannia) guyanensis is another important cause of this disease in the Brazilian Amazon. In this study, we aimed at detecting Leishmaniadeoxyribonucleic acid (DNA) within paraffin-embedded fragments of mucosal tissues, and characterizing the infecting parasite species.METHODS: We evaluated samples collected from 114 patients treated at a reference center in the Brazilian Amazon by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analyses.RESULTS: Direct examination of biopsy imprints detected parasites in 10 of the 114 samples, while evaluation of hematoxylin and eosin-stained slides detected amastigotes in an additional 17 samples. Meanwhile, 31/114 samples (27.2%) were positive for Leishmania spp. kinetoplast deoxyribonucleic acid (kDNA) by PCR analysis. Of these, 17 (54.8%) yielded amplification of the mini-exon PCR target, thereby allowing for PCR-RFLP-based identification. Six of the samples were identified as L. (V.) braziliensis, while the remaining 11 were identified as L. (V.) guyanensis.CONCLUSIONS: The results of this study demonstrate the feasibility of applying molecular techniques for the diagnosis of human parasites within paraffin-embedded tissues. Moreover, our findings confirm that L. (V.) guyanensisis a relevant causative agent of mucosal leishmaniasis in the Brazilian Amazon.
Resumo:
Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.
Resumo:
The morphology of the ovaries in Uca rapax (Smith, 1870) was described based on macroscopic and microscopic analysis. Females were collected in Itamambuca mangrove, Ubatuba, state of São Paulo, Brazil. In the laboratory, 18 females had their ovaries removed and prepared for histology. Each gonad developmental stage was previously determined based on external and macroscopic morphology and afterwards each stage was microscopically described. The ovaries of U. rapax showed a pronounced macroscopic differentiation in size and coloration with the maturation of the gonad, with six ovarian developmental stages: immature, rudimentary, developing, developed, advanced and spent. During the vitellogenesis, the amount of oocytes in secondary stage increases in the ovary, resulting in a change in coloration of the gonad. Oogonias, primary oocytes, secondary oocytes and follicular cells were histologically described and measured. In females ovaries of U. rapax the modifications observed in the oocytes during the process of gonad maturation are similar to descriptions of gonads of other females of brachyuran crustaceans. The similarities are specially found in the morphological changes in the reproductive cells, and also in the presence and arrange of follicle cells during the process of ovary maturation. When external morphological characteristics of the gonads were compared to histological descriptions, it was possible to observe modifications that characterize the process in different developmental stages throughout the ovarian cycle and, consequently, the macroscopic classification of gonad stages agree with the modifications of the reproductive cells.