Comparing different methods to measure biofilm thickness: the techniques are: optical coherence tomography, confocal laser scanning microscopy and low load compression test

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Ichthyometry and electrical bioimpedance analysis to estimate the body composition of tambatinga

Body composition analysis is relevant to characterize the nutritional requirements and finishing phase of fish. The aim of this study was to investigate the relationship between ichthyometric (weight, total and standard length, density and yields), bromatological (fat, protein, ash and water content) and bioelectrical-impedance-analysis (BIA) (resistance, reactance, phase angle and composition indexes) variables in the hybrid tambatinga (Colossoma macropomum × Piaractus brachypomus). In a non-fertilized vivarium, 520 juveniles were housed and fed commercial rations. Then, 136 days after hatching (DAH), 15 fish with an average weight of 37.69 g and average total length of 12.96 cm were randomly chosen, anesthetized (eugenol) and subjected to the first of fourteen fortnightly assessments (BIA and biometry). After euthanasia, the following parts were weighed: whole carcass with the head, fillet, and skin (WC); fillet with skin (FS); and the remainder of the carcass with the head (CH). Together, FS and CH were ground and homogenized for the bromatological analyses. Estimates of the body composition and yields of tambatinga, with models including ichthyometric and BIA variables, showed correlation coefficients ranging from 0.81 (for the FS yield) to 1,00 (for the total ash). Similarly, models that included only BIA variables had correlation coefficients ranging from 0.81 (FS and CH yields) to 0.98 (for the total ash). Therefore, in tambatinga, the BIA technique allows the estimation of the yield of the fillet with skin and the body composition (water content, fat, ash, and protein). The best models combine ichthyometric and BIA variables.

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

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.

Production of secondary metabolites in cell suspension cultures of Ocimum sanctum L.

Dissertação de mestrado em Plant Molecular Biology, Biotechnology and Bioentrepreneurship

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Poly lactic acid based biodegradable stents and functionalization techniques: brief review

Commercial stents, especially metallic ones, present several disadvantages, and this gives rise to the necessity of producing or coating stents with different materials, like natural polymers, in order to improve their biocompatibility and minimize the disadvantages of metallic ones. This review paper discusses some applications of natural-based polymers in stents, namely polylactic acid (PLA) for stent development and chitosan for biocompatible coatings of stents . Furthermore, some effective stent functionalization techniques will be discussed, namely Layer by Layer (LBL) technique.

Eating behavior and body image among psychology students

OBJECTIVE: To characterize eating habits and possible risk factors associated with eating disorders among psychology students, a segment at risk for eating disorders. METHOD: This is a cross-sectional study. The questionnaires Bulimic Investigatory Test Edinburgh (BITE), Eating Attitudes Test (EAT-26), Body Shape Questionnaire (BSQ) and a variety that considers related issues were applied. Statistical Package for the Social Sciences (SPSS) 11.0 was utilized in analysis. The study population was composed of 175 female students, with a mean age of 21.2 (DP ± 3.6 years). RESULTS: A positive result was detected on the EAT-26 for 6.9% of the cases (CI95%: 3.6-11.7%). The prevalence of increased symptoms and intense gravity, according to the BITE questionnaire was 5% (CI95%: 2.4-9.5%) and 2.5% (CI95%: 0.7-6.3%), respectively. According to the findings, 26.29% of the students presented abnormal eating behavior. The population with moderate/severe BSQ scores presented dissatisfaction with corporal weight. CONCLUSION: The results indicate that attention must be given to eating behavior risks within this group. A differentiated gaze is justified with respect to these future professionals, whose practice is jeopardized in cases in which they are themselves the bearers of installed symptoms or precursory behavior.

Segmentação de imagens fetais com potencial para desenvolvimento de ferramentas de apoio ao diagnóstico

Programa Doutoral em Engenharia Eletrónica e de Computadores

Body image dissatisfaction and its relationship with physical activity and body mass index in Brazilian adolescents

Objective: To evaluate body image dissatisfaction and its relationship with physical activity and body mass index in a Brazilian sample of adolescents. Methods: A total of 275 adolescents (139 boys and 136 girls) between the ages of 14 and 18 years completed measures of body image dissatisfaction through the Contour Drawing Scale and current physical activity by the International Physical Activity Questionnaire. Weight and height were also measured for subsequent calculation of body mass index. Results: Boys and girls differed significantly regarding body image dissatisfaction, with girls reporting higher levels of dissatisfaction. Underweight and eutrophic boys preferred to be heavier, while those overweight preferred be thinner and, in contrast, girls desired to be thinner even when they are of normal weight. Conclusion: Body image dissatisfaction was strictly related to body mass index, but not to physical activity.

The diagnostic and prognostic role of liquid-based cytology: are we ready to monitor therapy and resistance?

Here, we evaluate the diagnostic and prognostic role of liquid-based cytology (LBC) in different body lesions, including thyroid, lung, effusions and malignant breast lesions. LBC has gained consensus after being applied to both non-gynecologic and fine-needle aspiration cytology. Although some remain sceptical regarding the diagnostic efficacy of LBC, mainly when used alone, in recent years, good results have been obtained as long as it showed a high diagnostic accuracy. Here, we discuss the additional possibility of storing material for the application of ancillary techniques (immunocytochemistry–molecular analysis) with several diagnostic and prognostic advantages, which may pave the way for the challenging evaluation of both monitoring responses to treatment and resistance to targeted therapies in thyroid, lung, breast carcinoma or malignant effusions. Furthermore, it provides the use of several molecular spots as specific targets for personalized therapy.

A new page on the road book of inorganic mercury in fish body - tissue distribution and elimination following waterborne exposure and post-exposure periods

prova tipográfica / uncorrected proof

Development of a novel aptamer-based multi-sensor device for the detection of osteopontin

Doctoral Dissertation for PhD degree in Chemical and Biological Engineering

Intervir através da educação física na coeducação: realidade ou intenção?

Intervir de forma consciente e organizada em prol da promoção da igualdade de oportunidades na escola tem sido, nas últimas décadas, um dos propósitos da Educação Física (EF) na Europa. Através das rotinas e das oportunidades que se proporcionam, rapazes e raparigas têm acesso a uma prática de atividade física e desportiva (AFD) que lhes possibilita aperfeiçoar capacidades, competências e atitudes. Consideramos que o contributo da EF na educação é de um valor significativo, viabilizando às crianças e jovens construir a sua imagem corporal e os estereótipos de género, desenvolver afectos e emoções, cultivar a sua relação com os outros, criar capacidades e valores, ajudando deste modo uma formação das atitudes individuais ou coletivas, que respeitem a igualdade de género e, por isso, os direitos humanos. Este estudo foi realizado a partir da informação recolhida, através da aplicação de um questionário, a uma amostra de 993 crianças, 57.5% raparigas e 42.5% rapazes, com idades compreendidas entre os 10 e 12 anos, pertencentes a várias escolas do ensino público e ambicionou comparar as perceções e preferências de rapazes e raparigas relativamente às práticas AFD que decorrem na disciplina de EF, para se poderem apresentar alternativas de práticas mais flexíveis e integradoras. A partir dos nossos resultados podemos concluir que a AFD na escola continua a ser muito marcada por práticas de técnicas de movimento, jogos e competições desportivas, vivências muito identificadas com os estereótipos masculinos e que, nem sempre ajudam à formação de um bom esquema corporal e de comportamentos que se tendem a manter ao longo da vida, para muita(o)s jovens. Sugerimos que as atividades oferecidas às crianças e jovens nas escolas sejam mais diversificadas e inclusivas, impondo um nível de desempenho e de satisfação mais adequado a cada caso em particular, devendo estar mais centradas quer em atividades de ar livre, quer em práticas que desenvolvem também as dimensões sensitiva, expressiva e corporal do(a)s aluno(a)s.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.