3 resultados para mineral binding

em Universidade do Minho


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Dissertação de mestrado integrado em Arquitectura

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Despite the vast investigation and the large amount of products already available in the market to treat the different bone defects there is still a growing need to develop more advanced and complex therapeutic strategies. In this context, a mixture of Marine Hydroxyapatite-Fluorapatite:Collagen (HA-FP:ASC) seems to be a promising solution to overcome these bone defects, specifically, dental defects. HA-FP particles (20–63 μm) were obtained through pyrolysis (950°C, 12 h) of shark teeth (Isurus oxyrinchus, P. glauca), and Type I collagen was isolated from Prionace glauca skin as previously described (1). After the steps of purification, collagen was solubilized in 0.5 M acetic acid and HA-FP added producing three different formulations: were produced, 30:70, 50:50 and 70:30 of HA-FP:ASC, respectively. EDC/NHS and HMDI binding agents were used to stabilize the produced scaffolds. Mechanical properties were evaluated by compression tests. SEM analysis allowed observing the mineral deposition, after immersion in simulated body fluid and also permitted to evaluate how homogenous was the distribution of HA-FP in the different scaffold formulations, also confirmed by μ-CT assay. It was readily visible by Cytotoxicity and life/dead CLSM assays that cells were able to adhere and proliferate in the produced scaffolds. Scaffolds crosslinked with EDC/NHS showed lower cytotoxicity, being the ones chosen for further cellular evaluation.

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Natural mineral waters (still), effervescent natural mineral waters (sparkling) and aromatized waters with fruit-flavors (still or sparkling) are an emerging market. In this work, the capability of a potentiometric electronic tongue, comprised with lipid polymeric membranes, to quantitatively estimate routinely quality physicochemical parameters (pH and conductivity) as well as to qualitatively classify water samples according to the type of water was evaluated. The study showed that a linear discriminant model, based on 21 sensors selected by the simulated annealing algorithm, could correctly classify 100 % of the water samples (leave-one out cross-validation). This potential was further demonstrated by applying a repeated K-fold cross-validation (guaranteeing that at least 15 % of independent samples were only used for internal-validation) for which 96 % of correct classifications were attained. The satisfactory recognition performance of the E-tongue could be attributed to the pH, conductivity, sugars and organic acids contents of the studied waters, which turned out in significant differences of sweetness perception indexes and total acid flavor. Moreover, the E-tongue combined with multivariate linear regression models, based on sub-sets of sensors selected by the simulated annealing algorithm, could accurately estimate waters pH (25 sensors: R 2 equal to 0.99 and 0.97 for leave-one-out or repeated K-folds cross-validation) and conductivity (23 sensors: R 2 equal to 0.997 and 0.99 for leave-one-out or repeated K-folds cross-validation). So, the overall satisfactory results achieved, allow envisaging a potential future application of electronic tongue devices for bottled water analysis and classification.