Relato de uma experiência: recuperação e cadastramento de resíduos dos laboratórios de graduação do Instituto de Química da Universidade Federal do Rio Grande do Sul

An experience aiming to promote a residue interchange and recovery between the teaching laboratories of the Chemistry Institute of this University is described. At the present, several residues interchange have already appeared as advantageous. To make the work easier, a software has been developed in order to keep a record of all the residues generated by the teaching laboratories. Standard labels have been developed for the residues in order to organize them. The software and the label design are described.

Glicídios no mel

A review about composition, origin and importance of carbohydrates in honey is presented. Fructose and glucose are the major carbohydrates, ranging from 65-85 % of the total soluble solids. Other minor carbohydrates, chiefly di- and trisaccharides, have been also identified. Fructose, glucose and sucrose are mainly originated from nectar. Oligosaccharides are mainly formed by trans-alpha-D-glucosylation reactions catalysed by honeybee alpha-D-glucosidase. The profile of carbohydrates can be useful for the identification of the brazilian region in which honey was produced and may also be useful for testing brazilian honey authenticity.

Suite No. 2 in D minor

Soitinnus: Alttoviulu.

Análisis de viabilidad de la ejecución y puesta en marcha de un hotel con encanto en el Pirineo Aragonés

A través de este proyecto final de carrera se pretende analizar la viabilidad técnica y económica para la puesta en marcha de un hotel de montaña en una comarca concreta del Pirineo Aragonés, como alternativa de negocio. Aunque no podemos olvidar que es un sector que puede parecer saturado, se tratará de buscar el elemento diferenciador para superar esta amenaza competitiva. Desde el año 2000, el número total de turistas que llegan a España, ha ido ascendiendo año a año, hasta alcanzar valores máximos en 2007 y de nuevo en 2013. Las estadísticas demuestran que es un sector al alza y en la comunidad aragonesa aporta al PIB aragonés, cerca de 3.000 millones de euros. Por otro lado, la crisis ha provocado una bajada importante en los precios de los inmuebles y parcelas, por lo que nos aprovecharemos de esta oportunidad de negocio. A través de otros estudios que implementan el trabajo, llegamos a los resultados del análisis que demuestran que la inversión es posible. La modalidad escogida para la construcción y diseño del hotel, el efecto diferenciador en los productos y servicios ofertados y la cercanía del hotel de las estaciones de esquí, hacen posible el sueño de los futuros promotores, que apuestan por un tipo de negocio sostenible e integrado en la naturaleza y que respete la autenticidad sociocultural de la comarca y el entono.

Suite No. 6 in D major

Soitinnus: Alttoviulu.

Genomic analysis of the blood attributed to Louis XVI (1754-1793), king of France.

A pyrographically decorated gourd, dated to the French Revolution period, has been alleged to contain a handkerchief dipped into the blood of the French king Louis XVI (1754-1793) after his beheading but recent analyses of living males from two Bourbon branches cast doubts on its authenticity. We sequenced the complete genome of the DNA contained in the gourd at low coverage (similar to 2.5x) with coding sequences enriched at a higher similar to 7.3x coverage. We found that the ancestry of the gourd's genome does not seem compatible with Louis XVI's known ancestry. From a functional perspective, we did not find an excess of alleles contributing to height despite being described as the tallest person in Court. In addition, the eye colour prediction supported brown eyes, while Louis XVI had blue eyes. This is the first draft genome generated from a person who lived in a recent historical period; however, our results suggest that this sample may not correspond to the alleged king.

Detecção de adulterações em produtos alimentares contendo leite e/ou proteínas lácteas

A critical review of the most relevant analytical methodologies for quality and authenticity control of dairy products and foods containing milk proteins is presented. Chromatographic, electrophoretic and immunological methods are used for: detection of cow's milk in ewe and goat milks, detection of whey added to milk, detection of caseins and/or whey proteins in non-lactic foods and study compounds resulting from milk proteins degradation. Techniques based on polimerase chain reaction are also suitable for detection of cow's milk on cheeses of ewe and goat milks.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Decay of linkage disequilibrium within genes across HGDP-CEPH human samples: most population isolates do not show increased LD

Background It is well known that the pattern of linkage disequilibrium varies between human populations, with remarkable geographical stratification. Indirect association studies routinely exploit linkage disequilibrium around genes, particularly in isolated populations where it is assumed to be higher. Here, we explore both the amount and the decay of linkage disequilibrium with physical distance along 211 gene regions, most of them related to complex diseases, across 39 HGDP-CEPH population samples, focusing particularly on the populations defined as isolates. Within each gene region and population we use r2 between all possible single nucleotide polymorphism (SNP) pairs as a measure of linkage disequilibrium and focus on the proportion of SNP pairs with r2 greater than 0.8. Results Although the average r2 was found to be significantly different both between and within continental regions, a much higher proportion of r2 variance could be attributed to differences between continental regions (2.8% vs. 0.5%, respectively). Similarly, while the proportion of SNP pairs with r2 > 0.8 was significantly different across continents for all distance classes, it was generally much more homogenous within continents, except in the case of Africa and the Americas. The only isolated populations with consistently higher LD in all distance classes with respect to their continent are the Kalash (Central South Asia) and the Surui (America). Moreover, isolated populations showed only slightly higher proportions of SNP pairs with r2 > 0.8 per gene region than non-isolated populations in the same continent. Thus, the number of SNPs in isolated populations that need to be genotyped may be only slightly less than in non-isolates. Conclusion The 'isolated population' label by itself does not guarantee a greater genotyping efficiency in association studies, and properties other than increased linkage disequilibrium may make these populations interesting in genetic epidemiology.

Uso de métodos analíticos convencionados no estudo da autenticidade do óleo de copaíba

The acidity and ester index are suggested, as simple and cheap methods, adequate to be employed in the study of the authenticity of copaíba oil by small drugstores and export firms. The acidity index permits both the detection and the evaluation of the content of adulteration of copaíba oil. The ester index permits to know if the adulterant either contain ester compounds,as the case of fatty oils, or contain only non saponifiable compounds as is the case of ethyl alchool or mineral oil. The results of the aplication of the methods to eight commercial samples, of copaiba oil, where three samples were adultered, are coherent with those obtained by more sophisticated instrumental methods.

Design and production of protein nanostructures for biomolecular detection

Particulate nanostructures are increasingly used for analytical purposes. Such particles are often generated by chemical synthesis from non-renewable raw materials. Generation of uniform nanoscale particles is challenging and particle surfaces must be modified to make the particles biocompatible and water-soluble. Usually nanoparticles are functionalized with binding molecules (e.g., antibodies or their fragments) and a label substance (if needed). Overall, producing nanoparticles for use in bioaffinity assays is a multistep process requiring several manufacturing and purification steps. This study describes a biological method of generating functionalized protein-based nanoparticles with specific binding activity on the particle surface and label activity inside the particles. Traditional chemical bioconjugation of the particle and specific binding molecules is replaced with genetic fusion of the binding molecule gene and particle backbone gene. The entity of the particle shell and binding moieties are synthesized from generic raw materials by bacteria, and fermentation is combined with a simple purification method based on inclusion bodies. The label activity is introduced during the purification. The process results in particles that are ready-to-use as reagents in bioaffinity. Apoferritin was used as particle body and the system was demonstrated using three different binding moieties: a small protein, a peptide and a single chain Fv antibody fragment that represents a complex protein including disulfide bridge.If needed, Eu3+ was used as label substance. The results showed that production system resulted in pure protein preparations, and the particles were of homogeneous size when visualized with transmission electron microscopy. Passively introduced label was stably associated with the particles, and binding molecules genetically fused to the particle specifically bound target molecules. Functionality of the particles in bioaffinity assays were successfully demonstrated with two types of assays; as labels and in particle-enhanced agglutination assay. This biological production procedure features many advantages that make the process especially suited for applications that have frequent and recurring requirements for homogeneous functional particles. The production process of ready, functional and watersoluble particles follows principles of “green chemistry”, is upscalable, fast and cost-effective.

Aplicação da CLAE para determinação do ácido 10-Hidróxi-2-decenóico (10-HDA) em geléia real pura e adicionada a mel brasileiro

The aim of this paper was to determine the 10-HDA in pure royal jelly and products containing royal jelly, using HPLC methodology. 10-HDA is the natural indicator of the presence of royal jelly in products and also gives the authenticity of pure royal jelly. The chromatographic conditions used were: isocratic system, C18-H column, auto sampler, diode array UV-VIS detector (225 nm), mobile phase with methanol/water (45:55), pH= 2.5 and a-naphtol as internal standard. The results obtained using laboratory samples for pure royal jelly were 2.37%, varying from 0.15% for honey with 10% of royal jelly to 2.10% for honey with 90% of royal jelly respectivelly. For commercial products, the 10-HDA content varied from no detectable to 0.026%. The recovery test presented a minumum of 100.44% The detection limit was 45.92 ng/mL and the quantification limit was 76.53 ng/mL.

Determinação espectrofotométrica simultânea de paracetamol e ibuprofeno em formulações farmacêuticas usando calibração multivariada

A simple method was proposed for determination of paracetamol and ibuprofen in tablets, based on UV measurements and partial least squares. The procedure was performed at pH 10.5, in the concentration ranges 3.00-15.00 µg ml-1 (paracetamol) and 2.40-12.00 µg ml-1 (ibuprofen). The model was able to predict paracetamol and ibuprofen in synthetic mixtures with root mean squares errors of prediction of 0.12 and 0.17 µg ml-1, respectively. Figures of merit (sensitivity, limit of detection and precision) were also estimated. The results achieved for the determination of these drugs in pharmaceutical formulations were in agreement with label claims and verified by HPLC.