930 resultados para extraction methods


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In this dissertation, there are developed different analytical strategies to discover and characterize mammalian brain peptides using small amount of tissues. The magnocellular neurons of rat supraoptic nucleus in tissue and cell culture served as the main model to study neuropeptides, in addition to hippocampal neurons and mouse embryonic pituitaries. The neuropeptidomcis studies described here use different extraction methods on tissue or cell culture combined with mass spectrometry (MS) techniques, matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI). These strategies lead to the identification of multiple peptides from the rat/mouse brain in tissue and cell cultures, including novel compounds One of the goals in this dissertation was to optimize sample preparations on samples isolated from well-defined brain regions for mass spectrometric analysis. Here, the neuropeptidomics study of the SON resulted in the identification of 85 peptides, including 20 unique peptides from known prohormones. This study includes mass spectrometric analysis even from individually isolated magnocellular neuroendocrine cells, where vasopressin and several other peptides are detected. At the same time, it was shown that the same approach could be applied to analyze peptides isolated from a similar hypothalamic region, the suprachiasmatic nucleus (SCN). Although there were some overlaps regarding the detection of the peptides in the two brain nuclei, different peptides were detected specific to each nucleus. Among other peptides, provasopressin fragments were specifically detected in the SON while angiotensin I, somatostatin-14, neurokinin B, galanin, and vasoactive-intestinal peptide (VIP) were detected in the SCN only. Lists of peptides were generated from both brain regions for comparison of the peptidome of SON and SCN nuclei. Moving from analysis of magnocellular neurons in tissue to cell culture, the direct peptidomics of the magnocellular and hippocampal neurons led to the detection of 10 peaks that were assigned to previously characterized peptides and 17 peaks that remain unassigned. Peptides from the vasopressin prohormone and secretogranin-2 are attributed to magnocellular neurons, whereas neurokinin A, peptide J, and neurokinin B are attributed to cultured hippocampal neurons. This approach enabled the elucidation of cell-specific prohormone processing and the discovery of cell-cell signaling peptides. The peptides with roles in the development of the pituitary were analyzed using transgenic mice. Hes1 KO is a genetically modified mouse that lives only e18.5 (embryonic days). Anterior pituitaries of Hes1 null mice exhibit hypoplasia due to increased cell death and reduced proliferation and in the intermediate lobe, the cells differentiate abnormally into somatotropes instead of melanotropes. These previous findings demonstrate that Hes1 has multiple roles in pituitary development, cell differentiation, and cell fate. AVP was detected in all samples. Interestingly, somatostatin [92-100] and provasopressin [151-168] were detected in the mutant but not in the wild type or heterozygous pituitaries while somatostatin-14 was detected only in the heterozygous pituitary. In addition, the putative peptide corresponding to m/z 1330.2 and POMC [205-222] are detected in the mutant and heterozygous pituitaries, but not in the wild type. These results indicate that Hes1 influences the processing of different prohormones having possible roles during development and opens new directions for further developmental studies. This research demonstrates the robust capabilities of MS, which ensures the unbiased direct analysis of peptides extracted from complex biological systems and allows addressing important questions to understand cell-cell signaling in the brain.

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Chemical speciation in foodstuffs is of uttermost importance since it is nowadays recognized that both toxicity and bioavailability of an element depend on the chemical form in which the element is present. Regarding arsenic, inorganic species are classified as carcinogenic while organic arsenic, such as arsenobetaine (AsB) or arsenocholine (AsC), is considered less toxic or even non-toxic. Coupling a High Performance Liquid Chromatographer (HPLC) with an Inductively Coupled Plasma Mass Spectrometer (ICP-MS) combines the power of separation of the first with the selectivity and sensitivity of the second. The present work aims at developing a method, using HPLC-ICP-MS technique, to identify and quantify the chemical species of arsenic present in two food matrices, rice and fish. Two extraction methods, ultrasound and microwave, and different settings were studied. The best method was chosen based on recovery percentages. To ensure that no interconversion of species was occurring, individual spikes of each species of arsenic were made in both matrices and recovery rates were calculated. To guaranty accurate results reference material BCR-627 TUNA FISH, containing certified values for AsB and DMA, was analyzed. Chromatographic separation was achieved using an anion exchange column, HAMILTON-PRP X-100, which allowed to separate the four arsenic species for which standards were available (AsB, dimethylarsenic (DMA), arsenite (AsIII), arsenate (AsV). The mobile phase was chosen based on scientific literature and adjusted to laboratory conditions. Different gradients were studied. As a result we verified that the arsenic species present in both matrices were not the same. While in fish 90% of the arsenic present was in the form of arsenobetaine, in rice 80% of arsenic was present as DMA and 20% as inorganic arsenic.

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Archived specimens are highly valuable sources of DNA for retrospective genetic/genomic analysis. However, often limited effort has been made to evaluate and optimize extraction methods, which may be crucial for downstream applications. Here, we assessed and optimized the usefulness of abundant archived skeletal material from sharks as a source of DNA for temporal genomic studies. Six different methods for DNA extraction, encompassing two different commercial kits and three different protocols, were applied to material, so-called bio-swarf, from contemporary and archived jaws and vertebrae of tiger sharks (Galeocerdo cuvier). Protocols were compared for DNA yield and quality using a qPCR approach. For jaw swarf, all methods provided relatively high DNA yield and quality, while large differences in yield between protocols were observed for vertebrae. Similar results were obtained from samples of white shark (Carcharodon carcharias). Application of the optimized methods to 38 museum and private angler trophy specimens dating back to 1912 yielded sufficient DNA for downstream genomic analysis for 68% of the samples. No clear relationships between age of samples, DNA quality and quantity were observed, likely reflecting different preparation and storage methods for the trophies. Trial sequencing of DNA capture genomic libraries using 20 000 baits revealed that a significant proportion of captured sequences were derived from tiger sharks. This study demonstrates that archived shark jaws and vertebrae are potential high-yield sources of DNA for genomic-scale analysis. It also highlights that even for similar tissue types, a careful evaluation of extraction protocols can vastly improve DNA yield.

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Over the past years, ω3 fatty acids, namely EPA and DHA, have been recognized as presenting multiple health benefits. Several studies consider fish oil as the most important source of EPA and DHA. Nowadays, canned fish industry plays a very important role in Portuguese economy. However, expansion of this business brought some environmental concerns due to the high amount of by-products generated. Nevertheless, this problem can be substantially reduced by the recovery of some of the by-product components, diminishing its contamination load and simultaneously obtaining value-added products. This study was born from the growing interest in obtaining new sources of lipids rich in ω3 fatty acids, combined with environmental concerns related to the production of wastes from the fish canning industries, rich in these compounds. It thus intends to evaluate lipid extraction methods in liquid by-products from the fish canning industry, aiming to obtain fractions rich in ω3 fatty acids. Additionally, in a biorefining concept, the protein content of the remaining aqueous fractions was also quantified.

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A produção de biodiesel a partir do óleo de microalgas tem sido demonstrada na literatura usando rotas convencionais, que envolvem a extração dos lipídeos seguida pela sua conversão para ésteres graxos. A extração de lipídeos a partir da biomassa microalgal é uma etapa importante do processo global de produção de biodiesel. Este trabalho teve como objetivo determinar o teor de lipídeos da Chlorella pyrenoidosa bem como o perfil graxo dos diferentes extratos lipídicos. Os métodos de extração utilizados envolveram o uso de ultrassom, agitação magnética e soxhlet na presença dos solventes: clorofórmio:metanol (2:1 v/v) (método de Bligh & Dyer), metanol, clorofórmio, etanol e hexano. Os melhores resultados foram obtidos a partir do método com agitação magnética utilizando clorofórmio:metanol 2:1 (v/v), onde foram extraídos em média de 20 % de lipídeos totais seguido de metanol (17 %), clorofórmio (10,5 %), etanol (7,8 %) e hexano (1,15 %). A presença dos ácidos graxos 14:0, 16:0, 18:1, 18:0, 18:2 e 18:3 foram confirmados pelas análises de cromatografia gasosa. A partir das frações lipídicas extraídas foram realizadas as reações para obtenção dos ésteres graxos utilizando temperatura de 60°C por 4h na presença de 3% de H2SO4 em relação à massa de lipídeos. Os extratos lipídicos foram obtidos usando 100 g de biomassa seca. A partir das frações extraídas com clorofórmio:metanol 2:1 (v/v), metanol e etanol foram produzidos em média 6,40g, 8,98g, 6,98g de ésteres graxos, respectivamente.

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Purpose: To develop liposome formulations containing monoclonal antibody anti-HER2 (MabHer2), and Paclitaxel (PTX). Methods: Seven different liposomal systems containing PTX, or MabHer2 or a combination of PTX and MabHer2 were made using lipid film hydration technique and sonication. The effects of liposome preparation conditions and extraction methods on antibody structure were investigated by polyacrylamide gel electrophoresis and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The characteristics of the liposomes were determined by a zetasizer, while drug-loading efficiency was evaluated by high-performance liquid chromatography. The cytotoxic effect of the liposome formulations was evaluated on MDA-MB-453 (HER2+) and MCF-7 (HER2-) breast cancer cell lines by MTT assay. Results: The antibody was not significantly affected by the stress conditions and the method of extraction. The particle size of liposomes was < 200 nm while the amount of incorporated PTX was 97.6 % for liposome without cationic agent and 98.2 % for those with cationic agent. Recovery of MabHer2 was 94.38 % after extraction. Combined PTX/MabHer2 liposome was more toxic on HER2 overexpressing positive MDA-MB-453 cell line than PTX-loaded liposomes and MabHer2. MabHer2 and combined PTX/MabHer2 liposomes showed no toxic effects on HER2 overexpressing negative MCF-7 cells relative to cationic PTX-loaded liposomes. Conclusions: This results obtained show that PTX can be encapsulated successfully into liposoma systems and that owing to Her2 specific antibody, these systems can be delivered directly to the target cell.

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To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

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The presence of inhibitory substances in biological forensic samples has, and continues to affect the quality of the data generated following DNA typing processes. Although the chemistries used during the procedures have been enhanced to mitigate the effects of these deleterious compounds, some challenges remain. Inhibitors can be components of the samples, the substrate where samples were deposited or chemical(s) associated to the DNA purification step. Therefore, a thorough understanding of the extraction processes and their ability to handle the various types of inhibitory substances can help define the best analytical processing for any given sample. A series of experiments were conducted to establish the inhibition tolerance of quantification and amplification kits using common inhibitory substances in order to determine if current laboratory practices are optimal for identifying potential problems associated with inhibition. DART mass spectrometry was used to determine the amount of inhibitor carryover after sample purification, its correlation to the initial inhibitor input in the sample and the overall effect in the results. Finally, a novel alternative at gathering investigative leads from samples that would otherwise be ineffective for DNA typing due to the large amounts of inhibitory substances and/or environmental degradation was tested. This included generating data associated with microbial peak signatures to identify locations of clandestine human graves. Results demonstrate that the current methods for assessing inhibition are not necessarily accurate, as samples that appear inhibited in the quantification process can yield full DNA profiles, while those that do not indicate inhibition may suffer from lowered amplification efficiency or PCR artifacts. The extraction methods tested were able to remove >90% of the inhibitors from all samples with the exception of phenol, which was present in variable amounts whenever the organic extraction approach was utilized. Although the results attained suggested that most inhibitors produce minimal effect on downstream applications, analysts should practice caution when selecting the best extraction method for particular samples, as casework DNA samples are often present in small quantities and can contain an overwhelming amount of inhibitory substances.^

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Background: Alterations in intestinal microbiota have been correlated with a growing number of diseases. Investigating the faecal microbiota is widely used as a non-invasive and ethically simple proxy for intestinal biopsies. There is an urgent need for collection and transport media that would allow faecal sampling at distance from the processing laboratory, obviating the need for same-day DNA extraction recommended by previous studies of freezing and processing methods for stool. We compared the faecal bacterial DNA quality and apparent phylogenetic composition derived using a commercial kit for stool storage and transport (DNA Genotek OMNIgene GUT) with that of freshly extracted samples, 22 from infants and 20 from older adults. Results: Use of the storage vials increased the quality of extracted bacterial DNA by reduction of DNA shearing. When infant and elderly datasets were examined separately, no differences in microbiota composition were observed due to storage. When the two datasets were combined, there was a difference according to a Wilcoxon test in the relative proportions of Faecalibacterium, Sporobacter, Clostridium XVIII, and Clostridium XlVa after 1 week's storage compared to immediately extracted samples. After 2 weeks' storage, Bacteroides abundance was also significantly different, showing an apparent increase from week 1 to week 2. The microbiota composition of infant samples was more affected than that of elderly samples by storage, with significantly higher Spearman distances between paired freshly extracted and stored samples (p

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Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

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A survey was undertaken of methods available for the extraction of fin rays from shark fins. The development of new, quicker and easier methods of processing is presented.

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A new approach for extracting stress intensity factors (SIFs) by the element-free Galerkin (EFG) class of methods through a modified crack closure integral (MCCI) scheme is proposed. Its primary feature is that it allows accurate calculation of mode I and mode II SIFs with a relatively simple and straightforward analysis even when a coarser nodal density is employed. The details of the adoption of the MCCI technique in the EFG method are described. Its performance is demonstrated through a number of case studies including mixed-mode and thermal problems in linear elastic fracture mechanics (LEFM). The results are compared with published theoretical solutions and those based on the displacement method, stress method, crack closure integral in conjunction with local smoothing (CCI–LS) technique, as well as the M-integral method. Its advantages are discussed.

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Procedures for routine analysis of soil phosphorus (P) have been used for assessment of P status, distribution and P losses from cultivated mineral soils. No similar studies have been carried out on wetland peat soils. The objective was to compare extraction efficiency of ammonium lactate (PAL), sodium bicarbonate (P-Olsen), and double calcium lactate (P-DCaL) and P distribution in the soil profile of wetland peat soils. For this purpose, 34 samples of the 0-30, 30-60 and 60-90 cm layers were collected from peat soils in Germany, Israel, Poland, Slovenia, Sweden and the United Kingdom and analysed for P. Mean soil pH (CaCl2, 0.01 M) was 5.84, 5.51 and 5.47 in the 0-30, 30-60 and 60-90 cm layers, respectively. The P-DCaL was consistently about half the magnitude of either P-AL or P-Olsen. The efficiency of P extraction increased in the order P-DCaL < P-AL &LE; P-Olsen, with corresponding means (mg kg(-1)) for all soils (34 samples) of 15.32, 33.49 and 34.27 in 0-30 cm; 8.87, 17.30 and 21.46 in 30-60 cm; and 5.69, 14.00 and 21.40 in 60-90 cm. The means decreased with depth. When examining soils for each country separately, P-Olsen was relatively evenly distributed in the German, UK and Slovenian soils. P-Olsen was linearly correlated (r = 0.594, P = 0.0002) with pH, whereas the three P tests (except P-Olsen vs P-DCaL) significantly correlated with each other (P = 0.017850.0001). The strongest correlation (r = 0.617, P = 0.0001) was recorded for P-AL vs P-DCaL) and the two methods were inter-convertible using a regression equation: P-AL = -22.593 + 5.353 pH + 1.423 P-DCaL, R-2 = 0.550.

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There are many published methods available for creating keyphrases for documents. Previous work in the field has shown that in a significant proportion of cases author selected keyphrases are not appropriate for the document they accompany. This requires the use of such automated methods to improve the use of keyphrases. Often the keyphrases are not updated when the focus of a paper changes or include keyphrases that are more classificatory than explanatory. The published methods are all evaluated using different corpora, typically one relevant to their field of study. This not only makes it difficult to incorporate the useful elements of algorithms in future work but also makes comparing the results of each method inefficient and ineffective. This paper describes the work undertaken to compare five methods across a common baseline of six corpora. The methods chosen were term frequency, inverse document frequency, the C-Value, the NC-Value, and a synonym based approach. These methods were compared to evaluate performance and quality of results, and to provide a future benchmark. It is shown that, with the comparison metric used for this study Term Frequency and Inverse Document Frequency were the best algorithms, with the synonym based approach following them. Further work in the area is required to determine an appropriate (or more appropriate) comparison metric.

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Regulatory, safety, and environmental issues have prompted the development of aqueousenzymatic extraction (AEE) for extracting components from oil-bearing materials. The emulsion resulting from AEE requires de-emulsification to separate the oil; when enzymes are used for this purpose, the method is known as aqueous enzymatic emulsion de-emulsification (AEED). In general, enzyme assisted oil extraction is known to yield oil having highly favourable characteristics. This review covers technological aspects of enzyme assisted oil extraction, and explores the quality characteristics of the oils obtained,focusing particularly on recent efforts undertaken to improve process economics by recovering and reusing enzymes.