Metabolomics reveals novel biomarkers of illegal 5-nitromimidazole treatment in pigs. Further evidence of drug toxicity uncovered

The aim of the study was to investigate the potential of a metabolomics platform to distinguish between pigs treated with ronidazole, dimetridazole and metronidazole and non-medicated animals (controls), at two withdrawal periods (day 0 and 5). Livers from each animal were biochemically profiled using UHPLC–QTof-MS in ESI+ mode of acquisition. Several Orthogonal Partial Least Squares-Discriminant Analysis models were generated from the acquired mass spectrometry data. The models classified the two groups control and treated animals. A total of 42 ions of interest explained the variation in ESI+. It was possible to find the identity of 3 of the ions and to positively classify 4 of the ionic features, which can be used as potential biomarkers of illicit 5-nitroimidazole abuse. Further evidence of the toxic mechanisms of 5-nitroimidazole drugs has been revealed, which may be of substantial importance as metronidazole is widely used in human medicine.

Metabonomic studies to assess beer quality and stability

The work reported in this thesis aimed at applying the methodology known as metabonomics to the detailed study of a particular type of beer and its quality control, with basis on the use of multivariate analysis (MVA) to extract meaningful information from given analytical data sets. In Chapter 1, a detailed description of beer is given considering the brewing process, main characteristics and typical composition of beer, beer stability and the commonly used analytical techniques for beer analysis. The fundamentals of the analytical methods employed here, namely nuclear magnetic resonance (NMR) spectroscopy, gas-chromatography-mass spectrometry (GC-MS) and mid-infrared (MIR) spectroscopy, together with the description of the metabonomics methodology are described shortly in Chapter 2. In Chapter 3, the application of high resolution NMR to characterize the chemical composition of a lager beer is described. The 1H NMR spectrum obtained by direct analysis of beer show a high degree of complexity, confirming the great potential of NMR spectroscopy for the detection of a wide variety of families of compounds, in a single run. Spectral assignment was carried out by 2D NMR, resulting in the identification of about 40 compounds, including alcohols, amino acids, organic acids, nucleosides and sugars. In a second part of Chapter 3, the compositional variability of beer was assessed. For that purpose, metabonomics was applied to 1H NMR data (NMR/MVA) to evaluate beer variability between beers from the same brand (lager), produced nationally but differing in brewing site and date of production. Differences between brewing sites and/or dates were observed, reflecting compositional differences related to particular processing steps, including mashing, fermentation and maturation. Chapter 4 describes the quantification of organic acids in beer by NMR, using different quantitative methods: direct integration of NMR signals (vs. internal reference or vs. an external electronic reference, ERETIC method) and by quantitative statistical methods (using the partial least squares (PLS) regression) were developed and compared. PLS1 regression models were built using different quantitative methods as reference: capillary electrophoresis with direct and indirect detection and enzymatic essays. It was found that NMR integration results generally agree with those obtained by the best performance PLS models, although some overestimation for malic and pyruvic acids and an apparent underestimation for citric acid were observed. Finally, Chapter 5 describes metabonomic studies performed to better understand the forced aging (18 days, at 45 ºC) beer process. The aging process of lager beer was followed by i) NMR, ii) GC-MS, and iii) MIR spectroscopy. MVA methods of each analytical data set revealed clear separation between different aging days for both NMR and GC-MS data, enabling the identification of compounds closely related with the aging process: 5-hydroxymethylfurfural (5-HMF), organic acids, γ-amino butyric acid (GABA), proline and the ratio linear/branched dextrins (NMR domain) and 5-HMF, furfural, diethyl succinate and phenylacetaldehyde (known aging markers) and, for the first time, 2,3-dihydro-3,5-dihydroxy-6-methyl-4(H)-pyran-4-one xii (DDMP) and maltoxazine (by GC-MS domain). For MIR/MVA, no aging trend could be measured, the results reflecting the need of further experimental optimizations. Data correlation between NMR and GC-MS data was performed by outer product analysis (OPA) and statistical heterospectroscopy (SHY) methodologies, enabling the identification of further compounds (11 compounds, 5 of each are still unassigned) highly related with the aging process. Data correlation between sensory characteristics and NMR and GC-MS was also assessed through PLS1 regression models using the sensory response as reference. The results obtained showed good relationships between analytical data response and sensory response, particularly for the aromatic region of the NMR spectra and for GC-MS data (r > 0.89). However, the prediction power of all built PLS1 regression models was relatively low, possibly reflecting the low number of samples/tasters employed, an aspect to improve in future studies.

Metabonomics of human amniotic fluid for prenatal diagnostics

O trabalho apresentado nesta tese teve como principais objectivos contribuir para o conhecimento da composição do líquido amniótico humano (LA), colhido no 2º trimestre de gravidez, assim como investigar possíveis alterações na sua composição devido à ocorrência de patologias pré-natais, recorrendo à metabonómica e procurando, assim, definir novos biomarcadores de doenças da grávida e do feto. Após uma introdução descrevendo o estado da arte relacionado com este trabalho (Capítulo 1) e os princípios das metodologias analíticas usadas (Capítulo 2), seguida de uma descrição dos aspectos experimentais associados a esta tese (Capítulo 3), apresentam-se os resultados da caracterização da composição química do LA (gravidez saudável) por espectroscopia de ressonância magnética nuclear (RMN), assim como da monitorização da sua estabilidade durante o armazenamento e após ciclos de congelamento-descongelamento (Capítulo 4). Amostras de LA armazenadas a -20°C registaram alterações significativas, tornando-se estas menos pronunciadas (mas ainda mensuráveis) a -70°C, temperatura recomendada para o armazenamento de LA. Foram também observadas alterações de composição após 1-2 ciclos de congelamento-descongelamento (a ter em conta aquando da reutilização de amostras), assim como à temperatura ambiente (indicando um período máximo de 4h para a manipulação e análise de LA). A aquisição de espectros de RMN de 1H de alta resolução e RMN acoplado (LC-NMR/MS) permitiu a detecção de 75 compostos no LA do 2º trimestre, 6 dos quais detectados pela primeira vez no LA. Experiências de difusão (DOSY) permitiram ainda a caracterização das velocidades de difusão e massas moleculares médias das proteínas mais abundantes. O Capítulo 5 descreve o estudo dos efeitos de malformações fetais (FM) e de cromossomopatias (CD) na composição do LA do 2º trimestre de gravidez. A extensão deste trabalho ao estudo dos efeitos de patologias no LA que ocorrem no 3º trimestre de gravidez é descrita no Capítulo 6, nomeadamente no que se refere ao parto pré-termo (PTD), pré-eclampsia (PE), restrição do crescimento intra-uterino (IUGR), ruptura prematura de membranas (PROM) e diabetes mellitus gestacional (GDM). Como complemento a estes estudos, realizou-se uma análise preliminar da urina materna do 2º trimestre para o estudo de FM e GDM, descrita no Capítulo 7. Para interpretação dos dados analíticos, obtidos por espectroscopia RMN de 1H, cromatografia líquida de ultra eficiência acoplada a espectrometria de massa (UPLC-MS) e espectroscopia do infravermelho médio (MIR), recorreu-se à análise discriminante pelos métodos dos mínimos quadrados parciais e o método dos mínimos quadrados parciais ortogonal (PLS-DA e OPLS-DA) e à correlação espectral. Após análise por validação cruzada de Monte-Carlo (MCCV), os modelos PLS-DA de LA permitiram distinguir as FM dos controlos (sensibilidades 69-85%, especificidades 80-95%, taxas de classificação 80-90%), revelando variações metabólicas ao nível do metabolismo energético, dos metabolismos dos aminoácidos e glícidos assim como possíveis alterações ao nível do funcionamento renal. Observou-se também um grande impacto das FM no perfil metabólico da urina materna (medido por UPLC-MS), tendo no entanto sido registados modelos PLS-DA com menor sensibilidade (40-60%), provavelmente devido ao baixo número de amostras e maior variabilidade da composição da urina (relativamente ao LA). Foram sugeridos possíveis marcadores relacionados com a ocorrência de FM, incluindo lactato, glucose, leucina, valina, glutamina, glutamato, glicoproteínas e conjugados de ácido glucurónico e/ou sulfato e compostos endógenos e/ou exógenos (<1 M) (os últimos visíveis apenas na urina). No LA foram também observadas variações metabólicas devido à ocorrência de vários tipos de cromossomopatias (CD), mas de menor magnitude. Os perfis metabólicos de LA associado a pré- PTD produziram modelos que, apesar do baixo poder de previsão, sugeriram alterações precoces no funcionamento da unidade fetoplacentária, hiperglicémia e stress oxidativo. Os modelos obtidos para os grupos pré- IUGR pré- PE, pré- PROM e pré-diagnóstico GDM (LA e urina materna) registaram baixo poder de previsão, indicando o pouco impacto destas condições na composição do LA e/ou urina do 2º trimestre. Os resultados obtidos demonstram as potencialidades da análise dos perfis metabólicos do LA (e, embora com base em menos estudos, da urina materna) do 2º trimestre para o desenvolvimento de novos e complementares métodos de diagnóstico, nomeadamente para FM e PTD.

Determinants of online travel purchase intentions: a holistic approach

Online travel shopping has attracted researchers due to its significant growth and there is a growing body of literature in this field. However, research on what drives consumers to purchase travel online has typically been fragmented. In fact, existing studies have largely concentrated on examining consumers’ online travel purchases either grounded on Davis’s Technology Acceptance Model, on the Theory of Reasoned Action and its extension, the Theory of Planned Behaviour or on Roger’s model of perceived innovation attributes, the Innovation Diffusion Theory. A thorough literature review has revealed that there is a lack of studies that integrate all theories to better understand online travel shopping. Therefore, based on relevant literature in tourism and consumer behaviour, this study proposes and tests an integrated model to explore which factors affect intentions to purchase travel online. Furthermore, it proposes a new construct, termed social media involvement, defined as a person’s level of interest or emotional attachment with social media, and examines its relationship with intentions to purchase travel online. To test the 18 hypotheses, a quantitative approach was followed by first collecting data through an online survey. With a sample of 1,532 Worldwide Internet users, Partial Least Squares analysis was than conducted to assess the validity and reliability of the data and empirically test the hypothesized relationships between the constructs. The results indicate that intentions to purchase travel online is mostly determined by attitude towards online shopping, which is influenced by perceived relative advantages of online travel shopping and trust in online travel shopping. In addition, the findings indicate that the second most important predictor of intentions to purchase travel online is compatibility, an attribute from the Innovation Diffusion Theory. Furthermore, even though online shopping is nowadays a common practice, perceived risk continues to negatively affect intentions to purchase travel online. The most surprising finding of this study was that Internet users more involved with social media for travel purposes did not have higher intentions to purchase travel online. The theoretical contributions of this study and the practical implications are discussed and future research directions are detailed.

A experiência de visita dirigida a múltiplas atrações: análise do comportamento espacial do turista e da sua satisfação

Esta investigação teve como objetivo central averiguar se o comportamento espaciotemporal do turista urbano influencia a sua satisfação com a experiência de visita multiatração. Apesar de a mobilidade ser uma condição sine qua non do turismo, e, por outro lado, a visita a múltiplas atrações o contexto habitual em que se desenvolve a experiência turística em contexto urbano, a investigação neste domínio tende a ignorar a dimensão espaciotemporal e multiatração dessa experiência. O modelo conceptual proposto visa a sistematização da análise do comportamento espaciotemporal do turista bem como o estudo da sua relação com a satisfação, enquanto satisfação global e satisfação com dimensões da experiência. A partir deste, foi definido o modelo da pesquisa que, modelizando a questão central em estudo, teve por base dois instrumentos principais: estudo de rastreamento através de equipamento GPS e inquérito por questionário, realizados junto de hóspedes de dez hotéis de Lisboa (n= 413). A análise dos dados assume, por sua vez, dupla natureza: espacial e estatística. Em termos de análise espacial, a metodologia SIG em que se baseou a concretização dos mapas foi executada tendo como suporte a solução ArcGIS for Desktop 10.1, permitindo gerar visualizações úteis do ponto de vista da questão em estudo. A análise estatística dos dados compreendeu métodos descritivos, exploratórios e inferenciais, tendo como principal instrumento de teste das hipóteses formuladas a modelação PLS-PM, complementada pela análise PLS-MGA, com recurso ao programa SmartPLS 2.0. Entre as várias relações significativas encontradas, a conclusão mais importante que se pode retirar da investigação empírica é que, de facto, o comportamento espaciotemporal do turista urbano influencia a sua satisfação com a experiência de visita multiatração, afigurando-se particularmente importante neste contexto, em termos científicos e empíricos, investigar a heterogeneidade subjacente à população em estudo.

NMR in the characterization of heavy residual procedural streams

The main objective of this work was to monitor a set of physical-chemical properties of heavy oil procedural streams through nuclear magnetic resonance spectroscopy, in order to propose an analysis procedure and online data processing for process control. Different statistical methods which allow to relate the results obtained by nuclear magnetic resonance spectroscopy with the results obtained by the conventional standard methods during the characterization of the different streams, have been implemented in order to develop models for predicting these same properties. The real-time knowledge of these physical-chemical properties of petroleum fractions is very important for enhancing refinery operations, ensuring technically, economically and environmentally proper refinery operations. The first part of this work involved the determination of many physical-chemical properties, at Matosinhos refinery, by following some standard methods important to evaluate and characterize light vacuum gas oil, heavy vacuum gas oil and fuel oil fractions. Kinematic viscosity, density, sulfur content, flash point, carbon residue, P-value and atmospheric and vacuum distillations were the properties analysed. Besides the analysis by using the standard methods, the same samples were analysed by nuclear magnetic resonance spectroscopy. The second part of this work was related to the application of multivariate statistical methods, which correlate the physical-chemical properties with the quantitative information acquired by nuclear magnetic resonance spectroscopy. Several methods were applied, including principal component analysis, principal component regression, partial least squares and artificial neural networks. Principal component analysis was used to reduce the number of predictive variables and to transform them into new variables, the principal components. These principal components were used as inputs of the principal component regression and artificial neural networks models. For the partial least squares model, the original data was used as input. Taking into account the performance of the develop models, by analysing selected statistical performance indexes, it was possible to conclude that principal component regression lead to worse performances. When applying the partial least squares and artificial neural networks models better results were achieved. However, it was with the artificial neural networks model that better predictions were obtained for almost of the properties analysed. With reference to the results obtained, it was possible to conclude that nuclear magnetic resonance spectroscopy combined with multivariate statistical methods can be used to predict physical-chemical properties of petroleum fractions. It has been shown that this technique can be considered a potential alternative to the conventional standard methods having obtained very promising results.

Um modelo de medição e gestão de desempenho para as universidades públicas

Nas últimas décadas as instituições de ensino superior têm sido alvo de uma pressão crescente para aumentar a sua eficiência e a sua eficácia. Fatores como a diversificação da oferta formativa, a massificação, o aumento da internacionalização, entre outros, conduziram a uma maior monitorização das instituições e, por sua vez, geraram o desenvolvimento de novos sistemas de informação. A constante solicitação de informação, quer pelo Estado, quer pelo mercado constitui a base para a definição do objetivo desta investigação: construir um modelo integrado de medição e gestão de desempenho para as universidades públicas e testá-lo no universo português. Para a construção conceptual deste modelo foi realizada uma revisão da literatura baseada em diferentes contextos: organizacional, europeu e nacional. Este modelo foi depois aplicado às universidades públicas portuguesas recorrendo a dados disponibilizados por entidades públicas, tendo em conta a área de educação e formação (CNAEF). Uma análise descritiva aos dados constituiu uma contribuição desta investigação para a prática, no sentido de que permitiu fornecer um conjunto de recomendações às universidades e às entidades oficiais responsáveis pela recolha de dados a nível nacional, relativamente aos sistemas de informação e processos de recolha de dados. O modelo proposto constitui a contribuição teórica desta investigação, no sentido de que integra, no mesmo modelo, as diferentes dimensões de desempenho, a visão dos diferentes stakeholders, quer no contexto do ensino, quer no da investigação, quer no da própria gestão da universidade. A vertente analítica deste modelo, representada pelas diferentes relações entre os grupos de indicadores, foi testada recorrendo à técnica de análise de equações estruturais baseada na variância (nomeadamente Partial Least Squares) em quatro áreas CNAEF. Os resultados demonstraram que o comportamento em termos de medição e gestão de desempenho difere consoante a CNAEF, identificando um maior ajustamento às áreas hard e evidenciando que as áreas soft necessitam de indicadores mais ajustados às suas especificidades.

Parallel implementation of a learning algorithm for multilayer perceptrons using transputers

In this paper the parallelization of a new learning algorithm for multilayer perceptrons, specifically targeted for nonlinear function approximation purposes, is discussed. Each major step of the algorithm is parallelized, a special emphasis being put in the most computationally intensive task, a least-squares solution of linear systems of equations.

Chromatographic analysis and comparison of chemical composition of the samples between olive oils in Europe and some chinese oils

Dissertação de mest., Qualidade em Análises, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2013

Portuguese Citizens’ Support for Democracy: 40 Years after the Carnation Revolution

Forty years after the Carnation Revolution, the relatively young Portuguese democracy is experiencing dramatically low levels of public specific support for democracy. This article tests the leverage of demand-side and supply-side accounts to explain differentials in public satisfaction with democracy. Through ordinary least squares regression analyses that draw on the unique data of the ‘Barometer 40 Years of Democracy in Portugal (2014)’, this articles shows that age cohort, identification with extreme parties, evaluation of the country’s political past, and economic performance are strong correlates of citizens’ specific support for democracy

Identification of meat spoilage by FTIR spectroscopy and neural networks

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid determination of meat spoilage, Fourier transform infrared (FTIR) spectroscopy technique, with the help of advanced learning-based methods, was attempted in this work. FTIR spectra were obtained from the surface of beef samples during aerobic storage at various temperatures, while a microbiological analysis had identified the population of Total viable counts. A fuzzy principal component algorithm has been also developed to reduce the dimensionality of the spectral data. The results confirmed the superiority of the adopted scheme compared to the partial least squares technique, currently used in food microbiology.

PLSR Models for Mechanical Strengths of Concrete Composite Materials Reinforced with Pultrusion Wastes

In this paper, we present two Partial Least Squares Regression (PLSR) models for compressive and flexural strength responses of a concrete composite material reinforced with pultrusion wastes. The main objective is to characterize this cost-effective waste management solution for glass fiber reinforced polymer (GFRP) pultrusion wastes and end-of-life products that will lead, thereby, to a more sustainable composite materials industry. The experiments took into account formulations with the incorporation of three different weight contents of GFRP waste materials into polyester based mortars, as sand aggregate and filler replacements, two waste particle size grades and the incorporation of silane adhesion promoter into the polyester resin matrix in order to improve binder aggregates interfaces. The regression models were achieved for these data and two latent variables were identified as suitable, with a 95% confidence level. This technological option, for improving the quality of GFRP filled polymer mortars, is viable thus opening a door to selective recycling of GFRP waste and its use in the production of concrete-polymer based products. However, further and complementary studies will be necessary to confirm the technical and economic viability of the process.

O papel das agências de rating e a dívida pública portuguesa

Durante as últimas décadas observou-se o crescimento da importância das avaliações fornecidas pelas agências de rating, sendo este um fator decisivo na tomada de decisão dos investidores. Também os emitentes de dívida são largamente afetados pelas alterações das classificações atribuídas por estas agências. Esta investigação pretende, por um lado, compreender se estas agências têm poder para conseguirem influenciar a evolução da dívida pública e qual o seu papel no mercado financeiro. Por outro, pretende compreender quais os fatores determinantes da dívida pública portuguesa, bem como a realização de uma análise por percentis com o objetivo de lhe atribuir um rating. Para a análise dos fatores que poderão influenciar a dívida pública, a metodologia utilizada é uma regressão linear múltipla estimada através do Método dos Mínimos Quadrados (Ordinary Least Squares – OLS), em que num cenário inicial era composta por onze variáveis independentes, sendo a dívida pública a variável dependente, para um período compreendido entre 1996 e 2013. Foram realizados vários testes ao modelo inicial, com o objetivo de encontrar um modelo que fosse o mais explicativo possível. Conseguimos ainda identificar uma relação inversa entre o rating atribuído por estas agências e a evolução da dívida pública, no sentido em que para períodos em que o rating desce, o crescimento da dívida é mais acentuado. Não nos foi, no entanto, possível atribuir um rating à dívida pública através de uma análise de percentis.

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Production of polyhydroxyalkanoates from oil-containing substrates

Different oil-containing substrates, namely, used cooking oil (UCO), fatty acids-byproduct from biodiesel production (FAB) and olive oil deodorizer distillate (OODD) were tested as inexpensive carbon sources for the production of polyhydroxyalkanoates (PHA) using twelve bacterial strains, in batch experiments. The OODD and FAB were exploited for the first time as alternative substrates for PHA production. Among the tested bacterial strains, Cupriavidus necator and Pseudomonas resinovorans exhibited the most promising results, producing poly-3-hydroxybutyrate, P(3HB), form UCO and OODD and mcl-PHA mainly composed of 3-hydroxyoctanoate (3HO) and 3-hydroxydecanoate (3HD) monomers from OODD, respectively. Afterwards, these bacterial strains were cultivated in bioreactor. C. necator were cultivated in bioreactor using UCO as carbon source. Different feeding strategies were tested for the bioreactor cultivation of C. necator, namely, batch, exponential feeding and DO-stat mode. The highest overall PHA productivity (12.6±0.78 g L-1 day-1) was obtained using DO-stat mode. Apparently, the different feeding regimes had no impact on polymer thermal properties. However, differences in polymer‟s molecular mass distribution were observed. C. necator was also tested in batch and fed-batch modes using a different type of oil-containing substrate, extracted from spent coffee grounds (SCG) by super critical carbon dioxide (sc-CO2). Under fed-batch mode (DO-stat), the overall PHA productivity were 4.7 g L-1 day-1 with a storage yield of 0.77 g g-1. Results showed that SCG can be a bioresource for production of PHA with interesting properties. Furthermore, P. resinovorans was cultivated using OODD as substrate in bioreactor under fed-batch mode (pulse feeding regime). The polymer was highly amorphous, as shown by its low crystallinity of 6±0.2%, with low melting and glass transition temperatures of 36±1.2 and -16±0.8 ºC, respectively. Due to its sticky behavior at room temperature, adhesiveness and mechanical properties were also studied. Its shear bond strength for wood (67±9.4 kPa) and glass (65±7.3 kPa) suggests it may be used for the development of biobased glues. Bioreactor operation and monitoring with oil-containing substrates is very challenging, since this substrate is water immiscible. Thus, near-infrared spectroscopy (NIR) was implemented for online monitoring of the C. necator cultivation with UCO, using a transflectance probe. Partial least squares (PLS) regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18 g L-1, 2.37 g L-1 and 1.58 g L-1 for biomass, UCO and PHA, respectively, which indicates the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control. UCO and OODD are low cost substrates with potential to be used in PHA batch and fed-batch production. The use of NIR in this bioprocess also opened an opportunity for optimization and control of PHA production process.