Pregnancy and newborns disorders followed by urine metabolomics

Chapter 1 introduces the scope of the work by identifying the clinically relevant prenatal disorders and presently available diagnostic methods. The methodology followed in this work is presented, along with a brief account of the principles of the analytical and statistical tools employed. A thorough description of the state of the art of metabolomics in prenatal research concludes the chapter, highlighting the merit of this novel strategy to identify robust disease biomarkers. The scarce use of maternal and newborn urine in previous reports enlightens the relevance of this work. Chapter 2 presents a description of all the experimental details involved in the work performed, comprising sampling, sample collection and preparation issues, data acquisition protocols and data analysis procedures. The proton Nuclear Magnetic Resonance (NMR) characterization of maternal urine composition in healthy pregnancies is presented in Chapter 3. The urinary metabolic profile characteristic of each pregnancy trimester was defined and a 21-metabolite signature found descriptive of the metabolic adaptations occurring throughout pregnancy. 8 metabolites were found, for the first time to our knowledge, to vary in connection to pregnancy, while known metabolic effects were confirmed. This chapter includes a study of the effects of non-fasting (used in this work) as a possible confounder. Chapter 4 describes the metabolomic study of 2nd trimester maternal urine for the diagnosis of fetal disorders and prediction of later-developing complications. This was achieved by applying a novel variable selection method developed in the context of this work. It was found that fetal malformations (FM) (and, specifically those of the central nervous system, CNS) and chromosomal disorders (CD) (and, specifically, trisomy 21, T21) are accompanied by changes in energy, amino acids, lipids and nucleotides metabolic pathways, with CD causing a further deregulation in sugars metabolism, urea cycle and/or creatinine biosynthesis. Multivariate analysis models´ validation revealed classification rates (CR) of 84% for FM (87%, CNS) and 85% for CD (94%, T21). For later-diagnosed preterm delivery (PTD), preeclampsia (PE) and intrauterine growth restriction (IUGR), it is found that urinary NMR profiles have early predictive value, with CRs ranging from 84% for PTD (11-20 gestational weeks, g.w., prior to diagnosis), 94% for PE (18-24 g.w. pre-diagnosis) and 94% for IUGR (2-22 g.w. pre-diagnosis). This chapter includes results obtained for an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) study of pre-PTD samples and correlation with NMR data. One possible marker was detected, although its identification was not possible. Chapter 5 relates to the NMR metabolomic study of gestational diabetes mellitus (GDM), establishing a potentially predictive urinary metabolic profile for GDM, 2-21 g.w. prior to diagnosis (CR 83%). Furthermore, the NMR spectrum was shown to carry information on individual phenotypes, able to predict future insulin treatment requirement (CR 94%). Chapter 6 describes results that demonstrate the impact of delivery mode (CR 88%) and gender (CR 76%) on newborn urinary profile. It was also found that newborn prematurity, respiratory depression, large for gestational age growth and malformations induce relevant metabolic perturbations (CR 82-92%), as well as maternal conditions, namely GDM (CR 82%) and maternal psychiatric disorders (CR 91%). Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the value of maternal or newborn urine metabolomics for pregnancy monitoring and disease prediction, towards the development of new early and non-invasive diagnostic methods.

Contributos para a eficácia do clustering usando o tagging social

Nos últimos anos temos vindo a assistir a uma mudança na forma como a informação é disponibilizada online. O surgimento da web para todos possibilitou a fácil edição, disponibilização e partilha da informação gerando um considerável aumento da mesma. Rapidamente surgiram sistemas que permitem a coleção e partilha dessa informação, que para além de possibilitarem a coleção dos recursos também permitem que os utilizadores a descrevam utilizando tags ou comentários. A organização automática dessa informação é um dos maiores desafios no contexto da web atual. Apesar de existirem vários algoritmos de clustering, o compromisso entre a eficácia (formação de grupos que fazem sentido) e a eficiência (execução em tempo aceitável) é difícil de encontrar. Neste sentido, esta investigação tem por problemática aferir se um sistema de agrupamento automático de documentos, melhora a sua eficácia quando se integra um sistema de classificação social. Analisámos e discutimos dois métodos baseados no algoritmo k-means para o clustering de documentos e que possibilitam a integração do tagging social nesse processo. O primeiro permite a integração das tags diretamente no Vector Space Model e o segundo propõe a integração das tags para a seleção das sementes iniciais. O primeiro método permite que as tags sejam pesadas em função da sua ocorrência no documento através do parâmetro Social Slider. Este método foi criado tendo por base um modelo de predição que sugere que, quando se utiliza a similaridade dos cossenos, documentos que partilham tags ficam mais próximos enquanto que, no caso de não partilharem, ficam mais distantes. O segundo método deu origem a um algoritmo que denominamos k-C. Este para além de permitir a seleção inicial das sementes através de uma rede de tags também altera a forma como os novos centróides em cada iteração são calculados. A alteração ao cálculo dos centróides teve em consideração uma reflexão sobre a utilização da distância euclidiana e similaridade dos cossenos no algoritmo de clustering k-means. No contexto da avaliação dos algoritmos foram propostos dois algoritmos, o algoritmo da “Ground truth automática” e o algoritmo MCI. O primeiro permite a deteção da estrutura dos dados, caso seja desconhecida, e o segundo é uma medida de avaliação interna baseada na similaridade dos cossenos entre o documento mais próximo de cada documento. A análise de resultados preliminares sugere que a utilização do primeiro método de integração das tags no VSM tem mais impacto no algoritmo k-means do que no algoritmo k-C. Além disso, os resultados obtidos evidenciam que não existe correlação entre a escolha do parâmetro SS e a qualidade dos clusters. Neste sentido, os restantes testes foram conduzidos utilizando apenas o algoritmo k-C (sem integração de tags no VSM), sendo que os resultados obtidos indicam que a utilização deste algoritmo tende a gerar clusters mais eficazes.

Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

Understanding and modelling hydrological and soil erosion processes in burnt forest catchments

Forest fires implications in overland flow and soil erosion have been researched for several years. Therefore, is widely known that fires enhance hydrological and geomorphological activity worldwide as also in Mediterranean areas. Soil burn severity has been widely used to describe the impacts of fire on soils, and has being recognized as a decisive factor controlling post-fire erosion rates. However, there is no unique definition of the term and the relationship between soil burn severity and post-fire hydrological and erosion response has not yet been fully established. Few studies have assessed post-fire erosion over multiple years, and the authors are aware of none which assess runoff. Small amount of studies concerning pre-fire management practices were also found. In the case of soil erosion models, the Revised Universal Soil Loss Equation (RUSLE) and the revised Morgan–Morgan–Finney (MMF) are well-known models, but not much information is available as regards their suitability in predicting post-fire soil erosion in forest soils. The lack of information is even more pronounced as regards post-fire rehabilitation treatments. The aim of the thesis was to perform an extensive research under the post fire hydrologic and erosive response subject. By understanding the effect of burn severity in ecosystems and its implications regarding post fire hydrological and erosive responses worldwide. Test the effect of different pre-fire land management practices (unplowed, downslope plowed and contour plowed) and time-since-fire, in the post fire hydrological and erosive response, between the two most common land uses in Portugal (pine and eucalypt). Assess the performance of two widely-known erosion models (RUSLE and Revised MMF), to predict soil erosion rates during first year following two wildfires of distinctive burn severity. Furthermore, to apply these two models considering different post-fire rehabilitation treatments in an area severely affected by fire. Improve model estimations of post-fire runoff and erosion rates in two different land uses (pine and eucalypt) using the revised MMF. To assess these improvements by comparing estimations and measurements of runoff and erosion, in two recently burned sites, as also with their post fire rehabilitation treatments. Model modifications involved: (1) focusing on intra-annual changes in parameters to incorporate seasonal differences in runoff and erosion; and (2) inclusion of soil water repellency in runoff predictions. Additionally, validate these improvements with the application of the model to other pine and eucalypt sites in Central Portugal. The review and meta-analysis showed that fire occurrence had a significant effect on the hydrological and erosive response. However, this effect was only significantly higher with increasing soil burn severity for inter-rill erosion, and not for runoff. This study furthermore highlighted the incoherencies between existing burn severity classifications, and proposed an unambiguous classification. In the case of the erosion plots with natural rainfall, land use factor affected annual runoff while land management affected both annual runoff and erosion amounts significantly. Time-since-fire had an important effect in erosion amounts among unplowed sites, while for eucalypt sites time affected both annual runoff and erosion amounts. At all studied sites runoff coefficients increase over the four years of monitoring. In the other hand, sediment concentration in the runoff, recorded a decrease during the same period. Reasons for divergence from the classic post-fire recovery model were also explored. Short fire recurrence intervals and forest management practices are viewed as the main reasons for the observed severe and continuing soil degradation. The revised MMF model presented reasonable accuracy in the predictions while the RUSLE clearly overestimated the observed erosion rates. After improvements: the revised model was able to predict first-year post-fire plot-scale runoff and erosion rates for both forest types, these predictions were improved both by the seasonal changes in the model parameters; and by considering the effect of soil water repellency on the runoff, individual seasonal predictions were considered accurate, and the inclusion of the soil water repellency in the model also improved the model at this base. The revised MMF model proved capable of providing a simple set of criteria for management decisions about runoff and erosion mitigation measures in burned areas. The erosion predictions at the validation sites attested both to the robustness of the model and of the calibration parameters, suggesting a potential wider application.

Channel modelling for MIMO systems

Systems equipped with multiple antennas at the transmitter and at the receiver, known as MIMO (Multiple Input Multiple Output) systems, offer higher capacities, allowing an efficient exploitation of the available spectrum and/or the employment of more demanding applications. It is well known that the radio channel is characterized by multipath propagation, a phenomenon deemed problematic and whose mitigation has been achieved through techniques such as diversity, beamforming or adaptive antennas. By exploring conveniently the spatial domain MIMO systems turn the characteristics of the multipath channel into an advantage and allow creating multiple parallel and independent virtual channels. However, the achievable benefits are constrained by the propagation channel’s characteristics, which may not always be ideal. This work focuses on the characterization of the MIMO radio channel. It begins with the presentation of the fundamental results from information theory that triggered the interest on these systems, including the discussion of some of their potential benefits and a review of the existing channel models for MIMO systems. The characterization of the MIMO channel developed in this work is based on experimental measurements of the double-directional channel. The measurement system is based on a vector network analyzer and a two-dimensional positioning platform, both controlled by a computer, allowing the measurement of the channel’s frequency response at the locations of a synthetic array. Data is then processed using the SAGE (Space-Alternating Expectation-Maximization) algorithm to obtain the parameters (delay, direction of arrival and complex amplitude) of the channel’s most relevant multipath components. Afterwards, using a clustering algorithm these data are grouped into clusters. Finally, statistical information is extracted allowing the characterization of the channel’s multipath components. The information about the multipath characteristics of the channel, induced by existing scatterers in the propagation scenario, enables the characterization of MIMO channel and thus to evaluate its performance. The method was finally validated using MIMO measurements.

Development of infrared spectroscopy for assessing bacterial quality in foods

Rapid and specific detection of foodborne bacteria that can cause food spoilage or illness associated to its consumption is an increasingly important task in food industry. Bacterial detection, identification, and classification are generally performed using traditional methods based on biochemical or serological tests and the molecular methods based on DNA or RNA fingerprints. However, these methodologies are expensive, time consuming and laborious. Infrared spectroscopy is a reliable, rapid, and economic technique which could be explored as a tool for bacterial analysis in the food industry. In this thesis it was evaluated the potential of IR spectroscopy to study the bacterial quality of foods. In Chapter 2, it was developed a calibration model that successfully allowed to predict the bacterial concentration of naturally contaminated cooked ham samples kept at refrigeration temperature during 8 days. In this part, it was developed the methodology that allowed the best reproducibility of spectra from bacteria colonies with minimal sample preparation, which was used in the subsequent work. Several attempts trying different resolutions and number of scans in the IR were made. A spectral resolution of 4 cm-1, with 32 scans were the settings that allowed the best results. Subsequently, in Chapter 3, it was made an attempt to identify 22 different foodborne bacterial genera/species using IR spectroscopy coupled with multivariate analysis. The principal component analysis, used as an exploratory technique, allowed to form distinct groups, each one corresponding to a different genus, in most of the cases. Then, a hierarchical cluster analysis was performed to further analyse the group formation and the possibility of distinction between species of the same bacterial genus. It was observed that IR spectroscopy not only is suitable to the distinction of the different genera, but also to differentiate species of the same genus, with the simultaneous use of principal component analysis and cluster analysis techniques. The utilization of IR spectroscopy and multivariate statistical analysis were also investigated in Chapter 4, in order to confirm the presence of Listeria monocytogenes and Salmonella spp. isolated from contaminated foods, after growth in selective medium. This would allow to substitute the traditional biochemical and serological methods that are used to confirm these pathogens and that delay the obtainment of the results up to 2 days. The obtained results allowed the distinction of 3 different Listeria species and the distinction of Salmonella spp. from other bacteria that can be mistaken with them. Finally, in chapter 5, high pressure processing, an emerging methodology that permits to produce microbiologically safe foods and extend their shelf-life, was applied to 12 foodborne bacteria to determine their resistance and the effects of pressure in cells. A treatment of 300 MPa, during 15 minutes at room temperature was applied. Gram-negative bacteria were inactivated to undetectable levels and Gram-positive showed different resistances. Bacillus cereus and Staphylococcus aureus decreased only 2 logs and Listeria innocua decreased about 5 logs. IR spectroscopy was performed in bacterial colonies before and after HPP in order to investigate the alterations of the cellular compounds. It was found that high pressure alters bands assigned to some cellular components as proteins, lipids, oligopolysaccharides, phosphate groups from the cell wall and nucleic acids, suggesting disruption of the cell envelopes. In this work, bacterial quantification and classification, as well as assessment of cellular compounds modification with high pressure processing were successfully performed. Taking this into account, it was showed that IR spectroscopy is a very promising technique to analyse bacteria in a simple and inexpensive manner.

Application of LOICZ DPSIR framework to South asia Basins and developing typology for coastal vulnerability in South Asia

Dissertação de Mestrado, Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2007

Seasonal and storm induced morphological variations at praia de Faro, península do Ancão, southern Portugal

Dissertação de Mestrado, Estudos Marinhos e Costeiros, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2009

Aplicação de técnicas de vídeo subaquático na caracterização de biocenoses marinhas

Dissertação mest., Biologia Marinha - Ecologia e Conservação Marinha, Universidade do Algarve, 2008

Identificação das características dos clientes associadas ao risco de crédito

O processo da tomada de decisão sobre a avaliação de uma solicitação de crédito comercial é por vezes difícil para o julgamento humano, devido à imensidão de variáveis que estão em jogo e das suas inter- relações. Neste artigo propomo-nos identificar as características dos clientes associadas a alto e a baixo risco, com recurso a um modelo aplicacional. A partir de uma base de dados de um cartão de crédito, formada por variáveis de natureza qualitativa e quantitativa, ajustámos um modelo logit binário, com o objectivo de tornar o processo de decisão mais objectivo e quantificável. Em seguida, identificámos oito classes de risco através da aplicação de um método de classificação não hierárquica (K-means) sobre o vector da pontuação do modelo logit. Aferimos temporalmente o comportamento de cada classe de risco ao longo de 70 meses, verificando-se que probabilidades baixas de default estão associadas a classes de risco baixo. As características dos clientes tipicamente associadas ao risco de crédito foram identificadas através de uma Análise Factorial das Correspondências.

Da memória do povo - Recolha de literatura popular da tradição oral do Concelho de Portimão

Margarida Tengarrinha oferece - nos, nesta obra, um leque bastante diversificado do património, adentro das “artes da fala”, correndo nas memórias do povo do concelho de Portimão. O fruto da sua recolecção, os “textos” que recebeu, transcreveu e estudou, é aqui editado com uma valência, cremos,, primeiro que tudo pedagógica. Assim, os textos agrupam - se por “manchas de leitura” com uma coerência interna aglutinadora, aparecendo ordenados sob uma classificação entre formal — segundo os “géneros”, como “contos” , “lendas”, “romances”, “orações”, por exemplo — e temática — por “fundos de sentido” semantizados nas comunicações: “bruxas e bruxedos”, “benzeduras, mezinhas, maldições e superstições”, “poesias maliciosas”, por exemplo.

Spectral analysis of embolic signals

Tese de dout., Engenharia Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2005

Recuperação e valorização de lagoas em zonas húmidas: o caso da Lagoa dos Salgados

Dissertação de mest., Arquitectura Paisagista, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011

Contributo para o estudo da literatura oral no Algarve

Dissertação de mest., Promoção e Mediação da Leitura, Faculdade de Ciências Humanas e Sociais, Univ. do Algarve, 2012

Beach quality assessment and management in the Sotavento (Eastern) Algarve, Portugal

The purpose of this study on beach quality assessment and management was to evaluate the quality of five beaches in the Algarve Sotavento region of Portugal and to identify beach users’ preferences and priorities regarding their visit to a beach. The Algarve is one of the country’s most internationally known regions and it is generally perceived as a major tourist destination. Because of the increasing level of tourists, there is a specific need to address beach quality, as overcrowding can result in excessive litter, reduce water quality and consequently reduce the socio-economic value of the area. The main methodology for the evaluation of the beach quality in this pilot project was the Bathing Area Registration and Evaluation framework (BARE), which recognizes five beach types (rural, remote, resort, urban and village) through five main priority issues of concern to beach users (water quality, scenery, litter, safety, facilities) and evaluates the beach quality, ranging from one (low) to five (high) stars. After overall bathing area classification, Quarteira-Vilamoura, Ilha do Farol, Ilha Deserta and Ilha da Armona received three-star rating and Quinta do Lago site obtained a one-star rating. The quantitative research data on beach users’ preferences and priorities was obtained through administration of 50 questionnaires per beach and showed that beach users at all sites expressed the need for improved cleanliness, safety and facilities on the beach. The BARE framework, together with the questionnaire surveys, allowed the identification of management priorities required to improve the quality of individual beaches and therefore increase income from tourism.