Tracing coastal organic enrichment: stable isotopes and biotic indices

Neste trabalho foi efectuada uma avaliação integrada usando descritores sedimentares e biológicos ao nível da espécie e da comunidade e índices bióticos de síntese para o traçamento do enriquecimento orgânico numa região, com características dispersivas, da costa Oeste de Portugal. Na área estudada existem gradientes ambientais e biológicos relacionados com a heterogeneidade da paisagem sedimentar, a qual inclui sedimentos desde areias finas limpas a vasas. Contudo, na área próxima do emissário, esta paisagem é mais homogénea e constituída por areia fina com baixo teor em finos. Nesta região, alguns dos descritores estudados deram uma indicação coerente de alterações ambientais associadas ao enriquecimento orgânico. O potencial de oxidação - redução mostrou valores negativos até 250 m do emissário, o que indicia que a degradação da matéria orgânica que entra no sistema cria condições reduzidas no sedimento. Os isótopos estáveis de carbono e azoto no sedimento diferenciam a área mais próxima do emissário, que apresenta uma depleção de acordo com uma origem terrestre da matéria orgânica naquela parte da plataforma. Uma imagem similar foi obtida pela análise dos isótopos estáveis na macrofauna que diagnosticou a origem terrestre da matéria orgânica consumida. A composição específica e a abundância das comunidades bentónicas também são significativamente diferentes junto ao emissário, onde são dominadas por espécies oportunistas, tolerantes ao enriquecimento orgânico. No entanto, os índices bióticos em validação no âmbito da implementação da Directiva Quadro da Água, não foram eficientes a mostrar as alterações bentónicas associadas ao enriquecimento orgânico apesar de alguns índices se basearem nos limiares de tolerância/sensibilidade a este tipo de perturbação. Apesar deste caso de estudo reflectir um enriquecimento orgânico moderado, uma vez que não foram detectadas alterações sedimentares ou acumulação de matéria orgânica, nem um significativo empobrecimento das comunidades biológicas junto ao emissário, a análise ao nível dos índices bióticos de síntese pode levar à perda de informação essencial e, portanto, prejudicar a nossa capacidade de diagnóstico devendo ser usados com cuidado. A análise do conjunto de dados da composição específica forneceu uma imagem mais precisa da perturbação ambiental e descritores específicos, tais como os isótopos estáveis, permitiram uma melhor compreensão da extensão espacial do enriquecimento orgânico.

Radiological imaging in digital systems: the effect of exposure parameters in diagnostic quality and patient dose

Esta tese pretende contribuir para o estudo e análise dos factores relacionados com as técnicas de aquisição de imagens radiológicas digitais, a qualidade diagnóstica e a gestão da dose de radiação em sistema de radiologia digital. A metodologia encontra-se organizada em duas componentes. A componente observacional, baseada num desenho do estudo de natureza retrospectiva e transversal. Os dados recolhidos a partir de sistemas CR e DR permitiram a avaliação dos parâmetros técnicos de exposição utilizados em radiologia digital, a avaliação da dose absorvida e o índice de exposição no detector. No contexto desta classificação metodológica (retrospectiva e transversal), também foi possível desenvolver estudos da qualidade diagnóstica em sistemas digitais: estudos de observadores a partir de imagens arquivadas no sistema PACS. A componente experimental da tese baseou-se na realização de experiências em fantomas para avaliar a relação entre dose e qualidade de imagem. As experiências efectuadas permitiram caracterizar as propriedades físicas dos sistemas de radiologia digital, através da manipulação das variáveis relacionadas com os parâmetros de exposição e a avaliação da influência destas na dose e na qualidade da imagem. Utilizando um fantoma contrastedetalhe, fantomas antropomórficos e um fantoma de osso animal, foi possível objectivar medidas de quantificação da qualidade diagnóstica e medidas de detectabilidade de objectos. Da investigação efectuada, foi possível salientar algumas conclusões. As medidas quantitativas referentes à performance dos detectores são a base do processo de optimização, permitindo a medição e a determinação dos parâmetros físicos dos sistemas de radiologia digital. Os parâmetros de exposição utilizados na prática clínica mostram que a prática não está em conformidade com o referencial Europeu. Verifica-se a necessidade de avaliar, melhorar e implementar um padrão de referência para o processo de optimização, através de novos referenciais de boa prática ajustados aos sistemas digitais. Os parâmetros de exposição influenciam a dose no paciente, mas a percepção da qualidade de imagem digital não parece afectada com a variação da exposição. Os estudos que se realizaram envolvendo tanto imagens de fantomas como imagens de pacientes mostram que a sobreexposição é um risco potencial em radiologia digital. A avaliação da qualidade diagnóstica das imagens mostrou que com a variação da exposição não se observou degradação substancial da qualidade das imagens quando a redução de dose é efectuada. Propõe-se o estudo e a implementação de novos níveis de referência de diagnóstico ajustados aos sistemas de radiologia digital. Como contributo da tese, é proposto um modelo (STDI) para a optimização de sistemas de radiologia digital.

Calibration and validation of hydrodynamic, salt and heat transport models for Ria de Aveiro lagoon (Portugal)

Ria deAveiro is a very complex shallow water coastal lagoon located on the northwest of Portugal. Important issues would be left unanswered without a good understanding of hydrodynamic and transport processes occurring in the lagoon. Calibration and validation of hydrodynamic, salt and heat transport models for Ria de Aveiro lagoon are presented. The calibration of the hydrodynamic model was performed adjusting the bottom friction coefficient, through the comparison between measured and predicted time series of sea surface elevation for 22 stations. Harmonic analysis was performed in order to evaluate the model's accuracy. To validate the hydrodynamic model measured and predicted SSE values were compared for 11 stations, as well as main flow direction velocities for 10 stations. The salt and heat transport models were calibrated comparing measured and predicted time series of salinity and water temperature for 7 stations, and the RMS of the difference between the series was determined. These models were validated comparing the model results with an independent field data set. The hydrodynamic and the salt and heat transport models for Ria de Aveiro were successfully calibrated and validated. They reproduce accurately the barotropic flows and can therefore adequately represent the salt and heat transport and the heat transfer processes occurring in Ria deAveiro.

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.

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.