Híbridos orgânicos-inorgânicos para aplicações de baixo custo em óptica integrada

O objectivo desta tese é a utilização de materiais híbridos orgânicos-inorgânicos, designados por di-ureiasis modificados pela adição de tetra-propóxido de zircónio (Zr(i-OPr)4) estabilizado com ácido metacrílico (CH2=C(CH3)COOH), obtidos pela via sol-gel, para aplicações em dispositivos ópticos integrados de baixo custo. A estrutura local dos di-ureiasis com diferentes concentrações de propóxido de zircónio (20 a 80 % mol) foi estudada por difracção de raios-X, espalhamento de raios X a baixos ângulos, microscopia de força atómica, ressonância magnética nuclear dos núcleos dos átomos de 29Si e 13C, espectroscopia no infravermelho por transformada de Fourier, espectroscopia de Raman por transformada de Fourier e termogravimetria. A influência dos parâmetros de síntese, concentração de tetra propóxido de zircónio e rácio tetra propóxido de zircónio: ácido metacrilico na estrutura e propriedades das amostras em monólito e filmes finos (depositados pela técnica de deposição por rotação do substrato) foram avaliadas, permitindo obter amostras transparentes, fotopolimerizáveis e estáveis termicamente até aos 100 ºC. Foram determinadas as propriedades dos guias planares em substratos de vidro borosilicato e silício oxidado (1spectral livre de 16,5 e 35,5 GHz. A actuação termo-óptica de uma estrutura do tipo Mach-Zhender simétrica conduziu a uma atenuação do sinal óptico de 7,5 dB.

Spectral characterization of families of split graphs

An upper bound for the sum of the squares of the entries of the principal eigenvector corresponding to a vertex subset inducing a k-regular subgraph is introduced and applied to the determination of an upper bound on the order of such induced subgraphs. Furthermore, for some connected graphs we establish a lower bound for the sum of squares of the entries of the principal eigenvector corresponding to the vertices of an independent set. Moreover, a spectral characterization of families of split graphs, involving its index and the entries of the principal eigenvector corresponding to the vertices of the maximum independent set is given. In particular, the complete split graph case is highlighted.

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.

Evaluation of the matabolic response of osteosarcoma cells to conventional and new anticancer drugs by NMR metabolomics

The main scope of this work was to evaluate the metabolic effects of anticancer agents (three conventional and one new) in osteosarcoma (OS) cells and osteoblasts, by measuring alterations in the metabolic profile of cells by nuclear magnetic resonance (NMR) spectroscopy metabolomics. Chapter 1 gives a theoretical framework of this work, beginning with the main metabolic characteristics that globally describe cancer as well as the families and mechanisms of action of drugs used in chemotherapy. The drugs used nowadays to treat OS are also presented, together with the Palladium(II) complex with spermine, Pd2Spm, potentially active against cancer. Then, the global strategy for cell metabolomics is explained and the state of the art of metabolomic studies that analyze the effect of anticancer agents in cells is presented. In Chapter 2, the fundamentals of the analytical techniques used in this work, namely for biological assays, NMR spectroscopy and multivariate and statistical analysis of the results are described. A detailed description of the experimental procedures adopted throughout this work is given in Chapter 3. The biological and analytical reproducibility of the metabolic profile of MG-63 cells by high resolution magic angle spinning (HRMAS) NMR is evaluated in Chapter 4. The metabolic impact of several factors (cellular integrity, spinning rate, temperature, time and acquisition parameters) on the 1H HRMAS NMR spectral profile and quality is analysed, enabling the definition of the best acquisition parameters for further experiments. The metabolic consequences of increasing number of passages in MG-63 cells as well as the duration of storage are also investigated. Chapter 5 describes the metabolic impact of drugs conventionally used in OS chemotherapy, through NMR metabolomics studies of lysed cells and aqueous extracts analysis. The results show that MG-63 cells treated with cisplatin (cDDP) undergo a strong up-regulation of lipid contents, alterations in phospholipid constituents (choline compounds) and biomarkers of DNA degradation, all associated with cell death by apoptosis. Cells exposed to doxorubicin (DOX) or methotrexate (MTX) showed much slighter metabolic changes, without any relevant alteration in lipid contents. However, metabolic changes associated with altered Krebs cycle, oxidative stress and nucleotides metabolism were detected and were tentatively interpreted at the light of the known mechanisms of action of these drugs. The metabolic impact of the exposure of MG-63 cells and osteoblasts to cDDP and the Pd2Spm complex is described in Chapter 6. Results show that, despite the ability of the two agents to bind DNA, the metabolic consequences that arise from exposure to them are distinct, namely in what concerns to variation in lipid contents (absent for Pd2Spm). Apoptosis detection assays showed that, differently from what was seen for MG-63 cells treated with cDDP, the decreased number of living cells upon exposure to Pd2Spm was not due to cell death by apoptosis or necrosis. Moreover, the latter agent induces more marked alterations in osteoblasts than in cancer cells, while the opposite seemed to occur upon cDDP exposure. Nevertheless, the results from MG-63 cells exposure to combination regimens with cDDP- or Pd2Spm-based cocktails, described in Chapter 7, revealed that, in combination, the two agents induce similar metabolic responses, arising from synergy mechanisms between the tested drugs. Finally, the main conclusions of this thesis are summarized in Chapter 8, and future perspectives in the light of this work are presented.