3 resultados para Resistencia insulina

em Repositório Institucional da Universidade de Aveiro - Portugal


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A glicosilação não-enzimática e o stress oxidativo representam dois processos importantes visto desempenharem um papel importante no que respeita às complicações de vários processos patofisiológicos. No presente, a associação entre a glicosilação não-enzimática e a oxidação de proteínas é reconhecida como sendo um dos principais responsáveis pela acumulação de proteínas não-funcionais que, por sua vez, promove uma contínua sensibilização para um aumento do stress oxidativo ao nível celular. Embora esteja disponível bastante informação no que respeita aos dois processos e suas consequências ao nível estrutural e funcional, permanecem questões por esclarecer acerca do que se desenvolve ao nível molecular. Com o objectivo de contribuir para uma melhor compreensão da relação entre a glicosilação não-enzimática e a oxidação, proteínas modelo (albumina, insulina e histonas H2B e H1) foram submetidas a sistemas in vitro de glicosilação não-enzimática e oxidação em condições controladas e durante um período de tempo específico. A identificação dos locais de glicosilação e oxidação foi realizada através de uma abordagem proteómica, na qual após digestão enzimática se procedeu à análise por cromatografia líquida acoplada a espectrometria de massa tandem (MALDI-TOF/TOF). Esta abordagem permitiu a obtenção de elevadas taxas de cobertura das sequências proteicas, permitindo a identificação dos locais preferenciais de glicosilação e oxidação nas diferentes proteínas estudadas. Como esperado, os resíduos de lisina foram os preferencialmente glicosilados. No que respeita à oxidação, além das modificações envolvendo hidroxilações e adições de oxigénio, foram identificadas deamidações, carbamilações e conversões oxidativas específicas de vários aminoácidos. No geral, os resíduos mais afectados pela oxidação foram os resíduos de cisteína, metionina, triptofano, tirosina, prolina, lisina e fenilalanina. Ao longo do período de tempo estudado, os resultados indicaram que a oxidação teve início em zonas expostas da proteína e/ou localizadas na vizinhança de resíduos de cisteína e metionina, ao invés de exibir um comportamente aleatório, ocorrendo de uma forma nãolinear por sua vez dependente da estabilidade conformacional da proteína. O estudo ao longo do tempo mostrou igualmente que, no caso das proteínas préglicosiladas, a oxidação das mesmas ocorreu de forma mais rápida e acentuada, sugerindo que as alterações estruturais induzidas pela glicosilação promovem um estado pro-oxidativo. No caso das proteínas pré-glicosiladas e oxidadas, foi identificado um maior número de modificações oxidativas assim como de resíduos modificados na vizinhança de resíduos glicosilados. Com esta abordagem é realizada uma importante contribuição na investigação das consequências do dano ‘glico-oxidativo’ em proteínas ao nível molecular através da combinação da espectrometria de massa e da bioinformática.

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Estrogens, such as 17β-estradiol (E2) are essential for normal growth and differentiation of the mammary gland. There are two estrogen receptors (ERs), ERα and ERβ which are ligand activated transcription factors. ERα stimulates proliferation and is the single most powerful predictor of breast cancer prognosis and since 70% of breast cancers express ERα, strategies to block this receptor are the primary breast cancer treatment. Unlike ERα, the role of ERβ in breast cancer and its potential as alternative therapeutic target remains controversial, mainly due to the lack of correlation between results obtained in vitro and epidemiological studies. The aim of this thesis was to increase our understanding of the molecular and cellular mechanisms of estrogen signaling in normal and cancerous cells, in different cellular contexts and with focus on ERβ. In Paper I we characterized the effect of the flavone PD098059 - which is a commonly used MEK1 inhibitor - on activation of transcription by ERα and ERβ. We found that the estrogenic effect of PD098059 is dose dependent in concentrations ranging from 1 – 10 μM and that activation of transcription by ER is suppressed by the inhibitory effect of PD98059 on MEK1 at concentrations above 50 μM. In agreement with its flavone nature, PD098059 had a much stronger effect on ERβ than on ERα transcriptional activity. Therefore, use of this compound for the study of signalling events in cells expressing ER should be carefully considered. In Paper II we assessed the effect of ERβ agonists in vivo and administered under different conditions in vitro. In basal conditions, ERβ induced apoptosis; however, in vivo ERβ agonists stimulated proliferation and inhibited apoptosis. In vivo effects were reproduced in culture, by activation of MAPK/ERK½ pathway with epidermal growth factor or basement membrane extract. In addition, insulin signalling and PI3-K/AKT activation was necessary for stimulation of proliferation. These results suggest that the cellular context modulates ERβ activity. Manuscript presents preliminary work aimed at the set-up of a methodological strategy to isolate ERs and to identify interacting proteins in different cellular contexts and which could modulate the bi-phased effects of ERβ in cell growth. In conclusion, the studies presented in this thesis contribute to clarify the apparent contradictory information regarding ERβ function in normal and cancerous mammary epithelium and suggest that the cellular context should be considered when ERβ effects are studied.

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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.