3 resultados para spectrometry spectra interpretation

em Universidade do Minho


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Since the last two decades mass spectrometry (MS) has been applied to analyse the chemical cellular components of microorganisms, providing rapid and discriminatory proteomic profiles for their species identification and, in some cases, subtyping. The application of MS for the microbial diagnosis is currently well-established. The remarkable reproducibility and objectivity of this method is based on the measurement of constantly expressed and highly abundant proteins, mainly important conservative ribosomal proteins, which are used as markers to generate a cellular fingerprint. Mass spectrometry based on matrix-assisted laser desorption ionization-time of flight (MALDI- TOF) technique has been an important tool for the microbial diagnostic. However, some technical limitation concerning both MALDI-TOF and its used protocols for sample preparation have fostered the research of new mass spectrometry systems (e.g. LC MS/MS). LC MS/MS is able to generate online mass spectra of specific ions with further online sequencing of these ions, which include both specific proteins and DNA fragments. In this work a set of data for yeasts and filamentous fungi diagnostic obtained through an international collaboration project involving partners from Argentina, Brazil, Chile and Portugal will be presented and discussed.

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Charged-particle spectra obtained in 0.15nb−1 of Pb+Pb interactions at sNN−−−√=2.76TeV and 4.2pb−1 of pp interactions at s√=2.76TeV with the ATLAS detector at the LHC are presented in a wide transverse momentum (0.5spectra are presented as a function of collision centrality, which is determined by the response of the forward calorimeter located on both sides of the interaction point. The nuclear modification factors RAA and RCP are presented in detail as function of centrality, pT and η. They show a distinct pT-dependence with a pronounced minimum at about 7GeV. Above 60GeV, RAA is consistent with a plateau at a centrality-dependent value, within the uncertainties. The value is 0.55±0.01(stat.)±0.04(syst.) in the most central collisions. The RAA distribution is consistent with flat |η| dependence over the whole transverse momentum range in all centrality classes.

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The emerging field of lipidomics has identified lipids as key players in disease physiology. Their physicochemical diversity allows precise control of cell structure and signaling events through modulation of membrane prop- erties and trafficking of proteins. As such, lipids are important regulators of brain function and have been implicated in neurodegenerative and mood disorders. Importantly, environmental chronic stress has been associated with anxiety and depression and its exposure in rodents has been extensively used as a model to study these diseases. With the accessibility to modern mass- spectrometry lipidomic platforms, it is now possible to snapshot the extensively interconnected lipid network. Here, we review the fundamentals of lipid biology and outline a framework for the interpretation of lipidomic studies as a new approach to study brain pathophysiology. Thus, lipid profiling provides an exciting avenue for the identification of disease signatures with important implications for diagnosis and treatment of mood disorders.