38 resultados para time-domain NMR
Resumo:
Acid-sensing ion channels (ASICs) are neuronal Na(+) channels that are members of the epithelial Na(+) channel/degenerin family and are transiently activated by extracellular acidification. ASICs in the central nervous system have a modulatory role in synaptic transmission and are involved in cell injury induced by acidosis. We have recently demonstrated that ASIC function is regulated by serine proteases. We provide here evidence that this regulation of ASIC function is tightly linked to channel cleavage. Trypsin cleaves ASIC1a with a similar time course as it changes ASIC1a function, whereas ASIC1b, whose function is not modified by trypsin, is not cleaved. Trypsin cleaves ASIC1a at Arg-145, in the N-terminal part of the extracellular loop, between a highly conserved sequence and a sequence that is critical for ASIC1a inhibition by the venom of the tarantula Psalmopoeus cambridgei. This channel domain controls the inactivation kinetics and co-determines the pH dependence of ASIC gating. It undergoes a conformational change during inactivation, which renders the cleavage site inaccessible to trypsin in inactivated channels.
Resumo:
In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.
Resumo:
Despite obvious improvements in spectral resolution at high magnetic field, the detection of 13C labeling by 1H-[13C] NMR spectroscopy remains hampered by spectral overlap, such as in the spectral region of 1H resonances bound to C3 of glutamate (Glu) and glutamine (Gln), and C6 of N-acetylaspartate (NAA). The aim of this study was to develop, implement, and apply a novel 1H-[13C] NMR spectroscopic editing scheme, dubbed "selective Resonance suppression by Adiabatic Carbon Editing and Decoupling single-voxel STimulated Echo Acquisition Mode" (RACED-STEAM). The sequence is based on the application of two asymmetric narrow-transition-band adiabatic RF inversion pulses at the resonance frequency of the 13C coupled to the protons that need to be suppressed during the mixing time (TM) period, alternating the inversion band downfield and upfield from the 13C resonance on odd and even scans, respectively, thus suppressing the detection of 1H resonances bound to 13C within the transition band of the inversion pulse. The results demonstrate the efficient suppression of 1H resonances bound to C3 of Glu and Gln, and C4 of Glu, which allows the 1H resonances bound to C6 of NAA and C4 of Gln to be revealed. The measured time course of the resolved labeling into NAA C6 with the new scheme was consistent with the slow turnover of NAA.
Resumo:
Project No. 369 (''Comparative Evolution of PeriTethyan Rift Basins'') of the International Geological Correlation Program produced a new palaeotectonic-palaeo-geographic atlas of the western PeriTethyan domain. The atlas contains more than two hundred new maps and documents grouped in nine regional sets (Iberia, Polish Trough, Eastern European and Scythian Platforms, Moesian Platform, Levant, Arabian Platform,, Northern Africa, NE Africa-NW Arabia, Libya-Pelagian Shelf plus a set of reconstructions for the whole western Tethys. The area, considered in the atlas stretches. from west to east, from the eastern Atlantic shores to the Urals and, from north to south, from the Baltic shield to equatorial Africa; the time span covered extends from the Late. Carboniferous to the Present. The dataset, resulting from an extensive cooperation between industrial and academic sources, is accessible interactively on a CD-ROM (Stampfli et al., 2001a) and includes legend, timetable, short explanatory notes, full references and additional supporting data. This dataset provides information on the development of the Tethyan realm in space and time. In particular, the relation between the Variscan and Cimmerian cycles in the Mediterranean realm is illustrated by numerous palaeogeographic and palaeotectonic maps.
Resumo:
(13)C magnetic resonance spectroscopy (MRS) combined with the administration of (13)C labeled substrates uniquely allows to measure metabolic fluxes in vivo in the brain of humans and rats. The extension to mouse models may provide exclusive prospect for the investigation of models of human diseases. In the present study, the short-echo-time (TE) full-sensitivity (1)H-[(13)C] MRS sequence combined with high magnetic field (14.1 T) and infusion of [U-(13)C6] glucose was used to enhance the experimental sensitivity in vivo in the mouse brain and the (13)C turnover curves of glutamate C4, glutamine C4, glutamate+glutamine C3, aspartate C2, lactate C3, alanine C3, γ-aminobutyric acid C2, C3 and C4 were obtained. A one-compartment model was used to fit (13)C turnover curves and resulted in values of metabolic fluxes including the tricarboxylic acid (TCA) cycle flux VTCA (1.05 ± 0.04 μmol/g per minute), the exchange flux between 2-oxoglutarate and glutamate Vx (0.48 ± 0.02 μmol/g per minute), the glutamate-glutamine exchange rate V(gln) (0.20 ± 0.02 μmol/g per minute), the pyruvate dilution factor K(dil) (0.82 ± 0.01), and the ratio for the lactate conversion rate and the alanine conversion rate V(Lac)/V(Ala) (10 ± 2). This study opens the prospect of studying transgenic mouse models of brain pathologies.
Resumo:
Alterations in the hepatic lipid content (HLC) and fatty acid composition are associated with disruptions in whole body metabolism, both in humans and in rodent models, and can be non-invasively assessed by (1)H-MRS in vivo. We used (1)H-MRS to characterize the hepatic fatty-acyl chains of healthy mice and to follow changes caused by streptozotocin (STZ) injection. Using STEAM at 14.1 T with an ultra-short TE of 2.8 ms, confounding effects from T2 relaxation and J-coupling were avoided, allowing for accurate estimations of the contribution of unsaturated (UFA), saturated (SFA), mono-unsaturated (MUFA) and poly-unsaturated (PUFA) fatty-acyl chains, number of double bonds, PU bonds and mean chain length. Compared with in vivo (1) H-MRS, high resolution NMR performed in vitro in hepatic lipid extracts reported longer fatty-acyl chains (18 versus 15 carbons) with a lower contribution from UFA (61 ± 1% versus 80 ± 5%) but a higher number of PU bonds per UFA (1.39 ± 0.03 versus 0.58 ± 0.08), driven by the presence of membrane species in the extracts. STZ injection caused a decrease of HLC (from 1.7 ± 0.3% to 0.7 ± 0.1%), an increase in the contribution of SFA (from 21 ± 2% to 45 ± 6%) and a reduction of the mean length (from 15 to 13 carbons) of cytosolic fatty-acyl chains. In addition, SFAs were also likely to have increased in membrane lipids of STZ-induced diabetic mice, along with a decrease of the mean chain length. These studies show the applicability of (1)H-MRS in vivo to monitor changes in the composition of the hepatic fatty-acyl chains in mice even when they exhibit reduced HLC, pointing to the value of this methodology to evaluate lipid-lowering interventions in the scope of metabolic disorders.
Resumo:
This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.
Resumo:
The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.