MRI of coronary vessel walls using radial k-space sampling and steady-state free precession imaging.

OBJECTIVE: The objective of our study was to investigate the impact of radial k-space sampling and steady-state free precession (SSFP) imaging on image quality in MRI of coronary vessel walls. SUBJECTS AND METHODS: Eleven subjects were examined on a 1.5-T MR system using three high-resolution navigator-gated and cardiac-triggered 3D black blood sequences (cartesian gradient-echo [GRE], radial GRE, and radial SSFP) with identical spatial resolution (0.9 x 0.9 x 2.4 mm3). The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel wall sharpness, and motion artifacts were analyzed. RESULTS: The mean SNR and CNR of the coronary vessel wall were improved using radial imaging and were best using radial k-space sampling combined with SSFP imaging. Vessel border definition was similar for all three sequences. Radial k-space sampling was found to be less sensitive to motion. Consistently good image quality was seen with the radial GRE sequence. CONCLUSION: Radial k-space sampling in MRI of coronary vessel walls resulted in fewer motion artifacts and improved SNR and CNR. The use of SSFP imaging, however, did not result in improved coronary vessel wall visualization.

Effects of group size and space allocation on physiological, behavioural and production-related welfare parameters in farmed silver fox cubs

Selostus: Ryhmäkoon ja käytössä olevan tilan vaikutus tarhattujen hopeakettupentujen hyvinvointiin

Space Competition and Time Delays in Human Range Expansions. Application to the Neolithic Transition

Space competition effects are well-known in many microbiological and ecological systems. Here we analyze such an effectin human populations. The Neolithic transition (change from foraging to farming) was mainly the outcome of a demographic process that spread gradually throughout Europe from the Near East. In Northern Europe, archaeological data show a slowdown on the Neolithic rate of spread that can be related to a high indigenous (Mesolithic) population density hindering the advance as a result of the space competition between the two populations. We measure this slowdown from a database of 902 Early Neolithic sites and develop a time-delayed reaction-diffusion model with space competition between Neolithic and Mesolithic populations, to predict the observed speeds. The comparison of the predicted speed with the observations and with a previous non-delayed model show that both effects, the time delay effect due to the generation lag and the space competition between populations, are crucial in order to understand the observations

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Poxvirus vector-based HIV vaccines.

PURPOSE OF REVIEW: In this review, we will provide the scientific rationale for the use of poxvirus vectors in the field of HIV vaccines, the immunological profile of the vaccine-induced immune responses, an update on the current use of poxvirus vector-based vaccines in HIV vaccine clinical trials, and the development of new modified poxvirus vectors with improved immunological profile. RECENT FINDINGS: An Ad5-HIV vaccine was tested in a phase IIb clinical trial (known as the Step trial). Vaccinations in the Step trial were discontinued because the vaccine did not show any effect on acquisition of infection and on viral load. After the disappointing failure of the Step trial, the field of HIV vaccine has regained enthusiasm and vigour due to the promising protective effect observed in the phase III efficacy trial (known as RV-144) performed in Thailand which has tested a poxvirus-gp120 combination. SUMMARY: The RV-144 phase III has provided for the first time evidence that an HIV vaccine can prevent HIV infection. The results from the RV-144 trial are providing the scientific rationale for the future development of the HIV vaccine field and for designing future efficacy trials.

The neuronal monocarboxylate transporter MCT2: its regulation by BDNF and its role in learning and memory

Glucose has been considered the major, if not the exclusive, energy substrate for the brain. But under certain physiological and pathological conditions other substrates, namely monocarboxylates (lactate, pyruvate and ketone bodies), can contribute significantly to satisfy brain energy demands. These monocarboxylates need to be transported across the blood-brain barrier or out of astrocytes into the extracellular space and taken up into neurons. It has been shown that monocarboxylates are transported by a family of proton-linked transporters called monocarboxylate transporters (MCTs). In the central nervous system, MCT2 is the predominant neuronal isoform and little is known about the regulation of its expression. Noradrenaline (NA), insulin and IGF-1 were previously shown to enhance the expression of MCT2 in cultured cortical neurons via a translational mechanism. Here we demonstrate that the well known brain neurotrophic factor BDNF enhances MCT2 protein expression in cultured cortical neurons and in synaptoneurosome preparations in a time- and concentrationdependent manner without affecting MCT2 mRNA levels. We observed that BDNF induced MCT2 expression by activation of MAPK as well as PI3K/Akt/mTOR signaling pathways. Furthermore, we investigated the possible post-transcriptional regulation of MCT2 expression by a neuronal miRNA. Then, we demonstrated that BDNF enhanced MCT2 expression in the hippocampus in vivo, in parallel with some post-synaptic proteins such as PSD95 and AMPA receptor GluR2/3 subunits, and two immediate early genes Arc and Zif268 known to be expressed in conditions related to synaptic plasticity. In the last part, we demonstrated in vivo that a downregulation of hippocampal MCT2 via silencing with an appropriate lentiviral vector in mice caused an impairment of working memory without reference memory deficit. In conclusion, these results suggest that regulation of neuronal monocarboxylate transporter MCT2 expression could be a key event in the context of synaptic plasticity, allowing an adequate energy substrate supply in situations of altered synaptic efficacy. - Le glucose représente le substrat énergétique majeur pour le cerveau. Cependant, dans certaines conditions physiologiques ou pathologiques, le cerveau a la capacité d'utiliser des substrats énergéiques appartenant à la classe des monocarboxylates (lactate, pyruvate et corps cétoniques) afin de satisfaire ses besoins énergétiques. Ces monocarboxylates doivent être transportés à travers la barrière hématoencéphalique mais aussi hors des astrocytes vers l'espace extracellulaire puis re-captés par les neurones. Leur transport est assuré par une famillle de transporteurs aux monocarboxylates (MCTs). Dans le système nerveux central, les neurones expriment principalement l'isoforme MCT2 mais peu d'informations sont disponibles concernant la régulation de son expression. Il a été montré que la noradrénaline, l'insuline et l'IGF-1 induisent l'expression de MCT2 dans des cultures de neurones corticaux par un mécanisme traductionnel. Dans cette étude nous démontrons dans un premier temps que le facteur neurotrophique BDNF augmente l'expression de MCT2 à la fois dans des cultures de neurones corticaux et dans les préparations synaptoneurosomales selon un décours temporel et une gamme de concentrations propre. Aucun changement n'a été observé concernant les niveaux d'ARNm de MCT2. Nous avons observé que le BDNF induisait l'expression de MCT2 par l'activation simultanée des voies de signalisation MAPK et PI3K/Akt/mTOR. De plus, nous nous sommes intéressés à une potentielle régulation par les micro-ARNs de la synthèse de MCT2. Ensuite, nous avons démontré que le BDNF induit aussi l'expression de MCT2 dans l'hippocampe de la souris en parallèle avec d'autres protéines post-synaptiques telles que PSD95 et GluR2/3 et avec deux « immediate early genes » tels que Arc et Zif268 connus pour être exprimés dans des conditions de plasticité synaptique. Dans un dernier temps, nous avons démontré qu'une diminution d'expression de MCT2 induite par le biais d'un siRNA exprimé via un vecteur lentiviral dans l'hippocampe de souris générait des déficits de mémoire de travail sans affecter la mémoire de référence. En conclusion, ces résultats nous suggèrent que le transporteur aux monocarboxylates neuronal MCT2 serait essentiel pour l'apport énergétique du lactate pour les neurones dans des conditions de haute activité neuronale comme c'est le cas pendant les processus de plasticité synaptique.

Impact of controlled changes in grain size and pore space characteristics on the hydraulic conductivity and spectral induced polarization response of "proxies" of saturated alluvial sediments

Understanding the influence of pore space characteristics on the hydraulic conductivity and spectral induced polarization (SIP) response is critical for establishing relationships between the electrical and hydrological properties of surficial unconsolidated sedimentary deposits, which host the bulk of the world's readily accessible groundwater resources. Here, we present the results of laboratory SIP measurements on industrial-grade, saturated quartz samples with granulometric characteristics ranging from fine sand to fine gravel, which can be regarded as proxies for widespread alluvial deposits. We altered the pore space characteristics by changing (i) the grain size spectra, (ii) the degree of compaction, and (iii) the level of sorting. We then examined how these changes affect the SIP response, the hydraulic conductivity, and the specific surface area of the considered samples. In general, the results indicate a clear connection between the SIP response and the granulometric as well as pore space characteristics. In particular, we observe a systematic correlation between the hydraulic conductivity and the relaxation time of the Cole-Cole model describing the observed SIP effect for the entire range of considered grain sizes. The results do, however, also indicate that the detailed nature of these relations depends strongly on variations in the pore space characteristics, such as, for example, the degree of compaction. The results of this study underline the complexity of the origin of the SIP signal as well as the difficulty to relate it to a single structural factor of a studied sample, and hence raise some fundamental questions with regard to the practical use of SIP measurements as site- and/or sample-independent predictors of the hydraulic conductivity.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Meta-structure correlation in protein space unveils different selection rules for folded and intrinsically disordered proteins

The number of existing protein sequences spans a very small fraction of sequence space. Natural proteins have overcome a strong negative selective pressure to avoid the formation of insoluble aggregates. Stably folded globular proteins and intrinsically disordered proteins (IDP) use alternative solutions to the aggregation problem. While in globular proteins folding minimizes the access to aggregation prone regions IDPs on average display large exposed contact areas. Here, we introduce the concept of average meta-structure correlation map to analyze sequence space. Using this novel conceptual view we show that representative ensembles of folded and ID proteins show distinct characteristics and responds differently to sequence randomization. By studying the way evolutionary constraints act on IDPs to disable a negative function (aggregation) we might gain insight into the mechanisms by which function - enabling information is encoded in IDPs.