Because obesity is associated with many co-morbidities, including diabetes mellitus, this study evaluated the second-meal effect of a commercial prebiotic, inulin-type fructans, and the effects of the prebiotic on faecal microbiota, metabolites and bile acids (BA). Nine overweight beagles were used in a replicated 3×3 Latin square design to test a non-prebiotic control (cellulose) against a low (equivalent to 0·5 % diet) and high dose (equivalent to 1·0 % diet) of prebiotic over 14-d treatments. All dogs were fed the same diet twice daily, with treatments provided orally via gelatin capsules before meals. On days 13 or 14 of each period, fresh faecal samples were collected, dogs were fed at 08.00 hours and then challenged with 1 g/kg body weight of maltodextrin in place of the 16.00 hours meal. Repeated blood samples were analysed for glucose and hormone concentrations to determine postprandial incremental AUC (IAUC) data. Baseline glucose, insulin and active glucagon-like peptide-1 levels were similar between all groups (P>0·10). Glucose and insulin IAUC after glucose challenge appeared lower following the high dose, but did not reach statistical relevance. Prebiotic intervention resulted in an increase in relative abundance of some Firmicutes and a decrease in the relative abundance of some Proteobacteria. Individual and total faecal SCFA were significantly increased (P<0·05) following prebiotic supplementation. Total concentration of excreted faecal BA tended to increase in dogs fed the prebiotic (P=0·06). Our results indicate that higher doses of inulin-type prebiotics may serve as modulators of gut microbiota, metabolites and BA pool in overweight dogs.

In this paper, we consider the inverse problem of restoring an unknown signal or image, knowing the transformation suffered by the unknowns. More specifically we deal with transformations described by a linear model linking the unknown signal to an unnoisy version of the data. The measured data are generally corrupted by noise. This aspect of the problem is presented in the introduction for general models. In Section 2, we introduce the linear models, and some examples of linear inverse problems are presented. The specificities of the inverse problems are briefly mentionned and shown on a simple example. In Section 3, we give some information on classical distances or divergences. Indeed, an inverse problem is generally solved by minimizing a discrepancy function (divergence or distance) between the measured data and the model (here linear) of such data. Section 4 deals with the likelihood maximization and with their links with divergences minimization. The physical constraints on the solution are indicated and the Split Gradient Method (SGM) is detailed in Section 5. A constraint on the inferior bound of the solution is introduced at first; the positivity constraint is a particular case of such a constraint. We show how to obtain strictly, the multiplicative form of the algorithms. In a second step, the so-called flux constraint is introduced, and a complete algorithmic form is given. In Section 6 we give some brief information on acceleration method of such algorithms. A conclusion is given in Section 7.

Spectral unmixing is an important issue to analyze remotely sensed hyperspectral data. This involves the decomposition of each mixed pixel into its pure endmember spectra, and the estimation of the abundance value for each endmember. Although linear mixture models are often considered because of their simplicity, there are many situations in which they can be advantageously replaced by nonlinear mixture models. In this chapter, we derive a supervised kernel-based unmixing method that relies on a pre-image problem-solving technique. The kernel selection problem is also briefly considered. We show that partially-linear kernels can serve as an appropriate solution, and the nonlinear part of the kernel can be advantageously designed with manifold-learning-based techniques. Finally, we incorporate spatial information into our method in order to improve unmixing performance.

This article deals with the problem of minimization of a general cost function under non-negativity and flux conservation constraints. The proposed algorithm is founded on the Split Gradient Method (SGM) adapted here to solve the Non Negative Matrix Factorization (NMF). We show that SGM can be easily regularized, allowing to introduce some physical constraints. Finally, to validate the algorithm, we propose an example of application to hyperspectral data unmixing.

There is substantial evidence to link what we eat to the reduction of the risk of major chronic diseases and/or the improvement of functions. Thus, it is important for public health agencies and the food industry to facilitate the consumption of foods with particular health benefits by providing consumer products and messages based on scientific evidence. Although fragmentary advice is available from a range of sources, there is a lack of comprehensive scientific guidelines for the design, conduct and reporting of human intervention studies to evaluate the health benefits of foods. Such guidelines are needed both to support nutrition science in general, and to facilitate the substantiation of health claims. In the present study, which presents the consensus view of an International Life Sciences Institute Europe Expert Group that included senior scientists from academia and industry, the term ‘foods’ refers to foods, dietary supplements and food constituents, but not to whole diets. The present study is based on an initial survey of published papers, which identified the range and strengths and weaknesses of current methodologies, and was finalised following exchanges between representatives from industry, academia and regulatory bodies. The major factors involved in the design, conduct and reporting of studies are identified, summarised in a checklist table that is based on the Consolidated Standards of Reporting Trials guidelines, and elaborated and discussed in the text.

We studied the impact of the revisited values for the LSR circular velocity of the Milky Way (Reid et al. 2004) on the formation of the Magellanic Stream. The LSR circular velocity was varied within its observational uncertainties as a free parameter of the interaction between the Large (LMC) and the Small (SMC) Magellanic Clouds and the Galaxy. We have shown that the large–scale morphology and kinematics of the Magellanic Stream may be reproduced as tidal features, assuming the recent values of the proper motions of the Magellanic Clouds (Kallivayalil  2006). Automated exploration of the entire parameter space for the interaction was performed to identify all parameter combinations that allow for modeling the Magellanic Stream. Satisfactory models exist for the dynamical mass of the Milky Way within a wide range of 0.6 ⋅ 1012 M⊙ to 3.0 ⋅ 1012 M⊙ and over the entire 1–σ errors of the proper motions of the Clouds. However, the successful models share a common interaction scenario. The Magellanic Clouds are satellites of the Milky Way, and in all cases two close LMC–SMC encounters occurred within the last 4 Gyr at t < −2.5 Gyr and t ≈ −150 Myr, triggering the formation of the Stream and of the Magellanic Bridge, respectively. The latter encounter is encoded in the observed proper motions and inevitable in any model of the interaction. We conclude that the tidal origin of the Magellanic Stream implies the previously introduced LMC/SMC orbital history, unless the parameters of the interaction are revised substantially.

Observing nearby interacting galaxies is a key to understanding galactic physics provided that we know the spatial and temporal perturbations acting on these galaxies. Thus, we have to know the orbits and the gross internal properties of the galaxies. In order to cope with the related extended parameter space, we developed the code MINGA which combines a genetic algorithm with a fast N-body method. As an example for this method, we present a re-analysis of the prototypical system NGC 4449 which is now based on both, the full HI data cube of the NGC 4449 system and on improved determinations of the galactic orbits within a restricted N-body calculation.

Motivated by the closest major merger, the Antennae Galaxies (NGC4038/4039), we want to improve our genetic algorithm based modeling code Minga (Theis 1999). The aim is to reveal the major interaction and galaxy parameters, e.g. orbital information and halo properties of such an equal mass merger system. Together with the sophisticated search strategy of Minga, one needs fast and reliable models in order to investigate the high dimensional parameter space of this problem. Therefore we use a restricted N-body code which is based on the approach by Toomre & Toomre (1972), however with some refinements like consistent orbits of extended dark matter halos. Recently also dynamical friction was included to this code (Petsch 2007). While a good description for dynamical friction was found for mass ratios up to q = 1/3 (Petsch & Theis 2008), major merger systems were only imperfectly remodeled. Here we show recent improvements for a major merger system by including mass-loss and using NFW halos.

Our aim is to study the evolution of tidal dwarf galaxies. The firststep is to understand whether a model galaxy without Dark Matter cansustain the feedback of the ongoing star formation. We present testsof the evolution of models in which star formation efficiency,temperature threshold, initial distribution of gas and infall arevaried. We conclude that it is feasible to keep a fraction of gasbound for several hundreds of Myr and that the development of galacticwinds does not necessarily stop continuous star formation.

Founding on a physical transformation process described by aFredholm integral equation of the first kind, we first recall themain difficulties appearing in linear inverse problems in thecontinuous case as well as in the discrete case. We describe severalsituations corresponding to various properties of the kernel of theintegral equation. The need to take into account the properties of the solution notcontained in the model is then put in evidence. This leads to theregularization principles for which the classical point of view aswell as the Bayesian interpretation are briefly reminded. We then focus on the problem of deconvolution specially applied toastronomical images. A complete model of image formation isdescribed in Section 4, and a general method allowing to deriveimage restoration algorithms, the Split Gradient Method (SGM), is detailedin Section 5. We show in Section 6, that when this method is applied to thelikelihood maximization problems with positivity constraint, theISRA algorithm can be recovered in the case of the pure Gaussianadditive noise case, while in the case of pure Poisson noise, thewell known EM, Richardson-Lucy algorithm is easily obtained. Themethod is then applied to the more realistic situation typical ofCCD detectors: Poisson photo-conversion noise plus Gaussian readoutnoise, and to a new particular situation corresponding to dataacquired with Low Light Level CCD. Some numerical results areexhibited in Section 7 for these two last cases. Finally, we showhow all these algorithms can be regularized in the context of theSGM and we give a general conclusion.

A major goal of contemporary astrophysics is understanding theorigin of the most massive galaxies in the universe, particularly nearbyellipticals and spirals. Theoretical models ofgalaxy formation have existed for many decades, although observationalevidence at both low and high redshifts is only beginning to put constraints on different ideas. We briefly describe theseobservations and how they are revealing the methods by which galaxies form by contrastingand comparing fiducial rapid collapse and hierarchical formation modelpredictions. The available data show that cluster ellipticals must haverapidly formed at z > 2, and that up to50% of all massive galaxies at z ~ 2.5 are involved in major mergers.While the former is consistent with the monolithic collapse picture, weargue that hierarchical formation is the only model that can reproduce all the available observations.

New GSC-II proper motions of RR Lyrae and Blue Horizontal Branch (BHB) stars near the North Galactic Pole are used to show that the Galactic Halo 5 kpc above the Plane has a significantly retrograde galactic rotation.

We summarize results from the first year of the Lenses Structure andDynamics Survey (LSD). Using the Echelle Imager and Spectrograph atthe Keck-II Telescope, we have measured spatially resolved velocitydispersion profiles of a sample of distant (up to z=1) early-typegalaxies that are gravitational lenses. By combining lensing anddynamical analyses we can set firm limits on the dark matter densityprofile, the controversial inner slope of the dark matter halo, themass-to-light ratio of the luminous component, the total massdistribution, and on the velocity ellipsoid by breaking the massanisotropy-relation. The implications of these measurements in termson the epoch and mechanism of formation of E/S0 galaxies and of thevalue of the Hubble constant are briefly discussed.

We use the method of statistical parallaxes to construct the rotationcurve of the Milky Way spanning the Galactocentric distance intervalfrom 2 to 14 kpc based on observational data for young disk populationsand refine the distance scales of the objects belonging to young diskpopulations (classical Cepheids, young open clusters, blue supergiants,HII regions, and HI).