Understanding and meeting the needs of the older population: a global challenge.

BACKGROUND: In the past century, there has been a significant rise in life expectancy in almost all regions of the world, contributing to an increasingly older population. The aging of the population, in conjunction with urbanization and industrialization, has resulted in an important epidemiological transition marked by a widespread increase in the prevalence of chronic diseases and their sequelae. Current trends suggest that the transition will have a greater impact on developing countries compared to developed countries. An adequate response to the transition requires a strong emphasis on primary prevention and adequate resource allocation.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

The functions of DNA methylation by CcrM in Caulobacter crescentus: a global approach.

DNA methylation is involved in a diversity of processes in bacteria, including maintenance of genome integrity and regulation of gene expression. Here, using Caulobacter crescentus as a model, we exploit genome-wide experimental methods to uncover the functions of CcrM, a DNA methyltransferase conserved in most Alphaproteobacteria. Using single molecule sequencing, we provide evidence that most CcrM target motifs (GANTC) switch from a fully methylated to a hemi-methylated state when they are replicated, and back to a fully methylated state at the onset of cell division. We show that DNA methylation by CcrM is not required for the control of the initiation of chromosome replication or for DNA mismatch repair. By contrast, our transcriptome analysis shows that >10% of the genes are misexpressed in cells lacking or constitutively over-expressing CcrM. Strikingly, GANTC methylation is needed for the efficient transcription of dozens of genes that are essential for cell cycle progression, in particular for DNA metabolism and cell division. Many of them are controlled by promoters methylated by CcrM and co-regulated by other global cell cycle regulators, demonstrating an extensive cross talk between DNA methylation and the complex regulatory network that controls the cell cycle of C. crescentus and, presumably, of many other Alphaproteobacteria.

Voir le monde à travers les lunettes du métacontraste : un modèle mathématique inspiré de la psychologie sociale

Résumé La théorie de l'autocatégorisation est une théorie de psychologie sociale qui porte sur la relation entre l'individu et le groupe. Elle explique le comportement de groupe par la conception de soi et des autres en tant que membres de catégories sociales, et par l'attribution aux individus des caractéristiques prototypiques de ces catégories. Il s'agit donc d'une théorie de l'individu qui est censée expliquer des phénomènes collectifs. Les situations dans lesquelles un grand nombre d'individus interagissent de manière non triviale génèrent typiquement des comportements collectifs complexes qui sont difficiles à prévoir sur la base des comportements individuels. La simulation informatique de tels systèmes est un moyen fiable d'explorer de manière systématique la dynamique du comportement collectif en fonction des spécifications individuelles. Dans cette thèse, nous présentons un modèle formel d'une partie de la théorie de l'autocatégorisation appelée principe du métacontraste. À partir de la distribution d'un ensemble d'individus sur une ou plusieurs dimensions comparatives, le modèle génère les catégories et les prototypes associés. Nous montrons que le modèle se comporte de manière cohérente par rapport à la théorie et est capable de répliquer des données expérimentales concernant divers phénomènes de groupe, dont par exemple la polarisation. De plus, il permet de décrire systématiquement les prédictions de la théorie dont il dérive, notamment dans des situations nouvelles. Au niveau collectif, plusieurs dynamiques peuvent être observées, dont la convergence vers le consensus, vers une fragmentation ou vers l'émergence d'attitudes extrêmes. Nous étudions également l'effet du réseau social sur la dynamique et montrons qu'à l'exception de la vitesse de convergence, qui augmente lorsque les distances moyennes du réseau diminuent, les types de convergences dépendent peu du réseau choisi. Nous constatons d'autre part que les individus qui se situent à la frontière des groupes (dans le réseau social ou spatialement) ont une influence déterminante sur l'issue de la dynamique. Le modèle peut par ailleurs être utilisé comme un algorithme de classification automatique. Il identifie des prototypes autour desquels sont construits des groupes. Les prototypes sont positionnés de sorte à accentuer les caractéristiques typiques des groupes, et ne sont pas forcément centraux. Enfin, si l'on considère l'ensemble des pixels d'une image comme des individus dans un espace de couleur tridimensionnel, le modèle fournit un filtre qui permet d'atténuer du bruit, d'aider à la détection d'objets et de simuler des biais de perception comme l'induction chromatique. Abstract Self-categorization theory is a social psychology theory dealing with the relation between the individual and the group. It explains group behaviour through self- and others' conception as members of social categories, and through the attribution of the proto-typical categories' characteristics to the individuals. Hence, it is a theory of the individual that intends to explain collective phenomena. Situations involving a large number of non-trivially interacting individuals typically generate complex collective behaviours, which are difficult to anticipate on the basis of individual behaviour. Computer simulation of such systems is a reliable way of systematically exploring the dynamics of the collective behaviour depending on individual specifications. In this thesis, we present a formal model of a part of self-categorization theory named metacontrast principle. Given the distribution of a set of individuals on one or several comparison dimensions, the model generates categories and their associated prototypes. We show that the model behaves coherently with respect to the theory and is able to replicate experimental data concerning various group phenomena, for example polarization. Moreover, it allows to systematically describe the predictions of the theory from which it is derived, specially in unencountered situations. At the collective level, several dynamics can be observed, among which convergence towards consensus, towards frag-mentation or towards the emergence of extreme attitudes. We also study the effect of the social network on the dynamics and show that, except for the convergence speed which raises as the mean distances on the network decrease, the observed convergence types do not depend much on the chosen network. We further note that individuals located at the border of the groups (whether in the social network or spatially) have a decisive influence on the dynamics' issue. In addition, the model can be used as an automatic classification algorithm. It identifies prototypes around which groups are built. Prototypes are positioned such as to accentuate groups' typical characteristics and are not necessarily central. Finally, if we consider the set of pixels of an image as individuals in a three-dimensional color space, the model provides a filter that allows to lessen noise, to help detecting objects and to simulate perception biases such as chromatic induction.

La « présence thérapeutique » en contexte scolaire, éducatif et pédagogique : esquisse d'un modèle de consultation psychanalytique

Cet article présente une pratique de consultation psychanalytique développée par des psychologues tra- vaillant en milieux éducatifs et pédagogiques. Les auteurs se réfèrent à des concepts issus de l'école de psychanalyse britannique de la relation d'objet pour monter comment le processus de «présence théra- peutique » peut améliorer et enrichir les interventions en milieu scolaire. Les bénéfices engendrés par une « présence thérapeutique » sur les lieux scolaires et éducatifs et les défis rencontrés seront discutés. Des illustrations cliniques ainsi que des exemples issus de notre pratique avec les enfants, leur famille et les professionnels de l'enfance, que ce soit dans les écoles primaires et secondaires, les garderies, les services spécialisés ou les lieux de formation serviront d'illustration des concepts théoriques présentés.

Transcatheter aortic valve replacement for degenerative bioprosthetic surgical valves: results from the global valve-in-valve registry.

BACKGROUND: Transcatheter aortic valve-in-valve implantation is an emerging therapeutic alternative for patients with a failed surgical bioprosthesis and may obviate the need for reoperation. We evaluated the clinical results of this technique using a large, worldwide registry. METHODS AND RESULTS: The Global Valve-in-Valve Registry included 202 patients with degenerated bioprosthetic valves (aged 77.7±10.4 years; 52.5% men) from 38 cardiac centers. Bioprosthesis mode of failure was stenosis (n=85; 42%), regurgitation (n=68; 34%), or combined stenosis and regurgitation (n=49; 24%). Implanted devices included CoreValve (n=124) and Edwards SAPIEN (n=78). Procedural success was achieved in 93.1% of cases. Adverse procedural outcomes included initial device malposition in 15.3% of cases and ostial coronary obstruction in 3.5%. After the procedure, valve maximum/mean gradients were 28.4±14.1/15.9±8.6 mm Hg, and 95% of patients had ≤+1 degree of aortic regurgitation. At 30-day follow-up, all-cause mortality was 8.4%, and 84.1% of patients were at New York Heart Association functional class I/II. One-year follow-up was obtained in 87 patients, with 85.8% survival of treated patients. CONCLUSIONS: The valve-in-valve procedure is clinically effective in the vast majority of patients with degenerated bioprosthetic valves. Safety and efficacy concerns include device malposition, ostial coronary obstruction, and high gradients after the procedure.

Promoter recognition and activation by the global response regulator CbrB in Pseudomonas aeruginosa.

In Pseudomonas aeruginosa, the CbrA/CbrB two-component system is instrumental in the maintenance of the carbon-nitrogen balance and for growth on carbon sources that are energetically less favorable than the preferred dicarboxylate substrates. The CbrA/CbrB system drives the expression of the small RNA CrcZ, which antagonizes the repressing effects of the catabolite repression control protein Crc, an RNA-binding protein. Dicarboxylates appear to cause carbon catabolite repression by inhibiting the activity of the CbrA/CbrB system, resulting in reduced crcZ expression. Here we have identified a conserved palindromic nucleotide sequence that is present in upstream activating sequences (UASs) of promoters under positive control by CbrB and σ(54) RNA polymerase, especially in the UAS of the crcZ promoter. Evidence for recognition of this palindromic sequence by CbrB was obtained in vivo from mutational analysis of the crcZ promoter and in vitro from electrophoretic mobility shift assays using crcZ promoter fragments and purified CbrB protein truncated at the N terminus. Integration host factor (IHF) was required for crcZ expression. CbrB also activated the lipA (lipase) promoter, albeit less effectively, apparently by interacting with a similar but less conserved palindromic sequence in the UAS of lipA. As expected, succinate caused CbrB-dependent catabolite repression of the lipA promoter. Based on these results and previously published data, a consensus CbrB recognition sequence is proposed. This sequence has similarity to the consensus NtrC recognition sequence, which is relevant for nitrogen control.