Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

Actualisation de la théorie d'action du projet Girasole et proposition d'indicateurs en vue de l'évaluation

Face au fardeau croissant que représentent les maladies non transmissibles, et face à une proportion plus élevée de sa population qui est insuffisamment active physiquement par rapport au reste de la Suisse, le canton du Tessin (Service de promotion et d'évaluation sanitaire, SPVS) lance le projet pilote « Girasole » qui s'adresse aux médecins de premier recours et à leurs patients sédentaires. Ce projet s'appuie sur le concept « Coaching Santé », porté par le Collège de médecine de premier recours, et sur le concept « Paprica », développé notamment par la Policlinique médicale universitaire de Lausanne. Le projet s'appuie sur une vision de prise en charge qui s'inspire du « Chronic care model ». Le réseau de soin, centré autour des compétences et des ressources du patient et de sa communauté, comprend le médecin de premier recours ainsi que les éventuels autres professionnels et les structures existantes susceptibles de faciliter la mise en oeuvre du changement de comportement visé par le patient. Les patients présentant des atteintes à leur santé ou des risques particuliers pourront également bénéficier d'un conseil adapté à leur situation (activité physique adaptée).

A cognitive hierarchy model of behavior in the action commitment game

We apply the cognitive hierarchy model of Camerer et al. (Q J Econ 119(3):861-898, 2004)-where players have different levels of reasoning-to Huck et al. (Games Econ Behav 38:240-264, 2002) discrete version of Hamilton and Slutsky (Games Econ Behav 2:29-46, 1990) action commitment game-a duopoly with endogenous timing of entry. We show that, for an empirically reasonable average number of thinking steps, the model rules out Stackelberg equilibria, generates Cournot outcomes including delay, and outcomes where the first mover commits to a quantity higher than Cournot but lower than Stackelberg leader. We show that a cognitive hierarchy model with quantal responses can explain the most important features of the experimental data on the action commitment game in (2002). In order to gauge the success of the model in fitting the data, we compare it to a noisy Nash model. We find that the cognitive hierarchy model with quantal responses fits the data better than the noisy Nash model.

Learning analytics in practice: setting up a laboratory for action research at the Universitat Oberta de Catalunya

Since its inception in 1994 as a purely online university, the Universitat Oberta de Catalunya(UOC) has been able to position itself among the main universities of the Catalan and Spanish university systems. Most of the students at the UOC (currently more than 60,000) are adults who have a profile that could hardly fit into the traditional university system, thus finding in the UOC an opportunity to start or continue their higher education grades, in a very innovative environment. The intensive use of ICT for both theteaching/learning processes and management allowsresearchers and practitioners to obtain data aboutwhat takes place in the UOC Virtual Campus, which is continuously being improved according to suchfindings.

A new approach to segmentation based on fusing circumscribed contours, region growing and clustering

One of the major problems in machine vision is the segmentation of images of natural scenes. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. The main contours of the scene are detected and used to guide the posterior region growing process. The algorithm places a number of seeds at both sides of a contour allowing stating a set of concurrent growing processes. A previous analysis of the seeds permits to adjust the homogeneity criterion to the regions's characteristics. A new homogeneity criterion based on clustering analysis and convex hull construction is proposed

Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

Role of Myotonic Dystrophy Protein Kinase [DMPK] in Glucose Homeostasis and Muscle Insulin Action

Myotonic dystrophy 1 (DM1) is caused by a CTG expansion in the 3′-unstranslated region of the DMPK gene, which encodes a serine/threonine protein kinase. One of the common clinical features of DM1 patients is insulin resistance, which has been associated with a pathogenic effect of the repeat expansions. Here we show that DMPK itself is a positive modulator of insulin action. DMPK-deficient (dmpk−/−) mice exhibit impaired insulin signaling in muscle tissues but not in adipocytes and liver, tissues in which DMPK is not expressed. Dmpk−/− mice display metabolic derangements such as abnormal glucose tolerance, reduced glucose uptake and impaired insulin-dependent GLUT4 trafficking in muscle. Using DMPK mutants, we show that DMPK is required for a correct intracellular trafficking of insulin and IGF-1 receptors, providing a mechanism to explain the molecular and metabolic phenotype of dmpk−/− mice. Taken together, these findings indicate that reduced DMPK expression may directly influence the onset of insulin-resistance in DM1 patients and point to dmpk as a new candidate gene for susceptibility to type 2-diabetes.

Role of Myotonic Dystrophy Protein Kinase [DMPK] in Glucose Homeostasis and Muscle Insulin Action

Myotonic dystrophy 1 (DM1) is caused by a CTG expansion in the 3′-unstranslated region of the DMPK gene, which encodes a serine/threonine protein kinase. One of the common clinical features of DM1 patients is insulin resistance, which has been associated with a pathogenic effect of the repeat expansions. Here we show that DMPK itself is a positive modulator of insulin action. DMPK-deficient (dmpk−/−) mice exhibit impaired insulin signaling in muscle tissues but not in adipocytes and liver, tissues in which DMPK is not expressed. Dmpk−/− mice display metabolic derangements such as abnormal glucose tolerance, reduced glucose uptake and impaired insulin-dependent GLUT4 trafficking in muscle. Using DMPK mutants, we show that DMPK is required for a correct intracellular trafficking of insulin and IGF-1 receptors, providing a mechanism to explain the molecular and metabolic phenotype of dmpk−/− mice. Taken together, these findings indicate that reduced DMPK expression may directly influence the onset of insulin-resistance in DM1 patients and point to dmpk as a new candidate gene for susceptibility to type 2-diabetes.

Combined drug action of 2-phenylimidazo[2,1-b]benzothiazole derivatives on cancer cells according to their oncogenic molecular signatures

The development of targeted molecular therapies has provided remarkable advances into the treatment of human cancers. However, in most tumors the selective pressure triggered by anticancer agents encourages cancer cells to acquire resistance mechanisms. The generation of new rationally designed targeting agents acting on the oncogenic path(s) at multiple levels is a promising approach for molecular therapies. 2-phenylimidazo[2,1-b]benzothiazole derivatives have been highlighted for their properties of targeting oncogenic Met receptor tyrosine kinase (RTK) signaling. In this study, we evaluated the mechanism of action of one of the most active imidazo[2,1-b]benzothiazol-2-ylphenyl moiety-based agents, Triflorcas, on a panel of cancer cells with distinct features. We show that Triflorcas impairs in vitro and in vivo tumorigenesis of cancer cells carrying Met mutations. Moreover, Triflorcas hampers survival and anchorage-independent growth of cancer cells characterized by 'RTK swapping' by interfering with PDGFRβ phosphorylation. A restrained effect of Triflorcas on metabolic genes correlates with the absence of major side effects in vivo. Mechanistically, in addition to targeting Met, Triflorcas alters phosphorylation levels of the PI3K-Akt pathway, mediating oncogenic dependency to Met, in addition to Retinoblastoma and nucleophosmin/B23, resulting in altered cell cycle progression and mitotic failure. Our findings show how the unusual binding plasticity of the Met active site towards structurally different inhibitors can be exploited to generate drugs able to target Met oncogenic dependency at distinct levels. Moreover, the disease-oriented NCI Anticancer Drug Screen revealed that Triflorcas elicits a unique profile of growth inhibitory-responses on cancer cell lines, indicating a novel mechanism of drug action. The anti-tumor activity elicited by 2-phenylimidazo[2,1-b]benzothiazole derivatives through combined inhibition of distinct effectors in cancer cells reveal them to be promising anticancer agents for further investigation.

Combined drug action of 2-phenylimidazo[2,1-b]benzothiazole derivatives on cancer cells according to their oncogenic molecular signatures

The development of targeted molecular therapies has provided remarkable advances into the treatment of human cancers. However, in most tumors the selective pressure triggered by anticancer agents encourages cancer cells to acquire resistance mechanisms. The generation of new rationally designed targeting agents acting on the oncogenic path(s) at multiple levels is a promising approach for molecular therapies. 2-phenylimidazo[2,1-b]benzothiazole derivatives have been highlighted for their properties of targeting oncogenic Met receptor tyrosine kinase (RTK) signaling. In this study, we evaluated the mechanism of action of one of the most active imidazo[2,1-b]benzothiazol-2-ylphenyl moiety-based agents, Triflorcas, on a panel of cancer cells with distinct features. We show that Triflorcas impairs in vitro and in vivo tumorigenesis of cancer cells carrying Met mutations. Moreover, Triflorcas hampers survival and anchorage-independent growth of cancer cells characterized by 'RTK swapping' by interfering with PDGFRβ phosphorylation. A restrained effect of Triflorcas on metabolic genes correlates with the absence of major side effects in vivo. Mechanistically, in addition to targeting Met, Triflorcas alters phosphorylation levels of the PI3K-Akt pathway, mediating oncogenic dependency to Met, in addition to Retinoblastoma and nucleophosmin/B23, resulting in altered cell cycle progression and mitotic failure. Our findings show how the unusual binding plasticity of the Met active site towards structurally different inhibitors can be exploited to generate drugs able to target Met oncogenic dependency at distinct levels. Moreover, the disease-oriented NCI Anticancer Drug Screen revealed that Triflorcas elicits a unique profile of growth inhibitory-responses on cancer cell lines, indicating a novel mechanism of drug action. The anti-tumor activity elicited by 2-phenylimidazo[2,1-b]benzothiazole derivatives through combined inhibition of distinct effectors in cancer cells reveal them to be promising anticancer agents for further investigation.