7 resultados para Mathieu, Emile

em Queensland University of Technology - ePrints Archive


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Macrophages are the main components of inflammation during skin wound healing. They are critical in wound closure and in excessive inflammation, resulting in defective healing observed in chronic wounds. Given the heterogeneity of macrophage phenotypes and functions, we here hypothesized that different subpopulations of macrophages would have different and sometimes opposing effects on wound healing. Using multimarker flow cytometry and RNA expression array analyses on macrophage subpopulations from wound granulation tissue, we identified a Ly6cloMHCIIhi “noninflammatory” subset that increased both in absolute number and proportion during normal wound healing and was missing in Ob/Ob and MYD88−/− models of delayed healing. We also identified IL17 as the main cytokine distinguishing this population from proinflammatory macrophages and demonstrated that inhibition of IL17 by blocking Ab or in IL17A−/− mice accelerated normal and delayed healing. These findings dissect the complexity of the role and activity of the macrophages during wound inflammation and may contribute to the development of therapeutic approaches to restore healing in chronic wounds.

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The term post-war violence has been with us for much of the twentieth century but the issue itself has existed for centuries. The study of violence in post-war societies has been explored by philosophers (Erasmus), statesmen (Sir Thomas More) and sociologists (Emile Durkheim). In many cases the cessation of war and the signing of peace accords do not always mean an end to the violence. This book examines in considerable detail the causes and purposes of post-conflict violence and argues that features which constrain or encourage violence accumulate in such a manner as to create distinct and different types of post-war environments...

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This study investigates the impact of polystyrene sodium sulfonate (PolyNaSS) grafting onto the osseo-integration of a polyethylene terephthalate artificial ligament (Ligament Advanced Reinforcement System, LARS™) used for Anterior Cruciate Ligament (ACL). The performance of grafted and non-grafted ligaments was assessed in vitro by culturing human osteoblasts under osteogenic induction and this demonstrated that the surface modification was capable of up-regulating the secretion of ALP and induced higher level of mineralisation as measured 6 weeks post-seeding by Micro-Computed Tomography. Grafted and non-grafted LARS™ were subsequently implanted in an ovine model for ACL reconstruction and the ligament-to-bone interface was evaluated by histology and biomechanical testings 3 and 12 months post-implantation. The grafted ligaments exhibited more frequent direct ligament-to-bone contact and bone formation in the core of the ligament at the later time point than the non-grafted specimens, the grafting also significantly reduced the fibrous encapsulation of the ligament 12 months post-implantation. However, this improved osseo-integration was not translated into a significant increase in the biomechanical pull-out loads. These results provide evidences that PolyNaSS grafting improved the osseo-integration of the artificial ligament within the bone tunnels. This might positively influence the outcome of the surgical reconstructions, as higher ligament stability is believed to limit micro-movement and therefore permits earlier and enhanced healing.

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A series of conjugated copolymers containing fluorene or indenofluorene units alternating with oligothiophene segments, with potential interest for use as the active layer in field-effect transistors, is investigated. Atomic force microscopy analysis of the morphology of thin deposits shows either the formation of fibrillar structures, which are the signature of long-range π stacking, or the presence of untextured aggregates, resulting from disordered assembly. These morphologies are interpreted in terms of the supramolecular organization of the conjugated chains. Molecular modeling simulations indicate that the commensurability between the lengths of the monomer units and the presence of alkyl side groups are the two key structural factors governing the chain organization into highly ordered assemblies. The most favorable structures are those combining fluorene (indenofluorene) units with unsubstituted bithiophene (terthiophene) segments.

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This chapter examines connections between religion, spirituality and mental health. Religion and spirituality influence the way people conceive themselves, others and the world around them, as well as how they behave – and are strongly associated with numerous mental health outcomes. Religion and spirituality therefore demand the attention of those who seek a comprehensive understanding of the factors that affect mental health. Mental health professionals are increasingly being asked to consider their clients’ religious and/or spiritual beliefs when devising their treatment plans, making the study of religion and spirituality an essential area of learning for those working in the mental health field. Initial discussion in this chapter will focus on the different approaches taken by sociologists in studying mental health. Emile Durkheim, one of the founders of sociology, proposed that religion was fundamental to societal wellbeing and was the first to demonstrate a link between religion and mental health at a population level in the late 19th century. Durkheim’s classic theory of religion, together with the work of Thomas Luckmann and other contemporary social theorists who have sought to explain widespread religious change in Western countries since World War II will be examined. Two key changes during this period are the shift away from mainstream Christian religions and the widespread embracing of ‘spirituality’ as an alternative form of religious expression. In combination, the theories of Durkheim, Luckmann and other sociologists provide a platform from which to consider reasons for variations in rates of mental health problems observed in contemporary Western societies according to people’s religious/spiritual orientation. This analysis demonstrates the relevance of both classic and contemporary sociological theories to issues confronting societies in the present day.

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In an attempt to generate supramolecular assemblies able to function as self-healing hydrogels, a novel ureido-pyrimidinone (UPy) monomer, 2-(N ′-methacryloyloxyethylureido)-6-(1-adamantyl)-4[1H]-pyrimidinone, was synthesized and then copolymerized with N,N-dimethylacrylamide at four different feed compositions, using a solution of lithium chloride in N,N-dimethylacetamide as the polymerization medium. The assembling process in the resulting copolymers is based on crosslinking through the reversible quadruple hydrogen bonding between side-chain UPy modules. The adamantyl substituent was introduced in order to create a “hydrophobic pocket” that may protect the hydrogen bonds against the disruptive effect of water molecules. Upon hydration to equilibrium, all copolymers generated typical hydrogels when their concentration in the hydrated system was at least 15%. The small-deformation rheometry showed that all hydrated copolymers were hydrogels that maintained a solid-like behavior, and that their extrusion through a syringe needle did not affect significantly this behavior, suggesting a self-healing capacity in these materials. An application as injectable substitutes for the eye's vitreous humor was proposed

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State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.