971 resultados para cytochrome c oxidase subunit I
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ADP-ribosylation factor-1 (ARF1) est une petite GTPase principalement connue pour son rôle dans la formation de vésicules au niveau de l’appareil de Golgi. Récemment, dans des cellules de cancer du sein, nous avons démontré qu’ARF1 est aussi un médiateur important de la signalisation du récepteur du facteur de croissance épidermique (EGFR) contrôlant la prolifération, la migration et l'invasion cellulaire. Cependant, le mécanisme par lequel l’EGFR active la GTPase ainsi que le rôle de cette dernière dans la régulation de la fonction du récepteur demeure inconnue. Dans cette thèse, nous avions comme objectifs de définir le mécanisme d'activation de ARF1 dans les cellules de cancer du sein hautement invasif et démontrer que l’activation de cette isoforme de ARF joue un rôle essentiel dans la résistance de ces cellules aux inhibiteurs de l'EGFR. Nos études démontrent que les protéines d’adaptatrices Grb2 et p66Shc jouent un rôle important dans l'activation de ARF1. Alors que Grb2 favorise le recrutement d’ARF1 à l'EGFR ainsi que l'activation de cette petite GTPase, p66Shc inhibe le recrutement du complexe Grb2-ARF1 au récepteur et donc contribue à limiter l’activation d’ARF1. De plus, nous démontrons que ARF1 favorise la résistance aux inhibiteurs des tyrosines kinases dans les cellules de cancer du sein hautement invasif. En effet, une diminution de l’expression de ARF1 a augmenté la sensibilité descellules aux inhibiteurs de l'EGFR. Nous montrons également que de hauts niveaux de ARF1 contribuent à la résistance des cellules à ces médicaments en améliorant la survie et les signaux prolifératifs à travers ERK1/2, Src et AKT, tout en bloquant les voies apoptotiques (p38MAPK et JNK). Enfin, nous mettons en évidence le rôle de la protéine ARF1 dans l’apoptose en réponse aux traitements des inhibiteurs de l’EGFR. Nos résultats indiquent que la dépletion d’ARF1 promeut la mort cellulaire induite par gefitinib, en augmentant l'expression de facteurs pro-apoptotiques (p66shc, Bax), en altérant le potentiel de la membrane mitochondriale et la libération du cytochrome C. Ensemble, nos résultats délimitent un nouveau mécanisme d'activation de ARF1 dans les cellules du cancer du sein hautement invasif et impliquent l’activité d’ARF1 comme un médiateur important de la résistance aux inhibiteurs EGFR.
Resumo:
The mechanism of devulcanization of sulfur-vulcanized natural rubber with aromatic disulfides and aliphatic amines has been studied using 23-dimethyl-2-butene (C5H1,) as a low-molecular weight model compound. First C6H12 was vulcanized with a mixture of sulfur, zinc stearate and N-cyclohexyl-2-benzothiazylsulfenamide (CBS) as accelerator at 140 °C, resulting in a mixture of addition products (C(,H 1 i-S,-C5H 1 i ). The compounds were isolated and identified by High Performance Liquid Chromatography (HPLC) with respect to their various sulfur ranks. In it second stage, the vulcanized products were devulcanized using the agents mentioned above at 200 °C. The kinetics and chemistry of the breakdown of the sulfur-hridges were monitored. Both devulcanization agents decompose sulfidic vulcanization products with sulfur ranks equal or higher than 3 quite effectively and with comparable speed. Di phenyldisulfide as devulcanization agent gives rise to a high amount of mono- and disulfidic compounds formed during the devulcanization, hexadecylamine, as devulcanization agent, prevents these lower sulfur ranks from being formed.
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Many examples for emergent behaviors may be observed in self-organizing physical and biological systems which prove to be robust, stable, and adaptable. Such behaviors are often based on very simple mechanisms and rules, but artificially creating them is a challenging task which does not comply with traditional software engineering. In this article, we propose a hybrid approach by combining strategies from Genetic Programming and agent software engineering, and demonstrate that this approach effectively yields an emergent design for given problems.
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Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.
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Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.
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In recent years, application of fluorescent conjugated polymers to sense chemical and biological analytes has received much attention owing to its technological significance. Water soluble conjugated polymers are interesting towards the developing sensors for biomolecules. In this present contribution, we describe the syntheses and characterization of a series of water soluble conjugated polymers with sulfonic acid groups in the side chain. Such anionic conjugated polymers are designed to interact with biomolecules such as cytochrome-C. All polymers are water soluble and showed strong blue emission. Significant quenching of the fluorescence from our functionalized PPP was observed upon addition of viologen derivatives or cytochrome -C.
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We compare correspondance análisis to the logratio approach based on compositional data. We also compare correspondance análisis and an alternative approach using Hellinger distance, for representing categorical data in a contingency table. We propose a coefficient which globally measures the similarity between these approaches. This coefficient can be decomposed into several components, one component for each principal dimension, indicating the contribution of the dimensions to the difference between the two representations. These three methods of representation can produce quite similar results. One illustrative example is given
Resumo:
By using suitable parameters, we present a uni¯ed aproach for describing four methods for representing categorical data in a contingency table. These methods include: correspondence analysis (CA), the alternative approach using Hellinger distance (HD), the log-ratio (LR) alternative, which is appropriate for compositional data, and the so-called non-symmetrical correspondence analysis (NSCA). We then make an appropriate comparison among these four methods and some illustrative examples are given. Some approaches based on cumulative frequencies are also linked and studied using matrices. Key words: Correspondence analysis, Hellinger distance, Non-symmetrical correspondence analysis, log-ratio analysis, Taguchi inertia
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Learning contents adaptation has been a subject of interest in the research area of the adaptive hypermedia systems. Defining which variables and which standards can be considered to model adaptive content delivery processes is one of the main challenges in pedagogical design over e-learning environments. In this paper some specifications, architectures and technologies that can be used in contents adaptation processes considering characteristics of the context are described and a proposal to integrate some of these characteristics in the design of units of learning using adaptation conditions in a structure of IMS-Learning Design (IMS-LD) is presented. The key contribution of this work is the generation of instructional designs considering the context, which can be used in Learning Management Systems (LMSs) and diverse mobile devices
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Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance
Resumo:
Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of non-textured objects or objects for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance
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This paper focuses on the problem of realizing a plane-to-plane virtual link between a camera attached to the end-effector of a robot and a planar object. In order to do the system independent to the object surface appearance, a structured light emitter is linked to the camera so that 4 laser pointers are projected onto the object. In a previous paper we showed that such a system has good performance and nice characteristics like partial decoupling near the desired state and robustness against misalignment of the emitter and the camera (J. Pages et al., 2004). However, no analytical results concerning the global asymptotic stability of the system were obtained due to the high complexity of the visual features utilized. In this work we present a better set of visual features which improves the properties of the features in (J. Pages et al., 2004) and for which it is possible to prove the global asymptotic stability
Resumo:
In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory
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In this article, a new technique for grooming low-speed traffic demands into high-speed optical routes is proposed. This enhancement allows a transparent wavelength-routing switch (WRS) to aggregate traffic en route over existing optical routes without incurring expensive optical-electrical-optical (OEO) conversions. This implies that: a) an optical route may be considered as having more than one ingress node (all inline) and, b) traffic demands can partially use optical routes to reach their destination. The proposed optical routes are named "lighttours" since the traffic originating from different sources can be forwarded together in a single optical route, i.e., as taking a "tour" over different sources towards the same destination. The possibility of creating lighttours is the consequence of a novel WRS architecture proposed in this article, named "enhanced grooming" (G+). The ability to groom more traffic in the middle of a lighttour is achieved with the support of a simple optical device named lambda-monitor (previously introduced in the RingO project). In this article, we present the new WRS architecture and its advantages. To compare the advantages of lighttours with respect to classical lightpaths, an integer linear programming (ILP) model is proposed for the well-known multilayer problem: traffic grooming, routing and wavelength assignment The ILP model may be used for several objectives. However, this article focuses on two objectives: maximizing the network throughput, and minimizing the number of optical-electro-optical conversions used. Experiments show that G+ can route all the traffic using only half of the total OEO conversions needed by classical grooming. An heuristic is also proposed, aiming at achieving near optimal results in polynomial time
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This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage