21 research outputs found

    Proteome Analyses of Cellular Proteins in Methicillin-Resistant Staphylococcus aureus Treated with Rhodomyrtone, a Novel Antibiotic Candidate

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    The ethanolic extract from Rhodomyrtus tomentosa leaf exhibited good antibacterial activities against both methicillin-resistant Staphylococcus aureus (MRSA) and S. aureus ATCC 29213. Its minimal inhibitory concentration (MIC) values ranged from 31.25–62.5 µg/ml, and the minimal bactericidal concentration (MBC) was 250 µg/ml. Rhodomyrtone, an acylphloroglucinol derivative, was 62.5–125 times more potent at inhibiting the bacteria than the ethanolic extract, the MIC and MBC values were 0.5 µg/ml and 2 µg/ml, respectively. To provide insights into antibacterial mechanisms involved, the effects of rhodomyrtone on cellular protein expression of MRSA have been investigated using proteomic approaches. Proteome analyses revealed that rhodomyrtone at subinhibitory concentration (0.174 µg/ml) affected the expression of several major functional classes of whole cell proteins in MRSA. The identified proteins involve in cell wall biosynthesis and cell division, protein degradation, stress response and oxidative stress, cell surface antigen and virulence factor, and various metabolic pathways such as amino acid, carbohydrate, energy, lipid, and nucleotide metabolism. Transmission electron micrographs confirmed the effects of rhodomyrtone on morphological and ultrastructural alterations in the treated bacterial cells. Biological processes in cell wall biosynthesis and cell division were interrupted. Prominent changes including alterations in cell wall, abnormal septum formation, cellular disintegration, and cell lysis were observed. Unusual size and shape of staphylococcal cells were obviously noted in the treated MRSA. These pioneer findings on proteomic profiling and phenotypic features of rhodomyrtone-treated MRSA may resolve its antimicrobial mechanisms which could lead to the development of a new effective regimen for the treatment of MRSA infections

    A methodology for identifying and formalizing farmers’ representations of watershed management: a case study from northern Thailand

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    Linking modeling tools and the participatory approach for development is not a common combination. Participatory multi-agent system modeling (PMASM) is a tool for sharing viewpoints among stakeholders and facilitating the negotiation process. A key question of this approach is the acquisition and the modeling of the various stakeholders’ representations. Our research team, whose Asian branch is represented in this book, tries to formalize the passage from fieldwork to the model by defining a methodology that can be implemented in the field. This methodology adapts knowledge engineering acquisition techniques to in-field stakeholders’ representations for PMASM. In a northern Thailand watershed, we pursued implementation tests of this methodology. We first explored two ways to tackle fieldwork (ethnographic and project surveys), both showing weaknesses and strengths. We then built a first-version diagram syntax used for representing individual farmers’ representations, and we considered options for analyzing those diagrams. Finally, we tested the elicited representations by leading farmers, through game-like sessions, to rebuild a model of their system structured by elements and links. Results reveal a great heterogeneity of farmers’ representations, which we intend to manage by establishing farmers’ synthetic profiles based on their orientations toward specific elements and aspects of their social and natural environment. Orientations of those profiles convey different conceptions of the functioning of the system with which farmers interact. This also results in decisions and reactions to issues that are different from one profile to another. The identification and formalization will contribute to the implementation of a computer model of farmers’ representations. Perspectives are drawn on two ways to integrate representations into the modeling

    Une méthodologie pour l'identification et la formalisation des représentations des agriculteurs sur la gestion des bassins versants: une étude de cas au Nord Thaïlande

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    International audienceLinking modeling tools and the participatory approach for development is not a common combination. Participatory multi-agent system modeling (PMASM) is a tool for sharing viewpoints among stakeholders and facilitating the negotiation process. A key question of this approach is the acquisition and the modeling of the various stakeholders' representations. Our research team, whose Asian branch is represented in this book, tries to formalize the passage from fieldwork to the model by defining a methodology that can be implemented in the field. This methodology adapts knowledge engineering acquisition techniques to in-field stakeholders' representations for PMASM. In a northern Thailand watershed, we pursued implementation tests of this methodology. We first explored two ways to tackle fieldwork (ethnographic and project surveys), both showing weaknesses and strengths. We then built a first-version diagram syntax used for representing individual farmers' representations, and we considered options for analyzing those diagrams. Finally, we tested the elicited representations by leading farmers, through game-like sessions, to rebuild a model of their system structured by elements and links. Results reveal a great heterogeneity of farmers' representations, which we intend to manage by establishing farmers' synthetic profiles based on their orientations toward specific elements and aspects of their social and natural environment. Orientations of those profiles convey different conceptions of the functioning of the system with which farmers interact. This also results in decisions and reactions to issues that are different from one profile to another. The identification and formalization will contribute to the implementation of a computer model of farmers' representations. Perspectives are drawn on two ways to integrate representations into the modeling
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