Cette thèse s’inscrit dans le cadre de la thématique du laboratoire de Pharmacognosie de l’UFR Santé, au sein de l’Université de Bourgogne. Elle vise essentiellement la recherche de molécules d’origine végétale issue de la biodiversité tropicale dotées d’une activité antitumorale et immuno-modulatoire dont principalement les saponines. Ce sont des glycosides triterpéniques ou stéroïdiques connus pour leurs nombreuses propriétés pharmacologiques. L’étude de 4 espèces végétales appartenant à 3 familles à savoir Dracaena marginata L., Dracaena fragrans Ker Gawl (Asparagaceae), Allium flavum L. (Amaryllidaceae) et Weigela stelzneri (Caprifoliaceae),a conduit à l’isolement et à la caractérisation de 26 glycosides naturels. Il s’agit de 22 saponines stéroïdiques parmi lesquelles 6 sont de structure nouvelle ainsi que 4 saponines triterpéniques dont 3 nouvelles. Les structures ont été élucidées principalement par l’utilisation de la RMN 2D ainsi que la spectrométrie de masse. 10 des 26 molécules isolées ont été testées en vue d’évaluer leurs activités cytotoxiques sur deux lignées cellulaires cancéreuses (SW480 et EMT-6), et 3 pour l’étude de la modulation de la production d’une cytokine pro-inflammatoire, l’interleukine IL-1β sur cellules PBMC stimulées par le LPS. Nos résultats montrent que 6 d’entre elles possèdent une activité cytotoxique modérée sur les deux lignées cancéreuses. En revanche, deux saponines triterpéniques de type oléanane exercent les plus fortes cytotoxicités sur les deux lignées cancéreuses comparées à celles des références internes (Etoposide et Methotrexate). De plus elles révèlent un important effet de modulation de la production de l’interleukine IL-1β sur cellules PBMC et de ce fait, un fort potentiel anti-inflammatoire. Des relations structure/activité ont été ainsi proposées.
This research work deals with the problem of karst sinkhole collapse occurring in the last few years in Cheria area (NE Algeria). This newly revealed phenomenon is of a major constrain in land use planning and urbanization, it has become necessary to locate and assess the stability of these underground features before any planning operation. Several exploration methods for the localization of underground cavities have been considered. Geological survey, discontinuity analysis, resistivity survey [ground penetrating radar has not been used as most of the Mio-Plio-Quaternary filling deposit covering Eocene limestone contains clay layers which limits the applicability of the method (Roth et al. in Eng Geol 65:225–232, 2002)] and borehole drilling were undertaken in order to locate underground cavities and assess their depth, geometry, dimensions, etc. Laboratory testing and field work were also undertaken in order to determine both intact rock and rock mass properties. All the rock mechanics testing and measurement were undertaken according to the ISRM recommendations. It has been found that under imposed loading, the stability of the karst cavities depends on the geo-mechanical parameters (RMR, Rock Mass Rating; GSI, Geological Strength Index; E, Young modulus) of the host rock as well as the depth and dimensions of the gallery. It increases with RMR, GSI, E and depth and decreases as the cavity becomes wider. Furthermore, the calculation results show that a ratio (roof thickness to gallery width) of 0.3 and more indicate, a stable conditions. The results obtained in this work allow identifying and assessing the stability of underground karst cavities. The methodology followed in this paper can be taken as a road map in the establishment of a hazard map related to the studied phenomenon. This map will be a useful tool for the future urban extension planning in Cheria area.
In this paper, we propose to combine the shape context (SC) descriptor with quantum genetic algorithms (QGA) to define a new shape matching and retrieval method. The SC matching method is based on finding the best correspondence between two point sets. The proposed method uses the QGA to find the best configuration of sample points in order to achieve the best possible matching between the two shapes. This combination of SC and QGA leads to a better retrieval results based on our tests. The SC is a very powerful discriminative descriptor which is translation and scale invariant, but weak against rotation and flipping. In our proposed quantum shape context algorithm (QSC), we use the QGA to estimate the best orientation of the target shape to ensure the best matching for rotated and flipped shapes. The experimental results showed that our proposed QSC matching method is much powerful than the classic SC method for the retrieval of shapes with orientation changes.