Gold-nanoparticle (AuNP)-conjugated drugs represent a promising and innovative antitumor therapeutic approach. In our study, we describe the design, the synthesis, the preparation, and the characterization of AuNPs conjugated with the pyrazolo­[3,4-d]­pyrimidine derivative SI306, a c-Src inhibitor. AuNPs–SI306 showed a good loading efficacy (65%), optimal stability in polar media and in human plasma, and a suitable morphological profile: a ζ-potential of −43.9 mV, a nanoparticle diameter of 48.6 nm, and a 0.441 PDI value. The antitumoral activity of AuNPs–SI306 was evaluated in vitro in the glioblastoma model, by the low-density growth assay, and also in combination with radiotherapy (RT). Results demonstrated that AuNPs had a basal radiosensitization ability and that AuNPs–SI306, when used in combination with RT, were more effective in inhibiting tumor cell growth with respect to AuNPs and free SI306.

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The N-alkylation reaction of pyrazole derivatives with halomethanes was studied using density functional theory (DFT). The hybrid method B3LYP was employed, along with an ECP basis set such as LANL2DZ for halogen atoms (X = Cl, Br, I) and the 6-311 + G(d,p) basis set for all other atoms. In order to predict the specific site at which the pyrazole derivatives interact with halomethanes, local reactivity descriptors such as the Fukui functions were calculated. Detailed analysis of transition-state energies showed that alkylation occurred at the nitrogen atom N in the pyrazole derivatives, in agreement with the chemical reactivity results. The reaction mechanisms were elucidated by performing intrinsic reaction coordinate (IRC) calculations that considered the effects of the solvent and the species of halogen in the halomethane.

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International audience Le modèle AM2b est classiquement représenté par un système d'équations différentielles. Toutefois ce modèle n'est valide qu'en grande population et notre objectif est d'établir plusieurs mo-dèles stochastiques à différentes échelles. À l'échelle microscopique, on propose un modèle sto-chastique de saut pur que l'on peut simuler de fa con exacte. Mais dans la plupart des situations ce genre de simulation n'est pas réaliste, et nous proposons des méthodes de simulation approchées de type poissonnien ou de type diffusif. La méthode de simulation de type diffusif peut être vue comme une discrétisation d'une équation différentielle stochastique. Nous présentons enfin de fa con infor-melle un résultat de type loi des grands nombres/théorème central limite fonctionnelle qui démontre la convergence de ses modèles stochastiques vers le modèles déterministe initial. The model AM2b is conventionally represented by a system of differential equations. However, this model is valid only in a large population context and our objective is to establish several stochastic models at different scales. At a microscopic scale, we propose a pure jump stochastic model that can be simulated exactly. But in most situations this exact simulation is not feasible, and we propose approximate simulation methods of Poisson type and of diffusive type. The diffusive type simulation method can be seen as a discretization of a stochastic differential equation. Finally, we formally present a result of law of large numbers and of functional central limit theorem which demonstrates the convergence of these stochastic models towards the initial deterministic models.

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