Mesoporous chitosan–SiO2 nanoparticles (NPs) were successfully synthesized. The prepared nanoparticles were characterized using TEM, FTIR, XRD, TGA, EDX, and (CHN) elemental analysis. From TEM micrograph, chitosan–SiO2 NPs were sphere-like, pretty uniformly distributed with coarse surface. The average size of chitosan–SiO2 NPs was determined as 211 nm with DLS, which was confirmed by TEM. The mesoporous structure of chitosan–SiO2 NPs was characterized with N2 adsorption/desorption measurements. BET surface area was 621 m2 g–1 and the total pore volume was 0.71 m3 g–1. CO2 adsorption was evaluated by a volumetric method. Chitosan–SiO2 NPs showed a maximum CO2 adsorption capacity of 4.39 mmol g–1 at 25 °C and a high selective separation capacity for CO2 over N2 (S CO2/N2 = 15.46). The influence of amines on carbon dioxide adsorption was discussed. Stable CO2 adsorption/desorption was confirmed after six cycles of experiments. Therefore, chitosan–SiO2 NPs exhibit great potential for CO2 capture.

Hydrogen, as chain transfer agent, effects on kinetic of propylene polymerization; consequently variation of hydrogen concentration leads to change final product properties and also activates site of used catalyst. This phenomenon is one of the most important process variables is to adjust the final product properties and optimize the operating conditions. This work has attempted to present a mathematical model that cable to calculate the most important indices of end used product, such as melt flow index, number and weight average molecular weight and poly dispersity index. The model can predict profile polymerization rates determining important kinetic parameters such as the activation energy, lumped deactivation reaction initial reaction rate and deactivation constant. The mathematical model was implemented in Matlab/Simulink environment for slurry polymerization in laboratory scale. The modeling approach is based on polymer moment balance method in the slurry semi-batch reactor. In addition, in this work have provided a model that calculating fraction activated sites catalyst via hydrogen concentration. The model was validated by experimental data from lab scale, reactor. The experimental and model outputs were compared; consequently, the errors were within acceptable range.

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Background: Drug delivery systems have demonstrated promising results to cross bloodbrain barrier (BBB) and deliver the loaded therapeutics to the brain tumor. This study aims to utilize the transferrin receptor (TR)-targeted liposomal cisplatin (Cispt) for transporting Cispt across the BBB and deliver Cispt to the brain tumor. Methods: Targeted pegylated liposomal cisplatin (TPL-Cispt) was synthesized using reverse phase evaporation method and thiolated OX26 monoclonal antibody. The formulation was characterized in terms of size, size distribution, zeta potential, drug encapsulation and loading efficiencies, bioactivity, drug release profile, stability and cellular uptake using dynamic light scattering, flame atomic absorption spectroscopy (AAS), ELISA, dialysis membrane, and fluorescence assay. Next, the potency of the formulation to increase the therapeutic effects of Cispt and decrease its toxicity effects was evaluated in the brain tumorbearing rats through measuring the mean survival time (MST), blood factors and histopathological studies. Results: The results showed that TPL-Cispt with a size of 157±8 nm and drug encapsulation efficiency of 24%±1.22 was synthesized, that was biologically active and released Cispt in a slow-controlled manner. The formulation compared to Cispt-loaded PEGylated liposome nanoparticles (PL-Cispt) caused an increase in the cellular uptake by 1.43fold, as well as an increase in the MST of the brain tumor-bearing rats by 1.7-fold compared to the PL-Cispt (P<0.001). TPL-Cispt was potent enough to cause a significant decrease in Cispt toxicity effects (P<0.001). Conclusion: Overall, the results suggest that targeting the Cispt-loaded PEGylated liposome is a promising approach to develop formulation with enhanced efficacy and reduced toxicity for the treatment of brain tumor.

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