Design and Engineering of "Green" Nanoemulsions for Enhanced Topical Delivery of Bakuchiol Achieved in a Sustainable Manner: A Novel Eco-Friendly Approach to Bioretinol

In the present work, we establish novel "environmentally-friendly" oil-in-water nanoemulsions to enhance the transdermal delivery of bakuchiol, the so-called "bioretinol" obtained from powdered Psoralea corylifolia seeds via a sustainable process, i.e., using a supercritical fluid extraction approach with pure carbon dioxide (SC-CO₂). According to Green Chemistry principles, five novel formulations were stabilized by "green" hybrid ionic surfactants such as coco-betaine-surfactin molecules obtained from coconut and fermented rapeseed meal. Preliminary optimization studies involving three dispersion stability tests, i.e., centrifugation, heating, and cooling cycles, indicated the most promising candidates for further physicochemical analysis. Finally, nanoemulsion colloidal characterization provided by scattering (dynamic and electrophoretic light scattering as well as backscattering), microscopic (transmission electron and confocal laser scanning microscopy), and spectroscopic (UV-Vis spectroscopy) methods revealed the most stable nanocarrier for transdermal biological investigation. In vitro, topical experiments provided on human skin cell line HaCaT keratinocytes and normal dermal NHDF fibroblasts indicated high cell viability upon treatment of the tested formulation with a final 0.02-0.2 mg/mL bakuchiol concentration. This excellent biocompatibility was confirmed by ex vivo and in vivo tests on animal and human skin tissue. The improved permeability and antiaging potential of the bakuchiol-encapsulated rich extract were observed, indicating that the obtained ecological nanoemulsions are competitive with commercial retinol formulations.

Solubility of caffeine from green tea in supercritical CO2: a theoretical and empirical approach

Decaffeination of fresh green tea was carried out with supercritical CO2 in the presence of ethanol as co-solvent. The solubility of caffeine in supercritical CO2 varied from 44.19 × 10(-6) to 149.55 × 10(-6) (mole fraction) over a pressure and temperature range of 15 to 35 MPa and 313 to 333 K, respectively. The maximum solubility of caffeine was obtained at 25 MPa and 323 K. Experimental solubility data were correlated with the theoretical equation of state models Peng-Robinson (PR), Soave Redlich-Kwong (SRK), and Redlich-Kwong (RK). The RK model had regressed experimental data with 15.52 % average absolute relative deviation (AARD). In contrast, Gordillo empirical model regressed the best to experimental data with only 0.96 % AARD. Under supercritical conditions, solubility of caffeine in tea matrix was lower than the solubility of pure caffeine. Further, solubility of caffeine in supercritical CO2 was compared with solubility of pure caffeine in conventional solvents and a maximum solubility 90 × 10(-3) mol fraction was obtained with chloroform.

Modelling solubility of phenolics of mango ginger extract in supercritical carbon dioxide using equation of state and empirical models

Solubility of phenolics of mango ginger extract in supercritical carbon dioxide was studied at 40-60 °C and 100-350 bar. Critical temperature, critical pressure and critical volume of caffeic acid, the principal component of the extract were calculated using group contribution methods and compared with the values obtained by CHEMDRAW®. Vapor pressure of caffeic acid was predicted by Reidel method. Solubility prediction in supercritical carbon dioxide was studied using two different equation of states (EOS) models and eight empirical models. Peng-Robinson EOS predicted the solubility very well with average deviation of 0.68 % from the experimental solubility. Empirical equations based on the simple error minimization using non-linear regression method which do not require complex physiochemical properties was also found suitable to predict the solubility at different extraction conditions. Jouyban et al. model showed very less deviation (2.25 %) for predicted solubility values from the experiment.