During recent years, there has been growing interest in the use of nanoemulsion as a drug-carrier system for topical delivery. A nanoemulsion is a transparent mixture of oil, surfactant and water with a very low viscosity, usually the product of its high water content. The present study investigated the modification of nanoemulsions with different hydrocolloid gums, to enhanced drug delivery of ibuprofen. The in vitro characterization of the initial and modified nanoemulsions was also studied.
A Taguchi robust design method with an L₉ orthogonal array was implemented to optimize experimental conditions for the biosynthesis of triethanolamine (TEA)-based esterquat cationic surfactants using an enzymatic reaction method. The esterification reaction conversion% was considered as the response. Enzyme amount, reaction time, reaction temperature and molar ratio of substrates, [oleic acid: triethanolamine (OA:TEA)] were chosen as main parameters. As a result of the Taguchi analysis in this study, the molar ratio of substrates was found to be the most influential parameter on the esterification reaction conversion%. The amount of enzyme in the reaction had also a significant effect on reaction conversion%.
e effects of biological pretreatment on the rubberwood (Hevea brasiliensis), was evaluated after cultivation of white rot fungi Ceriporiopsis subvermispora, Trametes versicolor, and a mixed culture of C. subvermispora and T. versicolor. The analysis of chemical compositions indicated that C. subvermispora had greater selectivity for lignin degradation with the highest lignin and hemicellulose loss at 45.06% and 42.08%, respectively, and lowest cellulose loss (9.50%) after 90 days among the tested samples. X-ray analysis showed that pretreated samples had a higher crystallinity than untreated samples. The sample pretreated by C. subvermispora presented the highest crystallinity of all the samples which might be caused by the selective degradation of amorphous components. Fourier transform infrared (FT-IR) spectroscopy demonstrated that the content of lignin and hemicellulose decreased during the biological pretreatment process. A study on hydrolysis of rubberwood treated with C. subvermispora, T. versicolor, and mixed culture for 90 days resulted in an increased sugar yield of about 27.67%, 16.23%, and 14.20%, respectively, as compared with untreated rubberwood (2.88%). The results obtained demonstrate that rubberwood is a potential raw material for industrial applications and white rot fungus C. subevermispora provides an effective method for improving the enzymatic hydrolysis of rubberwood.
Rubberwood (Hevea brasiliensis), a potential raw material for bioethanol production due to its high cellulose content, was used as a novel feedstock for enzymatic hydrolysis and bioethanol production using biological pretreatment. To improve ethanol production, rubberwood was pretreated with white rot fungus Ceriporiopsis subvermispora to increase fermentation efficiency. The effects of particle size of rubberwood (1 mm, 0.5 mm, and 0.25 mm) and pretreatment time on the biological pretreatment were first determined by chemical analysis and X-ray diffraction and their best condition obtained with 1 mm particle size and 90 days pretreatment. Further morphological study on rubberwood with 1 mm particle size pretreated by fungus was performed by FT-IR spectra analysis and SEM observation and the result indicated the ability of this fungus for pretreatment. A study on enzymatic hydrolysis resulted in an increased sugar yield of 27.67% as compared with untreated rubberwood (2.88%). The maximum ethanol concentration and yield were 17.9 g/L and 53% yield, respectively, after 120 hours. The results obtained demonstrate that rubberwood pretreated by C. subvermispora can be used as an alternative material for the enzymatic hydrolysis and bioethanol production.
Lipase-catalyzed production of triethanolamine-based esterquat by esterification of oleic acid (OA) with triethanolamine (TEA) in n-hexane was performed in 2 L stirred-tank reactor. A set of experiments was designed by central composite design to process modeling and statistically evaluate the findings. Five independent process variables, including enzyme amount, reaction time, reaction temperature, substrates molar ratio of OA to TEA, and agitation speed, were studied under the given conditions designed by Design Expert software. Experimental data were examined for normality test before data processing stage and skewness and kurtosis indices were determined. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum conversion of product. Response surface methodology with central composite design gave the best performance in this study, and the methodology as a whole has been proven to be adequate for the design and optimization of the enzymatic process.
An Artificial Neural Network (ANN) based on the Quick Propagation (QP) algorithm was used in conjunction with an experimental design to optimize the lipase-catalyzed reaction conditions for the preparation of a triethanolamine (TEA)-based esterquat cationic surfactant. Using the best performing ANN, the optimum conditions predicted were an enzyme amount of 4.77 w/w%, reaction time of 24 h, reaction temperature of 61.9 °C, substrate (oleic acid: triethanolamine) molar ratio of 1:1 mole and agitation speed of 480 r.p.m. The relative deviation percentage under these conditions was less than 4%. The optimized method was successfully applied to the synthesis of the TEA-based esterquat cationic surfactant at a 2,000 mL scale. This method represents a more flexible and convenient means for optimizing enzymatic reaction using ANN than has been previously reported by conventional methods.