Optimization of ß-Cyclodextrin-Assisted Extraction of Apigenin and Luteolin from Chrysanthemum indicum L. Using Response Surface Methodology Combined with Different Optimization Algorithms and Evaluation of Its Antioxidant Capacity.

Cyclodextrins and their derivatives have shown successful applications in extracting active compounds from medicinal plants. However, the use of ß-cyclodextrin derivatives for extracting apigenin and luteolin from Chrysanthemum indicum L. remains unexplored. Additionally, the application of nature-inspired optimization algorithms in optimizing extraction conditions has been limited. Therefore, this study was performed with the aims of optimizing the extraction of apigenin and luteolin from C. indicum with the assistance of 2-hydroxypropyl-ß-cyclodextrin (HP-ß-CD) using response surface methodology combined with various optimization algorithms, including desirability function approach, genetic algorithm, particle swarm optimization, and firefly algorithm. The results showed that the optimal conditions obtained by the four algorithms were consistent, with an extraction time of 60 min, HP-ß-CD concentration of 30 mg/mL, and a solvent-to-solid ratio of 24 mg/mL. At these conditions, the apigenin and luteolin contents were 1.362±0.008 and 8.724±0.117 mg/g, respectively. The results also showed that HP-ß-CD-assisted extraction exhibited significantly higher apigenin and luteolin contents compared to conventional solvent. Comparable results were also yielded from the antioxidant assay. Our study suggested that the nature-inspired optimization algorithms might be potential options in enhancing the effectiveness of the traditional response surface methodology for the optimization of extraction of natural products.

Self-Determination Theory and Accountant Employees' Psychological Wellbeing: The Roles of Positive Affectivity and Psychological Safety.

This study investigates the influence of self-determination motivations on accountant employees' psychological wellbeing with the mediating role of positive affectivity and the moderating role of psychological safety. Multivariate analysis and structural equation modeling are used to analyze a three-way time-lagged sample data of 391 accountant employees. Results indicate that positive affectivity positively mediates the relationship between extrinsic motivation and psychological wellbeing and between intrinsic motivation and psychological wellbeing. Furthermore, psychological safety positively moderates the relationship between extrinsic motivation and positive affectivity and between intrinsic motivation and positive affectivity. In addition, psychological safety also positively moderates the relationship between positive affectivity and psychological wellbeing. The findings of this study provide implications for researchers and business managers in managing and enhancing accountant employees' psychological wellbeing.

Application of multivariate linear regression models for selection of deep eutectic solvent for extraction of apigenin and luteolin from Chrysanthemum indicum L.

INTRODUCTION: Among a variety of compounds presented in chrysanthemum, apigenin and luteolin are the two main components that play a major role in numerous biological activities of this herb. OBJECTIVES: We aimed to obtain linear models showing the dependence of the yield of extraction of apigenin and luteolin on the composition of deep eutectic solvent and investigate the extraction of these two ingredients from Chrysanthemum indicum L. METHODS: Two models showing the dependence of luteolin and apigenin concentrations on the composition of the solvent were established using a multilinear regression algorithm and were applied to screen 119 different solvents. After that, the extraction process was optimized using response surface methodology and an artificial neural network. Apigenin and luteolin were recovered from the extract by the combination of distillation and addition of water. RESULTS: The screening results on 119 solvents revealed that choline chloride-acetic acid (1:4) was the most suitable deep eutectic solvent. It was showed that both response surface methodology and the artificial neural network could accurately determine the optimal conditions of extraction of apigenin and luteolin from C. indicum L., including time of extraction (65 minutes), temperature of extraction (90°C) and water content (20%). By the combination of distillation and addition of water, apigenin and luteolin could be effectively recovered from the deep eutectic solvent extract with a recovery rate of over 80%. CONCLUSIONS: Deep eutectic solvent could be used as an effective green alternative to the conventional solvents for the extraction of bioactive compounds from plants.