Optimization of Ultrasonic-Assisted Extraction of α-Glucosidase Inhibitors from Dryopteris crassirhizoma Using Artificial Neural Network and Response Surface Methodology

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초록

Dryopteris crassirhizoma Nakai is a plant with significant medicinal properties, such as anticancer, antioxidant, and anti-inflammatory activities, making it an attractive research target. Our study describes the isolation of major metabolites from D. crassirhizoma, and their inhibitory activities on ff-glucosidase were evaluated for the first time. The results revealed that nortrisflavaspidic acid ABB (2) is the most potent alpha-glucosidase inhibitor, with an IC50 of 34.0 +/- 0.14 mu M. In addition, artificial neural network (ANN) and response surface methodology (RSM) were used in this study to optimize the extraction conditions and evaluate the independent and interactive effects of ultrasonic-assisted extraction parameters. The optimal extraction conditions are extraction time of 103.03 min, sonication power of 342.69W, and solvent-to-material ratio of 94.00 mL/g. The agreement between the predicted models of ANN and RSM and the experimental values was notably high, with a percentage of 97.51% and 97.15%, respectively, indicating that both models have the potential to be utilized for optimizing the industrial extraction process of active metabolites from D. crassirhizoma. Our results could provide relevant information for producing high-quality extracts from D. crassirhizoma for functional foods, nutraceuticals, and pharmaceutical industries.

키워드

Dryopteris crassirhizoma; phloroglucinol; alpha-glucosidase; response surface methodology; artificial neural network; PHLOROGLUCINOLS; UAE
제목
Optimization of Ultrasonic-Assisted Extraction of α-Glucosidase Inhibitors from Dryopteris crassirhizoma Using Artificial Neural Network and Response Surface Methodology
저자
Phong, Nguyen Viet; Gao, Dan; Kim, Jeong Ah; Yang, Seo Young
DOI
10.3390/metabo13040557
발행일
2023-04
유형
Article
저널명
Metabolites
권
13
호
4