Daphne genkwa (D. genkwa) is the dried flower buds of a Chinese medicinal plant with multiple biological activities. Response surface methodology (RSM) combined with artificial neural network (ANN) techniques were utilized to optimize ultrasound-assisted extraction conditions for D. genkwa. Antioxidant activity and anti-inflammatory and analgesic properties of total flavonoids from D. genkwa (TFDG) were assessed. Optimal conditions involving ultrasonic power of 225 W, 30 min extraction time, 30 mL/g liquid-solid ratio, 60 °C extraction temperature, and 70% ethanol concentration yielded a maximum total flavonoids content (TFC) of 5.41 mg/g. After microporous resin purification, four specific flavonoids in D. genkwa were identified and quantified using high-performance liquid chromatography (HPLC). The TFDG demonstrated potent antioxidant activity, with a 94% rate of scavenging the 2, 2-diphenyl-1-picrylhydrazyl (DPPH). Furthermore, TFDG exhibited pain-alleviating properties in hot plate and acetic acid-induced writhing tests and noteworthy inhibitory effects on xylene-induced ear swelling in mice. The total flavonoids extracted by ultrasound had excellent biological activity. This establishes a foundation for further investigation into the potential medical value of D. genkwa.
Keywords: Artificial neural network; Daphne genkwa; Flavonoids; Response surface methodology; Ultrasonic.
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