Chen Yusang, Wu Meiling, Xu Xiao, Zhu Shunyao, Shen Mengdan, Ma Anting, She Zhennan, Shi Senlin, Han Xi, Zhang Ting
School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Asset Management Co., Ltd, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Ultrason Sonochem. 2025 Jun 26;120:107447. doi: 10.1016/j.ultsonch.2025.107447.
This study investigated the extraction, structural characterization, and antioxidant activity of polysaccharides derived from Akebia Fruit. The ultrasonic-assisted extraction (UAE) process of polysaccharides was optimized through the application of the Box-Behnken Design (BBD) in conjunction with the genetic algorithm-back propagation (GA-BP) artificial neural network model. The experimental data showed that the GA-BP model performed better than the BBD model, and more polysaccharide components could be extracted under the process parameters predicted by this model. The GA-BP model predicted the optimal extraction parameters as follows: the extraction temperature was 65 ℃, the solid-liquid ratio was 1:50 g/mL, the extraction power was 400 W. Experimental results showed that combining UAE with GA-BP artificial neural network not only enabled efficient extraction of polysaccharides but also optimized the extraction process. After purification, AFP-1 was obtained and its characterization was conducted. Structural analysis results indicated that compound AFP-1 was a homogeneous polysaccharide with a lamellar structure and a molecular weight of 13,775 Da. The polysaccharide contained a network of pyranose rings, which were interconnected to form a complex framework. The polysaccharide was composed of a mixture of monosaccharide units, specifically arranged in a specific configuration that included mannose, ribose, glucose, galactose, and fucose. Finally, the antioxidant activity of AFP-1 was preliminarily verified through in vitro experiments. Subsequent research could systematically explore the biological activities of AFP-1, by employing both in vitro and in vivo models.
本研究对木通果实多糖的提取、结构表征及抗氧化活性进行了研究。通过应用Box-Behnken设计（BBD）结合遗传算法-反向传播（GA-BP）人工神经网络模型，对多糖的超声辅助提取（UAE）工艺进行了优化。实验数据表明，GA-BP模型的性能优于BBD模型，在该模型预测的工艺参数下可提取出更多的多糖成分。GA-BP模型预测的最佳提取参数如下：提取温度为65℃，固液比为1:50 g/mL，提取功率为400 W。实验结果表明，将UAE与GA-BP人工神经网络相结合，不仅能够高效提取多糖，还能优化提取工艺。纯化后得到AFP-1并对其进行了表征。结构分析结果表明，化合物AFP-1是一种具有层状结构、分子量为13775 Da的均一多糖。该多糖含有吡喃糖环网络，这些环相互连接形成一个复杂的框架。该多糖由单糖单元混合物组成，具体排列成特定的构型，包括甘露糖、核糖、葡萄糖、半乳糖和岩藻糖。最后，通过体外实验初步验证了AFP-1的抗氧化活性。后续研究可通过体外和体内模型系统地探索AFP-1的生物活性。
