College of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, PR China.
College of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, PR China.
Carbohydr Polym. 2016 Oct 20;151:358-363. doi: 10.1016/j.carbpol.2016.05.079. Epub 2016 May 24.
Benincasa hispida is a popular vegetable in China. Our previous experiments suggested that polysaccharides isolated from B. hispida fruits (PBH) have antiglycation effect and DPPH free radical scavenging activity. Ultrasonic treatments can be used to extract polysaccharides from Benincasa hispida (PBH). The aim of this study was to investigate the correlation between the ultrasonic treatment conditions and the antiglycation activity of PBH. A mathematical model was generated with an artificial neural network (ANN) toolbox from MATLAB to analyze the effects of ultrasonic treatment conditions on antiglycation activity. The response surface plots showed relationships between ultrasonic extraction conditions and bioactivity. The R(2) value of the model was 0.9919, which suggested good fitness of the neural network. The application of genetic algorithms showed that the optimal ultrasonic extraction conditions resulted in the highest antiglycation activity for PBH. These were 150W, 46°C, and 35min. These conditions produced a predicted antiglycation activity of 41.2%; the actual activity was 40.9% under optimal conditions. This is very close to the predicted value. The experimental data indicated that the PBH possessed both antiglycation and antioxidant activities. The maximum actual value of antiglycation was 101.7% that of the positive control, and the PBH inhibited the DPPH free radicals with an EC50 value of 0.98mg/mL. This is 66.2% that of ascorbic acid. These results explained the observations that B. hispida can decrease glucose levels in diabetic patients. The experimental results also showed that the ANN could be used for optimization and prediction.
白皮冬瓜是中国常见的蔬菜。我们之前的实验表明，从白皮冬瓜果实中分离得到的多糖（PBH）具有抗糖化作用和 DPPH 自由基清除活性。超声处理可用于从白皮冬瓜（PBH）中提取多糖。本研究旨在探讨超声处理条件与 PBH 抗糖化活性之间的相关性。利用 MATLAB 中的人工神经网络（ANN）工具箱生成数学模型，分析超声处理条件对糖化活性的影响。响应面图显示了超声提取条件与生物活性之间的关系。模型的 R(2)值为 0.9919，表明神经网络拟合度较好。遗传算法的应用表明，超声提取的最佳条件可使 PBH 的抗糖化活性达到最高。这些最佳条件为 150W、46°C 和 35min。在此条件下，预测的抗糖化活性为 41.2%；在最佳条件下，实际活性为 40.9%。这非常接近预测值。实验数据表明，PBH 具有抗糖化和抗氧化活性。抗糖化的最大实际值是阳性对照的 101.7%，PBH 对 DPPH 自由基的抑制作用的 EC50 值为 0.98mg/mL，这相当于抗坏血酸的 66.2%。这些结果解释了白皮冬瓜可以降低糖尿病患者血糖水平的观察结果。实验结果还表明，ANN 可用于优化和预测。
