Department of Pharmacognosy, Hanoi University of Pharmacy, Hanoi, Vietnam.
Biomed Chromatogr. 2021 Nov;35(11):e5181. doi: 10.1002/bmc.5181. Epub 2021 Jun 9.
Celery seeds are medicinal herbs used for the prevention and treatment of gout as these have the ability to inhibit the activity of xanthine oxidase and reduce the concentration of serum uric acid. In this study, the relationship between xanthine oxidase inhibitory effects and high-performance thin-layer chromatography data of celery seed extracts was established using multilayer neural network (MNN) in combination with principal component analysis (PCA). The constructed MNN-PCA model was stable and had accurate prediction ability with coefficient of determination = 0.9998, leave-one-out coefficient = 0.7371, root mean square error = 0.0025, and mean absolute deviation = 0.0019 for the training set and coefficient of determination = 0.8124, root mean square error = 0.0784, and mean absolute deviation = 0.0645 for the test set. This model can be used to identify the main compounds related to the xanthine oxidase inhibitory effect of celery seed extract. These results can be applied not only to celery extract but also to other herbal medicines.
芹菜籽是一种药食同源的中药材，具有抑制黄嘌呤氧化酶的活性，降低血尿酸浓度的作用，用于痛风的防治。本研究采用多层神经网络（MNN）结合主成分分析（PCA）建立了芹菜籽提取物的黄嘌呤氧化酶抑制作用与高效薄层色谱数据之间的关系。所建立的 MNN-PCA 模型稳定性好，预测能力准确，其训练集的决定系数为 0.9998，留一法验证系数为 0.7371，均方根误差为 0.0025，平均绝对偏差为 0.0019；测试集的决定系数为 0.8124，均方根误差为 0.0784，平均绝对偏差为 0.0645。该模型可用于鉴定与芹菜籽提取物黄嘌呤氧化酶抑制作用相关的主要化合物。该结果不仅适用于芹菜提取物，也适用于其他草药。
