Li Chaoping, Zhu Xinyan, Shen Tao, Wang Yuanzhong, Zhang Rongping
College of Traditional Chinese Medicine & Yunnan Key Laboratory of Southern Medicinal Resources, Yunnan University of Chinese Medicine, Kunming, 650500, China.
Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, 2238, Beijing Road, Panlong District, Kunming, 650200, China.
Chem Biodivers. 2025 Feb;22(2):e202401228. doi: 10.1002/cbdv.202401228. Epub 2024 Nov 9.
Gentiana rigescens Franch. (G. rigescens) is a unique traditional medicinal herb from southwestern China, and its clinical mechanism for the treatment of hepatitis and the quality differences between different origins are not clear. The research aims to analyze the mechanisms for the treatment of hepatitis and differences in inter-origin differences using analytical techniques, chemometrics, and network pharmacology. Through infrared spectroscopy, spectral images, and high-performance liquid chromatography (HPLC) analysis, it was found that there were differences in absorbance intensity and significant differences in compound content among the samples' origin. G. rigescens iridoids and flavonoids exert therapeutic effects on hepatitis through multiple targets (GAPDH, EGFR, and MMP9, etc.) and multiple pathways (non-small cell lung cancer, hepatitis C, etc.). The above HPLC, chemometrics, and network pharmacology results revealed that gentiopicroside, and swertiamarine was the best quality marker among origins. The accuracy of the ResNet model train, test, and external validation sets for synchronous spectral images were 100 %, which could be utilized as an effective tool for tracing G. rigescens's origins. The R of the calibration and validation sets of the PLSR model was higher than 0.70. This model had excellent predictive performance in determining the content of gentiopicroside and swertiamarine, and could quickly, accurately, and effectively predict these two compounds. The research investigates the differences in G. rigescens origins from multiple perspectives, establishes image recognition models and prediction models, and provides new methods and theoretical basis for quality control of G. rigescens.
滇龙胆（Gentiana rigescens Franch.）是中国西南地区特有的传统药用植物，其治疗肝炎的临床机制以及不同产地之间的质量差异尚不清楚。本研究旨在运用分析技术、化学计量学和网络药理学分析其治疗肝炎的机制以及产地间的差异。通过红外光谱、光谱成像和高效液相色谱（HPLC）分析发现，样品产地之间的吸光度强度存在差异，化合物含量也有显著差异。滇龙胆环烯醚萜类和黄酮类化合物通过多个靶点（甘油醛-3-磷酸脱氢酶、表皮生长因子受体和基质金属蛋白酶9等）和多条途径（非小细胞肺癌、丙型肝炎等）对肝炎发挥治疗作用。上述HPLC、化学计量学和网络药理学结果表明，龙胆苦苷和獐牙菜苦苷是不同产地中最佳的质量标志物。ResNet模型对同步光谱图像的训练集、测试集和外部验证集的准确率均为100%，可作为追踪滇龙胆产地的有效工具。PLSR模型校正集和验证集的R高于0.70。该模型在测定龙胆苦苷和獐牙菜苦苷含量方面具有优异的预测性能，能够快速、准确、有效地预测这两种化合物。本研究从多个角度考察了滇龙胆产地的差异，建立了图像识别模型和预测模型，为滇龙胆的质量控制提供了新方法和理论依据。
