Neuroprotective Effect of Ginseng Fibrous Root Enzymatic Hydrolysate against Oxidative Stress

Oxidative stress is one of the potential causes of nervous system disease. Ginseng extract possesses excellent antioxidant activity; however, little research on the function of the ginseng fibrous root. This study aimed to investigate the neuroprotective effects of ginseng fibrous root to alleviate the pathogenesis of Alzheimer’s disease (AD) against oxidative stress. Ginseng fibrous root enzymatic hydrolysate (GFREH) was first prepared by digesting ginseng fibrous roots with alkaline protease. In vitro, the GFREH showed antioxidant activities in free radical scavenging mechanisms. With a cellular model of AD, GFREH inhibited the increase in Ca²⁺ levels and intracellular ROS content, maintained the balance of mitochondrial membrane potential, and relieved L-glutamic acid-induced neurotoxicity. In vivo, GFREH improved the survival rate of Caenorhabditis elegans (C. elegans) under oxidative stress, upregulated SOD-3 expression, and reduced reactive oxygen species (ROS) content. Therefore, our findings provide evidence for the alleviation effect of GFREH against oxidative stress in neuroprotection, which may accelerate the development of anti-Alzheimer’s drugs and treatments in the future.     

Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM

Ginseng, which contains abundant ginsenosides, grows mainly in the Jilin, Liaoning, and Heilongjiang in China. It has been reported that the quality and traits of ginsengs from different origins were greatly different. To date, the accurate prediction of the origins of ginseng samples is still a challenge. Here, we integrated ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) with a support vector machine (SVM) for rapid discrimination and prediction of ginseng from the three main regions where it is cultivated in China. Firstly, we develop a stable and reliable UHPLC-Q-TOF-MS method to obtain robust information for 31 batches of ginseng samples after reasonable optimization. Subsequently, a rapid pre-processing method was established for the rapid screening and identification of 69 characteristic ginsenosides in 31 batches ginseng samples from three different origins. The SVM model successfully distinguished ginseng origin, and the accuracy of SVM model was improved from 83% to 100% by optimizing the normalization method. Six crucial quality markers for different origins of ginseng were screened using a permutation importance algorithm in the SVM model. In addition, in order to validate the method, eight batches of test samples were used to predict the regions of cultivation of ginseng using the SVM model based on the six selected quality markers. As a result, the proposed strategy was suitable for the discrimination and prediction of the origin of ginseng samples.     

红外光谱结合判别分析对三七道地性及产地的鉴别研究

利用傅里叶变换红外光谱结合判别分析对三七的道地性及产地进行鉴别研究。测试了11个县13个种植点的136株三七主根样品的红外光谱,利用Omnic8.0软件计算了每个样品红外光谱的二阶导数光谱。分别采用1 800~700cm-1光谱范围的红外光谱数据和二阶导数光谱数据,运用逐步判别分析法建立模型对三七的道地性进行判别研究,二阶导数光谱数据建立的模型对三七道地性的识别效果更好,回判正确率为100%,预测正确率为93.4%。采用交叉验证法检验了模型的稳定性,并对此方法进行了外推性验证。用二阶导数光谱数据结合相同的判别方法对三七的产地进行识别,比较了不同光谱范围和不同训练样本数建立的模型判别效果,每个种植点选择8个样本作为训练样本,采用1 500~1 200cm-1光谱范围的数据建立的模型判别效果较好,回判正确率为99.0%,预测正确率为76.5%。结果表明,红外光谱结合判别分析对三七道地性的识别效果好,有望成为实际中鉴别三七道地性的新方法;对三七产地的识别有一定的效果,可作为三七产地鉴别的一种新思路。     

Preparative isolation and purification of ginsenosides Rf,Re, Rd and Rb1 from the roots of Panax ginseng with a salt/containing solvent system and flow step-gradient by high performance counter-current chromatography coupled with an evaporative light scattering detector

Ginseng is a popular herb worldwide and has had varied uses in traditional Asian medicine for thousands of years. There are several different species of the herb, but all share the same constituents. Ginsenosides, the most extensively studied chemical components of ginseng, are generally considered to be one of the most important active ingredients of the plant. In this study, we have developed fast and efficient methodology for isolation of four known ginsenosides Rf, Rd, Re and Rb1 from Ginseng by high performance counter-current chromatography (HPCCC) coupled with evaporative light scattering detection (ELSD). The crude sample for HPCCC was purified firstly from a ginseng extraction using macroporous resin. The enriched saponin fraction (480 mg) was separated by using methylene chloride–methanol–5 mM aqueous ammonium acetate–isopropanol (6:2:4:3, v/v,) as the two-phase solvent system and yielded 10.7 mg of Rf, 11.0 mg of Rd, 13.4 mg of Re and 13.9 mg of Rb1. The purity of these ginsenosides was 99.2%, 88.3%, 93.7% and 91.8%, respectively assessed by HPLC-DAD-ELSD, and their structures were characterized by electrospray ionization mass spectrometry (ESI-MS) and compared with standards. Ammonium acetate was used to shorten the separation time and eliminate emulsification together with a flow step-gradient. The salt can be removed by re-dissolving the sample using acetone.     

Determination of Active Components in a Natural Herb with Near Infrared Spectroscopy Based on Artificial Neural Networks

The non-linear relationships between the contents of ginsenoside Rg1, Rb2, Rd and Panax notoginseng saponins(PNS) in Panax notoginseng root herb and the near infrared(NIR) diffuse reflectance spectra of the herb were established by means of artificial neural networks(ANNs). Four three-layered perception feed-for-ward networks were trained with an error back-propagation algorithm. The significant principal components of the NIR spectral data matrix were utilized as the input of the networks. The networks architecture and parameters were selected so as to offer less prediction errors. Relative prediction errors for Rg1, Rb1, Rd and PNS obtained with the optimum ANN models were 8.99%, 6.54%, 8.29%, and 5.17%, respectively, which were superior to those obtained with PLSR methods. It is verified that ANN is a suitable approach to model this complex non-linearity. The developed method is fast, non-destructive and accurate and it provides a new efficient approach for determining the active components in the complex system of natural herbs.     

液质联用技术分析西洋参花化学成分及H9c2心肌细胞损伤保护作用

高温高压转化前后西洋参花醇提液经正己烷、氯仿、乙酸乙酯和正丁醇分级萃取后共得10种不同极性组分,通过H9c2心肌细胞损伤模型筛选最佳活性组分,并对其进行抗氧化活性的测定以及化学组成分析,利用液质联用技术检测其处理前后的化学成分。结果表明,提取的10种活性组分中,高温高压转化后西洋参花乙酸乙酯萃取层(PEE)能够有效保护H9c2心肌细胞损伤,显著提高细胞存活率并降低细胞ROS水平,与高温高压转化处理前西洋参花乙酸乙酯层(OEE)相较,二者总体皂苷含量相近且均具有较强的抗氧化活性。通过液质分析,初步确定了PEE中所含高温高压转化裂解生成的Rk₁与Rg₅更具良好的心肌细胞损伤保护作用。     

Production of Minor Ginsenosides from Panax notoginseng Flowers by Cladosporium xylophilum

Panax notoginseng flowers have the highest content of saponins compared to the other parts of Panax notoginseng, but minor ginsenosides have higher pharmacological activity than the main natural ginsenosides. Therefore, this study focused on the transformation of the main ginsenosides in Panax notoginseng flowers to minor ginsenosides using the fungus of Cladosporium xylophilum isolated from soil. The main ginsenosides Rb₁, Rb₂, Rb₃, and Rc and the notoginsenoside Fa in Panax notoginseng flowers were transformed into the ginsenosides F₂ and Rd₂, the notoginsenosides Fd and Fe, and the ginsenoside R₇; the conversion rates were 100, 100, 100, 88.5, and 100%, respectively. The transformation products were studied by TLC, HPLC, and MS analyses, and the biotransformation pathways of the major ginsenosides were proposed. In addition, the purified enzyme of the fungus was prepared with the molecular weight of 66.4 kDa. The transformation of the monomer ginsenosides by the crude enzyme is consistent with that by the fungus. Additionally, three saponins were isolated from the transformation products and identified as the ginsenoside Rd₂ and the notoginsenosides Fe and Fd by NMR and MS analyses. This study provided a unique and powerful microbial strain for efficiently transformating major ginsenosides in P. notoginseng flowers to minor ginsenosides, which will help raise the functional and economic value of the P. notoginseng flower.     

人参中皂苷类化合物的HPLC-ESI MS研究

利用高效液相色谱与电喷雾质谱联用技术分析鉴定了人参粗提物中人参皂苷类化合物。实验采用反相C18色谱柱,二元线性梯度洗脱（0．2％的醋酸水溶液和乙腈）,分离并检测了人参中的皂苷类化合物：通过与电喷雾质谱的联用和质谱的源内CID技术获得了其中主要色谱峰相对应化合物的相对分子质量和结构信息。     

FTIR结合化学计量学对三七地下部位鉴别及皂苷含量预测

当今中药市场上掺假现象屡见不鲜，不良商贩利用三七须根粉末假冒主根和剪口粉末，严重影响三七的质量与药效。通过傅里叶变换红外光谱(FTIR)结合化学计量学建立三七主根、剪口和须根粉末鉴别及四种皂苷含量快速预测模型，为快速三七质量控制提供基础。采集三七主根、剪口和须根红外光谱，超高效液相色谱(UPLC)测量样品中三七皂苷R₁、人参皂苷Rg₁、人参皂苷Rb₁和人参皂苷Rd含量。采用纵坐标归一化及二阶导数对原始红外光谱进行预处理；Kennard-stone算法将60个样本分为2/3训练集与1/3预测集。训练集数据结合支持向量机(SVM)判别建立三七主根、剪口和须根粉末鉴别模型，最佳核函数c和g采用交叉验证进行网格式搜索，预测集数据用于对判别模型进行外部验证。正交信号校正偏最小二乘回归(OSC-PLSR)建立三七中四种皂苷含量预测模型，红外光谱采用一阶、二阶导数及Savitsky-Golay平滑5点、7点、9点、11点预处理。60个样本分为2/3训练集与1/3预测集，训练集数据建立OSC-PLSR模型，预测集数据对OSC-PLSR模型的预测结果进行外部验证。结果显示： (1)二阶导数可有效的分离原始谱图的叠合隐蔽谱峰，并提高谱图的分辨率；(2)交叉验证网格式搜索计算出最佳核函数c=2.828 43，g=4.882 81×10-4，此时训练集判别正确率为100%；(3)SVM判别模型核函数设置为最佳核函数，预测集数据外部验证正确率为100%，所有样本均被正确鉴别；(4)三七皂苷R₁、人参皂苷Rg₁、人参皂苷Rb₁和人参皂苷Rd最优含量预测模型预测值与UPLC检测值接近，预测效果良好。FTIR结合SVM判别能对三七主根、剪口和须根粉末快速鉴别，结合OSC-PLSR能对四种皂苷含量进行准确预测。该方法准确可靠，可为中药材三七提供快速有效的质量控制。