PDF(Pubmed)
Abstract：
UNASSIGNED: Scutellariae Radix (SR), derived from the root of Scutellaria baicalensis Georgi, is a traditional Chinese medicine (TCM) for clearing heat and cooling blood. It has been used as a traditional herbal medicine and is popular as a functional food in Asian countries today.
UNASSIGNED: In this study, UPLC-Q-TOF-MS was first employed to identify the chemical components in the ethanol extract of SR. Then, the extraction process was optimized using star point design-response surface methodology. Fingerprints of different batches and processed products were established, and chemical markers were screened through a combination of various artificial neural network models. Finally, network pharmacology and molecular simulation techniques were utilized for verification to determine the quality markers.
UNASSIGNED: A total of 35 chemical components in SR were identified, and the optimal extraction process was determined as follows: ultrasonic extraction with 80% methanol at a ratio of 120:1 for 70 minutes, with a soaking time of 30 minutes. Through discriminant analysis using various artificial neural network models, the samples of SR could be classified into two categories based on their growth years: Kuqin (dried roots of older plants) and Ziqin (roots of younger plants). Moreover, the samples within each category could be further clustered according to their origins. The four different processed products of SR could also be distinguished separately. Finally, through the integration of network pharmacology and molecular simulation techniques, it was determined that baicalin, baicalein, wogonin, norwogonin, norwogonin-8-O-glucuronide, skullcapflavone II, hispidulin, 8, 8\"-bibaicalein, and oroxylin A-7-O-beta-D-glucuronide could serve as quality markers for SR.
UNASSIGNED: The primary factors affecting the quality of SR were its growth years. The geographic origin of SR was identified as a secondary factor affecting its quality. Processing also had a significant impact on its quality. The selected quality markers have laid the foundation for the quality control of SR, and this research strategy also provides a research paradigm for improving the quality of TCM.
UNASSIGNED: In this study, UPLC-Q-TOF-MS was first employed to identify the chemical components in the ethanol extract of SR. Then, the extraction process was optimized using star point design-response surface methodology. Fingerprints of different batches and processed products were established, and chemical markers were screened through a combination of various artificial neural network models. Finally, network pharmacology and molecular simulation techniques were utilized for verification to determine the quality markers.
UNASSIGNED: A total of 35 chemical components in SR were identified, and the optimal extraction process was determined as follows: ultrasonic extraction with 80% methanol at a ratio of 120:1 for 70 minutes, with a soaking time of 30 minutes. Through discriminant analysis using various artificial neural network models, the samples of SR could be classified into two categories based on their growth years: Kuqin (dried roots of older plants) and Ziqin (roots of younger plants). Moreover, the samples within each category could be further clustered according to their origins. The four different processed products of SR could also be distinguished separately. Finally, through the integration of network pharmacology and molecular simulation techniques, it was determined that baicalin, baicalein, wogonin, norwogonin, norwogonin-8-O-glucuronide, skullcapflavone II, hispidulin, 8, 8\"-bibaicalein, and oroxylin A-7-O-beta-D-glucuronide could serve as quality markers for SR.
UNASSIGNED: The primary factors affecting the quality of SR were its growth years. The geographic origin of SR was identified as a secondary factor affecting its quality. Processing also had a significant impact on its quality. The selected quality markers have laid the foundation for the quality control of SR, and this research strategy also provides a research paradigm for improving the quality of TCM.
摘要：
■黄芩（SR），来源于黄芩的根，是一种清热凉血的传统中药。它已被用作传统草药，并在当今的亚洲国家中作为功能性食品而流行。
■在这项研究中，UPLC-Q-TOF-MS首次用于鉴定SR乙醇提取物中的化学成分。然后，采用星点设计-响应面法对提取工艺进行了优化。建立了不同批次和加工产品的指纹图谱，和化学标记物通过各种人工神经网络模型的组合进行筛选。最后,网络药理学和分子模拟技术用于验证以确定质量标记。
■共鉴定出SR中的35种化学成分，并确定最佳提取工艺为:用80%甲醇以120:1的比例超声提取70分钟,浸泡时间为30分钟。通过使用各种人工神经网络模型的判别分析，SR的样品可以根据其生长年限分为两类：库琴（较老植物的干燥根）和紫琴（较年轻植物的根）。此外，每个类别中的样本可以根据其来源进一步聚类。SR的四种不同的加工产品也可以分别区分。最后,通过网络药理学和分子模拟技术的整合，确定黄芩苷,黄芩素,Wogonin,诺沃金宁,去甲Wogonin-8-O-葡糖苷酸，黄芩黄酮II,hispidulin,8，8“-bibaicalein，和OxylinA-7-O-β-D-葡糖苷酸可以作为SR的质量标记。
■影响SR质量的主要因素是其生长年限。SR的地理起源被确定为影响其质量的次要因素。加工对其质量也有很大影响。选定的质量标记为SR的质量控制奠定了基础，这一研究策略也为提高中药质量提供了研究范式。
■在这项研究中，UPLC-Q-TOF-MS首次用于鉴定SR乙醇提取物中的化学成分。然后，采用星点设计-响应面法对提取工艺进行了优化。建立了不同批次和加工产品的指纹图谱，和化学标记物通过各种人工神经网络模型的组合进行筛选。最后,网络药理学和分子模拟技术用于验证以确定质量标记。
■共鉴定出SR中的35种化学成分，并确定最佳提取工艺为:用80%甲醇以120:1的比例超声提取70分钟,浸泡时间为30分钟。通过使用各种人工神经网络模型的判别分析，SR的样品可以根据其生长年限分为两类：库琴（较老植物的干燥根）和紫琴（较年轻植物的根）。此外，每个类别中的样本可以根据其来源进一步聚类。SR的四种不同的加工产品也可以分别区分。最后,通过网络药理学和分子模拟技术的整合，确定黄芩苷,黄芩素,Wogonin,诺沃金宁,去甲Wogonin-8-O-葡糖苷酸，黄芩黄酮II,hispidulin,8，8“-bibaicalein，和OxylinA-7-O-β-D-葡糖苷酸可以作为SR的质量标记。
■影响SR质量的主要因素是其生长年限。SR的地理起源被确定为影响其质量的次要因素。加工对其质量也有很大影响。选定的质量标记为SR的质量控制奠定了基础，这一研究策略也为提高中药质量提供了研究范式。
