Identification of the Origin, Authenticity and Quality of Panax Japonicus Based on a Multistrategy Platform

主成分分析 鉴定(生物学) 化学计量学 指纹(计算) 计算机科学 人工智能 人参皂甙 人工神经网络 皂甙 模式识别(心理学) 机器学习 计算生物学 人参 生物 医学 替代医学 病理 植物
作者
Ziying Qiu,Xiaoran Zhao,Meiqi Liu,Yanan Liu,Lili Sun,Xiaoliang Ren,Yanru Deng
出处
期刊:Combinatorial Chemistry & High Throughput Screening [Bentham Science Publishers]
卷期号:26 (7): 1375-1384 被引量:4
标识
DOI:10.2174/1386207325666220822102014
摘要

Panax Japonicus (PJ) is a widely used Chinese herbal medicine, functional food and tonic. However, its origin has a great influence on the quality of PJ, and with the increasing demand for PJ, fake and inferior products, such as Panax Stipuleanatus (PS), often appear. The identification of the origin and authenticity of PJ is critical for ensuring the quality, safety and effectiveness of drugs.Proposing a strategy to identify the origin, authenticity, and quality of PJ using HPLC fingerprints, chemometrics, and network pharmacology.The chromatographic fingerprint method was established to analyze the origin and authenticity of PJ. Multiple chemometric methods were performed to analyze the fingerprints, including a Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and Counter Propagation Artificial Neural Network (CP-ANN). Finally, the network pharmacology method was used to construct the "active ingredient-target" network, predict and assist in analyzing potential Qmarkers in PJ.Ward's method was used for the HCA. The results showed that PJ samples from different origins had significant regional differences and could be accurately distinguished from PS. The PCA classification results are consistent with the HCA classification results, further illustrating the model's accuracy. The CP-ANN model can analyze and predict PJ and PS and accurately obtain PJ and PS chemical markers to identify PJ and PS correctly. The network pharmacology of PJ was constructed, and three PJ Q-markers, namely, ginsenoside Ro, ginsenoside Rb1, and chikusetsu saponin Ⅳa, were identified, which lays a foundation for the establishment of PJ quality standards.This research provides a feasible platform for the quality evaluation of PJ in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
大个应助武雨寒采纳,获得10
1秒前
just_cook发布了新的文献求助10
2秒前
2秒前
可爱的函函应助干冷安采纳,获得10
3秒前
情怀应助合适芹菜采纳,获得10
4秒前
传奇3应助落叶风铃采纳,获得10
4秒前
科研通AI2S应助zhan采纳,获得10
5秒前
ylr发布了新的文献求助10
5秒前
5秒前
1022061620发布了新的文献求助10
6秒前
Natua完成签到,获得积分10
6秒前
chenjingying发布了新的文献求助10
7秒前
8秒前
科研通AI5应助juan采纳,获得50
8秒前
科研通AI5应助yiliu0111487采纳,获得10
9秒前
sfjww发布了新的文献求助10
10秒前
11秒前
星辰大海应助木火采纳,获得10
11秒前
欢快的芹菜完成签到,获得积分10
11秒前
11秒前
662澜关注了科研通微信公众号
12秒前
安静元槐完成签到,获得积分20
12秒前
123456完成签到 ,获得积分20
12秒前
快乐茗完成签到,获得积分10
12秒前
14秒前
14秒前
yitiaoyezi发布了新的文献求助10
14秒前
15秒前
落叶风铃完成签到,获得积分10
15秒前
16秒前
JACK完成签到,获得积分10
16秒前
长情忆秋完成签到,获得积分10
16秒前
Jaydonnn完成签到 ,获得积分10
16秒前
CodeCraft应助墨尔根戴青采纳,获得10
16秒前
Ava应助zing采纳,获得30
17秒前
17秒前
CipherSage应助完美时间线采纳,获得10
17秒前
18秒前
19秒前
xaaaa发布了新的文献求助30
19秒前
高分求助中
Worked Bone, Antler, Ivory, and Keratinous Materials 1000
Algorithmic Mathematics in Machine Learning 500
Разработка метода ускоренного контроля качества электрохромных устройств 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Advances in Underwater Acoustics, Structural Acoustics, and Computational Methodologies 300
The Monocyte-to-HDL ratio (MHR) as a prognostic and diagnostic biomarker in Acute Ischemic Stroke: A systematic review with meta-analysis (P9-14.010) 240
Dynamic Programming and Optimal Control 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3830036
求助须知:如何正确求助?哪些是违规求助? 3372542
关于积分的说明 10473141
捐赠科研通 3092138
什么是DOI,文献DOI怎么找? 1701823
邀请新用户注册赠送积分活动 818638
科研通“疑难数据库(出版商)”最低求助积分说明 770986