A three-dimensional integration strategy for Q-markers identification: Taken Euphorbia Pekinensis Radix as an example

可测试性 化学 根(腹足类) 鉴定(生物学) 电子顺磁共振 维数(图论) 主成分分析 计算生物学 生物系统 数学 统计 生物 植物 物理 核磁共振 纯数学
作者
Xiao‐Tao Zeng,Yanyan Chen,Shi‐Jun Yue,Ding‐Qiao Xu,Rui‐Jia Fu,JieYang,Yuping Tang
出处
期刊:Journal of Pharmaceutical and Biomedical Analysis [Elsevier]
卷期号:224: 115170-115170 被引量:5
标识
DOI:10.1016/j.jpba.2022.115170
摘要

Euphorbia Pekinensis Radix (EPR) is an important antitumor medicinal resource. However, quality control of EPR has not been well established due to the lack of quality markers (Q-markers) research. In this study, a three-dimensional integration strategy was developed to systematically characterize Q-markers and this method was successfully applied to identify Q-markers of EPR. Firstly, three core quality attributes-effectiveness, testability and specificity-were considered as three dimensions, and the weights of each dimension were calculated by analytical hierarch process. Then, the values of each dimension were evaluated by multi-indicators. For EPR with antitumor activity, cytotoxic assay and network pharmacology, UPLC analysis and literature search, compound belonging search were employed to calculate the values of effectiveness, testability and specificity, respectively. Finally, the weights and values were multiplied as the scores of each component on that dimension, and the total scores of the three dimensions were further integrated based on the radar plot and expressed as regression area, by which Q-markers were quantified and visualized. Five components were identified as Q-markers of EPR due to their high-ranked antitumor capacity, ease of measurement and excellent specificity, which laid an important foundation for the quality control improvement of EPR. Furthermore, the integrated strategy summarized here is helpful for the quantitative identification of Q-markers and promote the quality standard of traditional Chinese medicine.
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
hahaer完成签到,获得积分10
1秒前
领导范儿应助失眠虔纹采纳,获得10
2秒前
3秒前
Owen应助凝子老师采纳,获得10
6秒前
6秒前
南宫炽滔完成签到 ,获得积分10
8秒前
8秒前
丘比特应助飞羽采纳,获得10
9秒前
沙拉发布了新的文献求助10
9秒前
10秒前
11秒前
椰子糖完成签到 ,获得积分10
12秒前
12秒前
ZHU完成签到,获得积分10
13秒前
阳阳发布了新的文献求助10
14秒前
Raymond应助雪山飞龙采纳,获得10
14秒前
kk发布了新的文献求助10
15秒前
15秒前
16秒前
16秒前
16秒前
17秒前
20秒前
果果瑞宁发布了新的文献求助10
20秒前
wewewew发布了新的文献求助10
20秒前
20秒前
打打应助沙拉采纳,获得10
20秒前
21秒前
诸笑白发布了新的文献求助10
22秒前
丹丹完成签到 ,获得积分10
22秒前
kk完成签到,获得积分10
22秒前
23秒前
caoyy发布了新的文献求助10
23秒前
24秒前
25秒前
斗图不怕输完成签到,获得积分10
27秒前
aikeyan完成签到,获得积分10
28秒前
imaginehdxy发布了新的文献求助10
29秒前
派大星完成签到,获得积分10
29秒前
29秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
Luis Lacasa - Sobre esto y aquello 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527998
求助须知:如何正确求助?哪些是违规求助? 3108225
关于积分的说明 9288086
捐赠科研通 2805889
什么是DOI,文献DOI怎么找? 1540195
邀请新用户注册赠送积分活动 716950
科研通“疑难数据库(出版商)”最低求助积分说明 709849