Identification and quantitation of NF-κB inhibitory components in weichang'an pill based on UHPLC-QE-MS and spectrum-effect relationship

化学 大黄素 厚朴酚 金丝桃苷 根(腹足类) 中医药 柚皮苷 橙皮苷 传统医学 色谱法 药理学 生物化学 槲皮素 抗氧化剂 医学 植物 替代医学 病理 生物
作者
Cao Xiaoxia,Cunyu Hu,Fei Shang,Yingshuang Lv,Ziyan Bian,Qing Yuan,Han Zhang,Yi Wang,Nan Li,Lin Wang,Yujing Wang,Yingjie Sun,Lin Miao,Yanxu Chang,Yuefei Wang,Wenzhi Yang,Lijuan Chai,Peng Zhang
出处
期刊:Arabian Journal of Chemistry [Elsevier]
卷期号:17 (1): 105328-105328 被引量:2
标识
DOI:10.1016/j.arabjc.2023.105328
摘要

Weichang'an pill (WCAP) is a traditional Chinese patent medicine, which is clinically used for the treatment of bowel syndrome and functional dyspepsia such as diarrhea, abdominal distension, and enteritis. So far, quality control studies of WCAP have mainly focused on the determination of chemical composition content, which has little relevance to biological activity and clinical effects. With the aim of identifying the multi-index ingredients with NF-κB inhibitory activities related to WCAP clinical effect, this present work described the chemical profile of WCAP by UHPLC-QE-MS, established the correlated relationship between chromatographic fingerprints and the NF-κB inhibitory activities based on multivariate statistical analysis, including hierarchical clustering analysis (HCA), Pearson correlation analysis, and Partial least squares regression analysis (PLSR). The spectrum-effect relationship analysis indicated 10 compounds, which were ferulic acid, naringin, narirutin, hesperidin, neohesperidin, aloe emodin, emodin, honokiol, magnolol, and physcion, might be the potential NF-κB inhibitory constituents in the pill. The NF-κB inhibitory effects of the ten compounds were verified by in vitro dual luciferase reporting detection system. Considering that the detection index should be representative of more medicinal materials, a rapid and efficient UPLC-DAD method was eventually developed to determine the content of the 13 components. Our findings will provide data support for WCAP quality control and advance the understanding of the quality assessment of traditional Chinese patent medicines.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
奶龙完成签到,获得积分20
1秒前
1秒前
深情安青应助WYP采纳,获得10
1秒前
3333完成签到,获得积分10
2秒前
CodeCraft应助高挑的小虾米采纳,获得10
2秒前
上官若男应助云宝采纳,获得10
2秒前
3秒前
大方惜天发布了新的文献求助10
3秒前
小U完成签到,获得积分10
4秒前
燕子完成签到,获得积分20
4秒前
4秒前
3333发布了新的文献求助10
6秒前
za发布了新的文献求助10
6秒前
哈哈军哥哥完成签到,获得积分10
7秒前
一一应助shu采纳,获得10
7秒前
文献期待完成签到,获得积分10
7秒前
8秒前
9秒前
11秒前
糖不甜发布了新的文献求助10
11秒前
Syening完成签到 ,获得积分10
12秒前
慕青应助kaka采纳,获得10
12秒前
南瓜猪猪头完成签到,获得积分10
13秒前
爆米花应助TYQ采纳,获得10
13秒前
田様应助222采纳,获得10
13秒前
Canon发布了新的文献求助10
14秒前
花痴的幻儿完成签到,获得积分10
15秒前
15秒前
小二发布了新的文献求助10
15秒前
16秒前
CHENCHEN完成签到 ,获得积分10
16秒前
XuLiu发布了新的文献求助10
17秒前
17秒前
量子星尘发布了新的文献求助10
18秒前
19秒前
19秒前
脑洞疼应助若米采纳,获得10
20秒前
21秒前
隐形曼青应助ztq采纳,获得10
21秒前
HHHHHJ完成签到,获得积分10
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Washback Research in Language Assessment:Fundamentals and Contexts 400
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
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 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 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5469224
求助须知:如何正确求助?哪些是违规求助? 4572331
关于积分的说明 14335257
捐赠科研通 4499207
什么是DOI,文献DOI怎么找? 2464985
邀请新用户注册赠送积分活动 1453533
关于科研通互助平台的介绍 1428051