Characterization of chemical components in the Guanxinning injection by liquid chromatography–mass spectrometry

化学 轨道轨道 脑血栓形成 质谱法 色谱法 化学成分 萜类 高效液相色谱法 立体化学 医学 内科学
作者
Rongrong Li,Yifan Cui,Xiaofen Zheng,Xuemei Qin,Jianjun Cao,Zhenyu Li
出处
期刊:Journal of Mass Spectrometry [Wiley]
卷期号:55 (12) 被引量:6
标识
DOI:10.1002/jms.4662
摘要

Guanxinning injection (GXNI) is widely used in the treatments of cerebral thrombosis, cerebral hemorrhage, sequela, coronary disease, stenocardia, arrhythmia, and so on. For the herbal injections, more components should be characterized and quantified as much as possible to guarantee the drug safety. However, large numbers of the chemical constituents in the GXNI still remain unknown. In this study, ultrahigh performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q Orbitrap HRMS), in combination of nuclear magnetic resonance (NMR), was used to identify the components in GXNI, which led to the identification of 194 compounds. With the aid of solvent partition, more phthalides, diterpenoid quinines, and salvianolic acids were tentatively identified, and minor compounds with the other structural types were also detected. The structural diversity of phthalides and diterpenoid quinones were revealed by the structural network, and six phthalides and 13 diterpenoid quinones were further detected in GXNI with the help of the characteristic fragmentation pattern and structural network. In addition, NMR also revealed the presence of a series of primary metabolites in the GXNI, which could be used as a complimentary approach for the rapid identification of the chemical components in the traditional Chinese medicines (TCM). However, the unknown NMR signals of GXNI needed to be further identified to guarantee the drug safety.
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
魔幻的凝荷完成签到,获得积分10
1秒前
wzxhhh发布了新的文献求助10
1秒前
NexusExplorer应助yeah采纳,获得10
2秒前
ding应助洪福齐天采纳,获得10
3秒前
高宇航发布了新的文献求助10
3秒前
若什么至完成签到,获得积分10
3秒前
yayika完成签到,获得积分10
3秒前
zyl发布了新的文献求助10
3秒前
zzz完成签到,获得积分10
4秒前
ssrich发布了新的文献求助10
4秒前
4秒前
伶俐的灵珊完成签到,获得积分10
4秒前
ding应助爱啃大虾采纳,获得10
5秒前
ED应助CJY采纳,获得10
5秒前
5秒前
酷波er应助CJY采纳,获得10
5秒前
搜集达人应助CJY采纳,获得20
5秒前
BurgerKing完成签到,获得积分10
6秒前
青吟子完成签到,获得积分10
6秒前
6秒前
7秒前
花落无声发布了新的文献求助10
7秒前
大个应助一直祝我快乐采纳,获得10
8秒前
科目三应助liiy采纳,获得10
10秒前
FashionBoy应助冷静的方盒采纳,获得10
10秒前
10秒前
高木同学完成签到,获得积分10
10秒前
酷波er应助小鱼采纳,获得10
11秒前
zhao发布了新的文献求助10
11秒前
11秒前
11秒前
蛇從革应助su采纳,获得30
12秒前
椰瓜w完成签到,获得积分10
12秒前
外向秋灵完成签到,获得积分10
13秒前
ssrich完成签到,获得积分10
13秒前
大模型应助魔幻的凝荷采纳,获得10
13秒前
13秒前
14秒前
14秒前
Wmhan完成签到 ,获得积分10
14秒前
高分求助中
【重要!!请各位用户详细阅读此贴】科研通的精品贴汇总(请勿应助) 10000
Genomic signature of non-random mating in human complex traits 2000
Semantics for Latin: An Introduction 1099
醤油醸造の最新の技術と研究 1000
Plutonium Handbook 1000
Three plays : drama 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 640
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 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4108675
求助须知:如何正确求助?哪些是违规求助? 3646863
关于积分的说明 11551815
捐赠科研通 3352773
什么是DOI,文献DOI怎么找? 1842192
邀请新用户注册赠送积分活动 908446
科研通“疑难数据库(出版商)”最低求助积分说明 825578