Integrated Serum Pharmacochemistry and Network Pharmacology Used to Explore Potential Antidepressant Mechanisms of the Kaixin San

化学 抗抑郁药 药理学 色谱法 精神科 心理学 医学 焦虑
作者
Guoliang Dai,Deming Liu,Youjin Wang,Yanjun Wang,Qian Huang,Wenqing San,Xiaoyong Wang,Wenzheng Ju
出处
期刊:Biomedical Chromatography [Wiley]
卷期号:39 (4)
标识
DOI:10.1002/bmc.70041
摘要

ABSTRACT Kaixin San (KXS) is a classical prescription for the treatment of depression. However, the mechanism is not clear. In this study, serum pharmacochemistry, mediated by the UHPLC‐Orbitrap Exploris 480 mass spectrometer, was used to identify compounds derived from the KXS‐medicated serum. These components were used to construct a compound‐target network for depression using a network pharmacology approach to predict potential biological targets of KXS. Subsequently, we established a mouse model of CUMS‐induced depression and observed the antidepressant effect of KXS. The signalling pathways predicted by the network pharmacology were further validated in animal experiments. The results showed that 36 compounds were identified from the KXS‐medicated serum. Based on this, 984 genes related to the compounds and 4966 genes related to depression were identified using network pharmacology. Critically, KEGG analysis identified the PI3K/Akt and NF‐κB signalling pathways as the main pathways through which KXS exerts its antidepressant effect. KXS significantly alleviated depression‐like behaviour and hippocampal histopathological changes in a mouse model of depression. Compared with the model group, the treatment of KXS significantly reduced the expression of protein targets in the PI3K/Akt/NF‐κB signalling pathway. All these studies effectively corroborated the predicted results, confirming the feasibility of this integrated strategy.
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
1秒前
爆米花应助xxp采纳,获得10
2秒前
2秒前
江川直子完成签到,获得积分10
2秒前
叽里呱啦发布了新的文献求助10
3秒前
4秒前
tangyandi完成签到,获得积分10
4秒前
tttt发布了新的文献求助10
4秒前
小怪兽完成签到,获得积分10
4秒前
DH完成签到,获得积分10
6秒前
6秒前
橙子完成签到 ,获得积分10
7秒前
苏梗完成签到 ,获得积分10
7秒前
乐乐乐乐乐乐应助shallyping采纳,获得10
8秒前
8秒前
9秒前
健壮代柔发布了新的文献求助20
9秒前
ll完成签到,获得积分10
11秒前
xxp发布了新的文献求助10
12秒前
Anderson完成签到,获得积分10
13秒前
15秒前
16秒前
17秒前
快乐小韩发布了新的文献求助10
19秒前
liu发布了新的文献求助10
19秒前
20秒前
自由如南完成签到 ,获得积分10
22秒前
Rubby应助JF采纳,获得10
25秒前
笨小孩完成签到,获得积分10
26秒前
退后分裂搁浅完成签到,获得积分10
27秒前
29秒前
yjzzz完成签到,获得积分10
29秒前
大模型应助ttt采纳,获得10
29秒前
坚强白凝完成签到,获得积分10
29秒前
李总要发财小苏发文章完成签到,获得积分10
30秒前
苏苏苏发布了新的文献求助10
33秒前
积极从蕾应助黎黎原上草采纳,获得10
34秒前
34秒前
35秒前
研友_85YNe8发布了新的文献求助10
36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
Plutonium Handbook 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 680
北师大毕业论文 基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 540
Thermal Quadrupoles: Solving the Heat Equation through Integral Transforms 500
SPSS for Windows Step by Step: A Simple Study Guide and Reference, 17.0 Update (10th Edition) 500
Chinese Buddhist Monasteries: Their Plan and Its Function As a Setting for Buddhist Monastic Life 300
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 4120710
求助须知:如何正确求助?哪些是违规求助? 3658901
关于积分的说明 11582302
捐赠科研通 3360465
什么是DOI,文献DOI怎么找? 1846381
邀请新用户注册赠送积分活动 911179
科研通“疑难数据库(出版商)”最低求助积分说明 827352