Research progress of traditional Chinese medicine processing based on component structure theory

组分(热力学) 机制(生物学) 计算机科学 中医药 生化工程 人工智能 数据科学 医学 工程类 替代医学 热力学 认识论 物理 哲学 病理
作者
Kunming Qin,Gang Cao,Bing Yang,Weidong Li,Xiao Liu,Hao Cai,Tulin Lu,BaoChang CAI
出处
期刊:aZhongguo kexue [Science in China Press]
卷期号:49 (2): 129-139 被引量:1
标识
DOI:10.1360/n052018-00168
摘要

Processing is the main characteristic of the products used in traditional Chinese medicine (TCM), and this is how they differ from natural medicines. The characteristics of the medicines used in TCM have rich scientific connotations. Because of the complexity and diversity of TCM, the processing mechanism has not been fully elucidated. In recent years, the theory of component structure has been put forward and applied to guide TCM research, resulting in substantial progress. This paper presents a systematic review of mechanism research in TCM processing. It can be used as a reference of the ideas and methods of component structure theory for studying component content changes caused by processing, for studying in vivo changes in components caused by processing, for studying the effects and toxicity changes in components caused by processing, for studying metabolic changes of components caused by processing, and for developing component structure theory in the study of the mechanism of TCM processing. Combining component structure theory with various new methods and technologies will enable better understanding of the processing mechanisms of TCM and speed up the modernization of TCM.

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
weihan1113发布了新的文献求助10
刚刚
科研通AI5应助耶耶采纳,获得10
刚刚
典雅碧空发布了新的文献求助10
1秒前
wbslsp发布了新的文献求助10
1秒前
科研通AI5应助细心的岩采纳,获得10
1秒前
kkk发布了新的文献求助30
1秒前
调皮秋尽完成签到,获得积分10
2秒前
2秒前
凝雁发布了新的文献求助10
3秒前
烟花应助wye采纳,获得10
3秒前
4秒前
小宇子发布了新的文献求助10
5秒前
CJ发布了新的文献求助10
5秒前
qql发布了新的文献求助10
5秒前
天天快乐应助狸小狐采纳,获得200
5秒前
5秒前
乐乐应助大力紫萱采纳,获得10
6秒前
雾草生完成签到,获得积分10
6秒前
533发布了新的文献求助10
7秒前
8秒前
8秒前
8秒前
yiheng发布了新的文献求助10
9秒前
六水居士发布了新的文献求助10
10秒前
10秒前
木目耶耶耶完成签到 ,获得积分10
11秒前
隐形曼青应助FK7采纳,获得10
11秒前
Marksman497发布了新的文献求助10
12秒前
阿托品Atropine完成签到,获得积分10
12秒前
wer完成签到 ,获得积分10
12秒前
maodou发布了新的文献求助10
12秒前
bkagyin应助kkk采纳,获得10
12秒前
领导范儿应助kkk采纳,获得10
12秒前
哈尼完成签到,获得积分10
13秒前
qql完成签到,获得积分10
14秒前
Akim应助T拐拐采纳,获得10
14秒前
15秒前
kkkkkkk发布了新的文献求助10
16秒前
细心的岩发布了新的文献求助10
16秒前
17秒前
高分求助中
Algorithmic Mathematics in Machine Learning 500
Handbook of Innovations in Political Psychology 400
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Visceral obesity is associated with clinical and inflammatory features of asthma: A prospective cohort study 300
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Engineering the boosting of the magnetic Purcell factor with a composite structure based on nanodisk and ring resonators 240
HVAC 1 toolkit : a toolkit for primary HVAC system energy calculation 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 3839571
求助须知:如何正确求助?哪些是违规求助? 3381905
关于积分的说明 10520504
捐赠科研通 3101362
什么是DOI,文献DOI怎么找? 1708032
邀请新用户注册赠送积分活动 822099
科研通“疑难数据库(出版商)”最低求助积分说明 773174