Evidence map›Paper›PMID 39369254›Full record

ArticleChinese medicine2024

Development of a new paradigm model for deciphering action mechanism of Danhong injection using a combination of isothermal shift assay and database interrogation.

Tianxiang Wang, Changmei Yang, Yuxiang Tang, Ke Wen, Yuxin Ma, Yuling Chen, Zhiqiang Li, Yujiao Zhao, Songbiao Zhu, Xianbin Meng and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Chinese medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Tianxiang Wang *MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Changmei Yang *MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Yuxiang Tang *MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Ke WenMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Yuxin MaMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Yuling ChenMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Zhiqiang LiMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Yujiao ZhaoMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Songbiao ZhuChinese Institutes for Medical Research, Beijing, China.
Xianbin MengMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Sijing DuMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Zelong MiaoMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Wei WeiWangjing hospital of China Academy of Chinese Medical Sciences, Beijing, China. sxxtyy@sina.com.
Haiteng DengMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, People's Republic of China. dht@mail.tsinghua.edu.cn.ORCID http://orcid.org/0000-0001-9496-1280

Funding

Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine ZYYCXTD-C-202210National Key Research and Development Program of China 2021YFA1302601National Natural Science Foundation of China 82172556National Natural Science Foundation of China T2293763
6 · The paper itself

Abstract

backgroundIdentification of active components of traditional Chinese Medicine (TCM) and their respective targets is important for understanding the mechanisms underlying TCM efficacy. However, there are still no effective technical methods to achieve this.

methodsHerein, we have established a method for rapidly identifying targets of a specific TCM and interrogating the targets with their corresponding active components based on Isothermal Shift Assay (iTSA) and database interrogation.

resultsWe optimized iTSA workflow and identified 110 targets for Danhong injection (DHI) which is used as an effective remedy for cardiovascular and cerebrovascular diseases. Moreover, we identified the targets of the nine major ingredients found in DHI. Database interrogation found that the potential targets for DHI, in which we verified that ADK as the target for salvianolic acid A and ALDH1B1 as the target for protocatechualdehyde in DHI, respectively.

conclusionOverall, we established a novel paradigm model for the identification of targets and their respective ingredients in DHI, which facilitates the discovery of drug candidates and targets for improving disease management and contributes to revealing the underlying mechanisms of TCM and fostering TCM development and modernization.

Indexed as

ADKALDH1B1DHIIsothermal shift assay (iTSA)Target identificationTCM

Identifiers

PMID39369254
PMCPMC11452974

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.