Evidence map›Paper›PMID 29567258›Full record

ArticleJournal of food and drug analysis2018

A new strategy for choosing "Q-markers" via network pharmacology, application to the quality control of a Chinese medical preparation.

Wei Xiang, Tong-Chuan Suo, Hua Yu, An-Ping Li, Shou-Qing Zhang, Chun-Hua Wang, Yan Zhu, Zheng Li

Abstract readEvaluation Study
In one paragraph

Article in Journal of food and drug analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
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

8 authors.

Wei XiangTianjin Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
Tong-Chuan SuoCollege of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
Hua YuTianjin Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
An-Ping LiHarmonia Testing (Tianjin) Limited Company, Tianjin 300457, China.
Shou-Qing ZhangHarmonia Testing (Tianjin) Limited Company, Tianjin 300457, China.
Chun-Hua WangTianjin Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
Yan ZhuTianjin Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
Zheng LiCollege of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to its chemical complexity, proper quality control for a Chinese medical preparation (CMP) has been a great challenge. Choosing the appropriate quality markers (Q-markers) for quality control of CMP is an important work. Best of all, the chosen Q-markers are the main chemical compounds from the herbals as well as the active constituents of this CMP. Only in this way the established quality control system can really achieve the purpose of controlling the quality of CMP and ensuring the safely and effectively use of CMP. To achieve the purpose, network pharmacology combined with the contents of chemical compounds in the CMP has been used in this research. We took an anti-arrhythmic CMP, Shenxian-Shengmai oral liquid (SSOL), as an example. Firstly, UPLC-QTOF-MS/MS method was used to analyze the main components of SSOL. A total of 64 compounds were unambiguously or tentatively identified and 32 of them were further validated by reference compounds. Secondly, the network was constructed based on the identified compounds to predict the effective compounds related to cardiac arrhythmias. Based on the existing database and the operation method of topology, a method of double network analysis (DNAA) was proposed, from which 10 important targets in the pathway of arrhythmia were screened out, and 26 compounds had good antiarrhythmic activity. Based on the prediction results of network pharmacology along with the contents of the compounds in this CMP, ten representative compounds were chosen as the Q-markers for the quality control of SSOL. We find that five of these ten compounds, including danshensu, rosmarinic acid, salvianolic acid A, epimedin A and icariin, have antiarrhythmic activity. Then, the UPLC-DAD method was established as the control method for SSOL.

Indexed as

Arrhythmias, CardiacBiomarkersChromatography, High Pressure LiquidCinnamatesDepsidesDrugs, Chinese HerbalFlavonoidsHumansQuality ControlRosmarinic AcidTandem Mass SpectrometryBiomarkersCinnamatesDepsidesDrugs, Chinese Herbalepimedin AFlavonoidsRosmarinic AcidNetwork pharmacologyQuality controlQuality markerShenxian Shengmai oral liquid

Identifiers

PMID29567258
PMCPMC9322248

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.