Evidence mapPaperPMID 41322308Full record

ReviewFrontiers in pharmacology2025

Application of network pharmacology in traditional Chinese medicine for the treatment of cardiac diseases.

Xi Zhai, Xingyu Chen, Xiao Xiao, Lan Wu

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

4 authors.

Xi Zhai *School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Xingyu Chen *Institute of Wound Prevention and Treatment, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Xiao Xiao *Institute of Wound Prevention and Treatment, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Lan WuInstitute of Wound Prevention and Treatment, Shanghai University of Medicine and Health Sciences, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many innovative traditional Chinese medicines (TCMs) play a significant role in cardioprotection against cardiac diseases by addressing the basic causes of heart attack, which presents as a dual deficiency of qi and yang. Network pharmacology, offering a multi-dimensional perspective, can elucidate the specific mechanisms of the active components of TCM via a system pharmacology strategy. The methodology of network pharmacology is highly consistent with the modernization of TCM and provides a new perspective and theoretical basis for both basic research and its supplementary clinical research on cardiac diseases. This review summarizes the steps, databases, and software used in network pharmacology systematically. It also discusses the current achievements in applying network pharmacology to understand the mechanisms of some important TCMs (Huangqi, Renshen, and Danshen) and their active components in the context of cardioprotection against cardiac diseases based on a comprehensive literature search on PubMed. Anti-inflammation, anti-oxidation, anti-apoptosis, anti-pyroptosis, and regulation of the PI3K-AKT-mammalian target of the rapamycin (mTOR) signaling pathway were identified as the main mechanisms through which these TCMs exert cardioprotective effects. In addition, this approach provides new ideas for the cure of cancer-induced cardiac injury through network pharmacology.

Indexed as

cardiac diseasescardioprotectionmechanismsnetwork pharmacologytraditional Chinese medicine

Identifiers

PMID41322308
PMCPMC12660193

What Socratic holds

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Registered trials

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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.