Evidence map›Paper›PMID 40661082›Full record

ArticleFrontiers in pharmacology2025

Identifying potential drugs for treating Cardiovascular-kidney metabolic syndrome via reverse network pharmacology.

Si'ao Wen, Ao'ni Fu, Fen Liu, Yayu You, Linkai Li, Wen Xiao, Haoran Zhong, Xiuqin Hong, Xin Zhong, Yongjun Hu and 1 more

Abstract read
In one paragraph

Article 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Genes · 2025
    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

11 authors.

Si'ao Wen *Department of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Ao'ni Fu *Key Laboratory for Arteriosclerology of Hunan Province, Hunan International Scientific and Technological Cooperation Base of Arteriosclerotic Disease, Hengyang Medical School, Institute of Cardiovascular Disease, University of South China, Hengyang, Hunan, China.
Fen LiuDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Yayu YouDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Linkai LiDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Wen XiaoDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Haoran ZhongDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Xiuqin HongDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Xin ZhongDepartment of Ultrasonic Medicine, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, China.
Yongjun HuDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Zhengyu LiuDepartment of Cardiology, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiovascular, Kidney and metabolic syndrome (CKM) is a complex disease, for which current therapeutic approaches have limited efficacy. This study aims to screen for potential targets and novel drugs for treating CKM using network pharmacology. Methods: Using reverse network pharmacology, core targets and potential drugs for CKM were identified. Candidate compounds were screened from a natural product library. Male C57BL/6J mice were fed a high-fat L-NAME diet for 12 weeks to induce CKM and confirm successful model establishment, followed by 4 weeks of BBR (Berberine) treatment. Metabolic parameters, as well as cardiac and renal structural and functional indices, were assessed. Key targets and potential drugs identified through network pharmacology and bioinformatics were validated using pathological analysis, RT-qPCR, and Western blotting (WB), collectively demonstrating the therapeutic effects of BBR on CKM. Results: Network pharmacology identified multiple core targets of CKM, and reverse pharmacology discovered the potential drug BBR (Berberine) from a natural product library. Conclusion: The "two-hit" HFPEF model can be used as a new model of CKM, and BBR may become a new candidate drug for the treatment of CKM through multiple targets.

Indexed as

animal modelBerberineCardiovascular-kidney metabolic syndrome (CKM)HFpEFnetwork pharmacology“two-hit” model

Identifiers

PMID40661082
PMCPMC12256536

What Socratic holds

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LicenceCC BY
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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.