Evidence map›Paper›PMID 42724825›Full record

ArticleAnnals of medicine and surgery (2012)2026

Exploring the therapeutic potential of Astragalin in Parkinson's disease: a network pharmacology approach.

Hongyan Liu, Wenwen Shen, Hongcheng Zhou, Yang Gao, Xiaobo Li

Abstract read
In one paragraph

Article in Annals of medicine and surgery (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Hongyan LiuDepartment of Geriatric Neurology, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Medical College of Yangzhou University, Yangzhou, Jiangsu, China.ORCID https://orcid.org/0009-0007-5963-2239
Wenwen ShenDepartment of Internal Medicine, Jiamusi University, Jiamusi, Heilongjiang, China.
Hongcheng ZhouDepartment of Experimental Animal Center, Jiangsu Medical College, Yancheng, Jiangsu, China.
Yang GaoDepartment of Neurology, Yancheng First Hospital, Affiliated Hospital of Nanjing University Medical School, The First People's Hospital of Yancheng, Yancheng, Jiangsu, China.
Xiaobo LiDepartment of Geriatric Neurology, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Medical College of Yangzhou University, Yangzhou, Jiangsu, China.ORCID https://orcid.org/0009-0001-0358-5783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/objectives: Parkinson's disease (PD) is a neurodegenerative disorder with limited treatment options. This study investigated the therapeutic potential of astragalin (AST) in PD and explored its underlying mechanisms. Methods: Network pharmacology identified nine overlapping genes between the AST and PD target sets. Protein-protein interaction networks were constructed using Cytoscape and STRING. Based on KEGG pathway analysis, AST may influence PD through the IL-17 signaling pathway. Molecular docking simulations demonstrated a strong binding affinity between AST and key target proteins. Results: Nine overlapping genes were identified. Molecular docking analyses revealed robust binding interactions between AST and PTGS2, PRSS1, PRKACA, and PIK3CG. Conclusions: This study provides comprehensive evidence that AST may alleviate symptoms associated with PD by modulating the IL-17 signaling pathway. These findings highlight the potential of AST as a novel treatment for PD.

Indexed as

astragalinIL-17 signaling pathwaymolecular dockingMPTPnetwork pharmacologyneuroinflammationParkinson’s diseaseSH-SY5Y cellstyrosine hydroxylase

Identifiers

PMID42724825
PMCPMC13561219

What OpenQuestion 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 OpenQuestion graph.