Evidence map›Paper›PMID 39857687›Full record

ArticleBiomedicines2025

A Network Pharmacology Study and Experimental Validation to Identify the Potential Mechanism of Heparan Sulfate on Alzheimer's Disease-Related Neuroinflammation.

Dong-Uk Kim, Bitna Kweon, Jinyoung Oh, Yebin Lim, Gyeongran Noh, Jihyun Yu, Hyang-Rin Kang, Tackmin Kwon, Kwang Youll Lee, Gi-Sang Bae

Abstract read
In one paragraph

Article in Biomedicines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

10 authors.

Dong-Uk KimDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Bitna KweonDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Jinyoung OhDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Yebin LimDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Gyeongran NohDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Jihyun YuDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Hyang-Rin KangWoori B&B Life Science Laboratory, Jeonju 54853, Republic of Korea.
Tackmin KwonWoori B&B Life Science Laboratory, Jeonju 54853, Republic of Korea.
Kwang Youll LeeWoori B&B Life Science Laboratory, Jeonju 54853, Republic of Korea.
Gi-Sang BaeDepartment of Pharmacology, School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.

Funding

Ministry of Education 2023RIS-008
6 · The paper itself

Abstract

BACKGROUND/

objectivesHeparan sulfate (HS) is a polysaccharide that is found on the surface of cells and has various biological functions in the body.

methodsThe purpose of this study was to predict the pharmacological effects and molecular mechanisms of HS on Alzheimer's disease (AD) and neuroinflammation (NI) through a network pharmacology analysis and to experimentally verify them.

resultsWe performed functional enrichment analysis of common genes between HS target genes and AD-NI gene sets and obtained items such as the "Cytokine-Mediated Signaling Pathway", "Positive Regulation Of MAPK Cascade", and "MAPK signaling pathway". To confirm the predicted results, the anti-inflammatory effect of HS was investigated using lipopolysaccharide (LPS)-stimulated BV2 microglia cells. HS inhibited the production of nittic oxide, interleukin (IL)-6, and tumor necrosis factor-α in LPS-stimulated BV2 cells, but not IL-1β. In addition, HS inactivated P38 in the MAPK signaling pathway.

conclusionsThese findings suggest the potential for HS to become a new treatment for AD and NI.

Indexed as

Alzheimer’s diseaseBV2heparan sulfatenetwork pharmacologyneuroinflammation

Identifiers

PMID39857687
PMCPMC11761859

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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.