Evidence map›Paper›PMID 40593167›Full record

ArticleScientific reports2025

Integrative network pharmacology and experimental validation of anti-inflammatory triterpenoids from hawthorn leaves.

Zhixing Liu, Jihua Liu

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Life (Basel, Switzerland) · 2026
    Review
  3. Phytochemical small molecules fromAmerican journal of translational research · 2026
    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

2 authors.

Zhixing LiuCollege of Pharmaceutical Science, Jilin University, Changchun, 130021, China.
Jihua LiuCollege of Pharmaceutical Science, Jilin University, Changchun, 130021, China. liujh@jlu.edu.cn.

Funding

the Science and Technology Development Program of Jilin Province 20210402038GH
6 · The paper itself

Abstract

A network pharmacology approach was employed to identify key bioactive compounds and core targets in hawthorn leaves with potential anti-inflammatory properties. The predicted biological effects and underlying mechanisms were systematically validated through target enzyme activity evaluations, molecular docking simulations, LPS-induced inflammatory models in RAW264.7 macrophages, western blot and quantitative real-time PCR (qRT-PCR) analyses. Molecular docking studies revealed strong binding affinities of triterpenoids 99, 102, and 116 to SRC (Proto-Oncogene Tyrosine-Protein Kinase Src), a critical regulator of inflammatory signaling pathways. These interactions were further substantiated by enzymatic activity assays and macrophage-based inflammatory models. Notably, the triterpenoids showed strong anti-inflammatory properties by significantly reducing nitric oxide (NO) release and altering the expression of inflammatory genes in LPS-stimulated RAW264.7 macrophages. Among them, triterpenoid 99 demonstrated the most pronounced activity, primarily by downregulating SRC mRNA and protein expression. These findings provide compelling scientific evidence supporting the use of hawthorn leaves as a natural reservoir of anti-inflammatory agents, offering a strong foundation for future pharmacological and therapeutic developments.

Indexed as

Anti-Inflammatory AgentsCrataegusNetwork PharmacologyPlant ExtractsPlant LeavesTriterpenesAnimalsLipopolysaccharidesMacrophagesMiceMolecular Docking SimulationNitric OxideRAW 264.7 Cellssrc-Family KinasesAnti-Inflammatory AgentsLipopolysaccharidesNitric OxidePlant Extractssrc-Family KinasesTriterpenes

Identifiers

PMID40593167
PMCPMC12219075

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.