Evidence map›Paper›PMID 41230084›Full record

ArticleFrontiers in endocrinology2025

Exploring the mechanism of Zishen Quyu Jiedu formula in treating endometriosis based on network pharmacology and experimental verification.

Ruolin Wang, Xinyang Tian, Peiyu Liu, Fang Lian

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 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

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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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.

Ruolin WangFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Xinyang TianInstitute of Traditional Chinese Medicine Literature and Culture, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Peiyu LiuState Key Laboratory of Traditional Chinese Medicine Syndrome/The Second Clinical College, Guangzhou University of Chinese Medicine, Guangdong, China.
Fang LianFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Zishen Quyu Jiedu formula (ZQYJDF) is a commonly used prescription for endometriosis (EMs) with clinical efficacy. However, its active components and potential mechanisms remain unknown. This study aimed to identify the key targets and signaling pathways involved in the treatment of EMs by ZSQYJDF and to clarify its mechanism. Materials and methods: Multiple databases were integrated to screen the effective components of ZSQYJDF and their protein targets, with redundancies removed. EMs-related genes were obtained from several disease databases. A drug-component-target network was constructed using overlapping targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to identify key pathways and proteins. An autologous transplantation rat model of EMs was established. Hematoxylin and eosin (H&E) staining was used to observe lesion morphology; immunohistochemistry (IHC) was used to assess positive expression of NRF2, HO1, and NQO1; serum SOD, MDA, GSHPx, 8epiPGF2α, IL6, IL1β, and TNFα were measured by ELISA; and mRNA and protein levels of NRF2, HO1, NQO1, and KEAP1 in endometrial tissue were detected by qPCR and Western blot. Results: comparisonon of the screened compounds with 1,225 known disease-related targets identified 134 potential targets for ZSQYJDF. GO terms were enriched in response to oxidative stress and cellular responses to oxidative stress. KEGG pathways were enriched in the TNF, NRF2, and HIF signaling pathways. HPLC-QOrbitrap-MS identified and inferred 48 compounds. In Conclusion: Utilizing methods including network pharmacology, HPLC-Q-Orbitrap-MS component identification, and animal experiments, the main active components and potential therapeutic targets of ZSQYJDF were identified, and its mechanism of action in treating EMs was preliminarily elucidated, providing a scientific basis for further research on EMs.

Indexed as

Drugs, Chinese HerbalEndometriosisNetwork PharmacologyAnimalsDisease Models, AnimalFemaleHumansNF-E2-Related Factor 2RatsRats, Sprague-DawleySignal TransductionDrugs, Chinese HerbalNF-E2-Related Factor 2blood stasis with toxin accumulationendometriosisnuclear factor E2-related factor 2oxidative stressZSQYJDF

Identifiers

PMID41230084
PMCPMC12602249

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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.