ArticleReproductive sciences (Thousand Oaks, Calif.)2023
Network Pharmacology Was Used to Predict the Active Components and Prospective Targets of Paeoniae Radix Alba for Treatment in Endometriosis.
Article in Reproductive sciences (Thousand Oaks, Calif.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Exploring the therapeutic efficacy and pharmacological mechanism of Guizhi Fuling Pill on ischemic stroke: a meta-analysis and network pharmacology analysis.Metabolic brain disease · 2024Pooled it
- Astragalin: A promising herbal compound with broad anticancer potential (Review).Oncology letters · 2026Review
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Endometriosis is one of the most common benign gynecologic diseases. Paeoniae Radix Alba (PRA) has been utilized to treat endometriosis. We wished to identify potential targets for PRA in the treatment of endometriosis, as well as to provide a groundwork for future studies into its pharmacological mechanism of action. Network pharmacology was employed to conduct investigations on PRA. Target proteins were chosen from the components of PRA for endometriosis treatment. A protein-protein interaction (PPI) was established using overlapping genes. Analyses of enrichment of function and signaling pathways were undertaken using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes databases to select "hub genes." Finally, the feasibility of analysis based on network pharmacology was determined using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting. We demonstrated that PRA has 25 bioactive components and 167 putative targets that are therapeutically important. The anti-inflammatory and immune-boosting actions of tumor necrosis factor, albumin, signal transducer and activator of transcription (STAT)3, mitogen-activated protein kinase, Jun, interleukin (IL)-1B, prostaglandin-endoperoxide synthase 2, matrix metalloproteinase-9, vascular endothelial growth factor A, and IL-6 were identified as prospective targets. Seven major compounds in PRA and related to the STAT3 pathway could bind spontaneously to it. RT-qPCR and western blotting showed that expression of STAT3 and phospho-STAT3 was reduced significantly after PRA intervention. Hence, analyses of the active components of traditional Chinese medicine formulations through network pharmacology may open up new ideas for the treatment of diseases.
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Registered trials
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