ArticleEvidence-based complementary and alternative medicine : eCAM2021
Revealing the Mechanism of
Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Efficacy of Astragalus Membranaceus (Huang Qi) for Cancer-Related Fatigue: A Systematic Review and Meta-Analysis of Randomized Controlled Studies.Integrative cancer therapiesPooled it
- Network pharmacology and in silico approach to study the mechanism of quercetin against breast cancer.In silico pharmacology · 2025Article
- Medicinal plants for the management of post-COVID-19 fatigue: A literature review on the role and mechanisms.Journal of traditional and complementary medicine · 2025Review
- Molecular network mechanism in cerebral ischemia-reperfusion rats treated with human urine stem cells.Heliyon · 2024Article
- Potential Mechanisms of White Peony against Primary Sjögren's Syndrome Based on Network Pharmacology and Molecular Docking.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Exploring the Molecular Mechanism of Tong Xie Yao Fang in Treating Ulcerative Colitis Using Network Pharmacology and Molecular Docking.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Network pharmacology and molecular docking-based investigations of Kochiae Fructus's active phytomolecules, molecular targets, and pathways in treating COVID-19.Frontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCancer-related fatigue (CRF) is an increasingly appreciated complication in cancer patients, which severely impairs their quality of life for a long time.
objectiveTo systematically analyze the mechanism of AR against CRF by network pharmacology.
methodsTCMSP was searched to obtain the active compounds and targets of AR. The active compound-target (AC-T) network was established and exhibited by related visualization software. The GeneCards database was searched to acquire CRF targets, and the intersection targets with AR targets were used to make the Venny diagram. The protein-protein interaction (PPI) network of intersection targets was established, and further, the therapeutic core targets were selected by topological parameters. The selected core targets were uploaded to Metascape for GO and KEGG analysis. Finally, AutoDock Vina and PyMOL were employed for molecular docking validation.
results16 active compounds of AR were obtained, such as quercetin, kaempferol, 7-O-methylisomucronulatol, formononetin, and isorhamnetin. 57 core targets were screened, such as AKT1, TP53, VEGFA, IL-6, and CASP3. KEGG analysis manifested that the core targets acted on various pathways, including 137 pathways such as TNF, IL-17, and the AGE-RAGE signaling pathway. Molecular docking demonstrated that active compounds docked well with the core targets.
conclusionThe mechanism of AR in treating CRF involves multiple targets and multiple pathways. The present study laid a theoretical foundation for the subsequent research and clinical application of AR and its extracts against CRF.
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Registered trials
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.