ArticleMolecular medicine reports2019
Identification of a key candidate gene‑phenotype network mediated by glycyrrhizic acid using pharmacogenomic analysis.
Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- The effects of compound probiotics on production performance, rumen fermentation and microbiota ofFrontiers in veterinary science · 2024Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glycyrrhizic acid (GA) is primarily used as an anti‑inflammatory agent in cases of chronic hepatitis. However, its underlying mechanisms in diverse biological processes and its reported benefits are yet to be fully elucidated. In the current study, an analytical method based on pharmacogenomics was established to mine disease‑modulatory activities mediated by GA. Five primary protein targets and 138 functional partners were identified for GA by querying open‑source databases, including Drugbank and STRING. Subsequently, GA‑associated primary and secondary protein targets were integrated into Cytoscape to construct a protein‑protein interaction network to establish connectivity. GA‑associated target genes were then clustered based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The tumor necrosis factor axis was revealed to be a primary module regulated by GA‑associated targets. Furthermore, 12 hub genes were queried to assess their potential anti‑cancer effects using cBioPortal. The results indicated that pharmacogenomics‑based analysis improved understanding of the underlying drug‑target events of GA and provided predictive and definitive leads for future studies.
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