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The Toll-like Receptor-2/4 Antagonist, Sparstolonin B, and Inflammatory Diseases: A Literature Mining and Network Analysis

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机构: [1]State Key Laboratory of Traditional Chinese Medicine Syndrome, The Second Clinical School of Medicine, Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou 510120, China [2]The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangdong 510405, China [3]Ganzhou Hospital of Guangdong Provincial People’s Hospital, Ganzhou Municipal Hospital, Ganzhou 341000, China [4]Department of Cell Biology and Anatomy, University of South Carolina School of Medicine, Columbia, SC 29209, USA
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关键词: Sparstolonin B (SsnB) Inflammatory diseases Related proteins Data mining Network analysis

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Sparstolonin B (SsnB) is characterized as a new toll-like receptor (TLR)-2/4 antagonist. However, the effects of SsnB on different inflammatory diseases have not been systemically reviewed.We investigated the effects of SsnB on inflammatory diseases with data mining and network analysis of literature, including frequency description, cluster analysis, association rule mining, functional enrichment, and protein-protein interaction (PPI) mining.A total of 27 experimental reports were included. The ARRIVE 2.0 guidelines were used to evaluate the quality of animal studies. Frequency analysis revealed 13 different diseases (cardio-cerebrovascular system diseases account for 23.53%), 12 pharmacological effects (anti-inflammatory effect accounts for 53.85%), and 67 therapeutic targets. The overview of investigation sequence of SsnB studies was depicted by Sankey diagram. Cluster analysis classified the therapeutic targets for SsnB into four main categories: (1) NF-κB; (2) IL-1β, IL-6, and TNF-α; (3) TLR2, TLR4, and MyD88; (4) the other targets. Moreover, the Apriori association discovered two main association pairs: (1) TNF-α, IL-1β, and IL-6 and (2) TLR2, TLR4, and MyD88 (support range 33.33-50%, confidence range 83.33-88.89%). Functional enrichment of the therapeutic targets for SsnB showed that the top enriched items in the biological process were mainly the response to lipopolysaccharide (LPS)/bacterial origin and regulation of cytokine production. Finally, the PPI network and hub gene selection by maximal clique centrality (MCC) algorithm indicated the top ranked proteins were TNF-α, IL-1β, IL-6, AKT1, PPAR-γ, TLR4, CCL2, and TLR2.These results emphasized the importance of TLR2/TLR4-MyD88-NF-κB-IL-1β/IL-6/TNF-α pathways as therapeutic targets of SsnB in inflammatory diseases.© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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出版当年[2023]版:
大类 | 3 区 医学
小类 | 3 区 药学 4 区 心脏和心血管系统
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大类 | 3 区 医学
小类 | 3 区 药学 4 区 心脏和心血管系统
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出版当年[2022]版:
Q2 CARDIAC & CARDIOVASCULAR SYSTEMS Q2 PHARMACOLOGY & PHARMACY
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Q2 CARDIAC & CARDIOVASCULAR SYSTEMS Q2 PHARMACOLOGY & PHARMACY

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第一作者机构: [1]State Key Laboratory of Traditional Chinese Medicine Syndrome, The Second Clinical School of Medicine, Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou 510120, China
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