ArticleCardiovascular drugs and therapy2025
The Toll-like Receptor-2/4 Antagonist, Sparstolonin B, and Inflammatory Diseases: A Literature Mining and Network Analysis.
Article in Cardiovascular drugs and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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Who cites it
4 citing papers in PubMed.
- DAMP signaling networks: from receptors to diverse pathophysiological functions.Journal of advanced research · 2026Review
- Intestinal reengineering: Scientific advances in intestinal transplantation.World journal of gastrointestinal surgery · 2025Review
- Pattern recognition receptors: function, regulation and therapeutic potential.Signal transduction and targeted therapy · 2025Review
- Sparstolonin B nano-formulation attenuates LPS-induced lung injury.Frontiers in pharmacology · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSparstolonin 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.
methodsWe 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.
resultsA 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.
conclusionThese 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.
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Registered trials
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