Research Article

Mechanism and Experimental Validation of Total Flavonoids of Rhizoma Drynariae in Treating Gouty Arthritis

110 views

⸱

DOI:

10.3791/70849

⸱

June 5th, 2026

 ,  , 
1School of Chinese Materia Medica, Beijing University of Chinese Medicine, 2Quality department, Beijing Tongrentang Kangyang Industry Development Co., Ltd, 3Engineering Research Center of Good Agricultural Practice for Chinese Crude Drugs, Ministry of Education

In This Article

Summary

Total flavonoids of Rhizoma Drynariae (TFRD) alleviate gouty arthritis (GA) by suppressing inflammatory cell infiltration and reducing TNF-α, IL-6, and IL-17A levels, primarily through inhibition of AKT, MAPK, and NF-κB signaling pathways, highlighting its anti-inflammatory and immunomodulatory therapeutic potential.

Abstract

Gouty arthritis (GA) is an inflammatory joint disease caused by the deposition of monosodium urate (MSU) crystals within the joint space and surrounding tissues. In traditional Chinese medicine, Rhizoma Drynariae (Gusuibu) has long been widely used in the clinical treatment of GA, and flavonoids are considered its key bioactive constituents. This research employed network pharmacology to construct a component-target network of total flavonoids of Rhizoma Drynariae (TFRD) against GA, thereby identifying key components, core targets, and related pathways. Rat models were established by intra-articular injection of a monosodium urate crystal suspension and treated with TFRD or the positive control, colchicine, by oral gavage. After sample collection, network pharmacology-based prediction results were subsequently validated using rat serum metabolomics, enzyme-linked immunosorbent assay (ELISA), and Western blot analysis. Network pharmacology analysis indicated that the anti-GA effects of TFRD are mediated through key targets, including IL6, AKT1, TNF, EGFR, JUN, and PTGS2, and are mainly associated with inflammation, immune, and apoptosis-related pathways, such as the IL-17, TNF, NF-κB, MAPK, PI3K-AKT, JAK-STAT, and T-cell receptor signaling pathways. Similarly, metabolomics also uncovered the pivotal roles of the inflammatory response. Hematoxylin and eosin (H&E) staining confirmed that TFRD reduced infiltration of inflammatory cells. ELISA assay confirmed that the TFRD group significantly inhibited the expression of inflammatory factors TNF-α, IL-6, and IL-17A in synovial tissue. Western blot analysis revealed that TFRD inhibited the GA-induced hyperphosphorylation of AKT, MAPK p38, and NF-κB p65 in rat synovial tissue. TFRD can effectively ameliorate the inflammation-triggered changes in the GA rats by directly modulating related inflammatory factors and pathways.

Introduction

Gouty arthritis (GA) is an inflammatory joint disease triggered by the deposition of monosodium urate (MSU) crystals within and around the joints, which stimulate the joint area1,2. The pathogenesis of GA involves a complex interplay of genetic predisposition, environmental influences, and metabolic dysregulation characterized primarily by hyperuricemia resulting from either excessive uric acid production or insufficient renal excretion3,4. This leads to the systemic accumulation of urate crystals in renal tissues and articular spaces, where they activate the innate immune system and provoke intense inflammatory cascades5,6. In recent years, a series of studies have shown that the global prevalence of GA has risen in parallel with the increasing incidence of obesity and metabolic syndrome, leading to functional impairment and imposing a substantial socioeconomic burden on affected individuals7. The treatment strategy for gouty arthritis centers on controlling acute local joint inflammation and managing long-term uric acid levels8,9. Nevertheless, the utility of existing pharmacotherapies is often constrained by their adverse effect profiles and specific contraindications. For instance, non-steroidal anti-inflammatory drugs are generally avoided in patients with chronic kidney disease due to the associated risk of precipitating or exacerbating acute kidney injury10,11. Likewise, the urate-lowering agent allopurinol carries a well-documented risk of severe cutaneous adverse reactions such as Stevens–Johnson syndrome, whereas benzbromarone may induce significant hepatotoxicity11,12,13,14,15. Therefore, there remains a compelling need for the development of safer, more broadly applicable, and mechanistically targeted therapeutics for the effective management of GA.

In traditional Chinese medicine (TCM), GA falls under diagnostic categories such as “Lijie Disease” (joint-running pain), “Gout bi” (gout impediment), and “Yu Zhuo bi” (stasis-turbidity impediment). TCM interventions for GA offer the synergistic effects through anti-inflammatory and analgesic actions, modulation of uric acid metabolism, improvement of microcirculation, and preservation of joint function, making it a prominent area of contemporary research16,17,18,19. Rhizoma Drynariae (Gusuibu) derived from the dried rhizome of Drynaria fortunei (Kunze) J.Sm., a perennial fern of the Polypodiaceae family, is commonly used in clinical practice to treat GA. The bioactive compounds of Rhizoma Drynariae primarily contains flavonoids, phenylpropanoids, triterpenoids, phenolic acids, and their glycosides20,21. Among these, flavonoids represent the most extensively studied class of compounds in recent years22,23,24. Previous studies have demonstrated that flavonoids possess notable anti-inflammatory and antioxidant properties25.

Preliminary research has found that total flavonoids of Rhizoma Drynariae (TFRD) can effectively suppress inflammatory responses in osteoarthritis, rheumatoid arthritis, and other inflammatory joint conditions26,27,28. However, the underlying mechanisms of TFRD against GA are yet to be thoroughly investigated. Therefore, this study aims to employ an integrated approach combining network pharmacology, metabolomics, and molecular biology experiments to explore and validate the specific mechanisms and therapeutic efficacy of TFRD in the treatment of GA. A systematic investigation of multi-component, multi-target, and multi-pathway mechanisms underlying TFRD treatment against GA is expected to advance drug discovery and provide innovative options and practical solutions for the clinical management of GA.

Access restricted. Please log in or start a trial to view this content.

Protocol

This study was reviewed and approved by the Animal Ethics Committee of China-Japan Friendship Hospital (Approval No: zryhyy21-22-08-10) and conducted following institutional guidelines for the ethical care and use of laboratory animals.

Prediction and Screening of TFRD-related and GA-associated Targets
The chemical constituents of Rhizoma Drynariae were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) using “Rhizoma Drynariae” as the search term29. Screening for potentially bioactive constituents was performed based on the criteria of oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.1830,31,32. From the resulting pool of compounds, flavonoid components were subsequently identified and selected according to their chemical structures. These flavonoid components, hereafter referred to as the total flavonoids of Rhizoma Drynariae (TFRD), were incorporated in downstream analysis. Upon retrieving the target genes associated with TFRD from the TCMSP database, their corresponding standardized gene symbols were annotated using the UniProt database33. Using “gout” as a search term, disease-related targets were retrieved from the GeneCards database to establish a set of candidate genes34.

Establishment of compound-target network
The intersection between TFRD-associated targets and GA-related targets was identified and defined as the key therapeutic targets mediating TFRD's anti-GA effects, and the overlapping set was visualized using a Venn diagram. Furthermore, a regulatory network of “TFRD - targets - GA” was constructed and analyzed using Cytoscape software35.

Protein-protein interaction network
The key therapeutic targets of TFRD against GA were imported into an online database to generate a protein-protein interaction (PPI) network, with the minimum required interaction score set to “high confidence (0.700)”36. The PPI network was optimized using Cytoscape software, and the top 30 core targets ranked by degree centrality were selected to generate a bar plot37,38.

KEGG pathway enrichment analysis
KEGG pathway enrichment analysis was performed on these core targets using R software and the Bioconductor database38,39. Pathways with a p-value < 0.05 were considered statistically significant. After excluding disease- and metabolism-related pathways, a pathway-target interaction network was visualized in Cytoscape. Among these pathways, the top 20 pathways ranked by ascending P value were presented in a bar plot.

Drug preparation
For the preparation of a monosodium urate (MSU) crystal suspension, 500 mg of MSU crystals were weighed using an analytical balance, dispersed in 10 mL of normal saline and 2 mL of Tween 80, and heated while stirring magnetically. The mixture was then adjusted to a final volume of 20 mL with normal saline to obtain a 25 mg/mL suspension. After autoclaving, the suspension was stored at 4 °C until use. The common clinical dosage for TFRD is 750 mg per day for a 70 kg adult, corresponding to a rat dose of 67.5 mg/kg body weight per day. TFRD was dissolved in distilled water to a concentration of 6.75 mg/mL and stored at 4 °C for later use. According to the body surface area normalization method, the equivalent oral dose of colchicine (the positive drug) in rats converted from the clinical human dose (0.6 mg/60 kg) is 0.062 mg/kg. A colchicine solution was prepared in distilled water at a concentration of 0.0062 mg/mL and stored at 4 °C for later use.

Animals
A total of 36 six-week-old male Sprague–Dawley (SD) rats (220 ± 10 g) were used in this study (animal license No. SCXK [Jing] 2025-0008). Animals were housed at the Laboratory Animal Center of China-Japan Friendship Hospital under standard diet conditions at a temperature of 22–24 °C and humidity of 50–70%.

Model establishment and intervention
Following one week of acclimation, rats were randomly divided into four groups (n = 9 each): control, model, TFRD, and positive drug. Randomization was performed using a random number table. Data collection and analysis were conducted under blinded conditions. All treatments were given once daily by oral gavage. All interventions were administered once daily by oral gavage at 08:00 for seven consecutive days. The blank control and model groups received normal saline (10 mL/kg), while the TFRD and the positive drug groups were given their respective drug suspensions at an equivalent volume (10 mL/kg). On the fourth day of the interventions, the blank control group received an intra-articular injection of sterile normal saline, while rats in the model, TFRD, and the positive drug groups were injected with an MSU crystal suspension to induce acute gouty arthritis. Prior to injection, rats were anesthetized using an isoflurane anesthesia system. Each rat in the model, TFRD, and the positive drug groups received 200 µL of the MSU suspension into the left ankle joint cavity. Following needle withdrawal, gentle pressure was applied at the injection site with a sterile cotton swab for several seconds to prevent leakage.

Sample collection and processing
72 h after model induction, rats were anesthetized and positioned supine. Following abdominal disinfection, the peritoneal cavity was opened, and the intestines were gently retracted to expose the abdominal aorta. A blood collection needle was inserted parallel to the vessel to draw abdominal aortic blood, which was immediately transferred into heparinized tubes pre-chilled in an ice water bath. Samples were centrifuged at 3000 × g for 10 min at 4 °C to obtain serum, which was aliquoted and stored at -80 °C for subsequent metabolomic profiling. Animals were then euthanized via CO₂ asphyxiation. The fur around the left ankle joint was shaved, and the surrounding skin and muscle were carefully removed to expose the intact joint structure. Synovial tissue, appearing as a thin whitish membrane lining the joint capsule, was gently isolated from adjacent fascia using fine forceps. The collected joint samples were fixed in 4% paraformaldehyde at 4 °C for 72 h. Then, part of the joint tissue was decalcified in EDTA decalcification solution, with the solution refreshed weekly for 8 weeks. Complete decalcification was confirmed by needle puncture testing: if resistance was encountered, decalcification was continued until the tissue was fully penetrable.

Following decalcification, ankle joints were sagittally sectioned, placed in processing cassettes, and subjected to gradient ethanol dehydration. Tissues were cleared in xylene, infiltrated with paraffin, and embedded in paraffin blocks. Sections of 6 µm thickness were cut using an automated microtome, floated on a 40 °C water bath, and mounted onto adhesive slides. After drying at 60 °C for 30 min, sections were deparaffinized, stained with hematoxylin and eosin (H&E) according to standard protocols, and finally coverslipped with neutral balsam. Whole slide images were acquired using a digital slide scanner.

Serum metabolomics analysis
Serum samples from the model and TFRD groups were thawed at 4 °C prior to processing. For each sample, 100 µL of serum was transferred into a microcentrifuge tube and combined with 400 µL of precooled extraction solvent (methanol: acetonitrile, 1:1, v/v) containing internal standards. The mixture was vortexed for 1 min, followed by sonication in an ice-water bath for 10 min. It was then incubated at -40 °C for 1 h to facilitate protein precipitation and subsequently centrifuged at 12,000 × g for 15 min at 4 °C. The supernatant obtained after centrifugation was carefully collected and transferred into autosampler vials for UHPLC–MS analysis. In addition, equal volumes of supernatant from each sample within the same group were pooled to generate quality control (QC) samples.

Following metabolite detection in serum samples from the two groups, the raw mass spectrometry data were processed by dedicated software for automated peak detection, extraction, alignment, and integration, yielding a structured data matrix of ion spectral features. The detected spectral features were matched against established metabolomics spectral libraries to identify metabolites derived from TFRD that had entered systemic circulation. Unidentified features and those containing excessive missing values were removed from the dataset. The curated dataset was re-indexed and structured into a standardized format40.

The differential expression of metabolites between the two groups was evaluated by calculating both fold change (FC, expressed as the inter-group ratio) and statistical significance (p-value). Metabolites meeting the threshold of |log₂FC| ≥ 1 and P < 0.05 were defined as differentially expressed metabolites (DEMs). The screening results were visually summarized using methods such as volcano plots. The screened differential metabolites were subsequently imported into the PubChem database to obtain their canonical identifiers (CIDs)41. The corresponding KEGG IDs were then obtained based on the CIDs. Finally, the KEGG IDs were imported into a metabolomics analysis platform to perform metabolic pathway enrichment analysis and identify the signaling pathways significantly associated with the DEMs.

ELISA
Synovial tissue samples were flash-frozen in liquid nitrogen and pulverized into a fine powder. Approximately 100 mg of the powder was weighed using an electronic precision balance, mixed with 1 mL of ice-cold PBS, and homogenized on ice using a glass homogenizer. The homogenate was centrifuged at 10,000 × g for 5 min at 4 °C, and the supernatant was collected for subsequent ELISA detection. Prior to analysis, the ELISA kit was allowed to equilibrate to room temperature for 30 min. All reagents, including serially diluted standards, wash buffer, biotin-labeled antibody working solution, and enzyme conjugate solution, were prepared in accordance with the manufacturer’s instructions. Subsequently, 100 µL of standards at different concentrations and samples were added to the designated wells of the pre-coated microplate. The plate was sealed and incubated at 37 °C for 90 min. After incubation, the contents were discarded, and the wells were washed four times. Then, 100 µL of biotinylated antibody working solution was added to each well, followed by incubation at 37 °C for 60 min and another washing step. Next, 100 µL of enzyme conjugate working solution was introduced, and the plate was incubated at 37 °C for 30 min, followed by additional washing. A chromogenic substrate was then added, and the plate was incubated in the dark at 37 °C for 10 min. The reaction was terminated by adding 100 µL of stop solution, and absorbance was measured at 450 nm using a microplate reader. A standard curve was constructed by fitting the optical density (OD) values of the standards against their corresponding concentrations, and sample concentrations were calculated accordingly.

Western blot
Synovial tissues were rapidly frozen and mechanically ground into a fine powder. A measured portion of the powder was lysed in an appropriate volume of ice-cold RIPA buffer supplemented with protease and phosphatase inhibitors (1:100, v/v), followed by incubation on ice for 30 min. The lysates were then centrifuged at 10,000 × g for 5 min at 4 °C, and the supernatants were carefully collected. Protein concentrations were quantified using a BCA assay, and all samples were adjusted to equal concentrations with RIPA buffer. Proteins were separated via SDS-PAGE and transferred onto PVDF membranes. Membranes were blocked and then incubated with primary antibodies (1:1000 dilution), followed by secondary antibodies (1:5000 dilution). Protein signals were visualized using an ECL detection system, and band intensities were quantified using Image Lab software (Version 5.2.1). The relative expression levels were normalized against β-actin.

Statistical analysis
Statistical analyses were performed using SPSS software (version 20.0). Data are presented as mean ± standard deviation (SD). For comparisons among multiple groups, one-way analysis of variance (ANOVA) was used when the assumption of homogeneity of variance was satisfied, followed by the LSD test for post hoc pairwise comparisons. If variance homogeneity was not met, Welch’s ANOVA was performed, followed by Dunnett's T3 test for multiple comparisons. A p-value < 0.05 was considered statistically significant.

Access restricted. Please log in or start a trial to view this content.

Results

Key components of TFRD
Potential bioactive ingredients of Rhizoma Drynariae were retrieved from the TCMSP database, yielding 71 candidates. These 71 active constituents were then subjected to a screening process based on oral bioavailability (OB ≥ 30%) and drug-likeness (DL ≥ 0.18), which resulted in the identification of 18 compounds. Further refinement of this list revealed that 10 of these active compounds were flavonoids, including: (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one, Au...

Access restricted. Please log in or start a trial to view this content.

Discussion

GA is a common form of inflammatory arthritis. Currently, clinical management mainly relies on nonsteroidal anti-inflammatory drugs (NSAIDs), corticosteroids, and urate-lowering agents42. However, the combined administration of these drugs inflicts a range of adverse effects on patients and imposes a significant metabolic burden on the liver and kidneys43. This is particularly detrimental for patients with pre-existing hepatic or renal impairment. Flavonoids, a class of pol...

Access restricted. Please log in or start a trial to view this content.

Disclosures

The authors report there are no conflicts of interest in this work.

Materials

List of materials used in this article
NameCompanyCatalog NumberComments
4% ParaformaldehydeSolarbioP1110
5X Protein Loading BufferSolarbioP1040
AKT AntibodyCell Signaling Technology4691S
Antibody Diluent SolutionBeyotime BiotechnologyP0268
Bioconductor database https://www.bioconductor.org/
colchicineShanghai Yuanye Co., Ltd
GeneCards database https://www.genecards.org/
Hematoxylin and Eosin (H&E) Staining KitSolarbioG1120
MetaboAnalyst 6.0 online platform https://www.metaboanalyst.ca/
Mouse IL-17A ELISA Kit4a Biotech Co LtdCME0041
Mouse IL-6 ELISA Kit4a Biotech Co LtdCME0006
Mouse TNF-α ELISA Kit4a Biotech Co LtdCME0004
NF-κB p65 AntibodyCell Signaling Technology8242T
Non-fat Dry MilkSolarbioD8340
p38 MAPK AntibodyAbclonalA14401
Phosphatase Inhibitor CocktailBeyotime BiotechnologyP1081
Phospho-AKT (Ser473) AntibodyCell Signaling Technology4060S
Phospho-NF-κB p65 AntibodyCell Signaling Technology3031S
Phospho-p38 MAPK AntibodyAbclonalAP0526
Phenylmethylsulfonyl Fluoride (PMSF)SolarbioR0010
Polyvinylidene Fluoride (PVDF) MembraneMilliporeIPVH00010
PubChem databashttps://pubchem.ncbi.nlm.nih.gov/
R software www.r project.org/
RIPA Lysis BufferSolarbioR0010
RNase-free waterAmbionAM9937
SD ratsBeijing Vital River Laboratory Animal Technology Co., Ltd. 
SDS-PAGE Electrophoresis BufferServicebioG2144
STRING Databasehttps://string-db.org/
TBST Buffer (10X)SolarbioT1085
TCMSPhttps://old.tcmsp-e.com
Tris-Glycine Transfer BufferServicebioG2017
TFRDBeijing Qihuang Pharmaceutical Co., Ltd.
UniProt database https://www.uniprot.org/
β-Actin AntibodyZhongshan Jingqiao BiotechnologyTA-09

References

  1. Keller, S. F., Mandell, B. F. Management and cure of gouty arthritis. Rheum Dis Clin North Am. 48 (2), 479-492 (2022).
  2. Ma, C., et al. Metabolic reprogramming of macrophages by biomimetic melatonin-loaded liposomes effectively attenuates acute gouty arthritis in a mouse model. Adv Sci (Weinh). , e2410107 (2024).
  3. Li, C., et al. Targeting neutrophil extracellular traps in gouty arthritis: insights into pathogenesis and therapeutic potential. J Inflamm Res. 17, 1735-1763 (2024).
  4. Zhang, Y., Chen, S., Yuan, M., Xu, Y., Xu, H. Gout and diet: a comprehensive review of mechanisms and management. Nutrients. 14 (17), 3525 (2022).
  5. Wang, R., et al. Sulforaphane-driven reprogramming of gut microbiome and metabolome ameliorates the progression of hyperuricemia. J Adv Res. 52, 19-28 (2023).
  6. Zhang, S., et al. Mechanism of reactive oxygen species-guided immune responses in gouty arthritis and potential therapeutic targets. Biomolecules. 14 (8), 978 (2024).
  7. GBD 2021 Gout Collaborators. Global, regional, and national burden of gout, 1990-2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021. Lancet Rheumatol. 6 (8), e507-e517 (2024).
  8. Towiwat, P., Li, Z. Long-term remission in gout: challenges and future opportunities. Rheumatol Autoimmun. 6, 7-15 (2026).
  9. Chen, S., Li, Z., Deng, X., Gao, L. Advances in understanding the mechanisms of treatment for gouty arthritis: a comprehensive review. Physiol Res. 74 (5), 693-710 (2025).
  10. LaForge, J. M., et al. Non-steroidal anti-inflammatory drugs: clinical implications, renal impairment risks, and AKI. Adv Ther. 40 (5), 2082-2096 (2023).
  11. Klomjit, N., Ungprasert, P. Acute kidney injury associated with non-steroidal anti-inflammatory drugs. Eur J Intern Med. 101, 21-28 (2022).
  12. Anis, T. R., Meher, J. Allopurinol-induced Stevens-Johnson syndrome (SJS). Clin Pharmacol. 15, 99-105 (2023).
  13. Hasegawa, A., Abe, R. Stevens-Johnson syndrome and toxic epidermal necrolysis: updates in pathophysiology and management. Chin Med J (Engl). 137 (19), 2294-2307 (2024).
  14. Gupta, S. S., Sabharwal, N., Patti, R., Kupfer, Y. Allopurinol-induced Stevens-Johnson syndrome. Am J Med Sci. 357 (4), 348-351 (2019).
  15. Sun, W., et al. Risk of hepatotoxicity in patients with gout treated with febuxostat or benzbromarone: a propensity score-matched cohort study. Arthritis Care Res (Hoboken). 77 (9), 1149-1156 (2025).
  16. Guo, J. W., et al. Therapeutic potential and pharmacological mechanisms of traditional Chinese medicine in gout treatment. Acta Pharmacol Sin. 46 (5), 1156-1176 (2025).
  17. Jiang, Z., et al. The correlation between traditional Chinese medicine constitution and hyperuricemia and gout: a systematic review and meta-analysis. Evid Based Complement Alternat Med. 2023, 5097490 (2023).
  18. Wang, S., et al. Traditional herbal medicine: therapeutic potential in acute gouty arthritis. J Ethnopharmacol. 330, 118182 (2024).
  19. Wang, Y. B., Jin, C. Z. Roles of traditional Chinese medicine extracts in hyperuricemia and gout treatment: mechanisms and clinical applications. World J Gastroenterol. 30 (47), 5076-5080 (2024).
  20. Jingying, G., et al. A comprehensive review of Drynariae Rhizoma: botany, traditional applications, and active flavonoid components. J Pharm Pharmacol. 77 (10), 1319-1337 (2025).
  21. Chen, G. Y., et al. Prediction of Rhizoma Drynariae targets in the treatment of osteoarthritis based on network pharmacology and experimental verification. Evid Based Complement Alternat Med. 2021, 5233462 (2021).
  22. Zhang, Y., et al. Total flavonoids from Rhizoma Drynariae (Gusuibu) for treating osteoporotic fractures: implication in clinical practice. Drug Des Devel Ther. 11, 1881-1890 (2017).
  23. Yu, X. B., et al. Chondroprotective effects of Gubitong Recipe via inhibiting excessive mitophagy of chondrocytes. Evid Based Complement Alternat Med. 2022, 8922021 (2022).
  24. Zhang, F., et al. Total flavonoids of Drynariae Rhizoma improve glucocorticoid-induced osteoporosis of rats: UHPLC-MS-based qualitative analysis, network pharmacology strategy and pharmacodynamic validation. Front Endocrinol (Lausanne). 13, 920931 (2022).
  25. Liu, F., et al. Mechanism of flavonoids in the treatment of gouty arthritis (review). Mol Med Rep. 30 (2), 132 (2024).
  26. Chen, G. Y., et al. Network pharmacology analysis and experimental validation to investigate the mechanism of total flavonoids of Rhizoma Drynariae in treating rheumatoid arthritis. Drug Des Devel Ther. 16, 1743-1766 (2022).
  27. Chen, G. Y., et al. Total flavonoids of Rhizoma Drynariae restore the MMP/TIMP balance in models of osteoarthritis by inhibiting the activation of the NF-λB and PI3K/AKT pathways. Evid Based Complement Alternat Med. 2021, 6634837 (2021).
  28. Chen, G. Y., et al. Total flavonoids of Rhizoma Drynariae treat osteoarthritis by inhibiting arachidonic acid metabolites through AMPK/NFλB pathway. J Inflamm Res. 16, 4123-4140 (2023).
  29. Ru, J., et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform. 6, 13 (2014).
  30. Chen, G. Y., et al. Mechanisms of total glucosides of paeony in alleviating methotrexate-induced liver injury. Drug Des Devel Ther. 19, 3407-3423 (2025).
  31. Zhang, P., et al. Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine. Brief Bioinform. 25 (1), bbad518 (2023).
  32. Luo, W., et al. Integration of molecular docking, molecular dynamics, and network pharmacology to explore the multi-target pharmacology of fenugreek against diabetes. J Cell Mol Med. 27 (14), 1959-1974 (2023).
  33. UniProt Consortium. UniProt: the universal protein knowledgebase in 2023. Nucleic Acids Res. 51 (D1), D523-D531 (2023).
  34. Stelzer, G., et al. The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr Protoc Bioinformatics. 54, 1.30.1-1.30.33 (2016).
  35. Chen, G. Y., et al. Integrating network pharmacology and experimental validation to explore the key mechanism of Gubitong Recipe in the treatment of osteoarthritis. Comput Math Methods Med. 2022, 7858925 (2022).
  36. Szklarczyk, D., et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51 (D1), D638-D646 (2023).
  37. Chen, G. Y., et al. Network pharmacology-based strategy to investigate the mechanisms of Cibotium barometz in treating osteoarthritis. Evid Based Complement Alternat Med. 2022, 1826299 (2022).
  38. Robinson, M. D., McCarthy, D. J., Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 26 (1), 139-140 (2010).
  39. Jin, Q., et al. Network and experimental pharmacology to decode the action of Wendan Decoction against generalized anxiety disorder. Drug Des Devel Ther. 16, 3297-3314 (2022).
  40. Pang, Z., et al. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis, and interpretation. Nucleic Acids Res. 52 (W1), W398-W406 (2024).
  41. Kim, S., et al. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 49 (D1), D1388-D1395 (2021).
  42. Pillinger, M. H., Mandell, B. F. Therapeutic approaches in the treatment of gout. Semin Arthritis Rheum. 50 (3S), S24-S30 (2020).
  43. Yao, T. K., et al. Advances in gouty arthritis management: integration of established therapies, emerging treatments, and lifestyle interventions. Int J Mol Sci. 25 (19), 10853 (2024).
  44. Li, W., et al. Effects of total flavonoids of Rhizoma Drynariae on biochemical indicators of bone metabolism: a systematic review and meta-analysis. Front Pharmacol. 15, 1443235 (2024).
  45. Mohammed, H. S., et al. Investating the involvement of the NLRP3/ASC/caspase-1 and NF-λB/MAPK pathways in the pathogenesis of gouty arthritis: insights from irradiated and non-irradiated Trifolium alexandrium L. extracts and some metabolites. J Ethnopharmacol. 334, 118566 (2024).
  46. Shi, M. F., et al. Study on the effect and mechanism of Zexie Decoction in treating MSU-induced acute gouty arthritis model through PI3K-AKT-mTOR signaling pathway. Int Immunopharmacol. 150, 114214 (2025).
  47. Cui, L., et al. Selenium suppressed the LPS-induced inflammation of bovine endometrial epithelial cells through NF-λB and MAPK pathways under high cortisol background. J Cell Mol Med. 27 (10), 1373-1383 (2023).
  48. Balakin, E., et al. Regulation of stress-induced immunosuppression in the context of neuroendocrine, cytokine, and cellular processes. Biology (Basel). 14 (1), 76 (2025).
  49. Chen, L., et al. AMPK signaling in osteoarthritis: from mechanisms to targeted therapeutics. Front Pharmacol. 16, 1681610 (2025).
  50. FitzGerald, J. D., et al. 2020 American College of Rheumatology guideline for the management of gout. Arthritis Care Res (Hoboken). 72 (6), 744-760 (2020).
  51. Limbachia, V., et al. The effect of different types of oral or intravenous corticosteroids on capillary blood glucose levels in hospitalized inpatients with and without diabetes. Clin Ther. 46 (2), e59-e63 (2024).
  52. Xue, Y., et al. Association of serum glucocorticoids with various blood pressure indices in patients with dysglycemia and hypertension: the Henan Rural Cohort Study. Biomed Environ Sci. 34 (12), 952-962 (2021).
  53. Uson, J., et al. EULAR recommendations for intra-articular therapies. Ann Rheum Dis. 80 (10), 1299-1305 (2021).
  54. Lucenti, L., et al. Do preoperative corticosteroid injections increase the risk of infection after shoulder arthroscopy or shoulder arthroplasty? A systematic review. Healthcare (Basel). 12 (5), 543 (2024).
  55. Feng, W., Cui, D., Yang, T. Interpretation of key points of Chinese guidelines for diagnosis and management of hyperuricemia and gout (2019). J Clin Intern Med. 37 (07), 528-531 (2020).
  56. Lin, Y., et al. Luteolin-4'-O-glucoside and its aglycone, two major flavones of Gnaphalium affine D. Don, resist hyperuricemia and acute gouty arthritis activity in animal models. Phytomedicine. 41, 54-61 (2018).
  57. Wang, Y., et al. A luteolin-loaded electrospun fibrous implantable device for potential therapy of gout attacks. Macromol Biosci. 16 (11), 1598-1609 (2016).

Access restricted. Please log in or start a trial to view this content.

Reprints and Permissions

Request permission to reuse the text or figures of this JoVE article

Request Permission

Tags

Network PharmacologyRat ModelSerum MetabolomicsEnzyme Linked ImmunosorbentWestern BlotInflammatory PathwaysSynovial Tissue

Related Articles