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Objective: Diabetes mellitus (DM) is an important risk factor for the development of osteoarthritis (OA), increasing OA progression and OA pain. To gain insight into the underlying mechanisms of how DM exacerbates OA processes and OA pain, this study analyzed histological differences of synovial tissues from non-DM and DM patients with OA and correlated these differences with knee pain severity. Materials and methods: Synovial tissue was obtained from12 non-DM and 10 DM patients with advanced knee OA who underwent total knee arthroplasty. Synovial inflammation was assessed using the Synovitis score developed by Krenn. The Knee Injury and Osteoarthritis Outcome Score (KOOS) was used to assess knee pain intensity and disability in OA patients. The number of mast cells, macrophages, nerve fibers, capillaries, larger vessels and erythrocyte extravasation were analyzed microscopically in histological and immunostained synovial sections fromnon-DM and DM patients. Association analyses were performed to determine associations between OA knee pain and synovial changes affected by DM. Results: Synovial tissue from OA patients with DM had a higher synovitis score, more erythrocyte extravasation, and contained higher numbers of mast cells and macrophages compared to non-DM patients. The number of capillaries and vessels in the lining/sublining layer of the synovial tissue was reduced in DM patients. OA patients with DM had more severe knee pain compared to non-DM patients. The KOOS pain score was associated with the synovitis score, the number of tissue macrophages, and the number of mast cells in the synovial tissue (adjusted for age, sex, and BMI). In addition, the erythrocyte extravasation score was associated with the KOOS pain score and with the synovitis score. Conclusion: The study suggests that increased OA progression and pain severity in patients with DM result from more pronounced synovitis and synovial vascular leakage and increased infiltration of macrophages and mast cells. [ABSTRACT FROM AUTHOR]

Objective To screen and validate the aging-related diagnostic markers of synovial tissue in osteoarthritis (OA) by bioinformatics methods. Methods GSE206848, GSE55235 and GSE554573 datasets of bone and joint synovial tissue were obtained from Gene Expression Omnibus (GEO) database and GSE206848 differentially expressed genes (DEGs) were screened. Senescence-associated genes (SRGs) were downloaded from the CellAge database. Differentially expressed senescence-related genes (DESRGs) were obtained by intersection of DEGs and SRGs. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed, and protein-protein interaction (PPI) was analyzed by using STRING online database and Cyto- scape software. The predicted area under curve (AUC) value and gene expression level were verified. The key genes were verified by GSE55235 and GSE55457 datasets, and the immune infiltration analysis was performed by CIBERSORT. Results Finally, 30 DESRGs were obtained. GOs were enriched in the regulation of transcription regulation, nucleoplasm and protein binding of RNA polymerase II, while KEGGs were mainly enriched in the signaling pathways such as "cellular senescence, endocrine resistance, and breast cancer". SNAIL, NOX4 and DHX9 were identified as synovial cell senescence-related diagnostic genes. OA synovial tissue contained fewer resting memory CD4 T cells (P=0.007), and there was a correlation between immune cells (P<0.05). Diagnostic marker NOX4 was correlated with a variety of immune cells (P<0.05). Conclusion Bioinformatics analysis is used to screen out the diagnostic markers related to synovial aging in OA, which is helpful to understand the pathogenesis of OA and provide research directions for targeted therapy in the future. [ABSTRACT FROM AUTHOR]

With the increasing burden of osteoarthritis worldwide, cost efficient and reliable models are needed to enable the development of innovative therapies or therapeutic interventions. Ex vivo models have been identified as valuable modalities in translational research, bridging the gap between in vitro and in vivo models. Osteocartilaginous explants from Osteoarthritis (OA) patients offer an exquisite opportunity for studying OA progression and testing novel therapies. We describe the protocol for establishing human osteocartilaginous explants with or without co-culture of homologous synovial tissue. Furthermore, a detailed protocol for the assessment of explanted tissue in terms of protein content using Western blot and immunohistochemistry is provided. Commentaries regarding the technique of choice, possible variations and expected results are inserted. [ABSTRACT FROM AUTHOR]

Knee osteoarthritis (KOA) is a common chronic joint disease globally. Synovial inflammation plays a pivotal role in its pathogenesis, preceding cartilage damage. Identifying biomarkers in osteoarthritic synovial tissues holds promise for early diagnosis and targeted interventions. Gene expression profiles were obtained from the Gene Expression Omnibus database. Subsequent analyses included differential expression gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) on the combined datasets. We performed functional enrichment analysis on the overlapping genes between DEGs and module genes and constructed a protein–protein interaction network. Using Cytoscape software, we identified hub genes related to the disease and conducted gene set enrichment analysis on these hub genes. The CIBERSORT algorithm was employed to evaluate the correlation between hub genes and the abundance of immune cells within tissues. Finally, Mendelian randomization analysis was utilized to assess the potential of these hub genes as biomarkers. We identified 46 differentially expressed genes (DEGs), comprising 20 upregulated and 26 downregulated genes. Using WGCNA, we constructed a gene co-expression network and selected the most relevant modules, resulting in 24 intersecting genes with the DEGs. KEGG enrichment analysis of the intersecting genes identified the IL-17 signaling pathway, associated with inflammation, as the most significant pathway. Cytoscape software was utilized to rank the candidate genes, with JUN, ATF3, FOSB, NR4A2, and IL6 emerging as the top five based on the Degree algorithm. A nomogram model incorporating these five genes, supported by ROC curve analysis, validated their diagnostic efficacy. Immune infiltration and correlation analysis revealed that macrophages were significantly associated with JUN (p < 0.01), FOSB (p < 0.01), and NR4A2 (p < 0.05). Additionally, T follicular helper cells showed significant associations with ATF3 (p < 0.05), FOSB (p < 0.05), and JUN (p < 0.05). Mendelian randomization analysis provided strong evidence linking JUN (IVW: OR = 0.910, p = 0.005) and IL6 (IVW: OR = 1.024, p = 0.026) with KOA. Through the utilization of various bioinformatics analysis methods, we have pinpointed key hub genes relevant to knee osteoarthritis. These findings hold promise for advancing pre-symptomatic diagnostic strategies and enhancing our understanding of the biological underpinnings behind knee osteoarthritis susceptibility genes. [ABSTRACT FROM AUTHOR]

Objective: To discuss the effect of cold exposure on nociception in the rats and its regulatory mechanism on transient receptor potential (TRP) ion channels in the sensory neurons, and to provide the basis for clarifying the biological mechanism of cold-sensitive pain. Methods: Sixteen female SD rats were divided into control group (n=8) and cold group (n=8). The rats in control group were exposed to the environment of (24±2) ℃, and the rats in cold group were exposed to low temperature (4 ℃±1 ℃) in an artificial intelligence climate chamber for 4 h daily, for one week. Von Frey filaments were used to detect the mechanical withdrawal threshold (MWT) of the rats in two groups； immunofluorescence staining was used to observe the expression levels of TRPA1, TRPM8, TRPV1, and TRPV4 in dorsal root ganglion (DRG) tissue of the rats in two groups, the expression levels of calcitonin gene-related peptide (CGRP) and substance P (SP) in DRG tissue of the rats in two groups, and the expression levels of TRPA1, TRPM8, TRPV1, and TRPV4 in synovial tissue of the rats in two groups. Results: Compared with control group, the MWT of the rats in cold group was significantly decreased (P< 0. 05), the expression levels of TRPA1 and TRPM8 in DRG tissue were significantly increased (P< 0. 05), the expression level of TRPV1 was significantly decreased (P<0. 05), there was no significant difference in the expression level of TRPV4 (P>0. 05), and the expression levels of CGRP and SP were significantly increased (P<0. 05). Compared with control group, the expression level of TRPA1 in synovial tissue of the rats in cold group was significantly increased (P<0. 05), while the expression levels of TRPM8, TRPV1, and TRPV4 were significantly decreased (P<0. 05). Conclusion: Short-term cold exposure can induce the hyperalgesia of the rats, and its mechanism may be associated with the changes in the expression of TRP ion channels in DRG and synovial tissues. TRPA1 sensory neurons play an important role in local joint cold pain. [ABSTRACT FROM AUTHOR]

Abstract Knee osteoarthritis (KOA) is a common chronic joint disease globally. Synovial inflammation plays a pivotal role in its pathogenesis, preceding cartilage damage. Identifying biomarkers in osteoarthritic synovial tissues holds promise for early diagnosis and targeted interventions. Gene expression profiles were obtained from the Gene Expression Omnibus database. Subsequent analyses included differential expression gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) on the combined datasets. We performed functional enrichment analysis on the overlapping genes between DEGs and module genes and constructed a protein–protein interaction network. Using Cytoscape software, we identified hub genes related to the disease and conducted gene set enrichment analysis on these hub genes. The CIBERSORT algorithm was employed to evaluate the correlation between hub genes and the abundance of immune cells within tissues. Finally, Mendelian randomization analysis was utilized to assess the potential of these hub genes as biomarkers. We identified 46 differentially expressed genes (DEGs), comprising 20 upregulated and 26 downregulated genes. Using WGCNA, we constructed a gene co-expression network and selected the most relevant modules, resulting in 24 intersecting genes with the DEGs. KEGG enrichment analysis of the intersecting genes identified the IL-17 signaling pathway, associated with inflammation, as the most significant pathway. Cytoscape software was utilized to rank the candidate genes, with JUN, ATF3, FOSB, NR4A2, and IL6 emerging as the top five based on the Degree algorithm. A nomogram model incorporating these five genes, supported by ROC curve analysis, validated their diagnostic efficacy. Immune infiltration and correlation analysis revealed that macrophages were significantly associated with JUN (p

Abstract Background Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease. Its pathogenesis is not fully understood, and early diagnosis is challenging owing to the lack of effective biomarkers. This study aimed to analyze different samples to identify potential biomarkers and therapeutic targets. Methods Microarray datasets of RA, osteoarthritis (OA), and healthy control (HC) were downloaded from the Gene Expression Omnibus database. R software was used to identify differentially expressed genes (DEGs), which were visualized using volcano and heat maps. Venn diagrams, principal component analysis, gene set enrichment analysis, gene ontology, and Kyoto Encyclopedia of genes and genomes were used to analyze the data. A protein–protein interaction network was constructed, and synovial tissues from patients with RA and OA were collected for verification using the collagen‐induced arthritis mouse model. Results More DEGs were found in synovial tissues than in peripheral blood mononuclear cells or fibroblast‐like synoviocytes. Principal component analysis revealed significant differences between the RA and OA samples, highlighting the unique advantages of synovial tissue. Enrichment analysis revealed that metabolic and cytokine signaling pathways play crucial roles in the development of RA. Further analysis of the four synovial datasets identified 54 DEGs, of which signaling lymphocytic activation molecule family (SLAMF) 8 was identified as the key molecule. SLAMF8 levels were increased in the synovial tissue of patients with RA compared to those of patients with OA (0.38 ± 0.19 vs. 12.40 ± 1.66), and SLAMF8 levels were similarly elevated in collagen‐induced arthritis model mice compared with those in the healthy mice (1.13 ± 0.47 vs. 9.05 ± 2.52). Conclusions This study established the unique advantages of synovial tissue for RA research and identified metabolic and cytokine signaling pathways as important for RA development. Thus, SLAMF8 may be a potential therapeutic target for RA.

ObjectiveDiabetes mellitus (DM) is an important risk factor for the development of osteoarthritis (OA), increasing OA progression and OA pain. To gain insight into the underlying mechanisms of how DM exacerbates OA processes and OA pain, this study analyzed histological differences of synovial tissues from non-DM and DM patients with OA and correlated these differences with knee pain severity.Materials and methodsSynovial tissue was obtained from 12 non-DM and 10 DM patients with advanced knee OA who underwent total knee arthroplasty. Synovial inflammation was assessed using the Synovitis score developed by Krenn. The Knee Injury and Osteoarthritis Outcome Score (KOOS) was used to assess knee pain intensity and disability in OA patients. The number of mast cells, macrophages, nerve fibers, capillaries, larger vessels and erythrocyte extravasation were analyzed microscopically in histological and immunostained synovial sections from non-DM and DM patients. Association analyses were performed to determine associations between OA knee pain and synovial changes affected by DM.ResultsSynovial tissue from OA patients with DM had a higher synovitis score, more erythrocyte extravasation, and contained higher numbers of mast cells and macrophages compared to non-DM patients. The number of capillaries and vessels in the lining/sublining layer of the synovial tissue was reduced in DM patients. OA patients with DM had more severe knee pain compared to non-DM patients. The KOOS pain score was associated with the synovitis score, the number of tissue macrophages, and the number of mast cells in the synovial tissue (adjusted for age, sex, and BMI). In addition, the erythrocyte extravasation score was associated with the KOOS pain score and with the synovitis score.ConclusionThe study suggests that increased OA progression and pain severity in patients with DM result from more pronounced synovitis and synovial vascular leakage and increased infiltration of macrophages and mast cells.

Objectives Autoantibody-negative RA differs from autoantibody-positive RA in several clinical aspects, possibly underpinned by pathogenetic differences. At present, the role of adaptive immune responses in autoantibody-negative RA remains unclear. Here, we investigated the synovial and serum immunophenotype indicative of B lymphocyte involvement across the spectrum of autoantibody-positive and -negative chronic arthritides. Methods Ultrasound-guided synovial biopsies were retrieved from 131 patients: 43 autoantibody-positive RA, 35 autoantibody-negative RA, 25 polyarticular PsA and 28 oligoarticular PsA. Samples were analysed for the degree of histological inflammation, B lymphocyte infiltration and the distribution of different pathotypes (lympho-myeloid, myeloid, pauci-immune). Serum levels of the B cell chemoattractant CXCL13 were compared among groups. Results Synovitis scores and CD68+ sublining macrophage infiltration were comparable irrespective of clinical diagnosis and disease subtype. In contrast, the degree of B lymphocyte infiltration and the frequency of lympho-myeloid synovitis in autoantibody-negative RA were lower than those of autoantibody-positive RA (mean [ s. d.] 1.8 [1] vs 2.4 [0.6], P  = 0.03, and 38.2% vs 62.9%, P  = 0.07, respectively), and similar to polyarticular PsA. Oligoarticular PsA had the lowest B cell scores. Serum CXCL13 was associated with lympho-myeloid synovitis and followed a similar gradient, with the highest levels in autoantibody-positive RA, intermediate and comparable levels in autoantibody-negative RA and polyarticular PsA, and low levels in oligoarticular PsA. Conclusions The synovial and serum immunophenotype indicative of B lymphocyte involvement in autoantibody-negative RA differs from that of autoantibody-positive RA and more closely resembles that observed in polyarticular PsA. The pathobiological stratification of chronic inflammatory arthritides beyond clinical diagnosis may fuel personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a chronic autoimmune disorder which can lead to long-term joint damage and significantly reduced quality of life if not promptly diagnosed and adequately treated. Despite significant advances in treatment, about 40% of patients with RA do not respond to individual pharmacological agents and up to 20% do not respond to any of the available medications. To address this large unmet clinical need, several recent studies have focussed on an in-depth histological and molecular characterisation of the synovial tissue to drive the application of precision medicine to RA. Currently, RA patients are clinically divided into "seropositive" or "seronegative" RA, depending on the presence of routinely checked antibodies. Recent work has suggested that over the last two decades, long-term outcomes have improved significantly in seropositive RA but not in seronegative RA. Here, we present up-to-date differences in epidemiology, clinical features, and serological biomarkers in seronegative versus seropositive RA and discuss how histological and molecular synovial signatures, revealed by recent large synovial biopsy-based clinical trials, may be exploited to refine the classification of RA patients, especially in the seronegative group. [ABSTRACT FROM AUTHOR]

Background: Delay in diagnosis and therapy in patients with arthritis commonly leads to progressive articular damage. The study aimed to investigate the immunohistochemical reactivity of synovial cytokines associated with inflammation and the bone erosives/neoformatives processes among individuals diagnosed with psoriatic arthritis (PsA), rheumatoid arthritis (RA), osteoarthritis (OA), and radiographic axial spondyloarthritis (r-axSpA), with the intention of identifying potential biomarkers. Methods: Specimens were collected from the inflamed knee joints of patients referred for arthroscopic procedures, and the synovial tissue (ST) was prepared for quantifying protein expression through immunohistochemical analysis (% expressed in Ratio_Area-Intensity) for TGF-β1, IL-17A, Dkk1, BMP2, BMP4, and Wnt5b. The collected data underwent thorough analysis and examination of their predictive capabilities utilising receiver operating characteristic (ROC) curves. Results: Valid synovial tissue samples were acquired from 40 patients for IHC quantification analysis. Initially, these patients had not undergone treatment with biologics. However, after 5 years, 4 out of 13 patients diagnosed with PsA and two out of nine patients diagnosed with RA had commenced biologic treatments. Individuals with early PsA who received subsequent biologic treatment exhibited significantly elevated IHC reactivity in ST for TGF-β1 (p = 0.015). Additionally, patients with both PsA and RA who underwent biologic therapy displayed increased IHC reactivity for IL-17A (p = 0.016), TGF-β1 (p = 0.009), and Dkk1 (p = 0.042). ROC curve analysis of IHC reactivity for TGF-β1, Dkk1, and IL-17A in the synovial seems to predict future treatment with biologics in the next 5 years with the area under the curve (AUC) of a combined sum of the three values: AUC: 0.828 (95% CI: 0.689–0.968; p 0.005) S 75% E 84.4%. Conclusions: Higher synovial immunohistochemistry reactivity of IL-17A, Dkk1, and TGF-β1 in patients with early psoriatic arthritis and rheumatoid arthritis may serve as potential indicators for predicting the necessity of utilising biologic treatments. [ABSTRACT FROM AUTHOR]

Purpose of Review: Rheumatoid arthritis is one of the most common rheumatic and autoimmune diseases. While it can affect many different organ systems, RA primarily involves inflammation in the synovium, the tissue that lines joints. Patients with RA exhibit significant clinical heterogeneity in terms of presence or absence of autoantibodies, degree of permanent deformities, and most importantly, treatment response. These clinical characteristics point to heterogeneity in the cellular and molecular pathogenesis of RA, an area that several recent studies have begun to address. Recent Findings: Single-cell RNA-sequencing initiatives and deeper focused studies have revealed several RA-associated cell populations in synovial tissues, including peripheral helper T cells, autoimmunity-associated B cells (ABCs), and NOTCH3+ sublining fibroblasts. Recent large transcriptional studies and translational clinical trials present frameworks to capture cellular and molecular heterogeneity in RA synovium. Technological developments, such as spatial transcriptomics and machine learning, promise to further elucidate the different types of RA synovitis and the biological mechanisms that characterize them, key elements of precision medicine to optimize patient care and outcomes in RA. Summary: This review recaps the findings of those recent studies and puts our current knowledge and future challenges into scientific and clinical perspective. [ABSTRACT FROM AUTHOR]

Abstract Background Inflammatory arthritis encompasses a group of immune-mediated diseases characterized by chronic joint inflammation. Despite having pathogenic mechanisms in common, the prognosis of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and undifferentiated arthritis (UA) could be different regarding progression to chronic, to erosive, or to self-limited disease. Our aim was to evaluate the potential association of synovial tissue (ST) inflammatory cell infiltrate, the presence of ectopic lymphoid neogenesis (LN +) structures, and poor prognosis factors (PPF) in patients with RA, PsA, and UA. Methods We conducted a retrospective study including patients with active arthritis (RA, PsA, UA) who had ST obtained by rheumatological arthroscopy or ultrasound-guided biopsy. Clinical, demographic, and immunohistochemical data of the synovium was evaluated. Patients with biological therapy at the time of synovial biopsy were excluded. PPF in patients with RA and UA were defined by the presence of anti-cyclic citrullinated peptide antibodies and/or rheumatoid factor, development of bone erosions, or requirement of biological therapy during the follow-up. PPF in patients with PsA were defined as the presence of high levels of acute-phase reactants (ESR/CRP), dactylitis or nail involvement at the time of biopsy, development of bone erosion, or requirement of biological therapy during the follow-up. Results A total of 88 patients were included: 26 RA, 33 PsA, and 29 UA. All patients were followed up for 5 years after the biopsy. Fourteen (53.84%) RA patients had PPF, and 17 (65.38%) had LN + . LN + was associated with PPF (p 0.038) and biologic therapy initiation (p 0.018). A total of 14 (43.75%) PsA patients had PPF. CD15 infiltrate (410.68 [SD 477.63] cells/mm2) was associated with PPF (p 0.008) in PsA patients. Sixteen (55.17%) patients with UA had PPF, and 13 (44.82%) had LN + . In this group, synovial CD68 + macrophages cells density was negatively correlated with DAS28-CRP (r = − 0.346, p 0.042). Conclusions The presence of LN + and higher CD15 + polymorphonuclear cells infiltrate was associated with PPF in RA and PsA, respectively. No associations were found for UA. These findings suggest a great heterogeneity of the ST features and its pathogenic implications in the subtypes of inflammatory arthritis.

With the increasing burden of osteoarthritis worldwide, cost efficient and reliable models are needed to enable the development of innovative therapies or therapeutic interventions. Ex vivo models have been identified as valuable modalities in translational research, bridging the gap between in vitro and in vivo models. Osteocartilaginous explants from Osteoarthritis (OA) patients offer an exquisite opportunity for studying OA progression and testing novel therapies. We describe the protocol for establishing human osteocartilaginous explants with or without co-culture of homologous synovial tissue. Furthermore, a detailed protocol for the assessment of explanted tissue in terms of protein content using Western blot and immunohistochemistry is provided. Commentaries regarding the technique of choice, possible variations and expected results are inserted.

Objectives: In knee osteoarthritis (OA), macrophages are the most predominant immune cells that infiltrate synovial tissues and infrapatellar fat pads (IPFPs). Both M1 and M2 macrophages have been described, but their role in OA has not been fully investigated. Therefore, we investigated macrophage subpopulations in IPFPs and synovial tissues of knee OA patients and their correlation with disease severity, examined their transcriptomics, and tested for factors that influenced their polarization. Methods: Synovial tissues and IPFPs were obtained from knee OA patients undergoing total knee arthroplasty. Macrophages isolated from these joint tissues were characterized via flow cytometry. Transcriptomic profiling of each macrophage subpopulations was performed using NanoString technology. Peripheral blood monocyte-derived macrophages (MDMs) were treated with synovial fluid and synovial tissue- and IPFP-conditioned media. Synovial fluidtreated MDMs were treated with platelet-rich plasma (PRP) and its effects on macrophage polarization were observed. Results: Our findings show that CD11c+CD206+ macrophages were predominant in IPFPs and synovial tissues compared to other macrophage subpopulations (CD11c+CD206-, CD11c-CD206+, and CD11c-CD206-macrophages) of knee OA patients. The abundance of macrophages in IPFPs reflected those in synovial tissues but did not correlate with disease severity as determined from Mankin scoring of cartilage destruction. Our transcriptomics data demonstrated highly expressed genes that were related to OA pathogenesis in CD11c+CD206+ macrophages than CD11c+CD206-, CD11c-CD206+, and CD11c-CD206-macrophages. In addition, MDMs treated with synovial fluid, synovial tissue-conditioned media, or IPFP-conditioned media resulted in different polarization profiles of MDMs. IPFP-conditioned media induced increases in CD86+CD206+ MDMs, whereas synovial tissue-conditioned media induced increases in CD86+CD206-MDMs. Synovial fluid treatment (at 1:8 dilution) induced a very subtle polarization in each macrophage subpopulation. PRP was able to shift macrophage subpopulations and partially reverse the profiles of synovial fluid-treated MDMs. Conclusion: Our study provides an insight on the phenotypes and genotypes of macrophages found in IPFPs and synovial tissues of knee OA patients. We also show that the microenvironment plays a role in driving macrophages to polarize differently and shifting macrophage profiles can be reversed by PRP. [ABSTRACT FROM AUTHOR]

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Objective: To explore pathogenesis, characteristic genes and immune infiltration of rheumatoid arthritis (RA) by bioinformatics and machine learning methods, and to find correlation between characteristic genes and immune cells. Methods: Chips related to RA were obtained from GEO database, gene differences were analyzed by R language, and GO and KEGG were enriched and analyzed; machine learning methods, namely LASSO regression and SVM-RFE were used to screen disease characteristic genes, ROC curve and sample chips were used to detect accuracy of characteristic genes, CIBERPORT algorithm was used to analyze immune infiltration of RA, and correlation between characteristic genes and immune cells was analyzed. Results: A total of 90 differential genes were obtained from GSE12021 and GSE55235, including 64 up-regulated and 26 down-regulated differentially expressed genes. A total of 209 main items were obtained by GO analysis, mainly involving leukocyte activation, lymphocyte activation, B-cell receptor signaling pathway, etc; KEGG analysis showed that chemokine signaling pathway, IL-17 signaling pathway, Toll-like receptor signaling pathway and PPAR signaling pathway were closely related to RA; ten key genes such as IGHM, SLAMF8, CXCL10, FNDC4, AIM2, EGR1 and AKR1B10 were screened by mechanical learning method. Disease characteristic genes were IGHM, SLAMF8, CXCL10, AIM2 and AKR1B10 by ROC curve and sample chip; immune infiltration results showed that there were significant differences between synovial tissues of RA and normal tissues in 9 kinds of immune cells, such as plasma cells, CD8 T cell, CD4 T cell and T cell follicle helper. By analyzing correlation between disease characteristic genes and immune cells, it was found that there were significant correlations between 5 characteristic genes and some immune cells. Conclusion: There is a significant correlation between characteristic genes and immune cells of RA, which provides a preliminary basis for follow-up in-depth study of targeted diagnosis and treatment of RA. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a serious threat to human health. However, the etiology and pathogenesis of the disease are not fully understood. Most researchers believe that the degeneration and imbalance of articular cartilage, extracellular matrix, and subchondral bone are the fundamental causes of osteoarthritis. However, recent studies have shown that synovial lesions may precede cartilage, which may be an important precipitating factor in the early stage of OA and the whole course of the disease. This study aimed to conduct an analysis based on sequence data from the Gene Expression Omnibus (GEO) database to investigate the presence of effective biomarkers in the synovial tissue of osteoarthritis for the diagnosis and control of OA progression. In this study, the differentially expressed OA-related genes (DE-OARGs) in osteoarthritis synovial tissues were extracted in the GSE55235 and GSE55457 datasets using the Weighted Gene Co-expression Network Analysis (WGCNA) and limma. Least-Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to select the diagnostic genes based on the DE-OARGs by glmnet package. 7 genes were selected as diagnostic genes including SAT1, RLF, MAFF, SIK1, RORA, ZNF529, and EBF2. Subsequently, the diagnostic model was constructed and the results of the Area Under the Curve (AUC) demonstrated that the diagnostic model had high diagnostic performance for OA. Additionally, among the 22 immune cells of the Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and the 24 immune cells of the single sample Gene Set Enrichment Analysis (ssGSEA), 3 immune cells and 5 immune cells were different between the OA and normal samples, respectively. The expression trends of the 7 diagnostic genes were consistent in the GEO datasets and the results of the real-time reverse transcription PCR (qRT-PCR). The results of this study demonstrate that these diagnostic markers have important significance in the diagnosis and treatment of OA, and will provide further evidence for the clinical and functional studies of OA. [ABSTRACT FROM AUTHOR]

BACKGROUND: Studies have shown that an elevation in miR-23b is closely related to the occurrence and development of rheumatoid arthritis; therefore, inhibiting the expression of miR-23b can be a new target for the treatment of the disease. OBJECTIVE: To explore the effect of miR-23b on the regulation of transforming growth factor-β1 in synovial tissue and the inhibition of osteoclast activity in rats with rheumatoid arthritis. METHODS: Sixty SPF male Sprague-Dawley rats were randomly divided into normal control group, model group, miR-NC group, and miR-23b inhibitor group (n=15 per group). Except for the normal control group, animal models of rheumatoid arthritis were prepared in the other three groups using Fredrin complete adjuvant method. After successful modeling, the miR-NC group was injected with 20 μL of 1×108 /L miR-NC and the miR-23b inhibitor group was injected with 20 μL of 1×108 /L miR-23b inhibitor. Normal control group and model group were injected with the same volume of normal saline at the same time. Twentyone days later, hematoxylin-eosin staining was used to detect the pathological morphology of the articular tissue of rats, real-time PCR was used to detect the relative mRNA expression of miR-23b in rat serum, and immunohistochemical method was used to detect the protein expression of transforming growth factor-β1 in the synovial tissue of rats. The activity of osteoclasts was detected by tartrate-resistant acid phosphatase staining and phalloidin staining. RESULTS AND CONCLUSION: In the normal control group, the structure of synovial cells was normal and neatly arranged. In the model and miR-NC groups, synovial cells proliferated obviously and arranged in disorder. At the same time, capillaries and fibrous connective tissue were obviously proliferated, accompanied by a large number of inflammatory cells infiltrated. In the miR-23b inhibitor group, mild hyperplasia of synovial cells and a small amount of inflammatory cell infiltration appeared, and edema and congestion were significantly improved. The relative expression of miR-23b in the serum was significantly increased in the model group compared with the normal control group (P < 0.05), while there was no significant difference between the model group and the miR-NC group (P > 0.05). The relative expression of miR-23b in the miR-23b inhibitor group was significantly lower than that in the miR-NC group (P < 0.05). Compared with the normal control group, the expression of transforming growth factor-β1 protein in the synovial tissue was significantly increased in the model group (P < 0.05), while there was no significant difference between the model and miR-NC groups (P > 0.05). The expression of transforming growth factor-β1 protein in the synovial tissue was significantly lower in the miR-23b inhibitor group than the miR-NC group (P < 0.05). Compared with the normal control group, a highly positive expression of typical multinucleated osteoclasts was found in the synovial fibroblasts of the model group by the tartrateresistant acid phosphatase staining (P < 0.05). There was no significant difference between the model and the miR-NC groups (P > 0.05). The volume and number of osteoclasts in the miR-23b inhibitor group were significantly lower than those in the miR-NC group (P < 0.05). Compared with the normal control group, the phalloidin staining of osteoclasts significantly indicated the formation of rings composed of actin filaments in the model group (P < 0.05) and there was no significant difference between the model and miR-NC groups (P > 0.05), while the actin ring area was significantly reduced in the miR-23b inhibitor group compared with the miR-NC group (P < 0.05). The above results indicate that reducing the expression of miR-23b can play a therapeutic effect on rheumatoid arthritis, which can effectively inhibit the expression of transforming growth factor-β1 and reduce the activity of osteoclasts in rat synovial tissue. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a chronic autoimmune disorder which can lead to long-term joint damage and significantly reduced quality of life if not promptly diagnosed and adequately treated. Despite significant advances in treatment, about 40% of patients with RA do not respond to individual pharmacological agents and up to 20% do not respond to any of the available medications. To address this large unmet clinical need, several recent studies have focussed on an in-depth histological and molecular characterisation of the synovial tissue to drive the application of precision medicine to RA. Currently, RA patients are clinically divided into “seropositive” or “seronegative” RA, depending on the presence of routinely checked antibodies. Recent work has suggested that over the last two decades, long-term outcomes have improved significantly in seropositive RA but not in seronegative RA. Here, we present up-to-date differences in epidemiology, clinical features, and serological biomarkers in seronegative versus seropositive RA and discuss how histological and molecular synovial signatures, revealed by recent large synovial biopsy-based clinical trials, may be exploited to refine the classification of RA patients, especially in the seronegative group.

Background: Delay in diagnosis and therapy in patients with arthritis commonly leads to progressive articular damage. The study aimed to investigate the immunohistochemical reactivity of synovial cytokines associated with inflammation and the bone erosives/neoformatives processes among individuals diagnosed with psoriatic arthritis (PsA), rheumatoid arthritis (RA), osteoarthritis (OA), and radiographic axial spondyloarthritis (r-axSpA), with the intention of identifying potential biomarkers. Methods: Specimens were collected from the inflamed knee joints of patients referred for arthroscopic procedures, and the synovial tissue (ST) was prepared for quantifying protein expression through immunohistochemical analysis (% expressed in Ratio_Area-Intensity) for TGF-β1, IL-17A, Dkk1, BMP2, BMP4, and Wnt5b. The collected data underwent thorough analysis and examination of their predictive capabilities utilising receiver operating characteristic (ROC) curves. Results: Valid synovial tissue samples were acquired from 40 patients for IHC quantification analysis. Initially, these patients had not undergone treatment with biologics. However, after 5 years, 4 out of 13 patients diagnosed with PsA and two out of nine patients diagnosed with RA had commenced biologic treatments. Individuals with early PsA who received subsequent biologic treatment exhibited significantly elevated IHC reactivity in ST for TGF-β1 (p = 0.015). Additionally, patients with both PsA and RA who underwent biologic therapy displayed increased IHC reactivity for IL-17A (p = 0.016), TGF-β1 (p = 0.009), and Dkk1 (p = 0.042). ROC curve analysis of IHC reactivity for TGF-β1, Dkk1, and IL-17A in the synovial seems to predict future treatment with biologics in the next 5 years with the area under the curve (AUC) of a combined sum of the three values: AUC: 0.828 (95% CI: 0.689–0.968; p 0.005) S 75% E 84.4%. Conclusions: Higher synovial immunohistochemistry reactivity of IL-17A, Dkk1, and TGF-β1 in patients with early psoriatic arthritis and rheumatoid arthritis may serve as potential indicators for predicting the necessity of utilising biologic treatments.

We investigated the potential involvement of pyroptosis, a proinflammatory form of regulated cell death, in rheumatoid arthritis (RA). Synovial fluid, synovial tissues and/or serum were compared among 32 patients with RA, 46 patients with osteoarthritis (OA) and 30 healthy controls. Samples were assayed for interleukin (IL)‐1β, IL‐18 and lactate hydrogenase (LDH). Synovial expression of NLRP3, caspase‐1 and cleaved gasdermin D (GSDMD) was assayed using immunohistochemistry and multiplex immunohistochemistry. Patients with RA showed significantly higher levels of IL‐1β and IL‐18 in synovial fluid than patients with OA, and significantly higher levels of both cytokines in serum than healthy controls. RA was associated with higher levels of LDH in synovial fluid than OA. Among patients with RA, levels of IL‐1β, IL‐18 and LDH were significantly higher in synovial fluid than in serum, and the levels in synovial fluid positively correlated with disease activity and inflammation. Synovial cells, particularly macrophages, showed upregulation of NLRP3, caspase‐1 and cleaved GSDMD in RA compared to OA. Our results implicate pyroptosis in the pathogenesis of RA, perhaps as a driver of local inflammation in joints. [ABSTRACT FROM AUTHOR]

BACKGROUND: Rheumatoid arthritis is an autoimmune disease. Research on rheumatoid arthritis mainly focuses on its pathogenesis and target therapy. OBJECTIVE: To search for differential genes by bioinformatics analysis of rheumatoid arthritis synovitis gene chip datasets, and to establish and improve the gene regulation network of rheumatoid arthritis. METHODS: GEO2R was used to analyze the differential expression of rheumatoid arthritis chips screened from the database. R language and DAVID were used for gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes. String database was used for protein-protein interaction network analysis. Cystoscape software was used to obtain key genes. qPCR and western blot were used for experimental verification of some key target genes. RESULTS AND CONCLUSION: There were 2 064 differentially expressed genes in the synovial tissue of patients with rheumatoid arthritis, including 625 upregulated genes and 1 439 down-regulated genes. Differentially expressed genes are mainly involved in immune response-activated cell surface receptor signaling pathway, antigen receptor mediated signaling pathway and other biological responses. Ten key target genes, including epidermal growth factor receptor (EGFR), MYC, RELA, ITGB2, LCK, EPHB2, IRF4, NRAS, FN1, and MAPK1, were identified by the protein-protein interaction network analysis. The number of protein interaction lines based on the protein-protein interaction network and Cystoscape algorithm score were used to obtain five genes with high significance, including EGFR, MYC, RELA, ITGB2, and LCK, and the experimental verification of these genes was carried out by qPCR and western blot experiments. The mRNA and protein expression levels of EGFR, MYC, RELA, ITGB2, and LCK genes in the synovial tissue of patients with rheumatoid arthritis were significantly higher than those of the control group, and the expression of EGFR changed most significantly. To conclude, there are distinct gene expression characteristics in the synovial tissue of knee joint after rheumatoid arthritis, and EGFR is the most valuable differentially expressed gene in the synovium of rheumatoid arthritis. [ABSTRACT FROM AUTHOR]

Abstract Objective To identify novel DNA methylation-regulated differentially expressed genes (MeDEGs) in RA by integrated analysis of DNA methylation and RNA-Seq data. Methods The transcription and DNA methylation profiles of 9 RA and 15 OA synovial tissue were generated by RNA-Seq and Illumina 850K DNA methylation BeadChip. Gene set enrichment analysis (GSEA) and Weighted gene co-expression network analysis (WGCNA) were used to analyze methylation-regulated expressed genes by R software. The differentially expressed genes (DEGs), differentially methylated probes (DMPs), differentially methylated genes (DMGs) were analyzed by DESeq and ChAMP R package. The functional correlation of MeDEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein–protein interaction (PPI) network of MeDEGs was constructed by STRING and Reactome FI Cytoscape Plugin. Correlation analysis between methylation level and mRNA expression was conducted with R software. Results A total of 17,736 genes, 25,578 methylated genes and 755,852 methylation probes were detected. A total of 16,421 methylation-regulated expressed genes were obtained. The GSEA showed that these genes are associated with activation of immune response, adaptive immune response, Inflammatory response in C5 (ontology gene sets). For KEGG analysis, these genes are associated with rheumatoid arthritis, NF-kappa B signaling pathway, T cell receptor signaling pathway. The WGCNA showed that the turquoise module exhibited the strongest correlation with RA (R = 0.78, P = 1.27 × 10− 05), 660 genes were screened in the turquoise module. A total of 707 MeDEGs were obtained. GO analysis showed that MeDEGs were enriched in signal transduction, cell adhesion for BP, enriched in plasma membrane, integral component of membrane for CC, and enriched in identical protein binding, calcium ion binding for MF. The KEGG pathway analysis showed that the MeDEGs were enriched in calcium signaling pathway, T cell receptor signaling pathway, NF-kappa B signaling pathway, Rheumatoid arthritis. The PPI network containing 706 nodes and 882 edges, and the enrichment p value

AimsThis study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue.MethodsThe gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.ResultsA total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018).ConclusionATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression.Cite this article: Bone Joint Res 2022;11(9):679–689.

Introduction: Arthroscopy for knee surgery is the most often used minimally invasive orthopaedic surgical technique. Postoperative discomfort can be caused by irritation to the nerve endings in the synovial tissue, the fat pad in the front of the knee, and the joint capsule that can take place during the excision and resection. Aim: To compare the efficacy of Intra-Articular (IA) dexmedetomidine versus buprenorphine for postoperative analgesia following arthroscopic knee surgeries. Materials and Methods: A prospective interventional study was carried out for a period of one and a half years from January 2021 to June 2022 at Department of Anaesthesiology B.L.D.E. (Deemed to be University) Shri B.M. Patil Medical College, Hospital and Research Centre, Vijayapura, Karnataka, India. Around 80 patients of both genders of American Society of Anaesthesiologists (ASA) grade I and II who were scheduled for arthroscopic knee surgeries were randomly divided into two equal groups of 40 each. After the operation was finished, the patients in each group received the respective medications intra-articularly through an arthroscopy port. Group D received Inj. Dexmedetomidine 100 mcg+ Inj. Bupivacaine 0.25%, 20 mL. Injections of buprenorphine 100 mcg and bupivacaine at a concentration of 0.25%, 20 mL were given to the participants in group B. Immediately following surgery, the patient's temperature, pulse, Mean Arterial Pressure (MAP), and Visual Analogue Scale (VAS) score for pain were all monitored and recorded at the 1st, 2nd, 4th, 8th, 12th and 24th hour. Time to first rescue analgesia, the number of patients requiring rescue analgesia within the next 24 h, the visual analog scale at rest, and on mobilisation at 1st, 2nd, 4th, 8th, 12th, and 24 hour were measured. Side-effects like sedation, pruritis, nausea, vomiting, respiratory depression, and hypotension were also monitored. Descriptive statistics were reported as mean (SD) for continuous variables, and frequencies (percentage) for categorical variables. Data were statistically evaluated with IBM Statistical Package for the Social Sciences (SPSS) Statistics for Windows, Version 26.0, IBM Corp., Chicago, IL. Results: The mean age of the study participants was 38.38±11.30 years among the buprenorphine group and 36.40±12.07 years among the Dexmedetomidine group. Among the Buprenorphine group 52.5% were females and 47.5% were males. There was a statistically significant difference in VAS score at rest and mobilisation between the groups. The mean time for first rescue analgesia was longer for the buprenorphine group 1016.22±137.54 minutes and for the dexmedetomidine group, it was 523.67±117.47 minutes. Rescue analgesia was given to 9 (22.5%) in the buprenorphine and 18 (45%) in the dexmedetomidine group. Conclusion: In comparison to IA dexmedetomidine, buprenorphine produces analgesia for a longer period of time and reduces the amount of postoperative rescue analgesic that is required. [ABSTRACT FROM AUTHOR]

Introduction: Arthroscopy for knee surgery is the most often used minimally invasive orthopaedic surgical technique. Postoperative discomfort can be caused by irritation to the nerve endings in the synovial tissue, the fat pad in the front of the knee, and the joint capsule that can take place during the excision and resection. Aim: To compare the efficacy of Intra-Articular (IA) dexmedetomidine versus buprenorphine for postoperative analgesia following arthroscopic knee surgeries. Materials and Methods: A prospective interventional study was carried out for a period of one and a half years from January 2021 to June 2022 at Department of Anaesthesiology B.L.D.E. (Deemed to be University) Shri B.M. Patil Medical College, Hospital and Research Centre, Vijayapura, Karnataka, India. Around 80 patients of both genders of American Society of Anaesthesiologists (ASA) grade I and II who were scheduled for arthroscopic knee surgeries were randomly divided into two equal groups of 40 each. After the operation was finished, the patients in each group received the respective medications intra-articularly through an arthroscopy port. Group D received Inj. Dexmedetomidine 100 mcg+ Inj. Bupivacaine 0.25%, 20 mL. Injections of buprenorphine 100 mcg and bupivacaine at a concentration of 0.25% , 20 mL were given to the participants in group B. Immediately following surgery, the patient’s temperature, pulse, Mean Arterial Pressure (MAP), and Visual Analogue Scale (VAS) score for pain were all monitored and recorded at the 1st, 2nd, 4th, 8th, 12th and 24th hour. Time to first rescue analgesia, the number of patients requiring rescue analgesia within the next 24 h, the visual analog scale at rest, and on mobilisation at 1st, 2nd, 4th, 8th, 12th, and 24 hour were measured. Side-effects like sedation, pruritis, nausea, vomiting, respiratory depression, and hypotension were also monitored. Descriptive statistics were reported as mean (SD) for continuous variables, and frequencies (percentage) for categorical variables. Data were statistically evaluated with IBM Statistical Package for the Social Sciences (SPSS) Statistics for Windows, Version 26.0, IBM Corp., Chicago, IL. Results: The mean age of the study participants was 38.38±11.30 years among the buprenorphine group and 36.40±12.07 years among the Dexmedetomidine group. Among the Buprenorphine group 52.5% were females and 47.5% were males. There was a statistically significant difference in VAS score at rest and mobilisation between the groups. The mean time for first rescue analgesia was longer for the buprenorphine group 1016.22±137.54 minutes and for the dexmedetomidine group, it was 523.67±117.47 minutes. Rescue analgesia was given to 9 (22.5%) in the buprenorphine and 18 (45%) in the dexmedetomidine group. Conclusion: In comparison to IA dexmedetomidine, buprenorphine produces analgesia for a longer period of time and reduces the amount of postoperative rescue analgesic that is required.

Osteoarthritis (OA) is a chronic disease common in the elderly population and imposes significant health and economic burden. Total joint replacement is the only currently available treatment but does not prevent cartilage degeneration. The molecular mechanism of OA, especially the role of inflammation in disease progression, is incompletely understood. We collected knee joint synovial tissue samples of eight OA patients and two patients with popliteal cysts (controls), measured the expression levels of lncRNAs, miRNAs, and mRNAs in these tissues by RNA-seq, and identified differentially expressed genes (DEGs) and key pathways. In the OA group, 343 mRNAs, 270 lncRNAs, and 247 miRNAs were significantly upregulated, and 232 mRNAs, 109 lncRNAs, and 157 miRNAs were significantly downregulated. mRNAs potentially targeted by lncRNAs were predicted. Nineteen overlapped miRNAs were screened based on our sample data and GSE 143514 data. Pathway enrichment and functional annotation analyses showed that the inflammation-related transcripts CHST11, ALDH1A2, TREM1, IL-1β, IL-8, CCL5, LIF, miR-146a-5p, miR-335-5p, lncRNA GAS5, LINC02288, and LOC101928134 were differentially expressed. In this study, inflammation-related DEGs and non-coding RNAs were identified in synovial samples, suggesting that competing endogenous RNAs have a role in OA. TREM1, LIF, miR146-5a, and GAS5 were identified to be OA-related genes and potential regulatory pathways. This research helps elucidate the pathogenesis of OA and identify novel therapeutic targets for this disorder. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a degenerative joint disease affecting millions of people worldwide. In OA, chondrocytes, synovial cells and other joint cells become activated when exposed to an abnormal environment, including mechanical stress, inflammatory cytokines or disorganization of matrix proteins. Several analogues of the hormones called incretins have been developed and are used notably for treating type 2 diabetes mellitus. Data has accumulated to suggest that incretinomimetics, which bind to the glucagon-like peptide-1 receptor (GLP-1R), have beneficial pleiotropic effects such as immunomodulation, anti-inflammation and neuronal protection. Thus, because of their anti-inflammatory properties, GLP-1–based therapies could benefit OA patients. This review focuses on the GLP-1R pathway, molecular mechanisms and phenotypes related to OA pathogenesis. The translational potential of this article: The search for new therapeutic targets to treat people suffering from OA remains urgent as there is currently no disease-modifyingtherapy available for this disease. This review discusses how GLP-1 analogues could be potential DMOADs for treating OA thanks to their anti-inflammatory, immunoregulatory and differentiation properties.

BackgroundDetailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.MethodsMultiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq.ResultsUpon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.ConclusionsWe have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

Rheumatoid arthritis (RA), a systemic autoimmune disease, is known to cause chronic inflammation in synovial joints. A number of inflammatory conditions are associated with stimulation of Clec4e, a macrophage-inducible C-type lectin (MINCLE) and transmembrane pattern recognition receptor that functions in innate immunity. We previously reported MINCLE expression in synovial macrophages isolated from the synovium of osteoarthritis (OA) patients. However, MINCLE expression has not been examined in RA synovial tissue. To examine MINCLE expression in RA patients, synovial tissue specimens were obtained from patients with RA and OA during joint replacement surgery (n = 20 each). Total RNA was extracted from synovial tissue and used to compare MINCLE expression in OA and RA (n = 15 each). We also extracted fresh CD14+ (macrophage-rich) and CD14– cell fractions from synovial tissue and compared MINCLE expression between OA and RA patients (n = 5 each). MINCLE levels in synovial tissue were significantly elevated in RA patients compared to OA patients. MINCLE expression was significantly elevated in the CD14+ fraction compared to the CD14– fraction in both OA and RA patients. Further, while there were no differences in the CD14+ fraction between RA and OA, MINCLE expression in the CD14– fraction was elevated in RA compared to OA. Our findings indicate that MINCLE expression is elevated in the synovium of RA patients and that MINCLE expression in non-macrophage cell fractions may be a key feature of RA.

BACKGROUND: Osteoarthritis is a common chronic degenerative disease with a high correlation with age. However, its specific pathogenesis is still unclear, and there are many deficiencies in early diagnosis and treatment. OBJECTIVE: To screen the key expressed genes in the synovium of osteoarthritis by bioinformatics method, so as to lay a foundation for finding biomarkers for the diagnosis of osteoarthritis and elucidating its underlying pathogenesis. METHODS: Four osteoarthritic synovial tissue data sets were downloaded from the Gene Expression Omnibus database (GSE32317, GSE55235, GSE55457, GSE82107), including 27 normal synovial tissue samples and 49 osteoarthritic synovial tissue samples. The intersection genes of differentially expressed genes and Weighted Co-expression Network Construction Analysis results were screened using R language. Functional annotation, protein-protein interaction network, and immune infiltration analyses of the intersection genes were performed, and cytoscape was used for network visualization. Prism was used to draw receiver operating characteristic curve for the top 10 genes for degree ranking and screen out key genes, and then another synovial data set, GSE12021, was used for verification. Finally, the key genes in the synovial samples from four osteoarthritis patients and four non-osteoarthritis patients (joint injury) were further detected by PCR. RESULTS AND CONCLUSION: (1) In this study, 263 differentially expressed genes and 1 237 key module genes of Weighted Co-expression Network Construction Analysis were identified, with a total of 98 intersection genes. (2) Protein-protein interaction node number of the top 10 most genes included interleukin 6, JUN, ATF3, MYC, DUSP1, VEGFA, FOSB, CXCL8, PTGS2, and NR4A1. (3) According to the receiver operating characteristic curve, ATF3 and DUSP1 had a higher diagnostic accuracy (area under the curve > 0.8). (4) Verification with the data set GSE12021 and PCR detection indicated that the gene expression difference of ATF3 and DUSP1 between the osteoarthritis group and the control group was statistically significant (P < 0.01), which was consistent with the results of network analysis. (5) Through bioinformatics analysis, ATF3 and DUSP1 are considered to have high diagnostic value for osteoarthritis and may be potential biomarkers and therapeutic targets for osteoarthritis diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Objective: To identify novel DNA methylation-regulated differentially expressed genes (MeDEGs) in RA by integrated analysis of DNA methylation and RNA-Seq data.Methods: The transcription and DNA methylation profiles of 9 RA and 15 OA synovial tissue were generated by RNA-Seq and Illumina 850K DNA methylation BeadChip. Gene set enrichment analysis (GSEA) and Weighted gene co-expression network analysis (WGCNA) were used to analyze methylation-regulated expressed genes by R software. The differentially expressed genes (DEGs), differentially methylated probes (DMPs), differentially methylated genes (DMGs) were analyzed by DESeq and ChAMP R package. The functional correlation of MeDEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction (PPI) network of MeDEGs was constructed by STRING and Reactome FI Cytoscape Plugin. Correlation analysis between methylation level and mRNA expression was conducted with R software.Results: A total of 17,736 genes, 25,578 methylated genes and 755,852 methylation probes were detected. A total of 16,421 methylation-regulated expressed genes were obtained. The GSEA showed that these genes are associated with activation of immune response, adaptive immune response, Inflammatory response in C5 (ontology gene sets). For KEGG analysis, these genes are associated with rheumatoid arthritis, NF-kappa B signaling pathway, T cell receptor signaling pathway. The WGCNA showed that the turquoise module exhibited the strongest correlation with RA (R = 0.78, P = 1.27 × 10- 05), 660 genes were screened in the turquoise module. A total of 707 MeDEGs were obtained. GO analysis showed that MeDEGs were enriched in signal transduction, cell adhesion for BP, enriched in plasma membrane, integral component of membrane for CC, and enriched in identical protein binding, calcium ion binding for MF. The KEGG pathway analysis showed that the MeDEGs were enriched in calcium signaling pathway, T cell receptor signaling pathway, NF-kappa B signaling pathway, Rheumatoid arthritis. The PPI network containing 706 nodes and 882 edges, and the enrichment p value < 1.0 × 10- 16. With Cytoscape, based on the range of more than 10 genes, a total of 8 modules were screened out. Spearman correlation analysis showed RGS1(cg10718027), RGS1(cg02586212), RGS1(cg10861751) were significantly correlated with RA.Conclusions: RGS1 can be used as novel methylated biomarkers for RA. [ABSTRACT FROM AUTHOR]

Background: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease with symptoms characterized by typical circadian rhythmic changes. This study aimed to identify the hub circadian rhythm genes (CRGs) in RA and explore their association with immune cell infiltration and pathogenesis of RA. Methods: The differentially expressed CRGs (DECRGs) between RA and normal control samples were screened from Datasets GSE12021 and GSE55235. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to explore the potential functional mechanisms of DECRGs in RA. Weighted Gene Co-expression Network Analysis and Least Absolute Shrinkage and Selection Operator regression analysis were performed to identify hub CRGs of RA. CIBERSORT was conducted to compare the infiltration level of immune cells in RA and control synovial tissue and their relationship with hub genes. In addition, the diagnostic value of hub biomarkers was evaluated by the area under the receiver operator characteristic curve. Further, a nomogram prediction model was constructed and its significance for clinical decision-making was evaluated. Results: The green module was identified as the hub module associated with RA. Four hub CRGs (EGR1, FOSL2, GADD45B, and NFIL3) were identified and showed that they had the highest specificity and sensitivity for RA diagnosis, respectively. The expression levels and diagnostic values of these genes were externally validated in the dataset GSE55457. A nomogram prediction model based on the four hub CRGs was constructed and proved to have a certain clinical decision value. Additionally, the correlation analysis of immune cells with hub genes showed that all hub genes were significantly positively correlated with activated mast cells, resting memory CD4+ T cells, and monocytes. Whereas, all hub genes were negatively correlated with plasma cells, CD8+ T cells, and activated memory CD4+ T cells. Meanwhile, FOSL2 and GADD45B were negatively correlated with Tfh cells. Conclusion: Four hub CRGs were identified and showed excellent diagnostic value for RA. These genes may be involved in the pathological process of RA by disrupting the rhythmic oscillations of cytokines through immune-related pathways and could be considered molecular targets for future chronotherapy against RA. [ABSTRACT FROM AUTHOR]

Objectives: The growth and differentiation factor 5 (GDF5) gene plays a significant role in facilitating chondrogenesis, and GDF5 polymorphism is a genetic factor contributing to osteoarthritis (OA). However, the role of GDF5 expression in the synovial membrane remains unclear. The aim of this study was to determine the expression of GDF5 in the synovium in patients with primary knee OA. Materials and methods: Thirty patients scheduled for total knee arthroplasty were enrolled. Patients were grouped according to the Kellgren and Lawrence classification (KL) as grade 3 (15 patients) and grade 4 (15 patients). Synovial tissue was collected, and the GDF5 expression level was determined by real-time PCR. Ten synovial samples were randomly selected to evaluate the degree of synovitis. Results: Baseline characteristics did not differ between the two groups. The expression of GDF5 was significantly higher in the KL4 group (median expression 3.50, range 1.45–13.62) than in the KL3 group (median expression 1.81, range 0–9.46) (p value = 0.02). Histological staining of the synovium indicated low-grade synovitis in both groups. Conclusions: GDF5 expression in the synovium was positively associated with the radiographic severity of knee OA. The difference in GDF5 expression between the KL3 and KL4 groups supports the hypothesis that, through GDF5, the synovium may have important roles in cartilage maintenance and homeostasis in primary knee OA.

BACKGROUND: Primary knee osteoarthritis is one of the most common chronic diseases among the elderly, which brings a heavy burden on society and families. Current clinical treatments only focus on surgeries such as total knee replacement, but it is difficult to prevent cartilage tissue degeneration at an early stage. The formation mechanism of knee osteoarthritis, especially the influence of inflammation in disease progression, has been reported to some extent, but its specific mechanism is still unclear. OBJECTIVE: To investigate the differentially expressed circRNA sites of primary knee osteoarthritis and rheumatoid arthritis and their effects on the pathogenesis of the disease. METHODS: In this study, we collected the synovial tissues from eight patients with primary knee osteoarthritis and two patients with rheumatoid arthritis (control group). The expression profile of circRNAs in the tissue was detected by RNA-seq technique, trying to find the differentially expressed genes and key biological function pathways. RESULTS AND CONCLUSION: Compared with patients with rheumatoid arthritis, 185 differentially expressed circRNAs were detected in patients with knee osteoarthritis, of which 14 were up-regulated and 171 were down-regulated. Through the pathway enrichment and functional annotation of these target genes, a variety of enrichment pathways were identified, including protein H3-K36 dimethylation, glycosphingolipid biosynthesis process, and positive regulation of Toll-like receptor 9 signaling pathway. Based on the above sequencing results, a circRNA-miRNA interaction network was created, contributing to understanding the effect of differentially expressed circRNAs. In this study, we determined the differential expression of inflammation-related circRNAs in synovial tissue and the control group. These differentially expressed transcripts may elucidate the effect of circRNA and its relationship network in synovial tissue on the progression of osteoarthritis. Findings from this study will be helpful to explore the pathogenesis and key therapeutic targets of osteoarthritis. [ABSTRACT FROM AUTHOR]

Background: In patients with rheumatoid arthritis (RA) different joints were shown to share the same dominant T-cell clones, suggesting shared characteristics of the inflammatory process and indicating that strategies to selectively target the antigen receptor might be feasible. Since T- and Blymphocytes closely interact in adaptive responses, we analysed to what extent different joints also share dominant B-cell clones. Methods: In 11 RA patients, quantitative B-cell receptor (BCR) repertoire analysis was performed in simultaneously obtained samples from inflamed synovial tissue (ST) from distinct locations within one joint, from multiple joints, from synovial fluid (SF) and peripheral blood (PB). Results: ST biopsies from different locations in the same joint showed clear overlap in the top-25 dominant BCR clones (16.7%, SD 12.5), in the same range as the overlap between ST and SF in the same joint (8.0%, SD 8.8) and the overlap between ST-ST between different joints (9.1%, SD 8.2), but clearly higher than the overlap between ST and PB (1.7%, SD 2.4; p<0.05) and SF and PB (2.7%, SD 4.1; p<0.05). Interestingly, these figures were substantially lower than the overlap observed in previous T-cell clonality studies. Conclusions: We conclude that in RA BCR clonal responses may be more localized than TCR clonal responses, pointing to antigen-selective influx, proliferation and/or maturation of B-cells. B lineage cells in the SF may adequately represent the dominant BCR clones of the ST, which is in contrast to T-cells. Collectively, the presence of shared B- and especially T-cells in different joints from the same patient suggests that approaches might be feasible that aim to develop antigen-receptor specific targeting of lymphocyte clones in RA as an alternative tomore generalized immunosuppressive strategies. [ABSTRACT FROM AUTHOR]

BACKGROUND: Osteoarthritis is a common degenerative disease. Its occurrence is related to a variety of risk factors. At present, there is no effective treatment plan other than surgical treatment. The regulatory genes related to osteoarthritis are involved in the occurrence and development of osteoarthritis. However, the gene regulatory network of osteoarthritis has not been established completely. OBJECTIVE: To carry out the bioinformatics analysis of osteoarthritis gene chip data set, so as to find new biomarkers of osteoarthritis and experimentally verify MYC and JUN genes. METHODS: GEO database online analysis tool GEO2R was used to screen the differential genes of GSE55457 and GSE55235 chip data. The common differential genes of the two data sets were taken for GO function enrichment analysis and pathway enrichment analysis. String database was then used to construct protein interaction network, and Cytoscape3.8.0 software was applied to obtain the key genes. Finally RT-PCR and western blot were used to detect the mRNA and protein expression of MYC and JUN genes in osteoarthritic and normal synovial tissue. Synovial specimens were taken from the synovial tissues of three patients with osteoarthritis and three patients with meniscal injuries in the Renmin Hospital of Wuhan University. RESULTS AND CONCLUSION: The GSE55457 dataset had 704 up-regulated genes and 113 down-regulated genes; the GSE55235 dataset had 492 up-regulated genes and 723 down-regulated genes; the two together had 89 up-regulated genes and 30 down-regulated genes. Functional enrichment showed that differential genes mainly played a role in response to macrophage colony stimulation and binding glucocorticoid receptors. Pathway enrichment analysis showed that differential genes were mainly involved in the MAPK signaling pathway and amino acid metabolism. Ten key target genes were identified based on the protein-protein interaction network, including MYC, JUN, MCL1, CDKN1A, HNRNPA1, VEGFA, NCOA3, ATF3, BTG2, and CD44. Two key genes, MYC and JUN, were obtained based on the higher score of the protein-protein interaction network graph algorithm and the number of protein interaction lines. The results of RT-PCR and western blot experiments showed that the expression of MYC and JUN at mRNA and protein levels was significantly increased in osteoarthritic synovial tissue compared with the control group (mRNA: MYC P=0.035 2, JUN P=0.015 6, protein: MYC P=0.027 2, JUN P=0.026 6). To conclude, the differential genes screened by comprehensive multiple biological information databases and R language analysis are involved in the occurrence and development of osteoarthritis. The 10 key genes identified are all involved in the key link of osteoarthritis. Up-regulation of MYC and JUN can promote the occurrence of osteoarthritis, which has been verified in the RT-PCR and western blot detections. [ABSTRACT FROM AUTHOR]

Background: Although biological therapies have transformed the outlook for those with rheumatoid arthritis, there is a lack of any meaningful response in approximately 40% of patients. The role of B cells in rheumatoid arthritis pathogenesis is well recognised and is supported by the clinical efficacy of the B-cell-depleting agent rituximab (MabThera, F. Hoffman La-Roche Ltd, Basel, Switzerland). Rituximab is licensed for use in rheumatoid arthritis following failure of conventional synthetic disease-modifying antirheumatic drugs and tumour necrosis factor inhibitor therapy. However, over 50% of patients show low/absent synovial B-cell infiltration, suggesting that, in these patients, inflammation is driven by alternative cell types. This prompted us to test the hypothesis that, in synovial biopsy B-cell-poor patients, tocilizumab (RoActemra, F. Hoffman La-Roche Ltd, Basel, Switzerland) (targeting interleukin 6) is superior to rituximab (targeting CD20+/B cells). Design: The R4–RA (A Randomised, open-labelled study in anti-TNFalpha inadequate responders to investigate the mechanisms for Response, Resistance to Rituximab versus Tocilizumab in Rheumatoid Arthritis patients) trial is a 48-week Phase IV, open-label, randomised controlled trial conducted in 19 European centres that recruited patients failing on or intolerant to conventional synthetic disease-modifying antirheumatic drug therapy and at least one tumour necrosis factor inhibitor. Participants: Synovial tissue was obtained at trial entry and classified histologically as B-cell rich or B-cell poor to inform balanced stratification. Patients were randomised on a 1 : 1 basis to receive standard therapy with rituximab or tocilizumab. B-cell-poor/-rich molecular classification was also carried out. The study was powered to test the superiority of tocilizumab over rituximab at 16 weeks in the B-cell-poor population. Main outcome measures: The primary end point was defined as an improvement in the Clinical Disease Activity Index (CDAI) score of ≥ 50% from baseline. In addition, patients were considered to be non-responders if they did not reach an improvement in CDAI score of ≥ 50% and a CDAI score of

BackgroundIn patients with rheumatoid arthritis (RA) different joints were shown to share the same dominant T-cell clones, suggesting shared characteristics of the inflammatory process and indicating that strategies to selectively target the antigen receptor might be feasible. Since T- and B-lymphocytes closely interact in adaptive responses, we analysed to what extent different joints also share dominant B-cell clones.MethodsIn 11 RA patients, quantitative B-cell receptor (BCR) repertoire analysis was performed in simultaneously obtained samples from inflamed synovial tissue (ST) from distinct locations within one joint, from multiple joints, from synovial fluid (SF) and peripheral blood (PB).ResultsST biopsies from different locations in the same joint showed clear overlap in the top-25 dominant BCR clones (16.7%, SD 12.5), in the same range as the overlap between ST and SF in the same joint (8.0%, SD 8.8) and the overlap between ST-ST between different joints (9.1%, SD 8.2), but clearly higher than the overlap between ST and PB (1.7%, SD 2.4; p

• This is the first described quantification method for the simultaneous determination of cefuroxime and flucloxacillin in synovial tissue and bone using UPC2-MS/MS. • Two of the commonly administered antimicrobial agents during the one-stage or two-stage arthroplasty exchange are researched in this analysis. • A fast and simple sample preparation is applied. • The method has already successfully been applied in a clinical study, to relate target-site concentrations to serum concentrations, which ultimately can lead to more precision dosing. After a revision surgery, approximately 1–2 % of patients will develop a periprosthetic joint infection (PJI). During the revision surgery, the infected prosthesis is removed, a debridement is performed and a new or temporary spacer is placed. Additionally, patients are treated with antibiotics during and after the surgery. Adequate exposure of the administered antibiotic to the pathogen is of crucial importance during the treatment of any infection. Inadequately low concentrations are associated with an increase in antibiotic resistance, antibiotic related side effects, treatment failures and prolonged infections. While high concentrations may lead to serious adverse events and potential lasting damage. Despite the importance of optimal dosing, there is a lack of knowledge with respect to the correlation between the plasma concentrations and target site concentrations of the antibiotics. Two of the commonly administered antimicrobial agents during the arthroplasty exchange are cefuroxime and flucloxacillin. Therefore, an accurate, specific, and sensitive quantification method is required in order to assess pharmacokinetics of cefuroxime and flucloxacillin in synovial tissue and bone. The aim of this study is to develop and validate a quantification method for the measurement of cefuroxime and flucloxacillin in human synovial tissue and bone using the UPC2-MS/MS conform Food and Drug Administration guidelines. The method was found linear for both compounds in both matrices (r 2 > 0.990) from 1 µg/g to 20 µg/g, except for cefuroxime in bone, which was validated from 1 µg/g to 15 µg/g. We developed and validated a quantification method for cefuroxime and flucloxacillin in synovial tissue and bone using a simple sample preparation and a short analysis run time of 5.0 min, which has been already successfully applied in a clinical study. To our knowledge, no methods have been described earlier for the simultaneous quantification of cefuroxime and flucloxacillin in synovial tissue and bone. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by neovascularization, immune cell infiltration, and synovial hyperplasia, which leads to degradation of articular cartilage and bone, and subsequent functional disability. Dysregulated angiogenesis, synovial hypoxia, and immune cell infiltration result in a 'bioenergetic crisis' in the inflamed joint which further exacerbates synovial invasiveness. Several studies have examined this vicious cycle between metabolism, immunity, and inflammation and the role metabolites play in these interactions. To add to this complexity, the inflamed synovium is a multicellular tissue with many cellular subsets having different metabolic requirements. Metabolites can shape the inflammatory phenotype of immune cell subsets during disease and act as central signalling hubs. In the RA joint, the increased energy demand of stromal and immune cells leads to the accumulation of metabolites such as lactate, citrate, and succinate as well as adipocytokines which can regulate downstream signalling pathways. Transcription factors such as HIF1ɑ and mTOR can act as metabolic sensors to activate synovial cells and drive pro-inflammatory effector function, thus perpetuating chronic inflammation further. These metabolic intermediates may be potential therapeutic targets and so understanding the complex interplay between metabolites and synovial cells in RA may allow for identification of novel therapeutic strategies but also may provide significant insight into the underlying mechanisms of disease pathogenesis. The adverse microenvironment of the RA inflamed joint forces cells to switch their metabolic pathways in order to sustain their pathogenic activated status. Metabolites act as central hubs influencing multiple cellular functions and signaling pathways that further drive inflammation. [ABSTRACT FROM AUTHOR]

Objective We aimed to investigate the mechanisms underlying the effects of Illicium henryi injection on rheumatoid arthritis (RA). Methods Male DBA/1 mice were randomly divided into: (i) the normal group, (ii) the model group, (iii) the leflunomide group, and (iv) the Illicium henryi injection group (n = 8 mice per group). A collagen-induced arthritis (CIA) mouse model was established by multipoint injection of bovine type II collagen emulsifier in the tail and back. Mice in the normal group and model group were given normal saline. Mice in the leflunomide group were given leflunomide (3 mg/kg) by gavage. Mice in the Illicium henryi injection group were intraperitoneally injected with Illicium henryi injection (0. 3 mL/kg) once a day for 28 consecutive days. Joint inflammatory scores were recorded every 7 days after the intervention to measure the degree of joint swelling. After 28: days, HE staining was used to observe the histopathological morphology and record the histopathological score of the ankle joint. Safranin 0 staining was used to observe the degree of damage to articular cartilage and score the loss of staining. The protein expression levels of JAK2, p-JAK2, STAT6, and p- JAK6 in synovial tissues were determined by Western blot. Results Compared with the model group, the arthritis index score was lower in the Illicium henryi injection group (P <0. 05), the foot joint was thinner (P <0. 05, P <0. 01), the pathological changes of the joint were less severe, and the expression and phosphorylation of JAK2 and STAT6 in synovium were lower (P <0. 05,P < 0.01). Conclusion Illicium henryi injection has anti-inflammatory and immunomodulatory effects on CIA mice through inhibiting the phosphorylation and expression of JAK2 and STAT6 and regulating the JAK/STAT signaling pathway. [ABSTRACT FROM AUTHOR]