Abstract:NLRP3 inflammasome-dependent pyroptosis has been implicated in liver fibrosis progression. However, the definite intrahepatic cell types that undergo pyroptosis and the underlying mechanism as well as the clinical importance remain unclear. Here, augmented levels of pyroptosis-related indicators GSDMD, IL-1β, and IL-18 were verified in both liver fibrosis patients and CCl4-induced fibrotic mouse model. Confocal imaging of NLRP3 with albumin, F4/80 or α-SMA revealed that enhanced NLRP3 was mainly localized to k… Show more
“…As a result, the transcription factor NF-kB is activated, which leads to the release of pro-inflammatory cytokines (IL-1β, IL-6 and TNFα) [58]. Moreover, the activation of S100A8/S100A9 in monocytes may promote ROS to enhance the production of pro-inflammatory cytokines and the expression of NLRP3 inflammasome [59,60]. An increased level of S100A8 has been revealed in the patients with arthritis and IBD, indicating that it could play a role in AS and UC by affecting the aforementioned pathways and cytokines.…”
Associations between ulcerative colitis (UC) and ankylosing spondylitis (AS) have been observed in multiple studies, but the common etiology of UC and AS remain unknown. Thus, the current research was conducted to investigate the shared genes and relevant mechanisms in UC and AS. GSE87466 and GSE25101 datasets were used to identify DEGs involved in UC and AS, respectively. The clusterProfiler R package was utilized to detect the biological processes of DEGs in UC and AS. The performance of common DEGs in distinguishing UC or AS samples from control ones were evaluated by ROC curves. The miRWalk, Cistrome and TransmiR database were utilized to construct the network of TF-miRNA-diagnostic biomarker. GSEA method and CTD database were used to investigate the common KEGG pathways shared by UC and AS. In addition, CTD database was also used to detect the interaction score between diagnostic biomarkers and diseases associated with UC or AS. Moreover, prospective diagnostic biomarker-targeting drugs were identified using the DGIdb database. A total of 20 common DEGs were obtained by analyzing data in GSE97466 and GSE25101 datasets. ROC curves revealed that GMFG, GNG11, CLEC4D, CMTM2, VAMP5, S100A8, S100A12 and DGKQ may serve as diagnostic biomarkers for the individuals with AS and UC. A network of TF-miRNA-diagnostic biomarker, composed of 212 nodes and 721 edges, was constructed and visualized by Cytoscape software. Toll-like receptor signaling pathway, antigen processing and presentation, allograft rejection, viral myocarditis, pathways in cancer, graft versus host disease and natural killer cell mediated cytotoxicity were identified as common pathways in UC and AS. For the first time, our study identified 8 common key genes and 7 common pathways in UC and AS. These findings may help to clarify the relationship between UC and AS, and provide guidance in the diagnosis and treatment of UC and AS patients.
“…As a result, the transcription factor NF-kB is activated, which leads to the release of pro-inflammatory cytokines (IL-1β, IL-6 and TNFα) [58]. Moreover, the activation of S100A8/S100A9 in monocytes may promote ROS to enhance the production of pro-inflammatory cytokines and the expression of NLRP3 inflammasome [59,60]. An increased level of S100A8 has been revealed in the patients with arthritis and IBD, indicating that it could play a role in AS and UC by affecting the aforementioned pathways and cytokines.…”
Associations between ulcerative colitis (UC) and ankylosing spondylitis (AS) have been observed in multiple studies, but the common etiology of UC and AS remain unknown. Thus, the current research was conducted to investigate the shared genes and relevant mechanisms in UC and AS. GSE87466 and GSE25101 datasets were used to identify DEGs involved in UC and AS, respectively. The clusterProfiler R package was utilized to detect the biological processes of DEGs in UC and AS. The performance of common DEGs in distinguishing UC or AS samples from control ones were evaluated by ROC curves. The miRWalk, Cistrome and TransmiR database were utilized to construct the network of TF-miRNA-diagnostic biomarker. GSEA method and CTD database were used to investigate the common KEGG pathways shared by UC and AS. In addition, CTD database was also used to detect the interaction score between diagnostic biomarkers and diseases associated with UC or AS. Moreover, prospective diagnostic biomarker-targeting drugs were identified using the DGIdb database. A total of 20 common DEGs were obtained by analyzing data in GSE97466 and GSE25101 datasets. ROC curves revealed that GMFG, GNG11, CLEC4D, CMTM2, VAMP5, S100A8, S100A12 and DGKQ may serve as diagnostic biomarkers for the individuals with AS and UC. A network of TF-miRNA-diagnostic biomarker, composed of 212 nodes and 721 edges, was constructed and visualized by Cytoscape software. Toll-like receptor signaling pathway, antigen processing and presentation, allograft rejection, viral myocarditis, pathways in cancer, graft versus host disease and natural killer cell mediated cytotoxicity were identified as common pathways in UC and AS. For the first time, our study identified 8 common key genes and 7 common pathways in UC and AS. These findings may help to clarify the relationship between UC and AS, and provide guidance in the diagnosis and treatment of UC and AS patients.
“…5‐aza‐2′‐deoxycytidine (Decitabine) at 10 μM (purchased from Sigma, St. Louis, USA) was used to restrain whole genome DNA methylation 24 . The proteins function of PRKCB2 and TLR4 (toll‐like receptors 4) were respectively restrained by 10 μM enzastaurin 25 (PRKCB inhibitor LY317615, purchased from Selleck, USA) and 10 μM resatorvid (TLR4 inhibitor TAK‐242, purchased from ApexBio, USA) 26 …”
Section: Methodsmentioning
confidence: 99%
“…24 The proteins function of PRKCB2 and TLR4 (toll-like receptors 4) were respectively restrained by 10 μM enzastaurin 25 (PRKCB inhibitor LY317615, purchased from Selleck, USA) and 10 μM resatorvid (TLR4 inhibitor TAK-242, purchased from ApexBio, USA). 26…”
Nickel oxide nanoparticles (Nano NiO) have been shown to cause pulmonary fibrosis; But, the underlying epigenetic mechanisms remain poorly understood. In this study, we aimed to investigate the role of lncRNA AP000487.1 in regulating PRKCB DNA methylation and the Toll‐like receptor 4 (TLR4)/ Myeloid differentiation primary response 88 (MyD88)/ Nuclear factor kappa‐B (NF‐κB) pathway in Nano NiO‐induced collagen formation. We found that lncRNA AP000487.1 was able to bind to the promoter region of the PRKCB gene by Chromosomal RNA pull‐down experiments (Ch‐RNA pull‐down). Moreover, Nano NiO exposure led to down‐regulation of lncRNA AP000487.1 expression and PRKCB DNA methylation, resulting in up‐regulation of PRKCB expression, activation of the TLR4/MyD88/NF‐κB pathway, and increased collagen formation in BEAS‐2B cells. Conversely, overexpression of lncRNA AP000487.1 restored PRKCB expression, reduced its hypomethylation and attenuated TLR4/MyD88/NF‐κB pathway activation and collagen formation. Furthermore, treatment with the DNA methylation inhibitor, decitabine, alleviated Nano NiO‐induced PRKCB2 expression, TLR4/MyD88/NF‐κB pathway activation, and collagen formation. Additionally, using PRKCB2 overexpression plasmid, PRKCB2 siRNA, and PRKCB2 protein inhibitor LY317615 influenced NF‐κB pathway activity and collagen formation. Finally, TLR4 inhibitor (TAK‐242) restrained Nano NiO‐induced MyD88/NF‐κB pathway activation and excessive collagen formation. In summary, we demonstrated that the down‐regulated lncRNA AP000487.1 could cause PRKCB hypomethylation and increased expression, resulting in NF‐κB pathway activation and collagen formation in Nano NiO‐induced BEAS‐2B cells. This is the first study to reveal the role of lncRNA AP000487.1 in regulating collagen formation in Nano NiO‐exposed BEAS‐2B cells. Our study identified that lncRNA AP000487.1/PRKCB hypomethylation/NF‐κB pathway was a regulatory axis of BEAS‐2B cells collagen excessive formation. Our findings indicate that lncRNA AP000487.1 and PRKCB DNA methylation may function as biomarkers or potential targets in response to Nano NiO exposure.
“… 98 , 99 Among them, S100A8 (Fold change = 56.23) is an atypical inflammatory cytokine that is most markedly elevated, which could also promote the M1 polarization of macrophage and the chronic inflammatory processes by activating the TLR4/NF-κB signal pathway according to published article. 100 The glucocorticoid-induced injury of bone microvascular endothelial vessels and subsequently enhanced level of BMECs-derived cytokines may act as a prerequisite for the macrophage-induced chronic inflammation in GIONFH. Figure 5 The heatmap about differentially expressed proteins between extracellular vesicles released by bone marrow endothelial cells (BMECs) in the glucocorticoid-induced group and the Control group.…”
Section: Mechanism Underlying the Macrophage Polarization Imbalance I...mentioning
Glucocorticoid-induced osteonecrosis of the femoral head (GIONFH) is a disabling disease with high mortality in China but the detailed molecular and cellular mechanisms remain to be investigated. Macrophages are considered the key cells in osteoimmunology, and the cross-talk between bone macrophages and other cells in the microenvironment is involved in maintaining bone homeostasis. M1 polarized macrophages launch a chronic inflammatory response and secrete a broad spectrum of cytokines (eg, TNF-α, IL-6 and IL-1β) and chemokines to initiate a chronic inflammatory state in GIONFH. M2 macrophage is the alternatively activated anti-inflammatory type distributed mainly in the perivascular area of the necrotic femoral head. In the development of GIONFH, injured bone vascular endothelial cells and necrotic bone activate the TLR4/NF-κB signal pathway, promote dimerization of PKM2 and subsequently enhance the production of HIF-1, inducing metabolic transformation of macrophage to the M1 phenotype. Considering these findings, putative interventions by local chemokine regulation to correct the imbalance between M1/M2 polarized macrophages by switching macrophages to an M2 phenotype, or inhibiting the adoption of an M1 phenotype appear to be plausible regimens for preventing or intervening GIONFH in the early stage. However, these results were mainly obtained by in vitro tissue or experimental animal model. Further studies to completely elucidate the alterations of the M1/M2 macrophage polarization and functions of macrophages in glucocorticoid-induced osteonecrosis of the femoral head are imperative.
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