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Objective: This study aimed to assess the role of synovial fluid (SF) CD4+T, CD19+B, follicular helper cells (Tfh), and cytokines in the pathogenesis of rheumatoid arthritis (RA). Methods: This study enrolled 16 patients with RA and 8 patients with osteoarthritis (OA). The frequencies of the SF CD4+ T, CD19+ B, Tfh cells, and Tfh subsets were assessed using flow cytometry. The medical condition in patients with RA was evaluated using The Disease Activity Score 28 (DAS28), the Clinical Disease Activity Index (CDAI), and the Simplified Disease Activity Index (SDAI). Levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), anti-cyclic citrullinated peptide (anti-CCP), and rheumatoid factor (RF) were measured. The cytokines IL-4, IL-13, IL-21, and BLyS were measured by ELISA test. Results: The percentages of SF CD4+T, CD19+B, and PD-1+CXCR5+ Tfh in RA patients were higher than those in OA patients. And the Tfh2 was the main subset among Tfh subsets. In addition, levels of IL-21 and BLyS were higher in patients with RA compared to patients with OA. Furthermore, the treatment of TNF-α inhibitors may be associated with decreased levels of SF Tfh. Conclusions: Elevated SF Tfh, B cell, and cytokines expression profiles were observed in RA patients. Tfh2 was the major subset of the Tfh, and IL-21 and BLyS were significantly enhanced. Additionally, TNF-α inhibitors reduced Tfh in SF. Therefore, Tfh, B, and Tfh2 cells could play a significant role in the progression of RA. Key Points •Tfh cells in the synovial fluid are significantly higher in RA patients and are dominated by the Tfh2 subpopulation. •Synovial fluid Tfh cells decrease in RA patients after anti-TNF-α treatment. [ABSTRACT FROM AUTHOR]

Background: Zinc oxide nanoparticle (nZnO) and chemicals with different mode of action (MOA, i.e., narcotic and reactive) were frequently detected in the Yangtze River. Organisms are typically exposed to mixtures of nZnO and other chemicals rather than individual nZnO. Toxicity of nZnO is caused by the dissolution of Zn2+, which has been proved in the field of single toxicity. However, it is still unclear whether the released Zn2+ plays a critical role in the nZnO toxicity of nZnO–chemicals mixtures. In the present study, the binary mixture toxicity of nZnO/Zn2+ and chemicals with different MOA was investigated in acute (15 min) and chronic (12 h) toxicity test upon Vibrio fischeri (V. fischeri). The joint effects of nZnO and tested chemicals were explored. Moreover, two classic models, concentration addition (CA) and independent action (IA) were applied to predict the toxicity of mixtures. Results: The difference of toxicity unit (TU) values between the mixtures of Zn2+–chemicals with those of nZnO–chemicals was not significant (P > 0.05), not only in acute toxicity test but also in chronic toxicity test. The antagonistic or additive effects for nZnO-chemicals can be observed in most mixtures, with the TU values ranging from 0.75 to 1.77 and 0.47 to 2.45 in acute toxicity test and chronic test, respectively. We also observed that the prediction accuracy of CA and IA models was not very well in the mixtures where the difference between the toxicity ratios of the components was small (less than about 10), with the mean absolute percentage error (MAPE) values ranging from 0.14 to 0.67 for CA model and 0.17–0.51 for IA model, respectively. Conclusion: We found that the dissolved Zn2+ mainly accounted for the nZnO toxicity in the mixtures of nZnO–chemicals, and the joint effects of these mixtures were mostly antagonism and additivity. CA and IA models were unsuitable for predicting the mixture toxicity of nZnO–chemicals at their equitoxic ratios. [ABSTRACT FROM AUTHOR]

The present study characterized the nutrients availability of three rare earth tailings deserted in different time stages in Southern Jiangxi of China, and revealed the influence of the soil nutrient properties on fungi composition and diversity by using an internal transcribed spacer (ITS) rRNA sequence approach. Three tailings (RS1, RS2 and RS3) and one reference soil (RS4) were sampled. Results showed that a higher levels of AN and TOC occurred in RS1 and RS4, whereas higher contents of SO2-4, TN, NO-3-N, NH+4-N and rare earth elements (REEs) existed in RS2 and RS3, suggesting a high environmental heterogeneity in the different tailings. Metagenomic analysis showed that RS1~RS4 harbored 355, 564, 366 and 507 operational taxonomic units (OTUs), respectively. Alpha diversity analysis showed that RS4, a control sample, had the highest Shannon diversity, whereas RS3, a newly formed tailings, exhibited the lowest Chao1 richness.Among the monitored environmental variables, AN and SO2-4 were the most important factors affecting the overall fungal community composition and the relative abundances of specific lineages. Additionally, genus Penicillium prevailed in RS1and RS4 while genus Aspergillus dominated in RS2 and RS3, indicating that the nitrification maybe conduct by different fungal genus in different tailings. Together, these results suggest that lower fungal community composition and diversity as well as the alteration in fungi-dominated heterotrophic nitrification may be due to the deteriorative nutrient in rare earth tailings, especially increasing level of sulfate and decreasing level of available nitrogen. [ABSTRACT FROM AUTHOR]

Objective: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous. The aim of this study is to find the key genes in peripheral blood mononuclear cells (PBMCs) of SLE patients and to provide a new direction for the diagnosis and treatment of lupus.GSE121239, GSE50772, GSE81622, and GSE144390 mRNA expression profiles were obtained from the website of Gene Expression Omnibus (GEO), and differential expressed genes (DEGs) analysis was performed by R. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate signaling pathways for the DEGs. Real-time qPCR (RT-qPCR) was used to verify the key gene EPSTI1 in PBMCs of SLE patients. Finally, the correlation analysis and ROC curve analysis of EPSTI1 for SLE were performed.A total of 12 upregulated DEGs were identified, including MMP8, MX1, IFI44, EPSTI1, OAS1, OAS3, HERC5, IFIT1, RSAD2, USP18, IFI44L, and IFI27. GO and KEGG pathway enrichment analysis showed that those DEGs were mainly concentrated in the response to virus and IFN signaling pathways. Real-time qPCR (RT-qPCR) revealed that EPSTI1 was increased in PBMCs of SLE. EPSTI1 was positively correlated with SLEDAI score in SLE patients. Besides, EPSTI1 was positively correlated with T cell activation- or differentiation-associated genes (BCL6 and RORC). Furthermore, ROC analyses proved EPSTI1 may have diagnostic value for SLE.Together, EPSTI1 was found to be a potential biomarker for SLE, closely related to T cell immune imbalance.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Methods: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous. The aim of this study is to find the key genes in peripheral blood mononuclear cells (PBMCs) of SLE patients and to provide a new direction for the diagnosis and treatment of lupus.GSE121239, GSE50772, GSE81622, and GSE144390 mRNA expression profiles were obtained from the website of Gene Expression Omnibus (GEO), and differential expressed genes (DEGs) analysis was performed by R. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate signaling pathways for the DEGs. Real-time qPCR (RT-qPCR) was used to verify the key gene EPSTI1 in PBMCs of SLE patients. Finally, the correlation analysis and ROC curve analysis of EPSTI1 for SLE were performed.A total of 12 upregulated DEGs were identified, including MMP8, MX1, IFI44, EPSTI1, OAS1, OAS3, HERC5, IFIT1, RSAD2, USP18, IFI44L, and IFI27. GO and KEGG pathway enrichment analysis showed that those DEGs were mainly concentrated in the response to virus and IFN signaling pathways. Real-time qPCR (RT-qPCR) revealed that EPSTI1 was increased in PBMCs of SLE. EPSTI1 was positively correlated with SLEDAI score in SLE patients. Besides, EPSTI1 was positively correlated with T cell activation- or differentiation-associated genes (BCL6 and RORC). Furthermore, ROC analyses proved EPSTI1 may have diagnostic value for SLE.Together, EPSTI1 was found to be a potential biomarker for SLE, closely related to T cell immune imbalance.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Results: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous. The aim of this study is to find the key genes in peripheral blood mononuclear cells (PBMCs) of SLE patients and to provide a new direction for the diagnosis and treatment of lupus.GSE121239, GSE50772, GSE81622, and GSE144390 mRNA expression profiles were obtained from the website of Gene Expression Omnibus (GEO), and differential expressed genes (DEGs) analysis was performed by R. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate signaling pathways for the DEGs. Real-time qPCR (RT-qPCR) was used to verify the key gene EPSTI1 in PBMCs of SLE patients. Finally, the correlation analysis and ROC curve analysis of EPSTI1 for SLE were performed.A total of 12 upregulated DEGs were identified, including MMP8, MX1, IFI44, EPSTI1, OAS1, OAS3, HERC5, IFIT1, RSAD2, USP18, IFI44L, and IFI27. GO and KEGG pathway enrichment analysis showed that those DEGs were mainly concentrated in the response to virus and IFN signaling pathways. Real-time qPCR (RT-qPCR) revealed that EPSTI1 was increased in PBMCs of SLE. EPSTI1 was positively correlated with SLEDAI score in SLE patients. Besides, EPSTI1 was positively correlated with T cell activation- or differentiation-associated genes (BCL6 and RORC). Furthermore, ROC analyses proved EPSTI1 may have diagnostic value for SLE.Together, EPSTI1 was found to be a potential biomarker for SLE, closely related to T cell immune imbalance.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Conclusion: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous. The aim of this study is to find the key genes in peripheral blood mononuclear cells (PBMCs) of SLE patients and to provide a new direction for the diagnosis and treatment of lupus.GSE121239, GSE50772, GSE81622, and GSE144390 mRNA expression profiles were obtained from the website of Gene Expression Omnibus (GEO), and differential expressed genes (DEGs) analysis was performed by R. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate signaling pathways for the DEGs. Real-time qPCR (RT-qPCR) was used to verify the key gene EPSTI1 in PBMCs of SLE patients. Finally, the correlation analysis and ROC curve analysis of EPSTI1 for SLE were performed.A total of 12 upregulated DEGs were identified, including MMP8, MX1, IFI44, EPSTI1, OAS1, OAS3, HERC5, IFIT1, RSAD2, USP18, IFI44L, and IFI27. GO and KEGG pathway enrichment analysis showed that those DEGs were mainly concentrated in the response to virus and IFN signaling pathways. Real-time qPCR (RT-qPCR) revealed that EPSTI1 was increased in PBMCs of SLE. EPSTI1 was positively correlated with SLEDAI score in SLE patients. Besides, EPSTI1 was positively correlated with T cell activation- or differentiation-associated genes (BCL6 and RORC). Furthermore, ROC analyses proved EPSTI1 may have diagnostic value for SLE.Together, EPSTI1 was found to be a potential biomarker for SLE, closely related to T cell immune imbalance.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE.Key Points• EPSTI1 expression was significantly increased in PBMCs of SLE patients.• EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients.• EPSTI1 might have a good diagnostic value for SLE. [ABSTRACT FROM AUTHOR]