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This study investigated the mechanisms driving the induction and sustained presence of neutrophil extracellular traps (NETs) in the synovial microenvironment of rheumatoid arthritis (RA). Synovial tissue and fluid samples were collected from patients with RA and osteoarthritis (OA), and NET levels and cytokine concentrations were measured using a cytometric bead array and enzyme-linked immunosorbent assay (ELISA). The ability of interleukin-33 (IL-33) to induce NET formation was evaluated using quantitative assays, immunofluorescence staining, live-cell imaging, and electron microscopy. Coincubation experiments of NETs with fibroblast-like synovial cells (FLSs) were conducted, and a modified Transwell migration assay was designed to assess neutrophil migration. The role of IL-33 and NETs in RA progression was further investigated using a collagen antibody-induced arthritis (CAIA) mouse model. The results revealed an increase in NETs and IL-33 levels in the synovial fluid of RA patients, with a significant positive correlation between them. NET formation assays confirmed that IL-33 activates neutrophils to produce NETs and that neutrophils from RA patients exhibit increased responsiveness to IL-33 stimulation. Both in vitro and in vivo evidence has demonstrated that NETs stimulate FLSs to secrete IL-33 and the chemokine CXCL8 via Toll-like receptor 9, promoting further neutrophil recruitment and increasing NET production within the RA synovium. This study reveals a novel positive feedback loop involving NETs and FLSs that is mediated by IL-33 that increases NET accumulation in RA. Targeting IL-33 or NET formation and amplification may offer new therapeutic strategies for managing RA. IL-33 drives neutrophil extracellular traps in rheumatoid arthritis Rheumatoid arthritis is a disease where the body’s defense system wrongly attacks the joints, leading to swelling and pain. This research explores the role of neutrophil extracellular traps in RA. NETs are net-like structures released by a type of white blood cell to catch harmful germs but in RA, NETs can harm the body’s own tissues. The team collected samples from 120 RA patients, comparing them with samples from osteoarthritis patients and healthy people. They studied how certain proteins, particularly IL-33, affect NET formation in RA patients’ joints. They found that IL-33 greatly increases NET production, suggesting a cycle where IL-33 and NETs continue the inflammation in RA. This highlights IL-33’s potential as a target for RA treatment, providing new understanding of this disabling disease. Future treatments might aim to break this cycle to ease RA symptoms. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Background. The aim of the study was to investigate the landscape of B-cell-related gene expression profiling in rheumatoid arthritis (RA) synovium and explore the biological and clinical significance of these genes in RA. Methods. Expression profiling of synovial biopsies from subjects with 152 RA patients, 22 osteoarthritis (OA) patients, and 28 healthy controls was downloaded from the Gene Expression Omnibus database. Single-sample gene set enrichment analysis (ssGSEA) was performed to evaluate the abundance of infiltrated immune cells, and the results were validated using immunohistochemical staining. GSEA was employed to decipher differences in B-cell-related biological pathways. B-cell-related differential expression genes (BRDEGs) were screened, and BRDEGs-based model was developed by machine learning algorithms and evaluated by an external validation set and clinical RA cohort, then biological functions were further analyzed. Results. High levels of immune cell infiltration and B-cell-related pathway activation were revealed in RA synovium. BRDEGs were screened, and three key molecular markers consisting of FAS, GPR183, and TFRC were identified. The diagnosis model was established, and these gene markers have good discriminative ability for RA. Molecular pathological evaluation confirmed RA patients with high-risk scores presented higher levels of B-cell activation and RA characteristics. In addition, a competitive endogenous RNA network was established to elucidate the molecular mechanisms of the posttranscriptional network. Conclusions. We described the B-cell-related molecular landscape of RA synovium and constructed a molecular diagnostic model in RA. The three genes FAS, GPR183, and TFRC may be potential targets for clinical diagnosis and immunoregulatory therapy of RA.

In the immune system, many tolerance checkpoints exist to prevent self-antigens from stimulating the growth of self-reactive T and B lymphocytes. [...]thymic selection ensures that the repertoire of available T cells is both MHC-restricted and self-tolerant. [...]due to the heterogeneity and plasticity of Th cells, various over-activated T cell subpopulations like iTh1 (inflammatory Th1), iTh2, iTh17, etc. can express different cell phenotypes and play pathogenic roles in autoimmune diseases, which may be the potential cause of poor therapeutic outcomes for certain patients (8,9). [...]exploring the exact reasons why such T cells become more pathogenic and targeting pathogenic T cells rather than all T cells, maybe more helpful in both treating and preventing autoimmune diseases from progressing. T cells of different lineages have been implicated in the pathogenesis of IIM.Anang et al.had shown the presence of highly expanded TCRβ clones in muscle tissues and peripheral blood of IIM patients. [...]increased clonal expansion and decreased diversity of the TCRβ repertoire in muscle tissue correlated with increased disease activity, which supported a role for specific clonal T cell responses in muscle tissue in the pathogenesis of the IIM. The maintenance of Th17/Treg balance could be considered as a therapeutic strategy for the treatment of RA and PMOP. Because the researchers have the different academic backgrounds, each of the above studies can be considered as an independent research.

Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease with unknown etiology. CCN1, an extracellular matrix-associated protein, is associated with carcinoma, inflammation, liver fibrosis, and even autoimmune diseases. However, the role that CCN1 plays in AIH has remained undetermined. In this study, expression of CCN1 in liver was detected by real-time PCR, western blot and immunohistochemistry (IHC). CCN1 level in serum was detected by ELISA. Diagnostic value of CCN1 was determined by receiver operating characteristic (ROC) curve analysis. CCN1 conditional knockout (CCN1 fl/fl Cre + ) mice were generated by mating CCN1 fl/fl C57BL/6J and CAG-Cre-ERT C57BL/6J mice. Autoimmune hepatitis mice model was induced by concanavalin A (ConA). IKKα/β, IκBα, NF-κB p65 and Akt phosphorylation were determined by western blot. NF-κB p65 nuclear translocation was examined by immunofluorescence. Here, we found that CCN1 was over-expressed in hepatocytes of AIH patients. CCN1 level also increased in serum of AIH patients compared to healthy controls (HC). ROC curve analysis results showed that serum CCN1 was able to distinguish AIH patients from HD. In ConA induced hepatitis mice model, CCN1 conditional knockout (CCN1 fl/fl Cre + ) attenuated inflammation by reducing ALT/AST level and IL-6 expression. In vitro , CCN1 treatment dramatically induced IL-6 production in LO2 cells. Moreover, the production of IL-6 was attenuated by CCN1 knockdown. Furthermore, we showed that CCN1 could activate IL-6 production via the PI3K/Akt/NF-κB signaling pathway by binding to α6β1 receptor. In summary, our results reveal a novel role of CCN1 in promoting inflammation by upregulation of IL-6 production in AIH. Our study also suggests that targeting of CCN1 may represent a novel strategy in AIH treatment.

Background Rheumatoid arthritis (RA) remains in urgent need of more effective biomarkers to improve diagnostic accuracy. Methods In this study, we conducted a comprehensive analysis of 2,863 blood samples obtained from seven cohorts comprising RA, osteoarthritis (OA), and healthy control (HC) subjects, recruited across five medical centers spanning three geographically diverse regions. Candidate biomarkers were first identified through untargeted metabolomic profiling, and subsequently validated using targeted approaches. Metabolite-based classification models were then developed employing a range of machine learning algorithms. Results Six metabolites were ultimately identified as promising diagnostic biomarkers, including imidazoleacetic acid, ergothioneine, N-acetyl-L-methionine, 2-keto-3-deoxy-D-gluconic acid, 1-methylnicotinamide and dehydroepiandrosterone sulfate. Based on these metabolites, we constructed classification models to differentiate RA from both HC and OA groups, and evaluated their performance across multiple independent validation cohorts. In three geographically distinct cohorts, RA vs. HC classifiers demonstrated robust discriminatory power, with an area under the receiver operating characteristic curve (AUC) ranging from 0.8375 to 0.9280, while RA vs. OA classifiers achieved moderate to good accuracy (AUC range: 0.7340–0.8181). Importantly, analysis of the seronegative RA subgroup indicated that the classifier’s performance was independent of serological status. Furthermore, validations conducted across different sample types and analytical platforms confirmed the reproducibility and stability of the models. Conclusions Taken together, these findings highlight the utility of metabolomics as a complementary approach for improving RA diagnosis and establish a broadly applicable framework for the development of metabolite-based classifiers across diverse and clinically heterogeneous disease contexts.

Major symbiotic organisms have evolved to establish beneficial relationships with hosts. However, understanding the interactions between symbionts and insect hosts, particularly for their roles in defense against pathogens, is still limited. In a previous study, we proposed that the fungus Metarhizium anisopliae can infect the brown planthopper Nilaparvata lugens , a harmful pest for rice crops. To expand on this, we investigated changes in N. lugens ’ intestinal commensal community after M. anisopliae infection and identified key gut microbiotas involved. Our results showed significant alterations in gut microbiota abundance and composition at different time points following infection with M. anisopliae . Notably, certain symbionts, like Acinetobacter baumannii , exhibited significant variations in response to the fungal infection. The decrease in these symbionts had a considerable impact on the insect host’s survival. Interestingly, reintroducing A. baumannii enhanced the host’s resistance to M. anisopliae , emphasizing its role in pathogen defense. Additionally, A. baumannii stimulated host immune responses, as evidenced by increased expression of immune genes after reintroduction. Overall, our findings highlight the significance of preserving a stable gut microbial community for the survival of insects. In specific conditions, the symbiotic microorganism A. baumannii can enhance the host’s ability to resist entomopathogenic pathogens through immune regulation. This study reveals that the symbiotic microorganism A. baumannii can enhance the insect host’s ability to resist the infection of entomopathogenic fungus Metarhizium anisopliae under specific conditions.

Th17 cells are involved in rheumatoid arthritis (RA) pathogenesis. Our previous studies have revealed that transcription factor Yin Yang 1 (YY1) plays an important role in the pathogenic mechanisms of RA. However, whether YY1 has any role in Th17 cell pathogenicity and what molecular regulatory mechanism is involved remain poorly understood. Here, we found the proportion of pathogenic Th17 (pTh17) cells was significantly higher in RA than in control individuals and showed a potential relationship with YY1 expression. In addition, we also observed YY1 expression was increased in pTh17, and the pTh17 differentiation was hampered by YY1 knockdown. Consistently, knockdown of YY1 decreased the proportion of pTh17 cells and attenuated joint inflammation in collagen-induced arthritis mice. Mechanistically, YY1 could regulate the pathogenicity of Th17 cells through binding to the promoter region of transcription factor T-bet and interacting with T-bet protein. This function of YY1 for promoting pTh17 differentiation was specific to Th17 cells and not to Th1 cells. Moreover, we found miR-124-3p negatively correlated with YY1 in RA patients, and it could bind to 3'-UTR regions of YY1 to inhibit the posttranscriptional translation of YY1. Altogether, these findings indicate YY1 regulation by miR-124-3p could specifically promote Th17 cell pathogenicity in part through interaction with T-bet, and these findings present promising therapeutic targets in RA.

Nilaparvata lugens is one of the major pests of rice and results in substantial yield loss every year. Our previous study found that the entomopathogenic fungus Metarhizium anisopliae showed effective potential for controlling this pest. However, the mechanisms underlying M. anisopliae infection of N. lugens are not well known. In the present study, we further examined the transcriptome of N. lugens at 4 h, 8 h, 16 h, and 24 h after M. anisopliae infection by Illumina deep sequencing. In total, 174.17 Gb of data was collected after sequencing, from which 23,398 unigenes were annotated by various databases, including 3694 newly annotated genes. The results showed that there were 246 vs 75, 275 vs 586, 378 vs 1055, and 638 vs 182 up- and downregulated differentially expressed genes (DEGs) at 4 h, 8 h, 16 h, and 24 h after M. anisopliae infection, respectively. The biological functions and associated metabolic processes of these genes were determined with the Clusters of Orthologous Groups (COG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The DEGs data were verified using RT-qPCR. These results indicated that the DEGs during the initial fungal infection appropriately reflected the time course of the response to the fungal infection. Taken together, the results of this study provide new insights into the molecular mechanisms underlying the insect host response to fungal infection, especially during the initial stage of infection, and may improve the potential control strategies for N. lugens.

Background Sequencing projects using a clone-by-clone approach require the availability of a robust physical map. The SNaPshot technology, based on pair-wise comparisons of restriction fragments sizes, has been used recently to build the first physical map of a wheat chromosome and to complete the maize physical map. However, restriction fragments sizes shared randomly between two non-overlapping BACs often lead to chimerical contigs and mis-assembled BACs in such large and repetitive genomes. Whole Genome Profiling (WGP™) was developed recently as a new sequence-based physical mapping technology and has the potential to limit this problem. Results A subset of the wheat 3B chromosome BAC library covering 230 Mb was used to establish a WGP physical map and to compare it to a map obtained with the SNaPshot technology. We first adapted the WGP-based assembly methodology to cope with the complexity of the wheat genome. Then, the results showed that the WGP map covers the same length than the SNaPshot map but with 30% less contigs and, more importantly with 3.5 times less mis-assembled BACs. Finally, we evaluated the benefit of integrating WGP tags in different sequence assemblies obtained after Roche/454 sequencing of BAC pools. We showed that while WGP tag integration improves assemblies performed with unpaired reads and with paired-end reads at low coverage, it does not significantly improve sequence assemblies performed at high coverage (25x) with paired-end reads. Conclusions Our results demonstrate that, with a suitable assembly methodology, WGP builds more robust physical maps than the SNaPshot technology in wheat and that WGP can be adapted to any genome. Moreover, WGP tag integration in sequence assemblies improves low quality assembly. However, to achieve a high quality draft sequence assembly, a sequencing depth of 25x paired-end reads is required, at which point WGP tag integration does not provide additional scaffolding value. Finally, we suggest that WGP tags can support the efficient sequencing of BAC pools by enabling reliable assignment of sequence scaffolds to their BAC of origin, a feature that is of great interest when using BAC pooling strategies to reduce the cost of sequencing large genomes.

Comparative genetic analysis has shown that different plant species often share orthologous genes for very similar functions, especially for cereal crops. In this study, we focused on analyzing the utility of EST-SSR markers among monocots in silico and by experiment. Based on 423,611 wheat ESTs, 101,299 were found to express commonly in rice, maize and barley ESTs, which accounted for 23.94% of wheat EST data. 1707 SSR-containing ESTs (SSR-ESTs) were mined from the 101,299 homologous ESTs, which accounted for 8.8% of all the 19,434 wheat EST-SSRs. It showed that the number of homologous SSR-ESTs much less than the homologous ESTs among grasses. The number of conserved ESTs and SSR-ESTs were inversely proportional to the evolutionary distance among species. Although these SSR-ESTs were in high similarity, the number of conserved SSRs between wheat and the other three crops decreased with the increased aligning regions, and only 13 types of SSR motifs in 21 ESTs were obtained by aligning sequences over a stretch of more than 40 bp. The variation at a microsatellite came from not only the differences in the numbers of repeat units and its location shift, but also base mutations flanking microsatellite repeats. From the 428 uni-SSR-ESTs universally in the four cereals, 243 primers were designed and tested in two genotypes of each species. 154 (63.4%) primers produced clear amplicons across the four species, which showed a high efficient transferability of wheat EST-SSR markers to the other three cereal crops.