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Varicella-zoster virus (VZV) infection downregulates surface major histocompatibility complex class I (MHC-I) expression and retains MHC-I in the Golgi complex of infected cells. However, the underlying mechanism is not fully understood. The VZV IE4 protein is a multifunctional protein that is essential for VZV infection. In this study, the human leucocyte antigen C (HLA-C) protein was identified as a novel cellular factor associated with IE4. Ectopically expressed IE4 co-localizes with HLA-C, sequesters HLA-C to the Golgi complex and downregulates cellular surface MHC-I. VZV, with a mutated Golgi localization signal in IE4, denoted as mutated IE4 (mIE4) VZV, was constructed. In mIE4 VZV-infected cells, the cellular surface MHC-I was restored, and HLA-C was not retained in the Golgi complex. In summary, for the first time, we demonstrate a novel role of VZV IE4 in interfering with the MHC-I presentation pathway, suggesting that it may contribute to the evasion of host antiviral adaptive immunity.

The paragraph “mIE4 VZV fails to downregulate MHC-I on the cell surface To characterize the function of IE4 during VZV infection, a mIE4 VZV was constructed as described in our previous study (Fig. 4A) [30] and showed a similar growth curve with WT VZV (data not shown). [...]flow cytometry analysis revealed that WT or ORF66-flag VZV significantly downregulated cellular surface MHC-I, whereas mIE4 VZV had a weaker effect (Fig. 4B). Confocal microscopy analysis revealed that WT VZV infection resulted in the retention of HLA-C-Red in the Golgi complex, similar to the ectopic expression of IE4 (Fig. 3A). [...]flow cytometry analysis revealed that WT or ORF66-flag VZV significantly downregulated cellular surface MHC-I, whereas mIE4 VZV had less effect (Fig. 4C). Confocal microscopy analysis revealed that WT VZV infection resulted in the retention of HLA-C-Red in the Golgi complex, similar to the ectopic expression of IE4 (Fig. 3A). The sentence Nonetheless, PAA was used to inhibit viral DNA replication in their study, suggesting that VZV IE or early gene product(s) is involved in the regulation of cellular surface MHC-I, and ORF66 delay the MHC-I transport from the ER to the cis/ medial-Golgi [20]. [...]they also demonstrated that VZV lacking ORF66 expression maintains the ability to downregulate cellular surface MHC-I [20], implying that one or more ORF66-independent genes might affect cellular surface MHC-I. in this article should have read as Nonetheless, PAA was used to inhibit viral DNA replication in their study, suggesting that VZV IE or early gene product(s) are involved in the regulation of cellular surface MHC-I, and ORF66 delay the MHC-I transport from the ER to the cis/medial-Golgi [20].

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). Staphylococcus aureus is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and S. aureus infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with S. aureus infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and S. aureus infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and S. aureus immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments.MethodsThe RA dataset (GSE93272) and the S. aureus bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells.ResultsA total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/β) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression.ConclusionsIFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and S. aureus immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and S. aureus infections.

Background It remains controversial whether lipids affect osteoporosis (OP) or bone mineral density (BMD), and causality has not been established. This study aimed to investigate the genetic associations between lipids, novel non-statin lipid-lowering drug target genes, and OP and BMD. Methods Mendelian randomization (MR) method was used to explore the genetic associations between 179 lipid species and OP, BMD. Drug-target MR analysis was used to explore the causal associations between angiopoietin-like protein 3 (ANGPTL3) and apolipoprotein C3 (APOC3) inhibitors on BMD. Results The IVW results with Bonferroni correction indicated that triglyceride (TG) (51:3) (OR = 1.0029; 95% CI: 1.0014–1.0045; P  = 0.0002) and TG (56:6) (OR = 1.0021; 95% CI: 1.0008–1.0033; P  = 0.0011) were associated with an increased risk of OP; TG (51:2) (OR = 0.9543; 95% CI: 0.9148–0.9954; P  = 0.0298) was associated with decreased BMD; and ANGPTL3 inhibitor (OR = 1.1342; 95% CI: 1.0393–1.2290; P  = 0.0093) and APOC3 inhibitor (OR = 1.0506; 95% CI: 1.0155–1.0857; P  = 0.0058) was associated with increased BMD. Conclusions MR analysis indicated causal associations between genetically predicted TGs and OP and BMD. Drug-target MR analysis showed that ANGPTL3 and APOC3 have the potential to serve as novel non-statin lipid-lowering drug targets to treat or prevent OP.

Background Finite element analysis (FEA) was performed to investigate the biomechanical differences between different adjunct fixation methods for oblique lumbar interbody fusion (OLIF) and to further analyze its effect on adjacent segmental degeneration. Methods We built a single-segment (Si-segment) finite element model (FEM) for L4-5 and a double-segment (Do-segment) FEM for L3-5. Each complete FEM was supplemented and modified, and both developed two surgical models of OLIF with assisted internal fixation. They were OLIF with posterior bilateral percutaneous pedicle screw (TINA system) fixation (OLIF + BPS) and OLIF with lateral plate system (OLIF + LPS). The range of motion (ROM) and displacement of the vertebral body, cage stress, adjacent segment disc stress, and spinal ligament tension were recorded for the four models during flexion/extension, right/left bending, and right/left rotation by applying follower load. Results For the BPS and LPS systems in the six postures of flexion, extension, right/left bending, and right/left rotation, the ROM of L4 in the Si-segment FEM were 0.32°/1.83°, 0.33°/1.34°, 0.23°/0.47°, 0.24°/0.45°, 0.33°/0.79°, and 0.34°/0.62°; the ROM of L4 in the Do-segment FEM were 0.39°/2.00°, 0.37°/1.38°, 0.23°/0.47°, 0.21°/0.44°, 0.33°/0.57°, and 0.31°/0.62°, and the ROM of L3 in the Do-segment FEM were 6.03°/7.31°, 2.52°/3.50°, 4.21°/4.38°, 4.21°/4.42°, 2.09°/2.32°, and 2.07°/2.43°. BPS system had less vertebral displacement, less cage maximum stress, and less spinal ligament tension in Si/Do-segment FEM relative to the LPS system. BPS system had a smaller upper adjacent vertebral ROM, greater intervertebral disc stress in terms of left and right bending as well as left and right rotation compared to the LPS system in the L3-4 of the Do-segment FEM. There was little biomechanical difference between the same fixation system in the Si/Do-segment FEM. Conclusions Our finite element analysis showed that compared to OLIF + LPS, OLIF + BPS (TINA) is more effective in reducing interbody stress and spinal ligament tension, and it better maintains the stability of the target segment and provides a better fusion environment to resist cage subsidence. However, OLIF + BPS (TINA) may be more likely to cause adjacent segment degeneration than OLIF + LPS.

The causal associations between infections with human herpes viruses (HHVs) and amyotrophic lateral sclerosis (ALS) has been disputed. This study investigated the causal associations between herpes simplex virus (HSV), varicella-zoster virus (VZV), Epstein-Barr virus (EBV), cytomegalovirus (CMV), HHV-6, and HHV-7 infections and ALS through a bidirectional Mendelian randomization (MR) method. The genome-wide association studies (GWAS) database were analyzed by inverse variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods. MR-Egger intercept test, MR-PRESSO test, Cochran's Q test, funnel plots, and leaveone-out analysis were used to verify the validity and robustness of the MR results. In the forward MR analysis of the IVW, genetically predicted HSV infections [odds ratio (OR) = 0.9917; 95% confidence interval (CI): 0.9685-1.0154;  = 0.4886], HSV keratitis and keratoconjunctivitis (OR = 0.9897; 95% CI: 0.9739-1.0059;  = 0.2107), anogenital HSV infection (OR = 1.0062; 95% CI: 0.9826-1.0304;  = 0.6081), VZV IgG (OR = 1.0003; 95% CI: 0.9849-1.0160;  = 0.9659), EBV IgG (OR = 0.9509; 95% CI: 0.8879-1.0183;  = 0.1497), CMV (OR = 0.9481; 95% CI: 0.8680-1.0357;  = 0.2374), HHV-6 IgG (OR = 0.9884; 95% CI: 0.9486-1.0298;  = 0.5765) and HHV-7 IgG (OR = 0.9991; 95% CI: 0.9693-1.0299;  = 0.9557) were not causally associated with ALS. The reverse MR analysis of the IVW revealed comparable findings, indicating no link between HHVs infections and ALS. The reliability and validity of the findings were verified by the sensitivity analysis. According to the MR study, there is no evidence of causal associations between genetically predicted HHVs (HSV, VZV, EBV, CMV, HHV-6, and HHV-7) and ALS.

Background Numerous investigations have suggested links between circulating inflammatory proteins (CIPs) and spinal degenerative diseases (SDDs), but causality has not been proven. This study used Mendelian randomization (MR) to investigate the causal associations between 91 CIPs and cervical spondylosis (CS), prolapsed disc/slipped disc (PD/SD), spinal canal stenosis (SCS), and spondylolisthesis/spondylolysis. Methods Genetic variants data for CIPs and SDDs were obtained from the genome‐wide association studies (GWAS) database. We used inverse variance weighted (IVW) as the primary method, analyzing the validity and robustness of the results through pleiotropy and heterogeneity tests and performing reverse MR analysis to test for reverse causality. Results The IVW results with Bonferroni correction indicated that beta‐nerve growth factor (β‐NGF), C‐X‐C motif chemokine 6 (CXCL6), and interleukin‐6 (IL‐6) can increase the risk of CS. Fibroblast growth factor 19 (FGF19), sulfotransferase 1A1 (SULT1A1), and tumor necrosis factor‐beta (TNF‐β) can increase PD/SD risk, whereas urokinase‐type plasminogen activator (u‐PA) can decrease the risk of PD/SD. FGF19 and TNF can increase SCS risk. STAM binding protein (STAMBP) and T‐cell surface glycoprotein CD6 isoform (CD6 isoform) can increase the risk of spondylolisthesis/spondylolysis, whereas monocyte chemoattractant protein 2 (MCP2) and latency‐associated peptide transforming growth factor beta 1 (LAP‐TGF‐β1) can decrease spondylolisthesis/spondylolysis risk. Conclusions MR analysis indicated the causal associations between multiple genetically predicted CIPs and the risk of four SDDs (CS, PD/SD, SCS, and spondylolisthesis/spondylolysis). This study provides reliable genetic evidence for in‐depth exploration of the involvement of CIPs in the pathogenic mechanism of SDDs and provides novel potential targets for SDDs. MR analyses indicated the causal associations between multiple genetically predicted CIPs and the risk of four SDDs (CS, PD/SD, SCS, and spondylolisthesis/spondylolysis). This study provides reliable genetic evidence for in‐depth exploration of the involvement of CIPs in the pathogenic mechanism of SDDs and provides novel potential targets for SDDs.

The coronavirus disease (COVID-19) is a pandemic disease that threatens worldwide public health, and rheumatoid arthritis (RA) is the most common autoimmune disease. COVID-19 and RA are each strong risk factors for the other, but their molecular mechanisms are unclear. This study aims to investigate the biomarkers between COVID-19 and RA from the mechanism of pyroptosis and find effective disease-targeting drugs. We obtained the common gene shared by COVID-19, RA (GSE55235), and pyroptosis using bioinformatics analysis and then did the principal component analysis(PCA). The Co-genes were evaluated by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ClueGO for functional enrichment, the protein-protein interaction (PPI) network was built by STRING, and the k-means machine learning algorithm was employed for cluster analysis. Modular analysis utilizing Cytoscape to identify hub genes, functional enrichment analysis with Metascape and GeneMANIA, and NetworkAnalyst for gene-drug prediction. Network pharmacology analysis was performed to identify target drug-related genes intersecting with COVID-19, RA, and pyroptosis to acquire Co-hub genes and construct transcription factor (TF)-hub genes and miRNA-hub genes networks by NetworkAnalyst. The Co-hub genes were validated using GSE55457 and GSE93272 to acquire the Key gene, and their efficacy was assessed using receiver operating curves (ROC); SPEED2 was then used to determine the upstream pathway. Immune cell infiltration was analyzed using CIBERSORT and validated by the HPA database. Molecular docking, molecular dynamics simulation, and molecular mechanics-generalized born surface area (MM-GBSA) were used to explore and validate drug-gene relationships through computer-aided drug design. COVID-19, RA, and pyroptosis-related genes were enriched in pyroptosis and pro-inflammatory pathways(the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome complex, death-inducing signaling complex, regulation of interleukin production), natural immune pathways (Network map of SARS-CoV-2 signaling pathway, activation of NLRP3 inflammasome by SARS-CoV-2) and COVID-19-and RA-related cytokine storm pathways (IL, nuclear factor-kappa B (NF-κB), TNF signaling pathway and regulation of cytokine-mediated signaling). Of these, CASP1 is the most involved pathway and is closely related to minocycline. YY1, hsa-mir-429, and hsa-mir-34a-5p play an important role in the expression of CASP1. Monocytes are high-caspase-1-expressing sentinel cells. Minocycline can generate a highly stable state for biochemical activity by docking closely with the active region of caspase-1. Caspase-1 is a common biomarker for COVID-19, RA, and pyroptosis, and it may be an important mediator of the excessive inflammatory response induced by SARS-CoV-2 in RA patients through pyroptosis. Minocycline may counteract cytokine storm inflammation in patients with COVID-19 combined with RA by inhibiting caspase-1 expression.

Rheumatoid arthritis (RA) is one of the most common chronic inflammatory autoimmune diseases. However, the underlying molecular mechanisms of its pathogenesis are unknown. This study aimed to identify the common biomarkers of ferroptosis and pyroptosis in RA and screen potential drugs. The RA-related differentially expressed genes (DEGs) in GSE55235 were screened by R software and intersected with ferroptosis and pyroptosis gene libraries to obtain differentially expressed ferroptosis-related genes (DEFRGs) and differentially expressed pyroptosis-related genes (DEPRGs). We performed Gene Ontology (GO), Kyoto Encyclopedia of the Genome (KEGG), ClueGO, and Protein-Protein Interaction (PPI) analysis for DEFRGs and DEPRGs and validated them by machine learning. The microRNA/transcription factor (TF)-hub genes regulatory network was further constructed. The key gene was validated using the GSE77298 validation set, cellular validation was performed in in vitro experiments, and immune infiltration analysis was performed using CIBERSORT. Network pharmacology was used to find key gene-targeting drugs, followed by molecular docking and molecular dynamics simulations to analyze the binding stability between small-molecule drugs and large-molecule proteins. Three hub genes (CASP8, PTGS2, and JUN) were screened via bioinformatics, and the key gene (CASP8) was validated and obtained through the validation set, and the diagnostic efficacy was verified to be excellent through the receiver operating characteristic (ROC) curves. The ferroptosis and pyroptosis phenotypes were constructed by fibroblast-like synoviocytes (FLS), and caspase-8 was detected and validated as a common biomarker for ferroptosis and pyroptosis in RA, and quercetin can reduce caspase-8 levels. Quercetin was found to be a potential target drug for caspase-8 by network pharmacology, and the stability of their binding was further verified using molecular docking and molecular dynamics simulations. Caspase-8 is an important biomarker for ferroptosis and pyroptosis in RA, and quercetin is a potential therapy for RA via targeting caspase-8 through ferroptosis and pyroptosis.

Trained immunity is a phenomenon in which brief exposure to an infectious agent or a vaccine can induce long-lasting changes in the host's immune system, enhancing protection against subsequent infections. The concept of trained immunity has a significant impact on the field of immunology and has the potential to revolutionize how we approach vaccination and infectious disease control. Investigations into trained immunity are rapidly advancing and have led to the development of new vaccines and immunotherapeutic strategies that harness the power of this phenomenon. While more investigations are needed to fully understand the mechanisms of trained immunity and its potential limitations, the prospects for its future application in clinical practice are promising. Here, we describe trained immunity as a biological process and explore the innate cues, epigenetic changes, and metabolic reprogramming activities that affect how trained immunity is induced.