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Abstract 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.

Abstract 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.

Abstract 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.

ObjectiveThere is a controversy in studies of circulating inflammatory proteins (CIPs) in association with osteoporosis (OP) and fractures, and it is unclear if these two conditions are causally related. This study used MR analyses to investigate the causal associations between 91 CIPs and OP and 9 types of fractures.MethodsGenetic variants data for CIPs, OP, and fractures were obtained from the publicly available genome-wide association studies (GWAS) database. We used inverse variance weighted (IVW) as the primary analysis, pleiotropy, and heterogeneity tests to analyze the validity and robustness of causality and reverse MR analysis to test for reverse causality.ResultsThe IVW results with Bonferroni correction indicated that CXCL11 (OR = 1.2049; 95% CI: 1.0308-1.4083; P = 0.0192) can increase the risk of OP; IL-4 (OR = 1.2877; 95% CI: 1.1003-1.5070; P = 0.0016), IL-7 (OR = 1.2572; 95% CI: 1.0401-1.5196; P = 0.0180), IL-15RA (OR = 1.1346; 95% CI: 1.0163-1.2668; P = 0.0246), IL-17C (OR = 1.1353; 95% CI: 1.0272-1.2547; P = 0.0129), CXCL10 (OR = 1.2479; 95% CI: 1.0832-1.4377; P = 0.0022), eotaxin/CCL11 (OR = 1.1552; 95% CI: 1.0525-1.2678; P = 0.0024), and FGF23 (OR = 1.9437; 95% CI: 1.1875-3.1816; P = 0.0082) can increase the risk of fractures; whereas IL-10RB (OR = 0.9006; 95% CI: 0.8335-0.9730; P = 0.0080), CCL4 (OR = 0.9101; 95% CI: 0.8385-0.9878; P = 0.0242), MCP-3/CCL7 (OR = 0.8579; 95% CI: 0.7506-0.9806; P = 0.0246), IFN-γ [shoulder and upper arm (OR = 0.7832; 95% CI: 0.6605-0.9287; P = 0.0049); rib(s), sternum and thoracic spine (OR = 0.7228; 95% CI: 0.5681-0.9197; P = 0.0083)], β-NGF (OR = 0.8384; 95% CI: 0.7473-0.9407; P = 0.0027), and SIRT2 (OR = 0.5167; 95% CI: 0.3296-0.8100; P = 0.0040) can decrease fractures risk.ConclusionMendelian randomization (MR) analyses indicated the causal associations between multiple genetically predicted CIPs and the risk of OP and fractures.

BackgroundThe 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.MethodsThe 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.ResultsIn the forward MR analysis of the IVW, genetically predicted HSV infections [odds ratio (OR) = 0.9917; 95% confidence interval (CI): 0.9685–1.0154; p = 0.4886], HSV keratitis and keratoconjunctivitis (OR = 0.9897; 95% CI: 0.9739–1.0059; p = 0.2107), anogenital HSV infection (OR = 1.0062; 95% CI: 0.9826–1.0304; p = 0.6081), VZV IgG (OR = 1.0003; 95% CI: 0.9849–1.0160; p = 0.9659), EBV IgG (OR = 0.9509; 95% CI: 0.8879–1.0183; p = 0.1497), CMV (OR = 0.9481; 95% CI: 0.8680–1.0357; p = 0.2374), HHV-6 IgG (OR = 0.9884; 95% CI: 0.9486–1.0298; p = 0.5765) and HHV-7 IgG (OR = 0.9991; 95% CI: 0.9693–1.0299; p = 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.ConclusionAccording 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.

Objectives To characterize the abundance and relative composition of seawater bacterioplankton communities in Changle city using Illumina MiSeq sequencing and bacterial culture techniques. Methods Seawater samples and physicochemical factors were collected from the coastal zone of Changle city on 8 September 2019. Nineteen filter membranes were obtained after using a suction filtration system. We randomly selected eight samples for total seawater bacteria (SWDNA group) sequencing and three samples for active seawater bacteria (SWRNA group) sequencing by Illumina MiSeq. The remaining eight samples were used for bacterial culture and identification. Alpha diversity including species coverage (Coverage), species diversity (Shannon–Wiener and Simpson index), richness estimators (Chao1), and abundance‐based richness estimation (ACE) were calculated to assess biodiversity of seawater bacterioplankton. Beta diversity was used to evaluate the differences between samples. The species abundance differences were determined using the Wilcoxon rank‐sum test. Statistical analyses were performed in R environment. Results The Alpha diversity in the SWDNA group in each index was ACE 3206.99, Chao1 2615.12, Shannon 4.64, Simpson 0.05, and coverage 0.97; the corresponding index was ACE 1199.55, Chao1 934.75, Shannon 3.49, Simpson 0.09, and coverage 0.99. The sequencing results of seawater bacterial genes in the coastal waters of Changle city showed that the phyla of high‐abundance bacteria of both the SWDNA and SWRNA groups included Cyanobacteria, Proteobacteria, and Bacteroidetes. The main classes included Oxyphotobacteria, Alphaproteobacteria, and Gammaproteobacteria. The main genera included Synechococcus CC9902, Chloroplast, and Cyanobium_PCC‐6307. Beta diversity analysis showed a significant difference between the SWDNA and SWRNA groups (P

BackgroundThe 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.MethodsWe 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.ResultsCOVID-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.ConclusionsCaspase-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.

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.

Abstract Objectives We aimed to explore the bacterial community composition following ocean bacterial infection using an animal model. Methods This animal-based experiment was conducted from September 2019 to November 2019. Eighteen seawater filter membranes were collected from Changle City, Fujiian Province, China, on September 8, 2019. Ten filter membranes were used for implantation. Eight filter membranes that were used in the bacterial culture for the exploration of seawater bacteria were assigned to the seawater group (SG). Fourteen healthy adult New Zealand rabbits were randomly divided into the experimental group (EG) and control group (CG). Seawater filter membranes and asepsis membranes were implanted into the tibia in the EG and CG, respectively. One week after surgery, tibial bone pathology tissues were collected and assessed using light microscopy and scanning electron microscopy (SEM). Medullary cavity tissues were collected for the performance of Illumina MiSeq sequencing and bacterial culture. The differences between EG and CG were assessed by pathological observation under light microscopy and SEM, high-throughput bacterial sequencing, and bacterial culture. Results Compared with the CG, the infection rate was 100%, and the mortality value was 20% after the implantation of the filter membranes in the EG. Both light microscopy and SEM showed that a large number of bacteria were distributed in the bone marrow cavity after ocean bacterial infection. No bacterial growth was found in the CG. Illumina MiSeq sequencing found that Firmicutes, Proteobacteria, Thermotogae, Fusobacteria, Bacteroidetes, and Actinobacteria were the dominant bacteria at the phylum level and Clostridium_sensu_stricto_7, Haloimpatiens, Clostridium_sensu_stricto_15, Clostridiaceae_1, Clostridium_sensu_stricto_18, and Oceanotoga were the dominant bacteria in genus level among the EG. In the bacterial culture of the medullary cavity tissues, Klebsiella pneumoniae, Shewanella algae, Staphylococcus aureus, Escherichia coli, Enterobacter cloacae, and Vibrio vulnificus were the predominant infective species. Moreover, compared with the SG, the EG showed a higher detection rate of E. coli and S. aureus (P = 0.008 and P = 0.001, respectively). The detection rates of V. alginolyticus, V. parahaemolyticus, and V. fluvialis were higher in the SG than the EG (P = 0.007, P = 0.03, and P = 0.03, respectively). Conclusions Our model, which was comprehensively evaluated using four techniques: histopathology and SEM observation, gene detection, and bacteria culture, provides a scientific basis for the clinical diagnosis and treatment of patients in such settings.

Regulated cell death is a form of cell death that is actively controlled by biomolecules. Several studies have shown that regulated cell death plays a key role after spinal cord injury. Pyroptosis and ferroptosis are newly discovered types of regulated cell deaths that have been shown to exacerbate inflammation and lead to cell death in damaged spinal cords. Autophagy, a complex form of cell death that is interconnected with various regulated cell death mechanisms, has garnered significant attention in the study of spinal cord injury. This injury triggers not only cell death but also cellular survival responses. Multiple signaling pathways play pivotal roles in influencing the processes of both deterioration and repair in spinal cord injury by regulating pyroptosis, ferroptosis, and autophagy. Therefore, this review aims to comprehensively examine the mechanisms underlying regulated cell deaths, the signaling pathways that modulate these mechanisms, and the potential therapeutic targets for spinal cord injury. Our analysis suggests that targeting the common regulatory signaling pathways of different regulated cell deaths could be a promising strategy to promote cell survival and enhance the repair of spinal cord injury. Moreover, a holistic approach that incorporates multiple regulated cell deaths and their regulatory pathways presents a promising multi-target therapeutic strategy for the management of spinal cord injury.