The optimum type of antibiotics and their administration route for treating Gram-negative (GN) periprosthetic joint infection (PJI) remain controversial. This study aimed to determine the GN bacterial species and antibacterial resistance rates related to clinical GN-PJI, and to determine the efficacy and safety of intra-articular (IA) antibiotic injection after one-stage revision in a GN pathogen-induced PJI rat model of total knee arthroplasty. A total of 36 consecutive PJI patients who had been infected with GN bacteria between February 2015 and December 2021 were retrospectively recruited in order to analyze the GN bacterial species involvement and antibacterial resistance rates. Antibiotic susceptibility assays of the GN bacterial species were performed to screen for the most sensitive antibiotic, which was then used to treat the most common GN pathogen-induced PJI rat model. The rats were randomized either to a PJI control group or to three meropenem groups (intraperitoneal (IP), IA, and IP + IA groups). After two weeks of treatment, infection control level, the side effects, and the volume of antibiotic use were evaluated.Aims
Methods
The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA. Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database.Aims
Methods
Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects.Aims
Methods
Kashin-Beck disease (KBD) is a kind of chronic osteochondropathy, thought to be caused by environmental risk factors such as T-2 toxin. However, the exact aetiology of KBD remains unclear. In this study, we explored the functional relevance and biological mechanism of cartilage oligosaccharide matrix protein (COMP) in the articular cartilage damage of KBD. The articular cartilage specimens were collected from five KBD patients and five control subjects for cell culture. The messenger RNA (mRNA) and protein expression levels were detected by quantitative reverse transcription PCR (qRT-PCR) and western blot. The survival rate of C28/I2 chondrocyte cell line was detected by MTT assay after T-2 toxin intervention. The cell viability and mRNA expression levels of apoptosis related genes between Aims
Methods
Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID).Aim
Patients and Methods
Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients’ BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05.Objectives
Method
The molecular mechanism of rheumatoid arthritis (RA) remains elusive. We conducted a protein-protein interaction network-based integrative analysis of genome-wide association studies (GWAS) and gene expression profiles of RA. We first performed a dense search of RA-associated gene modules by integrating a large GWAS meta-analysis dataset (containing 5539 RA patients and 20 169 healthy controls), protein interaction network and gene expression profiles of RA synovium and peripheral blood mononuclear cells (PBMCs). Gene ontology (GO) enrichment analysis was conducted by DAVID. The protein association networks of gene modules were generated by STRING.Objectives
Methods
