Aims. Despite the interest in the association of gut
Aims. The effect of the gut
Osteoporosis (OP) is a chronic metabolic bone disease characterized by the decrease of bone tissue per unit volume under the combined action of genetic and environmental factors, which leads to the decrease of bone strength, makes the bone brittle, and raises the possibility of bone fracture. However, the exact mechanism that determines the progression of OP remains to be underlined. There are hundreds of trillions of symbiotic bacteria living in the human gut, which have a mutually beneficial symbiotic relationship with the human body that helps to maintain human health. With the development of modern high-throughput sequencing (HTS) platforms, there has been growing evidence that the gut microbiome may play an important role in the programming of bone metabolism. In the present review, we discuss the potential mechanisms of the gut microbiome in the development of OP, such as alterations of bone metabolism, bone mineral absorption, and immune regulation. The potential of gut microbiome-targeted strategies in the prevention and treatment of OP was also evaluated. Cite this article:
We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.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
There is an increasing concern of osteoporotic fractures in the ageing population. Low-magnitude high-frequency vibration (LMHFV) was shown to significantly enhance osteoporotic fracture healing through alteration of osteocyte lacuno-canalicular network (LCN). Dentin matrix protein 1 (DMP1) in osteocytes is known to be responsible for maintaining the LCN and mineralization. This study aimed to investigate the role of osteocyte-specific DMP1 during osteoporotic fracture healing augmented by LMHFV. A metaphyseal fracture was created in the distal femur of ovariectomy-induced osteoporotic Sprague Dawley rats. Rats were randomized to five different groups: 1) DMP1 knockdown (KD), 2) DMP1 KD + vibration (VT), 3) Scramble + VT, 4) VT, and 5) control (CT), where KD was performed by injection of short hairpin RNA (shRNA) into marrow cavity; vibration treatment was conducted at 35 Hz, 0.3 g; 20 minutes/day, five days/week). Assessments included radiography, micro-CT, dynamic histomorphometry and immunohistochemistry on DMP1, sclerostin, E11, and fibroblast growth factor 23 (FGF23). In vitro, murine long bone osteocyte-Y4 (MLO-Y4) osteocyte-like cells were randomized as in vivo groupings. DMP1 KD was performed by transfecting cells with shRNA plasmid. Assessments included immunocytochemistry on osteocyte-specific markers as above, and mineralized nodule staining.Aims
Methods
With the ageing population, fragility fractures have become one of the most common conditions. The objective of this study was to investigate whether microbiological outcomes and fracture-healing in osteoporotic bone is worse than normal bone with fracture-related infection (FRI). A total of 120 six-month-old Sprague-Dawley (SD) rats were randomized to six groups: Sham, sham + infection (Sham-Inf), sham with infection + antibiotics (Sham-Inf-A), ovariectomized (OVX), OVX + infection (OVX-Inf), and OVX + infection + antibiotics (OVX-Inf-A). Open femoral diaphysis fractures with Kirschner wire fixation were performed. Aims
Methods
Methicillin-resistant Rats underwent intestinal colonization with green fluorescent protein (GFP)-tagged MRSA by gavage and an intra-articular wire was then surgically implanted. After ten days, the presence of PJI was determined by bacterial cultures of the distal femur, joint capsule, and implant. We excluded several other possibilities for PJI development. Intraoperative contamination was excluded by culturing the specimen obtained from surgical site. Extracellular bacteraemia-associated PJI was excluded by comparing with the infection rate after intravenous injection of MRSA or MRSA-carrying neutrophils. To further support this theory, we tested the efficacy of prophylactic membrane-permeable and non-membrane-permeable antibiotics in this model.Aims
Methods
The aim of this study was to evaluate the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens from synovial fluid of prosthetic joint infection (PJI) patients. A group of 75 patients who underwent revision knee or hip arthroplasties were enrolled prospectively. Ten patients with primary arthroplasties were included as negative controls. Synovial fluid was collected for mNGS analysis. Optimal thresholds were determined to distinguish pathogens from background microbes. Synovial fluid, tissue, and sonicate fluid were obtained for culture.Aims
Methods
Prosthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by conventional bacterial cultures, for which false-negative rates are 23% to 35%. In contrast, 16S rRNA metagenomics has been shown to quantitatively detect unculturable, unsuspected, and unviable pathogens. In this study, we investigated the use of 16S rRNA metagenomics for detection of bacterial pathogens in synovial fluid (SF) from patients with hip or knee PJI. We analyzed the bacterial composition of 22 SF samples collected from 11 patients with PJIs (first- and second-stage surgery). The V3 and V4 region of bacteria was assessed by comparing the taxonomic distribution of the 16S rDNA amplicons with microbiome sequencing analysis. We also compared the results of bacterial detection from different methods including 16S metagenomics, traditional cultures, and targeted Sanger sequencing.Objectives
Methods
