Identification of the causative pathogen in musculoskeletal infection is critical as it directs further treatment. Fracture-related infection is often associated with ‘no growth’ in standard culture. We investigated the efficiency of two alternate methods to identify the causative pathogen, namely extended bacterial culture and 16Sr RNA gene sequence analysis with next generation sequencing (NGS) in ‘culture negative’ fracture related infections. Patients were diagnosed as having fracture related infection based on the MSIS criteria (n=120). All patients had samples taken for culture and sensitivity. All samples which were culture negative by standard culture methods formed the study group. These samples were subjected to further extended culture in both aerobic and anaerobic medium for 14 days to improve recovery of pathogens. Further, DNA isolated from implants from a sub-group of these culture negative patients were subjected to 16SrRNA gene amplification followed by Sanger sequencing. Subsequent sequencing analysis was performed using the Illumina NGS platform which identified and detected the most abundant genera/species present in those samples more precisely.Introduction
Method
Recent studies suggested that both the soluble protein of the mesenchymal stromal cell (MSC) secretome, as well as the secreted extracellular vesicles (EVs) promote bone regeneration. However, there is limited knowledge of the changes in MSC secretome vesicular fraction during aging. We therefore aimed to characterize the release profiles and cargo of EVs from MSCs of different chronological ages. Conditioned medium (CM) was collected from 13 bone marrow MSC strains (20-89 years) and from one MSC strain derived from human induced pluripotent stem cells (iPSCs). The EV-containing fraction was enriched with ultracentrifugation. The number of particles in the CM was evaluated by nanoparticle tracking analysis (NTA), and the number of EVs was evaluated by flow cytometry (FC) after staining with cell-mask-green and anti-CD81 antibody. EV cargo analysis was conducted using
Introduction and Objective. Intervertebral disc (IVD) degeneration is one of the major contributors to low back pain, the leading cause of disability worldwide. This multifactorial pathological process involves the degradation of the extracellular matrix, inflammation, and cell loss due to apoptosis and senescence. While the deterioration of the extracellular matrix and cell loss lead to structural collapse of the IVD, increased levels of inflammation result in innervation and the development of pain. Amongst the known regulators of inflammation, toll-like receptors (TLRs) and more specifically TLR-2 have been shown to be specifically relevant in IVD degeneration. As strong post-transcriptional regulators, microRNAs (miRNAs) and their dysregulation has been connected to multiple pathologies, including degenerative diseases such as osteoarthritis and IVD degeneration. However, the role of miRNAs in TLR signalling in the IVD is still poorly understood and was hence investigated in this study. Materials and Methods. Human Nucleus pulposus (hNP) and Annulus fibrosus (hAF) cells (n=5) were treated with the TLR-2/6 specific agonist PAM2CSK4 (100 ng/mL for 6 hours) in order to activate the TLR2 signalling pathway. After the activation both miRNA and mRNA were isolated, followed by
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
We have previously investigated an association between the genome copy number variation (CNV) and acetabular dysplasia (AD). Hip osteoarthritis is associated with a genetic polymorphism in the aspartic acid repeat in the N-terminal region of the asporin ( Acetabular coverage of all subjects was evaluated using radiological findings (Sharp angle, centre-edge (CE) angle, acetabular roof obliquity (ARO) angle, and minimum joint space width). Genomic DNA was extracted from peripheral blood leukocytes. Agilent’s region-targeted high-density oligonucleotide tiling microarray was used to analyse 64 female AD patients and 32 female control subjects. All statistical analyses were performed using EZR software (Fisher’s exact probability test, Pearson’s correlation test, and Student’s Objectives
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