Aims. The aim of this study was to evaluate the performance of metagenomic
Aims. This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic
Aims. Use of molecular sequencing methods in periprosthetic joint infection (PJI) diagnosis and organism identification have gained popularity.
Aim. metagenomic
Aim. Surgical management of PJI remains challenging with patients failing treatment despite the best efforts. An important question is whether these later failures reflect reinfection or the persistence of infection. Proponents of reinfection believe hosts are vulnerable to developing infection and new organisms emerge. The alternative hypothesis is that later failure is a result of an organism that was present in the joint but was not picked up by initial culture or was not a pathogen initially but became so under antibiotic pressure. This multicenter study explores the above dilemma. Utilizing
Aim. The clinical relevance of microbial DNA detected via
Despite recent advances in the diagnosis of periprosthetic joint infection(PJI), identifying the infecting organism continues to be a challenge, with up to a third of PJIs reported to have negative cultures. Current molecular techniques have thus far been unable to replace culture as the gold standard for isolation of the infecting pathogen. Next- generation sequencing(NGS) is a well-established technique for comprehensively sequencing the entire pathogen DNA in a given sample and has recently gained much attention in many fields of medicine. Our aim was to evaluate the ability of NGS in identifying the causative organism(s) in patients with PJI. After obtaining Institutional Review Board approval and informed consent for all study participants, samples were prospectively collected from 148 revision total joint arthroplasty procedures (83 knees, 65 hips). Synovial fluid, deep tissue and swabs were obtained at the time of surgery and shipped to the laboratory for NGS analysis (MicroGenDx). Deep tissue specimens were also sent to the institutional laboratory(Thomas Jefferson University Hospital) for culture. PJI was diagnosed using the Musculoskeletal Infection Society(MSIS) definition of PJI. Statistical analysis was performed using SPSS software.Introduction
Methods
Recent reports demonstrate that Next Generation Sequencing (NGS) facilitates pathogen identification in the context of culture-negative PJI; however the clinical relevance of the polymicrobial genomic signal often generated remains unknown. This study was conceived to explore: (1) the ability of NGS to identify pathogens in culture-negative PJI; and (2) determine whether organisms detected by NGS, as part of a prospective observational study, had any role in later failure of patients undergoing surgical treatment for PJI. In this prospective study samples were collected in 238 consecutive patients undergoing revision total hip and knee arthroplasties. Of these 83 patients (34.9%) had PJI, as determined using the Musculoskeletal Infection Society (MSIS) criteria, and of these 20 were culture-negative (CN-PJI). Synovial fluid, deep tissue and swabs were obtained at the time of surgery and sent for NGS and culture/MALDI-TOF. Patients undergoing reimplantation were excluded. Treatment failure was assessed using the previously described Delphi criteria. In cases of re-operation, organisms present were confirmed by culture and MALDI-TOF. Concordance of the infecting pathogen(s) at failure with the NGS analysis at the initial stage CN- PJI procedure was determined.Background
Methods
Periprosthetic joint infection is an increasing reason for revision surgery. Tissue cultures are a standard (std.) diagnostic procedure but may be hindered by bacteria that are difficult to cultivate. The use of dithiothreitol (DTT) to detach the formed biofilm has been proposed to improve the diagnostic security. The aim was to compare the diagnosis results using the microDTTect device with the routine PJI diagnostics and next generation sequencing (NGS) from DTT treated explants. 66 patients with revision surgeries were included in this study (38 aseptic; 28 septic). We compared std. microbiology tissue cultures with the microDTTect cultures of the DTT treated explants and NGS of bacterial DNA isolated from DTT solution.Aim
Method
Next generation sequencing (NGS) has been shown to facilitate detection of microbes in a clinical sample, particularly in the setting of culture-negative periprosthetic joint infection (PJI). However, it is unknown whether every microbial DNA signal detected by NGS is clinically relevant. This multi-institutional study was conceived to 1) identify species detected by NGS that may predict PJI, then 2) build a predictive model for PJI in a developmental cohort; and 3) validate the predictive utility of the model in a separate multi-institutional cohort. This multicenter investigation involving 15 academic institutions prospectively collected samples from 194 revision total knee arthroplasties (TKA) and 184 revision hip arthroplasties (THA) between 2017–2019. Patients undergoing reimplantation or spacer exchange procedures were excluded. Synovial fluid, deep tissue and swabs were obtained at the time of surgery and shipped to MicrogenDx (Lubbock, TX) for NGS analysis. Deep tissue specimens were also sent to the institutional labs for culture. All patients were classified per the 2018 Consensus definition of PJI. Microbial DNA analysis of community similarities (ANCOM) was used to identify 17 candidate bacterial species out of 294 (W-value >50) for differentiating infected vs. noninfected cases. Logistic Regression with LASSO model selection and random forest algorithms were then used to build a model for predicting PJI. For this analysis, ICM classification was the response variable (gold standard) and the species identified through ANCOM were the predictor variables. Recruited cases were randomly split in half, with one half designated as the training set, and the other half as the validation set. Using the training set, a model for PJI diagnosis was generated. The optimal resulting model was then tested for prediction ability with the validation set. The entire model-building procedure and validation was iterated 1000 times. From the model set, distributions of overall assignment rate, specificity, sensitivity, positive predictive value (PPV) and negative predicative value (NPV) were assessed.Introduction
Methods
Recent focus has queried whether of deoxyribonucleic acid (DNA) sequencing modalities of bacterial DNA found in periarticular fluid and tissues will improve in periprosthetic joint infection (PJI) diagnosis and organism identification diagnostic accuracy for periprosthetic joint infection The purpose of this study was to compare the diagnostic accuracy of next generation sequencing (NGS) to polymerase chain reaction (PCR) multiplex, and culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al. [1] in the diagnosis of periprosthetic knee infections. In this retrospective study, aspirate or tissue samples were collected in 70 revision and 58 primary knee arthroplasties for routine diagnostic workup for PJI and sent to the laboratory for NGS and PCR multiplex. Concordance along with statistical differences between diagnostic studies were calculated using Chi-squared test for categorical data.Introduction
Methods
Recent focus has shifted towards the utilization of deoxyribonucleic acid (DNA) sequencing modalities in periprosthetic joint infection (PJI) diagnosis and organism identification. The purpose of this study was to compare the diagnostic accuracy of next generation sequencing (NGS) to polymerase chain reaction (PCR) multiplex, culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al. [1] in the diagnosis of periprosthetic hip infections. In this retrospective study, aspirate or tissue samples were collected in 23 revision and 19 primary hip arthroplasties for routine diagnostic workup for PJI and sent to the laboratory for NGS and PCR multiplex. Concordance along with statistical differences between diagnostic studies were calculated using Chi-squared test for categorical data.Introduction
Methods
Aims. The diagnosis of periprosthetic joint infection can be difficult
due to the high rate of culture-negative infections. The aim of
this study was to assess the use of
Aims. The decrease in the number of satellite cells (SCs), contributing to myofibre formation and reconstitution, and their proliferative capacity, leads to muscle loss, a condition known as sarcopenia. Resistance training can prevent muscle loss; however, the underlying mechanisms of resistance training effects on SCs are not well understood. We therefore conducted a comprehensive transcriptome analysis of SCs in a mouse model. Methods. We compared the differentially expressed genes of SCs in young mice (eight weeks old), middle-aged (48-week-old) mice with resistance training intervention (MID+ T), and mice without exercise (MID) using
Aims. As a proven and comprehensive molecular technique, metagenomic
Aims. Metagenomic
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