Aims. Developmental dysplasia of the hip (DDH) is a complex musculoskeletal disease that occurs mostly in children. This study aimed to investigate the molecular changes in the hip joint capsule of patients with DDH. Methods.
Osteoporosis is a common problem in postmenopausal women and the elderly. 11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a bi-directional enzyme that primarily activates glucocorticoids (GCs) in vivo, which is a considerable potential target as treatment for osteoporosis. Previous studies have demonstrated its effect on osteogenesis, and our study aimed to demonstrate its effect on osteoclast activation. In vivo, we used 11β-HSD1 knock-off (KO) and C57BL6/J mice to undergo the ovariectomy-induced osteoporosis (OVX). In vitro, In vivo, We used 11β-HSD1 knockoff (KO) and C57BL6/J mice to undergo the ovariectomy-induced osteoporosis (OVX). In vitro, bone marrow-derived macrophages (BMM) and bone marrow mesenchymal stem cell (BMSC) of KO and C57BL6/J mice were extracted to test their osteogenic and osteoclastic abilities. We then created osteoclastic 11β-HSD1 elimination mice (Ctsk::11β-HSD1fl/fl) and treated them with OVX. Micro-CT analysis, H&E, immunofluorescence staining, and qPCR were performed. Finally, we conducted the
Lumbar diseases have become a major problem affecting human health worldwide. Conservative treatment of lumbar diseases is difficult to achieve ideal results, and surgical treatment of trauma, complications, it is imperative to develop a new treatment method. This study aims to explore the regulatory mechanism of cartilage endplate ossification caused by abnormal stress, and design intervention targets for this mechanism, so as to provide theoretical reference for the prevention and treatment of lumbar degeneration. In vivo, we constructed spinal instability model in mice. In vitro, we used a mechanical tensile machine to simulate the abnormal stress conditions of the endplate cartilage cells. Through the
Aims. To investigate the effects of senescent osteocytes on bone homeostasis in the progress of age-related osteoporosis and explore the underlying mechanism. Methods. In a series of in vitro experiments, we used tert-Butyl hydroperoxide (TBHP) to induce senescence of MLO-Y4 cells successfully, and collected conditioned medium (CM) and senescent MLO-Y4 cell-derived exosomes, which were then applied to MC3T3-E1 cells, separately, to evaluate their effects on osteogenic differentiation. Furthermore, we identified differentially expressed microRNAs (miRNAs) between exosomes from senescent and normal MLO-Y4 cells by
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
Introduction. 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. Methods. 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. Results. The overall predictive accuracy achieved in the model was 75.9% (Figure 1). There was a high accuracy in true-negative and false-negative classification of patients using this predictive model (Figure 2), which has previously been a criticism of NGS interpretation and reporting. Specificity was 97.1%, PPV was 75.0%, and NPV was 76.2%. On comparison of the distribution of abundances between ICM-positive and ICM-negative patients, Staphylococcus aureus was the strongest contributor (F=0.99) to the predictive power of the model (Figure 3). In contrast, Cutibacterium acnes was less predictive (F=0.309) and noted to be abundant across both infected and noninfected revision TJA samples. Discussion. This study is the first to utilize predictive modeling algorithms on a large prospective multicenter database in order to transform analytic NGS data into a clinically relevant diagnostic signal. Our collaborative findings suggest the microbial DNA signal identified on NGS may be an independent useful adjunct for the diagnosis of PJI, as well as help identify causative organisms. Further work applying artificial intelligence tools will improve accuracy, predictive power and clinical utility of
Exosomes (exo) are involved in the progression of osteoarthritis (OA). This study aimed to investigate the function of dysfunctional chondrocyte-derived exo (DC-exo) on OA in rats and rat macrophages. Rat-derived chondrocytes were isolated, and DCs induced with interleukin (IL)-1β were used for exo isolation. Rats with OA (n = 36) or macrophages were treated with DC-exo or phosphate-buffered saline (PBS). Macrophage polarization and autophagy, and degradation and chondrocyte activity of cartilage tissues, were examined. RNA sequencing was used to detect genes differentially expressed in DC-exo, followed by RNA pull-down and ribonucleoprotein immunoprecipitation (RIP). Long non-coding RNA osteoarthritis non-coding transcript (OANCT) and phosphoinositide-3-kinase regulatory subunit 5 (PIK3R5) were depleted in DC-exo-treated macrophages and OA rats, in order to observe macrophage polarization and cartilage degradation. The PI3K/AKT/mammalian target of rapamycin (mTOR) pathway activity in cells and tissues was measured using western blot.Aims
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This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic next-generation sequencing (mNGS), and the impact of mNGS on clinical diagnosis and treatment. A retrospective analysis was conducted on 235 patients with BJIs who were treated at our hospital between January 2015 and December 2021. Patients were divided into the no-mNGS group (microbial culture only) and the mNGS group (mNGS testing and microbial culture) based on whether mNGS testing was used or not.Aims
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This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of intervertebral disc degeneration (IDD). The gene expression profile of GSE23130 was downloaded from the Gene Expression Omnibus (GEO) database. Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases, and we used Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to analyze the functions and pathways of EP-DEGs. STRING and Cytoscape were used to construct protein-protein interaction (PPI) networks and identify hub EP-DEGs. NetworkAnalyst was used to analyze transcription factors (TFs) and microRNAs (miRNAs) that regulate hub EP-DEGs. A search of the Drug Signatures Database (DSigDB) for hub EP-DEGs revealed multiple drug molecules and drug-target interactions.Aims
Methods
This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
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Osteoarthritis (OA), one of the most common motor system disorders, is a degenerative disease involving progressive joint destruction caused by a variety of factors. At present, OA has become the fourth most common cause of disability in the world. However, the pathogenesis of OA is complex and has not yet been clarified. Long non-coding RNA (lncRNA) refers to a group of RNAs more than 200 nucleotides in length with limited protein-coding potential, which have a wide range of biological functions including regulating transcriptional patterns and protein activity, as well as binding to form endogenous small interference RNAs (siRNAs) and natural microRNA (miRNA) molecular sponges. In recent years, a large number of lncRNAs have been found to be differentially expressed in a variety of pathological processes of OA, including extracellular matrix (ECM) degradation, synovial inflammation, chondrocyte apoptosis, and angiogenesis. Obviously, lncRNAs play important roles in regulating gene expression, maintaining the phenotype of cartilage and synovial cells, and the stability of the intra-articular environment. This article reviews the results of the latest research into the role of lncRNAs in a variety of pathological processes of OA, in order to provide a new direction for the study of OA pathogenesis and a new target for prevention and treatment. Cite this article:
Metagenomic next-generation sequencing (mNGS) is useful in the diagnosis of infectious disease. However, while it is highly sensitive at identifying bacteria, it does not provide information on the sensitivity of the organisms to antibiotics. The purpose of this study was to determine whether the results of mNGS can be used to guide optimization of culture methods to improve the sensitivity of culture from intraoperative samples. Between July 2014 and October 2019, patients with suspected joint infection (JI) from whom synovial fluid (SF) was obtained preoperatively were enrolled. Preoperative aspirated SF was analyzed by conventional microbial culture and mNGS. In addition to samples taken for conventional microbial culture, some samples were taken for intraoperative culture to optimize the culture method according to the preoperative mNGS results. The demographic characteristics, medical history, laboratory examination, mNGS, and culture results of the patients were recorded, and the possibility of the optimized culture methods improving diagnostic efficiency was evaluated.Aims
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MicroRNAs (miRNAs) are a class of small non-coding RNAs that have emerged as potential predictive, prognostic, and therapeutic biomarkers, relevant to many pathophysiological conditions including limb immobilization, osteoarthritis, sarcopenia, and cachexia. Impaired musculoskeletal homeostasis leads to distinct muscle atrophies. Understanding miRNA involvement in the molecular mechanisms underpinning conditions such as muscle wasting may be critical to developing new strategies to improve patient management. MicroRNAs are powerful post-transcriptional regulators of gene expression in muscle and, importantly, are also detectable in the circulation. MicroRNAs are established modulators of muscle satellite stem cell activation, proliferation, and differentiation, however, there have been limited human studies that investigate miRNAs in muscle wasting. This narrative review summarizes the current knowledge as to the role of miRNAs in the skeletal muscle differentiation and atrophy, synthesizing the findings of published data. Cite this article:
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
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