Biofilm infections are among the most challenging complications in orthopaedics, as bacteria within the biofilms are protected from the host immune system and many antibiotics. Halicin exhibits broad-spectrum activity against many planktonic bacteria, and previous studies have demonstrated that halicin is also effective against
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This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA. Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization.Aims
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Extracellular vesicles (EVs) are nanoparticles secreted by all cells, enriched in proteins, lipids, and nucleic acids related to cell-to-cell communication and vital components of cell-based therapies. Mesenchymal stromal cell (MSC)-derived EVs have been studied as an alternative for osteoarthritis (OA) treatment. However, their clinical translation is hindered by industrial and regulatory challenges. In contrast, platelet-derived EVs might reach clinics faster since platelet concentrates, such as platelet lysates (PL), are already used in therapeutics. Hence, we aimed to test the therapeutic potential of PL-derived extracellular vesicles (pEVs) as a new treatment for OA, which is a degenerative joint disease of articular cartilage and does not have any curative or regenerative treatment, by comparing its effects to those of human umbilical cord MSC-derived EVs (cEVs) on an ex vivo OA-induced model using human cartilage explants. pEVs and cEVs were isolated by size exclusion chromatography (SEC) and physically characterized by nanoparticle tracking analysis (NTA), protein content, and purity. OA conditions were induced in human cartilage explants (10 ng/ml oncostatin M and 2 ng/ml tumour necrosis factor alpha (TNFα)) and treated with 1 × 109 particles of pEVs or cEVs for 14 days. Then, DNA, glycosaminoglycans (GAG), and collagen content were quantified, and a histological study was performed. EV uptake was monitored using PKH26 labelled EVs.Aims
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Lumbar spinal stenosis (LSS) is a common skeletal system disease that has been partly attributed to genetic variation. However, the correlation between genetic variation and pathological changes in LSS is insufficient, and it is difficult to provide a reference for the early diagnosis and treatment of the disease. We conducted a transcriptome-wide association study (TWAS) of spinal canal stenosis by integrating genome-wide association study summary statistics (including 661 cases and 178,065 controls) derived from Biobank Japan, and pre-computed gene expression weights of skeletal muscle and whole blood implemented in FUSION software. To verify the TWAS results, the candidate genes were furthered compared with messenger RNA (mRNA) expression profiles of LSS to screen for common genes. Finally, Metascape software was used to perform enrichment analysis of the candidate genes and common genes.Aims
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Spinopelvic characteristics influence the hip’s biomechanical behaviour. However, to date there is little knowledge defining what ‘normal’ spinopelvic characteristics are. This study aims to determine how static spinopelvic characteristics change with age and ethnicity among asymptomatic, healthy individuals. This systematic review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines to identify English studies, including ≥ 18-year-old participants, without evidence of hip or spine pathology or a history of previous surgery or interventional treatment, documenting lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), and pelvic incidence (PI). From a total of 2,543 articles retrieved after the initial database search, 61 articles were eventually selected for data extraction.Aims
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The optimal choice of management for proximal humerus fractures (PHFs) has been increasingly discussed in the literature, and this work aimed to answer the following questions: 1) what are the incidence rates of PHF in the geriatric population in the USA; 2) what is the mortality rate after PHF in the elderly population, specifically for distinct treatment procedures; and 3) what factors influence the mortality rate? PHFs occurring between 1 January 2009 and 31 December 2019 were identified from the Medicare physician service records. Incidence rates were determined, mortality rates were calculated, and semiparametric Cox regression was applied, incorporating 23 demographic, clinical, and socioeconomic covariates, to compare the mortality risk between treatments.Aims
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Osteoarthritis (OA) is a common degenerative joint disease worldwide, which is characterized by articular cartilage lesions. With more understanding of the disease, OA is considered to be a disorder of the whole joint. However, molecular communication within and between tissues during the disease process is still unclear. In this study, we used transcriptome data to reveal crosstalk between different tissues in OA. We used four groups of transcription profiles acquired from the Gene Expression Omnibus database, including articular cartilage, meniscus, synovium, and subchondral bone, to screen differentially expressed genes during OA. Potential crosstalk between tissues was depicted by ligand-receptor pairs.Aims
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Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers.Aims
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Currently, the effect of drug treatment for osteoporosis is relatively poor, and the side effects are numerous and serious. Melatonin is a potential drug to improve bone mass in postmenopausal women. Unfortunately, the mechanism by which melatonin improves bone metabolism remains unclear. The aim of this study was to further investigate the potential mechanism of melatonin in the treatment of osteoporosis. The effects of melatonin on mitochondrial apoptosis protein, bmal1 gene, and related pathway proteins of RAW264.7 (mouse mononuclear macrophage leukaemia cells) were analyzed by western blot. Cell Counting Kit-8 was used to evaluate the effect of melatonin on cell viability. Flow cytometry was used to evaluate the effect of melatonin on the apoptosis of RAW264.7 cells and mitochondrial membrane potential. A reactive oxygen species (ROS) detection kit was used to evaluate the level of ROS in osteoclast precursors. We used bmal1-small interfering RNAs (siRNAs) to downregulate the Aims
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To investigate the optimal thresholds and diagnostic efficacy of commonly used serological and synovial fluid detection indexes for diagnosing periprosthetic joint infection (PJI) in patients who have rheumatoid arthritis (RA). The data from 348 patients who had RA or osteoarthritis (OA) and had previously undergone a total knee (TKA) and/or a total hip arthroplasty (THA) (including RA-PJI: 60 cases, RA-non-PJI: 80 cases; OA-PJI: 104 cases, OA-non-PJI: 104 cases) were retrospectively analyzed. A receiver operating characteristic curve was used to determine the optimal thresholds of the CRP, ESR, synovial fluid white blood cell count (WBC), and polymorphonuclear neutrophil percentage (PMN%) for diagnosing RA-PJI and OA-PJI. The diagnostic efficacy was evaluated by comparing the area under the curve (AUC) of each index and applying the results of the combined index diagnostic test.Aims
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This study was performed to explore the effect of melatonin on pyroptosis in nucleus pulposus cells (NPCs) and the underlying mechanism of that effect. This experiment included three patients diagnosed with lumbar disc herniation who failed conservative treatment. Nucleus pulposus tissue was isolated from these patients when they underwent surgical intervention, and primary NPCs were isolated and cultured. Western blotting, reverse transcription polymerase chain reaction, fluorescence staining, and other methods were used to detect changes in related signalling pathways and the ability of cells to resist pyroptosis.Aims
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Focal knee arthroplasty is an attractive alternative to knee arthroplasty for young patients because it allows preservation of a large amount of bone for potential revisions. However, the mechanical behaviour of cartilage has not yet been investigated because it is challenging to evaluate in vivo contact areas, pressure, and deformations from metal implants. Therefore, this study aimed to determine the contact pressure in the tibiofemoral joint with a focal knee arthroplasty using a finite element model. The mechanical behaviour of the cartilage surrounding a metal implant was evaluated using finite element analysis. We modelled focal knee arthroplasty with placement flush, 0.5 mm deep, or protruding 0.5 mm with regard to the level of the surrounding cartilage. We compared contact stress and pressure for bone, implant, and cartilage under static loading conditions.Aims
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This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated. A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification accuracy was calculated separately for each subcategory (reinfection, tissue and implant condition, non-human cells, and morbidity of the patient). Fleiss’ kappa and Cohen’s kappa were calculated for interobserver and intraobserver reliability, respectively.Aims
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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
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This study aimed to determine the expression and clinical significance of a cartilage protein, cartilage oligomeric matrix protein (COMP), in knee osteoarthritis (OA) patients. A total of 270 knee OA patients and 93 healthy controls were recruited. COMP messenger RNA (mRNA) and protein levels in serum, synovial fluid, synovial tissue, and fibroblast-like synoviocytes (FLSs) of knee OA patients were determined using enzyme-linked immunosorbent assay, real-time polymerase chain reaction, and immunohistochemistry.Aims
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CRP is an acute-phase protein that is used as a biomarker to follow severity and progression in infectious and inflammatory diseases. Its pathophysiological mechanisms of action are still poorly defined. CRP in its pentameric form exhibits weak anti-inflammatory activity. The monomeric isoform (mCRP) exerts potent proinflammatory properties in chondrocytes, endothelial cells, and leucocytes. No data exist regarding mCRP effects in human intervertebral disc (IVD) cells. This work aimed to verify the pathophysiological relevance of mCRP in the aetiology and/or progression of IVD degeneration. We investigated the effects of mCRP and the signalling pathways that are involved in cultured human primary annulus fibrosus (AF) cells and in the human nucleus pulposus (NP) immortalized cell line HNPSV-1. We determined messenger RNA (mRNA) and protein levels of relevant factors involved in inflammatory responses, by quantitative real-time polymerase chain reaction (RT-qPCR) and western blot. We also studied the presence of mCRP in human AF and NP tissues by immunohistochemistry.Aims
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The aim of this investigation was to compare risk of infection in both cemented and uncemented hemiarthroplasty (HA) as well as in total hip arthroplasty (THA) following femoral neck fracture. Data collection was performed using the German Arthroplasty Registry (EPRD). In HA and THA following femoral neck fracture, fixation method was divided into cemented and uncemented prostheses and paired according to age, sex, BMI, and the Elixhauser Comorbidity Index using Mahalanobis distance matching.Aims
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The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article:
