Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA. Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.Aims
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Accurate identification of the ankle joint centre is critical for estimating tibial coronal alignment in total knee arthroplasty (TKA). The purpose of the current study was to leverage artificial intelligence (AI) to determine the accuracy and effect of using different radiological anatomical landmarks to quantify mechanical alignment in relation to a traditionally defined radiological ankle centre. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A sub-cohort of 250 radiographs were annotated for landmarks relevant to knee alignment and used to train a deep learning (U-Net) workflow for angle calculation on the entire database. The radiological ankle centre was defined as the midpoint of the superior talus edge/tibial plafond. Knee alignment (hip-knee-ankle angle) was compared against 1) midpoint of the most prominent malleoli points, 2) midpoint of the soft-tissue overlying malleoli, and 3) midpoint of the soft-tissue sulcus above the malleoli.Aims
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This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.Aims
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The Postgraduate Medical Education and Training Board wants either ‘run through’ or ‘uncoupled’ orthopaedic training to be adopted throughout the United Kingdom but it is not willing to let both continue together as is the current situation. This
In comparing or assessing methods of treatment it is vital that the appropriate number of patients is selected in order to ensure that the conclusions drawn are statistically viable. This
The Canadian Orthopaedic Trauma Society was started in an endeavour to answer the difficult problem of obtaining enough patients to perform top-quality research into fractures. By maintaining a high standard, including randomised study design, inclusivity, open discussion among surgeons and excellent long-term follow-up, this group has become a leader in the orthopaedic research community. This
John Kirkup, the distinguished orthopaedic surgeon and archivist recently published a book describing the history of amputation. This
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Invasive group A streptococcus (iGAS) is the most common cause of monomicrobial necrotising fasciitis. Necrotising infections of the extremities may present directly to orthopaedic surgeons or by reference from another admitting specialty. Recent epidemiological data from the Health Protection Agency suggest an increasing incidence of iGAS infection in England. Almost 40% of those affected had no predisposing illnesses or risk factors, and the proportion of children presenting with infections has risen. These observations have prompted the Chief Medical Officer for the Central Alerting System in England to write to general practitioners and hospitals, highlighting the need for clinical vigilance, early diagnosis and rapid initiation of treatment in suspected cases. The purpose of this
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. 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 next-generation sequencing and bioinformatics.Aims
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The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an anteroposterior pelvic radiograph deep learning system for diagnosing DDH in children and analyze the feasibility of its application. In total, 10,219 anteroposterior pelvic radiographs were retrospectively collected from April 2014 to December 2018. Clinicians labelled each radiograph using a uniform standard method. Radiographs were grouped according to age and into ‘dislocation’ (dislocation and subluxation) and ‘non-dislocation’ (normal cases and those with dysplasia of the acetabulum) groups based on clinical diagnosis. The deep learning system was trained and optimized using 9,081 radiographs; 1,138 test radiographs were then used to compare the diagnoses made by deep learning system and clinicians. The accuracy of the deep learning system was determined using a receiver operating characteristic curve, and the consistency of acetabular index measurements was evaluated using Bland-Altman plots.Aims
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Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method. We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap) based on the high-throughput datasets.Aims
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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. High-throughput sequencing was used to identify genes that were differentially expressed in hip joint capsules between healthy controls and DDH patients. Biological assays including cell cycle, viability, apoptosis, immunofluorescence, reverse transcription polymerase chain reaction (RT-PCR), and western blotting were performed to determine the roles of the differentially expressed genes in DDH pathology.Aims
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The present study investigates the effectiveness of platelet-rich plasma (PRP) gel without adjunct to induce cartilage regeneration in large osteochondral defects in a rabbit model. A bilateral osteochondral defect was created in the femoral trochlear groove of 14 New Zealand white rabbits. The right knees were filled with PRP gel and the contralateral knees remained untreated and served as control sides. Some animals were killed at week 3 and others at week 12 postoperatively. The joints were harvested and assessed by Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) MRI scoring system, and examined using the International Cartilage Repair Society (ICRS) macroscopic and ICRS histological scoring systems. Additionally, the collagen type II content was evaluated by the immunohistochemical staining.Aims
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This study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network. Expression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs.Aims
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