Aims. Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. Methods. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP)
Aims. 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. Methods. 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
Aims. Degenerative cervical spondylosis (DCS) is a common musculoskeletal disease that encompasses a wide range of progressive degenerative changes and affects all components of the cervical spine. DCS imposes very large social and economic burdens. However, its genetic basis remains elusive. Methods. Predicted whole-blood and skeletal muscle gene expression and genome-wide association study (GWAS) data from a DCS database were integrated, and functional summary-based imputation (FUSION) software was used on the integrated data. A transcriptome-wide association study (TWAS) was conducted using FUSION software to assess the association between predicted gene expression and DCS risk. The TWAS-identified genes were verified via comparison with differentially expressed genes (DEGs) in DCS RNA expression profiles in the Gene Expression Omnibus (GEO) (Accession Number: GSE153761). The Functional Mapping and
Aims. 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. Methods. 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. Results. A total of 807 ion features were identified for KBD and OA, including 577 positive (240 for upregulated and 337 for downregulated) and 230 negative (107 for upregulated and 123 for downregulated) ions. After
Tennis elbow (lateral epicondylitis or lateral elbow tendinopathy) is a self-limiting condition in most patients. Surgery is often offered to patients who fail to improve with conservative treatment. However, there is no evidence to support the superiority of surgery over continued nonoperative care or no treatment. New evidence also suggests that the prognosis of tennis elbow is not influenced by the duration of symptoms, and that there is a 50% probability of recovery every three to four months. This finding challenges the belief that failed nonoperative care is an indication for surgery. In this
Aims. This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of intervertebral disc degeneration (IDD). Methods. 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
Aims. Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined
Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this
Initial treatment of traumatic spinal cord injury remains as controversial in 2023 as it was in the early 19th century, when Sir Astley Cooper and Sir Charles Bell debated the merits or otherwise of surgery to relieve cord compression. There has been a lack of high-class evidence for early surgery, despite which expeditious intervention has become the surgical norm. This evidence deficit has been progressively addressed in the last decade and more modern statistical methods have been used to clarify some of the issues, which is demonstrated by the results of the SCI-POEM trial. However, there has never been a properly conducted trial of surgery versus active conservative care. As a result, it is still not known whether early surgery or active physiological management of the unstable injured spinal cord offers the better chance for recovery. Surgeons who care for patients with traumatic spinal cord injuries in the acute setting should be aware of the arguments on all sides of the debate, a summary of which this
Aims. Osteoarthritis (OA) is the most prevalent joint disease. However, the specific and definitive genetic mechanisms of OA are still unclear. Methods. Tissue-related transcriptome-wide association studies (TWAS) of hip OA and knee OA were performed utilizing the genome-wide association study (GWAS) data of hip OA and knee OA (including 2,396 hospital-diagnosed hip OA patients versus 9,593 controls, and 4,462 hospital-diagnosed knee OA patients versus 17,885 controls) and gene expression reference to skeletal muscle and blood. The OA-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the messenger RNA (mRNA) expression profiles of hip OA and knee OA. Functional enrichment and
Cell therapies hold significant promise for the treatment of injured or diseased musculoskeletal tissues. However, despite advances in research, there is growing concern about the increasing number of clinical centres around the world that are making unwarranted claims or are performing risky biological procedures. Such providers have been known to recommend, prescribe, or deliver so called ‘stem cell’ preparations without sufficient data to support their true content and efficacy. In this
Aim. Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Patients and Methods. Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for
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
Methods
This study evaluates the association between consultant and hospital volume and the risk of re-revision and 90-day mortality following first-time revision of primary hip arthroplasty for aseptic loosening. We conducted a cohort study of first-time, single-stage revision hip arthroplasties (RHAs) performed for aseptic loosening and recorded in the National Joint Registry (NJR) data for England, Wales, Northern Ireland, and the Isle of Man between 2003 and 2019. Patient identifiers were used to link records to national mortality data, and to NJR data to identify subsequent re-revision procedures. Multivariable Cox proportional hazard models with restricted cubic splines were used to define associations between volume and outcome.Aims
Methods
This study describes the variation in the annual volumes of revision hip arthroplasty (RHA) undertaken by consultant surgeons nationally, and the rate of accrual of RHA and corresponding primary hip arthroplasty (PHA) volume for new consultants entering practice. National Joint Registry (NJR) data for England, Wales, Northern Ireland, and the Isle of Man were received for 84,816 RHAs and 818,979 PHAs recorded between April 2011 and December 2019. RHA data comprised all revision procedures, including first-time revisions of PHA and any subsequent re-revisions recorded in public and private healthcare organizations. Annual procedure volumes undertaken by the responsible consultant surgeon in the 12 months prior to every index procedure were determined. We identified a cohort of ‘new’ HA consultants who commenced practice from 2012 and describe their rate of accrual of PHA and RHA experience.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
Methods
Acute bone and joint infections in children are serious, and misdiagnosis can threaten limb and life. Most young children who present acutely with pain, limping, and/or loss of function have transient synovitis, which will resolve spontaneously within a few days. A minority will have a bone or joint infection. Clinicians are faced with a diagnostic challenge: children with transient synovitis can safely be sent home, but children with bone and joint infection require urgent treatment to avoid complications. Clinicians often respond to this challenge by using a series of rudimentary decision support tools, based on clinical, haematological, and biochemical parameters, to differentiate childhood osteoarticular infection from other diagnoses. However, these tools were developed without methodological expertise in diagnostic accuracy and do not consider the importance of imaging (ultrasound scan and MRI). There is wide variation in clinical practice with regard to the indications, choice, sequence, and timing of imaging. This variation is most likely due to the lack of evidence concerning the role of imaging in acute bone and joint infection in children. We describe the first steps of a large UK multicentre study, funded by the National Institute for Health Research, which seeks to integrate definitively the role of imaging into a decision support tool, developed with the assistance of individuals with expertise in the development of clinical prediction tools. Cite this article:
We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.Aims
Methods
The aim of this study was to investigate the global and local impact of fat on bone in obesity by using the diet-induced obese (DIO) mouse model. In this study, we generated a diet-induced mouse model of obesity to conduct lipidomic and 3D imaging assessments of bone marrow fat, and evaluated the correlated bone adaptation indices and bone mechanical properties.Aims
Methods
Impaired fracture repair in patients with type 2 diabetes mellitus (T2DM) is not fully understood. In this study, we aimed to characterize the local changes in gene expression (GE) associated with diabetic fracture. We used an unbiased approach to compare GE in the fracture callus of Zucker diabetic fatty (ZDF) rats relative to wild-type (WT) littermates at three weeks following femoral osteotomy. Zucker rats, WT and homozygous for leptin receptor mutation (ZDF), were fed a moderately high-fat diet to induce T2DM only in the ZDF animals. At ten weeks of age, open femoral fractures were simulated using a unilateral osteotomy stabilized with an external fixator. At three weeks post-surgery, the fractured femur from each animal was retrieved for analysis. Callus formation and the extent of healing were assessed by radiograph and histology. Bone tissue was processed for total RNA extraction and messenger RNA (mRNA) sequencing (mRNA-Seq).Aims
Methods
Current diagnostic tools are not always able to effectively identify periprosthetic joint infections (PJIs). Recent studies suggest that circulating microRNAs (miRNAs) undergo changes under pathological conditions such as infection. The aim of this study was to analyze miRNA expression in hip arthroplasty PJI patients. This was a prospective pilot study, including 24 patients divided into three groups, with eight patients each undergoing revision of their hip arthroplasty due to aseptic reasons, and low- and high-grade PJI, respectively. The number of intraoperative samples and the incidence of positive cultures were recorded for each patient. Additionally, venous blood samples and periarticular tissue samples were collected from each patient to determine miRNA expressions between the groups. MiRNA screening was performed by small RNA-sequencing using the miRNA next generation sequencing (NGS) discovery (miND) pipeline.Aims
Methods
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:
This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.Aims
Methods
To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment. Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue.Aims
Methods
Rheumatoid arthritis (RA) is a common chronic immune disease. Berberine, as its main active ingredient, was also contained in a variety of medicinal plants such as Berberaceae, Buttercup, and Rutaceae, which are widely used in digestive system diseases in traditional Chinese medicine with anti-inflammatory and antibacterial effects. The aims of this article were to explore the therapeutic effect and mechanism of berberine on rheumatoid arthritis. Cell Counting Kit-8 was used to evaluate the effect of berberine on the proliferation of RA fibroblast-like synoviocyte (RA-FLS) cells. The effect of berberine on matrix metalloproteinase (MMP)-1, MMP-3, receptor activator of nuclear factor kappa-Β ligand (RANKL), tumour necrosis factor alpha (TNF-α), and other factors was determined by enzyme-linked immunoassay (ELISA) kit. Transcriptome technology was used to screen related pathways and the potential targets after berberine treatment, which were verified by reverse transcription-polymerase chain reaction (RT-qPCR) and Western blot (WB) technology.Aims
Methods
This study aimed to explore the role of small colony variants (SCVs) of A PJI diagnosis was made according to the MusculoSkeletal Infection Society (MSIS) for PJI. Bone and tissue samples were collected intraoperatively and the intracellular invasion and intraosseous colonization were detected. Transcriptomics of PJI samples were analyzed and verified by polymerase chain reaction (PCR).Aims
Methods
This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms. We analyzed microarray data from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA), machine learning, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify common genetic factors between POMP and sarcopenia. Further validation was done via differential gene expression in a new cohort. Single-cell analysis identified high expression cell subsets, with mononuclear macrophages in osteoporosis and muscle stem cells in sarcopenia, among others. A competitive endogenous RNA network suggested regulatory elements for these genes.Aims
Methods
The rationale for exacting restoration of skeletal anatomy after unstable ankle fracture is to improve outcomes by reducing complications from malunion; however, current definitions of malunion lack confirmatory clinical evidence. Radiological (absolute radiological measurements aided by computer software) and clinical (clinical interpretation of radiographs) definitions of malunion were compared within the Ankle Injury Management (AIM) trial cohort, including people aged ≥ 60 years with an unstable ankle fracture. Linear regressions were used to explore the relationship between radiological malunion (RM) at six months and changes in function at three years. Function was assessed with the Olerud-Molander Ankle Score (OMAS), with a minimal clinically important difference set as six points, as per the AIM trial. Piecewise linear models were used to investigate new radiological thresholds which better explain symptom impact on ankle function.Aims
Methods
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
Methods
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
Methods
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
Methods
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
Methods
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
Methods
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
Methods
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
Methods
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
Methods
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
The aim of this study was to identify key pathological genes in osteoarthritis (OA). We searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis.Objectives
Methods
In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs.Objectives
Methods
Diabetes mellitus (DM) is known to impair fracture healing. Increasing evidence suggests that some microRNA (miRNA) is involved in the pathophysiology of diabetes and its complications. We hypothesized that the functions of miRNA and changes to their patterns of expression may be implicated in the pathogenesis of impaired fracture healing in DM. Closed transverse fractures were created in the femurs of 116 rats, with half assigned to the DM group and half assigned to the control group. Rats with DM were induced by a single intraperitoneal injection of streptozotocin. At post-fracture days five, seven, 11, 14, 21, and 28, miRNA was extracted from the newly generated tissue at the fracture site. Microarray analysis was performed with miRNA samples from each group on post-fracture days five and 11. For further analysis, real-time polymerase chain reaction (PCR) analysis was performed at each timepoint.Objectives
Methods
Wear of polyethylene inserts plays an important role in failure
of total knee replacement and can be monitored Before revision, the minimum joint space width values and their
locations on the insert were measured in 15 fully weight-bearing
radiographs. These measurements were compared with the actual minimum
thickness values and locations of the retrieved tibial inserts after
revision. Introduction
Method
Fractures of the proximal femur are one of the
greatest challenges facing the medical community, constituting a
heavy socioeconomic burden worldwide. Controversy exists regarding
the optimal treatment for independent patients with displaced intracapsular fractures
of the proximal femur. The recognised alternatives are hemiarthroplasty
and total hip replacement. At present there is no established standard
of care, with both types of arthroplasty being used in many centres.
The principal advantages of total hip replacement are a functional
benefit over hemiarthroplasty and a reduced risk of revision surgery.
The principal criticism is the increased risk of dislocation. We
believe that an alternative acetabular component may reduce the
risk of dislocation but still provide the functional benefit of
total hip replacement in these patients. We therefore propose to
investigate the dislocation risk of a dual-mobility acetabular component
compared with standard polyethylene component in total hip replacement
for independent patients with displaced intracapsular fractures
of the proximal femur within the framework of the larger WHiTE (Warwick
Hip Trauma Evaluation) Comprehensive Cohort Study. Cite this article:
Guidelines for the management of patients with metastatic bone
disease (MBD) have been available to the orthopaedic community for
more than a decade, with little improvement in service provision
to this increasingly large patient group. Improvements in adjuvant
and neo-adjuvant treatments have increased both the number and overall
survival of patients living with MBD. As a consequence the incidence
of complications of MBD presenting to surgeons has increased and
is set to increase further. The British Orthopaedic Oncology Society
(BOOS) are to publish more revised detailed guidelines on what represents
‘best practice’ in managing patients with MBD. This article is designed
to coincide with and publicise new BOOS guidelines and once again
champion the cause of patients with MBD. A series of short cases highlight common errors frequently being
made in managing patients with MBD despite the availability of guidelines.Objectives
Methods
