The number of revision arthroplasties being performed in the elderly is expected to rise, including revision for infection. The primary aim of this study was to measure the treatment success rate for octogenarians undergoing revision total hip arthroplasty (THA) for periprosthetic joint infection (PJI) compared to a younger cohort. Secondary outcomes were complications and mortality. Patients undergoing one- or two-stage revision of a primary THA for PJI between January 2008 and January 2021 were identified. Age, sex, BMI, American Society of Anesthesiologists grade, Charlson Comorbidity Index (CCI), McPherson systemic host grade, and causative organism were collated for all patients. PJI was classified as ‘confirmed’, ‘likely’, or ‘unlikely’ according to the 2021 European Bone and Joint Infection Society criteria. Primary outcomes were complications, reoperation, re-revision, and successful treatment of PJI. A total of 37 patients aged 80 years or older and 120 patients aged under 80 years were identified. The octogenarian group had a significantly lower BMI and significantly higher CCI and McPherson systemic host grades compared to the younger cohort.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
Methods
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
Circular RNA (circRNA) is involved in the regulation of articular cartilage degeneration induced by inflammatory factors or oxidative stress. In a previous study, we found that the expression of Minus RNA sequencing, fluorescence in situ hybridization, and quantitative real-time polymerase chain reaction (qRT-PCR) were used to detect the expression of 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
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The December 2022 Research Roundup360 looks at: Halicin is effective against
To explore the synovial expression of mucin 1 (MUC1) and its role in rheumatoid arthritis (RA), as well as the possible downstream mechanisms. Patients with qualified synovium samples were recruited from a RA cohort. Synovium from patients diagnosed as non-inflammatory orthopaedic arthropathies was obtained as control. The expression and localization of MUC1 in synovium and fibroblast-like synoviocytes were assessed by immunohistochemistry and immunofluorescence. Small interfering RNA and MUC1 inhibitor GO-203 were adopted for inhibition of MUC1. Lysophosphatidic acid (LPA) was used as an activator of Rho-associated pathway. Expression of inflammatory cytokines, cell migration, and invasion were evaluated using quantitative real-time polymerase chain reaction (PCR) and Transwell chamber assay.Aims
Methods
To investigate the correlations among cytokines and regulatory T cells (T-regs) in ankylosing spondylitis (AS) patients, and their changes after anti-tumour necrosis factor-α (TNF-α) treatment. We included 72 AS patients with detailed medical records, disease activity score (Bath Ankylosing Spondylitis Disease Activity Index), functional index (Bath Ankylosing Spondylitis Functional Index), and laboratory data (interleukin (IL)-2, IL-4, IL-10, TNF-α, interferon (IFN)-γ, transforming growth factor (TGF)-β, ESR, and CRP). Their peripheral blood mononuclear cells (PBMCs) were marked with anti-CD4, anti-CD25, and anti-FoxP3 antibodies, and triple positive T cells were gated by flow cytometry as T-regs. Their correlations were calculated and the changes after anti-TNF-α therapy were compared.Aims
Methods
Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.Aims
Methods
The aim of this study was to evaluate the association between chondral injury and interval from anterior cruciate ligament (ACL) tear to surgical reconstruction (ACLr). Between January 2012 and January 2022, 1,840 consecutive ACLrs were performed and included in a single-centre retrospective cohort. Exclusion criteria were partial tears, multiligament knee injuries, prior ipsilateral knee surgery, concomitant unicompartmental knee arthroplasty or high tibial osteotomy, ACL agenesis, and unknown date of tear. A total of 1,317 patients were included in the final analysis, with a median age of 29 years (interquartile range (IQR) 23 to 38). The median preoperative Tegner Activity Score (TAS) was 6 (IQR 6 to 7). Patients were categorized into four groups according to the delay to ACLr: < three months (427; 32%), three to six months (388; 29%), > six to 12 months (248; 19%), and > 12 months (254; 19%). Chondral injury was assessed during arthroscopy using the International Cartilage Regeneration and Joint Preservation Society classification, and its association with delay to ACLr was analyzed using multivariable analysis.Aims
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 next-generation sequencing for
detecting organisms in synovial fluid. Materials and Methods. In this prospective, single-blinded study, 86 anonymized samples
of synovial fluid were obtained from patients undergoing aspiration
of the hip or knee as part of the investigation of a periprosthetic
infection. A panel of synovial fluid tests, including levels of
C-reactive protein, human neutrophil elastase, total neutrophil
count, alpha-defensin, and culture were performed prior to next-generation
sequencing. Results. Of these 86 samples, 30 were alpha-defensin-positive and culture-positive
(Group I), 24 were alpha-defensin-positive and culture-negative
(Group II) and 32 were alpha-defensin-negative and culture-negative
(Group III). Next-generation sequencing was concordant with 25 results
for Group I. In four of these, it detected antibiotic resistant bacteria
whereas culture did not. In another four samples with relatively
low levels of inflammatory
The aim of this study was to identify factors associated with five-year cancer-related mortality in patients with limb and trunk soft-tissue sarcoma (STS) and develop and validate machine learning algorithms in order to predict five-year cancer-related mortality in these patients. Demographic, clinicopathological, and treatment variables of limb and trunk STS patients in the Surveillance, Epidemiology, and End Results Program (SEER) database from 2004 to 2017 were analyzed. Multivariable logistic regression was used to determine factors significantly associated with five-year cancer-related mortality. Various machine learning models were developed and compared using area under the curve (AUC), calibration, and decision curve analysis. The model that performed best on the SEER testing data was further assessed to determine the variables most important in its predictive capacity. This model was externally validated using our institutional dataset.Aims
Methods
Long non-coding RNAs (lncRNAs) act as crucial regulators in osteoporosis (OP). Nonetheless, the effects and potential molecular mechanism of lncRNA PCBP1 Antisense RNA 1 (PCBP1-AS1) on OP remain largely unclear. The aim of this study was to explore the role of lncRNA PCBP1-AS1 in the pathogenesis of OP. Using quantitative real-time polymerase chain reaction (qRT-PCR), osteogenesis-related genes (alkaline phosphatase (ALP), osteocalcin (OCN), osteopontin (OPN), and Runt-related transcription factor 2 (RUNX2)), PCBP1-AS1, microRNA (miR)-126-5p, group I Pak family member p21-activated kinase 2 (PAK2), and their relative expression levels were determined. Western blotting was used to examine the expression of PAK2 protein. Cell Counting Kit-8 (CCK-8) assay was used to measure cell proliferation. To examine the osteogenic differentiation, Alizarin red along with ALP staining was used. RNA immunoprecipitation assay and bioinformatics analysis, as well as a dual-luciferase reporter, were used to study the association between PCBP1-AS1, PAK2, and miR-126-5p.Aims
Methods
Astragalus polysaccharide (APS) participates in various processes, such as the enhancement of immunity and inhibition of tumours. APS can affect osteoporosis (OP) by regulating the osteogenic differentiation of human bone mesenchymal stem cells (hBMSCs). This study was designed to elucidate the mechanism of APS in hBMSC proliferation and osteoblast differentiation. Reverse transcriptase polymerase chain reaction (RT-PCR) and Western blotting were performed to determine the expression of microRNA (miR)-760 and ankyrin repeat and FYVE domain containing 1 (ANKFY1) in OP tissues and hBMSCs. Cell viability was measured using the Cell Counting Kit-8 assay. The expression of cyclin D1 and osteogenic marker genes (osteocalcin (OCN), alkaline phosphatase (ALP), and runt-related transcription factor 2 (RUNX2)) was evaluated using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Mineral deposits were detected through Alizarin Red S staining. In addition, Western blotting was performed to detect the ANKFY1 protein levels following the regulation of miR-760. The relationship between miR-760 and ANKFY1 was determined using a luciferase reporter assay.Aims
Methods
This study aimed to assess the risk of acute kidney injury (AKI) associated with combined intravenous (IV) and topical antibiotic therapy in patients undergoing treatment for periprosthetic joint infections (PJIs) following total knee arthroplasty (TKA), utilizing the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for classification. We conducted a retrospective analysis of 162 knees (162 patients) that received treatment for PJI post-TKA with combined IV and topical antibiotic infusions at a single academic hospital from 1 January 2010 to 31 December 2022. The incidence of AKI was evaluated using the KDIGO criteria, focussing on the identification of significant predictors and the temporal pattern of AKI development.Aims
Methods
The preventive effects of bisphosphonates on articular cartilage in non-arthritic joints are unclear. This study aimed to investigate the effects of oral bisphosphonates on the rate of joint space narrowing in the non-arthritic hip. We retrospectively reviewed standing whole-leg radiographs from patients who underwent knee arthroplasties from 2012 to 2020 at our institute. Patients with previous hip surgery, Kellgren–Lawrence grade ≥ II hip osteoarthritis, hip dysplasia, or rheumatoid arthritis were excluded. The rate of hip joint space narrowing was measured in 398 patients (796 hips), and the effects of the use of bisphosphonates were examined using the multivariate regression model and the propensity score matching (1:2) model.Aims
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