Objectives. The objective of this study was to assess the association between whole body sagittal
To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology.Aims
Methods
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
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
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
Non-coding microRNA (miRNA) in extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs) may promote neuronal repair after spinal cord injury (SCI). In this paper we report on the effects of MSC-EV-microRNA-381 (miR-381) in a rodent model of SCI. In the current study, the luciferase assay confirmed a binding site of bromodomain-containing protein 4 (BRD4) and Wnt family member 5A (WNT5A). Then we detected expression of miR-381, BRD4, and WNT5A in dorsal root ganglia (DRG) cells treated with MSC-isolated EVs and measured neuron apoptosis in culture by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining. A rat model of SCI was established to detect the in vivo effect of miR-381 and MSC-EVs on SCI.Aims
Methods