The goal was to evaluate tibiofemoral knee joint kinematics during stair descent, by simulating the full stair descent motion in vitro. The knee joint kinematics were evaluated for two types of knee implants: bi-cruciate retaining and bi-cruciate stabilized. It was hypothesized that the bi-cruciate retaining implant better approximates native kinematics. The in vitro study included 20 specimens which were tested during a full stair descent with physiological muscle forces in a dynamic knee rig. Laxity envelopes were measured by applying external loading conditions in varus/valgus and internal/external direction.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
Osteoporosis is a chronic disease. The aim of this study was to identify key genes in osteoporosis. Microarray data sets GSE56815 and GSE56814, comprising 67 osteoporosis blood samples and 62 control blood samples, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in osteoporosis using Limma package (3.2.1) and Meta-MA packages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify biological functions. Furthermore, the transcriptional regulatory network was established between the top 20 DEGs and transcriptional factors using the UCSC ENCODE Genome Browser. Receiver operating characteristic (ROC) analysis was applied to investigate the diagnostic value of several DEGs.Objectives
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