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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The biomembrane (induced membrane) formed around polymethylmethacrylate (PMMA) spacers has value in clinical applications for bone defect reconstruction. Few studies have evaluated its cellular, molecular or stem cell features. Our objective was to characterise induced membrane morphology, molecular features and osteogenic stem cell characteristics. Following Institutional Review Board approval, biomembrane specimens were obtained from 12 patient surgeries for management of segmental bony defects (mean patient age 40.7 years, standard deviation 14.4). Biomembranes from nine tibias and three femurs were processed for morphologic, molecular or stem cell analyses. Gene expression was determined using the Affymetrix GeneChip Operating Software (GCOS). Molecular analyses compared biomembrane gene expression patterns with a mineralising osteoblast culture, and gene expression in specimens with longer spacer duration (> 12 weeks) with specimens with shorter durations. Statistical analyses used the unpaired student Objectives
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