This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.

Blood loss after total knee arthroplasty (TKA) is a potentially serious medical problem since it leads to anemia, increased need for transfusion, and prolonged hospitalization. Some studies have reported that sealing of the intramedullary femoral canal during TKA may decrease postoperative blood loss. The purpose of this study is to determine the effects of sealing of the intramedullary femoral canal during TKA on blood loss and transfusion rate. Electronic databases, PubMed, EMBASE, the Cochrane Library, Web of Science, and Chinese Biomedical Database, were systematically searched. Only randomized controlled trials (RCTs) that compared the sealing group with the control group during TKA were included up to March 2019. Two reviewers independently extracted data and assessed the quality of included studies. The statistical analysis was performed by using Review Manager 5.3 software. Cochrane Risk of Bias tool was used for quality assessment. Overall, eight RCTs involving 996 patients met our criteria and were analyzed. The results of meta-analysis showed that patients in the sealed group had less total blood loss, less total drain output and less hidden blood loss, less transfusion rates, a lower drop of hemoglobin level at day 1 postoperatively, and less hematoma than the control group. On the other hand, there were no significant differences in infection, deep vein thrombosis, and redness of incision between sealed and control group. Current meta-analysis found that sealing the femoral canal during TKA was an effective method for the control of blood loss.

ObjectiveOsteosarcoma (OS), the most common malignant bone tumor, is prone to early metastasis and recurrence, resulting in poor prognosis. The purpose of this study was to investigate gene expression in OS samples, and to study the relationship between tumor infiltrating immune cells (TIICS) in the tumor microenvironment and the occurrence, development, and prognosis of OS. MethodsIntegrated analysis was performed on the gene expression profile of OS samples in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and normal muscle tissue samples in the Genotype-Tissue Expression (GTEx) database. Screening of differentially expressed genes in OS samples and healthy muscle tissue samples was performed using R software. Functional annotation and pathway enrichment analyses were performed, a protein-protein interaction network was constructed, and the Hub genes were screened. The infiltration differences of 22 TIICs in OS samples and normal muscle tissue samples were analyzed using CIBERSORT. ROC curve, and OS survival analyses were performed on the Hub genes and 22 TIICs. The correlation between Hub genes with prognostic value and the 22 TIICs was discussed. ResultsTen Hub genes were screened. OS and normal muscle tissue samples were compared. Significant differences were observed in the infiltration of follicular helper T cells, resting NK cells, plasma cells, activated CD4 memory T cells, gamma delta T cells, monocytes, M0 macrophages and resting dendritic cells (P<0.05). ROC curve analysis showed that the area under the curve (AUC) for the 10 hub genes was 0.9 ~ 1.0, and for naive B cells (AUC=0.942), plasma cells (AUC=0.999), follicular T helper cells (AUC=0.814), resting NK cells (AUC=0.864), monocytes (AUC=0.987), and M0 macrophages (AUC=0.995). Kaplan-Meier curves revealed positive correlation between the expression levels of TNNI2, TTN, ACTN3, TNNC2, MYL3, and survival of OS patients. Correlation analysis revealed close association between ACTN3, TNNI2, TNNC2, MYL3, TTN, and the infiltration of M0 macrophages and plasma cells. ConclusionOur findings provide a theoretical basis for further study of the molecular mechanisms underlying OS development and occurrence. It serves as a reference for the development of new diagnostics, identification of prognostic biomarkers, and targeted drug therapy for OS.