【Abstract】 Objective To explore the biomechanical properties of a new intramedullary controlled dynamicnail ing (ICDN). Methods Ten pairs of specimens of adult femurs, with the age of 18 to 55 years, were divided into twogroups (groups A1 and B2, n=10). The length of the specimens was (438 ± 10) mm , and the external diameter was (26.4 ± 1.5) mm. The specimens of the two groups were osteotomized transversely after the biomechanical test. ICDNs and GK nails were randomly implanted into the femurs, respectively (groups A2 and B2). Torsional, bending and axial compressive tests were made in each group, and the effect of dynamic compression between the fracture fragments was tested. Results The resistance to compression of groups A1, B1, A2 and B2 were (0.19 ± 0.18) × 106, (0.22 ± 0.12) × 106, (1.67 ± 0.68) × 106 and (0.86 ± 0.32) × 106 N/mm, respectively. There was statistically significant difference between groups A2 and B2 (P lt; 0.01). The bending stiffnesses of coronal section of groups A1, B1, A2 and B2 were (0.94 ± 0.25) × 103, (1.10 ± 0.21) × 103, (0.70 ± 0.22) × 103, (0.64 ± 0.21) × 103 N/mm, respectively. The bending stiffness of sagittal plane of groups A1, B1, A2 and B2 were (1.06 ± 0.26) × 103, (0.96 ± 0.25) × 103, (0.67 ± 0.25) × 103, (0.61 ± 0.18) × 103 N/mm, respectively. There were no statistically significant differences between groups A1 and B1 or between groups A2 and B2 (P gt; 0.05). When the torque was 5 Nm, the torsional stiffness of groups A1, B1, A2 and B2 were (4.00 ± 2.54), (4.76 ± 1.93), (0.50 ± 0.63), (0.35 ± 0.31) Nm/°, respectively. When the torque was8 Nm, the torsional stiffness of groups A1, B1, A2 and B2 were (4.30 ± 3.27), (3.94 ± 2.01), (0.42 ± 0.52), (0.36 ± 0.18) Nm/°, respectively. There were statistically significant differences between groups A1 and A2 or between groups B1 and B2 (P lt; 0.05), and no statistically significant difference between between groups A2 and B2 (P gt; 0.05). The average maximal pressure generated between the fracture fragments which were fixed with ICDN was 21.6 N, and the pressure between the fracture fragments which were fixed with GK nail ing could not be tested. Conclusion The design of ICDN conforms to the special anatomical structure of the femur. ICDN could provide a completely different structure, a different fixation principal and a more balancedfixation than GK nail. ICDN incorporates the flexible and rigid fixation, which is l ikely to be the trend of the fracture fixation.
Objective To identify genes of lipopolysaccharide (LPS) -induced acute lung injury (ALI) in mice base on bioinformatics and machine learning. Methods The acute lung injury dataset (GSE2411, GSE111241 and GSE18341) were download from the Gene Expression Database (GEO). Differential gene expression analysis was conducted. Gene ontology (GO) analysis, KEGG pathway analysis, GSEA enrichment analysis and protein-protein interaction analysis (PPI) network analysis were performed. LASSO-COX regression analysis and Support Vector Machine Expression Elimination (SVM-RFE) was utilized to identify key biomarkers. Receiver operator characteristic curve was used to evaluate the diagnostic ability. Validation was performed in GSE18341. Finally, CIBERSORT was used to analyze the composition of immune cells, and immunocorrelation analysis of biomarkers was performed. Results A total of 29 intersection DEGs were obtained after the intersection of GSE2411 and GSE111241 differentially expressed genes. Enrichment analysis showed that differential genes were mainly involved in interleukin-17, cytokine - cytokine receptor interaction, tumor necrosis factor and NOD-like receptor signaling pathways. Machine learning combined with PPI identified Gpx2 and Ifi44 were key biomarkers. Gpx2 is a marker of ferroptosis and Ifi44 is an type I interferon-induced protein, both of which are involved in immune regulation. Immunocorrelation analysis showed that Gpx2 and Ifi44 were highly correlated with Neutrophils, TH17 and M1 macrophage cells. Conclusion Gpx2 and Ifi44 have potential immunomodulatory abilities, and may be potential biomarkers for predicting and treating ALI in mince.