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In the present study, effect of ultrasonic impact treatment (UIT) on the microstructural characterization and mechanical properties of 316L stainless steel (hereinafter referred to as 316L) was investigated experimentally. The fatigue fracture mechanism of 316L before and after UIT was revealed. The experimental results indicated that the martensitic grain size induced at the impact edge was about 2.00 Å. The surface modified 316L formed a gradient nanostructure and induced a martensitic phase transformation. The hardness of the surface layer of the modified 316L was twice the hardness of its matrix. The tensile strengths of 316L before and after UIT were 576 MPa and 703 MPa, respectively. The stretching stripes of 316L were more disordered after UIT. The fatigue strengths of 316L before and after UIT were 267 MPa and 327 MPa, respectively. The fatigue cracking of 316L started from the austenite grain boundaries. The fatigue fracture surface was relatively rough. The fatigue crack sources of the modified 316L came from internal inclusions. The inclusions were oxides dominated by SiO2. As the stress range increased, the crack initiation site migrated to the interior and the fatigue fracture surface became flatter. [ABSTRACT FROM AUTHOR]

The present research focused on identifying necroptosis‐related differentially expressed genes (NRDEGs) in spinal cord injury (SCI) to highlight potential therapeutic and prognostic target genes in clinical SCI. Three SCI‐related datasets were downloaded, including GSE151371, GSE5296 and GSE47681. MSigDB and KEGG datasets were searched for necroptosis‐related genes (NRGs). Differentially expressed genes (DEGs) and NRGs were intersected to obtain NRDEGs. The MCC algorithm was employed to select the first 10 genes as hub genes. A protein–protein interaction (PPI) network related to NRDEGs was developed utilizing STRING. Several databases were searched to predict interactions between hub genes and miRNAs, transcription factors, potential drugs, and small molecules. Immunoassays were performed to identify DEGs using CIBERSORTx. Additionally, qRT‐PCR was carried out to verify NRDEGs in an animal model of SCI. Combined analysis of all datasets identified 15 co‐expressed DEGs and NRGs. GO and KEGG pathway analyses highlighted DEGs mostly belonged to pathways associated with necroptosis and apoptosis. Hub gene expression analysis showed high accuracy in SCI diagnosis was associated with the expression of CHMP7 and FADD. A total of two hub genes, i.e. CHMP7, FADD, were considered potential targets for SCI therapy. [ABSTRACT FROM AUTHOR]