Search

To study the influence of different cleaning methods on the corrosion resistance of 316L stainless steel surface, this paper carried out polarisation curves and electrochemical impedance spectroscopy studied on the uncleaned, acid pickling cleaning, and picosecond laser cleaning samples. The surface morphology of the samples after electrochemical testing was detected by laser confocal microscopy and scanning electron microscopy, and then the electrochemical corrosion behaviour of the samples in 3.5% NaCl solution was analysed under different cleaning methods. The results show that compared with the uncleaned sample, the corrosion potential of the sample after picosecond laser cleaning was relatively improved. At this time, the corrosion current density was as low as 2.29 × 10–6 A/cm2, the polarisation resistance value was as high as 18615 Ω·cm2, the impedance modulus was as high as 5.5 × 105 Ω, and the capacitance-impedance radius reached the maximum value. In conclusion, the corrosion resistance of the sample after picosecond laser cleaning was better. [ABSTRACT FROM AUTHOR]

Long non-coding RNA (lncRNA) is a type of non-protein-coding RNA with a length of at least 200 nucleotides. Existing evidence shows that lncRNA affects the growth and development of humans and the occurrence of diseases through various mechanisms, and plays an irreplaceable role in the differentiation and activation of immune cells and the development process of autoim-mune diseases. In recent years, lncRNA H19 has been found to play a unique regulatory function in pathological processes related to autoimmune diseases, such as inflammation and fibrosis. Therefore, the molecular mechanism involved in H19 is expected to become a potential target for the treatment of autoimmune diseases. In this review, we discussed the related mechanisms of H19 involved in the pathogenesis of autoimmune diseases based on the known functions of H19 and summarized the research results of H19 in several common autoimmune diseases. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects several organs and causes variable clinical symptoms. Exploring new insights on genetic factors may help reveal SLE etiology and improve the survival of SLE patients. The current study is designed to identify key genes involved in SLE and develop potential diagnostic biomarkers for SLE in clinical practice. Expression data of all genes of SLE and control samples in GSE65391 and GSE72509 datasets were downloaded from the Gene Expression Omnibus (GEO) database. A total of 11 accurate differentially expressed genes (DEGs) were identified by the "limma" and "RobustRankAggreg" R package. All these genes were functionally associated with several immune-related biological processes and a single KEGG (Kyoto Encyclopedia of Genes and Genome) pathway of necroptosis. The PPI analysis showed that IFI44, IFI44L, EIF2AK2, IFIT3, IFITM3, ZBP1, TRIM22, PRIC285, XAF1, and PARP9 could interact with each other. In addition, the expression patterns of these DEGs were found to be consistent in GSE39088. Moreover, Receiver operating characteristic (ROC) curves analysis indicated that all these DEGs could serve as potential diagnostic biomarkers according to the area under the ROC curve (AUC) values. Furthermore, we constructed the transcription factor (TF)-diagnostic biomarker-microRNA (miRNA) network composed of 278 nodes and 405 edges, and a drug-diagnostic biomarker network consisting of 218 nodes and 459 edges. To investigate the relationship between diagnostic biomarkers and the immune system, we evaluated the immune infiltration landscape of SLE and control samples from GSE6539. Finally, using a variety of machine learning methods, IFI44 was determined to be the optimal diagnostic biomarker of SLE and then verified by quantitative real-time PCR (qRT-PCR) in an independent cohort. Our findings may benefit the diagnosis of patients with SLE and guide in developing novel targeted therapy in treating SLE patients. [ABSTRACT FROM AUTHOR]