BackgroundQuiescin Q6 sulfhydryl oxidase 2 (QSOX2), an enzyme that can be directly secreted into the extracellular space, is known to be associated with oxidative protein folding. However, whether QSOX2 is abnormally expressed in non-small cell lung cancer (NSCLC) and its role in tumor growth remains unclear.MethodsReal-time quantitative PCR (qPCR), immunohistochemistry (IHC), bioinformatics analyses were applied to analyze the expression pattern and prognostic significance of QSOX2 in NSCLC. Xenografts model, enzyme-linked immunosorbent assays (ELISA), western blot analysis (WB), and IHC were preformed to examine in vivo tumor suppression and intracellular and extracellular expression of QSOX2. Flow cytometry, WB and qPCR analyses were used to elucidate the role of QSOX2 in cell cycle regulation. Chromatin immunoprecipitation assay (ChIP) assay and Dual-Luciferase reporter assay were employed to investigate transcriptional regulation of QSOX2 by E2F Transcription Factor 1 (E2F1).ResultsQuiescin sulfhydryl oxidase 2 was significantly overexpressed in NSCLC and associated with poor survival in advanced-stage patients. The intracellular and extracellular expression of QSOX2 by tumor cells markedly decreased after anti-cancer therapy in vitro, in vivo and in the clinic. Moreover, QSOX2 silencing in NSCLC cell lines resulted in inhibition of cancer cell proliferation, induction of apoptosis, and decreased expression of cell division-related genes (CENPF and NUSAP1) and Wnt pathway activators (PRRX2 and Nuc-β-catenin). Mechanistically, QSOX2 was expressed periodically during cell cycle and directly regulated by E2F1.ConclusionsOur findings demonstrate that QSOX2 is directly regulated by E2F1 in the cell cycle, which is essential for the proliferation of NSCLC cells. Furthermore, QSOX2 is a prognostic indicator for NSCLC and may be developed into a biomarker for monitoring tumor burden and therapeutic progress.
The long non-coding RNA (lncRNA) H19 acts as a competitive endogenous RNA (ceRNA) of miR-29b-3p and has been reported to exert pro-tumorigenic roles in several cancer types.However, the role of lncRNA H19 in lung cancer is not fully understood. Here, we investigated the role of the lncRNA H19/microRNA-29b-3p (miR-29b-3p)/high mobility group box 1 (HMGB1) signaling pathway in lung cancer cell growth using 293T, NCI-H1975, Calu-3 and 2BS cell lines. Cell viability was determined using a cell counting kit-8 (CCK-8) assay, while apoptosis and cell cycle distribution were assessed by flow cytometry. Cell migration was detected using a wound healing assay. Cell invasion was evaluated by transwell assay. The expression of lncRNA H19, miR-29b-3p, HMGB1, toll-like receptor 4 (TLR4), and matrix metallopeptidase 9 (MMP-9) was measured by fluorescence quantitative PCR or western blotting. We demonstrated that miR-29b-3p could directly bind to both lncRNA H19 and HMGB1 by dual-luciferase reporter assay. Three shRNAs targeting lncRNA H19 (shlncRNA H19) were designed, and shlncRNA H19-2 was selected to investigate the function of lncRNA H19 in tumor cell biology. Compared with controls, lung cancer cells expressing shlncRNA H19 exhibited decreased proliferation, cell-cycle arrest at the G1 phase, increased levels of cell apoptosis, and reduced migration and invasion. Moreover, shlncRNA H19 upregulated the expression of miR-29b-3p and reduced the protein expression of HMGB1, TLR4, and MMP-9 in lung cancer cells. Together, our data indicate that the lncRNA H19/miRNA-29b-3p/HMGB1 signaling axis is involved in the regulation of lung cancer cell growth.
In this paper, a three-dimensional axial symmetrical model of laser cutting is established by adopting N–S equation and shearing-stress transport k-ω turbulent model. Numerical simulation is carried out to analyze the flow field of shield gas inside a cut kerf; the results include velocity and pressure distribution and mass flow rate. The effects of oxidation on flow field are examined, and the formation of gas flow separation and vortex are predicted. The results show that the gas flow structure in the kerf is directly affected by the reaction between iron and oxygen in the case of laser-oxygen cutting.
Recycling scrap metal is an important way to protect the ecological environment. Design effective yet efficient techniques to automatically identify recyclable scrap metals is an important task within this topic. Due to the advantages of fast response and high accuracy, laser-induced breakdown spectroscopy (LIBS) recently played an important role in the mineral identification. However, the identification accuracy of peak-seeking is greatly affected by the data quality of the LIBS spectrum, whereas machine learning methods may be greatly affected by the number of training data. By considering the above open issues, this paper proposes a hybrid algorithm based on support vector machine (SVM) and element peak-seeking. By investing the identified difference of the major element (with the largest composition in the alloy) and the general element (with composition more than 1% in the alloy) between peak-seeking and SVM, three integration types (i.e., rejection, partial acceptance, complete acceptance) are defined. The final recognition result is generated according to different integration types and the corresponding integration methods. To verify the feasibility of the proposed approach, a simulated alloy LIBS database was established based on 31 metal elements and the simulated alloy LIBS data according to their compositions. Comparing with the result obtained by only using SVM, the proposed method greatly improved the recognition accuracy. The accuracy of identifying all general elements increased from 8% to 74.5%. Experimental results confirmed the effectiveness of the proposed method in identification of general metal elements in terms of higher detection accuracy.
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