22 research outputs found

    catena-Poly[[[diaqua­cobalt(II)]bis­(μ-1,3-di-4-pyridylpropane-κ2 N:N′)] bis­(perchlorate) bis­(1,3-di-4-pyridyl­propane) bis­(2-methyl-4-nitro­aniline)]

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    In the title compound, {[Co(C13H14N2)2(H2O)2](ClO4)2·2C13H14N2·2C7H8N2O2}n, the CoII ion lies on a crystallographic inversion center and is coordinated by four N atoms from four symmetry-related 1,3-di-4-pyridylpropane ligands and two O atoms from two water ligands in a slightly distorted octa­hedral coordination environment. The 1,3-di-4-pyridylpropane ligands are doubly bridging and connect the CoII ions into one-dimensional chains. The asymmetric unit also contains one uncoordinated 1,3-di-4-pyridylpropane mol­ecule, one 2-methyl-4-nitro­aniline mol­ecule and one perchlorate anion. In the crystal structure, inter­molecular O—H⋯N hydrogen bonds connect the one-dimensional chains into a two-dimensional network

    HOXA-AS2 Promotes Proliferation and Induces Epithelial-Mesenchymal Transition via the miR-520c-3p/GPC3 Axis in Hepatocellular Carcinoma

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    Background/Aims: Previous studies have demonstrated that long non-coding RNAs (lncRNAs) may play critical roles in cancer biology, including Hepatocellular carcinoma (HCC). The HOXA cluster antisense RNA2 (HOXA-AS2) lncRNA plays an important role in carcinogenesis, however, the underlying role of HOXA-AS2 in HCC remains unknown. The present study examined the effects of HOXA-AS2 on the progression of HCC, and explored the underlying molecular mechanisms. Methods: Quantitative real-time PCR was used to detect HOXA-AS2 expression in HCC tissues and cell lines. Furthermore, the effects of HOXA-AS2 silencing and overexpression on cell proliferation, cell cycle, apoptosis, migration, and invasion were assessed in HCC in vitro and in vivo. Furthermore, bioinformatics online programs predicted and luciferase reporter assay were used to validate the association of HOXA-AS2 and miR-520c-3p in HCC cells. Results: We observed that HOXA-AS2 was up-regulated in HCC tissues and cell lines. In vitro experiments revealed that HOXA-AS2 knockdown significantly inhibited HCC cells proliferation by causing G1 arrest and promoting apoptosis, whereas HOXA-AS2 overexpression promoted cell growth. Further functional assays indicated that HOXA-AS2 significantly promoted HCC cell migration and invasion by promoting EMT. Bioinformatics online programs predicted that HOXA-AS2 sponge miR-520c-3p at 3’-UTR with complementary binding sites, which was validated using luciferase reporter assay. HOXA-AS2 could negatively regulate the expression of miR-520c-3p in HCC cells. MiR-520c-3p was down-regulated and inversely correlated with HOXA-AS2 expression in HCC tissues. miR-520c-3p suppressed cell proliferation, invasion and migration in HCC cells, and enforced expression of miR-520c-3p attenuated the oncogenic effects of HOXA-AS2 in HCC cells. By bioinformatic analysis and dual-luciferase reporter assay, we found that miR-223-3p directly targeted the 3’-untranslated region (UTR) of Glypican-3 (GPC3), one of the key players in HCC. GPC3 was up-regulated in HCC tissues, and was negatively correlated with miR-520c-3p expression and positively correlated with HOXA-AS2 expression. Conclusion: In summary, our results suggested that the HOXA-AS2/miR-520c-3p/GPC3 axis may play an important role in the regulation of PTC progression, which could serve as a biomarker and therapeutic target for HCC

    Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics

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    PurposeThis study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS).MethodsThe MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge. Randomized splitting was used to divide the data into training and validation sets using a ratio of 7:3. Two radiologists used the 3D-slicer software to label the lesions on brain diffusion-weighted (DWI) MRI sequences. Radiomics features were extracted from the annotated images using the pyradiomics software package, and the features were filtered using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Four machine learning algorithms, logistic regression (LR), Support Vector Classification (SVC), LightGBM, and Random forest (RF), were used to construct a recurrence prediction model. For each algorithm, three models were constructed based on the MRI radiomics features, clinical features, and combined MRI radiomics and clinical features. The sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to compare the predictive efficacy of the models.ResultsTwenty features were selected from 1,037 radiomics features extracted from DWI images. The LightGBM model based on data with three different features achieved the best prediction accuracy from all 4 models in the validation set. The LightGBM model based solely on radiomics features achieved a sensitivity, specificity, and AUC of 0.65, 0.671, and 0.647, respectively, and the model based on clinical data achieved a sensitivity, specificity, and AUC of 0.7, 0.799, 0.735, respectively. The sensitivity, specificity, and AUC of the LightGBM model base on both radiomics and clinical features achieved the best performance with a sensitivity, specificity, and AUC of 0.85, 0.805, 0.789, respectively.ConclusionThe ischemic stroke recurrence prediction model based on LightGBM achieved the best prediction of recurrence within 1 year following an AIS. The combination of MRI radiomics features and clinical data improved the prediction performance of the model

    Effects of Welding Heat Input on Microstructure and Electrochemical Behavior of Flux-Cored Arc-Welded Q690 HSLA Steel

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    In this work, the weld metal (WM) for the Q690 high-strength low-alloy (HSLA) steel was prepared through flux-cored arc welding (FCAW) at 10 kJ/cm and 20 kJ/cm heat inputs. The effect of welding heat input on the relationship between the microstructural factors and the electrochemical behavior of the FCAW Q690 steel was studied. Due to the fine grain and acicular ferrite affected by the 10 kJ/cm low heat input, the WM presented similar electrochemical behavior to the Q690 base metal, which would minimize the risk of galvanic corrosion. Also, at 20 kJ/cm of high welding heat input, the WM with higher-sized bainite structure was prone to galvanic corrosion risk minimization

    Microstructure Evolution and Mechanical Properties of Underwater Dry and Local Dry Cavity Welded Joints of 690 MPa Grade High Strength Steel

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    Q690E high strength low alloy (HSLA) steel plays an important role in offshore structures. In addition, underwater local cavity welding (ULCW) technique was widely used to repair important offshore constructions. However, the high cooling rate of ULCW joints results in bad welding quality compared with underwater dry welding (UDW) joints. Q690E high strength low alloy steels were welded by multi-pass UDW and ULCW techniques, to study the microstructural evolution and mechanical properties of underwater welded joints. The microstructure and fracture morphology of welded joints were observed by scanning electron microscope and optical microscope. The elemental distribution in the microstructure was determined with an Electron Probe Microanalyzer. The results indicated that the microstructure of both two welded joints was similar. However, martensite and martensite-austenite components were significantly different with different underwater welding methods such that the micro-hardness of the HAZ and FZ in the ULCW specimen was higher than that of the corresponding regions in UDW joint. The yield strength and ultimate tensile strength of the ULCW specimen are 109 MPa lower and 77 MPa lower, respectively, than those of the UDW joint. The impact toughness of the UDW joint was superior to those of the ULCW joint

    Effect of Mixed Rare Earths on the Wetting Behavior and Interfacial Reaction between Sn-0.70Cu-0.05Ni Solder and Amorphous Fe

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    In order to explore the effect of addition of mixed rare earths (MRE) on the wetting behavior and interfacial reaction between Sn-0.70Cu-0.05Ni solder and amorphous Fe84.3Si10.3B5.4 alloy, 0.25 wt.% percentage of the MRE, which are mainly elements La and Ce, were added into the solder. Results show it can refine the microstructure of the solder alloy, and there is limited change of melting temperature with the addition of MRE in the solder. The wettability of the solder on amorphous substrate is improved by adding 0.25 wt.% percentage of the MRE into Sn-0.70Cu-0.05Ni solder. Moreover, research results indicate that, with the increase of wetting temperature, the final equilibrium wetting angles of Sn-0.70Cu-0.05Ni and Sn-0.70Cu-0.05Ni-0.25MRE on amorphous substrate decrease gradually, indicating the better wettability at the higher wetting temperature. In addition, with the increase of temperature, the distribution of intermetallic compound (IMC) FeSn2 formed at the interface between the two solders and amorphous substrate is changed from discontinuous state to continuous state. The thickness of the interfacial IMC layer between solder and amorphous substrates reduced with the addition of MRE, indicating that the presence of 0.25 wt.% percentage of the MRE is effective in suppressing the growth of IMC layer

    Effects of TiO

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    Series of overlay flux-cored wires with different content of TiO2 were fabricated, and different claddings of high-manganese steel are welded by flux cored arc welding (FCAW). The influences of TiO2 addition on the electrochemical behaviour of the FCAW claddings over a high-manganese steel were studied. The results demonstrate that all the LPR values of the overlay welded claddings are higher than that of the base metal. However, the LPR values did not increase with the addition of TiO2. The EIS simulation results indicate that the addition of titanium dioxide improves the corrosion resistance of the high-manganese steel cladding, and the trends of the Rp values is highly consistent with the change of LRP value. At the same time, the grain refinement was achieved by the TiO2 addition. In conclusion, the proper content of the titanium dioxide in high-manganese steel cladding contributes to its high LRP and Rp values, in this paper, the suitable content of the TiO2 addition is 20g (0.2wt.%)
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