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Introduction and Objective: Endothelial progenitor cells (EPCs) have been proven to exhibit a therapeutic effect in deep vein thrombosis, but are susceptible to microenvironment. Besides, Matrine has promotive effects on EPCs, but its effects on microRNA (miR)-126 remain obscure, which are therefore discussed in the study. Methods: The cultured EPCs were extracted from Sprague-Dawley rats and identified by immunofluorescence assay. After being treated with Matrine or transfected with miR-126b inhibitor and small interfering RNA targeting forkhead box (FOXO) 4, the viability and apoptosis of EPCs were determined by cell counting kit-8 assay and flow cytometry. The migration, invasion, and tube formation abilities were detected by scratch, Transwell, and tube formation assays. The target genes of miR-126b were predicted by TargetScan, and verified by dual-luciferase reporter assay. The expressions of miR-126b, FOXO4, matrix metalloproteinase (MMP) 2, MMP9, and vascular endothelial growth factor (VEGF) A were determined by quantitative real-time polymerase chain reaction and Western blot. Results: The EPCs were successfully extracted and cultured, as evidenced by positive reaction cluster of differentiation (CD) 34 and CD133. Matrine promoted the viability, migration, invasion, and tube formation while inhibiting the apoptosis of EPCs, and upregulated the expression of miR-126b. Besides, miR-126b inhibitor reversed the effects of Matrine on EPCs and downregulated the expression levels of MMP2, MMP9, and VEGFA. MiR-126b targeted the FOXO4, and siFOXO4 reversed the abovementioned effects of miR-126b inhibitor on EPCs. Conclusion: Matrine protects EPCs from apoptosis and promotes their migration, invasion, and tube formation abilities via regulating miR-126b/FOXO4 axis. [ABSTRACT FROM AUTHOR]

Device-level power electronic circuit simulation is so cumbersome that engineers are forced to make model simplification or reduce circuit size to obtain a reasonable execution time for repeated simulation runs. This paper proposes a massive-thread parallel simulation of large-scale power electronic circuits employing device-level modeling on the graphics processors (GPUs) to obtain higher data throughput and lower execution times. Parallel massive-thread modules are proposed for the nonlinear physics-based insulated gate bipolar transistor and power diode components. The nonlinear solution algorithm comprised of Newton–Raphson iterations and partial LU decomposition is fully parallelized on the GPU. Furthermore, the commonly used behavioral model with reduced computational complexity is also employed to represent the switches. The developed simulation codes are used to run large-scale test cases of the modular multilevel converter (MMC) system. The accuracy and efficiency of the GPU-based parallel simulation are compared with sequential CPU-based codes and the SaberRD program to show the advantages of the parallelized simulation; execution time speedups of 15 times and 70 times are reported for the MMC system using the nonlinear physics-based modeling and behavior-based modeling, respectively. [ABSTRACT FROM AUTHOR]

The electromagnetic transient (EMT) simulation of a large-scale power system consumes so much computational power that parallel programming techniques are urgently needed in this area. For example, realistic-sized power systems include thousands of buses, generators, and transmission lines. Massive-thread computing is one of the key developments that can increase the EMT computational capabilities substantially when the processing unit has enough hardware cores. Compared to the traditional CPU, the graphic-processing unit (GPU) has many more cores with distributed memory which can offer higher data throughput. This paper proposes a massive-thread EMT program (MT-EMTP) and develops massive-thread parallel modules for linear passive elements, the universal line model, and the universal machine model for offline EMT simulation. An efficient node-mapping structure is proposed to transform the original power system admittance matrix into a block-node diagonal sparse format to exploit the massive-thread parallel GPU architecture. The developed MT-EMTP program has been tested on large-scale power systems of up to 2458 three-phase buses with detailed component modeling. The simulation results and execution times are compared with mainstream commercial software, EMTP-RV, to show the improvement in performance with equivalent accuracy. [ABSTRACT FROM AUTHOR]

This paper proposes large-scale transient stability simulation based on the massively parallel architecture of multiple graphics processing units (GPUs). A robust and efficient instantaneous relaxation (IR)-based parallel processing technique which features implicit integration, full Newton iteration, and sparse LU-based linear solver is used to run the multiple GPUs simultaneously. This implementation highlights the combination of coarse-grained algorithm-level parallelism with fine-grained data-parallelism of the GPUs to accelerate large-scale transient stability simulation. Multithreaded parallel programming makes the entire implementation highly transparent, scalable, and efficient. Several large test systems are used for the simulation with a maximum size of 9,984 buses and 2,560 synchronous generators all modeled in detail resulting in matrices that are larger than 20\,000\times 20\,000. [ABSTRACT FROM AUTHOR]

To investigate the cellular target selectivity of small molecules targeting thioredoxin reductase 1, we reported the construction and functional research of a stable TrxR1 gene (encode thioredoxin reductase 1) knockout HCT-116 cell line. We designed and selected TrxR1 knockout sites according to the TrxR1 gene sequence and CRISPR/Cas9 target designing principles. SgRNA oligos based on the selected TrxR1 knockout sites were obtained. Next, we constructed knockout plasmid by cloning the sgRNA into the pCasCMV-Puro-U6 vector. After transfection of the plasmid into HCT-116 cells, TrxR1 knockout HCT-116 cells were selected using puromycin resistance. The TrxR1 knockout efficiency was identified and verified by DNA sequencing, immunoblotting, TRFS-green fluorescent probe, and cellular TrxR1 enzyme activity detection. Finally, the correlation between TrxR1 expression and cellular effects of drugs specifically targeting TrxR1 was investigated by CCK-8 assay. The results demonstrated that the knockout plasmid expressing the sgRNA effectively knocked-out TrxR1 gene within HCT-116 cells, and no expression of TrxR1 protein could be observed in stable TrxR1 knockout HCT-116 (HCT116- TrxR1 -KO) cells. The TrxR1-targeting inhibitor auranofin did not show any inhibitory activity against either cellular TrxR1 enzyme activity or cell proliferation. Based on these results, we conclude that a stable TrxR1 gene knockout HCT-116 cell line was obtained through CRISPR/Cas9 techniques, which may facilitate investigating the role of TrxR1 in various diseases.