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Open access

Yan Zhao and Qingshan Liu


In this paper, a continuous-time distributed algorithm is presented to solve a class of decomposable quadratic programming problems. In the quadratic programming, even if the objective function is nonconvex, the algorithm can still perform well under an extra condition combining with the objective, constraint and coupling matrices. Inspired by recent advances in distributed optimization, the proposed continuous-time algorithm described by multi-agent network with consensus is designed and analyzed. In the network, each agent only accesses the local information of its own and from its neighbors, then all the agents in a connected network cooperatively find the optimal solution with consensus.

Open access

Jinwei Luan, Xianglan Li, Rutao Guo, Shanshan Liu, Hongyu Luo and Qingshan You



Next generation sequencing and bio-informatic analyses were conducted to investigate the mechanism of reactivation of p53 and induction of tumor cell apoptosis (RITA)-enhancing X-ray susceptibility in FaDu cells.

Materials and methods

The cDNA was isolated from FaDu cells treated with 0 X-ray, 8 Gy X-ray, or 8 Gy X-ray + RITA. Then, cDNA libraries were created and sequenced using next generation sequencing, and each assay was repeated twice. Subsequently, differentially expressed genes (DEGs) were identified using Cuffdiff in Cufflinks and their functions were predicted by pathway enrichment analyses. Genes that were constantly up- or down-regulated in 8 Gy X-ray-treated FaDu cells and 8 Gy X-ray + RITA-treated FaDu cells were obtained as RITA genes. Afterward, the protein-protein interaction (PPI) relationships were obtained from the STRING database and a PPI network was constructed using Cytoscape. Furthermore, ClueGO was used for pathway enrichment analysis of genes in the PPI network.


Total 2,040 and 297 DEGs were identified in FaDu cells treated with 8 Gy X-ray or 8 Gy X-ray + RITA, respectively. PARP3 and NEIL1 were enriched in base excision repair, and CDK1 was enriched in p53 signaling pathway. RFC2 and EZH2 were identified as RITA genes. In the PPI network, many interaction relationships were identified (e.g., RFC2-CDK1, EZH2-CDK1 and PARP3-EZH2). ClueGO analysis showed that RFC2 and EZH2 were related to cell cycle.


RFC2, EZH2, CDK1, PARP3 and NEIL1 may be associated, and together enhance the susceptibility of FaDu cells treated with RITA to the deleterious effects of X-ray.