Bacterial infection influences genomic stability and integrity by causing DNA damage, which increases the possibility of tumor initiation and development. We aimed to investigate whether Fusobacterium nucleatum, one of the periodontal pathogens, promoted oral squamous cell carcinoma (OSCC) by causing DNA doublestrand break (DSB). Tca8113 tongue squamous cell carcinoma cells were infected with F. nucleatum. The expression of gH2AX was detected by western blots and immunofluorescence. The proliferation and cell cycle alterations were tested by CCK8 and flow cytometry, respectively. The expression levels of Ku70, p53, and p27 were evaluated by quantitative real-time polymerase chain reaction and western blots. A plasmid was used for the overexpression of Ku70 to verify the possible relationship between Ku70 and p53. We confirmed the presence of DSBs in the response to F. nucleatum by detecting the expression of gH2AX. The cell proliferation ability was increased with an accelerated cell cycle while the expression of p27 was decreased. Meanwhile, the expression of Ku70 and wild p53 was downregulated. When Ku70 was overexpressed, the expression of wild p53 in response to F. nucleatum infection was upregulated and cell proliferation was accordingly inhibited. We concluded that F. nucleatum infection promoted the proliferation ability of Tca8113 by causing DNA damage via the Ku70/p53 pathway.

MicroRNAs (miRNAs) are critical for both development and function of the central nervous system. Significant evidence suggests that abnormal expression of miRNAs is associated with neurodevelopmental disorders. MeCP2 protein is an epigenetic regulator repressing or activating gene transcription by binding to methylated DNA. Both loss-of-function and gain-of-function mutations in the MECP2 gene lead to neurodevelopmental disorders such as Rett syndrome, autism and MECP2 duplication syndrome. In this study, we demonstrate that miR-130a inhibits neurite outgrowth and reduces dendritic spine density as well as dendritic complexity. Bioinformatics analyses, cell cultures and biochemical experiments indicate that miR-130a targets MECP2 and down-regulates MeCP2 protein expression. Furthermore, expression of the wild-type MeCP2, but not a loss-of-function mutant, rescues the miR-130a-induced phenotype. Our study uncovers the MECP2 gene as a previous unknown target for miR-130a, supporting that miR-130a may play a role in neurodevelopment by regulating MeCP2. Together with data from other groups, our work suggests that a feedback regulatory mechanism involving both miR-130a and MeCP2 may serve to ensure their appropriate expression and function in neural development.Electronic supplementary materialThe online version of this article (doi:10.1007/s13238-016-0272-7) contains supplementary material, which is available to authorized users.

The effect of chemotherapy drug Mitomycin C (MMC) in combination with recombinant adeno-associated virus II (rAAV2) in cancer therapy was investigated, and the mechanism of MMC affecting rAAV2’s bioactivity was also studied. The combination effect was evaluated by the level of GFP and TNF expression in a human glioma cell line, and the mechanism of MMC effects on rAAV mediated gene expression was investigated by AAV transduction related signal molecules. C57 and BALB/c nude mice were injected with rAAV-EGFP or rAAV-TNF alone, or mixed with MMC, to evaluate the effect of MMC on AAV-mediated gene expression and tumor suppression. MMC was shown to improve the infection activity of rAAV2 both in vitro and in vivo. Enhancement was found to be independent of initial rAAV2 receptor binding stage or subsequent second-strand synthesis of target DNA, but was related to cell cycle retardation followed by blocked genome degradation. In vivo injection of MMC combined with rAAV2 into the tumors of the animals resulted in significant suppression of tumor growth. It was thus demonstrated for the first time that MMC could enhance the expression level of the target gene mediated by rAAV2. The combination of rAAV2 and MMC may be a promising strategy in cancer therapy.

Aiming at the problem that the number and decimal point of digital instruments in substations are prone to misdetection and missed detection, a method of digital meter readings in a substation based on connected domain analysis algorithm is proposed. This method uses Faster R-CNN (Faster Region Convolutional Neural Network) as a positioning network to localize the dial area, and after acquiring the partial image, it enhances the useful information of the digital area. YOLOv4 (You Only Look Once) convolutional neural network is used as the detector to detect the digital area. The purpose is to distinguish the numbers and obtain the digital area that may contain a decimal point or no decimal point at the tail. Combined with the connected domain analysis algorithm, the difference between the number of connected domain categories and the area ratio of the digital area is analyzed, and the judgment of the decimal point is realized. The method reduces the problem of mutual interference among categories when detecting YOLOv4. The experimental results show that the method improves the detection accuracy of the algorithm.

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