Correction to: miR-3928v is induced by HBx via NF-κB/EGR1 and contributes to hepatocellular carcinoma malignancy by down-regulating VDAC3.

An amendment to this paper has been published and can be accessed via the original article.

INPP1 up-regulation by miR-27a contributes to the growth, migration and invasion of human cervical cancer.

Inositol polyphosphate-1-phosphatase (INPP1) is an enzyme that is responsible for glycolysis and lipid metabolism. Here, we discovered that INPP1 expression was up-regulated in CC tissues compared to that in adjacent normal tissues by RT-qPCR. Inositol polyphosphate-1-phosphatase overexpression promoted and INPP1 knockdown suppressed cell viability, cellular migration/invasion and EMT in CC cells. To explore the mechanism of dysregulation, INPP1 was predicted to be a target of miR-27a, and a pmiRGLO dual-luciferase reporter assay showed that miR-27a bound to the 3' UTR of INPP1. RT-qPCR revealed that miR-27a was also up-regulated and had a positive correlation with INPP1 expression in CC tissues. Furthermore, shR-INPP1 could favour the malignant phenotype reversion induced by miR-27a, suggesting that miR-27a up-regulates INPP1 to promote tumorigenic activities. Altogether, our findings show that the up-regulation of INPP1 by miR-27a contributes to tumorigenic activities and may provide a potential biomarker for CC.

Purification and characterization of novel thermostable and Ca-independent α-amylase produced by Bacillus amyloliquefaciens BH072.

In the present study, a novel α-amylase produced by Bacillus amyloliquefaciens BH072 was purified and characterized. The molecular weight of purified α-amylase was approximately 68 kDa, determined by Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) and ten amino acid of N-terminal was NSGLNGYLTH. The kinetic parameters Km and Vmax were 4.27 ±â€¯0.21 mg/mL and 987.34 ±â€¯23.34 U/mg, respectively. Purified α-amylase showed maximal activity at pH 7 and 60 °C. Enzyme remained stable in pH range 6.0-7.0 and 50-80 °C. The activity of the α-amylase was Ca2+ independent and stability in the presence of surfactant, oxidizing and bleaching agents. The ß-mercaptoethanol and EDTA greatly enhanced and reduced α-amylase activity, respectively. This enzyme has high hydrolysis rate toward corn, wheat and potato starch and hydrolyzes soluble starch to glucose, maltose, maltotriose and maltotetraose, indicating that the α-amylase represents a promising candidate for applications in the food industry.

miR-3928v is induced by HBx via NF-κB/EGR1 and contributes to hepatocellular carcinoma malignancy by down-regulating VDAC3.

BACKGROUND: Hepatitis B virus (HBV) plays a critical role in the tumorigenic behavior of human hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) have been reported to participate in HCC development via the regulation of their target genes. However, HBV-modulated miRNAs involved in tumorigenesis remain to be identified. Here, we found that a novel highly expressed miRNA, TLRC-m0008_3p (miR-3928v), may be an important factor that promotes the malignancy of HBV-related HCC. METHODS: Solexa sequencing was applied to profile miRNAs, and RT-qPCR was used to identify and quantitate miRNAs. We studied miR-3928v function in HCC cell lines by MTT, colony formation, migration/invasion, and vascular mimicry (VM) assays in vitro and by a xenograft tumor model in vivo. Finally, we predicted and verified the target gene of miR-3928v by a reporter assay, studied the function of this target gene, and cloned the promoter of miR-3928v and the transcription factor for use in dual-luciferase reporter assays and EMSAs. RESULTS: A variant of miR-3928 (miR-3928v) was identified and found to be highly expressed in HBV (+) HCC tissues. Voltage-dependent anion channel 3 (VDAC3) was validated as a target of miR-3928v and found to mediate the effects of miR-3928v in promoting HCC growth and migration/invasion. Furthermore, HBx protein increased early growth response 1 (EGR1) expression and facilitated its translocation into the nucleus to enhance miR-3928v promoter activity in an NF-κB signaling-dependent manner. CONCLUSIONS: miR-3928v is induced by HBx through the NF-κB/EGR1 signaling pathway and down-regulates the tumor suppressor gene VDAC3 to accelerate the progression of HCC.

Transcriptomic profiling of long non-coding RNAs in hepatitis B virus-related hepatocellular carcinoma.

Long non-coding RNAs (lncRNAs) have been reported to be involved in the development and progression of hepatocellular carcinoma (HCC). However, few studies have focus on the dyregulation and the role of lncRNAs in HBV-related HCC. We performed a comprehensive analysis of lncRNAs expression profile in HBV-related HCC tissues samples using deep sequencing. We revealed that a total of 1242 lncRNA transcripts (983 up-regulated and 259 down-regulated) and 1841 mRNA transcripts were significantly differentially expressed in HBV-related HCC patients. Pathway and gene ontology analysis showed that they are involved in the biological process related to HCC development by cis-regulation of co-expressed protein-coding genes. 10 candidate lncRNAs were selected and validated with quantitative real-time PCR analysis. Furthermore, we found that one of most down-regulated lncRNAs, n346077, could suppress HCC cells invasion and migration in vitro. Our findings provide an overview of aberrantly expressed lncRNAs in HBV-related HCC and will be useful for further functional studies of lncRNAs in HBV-related pathogenesis.

Multiwavelet packet entropy and its application in transmission line fault recognition and classification.

Multiwavelets possess better properties than traditional wavelets. Multiwavelet packet transformation has more high-frequency information. Spectral entropy can be applied as an analysis index to the complexity or uncertainty of a signal. This paper tries to define four multiwavelet packet entropies to extract the features of different transmission line faults, and uses a radial basis function (RBF) neural network to recognize and classify 10 fault types of power transmission lines. First, the preprocessing and postprocessing problems of multiwavelets are presented. Shannon entropy and Tsallis entropy are introduced, and their difference is discussed. Second, multiwavelet packet energy entropy, time entropy, Shannon singular entropy, and Tsallis singular entropy are defined as the feature extraction methods of transmission line fault signals. Third, the plan of transmission line fault recognition using multiwavelet packet entropies and an RBF neural network is proposed. Finally, the experimental results show that the plan with the four multiwavelet packet energy entropies defined in this paper achieves better performance in fault recognition. The performance with SA4 (symmetric antisymmetric) multiwavelet packet Tsallis singular entropy is the best among the combinations of different multiwavelet packets and the four multiwavelet packet entropies.