Effect of Online Brand Community on Customer Behavior Exploration: Reconciling Mixed Findings via Regulatory Focus Theory

This study seeks to address the mixed findings of prior studies regarding the effect of online brand community on customer behavior. Based on the regulatory focus theory, we hypothesize that participation in a brand community tends to increase both visit and purchase frequencies of customers with promotion-focus; on the contrary, the same would typically decrease visit and purchase frequencies of customers with prevention-focus. By analyzing data from an online brand community using a “propensity-score matching” technique, we found a partial validation that attendance of the community led to increases in customer visit frequency for customers with both promotion-focus and prevention-focus. Further, our results show that customers with promotion-focus tend to purchase more; while customers with prevention-focus slightly decreased their purchase volume. Both theoretical and practical implications of our findings are discussed in the paper

A Novel Personalized Academic Knowledge Sharing System in Online Social Network

Information overload is a major problem for both readers and authors due to the rapid increase in scientific papers in recent years. Methods are proposed to help readers find right papers, but few research focuses on knowledge sharing and dissemination from authors’ perspectives. This paper proposes a personalized academic knowledge sharing system that takes advantages of author’s initiatives. In our method, we combine the user-level and document-level analysis in the same model, it works in two stages: 1) user-level analysis, which is used to profile users in three dimensions (i.e., research topic relevance, social relation and research quality); and 2) document-level analysis, which calculates the similarity between the target article and reader’s publications. The proposed method has been implemented in the ScholarMate, which is a popular academic social network. The experiment results show that the proposed method can effectively promote the academic knowledge sharing, it outperforms other baseline methods

Characterization of the Small RNA Transcriptomes of Androgen Dependent and Independent Prostate Cancer Cell Line by Deep Sequencing

Given the important roles of miRNA in post-transcriptional regulation and its implications for cancer, characterization of miRNA facilitates us to uncover molecular mechanisms underlying the progression of androgen-independent prostate cancer (PCa). The emergence of next-generation sequencing technologies has dramatically changed the speed of all aspects of sequencing in a rapid and cost-effective fashion, which can permit an unbiased, quantitive and in-depth investigation of small RNA transcriptome. In this study, we used high-throughput Illumina sequencing to comprehensively represent the full complement of individual small RNA and to characterize miRNA expression profiles in both the androgen dependent and independent Pca cell line. At least 83 miRNAs are significantly differentially expressed, of which 41 are up-regulated and 42 are down-regulated, indicating these miRNAs may be involved in the transition of LNCaP to an androgen-independent phenotype. In addition, we have identified 43 novel miRNAs from the androgen dependent and independent PCa library and 3 of them are specific to the androgen-independent PCa. Function annotation of target genes indicated that most of these differentially expressed miRNAs tend to target genes involved in signal transduction and cell communication, epically the MAPK signaling pathway. The small RNA transcriptomes obtained in this study provide considerable insights into a better understanding of the expression and function of small RNAs in the development of androgen-independent prostate cancer

Epigenetic Activation of ASCT2 in the Hippocampus Contributes to Depression-Like Behavior by Regulating D-Serine in Mice

The roles of D-serine in depression are raised concerned recently as an intrinsic co-agonist for the NMDA receptor. However, the mechanisms underlying its regulation are not fully elucidated. ASCT2 is a Na+-dependent D-serine transporter. We found that decreased D-serine and increased hippocampal ASCT2 levels correlated with chronic social defeat stress (CSDS) in mice. Lentivirus-mediated shRNA-mediated knockdown of ASCT2 and the administration of exogenous D-serine in the hippocampus alleviated CSDS-induced social avoidance and immobility. In vivo and in vitro experiments revealed that upregulation of ASCT2 expression in CSDS was regulated through histone hyper-acetylation, not DNA methylation in its promoter region. Immunohistochemistry demonstrated the co-localization of ASCT2 and D-serine. Uptake of D-serine by ASCT2 was demonstrated by in vivo and in vitro experiments. Our results indicate that CSDS induces ASCT2 expression through epigenetic activation and decreases hippocampal D-serine levels, leading to social avoidance, and immobility. Thus, targeting D-serine transport represents an attractive new strategy for treating depression

Glycyrrhizin inhibits the invasion and metastasis of breast cancer cells via upregulation of expressions of miR-200c and e-cadherin

Purpose: To determine the inhibitory effect of glycyrrhizin (GLA) on cell invasion and metastasis in mammary carcinoma cells, and the mechanisms of actions involved.Methods: The effect of GLA at different concentrations on proliferation of breast cancer MDA-MB-231 and BT549 cells was assayed by MTT method. Transwell assay was used to determine the effect of GLA at different concentrations on invasiveness and metastasis of breast cancer MDA-MB-231 and BT549 cells. The influence of LGA on expressions of microRNA-200c and miR-200c was assayed by reverse transcriptase-polymerase chain reaction (RT-PCR).Results: There was no statistically significant difference in cell proliferation amongst cells treated with 5 and 20 μM GLA and untreated breast cancer cells. However, the proliferation of cells treated with 40 μM GLA was significantly reduced (p < 0.05). In the cell invasion and migration experiments, cell population transferred to the base of Transwell chamber in the two cell lines treated with GLA was markedly decreased, relative to cells without GLA treatment, while the number of cells decreased with increase in GLA concentration (p < 0.05). Results from image-pro-plus analysis revealed that the population of cells quantitatively crossing the Transwell compartment membrane decreased with increase in GLA concentration (p < 0.05). The expression of e-cadherin was increased by GLA treatment in a concentration-dependent manner. Moreover, GLA treatment led to significant changes in amounts of miR-200s a, b and c, with changes in miR-200c being the most significant (p < 0.05).Conclusion: GLA suppresses the invasiveness and metastasis of breast cancer MDA-MB-231 and BT549 cells via upregulation of the expressions of miR-200c and e-cadherin. These findings provide a theoretical basis for the development of new breast cancer drugs. Keywords: Glycyrrhiza, GLA, miR-200c, E-cadherin, Inhibition, Breast cancer cells, Invasion, Metastasi

Ginsenoside induces cell death in breast cancer cells via ROS/PI3K/Akt signaling pathway

Purpose: To study the influence of ginsenoside on breast carcinoma, and the mechanism of action involved.Methods: Different concentrations of ginsenoside were used to treat MCF-7 breast cancer cell line. Cell viability was measured by MTT assay, while protein expressions of p-Akt and p-PI3K were determined using Western blotting. The concentrations of reactive oxidative reactants and reactive oxygen species (ROS) were assessed using fluorescence immunoassay and immunofluorescence assay. The mechanism of action involved in ginsenoside-mediated apoptosis was determined based on ROS/PI3K/Akt signaling pathway.Results: There was no change in the inhibition of MCF-7 cell proliferation in control cells with time (p > 0.05). However, inhibition of MCF-7 cell proliferation in ginsenoside group was significantly higher than that in the control group (p < 0.05); furthermore, it increased with time and ginsenoside concentration. Apoptosis was markedly and concentration-dependently higher in ginsenoside-treated MCF-7 cells than in controls (p > 0.05). There were lower protein levels of p-PI3K and p-Akt in ginsenoside-exposed MCF-7 cells than in control group; the protein expressions  decreased with increase in ginsenoside concentration (p < 0.05). The expressions of ROS in ginsenoside-treated MCF-7 cells declined, relative to the untreated group; in addition, the expressions decreased with increase in ginsenoside concentration (p < 0.05).Conclusion: Ginsenoside suppresses proliferation of MCF-7 cell line, and exerts apoptotic effect on the cells via inhibition of the ROS/PI3K/Akt signal pathway. This provides a new approach to treat breast cancer. Keywords: Breast cancer cells, Ginsenoside, Apoptosis, ROS/PI3K/Akt signaling pathwa

mirTools: microRNA profiling and discovery based on high-throughput sequencing

miRNAs are small, non-coding RNA that negatively regulate gene expression at post-transcriptional level, which play crucial roles in various physiological and pathological processes, such as development and tumorigenesis. Although deep sequencing technologies have been applied to investigate various small RNA transcriptomes, their computational methods are far away from maturation as compared to microarray-based approaches. In this study, a comprehensive web server mirTools was developed to allow researchers to comprehensively characterize small RNA transcriptome. With the aid of mirTools, users can: (i) filter low-quality reads and 3/5′ adapters from raw sequenced data; (ii) align large-scale short reads to the reference genome and explore their length distribution; (iii) classify small RNA candidates into known categories, such as known miRNAs, non-coding RNA, genomic repeats and coding sequences; (iv) provide detailed annotation information for known miRNAs, such as miRNA/miRNA*, absolute/relative reads count and the most abundant tag; (v) predict novel miRNAs that have not been characterized before; and (vi) identify differentially expressed miRNAs between samples based on two different counting strategies: total read tag counts and the most abundant tag counts. We believe that the integration of multiple computational approaches in mirTools will greatly facilitate current microRNA researches in multiple ways. mirTools can be accessed at http://centre.bioinformatics.zj.cn/mirtools/ and http://59.79.168.90/mirtools

Total and Methyl Mercury Contents and Distribution Characteristics in Cicada, Cryptotympana atrata (Fabricius)

Total and methyl mercury concentrations of cicada bodies, wings, and exuviae were investigated to study the mercury distribution characteristics. Results indicated that total and methyl mercury concentrations of cicada bodies were 2.64 mg/kg and 123.93 ng/g on average, respectively. In cicada tissues, total mercury concentrations were found to increase in the order of exuviae (0.50 mg/kg on average) < wings (0.98 mg/kg on average) < cicada bodies (2.64 mg/kg on average) and methyl mercury concentrations of cicada bodies were 123.93 ng/g on average and were the highest. Methyl mercury concentrations accounted for about 4.69% of total mercury in cicada bodies and most mercury was in inorganic forms in cicada. Sex differences of total mercury concentrations were significantly great (F = 8.433, p < 0.01) and total mercury concentrations of the males, which were 3.38 mg/kg on average, were much higher. Correlation analysis showed that neither total nor methyl mercury concentrations of cicada bodies was significantly related to the corresponding contents of soil (r = 0.0598, p > 0.05)

Mercury Bioaccumulation and Prediction in Terrestrial Insects from Soil in Huludao City, Northeast China

Mercury accumulation was investigated by constructing and testing empirical equations based on mercury in soil (Cs) and in 10 terrestrial insects (Ci). Cs ranged from 0.13 to 41.01 mg/kg. Ci differed with species and the highest was found in dragonfly. Cs and Ci showed a good linear fit, and a simple equation was used in predicting Ci when insects were classified into one Insecta group (r = 0.3399, p = 0.0037). The taxonomy can affect validities of empirical equations, which fit field data well when insects were grouped by feeding habits, and when grouped by species, empirical equations were suitable only for certain insects