THE BATTLE FOR SINGLES’ DAY: HOW SOCIAL MEDIA MARKETING CAMPAIGNS BOOST SALES

Numerous studies have shown that social media marketing strategies have positive impacts on the long-term financial performance of firms. However, whether short-term marketing campaigns have any influence on firm revenue remains unknown. This paper examines data from Singles’ Day, the world’s largest shopping event, revealing that firms’ social media efforts have a positive impact on product sales. Furthermore, we find that the two social media effort measures generally thought to have positive impacts on a firm’s long-term financial performance, richness and intensity, have no significant influence on the success of a firm’s short-term marketing campaign. Instead, relevance shows significant and positive impacts. Moreover, we compare the effects of social media marketing yields from company-owned accounts with those of employee-owned accounts, finding that employee-owned accounts have better marketing effects than company-owned ones

Constructing Media-based Enterprise Networks for Stock Market Risk Analysis

Stock comovement analysis is essential to understand the mechanism of stock markets. Previous studies focus on the comovement from the perspectives of fundamentals or preferences of investors. In this article, we propose a framework to explore the comovements of stocks in terms of their relationships in Web media. This is achieved by constructing media-based enterprise networks in terms of the co-exposure in news reports of stocks and mutual attentions among them. Our experiments based on CSI 300 listed firms show the significant comovements of stocks brought out by their behaviors in Web media. Furthermore, utilizing media based enterprise networks can help us identify the most influential firms which can stir up the stock markets

Long Noncoding RNA SNHG16 Promotes Cell Proliferation by Sponging MicroRNA-205 and Upregulating ZEB1 Expression in Osteosarcoma

Background/Aims: Long noncoding RNAs (lncRNAs) have been a research hotspot, as they play important roles in tumor development. However, their expression pattern and biological function in osteosarcoma have not yet been clarified. Methods: Differentially expressed lncRNAs in osteosarcoma and paracarcinoma tissues were identified by screening an lncRNA microarray, and candidate lncRNAs were verified by quantitative real-time PCR (qRT-PCR). A series of bioinformatics and molecular biological methods were adopted to investigate the interaction among lncRNA, microRNA (miRNA), and miRNA target genes during the development and occurrence of osteosarcoma. Cell viability was measured using a Cell Counting Kit-8 assay. Results: Chip microarray screening combined with the validation of differentially expressed candidate lncRNAs showed that the lncRNA small nucleolar RNA host gene 16 (SNHG16) had the largest fold change. SNHG16 was highly expressed in osteosarcoma tissues and cell lines, and its downregulation led to the suppressed proliferation of osteosarcoma cells. Further investigations revealed that SNHG16 could upregulate zinc finger E-box-binding homeobox 1 (ZEB1) expression by acting as an endogenous sponge of miR-205. Moreover, rescue assays proved that the effects of SNHG16 on the proliferation of osteosarcoma cells were dependent on miR-205. Conclusion: SNHG16 can significantly enhance the proliferation of osteosarcoma cells. In addition, SNHG16, miR-205, and ZEB1 interact in a common pathway during the development and occurrence of osteosarcoma, providing novel targets for intervention in the treatment of osteosarcoma

Whole transcriptome analysis reveals non-coding RNA's competing endogenous gene pairs as novel form of motifs in serous ovarian cancer

Publisher Copyright: © 2022The non-coding RNA (ncRNA) regulation appears to be associated to the diagnosis and targeted therapy of complex diseases. Motifs of non-coding RNAs and genes in the competing endogenous RNA (ceRNA) network would probably contribute to the accurate prediction of serous ovarian carcinoma (SOC). We conducted a microarray study profiling the whole transcriptomes of eight human SOCs and eight controls and constructed a ceRNA network including mRNAs, long ncRNAs, and circular RNAs (circRNAs). Novel form of motifs (mRNA-ncRNA-mRNA) were identified from the ceRNA network and defined as non-coding RNA's competing endogenous gene pairs (ceGPs), using a proposed method denoised individualized pair analysis of gene expression (deiPAGE). 18 cricRNA's ceGPs (cceGPs) were identified from multiple cohorts and were fused as an indicator (SOC index) for SOC discrimination, which carried a high predictive capacity in independent cohorts. SOC index was negatively correlated with the CD8+/CD4+ ratio in tumour-infiltration, reflecting the migration and growth of tumour cells in ovarian cancer progression. Moreover, most of the RNAs in SOC index were experimentally validated involved in ovarian cancer development. Our results elucidate the discriminative capability of SOC index and suggest that the novel competing endogenous motifs play important roles in expression regulation and could be potential target for investigating ovarian cancer mechanism or its therapy.Peer reviewe

MicroRNA-524 promotes cell proliferation by down-regulating PTEN expression in osteosarcoma

Abstract Background Increasing numbers of studies have examined the correlation between specific miRNAs and tumours to enable their diagnosis and treatment. However, there are few reports regarding the concrete role and mechanism of miRNA in osteosarcoma. Methods The expression of miR-524 in osteosarcoma tissues and cell lines was examined by qRT-PCR. The cell proliferation was examined using CCK-8 in vitro. A series of bioinformatics and molecular biology techniques were adopted to investigate the regulatory relationship between miR-524 and target genes in osteosarcoma. Results The results showed that the miRNA with the most significant differential expression in osteosarcoma was miR-524, which was significantly up-regulated in both osteosarcoma tissues and cell lines. MiR-524 knockdown inhibited proliferation and promoted apoptosis of osteosarcoma cells, while overexpression of miR-524 induced their proliferation. Bioinformatics analysis and luciferase assay confirmed that PTEN was a direct target gene of miR-524 and that miR-524 induced proliferation of osteosarcoma cells through activation of the PI3K/AKT pathway via inhibition of PTEN. Conclusions MiR-524 induces the proliferation of osteosarcoma cells through activation of the PI3K/AKT pathway via inhibition of the target gene PTEN, which provides a theoretical basis for selecting a new therapeutic target for osteosarcoma

Roadway traffic crash prediction using a state-space model based support vector regression approach.

Conventional traffic crash analyzing methods focus on identifying the relationship between traffic crash outcomes and impact risk factors and explaining the effects of risk factors, which ignore the changes of roadway systems and can lead to inaccurate results in traffic crash predictions. To address this issue, an innovative two-step method is proposed and a support vector regression (SVR) model is formulated into state-space model (SSM) framework for traffic crash prediction. The SSM was developed in the first step to identify the dynamic evolution process of the roadway systems that are caused by the changes of traffic flow and predict the changes of impact factors in roadway systems. Using the predicted impact factors, the SVR model was incorporated in the second step to perform the traffic crash prediction. A five-year dataset that obtained from 1152 roadway segments in Tennessee was employed to validate the model effectiveness. The proposed models result in an average prediction MAPE of 7.59%, a MAE of 0.11, and a RMSD of 0.32. For the performance comparison, a SVR model and a multivariate negative binomial (MVNB) model were developed to do the same task. The results show that the proposed model has superior performances in terms of prediction accuracy compared to the SVR and MVNB models. Compared to the SVR and MVNB models, the benefit of incorporating a state-space model to identify the changes of roadway systems is significant evident in the proposed models for all crash types, and the prediction accuracy that measured by MAPE can be improved by 4.360% and 6.445% on average, respectively. Apart from accuracy improvement, the proposed models are more robust and the predictions can retain a smoother pattern. Furthermore, the results show that the proposed model has a more precise and synchronized response behavior to the high variations of the observed data, especially for the phenomenon of extra zeros

L Antigen Family Member 3 Serves as a Prognostic Biomarker for the Clinical Outcome and Immune Infiltration in Skin Cutaneous Melanoma

L Antigen Family Member 3 (LAGE3) is an important RNA modification-related protein. Whereas few studies have interrogated the LAGE3 protein, there is limited data on its role in tumors. Here, we analyzed and profiled the LAGE3 protein in skin cutaneous melanoma (CM) using TCGA, GTEx, or GEO databases. Our data showed an upregulation of LAGE3 in melanoma cell lines compared to normal skin cell lines. Besides, the Kaplan–Meier curves and Cox proportional hazard model revealed that LAGE3 was an independent survival indicator for CM, especially in metastatic CM. Moreover, LAGE3 was negatively associated with multiple immune cell infiltration levels in CM, especially CD8+ T cells in metastatic CM. Taken together, our study suggests that LAGE3 could be a potential prognostic biomarker and might be a potential target for the development of novel CM treatment strategies

RIPK1 suppresses apoptosis mediated by TNF and caspase-3 in intervertebral discs

Abstract Background Low back pain has become a serious social and economic burden and the leading cause of disability worldwide. Among a variety of pathophysiological triggers, intervertebral disc (IVD) degeneration plays a primary underlying role in causing such pain. Specifically, multiple independent endplate changes have been implicated in the initiation and progression of IVD degeneration. Methods In this study, we built a signaling network comprising both well-characterized IVD pathology-associated proteins as well as some potentially correlated proteins that have been associated with one or more of the currently known pathology-associated proteins. We then screened for the potential IVD degeneration-associated proteins using patients’ normal and degenerative endplate specimens. Short hairpin RNAs for receptor interacting serine/threonine kinase 1 (RIPK1) were constructed to examine the effects of RIPK1 knockdown in primary chondrocyte cells and in animal models of caudal vertebra intervertebral disc degeneration in vivo. Results RIPK1 was identified as a potential IVD degeneration-associated protein based on IVD pathology-associated signaling networks and the patients’ degenerated endplate specimens. Construction of the short hairpin RNAs was successful, with short-term RIPK1 knockdown triggering inflammation in the primary chondrocytes, while long-term knockdown triggered apoptosis through cleavage of the caspase 3 pathway, down-regulated NF-κB and mitogen-activating protein kinase (MAPK)s cascades, and decreased cell survival and inflammation. Animal models of caudal vertebra intervertebral disc degeneration further demonstrated that apoptosis was induced by up-regulation of tumor necrosis factor (TNF) accompanied by down-regulation of NF-κB and MAPKs cascades that are dependent on caspase and RIPK1. Conclusions These results provide proof-of-concept for developing novel therapies to combat IVD degeneration through interfering with RIPK1-mediated apoptosis signaling pathways especially in patients with RIPK1 abnormality

Abnormal and Changing Information Interaction in Adults with Attention-Deficit/Hyperactivity Disorder Based on Network Motifs

Network motif analysis approaches provide insights into the complexity of the brain’s functional network. In recent years, attention-deficit/hyperactivity disorder (ADHD) has been reported to result in abnormal information interactions in macro- and micro-scale functional networks. However, most existing studies remain limited due to potentially ignoring meso-scale topology information. To address this gap, we aimed to investigate functional motif patterns in ADHD to unravel the underlying information flow and analyze motif-based node roles to characterize the different information interaction methods for identifying the abnormal and changing lesion sites of ADHD. The results showed that the interaction functions of the right hippocampus and the right amygdala were significantly increased, which could lead patients to develop mood disorders. The information interaction of the bilateral thalamus changed, influencing and modifying behavioral results. Notably, the capability of receiving information in the left inferior temporal and the right lingual gyrus decreased, which may cause difficulties for patients in processing visual information in a timely manner, resulting in inattention. This study revealed abnormal and changing information interactions based on network motifs, providing important evidence for understanding information interactions at the meso-scale level in ADHD patients