Circular RNA circ_0008450 upregulates CXCL9 expression by targeting miR-577 to regulate cell proliferation and invasion in nasopharyngeal carcinoma.

As a kind of malignant tumor, nasopharyngeal carcinoma (NPC) has attracted increasing attention from researchers. As a member of the circular RNA (circRNA) family, circ_0008450 has been investigated in hepatocellular carcinoma but not in NPC. This study aims to reveal the special biologic role and mechanism of circ_0008450 in NPC. qRT-PCR analysis was conducted to test the level of circ_0008450 in different tissues and cells. Loss/Gain of function assay was utilized to detect the influence of silenced/overexpressed circ_0008450 on the proliferation, apoptosis, migration, and invasion of NPC cells. The mechanism of circ_0008450 was assessed by performing qRT-PCR and luciferase reporter experiments. The results showed that circ_0008450 was elevated in NPC tissues and cells. Silenced circ_0008450 could inhibit cell proliferation, and metastatic properties and increased the number of apoptotic cells. Ectopically expressed circ_0008450 strengthened the abovementioned malignant biological behaviors. Mechanistically, circ_0008450 reduced miR-577-mediated repression of CXCL9, resulting in facilitating the oncogenic functions of NPC. In conclusion, circ_0008450 acts as an oncogene in NPC cells through regulating miR-577/CXCL9 signaling. Our findings might provide a new therapeutic target for treating NPC.

A Mixture of Transformed Hidden Markov Models for elastic motion estimation.

Elastic motion is a nonrigid motion constrained only by some degree of smoothness and continuity. Consequently, elastic motion estimation by explicit feature matching actually contains two correlated subproblems: shape registration and motion tracking, which account for spatial smoothness and temporal continuity, respectively. If we ignore their interrelationship, solving each of them alone will be rather challenging, especially when the cluttered features are involved. To integrate them into a probabilistic model, one straightforward approach is to draw the dependence between their hidden states. With regard to their separated states, there are, however, two different explanations of motion which are still made under the individual constraint of smoothness or continuity. Each one can be error-prone, and their coupling causes error propagation. Therefore, it is highly desirable to design a probabilistic model in which a unified state is shared by the two subproblems. This paper is intended to propose such a model, i.e., a Mixture of Transformed Hidden Markov Models (MTHMM), where a unique explanation of motion is made simultaneously under the spatiotemporal constraints. As a result, the MTHMM could find a coherent global interpretation of elastic motion from local cluttered edge features, and experiments show its robustness under ambiguities, data missing, and outliers.

Group interaction analysis in dynamic context.

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.

Group interaction analysis in dynamic context.

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.

[Expression and clinical significance of Mucin and E-cadherin in colorectal tumors].

BACKGROUND & OBJECTIVE: Mucin (MUC), a glycoprotein with high molecular weight, can lubricate and protect the epithelium. E-cadherin (E-cad) is helpful in keeping the polarity and integrity of the epithelium. The abnormal expression of Mucin and E-cad is involved in the genesis of many tumors. This study was to investigate the expression of MUC1, MUC2, MUC5AC and E-cad in different colorectal tumor tissues, and explore their correlations to clinicopathologic features of colorectal cancer and the correlations of MUC1, MUC2, and MUC5AC expression to E-cad expression. METHODS: The expression of MUC1, MUC2, MUC5AC and E-cad in 150 specimens of normal colorectal mucosa, 150 specimens of colorectal adenoma and 150 specimens of colorectal adenocarcinoma was detected by immunohistochemistry. Patients' survival was analyzed by Kaplan-Meier method. The correlations of MUC1, MUC2, and MUC5AC expression to E-cad expression were analyzed by spearman's rank correlation. RESULTS: The positive rates of MUC1 were 0.07% in normal colorectal mucosa, 12.7% in colorectal adenoma, and 45.3% in colorectal adenocarcinoma. Those of MUC2 were 100%, 90.0% and 52.6%, respectively. Those of MUC5AC were 8.7%, 30.7% and 44.0%, respectively. Those of E-cad were 98.7%, 82.0% and 54.0%, respectively. In colorectal adenocarcinoma, the expression of MUC1 and MUC2 was correlated to tumor differentiation, invasion, lymph node metastasis and Dukes' stage (P<0.05); the expression of MUC5AC was correlated to tumor differentiation and invasion (P<0.01); the expression of E-cad was correlated to tumor differentiation (P<0.01). The 5-year survival rate was significantly higher in MUC1-negative group, MUC2-positive group and E-cadherin-positive group than in their counterparts (P<0.05). In colorectal adenocarcinoma, MUC1 expression was negatively correlated to E-cad expression (r=-0.234, P=0.004), MUC2 and MUC5AC expression were positively correlated to E-cad expression (r=0.170, P=0.038; r=0.198, P=0.015). CONCLUSIONS: In colorectal adenocarcinoma, MUC expression is obviously correlated to E-cad expression. The up-regulation of MUC1 and MUC5AC expression and the down-regulation of MUC2 and E-cad expression may be involved in the genesis of colorectal tumors and reflect the prognosis to a certain extent.

Error analysis of pure rotation-based self-calibration.

Self-calibration using pure rotation is a well-known technique and has been shown to be a reliable means for recovering intrinsic camera parameters. However, in practice, it is virtually impossible to ensure that the camera motion for this type of self-calibration is a pure rotation. In this paper, we present an error analysis of recovered intrinsic camera parameters due to the presence of translation. We derived closed-form error expressions for a single pair of images with nondegenerate motion; for multiple rotations for which there are no closed-form solutions, analysis was done through repeated experiments. Among others, we show that translation-independent solutions do exist under certain practical conditions. Our analysis can be used to help choose the least error-prone approach (if multiple approaches exist) for a given set of conditions.