RIPK4 Suppresses the Invasion and Metastasis of Hepatocellular Carcinoma by Inhibiting the Phosphorylation of STAT3

Receptor interacting serine/threonine kinase 4 (RIPK4) is a member of the threonine/serine protein kinase family; it plays related functions in a variety of tumours, but its biological function has not been fully revealed. It has been reported that it is differentially expressed in hepatocellular carcinoma (HCC). Our research aimed to reveal the role of RIPK4 in the progression of HCC and to reveal the biological behaviour of RIPK4 in HCC. We analysed the differences in RIPK4 expression in HCC by using a publicly available data set. By using PCR, Western blotting and immunohistochemical staining methods, we detected the expression level of RIPK4 in HCC patient specimens and studied the relationship between the expression of RIPK4 and the clinicopathological features of HCC patients. The prognostic data were combined to analyse the relationship between RIPK4 and HCC patient survival and tumour recurrence. We found that the expression level of RIPK4 in nontumour tissues was significantly higher than that in tumour tissues, and the level of RIPK4 was significantly positively correlated with postoperative survival and recurrence in HCC patients. Further, our study found that RIPK4 inhibits the progression of HCC by influencing the invasion and metastasis of HCC and that overexpression of RIPK4 reduces the invasion and metastasis of HCC by inhibiting epithelial-mesenchymal transition (EMT) and the STAT3 pathway. In in vivo experiments, overexpression of RIPK4 stably inhibited HCC metastasis. To summarize, our research revealed the relationship between RIPK4 and the prognosis of patients with HCC. We discovered that RIPK4 affects the invasion and metastasis of HCC through the EMT and STAT3 pathways. Targeted inhibition of the RIPK4 gene and the STAT3 pathway may be potential therapeutic strategies for inhibiting the postoperative recurrence and metastasis of HCC

Parental Autonomy Support and Social Competence in Chinese Emerging Adults: the Mediation Role of Social Desirablity

Aims: The current study aimed to examine the relationship between parental autonomy support and social competence among Chinese emerging adults, and explore whether social desirablity plays a mediating role between parental support and social competence. Methods: This study used cross-sectional and correlational design. Participants were 386 Chinese college students (72.8% girls) aged between 18 and 25 years. Data was collected via self-report questionnaires, including parental autonomy support (Genevie`ve A. Mageau, 2015), social desirablity (Karl Schuessler et al., 1978) and social competence(Valkenburg & Peter, 2008). Results: Structural equation modeling analysis controlling for age, gender and SES showed that (a) There was a significant positive correlation between parental autonomy support, social desirablity, and social competence; (b) Parental autonomy support was positively predicted to social desirablity and social competence; Social desirablity was positively predicted to social competence; (c) Social desirablity mediated the relationship between parental autonomy support and social competence

Ensemble-Based Semi-Supervised Learning for Milling Chatter Detection

Chatter is one of the most deleterious phenomena during the machining process, and leads to a low quality of workpiece surface, a noisy workplace, and decreases in tool and machine life. In order to overcome these limitations and improve the machining performance, various effective methods have been developed for chatter detection. The main shortcoming of such methods is that they require all the data to be labeled. However, the labeled data that accurately reflect the chatter states are hard to collect in practical application. This paper proposes a semi-supervised method to classify chatter states with a small quantity of labeled data and large quantity of unlabeled ones. In order to improve the classification accuracy and generalization ability, ensemble learning is combined with the semi-supervised method, and an EB-SSL model is proposed in this paper. Take the non-stationarity and multiple scaling behaviors of chatter data into consideration, multifractal detrended fluctuation analysis (MF-DFA) is utilized to extract distinguished features from raw chatter detection signals. Experimental results show that this method can identify the chatter states more accurately. The performance analysis indicates that the proposed method is applicable in different milling conditions

Unraveling the Role of Human Activities and Climate Variability in Water Level Changes in the Taihu Plain Using Artificial Neural Network

© 2019 by the authors. Water level, as a key indicator for the floodplain area, has been largely affected by the interplay of climate variability and human activities during the past few decades. Due to a nonlinear dependence of water level changes on these factors, a nonlinear model is needed to more realistically estimate their relative contribution. In this study, the attribution analysis of long-term water level changes was performed by incorporating multilayer perceptron (MLP) artificial neural network. We took the Taihu Plain in China as a case study where water level series (1954-2014) were divided into baseline (1954-1987) and evaluation (1988-2014) periods based on abrupt change detection. The results indicate that climate variables are the dominant driver for annual and seasonal water level changes during the evaluation period, with the best performance of the MLP model having precipitation, evaporation, and tide level as inputs. In the evaluation period, the contribution of human activities to water level changes in the 2000s is higher than that in the 1990s, which indicates that human activities, including the rapid urbanization, are playing an important role in recent years. The influence of human activities, especially engineering operations, on water level changes in the 2000s is more evident during the dry season (March-April-May (MAM) and December-January-February (DJF)).status: publishe