Why and When Do Good Soldiers Behave Unethically? Introducing Conservation of Resources Theory to Explain the Curvilinear Effects of Organizational Citizenship Behavior.

Previous research about organizational citizenship behavior (OCB) and counterproductive work behavior (CWB) has produced contradictory results. Drawing from the conservation of resources (COR) theory, the present study tries to explain the contradictory findings by examining the curvilinear relationship between OCB and CWB. Using data collected at three time points from 426 employees and 110 supervisors in Chinese companies, data analysis shows that OCB has an inverted U-shaped relationship with CWB. The results also demonstrate that citizenship fatigue mediates the relationship between OCB and CWB, perceived organizational support (POS) moderates the relationship between OCB and citizenship fatigue. In addition, POS moderates the mediating effect of citizenship fatigue in the inverted U-shaped curvilinear relationship between OCB and CWB. This mediating effect is stronger under conditions of low POS than high POS. The findings present a complementary explanation of the conflicting relationships between OCB and CWB.

A novel prognostic model based on epithelial-mesenchymal transition-related genes predicts patient survival in gastric cancer.

BACKGROUND: Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. METHODS: Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. RESULTS: Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. CONCLUSIONS: We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.