The influence of social exclusion on prosocial behavior of college students: the role of relational need threat and regulatory focus.

The present study investigated the impact of social exclusion on prosocial behavior, examining the roles of relational need threat and regulatory focus. Utilizing a questionnaire study with 483 participants (Study 1) and an experimental study with 100 participants (Study 2), we found that (1) social exclusion negatively predicted prosocial behavior; (2) relational need threat fully mediated the relationship between social exclusion and prosocial behavior; and (3) regulatory focus, categorized as either promotion or prevention, moderated this relationship in opposite directions. In conclusion, our findings reveal that social exclusion does indeed trigger prosocial behavior.

Hsa_circ_0026628 promotes the development of colorectal cancer by targeting SP1 to activate the Wnt/β-catenin pathway.

Circular RNAs (circRNAs) have been reported to play crucial roles in the progression of various cancers, including colorectal cancer (CRC). SP1 (Sp1 transcription factor) is a well-recognized oncogene in CRC and is deemed to trigger the Wnt/β-catenin pathway. The present study was designed to investigate the role of circRNAs which shared the same pre-mRNA with SP1 in CRC cells.

FAM225A facilitates colorectal cancer progression by sponging miR-613 to regulate NOTCH3.

Colorectal cancer (CRC) is a fatal disease ranking the third among the commonplace cancer types around the world. It is extremely significant to exploit effective treatments against CRC. FAM225A was proved to influence cell progression and forecast unfavorable prognosis in nasopharyngeal carcinoma.

LncRNA TINCR/microRNA-107/CD36 regulates cell proliferation and apoptosis in colorectal cancer via PPAR signaling pathway based on bioinformatics analysis.

The present study aims to determine the potential biomarkers and uncover the regulatory mechanisms of the long-noncoding RNA (lncRNA) TINCR/miR-107/CD36 axis in colorectal cancer (CRC). Aberrantly-expressed lncRNAs and differential-expressed genes were identified by analyzing the dataset GSE40967. Gene set enrichment analysis was employed, and Cytoscape software helped in establishing the co-expression network between lncRNAs and genes.