112 research outputs found
A Weekly Diary Study on Playful Study Design, Study Engagement, and Goal Attainment: The Role of Proactive Personality
Full text linkStudents’ learning processes are heavily impeded by the COVID-19 pandemic. Students are experiencing more online learning environment and less face-to-face idea exchange, which may make them feel exhausted and demotivated. Using self-determination and proactivity theories, we propose and examine whether playful study design (PSD)—a proactive study strategy including designing fun and designing competition in learning tasks—is effective in fostering study engagement, which, in turn, improves study goal attainment during the COVID-19 period. Moreover, we examine whether students who are high in proactive personality will benefit more (e.g., reach a higher level of study engagement) when using the PSD strategy. We collected data using a weekly diary approach during four consecutive weeks, including 97 people and 308 within-person observations. Results of multilevel analyses showed that weekly PSD was positively related to weekly study engagement, and in turn, facilitated weekly goal attainment. Moreover, we found that proactive personality moderated and strengthened the positive associations between PSD and goal attainment, study engagement and goal attainment, but not for the relationship between PSD and study engagement. Overall, we provide one of the first attempts to demonstrate how PSD strategy can be used in student study life to improve study engagement and reach their goals. We shed light on how proactive personality can safeguard the success of PSD strategy. Theoretical and practical contributions are discussed.Design Conceptualization and Communicatio
Home crafting project
No full textThis project will test the effect of home crafting strategies on employee work outcomes. We will attempt to test a spillover effect and a crossover effect of home crafting from one domain to the other domain and from one person to another person. Finally, we aim to train individuals to master home crafting strategies and test the effectiveness of our intervention
Identification and Experimental Validation of PANoptosis-Related Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics Analysis
Full text linkDongguang Wang,1,2,* Yifan Yuan,3– 5,* Xiang Tong,1,2 Lian Wang,1,2 Jibo Sun,1,2 Shijie Zhang,1,2 Sitong Liu,1,2 Huatian Gan,3– 5 Hong Fan1,2 1Department of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 2State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 3Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 4Centre for Inflammatory Bowel Disease, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 5Lab of Inflammatory Bowel Disease, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Huatian Gan, Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, People’s Republic of China, Email [email protected] Hong Fan, Department of Respiratory and Critical Care Medicine, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, People’s Republic of China, Email [email protected]: To identify the molecular signature of differentially expressed genes (DEGs) associated with PANoptosis in idiopathic pulmonary fibrosis (IPF) and to interpret their immune landscape and cellular distribution characteristics.Methods and Results: We acquired two IPF datasets from the Gene Expression Omnibus (GEO) database to identify PANoptosis-related DGEs (PAN-DEGs), initially identifying thirty PAN-DEGs. Utilizing machine learning algorithms, we established a five-gene PANoptosis-related signature comprising IGF1, GPX3, GADD45β, SMAD7, and TIMP3, each demonstrating robust diagnostic performance. The expression of these hub genes was subsequently validated using a third GEO dataset and a bleomycin-induced pulmonary fibrosis model. Immune infiltration analysis revealed a close association of these genes with various immune cells, and single-cell RNA sequencing indicated significant expression changes in diverse pulmonary cell types, particularly endothelial cells and fibroblasts.Conclusion: We identified and validated a PANoptosis-related gene signature in IPF, providing insights into their immune infiltration and potential cellular distribution. Further research is necessary to elucidate the biological functions and mechanisms of these genes in the pathogenesis of IPF.Keywords: bioinformatics analysis, differentially expressed genes, idiopathic pulmonary fibrosis, PANoptosi
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