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This study investigated whether negative stereotypes are responsible for the effect of ASD knowledge on social distance from individuals with ASD among college students. A sample of 869 neurotypical Chinese college students completed a cross-sectional survey to assess social distance, ASD knowledge, and negative stereotypes. Pearson correlation analysis yielded significant correlations between social distance, ASD knowledge, and negative stereotypes. Multiple mediation analysis showed that negative stereotypes mediated the link between social distance and ASD knowledge. Specifically, greater ASD knowledge predicted reduced social distance through decreased stereotyping related to dangerousness, personal responsibility for the disorder, and discontinuity, but also predicted greater social distance through increased stereotyping related to social inappropriateness. The findings deepen our understanding of the association between ASD knowledge and social distance by revealing the mediating role of negative stereotypes, and provide information that can help improve anti-stigma initiatives in college settings. [ABSTRACT FROM AUTHOR]

Background: Cardiomyopathy is a complex type of myocardial disease, and its incidence has increased significantly in recent years. Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common and indistinguishable types of cardiomyopathy. Results: Here, a systematic multi-omics integration approach was proposed to identify cardiomyopathy-related core genes that could distinguish normal, DCM and ICM samples using cardiomyopathy expression profile data based on a human metabolic network. First, according to the differentially expressed genes between different states (DCM/ICM and normal, or DCM and ICM) of samples, three sets of initial modules were obtained from the human metabolic network. Two permutation tests were used to evaluate the significance of the Pearson correlation coefficient difference score of the initial modules, and three candidate modules were screened out. Then, a cardiomyopathy risk module that was significantly related to DCM and ICM was determined according to the significance of the module score based on Markov random field. Finally, based on the shortest path between cardiomyopathy known genes, 13 core genes related to cardiomyopathy were identified. These core genes were enriched in pathways and functions significantly related to cardiomyopathy and could distinguish between samples of different states. Conclusion: The identified core genes might serve as potential biomarkers of cardiomyopathy. This research will contribute to identifying potential biomarkers of cardiomyopathy and to distinguishing different types of cardiomyopathy. [ABSTRACT FROM AUTHOR]