The neural correlates of optimistic and depressive tendencies of self-evaluations and resting-state default mode network

Abstract: Unrealistic optimism is common among people making self-evaluations while reduced optimism has been linked to increased depressive symptoms. Given the importance of optimism for adaptive functioning, surprisingly little is known about resting brain states underlying optimistic and depressive tendencies. In the current study, two resting-state indices were used to examine the neural correlates of default mode network (DMN) and optimistic and depressive tendencies in a nonclinical young adult sample. Due to the self-referential nature of DMN, the analysis was constrained within it. Across different indices, bilateral superior frontal gyri of the dorsolateral prefrontal cortex (DLPFC) and bilateral superior medial frontal gyri of the dorsal medial prefrontal cortex (DMPFC) play a key role in maintaining optimistic tendencies of spontaneous self-evaluations. Conversely, decreased activity in DLPFC and bilateral medial orbitofrontal cortices (OFC) are related to accentuated depressive symptoms. Together, results highlight the pivotal roles of the DLPFC and DMPFC in mediating valences of self-referential content

Exploring potential new floral organ morphogenesis genes of Arabidopsis thaliana using systems biology approach

Flowering is one of the important defining features of angiosperms. The initiation of flower development and the formation of different floral organs are the results of the interplays among numerous genes. But until now, just fewer genes have been found linked with flower development. And the functions of lots of genes of Arabidopsis thaliana are still unknown. Although, the quartet model successfully simplified the ABCDE model to elaborate the molecular mechanism by introducing protein-protein interactions (PPIs). We still don't know much about several important aspects of flower development. So we need to discriminate even more genes involving in the flower development. In this study, we identified seven differentially modules through integrating the weighted gene co-expression network analysis (WGCNA) and Support Vector Machine (SVM) method to analyze co-expression network and PPIs using the public floral and non-floral expression profiles data of Arabidopsis thaliana. Gene set enrichment analysis was used for the functional annotation of the related genes, and some of the hub genes were identified in each module. The potential floral organ morphogenesis genes of two significant modules were integrated with PPI information in order to detail the inherent regulation mechanisms. Finally, the functions of the floral patterning genes were elucidated by combining the PPI and evolutionary information. It was indicated that the sub-networks or complexes, rather than the genes, were the regulation unit of flower development. We found that the most possible potential new genes underlining the floral pattern formation in A. thaliana were FY, CBL2, ZFN3 and AT1G77370; among them, FY, CBL2 acted as an upstream regulator of AP2; ZFN3 activated the flower primordial determining gene AP1 and AP2 by HY5/HYH gene via photo induction possibly. And AT1G77370 exhibited similar function in floral morphogenesis, same as ELF3. It possibly formed a complex between RFC3 and RPS15 in cytoplasm, which regulated TSO1 and CPSF160 in the nucleus, to control the floral organ morphogenesis. This process might also be fine tuning by AT5G53360 in the nucleus