Chonbuk National University

About: Chonbuk National University is a education organization based out in Jeonju, South Korea. It is known for research contribution in the topics: Apoptosis & Nanofiber. The organization has 14820 authors who have published 28884 publications receiving 554131 citations.

Structural and optical properties of single-crystalline ZnO nanorods grown on silicon by thermal evaporation.

Abstract: The growth of perfectly hexagonal-shaped ZnO nanorods, with Zn-terminated (0001) facets bounded with surfaces, has been performed on nickel-coated Si(100) substrate via thermal evaporation using metallic zinc powder and oxygen. Detailed structural investigations confirmed that the synthesized nanorods are single crystalline with the wurtzite hexagonal phase and preferentially grow along the c-axis direction. Raman spectra of the as-grown ZnO nanorods showed an optical-phonon E2 mode at 438?cm?1, indicating that as-grown nanostructures are in good crystallinity with the wurtzite hexagonal phase. The ZnO nanorods were found to show strong band edge emission with very weak or no deep-level emission, as shown by photoluminescence measurements. The clear observation of free excitons at low temperatures (13?50?K) indicates that the as-grown ZnO nanorods are of high quality.

Patterns of Gray Matter Abnormalities in Schizophrenia Based on an International Mega-analysis

Abstract: Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects.