Collinear and noncollinear spin structures of wurtzite phase CoO often appearing in nanosized samples are investigated using first-principles density functional theory calculations. We examined the total energy of several different spin configurations, electronic structure, and the effective magnetic coupling strengths. It is shown that the AF3-type antiferromagnetic ordering is energetically most stable among possible collinear configurations. Further, we found that a spiral spin order can be stabilized by including the relativistic spin-orbit coupling and the noncollinearity of spin direction. Our result suggests that a noncollinear spin ground state can be observed in the transition-metal-oxide nanostructures, which adds an interesting aspect to the nanomagnetism study.

We investigated the electronic structure of multiferroic hexagonal RMnO 3 (R = Gd, Tb, Dy, and Ho) thin films using both optical spectroscopy and first-principles calculations. One of the difficulties in explaining the electronic structures of hexagonal RMnO 3 is that they exist in nature with limited rare earth ions (i.e., R = Sc, Y, Ho -Lu), so a systematic study in terms of the different R ions has been lacking. Recently, our group succeeded in fabricating hexagonal RMnO 3 (R = Gd, Tb, and Dy) using the epitaxial stabilization technique [Adv. Mater. 18, 3125 (2006)]. Using artificially stabilized hexagonal RMnO 3 , we extended the optical spectroscopic studies on the hexagonal multiferroic manganite system. We observed two optical transitions located near 1.7 eV and 2.3 eV, in addition to the predominant absorption above 5 eV. With the help of first-principles calculations, we attribute the low-lying optical absorption peaks to inter-site transitions from the oxygen states hybridized strongly with different Mn orbital symmetries to the Mn 3d 3z 2 -r 2 state. As the ionic radius of the rare earth ion increased, the lowest peak showed a systematic increase in its peak position. We explained this systematic change in terms of a flattening of the MnO 5 triangular bipyramid.

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Numerous clinical trials of drug candidates for Alzheimer's disease (AD) have failed, and computational drug repositioning approaches using omics data have been proposed as effective alternative approaches to the discovery of drug candidates. However, little multiomics data is available for AD, due to limited availability of brain tissues. Even if omics data exist, systematic drug repurposing study for AD has suffered from lack of big data, insufficient clinical information, and difficulty in data integration on account of sample heterogeneity derived from poor diagnosis or shortage of qualified post-mortem tissue. In this study, we developed a proteotranscriptomic-based computational drug repositioning method named Drug Repositioning Perturbation Score/Class (DRPS/C) based on inverse associations between disease-and drug-induced gene and protein perturbation patterns, incorporating pharmacogenomic knowledge. We constructed a Drug-induced Gene Perturbation Signature Database (DGPSD) comprised of 61,019 gene signatures perturbed by 1,520 drugs from the Connectivity Map (CMap) and the L1000 CMap. Drugs were classified into three DRPCs (High, Intermediate, and Low) according to DRPSs that were calculated using drug-and disease-induced gene perturbation signatures from DGPSD and The Cancer Genome Atlas (TCGA), respectively. The DRPS/C method was evaluated using the area under the ROC curve, with a prescribed drug list from TCGA as the gold standard. Glioblastoma had the highest AUC. To predict anti-AD drugs, DRPS were calculated using DGPSD and AD-induced gene/protein perturbation signatures generated from RNA-seq, microarray and proteomic datasets in the Synapse database, and the drugs were classified into DRPCs. We predicted 31 potential anti-AD drug candidates commonly belonged to high DRPCs of transcriptomic and proteomic signatures. Of these, four drugs classified into the nervous system group of Anatomical Therapeutic Chemical (ATC) system are voltage-gated sodium channel blockers (bupivacaine, topiramate) and monamine oxidase inhibitors (selegiline, iproniazid), and their mechanism of action was inferred from a potential anti-AD drug perspective. Our approach suggests a shortcut to discover new efficacy of drugs for AD.