Electrical Investigation of the Oblique Hanle Effect in Ferromagnet/Oxide/Semiconductor Contacts

We have investigated the electrical Hanle effect with magnetic fields applied at an oblique angle ({\theta}) to the spin direction (the oblique Hanle effect, OHE) in CoFe/MgO/semiconductor (SC) contacts by employing a three-terminal measurement scheme. The electrical oblique Hanle signals obtained in CoFe/MgO/Si and CoFe/MgO/Ge contacts show clearly different line shapes depending on the spin lifetime of the host SC. Notably, at moderate magnetic fields, the asymptotic values of the oblique Hanle signals (in both contacts) are consistently reduced by a factor of cos^2({\theta}) irrespective of the bias current and temperature. These results are in good agreement with predictions of the spin precession and relaxation model for the electrical oblique Hanle effect. At high magnetic fields where the magnetization of CoFe is significantly tilted from the film plane to the magnetic field direction, we find that the observed angular dependence of voltage signals in the CoFe/MgO/Si and CoFe/MgO/Ge contacts are well explained by the OHE, considering the misalignment angle between the external magnetic field and the magnetization of CoFe.Comment: 19 pages, 8 figure

Axial strain dependence of all-fiber acousto-optic tunable filters

We report the axial strain dependence of two types of all-fiber acousto-optic tunable filters based on flexural and torsional acoustic waves. Experimental observation of the resonant wavelength shift under applied axial strain could be explained by theoretical consideration of the combination of acoustic and optical effects. We discuss the possibility of suppressing the strain effect in the filters, or conversely, the possibility of using the strain dependence for wavelength tuning or strain sensors

Computational Approach to Identify Enzymes That Are Potential Therapeutic Candidates for Psoriasis

Psoriasis is well known as a chronic inflammatory dermatosis. The disease affects persons of all ages and is a burden worldwide. Psoriasis is associated with various diseases such as arthritis. The disease is characterized by well-demarcated lesions on the skin of the elbows and knees. Various genetic and environmental factors are related to the pathogenesis of psoriasis. In order to identify enzymes that are potential therapeutic targets for psoriasis, we utilized a computational approach, combining microarray analysis and protein interaction prediction. We found 6,437 genes (3,264 upregulated and 3,173 downregulated) that have significant differences in expression between regions with and without lesions in psoriasis patients. We identified potential candidates through protein-protein interaction predictions made using various protein interaction resources. By analyzing the hub protein of the networks with metrics such as degree and centrality, we detected 32 potential therapeutic candidates. After filtering these candidates through the ENZYME nomenclature database, we selected 5 enzymes: DNA helicase (RUVBL2), proteasome endopeptidase complex (PSMA2), nonspecific protein-tyrosine kinase (ZAP70), I-kappa-B kinase (IKBKE), and receptor protein-tyrosine kinase (EGFR). We adopted a computational approach to detect potential therapeutic targets; this approach may become an effective strategy for the discovery of new drug targets for psoriasis

Electrical spin injection and accumulation in CoFe/MgO/Ge contacts at room temperature

We first report the all-electrical spin injection and detection in CoFe/MgO/moderately doped n-Ge contact at room temperature (RT), employing threeterminal Hanle measurements. A sizable spin signal of ~170 k{\Omega} {\mu}m^2 has been observed at RT, and the analysis using a single-step tunneling model gives a spin lifetime of ~120 ps and a spin diffusion length of ~683 nm in Ge. The observed spin signal shows asymmetric bias and temperature dependences which are strongly related to the asymmetry of the tunneling process.Comment: 28 pages, 5 figure

Predicting the Interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) play key roles in various cellular functions. In addition, some critical inter-species interactions such as host-pathogen interactions and pathogenicity occur through PPIs. Phytopathogenic bacteria infect hosts through attachment to host tissue, enzyme secretion, exopolysaccharides production, toxins release, iron acquisition, and effector proteins secretion. Many such mechanisms involve some kind of protein-protein interaction in hosts. Our first aim was to predict the whole protein interaction pairs (interactome) of <it>Xanthomonas oryzae </it>pathovar oryzae (Xoo) that is an important pathogenic bacterium that causes bacterial blight (BB) in rice. We developed a detection protocol to find possibly interacting proteins in its host using whole genome PPI prediction algorithms. The second aim was to build a DB server and a bioinformatic procedure for finding target proteins in Xoo for developing pesticides that block host-pathogen protein interactions within critical biochemical pathways.</p> <p>Description</p> <p>A PPI network in Xoo proteome was predicted by bioinformatics algorithms: PSIMAP, PEIMAP, and iPfam. We present the resultant species specific interaction network and host-pathogen interaction, XooNET. It is a comprehensive predicted initial PPI data for Xoo. XooNET can be used by experimentalists to pick up protein targets for blocking pathological interactions. XooNET uses most of the major types of PPI algorithms. They are: 1) Protein Structural Interactome MAP (PSIMAP), a method using structural domain of SCOP, 2) Protein Experimental Interactome MAP (PEIMAP), a common method using public resources of experimental protein interaction information such as HPRD, BIND, DIP, MINT, IntAct, and BioGrid, and 3) Domain-domain interactions, a method using Pfam domains such as iPfam. Additionally, XooNET provides information on network properties of the Xoo interactome.</p> <p>Conclusion</p> <p>XooNET is an open and free public database server for protein interaction information for Xoo. It contains 4,538 proteins and 26,932 possible interactions consisting of 18,503 (PSIMAP), 3,118 (PEIMAP), and 8,938 (iPfam) pairs. In addition, XooNET provides 3,407 possible interaction pairs between two sets of proteins; 141 Xoo proteins that are predicted as membrane proteins and rice proteomes. The resultant interacting partners of a query protein can be easily retrieved by users as well as the interaction networks in graphical web interfaces. XooNET is freely available from <url>http://bioportal.kobic.kr/XooNET/</url>.</p