1,376 research outputs found

    Selection of Color-Changing and Intensity-Increasing Fluorogenic Probe as Protein-Specific Indicator Obtained via the 10BASEd-T

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    To obtain a molecular probe for specific protein detection, we have synthesized fluorogenic probe library of vastdiversity on bacteriophage T7 via the gp10 based-thioetherificaion (10BASEd-T). A remarkable color-changing and turning-on probewas selected from the library, and its physicochemical properties upon target-specific binding were obtained. Combination analysesof fluorescence emission titration, isothermal titration calorimetry (ITC), and quantitative saturation-transfer difference (STD) NMRmeasurements followed by in silico docking simulation, rationalized most plausible geometry of the ligand-protein interaction

    Tetrahedron equation and quantum cluster algebras

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    We develop the quantum cluster algebra approach recently introduced by Sun and Yagi to investigate the tetrahedron equation, a three-dimensional generalization of the Yang-Baxter equation. In the case of square quiver, we devise a new realization of quantum Y-variables in terms qq-Weyl algebras and obtain a solution that possesses three spectral parameters. It is expressed in various forms, comprising four products of quantum dilogarithms depending on the signs in decomposing the quantum mutations into the automorphism part and the monomial part. For a specific choice of them, our formula precisely reproduces Sergeev's RR matrix, which corresponds to a vertex formulation of the Zamolodchikov-Bazhanov-Baxter model when qq is specialized to a root of unity.Comment: 24 page

    Quantum cluster algebras and 3D integrability: Tetrahedron and 3D reflection equations

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    We construct a new solution to the tetrahedron equation and the three-dimensional (3D) reflection equation by extending the quantum cluster algebra approach by Sun and Yagi concerning the former. We consider the Fock-Goncharov quivers associated with the longest elements of the Weyl groups of type AA and CC, and investigate the cluster transformations corresponding to changing a reduced expression into a `most distant' one. By devising a new realization of the quantum yy-variables in terms of qq-Weyl algebra, the solutions are extracted as the operators whose adjoint actions yield the cluster transformations of the quantum yy-variables. Explicit formulas of their matrix elements are also derived for some typical representations.Comment: 34 page

    <Preliminary>Components and Anti-fungal Efficiency of Wood-vinegar-liquor Prepared under Different Carbonization Conditions

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    この論文は国立情報学研究所の学術雑誌公開支援事業により電子化されました

    Involvement of Nitric Oxide in a Rat Model of Carrageenin-Induced Pleurisy

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    Some evidence indicates that nitric oxide (NO) contributes to inflammation, while other evidence supports the opposite conclusion. To clarify the role of NO in inflammation, we studied carrageenin-induced pleurisy in rats treated with an NO donor (NOC-18), a substrate for NO formation (L-arginine), and/or an NO synthase inhibitor (S-(2-aminoethyl) isothiourea or NG-nitro-L-arginine). We assessed inflammatory cell migration, nitrite/nitrate values, lipid peroxidation and pro-inflammatory mediators. NOC-18 and L-arginine reduced the migration of inflammatory cells and edema, lowered oxidative stress, and normalized antioxidant enzyme activities. NO synthase inhibitors increased the exudate formation and inflammatory cell number, contributed to oxidative stress, induced an oxidant/antioxidant imbalance by maintaining high O2−, and enhanced the production of pro-inflammatory mediators. L-arginine and NOC-18 reversed the proinflammatory effects of NO synthase inhibitors, perhaps by reducing the expression of adhesion molecules on endothelial cells. Thus, our results indicate that NO is involved in blunting—not enhancing—the inflammatory response

    Investigating the Generalizability of Deep Learning-based Clone Detectors

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    The generalizability of Deep Learning (DL) models is a significant challenge, as poor generalizability indicates that the model has overfitted to the training data and is not able to generalize to new data. Despite numerous DL-based clone detectors emerging in recent years, their generalizability has not been thoroughly assessed. This study investigates the generalizability of three DL-based clone detectors (CCLearner, ASTNN, and CodeBERT) by comparing their detection accuracy on different training and testing clone benchmarks. The results show that all three clone detectors do not generalize well to new data and there is a strong relationship between clone types and generalizability for CCLearner and ASTNN.Choi E., Fuke N., Fujiwara Y., et al. Investigating the Generalizability of Deep Learning-based Clone Detectors. IEEE International Conference on Program Comprehension 2023-May, 181 (2023); https://doi.org/10.1109/ICPC58990.2023.00032
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