Abstract: A disclosed drum-type washing machine having a softening apparatus comprises: a cylindrical water tank accommodating laundry and having a rotating drum; a case for accommodating the water tank; and a softening apparatus having a hardness component remover for removing hardness components from washing water, and a regeneration agent accommodation unit spaced apart from the hardness component remover on opposite sides from a center of the tub, and for accommodating a regeneration agent that regenerates a function of the hardness component remover.

Abstract: A health improvement path search device including: a first model generating unit configured to generate a first model predicting a value of a health index; a second model generating unit configured to generate a second model deriving a presence probability; and a path searching unit configured to derive the value of the health index and the presence probability corresponding to each measurement target value specify a plurality of paths transitioning to each of the measurement target values from the current values as start points, specify paths in which the value of the health index at an end point is improved from the current value of the health index among the plurality of paths as candidate paths, and specify a path for which a product of the presence probabilities of the measurement target values included in the candidate path is a maximum as a health improvement path.

Abstract: The present invention provides markers for judging the efficacy of therapy with a PD-1 signal inhibitor before or at an early stage of the therapy. As biomarkers for predicting or judging the efficacy of therapy with a PD-1 signal inhibitor, surrogate indicators of metabolic changes relating to mitochondrial activity in T cells and/or T cell activation in a subject are used. As such indicators, intestinal flora-related metabolites in the serum or plasma, energy metabolism-related metabolites in the serum or plasma, amino acid metabolism-related metabolites and/or derivatives thereof in the serum of plasma, oxygen consumption rate and/or ATP turnover in peripheral blood CD8+ cells, amino acids in T cells, and T-bet in peripheral blood CD8+ cells may be used.

Abstract: When the interaction of a compound is predicted by using a computer, a technique to highly precisely design a compound having a novel structure has been required. A compound designing device is provided which includes an input unit configured to receive, at least about one or more query proteins, one or more pieces of query protein information corresponding to the one or more query proteins; and a processing unit configured to perform steps of (a) generating one or more pieces of compound information, (b) computing a score indicating interaction potential between a compound corresponding to the compound information and each of the one or more query proteins, (c) updating the compound information by an optimization method with reference to the score computed at step (b) such that the interaction potential increases, and (d) repeating steps (b) and (c) a plurality of times.

Abstract: A data processing method for an estimation of compound-protein interaction using both chemical substance information, such as a chemical property of the compound, and biological information, such as sequence information of genes to rationally and efficiently screen compounds. First space representing space coordinates of a first chemical substance group and second space representing space coordinates of a second chemical substance group are defined, and the first chemical substance group is characterized by a first characteristic amount and the second chemical substance group is characterized by a second characteristic amount, and map transformation of the coordinates of the first space and the coordinates of the second space results in the solution so as to increase the correlation between the first space and the second space using a multivariable analysis technique or a machine learning method.

Abstract: A data processing method for an estimation of compound-protein interaction using both chemical substance information, such as a chemical property of the compound, and biological information, such as sequence information of genes to rationally and efficiently screen compounds. First space representing space coordinates of a first chemical substance group and second space representing space coordinates of a second chemical substance group are defined, and the first chemical substance group is characterized by a first characteristic amount and the second chemical substance group is characterized by a second characteristic amount, and map transformation of the coordinates of the first space and the coordinates of the second space results in the solution so as to increase the correlation between the first space and the second space using a multivariable analysis technique or a machine learning method.