Methods for analyzing a fluid sample can include providing a sensor comprising a non-conductive housing and having a first face and an electrode array mounted in the first face. The method can include disposing the first face of the housing into a fluid sample to be analyzed, selecting a mode of operation, and initiating sensor operation. Modes of operation can include electrochemical operation and conductivity analysis, and can be selected via positioning a switch. The method can include receiving information from the sensor regarding at least one parameter of the fluid. Such parameters can include a concentration of a target constituent in the fluid sample, combined concentrations of different species within the fluid sample, and/or information indicative of the conductivity of the fluid sample.

Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

The present invention relates to a novel azole derivative as an apelin receptor agonist and a method for treating cardiovascular disease, diabetic disease, renal disease, hypertension, and arteriosclerosis, etc., using the same. The present invention provides a compound represented by formula (I) or a pharmacologically acceptable salt thereof wherein X represents N or CH, X.sup.2 represents CH or N, R.sup.1 and R.sup.2 each represent a C.sub.1 to C.sub.6 alkoxy group or the like, R.sup.3 represents a heteroaryl group (the heteroaryl group is optionally substituted by a methyl group or the like) or the like, and R.sup.4 represents a C.sub.1 to C.sub.6 alkylthio group or a C.sub.2 to C.sub.6 alkenyl group (the C.sub.1 to C.sub.6 alkylthio group and the C.sub.2 to C.sub.6 alkenyl group are each optionally substituted by one carboxy group or the like) or the like.

##STR00001##

The present invention relates to a novel azole derivative as an apelin receptor agonist and a method for treating cardiovascular disease, diabetic disease, renal disease, hypertension, and arteriosclerosis, etc., using the same. The present invention provides a compound represented by formula (I) or a pharmacologically acceptable salt thereof wherein X represents N or CH, X.sup.2 represents CH or N, R.sup.1 and R.sup.2 each represent a C.sub.1 to C.sub.6 alkoxy group or the like, R.sup.3 represents a heteroaryl group (the heteroaryl group is optionally substituted by a methyl group or the like) or the like, and R.sup.4 represents a C.sub.1 to C.sub.6 alkylthio group or a C.sub.2 to C.sub.6 alkenyl group (the C.sub.1 to C.sub.6 alkylthio group and the C.sub.2 to C.sub.6 alkenyl group are each optionally substituted by one carboxy group or the like) or the like.

##STR00001##

A metabolized product ion spectrum is produced for a metabolized version of a known compound using tandem mass spectrometry. Metabolized structures are inferred from the metabolized product ion spectrum. An unmetabolized product ion spectrum is received for an unmetabolized version of the known compound and unmetabolized structures are inferred from the unmetabolized product ion spectrum. Each of the metabolized structures is compared to the unmetabolized structures, producing matched and unmatched structures. For each unmatched structure, a biotransformation repository is searched for modifications and each unmatched structure and the modifications found are again compared to the unmetabolized structures, producing modified matched structures. For each atomic index of the known compound, an unmodified specificity is calculated from the matched structures, a modified intensity specificity is calculated from the modified matched structures, and a score is calculated from the specificities. Atomic indices with the highest score are identified as sites of modification.

A metabolized product ion spectrum is produced for a metabolized version of a known compound using tandem mass spectrometry. Metabolized structures are inferred from the metabolized product ion spectrum. An unmetabolized product ion spectrum is received for an unmetabolized version of the known compound and unmetabolized structures are inferred from the unmetabolized product ion spectrum. Each of the metabolized structures is compared to the unmetabolized structures, producing matched and unmatched structures. For each unmatched structure, a biotransformation repository is searched for modifications and each unmatched structure and the modifications found are again compared to the unmetabolized structures, producing modified matched structures. For each atomic index of the known compound, an unmodified specificity is calculated from the matched structures, a modified intensity specificity is calculated from the modified matched structures, and a score is calculated from the specificities. Atomic indices with the highest score are identified as sites of modification.

A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

The present invention provides an evaluating system and the use thereof for the efficacy of antimicrobial peptide, which includes the following steps: (a) constructing a peptide by a first input unit, and load the peptide into an aqueous solution for a first time for equilibration; (b) constructing a lipid bilayer by a second input unit, and load the lipid bilayer into an aqueous solution for a second time for equilibration; (c) Using a first processing unit, simulations are carried out for an aqueous system containing an equilibrated peptide from the first input unit and the equilibrated lipid bilayer from the second input unit; (d) calculating the partition free energy of the peptide by a second processing unit; (e) outputting the prediction by an output unit, wherein the output unit is connected with the first processing unit and the second processing unit.

The present invention provides an evaluating system and the use thereof for the efficacy of antimicrobial peptide, which includes the following steps: (a) constructing a peptide by a first input unit, and load the peptide into an aqueous solution for a first time for equilibration; (b) constructing a lipid bilayer by a second input unit, and load the lipid bilayer into an aqueous solution for a second time for equilibration; (c) Using a first processing unit, simulations are carried out for an aqueous system containing an equilibrated peptide from the first input unit and the equilibrated lipid bilayer from the second input unit; (d) calculating the partition free energy of the peptide by a second processing unit; (e) outputting the prediction by an output unit, wherein the output unit is connected with the first processing unit and the second processing unit.