WO2020203878A1 - Evaluating method, calculating method, evaluating device, calculating device, evaluating program, calculating program, storage medium, evaluating system, and terminal device of amyloid beta accumulation in brain - Google Patents

Evaluating method, calculating method, evaluating device, calculating device, evaluating program, calculating program, storage medium, evaluating system, and terminal device of amyloid beta accumulation in brain Download PDF

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WO2020203878A1
WO2020203878A1 PCT/JP2020/014303 JP2020014303W WO2020203878A1 WO 2020203878 A1 WO2020203878 A1 WO 2020203878A1 JP 2020014303 W JP2020014303 W JP 2020014303W WO 2020203878 A1 WO2020203878 A1 WO 2020203878A1
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mecys
ser
orn
evaluation
value
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PCT/JP2020/014303
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French (fr)
Japanese (ja)
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由紀 矢野
直子 嵐田
和 佐藤
日比　滋樹
武彦 宮川
清明 小林
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味の素株式会社
エーザイ・アール・アンド・ディー・マネジメント株式会社
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Priority to JP2021512064A priority Critical patent/JP7543251B2/en
Publication of WO2020203878A1 publication Critical patent/WO2020203878A1/en

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    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
    • C07K14/46—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans from vertebrates
    • C07K14/47—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans from vertebrates from mammals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids

Definitions

  • the present invention relates to an evaluation method, calculation method, evaluation device, calculation device, evaluation program, calculation program, recording medium, evaluation system, and terminal device for the accumulation of amyloid beta (hereinafter referred to as “A ⁇ ”) in the brain. Is.
  • Alzheimer-type dementia is a dementia caused by Alzheimer's disease (AD) and accounts for about 50% of the number of dementia patients.
  • a pathological feature of AD is that a protein called "A ⁇ " aggregates and deposits in brain tissue and forms amyloid plaques called senile plaques as the condition progresses. It has been reported that the accumulation of A ⁇ in the brain begins about 20 years before the onset of AD (Non-Patent Documents 1 and 2). In response to this, in recent years, research and development of pathological modifiers based on the premise that treatment in the prodromal and prodromical stages, which are the preclinical stages, is required (Non-Patent Document 3).
  • Non-Patent Document 4 As a method for evaluating the presence or absence of accumulation of A ⁇ in the brain, measurement of A ⁇ 42 concentration in cerebrospinal fluid (Non-Patent Document 4) and amyloid PET imaging (non-patient) using positron emission tomography (Positron Emission Tomography) Patent documents 5 and 6) are mainly mentioned.
  • the measured values differ depending on the measurement facility, the measured values vary depending on the collection method and storage conditions, and the sample collection is invasive because it involves lumbar puncture.
  • Amyloid PET imaging has problems that it is invasive by radiation, the examination cost is high, and there are few medical institutions that can perform it due to equipment restrictions, so it is difficult to spread it in actual medical care. ..
  • Non-Patent Document 7 the quantitative value of A ⁇ fragments in blood correlates with the accumulation of A ⁇ in the brain.
  • amyloid PET a report for the Amyloid imaging Task Force, the Society of Nuclear Medicine and Molecular Imagine Johnson et al., Alzheimers Dement. (2013) 9 (4): e106-e109; Update on appropriate use criteria for amyloid PET imaging: dementia experts, mild cognitive impairment, and education.Amyloid Imaging Task Medicine and Molecular Imaging. Nakamura et al., Nature. (2016) 8; 554 (7691): 249-254; High performance plasma amyloid- ⁇ biomarkers for Alzheimer's disease.
  • the present invention has been made in view of the above, and is an evaluation method, a calculation method, an evaluation device, and a calculation capable of providing highly reliable information that can be used as a reference for knowing the state of accumulation of A ⁇ in the brain.
  • An object of the present invention is to provide an apparatus, an evaluation program, a calculation program, a recording medium, an evaluation system, and a terminal apparatus.
  • the method for evaluating the state of accumulation of A ⁇ in the brain according to the present invention is to evaluate 24 kinds of amino acids (Ala, Arg, Asn, Cit) in the blood to be evaluated.
  • the evaluation step is that Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, etc. in the blood to be evaluated.
  • the evaluation step uses at least one of the age, gender, BMI (Body Mass Index) and MMSE (Mini Mental State Evaluation) scores of the evaluation target and the measured value.
  • the formula containing at least one of the age, gender, BMI and MMSE scores and a variable to which the measurement is assigned, the age, gender, at least one of the BMI and MMSE scores and said It is characterized in that the state of accumulation of A ⁇ in the brain is evaluated for the evaluation target by using the value of the above formula calculated using the measured value.
  • the evaluation method according to the present invention is characterized in that the evaluation step is executed in the control unit of the information processing device provided with the control unit.
  • the method for calculating the value of the formula for evaluating the state of accumulation of A ⁇ in the brain is among the 24 types of amino acids and the 26 types of amino acid-related metabolites in the blood to be evaluated. Including a calculation step of calculating the value of the formula using at least one measurement of the above and a formula for evaluating the state of accumulation of A ⁇ in the brain containing the variable to which the measurement is assigned. It is characterized by.
  • the calculation method according to the present invention is characterized in that the calculation step is executed in the control unit of the information processing device provided with the control unit.
  • the device for evaluating the state of accumulation of A ⁇ in the brain includes a control unit, which controls the 24 types of amino acids and the 26 types of amino acid-related metabolites in the blood to be evaluated. Using at least one of the measured values, or a formula containing a variable to which the measured value is assigned, and the value of the formula calculated using the measured value, the evaluation target is introduced into the brain of A ⁇ . It is characterized by providing an evaluation means for evaluating the state of accumulation of.
  • the evaluation means is Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, etc. in the blood to be evaluated.
  • the evaluation means uses at least one of the age, gender, BMI and MMSE scores of the evaluation target and the measured value, or the age, gender, BMI and MMSE.
  • the formula including at least one of the scores and the variable to which the measured value is assigned, the age, gender, BMI and MMSE score of the evaluation target, and the formula calculated using the measured value.
  • the value is used to evaluate the state of accumulation of amyloid beta in the brain for the evaluation target.
  • the evaluation device is communicably connected to a terminal device that provides measurement data related to the measured value or the value of the formula via a network, and the control unit is transmitted from the terminal device.
  • a data receiving means for receiving the measurement data or the value of the formula and a result transmitting means for transmitting the evaluation result obtained by the evaluation means to the terminal device are further provided, and the evaluation means is the data receiving means. It is characterized in that the measured value or the value of the formula included in the received measurement data is used.
  • the device for calculating the value of the formula for evaluating the state of accumulation of A ⁇ in the brain includes a control unit, and the control unit contains the 24 kinds of amino acids in the blood to be evaluated and the above-mentioned 24 kinds of amino acids.
  • the formula is used to evaluate at least one measurement of the 26 amino acid-related metabolites and the state of accumulation of A ⁇ in the brain, including the variable to which the measurement is assigned. It is characterized in that it is provided with a calculation means for calculating the value of.
  • the evaluation program for the state of accumulation of A ⁇ in the brain includes the 24 kinds of amino acids in the blood to be evaluated and the above-mentioned 24 kinds of amino acids to be executed in the control unit of the information processing apparatus including the control unit.
  • the calculation program of the value of the formula for evaluating the state of accumulation of A ⁇ in the brain is in the blood to be evaluated for execution in the control unit of the information processing apparatus including the control unit.
  • To evaluate the state of accumulation of A ⁇ in the brain including the measured value of at least one of the 24 kinds of amino acids and the 26 kinds of amino acid-related metabolites, and the variable to which the measured value is assigned. It is characterized by including a calculation step of calculating the value of the formula using the formula.
  • the recording medium according to the present invention is a computer-readable recording medium on which the evaluation program or the calculation program is recorded.
  • the recording medium according to the present invention is a non-temporary computer-readable recording medium, and includes a programmed instruction for causing an information processing apparatus to execute the evaluation method or the calculation method. , Is a feature.
  • the evaluation system for the state of accumulation of A ⁇ in the brain includes an evaluation device including a control unit for evaluating the state of accumulation of A ⁇ in the brain and a terminal device including a control unit. It is configured to be communicably connected via a network, and the control unit of the terminal device measures at least one of the 24 types of amino acids and the 26 types of amino acid-related metabolites in the blood to be evaluated.
  • a data transmission means for transmitting the measurement data relating to the data, an expression including a variable to which the measurement value is assigned, and the value of the expression calculated using the measurement value to the evaluation device, and transmission from the evaluation device.
  • the measurement data is provided by a result receiving means for receiving the evaluation result regarding the state of accumulation of A ⁇ in the brain of the evaluation target, and the control unit of the evaluation device is transmitted from the terminal device.
  • the evaluation target is introduced into the brain of A ⁇ . It is characterized by including an evaluation means for evaluating the state of accumulation of the data, and a result transmission means for transmitting the evaluation result obtained by the evaluation means to the terminal device.
  • the terminal device is a terminal device including a control unit, and the control unit provides a result acquisition means for acquiring an evaluation result regarding a state of accumulation of A ⁇ in the brain of an evaluation target.
  • the evaluation result includes a measured value of at least one of the 24 kinds of amino acids and the 26 kinds of amino acid-related metabolites in the blood to be evaluated, or a variable to which the measured value is assigned. It is a result of evaluating the state of accumulation of A ⁇ in the brain of the evaluation target by using the value of the formula calculated by using the measured value.
  • the terminal device is communicably connected to the evaluation device for evaluating the state of accumulation of A ⁇ in the brain of the evaluation target via a network, and the control unit is connected to the measured value.
  • the data transmission means for transmitting the measurement data or the value of the above formula to the evaluation device is provided, and the result acquisition means receives the evaluation result transmitted from the evaluation device.
  • FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment.
  • FIG. 2 is a principle configuration diagram showing the basic principle of the second embodiment.
  • FIG. 3 is a diagram showing an example of the overall configuration of this system.
  • FIG. 4 is a diagram showing another example of the overall configuration of the system.
  • FIG. 5 is a block diagram showing an example of the configuration of the evaluation device 100 of this system.
  • FIG. 6 is a diagram showing an example of information stored in the measurement data file 106a.
  • FIG. 7 is a diagram showing an example of information stored in the index state information file 106b.
  • FIG. 8 is a diagram showing an example of information stored in the designated index state information file 106c.
  • FIG. 9 is a diagram showing an example of information stored in the formula file 106d1.
  • FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment.
  • FIG. 2 is a principle configuration diagram showing the basic principle of the second embodiment.
  • FIG. 3 is a diagram showing an example of
  • FIG. 10 is a diagram showing an example of information stored in the evaluation result file 106e.
  • FIG. 11 is a block diagram showing the configuration of the evaluation unit 102d.
  • FIG. 12 is a block diagram showing an example of the configuration of the client device 200 of this system.
  • FIG. 13 is a block diagram showing an example of the configuration of the database device 400 of this system.
  • first embodiment an embodiment of the evaluation method and the calculation method according to the present invention
  • second embodiment an embodiment of the terminal device will be described in detail with reference to the drawings. The present invention is not limited to these embodiments.
  • FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment.
  • Acquire measurement data regarding the measured value of the substance (step S11).
  • an individual having or suspected of having mild cognitive impairment or early Alzheimer's disease eg, having or suspected of having mild cognitive impairment or early Alzheimer's disease based on existing diagnostic criteria for mild cognitive impairment or early Alzheimer's disease). (Individuals diagnosed as having) may be evaluated.
  • the measured value is, for example, a concentration value, a peak area value, or a ratio of concentration values.
  • BCAA branched-chain amino acids
  • the concentration value of BCAA means the sum of the concentration values of Leu, Ile and Val.
  • step S11 measurement data regarding the substance measured by a company or the like may be acquired.
  • the concentration value of the substance may be obtained from the blood collected from the evaluation target by measuring the concentration value of the substance by the following measuring methods such as (A), (B) or (C). ..
  • the unit of the concentration value of the substance may be, for example, a molar concentration, a weight concentration, or an enzyme activity, and may be obtained by adding, subtracting, multiplying, or dividing an arbitrary constant to these concentrations.
  • A Plasma is separated from blood by centrifuging the collected blood sample. All plasma samples are cryopreserved at -80 ° C until the concentration value is measured.
  • acetonitrile is added to perform derivatization treatment, and if necessary, contaminants such as phospholipids are removed by solid layer extraction or the like, and a labeling reagent (3-aminopyridyl-N-hydroxysuccinimidimi) is removed.
  • a labeling reagent (3-aminopyridyl-N-hydroxysuccinimidimi) is removed.
  • Pre-column derivatization is performed using dizyl carbamate), and concentration values are analyzed by liquid chromatography-mass spectrometry (including tandem mass spectrometry) (International Publication No. 2003/066283, International Publication No. 2005/116629). See).
  • (B) Plasma is separated from blood by centrifuging the collected blood sample. All plasma samples are cryopreserved at -80 ° C until the concentration value is measured.
  • sulfosalicylic acid is added to perform deproteinization treatment, and then the concentration value is analyzed by an amino acid analyzer based on the post-column derivatization method using a ninhydrin reagent.
  • C The collected blood sample is subjected to blood cell separation using a membrane, MEMS (Micro Electro Mechanical Systems) technology or the principle of centrifugation, and plasma or serum is separated from the blood. Plasma or serum samples for which concentration values are not measured immediately after acquisition are cryopreserved at ⁇ 80 ° C. until concentration values are measured.
  • a molecule that reacts with or binds to a target blood substance such as an enzyme or an aptamer is used, and the concentration value is analyzed by quantifying the substance that increases or decreases due to substrate recognition or the spectroscopic value.
  • step S12 the state of accumulation of A ⁇ in the brain of the evaluation target is evaluated using the measured values included in the measurement data acquired in step S11 (step S12).
  • evaluating the state of accumulation of A ⁇ in the brain means, for example, evaluating the current amount of accumulation of A ⁇ in the brain or evaluating the positive or negative of A ⁇ . Note that data such as missing values and outliers may be removed from the measurement data acquired in step S11 before executing step S12.
  • the measurement data of the evaluation target is acquired in step S11, and in step S12, the measurement value included in the measurement data acquired in step S11 is used to move the evaluation target into the brain of A ⁇ .
  • Evaluate the state of accumulation of A ⁇ (in short, acquire information for evaluating the state of accumulation of A ⁇ in the brain for the evaluation target).
  • This makes it possible to provide highly reliable information that can be used as a reference for knowing the state of accumulation of A ⁇ in the brain for the evaluation target.
  • step S12 the accumulation of A ⁇ in the brain of the evaluation target is performed by calculating the value of the formula using the measured value of the at least one substance and the formula including the variable to which the measured value is substituted.
  • the condition may be evaluated.
  • the measured value or the value of the formula of at least one substance reflects the state of accumulation of A ⁇ in the brain for the evaluation target, and further, the measured value or the value of the formula may be determined.
  • the value may be converted by, for example, the method described below, and it may be determined that the converted value reflects the state of accumulation of A ⁇ in the brain for the evaluation target.
  • the measured value or the value of the formula or the converted value itself may be treated as an evaluation result regarding the state of accumulation of A ⁇ in the brain for the evaluation target.
  • the conversion method will be described below. In the following description, the measured value is the conversion target, but the same applies when the value of the equation is the conversion target.
  • the possible range of measured values is a predetermined range (for example, 0.0 to 1.0, 0.0 to 10.0, 0.0 to 100.0, or -10.0 to -10.0.
  • a predetermined range for example, 0.0 to 1.0, 0.0 to 10.0, 0.0 to 100.0, or -10.0 to -10.0.
  • any value can be added, subtracted, multiplied, divided, or the measured value can be converted into a predetermined conversion method (for example, exponential conversion, logarithmic conversion, etc.). Convert the measured value by converting it with angle conversion, square root conversion, probit conversion, reciprocal conversion, Box-Cox conversion, or power conversion, etc., or by combining these calculations with the measured value. You may.
  • the value of an exponential function with the measured value as an index and the base of the Napier number (specifically, the state of accumulation of A ⁇ in the brain is a predetermined state (for example, a state of being greater than the reference value)).
  • the value of p / (1-p) when the natural logarithm ln (p / (1-p)) when the probability p is defined is equal to the measured value) may be further calculated, or calculated.
  • a value obtained by dividing the value of the exponential function by the sum of 1 and the value (specifically, the value of the probability p) may be further calculated.
  • the measured value may be converted so that the converted value under a specific condition becomes a specific value.
  • the measured value may be converted so that the converted value when the specificity is 80% is 5.0 and the converted value when the specificity is 95% is 8.0.
  • the distribution of the measured values may be normally distributed and then deviated so as to have an average of 50 and a standard deviation of 10.
  • these conversions may be performed by gender or age.
  • the measured value in the present specification may be the measured value itself or the value after converting the measured value.
  • the value of the expression in the present specification may be the value of the expression itself or the value after converting the value of the expression.
  • the position information regarding the position of a predetermined mark on a predetermined measuring rod that is visually displayed on a display device such as a monitor or a physical medium such as paper is a measured value or a formula value of the at least one substance or the measured value.
  • a display device such as a monitor or a physical medium such as paper
  • the predetermined measuring rod is for evaluating the state of accumulation of A ⁇ in the brain. For example, it is a measuring rod with a scale shown, and is "a measured value or a value of an expression or a value after conversion".
  • the predetermined mark corresponds to the measured value or the value of the formula or the value after conversion, and is, for example, a circle mark or a star mark.
  • the measured value of at least one substance is lower than or less than a predetermined value (mean value ⁇ 1SD, 2SD, 3SD, N quantile, N percentile, cutoff value having clinical significance, etc.).
  • a predetermined value mean value ⁇ 1SD, 2SD, 3SD, N quantile, N percentile, cutoff value having clinical significance, etc.
  • the state of accumulation of A ⁇ in the brain may be evaluated for the evaluation target.
  • the deviation value may be used instead of the measured value itself. For example, when the deviation value is less than the mean value-2SD (when the deviation value ⁇ 30) or when the deviation value is higher than the mean value + 2SD (when the deviation value> 70), the accumulation of A ⁇ in the brain for the evaluation target The state of may be evaluated.
  • the degree of accumulation of A ⁇ in the brain in the evaluation target may be qualitatively evaluated. Specifically, "a measurement of at least one substance and one or more preset thresholds" or "a measurement of at least one substance, an expression containing a variable to which the measurement is assigned, and Using one or more preset thresholds, the evaluation target is classified into one of a plurality of categories defined at least considering the degree of accumulation of A ⁇ in the brain. May be good.
  • the plurality of categories include a category for belonging to a subject having a large amount of A ⁇ accumulated in the brain, a category for belonging a subject having a small amount of A ⁇ accumulated in the brain, and a category for belonging to a subject having a small amount of A ⁇ accumulated in the brain.
  • Divisions for belonging moderate objects may be included.
  • the plurality of categories may include a category for belonging a subject having a large amount of A ⁇ accumulated in the brain and a category for belonging a subject having a small amount of A ⁇ accumulated in the brain.
  • the measured value or the value of the formula may be converted by a predetermined method, and the evaluation target may be classified into any one of a plurality of categories using the converted value.
  • the format of the formula used for evaluation is not particularly limited, but may be, for example, the following format.
  • Linear models such as multiple regression equations, linear discriminant equations, principal component analysis, canonical discriminant analysis based on the least square method
  • Generalized linear models such as logistic regression and Cox regression based on the most likely method
  • Generalized linear mixed model considering variable effects such as individual differences and facility differences-Formulas created by cluster analysis such as K-means method and hierarchical cluster analysis-MCMC (Markov chain Monte Carlo method), Bayesian network, Expressions created based on Bayesian statistics such as the hierarchical Bayes method
  • Expressions created by classification such as support vector machines and decision trees
  • Expressions created by methods that do not belong to the above categories such as discriminant equations ⁇ Sum of expressions of different formats Expression as shown by
  • the formula used for evaluation is described in, for example, the method described in International Publication No. 2004/052191, which is an international application by the applicant, or International Publication No. 2006/098192, which is an international application by the applicant. It may be created by the method.
  • the formula is used for the accumulation of A ⁇ in the brain regardless of the unit of the measured value of the amino acid and / or the amino acid-related metabolite in the measurement data as input data. It can be suitably used for evaluating the state.
  • a coefficient and a constant term are added to each variable, and the coefficient and the constant term may be preferably a real number, more preferably.
  • each coefficient and its confidence interval may be obtained by multiplying it by a real number
  • the value of the constant term and its confidence interval may be obtained by adding, subtracting, multiplying or dividing an arbitrary real constant.
  • the numerator of the fractional expression is represented by the sum of variables A, B, C, ... And / or the denominator of the fractional expression is the sum of variables a, b, c, ... It is represented by.
  • the fractional formula also includes the sum of the fractional formulas ⁇ , ⁇ , ⁇ , ... (For example, ⁇ + ⁇ ) having such a configuration.
  • the fractional expression also includes a divided fractional expression.
  • the variables used for the numerator and denominator may have appropriate coefficients. Also, the variables used for the numerator and denominator may be duplicated. In addition, an appropriate coefficient may be added to each fractional formula.
  • each variable and the value of the constant term may be real numbers.
  • a certain denominator formula and the one in which the variable of the molecule and the variable of the denominator are exchanged in the denominator formula generally reverse the positive and negative signs of the correlation with the objective variable, but the correlation between them is maintained. Since the evaluation performance can be regarded as equivalent, the fractional expression includes the variable of the molecule and the variable of the denominator exchanged.
  • values related to other biological information may be further used in addition to the measured values of at least one substance. .. Further, in the formula used at the time of evaluation, in addition to the variable to which the measured value of at least one substance is substituted, one or one to which a value related to other biological information (for example, the value listed below) is substituted. Multiple variables may be further included.
  • Concentration values of amino acids and other blood metabolites sucgars, lipids, etc.
  • proteins, peptides, minerals, hormones, etc. other than amino acid-related metabolites 2.
  • Albumin total protein, triglyceride (neutral fat), HbA1c, glycated albumin, insulin resistance index, total cholesterol, LDL cholesterol, HDL cholesterol, amylase, total bilirubin, creatinine, estimated glomerular filtration rate (eGFR), uric acid, GOT Blood tests for (AST), GPT (ALT), GGTP ( ⁇ -GTP), glucose (blood glucose level), CRP (C-reactive protein), red blood cells, hemoglobin, hematocrit, MCV, MCH, MCHC, leukocytes, platelet count, etc. Value 3. 3. Values obtained from image information such as ultrasonic echo, X-ray, CT, MRI, and endoscopic image.
  • image information such as ultrasonic echo, X-ray, CT, MRI, and endoscopic image.
  • FIG. 2 is a principle configuration diagram showing the basic principle of the second embodiment.
  • the description overlapping with the above-described first embodiment may be omitted.
  • a case where the value of the formula or the value after conversion thereof is used when evaluating the state of accumulation of A ⁇ in the brain is described as an example.
  • “the above 24 kinds of amino acids and The measured value of at least one substance of the "26 kinds of amino acid-related metabolites” or the value after conversion thereof (for example, deviation value) may be used.
  • the control unit is substituted with the measured value included in the measured data of the evaluation target (for example, an individual such as an animal or a human) acquired in advance regarding the measured value of the at least one substance in the blood and the measured value of the at least one substance.
  • the measured value included in the measured data of the evaluation target for example, an individual such as an animal or a human
  • the state of accumulation of A ⁇ in the brain of the evaluation target is evaluated (step S21). This makes it possible to provide highly reliable information that can be used as a reference for knowing the state of accumulation of A ⁇ in the brain.
  • step S21 may be one created based on the formula creation process (steps 1 to 4) described below.
  • the outline of the expression creation process will be described.
  • the process described here is just an example, and the method of creating an expression is not limited to this.
  • a plurality of different formula creation methods are performed from the index state information.
  • a plurality of candidate formulas may be created in combination with those related to multivariate analysis such as trees.
  • a plurality of different algorithms for index state information which is multivariate data composed of measurement data and index data obtained by analyzing blood obtained from a plurality of persons having various degrees of A ⁇ accumulation. May be used to create multiple groups of candidate expressions in parallel.
  • discriminant analysis and logistic regression analysis may be performed simultaneously using different algorithms to create two different candidate formulas.
  • the candidate formula may be created by converting the index state information using the candidate formula created by performing the principal component analysis and performing discriminant analysis on the converted index state information. As a result, the optimum formula for evaluation can be finally created.
  • the candidate formula created using principal component analysis is a linear formula that includes each variable that maximizes the variance of all measurement data.
  • the candidate formula created using discriminant analysis is a higher-order formula (including exponents and logarithms) that includes each variable that minimizes the ratio of the sum of the variances within each group to the variances of all measured data. is there.
  • the candidate expression created using the support vector machine is a high-order expression (including a kernel function) including each variable that maximizes the boundary between groups.
  • the candidate formula created by using the multiple regression analysis is a higher-order formula including each variable that minimizes the sum of the distances from all the measurement data.
  • the candidate formula created by using Cox regression analysis is a linear model including a logarithmic hazard ratio, and is a linear formula including each variable and its coefficient that maximizes the likelihood of the model.
  • the candidate formula created by using logistic regression analysis is a linear model representing the logarithmic odds of the probability, and is a linear formula including each variable that maximizes the likelihood of the probability.
  • k-means method k neighborhoods of each measurement data are searched, the group to which the neighborhood points belong is defined as the group to which the data belongs, and the group to which the input measurement data belongs. This is a method of selecting a variable that best matches the group defined as.
  • cluster analysis is a method of clustering (grouping) points at the closest distance among all measurement data.
  • the decision tree is a method of ordering variables and predicting a group of measurement data from possible patterns of variables having a higher rank.
  • the control unit verifies (mutually verifies) the candidate formula created in step 1 based on a predetermined verification method (step 2).
  • the verification of the candidate formula is performed for each candidate formula created in step 1.
  • the discrimination rate, sensitivity, specificity, information criterion, ROC_AUC (ROC_AUC) of the candidate formula are based on at least one of the bootstrap method, the holdout method, the N-fold method, and the leave one-out method. At least one of (the area under the curve of the receiver characteristic curve) and the like may be verified.
  • the discrimination rate is an evaluation method according to the present embodiment, in which an evaluation target whose true state is negative (for example, an evaluation target diagnosed as A ⁇ negative) is correctly evaluated as negative, and the true state is determined.
  • This is the ratio at which a positive evaluation target (for example, an evaluation target diagnosed as A ⁇ positive) is correctly evaluated as positive.
  • the sensitivity is a ratio in which the evaluation target whose true state is positive is correctly evaluated as positive in the evaluation method according to the present embodiment.
  • the specificity is the ratio at which the evaluation target whose true state is negative is correctly evaluated as negative in the evaluation method according to the present embodiment.
  • the Akaike Information Criterion is a standard that indicates how well the observed data matches the statistical model in the case of regression analysis, etc., and is "-2 x (maximum log-likelihood of the statistical model) + 2 x (statistics).
  • the model with the smallest value defined in "Number of free parameters of the model)" is judged to be the best.
  • the value of is 1 in the complete discrimination, and the closer this value is to 1, the higher the discrimination.
  • the predictability is an average of the discrimination rate, sensitivity, and specificity obtained by repeating the verification of the candidate formula.
  • Robustness is a variance of discrimination rate, sensitivity, and specificity obtained by repeating verification of candidate formulas.
  • the control unit selects the variable of the candidate formula based on the predetermined variable selection method, and selects the combination of the measurement data included in the index state information used when creating the candidate formula. (Step 3).
  • the variable may be selected for each candidate formula created in step 1. This makes it possible to appropriately select the variables of the candidate expression.
  • step 1 is executed again using the index state information including the measurement data selected in step 3.
  • a variable of the candidate formula may be selected based on at least one of the stepwise method, the best path method, the neighborhood search method, and the genetic algorithm from the verification result in step 2.
  • the best path method is a method of selecting variables by sequentially reducing the variables included in the candidate formula one by one and optimizing the evaluation index given by the candidate formula.
  • the control unit repeatedly executes the above-mentioned steps 1, 2 and 3 and, based on the verification results accumulated by this, is a candidate to be used in the evaluation from among a plurality of candidate formulas.
  • the formula used for the evaluation is created (step 4).
  • candidate formulas for example, there are cases where the optimum one is selected from the candidate formulas created by the same formula creation method and cases where the optimum one is selected from all the candidate formulas.
  • the processes related to the creation of the candidate expression, the verification of the candidate expression, and the selection of the variable of the candidate expression are systematized (systematized) in a series of flows based on the index state information.
  • an optimal formula can be created for assessing the accumulation of A ⁇ in the brain.
  • the measured values of at least one substance are used for multivariate statistical analysis, and the variable selection method and cross-validation are combined to select the optimum and robust set of variables to evaluate the evaluation performance. Extract high equations.
  • FIG. 3 is a diagram showing an example of the overall configuration of this system.
  • FIG. 4 is a diagram showing another example of the overall configuration of this system.
  • this system includes an evaluation device 100 that evaluates the state of accumulation of A ⁇ in the brain of an individual to be evaluated, and individual measurement data regarding the measured values of at least one substance in the blood.
  • the client device 200 (corresponding to the terminal device of the present invention) is connected to the client device 200 (corresponding to the terminal device of the present invention) so as to be communicable via the network 300.
  • the client device 200 that provides the data used for the evaluation and the client device 200 that provides the evaluation result may be different.
  • this system is a database device that stores index state information used when creating an expression in the evaluation device 100, an expression used in the evaluation, and the like, in addition to the evaluation device 100 and the client device 200.
  • the 400 may be connected and configured so as to be communicable via the network 300. This is a reference for knowing the state of accumulation of A ⁇ in the brain from the evaluation device 100 to the client device 200 or the database device 400, or from the client device 200 or the database device 400 to the evaluation device 100 via the network 300. Information and so on are provided.
  • the information that can be used as a reference for knowing the state of accumulation of A ⁇ in the brain includes, for example, information on values measured for a specific item related to the state of accumulation of A ⁇ in the brain of an organism including humans. Is.
  • information that can be used as a reference for knowing the state of accumulation of A ⁇ in the brain is generated by the evaluation device 100, the client device 200, and other devices (for example, various measuring devices), and is mainly stored in the database device 400. Accumulate.
  • FIG. 5 is a block diagram showing an example of the configuration of the evaluation device 100 of the present system, and conceptually shows only the portion of the configuration related to the present invention.
  • the evaluation device 100 uses a control unit 102 such as a CPU (Central Processing Unit) that collectively controls the evaluation device, a communication device such as a router, and a wired or wireless communication line such as a dedicated line. It is composed of a communication interface unit 104 that is communicably connected to the network 300, a storage unit 106 that stores various databases, tables, files, and the like, and an input / output interface unit 108 that is connected to the input device 112 and the output device 114. These parts are connected so as to be able to communicate with each other via an arbitrary communication path.
  • the evaluation device 100 may be configured in the same housing as various analyzers (for example, an amino acid analyzer).
  • the evaluation unit 102d may be further provided, and the result obtained by the evaluation unit 102d may be output using the above configuration.
  • the communication interface unit 104 mediates communication between the evaluation device 100 and the network 300 (or a communication device such as a router). That is, the communication interface unit 104 has a function of communicating data with another terminal via a communication line.
  • the input / output interface unit 108 is connected to the input device 112 and the output device 114.
  • the output device 114 a speaker or a printer can be used in addition to a monitor (including a home television) (in the following, the output device 114 may be described as the monitor 114).
  • the input device 112 can use a monitor that realizes a pointing device function in cooperation with the mouse.
  • the storage unit 106 is a storage means, and for example, a memory device such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used.
  • a computer program for giving instructions to the CPU and performing various processes in cooperation with the OS (Operating System) is recorded in the storage unit 106.
  • the storage unit 106 stores the measurement data file 106a, the index state information file 106b, the designated index state information file 106c, the formula-related information database 106d, and the evaluation result file 106e.
  • the measurement data file 106a stores measurement data relating to the measured values of the at least one substance in blood.
  • FIG. 6 is a diagram showing an example of information stored in the measurement data file 106a.
  • the information stored in the measurement data file 106a is configured by correlating the individual number for uniquely identifying the individual (sample) to be evaluated and the measurement data.
  • the measurement data is treated as a numerical value, that is, a continuous scale, but the measurement data may be a nominal scale or an ordinal scale. In the case of a nominal scale or an ordinal scale, analysis may be performed by giving an arbitrary numerical value to each state.
  • the measurement data may be combined with values related to other biological information (see above).
  • the index state information file 106b stores the index state information used when creating the formula.
  • FIG. 7 is a diagram showing an example of information stored in the index state information file 106b.
  • the information stored in the index state information file 106b is an index related to an individual number and an index (index T1, index T2, index T3 ...) Representing the state of accumulation of A ⁇ in the brain.
  • the data (T) and the measurement data are associated with each other.
  • the index data and the measurement data are treated as numerical values (that is, continuous scales), but the index data and the measurement data may be a nominal scale or an ordinal scale. In the case of a nominal scale or an ordinal scale, analysis may be performed by giving an arbitrary numerical value to each state.
  • the index data is a known index or the like that serves as a marker of the state of accumulation of A ⁇ in the brain, and numerical data may be used.
  • the designated index status information file 106c stores the index status information designated by the designated unit 102b described later.
  • FIG. 8 is a diagram showing an example of information stored in the designated index state information file 106c. As shown in FIG. 8, the information stored in the designated index state information file 106c is configured by correlating the individual number, the designated index data, and the designated measurement data with each other.
  • the formula-related information database 106d is composed of a formula file 106d1 that stores the formula created by the formula creation unit 102c described later.
  • the expression file 106d1 stores the expression used at the time of evaluation.
  • FIG. 9 is a diagram showing an example of information stored in the formula file 106d1.
  • the information stored in the expression file 106d1 includes the rank, the expression (in FIG. 9, Fp (His, %), Fp (His, ADMA, GABA), Fk (His, ADMA,). GABA, ...), Etc.), the threshold value corresponding to each formula creation method, and the verification result of each formula (for example, the value of each formula) are associated with each other.
  • FIG. 10 is a diagram showing an example of information stored in the evaluation result file 106e.
  • the information stored in the evaluation result file 106e includes an individual number for uniquely identifying an individual (sample) to be evaluated, measurement data of an individual acquired in advance, and an evaluation regarding the state of accumulation of A ⁇ in the brain.
  • Results for example, the value of the formula calculated by the calculation unit 102d1 described later, the value after the value of the formula is converted by the conversion unit 102d2 described later, the position information generated by the generation unit 102d3 described later, or the classification unit 102d4 described later.
  • the classification results obtained in, etc. and are associated with each other.
  • control unit 102 has an internal memory for storing a control program such as an OS, a program that defines various processing procedures, required data, and the like, and various information processing is performed based on these programs. To execute. As shown in the drawing, the control unit 102 is roughly divided into an acquisition unit 102a, a designation unit 102b, an expression creation unit 102c, an evaluation unit 102d, a result output unit 102e, and a transmission unit 102f.
  • the control unit 102 removes data having missing values, removes data having many outliers, and data having missing values with respect to the index state information transmitted from the database device 400 and the measurement data transmitted from the client device 200. It also performs data processing such as removal of variables with many.
  • the acquisition unit 102a acquires information (specifically, measurement data, index state information, formula, etc.). For example, the acquisition unit 102a acquires information by receiving information (specifically, measurement data, index state information, formula, etc.) transmitted from the client device 200 or the database device 400 via the network 300. May be done. The acquisition unit 102a may receive data used for evaluation transmitted from a client device 200 different from the client device 200 to which the evaluation result is transmitted. Further, for example, when the evaluation device 100 includes a mechanism (including hardware and software) for reading out the information recorded on the recording medium, the acquisition unit 102a may use the information (specifically, the information) recorded on the recording medium. Specifically, the information may be acquired by reading the measurement data, the index state information, the formula, etc.) through the mechanism. The designation unit 102b designates index data and measurement data to be targeted when creating the formula.
  • the formula creation unit 102c creates a formula based on the index state information acquired by the acquisition unit 102a and the index state information designated by the designation unit 102b.
  • the formula creation unit 102c may create the formula by selecting a desired formula from the storage unit 106. Further, the formula creation unit 102c may create a formula by selecting and downloading a desired formula from another computer device (for example, database device 400) in which the formula is stored in advance.
  • the evaluation unit 102d is included in the formula obtained in advance (for example, the formula created by the formula creation unit 102c or the formula acquired by the acquisition unit 102a) and the measurement data of the individual acquired by the acquisition unit 102a.
  • the state of accumulation of A ⁇ in the brain of an individual is evaluated by calculating the value of the formula using the measured values of at least one substance.
  • the evaluation unit 102d may evaluate the state of accumulation of A ⁇ in the brain of an individual by using the measured value of at least one substance or the converted value (for example, deviation value) of the measured value. Good.
  • FIG. 11 is a block diagram showing the configuration of the evaluation unit 102d, and conceptually shows only the portion of the configuration related to the present invention.
  • the evaluation unit 102d further includes a calculation unit 102d1, a conversion unit 102d2, a generation unit 102d3, and a classification unit 102d4.
  • the calculation unit 102d1 calculates the value of the formula by using the formula including at least the measured value of the at least one substance and the variable to which the measured value of the at least one substance is substituted.
  • the evaluation unit 102d may store the value of the formula calculated by the calculation unit 102d1 as an evaluation result in a predetermined storage area of the evaluation result file 106e.
  • the conversion unit 102d2 converts the value of the formula calculated by the calculation unit 102d1 by, for example, the conversion method described above.
  • the evaluation unit 102d may store the value after conversion by the conversion unit 102d2 as an evaluation result in a predetermined storage area of the evaluation result file 106e. Further, the conversion unit 102d2 may convert the measured value of the at least one substance included in the measurement data by, for example, the conversion method described above.
  • the generation unit 102d3 uses the value of the formula calculated by the calculation unit 102d1 or the conversion unit 102d2 to obtain position information regarding the position of a predetermined mark on a predetermined measuring rod that is visibly displayed on a display device such as a monitor or a physical medium such as paper. It is generated using the value after conversion in (may be the measured value or the converted value of the measured value).
  • the evaluation unit 102d may store the position information generated by the generation unit 102d3 as an evaluation result in a predetermined storage area of the evaluation result file 106e.
  • the classification unit 102d4 uses the value of the formula calculated by the calculation unit 102d1 or the value converted by the conversion unit 102d2 (the measured value or the converted value of the measured value) to obtain an individual in the brain of A ⁇ . It is classified into one of a plurality of categories defined in consideration of at least the degree of accumulation in the brain.
  • the result output unit 102e outputs the processing results (including the evaluation results obtained by the evaluation unit 102d) of each processing unit of the control unit 102 to the output device 114.
  • the transmission unit 102f transmits the evaluation result to the client device 200 that is the source of the measurement data of the individual, and transmits the formula and the evaluation result created by the evaluation device 100 to the database device 400.
  • the transmission unit 102f may transmit the evaluation result to a client device 200 different from the client device 200 that transmits the data used for the evaluation.
  • FIG. 12 is a block diagram showing an example of the configuration of the client device 200 of the present system, and conceptually shows only the portion of the configuration related to the present invention.
  • the client device 200 is composed of a control unit 210, a ROM 220, an HD (Hard Disk) 230, a RAM 240, an input device 250, an output device 260, an input / output IF270, and a communication IF280, and each of these units is via an arbitrary communication path. Is connected so that it can communicate with each other.
  • the client device 200 is an information processing device (for example, a known personal computer, workstation, home game device, Internet TV, PHS (Personal Handyphone System)) in which peripheral devices such as a printer, a monitor, and an image scanner are connected as needed. It may be based on a terminal, a mobile terminal, a mobile communication terminal, an information processing terminal such as a PDA (Personal Digital Assist), or the like).
  • the input device 250 is a keyboard, mouse, microphone, or the like.
  • the monitor 261 described later also realizes the pointing device function in cooperation with the mouse.
  • the output device 260 is an output means for outputting information received via the communication IF 280, and includes a monitor (including a home television) 261 and a printer 262. In addition, the output device 260 may be provided with a speaker or the like.
  • the input / output IF270 is connected to the input device 250 and the output device 260.
  • the communication IF280 connects the client device 200 and the network 300 (or a communication device such as a router) in a communicable manner.
  • the client device 200 is connected to the network 300 via a communication device such as a modem, a TA (Terminal Adapter), or a router, and a telephone line, or via a dedicated line.
  • a communication device such as a modem, a TA (Terminal Adapter), or a router, and a telephone line, or via a dedicated line.
  • the client device 200 can access the evaluation device 100 according to a predetermined communication contract.
  • the control unit 210 includes a receiving unit 211 and a transmitting unit 212.
  • the receiving unit 211 receives various information such as the evaluation result transmitted from the evaluation device 100 via the communication IF280.
  • the transmission unit 212 transmits various information such as individual measurement data to the evaluation device 100 via the communication IF 280.
  • the control unit 210 may be realized by a CPU and a program that interprets and executes all or any part of the processing performed by the control unit by the CPU and the CPU.
  • a computer program for giving instructions to the CPU in cooperation with the OS and performing various processes is recorded in the ROM 220 or HD 230.
  • the computer program is executed by being loaded into the RAM 240, and constitutes the control unit 210 in cooperation with the CPU.
  • the computer program may be recorded in an application program server connected to the client device 200 via an arbitrary network, and the client device 200 may download all or a part thereof as needed. ..
  • all or any part of the processing performed by the control unit 210 may be realized by hardware such as wired logic.
  • control unit 210 has an evaluation unit 210a (including a calculation unit 210a1, a conversion unit 210a2, a generation unit 210a3, and a classification unit 210a4) having the same function as that of the evaluation unit 102d provided in the evaluation device 100. May be provided. Then, when the control unit 210 is provided with the evaluation unit 210a, the evaluation unit 210a uses the conversion unit 210a2 to obtain the value of the expression (in accordance with the information included in the evaluation result transmitted from the evaluation device 100). The measured value may be converted), the generation unit 210a3 may generate the position information corresponding to the value of the formula or the converted value (the measured value or the converted value of the measured value), or the classification unit 210a4. The individual may be classified into any one of a plurality of categories using the value of the formula or the converted value (the measured value or the converted value of the measured value).
  • the network 300 has a function of connecting the evaluation device 100, the client device 200, and the database device 400 so as to be able to communicate with each other.
  • the Internet for example, the Internet, an intranet, a LAN (Local Area Network) (including both wired and wireless) and the like.
  • the network 300 includes VAN (Value-Added Network), personal computer communication network, public switched telephone network (including both analog / digital), dedicated line network (including both analog / digital), and CATV ().
  • IMT International Mobile Telecommunication
  • GSM Global System for Mobile Communications
  • PDC Packet Control
  • wireless calling networks local wireless networks such as Bluetooth (registered trademark), PHS networks, satellite communication networks (CS (Communication Satellite), BS (Roadcasting Satellite), or ISDB (Integrated Services Digital Broadcast). ) Etc.) and the like.
  • Bluetooth registered trademark
  • PHS satellite communication networks
  • CS Common Communication Satellite
  • BS Roadcasting Satellite
  • ISDB Integrated Services Digital Broadcast
  • FIG. 13 is a block diagram showing an example of the configuration of the database device 400 of the present system, and conceptually shows only the portion of the configuration related to the present invention.
  • the database device 400 has a function of storing index state information used when creating a formula in the evaluation device 100 or the database device, a formula created in the evaluation device 100, an evaluation result in the evaluation device 100, and the like.
  • the database device 400 uses a control unit 402 such as a CPU that collectively controls the database device, a communication device such as a router, and a wired or wireless communication circuit such as a dedicated line.
  • a communication interface unit 404 that connects the device to the network 300 so that it can communicate, a storage unit 406 that stores various databases, tables, files (for example, files for Web pages), and an input / output device 412 and an output device 414 that are connected to each other. It is composed of an output interface unit 408, and each of these units is connected so as to be communicable via an arbitrary communication path.
  • the storage unit 406 is a storage means, and for example, a memory device such as a RAM / ROM, a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used.
  • the storage unit 406 stores various programs and the like used for various processes.
  • the communication interface unit 404 mediates communication between the database device 400 and the network 300 (or a communication device such as a router). That is, the communication interface unit 404 has a function of communicating data with another terminal via a communication line.
  • the input / output interface unit 408 is connected to the input device 412 and the output device 414.
  • the output device 414 a speaker or a printer can be used in addition to a monitor (including a home television).
  • the input device 412 in addition to a keyboard, a mouse, and a microphone, a monitor that realizes a pointing device function in cooperation with the mouse can be used.
  • the control unit 402 has an internal memory for storing a control program such as an OS, a program that defines various processing procedures, and required data, and executes various information processing based on these programs. As shown in the drawing, the control unit 402 is roughly classified into a transmission unit 402a and a reception unit 402b.
  • the transmission unit 402a transmits various information such as index state information and formulas to the evaluation device 100.
  • the receiving unit 402b receives various information such as an expression and an evaluation result transmitted from the evaluation device 100.
  • the evaluation device 100 executes the acquisition of measurement data, the calculation of the value of the formula, the classification into individual categories, and the transmission of the evaluation result, and the client device 200 receives the evaluation result.
  • the evaluation device 100 it is sufficient for the evaluation device 100 to calculate the value of the expression.
  • the conversion of the value of the expression and the position information The evaluation device 100 and the client device 200 may appropriately share and execute the generation of the data and the classification of the individual into categories.
  • the evaluation unit 210a converts the value of the expression by the conversion unit 210a2, or the value of the expression or the value after conversion by the generation unit 210a3.
  • the position information corresponding to the above may be generated, or the individual may be classified into any one of a plurality of categories by using the value of the formula or the value after conversion in the classification unit 210a4. Further, when the client device 200 receives the converted value from the evaluation device 100, the evaluation unit 210a generates position information corresponding to the converted value by the generation unit 210a3, or the classification unit 210a4 converts the value. The later values may be used to classify the individual into any one of a plurality of categories. Further, when the client device 200 receives the value of the formula or the converted value and the position information from the evaluation device 100, the evaluation unit 210a uses the value of the formula or the converted value in the classification unit 210a4. Individuals may be classified into any one of a plurality of categories.
  • all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed. It is also possible to automatically perform all or part of the above by a known method.
  • processing procedure, control procedure, specific name, information including parameters such as registration data and search conditions of each processing, screen examples, and database configuration shown in the above documents and drawings are not specified unless otherwise specified. Can be changed arbitrarily.
  • each component shown in the figure is a functional concept and does not necessarily have to be physically configured as shown in the figure.
  • each processing function performed by the control unit 102 even if all or any part thereof is realized by the CPU and a program interpreted and executed by the CPU. It may be realized as hardware by wired logic.
  • the program is recorded on a non-temporary computer-readable recording medium containing a programmed instruction for causing the information processing apparatus to execute the evaluation method or calculation method according to the present invention, and is evaluated as necessary. It is read mechanically by the device 100. That is, a computer program for giving instructions to the CPU in cooperation with the OS and performing various processes is recorded in a storage unit 106 or the like such as a ROM or an HDD (Hard Disk Drive). This computer program is executed by being loaded into RAM, and cooperates with a CPU to form a control unit.
  • this computer program may be stored in the application program server connected to the evaluation device 100 via an arbitrary network, and all or a part thereof can be downloaded as needed.
  • the evaluation program or calculation program according to the present invention may be stored in a non-temporary computer-readable recording medium, or may be configured as a program product.
  • the "recording medium” includes a memory card, a USB (Universal Serial Bus) memory, an SD (Secure Digital) card, a flexible disk, a magneto-optical disk, a ROM, an EPROM (Erasable Programmable Read Only Memory), and an EEPROM (EEEPROM).
  • Erasable and EEPROM Read Only Memory registered trademark
  • CD-ROM Compact Disc Read Only Memory
  • MO Magnetic-Optical Disk
  • MO Magnetic-Optical Disk
  • DVD Digital Digital
  • DVD Digital Digital
  • DVD Digital
  • DVD Digital It shall include any "portable physical medium”.
  • a “program” is a data processing method described in any language or description method, regardless of the format such as source code or binary code.
  • the "program” is not necessarily limited to a single program, but is distributed as a plurality of modules or libraries, or cooperates with a separate program represented by the OS to achieve its function. Including things. It should be noted that well-known configurations and procedures can be used for the specific configuration and reading procedure for reading the recording medium in each device shown in the embodiment, the installation procedure after reading, and the like.
  • Various databases and the like stored in the storage unit 106 are memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and storage means such as optical disks, and are used for various processes and website provision. Stores programs, tables, databases, files for web pages, etc.
  • the evaluation device 100 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as the information processing device to which an arbitrary peripheral device is connected. Further, the evaluation device 100 may be realized by mounting software (including a program or data) that realizes the evaluation method or calculation method of the present invention on the information processing device.
  • dispersion / integration of the device is not limited to that shown in the figure, and all or part of the device is functionally or physically in any unit according to various additions or functional loads. It can be distributed and integrated. That is, the above-described embodiments may be arbitrarily combined and implemented, or the embodiments may be selectively implemented.
  • Table 1 shows logistic regression using the plasma concentration values of the 23 amino acids and the 25 amino acid-related metabolites, the peak area value of the one amino acid-related metabolite, and the ratio of the two metabolites. The results are shown.
  • the amino acids and amino acid-related metabolites having a ROC_AUC of 0.6 or higher were MeCys, Ser, Orn, ADMA, EtOHNH2, Cys2, Gly, HyPro and Allyl-Cys. MeCys, Ser, Orn, ADMA, Cys2, Gly and HyPro decreased in the A ⁇ -positive group, and EtOHNH2 and Allyl-Cys increased in the A ⁇ -positive group. Concentrations of these metabolites are believed to be useful in assessing A ⁇ deposition.
  • Example 1 The sample data obtained in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of the two variables included in the logistic regression equation is described in Example 1, the plasma concentration values of the 23 types of amino acids, the plasma concentration values of the 25 types of amino acid-related biotransforms, and the one type of amino acid.
  • a logistic regression equation was searched for with good discrimination between the A ⁇ -positive group and the A ⁇ -negative group by searching from the peak area value of the related biotransforms and the ratio of the two types of biotransforms.
  • Example 1 The sample data used in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of the three variables included in the logistic regression equation is the same as in Example 2, the plasma concentration value of the 23 types of amino acids, the plasma concentration value of the 25 types of amino acid-related biotransforms, and the one type of amino acid.
  • a logistic regression equation with good discrimination between the A ⁇ -positive group and the A ⁇ -negative group was searched by searching from the peak area value of the related biotransforms and the ratio of the two types of biotransforms.
  • a logistic regression equation with good discriminative ability is searched for when the two types searched from the plasma concentration values of the 23 types of amino acids and the plasma concentration values of the 25 types of amino acid-related metabolites and the age are used as variables. Carried out.
  • a list of logistic regression equations in which the ROC_AUC value of the A ⁇ -positive group and the A ⁇ -negative group is 0.684 or more and the number of variables is 3 is shown in the following [2.3 variable equation].
  • the top 200 formulas having the highest ROC_AUC value are selected, and the 201 formulas including the formula having the same ROC_AUC value of 0.768 as the 200th formula are included in the following [2]. -1.
  • Example 1 The sample data used in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of the four variables included in the logistic regression equation is the plasma concentration value of the 23 types of amino acids, the plasma concentration value of the 25 types of amino acid-related biotransforms, and the above-mentioned one type.
  • a logistic regression equation was searched for with good discrimination between the A ⁇ -positive group and the A ⁇ -negative group by searching from the peak area value of amino acid-related biotransforms, the ratio of the two types of biotransforms, and the age.
  • the ROC_AUC value increased by incorporating age into the variable (20,825 in total), and there was an age variable.
  • the top 20 equations are shown in Table 2. Since the ROC_AUC value of all logistic regression equations was improved by adding the age variable, it is considered that the logistic regression equation with age added to the variable is useful in the above evaluation.
  • Example 1 The sample data used in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of four variables to be included in the logistic regression equation is the plasma concentration value of the 23 types of amino acids, the plasma concentration value of the 25 types of amino acid-related biotransforms, and the above-mentioned one type.
  • Example 1 The sample data used in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of four variables included in the logistic regression equation (BMI (Body Mass Index) variable is required) is the plasma concentration value of the 23 types of amino acids and the plasma concentration of the 25 types of amino acid-related metabolites.
  • a logistic regression equation was searched for with good discrimination between the A ⁇ -positive group and the A ⁇ -negative group by searching from the value, the peak area value of the one type of amino acid-related metabolite, the ratio of the two types of metabolites, and BMI.
  • Example 1 The sample data used in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of 4 variables included in the logistic regression equation (MMSE (Mini Menal State Examination) score variable is required) is the plasma concentration value of the 23 types of amino acids and the 25 types of amino acid-related biotransforms. Search from the plasma concentration value, the peak area value of the one type of amino acid-related metabolite, the ratio of the two types of biotransformers, and the MMSE, and search for a logistic regression equation with good discrimination between the A ⁇ -positive group and the A ⁇ -negative group. Carried out.
  • MMSE Mini Menal State Examination
  • Example 1 The sample data used in Example 1 was used.
  • a logistic regression equation was used as the multivariate discriminant.
  • the combination of 6 variables included in the logistic regression equation is the plasma concentration value of the 23 kinds of amino acids, the plasma concentration value of the 25 kinds of amino acid-related metabolites, and the peak area value of the one kind of amino acid-related metabolite.
  • a logistic regression equation was searched for with good discrimination between the A ⁇ -positive group and the A ⁇ -negative group. In order to exclude combinations with many missing values, the combination formula of 6 variables in which the total number of data that can be used in the calculation was less than 50 in the A ⁇ -positive group and the A ⁇ -negative group was excluded from the search results.
  • MeCys, Allyl-Cys, hCit, bAiBA, Cys2, N8-AcSpd, Val, Gly, ADMA, 1-MeHis, Met, Lys, Sar, Ser, Tau, SDMA, 3-MeHis, Ph, Thr, Gln , Leu, His, Kyn, N6-AcLys and HyPro were shown to appear as high as 200 times or more.
  • the frequency of appearance of MeCys, Allyl-Cys, hCit, bAiBA, Cys2, N8-AcSpd, Val, Gly, ADMA, 1-MeHis, Met, Lys and Sar was as high as 500 times or more.
  • the frequency of appearance of MeCys, Allyl-Cys and hCit was as high as 2,000 times or more.
  • the present invention can be widely implemented in many industrial fields, particularly in fields such as pharmaceuticals, foods, and medical treatments, and in particular, bioinformatics that may predict the accumulation of A ⁇ in the brain. Extremely useful in the field of informatics.
  • Evaluation device including calculation device
  • Control unit 102a Acquisition unit 102b Designation unit 102c Expression creation unit 102d Evaluation unit 102d1 Calculation unit 102d2 Conversion unit 102d3 Generation unit 102d4 Classification unit 102e Result output unit 102f Transmission unit 104 Communication interface unit 106 Storage unit 106a Measurement data file 106b Index status information File 106c Designated index status information file 106d Expression related information database 106d1 Expression file 106e Evaluation result file 108 Input / output interface unit 112 Input device 114 Output device 200 Client device (terminal device (information and communication terminal device)) 300 network 400 database device

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Abstract

The present invention addresses the problem of providing an evaluating method, etc. which can provide highly reliable information which can serve as a reference in knowing the amyloid beta accumulation state in the brain. In the present embodiment, the Aβ accumulation state in the brain is evaluated with respect to a subject to be evaluated by using at least one measurement value from among Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Phe, Pro, Ser, Tau, Thr, Trp, Tyr, Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cystathionine, MeCys, N6-AcLys, N8-AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Thioproline, and BCAA in the blood of the subject to be evaluated.

Description

アミロイドベータの脳内への蓄積の評価方法、算出方法、評価装置、算出装置、評価プログラム、算出プログラム、記録媒体、評価システムおよび端末装置Evaluation method, calculation method, evaluation device, calculation device, evaluation program, calculation program, recording medium, evaluation system and terminal device for the accumulation of amyloid beta in the brain
　本発明は、アミロイドベータ（以下「Ａβ」と記す。）の脳内への蓄積の評価方法、算出方法、評価装置、算出装置、評価プログラム、算出プログラム、記録媒体、評価システムおよび端末装置に関するものである。 The present invention relates to an evaluation method, calculation method, evaluation device, calculation device, evaluation program, calculation program, recording medium, evaluation system, and terminal device for the accumulation of amyloid beta (hereinafter referred to as “Aβ”) in the brain. Is.
　アルツハイマー型認知症は、アルツハイマー病（ＡＤ）を原因疾患とする認知症であり、認知症患者数の５割程度を占める。ＡＤの病理的な特徴として、「Ａβ」というタンパク質が脳組織に凝集、沈着し、病態の進行とともに老人班と呼ばれるアミロイドプラークを形成する点が挙げられる。Ａβの脳への蓄積は、ＡＤを発症する約２０年前から始まるとの報告がある（非特許文献１，２）。これを受けて、近年では、発症前の段階であるｐｒｏｄｒｏｍａｌおよびｐｒｅｃｌｉｎｉｃａｌ期における治療が必要であるとの前提に基づく病態修飾薬の研究開発が進んでいる（非特許文献３）。 Alzheimer-type dementia is a dementia caused by Alzheimer's disease (AD) and accounts for about 50% of the number of dementia patients. A pathological feature of AD is that a protein called "Aβ" aggregates and deposits in brain tissue and forms amyloid plaques called senile plaques as the condition progresses. It has been reported that the accumulation of Aβ in the brain begins about 20 years before the onset of AD (Non-Patent Documents 1 and 2). In response to this, in recent years, research and development of pathological modifiers based on the premise that treatment in the prodromal and prodromical stages, which are the preclinical stages, is required (Non-Patent Document 3).
　Ａβの脳への蓄積の有無を評価する方法としては、脳脊髄液中のＡβ４２濃度の測定（非特許文献４）、および、陽電子放射断層撮影（Ｐｏｓｉｔｒｏｎ　Ｅｍｉｓｓｉｏｎ　Ｔｏｍｏｇｒａｐｈｙ）を用いたアミロイドＰＥＴイメージング（非特許文献５，６）が主に挙げられる。脳脊髄液検査については、測定施設ごとに測定値が異なる、採取法および保存条件による測定値のばらつきがある、ならびに、検体の採取時に腰椎穿刺を伴うため侵襲性があり実施者に熟練した手技が要求される、という課題がある。アミロイドＰＥＴイメージングについては、放射線による侵襲性がある、検査費用が高額である、および、設備面の制約から実施可能な医療機関が少ないため実診療用途での普及が困難である、という課題がある。 As a method for evaluating the presence or absence of accumulation of Aβ in the brain, measurement of Aβ42 concentration in cerebrospinal fluid (Non-Patent Document 4) and amyloid PET imaging (non-patient) using positron emission tomography (Positron Emission Tomography) Patent documents 5 and 6) are mainly mentioned. Regarding the cerebrospinal fluid test, the measured values differ depending on the measurement facility, the measured values vary depending on the collection method and storage conditions, and the sample collection is invasive because it involves lumbar puncture. There is a problem that is required. Amyloid PET imaging has problems that it is invasive by radiation, the examination cost is high, and there are few medical institutions that can perform it due to equipment restrictions, so it is difficult to spread it in actual medical care. ..
　これらの既存技術と比較して、血液検査は、より簡便且つ低価格での実施が可能であることから、脳へのＡβ蓄積のスクリーニング法として適している。実際、血液中のＡβ断片の定量値が脳へのＡβ蓄積と相関するとの報告がある（非特許文献７）。 Compared with these existing technologies, blood tests can be performed more easily and at a lower cost, and are therefore suitable as a screening method for Aβ accumulation in the brain. In fact, it has been reported that the quantitative value of Aβ fragments in blood correlates with the accumulation of Aβ in the brain (Non-Patent Document 7).
　しかしながら、血液中のＡβ断片の濃度は低濃度であるが故に測定方法が複雑であるため、脳へのＡβ蓄積の指標として血液中のＡβ断片の濃度を採用することは、実臨床への応用可能性という観点からみて厳しい、という課題がある。より簡便に測定可能なバイオマーカーが依然として求められる。 However, since the concentration of Aβ fragment in blood is low, the measurement method is complicated. Therefore, adopting the concentration of Aβ fragment in blood as an index of Aβ accumulation in the brain is applied to clinical practice. There is a problem that it is strict from the viewpoint of possibility. There is still a need for biomarkers that can be measured more easily.
　本発明は、上記に鑑みてなされたもので、Ａβの脳内への蓄積の状態を知る上で参考となり得る信頼性の高い情報を提供することができる評価方法、算出方法、評価装置、算出装置、評価プログラム、算出プログラム、記録媒体、評価システムおよび端末装置を提供することを目的とする。 The present invention has been made in view of the above, and is an evaluation method, a calculation method, an evaluation device, and a calculation capable of providing highly reliable information that can be used as a reference for knowing the state of accumulation of Aβ in the brain. An object of the present invention is to provide an apparatus, an evaluation program, a calculation program, a recording medium, an evaluation system, and a terminal apparatus.
　上述した課題を解決し、目的を達成するために、本発明にかかるＡβの脳内への蓄積の状態の評価方法は、評価対象の血液中の２４種類のアミノ酸（Ａｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、ＶａｌおよびＢＣＡＡ）および２６種類のアミノ酸関連代謝物（１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ　ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、ＳｐｄおよびＴｈｉｏｐｒｏｌｉｎｅ）のうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価する評価ステップを含むこと、を特徴とする。 In order to solve the above-mentioned problems and achieve the object, the method for evaluating the state of accumulation of Aβ in the brain according to the present invention is to evaluate 24 kinds of amino acids (Ala, Arg, Asn, Cit) in the blood to be evaluated. , Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, Val and BCAA) and 26 amino acid-related metabolites (Val and BCAA) 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, MeCys, Cys, N6 PEA, Pipeholic acid, Put, Sar, SDMA, Spd and Thioproline) or at least one measurement value, or an expression including a variable to which the measurement value is assigned and an expression calculated using the measurement value. It is characterized by including an evaluation step of evaluating the state of accumulation of Aβ in the brain for the evaluation target using the value.
　ここで、本明細書では各種アミノ酸および各種アミノ酸関連代謝物を主に略称で表記するが、それらの正式名称は以下の通りである。
（略称）             （正式名称）
Ala                  Alanine
Arg                  Arginine
Asn                  Asparagine
Cit                  Citrulline
Cys2                 Cystine
EtOHNH2              Ethanolamine
Gln                  Glutamine
Glu                  Glutamic acid
Gly                  Glycine
His                  Histidine
Ile                  Isoleucine
Leu                  Leucine
Lys                  Lysine
Met                  Methionine
Orn                  Ornithine
Phe                  Phenylalanine
Pro                  Proline
Ser                  Serine
Tau                  Taurine
Thr                  Threonine
Trp                  Tryptophan
Tyr                  Tyrosine
Val                  Valine Here, various amino acids and various amino acid-related metabolites are mainly abbreviated in the present specification, and their official names are as follows.
(Abbreviation) (Official name)
Ala Alanine
Arg Arginine
Asn Asparagine
Cit Citrulline
Cys2 Cystine
EtOHNH2 Ethanolamine
Gln Glutamine
Glu Glutamic acid
Gly Glycine
His Histidine
Ile Isoleucine
Leu Leucine
Lys Lysine
Met Methionine
Orn Ornithine
Phe Phenylalanine
Pro Proline
Ser Serine
Tau Taurine
Thr Threonine
Trp Tryptophan
Tyr Tyrosine
Val Valine
（略称）             （正式名称）
1-MeHis              N(pi)-Methyl-L-histidine
3-hKyn               3-Hydroxy-L-kynurenine
3-MeHis              N(tau)-Methyl-L-histidine
aABA                 3-Aminobutanoic acid
aAiBA                2-Aminoisobutyric acid
ADMA                 Asymmetric dimethylarginine
Allyl-Cys            Allyl cysteine
aAAA                 Aminoadipic acid
bAiBA                L-3-Aminoisobutyric acid
GABA                 4-Aminobutyric Acid
hArg                 L-Homoarginine
hCit                 L-Hommocitrulline
Hypotaurine          Hypotaurine
HyPro                4-Hydroxy-L-proline
Kyn                  L-Kynurenine
Cystathionine        L-Cystathionine
MeCys                Metylcysteine
N6-AcLys             Ne-Acetyl-L-lysine
N8-AcSpd             N8-Acetylspermidine
PEA                  Phosphoethanolamine
Pipecolic acid       Pipecolic acid
Put                  Putrescine
Sar                  Sarcosine
SDMA                 Symmetric dimethylarginine
Spd                  Spermidine
Thioproline          Thioproline (Abbreviation) (Official name)
1-MeHis N (pi)-Methyl-L-histidine
3-hKyn 3-Hydroxy-L-kynurenine
3-MeHis N (tau)-Methyl-L-histidine
aABA 3-Aminobutanoic acid
aAiBA 2-Aminoisobutyric acid
ADMA Asymmetric dimethylarginine
Allyl-Cys Allyl cysteine
aAAA Aminoadipic acid
bAiBA L-3-Aminoisobutyric acid
GABA 4-Aminobutyric Acid
hArg L-Homoarginine
hCit L-Hommocitrulline
Hypotaurine Hypotaurine
HyPro 4-Hydroxy-L-proline
Kyn L-Kynurenine
Cystathionine L-Cystathionine
MeCys Metylcysteine
N6-AcLys Ne-Acetyl-L-lysine
N8-AcSpd N8-Acetylspermidine
PEA Phosphoethanolamine
Pipecolic acid Pipecolic acid
Put Putrescine
Sar Sarcosine
SDMA Symmetric dimethylarginine
Spd Spermidine
Thioproline Thioproline
　また、本発明にかかる評価方法は、前記評価ステップが、前記評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも２つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価すること、を特徴とする。 Further, in the evaluation method according to the present invention, the evaluation step is that Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, etc. in the blood to be evaluated. Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allly-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, MeCys, N6-AcLys, N8-AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Thioproline and BCAA at least two of said values It is characterized in that the state of accumulation of Aβ in the brain is evaluated for the evaluation target by using the formula including the variable to be substituted and the value of the formula calculated using the measured value.
　また、本発明にかかる評価方法は、前記評価ステップが、前記評価対象の年齢、性別、ＢＭＩ（Ｂｏｄｙ　Ｍａｓｓ　Ｉｎｄｅｘ）およびＭＭＳＥ（Ｍｉｎｉ　Ｍｅｎｔａｌ　Ｓｔａｔｅ　Ｅｘａｍｉｎａｔｉｏｎ）の点数のうち少なくとも１つと前記測定値を用いて、または、年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値が代入される変数を含む前記式、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つおよび前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価すること、を特徴とする。 Further, in the evaluation method according to the present invention, the evaluation step uses at least one of the age, gender, BMI (Body Mass Index) and MMSE (Mini Mental State Evaluation) scores of the evaluation target and the measured value. Or, the formula containing at least one of the age, gender, BMI and MMSE scores and a variable to which the measurement is assigned, the age, gender, at least one of the BMI and MMSE scores and said It is characterized in that the state of accumulation of Aβ in the brain is evaluated for the evaluation target by using the value of the above formula calculated using the measured value.
　また、本発明にかかる評価方法は、前記評価ステップが、制御部を備えた情報処理装置の前記制御部において実行されること、を特徴とする。 Further, the evaluation method according to the present invention is characterized in that the evaluation step is executed in the control unit of the information processing device provided with the control unit.
　また、本発明にかかるＡβの脳内への蓄積の状態を評価するための式の値の算出方法は、評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値、ならびに、前記測定値が代入される変数を含むＡβの脳内への蓄積の状態を評価するための式を用いて、前記式の値を算出する算出ステップを含むこと、を特徴とする。 In addition, the method for calculating the value of the formula for evaluating the state of accumulation of Aβ in the brain according to the present invention is among the 24 types of amino acids and the 26 types of amino acid-related metabolites in the blood to be evaluated. Including a calculation step of calculating the value of the formula using at least one measurement of the above and a formula for evaluating the state of accumulation of Aβ in the brain containing the variable to which the measurement is assigned. It is characterized by.
　また、本発明にかかる算出方法は、前記算出ステップが、制御部を備えた情報処理装置の前記制御部において実行されること、を特徴とする。 Further, the calculation method according to the present invention is characterized in that the calculation step is executed in the control unit of the information processing device provided with the control unit.
　また、本発明にかかるＡβの脳内への蓄積の状態の評価装置は、制御部を備え、前記制御部が、評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価する評価手段を備えること、を特徴とする。 In addition, the device for evaluating the state of accumulation of Aβ in the brain according to the present invention includes a control unit, which controls the 24 types of amino acids and the 26 types of amino acid-related metabolites in the blood to be evaluated. Using at least one of the measured values, or a formula containing a variable to which the measured value is assigned, and the value of the formula calculated using the measured value, the evaluation target is introduced into the brain of Aβ. It is characterized by providing an evaluation means for evaluating the state of accumulation of.
　また、本発明にかかる評価装置は、前記評価手段が、前記評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも２つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価すること、を特徴とする。 Further, in the evaluation device according to the present invention, the evaluation means is Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, etc. in the blood to be evaluated. Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allly-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, MeCys, N6-AcLys, N8-AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Thioproline and BCAA at least two of the above measured values. It is characterized in that the state of accumulation of Aβ in the brain is evaluated for the evaluation target by using the formula including the variable to be substituted and the value of the formula calculated using the measured value.
　また、本発明にかかる評価装置は、前記評価手段が、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値を用いて、または、年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値が代入される変数を含む前記式、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つおよび前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価すること、を特徴とする。 Further, in the evaluation device according to the present invention, the evaluation means uses at least one of the age, gender, BMI and MMSE scores of the evaluation target and the measured value, or the age, gender, BMI and MMSE. The formula including at least one of the scores and the variable to which the measured value is assigned, the age, gender, BMI and MMSE score of the evaluation target, and the formula calculated using the measured value. The value is used to evaluate the state of accumulation of amyloid beta in the brain for the evaluation target.
　また、本発明にかかる評価装置は、前記測定値に関する測定データまたは前記式の値を提供する端末装置とネットワークを介して通信可能に接続され、前記制御部が、前記端末装置から送信された前記測定データまたは前記式の値を受信するデータ受信手段と、前記評価手段で得られた評価結果を前記端末装置へ送信する結果送信手段と、をさらに備え、前記評価手段が、前記データ受信手段で受信した前記測定データに含まれている前記測定値または前記式の値を用いること、を特徴とする。 Further, the evaluation device according to the present invention is communicably connected to a terminal device that provides measurement data related to the measured value or the value of the formula via a network, and the control unit is transmitted from the terminal device. A data receiving means for receiving the measurement data or the value of the formula and a result transmitting means for transmitting the evaluation result obtained by the evaluation means to the terminal device are further provided, and the evaluation means is the data receiving means. It is characterized in that the measured value or the value of the formula included in the received measurement data is used.
　また、本発明にかかるＡβの脳内への蓄積の状態を評価するための式の値の算出装置は、制御部を備え、前記制御部が、評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値、ならびに、前記測定値が代入される変数を含むＡβの脳内への蓄積の状態を評価するための式を用いて、前記式の値を算出する算出手段を備えること、を特徴とする。 Further, the device for calculating the value of the formula for evaluating the state of accumulation of Aβ in the brain according to the present invention includes a control unit, and the control unit contains the 24 kinds of amino acids in the blood to be evaluated and the above-mentioned 24 kinds of amino acids. The formula is used to evaluate at least one measurement of the 26 amino acid-related metabolites and the state of accumulation of Aβ in the brain, including the variable to which the measurement is assigned. It is characterized in that it is provided with a calculation means for calculating the value of.
　また、本発明にかかるＡβの脳内への蓄積の状態の評価プログラムは、制御部を備える情報処理装置の前記制御部において実行させるための、評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価する評価ステップを含むこと、を特徴とする。 Further, the evaluation program for the state of accumulation of Aβ in the brain according to the present invention includes the 24 kinds of amino acids in the blood to be evaluated and the above-mentioned 24 kinds of amino acids to be executed in the control unit of the information processing apparatus including the control unit. The evaluation target using the measured value of at least one of the 26 kinds of amino acid-related metabolites, or the value of the formula including the variable to which the measured value is substituted and the value of the formula calculated using the measured value. It is characterized by including an evaluation step for evaluating the state of accumulation of Aβ in the brain.
　また、本発明にかかるＡβの脳内への蓄積の状態を評価するための式の値の算出プログラムは、制御部を備える情報処理装置の前記制御部において実行させるための、評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値、ならびに、前記測定値が代入される変数を含むＡβの脳内への蓄積の状態を評価するための式を用いて、前記式の値を算出する算出ステップを含むこと、を特徴とする。 Further, the calculation program of the value of the formula for evaluating the state of accumulation of Aβ in the brain according to the present invention is in the blood to be evaluated for execution in the control unit of the information processing apparatus including the control unit. To evaluate the state of accumulation of Aβ in the brain, including the measured value of at least one of the 24 kinds of amino acids and the 26 kinds of amino acid-related metabolites, and the variable to which the measured value is assigned. It is characterized by including a calculation step of calculating the value of the formula using the formula.
　また、本発明にかかる記録媒体は、前記評価プログラムまたは前記算出プログラムを記録したコンピュータ読み取り可能な記録媒体である。具体的には、本発明にかかる記録媒体は、一時的でないコンピュータ読み取り可能な記録媒体であって、情報処理装置に前記評価方法または前記算出方法を実行させるためのプログラム化された命令を含むこと、を特徴とするものである。 Further, the recording medium according to the present invention is a computer-readable recording medium on which the evaluation program or the calculation program is recorded. Specifically, the recording medium according to the present invention is a non-temporary computer-readable recording medium, and includes a programmed instruction for causing an information processing apparatus to execute the evaluation method or the calculation method. , Is a feature.
　また、本発明にかかるＡβの脳内への蓄積の状態の評価システムは、制御部を備える、Ａβの脳内への蓄積の状態を評価する評価装置と、制御部を備える端末装置とを、ネットワークを介して通信可能に接続して構成され、前記端末装置の前記制御部が、評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値に関する測定データ、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を、前記評価装置へ送信するデータ送信手段と、前記評価装置から送信された、前記評価対象についての、Ａβの脳内への蓄積の状態に関する評価結果を受信する結果受信手段と、を備え、前記評価装置の前記制御部が、前記端末装置から送信された前記測定データまたは前記式の値を受信するデータ受信手段と、前記データ受信手段で受信した前記測定データに含まれている前記測定値または前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価する評価手段と、前記評価手段で得られた前記評価結果を前記端末装置へ送信する結果送信手段と、を備えること、を特徴とする。 Further, the evaluation system for the state of accumulation of Aβ in the brain according to the present invention includes an evaluation device including a control unit for evaluating the state of accumulation of Aβ in the brain and a terminal device including a control unit. It is configured to be communicably connected via a network, and the control unit of the terminal device measures at least one of the 24 types of amino acids and the 26 types of amino acid-related metabolites in the blood to be evaluated. A data transmission means for transmitting the measurement data relating to the data, an expression including a variable to which the measurement value is assigned, and the value of the expression calculated using the measurement value to the evaluation device, and transmission from the evaluation device. Further, the measurement data is provided by a result receiving means for receiving the evaluation result regarding the state of accumulation of Aβ in the brain of the evaluation target, and the control unit of the evaluation device is transmitted from the terminal device. Alternatively, using the data receiving means for receiving the value of the formula and the measured value or the value of the formula included in the measured data received by the data receiving means, the evaluation target is introduced into the brain of Aβ. It is characterized by including an evaluation means for evaluating the state of accumulation of the data, and a result transmission means for transmitting the evaluation result obtained by the evaluation means to the terminal device.
　また、本発明にかかる端末装置は、制御部を備えた端末装置であって、前記制御部が、評価対象についての、Ａβの脳内への蓄積の状態に関する評価結果を取得する結果取得手段を備え、前記評価結果が、前記評価対象の血液中の前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物のうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、Ａβの脳内への蓄積の状態を評価した結果であること、を特徴とする。 Further, the terminal device according to the present invention is a terminal device including a control unit, and the control unit provides a result acquisition means for acquiring an evaluation result regarding a state of accumulation of Aβ in the brain of an evaluation target. The evaluation result includes a measured value of at least one of the 24 kinds of amino acids and the 26 kinds of amino acid-related metabolites in the blood to be evaluated, or a variable to which the measured value is assigned. It is a result of evaluating the state of accumulation of Aβ in the brain of the evaluation target by using the value of the formula calculated by using the measured value.
　また、本発明にかかる端末装置は、前記評価対象について、Ａβの脳内への蓄積の状態を評価する評価装置とネットワークを介して通信可能に接続されており、前記制御部が、前記測定値に関する測定データまたは前記式の値を前記評価装置へ送信するデータ送信手段を備え、前記結果取得手段が、前記評価装置から送信された前記評価結果を受信すること、を特徴とする。 Further, the terminal device according to the present invention is communicably connected to the evaluation device for evaluating the state of accumulation of Aβ in the brain of the evaluation target via a network, and the control unit is connected to the measured value. The data transmission means for transmitting the measurement data or the value of the above formula to the evaluation device is provided, and the result acquisition means receives the evaluation result transmitted from the evaluation device.
　本発明によれば、Ａβの脳内への蓄積の状態を知る上で参考となり得る信頼性の高い情報を提供することができるという効果を奏する。 According to the present invention, it is possible to provide highly reliable information that can be used as a reference for knowing the state of accumulation of Aβ in the brain.
図１は、第１実施形態の基本原理を示す原理構成図である。FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment. 図２は、第２実施形態の基本原理を示す原理構成図である。FIG. 2 is a principle configuration diagram showing the basic principle of the second embodiment. 図３は、本システムの全体構成の一例を示す図である。FIG. 3 is a diagram showing an example of the overall configuration of this system. 図４は、本システムの全体構成の他の一例を示す図である。FIG. 4 is a diagram showing another example of the overall configuration of the system. 図５は、本システムの評価装置１００の構成の一例を示すブロック図である。FIG. 5 is a block diagram showing an example of the configuration of the evaluation device 100 of this system. 図６は、測定データファイル１０６ａに格納される情報の一例を示す図である。FIG. 6 is a diagram showing an example of information stored in the measurement data file 106a. 図７は、指標状態情報ファイル１０６ｂに格納される情報の一例を示す図である。FIG. 7 is a diagram showing an example of information stored in the index state information file 106b. 図８は、指定指標状態情報ファイル１０６ｃに格納される情報の一例を示す図である。FIG. 8 is a diagram showing an example of information stored in the designated index state information file 106c. 図９は、式ファイル１０６ｄ１に格納される情報の一例を示す図である。FIG. 9 is a diagram showing an example of information stored in the formula file 106d1. 図１０は、評価結果ファイル１０６ｅに格納される情報の一例を示す図である。FIG. 10 is a diagram showing an example of information stored in the evaluation result file 106e. 図１１は、評価部１０２ｄの構成を示すブロック図である。FIG. 11 is a block diagram showing the configuration of the evaluation unit 102d. 図１２は、本システムのクライアント装置２００の構成の一例を示すブロック図である。FIG. 12 is a block diagram showing an example of the configuration of the client device 200 of this system. 図１３は、本システムのデータベース装置４００の構成の一例を示すブロック図である。FIG. 13 is a block diagram showing an example of the configuration of the database device 400 of this system.
　以下に、本発明にかかる評価方法および算出方法の実施形態（第１実施形態）ならびに本発明にかかる評価装置、算出装置、評価方法、算出方法、評価プログラム、算出プログラム、記録媒体、評価システムおよび端末装置の実施形態（第２実施形態）を、図面に基づいて詳細に説明する。なお、本発明はこれらの実施形態により限定されるものではない。 Hereinafter, an embodiment of the evaluation method and the calculation method according to the present invention (first embodiment), and an evaluation device, a calculation device, an evaluation method, a calculation method, an evaluation program, a calculation program, a recording medium, an evaluation system, and the like according to the present invention. An embodiment (second embodiment) of the terminal device will be described in detail with reference to the drawings. The present invention is not limited to these embodiments.
［第１実施形態］
［１－１．第１実施形態の概要］
　ここでは、第１実施形態の概要について図１を参照して説明する。図１は第１実施形態の基本原理を示す原理構成図である。 [First Embodiment]
[1-1. Outline of the first embodiment]
Here, the outline of the first embodiment will be described with reference to FIG. FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment.
　まず、評価対象（例えば動物やヒトなどの個体）から採取した血液（例えば血漿、血清などを含む）中の「前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物」のうちの少なくとも１つの物質の測定値に関する測定データを取得する（ステップＳ１１）。ここで、例えば、軽度認知障害または初期のアルツハイマー病を有するまたはその疑いのある個体（例えば、軽度認知障害またはアルツハイマー病の既存の診断基準に基づき軽度認知障害もしくは初期のアルツハイマー病を有するまたはその疑いがあると診断された個体など）を評価対象としてもよい。また、測定値とは、例えば、濃度値、ピーク面積値または濃度値の比などである。また、ＢＣＡＡ（branched-chain amino acids）は、Ｌｅｕ、ＩｌｅおよびＶａｌを意味し、ＢＣＡＡの濃度値は、Ｌｅｕ、ＩｌｅおよびＶａｌの濃度値の和を意味する。 First, at least one of "the 24 kinds of amino acids and the 26 kinds of amino acid-related metabolites" in blood (including plasma, serum, etc.) collected from an evaluation target (for example, an individual such as an animal or a human). Acquire measurement data regarding the measured value of the substance (step S11). Here, for example, an individual having or suspected of having mild cognitive impairment or early Alzheimer's disease (eg, having or suspected of having mild cognitive impairment or early Alzheimer's disease based on existing diagnostic criteria for mild cognitive impairment or early Alzheimer's disease). (Individuals diagnosed as having) may be evaluated. The measured value is, for example, a concentration value, a peak area value, or a ratio of concentration values. Further, BCAA (branched-chain amino acids) means Leu, Ile and Val, and the concentration value of BCAA means the sum of the concentration values of Leu, Ile and Val.
　なお、ステップＳ１１では、例えば、企業等が測定した前記物質に関する測定データを取得してもよい。また、評価対象から採取した血液から、例えば以下の（Ａ）、（Ｂ）または（Ｃ）などの測定方法により前記物質の濃度値を測定することで前記物質の濃度値を取得してもよい。ここで、前記物質の濃度値の単位は、例えばモル濃度、重量濃度または酵素活性であってもよく、これらの濃度に任意の定数を加減乗除することで得られるものでもよい。
（Ａ）採取した血液サンプルを遠心することにより血液から血漿を分離する。全ての血漿サンプルは、濃度値の測定時まで－８０℃で凍結保存する。濃度値測定時には、アセトニトリルを添加し除蛋白処理を行った後、必要に応じて固層抽出等によりリン脂質等の夾雑物を除去し、標識試薬（３－アミノピリジル－Ｎ－ヒドロキシスクシンイミジルカルバメート）を用いてプレカラム誘導体化を行い、そして、液体クロマトグラフィー質量分析法（タンデム質量分析法を含む）により濃度値を分析する（国際公開第２００３／０６９３２８号、国際公開第２００５／１１６６２９号を参照）。
（Ｂ）採取した血液サンプルを遠心することにより血液から血漿を分離する。全ての血漿サンプルは、濃度値の測定時まで－８０℃で凍結保存する。濃度値測定時には、スルホサリチル酸を添加し除蛋白処理を行った後、ニンヒドリン試薬を用いたポストカラム誘導体化法を原理としたアミノ酸分析計により濃度値を分析する。
（Ｃ）採取した血液サンプルを、膜やＭＥＭＳ（Micro Electro Mechanical Systems）技術または遠心分離の原理を用いて血球分離を行い、血液から血漿または血清を分離する。血漿または血清取得後すぐに濃度値の測定を行わない血漿または血清サンプルは、濃度値の測定時まで－８０℃で凍結保存する。濃度値測定時には、酵素やアプタマーなど、標的とする血中物質と反応または結合する分子等を用い、基質認識によって増減する物質や分光学的値を定量等することにより濃度値を分析する。 In step S11, for example, measurement data regarding the substance measured by a company or the like may be acquired. Further, the concentration value of the substance may be obtained from the blood collected from the evaluation target by measuring the concentration value of the substance by the following measuring methods such as (A), (B) or (C). .. Here, the unit of the concentration value of the substance may be, for example, a molar concentration, a weight concentration, or an enzyme activity, and may be obtained by adding, subtracting, multiplying, or dividing an arbitrary constant to these concentrations.
(A) Plasma is separated from blood by centrifuging the collected blood sample. All plasma samples are cryopreserved at -80 ° C until the concentration value is measured. When measuring the concentration value, acetonitrile is added to perform derivatization treatment, and if necessary, contaminants such as phospholipids are removed by solid layer extraction or the like, and a labeling reagent (3-aminopyridyl-N-hydroxysuccinimidimi) is removed. Pre-column derivatization is performed using dizyl carbamate), and concentration values are analyzed by liquid chromatography-mass spectrometry (including tandem mass spectrometry) (International Publication No. 2003/066283, International Publication No. 2005/116629). See).
(B) Plasma is separated from blood by centrifuging the collected blood sample. All plasma samples are cryopreserved at -80 ° C until the concentration value is measured. When measuring the concentration value, sulfosalicylic acid is added to perform deproteinization treatment, and then the concentration value is analyzed by an amino acid analyzer based on the post-column derivatization method using a ninhydrin reagent.
(C) The collected blood sample is subjected to blood cell separation using a membrane, MEMS (Micro Electro Mechanical Systems) technology or the principle of centrifugation, and plasma or serum is separated from the blood. Plasma or serum samples for which concentration values are not measured immediately after acquisition are cryopreserved at −80 ° C. until concentration values are measured. When measuring the concentration value, a molecule that reacts with or binds to a target blood substance such as an enzyme or an aptamer is used, and the concentration value is analyzed by quantifying the substance that increases or decreases due to substrate recognition or the spectroscopic value.
　つぎに、ステップＳ１１で取得した測定データに含まれる測定値を用いて、評価対象についてＡβの脳内への蓄積の状態を評価する（ステップＳ１２）。ここで、Ａβの脳内への蓄積の状態を評価するとは、例えば、Ａβの脳内への蓄積の現在の蓄積量を評価することまたはＡβの陽性もしくは陰性を評価することなどである。なお、ステップＳ１２を実行する前に、ステップＳ１１で取得した測定データから欠損値や外れ値などのデータを除去してもよい。 Next, the state of accumulation of Aβ in the brain of the evaluation target is evaluated using the measured values included in the measurement data acquired in step S11 (step S12). Here, evaluating the state of accumulation of Aβ in the brain means, for example, evaluating the current amount of accumulation of Aβ in the brain or evaluating the positive or negative of Aβ. Note that data such as missing values and outliers may be removed from the measurement data acquired in step S11 before executing step S12.
　以上、第１実施形態によれば、ステップＳ１１では評価対象の測定データを取得し、ステップＳ１２では、ステップＳ１１で取得した測定データに含まれる測定値を用いて、評価対象についてＡβの脳内への蓄積の状態を評価する（要するに、評価対象についてＡβの脳内への蓄積の状態を評価するための情報を取得する）。これにより、評価対象についてＡβの脳内への蓄積の状態を知る上で参考となり得る信頼性の高い情報を提供することができる。また、簡便な測定方法で定量可能である血液中のアミノ酸および／またはアミノ酸関連代謝物の濃度等を指標とした高精度なＡβ蓄積評価技術を提供することができる。また、マススクリーニングに適した簡便且つ安価なＡβ蓄積評価検査法を提供することができる。また、Ａβの脳内への蓄積の評価を高精度で行うことができる新規な血液バイオマーカーを提供することができる。 As described above, according to the first embodiment, the measurement data of the evaluation target is acquired in step S11, and in step S12, the measurement value included in the measurement data acquired in step S11 is used to move the evaluation target into the brain of Aβ. Evaluate the state of accumulation of Aβ (in short, acquire information for evaluating the state of accumulation of Aβ in the brain for the evaluation target). This makes it possible to provide highly reliable information that can be used as a reference for knowing the state of accumulation of Aβ in the brain for the evaluation target. In addition, it is possible to provide a highly accurate Aβ accumulation evaluation technique using the concentration of amino acids and / or amino acid-related metabolites in blood, which can be quantified by a simple measurement method, as an index. Further, it is possible to provide a simple and inexpensive Aβ accumulation evaluation test method suitable for mass screening. In addition, it is possible to provide a novel blood biomarker capable of evaluating the accumulation of Aβ in the brain with high accuracy.
　なお、ステップＳ１２では、前記少なくとも１つの物質の測定値および当該測定値が代入される変数を含む式を用いて当該式の値を算出することで、評価対象についてＡβの脳内への蓄積の状態を評価してもよい。これにより、血液バイオマーカーの組み合わせを変数として含む、Ａβの脳内への蓄積の評価を高精度で行うことができる新規な式を提供することができる。 In step S12, the accumulation of Aβ in the brain of the evaluation target is performed by calculating the value of the formula using the measured value of the at least one substance and the formula including the variable to which the measured value is substituted. The condition may be evaluated. This makes it possible to provide a novel formula that includes a combination of blood biomarkers as a variable and can evaluate the accumulation of Aβ in the brain with high accuracy.
　また、前記少なくとも１つの物質の測定値または式の値が評価対象についてのＡβの脳内への蓄積の状態を反映したものであると決定してもよく、さらに、当該測定値または当該式の値を例えば以下に挙げた手法などで変換し、変換後の値が評価対象についてのＡβの脳内への蓄積の状態を反映したものであると決定してもよい。換言すると、測定値若しくは式の値または変換後の値そのものを、評価対象についてのＡβの脳内への蓄積の状態に関する評価結果として扱ってもよい。ここで、変換の手法について、以下に説明する。なお、以下の説明は、測定値を変換対象としたものであるが、式の値を変換対象とした場合も同様である。
　測定値の取り得る範囲が所定範囲（例えば０．０から１．０までの範囲、０．０から１０．０までの範囲、０．０から１００．０までの範囲、または－１０．０から１０．０までの範囲、など）に収まるようにするためなどに、例えば、測定値に対して任意の値を加減乗除したり、測定値を所定の変換手法（例えば、指数変換、対数変換、角変換、平方根変換、プロビット変換、逆数変換、Ｂｏｘ－Ｃｏｘ変換、またはべき乗変換など）で変換したり、また、測定値に対してこれらの計算を組み合わせて行ったりすることで、測定値を変換してもよい。例えば、測定値を指数としネイピア数を底とする指数関数の値（具体的には、Ａβの脳内への蓄積の状態が所定の状態（例えば、基準値よりも多い状態、など）である確率ｐを定義したときの自然対数ｌｎ（ｐ／（１－ｐ））が測定値と等しいとした場合におけるｐ／（１－ｐ）の値）をさらに算出してもよく、また、算出した指数関数の値を１と当該値との和で割った値（具体的には、確率ｐの値）をさらに算出してもよい。
　また、特定の条件のときの変換後の値が特定の値となるように、測定値を変換してもよい。例えば、特異度が８０％のときの変換後の値が５．０となり且つ特異度が９５％のときの変換後の値が８．０となるように測定値を変換してもよい。
　また、各アミノ酸および各アミノ酸関連代謝物ごとに、測定値の分布を正規分布化した後、平均５０、標準偏差１０となるように偏差値化してもよい。
　なお、これらの変換は、男女別や年齢別に行ってもよい。
　なお、本明細書における測定値は、測定値そのものであってもよく、測定値を変換した後の値であってもよい。また、本明細書における式の値は、式の値そのものであってもよく、式の値を変換した後の値であってもよい。 Further, it may be determined that the measured value or the value of the formula of at least one substance reflects the state of accumulation of Aβ in the brain for the evaluation target, and further, the measured value or the value of the formula may be determined. The value may be converted by, for example, the method described below, and it may be determined that the converted value reflects the state of accumulation of Aβ in the brain for the evaluation target. In other words, the measured value or the value of the formula or the converted value itself may be treated as an evaluation result regarding the state of accumulation of Aβ in the brain for the evaluation target. Here, the conversion method will be described below. In the following description, the measured value is the conversion target, but the same applies when the value of the equation is the conversion target.
The possible range of measured values is a predetermined range (for example, 0.0 to 1.0, 0.0 to 10.0, 0.0 to 100.0, or -10.0 to -10.0. In order to fit within the range up to 10.0, etc.), for example, any value can be added, subtracted, multiplied, divided, or the measured value can be converted into a predetermined conversion method (for example, exponential conversion, logarithmic conversion, etc.). Convert the measured value by converting it with angle conversion, square root conversion, probit conversion, reciprocal conversion, Box-Cox conversion, or power conversion, etc., or by combining these calculations with the measured value. You may. For example, the value of an exponential function with the measured value as an index and the base of the Napier number (specifically, the state of accumulation of Aβ in the brain is a predetermined state (for example, a state of being greater than the reference value)). The value of p / (1-p) when the natural logarithm ln (p / (1-p)) when the probability p is defined is equal to the measured value) may be further calculated, or calculated. A value obtained by dividing the value of the exponential function by the sum of 1 and the value (specifically, the value of the probability p) may be further calculated.
Further, the measured value may be converted so that the converted value under a specific condition becomes a specific value. For example, the measured value may be converted so that the converted value when the specificity is 80% is 5.0 and the converted value when the specificity is 95% is 8.0.
Further, for each amino acid and each amino acid-related metabolite, the distribution of the measured values may be normally distributed and then deviated so as to have an average of 50 and a standard deviation of 10.
In addition, these conversions may be performed by gender or age.
The measured value in the present specification may be the measured value itself or the value after converting the measured value. Further, the value of the expression in the present specification may be the value of the expression itself or the value after converting the value of the expression.
　また、モニタ等の表示装置または紙等の物理媒体に視認可能に示される所定の物差し上における所定の目印の位置に関する位置情報を、前記少なくとも１つの物質の測定値若しくは式の値または当該測定値若しくは当該式の値を変換した場合にはその変換後の値を用いて生成し、生成した位置情報が評価対象についてのＡβの脳内への蓄積の状態を反映したものであると決定してもよい。なお、所定の物差しとは、Ａβの脳内への蓄積の状態を評価するためのものであり、例えば、目盛りが示された物差しであって、「測定値若しくは式の値または変換後の値の取り得る範囲、または、当該範囲の一部分」における上限値と下限値に対応する目盛りが少なくとも示されたもの、などである。また、所定の目印とは、測定値若しくは式の値または変換後の値に対応するものであり、例えば、丸印または星印などである。 In addition, the position information regarding the position of a predetermined mark on a predetermined measuring rod that is visually displayed on a display device such as a monitor or a physical medium such as paper is a measured value or a formula value of the at least one substance or the measured value. Alternatively, when the value of the equation is converted, it is generated using the converted value, and it is determined that the generated position information reflects the state of accumulation of Aβ in the brain for the evaluation target. May be good. The predetermined measuring rod is for evaluating the state of accumulation of Aβ in the brain. For example, it is a measuring rod with a scale shown, and is "a measured value or a value of an expression or a value after conversion". At least the scales corresponding to the upper limit value and the lower limit value in "a possible range or a part of the range" are shown. Further, the predetermined mark corresponds to the measured value or the value of the formula or the value after conversion, and is, for example, a circle mark or a star mark.
　また、前記少なくとも１つの物質の測定値が、所定値（平均値±１ＳＤ、２ＳＤ、３ＳＤ、Ｎ分位点、Ｎパーセンタイルまたは臨床的意義の認められたカットオフ値など）より低い若しくは所定値以下の場合または所定値以上若しくは所定値より高い場合に、評価対象についてＡβの脳内への蓄積の状態を評価してもよい。その際、測定値そのものではなく、偏差値を用いてもよい。例えば、偏差値が平均値－２ＳＤ未満の場合（偏差値＜３０の場合）または偏差値が平均値＋２ＳＤより高い場合（偏差値＞７０の場合）に、評価対象についてＡβの脳内への蓄積の状態を評価してもよい。 In addition, the measured value of at least one substance is lower than or less than a predetermined value (mean value ± 1SD, 2SD, 3SD, N quantile, N percentile, cutoff value having clinical significance, etc.). In the case of, or when the value is equal to or higher than the predetermined value or higher than the predetermined value, the state of accumulation of Aβ in the brain may be evaluated for the evaluation target. At that time, the deviation value may be used instead of the measured value itself. For example, when the deviation value is less than the mean value-2SD (when the deviation value <30) or when the deviation value is higher than the mean value + 2SD (when the deviation value> 70), the accumulation of Aβ in the brain for the evaluation target The state of may be evaluated.
　また、評価対象におけるＡβの脳内への蓄積の程度を定性的に評価してもよい。具体的には、「前記少なくとも１つの物質の測定値および予め設定された１つまたは複数の閾値」または「前記少なくとも１つの物質の測定値、当該測定値が代入される変数を含む式、および予め設定された１つまたは複数の閾値」を用いて、評価対象を、Ａβの脳内への蓄積の程度を少なくとも考慮して定義された複数の区分のうちのどれか１つに分類してもよい。なお、複数の区分には、Ａβの脳内への蓄積が多い対象を属させるための区分、Ａβの脳内への蓄積が少ない対象を属させるための区分およびＡβの脳内への蓄積が中程度である対象を属させるための区分が含まれてもよい。また、複数の区分には、Ａβの脳内への蓄積が多い対象を属させるための区分およびＡβの脳内への蓄積が少ない対象を属させるための区分が含まれてもよい。また、測定値または式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか１つに分類してもよい。 Further, the degree of accumulation of Aβ in the brain in the evaluation target may be qualitatively evaluated. Specifically, "a measurement of at least one substance and one or more preset thresholds" or "a measurement of at least one substance, an expression containing a variable to which the measurement is assigned, and Using one or more preset thresholds, the evaluation target is classified into one of a plurality of categories defined at least considering the degree of accumulation of Aβ in the brain. May be good. The plurality of categories include a category for belonging to a subject having a large amount of Aβ accumulated in the brain, a category for belonging a subject having a small amount of Aβ accumulated in the brain, and a category for belonging to a subject having a small amount of Aβ accumulated in the brain. Divisions for belonging moderate objects may be included. In addition, the plurality of categories may include a category for belonging a subject having a large amount of Aβ accumulated in the brain and a category for belonging a subject having a small amount of Aβ accumulated in the brain. Further, the measured value or the value of the formula may be converted by a predetermined method, and the evaluation target may be classified into any one of a plurality of categories using the converted value.
　また、評価の際に用いる式について、その形式は特に問わないが、例えば、以下に示す形式のものでもよい。
・最小二乗法に基づく重回帰式、線形判別式、主成分分析、正準判別分析などの線形モデル
・最尤法に基づくロジスティック回帰、Ｃｏｘ回帰などの一般化線形モデル
・一般化線形モデルに加えて個体間差、施設間差などの変量効果を考慮した一般化線形混合モデル
・Ｋ－ｍｅａｎｓ法、階層的クラスタ解析などクラスタ解析で作成された式
・ＭＣＭＣ(マルコフ連鎖モンテカルロ法)、ベイジアンネットワーク、階層ベイズ法などベイズ統計に基づき作成された式
・サポートベクターマシンや決定木などクラス分類により作成された式
・分数式など上記のカテゴリに属さない手法により作成された式
・異なる形式の式の和で示されるような式 The format of the formula used for evaluation is not particularly limited, but may be, for example, the following format.
・ Linear models such as multiple regression equations, linear discriminant equations, principal component analysis, canonical discriminant analysis based on the least square method ・ Generalized linear models such as logistic regression and Cox regression based on the most likely method ・ In addition to generalized linear models Generalized linear mixed model considering variable effects such as individual differences and facility differences-Formulas created by cluster analysis such as K-means method and hierarchical cluster analysis-MCMC (Markov chain Monte Carlo method), Bayesian network, Expressions created based on Bayesian statistics such as the hierarchical Bayes method ・ Expressions created by classification such as support vector machines and decision trees ・ Expressions created by methods that do not belong to the above categories such as discriminant equations ・ Sum of expressions of different formats Expression as shown by
　また、評価の際に用いる式を、例えば、本出願人による国際出願である国際公開第２００４／０５２１９１号に記載の方法または本出願人による国際出願である国際公開第２００６／０９８１９２号に記載の方法で作成してもよい。なお、これらの方法で得られた式であれば、入力データとしての測定データにおけるアミノ酸および／またはアミノ酸関連代謝物の測定値の単位に因らず、当該式をＡβの脳内への蓄積の状態を評価するのに好適に用いることができる。 Further, the formula used for evaluation is described in, for example, the method described in International Publication No. 2004/052191, which is an international application by the applicant, or International Publication No. 2006/098192, which is an international application by the applicant. It may be created by the method. In addition, in the case of the formulas obtained by these methods, the formula is used for the accumulation of Aβ in the brain regardless of the unit of the measured value of the amino acid and / or the amino acid-related metabolite in the measurement data as input data. It can be suitably used for evaluating the state.
　ここで、重回帰式、多重ロジスティック回帰式、正準判別関数などにおいては各変数に係数および定数項が付加されるが、この係数および定数項は、好ましくは実数であれば構わず、より好ましくは、データから前記の各種分類を行うために得られた係数および定数項の９９％信頼区間の範囲に属する値であれば構わず、さらに好ましくは、データから前記の各種分類を行うために得られた係数および定数項の９５％信頼区間の範囲に属する値であれば構わない。また、各係数の値およびその信頼区間は、それを実数倍したものでもよく、定数項の値およびその信頼区間は、それに任意の実定数を加減乗除したものでもよい。ロジスティック回帰式、線形判別式、重回帰式などを評価の際に用いる場合、線形変換（定数の加算、定数倍）および単調増加（減少）の変換（例えばｌｏｇｉｔ変換など）は評価性能を変えるものではなく変換前と同等であるので、これらの変換が行われた後のものを用いてもよい。 Here, in the multiple regression equation, the multiple logistic regression equation, the canonical discrimination function, etc., a coefficient and a constant term are added to each variable, and the coefficient and the constant term may be preferably a real number, more preferably. Is a value that belongs to the range of the 99% confidence interval of the coefficient and the constant term obtained for performing the above-mentioned various classifications from the data, and more preferably, for performing the above-mentioned various classifications from the data. Any value that belongs to the range of the 95% confidence interval of the obtained coefficient and constant term may be used. Further, the value of each coefficient and its confidence interval may be obtained by multiplying it by a real number, and the value of the constant term and its confidence interval may be obtained by adding, subtracting, multiplying or dividing an arbitrary real constant. When logistic regression equations, linear discrimination equations, multiple regression equations, etc. are used for evaluation, linear transformation (addition of constants, multiplication of constants) and transformation of monotonous increase (decrease) (for example, logit transformation) change the evaluation performance. Since it is the same as before the conversion, the one after these conversions may be used.
　また、分数式とは、当該分数式の分子が変数Ａ，Ｂ，Ｃ，・・・の和で表わされおよび／または当該分数式の分母が変数ａ，ｂ，ｃ，・・・の和で表わされるものである。また、分数式には、このような構成の分数式α，β，γ，・・・の和（例えばα＋βのようなもの）も含まれる。また、分数式には、分割された分数式も含まれる。なお、分子や分母に用いられる変数にはそれぞれ適当な係数がついても構わない。また、分子や分母に用いられる変数は重複しても構わない。また、各分数式に適当な係数がついても構わない。また、各変数の係数の値や定数項の値は、実数であれば構わない。ある分数式と、当該分数式において分子の変数と分母の変数が入れ替えられたものとでは、目的変数との相関の正負の符号が概して逆転するものの、それらの相関性は保たれるが故に、評価性能も同等と見做せるので、分数式には、分子の変数と分母の変数が入れ替えられたものも含まれる。 In the fractional expression, the numerator of the fractional expression is represented by the sum of variables A, B, C, ... And / or the denominator of the fractional expression is the sum of variables a, b, c, ... It is represented by. The fractional formula also includes the sum of the fractional formulas α, β, γ, ... (For example, α + β) having such a configuration. The fractional expression also includes a divided fractional expression. The variables used for the numerator and denominator may have appropriate coefficients. Also, the variables used for the numerator and denominator may be duplicated. In addition, an appropriate coefficient may be added to each fractional formula. Further, the coefficient value of each variable and the value of the constant term may be real numbers. A certain denominator formula and the one in which the variable of the molecule and the variable of the denominator are exchanged in the denominator formula generally reverse the positive and negative signs of the correlation with the objective variable, but the correlation between them is maintained. Since the evaluation performance can be regarded as equivalent, the fractional expression includes the variable of the molecule and the variable of the denominator exchanged.
　そして、Ａβの脳内への蓄積の状態を評価する際、前記少なくとも１つの物質の測定値以外に、他の生体情報に関する値（例えば、以下に挙げた値など）をさらに用いても構わない。また、評価の際に用いる式には、前記少なくとも１つの物質の測定値が代入される変数以外に、他の生体情報に関する値（例えば、以下に挙げた値など）が代入される１つまたは複数の変数がさらに含まれていてもよい。
１．アミノ酸およびアミノ酸関連代謝物以外の他の血中の代謝物（糖類・脂質等）、タンパク質、ペプチド、ミネラル、ホルモン等の濃度値
２．アルブミン、総蛋白、トリグリセリド（中性脂肪）、ＨｂＡ１ｃ、糖化アルブミン、インスリン抵抗性指数、総コレステロール、ＬＤＬコレステロール、ＨＤＬコレステロール、アミラーゼ、総ビリルビン、クレアチニン、推算糸球体濾過量(ｅＧＦＲ)、尿酸、ＧＯＴ（ＡＳＴ）、ＧＰＴ（ＡＬＴ），ＧＧＴＰ（γ－ＧＴＰ）、グルコース（血糖値）、ＣＲＰ（Ｃ反応性蛋白）、赤血球、ヘモグロビン、ヘマトクリット、ＭＣＶ、ＭＣＨ，ＭＣＨＣ、白血球、血小板数等の血液検査値
３．超音波エコー、Ｘ線、ＣＴ、ＭＲＩ、内視鏡像等の画像情報から得られる値
４．年齢、身長、体重、ＢＭＩ、腹囲、収縮期血圧、拡張期血圧、性別、喫煙情報、食事情報、飲酒情報、運動情報、ストレス情報、睡眠情報、教育歴、家族の既往歴情報、疾患歴情報（糖尿病等）等の生体指標に関する値
５．アルツハイマー型認知症のリスク遺伝子（ＡＰＯＥε４アリル等）の保有数等の遺伝子情報から得られる値
６．ミニメンタルステート検査（MMSE）、改訂版長谷川式簡易知能評価スケール（HDS-R）等の神経心理検査の値 Then, when evaluating the state of accumulation of Aβ in the brain, values related to other biological information (for example, values listed below) may be further used in addition to the measured values of at least one substance. .. Further, in the formula used at the time of evaluation, in addition to the variable to which the measured value of at least one substance is substituted, one or one to which a value related to other biological information (for example, the value listed below) is substituted. Multiple variables may be further included.
1. 1. Concentration values of amino acids and other blood metabolites (sugars, lipids, etc.), proteins, peptides, minerals, hormones, etc. other than amino acid-related metabolites 2. Albumin, total protein, triglyceride (neutral fat), HbA1c, glycated albumin, insulin resistance index, total cholesterol, LDL cholesterol, HDL cholesterol, amylase, total bilirubin, creatinine, estimated glomerular filtration rate (eGFR), uric acid, GOT Blood tests for (AST), GPT (ALT), GGTP (γ-GTP), glucose (blood glucose level), CRP (C-reactive protein), red blood cells, hemoglobin, hematocrit, MCV, MCH, MCHC, leukocytes, platelet count, etc. Value 3. 3. Values obtained from image information such as ultrasonic echo, X-ray, CT, MRI, and endoscopic image. Age, height, weight, BMI, abdominal circumference, systolic blood pressure, diastolic blood pressure, gender, smoking information, dietary information, drinking information, exercise information, stress information, sleep information, educational history, family history information, disease history information Values related to biomarkers such as (diabetes, etc.) 5. 6. Values obtained from genetic information such as the number of possession of risk genes for Alzheimer's disease (APOEε4 allele, etc.). Values of neuropsychological tests such as the Mini-Mental State Examination (MMSE) and the revised Hasegawa Simple Intelligence Scale (HDS-R)
［第２実施形態］
［２－１．第２実施形態の概要］
　ここでは、第２実施形態の概要について図２を参照して説明する。図２は第２実施形態の基本原理を示す原理構成図である。なお、本第２実施形態の説明では、上述した第１実施形態と重複する説明を省略する場合がある。特に、ここでは、Ａβの脳内への蓄積の状態を評価する際に、式の値またはその変換後の値を用いるケースを一例として記載しているが、例えば、「前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物」のうちの少なくとも１つの物質の測定値またはその変換後の値（例えば偏差値など）を用いてもよい。 [Second Embodiment]
[2-1. Outline of the second embodiment]
Here, the outline of the second embodiment will be described with reference to FIG. FIG. 2 is a principle configuration diagram showing the basic principle of the second embodiment. In the description of the second embodiment, the description overlapping with the above-described first embodiment may be omitted. In particular, here, a case where the value of the formula or the value after conversion thereof is used when evaluating the state of accumulation of Aβ in the brain is described as an example. For example, "the above 24 kinds of amino acids and The measured value of at least one substance of the "26 kinds of amino acid-related metabolites" or the value after conversion thereof (for example, deviation value) may be used.
　制御部は、血液中の前記少なくとも１つの物質の測定値に関する予め取得した評価対象（例えば動物やヒトなどの個体）の測定データに含まれる測定値および前記少なくとも１つの物質の測定値が代入される変数を含む予め記憶部に記憶された式を用いて、式の値を算出することで、評価対象についてＡβの脳内への蓄積の状態を評価する（ステップＳ２１）。これにより、Ａβの脳内への蓄積の状態を知る上で参考となり得る信頼性の高い情報を提供することができる。 The control unit is substituted with the measured value included in the measured data of the evaluation target (for example, an individual such as an animal or a human) acquired in advance regarding the measured value of the at least one substance in the blood and the measured value of the at least one substance. By calculating the value of the formula using the formula stored in the storage unit in advance including the variable, the state of accumulation of Aβ in the brain of the evaluation target is evaluated (step S21). This makes it possible to provide highly reliable information that can be used as a reference for knowing the state of accumulation of Aβ in the brain.
　なお、ステップＳ２１で用いられる式は、以下に説明する式作成処理（工程１～工程４）に基づいて作成されたものでもよい。ここで、式作成処理の概要について説明する。なお、ここで説明する処理はあくまでも一例であり、式の作成方法はこれに限定されない。 The formula used in step S21 may be one created based on the formula creation process (steps 1 to 4) described below. Here, the outline of the expression creation process will be described. The process described here is just an example, and the method of creating an expression is not limited to this.
　まず、制御部は、測定データとＡβの脳内への蓄積の状態を表す指標（例えば、Ａβイメージング画像に基づく医師によるＡβ陽性または陰性の判定、アミロイドＰＥＴ検査等に基づく脳内へのＡβの集積度合、など）に関する指標データとを含む予め記憶部に記憶された指標状態情報（欠損値や外れ値などを持つデータが事前に除去されているものでもよい）から所定の式作成手法に基づいて、候補式（例えば、ｙ＝ａ１ｘ１＋ａ２ｘ２＋・・・＋ａｎｘｎ、ｙ：指標データ、ｘｉ：測定データ、ａｉ：定数、ｉ＝１，２，・・・，ｎ）を作成する（工程１）。 First, the control unit determines the measurement data and the index indicating the state of accumulation of Aβ in the brain (for example, Aβ positive or negative judgment by a doctor based on Aβ imaging images, Aβ in the brain based on an amyloid PET test, etc.) Based on a predetermined formula creation method from index state information (data with missing values, outliers, etc. may be removed in advance) stored in the storage unit in advance, including index data related to the degree of accumulation, etc.) Then, a candidate formula (for example, y = a1x1 + a2x2 + ... + anxn, y: index data, xi: measurement data, ai: constant, i = 1, 2, ..., N) is created (step 1).
　なお、工程１において、指標状態情報から、複数の異なる式作成手法（主成分分析や判別分析、サポートベクターマシン、重回帰分析、Ｃｏｘ回帰分析、ロジスティック回帰分析、ｋ－ｍｅａｎｓ法、クラスター解析、決定木などの多変量解析に関するものを含む。）を併用して複数の候補式を作成してもよい。具体的には、Ａβ蓄積の程度が様々な複数の者から得た血液を分析して得た測定データおよび指標データから構成される多変量データである指標状態情報に対して、複数の異なるアルゴリズムを利用して複数群の候補式を同時並行的に作成してもよい。例えば、異なるアルゴリズムを利用して判別分析およびロジスティック回帰分析を同時に行い、２つの異なる候補式を作成してもよい。また、主成分分析を行って作成した候補式を利用して指標状態情報を変換し、変換した指標状態情報に対して判別分析を行うことで候補式を作成してもよい。これにより、最終的に、評価に最適な式を作成することができる。 In step 1, a plurality of different formula creation methods (principal component analysis, discriminant analysis, support vector machine, multiple regression analysis, Cox regression analysis, logistic regression analysis, k-means method, cluster analysis, determination) are performed from the index state information. A plurality of candidate formulas may be created in combination with those related to multivariate analysis such as trees. Specifically, a plurality of different algorithms for index state information, which is multivariate data composed of measurement data and index data obtained by analyzing blood obtained from a plurality of persons having various degrees of Aβ accumulation. May be used to create multiple groups of candidate expressions in parallel. For example, discriminant analysis and logistic regression analysis may be performed simultaneously using different algorithms to create two different candidate formulas. Further, the candidate formula may be created by converting the index state information using the candidate formula created by performing the principal component analysis and performing discriminant analysis on the converted index state information. As a result, the optimum formula for evaluation can be finally created.
　ここで、主成分分析を用いて作成した候補式は、全ての測定データの分散を最大にするような各変数を含む一次式である。また、判別分析を用いて作成した候補式は、各群内の分散の和の全ての測定データの分散に対する比を最小にするような各変数を含む高次式（指数や対数を含む）である。また、サポートベクターマシンを用いて作成した候補式は、群間の境界を最大にするような各変数を含む高次式（カーネル関数を含む）である。また、重回帰分析を用いて作成した候補式は、全ての測定データからの距離の和を最小にするような各変数を含む高次式である。また、Ｃｏｘ回帰分析を用いて作成した候補式は、対数ハザード比を含む線形モデルで、そのモデルの尤度を最大とするような各変数とその係数を含む１次式であるである。また、ロジスティック回帰分析を用いて作成した候補式は、確率の対数オッズを表す線形モデルであり、その確率の尤度を最大にするような各変数を含む一次式である。また、ｋ－ｍｅａｎｓ法とは、各測定データのｋ個近傍を探索し、近傍点の属する群の中で一番多いものをそのデータの所属群と定義し、入力された測定データの属する群と定義された群とが最も合致するような変数を選択する手法である。また、クラスター解析とは、全ての測定データの中で最も近い距離にある点同士をクラスタリング（群化）する手法である。また、決定木とは、変数に序列をつけて、序列が上位である変数の取りうるパターンから測定データの群を予測する手法である。 Here, the candidate formula created using principal component analysis is a linear formula that includes each variable that maximizes the variance of all measurement data. In addition, the candidate formula created using discriminant analysis is a higher-order formula (including exponents and logarithms) that includes each variable that minimizes the ratio of the sum of the variances within each group to the variances of all measured data. is there. In addition, the candidate expression created using the support vector machine is a high-order expression (including a kernel function) including each variable that maximizes the boundary between groups. Further, the candidate formula created by using the multiple regression analysis is a higher-order formula including each variable that minimizes the sum of the distances from all the measurement data. The candidate formula created by using Cox regression analysis is a linear model including a logarithmic hazard ratio, and is a linear formula including each variable and its coefficient that maximizes the likelihood of the model. Further, the candidate formula created by using logistic regression analysis is a linear model representing the logarithmic odds of the probability, and is a linear formula including each variable that maximizes the likelihood of the probability. In the k-means method, k neighborhoods of each measurement data are searched, the group to which the neighborhood points belong is defined as the group to which the data belongs, and the group to which the input measurement data belongs. This is a method of selecting a variable that best matches the group defined as. In addition, cluster analysis is a method of clustering (grouping) points at the closest distance among all measurement data. The decision tree is a method of ordering variables and predicting a group of measurement data from possible patterns of variables having a higher rank.
　式作成処理の説明に戻り、制御部は、工程１で作成した候補式を、所定の検証手法に基づいて検証（相互検証）する（工程２）。候補式の検証は、工程１で作成した各候補式に対して行う。なお、工程２において、ブートストラップ法やホールドアウト法、Ｎ－フォールド法、リーブワンアウト法などのうち少なくとも１つに基づいて、候補式の判別率や感度、特異度、情報量基準、ＲＯＣ＿ＡＵＣ（受信者特性曲線の曲線下面積）などのうち少なくとも１つに関して検証してもよい。これにより、指標状態情報や評価条件を考慮した予測性または頑健性の高い候補式を作成することができる。 Returning to the explanation of the formula creation process, the control unit verifies (mutually verifies) the candidate formula created in step 1 based on a predetermined verification method (step 2). The verification of the candidate formula is performed for each candidate formula created in step 1. In step 2, the discrimination rate, sensitivity, specificity, information criterion, ROC_AUC (ROC_AUC) of the candidate formula are based on at least one of the bootstrap method, the holdout method, the N-fold method, and the leave one-out method. At least one of (the area under the curve of the receiver characteristic curve) and the like may be verified. As a result, it is possible to create a candidate formula with high predictability or robustness in consideration of index state information and evaluation conditions.
　ここで、判別率とは、本実施形態にかかる評価手法で、真の状態が陰性である評価対象（例えば、Ａβ陰性と診断された評価対象など）を正しく陰性と評価し、真の状態が陽性である評価対象（例えば、Ａβ陽性と診断された評価対象など）を正しく陽性と評価している割合である。また、感度とは、本実施形態にかかる評価手法で、真の状態が陽性である評価対象を正しく陽性と評価している割合である。また、特異度とは、本実施形態にかかる評価手法で、真の状態が陰性である評価対象を正しく陰性と評価している割合である。また、赤池情報量規準とは、回帰分析などの場合に，観測データが統計モデルにどの程度一致するかを表す基準であり、「－２×（統計モデルの最大対数尤度）＋２×（統計モデルの自由パラメータ数）」で定義される値が最小となるモデルを最もよいと判断する。また、ＲＯＣ＿ＡＵＣは、２次元座標上に（ｘ，ｙ）＝（１－特異度，感度）をプロットして作成される曲線である受信者特性曲線（ＲＯＣ）の曲線下面積として定義され、ＲＯＣ＿ＡＵＣの値は完全な判別では１となり、この値が１に近いほど判別性が高いことを示す。また、予測性とは、候補式の検証を繰り返すことで得られた判別率や感度、特異性を平均したものである。また、頑健性とは、候補式の検証を繰り返すことで得られた判別率や感度、特異性の分散である。 Here, the discrimination rate is an evaluation method according to the present embodiment, in which an evaluation target whose true state is negative (for example, an evaluation target diagnosed as Aβ negative) is correctly evaluated as negative, and the true state is determined. This is the ratio at which a positive evaluation target (for example, an evaluation target diagnosed as Aβ positive) is correctly evaluated as positive. Further, the sensitivity is a ratio in which the evaluation target whose true state is positive is correctly evaluated as positive in the evaluation method according to the present embodiment. The specificity is the ratio at which the evaluation target whose true state is negative is correctly evaluated as negative in the evaluation method according to the present embodiment. The Akaike Information Criterion is a standard that indicates how well the observed data matches the statistical model in the case of regression analysis, etc., and is "-2 x (maximum log-likelihood of the statistical model) + 2 x (statistics). The model with the smallest value defined in "Number of free parameters of the model)" is judged to be the best. ROC_AUC is defined as the area under the curve of the receiver operating characteristic curve (ROC), which is a curve created by plotting (x, y) = (1-specificity, sensitivity) on two-dimensional coordinates, and is defined as ROC_AUC. The value of is 1 in the complete discrimination, and the closer this value is to 1, the higher the discrimination. Further, the predictability is an average of the discrimination rate, sensitivity, and specificity obtained by repeating the verification of the candidate formula. Robustness is a variance of discrimination rate, sensitivity, and specificity obtained by repeating verification of candidate formulas.
　式作成処理の説明に戻り、制御部は、所定の変数選択手法に基づいて候補式の変数を選択することで、候補式を作成する際に用いる指標状態情報に含まれる測定データの組み合わせを選択する（工程３）。なお、工程３において、変数の選択は、工程１で作成した各候補式に対して行ってもよい。これにより、候補式の変数を適切に選択することができる。そして、工程３で選択した測定データを含む指標状態情報を用いて再び工程１を実行する。また、工程３において、工程２での検証結果からステップワイズ法、ベストパス法、近傍探索法、遺伝的アルゴリズムのうち少なくとも１つに基づいて候補式の変数を選択してもよい。なお、ベストパス法とは、候補式に含まれる変数を１つずつ順次減らしていき、候補式が与える評価指標を最適化することで変数を選択する方法である。 Returning to the explanation of the formula creation process, the control unit selects the variable of the candidate formula based on the predetermined variable selection method, and selects the combination of the measurement data included in the index state information used when creating the candidate formula. (Step 3). In step 3, the variable may be selected for each candidate formula created in step 1. This makes it possible to appropriately select the variables of the candidate expression. Then, step 1 is executed again using the index state information including the measurement data selected in step 3. Further, in step 3, a variable of the candidate formula may be selected based on at least one of the stepwise method, the best path method, the neighborhood search method, and the genetic algorithm from the verification result in step 2. The best path method is a method of selecting variables by sequentially reducing the variables included in the candidate formula one by one and optimizing the evaluation index given by the candidate formula.
　式作成処理の説明に戻り、制御部は、上述した工程１、工程２および工程３を繰り返し実行し、これにより蓄積した検証結果に基づいて、複数の候補式の中から評価の際に用いる候補式を選出することで、評価の際に用いる式を作成する（工程４）。なお、候補式の選出には、例えば、同じ式作成手法で作成した候補式の中から最適なものを選出する場合と、すべての候補式の中から最適なものを選出する場合とがある。 Returning to the explanation of the formula creation process, the control unit repeatedly executes the above-mentioned steps 1, 2 and 3 and, based on the verification results accumulated by this, is a candidate to be used in the evaluation from among a plurality of candidate formulas. By selecting the formula, the formula used for the evaluation is created (step 4). In the selection of candidate formulas, for example, there are cases where the optimum one is selected from the candidate formulas created by the same formula creation method and cases where the optimum one is selected from all the candidate formulas.
　以上、説明したように、式作成処理では、指標状態情報に基づいて、候補式の作成、候補式の検証および候補式の変数の選択に関する処理を一連の流れで体系化（システム化）して実行することにより、Ａβの脳内への蓄積の評価に最適な式を作成することができる。換言すると、式作成処理では、前記少なくとも１つの物質の測定値を多変量の統計解析に用い、最適でロバストな変数の組を選択するために変数選択法とクロスバリデーションとを組み合わせて、評価性能の高い式を抽出する。 As described above, in the expression creation process, the processes related to the creation of the candidate expression, the verification of the candidate expression, and the selection of the variable of the candidate expression are systematized (systematized) in a series of flows based on the index state information. By performing this, an optimal formula can be created for assessing the accumulation of Aβ in the brain. In other words, in the formula creation process, the measured values of at least one substance are used for multivariate statistical analysis, and the variable selection method and cross-validation are combined to select the optimum and robust set of variables to evaluate the evaluation performance. Extract high equations.
［２－２．第２実施形態の構成］
　ここでは、第２実施形態にかかる評価システム（以下では本システムと記す場合がある。）の構成について、図３から図１４を参照して説明する。なお、本システムはあくまでも一例であり、本発明はこれに限定されない。特に、ここでは、Ａβの脳内への蓄積の状態を評価する際に、式の値またはその変換後の値を用いるケースを一例として記載しているが、例えば、「前記２４種類のアミノ酸および前記２６種類のアミノ酸関連代謝物」のうちの少なくとも１つの物質の測定値またはその変換後の値（例えば偏差値など）を用いてもよい。 [2-2. Configuration of the second embodiment]
Here, the configuration of the evaluation system according to the second embodiment (hereinafter, may be referred to as this system) will be described with reference to FIGS. 3 to 14. The present system is merely an example, and the present invention is not limited thereto. In particular, here, a case where the value of the formula or the value after conversion thereof is used when evaluating the state of accumulation of Aβ in the brain is described as an example. For example, "the above 24 kinds of amino acids and The measured value of at least one substance of the "26 kinds of amino acid-related metabolites" or the value after conversion thereof (for example, deviation value) may be used.
　まず、本システムの全体構成について図３および図４を参照して説明する。図３は本システムの全体構成の一例を示す図である。また、図４は本システムの全体構成の他の一例を示す図である。本システムは、図３に示すように、評価対象である個体についてＡβの脳内への蓄積の状態を評価する評価装置１００と、血液中の前記少なくとも１つの物質の測定値に関する個体の測定データを提供するクライアント装置２００（本発明の端末装置に相当）とを、ネットワーク３００を介して通信可能に接続して構成されている。 First, the overall configuration of this system will be described with reference to FIGS. 3 and 4. FIG. 3 is a diagram showing an example of the overall configuration of this system. Further, FIG. 4 is a diagram showing another example of the overall configuration of this system. As shown in FIG. 3, this system includes an evaluation device 100 that evaluates the state of accumulation of Aβ in the brain of an individual to be evaluated, and individual measurement data regarding the measured values of at least one substance in the blood. The client device 200 (corresponding to the terminal device of the present invention) is connected to the client device 200 (corresponding to the terminal device of the present invention) so as to be communicable via the network 300.
　なお、本システムにおいて、評価に用いられるデータの提供元となるクライアント装置２００と評価結果の提供先となるクライアント装置２００は別々のものであってもよい。本システムは、図４に示すように、評価装置１００やクライアント装置２００の他に、評価装置１００で式を作成する際に用いる指標状態情報や、評価の際に用いる式などを格納したデータベース装置４００を、ネットワーク３００を介して通信可能に接続して構成されてもよい。これにより、ネットワーク３００を介して、評価装置１００からクライアント装置２００やデータベース装置４００へ、あるいはクライアント装置２００やデータベース装置４００から評価装置１００へ、Ａβの脳内への蓄積の状態を知る上で参考となる情報などが提供される。ここで、Ａβの脳内への蓄積の状態を知る上で参考となる情報とは、例えば、ヒトを含む生物のＡβの脳内への蓄積の状態に関する特定の項目について測定した値に関する情報などである。また、Ａβの脳内への蓄積の状態を知る上で参考となる情報は、評価装置１００やクライアント装置２００や他の装置（例えば各種の計測装置等）で生成され、主にデータベース装置４００に蓄積される。 In this system, the client device 200 that provides the data used for the evaluation and the client device 200 that provides the evaluation result may be different. As shown in FIG. 4, this system is a database device that stores index state information used when creating an expression in the evaluation device 100, an expression used in the evaluation, and the like, in addition to the evaluation device 100 and the client device 200. The 400 may be connected and configured so as to be communicable via the network 300. This is a reference for knowing the state of accumulation of Aβ in the brain from the evaluation device 100 to the client device 200 or the database device 400, or from the client device 200 or the database device 400 to the evaluation device 100 via the network 300. Information and so on are provided. Here, the information that can be used as a reference for knowing the state of accumulation of Aβ in the brain includes, for example, information on values measured for a specific item related to the state of accumulation of Aβ in the brain of an organism including humans. Is. In addition, information that can be used as a reference for knowing the state of accumulation of Aβ in the brain is generated by the evaluation device 100, the client device 200, and other devices (for example, various measuring devices), and is mainly stored in the database device 400. Accumulate.
　つぎに、本システムの評価装置１００の構成について図５から図１１を参照して説明する。図５は、本システムの評価装置１００の構成の一例を示すブロック図であり、該構成のうち本発明に関係する部分のみを概念的に示している。 Next, the configuration of the evaluation device 100 of this system will be described with reference to FIGS. 5 to 11. FIG. 5 is a block diagram showing an example of the configuration of the evaluation device 100 of the present system, and conceptually shows only the portion of the configuration related to the present invention.
　評価装置１００は、当該評価装置を統括的に制御するＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）等の制御部１０２と、ルータ等の通信装置および専用線等の有線または無線の通信回線を介して当該評価装置をネットワーク３００に通信可能に接続する通信インターフェース部１０４と、各種のデータベースやテーブルやファイルなどを格納する記憶部１０６と、入力装置１１２や出力装置１１４に接続する入出力インターフェース部１０８と、で構成されており、これら各部は任意の通信路を介して通信可能に接続されている。ここで、評価装置１００は、各種の分析装置（例えばアミノ酸分析装置等）と同一筐体で構成されてもよい。例えば、血液中の前記少なくとも１つの物質の測定値を算出（測定）し、算出した値を出力（印刷やモニタ表示など）する構成（ハードウェアおよびソフトウェア）を備えた小型分析装置において、後述する評価部１０２ｄをさらに備え、当該評価部１０２ｄで得られた結果を前記構成を用いて出力すること、を特徴とするものでもよい。 The evaluation device 100 uses a control unit 102 such as a CPU (Central Processing Unit) that collectively controls the evaluation device, a communication device such as a router, and a wired or wireless communication line such as a dedicated line. It is composed of a communication interface unit 104 that is communicably connected to the network 300, a storage unit 106 that stores various databases, tables, files, and the like, and an input / output interface unit 108 that is connected to the input device 112 and the output device 114. These parts are connected so as to be able to communicate with each other via an arbitrary communication path. Here, the evaluation device 100 may be configured in the same housing as various analyzers (for example, an amino acid analyzer). For example, in a small analyzer equipped with a configuration (hardware and software) that calculates (measures) the measured value of the at least one substance in blood and outputs the calculated value (printing, monitor display, etc.), which will be described later. The evaluation unit 102d may be further provided, and the result obtained by the evaluation unit 102d may be output using the above configuration.
　通信インターフェース部１０４は、評価装置１００とネットワーク３００（またはルータ等の通信装置）との間における通信を媒介する。すなわち、通信インターフェース部１０４は、他の端末と通信回線を介してデータを通信する機能を有する。 The communication interface unit 104 mediates communication between the evaluation device 100 and the network 300 (or a communication device such as a router). That is, the communication interface unit 104 has a function of communicating data with another terminal via a communication line.
　入出力インターフェース部１０８は、入力装置１１２や出力装置１１４に接続する。ここで、出力装置１１４には、モニタ（家庭用テレビを含む）の他、スピーカやプリンタを用いることができる（なお、以下では、出力装置１１４をモニタ１１４として記載する場合がある。）。入力装置１１２には、キーボードやマウスやマイクの他、マウスと協働してポインティングデバイス機能を実現するモニタを用いることができる。 The input / output interface unit 108 is connected to the input device 112 and the output device 114. Here, as the output device 114, a speaker or a printer can be used in addition to a monitor (including a home television) (in the following, the output device 114 may be described as the monitor 114). In addition to the keyboard, mouse, and microphone, the input device 112 can use a monitor that realizes a pointing device function in cooperation with the mouse.
　記憶部１０６は、ストレージ手段であり、例えば、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）・ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）等のメモリ装置や、ハードディスクのような固定ディスク装置、フレキシブルディスク、光ディスク等を用いることができる。記憶部１０６には、ＯＳ（Ｏｐｅｒａｔｉｎｇ　Ｓｙｓｔｅｍ）と協働してＣＰＵに命令を与え各種処理を行うためのコンピュータプログラムが記録されている。記憶部１０６は、図示の如く、測定データファイル１０６ａと、指標状態情報ファイル１０６ｂと、指定指標状態情報ファイル１０６ｃと、式関連情報データベース１０６ｄと、評価結果ファイル１０６ｅと、を格納する。 The storage unit 106 is a storage means, and for example, a memory device such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used. A computer program for giving instructions to the CPU and performing various processes in cooperation with the OS (Operating System) is recorded in the storage unit 106. As shown in the figure, the storage unit 106 stores the measurement data file 106a, the index state information file 106b, the designated index state information file 106c, the formula-related information database 106d, and the evaluation result file 106e.
　測定データファイル１０６ａは、血液中の前記少なくとも１つの物質の測定値に関する測定データを格納する。図６は、測定データファイル１０６ａに格納される情報の一例を示す図である。測定データファイル１０６ａに格納される情報は、図６に示すように、評価対象である個体（サンプル）を一意に識別するための個体番号と、測定データとを相互に関連付けて構成されている。ここで、図６では、測定データを数値、すなわち連続尺度として扱っているが、測定データは名義尺度や順序尺度でもよい。なお、名義尺度や順序尺度の場合は、それぞれの状態に対して任意の数値を与えることで解析してもよい。また、測定データに、他の生体情報に関する値（上記参照）を組み合わせてもよい。 The measurement data file 106a stores measurement data relating to the measured values of the at least one substance in blood. FIG. 6 is a diagram showing an example of information stored in the measurement data file 106a. As shown in FIG. 6, the information stored in the measurement data file 106a is configured by correlating the individual number for uniquely identifying the individual (sample) to be evaluated and the measurement data. Here, in FIG. 6, the measurement data is treated as a numerical value, that is, a continuous scale, but the measurement data may be a nominal scale or an ordinal scale. In the case of a nominal scale or an ordinal scale, analysis may be performed by giving an arbitrary numerical value to each state. In addition, the measurement data may be combined with values related to other biological information (see above).
　図５に戻り、指標状態情報ファイル１０６ｂは、式を作成する際に用いる指標状態情報を格納する。図７は、指標状態情報ファイル１０６ｂに格納される情報の一例を示す図である。指標状態情報ファイル１０６ｂに格納される情報は、図７に示すように、個体番号と、Ａβの脳内への蓄積の状態を表す指標（指標Ｔ１、指標Ｔ２、指標Ｔ３・・・）に関する指標データ（Ｔ）と、測定データと、を相互に関連付けて構成されている。ここで、図７では、指標データおよび測定データを数値（すなわち連続尺度）として扱っているが、指標データおよび測定データは名義尺度や順序尺度でもよい。なお、名義尺度や順序尺度の場合は、それぞれの状態に対して任意の数値を与えることで解析してもよい。また、指標データは、Ａβの脳内への蓄積の状態のマーカーとなる既知の指標などであり、数値データを用いてもよい。 Returning to FIG. 5, the index state information file 106b stores the index state information used when creating the formula. FIG. 7 is a diagram showing an example of information stored in the index state information file 106b. As shown in FIG. 7, the information stored in the index state information file 106b is an index related to an individual number and an index (index T1, index T2, index T3 ...) Representing the state of accumulation of Aβ in the brain. The data (T) and the measurement data are associated with each other. Here, in FIG. 7, the index data and the measurement data are treated as numerical values (that is, continuous scales), but the index data and the measurement data may be a nominal scale or an ordinal scale. In the case of a nominal scale or an ordinal scale, analysis may be performed by giving an arbitrary numerical value to each state. Further, the index data is a known index or the like that serves as a marker of the state of accumulation of Aβ in the brain, and numerical data may be used.
　図５に戻り、指定指標状態情報ファイル１０６ｃは、後述する指定部１０２ｂで指定した指標状態情報を格納する。図８は、指定指標状態情報ファイル１０６ｃに格納される情報の一例を示す図である。指定指標状態情報ファイル１０６ｃに格納される情報は、図８に示すように、個体番号と、指定した指標データと、指定した測定データと、を相互に関連付けて構成されている。 Returning to FIG. 5, the designated index status information file 106c stores the index status information designated by the designated unit 102b described later. FIG. 8 is a diagram showing an example of information stored in the designated index state information file 106c. As shown in FIG. 8, the information stored in the designated index state information file 106c is configured by correlating the individual number, the designated index data, and the designated measurement data with each other.
　図５に戻り、式関連情報データベース１０６ｄは、後述する式作成部１０２ｃで作成した式を格納する式ファイル１０６ｄ１で構成される。式ファイル１０６ｄ１は、評価の際に用いる式を格納する。図９は、式ファイル１０６ｄ１に格納される情報の一例を示す図である。式ファイル１０６ｄ１に格納される情報は、図９に示すように、ランクと、式（図９では、Ｆｐ（Ｈｉｓ，・・・）やＦｐ（Ｈｉｓ，ＡＤＭＡ，ＧＡＢＡ）、Ｆｋ（Ｈｉｓ，ＡＤＭＡ，ＧＡＢＡ，・・・）など）と、各式作成手法に対応する閾値と、各式の検証結果（例えば各式の値）と、を相互に関連付けて構成されている。 Returning to FIG. 5, the formula-related information database 106d is composed of a formula file 106d1 that stores the formula created by the formula creation unit 102c described later. The expression file 106d1 stores the expression used at the time of evaluation. FIG. 9 is a diagram showing an example of information stored in the formula file 106d1. As shown in FIG. 9, the information stored in the expression file 106d1 includes the rank, the expression (in FIG. 9, Fp (His, ...), Fp (His, ADMA, GABA), Fk (His, ADMA,). GABA, ...), Etc.), the threshold value corresponding to each formula creation method, and the verification result of each formula (for example, the value of each formula) are associated with each other.
　図５に戻り、評価結果ファイル１０６ｅは、後述する評価部１０２ｄで得られた評価結果を格納する。図１０は、評価結果ファイル１０６ｅに格納される情報の一例を示す図である。評価結果ファイル１０６ｅに格納される情報は、評価対象である個体（サンプル）を一意に識別するための個体番号と、予め取得した個体の測定データと、Ａβの脳内への蓄積の状態に関する評価結果（例えば、後述する算出部１０２ｄ１で算出した式の値、後述する変換部１０２ｄ２で式の値を変換した後の値、後述する生成部１０２ｄ３で生成した位置情報、または、後述する分類部１０２ｄ４で得られた分類結果、など）と、を相互に関連付けて構成されている。 Returning to FIG. 5, the evaluation result file 106e stores the evaluation results obtained by the evaluation unit 102d, which will be described later. FIG. 10 is a diagram showing an example of information stored in the evaluation result file 106e. The information stored in the evaluation result file 106e includes an individual number for uniquely identifying an individual (sample) to be evaluated, measurement data of an individual acquired in advance, and an evaluation regarding the state of accumulation of Aβ in the brain. Results (for example, the value of the formula calculated by the calculation unit 102d1 described later, the value after the value of the formula is converted by the conversion unit 102d2 described later, the position information generated by the generation unit 102d3 described later, or the classification unit 102d4 described later. The classification results obtained in, etc.) and are associated with each other.
　図５に戻り、制御部１０２は、ＯＳ等の制御プログラム・各種の処理手順等を規定したプログラム・所要データなどを格納するための内部メモリを有し、これらのプログラムに基づいて種々の情報処理を実行する。制御部１０２は、図示の如く、大別して、取得部１０２ａと指定部１０２ｂと式作成部１０２ｃと評価部１０２ｄと結果出力部１０２ｅと送信部１０２ｆとを備えている。制御部１０２は、データベース装置４００から送信された指標状態情報やクライアント装置２００から送信された測定データに対して、欠損値のあるデータの除去・外れ値の多いデータの除去・欠損値のあるデータの多い変数の除去などのデータ処理も行う。 Returning to FIG. 5, the control unit 102 has an internal memory for storing a control program such as an OS, a program that defines various processing procedures, required data, and the like, and various information processing is performed based on these programs. To execute. As shown in the drawing, the control unit 102 is roughly divided into an acquisition unit 102a, a designation unit 102b, an expression creation unit 102c, an evaluation unit 102d, a result output unit 102e, and a transmission unit 102f. The control unit 102 removes data having missing values, removes data having many outliers, and data having missing values with respect to the index state information transmitted from the database device 400 and the measurement data transmitted from the client device 200. It also performs data processing such as removal of variables with many.
　取得部１０２ａは、情報（具体的には、測定データや指標状態情報、式など）を取得する。例えば、取得部１０２ａは、クライアント装置２００やデータベース装置４００から送信された情報（具体的には、測定データや指標状態情報、式など）を、ネットワーク３００を介して受信することで、情報の取得を行ってもよい。なお、取得部１０２ａは、評価結果の送信先のクライアント装置２００とは異なるクライアント装置２００から送信された評価に用いられるデータを受信してもよい。また、例えば、記録媒体に記録されている情報の読み出しを行うための機構（ハードウェアおよびソフトウェアを含む）を評価装置１００が備える場合、取得部１０２ａは、記録媒体に記録されている情報（具体的には、測定データや指標状態情報、式など）を当該機構を介して読み出すことで、情報の取得を行ってもよい。指定部１０２ｂは、式を作成するにあたり対象とする指標データおよび測定データを指定する。 The acquisition unit 102a acquires information (specifically, measurement data, index state information, formula, etc.). For example, the acquisition unit 102a acquires information by receiving information (specifically, measurement data, index state information, formula, etc.) transmitted from the client device 200 or the database device 400 via the network 300. May be done. The acquisition unit 102a may receive data used for evaluation transmitted from a client device 200 different from the client device 200 to which the evaluation result is transmitted. Further, for example, when the evaluation device 100 includes a mechanism (including hardware and software) for reading out the information recorded on the recording medium, the acquisition unit 102a may use the information (specifically, the information) recorded on the recording medium. Specifically, the information may be acquired by reading the measurement data, the index state information, the formula, etc.) through the mechanism. The designation unit 102b designates index data and measurement data to be targeted when creating the formula.
　式作成部１０２ｃは、取得部１０２ａで取得した指標状態情報や指定部１０２ｂで指定した指標状態情報に基づいて式を作成する。なお、式が予め記憶部１０６の所定の記憶領域に格納されている場合には、式作成部１０２ｃは、記憶部１０６から所望の式を選択することで、式を作成してもよい。また、式作成部１０２ｃは、式を予め格納した他のコンピュータ装置（例えばデータベース装置４００）から所望の式を選択しダウンロードすることで、式を作成してもよい。 The formula creation unit 102c creates a formula based on the index state information acquired by the acquisition unit 102a and the index state information designated by the designation unit 102b. When the formula is stored in a predetermined storage area of the storage unit 106 in advance, the formula creation unit 102c may create the formula by selecting a desired formula from the storage unit 106. Further, the formula creation unit 102c may create a formula by selecting and downloading a desired formula from another computer device (for example, database device 400) in which the formula is stored in advance.
　評価部１０２ｄは、事前に得られた式（例えば、式作成部１０２ｃで作成した式、または、取得部１０２ａで取得した式など）、および、取得部１０２ａで取得した個体の測定データに含まれる、前記少なくとも１つの物質の測定値を用いて、式の値を算出することで、個体についてＡβの脳内への蓄積の状態を評価する。なお、評価部１０２ｄは、前記少なくとも１つの物質の測定値または当該測定値の変換後の値（例えば偏差値など）を用いて、個体についてＡβの脳内への蓄積の状態を評価してもよい。 The evaluation unit 102d is included in the formula obtained in advance (for example, the formula created by the formula creation unit 102c or the formula acquired by the acquisition unit 102a) and the measurement data of the individual acquired by the acquisition unit 102a. , The state of accumulation of Aβ in the brain of an individual is evaluated by calculating the value of the formula using the measured values of at least one substance. The evaluation unit 102d may evaluate the state of accumulation of Aβ in the brain of an individual by using the measured value of at least one substance or the converted value (for example, deviation value) of the measured value. Good.
　ここで、評価部１０２ｄの構成について図１１を参照して説明する。図１１は、評価部１０２ｄの構成を示すブロック図であり、該構成のうち本発明に関係する部分のみを概念的に示している。評価部１０２ｄは、算出部１０２ｄ１と、変換部１０２ｄ２と、生成部１０２ｄ３と、分類部１０２ｄ４と、をさらに備えている。 Here, the configuration of the evaluation unit 102d will be described with reference to FIG. FIG. 11 is a block diagram showing the configuration of the evaluation unit 102d, and conceptually shows only the portion of the configuration related to the present invention. The evaluation unit 102d further includes a calculation unit 102d1, a conversion unit 102d2, a generation unit 102d3, and a classification unit 102d4.
　算出部１０２ｄ１は、前記少なくとも１つの物質の測定値、および、前記少なくとも１つの物質の測定値が代入される変数を少なくとも含む式を用いて、式の値を算出する。なお、評価部１０２ｄは、算出部１０２ｄ１で算出した式の値を評価結果として評価結果ファイル１０６ｅの所定の記憶領域に格納してもよい。 The calculation unit 102d1 calculates the value of the formula by using the formula including at least the measured value of the at least one substance and the variable to which the measured value of the at least one substance is substituted. The evaluation unit 102d may store the value of the formula calculated by the calculation unit 102d1 as an evaluation result in a predetermined storage area of the evaluation result file 106e.
　変換部１０２ｄ２は、算出部１０２ｄ１で算出した式の値を例えば上述した変換手法などで変換する。なお、評価部１０２ｄは、変換部１０２ｄ２で変換した後の値を評価結果として評価結果ファイル１０６ｅの所定の記憶領域に格納してもよい。また、変換部１０２ｄ２は、測定データに含まれる前記少なくとも１つの物質の測定値を、例えば上述した変換手法などで変換してもよい。 The conversion unit 102d2 converts the value of the formula calculated by the calculation unit 102d1 by, for example, the conversion method described above. The evaluation unit 102d may store the value after conversion by the conversion unit 102d2 as an evaluation result in a predetermined storage area of the evaluation result file 106e. Further, the conversion unit 102d2 may convert the measured value of the at least one substance included in the measurement data by, for example, the conversion method described above.
　生成部１０２ｄ３は、モニタ等の表示装置または紙等の物理媒体に視認可能に示される所定の物差し上における所定の目印の位置に関する位置情報を、算出部１０２ｄ１で算出した式の値または変換部１０２ｄ２で変換した後の値（測定値または当該測定値の変換後の値でもよい）を用いて生成する。なお、評価部１０２ｄは、生成部１０２ｄ３で生成した位置情報を評価結果として評価結果ファイル１０６ｅの所定の記憶領域に格納してもよい。 The generation unit 102d3 uses the value of the formula calculated by the calculation unit 102d1 or the conversion unit 102d2 to obtain position information regarding the position of a predetermined mark on a predetermined measuring rod that is visibly displayed on a display device such as a monitor or a physical medium such as paper. It is generated using the value after conversion in (may be the measured value or the converted value of the measured value). The evaluation unit 102d may store the position information generated by the generation unit 102d3 as an evaluation result in a predetermined storage area of the evaluation result file 106e.
　分類部１０２ｄ４は、算出部１０２ｄ１で算出した式の値または変換部１０２ｄ２で変換した後の値（測定値または当該測定値の変換後の値でもよい）を用いて、個体を、Ａβの脳内への蓄積の程度を少なくとも考慮して定義された複数の区分のうちのどれか１つに分類する。 The classification unit 102d4 uses the value of the formula calculated by the calculation unit 102d1 or the value converted by the conversion unit 102d2 (the measured value or the converted value of the measured value) to obtain an individual in the brain of Aβ. It is classified into one of a plurality of categories defined in consideration of at least the degree of accumulation in the brain.
　結果出力部１０２ｅは、制御部１０２の各処理部での処理結果（評価部１０２ｄで得られた評価結果を含む）等を出力装置１１４に出力する。 The result output unit 102e outputs the processing results (including the evaluation results obtained by the evaluation unit 102d) of each processing unit of the control unit 102 to the output device 114.
　送信部１０２ｆは、個体の測定データの送信元のクライアント装置２００に対して評価結果を送信したり、データベース装置４００に対して、評価装置１００で作成した式や評価結果を送信したりする。なお、送信部１０２ｆは、評価に用いられるデータの送信元のクライアント装置２００とは異なるクライアント装置２００に対して評価結果を送信してもよい。 The transmission unit 102f transmits the evaluation result to the client device 200 that is the source of the measurement data of the individual, and transmits the formula and the evaluation result created by the evaluation device 100 to the database device 400. The transmission unit 102f may transmit the evaluation result to a client device 200 different from the client device 200 that transmits the data used for the evaluation.
　つぎに、本システムのクライアント装置２００の構成について図１２を参照して説明する。図１２は、本システムのクライアント装置２００の構成の一例を示すブロック図であり、該構成のうち本発明に関係する部分のみを概念的に示している。 Next, the configuration of the client device 200 of this system will be described with reference to FIG. FIG. 12 is a block diagram showing an example of the configuration of the client device 200 of the present system, and conceptually shows only the portion of the configuration related to the present invention.
　クライアント装置２００は、制御部２１０とＲＯＭ２２０とＨＤ（Ｈａｒｄ　Ｄｉｓｋ）２３０とＲＡＭ２４０と入力装置２５０と出力装置２６０と入出力ＩＦ２７０と通信ＩＦ２８０とで構成されており、これら各部は任意の通信路を介して通信可能に接続されている。クライアント装置２００は、プリンタ・モニタ・イメージスキャナ等の周辺装置を必要に応じて接続した情報処理装置（例えば、既知のパーソナルコンピュータ・ワークステーション・家庭用ゲーム装置・インターネットＴＶ・ＰＨＳ（Ｐｅｒｓｏｎａｌ　Ｈａｎｄｙｐｈｏｎｅ　Ｓｙｓｔｅｍ）端末・携帯端末・移動体通信端末・ＰＤＡ（Ｐｅｒｓｏｎａｌ　Ｄｉｇｉｔａｌ　Ａｓｓｉｓｔａｎｔ）等の情報処理端末など）を基にしたものであってもよい。 The client device 200 is composed of a control unit 210, a ROM 220, an HD (Hard Disk) 230, a RAM 240, an input device 250, an output device 260, an input / output IF270, and a communication IF280, and each of these units is via an arbitrary communication path. Is connected so that it can communicate with each other. The client device 200 is an information processing device (for example, a known personal computer, workstation, home game device, Internet TV, PHS (Personal Handyphone System)) in which peripheral devices such as a printer, a monitor, and an image scanner are connected as needed. It may be based on a terminal, a mobile terminal, a mobile communication terminal, an information processing terminal such as a PDA (Personal Digital Assist), or the like).
　入力装置２５０はキーボードやマウスやマイク等である。なお、後述するモニタ２６１もマウスと協働してポインティングデバイス機能を実現する。出力装置２６０は、通信ＩＦ２８０を介して受信した情報を出力する出力手段であり、モニタ（家庭用テレビを含む）２６１およびプリンタ２６２を含む。この他、出力装置２６０にスピーカ等を設けてもよい。入出力ＩＦ２７０は入力装置２５０や出力装置２６０に接続する。 The input device 250 is a keyboard, mouse, microphone, or the like. The monitor 261 described later also realizes the pointing device function in cooperation with the mouse. The output device 260 is an output means for outputting information received via the communication IF 280, and includes a monitor (including a home television) 261 and a printer 262. In addition, the output device 260 may be provided with a speaker or the like. The input / output IF270 is connected to the input device 250 and the output device 260.
　通信ＩＦ２８０は、クライアント装置２００とネットワーク３００（またはルータ等の通信装置）とを通信可能に接続する。換言すると、クライアント装置２００は、モデムやＴＡ（Ｔｅｒｍｉｎａｌ　Ａｄａｐｔｅｒ）やルータなどの通信装置および電話回線を介して、または専用線を介してネットワーク３００に接続される。これにより、クライアント装置２００は、所定の通信規約に従って評価装置１００にアクセスすることができる。 The communication IF280 connects the client device 200 and the network 300 (or a communication device such as a router) in a communicable manner. In other words, the client device 200 is connected to the network 300 via a communication device such as a modem, a TA (Terminal Adapter), or a router, and a telephone line, or via a dedicated line. As a result, the client device 200 can access the evaluation device 100 according to a predetermined communication contract.
　制御部２１０は、受信部２１１および送信部２１２を備えている。受信部２１１は、通信ＩＦ２８０を介して、評価装置１００から送信された評価結果などの各種情報を受信する。送信部２１２は、通信ＩＦ２８０を介して、個体の測定データなどの各種情報を評価装置１００へ送信する。 The control unit 210 includes a receiving unit 211 and a transmitting unit 212. The receiving unit 211 receives various information such as the evaluation result transmitted from the evaluation device 100 via the communication IF280. The transmission unit 212 transmits various information such as individual measurement data to the evaluation device 100 via the communication IF 280.
　制御部２１０は、当該制御部で行う処理の全部または任意の一部を、ＣＰＵおよび当該ＣＰＵにて解釈して実行するプログラムで実現してもよい。ＲＯＭ２２０またはＨＤ２３０には、ＯＳと協働してＣＰＵに命令を与え、各種処理を行うためのコンピュータプログラムが記録されている。当該コンピュータプログラムは、ＲＡＭ２４０にロードされることで実行され、ＣＰＵと協働して制御部２１０を構成する。また、当該コンピュータプログラムは、クライアント装置２００と任意のネットワークを介して接続されるアプリケーションプログラムサーバに記録されてもよく、クライアント装置２００は、必要に応じてその全部または一部をダウンロードしてもよい。また、制御部２１０で行う処理の全部または任意の一部を、ワイヤードロジック等によるハードウェアで実現してもよい。 The control unit 210 may be realized by a CPU and a program that interprets and executes all or any part of the processing performed by the control unit by the CPU and the CPU. A computer program for giving instructions to the CPU in cooperation with the OS and performing various processes is recorded in the ROM 220 or HD 230. The computer program is executed by being loaded into the RAM 240, and constitutes the control unit 210 in cooperation with the CPU. Further, the computer program may be recorded in an application program server connected to the client device 200 via an arbitrary network, and the client device 200 may download all or a part thereof as needed. .. Further, all or any part of the processing performed by the control unit 210 may be realized by hardware such as wired logic.
　ここで、制御部２１０は、評価装置１００に備えられている評価部１０２ｄが有する機能と同様の機能を有する評価部２１０ａ（算出部２１０ａ１、変換部２１０ａ２、生成部２１０ａ３および分類部２１０ａ４を含む）を備えていてもよい。そして、制御部２１０に評価部２１０ａが備えられている場合には、評価部２１０ａは、評価装置１００から送信された評価結果に含まれている情報に応じて、変換部２１０ａ２で式の値（測定値でもよい）を変換したり、生成部２１０ａ３で式の値または変換後の値（測定値または当該測定値の変換後の値でもよい）に対応する位置情報を生成したり、分類部２１０ａ４で式の値または変換後の値（測定値または当該測定値の変換後の値でもよい）を用いて個体を複数の区分のうちのどれか１つに分類したりしてもよい。 Here, the control unit 210 has an evaluation unit 210a (including a calculation unit 210a1, a conversion unit 210a2, a generation unit 210a3, and a classification unit 210a4) having the same function as that of the evaluation unit 102d provided in the evaluation device 100. May be provided. Then, when the control unit 210 is provided with the evaluation unit 210a, the evaluation unit 210a uses the conversion unit 210a2 to obtain the value of the expression (in accordance with the information included in the evaluation result transmitted from the evaluation device 100). The measured value may be converted), the generation unit 210a3 may generate the position information corresponding to the value of the formula or the converted value (the measured value or the converted value of the measured value), or the classification unit 210a4. The individual may be classified into any one of a plurality of categories using the value of the formula or the converted value (the measured value or the converted value of the measured value).
　つぎに、本システムのネットワーク３００について図３、図４を参照して説明する。ネットワーク３００は、評価装置１００とクライアント装置２００とデータベース装置４００とを相互に通信可能に接続する機能を有し、例えばインターネットやイントラネットやＬＡＮ（Ｌｏｃａｌ　Ａｒｅａ　Ｎｅｔｗｏｒｋ）（有線／無線の双方を含む）等である。なお、ネットワーク３００は、ＶＡＮ（Ｖａｌｕｅ－Ａｄｄｅｄ　Ｎｅｔｗｏｒｋ）や、パソコン通信網や、公衆電話網（アナログ／デジタルの双方を含む）や、専用回線網（アナログ／デジタルの双方を含む）や、ＣＡＴＶ（Ｃｏｍｍｕｎｉｔｙ　Ａｎｔｅｎｎａ　ＴｅｌｅＶｉｓｉｏｎ）網や、携帯回線交換網または携帯パケット交換網（ＩＭＴ（Ｉｎｔｅｒｎａｔｉｏｎａｌ　Ｍｏｂｉｌｅ　Ｔｅｌｅｃｏｍｍｕｎｉｃａｔｉｏｎ）２０００方式、ＧＳＭ（登録商標）（Ｇｌｏｂａｌ　Ｓｙｓｔｅｍ　ｆｏｒ　Ｍｏｂｉｌｅ　Ｃｏｍｍｕｎｉｃａｔｉｏｎｓ）方式またはＰＤＣ（Ｐｅｒｓｏｎａｌ　Ｄｉｇｉｔａｌ　Ｃｅｌｌｕｌａｒ）／ＰＤＣ－Ｐ方式等を含む）や、無線呼出網や、Ｂｌｕｅｔｏｏｔｈ（登録商標）等の局所無線網や、ＰＨＳ網や、衛星通信網（ＣＳ（Ｃｏｍｍｕｎｉｃａｔｉｏｎ　Ｓａｔｅｌｌｉｔｅ）、ＢＳ（Ｂｒｏａｄｃａｓｔｉｎｇ　Ｓａｔｅｌｌｉｔｅ）またはＩＳＤＢ（Ｉｎｔｅｇｒａｔｅｄ　Ｓｅｒｖｉｃｅｓ　Ｄｉｇｉｔａｌ　Ｂｒｏａｄｃａｓｔｉｎｇ）等を含む）等でもよい。 Next, the network 300 of this system will be described with reference to FIGS. 3 and 4. The network 300 has a function of connecting the evaluation device 100, the client device 200, and the database device 400 so as to be able to communicate with each other. For example, the Internet, an intranet, a LAN (Local Area Network) (including both wired and wireless) and the like. Is. The network 300 includes VAN (Value-Added Network), personal computer communication network, public switched telephone network (including both analog / digital), dedicated line network (including both analog / digital), and CATV (). Community Antenna TeleVision) network, mobile line exchange network or mobile packet exchange network (IMT (International Mobile Telecommunication) 2000 system, GSM (registered trademark) (Global System for Mobile Communications) system or PDCar (PDC) PDCul-Pill (Including methods, etc.), wireless calling networks, local wireless networks such as Bluetooth (registered trademark), PHS networks, satellite communication networks (CS (Communication Satellite), BS (Roadcasting Satellite), or ISDB (Integrated Services Digital Broadcast). ) Etc.) and the like.
　つぎに、本システムのデータベース装置４００の構成について図１３を参照して説明する。図１３は、本システムのデータベース装置４００の構成の一例を示すブロック図であり、該構成のうち本発明に関係する部分のみを概念的に示している。 Next, the configuration of the database device 400 of this system will be described with reference to FIG. FIG. 13 is a block diagram showing an example of the configuration of the database device 400 of the present system, and conceptually shows only the portion of the configuration related to the present invention.
　データベース装置４００は、評価装置１００または当該データベース装置で式を作成する際に用いる指標状態情報や、評価装置１００で作成した式、評価装置１００での評価結果などを格納する機能を有する。図１３に示すように、データベース装置４００は、当該データベース装置を統括的に制御するＣＰＵ等の制御部４０２と、ルータ等の通信装置および専用線等の有線または無線の通信回路を介して当該データベース装置をネットワーク３００に通信可能に接続する通信インターフェース部４０４と、各種のデータベースやテーブルやファイル（例えばＷｅｂページ用ファイル）などを格納する記憶部４０６と、入力装置４１２や出力装置４１４に接続する入出力インターフェース部４０８と、で構成されており、これら各部は任意の通信路を介して通信可能に接続されている。 The database device 400 has a function of storing index state information used when creating a formula in the evaluation device 100 or the database device, a formula created in the evaluation device 100, an evaluation result in the evaluation device 100, and the like. As shown in FIG. 13, the database device 400 uses a control unit 402 such as a CPU that collectively controls the database device, a communication device such as a router, and a wired or wireless communication circuit such as a dedicated line. A communication interface unit 404 that connects the device to the network 300 so that it can communicate, a storage unit 406 that stores various databases, tables, files (for example, files for Web pages), and an input / output device 412 and an output device 414 that are connected to each other. It is composed of an output interface unit 408, and each of these units is connected so as to be communicable via an arbitrary communication path.
　記憶部４０６は、ストレージ手段であり、例えば、ＲＡＭ・ＲＯＭ等のメモリ装置や、ハードディスクのような固定ディスク装置や、フレキシブルディスクや、光ディスク等を用いることができる。記憶部４０６には、各種処理に用いる各種プログラム等を格納する。通信インターフェース部４０４は、データベース装置４００とネットワーク３００（またはルータ等の通信装置）との間における通信を媒介する。すなわち、通信インターフェース部４０４は、他の端末と通信回線を介してデータを通信する機能を有する。入出力インターフェース部４０８は、入力装置４１２や出力装置４１４に接続する。ここで、出力装置４１４には、モニタ（家庭用テレビを含む）の他、スピーカやプリンタを用いることができる。また、入力装置４１２には、キーボードやマウスやマイクの他、マウスと協働してポインティングデバイス機能を実現するモニタを用いることができる。 The storage unit 406 is a storage means, and for example, a memory device such as a RAM / ROM, a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used. The storage unit 406 stores various programs and the like used for various processes. The communication interface unit 404 mediates communication between the database device 400 and the network 300 (or a communication device such as a router). That is, the communication interface unit 404 has a function of communicating data with another terminal via a communication line. The input / output interface unit 408 is connected to the input device 412 and the output device 414. Here, as the output device 414, a speaker or a printer can be used in addition to a monitor (including a home television). Further, as the input device 412, in addition to a keyboard, a mouse, and a microphone, a monitor that realizes a pointing device function in cooperation with the mouse can be used.
　制御部４０２は、ＯＳ等の制御プログラム・各種の処理手順等を規定したプログラム・所要データなどを格納するための内部メモリを有し、これらのプログラムに基づいて種々の情報処理を実行する。制御部４０２は、図示の如く、大別して、送信部４０２ａと受信部４０２ｂを備えている。送信部４０２ａは、指標状態情報や式などの各種情報を、評価装置１００へ送信する。受信部４０２ｂは、評価装置１００から送信された、式や評価結果などの各種情報を受信する。 The control unit 402 has an internal memory for storing a control program such as an OS, a program that defines various processing procedures, and required data, and executes various information processing based on these programs. As shown in the drawing, the control unit 402 is roughly classified into a transmission unit 402a and a reception unit 402b. The transmission unit 402a transmits various information such as index state information and formulas to the evaluation device 100. The receiving unit 402b receives various information such as an expression and an evaluation result transmitted from the evaluation device 100.
　なお、本説明では、評価装置１００が、測定データの取得から、式の値の算出、個体の区分への分類、そして評価結果の送信までを実行し、クライアント装置２００が評価結果の受信を実行するケースを例として挙げたが、クライアント装置２００に評価部２１０ａが備えられている場合は、評価装置１００は式の値の算出を実行すれば十分であり、例えば式の値の変換、位置情報の生成、および、個体の区分への分類などは、評価装置１００とクライアント装置２００とで適宜分担して実行してもよい。
　例えば、クライアント装置２００は、評価装置１００から式の値を受信した場合には、評価部２１０ａは、変換部２１０ａ２で式の値を変換したり、生成部２１０ａ３で式の値または変換後の値に対応する位置情報を生成したり、分類部２１０ａ４で式の値または変換後の値を用いて個体を複数の区分のうちのどれか１つに分類したりしてもよい。
　また、クライアント装置２００は、評価装置１００から変換後の値を受信した場合には、評価部２１０ａは、生成部２１０ａ３で変換後の値に対応する位置情報を生成したり、分類部２１０ａ４で変換後の値を用いて個体を複数の区分のうちのどれか１つに分類したりしてもよい。
　また、クライアント装置２００は、評価装置１００から式の値または変換後の値と位置情報とを受信した場合には、評価部２１０ａは、分類部２１０ａ４で式の値または変換後の値を用いて個体を複数の区分のうちのどれか１つに分類してもよい。 In this description, the evaluation device 100 executes the acquisition of measurement data, the calculation of the value of the formula, the classification into individual categories, and the transmission of the evaluation result, and the client device 200 receives the evaluation result. However, when the client device 200 is provided with the evaluation unit 210a, it is sufficient for the evaluation device 100 to calculate the value of the expression. For example, the conversion of the value of the expression and the position information The evaluation device 100 and the client device 200 may appropriately share and execute the generation of the data and the classification of the individual into categories.
For example, when the client device 200 receives the value of the expression from the evaluation device 100, the evaluation unit 210a converts the value of the expression by the conversion unit 210a2, or the value of the expression or the value after conversion by the generation unit 210a3. The position information corresponding to the above may be generated, or the individual may be classified into any one of a plurality of categories by using the value of the formula or the value after conversion in the classification unit 210a4.
Further, when the client device 200 receives the converted value from the evaluation device 100, the evaluation unit 210a generates position information corresponding to the converted value by the generation unit 210a3, or the classification unit 210a4 converts the value. The later values may be used to classify the individual into any one of a plurality of categories.
Further, when the client device 200 receives the value of the formula or the converted value and the position information from the evaluation device 100, the evaluation unit 210a uses the value of the formula or the converted value in the classification unit 210a4. Individuals may be classified into any one of a plurality of categories.
［２－３．他の実施形態］
　本発明にかかる評価装置、算出装置、評価方法、算出方法、評価プログラム、算出プログラム、記録媒体、評価システムおよび端末装置は、上述した第２実施形態以外にも、請求の範囲に記載した技術的思想の範囲内において種々の異なる実施形態にて実施されてよいものである。 [2-3. Other embodiments]
The evaluation device, calculation device, evaluation method, calculation method, evaluation program, calculation program, recording medium, evaluation system, and terminal device according to the present invention are technically described in the scope of the claim in addition to the above-described second embodiment. It may be implemented in various different embodiments within the scope of the idea.
　また、第２実施形態において説明した各処理のうち、自動的に行われるものとして説明した処理の全部または一部を手動的に行うこともでき、あるいは、手動的に行われるものとして説明した処理の全部または一部を公知の方法で自動的に行うこともできる。 Further, among the processes described in the second embodiment, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed. It is also possible to automatically perform all or part of the above by a known method.
　このほか、上記文献中や図面中で示した処理手順、制御手順、具体的名称、各処理の登録データや検索条件等のパラメータを含む情報、画面例、データベース構成については、特記する場合を除いて任意に変更することができる。 In addition, the processing procedure, control procedure, specific name, information including parameters such as registration data and search conditions of each processing, screen examples, and database configuration shown in the above documents and drawings are not specified unless otherwise specified. Can be changed arbitrarily.
　また、評価装置１００に関して、図示の各構成要素は機能概念的なものであり、必ずしも物理的に図示の如く構成されていることを要しない。 Further, with respect to the evaluation device 100, each component shown in the figure is a functional concept and does not necessarily have to be physically configured as shown in the figure.
　例えば、評価装置１００が備える処理機能、特に制御部１０２にて行われる各処理機能については、その全部または任意の一部を、ＣＰＵおよび当該ＣＰＵにて解釈実行されるプログラムにて実現してもよく、また、ワイヤードロジックによるハードウェアとして実現してもよい。尚、プログラムは、情報処理装置に本発明にかかる評価方法または算出方法を実行させるためのプログラム化された命令を含む一時的でないコンピュータ読み取り可能な記録媒体に記録されており、必要に応じて評価装置１００に機械的に読み取られる。すなわち、ＲＯＭまたはＨＤＤ（Ｈａｒｄ　Ｄｉｓｋ　Ｄｒｉｖｅ）などの記憶部１０６などには、ＯＳと協働してＣＰＵに命令を与え、各種処理を行うためのコンピュータプログラムが記録されている。このコンピュータプログラムは、ＲＡＭにロードされることによって実行され、ＣＰＵと協働して制御部を構成する。 For example, with respect to the processing functions included in the evaluation device 100, particularly each processing function performed by the control unit 102, even if all or any part thereof is realized by the CPU and a program interpreted and executed by the CPU. It may be realized as hardware by wired logic. The program is recorded on a non-temporary computer-readable recording medium containing a programmed instruction for causing the information processing apparatus to execute the evaluation method or calculation method according to the present invention, and is evaluated as necessary. It is read mechanically by the device 100. That is, a computer program for giving instructions to the CPU in cooperation with the OS and performing various processes is recorded in a storage unit 106 or the like such as a ROM or an HDD (Hard Disk Drive). This computer program is executed by being loaded into RAM, and cooperates with a CPU to form a control unit.
　また、このコンピュータプログラムは評価装置１００に対して任意のネットワークを介して接続されたアプリケーションプログラムサーバに記憶されていてもよく、必要に応じてその全部または一部をダウンロードすることも可能である。 Further, this computer program may be stored in the application program server connected to the evaluation device 100 via an arbitrary network, and all or a part thereof can be downloaded as needed.
　また、本発明にかかる評価プログラムまたは算出プログラムを、一時的でないコンピュータ読み取り可能な記録媒体に格納してもよく、また、プログラム製品として構成することもできる。ここで、この「記録媒体」とは、メモリーカード、ＵＳＢ（Ｕｎｉｖｅｒｓａｌ　Ｓｅｒｉａｌ　Ｂｕｓ）メモリ、ＳＤ（Ｓｅｃｕｒｅ　Ｄｉｇｉｔａｌ）カード、フレキシブルディスク、光磁気ディスク、ＲＯＭ、ＥＰＲＯＭ（Ｅｒａｓａｂｌｅ　Ｐｒｏｇｒａｍｍａｂｌｅ　Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、ＥＥＰＲＯＭ（Ｅｌｅｃｔｒｉｃａｌｌｙ　Ｅｒａｓａｂｌｅ　ａｎｄ　Ｐｒｏｇｒａｍｍａｂｌｅ　Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）（登録商標）、ＣＤ－ＲＯＭ（Ｃｏｍｐａｃｔ　Ｄｉｓｃ　Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、ＭＯ（Ｍａｇｎｅｔｏ－Ｏｐｔｉｃａｌ　ｄｉｓｋ）、ＤＶＤ（Ｄｉｇｉｔａｌ　Ｖｅｒｓａｔｉｌｅ　Ｄｉｓｋ）、および、Ｂｌｕ－ｒａｙ（登録商標）　Ｄｉｓｃ等の任意の「可搬用の物理媒体」を含むものとする。 Further, the evaluation program or calculation program according to the present invention may be stored in a non-temporary computer-readable recording medium, or may be configured as a program product. Here, the "recording medium" includes a memory card, a USB (Universal Serial Bus) memory, an SD (Secure Digital) card, a flexible disk, a magneto-optical disk, a ROM, an EPROM (Erasable Programmable Read Only Memory), and an EEPROM (EEEPROM). Erasable and EEPROM Read Only Memory (registered trademark), CD-ROM (Compact Disc Read Only Memory), MO (Magnet-Optical Disk), MO (Magnet-Optical Disk), DVD (Digital Digital), DVD (Digital Digital), DVD (Digital) It shall include any "portable physical medium".
　また、「プログラム」とは、任意の言語または記述方法にて記述されたデータ処理方法であり、ソースコードまたはバイナリコード等の形式を問わない。なお、「プログラム」は必ずしも単一的に構成されるものに限られず、複数のモジュールやライブラリとして分散構成されるものや、ＯＳに代表される別個のプログラムと協働してその機能を達成するものをも含む。なお、実施形態に示した各装置において記録媒体を読み取るための具体的な構成および読み取り手順ならびに読み取り後のインストール手順等については、周知の構成や手順を用いることができる。 A "program" is a data processing method described in any language or description method, regardless of the format such as source code or binary code. The "program" is not necessarily limited to a single program, but is distributed as a plurality of modules or libraries, or cooperates with a separate program represented by the OS to achieve its function. Including things. It should be noted that well-known configurations and procedures can be used for the specific configuration and reading procedure for reading the recording medium in each device shown in the embodiment, the installation procedure after reading, and the like.
　記憶部１０６に格納される各種のデータベース等は、ＲＡＭ、ＲＯＭ等のメモリ装置、ハードディスク等の固定ディスク装置、フレキシブルディスク、および、光ディスク等のストレージ手段であり、各種処理やウェブサイト提供に用いる各種のプログラム、テーブル、データベース、および、ウェブページ用ファイル等を格納する。 Various databases and the like stored in the storage unit 106 are memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and storage means such as optical disks, and are used for various processes and website provision. Stores programs, tables, databases, files for web pages, etc.
　また、評価装置１００は、既知のパーソナルコンピュータまたはワークステーション等の情報処理装置として構成してもよく、また、任意の周辺装置が接続された当該情報処理装置として構成してもよい。また、評価装置１００は、当該情報処理装置に本発明の評価方法または算出方法を実現させるソフトウェア（プログラムまたはデータ等を含む）を実装することにより実現してもよい。 Further, the evaluation device 100 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as the information processing device to which an arbitrary peripheral device is connected. Further, the evaluation device 100 may be realized by mounting software (including a program or data) that realizes the evaluation method or calculation method of the present invention on the information processing device.
　更に、装置の分散・統合の具体的形態は図示するものに限られず、その全部または一部を、各種の付加等に応じてまたは機能負荷に応じて、任意の単位で機能的または物理的に分散・統合して構成することができる。すなわち、上述した実施形態を任意に組み合わせて実施してもよく、実施形態を選択的に実施してもよい。 Furthermore, the specific form of dispersion / integration of the device is not limited to that shown in the figure, and all or part of the device is functionally or physically in any unit according to various additions or functional loads. It can be distributed and integrated. That is, the above-described embodiments may be arbitrarily combined and implemented, or the embodiments may be selectively implemented.
　軽度認知障害（ＭＣＩ）または初期のアルツハイマー病（Ｍｉｌｄ　Ａｌｚｈｅｉｍｅｒ’ｓ　ｄｉｓｅａｓｅ）の臨床診断が行われた患者のうち、アミロイドＰＥＴイメージングによってＡβ陽性と診断された患者（Ａβ陽性群：３０名）およびＡβ陰性と診断された患者（Ａβ陰性群：３０名）の血漿サンプルから、前述の分析法（Ａ）により血中代謝物濃度を測定した。 Among patients who have been clinically diagnosed with mild cognitive impairment (MCI) or early Alzheimer's disease, patients diagnosed as Aβ-positive by amyloid PET imaging (Aβ-positive group: 30) and Aβ Blood metabolite concentrations were measured from plasma samples of patients diagnosed as negative (Aβ-negative group: 30 persons) by the above-mentioned analysis method (A).
　以下に列挙したデータを用いて、Ａβ陽性群とＡβ陰性群の判別能を評価した。
・２３種類のアミノ酸（Ａｌａ，Ａｒｇ，Ａｓｎ，Ｃｉｔ，Ｃｙｓ２，ＥｔＯＨＮＨ２，Ｇｌｎ，Ｇｌｕ，Ｇｌｙ，Ｈｉｓ，Ｉｌｅ，Ｌｅｕ，Ｌｙｓ，Ｍｅｔ，Ｏｒｎ，Ｐｈｅ，Ｐｒｏ，Ｓｅｒ，Ｔａｕ，Ｔｈｒ，Ｔｒｐ，Ｔｙｒ，Ｖａｌ）の血漿中濃度値（ｎｍｏｌ／ｍｌ）
・２５種類のアミノ酸関連代謝物（１－ＭｅＨｉｓ，３－ｈＫｙｎ，３－ＭｅＨｉｓ，ａＡＢＡ，ａＡｉＢＡ，ＡＤＭＡ，Ａｌｌｙｌ－Ｃｙｓ，ａＡＡＡ，ｂＡｉＢＡ，ＧＡＢＡ，ｈＡｒｇ，ｈＣｉｔ，Ｈｙｐｏｔａｕｒｉｎｅ，ＨｙＰｒｏ，Ｋｙｎ，Ｃｙｓｔａｔｈｉｏｎｉｎｅ，ＭｅＣｙｓ，Ｎ６－ＡｃＬｙｓ，Ｎ８－ＡｃＳｐｄ，ＰＥＡ，Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ，Ｐｕｔ，Ｓａｒ，ＳＤＭＡ，Ｓｐｄ）の血漿中濃度値（ｎｍｏｌ／ｍｌ）
・１種類のアミノ酸関連代謝物（Ｔｈｉｏｐｒｏｌｉｎｅ）のピーク面積値
・２種類の代謝物比（Ｋｙｎ／Ｔｒｐ，Ｋｙｎ／ＢＣＡＡ） The data listed below were used to evaluate the ability to discriminate between the Aβ-positive group and the Aβ-negative group.
・ 23 kinds of amino acids (Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, Val) plasma concentration value (nmol / ml)
-25 kinds of amino acid-related biotransformers (1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cystathionine, Cystathionine , N6-AcLys, N8-AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd) plasma concentration values (nmol / ml)
-Peak area value of one type of amino acid-related metabolite (Thioproline) -Ratio of two types of metabolites (Kyn / Trp, Kyn / BCAA)
　表１に、前記２３種のアミノ酸および前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値ならびに前記２種類の代謝物比を用いたロジスティック回帰の結果を示した。ＲＯＣ＿ＡＵＣが０．６以上であったアミノ酸およびアミノ酸関連代謝物は、ＭｅＣｙｓ、Ｓｅｒ、Ｏｒｎ、ＡＤＭＡ、ＥｔＯＨＮＨ２、Ｃｙｓ２、Ｇｌｙ、ＨｙＰｒｏおよびＡｌｌｙｌ－Ｃｙｓであった。ＭｅＣｙｓ、Ｓｅｒ、Ｏｒｎ、ＡＤＭＡ、Ｃｙｓ２、ＧｌｙおよびＨｙＰｒｏはＡβ陽性群で減少し、ＥｔＯＨＮＨ２およびＡｌｌｙｌ－ＣｙｓはＡβ陽性群で増加した。これらの代謝物の濃度値は、Ａβ沈着の評価において有用なものであると考えられる。 Table 1 shows logistic regression using the plasma concentration values of the 23 amino acids and the 25 amino acid-related metabolites, the peak area value of the one amino acid-related metabolite, and the ratio of the two metabolites. The results are shown. The amino acids and amino acid-related metabolites having a ROC_AUC of 0.6 or higher were MeCys, Ser, Orn, ADMA, EtOHNH2, Cys2, Gly, HyPro and Allyl-Cys. MeCys, Ser, Orn, ADMA, Cys2, Gly and HyPro decreased in the Aβ-positive group, and EtOHNH2 and Allyl-Cys increased in the Aβ-positive group. Concentrations of these metabolites are believed to be useful in assessing Aβ deposition.
Figure JPOXMLDOC01-appb-T000001
Figure JPOXMLDOC01-appb-T000001
　実施例１で得られたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data obtained in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める２個の変数の組み合わせを、実施例１に記載した、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値および前記２種類の代謝物比から探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。 A logistic regression equation was used as the multivariate discriminant. The combination of the two variables included in the logistic regression equation is described in Example 1, the plasma concentration values of the 23 types of amino acids, the plasma concentration values of the 25 types of amino acid-related biotransforms, and the one type of amino acid. A logistic regression equation was searched for with good discrimination between the Aβ-positive group and the Aβ-negative group by searching from the peak area value of the related biotransforms and the ratio of the two types of biotransforms.
　Ａβ陽性群とＡβ陰性群のＲＯＣ＿ＡＵＣ値が０．６８４以上で、変数の個数が２個のロジスティック回帰式の一覧を、以下の［１．２変数の式］に示した。これらのロジスティック回帰式は、ＲＯＣ＿ＡＵＣ値が高いことから、前記の評価において有用なものであると考えられる。なお、以下の［１．２変数の式］には、各式に関して、式に含まれる変数とＲＯＣ＿ＡＵＣ値が示されている（以下同様）。 A list of logistic regression equations in which the ROC_AUC value of the Aβ-positive group and the Aβ-negative group is 0.684 or more and the number of variables is two is shown in the following [1.2 variable equation]. Since these logistic regression equations have a high ROC_AUC value, they are considered to be useful in the above evaluation. In the following [1.2 Variable Expression], the variables included in the expression and the ROC_AUC value are shown for each expression (the same applies hereinafter).
　実施例１で用いたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data used in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める３個の変数の組み合わせを、実施例２と同様に、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値および前記２種類の代謝物比から探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。更に、前記２３種類のアミノ酸の血漿中濃度値および前記２５種類のアミノ酸関連代謝物の血漿中濃度値から探索した２種類と年齢を変数とした場合に判別能が良好なロジスティック回帰式の探索を実施した。 A logistic regression equation was used as the multivariate discriminant. The combination of the three variables included in the logistic regression equation is the same as in Example 2, the plasma concentration value of the 23 types of amino acids, the plasma concentration value of the 25 types of amino acid-related biotransforms, and the one type of amino acid. A logistic regression equation with good discrimination between the Aβ-positive group and the Aβ-negative group was searched by searching from the peak area value of the related biotransforms and the ratio of the two types of biotransforms. Furthermore, a logistic regression equation with good discriminative ability is searched for when the two types searched from the plasma concentration values of the 23 types of amino acids and the plasma concentration values of the 25 types of amino acid-related metabolites and the age are used as variables. Carried out.
　Ａβ陽性群とＡβ陰性群のＲＯＣ＿ＡＵＣ値が０．６８４以上で、変数の個数が３個のロジスティック回帰式の一覧を、以下の［２．３変数の式］に示した。また、アミノ酸及びアミノ酸関連代謝物２種類と年齢を変数とした場合に、ＲＯＣ＿ＡＵＣ値が高い上位２００式を選び、２００番目と同じＲＯＣ＿ＡＵＣ値０．７６８を有する式まで含め２０１式を以下の[２－１. ２変数と年齢（Age）を組み合わせた式]に示した。これらのロジスティック回帰式は、ＲＯＣ＿ＡＵＣ値が高いことから、前記の評価において有用なものであると考えられる。 A list of logistic regression equations in which the ROC_AUC value of the Aβ-positive group and the Aβ-negative group is 0.684 or more and the number of variables is 3 is shown in the following [2.3 variable equation]. In addition, when two types of amino acids and amino acid-related metabolites and age are used as variables, the top 200 formulas having the highest ROC_AUC value are selected, and the 201 formulas including the formula having the same ROC_AUC value of 0.768 as the 200th formula are included in the following [2]. -1. Formula combining 2 variables and age (Age)]. Since these logistic regression equations have a high ROC_AUC value, they are considered to be useful in the above evaluation.
　実施例１で用いたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data used in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める４個の変数の組み合わせ（年齢の変数を必須とする）を、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値、前記２種類の代謝物比および年齢から探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。 A logistic regression equation was used as the multivariate discriminant. The combination of the four variables included in the logistic regression equation (requiring the age variable) is the plasma concentration value of the 23 types of amino acids, the plasma concentration value of the 25 types of amino acid-related biotransforms, and the above-mentioned one type. A logistic regression equation was searched for with good discrimination between the Aβ-positive group and the Aβ-negative group by searching from the peak area value of amino acid-related biotransforms, the ratio of the two types of biotransforms, and the age.
　得られたロジスティック回帰式（計２０，８２５（＝５１Ｃ３）個）のうち、年齢を変数に組み込むことでＲＯＣ＿ＡＵＣ値が上昇した式（計２０，８２５個）の中から、年齢変数有りの上位２０式を表２に示した。年齢の変数を加えることで全てのロジスティック回帰式のＲＯＣ＿ＡＵＣ値が改善されたことから、年齢を変数に加えたロジスティック回帰式は前記の評価において有用なものであると考えられる。 Among the obtained logistic regression equations (20,825 (= 51 C 3 ) in total), the ROC_AUC value increased by incorporating age into the variable (20,825 in total), and there was an age variable. The top 20 equations are shown in Table 2. Since the ROC_AUC value of all logistic regression equations was improved by adding the age variable, it is considered that the logistic regression equation with age added to the variable is useful in the above evaluation.
Figure JPOXMLDOC01-appb-T000002
Figure JPOXMLDOC01-appb-T000002
　実施例１で用いたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data used in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める４個の変数の組み合わせ（性別の変数を必須とする）を、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値、前記２種類の代謝物比および性別から探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。 A logistic regression equation was used as the multivariate discriminant. The combination of four variables to be included in the logistic regression equation (gender variables are required) is the plasma concentration value of the 23 types of amino acids, the plasma concentration value of the 25 types of amino acid-related biotransforms, and the above-mentioned one type. We searched from the peak area value of amino acid-related biotransforms, the ratio of the two types of biotransforms, and sex, and searched for a logistic regression equation with good discrimination between Aβ-positive group and Aβ-negative group.
　得られたロジスティック回帰式（計２０，８２５（＝５１Ｃ３）個）のうち、性別を変数に組み込むことでＲＯＣ＿ＡＵＣ値が上昇した式（計１１，３９８個）の中から、性別変数有りの上位２０式を表３に示した。性別の変数を加えることで約半数以上（５４．７％）のロジスティック回帰式のＲＯＣ＿ＡＵＣ値が改善されたことから、性別を変数に加えたロジッティック回帰式は前記の評価において有用なものであると考えられる。 Of the obtained logistic regression equations (20,825 (= 51 C 3 ) in total), among the equations in which the ROC_AUC value increased by incorporating gender into variables (11,398 in total), there was a gender variable. The top 20 equations are shown in Table 3. Since the ROC_AUC value of the logistic regression equation of about half (54.7%) was improved by adding the gender variable, the logistic regression equation with the gender added to the variable is useful in the above evaluation. it is conceivable that.
Figure JPOXMLDOC01-appb-T000003
Figure JPOXMLDOC01-appb-T000003
　実施例１で用いたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data used in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める４個の変数の組み合わせ（ＢＭＩ（Ｂｏｄｙ　Ｍａｓｓ　Ｉｎｄｅｘ）の変数を必須とする）を、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値、前記２種類の代謝物比およびＢＭＩから探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。 A logistic regression equation was used as the multivariate discriminant. The combination of four variables included in the logistic regression equation (BMI (Body Mass Index) variable is required) is the plasma concentration value of the 23 types of amino acids and the plasma concentration of the 25 types of amino acid-related metabolites. A logistic regression equation was searched for with good discrimination between the Aβ-positive group and the Aβ-negative group by searching from the value, the peak area value of the one type of amino acid-related metabolite, the ratio of the two types of metabolites, and BMI.
　得られたロジスティック回帰式（計２０，８２５（＝５１Ｃ３）個）のうち、ＢＭＩを変数に組み込むことでＲＯＣ＿ＡＵＣ値が上昇した式（計２０，７６９個）の中から、ＢＭＩ変数有りの上位２０式を表４に示した。ＢＭＩの変数を加えることで大多数（９９．７％）のロジスティック回帰式のＲＯＣ＿ＡＵＣ値が改善されたことから、ＢＭＩを変数に加えたロジスティック回帰式は前記の評価において有用なものであると考えられる。 Among the obtained logistic regression equations (20,825 (= 51 C 3 ) in total), among the equations (20,769 in total) in which the ROC_AUC value increased by incorporating BMI into the variable, there was a BMI variable. The top 20 equations are shown in Table 4. Since the ROC_AUC value of the majority (99.7%) of the logistic regression equations was improved by adding the BMI variable, it is considered that the logistic regression equation with the BMI added to the variable is useful in the above evaluation. Be done.
Figure JPOXMLDOC01-appb-T000004
Figure JPOXMLDOC01-appb-T000004
　実施例１で用いたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data used in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める４個の変数の組み合わせ（ＭＭＳＥ（Ｍｉｎｉ　Ｍｅｎｔａｌ　Ｓｔａｔｅ　Ｅｘａｍｉｎａｔｉｏｎ）の点数の変数を必須とする）を、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値、前記２種類の代謝物比およびＭＭＳＥから探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。 A logistic regression equation was used as the multivariate discriminant. The combination of 4 variables included in the logistic regression equation (MMSE (Mini Menal State Examination) score variable is required) is the plasma concentration value of the 23 types of amino acids and the 25 types of amino acid-related biotransforms. Search from the plasma concentration value, the peak area value of the one type of amino acid-related metabolite, the ratio of the two types of biotransformers, and the MMSE, and search for a logistic regression equation with good discrimination between the Aβ-positive group and the Aβ-negative group. Carried out.
　得られたロジスティック回帰式（計２０，８２５（＝５１Ｃ３）個）のうち、ＭＭＳＥを変数に組み込むことでＲＯＣ＿ＡＵＣ値が上昇した式（計２０，８２５個）の中から、ＭＭＳＥ変数有りの上位２０式を表５に示した。ＭＭＳＥの変数を加えることで全てのロジスティック回帰式のＲＯＣ＿ＡＵＣ値が改善されたことから、ＭＭＳＥを変数に加えたロジスティック回帰式は前記の評価において有用なものであると考えられる。 Among the obtained logistic regression equations (20,825 (= 51 C 3 ) in total), among the equations (20,825 in total) in which the ROC_AUC value increased by incorporating the MMSE into the variable, there was an MMSE variable. The top 20 equations are shown in Table 5. Since the ROC_AUC value of all logistic regression equations was improved by adding the MMSE variable, it is considered that the logistic regression equation with the MMSE added to the variable is useful in the above evaluation.
Figure JPOXMLDOC01-appb-T000005
Figure JPOXMLDOC01-appb-T000005
　実施例１で用いたサンプルデータを用いた。血漿中の代謝物濃度値が代入される変数を含む、Ａβ陽性群とＡβ陰性群との２群を判別するための多変量判別式（多変量関数）を求めた。 The sample data used in Example 1 was used. A multivariate discriminant (multivariate function) for discriminating between two groups, an Aβ-positive group and an Aβ-negative group, including a variable to which the plasma metabolite concentration value is substituted was obtained.
　多変量判別式としてロジスティック回帰式を用いた。ロジスティック回帰式に含める６個の変数の組み合わせを、前記２３種類のアミノ酸の血漿中濃度値、前記２５種類のアミノ酸関連代謝物の血漿中濃度値、前記１種類のアミノ酸関連代謝物のピーク面積値および前記２種類の代謝物比から探索し、Ａβ陽性群とＡβ陰性群の判別能が良好なロジスティック回帰式の探索を実施した。なお、欠損値が多い組み合わせを除くため、計算に用いる事が出来るデータ数がＡβ陽性群とＡβ陰性群を合計して５０より少なかった６変数の組み合わせ式は探索結果から除外した。 A logistic regression equation was used as the multivariate discriminant. The combination of 6 variables included in the logistic regression equation is the plasma concentration value of the 23 kinds of amino acids, the plasma concentration value of the 25 kinds of amino acid-related metabolites, and the peak area value of the one kind of amino acid-related metabolite. A logistic regression equation was searched for with good discrimination between the Aβ-positive group and the Aβ-negative group. In order to exclude combinations with many missing values, the combination formula of 6 variables in which the total number of data that can be used in the calculation was less than 50 in the Aβ-positive group and the Aβ-negative group was excluded from the search results.
　得られたロジスティック回帰式（計１５，６９６，１２０個）のうち、ＲＯＣ＿ＡＵＣが０．８５以上の３，６２１通りの式に含まれる各変数の出現頻度を求め、表６に示した。 Of the obtained logistic regression equations (15,696,120 in total), the frequency of occurrence of each variable included in 3,621 equations with ROC_AUC of 0.85 or more was calculated and shown in Table 6.
Figure JPOXMLDOC01-appb-T000006
Figure JPOXMLDOC01-appb-T000006
　これより、ＭｅＣｙｓ、Ａｌｌｙｌ－Ｃｙｓ、ｈＣｉｔ、ｂＡｉＢＡ、Ｃｙｓ２、Ｎ８－ＡｃＳｐｄ、Ｖａｌ、Ｇｌｙ、ＡＤＭＡ、１－ＭｅＨｉｓ、Ｍｅｔ、Ｌｙｓ、Ｓａｒ、Ｓｅｒ、Ｔａｕ、ＳＤＭＡ、３－ＭｅＨｉｓ、Ｐｈｅ、Ｔｈｒ、Ｇｌｎ、Ｌｅｕ、Ｈｉｓ、Ｋｙｎ、Ｎ６－ＡｃＬｙｓおよびＨｙＰｒｏの出現頻度は２００回以上と高いことが示された。特に、ＭｅＣｙｓ、Ａｌｌｙｌ－Ｃｙｓ、ｈＣｉｔ、ｂＡｉＢＡ、Ｃｙｓ２、Ｎ８－ＡｃＳｐｄ、Ｖａｌ、Ｇｌｙ、ＡＤＭＡ、１－ＭｅＨｉｓ、Ｍｅｔ、ＬｙｓおよびＳａｒの出現頻度は５００回以上と高いことが示された。更に、ＭｅＣｙｓ、Ａｌｌｙｌ－ＣｙｓおよびｈＣｉｔの出現頻度は２，０００回以上と高いことが示された。 From this, MeCys, Allyl-Cys, hCit, bAiBA, Cys2, N8-AcSpd, Val, Gly, ADMA, 1-MeHis, Met, Lys, Sar, Ser, Tau, SDMA, 3-MeHis, Ph, Thr, Gln , Leu, His, Kyn, N6-AcLys and HyPro were shown to appear as high as 200 times or more. In particular, it was shown that the frequency of appearance of MeCys, Allyl-Cys, hCit, bAiBA, Cys2, N8-AcSpd, Val, Gly, ADMA, 1-MeHis, Met, Lys and Sar was as high as 500 times or more. Furthermore, it was shown that the frequency of appearance of MeCys, Allyl-Cys and hCit was as high as 2,000 times or more.
　また、前記３，６２１通りの式に含まれる２種類の変数の組み合わせの出現頻度を求め、表７に示した。 In addition, the frequency of appearance of combinations of two types of variables included in the above 3,621 equations was calculated and shown in Table 7.
Figure JPOXMLDOC01-appb-T000007
Figure JPOXMLDOC01-appb-T000007
　これより、以下の２種類の変数の組み合わせの出現頻度は２００回以上と高いことが示された。
Allyl-Cys,MeCys;hCit,MeCys;Allyl-Cys,hCit;Cys2,MeCys;MeCys,N8-AcSpd;bAiBA,MeCys;Cys2,Allyl-Cys;Allyl-Cys,N8-AcSpd;Gly,MeCys;Val,MeCys;1-MeHis,MeCys;Met,MeCys;1-MeHis,Allyl-Cys;Lys,MeCys;Lys,Allyl-Cys;ADMA,MeCys;hCit,N8-AcSpd;MeCys,Sar;Lys,hCit;Allyl-Cys,bAiBA;Allyl-Cys,Sar;Met,Val;Gly,Val;1-MeHis,hCit;Gly,Met;bAiBA,hCit;Tau,MeCys;ADMA,bAiBA;Tau,Allyl-Cys;Ser,MeCys;MeCys,SDMA;3-MeHis,MeCys;ADMA,hCit;hCit,Sar;Allyl-Cys,SDMA;Thr,MeCys;Ser,hCit;Thr,Allyl-Cys;hCit,SDMA;Leu,MeCys;Allyl-Cys,3-MeHis;Cys2,bAiBA;Thr,hCit;Ser,bAiBA;Gln,MeCys;Phe,MeCys;Tau,hCit;Ser,ADMA;Cys2,Sar;Cys2,N8-AcSpd;Allyl-Cys,ADMA;Val,hCit From this, it was shown that the frequency of appearance of the combination of the following two types of variables was as high as 200 times or more.
Allyl-Cys, MeCys; hCit, MeCys; Allyl-Cys, hCit; Cys2, MeCys; MeCys, N8-AcSpd; bAiBA, MeCys; Cys2, Allyl-Cys; Allyl-Cys, N8-AcSpd; Gly, MeCys; Val, MeCys; 1-MeHis, MeCys; Met, MeCys; 1-MeHis, Allyl-Cys; Lys, MeCys; Lys, Allyl-Cys; ADMA, MeCys; hCit, N8-AcSpd; MeCys, Sar; Lys, hCit; Allyl- Cys, bAiBA; Allyl-Cys, Sar; Met, Val; Gly, Val; 1-MeHis, hCit; Gly, Met; bAiBA, hCit; Tau, MeCys; ADMA, bAiBA; Tau, Allyl-Cys; Ser, MeCys; MeCys, SDMA; 3-MeHis, MeCys; ADMA, hCit; hCit, Sar; Allyl-Cys, SDMA; Thr, MeCys; Ser, hCit; Thr, Allyl-Cys; hCit, SDMA; Leu, MeCys; Allyl-Cys, 3-MeHis; Cys2, bAiBA; Thr, hCit; Ser, bAiBA; Gln, MeCys; Phe, MeCys; Tau, hCit; Ser, ADMA; Cys2, Sar; Cys2, N8-AcSpd; Allyl-Cys, ADMA; Val, hCit
　特に、以下の２種類の変数の組み合わせの出現頻度は５００回以上と高いことが示された。
Allyl-Cys,MeCys;hCit,MeCys;Allyl-Cys,hCit;Cys2,MeCys;MeCys,N8-AcSpd;bAiBA,MeCys;Cys2,Allyl-Cys;Allyl-Cys,N8-AcSpd;Gly,MeCys;Val,MeCys;1-MeHis,MeCys;Met,MeCys;1-MeHis,Allyl-Cys;Lys,MeCys;Lys,Allyl-Cys;ADMA,MeCys;hCit,N8-AcSpd;MeCys,Sar In particular, it was shown that the frequency of appearance of the combination of the following two types of variables was as high as 500 times or more.
Allyl-Cys, MeCys; hCit, MeCys; Allyl-Cys, hCit; Cys2, MeCys; MeCys, N8-AcSpd; bAiBA, MeCys; Cys2, Allyl-Cys; Allyl-Cys, N8-AcSpd; Gly, MeCys; Val, MeCys; 1-MeHis, MeCys; Met, MeCys; 1-MeHis, Allyl-Cys; Lys, MeCys; Lys, Allyl-Cys; ADMA, MeCys; hCit, N8-AcSpd; MeCys, Sar
　更に、Ａｌｌｙｌ－ＣｙｓとＭｅＣｙｓの組み合わせの出現頻度およびｈＣｉｔとＭｅＣｙｓの組み合わせの出現頻度は２，０００回以上と高いことが示された。 Furthermore, it was shown that the frequency of appearance of the combination of Allyl-Cys and MeCys and the frequency of appearance of the combination of hCit and MeCys were as high as 2,000 times or more.
　以上のように、本発明は、産業上の多くの分野、特に医薬品や食品、医療などの分野で広く実施することができ、特に、Ａβの脳内への蓄積を予測できる可能性があるバイオインフォマティクス分野において極めて有用である。 As described above, the present invention can be widely implemented in many industrial fields, particularly in fields such as pharmaceuticals, foods, and medical treatments, and in particular, bioinformatics that may predict the accumulation of Aβ in the brain. Extremely useful in the field of informatics.
　１００　評価装置（算出装置を含む）
　１０２　制御部
　１０２ａ　取得部
　１０２ｂ　指定部
　１０２ｃ　式作成部
　１０２ｄ　評価部
　１０２ｄ１　算出部
　１０２ｄ２　変換部
　１０２ｄ３　生成部
　１０２ｄ４　分類部
　１０２ｅ　結果出力部
　１０２ｆ　送信部
　１０４　通信インターフェース部
　１０６　記憶部
　１０６ａ　測定データファイル
　１０６ｂ　指標状態情報ファイル
　１０６ｃ　指定指標状態情報ファイル
　１０６ｄ　式関連情報データベース
　１０６ｄ１　式ファイル
　１０６ｅ　評価結果ファイル
　１０８　入出力インターフェース部
　１１２　入力装置
　１１４　出力装置
　２００　クライアント装置（端末装置（情報通信端末装置））
　３００　ネットワーク
　４００　データベース装置 100 Evaluation device (including calculation device)
102 Control unit 102a Acquisition unit 102b Designation unit 102c Expression creation unit 102d Evaluation unit 102d1 Calculation unit 102d2 Conversion unit 102d3 Generation unit 102d4 Classification unit 102e Result output unit 102f Transmission unit 104 Communication interface unit 106 Storage unit 106a Measurement data file 106b Index status information File 106c Designated index status information file 106d Expression related information database 106d1 Expression file 106e Evaluation result file 108 Input / output interface unit 112 Input device 114 Output device 200 Client device (terminal device (information and communication terminal device))
300 network 400 database device
［１．２変数の式］
3-hKyn, MeCys, 0.744; Ser, MeCys, 0.736; ADMA, MeCys, 0.73; Glu, MeCys, 0.722; Orn, MeCys, 0.722; Cys2, MeCys, 0.72; Lys, MeCys, 0.718; bAiBA, MeCys, 0.717; 1-MeHis, MeCys, 0.716; Ser, ADMA, 0.714; Val, MeCys, 0.714; Allyl-Cys, MeCys, 0.714; Gly, MeCys, 0.713; Leu, MeCys, 0.713; MeCys, N6-AcLys, 0.713; MeCys, N8-AcSpd, 0.713; HyPro, MeCys, 0.709; Glu, Gly, 0.708; Tau, MeCys, 0.707; hCit, MeCys, 0.704; Ile, MeCys, 0.703; Thr, MeCys, 0.702; Leu, Phe, 0.699; MeCys, Pipecolic acid, 0.699; 3-MeHis, MeCys, 0.697; Kyn, MeCys, 0.696; EtOHNH2, aAiBA, 0.695; aAAA, MeCys, 0.694; Met, Orn, 0.693; Trp, MeCys, 0.693; aABA, MeCys, 0.692; Phe, MeCys, 0.691; Ser, Cystathionine, 0.691; His, MeCys, 0.69; Orn, Phe, 0.69; Phe, Val, 0.69; Ser, hCit, 0.69; MeCys, PEA, 0.69; MeCys, Put, 0.69; Cys2, ADMA, 0.69; Orn, Cystathionine, 0.689; Pro, MeCys, 0.688; Orn, aAiBA, 0.687; Ser, Pipecolic acid, 0.686; Tyr, MeCys, 0.686; Cit, MeCys, 0.684; Glu, Ser, 0.684; MeCys, SDMA, 0.684; [1.2 Variable formula]
3-hKyn, MeCys, 0.744; Ser, MeCys, 0.736; ADMA, MeCys, 0.73; Glu, MeCys, 0.722; Orn, MeCys, 0.722; Cys2, MeCys, 0.72; Lys, MeCys, 0.718; bAiBA, MeCys, 0.717; 1-MeHis, MeCys, 0.716; Ser, ADMA, 0.714; Val, MeCys, 0.714; Allyl-Cys, MeCys, 0.714; Gly, MeCys, 0.713; Leu, MeCys, 0.713; MeCys, N6-AcLys, 0.713; MeCys, N8-AcSpd, 0.713; HyPro, MeCys, 0.709; Glu, Gly, 0.708; Tau, MeCys, 0.707; hCit, MeCys, 0.704; Ile, MeCys, 0.703; Thr, MeCys, 0.702; Leu, Phe, 0.699; MeCys, Pipecolic acid, 0.699; 3-MeHis, MeCys, 0.697; Kyn, MeCys, 0.696; EtOHNH2, aAiBA, 0.695; aAAA, MeCys, 0.694; Met, Orn, 0.693; Trp, MeCys, 0.693; aABA, MeCys, 0.692; Phe , MeCys, 0.691; Ser, Cystathionine, 0.691; His, MeCys, 0.69; Orn, Phe, 0.69; Phe, Val, 0.69; Ser, hCit, 0.69; MeCys, PEA, 0.69; MeCys, Put, 0.69; Cys2, ADMA , 0.69; Orn, Cystathionine, 0.689; Pro, MeCys, 0.688; Orn, aAiBA, 0.687; Ser, Pipecolic acid, 0.686; Tyr, MeCys, 0.686; Cit, MeCys, 0.684; Glu, Ser, 0.684; MeCys, SDMA, 0.684;
［２．３変数の式］
EtOHNH2, Leu, Phe, 0.797; Gly, Met, Val, 0.787; 3-hKyn, bAiBA, MeCys, 0.786; Tau, Allyl-Cys, MeCys, 0.781; Glu, Gly, MeCys, 0.779; Cys2, Allyl-Cys, MeCys, 0.779; Lys, Allyl-Cys, MeCys, 0.778; 3-hKyn, Allyl-Cys, MeCys, 0.777; Ser, ADMA, bAiBA, 0.777; 3-hKyn, MeCys, N8-AcSpd, 0.777; Cys2, ADMA, MeCys, 0.775; Leu, Phe, MeCys, 0.773; Phe, Val, MeCys, 0.772; Gly, Val, MeCys, 0.771; EtOHNH2, MeCys, Kyn/BCAA, 0.771; 1-MeHis, Allyl-Cys, MeCys, 0.771; Allyl-Cys, hCit, MeCys, 0.771; Ser, Kyn, MeCys, 0.77; Cys2, aABA, MeCys, 0.768; Val, Allyl-Cys, MeCys, 0.768; 3-MeHis, Allyl-Cys, MeCys, 0.768; Leu, aAiBA, MeCys, 0.768; ADMA, MeCys, N8-AcSpd, 0.767; Leu, 3-hKyn, MeCys, 0.766; 3-hKyn, ADMA, MeCys, 0.766; 3-hKyn, MeCys, SDMA, 0.766; Val, 3-hKyn, MeCys, 0.765; Val, aAiBA, MeCys, 0.764; hCit, MeCys, N8-AcSpd, 0.764; Cys2, MeCys, N8-AcSpd, 0.764; EtOHNH2, bAiBA, MeCys, 0.763; Glu, Ser, MeCys, 0.762; Ser, hCit, MeCys, 0.762; ADMA, bAiBA, MeCys, 0.762; HyPro, MeCys, N8-AcSpd, 0.762; MeCys, N6-AcLys, N8-AcSpd, 0.762; Glu, 3-hKyn, MeCys, 0.762; 1-MeHis, 3-hKyn, MeCys, 0.76; Ile, Leu, MeCys, 0.76; Cys2, Orn, MeCys, 0.76; Gly, Leu, MeCys, 0.759; Leu, Met, MeCys, 0.759; Tau, 3-hKyn, MeCys, 0.759; Leu, Allyl-Cys, MeCys, 0.758; Ser, Val, MeCys, 0.758; EtOHNH2, 3-hKyn, MeCys, 0.758; Orn, 3-hKyn, MeCys, 0.757; Ser, bAiBA, MeCys, 0.757; Gln, Ser, MeCys, 0.756; Ser, Trp, MeCys, 0.756; Ser, aAiBA, MeCys, 0.756; Ser, MeCys, N6-AcLys, 0.756; aABA, MeCys, N6-AcLys, 0.756; EtOHNH2, Ser, bAiBA, 0.755; EtOHNH2, aABA, Kyn/BCAA, 0.755; Asn, Leu, MeCys, 0.754; Lys, Ser, MeCys, 0.754; Gly, ADMA, bAiBA, 0.753; Ser, 1-MeHis, MeCys, 0.753; Ser, ADMA, MeCys, 0.753; Ile, 3-hKyn, MeCys, 0.753; Lys, 3-hKyn, MeCys, 0.753; 3-hKyn, MeCys, N6-AcLys, 0.753; EtOHNH2, aAiBA, MeCys, 0.753; Gly, Leu, Met, 0.752; Ser, 3-MeHis, MeCys, 0.752; Val, aABA, MeCys, 0.752; 1-MeHis, bAiBA, MeCys, 0.752; ADMA, hCit, MeCys, 0.752; Ile, Allyl-Cys, MeCys, 0.752; Allyl-Cys, HyPro, MeCys, 0.752; Cys2, bAiBA, MeCys, 0.752; Asn, 3-hKyn, MeCys, 0.751; Pro, 3-hKyn, MeCys, 0.751; Thr, 3-hKyn, MeCys, 0.751; ADMA, Allyl-Cys, MeCys, 0.751; Cit, Ser, MeCys, 0.75; Gly, hCit, MeCys, 0.75; Leu, bAiBA, MeCys, 0.75; Ser, aAAA, MeCys, 0.75; Ser, MeCys, Put, 0.75; Tyr, Val, MeCys, 0.75; 1-MeHis, hCit, MeCys, 0.75; 3-hKyn, MeCys, Pipecolic acid, 0.75; ADMA, HyPro, MeCys, 0.75; ADMA, MeCys, SDMA, 0.75; Cys2, Glu, MeCys, 0.749; Ser, Allyl-Cys, MeCys, 0.749; Glu, bAiBA, MeCys, 0.749; Gly, Ile, MeCys, 0.749; Leu, Ser, MeCys, 0.749; Orn, hCit, MeCys, 0.749; Ser, bAiBA, hCit, 0.749; Cys2, 3-hKyn, MeCys, 0.749; 3-hKyn, MeCys, Sar, 0.749; 3-hKyn, MeCys, Thioproline, 0.749; Glu, Allyl-Cys, MeCys, 0.748; Orn, Allyl-Cys, MeCys, 0.748; Allyl-Cys, MeCys, PEA, 0.748; Asn, Ser, MeCys, 0.748; Gly, Phe, Val, 0.748; Orn, MeCys, N6-AcLys, 0.748; Ser, ADMA, SDMA, 0.748; Ser, Hypotaurine, MeCys, 0.748; Ser, MeCys, Kyn/Trp, 0.748; ADMA, MeCys, Put, 0.748; hCit, MeCys, Pipecolic acid, 0.748; Cys2, ADMA, bAiBA, 0.747; Gly, bAiBA, MeCys, 0.747; Lys, aAiBA, MeCys, 0.747; Lys, MeCys, N8-AcSpd, 0.747; Orn, bAiBA, MeCys, 0.747; Ser, Tau, MeCys, 0.747; Ser, aABA, MeCys, 0.747; Allyl-Cys, aAAA, MeCys, 0.746; His, 3-hKyn, MeCys, 0.746; 3-hKyn, aAAA, MeCys, 0.746; 3-hKyn, MeCys, PEA, 0.746; 3-hKyn, MeCys, Kyn/BCAA, 0.746; Glu, MeCys, N6-AcLys, 0.746; Gly, Lys, MeCys, 0.746; Ser, ADMA, Pipecolic acid, 0.746; Thr, hCit, MeCys, 0.746; 1-MeHis, HyPro, MeCys, 0.746; bAiBA, hCit, MeCys, 0.746; bAiBA, HyPro, MeCys, 0.746; Allyl-Cys, MeCys, N6-AcLys, 0.745; Allyl-Cys, MeCys, N8-AcSpd, 0.745; EtOHNH2, Leu, Cystathionine, 0.745; EtOHNH2, Val, Cystathionine, 0.745; Glu, aAiBA, MeCys, 0.744; Gly, ADMA, SDMA, 0.744; Gly, aAAA, MeCys, 0.744; Leu, aABA, MeCys, 0.744; Met, Val, MeCys, 0.744; Orn, Cystathionine, MeCys, 0.744; Phe, Ser, Val, 0.744; Val, Cystathionine, MeCys, 0.744; Allyl-Cys, Kyn, MeCys, 0.744; Allyl-Cys, MeCys, Spd, 0.744; Gly, MeCys, Put, 0.743; Met, Ser, Val, 0.743; Orn, Ser, MeCys, 0.743; Orn, MeCys, N8-AcSpd, 0.743; Pro, Ser, MeCys, 0.743; Ser, hCit, Cystathionine, 0.743; Ser, MeCys, PEA, 0.743; Val, MeCys, N8-AcSpd, 0.743; Cys2, Kyn, MeCys, 0.743; Cys2, MeCys, Thioproline, 0.743; Ser, 3-hKyn, MeCys, 0.743; 3-hKyn, 3-MeHis, MeCys, 0.743; 3-hKyn, aABA, MeCys, 0.743; 3-hKyn, Cystathionine, MeCys, 0.743; 3-hKyn, MeCys, Put, 0.743; Gly, MeCys, N6-AcLys, 0.742; Ile, Ser, MeCys, 0.742; Thr, ADMA, MeCys, 0.742; EtOHNH2, Lys, MeCys, 0.742; EtOHNH2, Orn, aAiBA, 0.742; EtOHNH2, Phe, Val, 0.742; Trp, Allyl-Cys, MeCys, 0.742; Allyl-Cys, MeCys, Sar, 0.742; Trp, 3-hKyn, MeCys, 0.741; 3-hKyn, GABA, MeCys, 0.741; 3-hKyn, Kyn, MeCys, 0.741; 3-hKyn, MeCys, Kyn/Trp, 0.741; Ala, Ser, MeCys, 0.741; Ile, aAiBA, MeCys, 0.741; Ile, MeCys, N8-AcSpd, 0.741; Leu, MeCys, N8-AcSpd, 0.741; Lys, aABA, MeCys, 0.741; Orn, aAiBA, MeCys, 0.741; Ser, Cystathionine, MeCys, 0.741; Val, bAiBA, MeCys, 0.741; Val, HyPro, MeCys, 0.741; Thr, Allyl-Cys, MeCys, 0.741; Gly, Ser, MeCys, 0.74; Leu, Cystathionine, MeCys, 0.74; Ser, hArg, MeCys, 0.74; Ser, HyPro, MeCys, 0.74; Ser, MeCys, N8-AcSpd, 0.74; Tau, ADMA, MeCys, 0.74; Val, hCit, MeCys, 0.74; aAiBA, MeCys, N8-AcSpd, 0.74; ADMA, GABA, MeCys, 0.74; ADMA, MeCys, N6-AcLys, 0.74; hCit, MeCys, Sar, 0.74; Arg, 3-hKyn, MeCys, 0.74; Met, 3-hKyn, MeCys, 0.74; EtOHNH2, Gly, bAiBA, 0.74; EtOHNH2, Leu, aAAA, 0.74; Gln, Gly, MeCys, 0.739; Gln, ADMA, MeCys, 0.739; Orn, Tyr, MeCys, 0.739; Orn, MeCys, Pipecolic acid, 0.739; Ser, ADMA, Cystathionine, 0.739; Ser, MeCys, Pipecolic acid, 0.739; Ser, MeCys, Thioproline, 0.739; 1-MeHis, MeCys, N8-AcSpd, 0.739; ADMA, bAiBA, Pipecolic acid, 0.739; Tyr, 3-hKyn, MeCys, 0.738; 3-hKyn, hArg, MeCys, 0.738; Allyl-Cys, bAiBA, MeCys, 0.738; Glu, aABA, MeCys, 0.738; Gly, ADMA, MeCys, 0.738; Phe, Val, ADMA, 0.738; 3-MeHis, MeCys, N8-AcSpd, 0.738; aABA, ADMA, MeCys, 0.738; aAiBA, ADMA, MeCys, 0.738; Cys2, aABA, ADMA, 0.737; Cys2, MeCys, Pipecolic acid, 0.737; EtOHNH2, Leu, MeCys, 0.737; EtOHNH2, bAiBA, Kyn/BCAA, 0.737; Gln, 3-hKyn, MeCys, 0.737; Phe, 3-hKyn, MeCys, 0.737; Glu, Gly, Pipecolic acid, 0.737; Glu, ADMA, MeCys, 0.737; Gly, Orn, MeCys, 0.737; Gly, Tyr, MeCys, 0.737; Gly, Val, Cystathionine, 0.737; Ile, bAiBA, MeCys, 0.737; Lys, hCit, MeCys, 0.737; Ser, Thr, MeCys, 0.737; Ser, MeCys, Sar, 0.737; Ser, MeCys, Kyn/BCAA, 0.737; ADMA, bAiBA, hCit, 0.737; Hypotaurine, MeCys, PEA, 0.737; Cys2, 3-MeHis, MeCys, 0.736; Cys2, MeCys, N6-AcLys, 0.736; Cys2, MeCys, Sar, 0.736; Asn, Ile, MeCys, 0.736; Leu, Orn, Phe, 0.736; Leu, Tyr, MeCys, 0.736; Orn, MeCys, SDMA, 0.736; 1-MeHis, aAiBA, MeCys, 0.736; Ala, 3-hKyn, MeCys, 0.735; Cys2, hCit, MeCys, 0.735; Cys2, MeCys, Put, 0.735; Arg, Ser, MeCys, 0.734; Asn, Val, MeCys, 0.734; Glu, Gly, Cystathionine, 0.734; Glu, His, MeCys, 0.734; Gly, 1-MeHis, MeCys, 0.734; His, Ser, MeCys, 0.734; His, ADMA, MeCys, 0.734; Leu, hCit, MeCys, 0.734; Phe, Ser, MeCys, 0.734; Phe, ADMA, MeCys, 0.734; Ser, MeCys, Spd, 0.734; Tau, Hypotaurine, MeCys, 0.734; Tau, HyPro, MeCys, 0.734; aAiBA, hCit, MeCys, 0.734; ADMA, Cystathionine, MeCys, 0.734; hCit, MeCys, N6-AcLys, 0.734; EtOHNH2, aABA, MeCys, 0.734; Cit, 3-hKyn, MeCys, 0.734; 3-hKyn, hCit, MeCys, 0.734; Cys2, Tau, MeCys, 0.733; Cys2, Trp, MeCys, 0.733; Cys2, 1-MeHis, MeCys, 0.733; Asn, Orn, MeCys, 0.733; Cit, Ser, ADMA, 0.733; EtOHNH2, Lys, Allyl-Cys, 0.733; Glu, Phe, MeCys, 0.733; Glu, Ser, ADMA, 0.733; Glu, hCit, MeCys, 0.733; Leu, Phe, ADMA, 0.733; Leu, HyPro, MeCys, 0.733; Orn, ADMA, bAiBA, 0.733; Pro, aAiBA, MeCys, 0.733; Ser, ADMA, hCit, 0.733; Ser, GABA, MeCys, 0.733; ADMA, MeCys, PEA, 0.733; ADMA, MeCys, Sar, 0.733; Kyn, MeCys, N8-AcSpd, 0.733; Arg, Leu, MeCys, 0.732; Asn, MeCys, N6-AcLys, 0.732; Gln, Leu, MeCys, 0.732; Ile, ADMA, MeCys, 0.732; Leu, Met, Ser, 0.732; Met, Ser, MeCys, 0.732; Met, ADMA, MeCys, 0.732; Orn, Phe, Val, 0.732; Orn, HyPro, MeCys, 0.732; Tau, MeCys, N8-AcSpd, 0.732; Val, aAAA, MeCys, 0.732; Asn, Cys2, MeCys, 0.732; Cit, Cys2, MeCys, 0.732; Asn, ADMA, MeCys, 0.731; Gln, Orn, MeCys, 0.731; Glu, Cystathionine, MeCys, 0.731; Glu, MeCys, Sar, 0.731; Gly, 3-MeHis, MeCys, 0.731; Ile, Met, MeCys, 0.731; Ile, Val, MeCys, 0.731; Leu, ADMA, MeCys, 0.731; Lys, MeCys, Sar, 0.731; Orn, Hypotaurine, MeCys, 0.731; Ser, Trp, ADMA, 0.731; Ser, Tyr, MeCys, 0.731; Ser, MeCys, SDMA, 0.731; Trp, ADMA, MeCys, 0.731; 1-MeHis, aABA, MeCys, 0.731; Cys2, Glu, Gly, 0.731; Cys2, Gly, MeCys, 0.731; Cys2, Ser, MeCys, 0.731; Cys2, ADMA, Pipecolic acid, 0.731; 3-hKyn, aAiBA, MeCys, 0.731; Arg, ADMA, MeCys, 0.73; Cit, ADMA, MeCys, 0.73; Cit, MeCys, N8-AcSpd, 0.73; Glu, Pro, MeCys, 0.73; Glu, Hypotaurine, MeCys, 0.73; Glu, HyPro, MeCys, 0.73; Gly, Orn, bAiBA, 0.73; Gly, Val, bAiBA, 0.73; Gly, MeCys, Pipecolic acid, 0.73; Lys, ADMA, MeCys, 0.73; Met, MeCys, N8-AcSpd, 0.73; Orn, Ser, Cystathionine, 0.73; Orn, MeCys, Sar, 0.73; Pro, 1-MeHis, MeCys, 0.73; Pro, MeCys, N8-AcSpd, 0.73; Ser, aABA, ADMA, 0.73; Ser, ADMA, GABA, 0.73; Ser, ADMA, N8-AcSpd, 0.73; 1-MeHis, ADMA, MeCys, 0.73; 1-MeHis, MeCys, Pipecolic acid, 0.73; 1-MeHis, MeCys, Put, 0.73; 3-MeHis, ADMA, MeCys, 0.73; ADMA, hArg, MeCys, 0.73; ADMA, MeCys, Kyn/Trp, 0.73; aAAA, MeCys, N8-AcSpd, 0.73; hArg, hCit, MeCys, 0.73; EtOHNH2, Ser, Cystathionine, 0.729; EtOHNH2, aAiBA, Spd, 0.729; Glu, Lys, MeCys, 0.729; Glu, hArg, MeCys, 0.729; Glu, MeCys, Pipecolic acid, 0.729; Glu, MeCys, Spd, 0.729; Gly, Trp, MeCys, 0.729; Gly, Hypotaurine, MeCys, 0.729; Gly, MeCys, SDMA, 0.729; Leu, hArg, MeCys, 0.729; Ser, ADMA, N6-AcLys, 0.729; Ser, ADMA, Kyn/Trp, 0.729; Thr, aAiBA, MeCys, 0.729; Tyr, ADMA, MeCys, 0.729; 1-MeHis, hArg, MeCys, 0.729; ADMA, Kyn, MeCys, 0.729; ADMA, MeCys, Kyn/BCAA, 0.729; bAiBA, MeCys, N6-AcLys, 0.729; bAiBA, MeCys, N8-AcSpd, 0.729; HyPro, MeCys, N6-AcLys, 0.729; HyPro, MeCys, Pipecolic acid, 0.729; Cys2, Lys, MeCys, 0.728; Gln, Ser, ADMA, 0.728; Glu, MeCys, N8-AcSpd, 0.728; Gly, HyPro, MeCys, 0.728; Leu, MeCys, Pipecolic acid, 0.728; Lys, bAiBA, MeCys, 0.728; Met, aAiBA, MeCys, 0.728; Trp, Val, MeCys, 0.728; Val, ADMA, MeCys, 0.728; aABA, aAAA, MeCys, 0.728; aAiBA, aAAA, MeCys, 0.728; aAiBA, HyPro, MeCys, 0.728; ADMA, aAAA, MeCys, 0.728; Ala, Cys2, MeCys, 0.727; Cys2, Phe, ADMA, 0.727; Cys2, aAiBA, MeCys, 0.727; Asn, Lys, MeCys, 0.727; Glu, GABA, MeCys, 0.727; Gly, Orn, Cystathionine, 0.727; Gly, ADMA, Kyn/B


CAA, 0.727; Ile, Phe, MeCys, 0.727; Leu, Tau, MeCys, 0.727; Leu, aAAA, MeCys, 0.727; Orn, Phe, Ser, 0.727; Orn, Val, MeCys, 0.727; Orn, aABA, MeCys, 0.727; Ser, ADMA, Kyn/BCAA, 0.727; Tau, Val, MeCys, 0.727; Tau, 1-MeHis, MeCys, 0.727; Tau, MeCys, N6-AcLys, 0.727; 1-MeHis, Kyn, MeCys, 0.727; 1-MeHis, Cystathionine, MeCys, 0.727; 3-MeHis, bAiBA, MeCys, 0.727; aAiBA, MeCys, N6-AcLys, 0.727; ADMA, Hypotaurine, MeCys, 0.727; ADMA, MeCys, Spd, 0.727; HyPro, MeCys, Sar, 0.727; MeCys, N8-AcSpd, Pipecolic acid, 0.727; Arg, EtOHNH2, aAiBA, 0.727; EtOHNH2, Orn, bAiBA, 0.727; EtOHNH2, GABA, Kyn/BCAA, 0.727; EtOHNH2, MeCys, N8-AcSpd, 0.727; Pro, Allyl-Cys, MeCys, 0.726; Tyr, Allyl-Cys, MeCys, 0.726; 3-hKyn, HyPro, MeCys, 0.726; Ala, Ser, ADMA, 0.726; Arg, Val, MeCys, 0.726; Gln, bAiBA, MeCys, 0.726; Glu, Leu, MeCys, 0.726; Glu, Tyr, MeCys, 0.726; Glu, 1-MeHis, MeCys, 0.726; Glu, MeCys, SDMA, 0.726; Gly, Leu, Phe, 0.726; Gly, aAiBA, MeCys, 0.726; His, MeCys, N8-AcSpd, 0.726; Ile, aABA, MeCys, 0.726; Leu, Phe, Pipecolic acid, 0.726; Lys, Phe, MeCys, 0.726; Lys, 1-MeHis, MeCys, 0.726; Orn, Phe, MeCys, 0.726; Ser, 3-MeHis, ADMA, 0.726; Ser, ADMA, HyPro, 0.726; Tau, MeCys, Pipecolic acid, 0.726; Val, 1-MeHis, MeCys, 0.726; Val, MeCys, Pipecolic acid, 0.726; 3-MeHis, aAiBA, MeCys, 0.726; aABA, hCit, MeCys, 0.726; Arg, Cys2, MeCys, 0.725; Cys2, Glu, aABA, 0.725; Asn, Glu, MeCys, 0.724; Cit, Leu, MeCys, 0.724; Cit, Ser, hCit, 0.724; Gln, Ile, MeCys, 0.724; Glu, Gly, hCit, 0.724; Glu, Ile, MeCys, 0.724; Glu, Tau, MeCys, 0.724; Glu, 3-MeHis, MeCys, 0.724; Glu, aAAA, MeCys, 0.724; Glu, MeCys, PEA, 0.724; Glu, MeCys, Thioproline, 0.724; Glu, MeCys, Kyn/BCAA, 0.724; Gly, Tau, MeCys, 0.724; Gly, MeCys, N8-AcSpd, 0.724; Ile, hCit, MeCys, 0.724; Ile, HyPro, MeCys, 0.724; Lys, Met, MeCys, 0.724; Lys, HyPro, MeCys, 0.724; Orn, ADMA, MeCys, 0.724; Orn, GABA, MeCys, 0.724; Orn, MeCys, Put, 0.724; Ser, Kyn, Cystathionine, 0.724; 3-MeHis, MeCys, Pipecolic acid, 0.724; 3-MeHis, MeCys, Sar, 0.724; aABA, MeCys, N8-AcSpd, 0.724; Cys2, Met, Orn, 0.724; Cys2, Phe, MeCys, 0.724; Cys2, Cystathionine, MeCys, 0.724; Cys2, MeCys, PEA, 0.724; EtOHNH2, Gly, Kyn/BCAA, 0.724; EtOHNH2, Phe, Kyn/BCAA, 0.724; EtOHNH2, MeCys, Pipecolic acid, 0.724; Phe, Val, 3-hKyn, 0.723; Arg, HyPro, MeCys, 0.723; Asn, Ser, ADMA, 0.723; Cit, Orn, MeCys, 0.723; Gln, Lys, MeCys, 0.723; Gln, Tau, MeCys, 0.723; Glu, Ser, Cystathionine, 0.723; Glu, Thr, MeCys, 0.723; Glu, MeCys, Put, 0.723; Ile, Tyr, MeCys, 0.723; Leu, Met, Orn, 0.723; Leu, Ser, ADMA, 0.723; Leu, 1-MeHis, MeCys, 0.723; Pro, MeCys, N6-AcLys, 0.723; Thr, MeCys, N8-AcSpd, 0.723; Trp, hCit, MeCys, 0.723; Trp, MeCys, N8-AcSpd, 0.723; 1-MeHis, MeCys, Sar, 0.723; 3-MeHis, MeCys, SDMA, 0.723; aAAA, HyPro, MeCys, 0.723; bAiBA, hArg, MeCys, 0.723; MeCys, N6-AcLys, Put, 0.723; Cys2, Orn, Phe, 0.723; Cys2, ADMA, GABA, 0.723; Cys2, ADMA, N8-AcSpd, 0.723; Ala, Glu, MeCys, 0.722; Arg, Glu, MeCys, 0.722; Gln, Thr, MeCys, 0.722; Glu, Gly, ADMA, 0.722; Glu, Kyn, MeCys, 0.722; His, hCit, MeCys, 0.722; Ile, Ser, ADMA, 0.722; Leu, Phe, Ser, 0.722; Met, Orn, MeCys, 0.722; Orn, Tau, MeCys, 0.722; Orn, Trp, MeCys, 0.722; Tau, aAiBA, MeCys, 0.722; aAiBA, bAiBA, MeCys, 0.722; aAAA, bAiBA, MeCys, 0.722; bAiBA, Kyn, MeCys, 0.722; hCit, MeCys, SDMA, 0.722; Cys2, Ile, MeCys, 0.721; Cys2, Orn, aABA, 0.721; EtOHNH2, Orn, Cystathionine, 0.721; EtOHNH2, Ser, Put, 0.721; Arg, Glu, Gly, 0.721; Arg, Orn, MeCys, 0.721; Cit, Glu, MeCys, 0.721; Glu, Orn, MeCys, 0.721; Glu, Trp, MeCys, 0.721; Gly, Ile, Met, 0.721; Ile, Orn, MeCys, 0.721; Leu, MeCys, PEA, 0.721; Pro, Tau, MeCys, 0.721; Pro, ADMA, MeCys, 0.721; Ser, Val, ADMA, 0.721; Tau, MeCys, Spd, 0.721; Val, GABA, MeCys, 0.721; Val, MeCys, Kyn/Trp, 0.721; 1-MeHis, MeCys, N6-AcLys, 0.721; 1-MeHis, MeCys, Kyn/Trp, 0.721; aABA, HyPro, MeCys, 0.721; bAiBA, MeCys, Kyn/Trp, 0.721; MeCys, N8-AcSpd, Put, 0.721; Gly, Allyl-Cys, MeCys, 0.721; Gly, 3-hKyn, MeCys, 0.72; Cys2, Val, MeCys, 0.72; Cys2, GABA, MeCys, 0.72; Cys2, MeCys, Kyn/BCAA, 0.72; Arg, Ser, ADMA, 0.72; Cit, Val, MeCys, 0.72; Gln, Gly, ADMA, 0.72; Glu, Gly, Met, 0.72; Glu, Met, MeCys, 0.72; Gly, Met, MeCys, 0.72; Gly, bAiBA, hCit, 0.72; His, Ser, ADMA, 0.72; Leu, Thr, MeCys, 0.72; Lys, hArg, MeCys, 0.72; Orn, Thr, MeCys, 0.72; Orn, 1-MeHis, MeCys, 0.72; Orn, aAAA, MeCys, 0.72; Orn, MeCys, Kyn/Trp, 0.72; Phe, Ser, ADMA, 0.72; Phe, MeCys, N6-AcLys, 0.72; Phe, MeCys, N8-AcSpd, 0.72; Ser, aAiBA, ADMA, 0.72; Tau, bAiBA, MeCys, 0.72; Thr, 1-MeHis, MeCys, 0.72; Tyr, aAiBA, MeCys, 0.72; Val, MeCys, Sar, 0.72; aAAA, hCit, MeCys, 0.72; Hypotaurine, MeCys, N8-AcSpd, 0.72; MeCys, N6-AcLys, SDMA, 0.72; MeCys, N8-AcSpd, Kyn/Trp, 0.72; Allyl-Cys, hArg, MeCys, 0.719; Allyl-Cys, MeCys, SDMA, 0.719; Ala, ADMA, MeCys, 0.719; Ala, bAiBA, MeCys, 0.719; Gln, Val, MeCys, 0.719; Gly, His, MeCys, 0.719; Gly, Kyn, MeCys, 0.719; His, Orn, MeCys, 0.719; His, aAiBA, MeCys, 0.719; Ile, Tau, MeCys, 0.719; Leu, Orn, MeCys, 0.719; Leu, MeCys, Put, 0.719; Lys, Val, MeCys, 0.719; Orn, Ser, bAiBA, 0.719; Orn, MeCys, PEA, 0.719; Thr, MeCys, N6-AcLys, 0.719; Val, MeCys, N6-AcLys, 0.719; 1-MeHis, GABA, MeCys, 0.719; 1-MeHis, Hypotaurine, MeCys, 0.719; 1-MeHis, MeCys, Spd, 0.719; aAiBA, Kyn, MeCys, 0.719; MeCys, N6-AcLys, PEA, 0.719; MeCys, PEA, Pipecolic acid, 0.719; Cys2, Orn, Pipecolic acid, 0.719; Cys2, Pro, MeCys, 0.719; Cys2, Tyr, MeCys, 0.719; Cys2, hArg, MeCys, 0.719; Cys2, HyPro, MeCys, 0.719; EtOHNH2, Leu, Met, 0.719; EtOHNH2, Orn, MeCys, 0.719; EtOHNH2, Allyl-Cys, MeCys, 0.718; Ser, Allyl-Cys, hCit, 0.718; Ala, 1-MeHis, MeCys, 0.718; Arg, Gly, Val, 0.718; Arg, MeCys, N8-AcSpd, 0.718; Asn, bAiBA, MeCys, 0.718; Gln, Glu, MeCys, 0.718; Glu, Gly, bAiBA, 0.718; Glu, Val, MeCys, 0.718; Gly, MeCys, Kyn/BCAA, 0.718; His, Lys, MeCys, 0.718; Leu, MeCys, Kyn/BCAA, 0.718; Met, Ser, ADMA, 0.718; Orn, Pro, HyPro, 0.718; Orn, Ser, hCit, 0.718; Orn, MeCys, Thioproline, 0.718; Ser, ADMA, Put, 0.718; Ser, bAiBA, HyPro, 0.718; Tau, Kyn, MeCys, 0.718; Thr, HyPro, MeCys, 0.718; 1-MeHis, MeCys, SDMA, 0.718; ADMA, MeCys, Pipecolic acid, 0.718; bAiBA, MeCys, Thioproline, 0.718; hCit, MeCys, Kyn/BCAA, 0.718; HyPro, Kyn, MeCys, 0.718; MeCys, N6-AcLys, Pipecolic acid, 0.718; MeCys, N8-AcSpd, SDMA, 0.718; 3-hKyn, Hypotaurine, MeCys, 0.717; Ala, Gly, MeCys, 0.717; Asn, Gly, MeCys, 0.717; Asn, 1-MeHis, MeCys, 0.717; Gly, Leu, Cystathionine, 0.717; Gly, Thr, MeCys, 0.717; Gly, Hypotaurine, Spd, 0.717; His, 1-MeHis, MeCys, 0.717; Ile, Met, Ser, 0.717; Ile, 1-MeHis, MeCys, 0.717; Ile, Cystathionine, MeCys, 0.717; Leu, Hypotaurine, MeCys, 0.717; Orn, Kyn, MeCys, 0.717; Ser, ADMA, aAAA, 0.717; Ser, ADMA, Sar, 0.717; Tau, hCit, MeCys, 0.717; Tau, MeCys, Put, 0.717; Thr, Val, MeCys, 0.717; Thr, MeCys, Pipecolic acid, 0.717; Tyr, MeCys, N8-AcSpd, 0.717; Val, 3-MeHis, MeCys, 0.717; Val, MeCys, Put, 0.717; Val, MeCys, SDMA, 0.717; 1-MeHis, MeCys, PEA, 0.717; 3-MeHis, HyPro, MeCys, 0.717; bAiBA, MeCys, Spd, 0.717; HyPro, MeCys, PEA, 0.717; His, Allyl-Cys, MeCys, 0.717; Phe, Allyl-Cys, MeCys, 0.717; Allyl-Cys, Hypotaurine, MeCys, 0.717; Cys2, His, MeCys, 0.716; Cys2, Leu, MeCys, 0.716; Cys2, Orn, Pro, 0.716; Cys2, aABA, aAiBA, 0.716; Cys2, ADMA, Put, 0.716; EtOHNH2, Gln, aAiBA, 0.716; EtOHNH2, Gly, GABA, 0.716; EtOHNH2, Gly, Put, 0.716; EtOHNH2, Pro, Kyn/BCAA, 0.716; EtOHNH2, Ser, aABA, 0.716; EtOHNH2, Val, bAiBA, 0.716; EtOHNH2, MeCys, SDMA, 0.716; EtOHNH2, MeCys, Kyn/Trp, 0.716; Ala, MeCys, N8-AcSpd, 0.716; Arg, 1-MeHis, MeCys, 0.716; Cit, Orn, Ser, 0.716; Cit, 1-MeHis, MeCys, 0.716; Gln, Glu, Gly, 0.716; Gln, MeCys, N8-AcSpd, 0.716; Glu, Gly, Put, 0.716; Glu, Gly, Sar, 0.716; Gly, Phe, MeCys, 0.716; Gly, Pro, MeCys, 0.716; Gly, Val, Pipecolic acid, 0.716; Gly, ADMA, Pipecolic acid, 0.716; Leu, Lys, MeCys, 0.716; Leu, Val, MeCys, 0.716; Lys, Tau, MeCys, 0.716; Lys, Tyr, MeCys, 0.716; Lys, aAAA, MeCys, 0.716; Lys, GABA, MeCys, 0.716; Met, Orn, Val, 0.716; Orn, Ser, Pipecolic acid, 0.716; Orn, hArg, MeCys, 0.716; Orn, MeCys, Kyn/BCAA, 0.716; Phe, HyPro, MeCys, 0.716; Ser, aABA, hCit, 0.716; Ser, ADMA, Thioproline, 0.716; Tau, aABA, MeCys, 0.716; Thr, bAiBA, MeCys, 0.716; Trp, HyPro, MeCys, 0.716; Tyr, MeCys, N6-AcLys, 0.716; aABA, bAiBA, MeCys, 0.716; aAiBA, MeCys, Pipecolic acid, 0.716; ADMA, MeCys, Thioproline, 0.716; bAiBA, GABA, MeCys, 0.716; bAiBA, Cystathionine, MeCys, 0.716; bAiBA, MeCys, Sar, 0.716; GABA, MeCys, N8-AcSpd, 0.716; GABA, MeCys, Put, 0.716; HyPro, MeCys, SDMA, 0.716; Kyn, MeCys, Pipecolic acid, 0.716; Cystathionine, MeCys, N8-AcSpd, 0.716; MeCys, N8-AcSpd, PEA, 0.716; MeCys, N8-AcSpd, Sar, 0.716; MeCys, N8-AcSpd, Kyn/BCAA, 0.716; EtOHNH2, Allyl-Cys, Kyn/BCAA, 0.715; Arg, Allyl-Cys, MeCys, 0.715; Gln, Allyl-Cys, MeCys, 0.715; Cys2, Gln, MeCys, 0.715; Cys2, Met, MeCys, 0.715; Cys2, Ser, ADMA, 0.715; Cys2, MeCys, Spd, 0.715; Arg, Gly, Leu, 0.714; Arg, Ile, MeCys, 0.714; Arg, hCit, MeCys, 0.714; Cit, Gly, Orn, 0.714; Cit, Ile, MeCys, 0.714; Cit, Lys, MeCys, 0.714; Gln, MeCys, N6-AcLys, 0.714; Glu, Phe, Ser, 0.714; Gly, hArg, MeCys, 0.714; Gly, MeCys, Sar, 0.714; Gly, MeCys, Kyn/Trp, 0.714; His, Val, MeCys, 0.714; His, bAiBA, MeCys, 0.714; Ile, MeCys, PEA, 0.714; Leu, Phe, aABA, 0.714; Leu, Pro, MeCys, 0.714; Leu, 3-MeHis, MeCys, 0.714; Leu, GABA, MeCys, 0.714; Leu, Kyn, MeCys, 0.714; Leu, MeCys, N6-AcLys, 0.714; Leu, MeCys, Sar, 0.714; Lys, Orn, MeCys, 0.714; Lys, Pro, MeCys, 0.714; Lys, MeCys, PEA, 0.714; Lys, MeCys, Pipecolic acid, 0.714; Lys, MeCys, Thioproline, 0.714; Met, Ser, aAAA, 0.714; Met, Tau, MeCys, 0.714; Phe, Val, hCit, 0.714; Ser, Tau, ADMA, 0.714; Ser, ADMA, hArg, 0.714; Tau, Trp, MeCys, 0.714; Tau, hArg, MeCys, 0.714; Trp, 1-MeHis, MeCys, 0.714; Trp, MeCys, N6-AcLys, 0.714; Tyr, 1-MeHis, MeCys, 0.714; Val, hArg, MeCys, 0.714; Val, MeCys, Thioproline, 0.714; 1-MeHis, aAAA, MeCys, 0.714; 1-MeHis, MeCys, Thioproline, 0.714; bAiBA, MeCys, Pipecolic acid, 0.714; GABA, MeCys, N6-AcLys, 0.714; MeCys, N6-AcLys, Kyn/Trp, 0.714; Met, Allyl-Cys, MeCys, 0.714; Ser, Allyl-Cys, Pipecolic acid, 0.714; Allyl-Cys, Cystathionine, MeCys, 0.714; EtOHNH2, Leu, bAiBA, 0.714; EtOHNH2, Ser, GABA, 0.714; Cys2, Gly, ADMA, 0.714; Cys2, Thr, MeCys, 0.714; Cys2, aAAA, MeCys, 0.714; Ala, Orn, MeCys, 0.713; Arg, Lys, MeCys, 0.713; Asn, Met, MeCys, 0.713


; Glu, Gly, Pro, 0.713; Glu, Gly, Kyn, 0.713; Gly, Cystathionine, MeCys, 0.713; Gly, MeCys, Thioproline, 0.713; His, MeCys, N6-AcLys, 0.713; Ile, hArg, MeCys, 0.713; Leu, Phe, hArg, 0.713; Leu, MeCys, SDMA, 0.713; Leu, MeCys, Thioproline, 0.713; Lys, MeCys, SDMA, 0.713; Phe, bAiBA, MeCys, 0.713; Pro, hCit, MeCys, 0.713; Ser, ADMA, Kyn, 0.713; Ser, ADMA, PEA, 0.713; Tau, Thr, MeCys, 0.713; Thr, Kyn, MeCys, 0.713; Val, MeCys, PEA, 0.713; 1-MeHis, 3-MeHis, MeCys, 0.713; aAiBA, MeCys, PEA, 0.713; bAiBA, MeCys, PEA, 0.713; aABA, Allyl-Cys, MeCys, 0.712; Arg, MeCys, N6-AcLys, 0.712; Asn, HyPro, MeCys, 0.712; Asn, MeCys, N8-AcSpd, 0.712; Cit, hCit, MeCys, 0.712; Gln, 1-MeHis, MeCys, 0.712; Gln, HyPro, MeCys, 0.712; Glu, Ser, Pipecolic acid, 0.712; Glu, MeCys, Kyn/Trp, 0.712; Gly, GABA, MeCys, 0.712; His, Leu, MeCys, 0.712; Ile, Kyn, MeCys, 0.712; Leu, Phe, Tyr, 0.712; Lys, Ser, ADMA, 0.712; Lys, Thr, MeCys, 0.712; Met, MeCys, N6-AcLys, 0.712; Orn, Pro, MeCys, 0.712; Orn, MeCys, Spd, 0.712; Pro, Val, MeCys, 0.712; Pro, HyPro, MeCys, 0.712; Ser, Thr, ADMA, 0.712; Ser, 1-MeHis, ADMA, 0.712; Val, Kyn, MeCys, 0.712; 3-MeHis, hCit, MeCys, 0.712; 3-MeHis, MeCys, N6-AcLys, 0.712; aAAA, Cystathionine, MeCys, 0.712; aAAA, MeCys, N6-AcLys, 0.712; bAiBA, MeCys, Kyn/BCAA, 0.712; hArg, MeCys, N6-AcLys, 0.712; Hypotaurine, HyPro, MeCys, 0.712; Kyn, MeCys, Sar, 0.712; MeCys, N6-AcLys, Sar, 0.712; MeCys, N6-AcLys, Kyn/BCAA, 0.712; Cys2, MeCys, SDMA, 0.712; Ala, HyPro, MeCys, 0.711; Asn, Thr, MeCys, 0.711; Cit, Glu, Gly, 0.711; Cit, bAiBA, MeCys, 0.711; Glu, Gly, Phe, 0.711; Glu, Gly, Trp, 0.711; Glu, Gly, aABA, 0.711; Glu, Met, Ser, 0.711; Gly, Val, aAiBA, 0.711; His, HyPro, MeCys, 0.711; Ile, Lys, MeCys, 0.711; Ile, MeCys, Put, 0.711; Met, 1-MeHis, MeCys, 0.711; Phe, 1-MeHis, MeCys, 0.711; Ser, ADMA, Spd, 0.711; Tau, MeCys, Sar, 0.711; Thr, hArg, MeCys, 0.711; Thr, MeCys, Put, 0.711; Trp, bAiBA, MeCys, 0.711; Tyr, bAiBA, MeCys, 0.711; Val, MeCys, Kyn/BCAA, 0.711; aABA, MeCys, Sar, 0.711; aAAA, MeCys, Pipecolic acid, 0.711; bAiBA, Hypotaurine, MeCys, 0.711; GABA, HyPro, MeCys, 0.711; hArg, MeCys, Pipecolic acid, 0.711; hCit, Hypotaurine, MeCys, 0.711; HyPro, MeCys, Kyn/BCAA, 0.711; Kyn, MeCys, N6-AcLys, 0.711; Kyn, MeCys, PEA, 0.711; Cystathionine, MeCys, N6-AcLys, 0.711; MeCys, N6-AcLys, Thioproline, 0.711; MeCys, N8-AcSpd, Thioproline, 0.711; Cys2, Orn, bAiBA, 0.711; Orn, Allyl-Cys, Pipecolic acid, 0.711; Allyl-Cys, MeCys, Put, 0.711; Arg, Gly, MeCys, 0.71; Arg, Leu, Phe, 0.71; Gln, Gly, Orn, 0.71; Glu, Gly, Hypotaurine, 0.71; Glu, Gly, N8-AcSpd, 0.71; Gly, MeCys, Spd, 0.71; His, aABA, MeCys, 0.71; Ile, 3-MeHis, MeCys, 0.71; Ile, MeCys, N6-AcLys, 0.71; Lys, MeCys, Spd, 0.71; Orn, Pro, aAiBA, 0.71; Orn, Ser, aAiBA, 0.71; Orn, 3-MeHis, MeCys, 0.71; Pro, Ser, ADMA, 0.71; Pro, MeCys, Pipecolic acid, 0.71; Ser, Tyr, ADMA, 0.71; Ser, hCit, Pipecolic acid, 0.71; Tau, Tyr, MeCys, 0.71; Tau, GABA, MeCys, 0.71; Thr, 3-MeHis, MeCys, 0.71; Trp, aABA, MeCys, 0.71; Val, Hypotaurine, MeCys, 0.71; 3-MeHis, aABA, MeCys, 0.71; GABA, hCit, MeCys, 0.71; hArg, HyPro, MeCys, 0.71; hCit, Kyn, MeCys, 0.71; hCit, MeCys, PEA, 0.71; hCit, MeCys, Kyn/Trp, 0.71; HyPro, Cystathionine, MeCys, 0.71; Cys2, Lys, aABA, 0.71; Cys2, Orn, Tyr, 0.71; Asn, Allyl-Cys, MeCys, 0.709; Ser, ADMA, Allyl-Cys, 0.709; Allyl-Cys, GABA, MeCys, 0.709; Allyl-Cys, MeCys, Thioproline, 0.709; Allyl-Cys, MeCys, Kyn/BCAA, 0.709; Arg, bAiBA, MeCys, 0.709; Cit, HyPro, MeCys, 0.709; Gln, aAiBA, MeCys, 0.709; Glu, Gly, GABA, 0.709; Glu, Gly, N6-AcLys, 0.709; Glu, Gly, Spd, 0.709; Glu, Gly, Thioproline, 0.709; Glu, Gly, Kyn/Trp, 0.709; Gly, Val, ADMA, 0.709; Gly, aABA, MeCys, 0.709; His, Tau, MeCys, 0.709; Leu, Phe, aAAA, 0.709; Leu, Ser, Cystathionine, 0.709; Leu, Trp, MeCys, 0.709; Lys, MeCys, N6-AcLys, 0.709; Lys, MeCys, Kyn/BCAA, 0.709; Met, hCit, MeCys, 0.709; Pro, bAiBA, MeCys, 0.709; Ser, Val, Cystathionine, 0.709; Ser, aAiBA, hCit, 0.709; Ser, ADMA, Hypotaurine, 0.709; Ser, bAiBA, Kyn, 0.709; Tau, MeCys, SDMA, 0.709; Val, MeCys, Spd, 0.709; 1-MeHis, MeCys, Kyn/BCAA, 0.709; ADMA, bAiBA, HyPro, 0.709; EtOHNH2, Gly, Leu, 0.708; EtOHNH2, Gly, MeCys, 0.708; EtOHNH2, Orn, Kyn/BCAA, 0.708; EtOHNH2, Ser, MeCys, 0.708; EtOHNH2, Val, MeCys, 0.708; EtOHNH2, aAiBA, Kyn, 0.708; Cys2, Glu, Met, 0.708; Cys2, ADMA, SDMA, 0.708; EtOHNH2, 3-hKyn, Kyn/BCAA, 0.708; Ala, Allyl-Cys, MeCys, 0.708; Cit, Allyl-Cys, MeCys, 0.708; Glu, Gly, Tyr, 0.708; Glu, Gly, Val, 0.708; Glu, Gly, hArg, 0.708; Glu, Gly, PEA, 0.708; Glu, Ser, hCit, 0.708; Gly, ADMA, Put, 0.708; Gly, ADMA, Kyn/Trp, 0.708; Gly, MeCys, PEA, 0.708; Ile, Thr, MeCys, 0.708; Ile, Hypotaurine, MeCys, 0.708; Ile, MeCys, Kyn/Trp, 0.708; Leu, Phe, hCit, 0.708; Leu, MeCys, Kyn/Trp, 0.708; Lys, Trp, MeCys, 0.708; Lys, Hypotaurine, MeCys, 0.708; Met, MeCys, Pipecolic acid, 0.708; Orn, hCit, Cystathionine, 0.708; Phe, hCit, MeCys, 0.708; Pro, Thr, MeCys, 0.708; Pro, MeCys, Sar, 0.708; Ser, hCit, Put, 0.708; Ser, Cystathionine, Put, 0.708; Tau, 3-MeHis, MeCys, 0.708; Tau, MeCys, Kyn/Trp, 0.708; Trp, 3-MeHis, MeCys, 0.708; Tyr, HyPro, MeCys, 0.708; ADMA, bAiBA, N8-AcSpd, 0.708; hCit, MeCys, Put, 0.708; Hypotaurine, MeCys, N6-AcLys, 0.708; HyPro, MeCys, Spd, 0.708; HyPro, MeCys, Thioproline, 0.708; MeCys, N8-AcSpd, Spd, 0.708; MeCys, Put, Sar, 0.708; 3-hKyn, MeCys, Spd, 0.707; Cys2, Orn, ADMA, 0.707; Cys2, Orn, hArg, 0.707; Cys2, aABA, Pipecolic acid, 0.707; Cys2, MeCys, Kyn/Trp, 0.707; Asn, Glu, Gly, 0.707; Asn, hCit, MeCys, 0.707; Gln, Pro, MeCys, 0.707; Gln, MeCys, PEA, 0.707; Glu, Gly, Orn, 0.707; Glu, Gly, Thr, 0.707; Gly, Ser, ADMA, 0.707; Gly, ADMA, N8-AcSpd, 0.707; Gly, hCit, Cystathionine, 0.707; His, Ile, MeCys, 0.707; Ile, Trp, MeCys, 0.707; Ile, MeCys, Sar, 0.707; Lys, 3-MeHis, MeCys, 0.707; Lys, Cystathionine, MeCys, 0.707; Met, bAiBA, MeCys, 0.707; Met, HyPro, MeCys, 0.707; Orn, Phe, aAiBA, 0.707; Orn, Phe, hCit, 0.707; Orn, Phe, N6-AcLys, 0.707; Orn, Phe, Kyn/BCAA, 0.707; Phe, Ser, Trp, 0.707; Phe, Tau, MeCys, 0.707; Pro, MeCys, PEA, 0.707; Trp, MeCys, Kyn/Trp, 0.707; ADMA, bAiBA, N6-AcLys, 0.707; hArg, MeCys, N8-AcSpd, 0.707; HyPro, MeCys, Put, 0.707; Kyn, MeCys, SDMA, 0.707; EtOHNH2, Gly, Orn, 0.706; EtOHNH2, Gly, Val, 0.706; EtOHNH2, Gly, Cystathionine, 0.706; EtOHNH2, aAiBA, Kyn/Trp, 0.706; EtOHNH2, Put, Kyn/BCAA, 0.706; EtOHNH2, Thioproline, Kyn/BCAA, 0.706; Cys2, Orn, Cystathionine, 0.706; Arg, Orn, Phe, 0.706; Arg, Ser, Val, 0.706; Asn, Pro, MeCys, 0.706; Cit, Gly, Val, 0.706; Glu, Gly, Ser, 0.706; Glu, Gly, Tau, 0.706; Glu, Gly, 3-MeHis, 0.706; Glu, Gly, aAiBA, 0.706; Glu, Gly, SDMA, 0.706; Gly, Leu, Pipecolic acid, 0.706; Ile, Leu, Ser, 0.706; Ile, Met, Orn, 0.706; Ile, MeCys, SDMA, 0.706; Ile, MeCys, Thioproline, 0.706; Leu, Phe, N6-AcLys, 0.706; Leu, MeCys, Spd, 0.706; Met, Orn, Ser, 0.706; Orn, Ser, ADMA, 0.706; Phe, aAAA, MeCys, 0.706; Ser, Val, Pipecolic acid, 0.706; Ser, aAAA, Cystathionine, 0.706; Thr, aABA, MeCys, 0.706; Thr, aAAA, MeCys, 0.706; HyPro, MeCys, Kyn/Trp, 0.706; Ala, Val, MeCys, 0.706; Tau, Cystathionine, MeCys, 0.706; Thr, MeCys, Sar, 0.706; 3-MeHis, Cystathionine, MeCys, 0.706; aABA, MeCys, Pipecolic acid, 0.706; Orn, Phe, Allyl-Cys, 0.705; Ala, Leu, MeCys, 0.704; Ala, Lys, MeCys, 0.704; Ala, Tau, MeCys, 0.704; Ala, MeCys, N6-AcLys, 0.704; Arg, aAiBA, MeCys, 0.704; Asn, Gly, Val, 0.704; Asn, 3-MeHis, MeCys, 0.704; Cit, Gly, MeCys, 0.704; Cit, Tau, MeCys, 0.704; Cit, 3-MeHis, MeCys, 0.704; Cit, MeCys, N6-AcLys, 0.704; Gln, His, MeCys, 0.704; Glu, Gly, aAAA, 0.704; Gly, Leu, bAiBA, 0.704; Gly, Tyr, Val, 0.704; Ile, Orn, Phe, 0.704; Leu, Phe, aAiBA, 0.704; Lys, MeCys, Put, 0.704; Met, Ser, Trp, 0.704; Orn, Ser, HyPro, 0.704; Ser, Cystathionine, N6-AcLys, 0.704; Tyr, hCit, MeCys, 0.704; 3-MeHis, GABA, MeCys, 0.704; 3-MeHis, hArg, MeCys, 0.704; aABA, Kyn, MeCys, 0.704; aAAA, hArg, MeCys, 0.704; aAAA, MeCys, Sar, 0.704; bAiBA, MeCys, Put, 0.704; hCit, HyPro, MeCys, 0.704; hCit, MeCys, Thioproline, 0.704; Kyn, MeCys, Kyn/BCAA, 0.704; MeCys, Pipecolic acid, Sar, 0.704; Asn, Cys2, ADMA, 0.704; Cys2, Met, ADMA, 0.704; Cys2, ADMA, Cystathionine, 0.704; Cys2, Hypotaurine, MeCys, 0.704; Leu, Met, 3-hKyn, 0.704; Allyl-Cys, MeCys, Kyn/Trp, 0.704; Ala, hCit, MeCys, 0.703; Glu, Gly, Lys, 0.703; Glu, Gly, 1-MeHis, 0.703; Glu, Ser, hArg, 0.703; Gly, Ile, Val, 0.703; Gly, Lys, Pipecolic acid, 0.703; Gly, Orn, Pipecolic acid, 0.703; Gly, ADMA, HyPro, 0.703; Gly, bAiBA, Pipecolic acid, 0.703; Ile, MeCys, Pipecolic acid, 0.703; Ile, MeCys, Spd, 0.703; Leu, Met, Phe, 0.703; Leu, Met, Thr, 0.703; Lys, MeCys, Kyn/Trp, 0.703; Met, Val, ADMA, 0.703; Orn, Phe, HyPro, 0.703; Orn, aAiBA, bAiBA, 0.703; Orn, aAiBA, Cystathionine, 0.703; Ser, Val, hCit, 0.703; Ser, 1-MeHis, Cystathionine, 0.703; Ser, Cystathionine, Pipecolic acid, 0.703; Tau, aAAA, MeCys, 0.703; Trp, MeCys, Sar, 0.703; 3-MeHis, MeCys, Kyn/BCAA, 0.703; aABA, MeCys, PEA, 0.703; EtOHNH2, Ile, Cystathionine, 0.703; EtOHNH2, Ile, MeCys, 0.703; EtOHNH2, Ser, Hypotaurine, 0.703; EtOHNH2, Trp, aAiBA, 0.703; EtOHNH2, GABA, Cystathionine, 0.703; EtOHNH2, hArg, Kyn/BCAA, 0.703; EtOHNH2, Cystathionine, Kyn/BCAA, 0.703; Cys2, Gly, Orn, 0.703; Cys2, Pro, ADMA, 0.703; Ala, Leu, Phe, 0.702; Arg, Glu, Ser, 0.702; Arg, Orn, HyPro, 0.702; Asn, Tau, MeCys, 0.702; Cit, Orn, Cystathionine, 0.702; Gly, Ile, bAiBA, 0.702; His, 3-MeHis, MeCys, 0.702; His, Kyn, MeCys, 0.702; His, MeCys, Put, 0.702; Ile, Pro, MeCys, 0.702; Ile, GABA, MeCys, 0.702; Met, Thr, Val, 0.702; Orn, Phe, Cystathionine, 0.702; Orn, aAiBA, Kyn/BCAA, 0.702; Phe, Val, Pipecolic acid, 0.702; Ser, 3-MeHis, Cystathionine, 0.702; Ser, GABA, hCit, 0.702; Ser, N6-AcLys, Pipecolic acid, 0.702; Thr, Trp, MeCys, 0.702; Thr, ADMA, bAiBA, 0.702; Thr, GABA, MeCys, 0.702; Trp, aAiBA, MeCys, 0.702; 3-MeHis, MeCys, Put, 0.702; 3-MeHis, MeCys, Kyn/Trp, 0.702; aABA, aAiBA, MeCys, 0.702; aAAA, MeCys, Kyn/BCAA, 0.702; bAiBA, MeCys, SDMA, 0.702; hCit, Cystathionine, MeCys, 0.702; MeCys, N6-AcLys, Spd, 0.702; MeCys, PEA, Spd, 0.702; EtOHNH2, 3-hKyn, Cystathionine, 0.702; Cys2, Glu, ADMA, 0.702; Cys2, Orn, Ser, 0.702; Cys2, Orn, aAAA, 0.702; Cys2, Orn, hCit, 0.702; Orn, 3-hKyn, bAiBA, 0.701; Arg, Tau, MeCys, 0.701; Arg, Thr, MeCys, 0.701; Gln, hCit, MeCys, 0.701; Glu, Gly, Leu, 0.701; Gly, ADMA


, Cystathionine, 0.701; Gly, hCit, SDMA, 0.701; His, MeCys, Pipecolic acid, 0.701; His, MeCys, Sar, 0.701; Ile, Ser, Cystathionine, 0.701; Leu, Phe, Val, 0.701; Orn, Ser, Hypotaurine, 0.701; Tyr, Kyn, MeCys, 0.701; aAAA, MeCys, SDMA, 0.701; hCit, MeCys, Spd, 0.701; MeCys, PEA, Put, 0.701; Allyl-Cys, MeCys, Pipecolic acid, 0.701; EtOHNH2, Glu, aAiBA, 0.701; EtOHNH2, Glu, MeCys, 0.701; EtOHNH2, Gly, Hypotaurine, 0.701; EtOHNH2, Leu, Ser, 0.701; EtOHNH2, Leu, aABA, 0.701; EtOHNH2, Ser, aAiBA, 0.701; EtOHNH2, Val, aABA, 0.701; EtOHNH2, 3-MeHis, aAiBA, 0.701; EtOHNH2, aABA, hCit, 0.701; EtOHNH2, aAiBA, SDMA, 0.701; EtOHNH2, ADMA, bAiBA, 0.701; EtOHNH2, hArg, MeCys, 0.701; EtOHNH2, Pipecolic acid, Kyn/BCAA, 0.701; Cys2, His, Orn, 0.7; Cys2, Orn, aAiBA, 0.7; Cit, Orn, HyPro, 0.7; Gln, 3-MeHis, MeCys, 0.7; Glu, Gly, Kyn/BCAA, 0.7; Ile, Phe, Ser, 0.7; Ile, aAAA, MeCys, 0.7; Leu, Met, hArg, 0.7; Lys, Met, Ser, 0.7; Met, aABA, MeCys, 0.7; Met, MeCys, PEA, 0.7; Orn, Tyr, N6-AcLys, 0.7; Phe, Ser, hCit, 0.7; Ser, Trp, bAiBA, 0.7; Ser, aABA, Pipecolic acid, 0.7; Ser, HyPro, Cystathionine, 0.7; Tau, MeCys, PEA, 0.7; Thr, MeCys, PEA, 0.7; Trp, Kyn, MeCys, 0.7; Trp, MeCys, PEA, 0.7; Kyn, Cystathionine, MeCys, 0.7; MeCys, Put, Kyn/BCAA, 0.7; Leu, Phe, Allyl-Cys, 0.699; Orn, Allyl-Cys, Cystathionine, 0.699; Thr, Allyl-Cys, Pipecolic acid, 0.699; Cys2, Gln, aABA, 0.699; Cys2, Orn, Hypotaurine, 0.699; Cys2, aABA, hCit, 0.699; Cys2, aABA, Hypotaurine, 0.699; Cys2, ADMA, aAAA, 0.699; Cys2, ADMA, hArg, 0.699; Cys2, ADMA, Hypotaurine, 0.699; Ala, ADMA, bAiBA, 0.699; Asn, Leu, Phe, 0.699; Cit, Orn, aAiBA, 0.699; Cit, MeCys, Pipecolic acid, 0.699; Gln, MeCys, Sar, 0.699; Glu, Gly, His, 0.699; Glu, Ser, aAiBA, 0.699; Gly, Met, Orn, 0.699; Gly, Orn, SDMA, 0.699; Gly, aAiBA, Pipecolic acid, 0.699; His, Leu, Phe, 0.699; His, Trp, MeCys, 0.699; His, MeCys, PEA, 0.699; Ile, Ser, Val, 0.699; Ile, MeCys, Kyn/BCAA, 0.699; Leu, Lys, Phe, 0.699; Leu, Phe, 3-MeHis, 0.699; Lys, Kyn, MeCys, 0.699; Met, Ser, hCit, 0.699; Met, Thr, MeCys, 0.699; Met, aAAA, MeCys, 0.699; Orn, aAiBA, hCit, 0.699; Orn, aAiBA, N6-AcLys, 0.699; Orn, ADMA, Cystathionine, 0.699; Phe, Val, aABA, 0.699; Phe, Val, aAiBA, 0.699; Phe, ADMA, Pipecolic acid, 0.699; Ser, Trp, Pipecolic acid, 0.699; Ser, Tyr, hCit, 0.699; Ser, aABA, N6-AcLys, 0.699; Ser, Hypotaurine, Cystathionine, 0.699; Thr, MeCys, Kyn/Trp, 0.699; Thr, MeCys, Kyn/BCAA, 0.699; Tyr, aABA, MeCys, 0.699; Tyr, MeCys, Pipecolic acid, 0.699; aABA, MeCys, SDMA, 0.699; aABA, MeCys, Kyn/BCAA, 0.699; ADMA, bAiBA, Kyn/BCAA, 0.699; ADMA, Cystathionine, Pipecolic acid, 0.699; aAAA, MeCys, PEA, 0.699; GABA, MeCys, Pipecolic acid, 0.699; Hypotaurine, MeCys, Spd, 0.699; MeCys, PEA, Sar, 0.699; MeCys, Pipecolic acid, SDMA, 0.699; EtOHNH2, 3-hKyn, bAiBA, 0.699; Arg, EtOHNH2, Kyn/BCAA, 0.698; EtOHNH2, Phe, aAiBA, 0.698; EtOHNH2, Ser, Kyn/BCAA, 0.698; EtOHNH2, Tyr, Kyn/BCAA, 0.698; Ala, Glu, Gly, 0.698; Arg, Gln, MeCys, 0.698; Gln, aAAA, MeCys, 0.698; Glu, Gly, Ile, 0.698; Glu, Ser, bAiBA, 0.698; Gly, Orn, Hypotaurine, 0.698; His, Met, Orn, 0.698; Leu, Phe, bAiBA, 0.698; Leu, Phe, Put, 0.698; Lys, Met, Orn, 0.698; Orn, 1-MeHis, Cystathionine, 0.698; Orn, aABA, Cystathionine, 0.698; Ser, aABA, Kyn, 0.698; Ser, HyPro, N8-AcSpd, 0.698; Tau, MeCys, Thioproline, 0.698; Tau, MeCys, Kyn/BCAA, 0.698; Thr, Tyr, MeCys, 0.698; Thr, Cystathionine, MeCys, 0.698; Tyr, 3-MeHis, MeCys, 0.698; 3-MeHis, MeCys, Thioproline, 0.698; aAiBA, Hypotaurine, MeCys, 0.698; GABA, Kyn, MeCys, 0.698; hArg, Kyn, MeCys, 0.698; MeCys, Put, Spd, 0.698; Cys2, Orn, GABA, 0.698; Cys2, Orn, Put, 0.698; Cys2, Orn, Thioproline, 0.698; Cys2, ADMA, Thioproline, 0.698; EtOHNH2, Ser, Allyl-Cys, 0.697; Ala, Thr, MeCys, 0.697; Cit, Leu, Phe, 0.697; Cit, Orn, bAiBA, 0.697; Gln, Met, MeCys, 0.697; Gln, Trp, MeCys, 0.697; Gln, Tyr, MeCys, 0.697; Gln, MeCys, Kyn/BCAA, 0.697; Glu, Ser, Kyn/Trp, 0.697; Gly, Ile, Cystathionine, 0.697; Gly, Val, 3-MeHis, 0.697; Gly, ADMA, Hypotaurine, 0.697; Leu, Phe, Pro, 0.697; Leu, Phe, Hypotaurine, 0.697; Orn, Val, aAiBA, 0.697; Orn, Cystathionine, N8-AcSpd, 0.697; Orn, Cystathionine, Thioproline, 0.697; Phe, Pro, Val, 0.697; Pro, Ser, HyPro, 0.697; Ser, Trp, hCit, 0.697; Ser, Val, hArg, 0.697; Ser, aAiBA, N6-AcLys, 0.697; Ser, aAAA, Pipecolic acid, 0.697; Ser, hArg, hCit, 0.697; Ser, HyPro, Pipecolic acid, 0.697; Thr, ADMA, Put, 0.697; Trp, aAAA, MeCys, 0.697; 3-MeHis, aAAA, MeCys, 0.697; 3-MeHis, Kyn, MeCys, 0.697; 3-MeHis, MeCys, PEA, 0.697; aABA, MeCys, Put, 0.697; aABA, MeCys, Kyn/Trp, 0.697; ADMA, N8-AcSpd, Pipecolic acid, 0.697; aAiBA, Allyl-Cys, MeCys, 0.697; Arg, Cys2, ADMA, 0.696; Cit, Cys2, Orn, 0.696; Cys2, Glu, Phe, 0.696; Cys2, Glu, aAAA, 0.696; Cys2, Orn, Sar, 0.696; Cys2, Trp, ADMA, 0.696; Cys2, aAiBA, ADMA, 0.696; Arg, Ser, hCit, 0.696; Asn, Orn, Phe, 0.696; Asn, MeCys, Pipecolic acid, 0.696; Cit, Gly, ADMA, 0.696; Gln, Ser, hCit, 0.696; Gln, aABA, MeCys, 0.696; Gln, MeCys, Pipecolic acid, 0.696; Glu, Ser, aABA, 0.696; Gly, Ile, Leu, 0.696; Gly, Ile, Pipecolic acid, 0.696; Gly, ADMA, hCit, 0.696; Gly, ADMA, N6-AcLys, 0.696; Gly, bAiBA, Kyn, 0.696; Ile, Ser, Pipecolic acid, 0.696; Leu, Phe, PEA, 0.696; Leu, Phe, Thioproline, 0.696; Lys, Orn, aAiBA, 0.696; Met, Phe, MeCys, 0.696; Met, 3-MeHis, MeCys, 0.696; Orn, Phe, 1-MeHis, 0.696; Orn, Ser, Trp, 0.696; Orn, Ser, hArg, 0.696; Orn, Ser, N6-AcLys, 0.696; Orn, aABA, aAiBA, 0.696; Orn, Hypotaurine, Cystathionine, 0.696; Phe, Pro, MeCys, 0.696; Phe, 3-MeHis, MeCys, 0.696; Pro, aAAA, MeCys, 0.696; Pro, Cystathionine, MeCys, 0.696; Ser, Tyr, Cystathionine, 0.696; Ser, Val, aABA, 0.696; Ser, bAiBA, Pipecolic acid, 0.696; Ser, hCit, SDMA, 0.696; Thr, MeCys, Thioproline, 0.696; Trp, Cystathionine, MeCys, 0.696; Tyr, aAAA, MeCys, 0.696; Val, ADMA, Cystathionine, 0.696; 3-MeHis, Hypotaurine, MeCys, 0.696; aAAA, MeCys, Thioproline, 0.696; aAAA, MeCys, Kyn/Trp, 0.696; Kyn, MeCys, Put, 0.696; Kyn, MeCys, Thioproline, 0.696; EtOHNH2, Leu, Pro, 0.695; EtOHNH2, Met, Kyn/BCAA, 0.695; EtOHNH2, Orn, Phe, 0.695; EtOHNH2, aAiBA, hCit, 0.695; EtOHNH2, hCit, MeCys, 0.695; EtOHNH2, Kyn, MeCys, 0.695; Ser, 3-hKyn, ADMA, 0.695; Gly, Allyl-Cys, Pipecolic acid, 0.695; Orn, Ser, Allyl-Cys, 0.695; Orn, Allyl-Cys, hCit, 0.695; Ser, Trp, Allyl-Cys, 0.695; Ala, Cys2, Orn, 0.695; Ala, Cys2, ADMA, 0.695; Arg, Cys2, Orn, 0.695; Asn, Cys2, Orn, 0.695; Cit, Cys2, ADMA, 0.695; Cys2, Gln, ADMA, 0.695; Cys2, Orn, Kyn, 0.695; Cys2, Orn, Spd, 0.695; Cys2, aAiBA, bAiBA, 0.695; Ala, Ile, MeCys, 0.694; Arg, 3-MeHis, MeCys, 0.694; Arg, aAAA, MeCys, 0.694; Arg, MeCys, Pipecolic acid, 0.694; Asn, Ser, Pipecolic acid, 0.694; Asn, aAAA, MeCys, 0.694; Cit, Ser, Kyn, 0.694; Cit, Thr, MeCys, 0.694; Gln, Gly, Val, 0.694; Gln, Leu, Phe, 0.694; Glu, Gly, HyPro, 0.694; Glu, Orn, Cystathionine, 0.694; Glu, Ser, Thr, 0.694; Glu, Ser, Kyn, 0.694; Gly, Leu, ADMA, 0.694; Gly, Trp, Cystathionine, 0.694; Gly, Val, aABA, 0.694; Leu, Phe, HyPro, 0.694; Leu, Phe, Spd, 0.694; Met, Orn, N6-AcLys, 0.694; Met, Ser, Cystathionine, 0.694; Orn, Phe, bAiBA, 0.694; Orn, Phe, SDMA, 0.694; Orn, 3-MeHis, Cystathionine, 0.694; Orn, aAiBA, N8-AcSpd, 0.694; Orn, Cystathionine, Put, 0.694; Phe, Thr, MeCys, 0.694; Phe, Tyr, MeCys, 0.694; Phe, Val, Cystathionine, 0.694; Phe, aABA, MeCys, 0.694; Phe, MeCys, Pipecolic acid, 0.694; Pro, aABA, MeCys, 0.694; Ser, Trp, Cystathionine, 0.694; Ser, hCit, N8-AcSpd, 0.694; Thr, MeCys, SDMA, 0.694; Trp, GABA, MeCys, 0.694; Trp, MeCys, Pipecolic acid, 0.694; aABA, Cystathionine, MeCys, 0.694; aAiBA, MeCys, Put, 0.694; aAAA, Kyn, MeCys, 0.694; hArg, MeCys, PEA, 0.694; MeCys, PEA, Thioproline, 0.694; Cys2, Orn, Val, 0.694; Cys2, Tyr, ADMA, 0.694; Cys2, Val, aABA, 0.694; Cys2, 3-MeHis, ADMA, 0.694; Arg, Leu, HyPro, 0.693; Arg, Orn, Ser, 0.693; Asn, Kyn, MeCys, 0.693; Cit, Glu, Ser, 0.693; Cit, Ser, PEA, 0.693; Cit, aABA, MeCys, 0.693; Gln, Met, Orn, 0.693; Gln, Orn, aAiBA, 0.693; Gly, Orn, hCit, 0.693; Gly, Pro, Val, 0.693; Gly, aAAA, Cystathionine, 0.693; Lys, Ser, aABA, 0.693; Met, Orn, Phe, 0.693; Met, Orn, Pro, 0.693; Met, Orn, aAiBA, 0.693; Met, Orn, aAAA, 0.693; Met, Orn, Put, 0.693; Met, MeCys, Put, 0.693; Met, MeCys, Sar, 0.693; Orn, Thr, Cystathionine, 0.693; Orn, Tyr, hCit, 0.693; Orn, hArg, Cystathionine, 0.693; Orn, HyPro, N8-AcSpd, 0.693; Orn, Kyn, Cystathionine, 0.693; Phe, Ser, Cystathionine, 0.693; Phe, Kyn, MeCys, 0.693; Phe, Kyn, Kyn/BCAA, 0.693; Pro, Trp, MeCys, 0.693; Ser, Tau, Cystathionine, 0.693; Ser, Trp, aAiBA, 0.693; Ser, Trp, HyPro, 0.693; Ser, Val, aAiBA, 0.693; Ser, Val, bAiBA, 0.693; Ser, Cystathionine, N8-AcSpd, 0.693; Ser, Pipecolic acid, Put, 0.693; Thr, hCit, Cystathionine, 0.693; Trp, Tyr, MeCys, 0.693; Tyr, hArg, MeCys, 0.693; aAiBA, MeCys, Sar, 0.693; ADMA, HyPro, N8-AcSpd, 0.693; ADMA, HyPro, Pipecolic acid, 0.693; Kyn, MeCys, Kyn/Trp, 0.693; MeCys, Pipecolic acid, Put, 0.693; MeCys, Pipecolic acid, Thioproline, 0.693; MeCys, Pipecolic acid, Kyn/Trp, 0.693; Cys2, EtOHNH2, aABA, 0.693; EtOHNH2, Gly, Lys, 0.693; EtOHNH2, His, MeCys, 0.693; EtOHNH2, Ile, Leu, 0.693; EtOHNH2, Orn, Tyr, 0.693; EtOHNH2, Orn, GABA, 0.693; EtOHNH2, Pro, MeCys, 0.693; EtOHNH2, Ser, Thr, 0.693; EtOHNH2, Trp, Kyn/BCAA, 0.693; EtOHNH2, aAiBA, PEA, 0.693; EtOHNH2, aAiBA, Kyn/BCAA, 0.693; EtOHNH2, HyPro, MeCys, 0.693; EtOHNH2, MeCys, Put, 0.693; EtOHNH2, Kyn/Trp, Kyn/BCAA, 0.693; Cys2, Glu, N8-AcSpd, 0.692; Cys2, His, ADMA, 0.692; Cys2, Orn, N8-AcSpd, 0.692; Cys2, Tyr, aABA, 0.692; Cys2, aABA, Kyn, 0.692; Cys2, aABA, Thioproline, 0.692; Cys2, ADMA, Allyl-Cys, 0.692; Cys2, ADMA, Sar, 0.692; Cys2, ADMA, Spd, 0.692; Cys2, ADMA, Kyn/Trp, 0.692; Cys2, bAiBA, HyPro, 0.692; Orn, Pro, Allyl-Cys, 0.692; Ser, 3-hKyn, bAiBA, 0.692; Arg, MeCys, Sar, 0.692; Cit, Ser, Cystathionine, 0.692; Cit, Trp, MeCys, 0.692; Cit, MeCys, PEA, 0.692; Glu, Orn, Phe, 0.692; Gly, Orn, Val, 0.692; Gly, Tau, Hypotaurine, 0.692; Gly, Val, hArg, 0.692; Gly, Val, Hypotaurine, 0.692; Gly, 3-MeHis, ADMA, 0.692; His, hArg, MeCys, 0.692; Leu, Phe, Kyn/BCAA, 0.692; Leu, Ser, hCit, 0.692; Leu, ADMA, bAiBA, 0.692; Lys, Orn, Phe, 0.692; Met, Orn, Trp, 0.692; Met, Orn, Cystathionine, 0.692; Met, Orn, Spd, 0.692; Met, Kyn, MeCys, 0.692; Orn, Val, Cystathionine, 0.692; Orn, aAiBA, Sar, 0.692; Orn, Cystathionine, Pi


pecolic acid, 0.692; Phe, Ser, Kyn, 0.692; Phe, Val, Put, 0.692; Phe, aAiBA, MeCys, 0.692; Phe, MeCys, PEA, 0.692; Phe, MeCys, Put, 0.692; Pro, MeCys, Kyn/BCAA, 0.692; Ser, hArg, Pipecolic acid, 0.692; Ser, hCit, Sar, 0.692; Trp, MeCys, Put, 0.692; Trp, MeCys, SDMA, 0.692; Tyr, MeCys, PEA, 0.692; aABA, hArg, MeCys, 0.692; aAiBA, ADMA, bAiBA, 0.692; aAiBA, hArg, MeCys, 0.692; aAiBA, Cystathionine, MeCys, 0.692; aAiBA, MeCys, Kyn/BCAA, 0.692; ADMA, hCit, SDMA, 0.692; GABA, MeCys, PEA, 0.692; hArg, MeCys, SDMA, 0.692; Hypotaurine, MeCys, Put, 0.692; MeCys, Pipecolic acid, Kyn/BCAA, 0.692; Ala, Orn, aAiBA, 0.691; Ala, Pro, MeCys, 0.691; Arg, Ser, Cystathionine, 0.691; Asn, MeCys, Put, 0.691; Cit, Gln, MeCys, 0.691; Gln, Orn, Cystathionine, 0.691; Gln, Kyn, MeCys, 0.691; Glu, Orn, Ser, 0.691; Gly, Orn, ADMA, 0.691; Gly, Orn, HyPro, 0.691; Gly, Cystathionine, N6-AcLys, 0.691; Gly, Cystathionine, Pipecolic acid, 0.691; His, Orn, aAiBA, 0.691; His, Ser, Cystathionine, 0.691; His, Thr, MeCys, 0.691; Leu, Orn, aAiBA, 0.691; Met, Orn, 1-MeHis, 0.691; Met, Orn, bAiBA, 0.691; Met, Orn, Kyn, 0.691; Orn, Phe, Tyr, 0.691; Orn, Phe, N8-AcSpd, 0.691; Orn, Phe, Sar, 0.691; Orn, Phe, Kyn/Trp, 0.691; Orn, Trp, aAiBA, 0.691; Orn, aAiBA, HyPro, 0.691; Orn, aAiBA, Kyn/Trp, 0.691; Orn, Cystathionine, Kyn/Trp, 0.691; Phe, Val, bAiBA, 0.691; Pro, Ser, Cystathionine, 0.691; Pro, 3-MeHis, MeCys, 0.691; Pro, Kyn, MeCys, 0.691; Pro, MeCys, SDMA, 0.691; Ser, Thr, Cystathionine, 0.691; Ser, Thr, Pipecolic acid, 0.691; Ser, hCit, N6-AcLys, 0.691; Ser, hCit, Kyn/Trp, 0.691; Ser, Cystathionine, Thioproline, 0.691; Trp, hArg, MeCys, 0.691; Val, ADMA, bAiBA, 0.691; ADMA, GABA, HyPro, 0.691; ADMA, hCit, Cystathionine, 0.691; ADMA, Pipecolic acid, SDMA, 0.691; aAAA, GABA, MeCys, 0.691; aAAA, MeCys, Put, 0.691; Cystathionine, MeCys, PEA, 0.691; Cystathionine, MeCys, Put, 0.691; Cystathionine, MeCys, Sar, 0.691; MeCys, PEA, Kyn/Trp, 0.691; Cys2, Gln, Orn, 0.691; Cys2, Glu, Cystathionine, 0.691; Cys2, Pro, aABA, 0.691; Cys2, Trp, aABA, 0.691; Cys2, Val, ADMA, 0.691; Cys2, aABA, Cystathionine, 0.691; Orn, Allyl-Cys, HyPro, 0.691; Ser, 3-hKyn, Pipecolic acid, 0.691; 3-hKyn, ADMA, bAiBA, 0.691; Cit, EtOHNH2, aAiBA, 0.69; Cit, EtOHNH2, Kyn/BCAA, 0.69; EtOHNH2, Leu, aAiBA, 0.69; EtOHNH2, Lys, aABA, 0.69; EtOHNH2, Orn, Ser, 0.69; EtOHNH2, Orn, aABA, 0.69; EtOHNH2, 1-MeHis, MeCys, 0.69; EtOHNH2, 3-MeHis, Kyn/BCAA, 0.69; EtOHNH2, aABA, aAiBA, 0.69; EtOHNH2, aABA, bAiBA, 0.69; EtOHNH2, aAiBA, aAAA, 0.69; Arg, Lys, Ser, 0.69; Arg, aABA, MeCys, 0.69; Arg, MeCys, Put, 0.69; Asn, His, MeCys, 0.69; Asn, Orn, aAiBA, 0.69; Asn, Tyr, MeCys, 0.69; Asn, aABA, MeCys, 0.69; Cit, Orn, ADMA, 0.69; Cit, Ser, 1-MeHis, 0.69; Cit, Ser, aAiBA, 0.69; Cit, ADMA, bAiBA, 0.69; Cit, aAAA, MeCys, 0.69; Cit, MeCys, SDMA, 0.69; Glu, Ser, N6-AcLys, 0.69; Gly, Lys, ADMA, 0.69; Gly, Orn, Put, 0.69; Gly, Orn, Kyn/BCAA, 0.69; Gly, ADMA, hArg, 0.69; Gly, aAAA, bAiBA, 0.69; His, Ser, hCit, 0.69; Leu, Phe, Kyn/Trp, 0.69; Met, Orn, Tyr, 0.69; Orn, Pro, Cystathionine, 0.69; Orn, Tau, Cystathionine, 0.69; Orn, ADMA, SDMA, 0.69; Orn, hArg, HyPro, 0.69; Orn, HyPro, Cystathionine, 0.69; Orn, Cystathionine, Spd, 0.69; Phe, ADMA, hCit, 0.69; Phe, MeCys, Kyn/Trp, 0.69; Pro, Ser, hCit, 0.69; Ser, Thr, hCit, 0.69; Ser, bAiBA, Cystathionine, 0.69; Ser, hCit, HyPro, 0.69; Ser, hCit, Kyn/BCAA, 0.69; Ser, Kyn, N8-AcSpd, 0.69; Ser, Cystathionine, Kyn/BCAA, 0.69; Ser, Pipecolic acid, Thioproline, 0.69; Tyr, MeCys, Sar, 0.69; Val, Cystathionine, Kyn/Trp, 0.69; aABA, GABA, MeCys, 0.69; aABA, MeCys, Thioproline, 0.69; ADMA, bAiBA, Sar, 0.69; MeCys, PEA, SDMA, 0.69; Cys2, Lys, ADMA, 0.69; Cys2, Orn, Tau, 0.69; Cys2, Orn, HyPro, 0.69; Cys2, ADMA, N6-AcLys, 0.69; Cys2, ADMA, PEA, 0.69; Orn, Allyl-Cys, Thioproline, 0.689; Ala, Gly, Val, 0.689; Ala, Met, Orn, 0.689; Ala, Orn, Phe, 0.689; Ala, Phe, Val, 0.689; Arg, Gly, ADMA, 0.689; Arg, Orn, Cystathionine, 0.689; Arg, Val, HyPro, 0.689; Arg, ADMA, bAiBA, 0.689; Asn, Gly, ADMA, 0.689; Asn, Orn, Cystathionine, 0.689; Asn, Phe, Val, 0.689; Asn, Ser, hCit, 0.689; Asn, aAiBA, MeCys, 0.689; Asn, MeCys, Sar, 0.689; Gln, Gly, Pipecolic acid, 0.689; Gln, ADMA, bAiBA, 0.689; Gln, MeCys, Put, 0.689; Glu, Ser, Val, 0.689; Glu, Ser, HyPro, 0.689; Glu, ADMA, bAiBA, 0.689; Gly, Orn, Phe, 0.689; Gly, Orn, 3-MeHis, 0.689; Gly, Trp, Hypotaurine, 0.689; Gly, aABA, Pipecolic acid, 0.689; Gly, aAiBA, ADMA, 0.689; Gly, Hypotaurine, PEA, 0.689; Gly, Hypotaurine, Pipecolic acid, 0.689; His, Met, MeCys, 0.689; His, Phe, Val, 0.689; His, Pro, MeCys, 0.689; Leu, Phe, Trp, 0.689; Leu, Phe, 1-MeHis, 0.689; Lys, Ser, hArg, 0.689; Orn, Pro, Ser, 0.689; Orn, Tyr, Cystathionine, 0.689; Orn, ADMA, N8-AcSpd, 0.689; Orn, bAiBA, hArg, 0.689; Orn, Cystathionine, PEA, 0.689; Orn, Cystathionine, SDMA, 0.689; Phe, Trp, MeCys, 0.689; Phe, hArg, MeCys, 0.689; Ser, 1-MeHis, Pipecolic acid, 0.689; Ser, aABA, Cystathionine, 0.689; Ser, aAiBA, Cystathionine, 0.689; Ser, hArg, Cystathionine, 0.689; Ser, hCit, Kyn, 0.689; Ser, Hypotaurine, Pipecolic acid, 0.689; Ser, Kyn, Put, 0.689; Trp, MeCys, Thioproline, 0.689; Tyr, MeCys, Put, 0.689; aABA, Hypotaurine, MeCys, 0.689; ADMA, bAiBA, SDMA, 0.689; ADMA, GABA, Pipecolic acid, 0.689; GABA, MeCys, SDMA, 0.689; hArg, MeCys, Put, 0.689; Cys2, Tau, ADMA, 0.688; Cys2, Lys, Orn, 0.688; Cys2, Orn, Thr, 0.688; Cys2, 1-MeHis, ADMA, 0.688; Cys2, aABA, Put, 0.688; Lys, Allyl-Cys, Pipecolic acid, 0.688; Leu, Phe, 3-hKyn, 0.688; Ala, Ser, Pipecolic acid, 0.688; Ala, 3-MeHis, MeCys, 0.688; Ala, MeCys, PEA, 0.688; Arg, His, MeCys, 0.688; Arg, Met, Orn, 0.688; Arg, Orn, aAiBA, 0.688; Arg, Phe, Val, 0.688; Cit, His, MeCys, 0.688; Cit, Ser, 3-MeHis, 0.688; Cit, aAiBA, MeCys, 0.688; Gln, Orn, Tyr, 0.688; Gln, Ser, Pipecolic acid, 0.688; Gln, MeCys, SDMA, 0.688; Glu, Pro, Ser, 0.688; Glu, Ser, Hypotaurine, 0.688; Glu, Ser, Sar, 0.688; Glu, ADMA, N8-AcSpd, 0.688; Gly, Ile, ADMA, 0.688; Gly, Val, hCit, 0.688; Gly, Val, HyPro, 0.688; Gly, Val, Put, 0.688; Gly, HyPro, Pipecolic acid, 0.688; His, GABA, MeCys, 0.688; His, MeCys, Thioproline, 0.688; Lys, Ser, Pipecolic acid, 0.688; Lys, ADMA, bAiBA, 0.688; Met, Orn, 3-MeHis, 0.688; Met, Orn, GABA, 0.688; Met, Orn, hCit, 0.688; Met, Pro, MeCys, 0.688; Met, hArg, MeCys, 0.688; Met, MeCys, SDMA, 0.688; Orn, Ser, aABA, 0.688; Orn, aAiBA, Put, 0.688; Orn, hArg, hCit, 0.688; Phe, Val, Hypotaurine, 0.688; Phe, Val, N6-AcLys, 0.688; Phe, ADMA, bAiBA, 0.688; Phe, GABA, MeCys, 0.688; Phe, MeCys, Thioproline, 0.688; Pro, ADMA, bAiBA, 0.688; Pro, MeCys, Put, 0.688; Ser, Val, HyPro, 0.688; Ser, aAAA, hCit, 0.688; Ser, bAiBA, SDMA, 0.688; Ser, hCit, Hypotaurine, 0.688; Ser, N8-AcSpd, Pipecolic acid, 0.688; Ser, Pipecolic acid, Sar, 0.688; Tyr, MeCys, SDMA, 0.688; 3-MeHis, MeCys, Spd, 0.688; aAiBA, MeCys, Spd, 0.688; ADMA, HyPro, Put, 0.688; ADMA, Cystathionine, N8-AcSpd, 0.688; hArg, MeCys, Sar, 0.688; MeCys, Put, Thioproline, 0.688; Cit, EtOHNH2, Ser, 0.688; EtOHNH2, Leu, Kyn/BCAA, 0.688; EtOHNH2, Met, Orn, 0.688; EtOHNH2, Orn, Kyn, 0.688; EtOHNH2, Pro, Ser, 0.688; EtOHNH2, Ser, ADMA, 0.688; EtOHNH2, Val, aAiBA, 0.688; EtOHNH2, 1-MeHis, bAiBA, 0.688; EtOHNH2, aAiBA, Cystathionine, 0.688; EtOHNH2, ADMA, MeCys, 0.688; EtOHNH2, Cystathionine, MeCys, 0.688; EtOHNH2, MeCys, Sar, 0.688; EtOHNH2, Sar, Kyn/BCAA, 0.688; Cys2, Glu, Ser, 0.687; Cys2, Ile, Orn, 0.687; Cys2, Orn, N6-AcLys, 0.687; Cys2, Orn, PEA, 0.687; Cys2, Orn, Kyn/Trp, 0.687; Cys2, Thr, ADMA, 0.687; Cys2, ADMA, Kyn, 0.687; Cys2, EtOHNH2, Cystathionine, 0.687; Ala, Gly, ADMA, 0.687; Ala, Ser, HyPro, 0.687; Ala, Trp, MeCys, 0.687; Ala, aAAA, MeCys, 0.687; Arg, Ser, Pipecolic acid, 0.687; Arg, Trp, MeCys, 0.687; Arg, MeCys, PEA, 0.687; Asn, Ser, Cystathionine, 0.687; Asn, MeCys, PEA, 0.687; Cit, Met, Orn, 0.687; Cit, Orn, Phe, 0.687; Cit, Orn, Pipecolic acid, 0.687; Cit, Kyn, MeCys, 0.687; Glu, Ile, Ser, 0.687; Glu, Phe, Val, 0.687; Glu, Ser, Tyr, 0.687; Glu, hArg, Cystathionine, 0.687; Gly, Leu, Orn, 0.687; Gly, Lys, Cystathionine, 0.687; Gly, Orn, aAiBA, 0.687; Gly, Orn, Thioproline, 0.687; Gly, Trp, SDMA, 0.687; Gly, Val, SDMA, 0.687; Gly, ADMA, Sar, 0.687; Gly, Kyn, Cystathionine, 0.687; Gly, Pipecolic acid, SDMA, 0.687; His, Orn, Cystathionine, 0.687; His, Phe, MeCys, 0.687; His, MeCys, SDMA, 0.687; Leu, Phe, GABA, 0.687; Met, Orn, hArg, 0.687; Met, Orn, Kyn/Trp, 0.687; Orn, Phe, Pro, 0.687; Orn, Ser, Tyr, 0.687; Orn, 3-MeHis, aAiBA, 0.687; Phe, Ser, aAAA, 0.687; Ser, aAiBA, Kyn, 0.687; Ser, GABA, Cystathionine, 0.687; Ser, hCit, Thioproline, 0.687; Ser, HyPro, N6-AcLys, 0.687; Ser, Cystathionine, SDMA, 0.687; Ser, Pipecolic acid, Spd, 0.687; Tyr, Cystathionine, MeCys, 0.687; Val, hArg, Cystathionine, 0.687; aABA, ADMA, hCit, 0.687; ADMA, bAiBA, Put, 0.687; ADMA, Pipecolic acid, Put, 0.687; Cystathionine, MeCys, Pipecolic acid, 0.687; MeCys, SDMA, Kyn/Trp, 0.687; Phe, Val, Allyl-Cys, 0.687; EtOHNH2, 3-hKyn, aAiBA, 0.686; Cys2, Glu, Orn, 0.686; Cys2, Ile, ADMA, 0.686; Cys2, aABA, bAiBA, 0.686; Cys2, aABA, N8-AcSpd, 0.686; Ala, Orn, Cystathionine, 0.686; Asn, Met, Orn, 0.686; Asn, Ser, HyPro, 0.686; Asn, Trp, MeCys, 0.686; Cit, Orn, hCit, 0.686; Cit, Phe, MeCys, 0.686; Cit, Ser, Pipecolic acid, 0.686; Cit, Tyr, MeCys, 0.686; Cit, MeCys, Put, 0.686; Gln, Glu, Ser, 0.686; Gln, Orn, Phe, 0.686; Gln, Ser, HyPro, 0.686; Gln, GABA, MeCys, 0.686; Glu, His, Ser, 0.686; Glu, Ser, Trp, 0.686; Glu, Ser, 1-MeHis, 0.686; Glu, Ser, aAAA, 0.686; Glu, Ser, PEA, 0.686; Gly, Val, aAAA, 0.686; Gly, ADMA, GABA, 0.686; His, Orn, Phe, 0.686; His, Ser, Pipecolic acid, 0.686; His, aAAA, MeCys, 0.686; Ile, Orn, aAiBA, 0.686; Leu, Phe, Tau, 0.686; Leu, Phe, Cystathionine, 0.686; Leu, Phe, N8-AcSpd, 0.686; Leu, Ser, aABA, 0.686; Leu, Ser, Pipecolic acid, 0.686; Lys, Phe, Val, 0.686; Lys, Ser, hCit, 0.686; Lys, Ser, Cystathionine, 0.686; Met, Orn, Sar, 0.686; Met, Orn, Kyn/BCAA, 0.686; Met, Ser, HyPro, 0.686; Met, Ser, Kyn, 0.686; Met, Ser, Pipecolic acid, 0.686; Met, Trp, MeCys, 0.686; Orn, Phe, GABA, 0.686; Orn, Phe, Spd, 0.686; Orn, Ser, Sar, 0.686; Orn, Ser, SDMA, 0.686; Orn, aAiBA, hArg, 0.686; Orn, aAiBA, Kyn, 0.686; Orn, ADMA, Kyn/BCAA, 0.686; Orn, aAAA, Cystathionine, 0.686; Orn, bAiBA, Sar, 0.686; Orn, GABA, Cystathionine, 0.686; Orn, Cystathionine, N6-AcLy


s, 0.686; Orn, Cystathionine, Sar, 0.686; Orn, Cystathionine, Kyn/BCAA, 0.686; Phe, Ser, Pipecolic acid, 0.686; Phe, Val, 3-MeHis, 0.686; Phe, Val, Spd, 0.686; Pro, Tyr, MeCys, 0.686; Pro, GABA, MeCys, 0.686; Ser, Tau, Pipecolic acid, 0.686; Ser, aAiBA, Pipecolic acid, 0.686; Ser, bAiBA, N6-AcLys, 0.686; Ser, hCit, Spd, 0.686; Ser, Kyn, Pipecolic acid, 0.686; Trp, MeCys, Kyn/BCAA, 0.686; Tyr, GABA, MeCys, 0.686; aABA, ADMA, bAiBA, 0.686; aAiBA, GABA, MeCys, 0.686; aAiBA, MeCys, Thioproline, 0.686; ADMA, Hypotaurine, N8-AcSpd, 0.686; ADMA, Pipecolic acid, Kyn/Trp, 0.686; GABA, MeCys, Sar, 0.686; hArg, Cystathionine, MeCys, 0.686; MeCys, Pipecolic acid, Spd, 0.686; MeCys, Sar, Kyn/BCAA, 0.686; Orn, 3-MeHis, Allyl-Cys, 0.685; Orn, aAiBA, Allyl-Cys, 0.685; Orn, Allyl-Cys, N8-AcSpd, 0.685; Orn, Allyl-Cys, Sar, 0.685; Asn, EtOHNH2, aAiBA, 0.685; EtOHNH2, Glu, Kyn/BCAA, 0.685; EtOHNH2, Gly, aAiBA, 0.685; EtOHNH2, Ile, Phe, 0.685; EtOHNH2, Met, Ser, 0.685; EtOHNH2, Pro, aAiBA, 0.685; EtOHNH2, Ser, Tyr, 0.685; EtOHNH2, Ser, Val, 0.685; EtOHNH2, Tau, aAiBA, 0.685; EtOHNH2, Thr, Kyn/BCAA, 0.685; EtOHNH2, Tyr, aAiBA, 0.685; EtOHNH2, aAiBA, GABA, 0.685; EtOHNH2, aAAA, Kyn/BCAA, 0.685; EtOHNH2, N8-AcSpd, Kyn/BCAA, 0.685; EtOHNH2, Spd, Kyn/BCAA, 0.685; Orn, bAiBA, N6-AcLys, 0.684; Arg, Leu, Ser, 0.684; Asn, Gln, MeCys, 0.684; Cit, Met, MeCys, 0.684; Cit, Pro, MeCys, 0.684; Cit, MeCys, Kyn/Trp, 0.684; Gln, Gly, hCit, 0.684; Gln, MeCys, Thioproline, 0.684; Glu, Leu, Phe, 0.684; Glu, Ser, Spd, 0.684; Glu, Ser, Thioproline, 0.684; Gly, Leu, aAiBA, 0.684; Gly, Met, ADMA, 0.684; Gly, Orn, Ser, 0.684; Gly, Ser, Cystathionine, 0.684; Gly, Pipecolic acid, Put, 0.684; Gly, Pipecolic acid, Spd, 0.684; Gly, Pipecolic acid, Kyn/BCAA, 0.684; Gly, Put, Spd, 0.684; His, Tyr, MeCys, 0.684; His, MeCys, Spd, 0.684; His, MeCys, Kyn/Trp, 0.684; Ile, Leu, Phe, 0.684; Leu, Ser, aAiBA, 0.684; Lys, Orn, Cystathionine, 0.684; Met, Orn, Tau, 0.684; Met, Orn, HyPro, 0.684; Met, Ser, N6-AcLys, 0.684; Orn, Phe, hArg, 0.684; Orn, Phe, Put, 0.684; Orn, Ser, Tau, 0.684; Orn, Thr, aAiBA, 0.684; Orn, Tyr, HyPro, 0.684; Orn, aAiBA, Pipecolic acid, 0.684; Orn, N6-AcLys, Pipecolic acid, 0.684; Pro, Ser, Pipecolic acid, 0.684; Ser, Tau, hCit, 0.684; Ser, Trp, hArg, 0.684; Ser, Tyr, Val, 0.684; Ser, 1-MeHis, hCit, 0.684; Ser, GABA, Pipecolic acid, 0.684; Ser, Cystathionine, Sar, 0.684; Ser, Cystathionine, Spd, 0.684; Tyr, MeCys, Thioproline, 0.684; aABA, MeCys, Spd, 0.684; aAiBA, MeCys, SDMA, 0.684; ADMA, bAiBA, GABA, 0.684; ADMA, bAiBA, hArg, 0.684; ADMA, HyPro, Kyn/BCAA, 0.684; ADMA, N8-AcSpd, Put, 0.684; ADMA, Put, SDMA, 0.684; hArg, MeCys, Kyn/Trp, 0.684; MeCys, Kyn/Trp, Kyn/BCAA, 0.684; Cys2, Glu, Tyr, 0.684; Cys2, Leu, Orn, 0.684; Cys2, Orn, 1-MeHis, 0.684; Cys2, Orn, Kyn/BCAA, 0.684; Cys2, Ser, Pipecolic acid, 0.684; Cys2, ADMA, Kyn/BCAA, 0.684; Gly, Orn, Allyl-Cys, 0.684; Met, Orn, Allyl-Cys, 0.684; Ser, Allyl-Cys, Kyn, 0.684; [2.3 variable formula]
EtOHNH2, Leu, Phe, 0.797; Gly, Met, Val, 0.787; 3-hKyn, bAiBA, MeCys, 0.786; Tau, Allyl-Cys, MeCys, 0.781; Glu, Gly, MeCys, 0.779; Cys2, Allyl-Cys, MeCys, 0.779; Lys, Allyl-Cys, MeCys, 0.778; 3-hKyn, Allyl-Cys, MeCys, 0.777; Ser, ADMA, bAiBA, 0.777; 3-hKyn, MeCys, N8-AcSpd, 0.777; Cys2, ADMA, MeCys, 0.775; Leu, Phe, MeCys, 0.773; Phe, Val, MeCys, 0.772; Gly, Val, MeCys, 0.771; EtOHNH2, MeCys, Kyn / BCAA, 0.771; 1-MeHis, Allyl-Cys, MeCys, 0.771; Allyl-Cys, hCit, MeCys, 0.771; Ser, Kyn, MeCys, 0.77; Cys2, aABA, MeCys, 0.768; Val, Allyl-Cys, MeCys, 0.768; 3-MeHis, Allyl-Cys, MeCys, 0.768; Leu, aAiBA, MeCys, 0.768; ADMA, MeCys, N8-AcSpd, 0.767; Leu, 3-hKyn, MeCys, 0.766; 3-hKyn, ADMA, MeCys, 0.766; 3-hKyn, MeCys, SDMA, 0.766; Val, 3- hKyn, MeCys, 0.765; Val, aAiBA, MeCys, 0.764; hCit, MeCys, N8-AcSpd, 0.764; Cys2, MeCys, N8-AcSpd, 0.764; EtOHNH2, bAiBA, MeCys, 0.763; Glu, Ser, MeCys, 0.762; Ser, hCit, MeCys, 0.762; ADMA, bAiBA, MeCys, 0.762; HyPro, MeCys, N8-AcSpd, 0.762; MeCys, N6-AcLys, N8- AcSpd, 0.762; Glu, 3-hKyn, MeCys, 0.762; 1-MeHis, 3-hKyn, MeCys, 0.76; Ile, Leu, MeCys, 0.76; Cys2, Orn, MeCys, 0.76; Gly, Leu, MeCys, 0.759; Leu, Met, MeCys, 0.759; Tau, 3-hKyn, MeCys, 0.759; Leu, Allyl-Cys, MeCys, 0.758; Ser, Val, MeCys, 0.758; EtOHNH2, 3-hKyn, MeCys, 0.758; Orn, 3- hKyn, MeCys, 0.757; Ser, bAiBA, MeCys, 0.757; Gln, Ser, MeCys, 0.756; Ser, Trp, MeCys, 0.756; Ser, aAiBA, MeCys, 0.756; Ser, MeCys, N6-AcLys, 0.756; aABA, MeCys, N6-AcLys, 0.756; EtOHNH2, Ser, bAiBA, 0.755; EtOHNH2, aABA, Kyn / BCAA, 0.755; Asn, Leu, MeCys, 0.754; Lys, Ser, MeCys, 0.754; Gly, ADMA, bAiBA, 0.753; Ser, 1-MeHis, MeCys, 0.753; Ser, ADMA, MeCys, 0.753; Ile, 3-hKyn, MeCys, 0.753; Lys, 3-hKyn, MeCys, 0.753; 3-hKyn, MeCys, N6-AcLys, 0.753; EtOHNH2, aAiBA, MeCys, 0.753; Gly, Leu, Met, 0.752; Ser, 3-MeHis, MeCys, 0.752; Val, aABA, MeCys, 0.752; 1-MeHis, bAiBA, MeCys, 0.752; ADMA, hCit, MeCys, 0.752; Ile, Allyl-Cys, MeCys, 0.752; Allyl-Cys, HyPro, MeCys, 0.752; Cys2, bAiBA, MeCys, 0.752; Asn, 3-hKyn, M eCys, 0.751; Pro, 3-hKyn, MeCys, 0.751; Thr, 3-hKyn, MeCys, 0.751; ADMA, Allyl-Cys, MeCys, 0.751; Cit, Ser, MeCys, 0.75; Gly, hCit, MeCys, 0.75; Leu, bAiBA, MeCys, 0.75; Ser, aAAA, MeCys, 0.75; Ser, MeCys, Put, 0.75; Tyr, Val, MeCys, 0.75; 1-MeHis, hCit, MeCys, 0.75; 3-hKyn, MeCys, Pipecolic acid , 0.75; ADMA, HyPro, MeCys, 0.75; ADMA, MeCys, SDMA, 0.75; Cys2, Glu, MeCys, 0.749; Ser, Allyl-Cys, MeCys, 0.749; Glu, bAiBA, MeCys, 0.749; Gly, Ile, MeCys , 0.749; Leu, Ser, MeCys, 0.749; Orn, hCit, MeCys, 0.749; Ser, bAiBA, hCit, 0.749; Cys2, 3-hKyn, MeCys, 0.749; 3-hKyn, MeCys, Sar, 0.749; 3-hKyn , MeCys, Thioproline, 0.749; Glu, Allyl-Cys, MeCys, 0.748; Orn, Allyl-Cys, MeCys, 0.748; Allyl-Cys, MeCys, PEA, 0.748; Asn, Ser, MeCys, 0.748; Gly, Phe, Val , 0.748; Orn, MeCys, N6-AcLys, 0.748; Ser, ADMA, SDMA, 0.748; Ser, Hypotaurine, MeCys, 0.748; Ser, MeCys, Kyn / Trp, 0.748; ADMA, MeCys, Put, 0.748; hCit, MeCys , Pipecolic acid, 0.748; Cys2, ADMA, bAiBA, 0.747; Gly, bAiBA, MeCys, 0.747; Lys, aAiBA, M eCys, 0.747; Lys, MeCys, N8-AcSpd, 0.747; Orn, bAiBA, MeCys, 0.747; Ser, Tau, MeCys, 0.747; Ser, aABA, MeCys, 0.747; Allyl-Cys, aAAA, MeCys, 0.746; His, 3-hKyn, MeCys, 0.746; 3-hKyn, aAAA, MeCys, 0.746; 3-hKyn, MeCys, PEA, 0.746; 3-hKyn, MeCys, Kyn / BCAA, 0.746; Glu, MeCys, N6-AcLys, 0.746; Gly, Lys, MeCys, 0.746; Ser, ADMA, Pipecolic acid, 0.746; Thr, hCit, MeCys, 0.746; 1-MeHis, HyPro, MeCys, 0.746; bAiBA, hCit, MeCys, 0.746; bAiBA, HyPro, MeCys, 0.746 Allyl-Cys, MeCys, N6-AcLys, 0.745; Allyl-Cys, MeCys, N8-AcSpd, 0.745; EtOHNH2, Leu, Cystathionine, 0.745; EtOHNH2, Val, Cystathionine, 0.745; Glu, aAiBA, MeCys, 0.744; Gly , ADMA, SDMA, 0.744; Gly, aAAA, MeCys, 0.744; Leu, aABA, MeCys, 0.744; Met, Val, MeCys, 0.744; Orn, Cystathionine, MeCys, 0.744; Phe, Ser, Val, 0.744; Val, Cystathionine , MeCys, 0.744; Allyl-Cys, Kyn, MeCys, 0.744; Allyl-Cys, MeCys, Spd, 0.744; Gly, MeCys, Put, 0.743; Met, Ser, Val, 0.743; Orn, Ser, MeCys, 0.743; Orn , MeCys, N8-AcSpd, 0.743; Pro, Ser, MeCys, 0.743; Se r, hCit, Cystathionine, 0.743; Ser, MeCys, PEA, 0.743; Val, MeCys, N8-AcSpd, 0.743; Cys2, Kyn, MeCys, 0.743; Cys2, MeCys, Thioproline, 0.743; Ser, 3-hKyn, MeCys, 0.743; 3-hKyn, 3-MeHis, MeCys, 0.743; 3-hKyn, aABA, MeCys, 0.743; 3-hKyn, Cystathionine, MeCys, 0.743; 3-hKyn, MeCys, Put, 0.743; Gly, MeCys, N6- AcLys, 0.742; Ile, Ser, MeCys, 0.742; Thr, ADMA, MeCys, 0.742; EtOHNH2, Lys, MeCys, 0.742; EtOHNH2, Orn, aAiBA, 0.742; EtOHNH2, Phe, Val, 0.742; Trp, Allyl-Cys, MeCys, 0.742; Allyl-Cys, MeCys, Sar, 0.742; Trp, 3-hKyn, MeCys, 0.741; 3-hKyn, GABA, MeCys, 0.741; 3-hKyn, Kyn, MeCys, 0.741; 3-hKyn, MeCys, Kyn / Trp, 0.741; Ala, Ser, MeCys, 0.741; Ile, aAiBA, MeCys, 0.741; Ile, MeCys, N8-AcSpd, 0.741; Leu, MeCys, N8-AcSpd, 0.741; Lys, aABA, MeCys, 0.741; Orn, aAiBA, MeCys, 0.741; Ser, Cystathionine, MeCys, 0.741; Val, bAiBA, MeCys, 0.741; Val, HyPro, MeCys, 0.741; Thr, Allyl-Cys, MeCys, 0.741; Gly, Ser, MeCys, 0.74; Leu, Cystathionine, MeCys, 0.74; Ser, hArg, MeCys, 0.74; Ser, HyPro, MeCys, 0 .74; Ser, MeCys, N8-AcSpd, 0.74; Tau, ADMA, MeCys, 0.74; Val, hCit, MeCys, 0.74; aAiBA, MeCys, N8-AcSpd, 0.74; ADMA, GABA, MeCys, 0.74; ADMA, MeCys , N6-AcLys, 0.74; hCit, MeCys, Sar, 0.74; Arg, 3-hKyn, MeCys, 0.74; Met, 3-hKyn, MeCys, 0.74; EtOHNH2, Gly, bAiBA, 0.74; EtOHNH2, Leu, aAAA, 0.74 Gln, Gly, MeCys, 0.739; Gln, ADMA, MeCys, 0.739; Orn, Tyr, MeCys, 0.739; Orn, MeCys, Pipecolic acid, 0.739; Ser, ADMA, Cystathionine, 0.739; Ser, MeCys, Pipecolic acid, 0.739 Ser, MeCys, Thioproline, 0.739; 1-MeHis, MeCys, N8-AcSpd, 0.739; ADMA, bAiBA, Pipecolic acid, 0.739; Tyr, 3-hKyn, MeCys, 0.738; 3-hKyn, hArg, MeCys, 0.738; Allyl-Cys, bAiBA, MeCys, 0.738; Glu, aABA, MeCys, 0.738; Gly, ADMA, MeCys, 0.738; Phe, Val, ADMA, 0.738; 3-MeHis, MeCys, N8-AcSpd, 0.738; aABA, ADMA, MeCys, 0.738; aAiBA, ADMA, MeCys, 0.738; Cys2, aABA, ADMA, 0.737; Cys2, MeCys, Pipecolic acid, 0.737; EtOHNH2, Leu, MeCys, 0.737; EtOHNH2, bAiBA, Kyn / BCAA, 0.737; Gln, 3 -hKyn, MeCys, 0.737; Phe, 3-hKyn, MeCys, 0.737; Glu, Gl y, Pipecolic acid, 0.737; Glu, ADMA, MeCys, 0.737; Gly, Orn, MeCys, 0.737; Gly, Tyr, MeCys, 0.737; Gly, Val, Cystathionine, 0.737; Ile, bAiBA, MeCys, 0.737; Lys, hCit , MeCys, 0.737; Ser, Thr, MeCys, 0.737; Ser, MeCys, Sar, 0.737; Ser, MeCys, Kyn / BCAA, 0.737; ADMA, bAiBA, hCit, 0.737; Hypotaurine, MeCys, PEA, 0.737; Cys2, 3 -MeHis, MeCys, 0.736; Cys2, MeCys, N6-AcLys, 0.736; Cys2, MeCys, Sar, 0.736; Asn, Ile, MeCys, 0.736; Leu, Orn, Phe, 0.736; Leu, Tyr, MeCys, 0.736; Orn , MeCys, SDMA, 0.736; 1-MeHis, aAiBA, MeCys, 0.736; Ala, 3-hKyn, MeCys, 0.735; Cys2, hCit, MeCys, 0.735; Cys2, MeCys, Put, 0.735; Arg, Ser, MeCys, 0.734 Asn, Val, MeCys, 0.734; Glu, Gly, Cystathionine, 0.734; Glu, His, MeCys, 0.734; Gly, 1-MeHis, MeCys, 0.734; His, Ser, MeCys, 0.734; His, ADMA, MeCys, 0.734 Leu, hCit, MeCys, 0.734; Phe, Ser, MeCys, 0.734; Phe, ADMA, MeCys, 0.734; Ser, MeCys, Spd, 0.734; Tau, Hypotaurine, MeCys, 0.734; Tau, HyPro, MeCys, 0.734; aAiBA , hCit, MeCys, 0.734; ADMA, Cystathionine, MeCys, 0.73 4; hCit, MeCys, N6-AcLys, 0.734; EtOHNH2, aABA, MeCys, 0.734; Cit, 3-hKyn, MeCys, 0.734; 3-hKyn, hCit, MeCys, 0.734; Cys2, Tau, MeCys, 0.733; Cys2, Trp, MeCys, 0.733; Cys2, 1-MeHis, MeCys, 0.733; Asn, Orn, MeCys, 0.733; Cit, Ser, ADMA, 0.733; EtOHNH2, Lys, Allyl-Cys, 0.733; Glu, Phe, MeCys, 0.733; Glu, Ser, ADMA, 0.733; Glu, hCit, MeCys, 0.733; Leu, Phe, ADMA, 0.733; Leu, HyPro, MeCys, 0.733; Orn, ADMA, bAiBA, 0.733; Pro, aAiBA, MeCys, 0.733; Ser, ADMA, hCit, 0.733; Ser, GABA, MeCys, 0.733; ADMA, MeCys, PEA, 0.733; ADMA, MeCys, Sar, 0.733; Kyn, MeCys, N8-AcSpd, 0.733; Arg, Leu, MeCys, 0.732; Asn, MeCys, N6-AcLys, 0.732; Gln, Leu, MeCys, 0.732; Ile, ADMA, MeCys, 0.732; Leu, Met, Ser, 0.732; Met, Ser, MeCys, 0.732; Met, ADMA, MeCys, 0.732; Orn, Phe, Val, 0.732; Orn, HyPro, MeCys, 0.732; Tau, MeCys, N8-AcSpd, 0.732; Val, aAAA, MeCys, 0.732; Asn, Cys2, MeCys, 0.732; Cit, Cys2, MeCys, 0.732; Asn, ADMA, MeCys, 0.731; Gln, Orn, MeCys, 0.731; Glu, Cystathionine, MeCys, 0.731; Glu, MeCys, Sar, 0.731; Gly, 3-MeHis, MeCys, 0.731; Ile, Met, MeCys, 0.731; Ile, Val, MeCys, 0.731; Leu, ADMA, MeCys, 0.731; Lys, MeCys, Sar, 0.731; Orn, Hypotaurine, MeCys, 0.731; Ser, Trp, ADMA, 0.731; Ser, Tyr, MeCys, 0.731; Ser, MeCys, SDMA, 0.731; Trp, ADMA, MeCys, 0.731; 1-MeHis, aABA, MeCys, 0.731; Cys2, Glu, Gly, 0.731; Cys2, Gly, MeCys, 0.731; Cys2, Ser, MeCys, 0.731; Cys2, ADMA, Pipecolic acid, 0.731; 3-hKyn, aAiBA, MeCys, 0.731; Arg, ADMA, MeCys, 0.73; Cit, ADMA, MeCys , 0.73; Cit, MeCys, N8-AcSpd, 0.73; Glu, Pro, MeCys, 0.73; Glu, Hypotaurine, MeCys, 0.73; Glu, HyPro, MeCys, 0.73; Gly, Orn, bAiBA, 0.73; Gly, Val, bAiBA , 0.73; Gly, MeCys, Pipecolic acid, 0.73; Lys, ADMA, MeCys, 0.73; Met, MeCys, N8-AcSpd, 0.73; Orn, Ser, Cystathionine, 0.73; Orn, MeCys, Sar, 0.73; Pro, 1- MeHis, MeCys, 0.73; Pro, MeCys, N8-AcSpd, 0.73; Ser, aABA, ADMA, 0.73; Ser, ADMA, GABA, 0.73; Ser, ADMA, N8-AcSpd, 0.73; 1-MeHis, ADMA, MeCys, 0.73; 1-MeHis, MeCys, Pipecolic acid, 0.73; 1-MeHis, MeCys, Put, 0.73; 3-MeHis, AD MA, MeCys, 0.73; ADMA, hArg, MeCys, 0.73; ADMA, MeCys, Kyn / Trp, 0.73; aAAA, MeCys, N8-AcSpd, 0.73; hArg, hCit, MeCys, 0.73; EtOHNH2, Ser, Cystathionine, 0.729; EtOHNH2, aAiBA, Spd, 0.729; Glu, Lys, MeCys, 0.729; Glu, hArg, MeCys, 0.729; Glu, MeCys, Pipecolic acid, 0.729; Glu, MeCys, Spd, 0.729; Gly, Trp, MeCys, 0.729; Gly , Hypotaurine, MeCys, 0.729; Gly, MeCys, SDMA, 0.729; Leu, hArg, MeCys, 0.729; Ser, ADMA, N6-AcLys, 0.729; Ser, ADMA, Kyn / Trp, 0.729; Thr, aAiBA, MeCys, 0.729 Tyr, ADMA, MeCys, 0.729; 1-MeHis, hArg, MeCys, 0.729; ADMA, Kyn, MeCys, 0.729; ADMA, MeCys, Kyn / BCAA, 0.729; bAiBA, MeCys, N6-AcLys, 0.729; bAiBA, MeCys , N8-AcSpd, 0.729; HyPro, MeCys, N6-AcLys, 0.729; HyPro, MeCys, Pipecolic acid, 0.729; Cys2, Lys, MeCys, 0.728; Gln, Ser, ADMA, 0.728; Glu, MeCys, N8-AcSpd, 0.728; Gly, HyPro, MeCys, 0.728; Leu, MeCys, Pipecolic acid, 0.728; Lys, bAiBA, MeCys, 0.728; Met, aAiBA, MeCys, 0.728; Trp, Val, MeCys, 0.728; Val, ADMA, MeCys, 0.728 aABA, aAAA, MeCys, 0.728; aAiBA, aAAA, MeCys, 0.728; aAiBA, HyPro, MeCys, 0.728; ADMA, aAAA, MeCys, 0.728; Ala, Cys2, MeCys, 0.727; Cys2, Phe, ADMA, 0.727; Cys2, aAiBA, MeCys, 0.727; Asn, Lys, MeCys, 0.727; Glu, GABA, MeCys, 0.727; Gly, Orn, Cystathionine, 0.727; Gly, ADMA, Kyn / B


CAA, 0.727; Ile, Phe, MeCys, 0.727; Leu, Tau, MeCys, 0.727; Leu, aAAA, MeCys, 0.727; Orn, Phe, Ser, 0.727; Orn, Val, MeCys, 0.727; Orn, aABA, MeCys, 0.727; Ser, ADMA, Kyn / BCAA, 0.727; Tau, Val, MeCys, 0.727; Tau, 1-MeHis, MeCys, 0.727; Tau, MeCys, N6-AcLys, 0.727; 1-MeHis, Kyn, MeCys, 0.727; 1-MeHis, Cystathionine, MeCys, 0.727; 3-MeHis, bAiBA, MeCys, 0.727; aAiBA, MeCys, N6-AcLys, 0.727; ADMA, Hypotaurine, MeCys, 0.727; ADMA, MeCys, Spd, 0.727; HyPro, MeCys, Sar, 0.727; MeCys, N8-AcSpd, Pipecolic acid, 0.727; Arg, EtOHNH2, aAiBA, 0.727; EtOHNH2, Orn, bAiBA, 0.727; EtOHNH2, GABA, Kyn / BCAA, 0.727; EtOHNH2, MeCys, N8-AcSpd, 0.727 Pro, Allyl-Cys, MeCys, 0.726; Tyr, Allyl-Cys, MeCys, 0.726; 3-hKyn, HyPro, MeCys, 0.726; Ala, Ser, ADMA, 0.726; Arg, Val, MeCys, 0.726; Gln, bAiBA , MeCys, 0.726; Glu, Leu, MeCys, 0.726; Glu, Tyr, MeCys, 0.726; Glu, 1-MeHis, MeCys, 0.726; Glu, MeCys, SDMA, 0.726; Gly, Leu, Phe, 0.726; Gly, aAiBA , MeCys, 0.726; His, MeCys, N8-AcSpd, 0.726; Ile, aABA, MeCys, 0.726 Leu, Phe, Pipecolic acid, 0.726; Lys, Phe, MeCys, 0.726; Lys, 1-MeHis, MeCys, 0.726; Orn, Phe, MeCys, 0.726; Ser, 3-MeHis, ADMA, 0.726; Ser, ADMA, HyPro, 0.726; Tau, MeCys, Pipecolic acid, 0.726; Val, 1-MeHis, MeCys, 0.726; Val, MeCys, Pipecolic acid, 0.726; 3-MeHis, aAiBA, MeCys, 0.726; aABA, hCit, MeCys, 0.726; Arg, Cys2, MeCys, 0.725; Cys2, Glu, aABA, 0.725; Asn, Glu, MeCys, 0.724; Cit, Leu, MeCys, 0.724; Cit, Ser, hCit, 0.724; Gln, Ile, MeCys, 0.724; Glu, Gly, hCit, 0.724; Glu, Ile, MeCys, 0.724; Glu, Tau, MeCys, 0.724; Glu, 3-MeHis, MeCys, 0.724; Glu, aAAA, MeCys, 0.724; Glu, MeCys, PEA, 0.724; Glu, MeCys, Thioproline, 0.724; Glu, MeCys, Kyn / BCAA, 0.724; Gly, Tau, MeCys, 0.724; Gly, MeCys, N8-AcSpd, 0.724; Ile, hCit, MeCys, 0.724; Ile, HyPro, MeCys, 0.724; Lys, Met, MeCys, 0.724; Lys, HyPro, MeCys, 0.724; Orn, ADMA, MeCys, 0.724; Orn, GABA, MeCys, 0.724; Orn, MeCys, Put, 0.724; Ser, Kyn, Cystathionine, 0.724; 3- MeHis, MeCys, Pipecolic acid, 0.724; 3-MeHis, MeCys, Sar, 0.724; aAB A, MeCys, N8-AcSpd, 0.724; Cys2, Met, Orn, 0.724; Cys2, Phe, MeCys, 0.724; Cys2, Cystathionine, MeCys, 0.724; Cys2, MeCys, PEA, 0.724; EtOHNH2, Gly, Kyn / BCAA, 0.724; EtOHNH2, Phe, Kyn / BCAA, 0.724; EtOHNH2, MeCys, Pipecolic acid, 0.724; Phe, Val, 3-hKyn, 0.723; Arg, HyPro, MeCys, 0.723; Asn, Ser, ADMA, 0.723; Cit, Orn , MeCys, 0.723; Gln, Lys, MeCys, 0.723; Gln, Tau, MeCys, 0.723; Glu, Ser, Cystathionine, 0.723; Glu, Thr, MeCys, 0.723; Glu, MeCys, Put, 0.723; Ile, Tyr, MeCys , 0.723; Leu, Met, Orn, 0.723; Leu, Ser, ADMA, 0.723; Leu, 1-MeHis, MeCys, 0.723; Pro, MeCys, N6-AcLys, 0.723; Thr, MeCys, N8-AcSpd, 0.723; Trp , hCit, MeCys, 0.723; Trp, MeCys, N8-AcSpd, 0.723; 1-MeHis, MeCys, Sar, 0.723; 3-MeHis, MeCys, SDMA, 0.723; aAAA, HyPro, MeCys, 0.723; bAiBA, hArg, MeCys , 0.723; MeCys, N6-AcLys, Put, 0.723; Cys2, Orn, Phe, 0.723; Cys2, ADMA, GABA, 0.723; Cys2, ADMA, N8-AcSpd, 0.723; Ala, Glu, MeCys, 0.722; Arg, Glu , MeCys, 0.722; Gln, Thr, MeCys, 0.722; Glu, Gly, ADMA, 0.722; Glu, Kyn, MeCys, 0.722; His, hCit, MeCys, 0.722; Ile, Ser, ADMA, 0.722; Leu, Phe, Ser, 0.722; Met, Orn, MeCys, 0.722; Orn, Tau, MeCys, 0.722; Orn, Trp, MeCys, 0.722; Tau, aAiBA, MeCys, 0.722; aAiBA, bAiBA, MeCys, 0.722; aAAA, bAiBA, MeCys, 0.722; bAiBA, Kyn, MeCys, 0.722; hCit, MeCys, SDMA, 0.722; Cys2, Ile, MeCys, 0.721; Cys2, Orn, aABA, 0.721; EtOHNH2, Orn, Cystathionine, 0.721; EtOHNH2, Ser, Put, 0.721; Arg, Glu, Gly, 0.721; Arg, Orn, MeCys, 0.721; Cit, Glu, MeCys, 0.721; Glu, Orn, MeCys, 0.721; Glu, Trp, MeCys, 0.721; Gly, Ile, Met, 0.721; Ile, Orn, MeCys, 0.721; Leu, MeCys, PEA, 0.721; Pro, Tau, MeCys, 0.721; Pro, ADMA, MeCys, 0.721; Ser, Val, ADMA, 0.721; Tau, MeCys, Spd, 0.721; Val, GABA, MeCys, 0.721; Val, MeCys, Kyn / Trp, 0.721; 1-MeHis, MeCys, N6-AcLys, 0.721; 1- MeHis, MeCys, Kyn / Trp, 0.721; aABA, HyPro, MeCys, 0.721; bAiBA, MeCys, Kyn / Trp, 0.721; MeCys, N8-AcSpd, Put, 0.721; Gly, Allyl-Cys, MeCys, 0.721; Gly, 3-hKyn, MeCys, 0.72; Cys2, Val, MeCys, 0.72; Cys2, GABA, MeCys, 0.72; Cys2, MeCys, K yn / BCAA, 0.72; Arg, Ser, ADMA, 0.72; Cit, Val, MeCys, 0.72; Gln, Gly, ADMA, 0.72; Glu, Gly, Met, 0.72; Glu, Met, MeCys, 0.72; Gly, Met, MeCys, 0.72; Gly, bAiBA, hCit, 0.72; His, Ser, ADMA, 0.72; Leu, Thr, MeCys, 0.72; Lys, hArg, MeCys, 0.72; Orn, Thr, MeCys, 0.72; Orn, 1-MeHis, MeCys, 0.72; Orn, aAAA, MeCys, 0.72; Orn, MeCys, Kyn / Trp, 0.72; Phe, Ser, ADMA, 0.72; Phe, MeCys, N6-AcLys, 0.72; Phe, MeCys, N8-AcSpd, 0.72; Ser, aAiBA, ADMA, 0.72; Tau, bAiBA, MeCys, 0.72; Thr, 1-MeHis, MeCys, 0.72; Tyr, aAiBA, MeCys, 0.72; Val, MeCys, Sar, 0.72; aAAA, hCit, MeCys, 0.72; Hypotaurine, MeCys, N8-AcSpd, 0.72; MeCys, N6-AcLys, SDMA, 0.72; MeCys, N8-AcSpd, Kyn / Trp, 0.72; Allyl-Cys, hArg, MeCys, 0.719; Allyl-Cys, MeCys, SDMA, 0.719; Ala, ADMA, MeCys, 0.719; Ala, bAiBA, MeCys, 0.719; Gln, Val, MeCys, 0.719; Gly, His, MeCys, 0.719; Gly, Kyn, MeCys, 0.719; His, Orn, MeCys, 0.719; His, aAiBA, MeCys, 0.719; Ile, Tau, MeCys, 0.719; Leu, Orn, MeCys, 0.719; Leu, MeCys, Put, 0.719; Lys, Val, MeCys, 0.719; Or n, Ser, bAiBA, 0.719; Orn, MeCys, PEA, 0.719; Thr, MeCys, N6-AcLys, 0.719; Val, MeCys, N6-AcLys, 0.719; 1-MeHis, GABA, MeCys, 0.719; 1-MeHis, Hypotaurine, MeCys, 0.719; 1-MeHis, MeCys, Spd, 0.719; aAiBA, Kyn, MeCys, 0.719; MeCys, N6-AcLys, PEA, 0.719; MeCys, PEA, Pipecolic acid, 0.719; Cys2, Orn, Pipecolic acid, 0.719; Cys2, Pro, MeCys, 0.719; Cys2, Tyr, MeCys, 0.719; Cys2, hArg, MeCys, 0.719; Cys2, HyPro, MeCys, 0.719; EtOHNH2, Leu, Met, 0.719; EtOHNH2, Orn, MeCys, 0.719; EtOHNH2, Allyl-Cys, MeCys, 0.718; Ser, Allyl-Cys, hCit, 0.718; Ala, 1-MeHis, MeCys, 0.718; Arg, Gly, Val, 0.718; Arg, MeCys, N8-AcSpd, 0.718; Asn, bAiBA, MeCys, 0.718; Gln, Glu, MeCys, 0.718; Glu, Gly, bAiBA, 0.718; Glu, Val, MeCys, 0.718; Gly, MeCys, Kyn / BCAA, 0.718; His, Lys, MeCys, 0.718; Leu, MeCys, Kyn / BCAA, 0.718; Met, Ser, ADMA, 0.718; Orn, Pro, HyPro, 0.718; Orn, Ser, hCit, 0.718; Orn, MeCys, Thioproline, 0.718; Ser, ADMA, Put, 0.718; Ser, bAiBA, HyPro, 0.718; Tau, Kyn, MeCys, 0.718; Thr, HyPro, MeCys, 0.718; 1-MeHis, MeCys, SDMA, 0.718; ADMA, MeCys, Pipecolic acid, 0.718; bAiBA, MeCys, Thioproline, 0.718; hCit, MeCys, Kyn / BCAA, 0.718; HyPro, Kyn, MeCys, 0.718; MeCys, N6-AcLys , Pipecolic acid, 0.718; MeCys, N8-AcSpd, SDMA, 0.718; 3-hKyn, Hypotaurine, MeCys, 0.717; Ala, Gly, MeCys, 0.717; Asn, Gly, MeCys, 0.717; Asn, 1-MeHis, MeCys, 0.717; Gly, Leu, Cystathionine, 0.717; Gly, Thr, MeCys, 0.717; Gly, Hypotaurine, Spd, 0.717; His, 1-MeHis, MeCys, 0.717; Ile, Met, Ser, 0.717; Ile, 1-MeHis, MeCys, 0.717; Ile, Cystathionine, MeCys, 0.717; Leu, Hypotaurine, MeCys, 0.717; Orn, Kyn, MeCys, 0.717; Ser, ADMA, aAAA, 0.717; Ser, ADMA, Sar, 0.717; Tau, hCit, MeCys, 0.717; Tau, MeCys, Put, 0.717; Thr, Val, MeCys, 0.717; Thr, MeCys, Pipecolic acid, 0.717; Tyr, MeCys, N8-AcSpd, 0.717; Val, 3-MeHis, MeCys, 0.717; Val, MeCys , Put, 0.717; Val, MeCys, SDMA, 0.717; 1-MeHis, MeCys, PEA, 0.717; 3-MeHis, HyPro, MeCys, 0.717; bAiBA, MeCys, Spd, 0.717; HyPro, MeCys, PEA, 0.717; His , Allyl-Cys, MeCys, 0.717; Phe, All yl-Cys, MeCys, 0.717; Allyl-Cys, Hypotaurine, MeCys, 0.717; Cys2, His, MeCys, 0.716; Cys2, Leu, MeCys, 0.716; Cys2, Orn, Pro, 0.716; Cys2, aABA, aAiBA, 0.716; Cys2, ADMA, Put, 0.716; EtOHNH2, Gln, aAiBA, 0.716; EtOHNH2, Gly, GABA, 0.716; EtOHNH2, Gly, Put, 0.716; EtOHNH2, Pro, Kyn / BCAA, 0.716; EtOHNH2, Ser, aABA, 0.716; EtOHNH2, Val, bAiBA, 0.716; EtOHNH2, MeCys, SDMA, 0.716; EtOHNH2, MeCys, Kyn / Trp, 0.716; Ala, MeCys, N8-AcSpd, 0.716; Arg, 1-MeHis, MeCys, 0.716; Cit, Orn, Ser, 0.716; Cit, 1-MeHis, MeCys, 0.716; Gln, Glu, Gly, 0.716; Gln, MeCys, N8-AcSpd, 0.716; Glu, Gly, Put, 0.716; Glu, Gly, Sar, 0.716; Gly, Phe, MeCys, 0.716; Gly, Pro, MeCys, 0.716; Gly, Val, Pipecolic acid, 0.716; Gly, ADMA, Pipecolic acid, 0.716; Leu, Lys, MeCys, 0.716; Leu, Val, MeCys, 0.716; Lys, Tau, MeCys, 0.716; Lys, Tyr, MeCys, 0.716; Lys, aAAA, MeCys, 0.716; Lys, GABA, MeCys, 0.716; Met, Orn, Val, 0.716; Orn, Ser, Pipecolic acid, 0.716; Orn, hArg , MeCys, 0.716; Orn, MeCys, Kyn / BCAA, 0.716; Phe, HyPro, MeCys , 0.716; Ser, aABA, hCit, 0.716; Ser, ADMA, Thioproline, 0.716; Tau, aABA, MeCys, 0.716; Thr, bAiBA, MeCys, 0.716; Trp, HyPro, MeCys, 0.716; Tyr, MeCys, N6-AcLys , 0.716; aABA, bAiBA, MeCys, 0.716; aAiBA, MeCys, Pipecolic acid, 0.716; ADMA, MeCys, Thioproline, 0.716; bAiBA, GABA, MeCys, 0.716; bAiBA, Cystathionine, MeCys, 0.716; bAiBA, MeCys, Sar 0.716; GABA, MeCys, N8-AcSpd, 0.716; GABA, MeCys, Put, 0.716; HyPro, MeCys, SDMA, 0.716; Kyn, MeCys, Pipecolic acid, 0.716; Cystathionine, MeCys, N8-AcSpd, 0.716; MeCys, N8 -AcSpd, PEA, 0.716; MeCys, N8-AcSpd, Sar, 0.716; MeCys, N8-AcSpd, Kyn / BCAA, 0.716; EtOHNH2, Allyl-Cys, Kyn / BCAA, 0.715; Arg, Allyl-Cys, MeCys, 0.715 Gln, Allyl-Cys, MeCys, 0.715; Cys2, Gln, MeCys, 0.715; Cys2, Met, MeCys, 0.715; Cys2, Ser, ADMA, 0.715; Cys2, MeCys, Spd, 0.715; Arg, Gly, Leu, 0.714 Arg, Ile, MeCys, 0.714; Arg, hCit, MeCys, 0.714; Cit, Gly, Orn, 0.714; Cit, Ile, MeCys, 0.714; Cit, Lys, MeCys, 0.714; Gln, MeCys, N6-AcLys, 0.714 Glu, Phe, Ser, 0.714; Gly, hAr g, MeCys, 0.714; Gly, MeCys, Sar, 0.714; Gly, MeCys, Kyn / Trp, 0.714; His, Val, MeCys, 0.714; His, bAiBA, MeCys, 0.714; Ile, MeCys, PEA, 0.714; Leu, Phe, aABA, 0.714; Leu, Pro, MeCys, 0.714; Leu, 3-MeHis, MeCys, 0.714; Leu, GABA, MeCys, 0.714; Leu, Kyn, MeCys, 0.714; Leu, MeCys, N6-AcLys, 0.714; Leu, MeCys, Sar, 0.714; Lys, Orn, MeCys, 0.714; Lys, Pro, MeCys, 0.714; Lys, MeCys, PEA, 0.714; Lys, MeCys, Pipecolic acid, 0.714; Lys, MeCys, Thioproline, 0.714; Met , Ser, aAAA, 0.714; Met, Tau, MeCys, 0.714; Phe, Val, hCit, 0.714; Ser, Tau, ADMA, 0.714; Ser, ADMA, hArg, 0.714; Tau, Trp, MeCys, 0.714; Tau, hArg , MeCys, 0.714; Trp, 1-MeHis, MeCys, 0.714; Trp, MeCys, N6-AcLys, 0.714; Tyr, 1-MeHis, MeCys, 0.714; Val, hArg, MeCys, 0.714; Val, MeCys, Thioproline, 0.714 1-MeHis, aAAA, MeCys, 0.714; 1-MeHis, MeCys, Thioproline, 0.714; bAiBA, MeCys, Pipecolic acid, 0.714; GABA, MeCys, N6-AcLys, 0.714; MeCys, N6-AcLys, Kyn / Trp, 0.714; Met, Allyl-Cys, MeCys, 0.714; Ser, Allyl-Cys, Pipecolic acid, 0.714; Allyl-Cys, Cystathionine, MeCys, 0.714; EtOHNH2, Leu, bAiBA, 0.714; EtOHNH2, Ser, GABA, 0.714; Cys2, Gly, ADMA, 0.714; Cys2, Thr, MeCys, 0.714; Cys2, aAAA, MeCys, 0.714; Ala, Orn, MeCys, 0.713; Arg, Lys, MeCys, 0.713; Asn, Met, MeCys, 0.713


Glu, Gly, Pro, 0.713; Glu, Gly, Kyn, 0.713; Gly, Cystathionine, MeCys, 0.713; Gly, MeCys, Thioproline, 0.713; His, MeCys, N6-AcLys, 0.713; Ile, hArg, MeCys, 0.713 Leu, Phe, hArg, 0.713; Leu, MeCys, SDMA, 0.713; Leu, MeCys, Thioproline, 0.713; Lys, MeCys, SDMA, 0.713; Phe, bAiBA, MeCys, 0.713; Pro, hCit, MeCys, 0.713; Ser , ADMA, Kyn, 0.713; Ser, ADMA, PEA, 0.713; Tau, Thr, MeCys, 0.713; Thr, Kyn, MeCys, 0.713; Val, MeCys, PEA, 0.713; 1-MeHis, 3-MeHis, MeCys, 0.713 aAiBA, MeCys, PEA, 0.713; bAiBA, MeCys, PEA, 0.713; aABA, Allyl-Cys, MeCys, 0.712; Arg, MeCys, N6-AcLys, 0.712; Asn, HyPro, MeCys, 0.712; Asn, MeCys, N8 -AcSpd, 0.712; Cit, hCit, MeCys, 0.712; Gln, 1-MeHis, MeCys, 0.712; Gln, HyPro, MeCys, 0.712; Glu, Ser, Pipecolic acid, 0.712; Glu, MeCys, Kyn / Trp, 0.712; Gly, GABA, MeCys, 0.712; His, Leu, MeCys, 0.712; Ile, Kyn, MeCys, 0.712; Leu, Phe, Tyr, 0.712; Lys, Ser, ADMA, 0.712; Lys, Thr, MeCys, 0.712; Met, MeCys, N6-AcLys, 0.712; Orn, Pro, MeCys, 0.712; Orn, MeCys, Spd, 0.712; Pr o, Val, MeCys, 0.712; Pro, HyPro, MeCys, 0.712; Ser, Thr, ADMA, 0.712; Ser, 1-MeHis, ADMA, 0.712; Val, Kyn, MeCys, 0.712; 3-MeHis, hCit, MeCys, 0.712; 3-MeHis, MeCys, N6-AcLys, 0.712; aAAA, Cystathionine, MeCys, 0.712; aAAA, MeCys, N6-AcLys, 0.712; bAiBA, MeCys, Kyn / BCAA, 0.712; hArg, MeCys, N6-AcLys, 0.712; Hypotaurine, HyPro, MeCys, 0.712; Kyn, MeCys, Sar, 0.712; MeCys, N6-AcLys, Sar, 0.712; MeCys, N6-AcLys, Kyn / BCAA, 0.712; Cys2, MeCys, SDMA, 0.712; Ala, HyPro, MeCys, 0.711; Asn, Thr, MeCys, 0.711; Cit, Glu, Gly, 0.711; Cit, bAiBA, MeCys, 0.711; Glu, Gly, Phe, 0.711; Glu, Gly, Trp, 0.711; Glu, Gly, aABA, 0.711; Glu, Met, Ser, 0.711; Gly, Val, aAiBA, 0.711; His, HyPro, MeCys, 0.711; Ile, Lys, MeCys, 0.711; Ile, MeCys, Put, 0.711; Met, 1-MeHis, MeCys, 0.711; Phe, 1-MeHis, MeCys, 0.711; Ser, ADMA, Spd, 0.711; Tau, MeCys, Sar, 0.711; Thr, hArg, MeCys, 0.711; Thr, MeCys, Put, 0.711; Trp, bAiBA, MeCys, 0.711; Tyr, bAiBA, MeCys, 0.711; Val, MeCys, Kyn / BCAA, 0.711; aABA, MeCys, Sar, 0.711; aAAA, MeCys, Pipecolic acid, 0.711; bAiBA, Hypotaurine, MeCys, 0.711; GABA, HyPro, MeCys, 0.711; hArg, MeCys, Pipecolic acid, 0.711; hCit, Hypotaurine, MeCys, 0.711; HyPro, MeCys, Kyn / BCAA, 0.711; Kyn, MeCys, N6-AcLys, 0.711; Kyn, MeCys, PEA, 0.711; Cystathionine, MeCys, N6-AcLys, 0.711; MeCys, N6-AcLys, Thioproline, 0.711; MeCys, N8-AcSpd, Thioproline, 0.711; Cys2, Orn, bAiBA, 0.711; Orn, Allyl-Cys, Pipecolic acid, 0.711; Allyl-Cys, MeCys, Put, 0.711; Arg, Gly, MeCys, 0.71; Arg, Leu, Phe, 0.71; Gln, Gly, Orn , 0.71; Glu, Gly, Hypotaurine, 0.71; Glu, Gly, N8-AcSpd, 0.71; Gly, MeCys, Spd, 0.71; His, aABA, MeCys, 0.71; Ile, 3-MeHis, MeCys, 0.71; Ile, MeCys , N6-AcLys, 0.71; Lys, MeCys, Spd, 0.71; Orn, Pro, aAiBA, 0.71; Orn, Ser, aAiBA, 0.71; Orn, 3-MeHis, MeCys, 0.71; Pro, Ser, ADMA, 0.71; Pro , MeCys, Pipecolic acid, 0.71; Ser, Tyr, ADMA, 0.71; Ser, hCit, Pipecolic acid, 0.71; Tau, Tyr, MeCys, 0.71; Tau, GABA, MeCys, 0.71; Thr, 3-MeHis, MeCys, 0.71 Trp, aABA, MeCys, 0.71; Val, Hypotaurine , MeCys, 0.71; 3-MeHis, aABA, MeCys, 0.71; GABA, hCit, MeCys, 0.71; hArg, HyPro, MeCys, 0.71; hCit, Kyn, MeCys, 0.71; hCit, MeCys, PEA, 0.71; hCit, MeCys , Kyn / Trp, 0.71; HyPro, Cystathionine, MeCys, 0.71; Cys2, Lys, aABA, 0.71; Cys2, Orn, Tyr, 0.71; Asn, Allyl-Cys, MeCys, 0.709; Ser, ADMA, Allyl-Cys, 0.709 Allyl-Cys, GABA, MeCys, 0.709; Allyl-Cys, MeCys, Thioproline, 0.709; Allyl-Cys, MeCys, Kyn / BCAA, 0.709; Arg, bAiBA, MeCys, 0.709; Cit, HyPro, MeCys, 0.709; Gln , aAiBA, MeCys, 0.709; Glu, Gly, GABA, 0.709; Glu, Gly, N6-AcLys, 0.709; Glu, Gly, Spd, 0.709; Glu, Gly, Thioproline, 0.709; Glu, Gly, Kyn / Trp, 0.709 Gly, Val, ADMA, 0.709; Gly, aABA, MeCys, 0.709; His, Tau, MeCys, 0.709; Leu, Phe, aAAA, 0.709; Leu, Ser, Cystathionine, 0.709; Leu, Trp, MeCys, 0.709; Lys , MeCys, N6-AcLys, 0.709; Lys, MeCys, Kyn / BCAA, 0.709; Met, hCit, MeCys, 0.709; Pro, bAiBA, MeCys, 0.709; Ser, Val, Cystathionine, 0.709; Ser, aAiBA, hCit, 0.709 Ser, ADMA, Hypotaurine, 0.709; Ser, bAiBA, Kyn, 0.709; Tau, MeCy s, SDMA, 0.709; Val, MeCys, Spd, 0.709; 1-MeHis, MeCys, Kyn / BCAA, 0.709; ADMA, bAiBA, HyPro, 0.709; EtOHNH2, Gly, Leu, 0.708; EtOHNH2, Gly, MeCys, 0.708; EtOHNH2, Orn, Kyn / BCAA, 0.708; EtOHNH2, Ser, MeCys, 0.708; EtOHNH2, Val, MeCys, 0.708; EtOHNH2, aAiBA, Kyn, 0.708; Cys2, Glu, Met, 0.708; Cys2, ADMA, SDMA, 0.708; EtOHNH2, 3-hKyn, Kyn / BCAA, 0.708; Ala, Allyl-Cys, MeCys, 0.708; Cit, Allyl-Cys, MeCys, 0.708; Glu, Gly, Tyr, 0.708; Glu, Gly, Val, 0.708; Glu, Gly, hArg, 0.708; Glu, Gly, PEA, 0.708; Glu, Ser, hCit, 0.708; Gly, ADMA, Put, 0.708; Gly, ADMA, Kyn / Trp, 0.708; Gly, MeCys, PEA, 0.708; Ile, Thr, MeCys, 0.708; Ile, Hypotaurine, MeCys, 0.708; Ile, MeCys, Kyn / Trp, 0.708; Leu, Phe, hCit, 0.708; Leu, MeCys, Kyn / Trp, 0.708; Lys, Trp, MeCys, 0.708; Lys, Hypotaurine, MeCys, 0.708; Met, MeCys, Pipecolic acid, 0.708; Orn, hCit, Cystathionine, 0.708; Phe, hCit, MeCys, 0.708; Pro, Thr, MeCys, 0.708; Pro, MeCys, Sar, 0.708; Ser , hCit, Put, 0.708; Ser, Cystathionine, Put, 0.708; Tau, 3-MeHis, Me Cys, 0.708; Tau, MeCys, Kyn / Trp, 0.708; Trp, 3-MeHis, MeCys, 0.708; Tyr, HyPro, MeCys, 0.708; ADMA, bAiBA, N8-AcSpd, 0.708; hCit, MeCys, Put, 0.708; Hypotaurine, MeCys, N6-AcLys, 0.708; HyPro, MeCys, Spd, 0.708; HyPro, MeCys, Thioproline, 0.708; MeCys, N8-AcSpd, Spd, 0.708; MeCys, Put, Sar, 0.708; 3-hKyn, MeCys, Spd, 0.707; Cys2, Orn, ADMA, 0.707; Cys2, Orn, hArg, 0.707; Cys2, aABA, Pipecolic acid, 0.707; Cys2, MeCys, Kyn / Trp, 0.707; Asn, Glu, Gly, 0.707; Asn, hCit , MeCys, 0.707; Gln, Pro, MeCys, 0.707; Gln, MeCys, PEA, 0.707; Glu, Gly, Orn, 0.707; Glu, Gly, Thr, 0.707; Gly, Ser, ADMA, 0.707; Gly, ADMA, N8 -AcSpd, 0.707; Gly, hCit, Cystathionine, 0.707; His, Ile, MeCys, 0.707; Ile, Trp, MeCys, 0.707; Ile, MeCys, Sar, 0.707; Lys, 3-MeHis, MeCys, 0.707; Lys, Cystathionine , MeCys, 0.707; Met, bAiBA, MeCys, 0.707; Met, HyPro, MeCys, 0.707; Orn, Phe, aAiBA, 0.707; Orn, Phe, hCit, 0.707; Orn, Phe, N6-AcLys, 0.707; Orn, Phe , Kyn / BCAA, 0.707; Phe, Ser, Trp, 0.707; Phe, Tau, MeCys, 0.707; Pro, M eCys, PEA, 0.707; Trp, MeCys, Kyn / Trp, 0.707; ADMA, bAiBA, N6-AcLys, 0.707; hArg, MeCys, N8-AcSpd, 0.707; HyPro, MeCys, Put, 0.707; Kyn, MeCys, SDMA, 0.707; EtOHNH2, Gly, Orn, 0.706; EtOHNH2, Gly, Val, 0.706; EtOHNH2, Gly, Cystathionine, 0.706; EtOHNH2, aAiBA, Kyn / Trp, 0.706; EtOHNH2, Put, Kyn / BCAA, 0.706; EtOHNH2, Thioproline, Kyn / BCAA, 0.706; Cys2, Orn, Cystathionine, 0.706; Arg, Orn, Phe, 0.706; Arg, Ser, Val, 0.706; Asn, Pro, MeCys, 0.706; Cit, Gly, Val, 0.706; Glu, Gly, Ser, 0.706; Glu, Gly, Tau, 0.706; Glu, Gly, 3-MeHis, 0.706; Glu, Gly, aAiBA, 0.706; Glu, Gly, SDMA, 0.706; Gly, Leu, Pipecolic acid, 0.706; Ile, Leu , Ser, 0.706; Ile, Met, Orn, 0.706; Ile, MeCys, SDMA, 0.706; Ile, MeCys, Thioproline, 0.706; Leu, Phe, N6-AcLys, 0.706; Leu, MeCys, Spd, 0.706; Met, Orn , Ser, 0.706; Orn, Ser, ADMA, 0.706; Phe, aAAA, MeCys, 0.706; Ser, Val, Pipecolic acid, 0.706; Ser, aAAA, Cystathionine, 0.706; Thr, aABA, MeCys, 0.706; Thr, aAAA, MeCys, 0.706; HyPro, MeCys, Kyn / Trp, 0.706; Ala, Val, Me Cys, 0.706; Tau, Cystathionine, MeCys, 0.706; Thr, MeCys, Sar, 0.706; 3-MeHis, Cystathionine, MeCys, 0.706; aABA, MeCys, Pipecolic acid, 0.706; Orn, Phe, Allyl-Cys, 0.705; Ala , Leu, MeCys, 0.704; Ala, Lys, MeCys, 0.704; Ala, Tau, MeCys, 0.704; Ala, MeCys, N6-AcLys, 0.704; Arg, aAiBA, MeCys, 0.704; Asn, Gly, Val, 0.704; Asn , 3-MeHis, MeCys, 0.704; Cit, Gly, MeCys, 0.704; Cit, Tau, MeCys, 0.704; Cit, 3-MeHis, MeCys, 0.704; Cit, MeCys, N6-AcLys, 0.704; Gln, His, MeCys , 0.704; Glu, Gly, aAAA, 0.704; Gly, Leu, bAiBA, 0.704; Gly, Tyr, Val, 0.704; Ile, Orn, Phe, 0.704; Leu, Phe, aAiBA, 0.704; Lys, MeCys, Put, 0.704 Met, Ser, Trp, 0.704; Orn, Ser, HyPro, 0.704; Ser, Cystathionine, N6-AcLys, 0.704; Tyr, hCit, MeCys, 0.704; 3-MeHis, GABA, MeCys, 0.704; 3-MeHis, hArg , MeCys, 0.704; aABA, Kyn, MeCys, 0.704; aAAA, hArg, MeCys, 0.704; aAAA, MeCys, Sar, 0.704; bAiBA, MeCys, Put, 0.704; hCit, HyPro, MeCys, 0.704; hCit, MeCys, Thioproline , 0.704; Kyn, MeCys, Kyn / BCAA, 0.704; MeCys, Pipecolic acid, Sar , 0.704; Asn, Cys2, ADMA, 0.704; Cys2, Met, ADMA, 0.704; Cys2, ADMA, Cystathionine, 0.704; Cys2, Hypotaurine, MeCys, 0.704; Leu, Met, 3-hKyn, 0.704; Allyl-Cys, MeCys , Kyn / Trp, 0.704; Ala, hCit, MeCys, 0.703; Glu, Gly, Lys, 0.703; Glu, Gly, 1-MeHis, 0.703; Glu, Ser, hArg, 0.703; Gly, Ile, Val, 0.703; Gly , Lys, Pipecolic acid, 0.703; Gly, Orn, Pipecolic acid, 0.703; Gly, ADMA, HyPro, 0.703; Gly, bAiBA, Pipecolic acid, 0.703; Ile, MeCys, Pipecolic acid, 0.703; Ile, MeCys, Spd, 0.703 Leu, Met, Phe, 0.703; Leu, Met, Thr, 0.703; Lys, MeCys, Kyn / Trp, 0.703; Met, Val, ADMA, 0.703; Orn, Phe, HyPro, 0.703; Orn, aAiBA, bAiBA, 0.703 Orn, aAiBA, Cystathionine, 0.703; Ser, Val, hCit, 0.703; Ser, 1-MeHis, Cystathionine, 0.703; Ser, Cystathionine, Pipecolic acid, 0.703; Tau, aAAA, MeCys, 0.703; Trp, MeCys, Sar, 0.703; 3-MeHis, MeCys, Kyn / BCAA, 0.703; aABA, MeCys, PEA, 0.703; EtOHNH2, Ile, Cystathionine, 0.703; EtOHNH2, Ile, MeCys, 0.703; EtOHNH2, Ser, Hypotaurine, 0.703; EtOHNH2, Trp, aAiBA, 0.703; EtOHNH2, GABA, Cystathionine, 0.703; EtOHNH2, hArg, Kyn / BCAA, 0.703; EtOHNH2, Cystathionine, Kyn / BCAA, 0.703; Cys2, Gly, Orn, 0.703; Cys2, Pro, ADMA, 0.703; Ala, Leu, Phe, 0.702; Arg, Glu, Ser, 0.702; Arg, Orn, HyPro, 0.702; Asn, Tau, MeCys, 0.702; Cit, Orn, Cystathionine, 0.702; Gly, Ile, bAiBA, 0.702; His, 3-MeHis, MeCys, 0.702; His, Kyn, MeCys, 0.702; His, MeCys, Put, 0.702; Ile, Pro, MeCys, 0.702; Ile, GABA, MeCys, 0.702; Met, Thr, Val, 0.702; Orn, Phe, Cystathionine, 0.702; Orn, aAiBA, Kyn / BCAA, 0.702; Phe, Val, Pipecolic acid, 0.702; Ser, 3-MeHis, Cystathionine, 0.702; Ser, GABA, hCit, 0.702; Ser, N6-AcLys, Pipecolic acid, 0.702; Thr, Trp, MeCys, 0.702; Thr, ADMA, bAiBA, 0.702; Thr, GABA, MeCys, 0.702; Trp, aAiBA, MeCys, 0.702; 3-MeHis, MeCys, Put, 0.702; 3-MeHis, MeCys, Kyn / Trp, 0.702; aABA, aAiBA, MeCys, 0.702; aAAA, MeCys, Kyn / BCAA, 0.702; bAiBA, MeCys, SDMA, 0.702; hCit, Cystathionine, MeCys, 0.702; MeCys, N6-AcLys, Spd, 0.702; MeCys, PEA, Spd, 0.702; EtOHNH2, 3-hKyn, Cystath ionine, 0.702; Cys2, Glu, ADMA, 0.702; Cys2, Orn, Ser, 0.702; Cys2, Orn, aAAA, 0.702; Cys2, Orn, hCit, 0.702; Orn, 3-hKyn, bAiBA, 0.701; Arg, Tau, MeCys, 0.701; Arg, Thr, MeCys, 0.701; Gln, hCit, MeCys, 0.701; Glu, Gly, Leu, 0.701; Gly, ADMA


, Cystathionine, 0.701; Gly, hCit, SDMA, 0.701; His, MeCys, Pipecolic acid, 0.701; His, MeCys, Sar, 0.701; Ile, Ser, Cystathionine, 0.701; Leu, Phe, Val, 0.701; Orn, Ser, Hypotaurine, 0.701; Tyr, Kyn, MeCys, 0.701; aAAA, MeCys, SDMA, 0.701; hCit, MeCys, Spd, 0.701; MeCys, PEA, Put, 0.701; Allyl-Cys, MeCys, Pipecolic acid, 0.701; EtOHNH2, Glu , aAiBA, 0.701; EtOHNH2, Glu, MeCys, 0.701; EtOHNH2, Gly, Hypotaurine, 0.701; EtOHNH2, Leu, Ser, 0.701; EtOHNH2, Leu, aABA, 0.701; EtOHNH2, Ser, aAiBA, 0.701; EtOHNH2, Val, aABA , 0.701; EtOHNH2, 3-MeHis, aAiBA, 0.701; EtOHNH2, aABA, hCit, 0.701; EtOHNH2, aAiBA, SDMA, 0.701; EtOHNH2, ADMA, bAiBA, 0.701; EtOHNH2, hArg, MeCys, 0.701; EtOHNH2, Pipecolic acid, Kyn / BCAA, 0.701; Cys2, His, Orn, 0.7; Cys2, Orn, aAiBA, 0.7; Cit, Orn, HyPro, 0.7; Gln, 3-MeHis, MeCys, 0.7; Glu, Gly, Kyn / BCAA, 0.7; Ile, Phe, Ser, 0.7; Ile, aAAA, MeCys, 0.7; Leu, Met, hArg, 0.7; Lys, Met, Ser, 0.7; Met, aABA, MeCys, 0.7; Met, MeCys, PEA, 0.7; Orn, Tyr, N6-AcLys, 0.7; Phe, Ser, h Cit, 0.7; Ser, Trp, bAiBA, 0.7; Ser, aABA, Pipecolic acid, 0.7; Ser, HyPro, Cystathionine, 0.7; Tau, MeCys, PEA, 0.7; Thr, MeCys, PEA, 0.7; Trp, Kyn, MeCys , 0.7; Trp, MeCys, PEA, 0.7; Kyn, Cystathionine, MeCys, 0.7; MeCys, Put, Kyn / BCAA, 0.7; Leu, Phe, Allyl-Cys, 0.699; Orn, Allyl-Cys, Cystathionine, 0.699; Thr , Allyl-Cys, Pipecolic acid, 0.699; Cys2, Gln, aABA, 0.699; Cys2, Orn, Hypotaurine, 0.699; Cys2, aABA, hCit, 0.699; Cys2, aABA, Hypotaurine, 0.699; Cys2, ADMA, aAAA, 0.699; Cys2, ADMA, hArg, 0.699; Cys2, ADMA, Hypotaurine, 0.699; Ala, ADMA, bAiBA, 0.699; Asn, Leu, Phe, 0.699; Cit, Orn, aAiBA, 0.699; Cit, MeCys, Pipecolic acid, 0.699; Gln , MeCys, Sar, 0.699; Glu, Gly, His, 0.699; Glu, Ser, aAiBA, 0.699; Gly, Met, Orn, 0.699; Gly, Orn, SDMA, 0.699; Gly, aAiBA, Pipecolic acid, 0.699; His, Leu, Phe, 0.699; His, Trp, MeCys, 0.699; His, MeCys, PEA, 0.699; Ile, Ser, Val, 0.699; Ile, MeCys, Kyn / BCAA, 0.699; Leu, Lys, Phe, 0.699; Leu, Phe, 3-MeHis, 0.699; Lys, Kyn, MeCys, 0.699; Met, Ser, hCit, 0.699; Met, Thr, MeCys, 0.699; Met, aAAA, MeCys, 0.699; Orn, aAiBA, hCit, 0.699; Orn, aAiBA, N6-AcLys, 0.699; Orn, ADMA, Cystathionine, 0.699; Phe, Val, aABA, 0.699; Phe, Val, aAiBA, 0.699; Phe, ADMA, Pipecolic acid, 0.699; Ser, Trp, Pipecolic acid, 0.699; Ser, Tyr, hCit, 0.699; Ser, aABA, N6-AcLys, 0.699; Ser, Hypotaurine, Cystathionine, 0.699; Thr, MeCys, Kyn / Trp, 0.699; Thr, MeCys, Kyn / BCAA, 0.699; Tyr, aABA, MeCys, 0.699; Tyr, MeCys, Pipecolic acid, 0.699; aABA, MeCys, SDMA, 0.699 AABA, MeCys, Kyn / BCAA, 0.699; ADMA, bAiBA, Kyn / BCAA, 0.699; ADMA, Cystathionine, Pipecolic acid, 0.699; aAAA, MeCys, PEA, 0.699; GABA, MeCys, Pipecolic acid, 0.699; Hypotaurine, MeCys , Spd, 0.699; MeCys, PEA, Sar, 0.699; MeCys, Pipecolic acid, SDMA, 0.699; EtOHNH2, 3-hKyn, bAiBA, 0.699; Arg, EtOHNH2, Kyn / BCAA, 0.698; EtOHNH2, Phe, aAiBA, 0.698; EtOHNH2, Ser, Kyn / BCAA, 0.698; EtOHNH2, Tyr, Kyn / BCAA, 0.698; Ala, Glu, Gly, 0.698; Arg, Gln, MeCys, 0.698; Gln, aAAA, MeCys, 0.698; Glu, Gly, Ile, 0.698; Glu, Ser, bAiBA, 0.698; Gly, Orn, Hypotaurine, 0.698; His, Met, Orn, 0.698; Leu, Phe, bAiBA, 0.698; Leu, Phe, Put, 0.698; Lys, Met, Orn, 0.698; Orn, 1-MeHis, Cystathionine, 0.698; Orn, aABA, Cystathionine, 0.698; Ser, aABA, Kyn, 0.698; Ser, HyPro, N8-AcSpd, 0.698; Tau, MeCys, Thioproline, 0.698; Tau, MeCys, Kyn / BCAA, 0.698; Thr, Tyr, MeCys, 0.698; Thr, Cystathionine, MeCys, 0.698; Tyr, 3-MeHis, MeCys, 0.698; 3-MeHis, MeCys, Thioproline, 0.698; aAiBA, Hypotaurine, MeCys, 0.698; GABA, Kyn, MeCys, 0.698; hArg, Kyn, MeCys, 0.698; MeCys, Put, Spd, 0.698; Cys2, Orn, GABA, 0.698; Cys2, Orn, Put, 0.698; Cys2, Orn, Thioproline, 0.698; Cys2, ADMA, Thioproline, 0.698; EtOHNH2, Ser, Allyl-Cys, 0.697; Ala, Thr, MeCys, 0.697; Cit, Leu, Phe, 0.697; Cit, Orn, bAiBA, 0.697; Gln, Met, MeCys, 0.697; Gln, Trp, MeCys, 0.697; Gln, Tyr, MeCys, 0.697; Gln, MeCys, Kyn / BCAA, 0.697; Glu, Ser, Kyn / Trp, 0.697; Gly, Ile, Cystathionine, 0.697; Gly, Val, 3-MeHis, 0.697; Gly, ADMA, Hypotaurine, 0.697; Leu, Phe, Pro, 0 .697; Leu, Phe, Hypotaurine, 0.697; Orn, Val, aAiBA, 0.697; Orn, Cystathionine, N8-AcSpd, 0.697; Orn, Cystathionine, Thioproline, 0.697; Phe, Pro, Val, 0.697; Pro, Ser, HyPro , 0.697; Ser, Trp, hCit, 0.697; Ser, Val, hArg, 0.697; Ser, aAiBA, N6-AcLys, 0.697; Ser, aAAA, Pipecolic acid, 0.697; Ser, hArg, hCit, 0.697; Ser, HyPro, Pipecolic acid, 0.697; Thr, ADMA, Put, 0.697; Trp, aAAA, MeCys, 0.697; 3-MeHis, aAAA, MeCys, 0.697; 3-MeHis, Kyn, MeCys, 0.697; 3-MeHis, MeCys, PEA, 0.697 aABA, MeCys, Put, 0.697; aABA, MeCys, Kyn / Trp, 0.697; ADMA, N8-AcSpd, Pipecolic acid, 0.697; aAiBA, Allyl-Cys, MeCys, 0.697; Arg, Cys2, ADMA, 0.696; Cit, Cys2, Orn, 0.696; Cys2, Glu, Phe, 0.696; Cys2, Glu, aAAA, 0.696; Cys2, Orn, Sar, 0.696; Cys2, Trp, ADMA, 0.696; Cys2, aAiBA, ADMA, 0.696; Arg, Ser, hCit, 0.696; Asn, Orn, Phe, 0.696; Asn, MeCys, Pipecolic acid, 0.696; Cit, Gly, ADMA, 0.696; Gln, Ser, hCit, 0.696; Gln, aABA, MeCys, 0.696; Gln, MeCys, Pipecolic acid, 0.696; Glu, Ser, aABA, 0.696; Gly, Ile, Leu, 0.696; Gly, Ile, Pipecolic acid, 0.696; Gly, ADMA, hCit, 0.696; Gly, ADMA, N6-AcLys, 0.696; Gly, bAiBA, Kyn, 0.696; Ile, Ser, Pipecolic acid, 0.696; Leu, Phe, PEA, 0.696; Leu, Phe, Thioproline, 0.696; Lys, Orn, aAiBA, 0.696; Met, Phe, MeCys, 0.696; Met, 3-MeHis, MeCys, 0.696; Orn, Phe, 1-MeHis, 0.696; Orn, Ser, Trp, 0.696; Orn, Ser, hArg, 0.696; Orn, Ser, N6-AcLys, 0.696; Orn, aABA, aAiBA, 0.696; Orn, Hypotaurine, Cystathionine, 0.696; Phe, Pro, MeCys, 0.696; Phe, 3-MeHis, MeCys, 0.696; Pro, aAAA, MeCys, 0.696; Pro, Cystathionine, MeCys, 0.696; Ser, Tyr, Cystathionine, 0.696; Ser, Val, aABA, 0.696; Ser, bAiBA, Pipecolic acid, 0.696; Ser , hCit, SDMA, 0.696; Thr, MeCys, Thioproline, 0.696; Trp, Cystathionine, MeCys, 0.696; Tyr, aAAA, MeCys, 0.696; Val, ADMA, Cystathionine, 0.696; 3-MeHis, Hypotaurine, MeCys, 0.696; aAAA , MeCys, Thioproline, 0.696; aAAA, MeCys, Kyn / Trp, 0.696; Kyn, MeCys, Put, 0.696; Kyn, MeCys, Thioproline, 0.696; EtOHNH2, Leu, Pro, 0.695; EtOHNH2, Met, Kyn / BCAA, 0.695 ; EtOHNH2, Orn, Phe, 0.695; EtOHNH2, aAiBA, hCit, 0.695; EtOHNH2, hCit, MeCys, 0.695; EtOHNH2, Kyn, MeCys, 0.695; Ser, 3-hKyn, ADMA, 0.695; Gly, Allyl-Cys, Pipecolic acid , 0.695; Orn, Ser, Allyl-Cys, 0.695; Orn, Allyl-Cys, hCit, 0.695; Ser, Trp, Allyl-Cys, 0.695; Ala, Cys2, Orn, 0.695; Ala, Cys2, ADMA, 0.695; Arg , Cys2, Orn, 0.695; Asn, Cys2, Orn, 0.695; Cit, Cys2, ADMA, 0.695; Cys2, Gln, ADMA, 0.695; Cys2, Orn, Kyn, 0.695; Cys2, Orn, Spd, 0.695; Cys2, aAiBA , bAiBA, 0.695; Ala, Ile, MeCys, 0.694; Arg, 3-MeHis, MeCys, 0.694; Arg, aAAA, MeCys, 0.694; Arg, MeCys, Pipecolic acid, 0.694; Asn, Ser, Pipecolic acid, 0.694; Asn , aAAA, MeCys, 0.694; Cit, Ser, Kyn, 0.694; Cit, Thr, MeCys, 0.694; Gln, Gly, Val, 0.694; Gln, Leu, Phe, 0.694; Glu, Gly, HyPro, 0.694; Glu, Orn , Cystathionine, 0.694; Glu, Ser, Thr, 0.694; Glu, Ser, Kyn, 0.694; Gly, Leu, ADMA, 0.694; Gly, Trp, Cystathionine, 0.694; Gly, Val, aABA, 0.694; Leu, Phe, HyPro , 0.694; Leu, Phe, Spd, 0.694; Met, Orn, N6-AcLys, 0.694; Met, Ser, Cys tathionine, 0.694; Orn, Phe, bAiBA, 0.694; Orn, Phe, SDMA, 0.694; Orn, 3-MeHis, Cystathionine, 0.694; Orn, aAiBA, N8-AcSpd, 0.694; Orn, Cystathionine, Put, 0.694; Phe, Thr, MeCys, 0.694; Phe, Tyr, MeCys, 0.694; Phe, Val, Cystathionine, 0.694; Phe, aABA, MeCys, 0.694; Phe, MeCys, Pipecolic acid, 0.694; Pro, aABA, MeCys, 0.694; Ser, Trp , Cystathionine, 0.694; Ser, hCit, N8-AcSpd, 0.694; Thr, MeCys, SDMA, 0.694; Trp, GABA, MeCys, 0.694; Trp, MeCys, Pipecolic acid, 0.694; aABA, Cystathionine, MeCys, 0.694; aAiBA, MeCys, Put, 0.694; aAAA, Kyn, MeCys, 0.694; hArg, MeCys, PEA, 0.694; MeCys, PEA, Thioproline, 0.694; Cys2, Orn, Val, 0.694; Cys2, Tyr, ADMA, 0.694; Cys2, Val, aABA, 0.694; Cys2, 3-MeHis, ADMA, 0.694; Arg, Leu, HyPro, 0.693; Arg, Orn, Ser, 0.693; Asn, Kyn, MeCys, 0.693; Cit, Glu, Ser, 0.693; Cit, Ser, PEA, 0.693; Cit, aABA, MeCys, 0.693; Gln, Met, Orn, 0.693; Gln, Orn, aAiBA, 0.693; Gly, Orn, hCit, 0.693; Gly, Pro, Val, 0.693; Gly, aAAA, Cystathionine, 0.693; Lys, Ser, aABA, 0.693; Met, Orn, Phe, 0.693; Met, Orn, Pro, 0.693; Met, Orn, aAiBA, 0.693; Met, Orn, aAAA, 0.693; Met, Orn, Put, 0.693; Met, MeCys, Put, 0.693; Met, MeCys, Sar, 0.693; Orn, Thr, Cystathionine, 0.693; Orn, Tyr, hCit, 0.693; Orn, hArg, Cystathionine, 0.693; Orn, HyPro, N8-AcSpd, 0.693; Orn, Kyn, Cystathionine, 0.693; Phe, Ser, Cystathionine, 0.693; Phe, Kyn, MeCys, 0.693; Phe, Kyn, Kyn / BCAA, 0.693; Pro, Trp, MeCys, 0.693; Ser, Tau, Cystathionine, 0.693; Ser, Trp, aAiBA, 0.693; Ser, Trp, HyPro, 0.693; Ser, Val, aAiBA, 0.693; Ser, Val, bAiBA, 0.693; Ser, Cystathionine, N8-AcSpd, 0.693; Ser, Pipecolic acid, Put, 0.693; Thr, hCit, Cystathionine, 0.693; Trp , Tyr, MeCys, 0.693; Tyr, hArg, MeCys, 0.693; aAiBA, MeCys, Sar, 0.693; ADMA, HyPro, N8-AcSpd, 0.693; ADMA, HyPro, Pipecolic acid, 0.693; Kyn, MeCys, Kyn / Trp, 0.693; MeCys, Pipecolic acid, Put, 0.693; MeCys, Pipecolic acid, Thioproline, 0.693; MeCys, Pipecolic acid, Kyn / Trp, 0.693; Cys2, EtOHNH2, aABA, 0.693; EtOHNH2, Gly, Lys, 0.693; EtOHNH2, Hi s, MeCys, 0.693; EtOHNH2, Ile, Leu, 0.693; EtOHNH2, Orn, Tyr, 0.693; EtOHNH2, Orn, GABA, 0.693; EtOHNH2, Pro, MeCys, 0.693; EtOHNH2, Ser, Thr, 0.693; EtOHNH2, Trp, Kyn / BCAA, 0.693; EtOHNH2, aAiBA, PEA, 0.693; EtOHNH2, aAiBA, Kyn / BCAA, 0.693; EtOHNH2, HyPro, MeCys, 0.693; EtOHNH2, MeCys, Put, 0.693; EtOHNH2, Kyn / Trp, Kyn / BCAA, 0.693; Cys2, Glu, N8-AcSpd, 0.692; Cys2, His, ADMA, 0.692; Cys2, Orn, N8-AcSpd, 0.692; Cys2, Tyr, aABA, 0.692; Cys2, aABA, Kyn, 0.692; Cys2, aABA, Thioproline, 0.692; Cys2, ADMA, Allyl-Cys, 0.692; Cys2, ADMA, Sar, 0.692; Cys2, ADMA, Spd, 0.692; Cys2, ADMA, Kyn / Trp, 0.692; Cys2, bAiBA, HyPro, 0.692; Orn, Pro, Allyl-Cys, 0.692; Ser, 3-hKyn, bAiBA, 0.692; Arg, MeCys, Sar, 0.692; Cit, Ser, Cystathionine, 0.692; Cit, Trp, MeCys, 0.692; Cit, MeCys, PEA, 0.692; Glu, Orn, Phe, 0.692; Gly, Orn, Val, 0.692; Gly, Tau, Hypotaurine, 0.692; Gly, Val, hArg, 0.692; Gly, Val, Hypotaurine, 0.692; Gly, 3-MeHis, ADMA, 0.692; His, hArg, MeCys, 0.692; Leu, Phe, Kyn / BCAA, 0.692; Leu, Se r, hCit, 0.692; Leu, ADMA, bAiBA, 0.692; Lys, Orn, Phe, 0.692; Met, Orn, Trp, 0.692; Met, Orn, Cystathionine, 0.692; Met, Orn, Spd, 0.692; Met, Kyn, MeCys, 0.692; Orn, Val, Cystathionine, 0.692; Orn, aAiBA, Sar, 0.692; Orn, Cystathionine, Pi


pecolic acid, 0.692; Phe, Ser, Kyn, 0.692; Phe, Val, Put, 0.692; Phe, aAiBA, MeCys, 0.692; Phe, MeCys, PEA, 0.692; Phe, MeCys, Put, 0.692; Pro, MeCys, Kyn / BCAA, 0.692; Ser, hArg, Pipecolic acid, 0.692; Ser, hCit, Sar, 0.692; Trp, MeCys, Put, 0.692; Trp, MeCys, SDMA, 0.692; Tyr, MeCys, PEA, 0.692; aABA, hArg, MeCys, 0.692; aAiBA, ADMA, bAiBA, 0.692; aAiBA, hArg, MeCys, 0.692; aAiBA, Cystathionine, MeCys, 0.692; aAiBA, MeCys, Kyn / BCAA, 0.692; ADMA, hCit, SDMA, 0.692; GABA, MeCys, PEA, 0.692; hArg, MeCys, SDMA, 0.692; Hypotaurine, MeCys, Put, 0.692; MeCys, Pipecolic acid, Kyn / BCAA, 0.692; Ala, Orn, aAiBA, 0.691; Ala, Pro, MeCys, 0.691; Arg, Ser , Cystathionine, 0.691; Asn, MeCys, Put, 0.691; Cit, Gln, MeCys, 0.691; Gln, Orn, Cystathionine, 0.691; Gln, Kyn, MeCys, 0.691; Glu, Orn, Ser, 0.691; Gly, Orn, ADMA , 0.691; Gly, Orn, HyPro, 0.691; Gly, Cystathionine, N6-AcLys, 0.691; Gly, Cystathionine, Pipecolic acid, 0.691; His, Orn, aAiBA, 0.691; His, Ser, Cystathionine, 0.691; His, Thr, MeCys, 0 .691; Leu, Orn, aAiBA, 0.691; Met, Orn, 1-MeHis, 0.691; Met, Orn, bAiBA, 0.691; Met, Orn, Kyn, 0.691; Orn, Phe, Tyr, 0.691; Orn, Phe, N8 -AcSpd, 0.691; Orn, Phe, Sar, 0.691; Orn, Phe, Kyn / Trp, 0.691; Orn, Trp, aAiBA, 0.691; Orn, aAiBA, HyPro, 0.691; Orn, aAiBA, Kyn / Trp, 0.691; Orn , Cystathionine, Kyn / Trp, 0.691; Phe, Val, bAiBA, 0.691; Pro, Ser, Cystathionine, 0.691; Pro, 3-MeHis, MeCys, 0.691; Pro, Kyn, MeCys, 0.691; Pro, MeCys, SDMA, 0.691 Ser, Thr, Cystathionine, 0.691; Ser, Thr, Pipecolic acid, 0.691; Ser, hCit, N6-AcLys, 0.691; Ser, hCit, Kyn / Trp, 0.691; Ser, Cystathionine, Thioproline, 0.691; Trp, hArg, MeCys, 0.691; Val, ADMA, bAiBA, 0.691; ADMA, GABA, HyPro, 0.691; ADMA, hCit, Cystathionine, 0.691; ADMA, Pipecolic acid, SDMA, 0.691; aAAA, GABA, MeCys, 0.691; aAAA, MeCys, Put , 0.691; Cystathionine, MeCys, PEA, 0.691; Cystathionine, MeCys, Put, 0.691; Cystathionine, MeCys, Sar, 0.691; MeCys, PEA, Kyn / Trp, 0.691; Cys2, Gln, Orn, 0.691; Cys2, Glu, Cystathionine , 0.691; Cys2, Pro, a ABA, 0.691; Cys2, Trp, aABA, 0.691; Cys2, Val, ADMA, 0.691; Cys2, aABA, Cystathionine, 0.691; Orn, Allyl-Cys, HyPro, 0.691; Ser, 3-hKyn, Pipecolic acid, 0.691; 3 -hKyn, ADMA, bAiBA, 0.691; Cit, EtOHNH2, aAiBA, 0.69; Cit, EtOHNH2, Kyn / BCAA, 0.69; EtOHNH2, Leu, aAiBA, 0.69; EtOHNH2, Lys, aABA, 0.69; EtOHNH2, Orn, Ser, 0.69 EtOHNH2, Orn, aABA, 0.69; EtOHNH2, 1-MeHis, MeCys, 0.69; EtOHNH2, 3-MeHis, Kyn / BCAA, 0.69; EtOHNH2, aABA, aAiBA, 0.69; EtOHNH2, aABA, bAiBA, 0.69; EtOHNH2, aAiBA , aAAA, 0.69; Arg, Lys, Ser, 0.69; Arg, aABA, MeCys, 0.69; Arg, MeCys, Put, 0.69; Asn, His, MeCys, 0.69; Asn, Orn, aAiBA, 0.69; Asn, Tyr, MeCys , 0.69; Asn, aABA, MeCys, 0.69; Cit, Orn, ADMA, 0.69; Cit, Ser, 1-MeHis, 0.69; Cit, Ser, aAiBA, 0.69; Cit, ADMA, bAiBA, 0.69; Cit, aAAA, MeCys , 0.69; Cit, MeCys, SDMA, 0.69; Glu, Ser, N6-AcLys, 0.69; Gly, Lys, ADMA, 0.69; Gly, Orn, Put, 0.69; Gly, Orn, Kyn / BCAA, 0.69; Gly, ADMA , hArg, 0.69; Gly, aAAA, bAiBA, 0.69; His, Ser, hCit, 0.69; Leu, Phe, Kyn / Trp, 0.69; Met, Orn, Tyr, 0.69; Orn, Pro, Cystathionine, 0.69; Orn, Tau, Cystathionine, 0.69; Orn, ADMA, SDMA, 0.69; Orn, hArg, HyPro, 0.69; Orn, HyPro, Cystathionine, 0.69; Orn, Cystathionine, Spd, 0.69; Phe, ADMA, hCit, 0.69; Phe, MeCys, Kyn / Trp, 0.69; Pro, Ser, hCit, 0.69; Ser, Thr, hCit, 0.69; Ser, bAiBA, Cystathionine, 0.69; Ser, hCit, HyPro, 0.69; Ser, hCit, Kyn / BCAA, 0.69; Ser, Kyn, N8-AcSpd, 0.69; Ser, Cystathionine, Kyn / BCAA, 0.69; Ser, Pipecolic acid, Thioproline, 0.69; Tyr, MeCys, Sar, 0.69; Val , Cystathionine, Kyn / Trp, 0.69; aABA, GABA, MeCys, 0.69; aABA, MeCys, Thioproline, 0.69; ADMA, bAiBA, Sar, 0.69; MeCys, PEA, SDMA, 0.69; Cys2, Lys, ADMA, 0.69; Cys2 , Orn, Tau, 0.69; Cys2, Orn, HyPro, 0.69; Cys2, ADMA, N6-AcLys, 0.69; Cys2, ADMA, PEA, 0.69; Orn, Allyl-Cys, Thioproline, 0.689; Ala, Gly, Val, 0.689 Ala, Met, Orn, 0.689; Ala, Orn, Phe, 0.689; Ala, Phe, Val, 0.689; Arg, Gly, ADMA, 0.689; Arg, Orn, Cystathionine, 0.689; Arg, Val, HyPro, 0.689; Arg , ADMA, bAiBA, 0.689; Asn, Gly, ADMA, 0.689; As n, Orn, Cystathionine, 0.689; Asn, Phe, Val, 0.689; Asn, Ser, hCit, 0.689; Asn, aAiBA, MeCys, 0.689; Asn, MeCys, Sar, 0.689; Gln, Gly, Pipecolic acid, 0.689; Gln , ADMA, bAiBA, 0.689; Gln, MeCys, Put, 0.689; Glu, Ser, Val, 0.689; Glu, Ser, HyPro, 0.689; Glu, ADMA, bAiBA, 0.689; Gly, Orn, Phe, 0.689; Gly, Orn , 3-MeHis, 0.689; Gly, Trp, Hypotaurine, 0.689; Gly, aABA, Pipecolic acid, 0.689; Gly, aAiBA, ADMA, 0.689; Gly, Hypotaurine, PEA, 0.689; Gly, Hypotaurine, Pipecolic acid, 0.689; His , Met, MeCys, 0.689; His, Phe, Val, 0.689; His, Pro, MeCys, 0.689; Leu, Phe, Trp, 0.689; Leu, Phe, 1-MeHis, 0.689; Lys, Ser, hArg, 0.689; Orn , Pro, Ser, 0.689; Orn, Tyr, Cystathionine, 0.689; Orn, ADMA, N8-AcSpd, 0.689; Orn, bAiBA, hArg, 0.689; Orn, Cystathionine, PEA, 0.689; Orn, Cystathionine, SDMA, 0.689; Phe , Trp, MeCys, 0.689; Phe, hArg, MeCys, 0.689; Ser, 1-MeHis, Pipecolic acid, 0.689; Ser, aABA, Cystathionine, 0.689; Ser, aAiBA, Cystathionine, 0.689; Ser, hArg, Cystathionine, 0.689; Ser, hCit, Kyn, 0.689; Ser, Hypotaurine, Pipecolic acid, 0.689; Ser, Kyn, Put, 0.689; Trp, MeCys, Thioproline, 0.689; Tyr, MeCys, Put, 0.689; aABA, Hypotaurine, MeCys, 0.689; ADMA, bAiBA, SDMA, 0.689 ADMA, GABA, Pipecolic acid, 0.689; GABA, MeCys, SDMA, 0.689; hArg, MeCys, Put, 0.689; Cys2, Tau, ADMA, 0.688; Cys2, Lys, Orn, 0.688; Cys2, Orn, Thr, 0.688; Cys2, 1-MeHis, ADMA, 0.688; Cys2, aABA, Put, 0.688; Lys, Allyl-Cys, Pipecolic acid, 0.688; Leu, Phe, 3-hKyn, 0.688; Ala, Ser, Pipecolic acid, 0.688; Ala, 3-MeHis, MeCys, 0.688; Ala, MeCys, PEA, 0.688; Arg, His, MeCys, 0.688; Arg, Met, Orn, 0.688; Arg, Orn, aAiBA, 0.688; Arg, Phe, Val, 0.688; Cit, His, MeCys, 0.688; Cit, Ser, 3-MeHis, 0.688; Cit, aAiBA, MeCys, 0.688; Gln, Orn, Tyr, 0.688; Gln, Ser, Pipecolic acid, 0.688; Gln, MeCys, SDMA, 0.688; Glu , Pro, Ser, 0.688; Glu, Ser, Hypotaurine, 0.688; Glu, Ser, Sar, 0.688; Glu, ADMA, N8-AcSpd, 0.688; Gly, Ile, ADMA, 0.688; Gly, Val, hCit, 0.688; Gly , Val, HyPro, 0.688; Gly, Val, Put, 0.688; Gly, HyPro, Pip ecolic acid, 0.688; His, GABA, MeCys, 0.688; His, MeCys, Thioproline, 0.688; Lys, Ser, Pipecolic acid, 0.688; Lys, ADMA, bAiBA, 0.688; Met, Orn, 3-MeHis, 0.688; Met, Orn, GABA, 0.688; Met, Orn, hCit, 0.688; Met, Pro, MeCys, 0.688; Met, hArg, MeCys, 0.688; Met, MeCys, SDMA, 0.688; Orn, Ser, aABA, 0.688; Orn, aAiBA, Put, 0.688; Orn, hArg, hCit, 0.688; Phe, Val, Hypotaurine, 0.688; Phe, Val, N6-AcLys, 0.688; Phe, ADMA, bAiBA, 0.688; Phe, GABA, MeCys, 0.688; Phe, MeCys, Thioproline, 0.688; Pro, ADMA, bAiBA, 0.688; Pro, MeCys, Put, 0.688; Ser, Val, HyPro, 0.688; Ser, aAAA, hCit, 0.688; Ser, bAiBA, SDMA, 0.688; Ser, hCit, Hypotaurine, 0.688; Ser, N8-AcSpd, Pipecolic acid, 0.688; Ser, Pipecolic acid, Sar, 0.688; Tyr, MeCys, SDMA, 0.688; 3-MeHis, MeCys, Spd, 0.688; aAiBA, MeCys, Spd, 0.688; ADMA, HyPro, Put, 0.688; ADMA, Cystathionine, N8-AcSpd, 0.688; hArg, MeCys, Sar, 0.688; MeCys, Put, Thioproline, 0.688; Cit, EtOHNH2, Ser, 0.688; EtOHNH2, Leu, Kyn / BCAA, 0.688; EtOHNH2, Met, Orn, 0.688; EtO HNH2, Orn, Kyn, 0.688; EtOHNH2, Pro, Ser, 0.688; EtOHNH2, Ser, ADMA, 0.688; EtOHNH2, Val, aAiBA, 0.688; EtOHNH2, 1-MeHis, bAiBA, 0.688; EtOHNH2, aAiBA, Cystathionine, 0.688; EtOHNH2, ADMA, MeCys, 0.688; EtOHNH2, Cystathionine, MeCys, 0.688; EtOHNH2, MeCys, Sar, 0.688; EtOHNH2, Sar, Kyn / BCAA, 0.688; Cys2, Glu, Ser, 0.687; Cys2, Ile, Orn, 0.687; Cys2, Orn, N6-AcLys, 0.687; Cys2, Orn, PEA, 0.687; Cys2, Orn, Kyn / Trp, 0.687; Cys2, Thr, ADMA, 0.687; Cys2, ADMA, Kyn, 0.687; Cys2, EtOHNH2, Cystathionine, 0.687; Ala, Gly, ADMA, 0.687; Ala, Ser, HyPro, 0.687; Ala, Trp, MeCys, 0.687; Ala, aAAA, MeCys, 0.687; Arg, Ser, Pipecolic acid, 0.687; Arg, Trp, MeCys, 0.687 Arg, MeCys, PEA, 0.687; Asn, Ser, Cystathionine, 0.687; Asn, MeCys, PEA, 0.687; Cit, Met, Orn, 0.687; Cit, Orn, Phe, 0.687; Cit, Orn, Pipecolic acid, 0.687; Cit, Kyn, MeCys, 0.687; Glu, Ile, Ser, 0.687; Glu, Phe, Val, 0.687; Glu, Ser, Tyr, 0.687; Glu, hArg, Cystathionine, 0.687; Gly, Leu, Orn, 0.687; Gly, Lys, Cystathionine, 0.687; Gly, Orn, aAiBA, 0.687; Gly, Orn, Thioproline, 0.687; Gly, Trp, SDMA, 0.687; Gly, Val, SDMA, 0.687; Gly, ADMA, Sar, 0.687; Gly, Kyn, Cystathionine, 0.687; Gly, Pipecolic acid , SDMA, 0.687; His, Orn, Cystathionine, 0.687; His, Phe, MeCys, 0.687; His, MeCys, SDMA, 0.687; Leu, Phe, GABA, 0.687; Met, Orn, hArg, 0.687; Met, Orn, Kyn / Trp, 0.687; Orn, Phe, Pro, 0.687; Orn, Ser, Tyr, 0.687; Orn, 3-MeHis, aAiBA, 0.687; Phe, Ser, aAAA, 0.687; Ser, aAiBA, Kyn, 0.687; Ser, GABA , Cystathionine, 0.687; Ser, hCit, Thioproline, 0.687; Ser, HyPro, N6-AcLys, 0.687; Ser, Cystathionine, SDMA, 0.687; Ser, Pipecolic acid, Spd, 0.687; Tyr, Cystathionine, MeCys, 0.687; Val, hArg, Cystathionine, 0.687; aABA, ADMA, hCit, 0.687; ADMA, bAiBA, Put, 0.687; ADMA, Pipecolic acid, Put, 0.687; Cystathionine, MeCys, Pipecolic acid, 0.687; MeCys, SDMA, Kyn / Trp, 0.687; Phe, Val, Allyl-Cys, 0.687; EtOHNH2, 3-hKyn, aAiBA, 0.686; Cys2, Glu, Orn, 0.686; Cys2, Ile, ADMA, 0.686; Cys2, aABA, bAiBA, 0.686; Cys2, aABA, N8- AcSpd, 0.686 Ala, Orn, Cystathionine, 0.686; Asn, Met, Orn, 0.686; Asn, Ser, HyPro, 0.686; Asn, Trp, MeCys, 0.686; Cit, Orn, hCit, 0.686; Cit, Phe, MeCys, 0.686; Cit , Ser, Pipecolic acid, 0.686; Cit, Tyr, MeCys, 0.686; Cit, MeCys, Put, 0.686; Gln, Glu, Ser, 0.686; Gln, Orn, Phe, 0.686; Gln, Ser, HyPro, 0.686; Gln, GABA, MeCys, 0.686; Glu, His, Ser, 0.686; Glu, Ser, Trp, 0.686; Glu, Ser, 1-MeHis, 0.686; Glu, Ser, aAAA, 0.686; Glu, Ser, PEA, 0.686; Gly, Val, aAAA, 0.686; Gly, ADMA, GABA, 0.686; His, Orn, Phe, 0.686; His, Ser, Pipecolic acid, 0.686; His, aAAA, MeCys, 0.686; Ile, Orn, aAiBA, 0.686; Leu, Phe , Tau, 0.686; Leu, Phe, Cystathionine, 0.686; Leu, Phe, N8-AcSpd, 0.686; Leu, Ser, aABA, 0.686; Leu, Ser, Pipecolic acid, 0.686; Lys, Phe, Val, 0.686; Lys, Ser, hCit, 0.686; Lys, Ser, Cystathionine, 0.686; Met, Orn, Sar, 0.686; Met, Orn, Kyn / BCAA, 0.686; Met, Ser, HyPro, 0.686; Met, Ser, Kyn, 0.686; Met, Ser, Pipecolic acid, 0.686; Met, Trp, MeCys, 0.686; Orn, Phe, GABA, 0.686; Orn, Phe, Spd, 0.686 Orn, Ser, Sar, 0.686; Orn, Ser, SDMA, 0.686; Orn, aAiBA, hArg, 0.686; Orn, aAiBA, Kyn, 0.686; Orn, ADMA, Kyn / BCAA, 0.686; Orn, aAAA, Cystathionine, 0.686 Orn, bAiBA, Sar, 0.686; Orn, GABA, Cystathionine, 0.686; Orn, Cystathionine, N6-AcLy


s, 0.686; Orn, Cystathionine, Sar, 0.686; Orn, Cystathionine, Kyn / BCAA, 0.686; Phe, Ser, Pipecolic acid, 0.686; Phe, Val, 3-MeHis, 0.686; Phe, Val, Spd, 0.686; Pro , Tyr, MeCys, 0.686; Pro, GABA, MeCys, 0.686; Ser, Tau, Pipecolic acid, 0.686; Ser, aAiBA, Pipecolic acid, 0.686; Ser, bAiBA, N6-AcLys, 0.686; Ser, hCit, Spd, 0.686 Ser, Kyn, Pipecolic acid, 0.686; Trp, MeCys, Kyn / BCAA, 0.686; Tyr, GABA, MeCys, 0.686; aABA, ADMA, bAiBA, 0.686; aAiBA, GABA, MeCys, 0.686; aAiBA, MeCys, Thioproline, 0.686; ADMA, Hypotaurine, N8-AcSpd, 0.686; ADMA, Pipecolic acid, Kyn / Trp, 0.686; GABA, MeCys, Sar, 0.686; hArg, Cystathionine, MeCys, 0.686; MeCys, Pipecolic acid, Spd, 0.686; MeCys, Sar, Kyn / BCAA, 0.686; Orn, 3-MeHis, Allyl-Cys, 0.685; Orn, aAiBA, Allyl-Cys, 0.685; Orn, Allyl-Cys, N8-AcSpd, 0.685; Orn, Allyl-Cys, Sar, 0.685; Asn, EtOHNH2, aAiBA, 0.685; EtOHNH2, Glu, Kyn / BCAA, 0.685; EtOHNH2, Gly, aAiBA, 0.685; EtOHNH2, Ile, Phe, 0.685; EtOHNH2, Met, Ser, 0.685; EtOHNH2, Pro, aAiBA, 0.685; EtOHNH2, Ser, Tyr, 0.685; EtOHNH2, Ser, Val, 0.685; EtOHNH2, Tau, aAiBA, 0.685; EtOHNH2, Thr, Kyn / BCAA, 0.685; EtOHNH2, Tyr, aAiBA, 0.685; EtOHNH2, aAiBA, GABA, 0.685; EtOHNH2, aAAA, Kyn / BCAA, 0.685; EtOHNH2, N8-AcSpd, Kyn / BCAA, 0.685; EtOHNH2, Spd, Kyn / BCAA, 0.685; Orn, bAiBA, N6-AcLys, 0.684; Arg, Leu, Ser, 0.684; Asn, Gln, MeCys, 0.684; Cit, Met, MeCys, 0.684; Cit, Pro, MeCys, 0.684; Cit, MeCys, Kyn / Trp, 0.684; Gln, Gly, hCit, 0.684; Gln, MeCys, Thioproline, 0.684; Glu, Leu, Phe, 0.684; Glu, Ser, Spd, 0.684; Glu, Ser, Thioproline, 0.684; Gly, Leu, aAiBA, 0.684; Gly, Met, ADMA, 0.684; Gly, Orn, Ser, 0.684; Gly, Ser, Cystathionine, 0.684; Gly, Pipecolic acid, Put, 0.684; Gly, Pipecolic acid, Spd, 0.684; Gly, Pipecolic acid, Kyn / BCAA, 0.684; Gly, Put, Spd, 0.684; His, Tyr, MeCys, 0.684; His , MeCys, Spd, 0.684; His, MeCys, Kyn / Trp, 0.684; Ile, Leu, Phe, 0.684; Leu, Ser, aAiBA, 0.684; Lys, Orn, Cystathionine, 0.684; Met, Orn, Tau, 0.684; Met , Orn, HyPro, 0.684; Met, Ser, N6-AcLys, 0.684; Orn, Phe , hArg, 0.684; Orn, Phe, Put, 0.684; Orn, Ser, Tau, 0.684; Orn, Thr, aAiBA, 0.684; Orn, Tyr, HyPro, 0.684; Orn, aAiBA, Pipecolic acid, 0.684; Orn, N6- AcLys, Pipecolic acid, 0.684; Pro, Ser, Pipecolic acid, 0.684; Ser, Tau, hCit, 0.684; Ser, Trp, hArg, 0.684; Ser, Tyr, Val, 0.684; Ser, 1-MeHis, hCit, 0.684; Ser, GABA, Pipecolic acid, 0.684; Ser, Cystathionine, Sar, 0.684; Ser, Cystathionine, Spd, 0.684; Tyr, MeCys, Thioproline, 0.684; aABA, MeCys, Spd, 0.684; aAiBA, MeCys, SDMA, 0.684; ADMA , bAiBA, GABA, 0.684; ADMA, bAiBA, hArg, 0.684; ADMA, HyPro, Kyn / BCAA, 0.684; ADMA, N8-AcSpd, Put, 0.684; ADMA, Put, SDMA, 0.684; hArg, MeCys, Kyn / Trp , 0.684; MeCys, Kyn / Trp, Kyn / BCAA, 0.684; Cys2, Glu, Tyr, 0.684; Cys2, Leu, Orn, 0.684; Cys2, Orn, 1-MeHis, 0.684; Cys2, Orn, Kyn / BCAA, 0.684 Cys2, Ser, Pipecolic acid, 0.684; Cys2, ADMA, Kyn / BCAA, 0.684; Gly, Orn, Allyl-Cys, 0.684; Met, Orn, Allyl-Cys, 0.684; Ser, Allyl-Cys, Kyn, 0.684;
[２－１. ２変数と年齢（Age）を組み合わせた式]
Gly, ADMA, Age, 0.863; ADMA, MeCys, Age, 0.854; Gly, MeCys, Age, 0.847; Ser, ADMA,Age, 0.843; Gly, hCit, Age, 0.843; Gly, hCit, Age, 0.841; ADMA, hCit, Age, 0.838; ADMA, hCit, Age, 0.837; Sar, ADMA, Age, 0.834; HyPro, MeCys, Age, 0.828; Arg, HyPro, Age, 0.827; Phe, ADMA, Age, 0.826; Orn, MeCys, Age, 0.824; hCit, MeCys, Age, 0.824; ADMA, N8-Acetylspd, Age, 0.823; Ser, MeCys, Age, 0.822; ADMA, HyPro, Age, 0.821; ADMA, SDMA, Age, 0.821; Arg, ADMA, Age, 0.821; MeCys, SDMA, Age, 0.821; Ala, ADMA, Age, 0.820; Gly, Thr, Age, 0.820; hCit, MeCys, Age, 0.820; Asn, ADMA, Age, 0.819; Asn, MeCys, Age, 0.819; Met, ADMA, Age, 0.817; Glu, ADMA, Age, 0.816; Orn, ADMA, Age, 0.816; ADMA, Pipecolic acid, Age, 0.816; aABA, MeCys, Age, 0.816; Gly, Pipecolic acid, Age, 0.816; Sar, MeCys, Age, 0.816; Gln, ADMA, Age, 0.814; Gly, HyPro, Age, 0.814; Arg, Gly, Age, 0.814; aABA, ADMA, Age, 0.813; Cit, ADMA, Age, 0.813; ADMA, bAiBA, Age, 0.813; His, ADMA, Age, 0.813; Phe, hCit, Age, 0.813; Tau, ADMA, Age, 0.812; Leu, MeCys, Age, 0.812; Val, MeCys, Age, 0.812; Gly, Pro, Age, 0.812; Thr, ADMA, Age, 0.811; Arg, MeCys, Age, 0.811; Orn, Phe, Age, 0.811; Val, ADMA, Age, 0.810; Trp, ADMA, Age, 0.810; Gln, MeCys, Age, 0.810; MeCys, N8-Acetylspd, Age, 0.810; Gly, Met, Age, 0.810; Gly, SDMA, Age, 0.810; Lys, MeCys, Age, 0.810; Phe, MeCys, Age, 0.809; Trp, MeCys, Age, 0.809; Gly, Val, Age, 0.809; aABA, Gly, Age, 0.809; Ala, Gly, Age, 0.809; Gly, His, Age, 0.809; Gly, N8-Acetylspd, Age, 0.809; Ser, SDMA, Age, 0.809; Asn, Gly, Age, 0.809; Gly, Phe, Age, 0.809; Gly, Sar, Age, 0.809; Pro, ADMA, Age, 0.808; Tyr, ADMA, Age, 0.808; ADMA, L-Cystathionine, Age, 0.808; Glu, MeCys, Age, 0.808; Tau, MeCys, Age, 0.808; His, MeCys, Age, 0.808; Thr, MeCys, Age, 0.808; Lys, ADMA, Age, 0.807; Cit, MeCys, Age, 0.807; Glu, Gly, Age, 0.807; Ser, hCit, Age, 0.807; Leu, ADMA, Age, 0.806; Ile, MeCys, Age, 0.806; bAiBA, MeCys, Age, 0.806; MeCys, Pipecolic acid, Age, 0.806; Gln, Gly, Age, 0.806; Gly, Tau, Age, 0.806; Ile, ADMA, Age, 0.804; Pro, MeCys, Age, 0.804; Ser, hCit, Age, 0.804; Met, MeCys, Age, 0.802; Ala, MeCys, Age, 0.802; Gly, Leu, Age, 0.802; Gly, L-Cystathionine, Age, 0.802; Gly, Ile, Age, 0.801; Gly, bAiBA, Age, 0.801; L-Cystathionine, MeCys, Age, 0.800; Tyr, MeCys, Age, 0.799; Cit, Gly, Age, 0.799; Gly, Orn, Age, 0.799; Gly, Trp, Age, 0.799; Orn, Trp, Age, 0.799; Phe, hCit, Age, 0.798; Gly, Ser, Age, 0.797; Pipecolic acid, Age, 0.796; Orn, HyPro, Age, 0.793; Gly, Lys, Age, 0.793; Gly, Tyr, Age, 0.793; Orn, Ser, Age, 0.793; Orn, Tyr, Age, 0.791; HyPro, SDMA, Age, 0.789; Arg, Ser, Age, 0.789; Met, Orn, Age, 0.788; hCit, L-Cystathionine, Age, 0.788; aABA, hCit, Age, 0.787; Orn, hCit, Age, 0.786; aABA, Ser, Age, 0.786; Orn, Sar, Age, 0.786; aABA, hCit, Age, 0.784; Arg, Orn, Age, 0.784; Met, hCit, Age, 0.784; Arg, hCit, Age, 0.783; Met, Ser, Age, 0.783; Trp, hCit, Age, 0.783; Tyr, hCit, Age, 0.783; Sar, hCit, Age, 0.782; Ser, Thr, Age, 0.782; His, Orn, Age, 0.781; Lys, hCit, Age, 0.781; Trp, hCit, Age, 0.781; Ala, hCit, Age, 0.780; Orn, hCit, Age, 0.780; hCit, HyPro, Age, 0.780; aABA, HyPro, Age, 0.779; HyPro, Pipecolic acid, Age, 0.779; Leu, Orn, Age, 0.779; Ser, HyPro, Age, 0.779; Thr, hCit, Age, 0.779; hCit, Pipecolic acid, Age, 0.779; hCit, SDMA, Age, 0.779; Asn, Ser, Age, 0.778; His, hCit, Age, 0.778; Ile, hCit, Age, 0.778; Orn, Pro, Age, 0.778; Orn, SDMA, Age, 0.778; Sar, bAiBA, Age, 0.778; Sar, SDMA, Age, 0.778; Tyr, hCit, Age,0.778; Val, hCit, Age, 0.778; hCit, L-Cystathionine, Age, 0.778; Sar, HyPro, Age, 0.777; Ile, Orn, Age, 0.777; Leu, hCit, Age, 0.777; Sar, hCit, Age, 0.777; Tau, hCit, Age, 0.777; Phe, Ser, Age, 0.777; Phe, SDMA, Age, 0.777; hCit, SDMA, Age, 0.777; Gln, hCit, Age, 0.776; Glu, Orn, Age, 0.776; Orn, Tau, Age, 0.776; Orn, Val, Age, 0.776; aABA, Orn, Age, 0.776; Orn, Thr, Age, 0.776; Pro, hCit, Age, 0.776; Thr, hCit, Age, 0.776; Cit, hCit, Age, 0.774; hCit, N8-Acetylspd, Age, 0.774; Met, hCit, Age, 0.774; Orn, bAiBA, Age, 0.774; Sar, Ser, Age, 0.774; Phe, HyPro, Age, 0.773; Pro, HyPro, Age, 0.773; Ala, hCit, Age, 0.773; Gln, Orn, Age, 0.773; hCit, HyPro, Age, 0.773; Asn, hCit, Age, 0.773; bAiBA, hCit, Age, 0.773; hCit, Pipecolic acid, Age, 0.773; Lys, Orn, Age, 0.772; Orn, N8-Acetylspd, Age, 0.772; Glu, hCit, Age, 0.771; Lys, hCit, Age, 0.771; Arg, hCit, Age, 0.771; Met, HyPro, Age, 0.770; Ala, Orn, Age, 0.770; Glu, SDMA, Age, 0.770; Orn, Pipecolic acid, Age, 0.770; Cit, Orn, Age, 0.770; Cit, hCit, Age, 0.770; Gln, hCit, Age, 0.770; hCit, N8-Acetylspd, Age, 0.770; Ser, bAiBA, Age, 0.770; Val, hCit, Age, 0.769; His, hCit, Age, 0.769; bAiBA, hCit, Age, 0.769; aABA, Pipecolic acid, Age, 0.768; Phe, Val, Age, 0.768; Val, HyPro, Age, 0.768; aABA, Sar, Age, 0.768; Ile, hCit, Age, 0.768; Leu, hCit, Age, 0.768; Tau, hCit, Age, 0.768; Orn, L-Cystathionine, Age, 0.768; Pro, Ser, Age, 0.768; Pro, hCit, Age, 0.768; [2-1. 1.2 Formula combining two variables and age]
Gly, ADMA, Age, 0.863; ADMA, MeCys, Age, 0.854; Gly, MeCys, Age, 0.847; Ser, ADMA, Age, 0.843; Gly, hCit, Age, 0.843; Gly, hCit, Age, 0.841; ADMA, hCit, Age, 0.838; ADMA, hCit, Age, 0.837; Sar, ADMA, Age, 0.834; HyPro, MeCys, Age, 0.828; Arg, HyPro, Age, 0.827; Phe, ADMA, Age, 0.826; Orn, MeCys, Age, 0.824; hCit, MeCys, Age, 0.824; ADMA, N8-Acetylspd, Age, 0.823; Ser, MeCys, Age, 0.822; ADMA, HyPro, Age, 0.821; ADMA, SDMA, Age, 0.821; Arg, ADMA, Age, 0.821; MeCys, SDMA, Age, 0.821; Ala, ADMA, Age, 0.820; Gly, Thr, Age, 0.820; hCit, MeCys, Age, 0.820; Asn, ADMA, Age, 0.819; Asn, MeCys, Age, 0.819; Met, ADMA, Age, 0.817; Glu, ADMA, Age, 0.816; Orn, ADMA, Age, 0.816; ADMA, Pipecolic acid, Age, 0.816; aABA, MeCys, Age, 0.816; Gly, Pipecolic acid, Age, 0.816; Sar, MeCys, Age, 0.816; Gln, ADMA, Age, 0.814; Gly, HyPro, Age, 0.814; Arg, Gly, Age, 0.814; aABA, ADMA, Age, 0.813; Cit, ADMA, Age, 0.813; ADMA, bAiBA, Age, 0.813; His, ADMA, Age, 0.813; Phe, hCit, Age, 0.813; Tau, ADMA, Age, 0.812; Le u, MeCys, Age, 0.812; Val, MeCys, Age, 0.812; Gly, Pro, Age, 0.812; Thr, ADMA, Age, 0.811; Arg, MeCys, Age, 0.811; Orn, Phe, Age, 0.811; Val, ADMA, Age, 0.810; Trp, ADMA, Age, 0.810; Gln, MeCys, Age, 0.810; MeCys, N8-Acetylspd, Age, 0.810; Gly, Met, Age, 0.810; Gly, SDMA, Age, 0.810; Lys, MeCys, Age, 0.810; Phe, MeCys, Age, 0.809; Trp, MeCys, Age, 0.809; Gly, Val, Age, 0.809; aABA, Gly, Age, 0.809; Ala, Gly, Age, 0.809; Gly, His, Age, 0.809; Gly, N8-Acetylspd, Age, 0.809; Ser, SDMA, Age, 0.809; Asn, Gly, Age, 0.809; Gly, Phe, Age, 0.809; Gly, Sar, Age, 0.809; Pro, ADMA, Age, 0.808; Tyr, ADMA, Age, 0.808; ADMA, L-Cystathionine, Age, 0.808; Glu, MeCys, Age, 0.808; Tau, MeCys, Age, 0.808; His, MeCys, Age, 0.808; Thr, MeCys, Age, 0.808; Lys, ADMA, Age, 0.807; Cit, MeCys, Age, 0.807; Glu, Gly, Age, 0.807; Ser, hCit, Age, 0.807; Leu, ADMA, Age, 0.806; Ile, MeCys, Age, 0.806; bAiBA, MeCys, Age, 0.806; MeCys, Pipecolic acid, Age, 0.806; Gln, Gly, Age, 0.806; Gly, Tau, Age, 0.806; Ile, ADMA, Ag e, 0.804; Pro, MeCys, Age, 0.804; Ser, hCit, Age, 0.804; Met, MeCys, Age, 0.802; Ala, MeCys, Age, 0.802; Gly, Leu, Age, 0.802; Gly, L-Cystathionine, Age, 0.802; Gly, Ile, Age, 0.801; Gly, bAiBA, Age, 0.801; L-Cystathionine, MeCys, Age, 0.800; Tyr, MeCys, Age, 0.799; Cit, Gly, Age, 0.799; Gly, Orn, Age, 0.799; Gly, Trp, Age, 0.799; Orn, Trp, Age, 0.799; Phe, hCit, Age, 0.798; Gly, Ser, Age, 0.797; Pipecolic acid, Age, 0.796; Orn, HyPro, Age, 0.793 Gly, Lys, Age, 0.793; Gly, Tyr, Age, 0.793; Orn, Ser, Age, 0.793; Orn, Tyr, Age, 0.791; HyPro, SDMA, Age, 0.789; Arg, Ser, Age, 0.789; Met , Orn, Age, 0.788; hCit, L-Cystathionine, Age, 0.788; aABA, hCit, Age, 0.787; Orn, hCit, Age, 0.786; aABA, Ser, Age, 0.786; Orn, Sar, Age, 0.786; aABA , hCit, Age, 0.784; Arg, Orn, Age, 0.784; Met, hCit, Age, 0.784; Arg, hCit, Age, 0.783; Met, Ser, Age, 0.783; Trp, hCit, Age, 0.783; Tyr, hCit , Age, 0.783; Sar, hCit, Age, 0.782; Ser, Thr, Age, 0.782; His, Orn, Age, 0.781; Lys, hCit, Age, 0.781; Trp, hCit, Age , 0.781; Ala, hCit, Age, 0.780; Orn, hCit, Age, 0.780; hCit, HyPro, Age, 0.780; aABA, HyPro, Age, 0.779; HyPro, Pipecolic acid, Age, 0.779; Leu, Orn, Age, 0.779; Ser, HyPro, Age, 0.779; Thr, hCit, Age, 0.779; hCit, Pipecolic acid, Age, 0.779; hCit, SDMA, Age, 0.779; Asn, Ser, Age, 0.778; His, hCit, Age, 0.778 Ile, hCit, Age, 0.778; Orn, Pro, Age, 0.778; Orn, SDMA, Age, 0.778; Sar, bAiBA, Age, 0.778; Sar, SDMA, Age, 0.778; Tyr, hCit, Age, 0.778; Val , hCit, Age, 0.778; hCit, L-Cystathionine, Age, 0.778; Sar, HyPro, Age, 0.777; Ile, Orn, Age, 0.777; Leu, hCit, Age, 0.777; Sar, hCit, Age, 0.777; Tau , hCit, Age, 0.777; Phe, Ser, Age, 0.777; Phe, SDMA, Age, 0.777; hCit, SDMA, Age, 0.777; Gln, hCit, Age, 0.776; Glu, Orn, Age, 0.776; Orn, Tau , Age, 0.776; Orn, Val, Age, 0.776; aABA, Orn, Age, 0.776; Orn, Thr, Age, 0.776; Pro, hCit, Age, 0.776; Thr, hCit, Age, 0.776; Cit, hCit, Age , 0.774; hCit, N8-Acetylspd, Age, 0.774; Met, hCit, Age, 0.774; Orn, bAiBA, Age, 0.774; Sar, Ser, Age, 0.774; Phe, HyPro, Age, 0.773; Pro, HyPro, Age, 0.773; Ala, hCit, Age, 0.773; Gln, Orn, Age, 0.773; hCit, HyPro, Age, 0.773; Asn, hCit, Age, 0.773; bAiBA, hCit, Age, 0.773; hCit, Pipecolic acid, Age, 0.773; Lys, Orn, Age, 0.772; Orn, N8-Acetylspd, Age, 0.772; Glu, hCit, Age, 0.771; Lys, hCit, Age, 0.771; Arg, hCit , Age, 0.771; Met, HyPro, Age, 0.770; Ala, Orn, Age, 0.770; Glu, SDMA, Age, 0.770; Orn, Pipecolic acid, Age, 0.770; Cit, Orn, Age, 0.770; Cit, hCit, Age, 0.770; Gln, hCit, Age, 0.770; hCit, N8-Acetylspd, Age, 0.770; Ser, bAiBA, Age, 0.770; Val, hCit, Age, 0.769; His, hCit, Age, 0.769; bAiBA, hCit, Age, 0.769; aABA, Pipecolic acid, Age, 0.768; Phe, Val, Age, 0.768; Val, HyPro, Age, 0.768; aABA, Sar, Age, 0.768; Ile, hCit, Age, 0.768; Leu, hCit, Age , 0.768; Tau, hCit, Age, 0.768; Orn, L-Cystathionine, Age, 0.768; Pro, Ser, Age, 0.768; Pro, hCit, Age, 0.768;

Claims (17)

  1. 　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価する評価ステップを含むこと、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態の評価方法。     Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, Cysteine, MeCys Calculated using at least one measurement of AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Thioproline and BCAA, or an expression containing the variable to which the measurement is assigned and the measurement. Including an evaluation step of evaluating the state of accumulation of amyloid beta in the brain for the evaluation target using the value of the above formula.
    A method for evaluating the state of accumulation of amyloid beta in the brain.
  2. 　前記評価ステップは、前記評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも２つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価すること、
    　を特徴とする請求項１に記載の評価方法。     The evaluation step includes Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, etc. in the blood to be evaluated. Thr, Trp, Tyr, Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allly-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Cystathionine, Cystathionine Expressions and measurements that include at least two measurements of N6-AcLys, N8-AcSpd, PEA, Pipeolic-acid, Put, Sar, SDMA, Spd, Cystathionine and BCAA, or variables to which the measurements are assigned. To evaluate the state of accumulation of amyloid beta in the brain for the evaluation target using the value of the above formula calculated using the value.
    The evaluation method according to claim 1.
  3. 　前記評価ステップは、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値を用いて、または、年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値が代入される変数を含む前記式、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つおよび前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価すること、
    　を特徴とする請求項１または２に記載の評価方法。     The evaluation step uses the measured value with at least one of the age, gender, BMI and MMSE scores of the evaluation target, or at least one of the age, gender, BMI and MMSE score and the measured value. For the evaluation target, using the formula including the variable to be assigned, the age, gender, BMI and MMSE score of the evaluation target, and the value of the formula calculated using the measured value. To assess the state of accumulation of amyloid beta in the brain,
    The evaluation method according to claim 1 or 2.
  4. 　前記評価ステップは、制御部を備えた情報処理装置の前記制御部において実行されること、
    　を特徴とする請求項１から３のいずれか１つに記載の評価方法。     The evaluation step is executed in the control unit of the information processing apparatus including the control unit.
    The evaluation method according to any one of claims 1 to 3, characterized in that.
  5. 　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、ならびに、前記測定値が代入される変数を含むアミロイドベータの脳内への蓄積の状態を評価するための式を用いて、前記式の値を算出する算出ステップを含むこと、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態を評価するための式の値の算出方法。     Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cystathionine, Cystathionine, MeCys The state of accumulation of amyloid beta in the brain, including at least one measurement of AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Cystathionine and BCAA, and the variable to which the measurement is assigned. Including a calculation step of calculating the value of the formula using the formula for evaluating.
    A method for calculating the value of an equation for evaluating the state of accumulation of amyloid beta in the brain.
  6. 　前記算出ステップは、制御部を備えた情報処理装置の前記制御部において実行されること、
    　を特徴とする請求項５に記載の算出方法。     The calculation step is executed in the control unit of the information processing device including the control unit.
    5. The calculation method according to claim 5.
  7. 　制御部を備え、
    　前記制御部は、
    　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価する評価手段
    　を備えること、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態の評価装置。     Equipped with a control unit
    The control unit
    Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, Cysteine, MeCys Calculated using at least one measurement of AcSpd, PEA, Pipepolilic-acid, Put, Sar, SDMA, Spd, Cysteine and BCAA, or an expression containing the variable to which the measurement is assigned and the measurement. To provide an evaluation means for evaluating the state of accumulation of amyloid beta in the brain for the evaluation target using the value of the above formula.
    A device for evaluating the state of accumulation of amyloid beta in the brain.
  8. 　前記評価手段は、前記評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも２つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価すること、
    　を特徴とする請求項７に記載の評価装置。     The evaluation means includes Ala, Arg, Asn, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, etc. in the blood to be evaluated. Thr, Trp, Tyr, Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allly-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Cystathionine, Cystathionine Expressions and measurements that include at least two measurements of N6-AcLys, N8-AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Cystathionine and BCAA, or variables to which the measurements are assigned. To evaluate the state of accumulation of amyloid beta in the brain for the evaluation target using the value of the above formula calculated using the value.
    7. The evaluation device according to claim 7.
  9. 　前記評価手段は、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値を用いて、または、年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つと前記測定値が代入される変数を含む前記式、前記評価対象の年齢、性別、ＢＭＩおよびＭＭＳＥの点数のうち少なくとも１つおよび前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価すること、
    　を特徴とする請求項７または８に記載の評価装置。     The evaluation means uses the measured value with at least one of the age, gender, BMI and MMSE scores of the evaluation target, or at least one of the age, gender, BMI and MMSE score and the measured value. For the evaluation target, using the formula including the variable to be assigned, the age, gender, BMI and MMSE score of the evaluation target, and the value of the formula calculated using the measured value. To assess the state of accumulation of amyloid beta in the brain,
    7. The evaluation device according to claim 7 or 8.
  10. 　前記測定値に関する測定データまたは前記式の値を提供する端末装置とネットワークを介して通信可能に接続され、
    　前記制御部は、
    　前記端末装置から送信された前記測定データまたは前記式の値を受信するデータ受信手段と、
    　前記評価手段で得られた評価結果を前記端末装置へ送信する結果送信手段と、
    　をさらに備え、
    　前記評価手段は、前記データ受信手段で受信した前記測定データに含まれている前記測定値または前記式の値を用いること、
    　を特徴とする請求項７から９のいずれか１つに記載の評価装置。     Communicatably connected via a network to a terminal device that provides measurement data for the measurements or values of the equation.
    The control unit
    A data receiving means for receiving the measurement data or the value of the formula transmitted from the terminal device, and
    A result transmitting means for transmitting the evaluation result obtained by the evaluation means to the terminal device, and
    With more
    The evaluation means uses the measured value or the value of the formula included in the measured data received by the data receiving means.
    The evaluation device according to any one of claims 7 to 9, wherein the evaluation device is characterized.
  11. 　制御部を備え、
    　前記制御部は、
    　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、ならびに、前記測定値が代入される変数を含むアミロイドベータの脳内への蓄積の状態を評価するための式を用いて、前記式の値を算出する算出手段
    　を備えること、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態を評価するための式の値の算出装置。     Equipped with a control unit
    The control unit
    Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cystathionine, Cystathionine, MeCys The state of accumulation of amyloid beta in the brain, including at least one measurement of AcSpd, PEA, Pipepolilic-acid, Put, Sar, SDMA, Spd, Cystathionine and BCAA, and the variable to which the measurement is assigned. Provided with a calculation means for calculating the value of the formula using the formula for evaluating.
    A device for calculating the value of an equation for evaluating the state of accumulation of amyloid beta in the brain.
  12. 　制御部を備える情報処理装置の前記制御部において実行させるための、
    　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価する評価ステップ
    　を含むこと、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態の評価プログラム。     An information processing device including a control unit to be executed in the control unit.
    Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, Cysteine, MeCys Calculated using at least one measurement of AcSpd, PEA, Pipepolilic-acid, Put, Sar, SDMA, Spd, Cysteine and BCAA, or an expression containing the variable to which the measurement is assigned and the measurement. Including an evaluation step of evaluating the state of accumulation of amyloid beta in the brain for the evaluation target using the value of the above formula.
    A program for assessing the state of accumulation of amyloid beta in the brain.
  13. 　制御部を備える情報処理装置の前記制御部において実行させるための、
    　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、ならびに、前記測定値が代入される変数を含むアミロイドベータの脳内への蓄積の状態を評価するための式を用いて、前記式の値を算出する算出ステップ
    　を含むこと、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態を評価するための式の値の算出プログラム。     An information processing device including a control unit to be executed in the control unit.
    Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cystathionine, Cystathionine, MeCys The state of accumulation of amyloid beta in the brain, including at least one measurement of AcSpd, PEA, Pipepolilic-acid, Put, Sar, SDMA, Spd, Cystathionine and BCAA, and the variable to which the measurement is assigned. Including a calculation step of calculating the value of the formula using the formula for evaluating.
    A program for calculating the value of an equation for evaluating the state of accumulation of amyloid beta in the brain.
  14. 　請求項１２または１３に記載のプログラムを記録したコンピュータ読み取り可能な記録媒体。 A computer-readable recording medium on which the program according to claim 12 or 13 is recorded.
  15. 　制御部を備える、アミロイドベータの脳内への蓄積の状態を評価する評価装置と、制御部を備える端末装置とを、ネットワークを介して通信可能に接続して構成され、
    　前記端末装置の前記制御部は、
    　評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値に関する測定データ、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を、前記評価装置へ送信するデータ送信手段と、
    　前記評価装置から送信された、前記評価対象についての、アミロイドベータの脳内への蓄積の状態に関する評価結果を受信する結果受信手段と、
    　を備え、
    　前記評価装置の前記制御部は、
    　前記端末装置から送信された前記測定データまたは前記式の値を受信するデータ受信手段と、
    　前記データ受信手段で受信した前記測定データに含まれている前記測定値または前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価する評価手段と、
    　前記評価手段で得られた前記評価結果を前記端末装置へ送信する結果送信手段と、
    　を備えること、
    　を特徴とする、アミロイドベータの脳内への蓄積の状態の評価システム。     An evaluation device for evaluating the state of accumulation of amyloid beta in the brain, which has a control unit, and a terminal device, which has a control unit, are configured to be communicably connected via a network.
    The control unit of the terminal device
    Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, Thr, Trp, Tyr, in the blood to be evaluated. Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allyl-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine, Cysteine, MeCys Using the measurement data for at least one measurement of AcSpd, PEA, Pipepolilic-acid, Put, Sar, SDMA, Spd, Thioproline and BCAA, or an expression containing the variable to which the measurement is assigned and the measurement. A data transmission means for transmitting the value of the formula calculated in the above manner to the evaluation device, and
    A result receiving means for receiving the evaluation result regarding the state of accumulation of amyloid beta in the brain for the evaluation target transmitted from the evaluation device.
    With
    The control unit of the evaluation device
    A data receiving means for receiving the measurement data or the value of the formula transmitted from the terminal device, and
    An evaluation means for evaluating the state of accumulation of amyloid beta in the brain of the evaluation target by using the measurement value or the value of the formula included in the measurement data received by the data receiving means.
    A result transmitting means for transmitting the evaluation result obtained by the evaluation means to the terminal device, and
    To prepare
    A system for assessing the state of accumulation of amyloid beta in the brain.
  16. 　制御部を備えた端末装置であって、
    　前記制御部は、
    　評価対象についての、アミロイドベータの脳内への蓄積の状態に関する評価結果を取得する結果取得手段
    　を備え、
    　前記評価結果は、前記評価対象の血液中のＡｌａ、Ａｒｇ、Ａｓｎ、Ｃｉｔ、Ｃｙｓ２、ＥｔＯＨＮＨ２、Ｇｌｎ、Ｇｌｕ、Ｇｌｙ、Ｈｉｓ、Ｉｌｅ、Ｌｅｕ、Ｌｙｓ、Ｍｅｔ、Ｏｒｎ、Ｐｈｅ、Ｐｒｏ、Ｓｅｒ、Ｔａｕ、Ｔｈｒ、Ｔｒｐ、Ｔｙｒ、Ｖａｌ、１－ＭｅＨｉｓ、３－ｈＫｙｎ、３－ＭｅＨｉｓ、ａＡＢＡ、ａＡｉＢＡ、ＡＤＭＡ、Ａｌｌｙｌ－Ｃｙｓ、ａＡＡＡ、ｂＡｉＢＡ、ＧＡＢＡ、ｈＡｒｇ、ｈＣｉｔ、Ｈｙｐｏｔａｕｒｉｎｅ、ＨｙＰｒｏ、Ｋｙｎ、Ｃｙｓｔａｔｈｉｏｎｉｎｅ、ＭｅＣｙｓ、Ｎ６－ＡｃＬｙｓ、Ｎ８－ＡｃＳｐｄ、ＰＥＡ、Ｐｉｐｅｃｏｌｉｃ－ａｃｉｄ、Ｐｕｔ、Ｓａｒ、ＳＤＭＡ、Ｓｐｄ、ＴｈｉｏｐｒｏｌｉｎｅおよびＢＣＡＡのうちの少なくとも１つの測定値、または、前記測定値が代入される変数を含む式および前記測定値を用いて算出された前記式の値を用いて、前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価した結果であること、
    　を特徴とする端末装置。     It is a terminal device equipped with a control unit.
    The control unit
    Equipped with a result acquisition means for acquiring the evaluation result regarding the state of accumulation of amyloid beta in the brain for the evaluation target.
    The evaluation results include Ala, Arg, Asn, Cit, Cys2, EtOHNH2, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Orn, Ph, Pro, Ser, Tau, etc. in the blood to be evaluated. Thr, Trp, Tyr, Val, 1-MeHis, 3-hKyn, 3-MeHis, aABA, aAiBA, ADMA, Allly-Cys, aAAA, bAiBA, GABA, hArg, hCit, Hypotaurine, HyPro, Kyn, Cysteine An expression and the measurement including at least one measurement value of N6-AcLys, N8-AcSpd, PEA, Pipecolic-acid, Put, Sar, SDMA, Spd, Hypotaurine and BCAA, or a variable to which the measurement value is assigned. It is the result of evaluating the state of accumulation of amyloid beta in the brain for the evaluation target using the value of the above formula calculated using the value.
    A terminal device characterized by.
  17. 　前記評価対象について、アミロイドベータの脳内への蓄積の状態を評価する評価装置とネットワークを介して通信可能に接続されており、
    　前記制御部は、前記測定値に関する測定データまたは前記式の値を前記評価装置へ送信するデータ送信手段を備え、
    　前記結果取得手段は、前記評価装置から送信された前記評価結果を受信すること、
    　を特徴とする請求項１６に記載の端末装置。     The evaluation target is communicably connected to an evaluation device that evaluates the state of accumulation of amyloid beta in the brain via a network.
    The control unit includes data transmission means for transmitting measurement data related to the measured value or the value of the formula to the evaluation device.
    The result acquisition means receives the evaluation result transmitted from the evaluation device.
    16. The terminal device according to claim 16.
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