Skin Information Provision Methods

Abstract

To provide a skin information provision method capable of obtaining information on antimicrobial ability to resist microorganisms such as bacteria and viruses relating to diseases without giving discomfort to a subject.SOLUTION: Skin information is provided in following steps: input steps (steps S201, S202, S203 and S204) to acquire from a subject, and to input values of a first index and a second index respectively selected from at least two groups among a lactic acid amount index group, a hydrogen-ion exponent index group, a temperature index group and a drying speed index group; and an information provision step (S205) to provide information pertaining to an index of the antimicrobial ability of a skin, or an agent or a service recommended for the subject, on the basis of relational data indicating a relation between the first index or another index belonging to either of the lactic acid amount index group, the hydrogen-ion exponent index group, the temperature index group and the drying speed index group to which the first index belongs as well as the second index or another index belonging to either of the lactic acid amount index group, the hydrogen-ion exponent index group, the temperature index group and the drying speed index group to which the second index belongs, and the antimicrobial ability of a skin.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a skin information providing method, a skin information providing device, and a skin information providing program. [Background technology]

[0002] Secretions from sweat glands and sebaceous glands, metabolic products of skin cells, and other substances are present on human skin, and these are also metabolized by resident skin bacteria. Therefore, a wide variety of chemical components are present on the skin, ranging from inorganic to organic substances, from hydrophilic to hydrophobic substances, and from low-molecular-weight substances to proteins. Indicators obtained from skin include the amounts and compositions of the aforementioned chemical components, as well as indicators related to skin properties such as pH, each of which varies from person to person. These indicators related to skin components and properties are obtained, and information about the skin and, ultimately, people is obtained from the obtained indicators. For example, Staphylococcus epidermidis is known as the major bacterium present on healthy skin surfaces. Patent Document 1 discloses a simple and rapid method for detecting S. epidermidis by wiping the facial skin surface of a subject with sterilized gauze to obtain a sample, and then performing a nucleic acid amplification reaction using the LAMP method. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-68261 Summary of the Invention [Problem to be solved by the invention]

[0004] The surface of the skin is the area of ​​human beings that comes into contact with the outside world the most, and bacteria and viruses often infect the human body via the skin. Therefore, the inventors believed that obtaining and sharing with the subject information regarding the condition of bacteria and viruses attached to the subject's skin, as well as information regarding skin agents and treatments appropriate for that condition, would be useful for the subject's establishment of hygienic habits and disease prevention. However, when testing for bacteria or viruses attached to the skin, it is desirable to attach the bacteria or virus to the skin and directly examine its behavior, but attaching bacteria, viruses, etc. to the skin is not desirable from the perspective of the risk of infection to the subject or the mental burden it places on the subject. Furthermore, for bacteria and viruses that cannot be tested by directly attaching them to the skin, one method of testing involves collecting a sample from the skin, then contacting it with the bacteria or virus and culturing it. However, such experiments take time to prepare the test sample, and therefore test results cannot be obtained immediately, which may reduce the subjects' motivation to undergo testing.

[0005] The present invention has been made in consideration of the above points, and aims to provide a skin information providing method, a skin information providing device, and a skin information providing program that can obtain information on antimicrobial ability to resist microorganisms such as bacteria and viruses, and other information, in a short period of time without causing discomfort to the subject. [Means for solving the problem]

[0006] The inventors have found through comprehensive analysis of human skin components and properties that four factors - lactic acid amount, pH, temperature, and drying speed - contribute to the rate at which bacteria counts are reduced on the skin (antimicrobial capacity), and that skin with a particularly high amount of lactic acid reduces microorganisms such as bacteria and viruses more quickly and is effective in preventing contact infection through the skin. Based on this finding, the inventors have conducted further research and found that the above-mentioned problem can be solved by obtaining from a subject values ​​of a first index and a second index that are different from each other and selected from at least two of the lactic acid amount index group, pH index group, temperature index group, and drying speed index group, and comparing these values ​​with the relationship data described below. That is, the present invention provides the following [1] to [3]. [1] An input step of acquiring and inputting values ​​of a first index and a second index selected from at least two of a lactate index group, a hydrogen ion index group, a temperature index group, and a drying rate index group from a subject; an information providing step of providing the index of the antimicrobial ability of the skin or information on an agent or service recommended to the subject based on relationship data showing the relationship between the first index or another index belonging to any of the lactic acid amount index group, the hydrogen ion index group, the temperature index group, and the drying rate index group to which the first index belongs, and the second index or another index belonging to any of the lactic acid amount index group, the hydrogen ion index group, the temperature index group, and the drying rate index group to which the second index belongs, and the antimicrobial ability of the skin; A method for providing skin information, comprising: [2] an input unit that acquires and inputs values ​​of a first index and a second index selected from at least two of a lactate index group, a hydrogen ion index group, a temperature index group, and a drying rate index group from a subject; an information providing unit that provides the index of the antimicrobial ability of the skin or information on an agent or service recommended to the subject based on relationship data that indicates the relationship between the first index or another index belonging to any of the lactic acid amount index group, the hydrogen ion index group, the temperature index group, and the drying rate index group to which the first index belongs, and the second index or another index belonging to any of the lactic acid amount index group, the hydrogen ion index group, the temperature index group, and the drying rate index group to which the second index belongs, and the antimicrobial ability of the skin; A skin information providing device comprising: [3] an input function for acquiring and inputting values ​​of a first index and a second index selected from at least two of a lactate index group, a hydrogen ion index group, a temperature index group, and a drying rate index group from a subject into a computer; an information provision function that provides an index of the antimicrobial ability of the skin or information related to an agent or service recommended to the subject based on relationship data that indicates the relationship between the first index or another index belonging to any of the lactic acid amount index group, the hydrogen ion index group, the temperature index group, and the drying rate index group to which the first index belongs, and the second index or another index belonging to any of the lactic acid amount index group, the hydrogen ion index group, the temperature index group, and the drying rate index group to which the second index belongs, and the antimicrobial ability of the skin; A skin information program that makes this possible. [Effects of the Invention]

[0007] The present invention can provide a skin information providing method, a skin information providing device, and a skin information providing program that can obtain information on antimicrobial ability to resist disease-related microorganisms and other information in a short period of time without causing discomfort to the subject. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 shows the results of an investigation into the relationship between antibacterial activity of the skin and disease susceptibility. [Figure 2] 1(a) is a flowchart illustrating a process for creating relational data, and FIG. 1(b) is a flowchart illustrating a process for predicting the antimicrobial ability of a subject using the created relational data. [Figure 3] FIG. 3 is a diagram for explaining a skin information providing device for executing the processes shown in FIGS. 2(a) and 2(b). [Figure 4] (a) shows the relationship between lactic acid content and antibacterial activity, (b) shows the relationship between pH and antibacterial activity, (c) shows the relationship between temperature and antibacterial activity, and (d) shows the relationship between drying speed and antibacterial activity. [Figure 5] FIG. 10 is a diagram showing the coefficient of determination of a regression equation according to a combination of indexes selected for creating relationship data (linear multiple regression equation). [Figure 6] FIG. 1(a) is a graph showing the correlation between antibacterial activity against Escherichia coli and antibacterial activity against Staphylococcus aureus, and FIG. 1(b) is a graph showing the correlation between antiviral activity against influenza virus and antibacterial activity against Staphylococcus aureus. [Figure 7] FIG. 1 is a diagram for explaining an example of the present invention, showing the relationship between the actually measured value and the predicted value of antibacterial activity. DETAILED DESCRIPTION OF THE INVENTION

[0009] [overview] First, an outline of the invention will be described. It is well known that many infectious diseases, such as influenza and infectious gastroenteritis, are transmitted by contact infection via the attachment of pathogens from the environment to the skin. For example, people often touch objects in the environment through the skin of their fingers and then touch other parts of their skin with the same fingers. Therefore, rapid removal of pathogens from the skin of the fingers is particularly important in infection prevention. On the other hand, since the skin is constantly exposed to the external environment, it is also the outermost barrier of the human body that resists the invasion of pathogens such as bacteria and viruses. Therefore, the present inventors focused on the antimicrobial ability of the skin itself to combat microorganisms such as viruses and bacteria. They found that the antimicrobial ability of the skin varies from person to person and that there is a correlation between the antimicrobial ability and the susceptibility of individuals with this antimicrobial ability.

[0010] The antimicrobial capacity of skin refers to the ability to reduce activity related to microbial activity, and in the first embodiment, it is determined by the degree to which bacteria or viruses are reduced after adhering to the skin. Microorganisms for which antimicrobial capacity is predicted include bacteria, parasites, viruses, fungi, and the like, such as those transmitted by contact. Furthermore, to predict antimicrobial capacity against these, microorganisms that have been confirmed to be safe for humans, can be used experimentally, and can be attached to the skin may also be used as prediction targets. Examples of activity related to microbial activity include the number of survivors, the infectivity titer, the growth rate, the maximum growth amount, the metabolic amount, and various enzyme activities. The lower the number of survivors (the greater the reduction) after a predetermined time has elapsed since the bacteria or the like adhered, the stronger the antimicrobial capacity is determined to be.

[0011] The number of surviving organisms can be measured by, for example, CFU counting using agar culture plates, direct counting by microscopic observation, or by detecting microbial particles in a sample, for example, by turbidity, flow cytometry, or dielectrophoretic impedance measurement, or by using chemical substances contained in the microorganisms as indicators, or by fluorescent staining methods in which nucleic acids, ATP, lipid membranes, or proteins such as enzymes are fluorescently labeled and measured. For example, nucleic acids can be measured by real-time PCR, using an increase in their fluorescence intensity as an indicator, and ATP can be measured by a luciferase assay, and enzymes can be detected as enzyme activity using a substrate specific to the enzyme.

[0012] Figure 1 shows the results of an investigation into the relationship between antibacterial activity of skin and disease susceptibility. The experiment shown in Figure 1 involved 109 subjects completing a questionnaire about their disease, and also collecting skin samples from the palms of the subjects and contacting them with Staphylococcus aureus. The vertical axis in Figure 1 represents the survival rate (%) of Staphylococcus aureus after suspending the skin samples in a bacterial solution and leaving them in contact for one hour at 37°C; a lower value indicates higher antibacterial activity. In addition, the subjects will answer the following three questions (a), (b), and (c) in the questionnaire. (a) Number of times you have had influenza in the past three years (b) Number of times you have had a cold in the past year (c) Do you feel that you are susceptible (or unlikely) to contracting an infectious disease?

[0013] In Figure 1, subjects were divided into high and low antibacterial activity groups based on the median of 109 data points. Based on the results of the questionnaire, subjects who answered "0 times" to both questions (a) and (b) and who responded that they were "unlikely to contract" an infectious disease were classified as low-incidence subjects, while subjects who answered "two or more times" to question (a) and "three or more times" to question (b) and who responded that they were "prone to contract" an infectious disease were classified as high-incidence subjects. In Figure 1, low-incidence subjects are indicated by a dashed line, and high-incidence subjects are indicated by a solid line.

[0014] As shown in Figure 1, among the subjects in the high antibacterial activity group, 37 had low infections and 18 had high infections. On the other hand, among the subjects in the low antimicrobial activity group, 17 had low infections and 37 had high infections. The p-value of the data shown in Figure 1 is less than 0.001, demonstrating sufficient statistical significance between the susceptibility of the high and low infection groups and the relative survival rate (antimicrobial activity) of Staphylococcus aureus. These results indicate that high antibacterial activity in the skin is associated with a low susceptibility to infection, and that assessing the antimicrobial activity of the skin can indirectly predict a subject's resistance to infection.

[0015] However, this type of measurement requires a very long sample preparation process, which involves bringing the collected components back to the laboratory, extracting and concentrating them in a liquid, and then mixing them with a bacterial solution in a certain ratio. This means that test results are not available immediately, which discourages test subjects from undergoing testing. While the need for sample preparation can be eliminated by directly examining the behavior of bacteria or viruses by attaching them to the skin, this type of measurement places a significant mental burden on test subjects, making them reluctant to undergo testing. Furthermore, due to the risk of infection during testing, only a limited number of types of bacteria or other microorganisms are permitted to be directly attached to the skin. Based on the above, in the present invention, relationship data relating indices related to the components and properties of the skin to antimicrobial activity is prepared in advance. The indices measured from the subject are then compared with the relationship data to determine the antimicrobial activity of the skin, and ultimately the subject's resistance to infection. Furthermore, the present invention is useful for clarifying the relationship between antimicrobial activity and indices related to the components and properties of the skin, and for reminding the subject of the need to bring the skin environment closer to a state with higher antimicrobial activity.

[0016] [Skin information providing method and skin information providing device] The skin information providing method of this embodiment includes an input step of obtaining from a subject and inputting a first index and a second index that are different from each other and selected from at least two of a lactic acid amount index group, a hydrogen ion index index group, a temperature index group, and a drying rate index group; and an information providing step of providing an index of the antimicrobial ability of the skin or information related to an agent or service recommended to the subject based on relationship data indicating the relationship between the first index, or another index belonging to the lactic acid amount index group, hydrogen ion index index group, temperature index group, or drying rate index group to which the first index belongs, and the second index, or another index belonging to the lactic acid amount index group, hydrogen ion index index group, temperature index group, or drying rate index group to which the second index belongs, and the antimicrobial ability of the skin.

[0017] Among the above, skin refers to the epidermis of the subject's body and refers to all components, tissues, resident microorganisms, etc. that may come into contact with bacteria, etc. on the epidermis. In this embodiment, data relating to the antimicrobial ability of skin, particularly the skin of the fingers (hereinafter simply referred to as "fingers"), is used to provide information. The index group is a group composed of multiple indexes, and the index may be a parameter itself, such as the amount of lactic acid or the hydrogen ion exponent, or may be another parameter that can estimate such a parameter. The index value is a numerical value that indicates the degree (amount, speed, etc.) of the index. Individual numerical values ​​obtained by various measurements may be used as is, or may be obtained by a process of extracting index values ​​by capturing images, sound waves, absorption spectra, etc., or a process of converting non-numerical data, such as sensory evaluations or questionnaire results, into numerical data.

[0018] Examples of microorganisms that are transmitted by contact infection include those designated as specific pathogens under the Infectious Diseases Control Law, or those listed in the Ministry of Health, Labor and Welfare's guidelines for infectious disease control in nurseries, and have contact infection as a route of infection. Specific examples include gram-positive bacteria such as Bacillus anthracis, Mycobacterium tuberculosis, Streptococcus hemolyticus, Staphylococcus aureus, and Streptococcus pneumoniae, and gram-negative bacteria such as Francisella tularensis, Yersinia pestis, Brucella, Bacillus mallei, Vibrio cholerae, Salmonella, Shigella, enterohemorrhagic Escherichia coli, Haemophilus influenzae, and Bordetella pertussis. These include the enveloped viruses arenaviruses, Ebola virus, variola virus, nairovirus, Marburg virus, coronavirus, monkeypox virus, betacoronavirus, influenza virus, respiratory syncytial virus, herpes virus, mumps virus, varicella-zoster virus, rubella virus, and measles virus, as well as the non-enveloped viruses enteroviruses, adenoviruses, coxsackieviruses, noroviruses, and rotaviruses, and the parasite Cryptosporidium. Microorganisms that have been confirmed to be safe for humans, can be used experimentally, and can be attached to the skin include microorganisms that are unlikely to cause disease in humans, or microorganisms for which evaluation methods for attaching them to human skin have been established in public testing methods or academic papers, etc.

[0019] Examples of microorganisms that are unlikely to cause disease in humans include bacteriophages, which are viruses that infect only limited bacteria. Specifically, these include the enveloped virus bacteriophage φ6, and the non-enveloped viruses bacteriophage PR772 and bacteriophage MS2. Other examples include microorganisms classified as BSL1 among those whose biosafety levels (BSL) are published by the Japanese Society for Bacteriology or the National Institute of Infectious Diseases. Specifically, these include strains of gram-positive bacteria such as lactic acid bacteria, Bacillus subtilis, and enterococci, and gram-negative bacteria such as Escherichia coli, which fall under BSL1. In addition to the above, examples of microorganisms for which evaluation methods involving attachment to human skin have been established in official testing methods or academic papers include strains of the Gram-negative bacterium Serratia marcescens, the enveloped virus influenza virus, and the non-enveloped virus feline calicivirus that have been evaluated. In this embodiment, prediction of antimicrobial ability is first explained using Escherichia coli, a gram-negative bacterium among microorganisms, as an example, but later an example of indirectly predicting antimicrobial ability against other bacteria or viruses based on the relationship between Escherichia coli and other bacteria, or between Escherichia coli and viruses, will also be explained. Note that when predicting antimicrobial ability against Escherichia coli, the expression "antibacterial activity" is clearly used, but antimicrobial ability is a concept that indicates not only antibacterial activity against bacteria, but also activity against microorganisms in general, including viruses and bacteria.

[0020] The recommendation of an agent or service based on the information provided in the information provision step is carried out by providing information about the agent or service. The agent may be a cosmetic, quasi-drug, or pharmaceutical formulated to enhance the antimicrobial ability of the skin, or a miscellaneous item used for purposes that substantially come into contact with human skin. It may be a cream, ointment, or liquid agent applied to the skin surface, or a solid substance rubbed onto the skin surface. The agent in this embodiment may also be a compress or bath additive that heats or cools the body. Furthermore, the agent may be an item used or ingested by the subject, such as a steam bath item, an orally ingested vitamin supplement, a drug, or a food for specified health uses. Services include prescribing and providing the above-mentioned medications, treatments such as massages, and bathing facilities.

[0021] The lactate amount indicator group is a group composed of the amount of lactate present on the skin of a subject, or indicators of the amount of lactate. The lactate amount indicators include at least one of the amount of chemical substances correlated with the amount of lactate and the skin properties correlated with the amount of lactate. The amount of chemical substances includes at least one of the amount of low-molecular-weight organic acids, the amount of low-molecular-weight bases, and the amount of peptides, and the skin properties include the amount of sweat produced by the subject. Of the above, the amount of chemical substances includes, for example, the following: Pyruvic acid Fumaric acid Amino acid (Creatinine) α-Ketoglutaric acid (2-Oxoglutarate) Ascorbic acid Choline Taurine 2-Hydroxybutyric acid Ammonia Carnitine (L-Carnitine) Citric acid Malic acid PIP (Prolactin-induced protein) DCD (Dermcidin)

[0022] Among the above, lactic acid and carnitine are low-molecular-weight organic acids, and ammonia is a low-molecular-weight base. Furthermore, PIP and DCD are peptides that have been reported to have antibacterial properties. Table 1 shows the correlation coefficients between the amount of several chemical substances belonging to the above lactate amount indicator group and the amount of lactate. These chemical substances can be used as substitutes for the amount of lactate, regardless of whether they directly contribute to the antibacterial activity of the skin. Specifically, any chemical substance with an absolute value of the correlation coefficient with lactate amount of 0.40 or more, more preferably 0.60 or more, can be used as a substitute indicator for the amount of lactate. The n shown in Table 1 is the number of samples when the correlation coefficient R was measured. Furthermore, the chemical substances shown in Table 1 were measured using the LC / MS method for organic acids (including amino acids), the LC-MS / MS method for peptides, and an ammonia measuring device (Pocket Chem) for ammonia. tm This was performed using a BA PA-4140 (manufactured by Arkray, Inc.).

[0023] [Table 1]

[0024] Skin properties used as indicators in the present invention include the hydrogen ion index of the skin surface, skin temperature, and the drying rate of moisture on the skin. Furthermore, skin properties can also include sweat rate, water evaporation rate, stratum corneum moisture content, stratum corneum thickness, skin wettability (contact angle), skin oil content, skin hardness, skin viscoelasticity, skin friction coefficient, skin shape (wrinkle depth, fingerprint / palmprint depth), skin color, blood flow, etc. All of the above skin properties can be measured using commercially available skin measuring devices, and it is preferable to measure them at rest, avoiding measurements immediately after strenuous exercise, etc.

[0025] The pH index group is a group of indicators that are correlated with the pH of the skin surface. The pH can be measured by contacting a glass electrode or a transistor electrode (ion-sensitive field-effect transistor) with the skin and measuring the potential difference across the electrode. Alternatively, an ion-sensitive chemical substance (such as a pH indicator) can be used, for example, by attaching a sheet carrying this to the skin and visually observing the color change, or by capturing an image and analyzing it.

[0026] The temperature index group includes the skin temperature of the subject or components and properties that correlate with the skin temperature. Here, the skin is preferably the skin of the fingers, and the fingers refer to the area from the wrist to the fingertips, including both the palm side and the back side of the hand, more preferably the palm side. An example of a temperature that correlates with the finger temperature is body temperature measured at a location other than the fingers of the same subject. The drying rate refers to the rate at which a drop of liquid on a finger evaporates or is absorbed and reduced. The drying rate index group includes such a drying rate, as well as components and properties that correlate with the drying rate. In addition to the lactate amount, hydrogen ion index, temperature, and drying speed, which are the starting indexes for the lactate amount index group, hydrogen ion index index group, temperature index group, and drying speed index group, the other indexes obtained are shown in Table 2. The values ​​in Table 2 are the correlation coefficients between the indexes, and are "1" for combinations of the same index. In Table 2, n is the number of samples.

[0027] In this embodiment, an index (e.g., index b) that is correlated with a certain index (e.g., index a) means that there is a correlation between index a and index b with an absolute value of the correlation coefficient of 0.4 or more, more preferably 0.6 or more. Even if an index has a correlation coefficient, if the absolute value of the correlation coefficient is less than 0.4, it is considered that there is no substantial correlation. For this reason, Table 2 lists only correlation coefficients with an absolute value of 0.4 or more, and blank spaces in the table indicate correlation coefficients less than 0.4. For example, the correlation coefficient between the amount of lactic acid and the pH of skin is -0.314, and the correlation coefficient between the pH index group and the amount of lactic acid is -0.314. In this embodiment, there is no correlation between the amount of lactic acid and the pH. On the other hand, the correlation coefficient between the amount of lactic acid and the amount of ammonia is 0.665, and the correlation coefficient between the amount of lactic acid and the amount of sweat is 0.488. There is a correlation between the amount of lactic acid and the amount of ammonia, and between the amount of lactic acid and the amount of sweat. In this embodiment, since correlated indices belong to the same index group, the expression "belongs" is partially synonymous with the expression "has a correlation." However, in this embodiment, the expressions "belongs" or "does not belong" are used to describe the relationship between a certain component or property and an index group, and the expressions "has a correlation" or "does not have a correlation" are used to describe the relationship between the amount of lactic acid, temperature, pH index, and drying rate, which are the starting indices, respectively. [Table 2]

[0028] The lactate levels shown in Table 2 can be measured, for example, by pressing a cup with a fixed opening against the skin, rinsing the internal skin surface with a fixed amount of water, and then collecting a sample using a lactate-specific enzyme reaction. Examples of lactate measurement methods using enzyme reactions include quantification of WST formazan, which develops a lactate-dependent color due to the enzyme reaction, by absorbance measurement, or electrical quantification of reduced iron ions produced by the enzyme reaction. These measurements can be performed using commercially available measurement kits or devices. Skin pH can be measured, for example, using a commercially available probe-integrated device. Skin surface temperature can be measured, for example, using a contact thermometer or a non-contact thermograph that measures infrared radiation. Ammonia levels can be measured using a commercially available measurement kit or device, similar to the measurement of lactate levels, by pressing a cup against the skin and collecting a sample with water, or by collecting blood ammonia levels or skin gases by contacting the skin. The amount of sweating can be measured, for example, by a sweating checker that is attached to the skin to measure the amount of sweating, or by a micro-sweating meter that can measure small amounts of sweating at rest. The fingerprint depth can be measured, for example, by a fingerprint reader that scans the fingerprint using ultrasound, or by creating a fingerprint replica using a dental silicone impression material and analyzing it in 3D using a digital microscope. The stratum corneum moisture content can be measured, for example, by contacting a probe with an electrode at its tip with the skin through glass and measuring the capacitance.

[0029] The first index and the second index are indexes selected from at least two of a lactic acid index group, a hydrogen ion index group, a temperature index group, and a drying rate index group. When the first index is selected from any one of a lactic acid index group, a hydrogen ion index group, a temperature index group, and a drying rate index group, the second index is selected from an index group different from the index group to which the first index belongs. In this embodiment, each of the above index groups is a set of parameters (other indexes) whose absolute value of the correlation coefficient between the index and the starting index is 0.4 or more. For example, the amount of ammonia has a certain level of correlation with both the amount of lactic acid and the pH index, but only with the amount of lactic acid, it has a correlation coefficient of 0.665, which is 0.4 or more. Therefore, the amount of ammonia belongs to the group of indexes for lactic acid, but not to the group of indexes for pH index. Furthermore, this embodiment is not limited to selecting one index from one index group, but may select multiple indexes. In other words, this embodiment may use indexes selected from multiple index groups to create relationship data. Furthermore, in addition to the indexes selected from the four index groups described above, an index other than these, such as stratum corneum moisture content or fingerprint depth, may also be used simultaneously.

[0030] Furthermore, in this embodiment, it is desirable to input the first and second indices obtained from the skin of the subject's fingers in any of the lactate amount index group, hydrogen ion index group, temperature index group, and drying rate index group. This is because, since many infectious diseases transmitted by contact are thought to be transmitted via fingers, measuring the antimicrobial ability of the palm can improve the prediction accuracy of antimicrobial ability.

[0031] The relationship data may represent the relationship between the first index and the second index and the antimicrobial ability. For example, if the amount of lactic acid in the lactic acid amount indexes shown in Table 2 is used as the first index, the temperature in the temperature index group can be selected as the second index. The relationship data may also represent the relationship between the antimicrobial ability and other indices belonging to the same index group as the first index and other indices belonging to the same index group as the second index. An example of such a relationship is selecting the amount of ammonia from the group of lactic acid indexes in Table 2 and the temperature other than that of fingers from the group of temperature indexes. The relationship data may also represent the relationship between the antimicrobial ability and other indices belonging to the same index group as the first index and the second index. For example, the ammonia amount may be selected from the lactate amount index group, and the temperature may be selected from the temperature index group. Furthermore, the relationship data may represent the relationship between the antimicrobial ability and other indices belonging to the same index group as the second index, and the first index, etc. An example of such a relationship is selecting ammonia from the lactate amount index group and temperature from the temperature index group.

[0032] Figures 2(a) and 2(b) are flowcharts illustrating the skin information providing method of this embodiment. Figure 2(a) illustrates the process for creating relational data, and Figure 2(b) illustrates the process for predicting the antimicrobial ability of skin using the created relational data. Figure 3 is a diagram illustrating the skin information providing device 1 for executing the processes shown in Figures 2(a) and 2(b). In this embodiment, steps S201, S202, and S203 shown in Fig. 2(b) correspond to the above-mentioned input step, and step S205 corresponds to the information providing step.

[0033] (Creating relational data) Before predicting antimicrobial ability in this embodiment, the creation of relational data used for the prediction will be described. Note that in this embodiment, whether or not to perform the step of creating relational data is optional. For example, relational data may be prepared using available secondary data obtained by other medical institutions, etc. Furthermore, data may be obtained without applying bacteria or viruses to the skin. As shown in Fig. 2(a), in creating the relationship data, data on the amount of lactic acid measured on the palm of a subject is input (step S101). Also, data on the hydrogen ion exponent measured on the subject's finger (step S102), temperature data (step S103), and drying rate data are input (step S104). In this embodiment, data on the antimicrobial activity actually measured on the palm of the subject on which the data input in steps S101 to S104 was measured is input (step S105). In this embodiment, the antimicrobial ability of the skin of a subject is determined by contacting the palm of the subject with E. coli. Specifically, for example, one minute after the E. coli is contacted with the palm, the E. coli is collected using a bacteria-collecting swab, and the antimicrobial ability of the skin against E. coli is determined based on the number of surviving E. coli bacteria collected.

[0034] Antimicrobial activity can be predicted by contacting the skin with microorganisms or by counting the number of remaining microorganisms after placing tissue collected from a subject in a liquid containing microorganisms and leaving it to stand. Tissue collection can be performed by tape stripping, scraping with a cotton swab soaked in various solvents, or attaching filter paper soaked in various solvents. The inventors compared the reduction in E. coli counts measured on the palms of seven subjects with the reduction in E. coli counts measured on tissue samples. As a result, a graph showing the logarithmic reduction in E. coli counts measured on tissue samples on the vertical axis and the logarithmic reduction in E. coli counts measured on the palms on the horizontal axis yielded a straight line with a correlation coefficient R of 0.66.

[0035] In this embodiment, the amount of lactic acid, the hydrogen ion exponent, the temperature, and the drying speed are each used as explanatory variables, and a multiple regression equation is created by determining partial regression coefficients so as to minimize the sum of squares of the residuals with the actual measured values, and this is used as the relational data (step S106). An example of creating a linear multiple regression equation as the relational data is shown below. However, this embodiment is not limited to creating relational data by linear multiple regression analysis. For example, nonlinear multiple regression analysis may be used to create the relational data, or the objective variable may not be a quantitative variable, and the weights (composite strengths) of a machine learning neural network using AI (Artificial Intelligence) may be used as the relational data.

[0036] As shown in FIG. 3, the skin information providing device 1 includes a lactic acid amount measuring device 11, a hydrogen ion index measuring device (pH measuring device) 12, and a thermometer 13. The drying speed data is the speed (μl / cm) at which water dropped on the palm of the subject dries. 2 In this embodiment, the drying rate is obtained by observation by an operator. The skin information providing device 1 also includes a control unit 2 and an output unit 3. The control unit 2 includes an input unit 21, which is a user interface that accepts input of lactic acid amount data, hydrogen ion exponent data, temperature data, drying rate data, and actual measured values ​​of antibacterial activity indicating antimicrobial capacity measured by the lactic acid amount meter 11, pH meter 12, and thermometer 13; a calculation unit 22 that creates relational data indicating the relationship between the input data and antimicrobial capacity; and an information database (DB) 23 that stores indicators of the antimicrobial capacity of the skin or information related to agents and services recommended for the subject. The output unit 3 outputs the results of the calculations and data stored in the DB 23 corresponding to the results. The information DB 23 will be described later in the section "Predicting Antimicrobial Capacity."

[0037] The input unit 21 may be a device for inputting characters such as a keyboard, a touch panel, a pen tablet, or even a voice input device, or may send information directly to a CPU (Central Processing Unit). The calculation unit 22 may be a CPU or a dedicated built-in processor. In this case, the input unit 21 may send information directly to the CPU or built-in processor. The information DB 23 may be a memory device provided within the skin information providing device 1, an external storage device, or a device that acquires and stores information via connection to the Internet. The output unit 3 may be a display screen of a PC or a printer connected to a PC. Furthermore, the output unit 3 may output the results by sending them to a personal terminal via email, a smartphone application, or the like.

[0038] The lactic acid amount data in step S101 shown in FIG. 2(a) is measured by the lactic acid amount measuring instrument 11. The hydrogen ion exponent data in step S102 is measured by the pH measuring instrument 12, and the temperature data in step S103 is measured by the thermometer 13. The drying rate data in step S105 is input by the measurer. All of the above data is input to the calculation unit 22 via the input unit 21. The calculation unit 22 performs calculations using the indices of the lactic acid amount, hydrogen ion exponent, temperature, and drying rate to create relationship data.

[0039] Next, the reason why the present embodiment creates the relationship data using four indices, namely, the amount of lactic acid, the hydrogen ion exponent, the temperature, and the drying rate, will be explained. Figures 4(a) to 4(d) are graphs showing the relationship between lactic acid amount, pH, temperature, drying speed, and antimicrobial ability. In Figure 4(a), the horizontal axis represents lactic acid amount, and the vertical axis represents antimicrobial ability. Antimicrobial ability is indicated by the amount of E. coli reduced one minute after contact with the palm, and the vertical axis represents the amount of reduction in logarithm. In Figure 4(b), the horizontal axis represents pH, and the vertical axis represents antimicrobial ability. In Figure 4(c), the horizontal axis represents temperature, and the vertical axis represents antimicrobial ability. In Figure 4(d), the horizontal axis represents drying speed, and the vertical axis represents antimicrobial ability.

[0040] When a line is drawn using the least squares method from the plot showing the relationship between antimicrobial activity and lactic acid content shown in Figure 4(a), the coefficient of determination of this line, R 2 is 0.25. In addition, when a line is drawn using the least squares method from the plot showing the relationship between antimicrobial activity and pH shown in Figure 4(b), the coefficient of determination of this line, R 2 is 0.21. When a line is drawn using the least squares method from the plots showing the relationship between antimicrobial activity and temperature shown in Figure 4(c) and the relationship between antimicrobial activity and drying speed shown in Figure 4(d), the coefficient of determination of this line, R 2 are both 0.23. The inventors of the present invention have determined that there is a sufficiently high correlation between the antimicrobial activity and the index when the coefficient of determination R2 is 0.27 or more, preferably 0.30 or more, more preferably 0.35 or more, and even more preferably 0.40 or more. From the relationships shown in Figures 4(a) to 4(d), it can be seen that the coefficient of determination R2 is 0.27 or more, preferably 0.30 or more, more preferably 0.35 or more, and even more preferably 0.40 or more, regardless of the amount of lactic acid, the hydrogen ion exponent, the temperature, or the drying speed. 2 does not seem to show a high correlation.

[0041] Therefore, the inventors predicted the antimicrobial activity using a multiple regression equation with multiple indicators, such as the amount of lactic acid, hydrogen ion exponent, palm temperature, and drying rate, as explanatory variables. The predicted antimicrobial activity is hereinafter referred to as the "predicted value." In this embodiment, the predicted multiple regression equation corresponds to the relational data.

[0042] Figure 5 shows the coefficient of determination R according to the combination of lactic acid amount, pH, temperature, and drying speed selected for creating the relationship data. 2 In Fig. 5, "+" corresponding to the amount of lactic acid, hydrogen ion exponent, temperature, and drying rate indicates that among these correlation parameters, they were used to create the relationship data. Also, "-" in Fig. 5 indicates that among the correlation parameters, they were not used to create the relationship data. However, the coefficient of determination R 2 is the coefficient of determination adjusted for the influence of the degrees of freedom to eliminate bias due to the number of parameters used (adjusted coefficient of determination).

[0043] As shown in Figure 5, when the number of indicators is 1, the coefficient of determination R 2 is at most 0.25. In addition, as shown in Fig. 5, in this embodiment, when the number of indicators is two, multiple regression lines, which are relational data, are created for each combination of lactic acid amount and hydrogen ion exponent, lactic acid amount and temperature, lactic acid amount and drying rate, hydrogen ion exponent and temperature, hydrogen ion exponent and drying rate, and temperature and drying rate. The coefficient of determination R of the linear multiple regression line is 2 were all 0.27 or higher, with a maximum of 0.40 or higher, demonstrating a correlation between the measured and predicted values. Furthermore, when ammonia or sweat rate, which belong to the lactate level indicator group, was used as an indicator instead of lactate level, the coefficients of determination for the multiple regression lines created by combining ammonia level and temperature, ammonia level and drying rate, and sweat rate and drying rate were all 0.30 or higher, and when ammonia level, which has a higher correlation with lactate level, was used, the coefficients of determination were 0.35 or higher in combination with temperature. On the other hand, when comparing the same lactate level indicators, lactate level and ammonia level, or lactate level and sweat rate, the coefficient of determination R 2 The coefficient of determination R 2 On the contrary, it decreased.

[0044] 5, in the case where the number of indexes is three, in this embodiment, multiple regression lines were created for the combination of hydrogen ion exponent, temperature, and drying speed, the combination of lactic acid amount, temperature, and drying speed, the combination of lactic acid amount, hydrogen ion exponent, and drying speed, and the combination of lactic acid amount, hydrogen ion exponent, and temperature. The coefficient of determination R of the multiple regression line 2 is 0.40 or more in all cases, and 0.49 when the amount of lactic acid, temperature, and drying speed are used, and when the amount of lactic acid, pH, and temperature are used, indicating a sufficient correlation between the correlation parameters and the predicted values. Furthermore, from this result, it can be seen that when the number of indices is three, it is preferable to include the amount of lactic acid and temperature among the three indices.

[0045] From the above explanation, the inventors have found the following: In other words, in this embodiment, from the viewpoint of improving the correlation between the index and the predicted value, the number of indexes is preferably two or more, and the number of indexes is more preferably three or more. When two indexes are used, from the viewpoint of improving the correlation between the correlation parameter and the predicted value, it is preferable to use an index included in the lactate amount index group as the first index or the second index, and it is more preferable to use an index belonging to the lactate amount index group and an index belonging to the temperature index group as the first index and the second index.

[0046] Furthermore, when three indices are used, from the viewpoint of improving the correlation between the correlation parameter and the predicted value, it is preferable to use an index belonging to the lactate amount index group as one of the first to third indices, and it is more preferable to include an index belonging to the lactate amount index group and an index belonging to the temperature index group among the three indices. From the viewpoint of improving the correlation between the correlation parameter and the predicted value, the present invention may use other indices belonging to the same index group or other indices belonging to other index groups in addition to these indices. However, from the viewpoint of reducing the burden on the subject, it is most preferable to use only a total of three indices, one each belonging to the lactate index group, the temperature index group, and the hydrogen ion index index group. Furthermore, in this embodiment, a multiple regression line was created using a combination of the lactic acid amount, the hydrogen ion exponent, the temperature, and the drying speed.2 is 0.54, and a high correlation is observed between the correlation parameter and the predicted value.

[0047] Based on the above, in this embodiment, a multiple regression equation is created with antimicrobial capacity as the response variable and four explanatory variables: lactic acid content, pH, temperature, and drying speed, and this is used as relational data. The relational data in this embodiment is represented by the following equation (1). In equation (1), y is the predicted value of antimicrobial capacity, and represents the predicted decrease in the number of E. coli bacteria between contact with the skin and collection, expressed as the logarithm of the ratio of the contact amount to the collection amount (antibacterial activity). a, b, c, and d are partial regression coefficients of equation (1), and e is a constant in the multiple regression equation represented by equation (1). x1, x2, x3, and x4 are explanatory variables, where x1 is the lactic acid content, x2 is the pH, x3 is the temperature, and x4 is the drying speed. y=ax1+bx2+cx3+dx4+e...Formula (1)

[0048] The inventors measured the antibacterial activity against Escherichia coli on the skin of 107 subjects, and simultaneously measured the amount of lactic acid, pH, temperature, and drying speed to determine the partial regression coefficients of the above formula (1) using the least squares method. As a result, the amount of lactic acid had a greater effect on the predicted value y than the other indicators. Furthermore, it was confirmed that the greater the values ​​of the amount of lactic acid, temperature, and drying speed, the higher the antimicrobial activity, and the smaller the pH, and that each of these indicators had an independent contribution to the predicted value y. Lactic acid exists in two types: dissociated and undissociated, and it is known that the undissociated form passes through the cell membrane of bacterial cells and contributes to antimicrobial activity. The pH of the palm varies widely from person to person, ranging from about pH 4 to about pH 6.5, but the chemical properties of lactic acid molecules indicate that when the pH is 4.0, the undissociated form accounts for 40% of the total amount of lactic acid, while when the pH reaches 6.5, the proportion of the undissociated form is almost zero. Furthermore, it is believed that a higher temperature increases the mobility of lactic acid molecules and phospholipid molecules that make up the outer layer of the bacterial cells, making it easier for lactic acid to penetrate into the bacterial cells. Therefore, it is believed that a higher temperature increases the antimicrobial ability rather than a lower temperature. It is believed that a faster drying speed reduces the water activity necessary for the survival of bacterial cells on the skin more quickly than a slower drying speed, and the higher the lactic acid concentration around the bacterial cells, the higher the antimicrobial ability.

[0049] However, this embodiment is not limited to creating the relationship data using the lactic acid amount, hydrogen ion exponent, temperature, and drying speed as described above. This embodiment may also create the relationship data using these four indices, or alternatively, using at least two other indices selected from the same index group instead of each of the four indices. Furthermore, this embodiment is not limited to creating the relationship data using all four indices, but may also use two or more of these indices. Furthermore, the relationship data may be created by adding the amounts and properties of ingredients on the skin that do not belong to the above index group to two or more indices selected from the index group. However, when multiple regression analysis is used to construct the relational data, the total number of indicators used is preferably one-tenth or less, and one-twentieth or less, of the number of subjects measured in constructing the relational data.

[0050] (Prediction of antimicrobial activity) Next, a process for providing an index of antimicrobial ability of skin using the relationship data created as described above will be described. In this embodiment, an example will be described in which information about the antimicrobial ability of skin is provided to a subject as an index of antimicrobial ability (antimicrobial ability is predicted). In this embodiment, as with the creation of the relationship data, the prediction of antimicrobial ability is performed using the skin information providing device 1 shown in FIG. 3.

[0051] In the skin information providing device 1, the input unit 21 inputs at least two of the four indices, and the calculation unit 22 and information DB 23 function as an information providing unit that provides an index of the antimicrobial ability of the skin or information related to agents and services recommended to the subject based on relational data showing the relationship between the input index or other indices belonging to the same lactic acid amount index group, hydrogen ion index group, temperature index group, or drying speed index group as this index and antimicrobial ability. Furthermore, in this embodiment, the skin information providing device 1 can be realized using a general-purpose personal computer (hereinafter referred to as "PC"). In this case, this embodiment can also be configured as a skin information providing program that causes the PC to operate as the above-mentioned skin information providing device 1. In such a case, the input unit 21 is a program that is an input function for operating the computer's user interface, and the calculation unit 22 is a program that creates relational data and operates as an information providing function.

[0052] As shown in FIG. 2(b), when the antimicrobial capacity prediction process begins, the amount of lactic acid in the skin is measured by the lactic acid amount meter 11. Furthermore, the pH meter 12 measures the hydrogen ion exponent of the skin, and the thermometer 13 measures the temperature of the subject's skin. The measured data, such as the amount of lactic acid, is input to the calculation unit 22 via the input unit 21 (steps S201, 202, 203). The lactic acid amount meter 11, pH meter 12, and thermometer 13 all complete their measurements in 20 to 30 seconds. Therefore, in this embodiment, the measurement results can be communicated to the subject immediately after the measurement, increasing the subject's motivation and interest in the test. The drying rate data is collected by quickly spreading a drop of water on a specific area on the palm of the subject and observing the degree of evaporation and absorption. The drying rate data, like the data on lactic acid, is input to the calculation unit 22 via the input unit 21 (step S204). The calculation unit 22 assigns each piece of data to the explanatory variables x1, x2, x3, and x4 of the relational data, calculates a predicted value y, and determines the antimicrobial ability (step S205). The determination result is output to the output unit 3 (step S206).

[0053] Furthermore, the input of the lactic acid amount, pH, temperature, and drying rate is not limited to numerical input, but may be input in other formats such as images. For example, the temperature may be input by the color of the output image of a thermograph. The pH may be input by the color of a test paper. The drying rate may be input by the difference between the captured images immediately after the dripping of water and after a predetermined time has elapsed.

[0054] In this embodiment, the lactic acid amount, pH, temperature, and drying rate are each directly measured and input. However, in this embodiment, for example, instead of the lactic acid amount, another index belonging to the same lactic acid amount index group may be measured and converted to the lactic acid amount according to its relationship with the lactic acid amount previously obtained. Similarly, the pH may be obtained by converting a measured value of an index other than the pH that belongs to the pH index index group. The temperature may be obtained by converting a measured value of an index other than the temperature that belongs to the temperature index group. The drying rate may be obtained by converting a measured value of an index other than the drying rate that belongs to the drying rate index group.

[0055] Furthermore, the relationship data may indicate the relationship between the input index and antimicrobial activity, or may indicate the relationship between the antimicrobial activity and an index belonging to the same index group as the input index. In this way, an index that is difficult to measure or for which sufficient measurement accuracy cannot be obtained can be measured using another index, and the relationship between the desired index and antimicrobial activity can be obtained.

[0056] The information DB 23 stores a plurality of data items associated with the predicted value y and may be stored inside or outside the skin information providing device 1. The data stored in the information DB 23 may be, for example, information indicating the level of antimicrobial ability corresponding to the predicted value y. The information indicating the level of antimicrobial ability may be, for example, "very strong," "strong," "average," "slightly weak," or "very weak," or may be "Rank A," "Rank B," or the like. Furthermore, in this embodiment, a message such as "You have a tendency to catch colds easily" or "Take a bath to raise your body temperature" may be stored in the information DB for each predicted antimicrobial ability, and the calculation unit 22 may retrieve the message from the information DB 23 and output it to the output unit 3.

[0057] In addition to the antimicrobial index, the information database 23 may also store information related to agents recommended to the subject. The agents recommended to the subject may be any agent that changes the four newly discovered indexes in a direction that enhances antimicrobial activity. For example, agents containing lactic acid for subjects with low lactic acid levels, agents containing a pH buffer (such as succinic acid) for subjects with high pH levels that can lower the pH of the skin surface to 5.5 or less, preferably 5.0 or less, when applied, agents containing polyols or porous agents that generate heat due to hydration heat for subjects with low body temperatures, and agents containing water-repellent agents or porous water-absorbing agents that quickly dry the skin for subjects with low drying rates. These agents may be individually recommended, may be prepared in advance, or may be prepared according to the subject's characteristics after the subject's measurement.

[0058] Applying such an agent to hands after washing can enhance the antimicrobial ability of the hands, i.e., the barrier properties against bacteria, etc. If the information DB 23 stores information related to the agent, the calculation unit 22 may acquire the information related to the agent according to the level of antimicrobial ability and output it to the output unit 3. Furthermore, this embodiment is not limited to providing an index of antimicrobial capacity or information related to agents or services recommended to the subject, but may also provide items such as kits that can obtain an index for measuring antimicrobial capacity, and further information on diet, exercise, massage methods, or recommended bath additives for bathing and other methods that recommend habits that will change the four indexes in a direction that increases antimicrobial capacity. Changing the four indicators mentioned above in a direction that increases antimicrobial capacity means increasing the amount of lactic acid, adjusting the hydrogen ion exponent to a low value that does not cause skin irritation (approximately pH 3 or higher), increasing the temperature, and increasing the drying rate.

[0059] Furthermore, the information DB 23 may store information related to services recommended to the subject. An example of a service recommended to the subject is a store or the like that offers a service to measure the antimicrobial ability of the subject's fingers. Furthermore, the service may be a website that predicts antimicrobial ability by inputting information related to body temperature, the subject's perceived amount of sweating, or the like as an index. When the information DB 23 stores information related to the service, the calculation unit 22 may obtain the information related to the service from the information DB 23 according to the level of the predicted antimicrobial ability and output it to the output unit 3.

[0060] Next, we will explain how to predict the antimicrobial ability of the skin against bacteria and viruses other than E. coli from the antimicrobial ability against E. coli explained above. That is, this embodiment is not limited to determining the antimicrobial ability against E. coli as described above. The inventors have also determined that the antimicrobial ability of skin can be determined by examining the correlation between the antimicrobial activity against Staphylococcus aureus and influenza virus (Flu virus), which cannot be directly attached to the skin for testing, and the antimicrobial activity against E. coli, measured by collecting tissue samples. Figure 6(a) is a graph showing the correlation between antibacterial activity against E. coli and antibacterial activity against Staphylococcus aureus, with the vertical axis showing antibacterial activity against E. coli and the horizontal axis showing antibacterial activity against Staphylococcus aureus. The coefficient of determination R 2 is 0.69. Figure 6(b) is a graph showing the correlation between antibacterial activity against influenza virus and antibacterial activity against Staphylococcus aureus, with the vertical axis showing antibacterial activity against influenza virus and the horizontal axis showing antibacterial activity against Staphylococcus aureus. The coefficient of determination R 2 is 0.64. The number of plots (samples) n shown in both Figures 6(a) and 6(b) is 54. In this embodiment, first, the antimicrobial ability of the subject against E. coli is determined from the relational data. Next, this determined value is compared with Figure 6(a) to predict the antimicrobial ability against Staphylococcus aureus. Furthermore, in this embodiment, the predicted value of the antimicrobial ability against Staphylococcus aureus is compared with Figure 6(b), and the antimicrobial ability of this subject against influenza virus can be predicted.

[0061] Thus, the antimicrobial activity of skin is highly correlated with the Gram-negative bacterium Escherichia coli, the Gram-positive bacterium Staphylococcus aureus, and the enveloped virus influenza virus. By determining these correlations in advance, it is possible to predict the antimicrobial activity of pathogenic microorganisms that are difficult to expose to skin due to safety concerns. Furthermore, these results suggest that the antimicrobial activity of skin may be a direct effect on lipid membranes, a structure common to Gram-negative bacteria, Gram-positive bacteria, and enveloped viruses, or an effect mediated by their permeability. Meanwhile, it is also possible to predict the antimicrobial activity of non-enveloped viruses, such as norovirus and rotavirus, which do not have lipid membranes, based on correlation data using, for example, feline calicivirus, bacteriophage PR772, bacteriophage MS2, and other non-enveloped viruses that can come into contact with the skin. In this way, the present invention allows for the measurement of the antimicrobial ability of the skin by attaching microorganisms that have been confirmed to be safe for humans and can be used experimentally and that can be attached to the skin, and for which the relationship with each indicator group is obtained, and for microorganisms that cannot be attached to the skin for experiments, tissue is collected and the relationship with the microorganism is obtained separately, thereby making it possible to predict the antimicrobial ability of the skin against a wide range of microorganisms.

[0062] As described above, this embodiment can obtain a predicted value of antimicrobial activity using a multiple regression equation with at least two explanatory variables, allowing for relatively high accuracy in predicting antimicrobial activity from an index. Furthermore, this embodiment can determine antimicrobial activity without actually measuring it, eliminating the need to expose the subject to bacteria on their hands and providing information on the ability to resist disease-related microorganisms without causing discomfort to the subject. This embodiment measures index values ​​in a relatively short time using the lactate amount meter 11, pH meter 12, and thermometer 13, allowing for even easier and quicker prediction of antimicrobial activity.

[0063] From the viewpoint of predicting antimicrobial capacity with higher accuracy and providing a subject with information on antimicrobial capacity against disease-related microorganisms and other information in a short period of time, the skin information providing method of the present invention preferably includes: an input step of acquiring from the subject and inputting values ​​of a first index and a second index selected from at least two of a lactic acid amount index group, a hydrogen ion index group, a temperature index group, and a drying rate index group, one of which belongs to the lactic acid amount index group; and an information providing step of providing the index of the antimicrobial capacity of the skin or information on an agent or service recommended to the subject based on relationship data showing the relationship between the antimicrobial capacity of the skin and the first index or another index belonging to the lactic acid amount index group, the hydrogen ion index group, the temperature index group, or the drying rate index group to which the first index belongs, and the second index or another index belonging to the lactic acid amount index group, the hydrogen ion index group, the temperature index group, or the drying rate index group to which the second index belongs.

[0064] The skin information providing method of the present invention, from the viewpoint of predicting antimicrobial ability with even higher accuracy and providing the subject with information on antimicrobial ability against disease-related microorganisms in a short period of time and other information, includes an input step of acquiring and inputting values ​​of a first index, a second index, and a third index selected from at least three of a lactic acid amount index group, a hydrogen ion index group, a temperature index group, and a drying rate index group, wherein an index belonging to the lactic acid amount index group and an index belonging to the temperature index group are included in the three indexes; and and an information providing step of providing an index of the antimicrobial ability of the skin or information related to an agent or service recommended for the subject, based on relationship data showing the relationship between the second index or another index belonging to the lactic acid amount index group, the hydrogen ion index group, the temperature index group, or the drying rate index group to which the second index belongs, the third index or another index belonging to the lactic acid amount index group, the hydrogen ion index group, the temperature index group, or the drying rate index group to which the third index belongs, and the antimicrobial ability of the skin. [Example]

[0065] Next, an example of the embodiment described above will be described. Figure 7 illustrates the relationship between the measured values ​​of palm antibacterial activity and the predicted value y calculated using the relational data. The vertical axis of Figure 7 represents the measured values, and the horizontal axis represents the predicted value y. The measured values ​​of antibacterial activity were measured 150 minutes after washing the palm, by applying 10 μl of E. coli liquid to a 2 cm x 2 cm area on the palm and physically collecting the sample with a cotton swab one minute later. The predicted value y was obtained by substituting the lactic acid content, hydrogen ion exponent, temperature, and drying rate obtained from the fingers of the subjects whose actual values ​​were measured into the relational data. The number of subjects was 107, and the average measured value was 0.98.

[0066] An example of an instrument for measuring lactic acid levels is Lactate Pro (registered trademark, manufactured by Arkray Factory Co., Ltd.). An example of an instrument for measuring hydrogen ion exponent is Skin-pH-Meter PH905 (trademark, manufactured by Courage+Khazaka). Temperature is measured using a thermometer that measures temperature by contacting the back or palm of the hand. Examples of such thermometers that can be used include the TM-300 series digital thermometer (trademark, manufactured by AS ONE Corporation). The drying rate is determined by dropping a drop of water onto the palm, spreading it over an area of ​​2 cm x 2 cm, and visually observing the rate of decrease by two people.

[0067] The line L represents the case where all predicted values ​​y and actual measured values ​​are equal. The plots in Figure 7 are plotted closer to the line L as the degree of agreement increases. The coefficient of determination R calculated using the plots in Figure 7 2 was 0.54, which indicates that there is a sufficient correlation between the predicted value y and the actual measured value.

[0068] (1) an input step of acquiring and inputting values ​​of a first index and a second index selected from at least two of a lactic acid amount index group, a hydrogen ion index group, a temperature index group, and a drying rate index group from a subject; and an information provision step of providing information on an index of the antimicrobial ability of the skin or an agent or service recommended to the subject based on relationship data showing the relationship between the first index or another index belonging to the lactic acid amount index group, the hydrogen ion index group, the temperature index group, or the drying rate index group to which the first index belongs, and the second index or another index belonging to the lactic acid amount index group, the hydrogen ion index group, the temperature index group, or the drying rate index group to which the second index belongs, and the antimicrobial ability of the skin; A method for providing skin information, comprising: (2) The skin information providing method of (1), wherein either the first index or the second index belongs to the group of lactic acid level indexes. (3) A skin information providing method according to (1) or (2), wherein either the first index or the second index belongs to the lactic acid amount index group, and the other index, different from the first index, belongs to the temperature index group. (4) A skin information providing method according to any one of (1) to (3), wherein the group of lactic acid level indicators includes at least one of the amount of lactic acid in the skin of the subject, the amount of chemical substances correlated with the amount of lactic acid, and skin properties correlated with the amount of lactic acid, wherein the amount of chemical substances includes at least one of the amount of low molecular weight organic acids, the amount of low molecular weight bases, and the amount of peptides, and wherein the skin properties include the amount of sweat produced by the subject. (5) A skin information providing method according to any one of (1) to (4), wherein the group of temperature indicators includes the temperature of the subject's skin or components and properties that are correlated with the skin temperature. (6) A skin information providing method according to any one of (1) to (5), in which the input step inputs the value of the first index and the value of the second index obtained from the skin of the subject's fingers. (7) A method for providing skin information according to any one of (1) to (6), wherein the antimicrobial ability of the skin is determined by the degree to which bacteria or viruses are reduced after adhering to the skin. (8) The method for providing skin information according to (7), wherein the bacteria is at least one selected from gram-negative bacteria or gram-positive bacteria. (9) The method for providing skin information according to (7), wherein the virus is at least one selected from enveloped viruses and non-enveloped viruses. (10) The skin information providing method according to any one of claims (1) to (9), wherein the information providing step provides information relating to an agent containing lactic acid. (11) A skin information providing device comprising: an input unit that acquires and inputs values ​​of a first index and a second index selected from at least two of a lactic acid amount index group, a hydrogen ion index index group, a temperature index group, and a drying rate index group from a subject; and an information providing unit that provides an index of the antimicrobial ability of the skin or information related to an agent or service recommended to the subject based on relationship data showing the relationship between the first index or another index belonging to the lactic acid amount index group, the hydrogen ion index index group, the temperature index group, or the drying rate index group to which the first index belongs, and the second index or another index belonging to the lactic acid amount index group, the hydrogen ion index index group, the temperature index group, or the drying rate index group to which the second index belongs, and the antimicrobial ability of the skin. (12) A skin information provision program that enables a computer to have an input function for obtaining and inputting values ​​of a first index and a second index selected from at least two of a lactic acid amount index group, a hydrogen ion index group, a temperature index group, and a drying rate index group from a subject, and an information provision function for providing an index of the antimicrobial ability of the skin or information related to an agent or service recommended to the subject based on relationship data showing the relationship between the first index or another index belonging to the lactic acid amount index group, the hydrogen ion index index group, the temperature index group, or the drying rate index group to which the first index belongs, and the second index or another index belonging to the lactic acid amount index group, the hydrogen ion index index group, the temperature index group, or the drying rate index group to which the second index belongs, and the antimicrobial ability of the skin. [Explanation of symbols]

[0069] 1...Skin information providing device 2. Control section 3. Output section 11... Lactic acid amount measuring device 12...pH measuring device 13...Thermometer 21 Input section 22... Arithmetic section DB23... Information

Claims

1. A lactate amount index that is an index of at least one of the amount of lactate on the skin of a subject, or the amount of sweat on the skin of the fingers of the subject that correlates with the amount of lactate on the skin of the subject; a pH index index based on the pH index of the skin surface of the subject; a temperature indicator based on the temperature of the subject's skin; and a drying rate index which is an index indicating the drying rate of moisture on the skin of the subject's fingers; and an input step of measuring and inputting values ​​of a first index and a second index, which are two indexes selected from the four indexes. an information providing step of calculating a predicted value of the index of the antimicrobial ability of the skin against E. coli based on relationship data showing a statistically obtained correlation between the first index and the second index and an index of the antimicrobial ability of the skin determined by the degree of reduction of E. coli after E. coli adheres to the skin, and the value of the first index and the value of the second index input in the input step, and providing information showing the level of antimicrobial ability corresponding to the calculated predicted value, information on an agent recommended for improving the antimicrobial ability of the skin that is pre-associated with the information showing the level of antimicrobial ability, or information on a service for improving the antimicrobial ability of the skin that is pre-associated with the information showing the level of antimicrobial ability; A method for providing skin information, comprising:

2. The skin information providing method according to claim 1 , wherein one of the first index and the second index is the lactic acid amount index.

3. The skin information providing method according to claim 1 or 2, wherein one of the first index and the second index is the lactic acid amount index, and the other index different from the first index is the temperature index.

4. The skin of the subject is skin of the subject's fingers, The skin information providing method according to claim 1 , wherein the input step comprises inputting the value of the first index and the value of the second index obtained from the skin of the subject's fingers.

5. A skin information providing method described in any one of claims 1 to 4, wherein the agent contains lactic acid.

6. A lactate amount index that is an index of at least one of the amount of lactate on the skin of a subject, or the amount of sweat on the skin of the fingers of the subject that correlates with the amount of lactate on the skin of the subject; a pH index index based on the pH index of the skin surface of the subject; a temperature indicator based on the temperature of the subject's skin; and a drying rate index which is an index indicating the drying rate of moisture on the skin of the subject's fingers; and an input unit which measures and inputs values ​​of a first index and a second index, which are two of the four indexes selected from the four indexes. an information providing unit that calculates a predicted value of the index of the antimicrobial ability of the skin against E. coli based on relationship data indicating a statistically obtained correlation between the first index and the second index and an index of the antimicrobial ability of the skin determined by the degree to which E. coli is reduced after adhering to the skin, and the value of the first index and the value of the second index input by the input unit, and provides information indicating the level of antimicrobial ability corresponding to the calculated predicted value, information on an agent recommended for improving the antimicrobial ability of the skin that is pre-associated with the information indicating the level of antimicrobial ability, or information on a service for improving the antimicrobial ability of the skin that is pre-associated with the information indicating the level of antimicrobial ability; A skin information providing device comprising:

7. a lactate amount index, which is stored in a computer and is determined based on at least one of the amount of lactate in the skin of the subject and the amount of sweating in the skin of the fingers of the subject, which is correlated with the amount of lactate in the skin of the subject; a pH index index based on the pH index of the skin surface of the subject; a temperature indicator based on the temperature of the subject's skin; and a drying rate index that indicates the drying rate of moisture on the skin of the subject's fingers; and an input function that measures and inputs the values ​​of the first index and the second index, which are two of the four indexes selected from the four indexes. an information provision function that calculates a predicted value of the index of the antimicrobial ability of the skin against E. coli based on relationship data showing a statistically obtained correlation between the first index and the second index and an index of the antimicrobial ability of the skin determined by the degree to which E. coli is reduced after adhering to the skin, and the value of the first index and the value of the second index input by the input function, and provides information showing the level of antimicrobial ability corresponding to the calculated predicted value, information on an agent recommended for improving the antimicrobial ability of the skin that is pre-associated with the information showing the level of antimicrobial ability, or information on a service for improving the antimicrobial ability of the skin that is pre-associated with the information showing the level of antimicrobial ability; A skin information program that makes this possible.

Images