Method and device for determining ketosis

Abstract

The present invention addresses the problem of making it possible to conveniently determine, in the field, etc., ketosis morbidity and / or the possibility of ketosis morbidity in an animal. The present invention also addresses the problem of providing a device for performing said determination.　A method for determining ketosis morbidity according to an embodiment of the present invention comprises presenting a gas generated from a body fluid collected from an animal (non-human) to a gas detection means, and using the response of the gas detection means to the gas generated from the body fluid to determine ketosis morbidity in the animal on the basis of the composition of the gas generated from the body fluid.

Description

[Technical field]

[0001] The present invention relates to determining whether an animal has ketosis, and more specifically, to determining whether an animal has ketosis based on the composition of gas generated from milk secreted by the animal or other body fluids collected from the animal. [Background technology]

[0002] Ketosis is a state in which a large amount of ketone bodies accumulate in the tissues and body fluids of an animal, mainly due to the production of ketone bodies being increased and exceeding their utilization. For example, an increase in the amount of ketone bodies in the blood is called ketonemia, an increase in the amount of ketone bodies in the urine is called ketonuria, and an increase in the amount of ketone bodies in milk is called ketone lactation. Ketone bodies are intermediate metabolic products in the synthesis and decomposition of fat, and are a general term for compounds in which a carbonyl group (>C=O) is bonded to two hydrocarbons (R-). Ketone bodies present in the animal body include acetoacetic acid, β-hydroxybutyric acid (also called 3-hydroxybutyric acid), and acetone.

[0003] Fatty acids are broken down in the liver into acetoacetate, then acetone or β-hydroxybutyrate, and finally oxidized in the tissues to be metabolized into carbon dioxide and water. When carbohydrate metabolism is impaired, stored fat is used as an energy source in the body instead of blood glucose, and the liver increases the production of ketone bodies associated with fat decomposition. Therefore, when ketone bodies gradually exceed the limits of tissue processing capacity in cases of diabetes-related glucose utilization disorder or fasting or starvation, ketosis (ketonemia) occurs.

[0004] When ketosis occurs, digestive symptoms such as nausea, vomiting, and abdominal pain appear. Because ketone bodies are acidic substances, if the amount of ketone bodies increases further and the blood becomes acidic, ketosis progresses to ketoacidosis (acidotic state). It is known that if this ketoacidosis continues, it can lead to impaired consciousness or a coma (e.g. diabetic coma), and in the worst case, death. Therefore, ketosis (or ketoacidosis) develops when the utilization of glucose in tissues is impaired (diabetes, etc.) or when the supply of carbohydrates is insufficient (fasting, starvation, etc.), as well as due to hyperemesis gravidarum, vomiting, diarrhea, dehydration, excessive fat diet, thyrotoxicosis, digestive and absorption disorders, pediatric autointoxication, glycogen storage disease, etc.

[0005] In addition, ruminants produce β-hydroxybutyrate from butyric acid, a fermentation product in the digestive tract, so that blood ketone body concentrations are higher in ruminants than in non-ruminants even under physiological conditions, and it is known that ketosis is more common in these animals. In particular, dairy cows experience a large energy change before and after parturition, and require a lot of energy as lactation begins after parturition, but they are in a negative energy balance (NEB) when their dry matter intake (DMI) is not sufficiently increased. Dairy cows try to adapt to this NEB by using carbohydrates, proteins, and lipids stored in their bodies, but if this is not achieved sufficiently, they fall into ketosis. Dairy cows suffering from ketosis show clinical symptoms such as a decrease in DMI and a decrease in milk production, but there is also a tendency for subclinical ketosis, in which ketone bodies in the body are increased without obvious clinical symptoms, to increase, which has the problem of affecting milk production and the onset of other metabolic diseases.

[0006] Conventionally, the concentration of β-hydroxybutyric acid (BHBA) in blood has been used to determine subclinical ketosis in dairy cows (see Non-Patent Document 1). This is because β-hydroxybutyric acid is more stable than other ketone bodies such as acetone and acetoacetate, and a specific reference value of 1.0 mmol / L to 1.4 mmol / L has been shown based on the association between subclinical ketosis and the subsequent occurrence of diseases and reduced productivity. In addition to blood, subclinical ketosis has also been determined using milk and urine, and a semi-quantitative method using test strips has been developed. For the diagnosis of subclinical ketosis in dairy cows, please refer to Non-Patent Document 1 as necessary. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] International Publication No. 2011 / 148774 [Patent Document 2] Patent No. 5535636 [Non-patent literature]

[0008] [Non-Patent Document 1] Shin Oikawa, "Recent research trends on subclinical ketosis," Journal of the Japanese Society of Veterinary Medicine 68 33-42 (2015). (http: / / nichiju.lin.gr.jp / mag / 06801 / b1.pdf) [Non-Patent Document 2] AH Gustafsson and U. Emanuelson, "Milk acetone concentration as an indicator of hyperketonaemia in dairy cows: The critical value revised", Animal Science 1996, 63: 183-188. [Non-Patent Document 3] F. Enjalbert, MC Nicot, C. Baourthe, and R. Moncoulon, "Ketone Bodies in Milk and Blood of Dairy Cows: Relationship between Concentrations and Utilization for Detection of Subclinical Ketosis", Journal of Dairy Science Vol. 84, No. 3, 2001. Summary of the Invention [Problem to be solved by the invention]

[0009] As farms have become larger in recent years, the feeding management systems for dairy cows and other livestock (industrial animals) are shifting from individual management to group management, creating a need for early detection of the perinatal diseases ketosis and subclinical ketosis.

[0010] Although the above-mentioned blood-based diagnosis is objective and highly accurate, it is expensive for its low throughput, and it is difficult to measure at the breeding site. Recently, a small device that allows on-site measurement has been developed, but the concentration of β-hydroxybutyrate in blood increases after feeding, so the timing of sampling is limited to ensure the accuracy of the test.

[0011] Although urine tests are non-invasive, the currently available semi-quantitative methods using test strips are less accurate than blood tests. In addition, urine samples may not be easy to collect from some animals, and there are restrictions on when urine samples can be collected, making them difficult to use as diagnostic samples.

[0012] Although the usefulness of semi-quantitative methods using test strips has been confirmed for tests using milk, there is room for improvement in sensitivity and specificity compared to blood tests. A system for automating the feeding, milking, and diagnosis of ketosis from milk of dairy cows has been proposed in Patent Document 2. However, since this system is based on the technical idea of ​​analyzing liquid milk in its original form, there are problems such as the complexity of the flow paths for testing (addition of flow paths for test reagents, etc.) and increased costs for consumables such as test reagents.

[0013] Therefore, an object of the present invention is to enable a simple, on-site determination of whether or not an animal is suffering from ketosis and / or has the potential to suffer from ketosis. Another object of the present invention is to provide an apparatus for making this determination. [Means for solving the problem]

[0014] In order to solve the above problems, the present inventors focused on the type of sample, that is, the fact that all samples used in conventional testing methods are liquid.

[0015] For example, in dairy cows, Non-Patent Document 3 discloses that the acetone concentration in milk is similar to the acetone concentration in blood and is highly correlated, but on the other hand, it is known that the smell and flavor of milk differs depending on the feed given to the cow, so that it can be clearly distinguished by human smell and taste. In other words, the smell and flavor of milk that can be distinguished by human smell and taste are greatly affected by the difference in feed. This suggests that even milk belonging to one category, that is, milk from healthy cows, has a large variation in the composition of its volatile and evaporated components, so that it may be difficult to distinguish between them when comparing the volatile and evaporated components of milk from diseased cows. In addition to the fact that practical olfactory sensors have hardly been available in the past, this possibility is also thought to be the cause, but until now, as far as the present inventors know, there has been little knowledge obtained about the relationship between gases generated from milk and diseases.

[0016] However, as shown in the examples described below, in measurements using a surface stress sensor as a gas detection means, when a specific sensitive film material was used, no significant differences due to the composition of gases generated from two types of milk obtained from healthy dairy cows fed different diets were confirmed.

[0017] From this, the inventors, not being bound by conventional common sense, came up with the idea of ​​using the gas generated from milk and the response of the gas detection means to the gas to determine whether or not a particular disease has occurred, based on the hypothesis that a certain correlation can be established between the gas generated from milk and the disease. Furthermore, they came up with the idea that it is possible to perform this type of disease determination using the gas generated from body fluids other than milk collected from animals, such as blood, urine, saliva, and sweat.

[0018] As a result of extensive research, the inventors discovered that it is possible to determine whether an animal is suffering from ketosis based on the composition of gas generated from the animal's body fluids, such as milk, and thus completed the present invention.

[0019] That is, the present invention relates to the following [1] to

[22] .

[0020] [1] A method for determining whether an animal is suffering from ketosis, comprising: providing a gas generated from a body fluid collected from an animal (excluding humans) to a gas detection means; and using the response of the gas detection means to the gas generated from the body fluid to determine whether the animal is suffering from ketosis based on the composition of the gas generated from the body fluid. [2] The method for determining whether or not a person is suffering from ketosis described in [1], wherein the body fluid is selected from the group consisting of milk, blood, urine, saliva, and sweat. [3] The method for determining the presence of ketosis described in [1] or [2], wherein the gas generated from the body fluid is at least one of ketones, alcohols, aldehydes, nitriles, organic acids, water (water vapor), nitrogen, oxygen, and carbon dioxide. [4] The method for determining the presence of ketosis described in [3], wherein the gas generated from the body fluid is at least one of ketones and alcohols, the ketones being acetone, and the alcohols being at least one selected from the group consisting of methanol, ethanol, propanol, and butanol. [5] The method for determining whether or not a patient is suffering from ketosis described in any one of [1] to [4], wherein the gas detection means is a gas sensor, and the response of the gas detection means is a signal output from the gas sensor. [6] The method for determining whether or not the patient is suffering from ketosis described in [5], wherein the determination of whether or not the patient is suffering from ketosis is made based on the pattern of change in the signal over time. [7] The method for determining whether or not a person is suffering from ketosis described in [5] or [6], wherein the gas sensor is a surface stress sensor. [8] A method for determining whether or not the patient is suffering from ketosis described in [7], comprising passing a gas that substantially does not contain any components that affect the determination of whether or not the patient is suffering from ketosis through a container containing the body fluid, and supplying the gas obtained by passing the gas through the container to the surface stress sensor as a gas generated from the body fluid. [9] The method for determining whether or not a patient is suffering from ketosis described in [7] or [8], in which the signal after the supply of gas generated from the body fluid to the surface stress sensor is started is used to determine whether or not a patient is suffering from ketosis.

[10] A method for determining whether or not a person is suffering from ketosis described in any of [7] to [9], wherein the surface stress sensor is a membrane-type surface stress sensor.

[11] A method for determining the presence of ketosis described in any of [7] to

[10] , wherein at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Cellulose Acetate Butyrate, Poly(ethyleneimine), phenyl group-modified silica / titania composite nanoparticles, and Polystyrene is used as a material for the sensitive film of the surface stress sensor.

[12] A method for determining the presence of ketosis as described in

[11] , which uses at least a first surface stress sensor using one material selected from the group as a sensitive film and a second surface stress sensor using another material selected from the group as a sensitive film as the surface stress sensor.

[13] A method for determining whether or not a patient is suffering from ketosis described in any of [7] to

[12] , wherein a gas generated from the body fluid and a purge gas are alternately applied to the surface stress sensor, and the presence or absence of ketosis is determined using the signal corresponding to the gas generated from the body fluid and the signal corresponding to the purge gas.

[14] The method for determining whether or not a patient is suffering from ketosis described in

[13] , further comprising providing a time period during which a predetermined standard gas is supplied to the surface stress sensor in addition to a time period during which the gas generated from the body fluid is supplied to the surface stress sensor and a time period during which the purge gas is supplied to the surface stress sensor, and further using the signal corresponding to the standard gas in determining whether or not a patient is suffering from ketosis.

[15] A method for determining whether or not ketosis is present as described in

[13] , comprising alternately supplying a standard gas and a purge gas to the surface stress sensor, preparing digital data corresponding to the standard gas based on the signal corresponding to the standard gas and the signal corresponding to the purge gas, and alternately supplying a gas generated from the body fluid and a purge gas to the surface stress sensor, and preparing digital data corresponding to the body fluid to be measured based on the signal corresponding to the gas generated from the body fluid and the signal corresponding to the purge gas, and determining whether or not ketosis is present based on the digital data corresponding to the standard gas and the digital data corresponding to the body fluid to be measured.

[16] The method for determining whether or not a patient is suffering from ketosis described in

[15] , wherein the surface stress sensor to which the standard gas and the purge gas are alternately applied and the surface stress sensor to which the gas generated from the body fluid and the purge gas are alternately applied are surface stress sensors that are the same individual, or are surface stress sensors that are different individuals.

[17] The method for determining whether or not a patient is suffering from ketosis described in any one of

[14] to

[16] , wherein the standard gas is a gas generated from a reference body fluid.

[18] A method for determining whether or not a patient is suffering from ketosis described in any of [7] to

[17] , comprising supplying gas generated from the body fluid to an additional gas sensor, and determining whether or not a patient is suffering from ketosis based on a signal from the surface stress sensor and a signal from the additional gas sensor.

[19] A ketosis diagnosis device comprising at least one surface stress sensor, a first gas flow path for supplying a sample gas generated from a test subject body fluid collected from an animal, and a second gas flow path for supplying a purge gas not containing the gas component to be measured, and alternately switching between the sample gas supplied from the first gas flow path and the purge gas supplied from the second gas flow path and supplying them to the at least one surface stress sensor to generate a signal from the at least one surface stress sensor, thereby determining whether the animal is suffering from ketosis based on the composition of the sample gas generated from the body fluid.

[20] A ketosis onset determination device as described in

[19] , which includes an additional gas sensor and an additional gas flow path that supplies the sample gas to the additional gas sensor, and determines whether or not the patient is suffering from ketosis based on the signal from the at least one surface stress sensor and the signal from the additional gas sensor.

[21] A ketosis diagnosis device comprising at least one surface stress sensor, a first gas flow path for supplying a sample gas generated from a test subject body fluid collected from an animal, a second gas flow path for supplying a purge gas not containing the gas component to be measured, and a third gas flow path for supplying a predetermined standard gas, and supplying the sample gas supplied from the first gas flow path, the purge gas supplied from the second gas flow path, and the standard gas supplied from the third gas flow path to the at least one surface stress sensor in a predetermined order to generate a signal from the at least one surface stress sensor, thereby determining whether the animal is suffering from ketosis based on the composition of the sample gas generated from the body fluid.

[22] A ketosis onset determination device as described in

[21] , which includes an additional gas sensor and an additional gas flow path that supplies the sample gas to the additional gas sensor, and determines whether or not the patient is suffering from ketosis based on the signal from the at least one surface stress sensor and the signal from the additional gas sensor. Effect of the Invention

[0021] According to the present invention, body fluids such as milk secreted by an animal are used as the test subject, and the animal's suffering from ketosis can be determined based on the composition of gas generated from the milk or the like. Therefore, according to the present invention, it is possible to provide a method that can determine whether or not an animal has ketosis and / or the possibility of having ketosis, easily, on-site, with high throughput and at low cost, using a technique that often imposes little burden and stress on the animal when collecting a sample. Moreover, according to the present invention, it is also possible to provide an apparatus for making this determination. [Brief description of the drawings]

[0022] [Figure 1] FIG. 1 is a diagram showing a schematic configuration of a measurement system that can be used in the present invention. [Diagram 2] Figure 1 shows an example of an optical microscope image of an MSS. [Diagram 3] A conceptual diagram explaining the change in signal intensity over time when a sample gas is applied to a surface stress sensor such as an MSS. [Figure 4] FIG. 1 shows the change in signal (in mV) from the MSS of ChA over time (in seconds) for Example Test 1. [Diagram 5] FIG. 13 shows the change in signal (in mV) from the MSS of ChA over time (in seconds) for Example Test 2. [Figure 6] FIG. 13 shows the change in signal (in mV) from the MSS of ChA over time (in seconds) for Example Test 3. [Figure 7] FIG. 13 shows the change in signal (in mV) from MSS of ChB over time (in seconds) for Example Test 3. [Figure 8] FIG. 13 shows the change in signal (in mV) from the MSS of ChD over time (in seconds) for Example Test 3. [Figure 9]FIG. 1 shows the change in signal (in mV) from the MSS of ChE over time (in seconds) for Example Test 3. [Figure 10] FIG. 13 shows the change in signal (in mV) from the MSS of ChA over time (in seconds) in measurement a for Example Test 4. [Figure 11] FIG. 13 shows the change in signal (in mV) from the MSS of ChD over time (in seconds) in measurement a for Example Test 4. [Figure 12] FIG. 13 shows the change in signal (in mV) from the MSS of ChA over time (in seconds) in measurement b for Example Test 4. [Figure 13] FIG. 13 shows the change in signal (in mV) from the MSS of ChD over time (in seconds) in measurement b for Example Test 4. [Figure 14] FIG. 13 shows the change in signal (in mV) from the MSS of ChE over time (in seconds) in measurement b for Example Test 4. [Figure 15A] FIG. 1 shows a mass spectrum obtained by proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) of milk from a cow suffering from ketosis in Example Test 5. [Figure 15B] FIG. 1 shows a mass spectrum obtained by PTR-TOF-MS of milk from healthy cows in Example Test 5. [Figure 16A] FIG. 1 shows a mass spectrum obtained by PTR-TOF-MS of urine from a cow suffering from ketosis in Example Test 5. [Figure 16B] FIG. 1 shows a mass spectrum obtained by PTR-TOF-MS of urine from a healthy cow in Example Test 5. [Figure 17A] FIG. 13 shows the results of measurement of acetone and 2-butanone concentrations in milk and urine of cows suffering from ketosis and in milk and urine of healthy cows by PTR-TOF-MS in Example Test 5. [Figure 17B] FIG. 17B is a graph showing the measurement results of acetone concentration from the measurement results shown in FIG. 17A. [Figure 17C] FIG. 17B is a graph showing the measurement results of the concentration of 2-butanone from the measurement results shown in FIG. 17A. [Figure 18] FIG. 13 shows the change in signal (in mV) from the MSS of ChA over time (in seconds) for Example Test 5. [Figure 19] FIG. 13 shows the change in signal (in mV) from MSS of ChB over time (in seconds) for Example Test 5. [Figure 20] FIG. 13 shows the change in signal (in mV) from the MSS of ChC over time (in seconds) for Example Test 5. [Figure 21] FIG. 13 shows the change in signal (in mV) from the MSS of ChF over time (in seconds) for Example Test 5. [Figure 22] FIG. 13 shows the change in signal (in mV) from the MSS of ChG over time (in seconds) for Example Test 5. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Hereinafter, an embodiment of the present invention will be described in detail. The following description of the constituent elements may be based on a representative embodiment of the present invention, but the present invention is not limited to such an embodiment. In addition, the following description will be given of the case where milk is used exclusively as the test subject, but other body fluids collected from animals, such as blood, or other body fluids such as saliva, urine, and sweat that reflect changes in blood components, can also be used if they are obtained in a manner convenient for testing. Regarding blood, when it is necessary to collect blood for the purpose of other tests, it is possible to divert a portion of the blood so as not to impose additional burden on the animal. Furthermore, if an apparatus and collection method that can collect blood from animals easily and with very little pain are established, it is considered that the usefulness of using gas generated from blood as a test subject sample for determining ketosis will be further increased. Regarding urine, in recent years, there has been increasing interest in suppressing the generation (volatilization) of ammonia from livestock barns where dairy cows and the like are raised, and from the viewpoint of more appropriate manure treatment, a device for collecting urine has been developed, and attempts have been made to use the collected urine as a substitute for chemical fertilizer. Therefore, by diverting some of the urine, it is possible to avoid placing an additional burden on the animals.

[0024] A method for determining whether or not an animal is suffering from ketosis according to one embodiment of the present invention (hereinafter also referred to as the "method of this embodiment") involves providing gas generated from milk produced by an animal to a gas detection means, and using the response of the gas detection means to the gas generated from the milk, determining whether or not the animal is suffering from ketosis based on the composition of the gas generated from the milk.

[0025] The method of the present embodiment is applied to animals that secrete milk. Examples of such animals include, but are not limited to, livestock (industrial animals) such as dairy cows (dairy cattle), beef cattle (beef cattle), goats, sheep, buffaloes (water buffalo), yaks, and horses. More preferably, the method of the present embodiment is used to diagnose ketosis in animals kept for milk production, or as a diagnostic aid. The method of the present embodiment can also be applied as a diagnostic aid for diseases associated with ketosis in humans.

[0026] In this specification, "gas generated from milk" refers to gas components that volatilize or evaporate from milk under a certain environment, i.e., volatile or evaporated components of milk. The volatile or evaporated components include both aroma components that can be detected by the human sense of smell and non-aroma components that cannot be detected by the human sense of smell. It should be noted that since human olfaction varies greatly from person to person and the components that can be detected also vary greatly from person to person, it is not intended to classify the gas generated from the milk to be tested by the presence or absence of aroma, nor is it intended to limit it to either of these. In addition, when a body fluid other than milk is used as the test subject, the gas generated from the body fluid is intended to be the body fluid in which "milk" in the above definition is replaced with the body fluid.

[0027] Specifically, examples of gases generated from milk include ketones such as acetone, alcohols such as methanol, ethanol, propanol, and butanol, aldehydes such as formaldehyde and acetaldehyde, nitriles such as acetonitrile, organic acids such as formic acid, acetic acid, propionic acid, and butyric acid, and water (water vapor), nitrogen, oxygen, and carbon dioxide. In addition, according to preliminary experiments by the present inventors, the results of proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) of milk from healthy cows and cows suffering from ketosis showed that in addition to the above substances, gases generated from milk may also include 2-butanone, butanal, 2-methoxy-1-propene, and 2-methyl-propanal.

[0028] Ketone bodies contained in milk include acetoacetic acid, β-hydroxybutyric acid, acetone, etc., but acetone is highly volatile and is not measured in conventional tests using liquid as a sample, and β-hydroxybutyric acid and / or acetoacetic acid are used instead. In contrast, in the method of the present embodiment, the gas generated from milk is used as a sample, so the ketone bodies to be measured are not limited to β-hydroxybutyric acid and acetoacetic acid, and can also include acetone. In addition, β-hydroxybutyric acid and acetoacetic acid are precursors of acetone, and there is a correlation between the concentrations of β-hydroxybutyric acid, acetoacetic acid, and acetone in a sample, so that the concentrations of all of these increase in animals suffering from ketosis. Therefore, in the method of the present embodiment, the acetone concentration in the gas generated from milk is used as an index to determine whether or not a patient suffers from ketosis.

[0029] In the method of the present embodiment, the gas detection means is not particularly limited, and may be any means capable of detecting gas generated from milk, such as a gas sensor, a gas chromatograph, or a gas analysis test paper. In one aspect of the method of the present embodiment, the gas detection means is a gas sensor, and the response of the gas detection means is a signal output from the gas sensor. In this aspect, the diagnosis of ketosis is made based on the pattern of time change of the signal. In this aspect, the gas sensor is preferably a surface stress sensor, and more preferably, the surface stress sensor is a membrane type surface stress sensor (MSS). In the following, in order to facilitate understanding of the present invention, an aspect in which the gas sensor is a surface stress sensor will be described as an example among the aspects in which the gas detection means is a gas sensor.

[0030] By selecting an appropriate sensitive film material, the surface stress sensor can obtain response signals (also called signals) for multiple target substances from one sensitive film in a superimposed form. In other words, by appropriately selecting a sensitive film material for many target substances, the amplitude and response waveform of the surface stress sensor's response to each target substance can be made different from each other. Therefore, by combining the outputs of multiple surface stress sensors, it is possible to obtain a measurement value that appropriately combines parameters corresponding to multiple target substances. In this case, by performing pattern matching or machine learning of the outputs of the surface stress sensors, features can be appropriately extracted from these outputs, and a ketosis diagnosis based on a larger number of parameters than the number of surface stress sensors can be realized by using only a relatively small number of surface stress sensors. Of course, this is not limited to this, but in cases where other types of gas sensors that are particularly suitable for detecting specific components that are present in the gas generated from the measurement target and are useful for ketosis diagnosis can be used, such gas sensors can be used in addition to the surface stress sensor as necessary.

[0031] Fig. 1 is a diagram showing a schematic configuration of a measurement system that can be used in the method of the present embodiment. Note that Fig. 1 shows a configuration in which a membrane-type surface stress sensor (MSS) is used as a surface stress sensor, but this does not of course cause a loss of generality.

[0032] In the schematic configuration shown in FIG. 1, an inert gas (also called a purge gas or a reference gas) that is not the gas component to be measured and that does not affect the measurement of the gas component as much as possible is supplied to two gas flow paths, as shown by the white arrows from the left side of the figure. For example, nitrogen gas or air can be used as the purge gas, and in the embodiment described later, nitrogen gas is used as the purge gas. When performing a simple measurement using air or the like as the purge gas, there is a possibility that the air at the measurement site (farm, etc.) is slightly mixed with gases that may affect the ketosis disease judgment, such as organic acids and ammonia generated from feed. In such a case, if the influence of the mixed gas concentration on the disease judgment result is to the extent that it does not adversely affect the realization of the intended measurement accuracy (such a case is referred to as "substantially free of components that affect the ketosis disease judgment"), the mixed gas can be ignored. The flow rate of such two gas flows is controlled by a mass flow controller (MFC) provided for each gas flow path. Specifically, the gas flows in the two gas flow paths are alternately switched at desired time intervals, and the gas flow rate is controlled to be constant on the time axis. Of course, the gas flow control is not limited to MFC, and a system combining various pumps and valves may be used. In this case, the pumps and valves may be installed upstream or downstream of the sample, and it goes without saying that they may be configured in any order, including the positions of the sample and the sensor.

[0033] In Fig. 1, the gas flow path shown on the upper side supplies the MSS with purge gas that does not contain the gas components to be measured, thereby performing a purge process to initialize the MSS by desorbing various gases that have diffused in the sensitive film applied to the surface of the MSS. Meanwhile, the gas flow passing through the gas flow path on the lower side of Fig. 1 is supplied to the MSS containing gas components that have volatilized or evaporated from the sample in a vial placed immediately after the MFC. Of course, if the sample is in a gaseous state from the beginning or if gas that has volatilized or evaporated from a liquid sample is supplied to the measurement system, a configuration that does not use a vial can be adopted. The gas flows from the two gas flow paths are merged in another vial before being supplied to the MSS.

[0034] In addition, since the rate of gas adsorption and desorption by the sensitive film on the MSS surface is affected by temperature, it is preferable to maintain the temperature of the measurement system shown in FIG. 1 at a desired value. For example, the entire measurement system may be housed in a thermostatic bath, incubator, etc., or the MSS and its peripheral parts (hereinafter, these are also referred to as the "sensor module" or simply "module") may be housed in an incubator, etc., and the temperature of the measurement system may be maintained at a desired value with the vial containing the sample installed outside the incubator, etc. In the latter configuration, when measuring multiple samples, the vial can be replaced outside the incubator, etc., containing the sensor module, so that the temperature of the measurement system (especially the sensor module) is relatively easy to maintain compared to the former configuration. In other words, the former configuration is more suitable for measuring a single sample, and the latter configuration (hereinafter, also referred to as the "open system") is more suitable for measuring multiple samples. In the examples described below, there are an example in which the entire measurement system is housed in an incubator and measurement is performed, and an example in which it is an open system.

[0035] It is also preferable to maintain the temperature of the vial containing the sample in FIG. 1 at a desired value. This can reduce the variation in the concentration of gas components volatilized or evaporated from the sample, and can further improve the measurement accuracy. In this case, the temperature of the vial may be the same as or different from the temperature of the measurement system described above. Specifically, the set value of the vial temperature can be, for example, 5°C, 10°C, 20°C, 25°C, 30°C, 40°C, or 50°C, but is not limited thereto.

[0036] In addition, this system also includes an information processing device that realizes the evaluation method described below by controlling the operation of various devices within the system, such as the MFC, and performing various processes such as capturing, recording, and analyzing signals from the surface stress sensor, as well as interfaces and communication devices for exchanging information, commands, etc. with external devices, but these are not shown in the figure.

[0037] An example of an optical microscope photograph of an MSS is shown in FIG. 2. The MSS shown in FIG. 2 is formed from a silicon wafer used in the field of semiconductor device technology, cut from a silicon single crystal, and its central circular part (which may be of other shapes such as a square) is connected and fixed to the surrounding frame-shaped part at four points on the top, bottom, left and right of the circular part. When gas components given to the MSS are adsorbed and desorbed to the sensitive film applied to the surface of the circular part, the surface stress applied to the MSS is concentrated in these four fixed areas, resulting in a change in the electrical resistance of the piezoresistance elements provided in these fixed areas. These piezoresistance elements are interconnected by a conductive area (shown as a grained area in FIG. 2) provided in the frame-shaped part to form a Wheatstone bridge. A voltage is applied between two opposing nodes of this Wheatstone bridge, and the voltage appearing between the remaining two nodes is taken out of the MSS as a signal output from the MSS and the required analysis is performed. The structure and operation of such an MSS are described in detail in, for example, Patent Document 1. In Figure 2, the sensitive film is applied widely over the MSS chip surface, including not only the circular part of the MSS but also the frame-shaped part. This is the state seen when the sensitive film is applied by spray coating, but since the sensitive film applied to the frame-shaped part etc. does not substantially contribute to the sensor output signal, it can still be used as a sensor without any problems even when applied in this way. Of course, it is also possible to use an MSS with the sensitive film applied only to the circular part by inkjet or dispenser.

[0038] Figure 3 shows a conceptual diagram of the change in signal intensity over time when a sample gas is given to a surface stress sensor such as an MSS. Figure 3(a) shows on the time axis whether the gas given to the MSS is a sample gas or a purge gas. Specifically, the concentration of the gas to be measured in the gas given to the MSS is greater than 0 during the sample gas injection period when the sample gas is given. C gDuring the purging period, in which the sample gas in the downstream gas flow path is flushed away by supplying purge gas and the sample gas components adsorbed on the sensitive membrane of the MSS (and the gas flow path pipe wall, etc.) are desorbed, the sample gas concentration is 0. Figure 3(b) shows the signal intensity from the MSS when the type of gas shown in Figure 3(a) is switched, with the time axis aligned with that of Figure 3(a). The signal intensity is governed by many factors, but fundamentally the main factor is the rate of adsorption and desorption of the component between the gas and the sensitive membrane, which is caused by the difference between the concentration of the component in the gas near the sensitive membrane on the MSS and the concentration of the same component on the surface of the sensitive membrane. Therefore, the signal intensity Changes over time starts immediately after the gas is switched as shown in Fig. 3(a), and approaches an exponential asymptotic curve toward the upper and lower saturation values. Fig. 3(b) shows the ideal curve. The actual shape of the curve and the maximum value of the curve vary considerably depending on the adsorption and desorption speed to the sensitive film and the type of components adsorbed and desorbed to the sensitive film, and the range of signal change often differs greatly. Furthermore, the signal may show more complex changes over time due to the viscoelastic properties of the sensitive film, the diffusion of the target gas to the sensitive film, or the physicochemical interaction between the sensitive film material and the target gas. In this way, it is possible to determine the amount and concentration of each main component in the sample and the ratio between multiple components based on the change over time and amplitude of the signal from the MSS. Specifically, there are sensitive film materials that give signals suitable for measuring ketones among the gases generated from milk, and there are also sensitive film materials that give signals suitable for measuring alcohols. Therefore, a surface stress sensor coated with an appropriate material selected from these materials can be used alone to measure the gas generated from milk, or similar measurements can be performed using multiple types of surface stress sensors each coated with a different material, allowing a determination based on the composition of the gas generated from milk.

[0039] The adsorption and desorption characteristics of the materials that form the sensitive film are diverse, and there are also sensitive film materials that show responses that deviate from the simplified model described above. However, when analyzing the response of a surface stress sensor, it can be said that it is often useful to perform an initial study using the above model.

[0040] In addition, although Fig. 3 shows that the sample gas is given to the MSS only once, in measurements using a surface stress sensor such as the MSS, it is normal to repeat the measurement shown in Fig. 3 multiple times by alternately supplying the sample gas and the purge gas. Hereinafter, a set of sample gas injection and the purge associated with the injection is called a measurement cycle (details will be described later). In addition, unless there are circumstances such as a large difference between the adsorption rate and the desorption rate of a certain component in the sample gas, the sample gas injection period and the purge period are often the same length of time, but of course the sample gas injection period and the purge period may be different lengths of time.

[0041] Usually, gas generated from the milk to be tested is a trace component in milk, so it may take a relatively long time to obtain a valid signal value among the sensor signals generated by the adsorption and desorption of the gas components to the sensor. In addition, if a component that is difficult to desorb remains in the sensor, the reproducibility of the signal value of the sample gas to be measured next may decrease. Therefore, in this embodiment, it may be effective to make the sample gas injection period and the purge period in one measurement cycle different in length, and it is preferable to make the purge period longer than the sample gas injection period while ensuring a sufficient time for obtaining a valid signal value as the sample gas injection period. Specifically, in the embodiment described later, the sample gas injection period is set to 120 seconds, and the purge period is set to twice that, 240 seconds. In addition, it is also effective to make one measurement cycle a measurement sequence of "purge period-sample gas injection period-purge period", so that when performing multiple measurements, purging is essentially performed twice before the second or subsequent sample gas injections. In the examples described later, this measurement sequence is also adopted, and a purge period of 480 seconds (240 seconds + 240 seconds) is ensured from the end of the most recent sample gas injection before the second or subsequent sample gas injection. In this way, by making the purge period longer than the sample gas injection period, the components adsorbed on the sensitive film on the MSS during the sample gas injection can be desorbed sufficiently easily, and the baseline can be more stabilized, which is particularly effective in ensuring the accuracy of the determination when the measurement is repeated multiple times.

[0042] In other words, if the purge period is short relative to the sample gas injection period, there is a possibility that the accuracy of the determination will be adversely affected. In actual measurements, a long measurement time not only has the disadvantage of lowering the throughput of the measurement, but also has the problems of making it difficult to stabilize various parameters (flow rate, gas pressure, temperature, etc.) in the environment inside and outside the measurement system for a long time, and of causing the measurement system to become larger and more expensive. Furthermore, since the measurement system usually includes active components such as pumps, long-term temperature changes due to heat generation from these components may also adversely affect the accuracy of the determination. Therefore, in this embodiment, it is desirable to allocate the time of the measurement cycle as short as possible within a range in which a valid signal value can be obtained during the sample gas injection period (sampling time), and to make the purge period (purge time) as long as possible. Alternatively, as a countermeasure when baseline fluctuation is a problem, it is possible to eliminate or reduce the adverse effects of short-term purging by preparing reference milk (details will be described later) in which the amount of components that may affect the accuracy of the determination is a predetermined value, and measuring the gas generated from the reference milk for each measurement and performing calibration, etc.

[0043] As described above, in a measurement system having the schematic configuration shown in FIG. 1, the gas flows in the two gas flow paths are usually switched alternately at desired time intervals and controlled by an MFC (or a pump, etc.) so that the gas flow rate is constant on the time axis. However, depending on the configuration of the measurement system and the specifications of the gas detection means (MSS in FIG. 1), it may be possible to make the baseline more stable by making the gas flow rate during the purge period greater than the gas flow rate during the sample gas injection period.

[0044] In this embodiment, the measurement results of the time change in signal intensity as shown in FIG. 3 (hereinafter simply referred to as the "measurement results") obtained by supplying a sample gas to a surface stress sensor such as an MSS are used to determine whether an animal suffers from ketosis based on the composition of the gas generated from the milk.

[0045] Specifically, the measurement results may be used as they are, or may be subjected to any data analysis processing. For example, a time point arbitrarily selected from the time range of the measurement cycle is set as a reference point, and offset processing is performed based on this time point. Then, another arbitrary time point from the above time range is set as a judgment point, and a feature amount is obtained from the judgment point or a value near the judgment point, so that the presence or absence of ketosis and / or the possibility of ketosis can be determined. Examples of the feature amount include the signal intensity after offset processing at the judgment point, the slope of the signal graph at the judgment point, the average slope or curvature of the signal graph near the judgment point, etc. Note that raw signals that have not been subjected to offset processing of signals contain unique information such as long-term changes in the sensor over time and the current state as the absolute value of the sensor signal, so that the raw signal value may be used as it is without performing offset processing, or any feature amount may be extracted from the raw signal for analysis.

[0046] Note that the offset process here refers to a process of calculating the signal intensity after offset process S'(t) = S(t) - S(t0) by translating the signal intensity graph along the intensity axis so that the signal intensity S(t0) at the reference point t0 becomes 0 (generally an arbitrary constant).

[0047] The reference point may be, for example, a point immediately before the start of the sample gas injection period (i.e., the end of the purge period) or a point immediately before the start of the purge period (i.e., the end of the sample gas injection period), but may be any other point. However, since the gas given to the surface stress sensor is switched at the time of switching between purge and injection, the signal from the surface stress sensor may be disturbed near this boundary point. Even if the gas is switched, there may be a non-negligible time delay until the gas around the surface stress sensor, which is located at a position via a gas flow path of a certain length from a switching mechanism such as a valve, is actually switched. If the influence of instability such as this signal disturbance or time delay can be a problem, the reference point may be a point slightly shifted in time from the time of this switching.

[0048] In addition, a time point arbitrarily selected from the time range of the measurement cycle is set as a reference point, and offset processing is performed based on the selected time point. Thereafter, another arbitrary time point within the above time range is set as a judgment point, and a feature amount is obtained from a value at or near the judgment point, thereby making it possible to determine the presence or absence of ketosis and / or the possibility of ketosis. Examples of the feature amount include the signal intensity after offset processing at the judgment point, the slope of the signal graph at the judgment point, and the average slope or curvature of the signal graph near the judgment point. Note that if the offset amount of the signal is sufficiently small, or the feature amount obtained from the signal intensity before offset is sufficiently large, the offset processing may be omitted. However, the decision point that satisfies such conditions can vary not only depending on the length of the measurement cycle, the length of the sample gas injection period and the purge period, but also on the configuration of the measurement system (gas flow path, gas supply form to the measurement system, gas flow rate, etc.) and measurement conditions, and even the type of sensitive membrane material if the gas detection means is a surface stress sensor (more specifically, MSS). Therefore, it is desirable to confirm in advance using reference milk, etc., the combination of reference point and decision point from which feature amounts effective in determining the presence of ketosis can be extracted for each sensitive membrane material.

[0049] As described above, in this embodiment, the baseline fluctuation can be suppressed and the baseline can be stabilized by appropriately setting the time allocation of the measurement cycle and the configuration of the measurement sequence, so that the accuracy of the determination can be ensured even when the difference in the extracted feature amount is small. Specifically, by lengthening the purge period, gas is sufficiently desorbed from the sensitive film, so that the state before the sample gas injection can be restored to a similar state every time. That is, lengthening the purge period is useful for sufficiently resetting the measurement system. The time when the reset is sufficiently performed is the time immediately before the sample gas injection, and by setting this as the reference point for offset, signal reproducibility is ensured, and as a result, highly accurate determination can be easily made. In particular, by performing offset processing based on the purge signal immediately before the start of sample gas injection and setting the determination point at a time when a short time has passed since the end of the injection period, the fluctuation in signal intensity at the determination point is more likely to be clear, and a feature amount effective for determining ketosis is easily obtained. In the experiments shown in the Examples, visual determination was made easiest by observing the signal intensity at or near the time several to several tens of seconds had elapsed since the end of the injection period.

[0050] In the above description, the measurement was performed based on a measurement sequence in which the sample gas and the purge gas were switched, but the present invention is not limited to this. For example, it is possible to insert a measurement of another gas (standard gas) that contains a component that is contained in the sample gas and whose concentration may affect the determination of the onset of ketosis into the measurement sequence, and to determine the onset of ketosis based on the signal from the measurement in which the three types of gases are switched.

[0051] As such a standard gas, milk obtained from a healthy animal not suspected of having ketosis may be used as the reference milk, and a gas having the same component composition as the sample gas components generated from the reference milk may be used as the standard gas. Such a reference milk may be, for example, milk obtained from an animal that belongs to the same rearing environment as the animal to be tested (hereinafter also referred to as "animals of the same group"). In this case, the milk may be individual milk (milk obtained from a single individual. Milk obtained from an animal known to be healthy among animals of the same group is preferable) or combined milk (milk in which multiple individual milks are mixed in a milking tank or the like. Also called bulk milk).

[0052] Alternatively, various compositions can be set as necessary, such as using a gas with the same composition as the standard gas for some of the components of the sample gas assumed in this way (for example, a component for which slight differences in the amount of the component are to be measured with particularly high accuracy). Then, taking into consideration various requirements and constraints on the measurement, the supply sequence of these three types of gas is set appropriately. For example, a measurement sequence including the repetition of the following gas supply time intervals is conceivable: A. Supply purge gas → [Supply either sample gas or standard gas → Supply purge gas → Supply the other sample gas or standard gas → Supply purge gas] (or repeat the steps in [ ]) B. Supply purge gas → [supply sample gas and standard gas alternately → supply purge gas] (or repeat the steps in [ ]) C. Supply purge gas → [Repeat alternate supply of sample gas, standard gas, and purge gas → Supply purge gas → Repeat alternate supply of sample gas, standard gas, and purge gas] (or repeat the contents in [ ]) In addition to the above, various gas supply sequences for the gas supply time section are possible. In any gas supply sequence, it is considered that the measurement conditions such as temperature, gas pressure / flow rate, and changes in sensor characteristics over time do not change significantly during a series of measurement sequences, so by comparing the sample gas with the standard gas, minute differences in composition between the two gases can be precisely measured, and the effect of disturbances on the measurement results can be reduced, improving the stability of the measurement.

[0053] When a standard gas is also used, a gas flow path for the standard gas is added to the gas supply system of the measurement device, but this can be easily realized by using various existing technologies for gas supply systems. For example, the standard gas can be prepared in a gaseous state from the beginning, or it can be introduced into the gas supply system by evaporating it from a liquid or solid. When providing the standard gas, another gas such as a purge gas can be mixed with the gas originally prepared or the gas generated from a liquid or solid. In addition, these three gas flow paths need to be ultimately joined, but the three flow paths can be joined at one point, or a part of the upstream side of the sample gas flow path can be made to flow to form a standard gas flow path, and after the standard gas is introduced there, both gas flow paths can be joined just before the joining point with the purge gas.

[0054] Furthermore, if the reproducibility of the measurement is high to the extent that the required determination accuracy can be realized and the variation between the sensor chips and the measuring devices can be calibrated, it is also possible to construct a measurement procedure and a measurement system for the measurement in which the measurement of the sample gas and the measurement of the standard gas are independent of each other and performed at different convenient times. For example, the measurement of the standard gas and the measurement of the sample gas may be performed separately, rather than simultaneously or successively in a series of measurement sequences, and the standard gas measurement data and the sample gas measurement data obtained from these measurements may be compared. Here, as long as the condition in the preface is satisfied, i.e., the condition that the reproducibility of the measurement is high to the extent that the required determination accuracy can be realized and the variation between the sensor chips and the measuring devices can be calibrated, the sensor chip and the measuring device used to measure the sample gas may be the same individual, or a sensor chip and a measuring device different from those used in one measurement may be used. Moreover, the measurement may be performed using only the sample gas and the standard gas without using a purge gas. In this case, the measurement may be performed using the standard gas as a purge gas. Furthermore, the measurement may be performed using only the sample gas or only the standard gas. In this case, you can expose the sample gas or standard gas to the sensor for a long enough time so that each gas is sufficiently adsorbed and diffused into the sensitive film and the sensor shows a certain signal value. You can use the absolute value of this signal as a feature value as it is, or you can measure the signal when exposed to the atmosphere for a long enough time before measurement and use it as a reference point.

[0055] For example, when comparing past milk from the same animal with the milk from the current milking result, it is not practical to store the past milk itself or the volatile and evaporated components from it without deterioration. Therefore, if the gas obtained from the milk at a time when it is already known that the animal was healthy in the past is measured and stored as data of the standard gas, the gas obtained from the current milk from the same animal can be similarly digitized as the sample gas, and as long as the reproducibility of the measurement and the possibility of calibrating various variations can be guaranteed, the above gases can be compared when the milk to be measured is all fresh. Note that there is no particular limit to the way in which the measurement results of each gas are digitized. As a non-limiting example, the output from the sensor when each gas and the purge gas are alternately switched may be digitized as it is, or the sensor output during other types of measurement may be digitized, or the digital value of the digitized result as described above may be further processed.

[0056] Examples of materials for the sensitive film of the surface stress sensor include, but are not limited to, Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Cellulose Acetate Butyrate, Poly(ethyleneimine), phenyl-modified silica / titania composite nanoparticles (hereinafter also referred to as "Phenyl-STNPs"), and Polystyrene. These sensitive film materials may be used alone or in combination.

[0057] For example, in an embodiment in which gas generated from milk is used as the sample to be tested, at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Cellulose Acetate Butyrate, and Poly(ethyleneimine) may be used as the sensitive film material. Of these, it is preferable to use at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Cellulose Acetate Butyrate, and Poly(ethyleneimine). In an embodiment in which gas generated from urine is used as the sample to be tested, at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Phenyl-STNPs, and Polystyrene can be used among the above-mentioned sensitive film materials. Among them, it is preferable to use at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), and Poly(vinylidene fluoride), and it is more preferable to use at least one selected from the group consisting of Poly(4-methylstyrene) and Poly(2,6-diphenyl-p-phenylene oxide). In other words, of the above-mentioned sensitive film materials, Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), and Poly(vinylidene fluoride) are sensitive film materials that can be suitably used for multiple types of test subjects, including milk and urine, and in that sense, they can be said to be more versatile sensitive film materials. Specific measurement examples using the above-mentioned sensitive film materials will be described later.

[0058] Poly(2,6-diphenyl-p-phenylene oxide) is a material also known as "Tenax" (registered trademark), and several types are commercially available depending on its purity and additives. For example, Tenax TA and Tenax GR (Tenax GR is Tenax polymerized with 23% graphite carbon) are given by adding a suffix after Tenax, and any of these can be used in the method of this embodiment. Tenax is provided in various particle size distributions, and the particle size range is expressed by mesh, for example, Tenax TA 20 / 35. In the examples described later, Tenax TA 60 / 80 (obtained from GL Sciences Inc.) was used as Poly(2,6-diphenyl-p-phenylene oxide).

[0059] The present invention will be described in more detail below with reference to examples. Note that the following examples are not intended to limit the present invention, but are intended to aid in understanding the present invention. EXAMPLES

[0060] In this embodiment, a measurement system whose schematic configuration is shown in FIG. 1 was used. The MSS used was an assembly of multiple MSSs coated with different sensitive film materials. In the following, the MSS using Poly(4-methylstyrene) is referred to as "ChA", the MSS using Poly(2,6-diphenyl-p-phenylene oxide) as "ChB", the MSS using Poly(vinylidene fluoride) as "ChC", the MSS using Cellulose Acetate Butyrate as "ChD", the MSS using Poly(ethyleneimine) as "ChE", the MSS using phenyl-modified silica / titania composite nanoparticles (Phenyl-STNPs) as "ChF", and the MSS using Polystyrene as "ChG".

[0061] <Test 1: Measurement of gases generated from milk of healthy cows in different rearing environments> At the Hokkaido Agricultural Research Center of the National Agriculture and Food Research Organization, 10 mL of milk (sample 1) from dairy cows raised in the pasture and fed raw grass (grazing cows) and 10 mL of milk (sample 2) from dairy cows raised in a barn and fed silage (barn-raised cows) were each placed into a vial and measurements were taken. The milk from Sample 1 and Sample 2 had different aromas that could be distinguished by the human sense of smell, and the flavors detected by the human palate were also significantly different.

[0062] The temperature of the incubator housing the measurement system was set to 30°C. The flow rates of the sample gas and purge gas were 10 sccm, and the sampling time (the time to inject the sample gas in each measurement cycle) was 120 seconds. The measurements were performed with a ratio of the sampling time to the purge time (the time to provide the purge gas to the MSS and purge it in each measurement cycle) of 1:4. Specifically, the measurement sequence in each measurement cycle was configured such that the purge gas was first flowed for 240 seconds, the sample gas was then flowed for 120 seconds, and then the purge gas was again flowed for 240 seconds. In other words, since each measurement was performed continuously, the purge gas flowed after the sample gas was flowed and the purge gas flowed before the next sample gas were flowed continuously without interruption. Therefore, the purge time was the sum of the above two purge times, and the ratio of the sampling time to the purge time was substantially 1:4. Note that these measurement conditions can be appropriately adjusted according to the configuration of the measurement system.

[0063] The procedure for switching samples (e.g., switching to a different milk) during the above measurement sequence is described here. After the sampling time has elapsed, the vial containing the sample is separated from the gas flow path by the switching valve. This allows the sample to be switched to the next sample at any time without affecting the measurement.

[0064] The operation of changing the measurement sample (such as changing the vial) takes several tens of seconds, and since it is necessary to input the data setting of the measurement system to reflect the fact that the sample has been changed, the sensor module needs to be stopped between two measurements of different samples. However, the module temperature drops when the sensor module is stopped, causing the baseline to fluctuate. This baseline fluctuation becomes a large noise in measuring minute signal differences, so it is ideal to keep the module stop between measurements to within one second. Here, as described above, by disconnecting the vial containing the sample (of course, the same applies to other types of sample containers, etc.) from the gas flow path after the sampling time has ended, the vial can be replaced and other operations associated with this replacement can be performed while it is disconnected. Therefore, in this method, the sample switching can be performed in parallel with the purging process, so that the sample switching time does not appear substantially in the measurement sequence.

[0065] The results are shown in Figure 4. 4 is a diagram showing the time change (unit: second) of the signal (unit: mV) from the MSS of ChA. In FIG. 4, the measurement results of Sample 1 are shown in light gray, and the measurement results of Sample 2 are shown in dark black. The results shown in Fig. 4 are plotted as typical results of measurements taken multiple times for the same sample, with the offset set to start at the start of the sample gas injection period in the measurement sequence (i.e., the end of the first purge period). The same applies to Figs. 5 to 14 and Figs. 18 to 22, which will be described later.

[0066] As can be seen from Figure 4, when the ChA sensitive membrane material was used, the signal intensity rose sharply immediately after the start of the sample gas injection period, and then approached the saturation value. In the time period (from about 270 seconds to 325 seconds), the signal intensity of the barn cows was slightly higher than that of the pasture cows, but there was no significant difference that would allow for the extraction of any feature value, and the time course of the signal outside of that time period was almost the same. In other words, when the ChA sensitive membrane material was used, no clear difference was observed in the signal for the gas components detected by the MSS, even in milk with aromas and flavors that were clearly distinguishable by human olfaction and taste. This suggests that if a different trend is observed in the time course of the signal from the ChA MSS, it is highly likely that it is due to a disease in the dairy cows.

[0067] <Test 2: Measurement of gas generated from milk simulating milk from cows with ketosis> According to Non-Patent Document 2, the acetone concentration in the milk of healthy cows is less than 0.7 mmol / L, whereas the acetone concentration in the milk of cows suffering from hyperketonaemia, which clearly shows a decrease in milk production, exceeds 1.4 mmol / L (see Table 1). Therefore, assuming that the acetone concentration in the milk of sample 2 (milk from a barn-housed cow) used in the above test 1 was 0.7 mmol / L, 0.1 mL of an aqueous solution with an acetone concentration of 70 mmol / L was added to 10 mL of milk from the same barn-housed cow to prepare a sample (sample 3) with an acetone concentration in the milk approximating 1.4 mmol / L, which was used as a sample simulating the milk of a cow suffering from ketosis. For comparison, a sample (sample 4) was prepared by adding 0.1 mL of distilled water to 10 mL of milk from the same barn-housed cow used in test 1, and samples 3 and 4 were each placed in a vial and measured.

[0068] The measurement conditions, such as the temperature of the incubator housing the measurement system, were the same as in Test 1.

[0069] The results are shown in Figure 5. 5 is a diagram showing the time change (unit: second) of the signal (unit: mV) from the MSS of ChA. In FIG. 5, the measurement results of Sample 3 are shown in light gray, and the measurement results of Sample 4 are shown in dark black.

[0070] As can be seen from FIG. 5, when the ChA sensitive membrane material was used, a difference in the change in the signal over time was confirmed between Sample 3 and Sample 4. Specifically, the behavior of the signal intensity rising sharply immediately after the start of the sample gas injection period and then approaching the saturation value is different. Also, a difference is observed in the behavior (tendency of the signal intensity to decrease) from the sharp drop in the signal intensity immediately after switching from the sample gas injection period to the purge period until it converges (returns) to the baseline. Furthermore, a difference is observed in the saturation value of the signal intensity. Compared to the case where the start point of the purge period was set as the starting point of the offset, the difference in the measurement results between Sample 3 and Sample 4 was more clear in the results shown in FIG. 5.

[0071] On the other hand, when the sensitive film materials of ChB, ChD, and ChE were used, differences in the signal changes over time were confirmed between Sample 3 and Sample 4, but they were not as clear as in the case of ChA (data not shown). This suggests that it may be difficult to make a judgment based on the measurement results of ChB, ChD, or ChE using MSS alone, but does not deny the possibility that it may be possible to make a judgment by combining it with MSS using ChA or other sensitive film materials (or other gas detection means including a surface stress sensor of a different type from MSS).

[0072] <Test 3: Measurement of gas generated from milk of cows with ketosis (1)> 10 mL of milk (sample 5) that was determined to be strongly positive (BHBA concentration 1000 μM) in a test using a product that semi-quantifies β-hydroxybutyric acid in milk (Sanketo Paper, Sanwa Kagaku Kenkyusho Co., Ltd.) and 10 mL of milk (sample 6) that was determined to be negative (BHBA concentration 50 μM) were each placed in a vial and measured. The measurements of Samples 5 and 6 were carried out using milk that had been left to stand at room temperature for about 24 hours after collection.

[0073] In the measurements of Samples 5 and 6, the vials were placed in a room temperature (approximately 25°C) environment, and the measurement system was an open system. During the measurements, the temperature of the sensor module was stable at approximately 36.5°C. Other measurement conditions, such as the flow rates of the sample gas and purge gas, were the same as in Test 1.

[0074] The fact that the dairy cows from which Samples 5 and 6 were taken were ketosis-afflicted and healthy, respectively, was determined by comprehensive analysis of the peak intensities derived from acetone in the mass spectra of the milk and urine samples obtained by PTR-TOF-MS, in addition to the results of tests on the milk samples using the above-mentioned products. The same applies to Tests 4 and 5 described below.

[0075] The results are shown in Figures 6 to 9. FIG. 6 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChA. FIG. 7 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChB. FIG. 8 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChD. FIG. 9 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChE. 6 to 9, the measurement results of Sample 5 are shown in light gray, and the measurement results of Sample 6 are shown in dark black.

[0076] As can be seen from Fig. 6, when the ChA sensitive membrane material was used, the change in the signal over time for sample 5 was significantly different from that for sample 6. Specifically, in sample 5, the signal intensity rises sharply immediately after the start of the sample gas injection period, and then increases and approaches the saturation value, whereas in sample 6, the signal intensity when it rises sharply immediately after the start of the sample gas injection period is smaller than that of sample 5, and the change in the signal intensity when it approaches the saturation value is within a range of about 0.1 mV. As a result, there is a significant difference in the saturation value of the signal intensity between sample 5 and sample 6. In addition, when examining the behavior (tendency for signal intensity to decrease) from the sharp drop in signal intensity immediately after switching from the sample gas injection period to the purge period to the convergence (return) to the baseline, both sample 5 and sample 6 experienced a sharp drop in signal intensity, but sample 5 converged more gradually from a higher signal intensity value toward the baseline than sample 6, while sample 6 saw the signal intensity converge and return to the baseline in a shorter time.

[0077] Moreover, measurement results similar to those obtained when the sensitive film material ChA shown in FIG. 6 was used were also obtained when the sensitive film materials ChB, ChD, and ChE shown in FIGS.

[0078] These results show that the MSS using the ChA, ChB, ChD, and ChE sensitive membrane materials can determine the presence of ketosis from the measurement results of each alone. More specifically, by applying an appropriate offset process to the measurement results, it was possible to clearly distinguish between milk determined to be negative and milk determined to be strongly positive by the semi-quantitative method using the above-mentioned test strips. It was also suggested that the accuracy of determining the presence of ketosis can be improved by combining multiple measurement results obtained using these MSSs.

[0079] Although not shown, the MSS using the ChC sensitive film material showed results indicating that it is possible to determine the presence of ketosis from a single measurement result, similar to the MSS using the ChA, ChB, ChD, and ChE sensitive film materials, but it was suggested that it is more preferable to combine multiple measurement results. In other words, it was suggested that the MSS using the ChC sensitive film material is more suitable for determination in combination with the MSS using the ChA, ChB, ChD, and ChE sensitive film materials (or other gas detection means including a surface stress sensor of a different type from the MSS).

[0080] <Test 4: Measurement of gas generated from milk of cows with ketosis (2)> 10 mL of milk (sample 7) that was determined to be false positive or positive (BHBA concentration 100-200 μM) in a test using a product that semi-quantifies β-hydroxybutyric acid in milk (Sanketo Paper, Sanwa Kagaku Kenkyusho Co., Ltd.) and 10 mL of milk (sample 8) that was determined to be negative (BHBA concentration 0-50 μM) were each placed in a vial and the following two types of measurements were performed under different temperature conditions. The measurements for Samples 7 and 8 were performed using milk that had been refrigerated immediately after collection.

[0081] [Measurement a] In measurement a, the vial was placed in a room temperature (approximately 20°C) environment, and the measurement system was open. During the measurement, the temperature of the sensor module was stable at approximately 36.5°C. Other measurement conditions, such as the flow rates of the sample gas and purge gas, other than the temperature conditions of the vial, were the same as in Test 1.

[0082] [Measurement b] In measurement b, the vial was placed in a water bath set to approximately 30°C, and the measurement system was an open system. During the measurement, the temperature of the sensor module was stable at approximately 36.5°C. Other measurement conditions, such as the flow rates of the sample gas and purge gas, other than the temperature conditions of the vial, were the same as in Test 1.

[0083] The results of measurement a and measurement b are shown in FIGS. 10 to 11 and FIGS. 12 to 14, respectively. FIG. 10 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChA in measurement a. FIG. 11 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChD in measurement a. FIG. 12 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChA in measurement b. FIG. 13 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChD in measurement b. FIG. 14 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChE in measurement b. 10 to 14, the measurement results of Sample 7 are shown in light gray, and the measurement results of Sample 8 are shown in dark black.

[0084] As can be seen from Figure 10, in measurement a, when the ChA sensitive membrane material was used, a difference in the signal change over time was confirmed between sample 7 and sample 8. Specifically, the behavior of the signal intensity rising sharply immediately after the start of the sample gas injection period and then approaching the saturation value is different. There is also a difference in the behavior (tendency of the signal intensity to decrease) from the sharp drop in the signal intensity immediately after switching from the sample gas injection period to the purge period until it converges (returns) to the baseline. Furthermore, a difference is also seen in the saturation value of the signal intensity.

[0085] Here, referring to FIG. 12 showing the results when the sensitive film material of ChA was used in the measurement b, it can be seen that the change in the signal over time of the sample 7 is significantly different from that of the sample 8, as compared to the results shown in FIG. 10. Specifically, in the sample 8, no particular difference was observed between the results obtained in the measurement a and the results obtained in the measurement b, but in the sample 7, the signal intensity value at the sharp fall of the signal intensity immediately after switching from the sample gas injection period to the purge period is higher in the result obtained in the measurement b than in the result obtained in the measurement a, and gradually converges from that value to the baseline. As a result, in the result of the measurement b shown in FIG. 12, the difference in the behavior of the decrease in the signal intensity during the purge period is more clear between the sample 7 and the sample 8.

[0086] These results suggest that by selecting an appropriate material as the sensitive membrane material for the MSS, as well as by appropriately controlling the temperature of the vial containing the sample, it is possible to further improve the accuracy of measuring the gas generated from the sample (milk), and in turn to further improve the accuracy of determining the presence or absence of ketosis and / or the possibility of having ketosis.

[0087] Furthermore, measurement results having the same characteristics as those obtained when the sensitive film material ChA shown in FIGS. 10 and 12 was used were also obtained when the sensitive film material ChD shown in FIGS. 11 and 13 was used.

[0088] Although not shown in the figure, when the ChB sensitive film material was used, measurement results with similar characteristics to those when the ChA and ChD sensitive film materials were used were obtained. However, the correlation between the difference in the temperature conditions of the vial and the measurement results was more pronounced when the ChA and ChD sensitive film materials were used.

[0089] Furthermore, when the ChE sensitive membrane material was used, the difference in the signal change over time between samples 7 and 8 in measurement a was not clear, whereas in measurement b, as shown in Figure 14, the signal change over time of sample 7 was different from that of sample 8, comparable to when the ChA and ChD sensitive membrane materials were used (Figures 12 and 13).

[0090] From these results, it was found that in the measurement by MSS using the sensitive film material of ChA and ChD, by maintaining the temperature of the vial containing the sample at an arbitrary value, it is possible to judge the possibility of ketosis from the measurement results of each alone. More specifically, it was found that by performing an appropriate offset process on the measurement results, it is possible to clearly distinguish the difference between milk judged as false positive to positive by the semi-quantitative method using the above-mentioned test paper and milk judged as negative. It was also found that the accuracy of judgment can be further improved by setting the temperature of the vial to an appropriate value. These findings are similarly applicable to MSS using the sensitive film material of ChB. Furthermore, it was suggested that depending on the combination of the temperature of the vial containing the sample and the sensitive film material of the MSS, it may be possible to judge the presence of ketosis from the measurement results alone, or that measurement results useful for judgment may be obtained by combining with MSS using other sensitive film materials (or other gas detection means including a surface stress sensor of a different type from MSS).

[0091] <Test 5: Measurement of gas generated from urine of cows with ketosis> [Proton transfer reaction time-of-flight mass spectrometry using milk and urine] To measure samples using the measurement system, proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) was used to measure milk and urine samples from cows with ketosis and healthy cows.

[0092] 15A and 15B show mass spectra obtained by PTR-TOF-MS of milk from a cow suffering from ketosis and milk from a healthy cow, respectively. Here, cows suffering from ketosis are dairy cows judged as positive to strongly positive (BHBA concentration 200-1000μM) in a test using a product (Sanketo Paper, Sanwa Kagaku Kenkyusho Co., Ltd.) that semi-quantifies β-hydroxybutyric acid in milk, and healthy cows are dairy cows judged as negative (BHBA concentration 0-50μM) in the above test. The amount of milk sample used in the measurement was 2mL, and the gas dilution ratio was 100 times. The same applies to the measurement of urine samples (Figures 16A and 16B) described later.

[0093] As can be seen from Figures 15A and 15B, the peak positions (m / z values) in the mass spectra of milk from cows with ketosis and healthy cows are highly similar, but the peak intensities in the m / z value range of approximately 50 to 80 were significantly different between cows with ketosis and healthy cows, and analysis confirmed that the milk contained peaks derived from acetone and 2-butanone, as indicated by the arrows in each figure.

[0094] 16A and 16B show mass spectra obtained by PTR-TOF-MS of urine from a cow suffering from ketosis and a healthy cow, respectively.

[0095] The mass spectra in Figures 16A and 16B also showed results similar to those of the milk sample described above. That is, in the mass spectra of the urine of cows with ketosis and the urine of healthy cows, the peak positions (m / z values) were highly similar, but the peak intensities in the m / z value range of approximately 50 to 80 showed significant differences between the ketotic and healthy cows, and the analysis confirmed that the peaks derived from acetone and 2-butanone were included, as indicated by the arrows in each figure.

[0096] Interestingly, comparing Figures 15A and 16A, and Figures 15B and 16B, it can be seen that the mass spectra of the milk and urine of ketosis cows and those of healthy cows are almost identical in overall peak profile. Therefore, further analysis was performed on the concentrations of acetone and 2-butanone, which are characteristic components in these samples.

[0097] Figures 17A, 17B, and 17C show the results of measuring the concentrations of acetone and 2-butanone by PTR-TOF-MS in milk and urine of cows with ketosis and in milk and urine of healthy cows. Figure 17A shows the results of measuring the concentrations of acetone and 2-butanone together, with the solid line being acetone and the dashed line being 2-butanone. Figures 17B and 17C show the results of measuring the concentrations of acetone and 2-butanone shown in Figure 17A separately, with Figure 17B showing acetone and Figure 17C showing 2-butanone.

[0098] From the measurement results shown in Figures 17A to 17C, it was found that the concentrations of acetone and 2-butanone, which are characteristic components in the milk and urine collected from cows with ketosis and healthy cows in this test, were very close in value between the milk and urine of cows with ketosis and the milk and urine of healthy cows, and moreover, the difference was so slight that they could be considered to be almost identical.

[0099] Thus, the PTR-TOF-MS results shown in Figures 15A and 15B, 16A and 16B, and 17A to 17C indicate that even for different types of bodily fluids, such as milk and urine from dairy cows, there is a common correlation between the presence or absence of ketosis and the content (concentration) of specific components (e.g., acetone and 2-butanone) in the composition of the gas generated from these bodily fluids. This suggests that it is possible to determine the presence or absence of ketosis not only from the milk used in the measurements in Tests 1 to 4 above, but also from bodily fluids other than milk collected from animals, such as blood, urine, saliva, and sweat, using the gas generated therefrom.

[0100] [Urine sample measurement] Next, based on the above findings, 2 mL of urine from a cow suffering from ketosis (sample 9) and 2 mL of urine from a healthy cow (sample 10) were each placed in a vial and measurements were performed.

[0101] In the measurements of Samples 9 and 10, the vials were placed in a room temperature (approximately 25°C) environment, and the measurement system was an open system. During the measurements, the temperature of the sensor module was stable at approximately 36.5°C. Other measurement conditions, such as the flow rates of the sample gas and purge gas, were the same as in Test 1.

[0102] The results are shown in Figures 18 to 22. FIG. 18 shows the change over time (unit: second) of the signal (unit: mV) from the MSS of ChA. FIG. 19 shows the change over time (unit: seconds) of the signal (unit: mV) from the MSS of ChB. FIG. 20 shows the time course (unit: seconds) of the signal (unit: mV) from the MSS of ChC. FIG. 21 shows the change over time (unit: second) of the signal (unit: mV) from the MSS of ChF. FIG. 22 shows the change over time (unit: second) of the signal (unit: mV) from the MSS of ChG. 18 to 22, the measurement results of Sample 9 are shown in light gray, and the measurement results of Sample 10 are shown in dark black.

[0103] As can be seen from Figure 18, when the ChA sensitive membrane material was used, a difference in the signal change over time was confirmed between Sample 9 and Sample 10. Specifically, the behavior of the signal intensity rising sharply immediately after the start of the sample gas injection period and then approaching the saturation value is different. There is also a difference in the behavior (tendency of the signal intensity to decrease) from the sharp drop in the signal intensity immediately after switching from the sample gas injection period to the purge period until it converges (returns) to the baseline. Furthermore, a difference is also seen in the saturation value of the signal intensity.

[0104] Moreover, measurement results similar to those obtained when the sensitive film material ChA shown in FIG. 18 was used were also obtained when the sensitive film materials ChB, ChC, ChF, and ChG shown in FIGS.

[0105] These results show that the MSS using the ChA, ChB, ChC, ChF, and ChG sensitive membrane materials can determine the presence of ketosis from the measurement results of each alone. More specifically, by applying an appropriate offset process to the measurement results, it was possible to clearly distinguish between the urine of dairy cows that were determined to be negative by the semi-quantitative method using the above-mentioned test paper and the urine of dairy cows that were determined to be positive to strongly positive. It was also suggested that the accuracy of determining the presence of ketosis can be improved by combining multiple measurement results obtained using these MSS.

[0106] For example, in a case where both milk and urine can be obtained relatively easily (without placing additional burden on the animal) as test samples, an MSS using a ChA-sensitive membrane material can be used alone as a measurement system to measure the gases generated from milk and urine, and the presence or absence of ketosis can be determined based on the results. As an example of using multiple sensitive membrane materials, a measurement system can be constructed with an assembly of MSSs coated with each of the ChA to ChG sensitive membrane materials, and the MSSs using the ChA, ChB, and ChC sensitive membrane materials can measure gases generated from milk and gases generated from urine, the MSSs using the ChD and ChE sensitive membrane materials can measure gases generated from milk, and the MSSs using the ChF and ChG sensitive membrane materials can measure gases generated from urine, and by combining these results, the presence of ketosis can be determined. [Industrial Applicability]

[0107] When milk is used as the body fluid to be tested, the present invention is typically suitable for application to dairy cows. In addition to dairy cows, the present invention is also suitable for application to animals raised to produce milk industrially, such as goats, sheep, buffaloes, yaks, and other bovine animals, and horses. More specifically, the present invention is particularly suitable for preliminary extraction (screening) of individuals suffering from ketosis and / or individuals suspected of suffering from ketosis in animals raised in large numbers to produce milk, such as dairy cows. In addition, body fluids other than milk can be tested as long as they are available as appropriate depending on the situation, although the ease of collection and the certainty of obtaining the required body fluids vary depending on the type of body fluid, the type of animal, and the collection method.

[0108] In recent years, efforts have been made in the early detection of signs of illness or changes in physical condition in dairy cow and other husbandry management systems by utilizing motion sensors, etc. By combining the present invention with such husbandry management systems, it is possible to more easily and efficiently manage the health of animals, and it is expected to contribute to improving or maintaining productivity.

Claims

1. A gas generated from a body fluid collected from an animal (excluding humans) is applied to a gas sensor, using a signal output from the gas sensor in response to the gas generated from the body fluid, determining whether the animal is suffering from ketosis based on a concentration of ketones in the gas generated from the body fluid; A method for determining whether or not one is suffering from ketosis.

2. 2. The method for determining whether or not a patient is suffering from ketosis according to claim 1, wherein the gas generated from the body fluid contains, in addition to the ketones, at least one selected from the group consisting of alcohols, aldehydes, nitriles, organic acids, water (water vapor), nitrogen, oxygen and carbon dioxide.

3. A gas generated from a body fluid collected from an animal (excluding humans) is applied to a gas sensor, using a signal output from the gas sensor for the gas generated from the body fluid, determining whether the animal is suffering from ketosis based on a concentration of a specific component in the gas generated from the body fluid; In the method for determining whether or not a person has ketosis, A method for determining whether or not a person is suffering from ketosis, wherein the specific component is a substance having a peak in the m / z value range of 50 to 80 in a mass spectrum.

4. The method for determining whether or not a patient is suffering from ketosis according to claim 3, wherein the body fluid or a gas generated from the body fluid is subjected to mass spectrometry to confirm the m / z value in the mass spectrum of the specific component.

5. The method for determining whether or not a patient is suffering from ketosis according to claim 4, wherein the body fluid or the gas generated from the body fluid is subjected to mass analysis by proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS).

6. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 3 to 5, wherein the specific component is at least one selected from the group consisting of acetone, propanol, butanol, acetic acid, propionic acid, butyric acid, 2-butanone, butanal, 2-methoxy-1-propene, and 2-methyl-propanal.

7. The method for determining whether or not a patient is suffering from ketosis according to claim 6, wherein the specific component is at least one selected from the group consisting of acetone and 2-butanone.

8. The method for determining the presence of ketosis according to any one of claims 3 to 5, wherein the gas generated from the body fluid contains at least one selected from the group consisting of ketones, alcohols, aldehydes, nitriles, organic acids, water (water vapor), nitrogen, oxygen and carbon dioxide.

9. The method for determining whether or not a patient has ketosis according to claim 2 or 8, wherein the ketones are at least one selected from the group consisting of acetone and 2-butanone, the alcohols are at least one selected from the group consisting of methanol, ethanol, propanol, and butanol, the aldehydes are at least one selected from the group consisting of formaldehyde, acetaldehyde, butanal, and 2-methyl-propanal, the nitriles are acetonitrile, and the organic acid is at least one selected from the group consisting of formic acid, acetic acid, propionic acid, and butyric acid.

10. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 1 to 9, wherein the body fluid is selected from the group consisting of milk, blood, urine, saliva, and sweat.

11. A method for determining the presence of ketosis described in any of claims 1 to 10, comprising setting the temperature of a container containing the body fluid to 5°C to 50°C, and providing the gas generated from the body fluid to the gas sensor.

12. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 1 to 11, wherein the determination of whether or not a patient is suffering from ketosis is made based on a pattern of change over time of the signal.

13. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 1 to 12, wherein the gas sensor is a surface stress sensor.

14. The method for determining whether or not a patient has ketosis according to claim 13, further comprising passing a gas that does not substantially contain components that affect the determination of whether or not a patient has ketosis through a container that contains the body fluid, and supplying the gas thus obtained to the surface stress sensor as a gas generated from the body fluid.

15. The method for determining whether or not a person is suffering from ketosis according to claim 13 or 14, wherein the determination of whether or not a person is suffering from ketosis is made using the signal after the supply of the gas generated from the body fluid to the surface stress sensor is started.

16. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 13 to 15, wherein the surface stress sensor is a membrane-type surface stress sensor.

17. The method for determining the onset of ketosis according to any one of claims 13 to 16, wherein at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Cellulose Acetate Butyrate, Poly(ethyleneimine), phenyl group-modified silica / titania composite nanoparticles, and Polystyrene is used as a material for the sensitive film of the surface stress sensor.

18. The method for determining whether or not a patient is suffering from ketosis as described in claim 17, wherein at least a first surface stress sensor using one material selected from the group as a sensitive film and a second surface stress sensor using another material selected from the group as a sensitive film are used as the surface stress sensor.

19. 19. A method for determining whether or not a patient is suffering from ketosis according to any one of claims 13 to 18, wherein the gas generated from the body fluid and a purge gas are alternately applied to the surface stress sensor, and the presence or absence of ketosis is determined using the signal corresponding to the gas generated from the body fluid and the signal corresponding to the purge gas.

20. 20. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 13 to 19, further comprising supplying gas generated from the body fluid to an additional gas sensor, and determining whether or not a patient is suffering from ketosis based on a signal from the surface stress sensor and a signal from the additional gas sensor.

21. The method for determining whether or not a patient is suffering from ketosis as described in claim 19, further comprising, in addition to a time period during which the gas generated from the body fluid is supplied to the surface stress sensor and a time period during which the purge gas is supplied to the surface stress sensor, a time period during which a predetermined standard gas is supplied to the surface stress sensor, and further using the signal corresponding to the standard gas in determining whether or not a patient is suffering from ketosis.

22. A standard gas and a purge gas are alternately applied to the surface stress sensor, and digital data corresponding to the standard gas is based on the signal corresponding to the standard gas and the signal corresponding to the purge gas. the gas generated from the body fluid and the purge gas are alternately applied to the surface stress sensor, and digital data corresponding to the body fluid to be measured is obtained based on the signal corresponding to the gas generated from the body fluid and the signal corresponding to the purge gas. Prepare The determination of the onset of ketosis is performed based on the digital data corresponding to the standard gas and the digital data corresponding to the body fluid to be measured. The method for determining whether or not a person is suffering from ketosis according to claim 19.

23. The method for determining whether or not a patient is suffering from ketosis as described in claim 22, wherein the surface stress sensor to which the standard gas and the purge gas are alternately applied and the surface stress sensor to which the gas generated from the body fluid and the purge gas are alternately applied are surface stress sensors that are the same individual, or are surface stress sensors that are different individuals.

24. The method for determining whether or not a patient is suffering from ketosis according to any one of claims 21 to 23, wherein the standard gas is a gas generated from a reference body fluid.

25. A method for determining whether or not a patient is suffering from ketosis according to any one of claims 21 to 24, further comprising supplying gas generated from the body fluid to an additional gas sensor, and determining whether or not a patient is suffering from ketosis based on a signal from the surface stress sensor and a signal from the additional gas sensor.

26. An apparatus for use in the method for determining whether or not a person has ketosis according to any one of claims 13 to 19, At least one surface stress sensor; a first gas flow path for supplying a sample gas generated from a test subject body fluid collected from an animal; a second gas flow path for supplying a purge gas that does not contain the gas component to be measured; Established a sample gas supplied from the first gas flow path and a purge gas supplied from the second gas flow path are alternately switched to be supplied to the at least one surface stress sensor to generate a signal from the at least one surface stress sensor, and the signal is processed by an information processing device to determine whether the animal is suffering from ketosis based on a concentration of ketones or a specific component in the sample gas generated from the body fluid, The specific component is a substance having a peak in the m / z range of 50 to 80 in a mass spectrum.

27. The ketosis onset determination device according to claim 26, providing an additional gas sensor and an additional gas flow path for supplying the sample gas to the additional gas sensor; A ketosis onset determining device that performs the ketosis onset determining method described in claim 20 by processing the signal from the at least one surface stress sensor and the signal from the additional gas sensor with the information processing device.

28. An apparatus for use in the method for determining whether or not a person has ketosis according to any one of claims 21 to 24, At least one surface stress sensor; a first gas flow path for supplying a sample gas generated from a test subject body fluid collected from an animal; a second gas flow path for supplying a purge gas that does not contain the gas component to be measured; a third gas flow path for supplying a predetermined standard gas; Established a sample gas supplied from the first gas flow path, a purge gas supplied from the second gas flow path, and a standard gas supplied from the third gas flow path are supplied to the at least one surface stress sensor in a predetermined order by switching between them, and a signal is generated from the at least one surface stress sensor, and the signal is processed by an information processing device, thereby determining whether the animal is suffering from ketosis based on a concentration of ketones or a specific component in the sample gas generated from the body fluid, The specific component is a substance having a peak in the m / z range of 50 to 80 in a mass spectrum.

29. The ketosis onset determination device according to claim 28, providing an additional gas sensor and an additional gas flow path for supplying the sample gas to the additional gas sensor; A ketosis onset determining device that performs the ketosis onset determining method described in claim 25 by processing the signal from the at least one surface stress sensor and the signal from the additional gas sensor with the information processing device.

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