CN109425670B - Method for detecting fatigue degree of team based on human urine - Google Patents

Abstract

The invention relates to a method for detecting the fatigue degree of a team based on human urine, which comprises the following steps: step 1, collecting urine samples of team members; step 2, preprocessing the sample collected in the step 1; step 3, detecting the sample pretreated in the step 2 by adopting a liquid chromatography-mass spectrometry method; step 4, processing and threshold setting are carried out on the data obtained by detection in the step 3, and potential biomarkers are screened out; and 5, comparing the potential biomarkers screened in the step 4 with fatigue degree markers, and judging the fatigue degree of the detected team members. The method realizes the determination of the fatigue degree detection marker by a small molecule metabonomics method, can judge the fatigue degree, and has good universality, high accuracy and high reliability.

Description

Method for detecting fatigue degree of team based on human urine

Technical Field

The invention belongs to the technical field of biological detection, and particularly relates to a method for detecting fatigue degree of teams and groups based on human urine.

Background

The history of human fatigue research can be traced back to world war world one hundred years ago at the earliest, firstly, the fatigue problem is researched by adopting an ergonomic method, and the fatigue is represented by indexes such as labor productivity, work performance and the like.

In the last 70 s of the century, people began to notice that driver fatigue easily caused traffic safety accidents and accident signs, thereby linking fatigue with safety accidents and accident signs. The aim of fatigue research is developed to prevent accidents and accident signs caused by fatigue and guarantee safety. With the high popularity of industrial automation, the labor intensity is reduced, and brain fatigue (mental fatigue) becomes the main form of fatigue in industrial production. Physical fatigue (also called muscle fatigue) corresponding to this is that muscular soreness occurs locally and the muscle becomes weak. This physical fatigue occurs in today's society primarily after strenuous exercise, also known as athletic fatigue. In the following discussion, when we refer to fatigue without specific indication, we refer to brain fatigue.

In industrial production, fatigue is linked to safety production, so that different safety production stations have different tolerance to fatigue. For example, in a post driving a transport vehicle on a highway, because the vehicle speed is high, the driver is required to be highly focused and have good reaction force to ensure the transport safety, and the light fatigue of the driver cannot be tolerated. Also, as the International Civil Aviation Organization (International Civil Aviation Organization) describes fatigue as: a physiological state of decreased mental and physiological functions due to loss of sleep, prolonged wake time, circadian rhythm changes, workload (mental or/and physical), decreased alertness of the human body and decreased ability to perform safety-related duties caused by these single or multiple factors. Therefore, the judgment of fatigue in industrial safety production is related to the ability of personnel to perform the duties of safety posts, and the tolerance of safety-sensitive posts to the fatigue degree, namely the influence of the human fatigue degree on the production safety, has been one of the research focuses on industrial safety production.

Along with the increasing attention of people to social safety, the research on the fatigue problem is also expanded from the work efficiency research to the subjects of psychology, neuroscience, sleeping, physiology and biochemistry and the like. The disciplines establish corresponding methods for detecting fatigue, such as Stanford sleepiness scale based on subjective perception, visual analog scale, and the like of psychology, and Wisconsin card classification test (WSCT), London Tower Test (TOL), and the like based on cognitive ability to detect fatigue. Subjective scales are easy to be interfered by emotions and other factors, parameter indexes are difficult to set in cognitive tests, and the ceiling or floor effect is often generated, so that the reliability and the effectiveness of the scales or software are not satisfactory; also, for example, a fatigue detection method based on electroencephalogram change is established in the science of neurology and sleep, and fatigue occurs when delta and theta waves are remarkably increased, and the method is difficult to apply to field detection due to the complexity of electroencephalograph instruments; and trying to establish a corresponding detection method based on physiological reactions such as yawning and eye movement changes such as winking, eyelid closure and the like when the human body is tired. The U.S. highway administration automobile transportation office published a technical report in 1998 of 10 months indicating that eyelid closure (PERCLOS) fatigue detection has a more accurate and stable detection result compared to electroencephalogram detection, head position detection, and blink detection. But eyelid closure detection is interfered by glasses, ambient light angle and brightness, eye angle and the like, and is difficult to popularize and apply. So far, people have little understanding on the biochemical mechanism of fatigue, and the explanation of the biochemical mechanism of fatigue can help to develop a method for objectively, stably and quickly detecting the fatigue degree based on biochemical indexes.

The method for detecting the fatigue degree by adopting biochemical indexes is a method which is tried all the time by people, such as detection of some hormones, peptides and the like, and researches find that the concentrations of cytosine nucleoside (Cytidine) and adrenocortical ester alcohol (Corticoid) are related to the working pressure; substances related to sleep and biological rhythm, such as Glycopeptides (Glycopeptides), are also detected; but Borbolby et al indicated evidence of the lack of consistency of the data with respect to the correlation of these compounds with fatigue. In summary, although many studies on the correlation between the metabolism of various compounds and the degree of fatigue have been attempted from various angles such as working stress, sleep, biorhythm, etc., no correlation between any of the metabolic compounds in the human body and the degree of fatigue has been found.

Metabonomics is a new subject for systematically researching in-vivo metabolic characteristics, and is mainly used for systematically exploring, searching and discovering characteristic indexes, namely biomarkers, of body fluid metabolism of a human body when the human body is influenced by diseases, medicines and the like by detecting and analyzing means such as nuclear magnetic resonance, gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry and the like in combination with chemometrics, so that the metabonomics is widely applied to the fields of disease diagnosis, medicine research and development and the like. For example, Mapstone and the like of the university of george town in the United states screen 10 characteristic biomarkers by using a metabonomics method of liquid chromatography mass spectrometry (liquid mass analysis) for detecting the Alzheimer disease, can diagnose the disease 2 to 3 years before the disease has clinical symptoms, and the accuracy can reach more than 90 percent; for another example, Naviaux and the like adopt a liquid mass analysis method to research the metabolic characteristics of long-term fatigue syndrome, find that male patients have 8 metabolites, female patients have 13 metabolites which are significantly changed, and the analysis result of characteristic working curves (ROC) of the testees shows that the diagnosis accuracy reaches 94 percent (male) and 96 percent (female); the professor schwann and the like carry out metabonomics research on blood and urine of depression and over-fatigue model rats by adopting liquid quality analysis, and the result shows that the metabolism of the two groups of rats is abnormally changed compared with the metabolism of the control group of rats. Metabonomics research is carried out on serum of a patient with chronic fatigue syndrome by an Armstrong sampling two-dimensional nuclear magnetic resonance spectrometer, and the result shows that the content of glutamine and ornithine in the serum of a case group is obviously lower than that of a control group.

In the above literature reports, case groups and control groups are used for group comparison for various diseases, but the existing literature methods are not suitable for screening biomarkers related to fatigue degree because fatigue is a recoverable physiological change. Chen et al in the literature utilized liquid chromatography-mass spectrometry to screen 3 fatigue-related biomarkers from urine samples of civil aviation air traffic controllers, but did not propose the concept of fatigue degree, and did not disclose how to quantify the detection of fatigue degree and accurately determine whether fatigue occurred and how to determine the fatigue degree.

During the course of a fatigue study over a hundred years, people recognize that fatigue exists in different strengths, namely fatigue degrees, and try to divide, characterize and detect the fatigue degrees. For example, the psychological stanford sleepiness scale, in which a person is divided into 7 fatigue levels from a fully awake state to almost dream, as if he were asleep the next second, and the subject is asked to make a selective division by subjective feeling. So far, reports of detecting fatigue degree by adopting objective indexes are not seen. The fatigue degree is related to the post safety execution capacity in industrial production, for example, a highway driver has slight fatigue after continuously driving for 2-3 hours, and needs to have a rest and recover for 30-60 minutes to continue to work with the work which needs high attention and high safety risk; while the general office staff can work continuously for 4-6 hours, and even if slight fatigue occurs, the safety risk is not generated. Therefore, the fatigue degree detection can provide powerful new technology and new means for production safety risk management and control.

Disclosure of Invention

Aiming at the defects in the prior art, the invention establishes a method for detecting the fatigue degree of a team based on human urine by using a liquid chromatography-mass spectrometry method by using a small molecule metabonomics method. And further carrying out workload evaluation and scheduling system evaluation in production according to the evaluation result of the fatigue degree, detecting and evaluating whether the job can be carried out before the job goes on duty, detecting and evaluating whether the job can be carried out on duty in the job, detecting and using to find the fatigue risk and adjusting in time in the job, detecting and evaluating the job workload of the job after the job, and the like. And a new technology and a new method are provided for detecting and monitoring the fatigue degree in industrial production, controlling the fatigue risk and guaranteeing the safety production.

The inventor provides a new idea of detecting and dividing the fatigue degree through the expression of the fatigue related biomarkers on the basis of a large number of experiments, and establishes a method for quantitatively detecting the fatigue degree and accurately judging whether the fatigue occurs and the fatigue degree.

The invention is realized by the following technical scheme:

a method for detecting the fatigue degree of a team based on human urine is characterized by comprising the following steps:

step 1, collecting urine samples of team members;

step 2, preprocessing the sample collected in the step 1;

step 3, detecting the sample pretreated in the step 2 by adopting a liquid chromatography-mass spectrometry method;

step 4, processing and threshold setting are carried out on the data obtained by detection in the step 3, and potential biomarkers are screened out;

and 5, comparing the potential biomarkers screened in the step 4 with fatigue degree markers, and judging the fatigue degree of the detected team members.

According to the present invention, in step 1,

the urine sample is derived from a healthy member of a team, preferably a woman not in the menstrual period when the member is a woman.

According to the invention, the step of acquiring comprises acquiring a non-fatigue sample and a fatigue level sample.

According to the invention, the step of collecting the sample comprises: collecting urine samples of members of a team before working or before fatigue is induced by simulation operation as non-fatigue samples; according to the fatigue degree, urine samples of the members of the team are collected after working or simulating operation induced fatigue to be used as fatigue degree samples.

According to the invention, the continuous working time, the working post, the working load and the scheduling situation of each member in the team are the same or similar.

The team can be, for example, a team consisting of drivers, controllers, mechanical maintenance personnel or medical personnel, and the like;

according to the invention, the team may be a sample size team of more than 5 people, for example a sample size team of 8-20 people, such as a sample size team of 8-10 people.

According to the invention, the sample collection step of step 1 further comprises the step of preserving the sample at a low temperature of not higher than-20 ℃ after the urine sample is collected.

For example, urine samples are dispensed into sterile centrifuge tubes and stored at-80 ℃.

In the process of low-temperature preservation, a proper amount of antibiotics can be added into the sample, so that the decomposition of partial metabolites caused by bacteria is avoided; for example, sodium azide is added to the sample at a mass concentration of 0.05 to 0.1%.

According to the present invention, in the step 2,

the pretreatment step comprises the following steps: the urine sample is centrifuged, the supernatant taken and optionally diluted to an aqueous solution of suitable assay concentration for the subsequent steps, for example by diluting the sample with 1-3 volumes of water.

For example, the urine sample is pretreated by the following steps:

before assay, the urine sample was removed, allowed to stand at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant diluted with 100. mu.L of water.

According to the method of the present invention, in step 3,

the liquid chromatography-mass spectrometry is preferably liquid chromatography-time-of-flight mass spectrometry.

The detection samples are fatigue degree samples and non-fatigue samples of a team;

the liquid chromatography can adopt polar chromatography column preferably HILIC column, and weak polar chromatography column preferably C ₁₈ The column and the nonpolar chromatographic column are preferably PFPP columns which respectively carry out separation detection on polar, weakly polar and nonpolar components in urine.

When the liquid chromatography uses a polar chromatographic column to separate and detect polar components, the mass spectrometry preferably adopts a positive ion detection mode; when the liquid chromatography uses weak-polarity and non-polarity columns to separately detect weak-polarity and non-polarity components, mass spectrometry adopts two modes of positive ions and negative ions.

Preferably, the liquid phase conditions using a polar HILIC chromatography column are: UPLC BEH Amide HILIC column [ (2.1-4.6) mm × (100-250) mm,1.5-5 μm ];

the mobile phase is composed of phase A of 95-100% acetonitrile or methanol and 0-5% aqueous solution containing 0.1-0.5% formic acid or acetic acid or trifluoroacetic acid, and phase B of 0.1-0.5% formic acid or acetic acid or trifluoroacetic acid;

the column temperature is 20-40 deg.C, the sample amount is 0.5-5.0 μ L, and the flow rate of mobile phase is 0.3-1.0 mL/min.

Preferably, with weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ Column [ (2.1-4.6) mm X (100-]；

The mobile phase A consists of an aqueous solution containing 0.1-5% of formic acid or acetic acid or trifluoroacetic acid, and the phase B consists of acetonitrile or methanol;

the column temperature is 20-40 deg.C, the sample injection amount is 0.5-5.0 μ L, and the flow rate of mobile phase is 0.3-1.0 mL/min.

Preferably, the liquid chromatography uses a nonpolar PFPP chromatographic column under the following liquid phase conditions: UPLC HSS PFPP column [ (2.1-4.6) mmX (100-250) mm,1.5-5 μm) ];

the mobile phase is a water solution containing 0.1-5% formic acid, acetic acid or trifluoroacetic acid in phase A, and methanol or acetonitrile in phase B;

the column temperature is 20-40 deg.C, the sample injection amount is 0.3-5.0 μ L, and the flow rate of mobile phase is 0.3-1.0 mL/min.

The detection conditions of the mass spectrometry are as follows:

when using positive ion ionization mode detection, the mass range is set to 50-1200m/z full scan mode. The capillary voltage of the electrospray ionizer is 2500-3500, preferably 3000V, and the cone voltage is 20-40V, preferably 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. Desolvation temperature ofThe ion source temperature was 100 ℃ at 400 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

When two ionization modes of positive ions and negative ions are used for detection, the mass range is set to be 50-1200m/z full-scanning mode; the capillary voltage of the electrospray ionizer is 2000-3500, preferably 3000V (positive ions) or 2200V (negative ions), the cone voltage is 20-40V, preferably 30V; the drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is adopted as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

When separating the sample of the test body fluid, it is preferable to insert 1 blank per 5 samples to prevent cross contamination, and it is also possible to insert one quality control sample to perform quality control.

The temperature of the sample chamber is preferably kept between 0 and 4 ℃ during the separation and detection process.

According to the method of the present invention, in step 4,

carrying out statistical analysis on the data separated and detected in the step 3 by adopting data processing software, preferably metabonomics data processing related software;

the analysis processing method comprises the steps of data alignment, peak extraction, partial least square method OPLS-DA analysis, and screening of potential biomarkers by taking P less than or equal to 0.05, CV less than or equal to 30%, VIP greater than 1.0 and maximum change multiple more than or equal to 1.2 as screening thresholds. The data are analyzed, for example using the data processing professional software prognesis QI, to obtain potential biomarkers.

Wherein the maximum fold change is selected to take into account that fatigue is a recoverable physiological change, the value is set differently from a disease study setting of 2.0 or even up to 3.0 or 4.0, and a smaller value of 1.2.

Preferably, the molecular formula of the potential biomarker is deduced by detecting the accurate molecular weight of the potential biomarker by using liquid chromatography-mass spectrometry, and the potential biomarker is screened by comparing the chromatographic characteristics and mass spectrometry characteristics shown by chromatographic retention time with a human urine component database in one or more databases of HMDB (www.hmdb.ca), METLIN (METLIN.

Preferably, a MetabioAnalyst online database (www.MetaboAnalyst.ca) is used for inquiring the metabolic pathway of the marker, and the comparison is carried out with a standard substance; the metabolic pathway is related to human sleep, and the detection result of the metabolic pathway is consistent with the measurement result of the retention time and the mass number of the standard substance in the liquid chromatogram-mass spectrum combined instrument, so that the metabolic pathway can be used as a biomarker related to fatigue degree.

Preferably, unknown potential biomarkers that are reproducible and trending consistently across multiple fatigue level panels, but not retrieved in the HMDB (www.hmdb.ca) and METLIN (METLIN script s.edu) databases, can be purified to produce a pure product, and the pure product is subjected to mass spectrometry, ultraviolet, infrared, and/or nuclear magnetic data, and structurally identified as fatigue level-related biomarkers.

According to the method of the present invention, in step 5,

the fatigue degree marker is selected from one or more than two of the following:

(1) urocanic acid (Urocanic acid);

(2) acetylcytosine (N4-Acetylcytidine);

(3) 5-hydroxytryptophan (5-Hydroxy-L-trphan);

(4) dimethylguanosine (N2, N2-Dimehtylguanosine);

(5) acetanilide (N-Acetylarylamine); and

(6)Alpha-CEHC。

according to the invention, when the screened potential fatigue degree marker is urocanic acid, the mild fatigue of the human body can be judged; preferably, when the selected potential fatigue degree marker is up-regulated by 1.4 times, the human body can be judged to have slight fatigue.

According to the invention, when the screened potential fatigue degree markers are urocanic acid, acetylcytosine and 5-hydroxytryptophan, the moderate fatigue of the human body can be judged; preferably, when the contents of the screened potential fatigue degree markers of urocanic acid, acetylcytosine and 5-hydroxytryptophan are reduced, the human body can be judged to have moderate fatigue; preferably, when the selected potential fatigue degree markers are urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide and Alpha-CEHC, the human body can be judged to have moderate fatigue; more preferably, when the screened potential fatigue degree markers urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine and acetanilide are decreased in content and Alpha-CEHC content is increased, it can be judged that the human body has moderate fatigue.

According to one embodiment of the detection method, when the detection result of the urine sample collected by the members of the team in 2-4 hours shows that the content of urocanic acid is increased by 1.4 times, namely the fatigue degree sample is increased by 1.4 times relative to the content of urocanic acid in the non-fatigue sample, the members of the team can be judged to have slight fatigue;

according to one embodiment of the detection method, when the detection result of the urine sample collected by the team member for 4-6 hours shows that the reduction multiples of the contents of urocanic acid, acetylcytosine and 5-hydroxytryptophan in the fatigue degree sample are respectively more than 1.4, more than 1.3 and more than 1.4 in the non-fatigue sample, the team member can be judged to have moderate fatigue;

according to one embodiment of the detection method of the present invention, when the urine sample collected from the team member for 5-8 hours shows that the fatigue degree sample has a decrease multiple of 1.4 or more, 1.3 or more, 1.4 or more, and 1.4 or more, respectively, in the content of urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, and acetanilide, relative to the non-fatigue sample, and the increase multiple of Alpha-CEHC reaches 1.3 or more, the team member can be judged to have moderate fatigue.

The invention also provides a method for workload evaluation, or detection and evaluation before post shift, or detection and evaluation in post shift for finding fatigue risk and adjusting in time, or detection and evaluation post workload after post shift, which is characterized by comprising the following steps:

1) when fatigue degree samples collected in the post of 2-4 hours of work of the members of the team judge that the members of the team are slightly tired by using the detection method, for the safety production sensitive key posts such as drivers and controllers, the members of the team are recommended to leave the post for rest (preferably rest for 20-30 minutes) and then go on the post for operation;

2) when the urocanic acid, the acetylcytosine and the 5-hydroxytryptophan are found in the urine sample by the detection method and the down-regulation times of the urocanic acid, the acetylcytosine and the 5-hydroxytryptophan relative to the non-fatigue sample are respectively below 1.4, below 1.3 and below 1.4, the workload of the members of the team is proper;

3) if the fatigue degree samples collected after working for more than 5 hours detect urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide and Alpha-CEHC in urine samples by the detection method, and the decreasing multiples of urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine and acetanilide relative to the non-fatigue samples are respectively more than 1.4, more than 1.3, more than 1.4 and more than 1.4, and the increasing multiple of Alpha-CEHC content reaches more than 1.3, the workload of the team members reaches the full load and the rest is recommended or the workload is reduced.

The invention also provides a method for evaluating the shift arrangement system, which is characterized in that the result of the method for detecting the fatigue degree is used for judging,

a1) when the fatigue degree samples collected when the team members work for 2-4 hours, judging that the team members have slight fatigue by using the detection method, and for the safety sensitive posts, indicating that the team members need to rest;

when the fatigue degree samples collected when the members of the team work for 2-4 hours judge that the members of the team do not have light fatigue by using the detection method, the working load of the members of the team is appropriate; or the like, or, alternatively,

a2) for the work of a safety sensitive post needing high attention, when the task of the members of a team is executed for less than 5 hours, urocanic acid, acetylcytosine and 5-hydroxytryptophan biomarkers are screened from collected fatigue samples, and when the down-regulation times of the fatigue degree samples relative to non-fatigue samples are respectively more than 1.4, more than 1.3 and more than 1.4, moderate fatigue occurs, which indicates that the scheduling system is unreasonable, and the work is recommended to be stopped, the off-post rest is carried out for a longer time, or the work load is reduced by adding personnel; the workload of the members of the team is overloaded;

if urocanic acid, acetylcytosine and 5-hydroxytryptophan are screened from fatigue samples collected during the off-duty time of the white class, and the down-regulation times of the fatigue degree samples relative to the non-fatigue samples are respectively below 1.4, below 1.3 and below 1.4, the workload of the members of the class is proper; or the like, or, alternatively,

a3) for the work of a safety sensitive post needing high attention, urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethyl guanosine, acetanilide and Alpha-CEHC are screened from collected fatigue degree samples after the work of the members of the team works for 5-7 hours, the down-regulation times of the fatigue degree samples relative to non-fatigue samples are respectively more than 1.4, more than 1.3, more than 1.4 and more than 1.4, and when the rising time of the Alpha-CEHC content reaches more than 1.3, the members of the team are proved to have moderate fatigue and overload, the workload of the members of the team is suggested to stop working, rest for a longer time off duty, or work off duty or increase of the personnel to reduce the workload, so the workload of the members of the team is suggested to be overloaded; when the work is carried out for 8 hours, the working time or the working load needs to be reduced, and the safety production risk is reduced; or the like, or, alternatively,

a4) and when the work is finished for 8 hours, screening urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide and Alpha-CEHC from the collected fatigue degree samples, wherein the down-regulation multiples of the fatigue degree samples relative to the non-fatigue samples are respectively more than 1.4, more than 1.3, more than 1.4 and more than 1.4, and when the content increase multiple of the Alpha-CEHC reaches more than 1.3, the members of the shift group are proved to have moderate fatigue, and the shift system staff is fully loaded.

The technical scheme of the invention has the following beneficial effects:

1) the method for judging the fatigue degree is more scientific and reasonable. For biochemical processes of fatigue human bodies, although research on the correlation between metabolism of various compounds and fatigue is tried from a plurality of angles such as working pressure, sleep, biorhythm and the like, no correlation between any metabolic compound of human bodies and fatigue is found. In the invention, considering that the biochemical process of a tired human body is completely unknown, when the potential biomarkers are screened and detected, chromatographic columns with different polarities are used for comprehensively detecting and analyzing the sample, and the missing detection is prevented, so that the accuracy of the method is improved.

2) Because the invention uses a plurality of chromatographic columns with different polarities to detect the same sample for a plurality of times, on one hand, the detection omission can be avoided, and on the other hand, the detection method of the chromatographic columns can be verified according to the result that different chromatographic columns simultaneously detect the same component. And errors of a certain chromatographic column are avoided, so that the accuracy of the screening method is improved.

3) In the prior art, micromolecular metabonomics are mainly applied to diagnosis and treatment of human diseases, drug research and development and the like, and are not applied to the research of normal physiological changes of human bodies. Fatigue is a physiological change of a human body in response to a workload, a pressure load, and/or a biorhythm change, and the degree of fatigue varies with the intensity of the load and the degree of the rhythm change. The present invention takes into account that physiological changes in the human body are a change that can be regulated by itself and can be restored by rest, such as sleep, and therefore physiological changes leading to metabolite levels will necessarily be different from changes in the levels of metabolites that are caused by disease or human pathologies caused by drug toxicology, i.e. physiological changes leading to metabolite levels that are less altered than pathological changes. The present invention sets the lower threshold fold change for metabolites at a 1.2 fold lower value, which is 2.0 fold or greater than the values typically set for disease and toxicology studies. Therefore, the screening method of the invention can avoid detection errors caused by diseases or other factors, so that the method has higher accuracy.

4) The screening method of the method adopts a mode of pre-and-post fatigue contrast, which can deduct the interference introduced by factors such as food diet, environment and the like and simultaneously avoid ambiguity and error introduced by inconsistent fatigue definition.

5) The method can detect, analyze and judge the fatigue degree of members of a team on a small amount of samples such as 5-10 people's samples based on the fatigue degree markers and the content change thereof obtained on the basis of a large amount of experiments, and provides technical support for safety production.

6) The fatigue degree of the members of the team is judged based on results of a large number of experimental bases for the first time, and the judgment of the fatigue degree is realized through quantitative detection. The inventor finds that the fatigue degree is related to the post safety execution capacity in industrial production, so that the fatigue degree detection can provide powerful new technology and new means for production safety risk management and control. The detection result of the fatigue degree is utilized to carry out workload assessment and scheduling system assessment in production, whether the post can be carried out before the post is finished is detected and assessed, the detection in the post is used for finding the fatigue risk and adjusting in time, and the method for detecting and assessing the post workload after the post is finished is more scientific and reasonable.

Drawings

Fig. 1 is a typical total ion flow diagram of polar components detected in positive ion mode by a polar HILIC column simulating plasma samples of driving volunteers.

FIG. 2 is a graph of principal component analysis scores of positive ion detection polar component data of plasma samples HILIC column of simulated driving volunteers.

FIG. 3 is a sample of plasma of a simulated driving volunteer with a low polarity C ₁₈ The column positive ion mode detects a typical total ion flow pattern of polar lipid components.

FIG. 4 is a sample of plasma of a simulated driving volunteer with low polarity C ₁₈ Column positive ion mode detection polar lipid component data principal component analysis score plot.

FIG. 5 is a weak polarity C of plasma samples from simulated driving volunteers ₁₈ The column negative ion mode detects a typical total ion flow diagram of polar lipid components.

FIG. 6 is a sample of plasma of a simulated driving volunteer with low polarity C ₁₈ And detecting a main component analysis score chart of the polar lipid component data in a column negative ion mode.

FIG. 7 is a weak polarity C of plasma samples from simulated driving volunteers ₁₈ The column positive ion mode detects a typical total ion flow diagram of a non-polar lipid component.

FIG. 8 is a sample of plasma of a simulated driving volunteer with a low polarity C ₁₈ And detecting a main component analysis score chart of the nonpolar lipid component data in a column positive ion mode.

Fig. 9 is a typical total ion flow diagram of polar components detected by polar HILIC column positive ion mode of urine sample of simulated driving volunteers in test example.

FIG. 10 is a principal component analysis score chart of positive ion detection polarity component data of urine sample HILIC column of a test example simulated driving volunteer.

FIG. 11 is a weak polarity C of urine sample from a test example simulated driving volunteer ₁₈ And detecting a typical total ion flow diagram of the weak-polarity component in a positive ion mode of the column.

FIG. 12 is a urine sample low polarity C of a volunteer simulated driving test example ₁₈ And detecting a main component analysis score chart of the weak polarity component data in a column positive ion mode.

FIG. 13 is a weak polarity C of urine samples from volunteers in simulated driving of test cases ₁₈ The column negative ion mode detects typical total ion flow diagram of weak polar components.

FIG. 14 is a urine sample weak polarity C of a test example simulated driving volunteer ₁₈ And detecting a main component analysis score chart of the weak polarity component data in a column negative ion mode.

Figure 15 is a typical total ion flowsheet of non-polar components detected by a non-polar PFPP column positive ion mode of a test example simulated urine sample from a driving volunteer.

FIG. 16 is a graph of the principal component analysis score of nonpolar component data detected by a nonpolar PFPP column positive ion mode of a urine sample of a simulated driving volunteer in a test example.

Fig. 17 is a typical total ion flow graph of nonpolar components detected by nonpolar PFPP column anion mode of test example simulation driving volunteer urine samples.

FIG. 18 is a graph of the principal component analysis score of nonpolar component data detected by a nonpolar PFPP column anion mode of a urine sample of a simulated driving volunteer in a test example.

FIG. 19 shows structural characterization of urocanic acid in test examples.

Detailed Description

The method of the present invention will be described in further detail with reference to specific examples. It is to be understood that the following examples are only illustrative and explanatory of the present invention and should not be construed as limiting the scope of the present invention. All the technologies realized based on the above-mentioned contents of the present invention are covered in the protection scope of the present invention.

Unless otherwise indicated, the raw materials and reagents used in the following examples are all commercially available products or can be prepared by known methods.

Test example 1 method for screening biomarkers of fatigue degree in body fluid by simulating 3.5 hours of operation of civil aircraft driver

1.1 volunteer recruitment and sample collection:

99 volunteers were recruited, and the cohort conditions were: the health is good, no medicine is taken, and the age is 20-55 years, wherein 55 men and 44 women need to be in the menstrual period, and female volunteers need not to be in the menstrual period.

The volunteers were scheduled to perform simulated aircraft piloting operations for 3.5 hours of continuous operation, inducing mild fatigue.

Collection of blood and urine samples: blood and urine samples are respectively collected before and after a volunteer carries out simulated driving operation, the blood sample adopts an anticoagulation blood collection tube to collect venous blood of not less than 2.0mL, and the urine sample uses a sterile urine cup to collect urine and is subpackaged in a sterile tube for preservation.

Storing human blood and urine samples, centrifuging the blood at 4000-; the urine sample is subpackaged in a sterile centrifuge tube and stored at-80 ℃.

1.2 pretreatment of human plasma and urine samples:

(1) the pretreatment steps of the plasma sample are as follows: thawing the plasma sample at 4 deg.C for 30-60 min; dividing into 2 parts, putting 100 μ L of plasma into a labeled 1.5mL centrifuge tube, and adding 300 μ L of acetonitrile; fully oscillating for 15 seconds, carrying out protein precipitation, centrifuging at 12000rpm and 4 ℃ for 10 minutes, taking 100 mu L of upper solution, placing the upper solution in a 200 mu L inner lining tube, and detecting polar components in the plasma; the second part takes 100 mu L of plasma to a 1.5mL centrifuge tube marked with a label, and 500 mu L of chloroform/methanol (3:1) solution is added; fully oscillating for 15 seconds, carrying out protein precipitation, centrifuging for 5 minutes at 12000rpm and 4 ℃, taking 200 mu L of lower-layer solution, and placing the lower-layer solution in a 1.5mL centrifuge tube; the samples were concentrated by centrifugation under vacuum for 4 hours and 300. mu.L of isopropanol/acetonitrile (1:1) was added to the dried samples and mixed by shaking for 40 seconds. After centrifugation at 12000rpm for 5 minutes, 100. mu.L of the supernatant was collected and placed in a 200. mu.L inner liner tube for measurement of lipid components in plasma. (2) The urine sample pretreatment steps are as follows: before assay, the urine sample was taken out and left at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant was diluted with 100. mu.L of water.

1.3 analyzing and detecting plasma and urine samples by adopting a liquid chromatography-time-of-flight mass spectrometry method:

(1) the plasma sample is detected by respectively adopting a polar chromatographic column HILIC and a weak polar chromatographic column C ₁₈ The polar component and the lipid component in the blood are separately detected.

The liquid phase conditions using a polar HILIC chromatography column were: UPLC BEH Amide HILIC column (2.1mM × 100mM,1.7 μm), mobile phase A is acetonitrile solution containing 0.1% formic acid and 1.0mM ammonium acetate, and phase B is aqueous solution containing 0.1% formic acid and 1.0mM ammonium acetate; the column temperature is 40 ℃; the flow rate of the mobile phase is 0.3 mL/min; the amount of the sample was 1.0. mu.L. The mass spectrum conditions are as follows: positive ion ionization mode detection, mass range was set to 50-1200m/z full scan mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

Using weak polarity C ₁₈ The liquid phase conditions for detecting the nonpolar components of the plasma lipids by the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1 mM. times.100 mM,1.7 μm), mobile phase A as a 6:4 acetonitrile/water solution containing 0.1% formic acid and 10mM ammonium acetate, and phase B as a 9:1 acetonitrile/isopropanol solution containing 0.1% formic acid and 10mM ammonium acetate; the column temperature is 50 ℃; the flow rate of the mobile phase is 0.3 mL/min; the amount of the sample was 1.0. mu.L. The mass spectrum conditions are as follows: positive ion separationDetecting in a sub-mode, and setting the mass range to be 50-1200m/z full scanning mode. The optimum capillary voltage for the electrospray ionizer was 3000V, and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )

Using weak polarity C ₁₈ The liquid phase conditions for detecting the polar components of the plasma lipid by the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1 mm. times.100 mm,1.7 μm), mobile phase A as an aqueous solution containing 0.1% formic acid, and phase B as a methanol solution containing 0.1% formic acid. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

Each plasma sample was tested with 2 chromatographic columns for polar and lipid polar and non-polar components, respectively, wherein the polar component was tested only in positive ion mode and the lipid component was tested in positive and negative ion mode, i.e. each plasma sample was tested 4 times in order to detect as many as possible all metabolic compounds in the plasma. A blank is inserted into every 10 samples in the detection to prevent cross contamination, and a quality control sample is inserted for quality control. The temperature of the sample chamber was maintained at 4 ℃ during the analytical test.

(2) The urine sample is detected by using polar chromatographic column HILIC and weak polar chromatographic column C ₁₈ And the non-polar chromatographic column PFPP is used for separating and detecting polar, weak-polar and non-polar components in the urine respectively.

The liquid phase conditions using a polar HILIC chromatography column were: UPLC BEH Amide HILIC column (2.1mm × 100mm,1.7 μm), the mobile phase is composed of phase A containing 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B containing 0.1% formic acid; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: positive ion ionization mode detection, mass range was set to 50-1200m/z full scan mode. The optimum capillary voltage of the electrospray ionizer was 3000V, and the cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

Using weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1mm × 100mm,1.7 μm), mobile phase A consisting of 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B consisting of 0.1% formic acid; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage of the electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and the cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is adopted as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

The liquid phase conditions using a non-polar PFPP chromatographic column were: UPLC HSS PFPP column (2.1mm × 100mm,1.7 μm), the mobile phase is aqueous solution containing 0.1% formic acid as phase A composition, and methanol as phase B composition; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas is nitrogen, toThe solvation flow rate was 800L/h and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

Each urine sample is respectively detected by 3 chromatographic columns for polar, weakly polar and nonpolar components, wherein the polar component is only detected in a positive ion mode, and the weakly polar and nonpolar components are detected in a positive ion mode and a negative ion mode, namely each urine sample is detected for 5 times, so that all metabolic compounds in the urine can be detected as far as possible. A blank is inserted into each 10 samples in the detection to prevent cross contamination, and a quality control sample is inserted for quality control. The temperature of the sample chamber was maintained at 4 ℃ during the analytical test.

1.4 data processing and preliminary screening of biomarkers

Analyzing a detection sample by using a liquid chromatography-mass spectrometer to obtain 435GB detection data, performing statistical analysis processing by using metabonomics data processing professional software Progenetics QI, wherein the statistical analysis processing comprises data alignment, peak extraction, grouping by using simulated aircraft driving as a processing mode for inducing mild fatigue, performing pairing grouping on the samples before and after processing, performing partial least square method OPLS-DA grouping analysis, and primarily screening potential biomarkers by using P less than or equal to 0.05, CV less than or equal to 30%, VIP greater than 1.0 and maximum change multiple more than or equal to 1.2 as screening thresholds. Wherein the maximum fold change is selected to take into account that fatigue is a recoverable physiological change, the value is set differently from the value set to 2.0 or even to 3.0 or 4.0 in a disease study, and to a smaller value of 1.2.

Processing the plasma sample detection data according to the steps, detecting 8625 compounds in the polar component in the plasma by using a polar HILIC column positive ion mode and detecting the compounds by using weak polar C ₁₈ Detection of 19646 polar components and 8625 nonpolar lipid components in plasma by using weak polarity C in positive ion mode ₁₈ In the data of 13648 compounds of polar lipid component in the plasma detected by the column negative ion mode, the biomarkers meeting the conditions can not be screenedA compound (I) is provided.

Processing the urine sample detection data according to the above steps while using the weak polarity C ₁₈ In the data of 12282 compounds of weak polar components in urine detected by a column positive ion mode, 1 compound is analyzed and screened as a potential biomarker; 9490 compounds in urine are detected by using a polar HILIC column positive ion mode and weak polar C ₁₈ In the data of 24363 compounds for detecting the weak polar components in the urine in the column negative ion mode, 13054 compounds for detecting the nonpolar components in the urine in the nonpolar PFPP column positive ion mode and 7702 compounds for detecting the nonpolar components in the urine in the nonpolar PFPP column negative ion mode, the biomarkers meeting the conditions can not be screened.

1.5 biomarker metabolic pathway retrieval and Structure confirmation

1 of the potential biomarkers initially selected in step 1.4 are at C ₁₈ The column retention time was: 3.0 min, the precise mass number m/z is 139.0508. The mass deviation was set to 5ppm, and the potential biomarker was presumed to have a possible structure of C by searching the alignment using the HMDB (www.hmdb.ca) database ₆ H ₆ N ₂ O ₂ And the compound name Urocanic acid (Urocanic acid). And further purchasing a pure urocanic acid product to confirm on a liquid chromatography-mass spectrometer, and comparing the pure urocanic acid product with the standard product, wherein the standard product and the compound to be detected have the same retention time and the measured accurate mass number is the same, so that the potential biomarker is determined to be urocanic acid.

The metabolic pathway of urocanic acid is inquired by using a MetabioAnalyst online database (www.MetaboAnalyst.ca), the result shows that the urocanic acid belongs to a histamine metabolic pathway, the correlation between histamine and sleep is further searched, and the result shows that the histamine is highly correlated with the sleep of a human body.

The change of the content of urocanic acid before and after the simulated driving operation is calculated, and the content of urocanic acid is found to be up-regulated by 1.4 times.

It follows from this that: when the human body is in mild fatigue, the content of urocanic acid in the histamine metabolic pathway is up-regulated by 1.4 times, namely, the increase of the content of urocanic acid can reflect that the human body is in a mild fatigue state. As urocanic acid is detected to be up-regulated by 1.4 times when the human body is slightly tired, the occurrence of the slight fatigue is characterized by up-regulating the urocanic acid by more than 1.4.

Test example 2 method for screening fatigue biomarkers in body fluid of civil aviation air traffic controller

2.1 volunteer enrollment and sample collection:

volunteer recruitment: volunteers 45 of civil aviation air traffic controller were recruited at an airport in a country, and the grouping conditions were as follows: healthy, male, no medication, age 20-35 years, divided into 2 groups, a first group (ATC1) of 20 people, and a second group (ATC2) of 25 people. Volunteers 23 of administrative staff in the airport were recruited simultaneously as a control group (CON), entry conditions: healthy body, male, no medicine taking, age 20-35 years old.

The civil aviation air traffic controller is responsible for commanding safe operation of the aircraft on the air traffic route, and colloquially speaking, the civil aviation air traffic controller is used for commanding the aircraft and comprehensively managing all aircrafts in the whole airspace by referring to information such as radar and the like. During work, controllers usually command the operation of a plurality of airplanes at the same time, and the abilities of concentration, accurate judgment, emergency treatment and the like are needed, so that the airplanes are very easy to fatigue, and the related regulations of the civil aviation bureau make it clear that the longest time of each controller for commanding the airplanes in the seats is not more than 2 hours. The fatigue produced during the work is mainly caused by mental labor.

The research mainly aims at screening and researching biomarkers related to fatigue degree of white ban controllers. Volunteers were engaged in air traffic guidance work during white class as a treatment for inducing moderate fatigue.

Collecting a urine sample: collecting a urine sample as a non-fatigue sample before a volunteer of a controller in white duty goes on duty, and collecting a urine sample as a moderate fatigue sample before the volunteer of the controller goes off duty after the volunteer goes off duty; similarly, volunteers also collected 2 urine samples before and after work for administrative staff. Administrative staff are used as a control sample to eliminate the interference of normal physiological metabolism of the human body.

ATC1 group samples were collected in 12 months winter 2014, and ATC2 and CON group samples were collected in 10 months autumn 2016.

The urine sample is collected by using a sterile urine cup and is subpackaged in a sterile tube for storage.

Urine samples were sub-packaged in sterile centrifuge tubes and stored at-80 ℃.

2.2 pretreatment of urine samples:

the urine sample pretreatment steps are as follows: before assay, the urine sample was taken out and left at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant was diluted with 100. mu.L of water.

2.3 analyzing and detecting the urine sample by adopting a liquid chromatography-time-of-flight mass spectrometry method:

the urine sample is detected by using polar chromatographic column HILIC and weak polar chromatographic column C ₁₈ And the non-polar chromatographic column PFPP is used for separating and detecting polar, weak-polar and non-polar components in the urine respectively.

The liquid phase conditions using a polar HILIC column were: UPLC BEH Amide HILIC column (2.1mm × 100mm,1.7 μm), mobile phase A is composed of 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B is composed of aqueous solution containing 0.1% formic acid; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: positive ion ionization mode detection, mass range set to 50-1200m/z full scan mode. The optimum capillary voltage for the electrospray ionizer was 3000V, and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

Using weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1mm × 100mm,1.7 μm), mobile phase A comprising 0.1% formic acid in water, and phase B comprising acetonitrile; the column temperature was 40 ℃, the sample injection amount was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas being nitrogen, the desolvation flowThe speed was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is adopted as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

The liquid phase conditions using a non-polar PFPP chromatographic column were: UPLC HSS PFPP column (2.1mm × 100mm,1.7 μm), the mobile phase is aqueous solution containing 0.1% formic acid as phase A, and methanol as phase B; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

Each urine sample is respectively detected by 3 chromatographic columns for polar, weakly polar and nonpolar components, wherein the polar component is only detected in a positive ion mode, and the weakly polar and nonpolar components are detected in a positive ion mode and a negative ion mode, namely each urine sample is detected for 5 times, so that all metabolic compounds in the urine can be detected as far as possible. A blank is inserted into each 10 samples in the detection to prevent cross contamination, and a quality control sample is inserted for quality control. The temperature of the sample chamber was maintained at 4 ℃ during the analytical test.

2.4 data processing and preliminary screening of biomarkers

The method comprises the steps of analyzing a detection sample by using a liquid chromatography/mass spectrometer to obtain 261GB detection data, performing statistical analysis processing by using metabonomics data processing professional software Progenetics QI, performing data alignment, peak extraction, grouping the sample before and after processing by using a working task execution mode as a processing mode for inducing moderate fatigue, performing partial least squares (OPLS) -DA grouping analysis, and primarily screening potential biomarkers by using P (P is less than or equal to 0.05), CV (CV) is less than or equal to 30%, VIP (VIP) is greater than 1.0, and the maximum change multiple is greater than or equal to 1.2 as a screening threshold. Wherein the maximum fold change is selected to take into account that fatigue is a recoverable physiological change, the value is set differently from the value set to 2.0 or even to 3.0 or 4.0 in a disease study, and to a smaller value of 1.2.

Processing the test data of a first group of controller ATC1 urine samples (see Table 2) according to the steps, and analyzing and screening 5 compounds as potential biomarkers from the data of 9490 compounds of the polar component in the urine by using a polar HILIC column positive ion mode; in the presence of weak polarity C ₁₈ In the data of 10809 compounds as weak-polarity components in the urine detected by the positive ion mode of the column, 12 compounds are analyzed and screened as potential biomarkers; using weak polarity C ₁₈ In the data of 5247 compounds of weak polar components in urine detected by a column negative ion mode, potential biomarkers meeting conditions cannot be analyzed and screened; analyzing and screening 6 compounds as potential biomarkers in the data of 11414 compounds of the nonpolar component in the urine by using the nonpolar PFPP column positive ion mode; in the data of 6176 compounds of nonpolar components in urine detected by a nonpolar PFPP column negative ion mode, 2 compounds are analyzed and screened as potential biomarkers.

Processing the test data of a second group of controller ATC2 urine samples (see Table 3) according to the steps, and analyzing and screening 4 compounds as potential biomarkers from the data of 7903 compounds of polar components in urine by using a polar HILIC column positive ion mode; in the presence of weak polarity C ₁₈ In the data of 10463 compounds of weak polar components in the urine detected by the positive ion mode of the column, 5 compounds are analyzed and screened as potential biomarkers; using weak polarity C ₁₈ In the data of 6014 compounds of weakly polar components in urine detected in a column negative ion mode, 1 compound is analyzed and screened as a potential biomarker; analyzing and screening 4 compounds as potential biomarkers in the data of 9739 compounds for detecting the nonpolar component in the urine by using the nonpolar PFPP column positive ion mode; detection in negative ion mode using a nonpolar PFPP columnIn the data of 5996 compounds of the nonpolar component in urine, potential biomarkers meeting the conditions cannot be screened out through analysis.

Processing the test data of the urine sample of the control group CON group (see Table 4) according to the steps, and analyzing and screening 10 compounds as potential biomarkers from the data of 8315 compounds of the polar components in the urine by using the polar HILIC column positive ion mode; in the presence of weak polarity C ₁₈ In the data of 10645 compounds of weak polar components in the urine detected by the positive ion mode of the column, 17 compounds are analyzed and screened as potential biomarkers; using weak polarity C ₁₈ In data of 6966 compounds of weak polar components in urine detected by a column negative ion mode, 7 compounds are analyzed and screened as potential biomarkers; analyzing and screening 10 compounds as potential biomarkers in the data of 10318 compounds of nonpolar components in urine by using a nonpolar PFPP column positive ion mode; in the data of 6571 compounds of the nonpolar component in the urine detected by the nonpolar PFPP column negative ion mode, the potential biomarkers meeting the conditions can not be analyzed and screened.

TABLE 2 biomarker related to degree of potential fatigue screened from urine samples from a first group of controllers

TABLE 3 biomarker related to degree of potential fatigue screened in urine samples from a second group of controllers

TABLE 4 relevant biomarkers screened in control urine samples

2.5 biomarker metabolic pathway retrieval and Structure confirmation

Comparing the biomarkers related to the fatigue potential levels screened from the three urine samples, the results showed (see Table 5) that there were 3 biomarkers related to the fatigue potential levels, urocanic acid, 5-hydroxytryptophan, and acetylcytosine, and that there were 3 biomarkers related to the fatigue potential levels, dimethylguanosine, acetanilide, and Alpha-CEHC, which were only present in the control group.

The above 6 compounds were searched in the MetabioAnalyst database (Table 4), and the results showed that the compounds dimethylguanosine belongs to the tyrosine metabolic pathway, acetanilide belongs to the aromatic amine metabolic pathway, 5-hydroxytryptophan belongs to the tryptophan metabolic pathway, urocanic acid belongs to the histidine metabolic pathway, and alpha-CEHC and acetylcytosine did not find corresponding metabolic pathways. Further literature query results show that the above-retrieved 4 metabolic pathways are all related to human sleep.

The above results show that over the course of one day the air traffic controller (fatigue group) increased the opening of 3 sleep-related metabolic pathways compared to the administrative back office (control group).

TABLE 5 biomarkers related to fatigue level screened in urine

Test example 3 method for screening biomarkers of fatigue degree in body fluid by simulating 1 hour of operation of civil aircraft driver

3.1 volunteer recruitment and sample collection:

volunteers were recruited 20, ad cohort conditions: healthy, no drug, age 20-40 years, with 10 men, 10 women, female volunteers needing to be non-menstrual.

The volunteers were scheduled to perform simulated aircraft piloting operations for 1 hour of continuous operation without experiencing fatigue.

Collecting a urine sample: urine samples are collected before and after the volunteer carries out the simulated driving operation, and the urine samples are collected by using a sterile urine cup and are subpackaged in a sterile tube for storage.

Human urine samples are preserved, and the urine samples are subpackaged in sterile centrifuge tubes and preserved at-80 ℃.

2.2 pretreatment of human urine samples:

the urine sample pretreatment step comprises: before assay, the urine sample was taken out and left at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant was diluted with 100. mu.L of water.

2.3, analyzing and detecting the urine sample by adopting a liquid chromatography-time-of-flight mass spectrometry method:

respectively adopting polar chromatographic column HILIC and weak polar chromatographic column C ₁₈ And the non-polar chromatographic column PFPP is used for separating and detecting polar, weak-polar and non-polar components in the urine respectively.

The liquid phase conditions using a polar HILIC chromatography column were: UPLC BEH Amide HILIC column (2.1mm × 100mm,1.7 μm), mobile phase A is 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B is 0.1% formic acid; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: positive ion ionization mode detection, mass range was set to 50-1200m/z full scan mode. The optimum capillary voltage for the electrospray ionizer was 3000V, and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

Using weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1mm × 100mm,1.7 μm), mobile phase A is aqueous solution containing 0.1% formic acid, and phase B is acetonitrile; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage of the electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and the cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

The liquid phase conditions using a non-polar PFPP chromatographic column were: UPLC HSS PFPP column (2.1mm × 100mm,1.7 μm), the mobile phase is aqueous solution containing 0.1% formic acid as phase A, and methanol as phase B; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

Each urine sample is respectively detected by 3 chromatographic columns for polar, weakly polar and nonpolar components, wherein the polar component only detects a positive ion mode, and the weakly polar and nonpolar components detect a positive ion mode and a negative ion mode, namely, each urine sample is detected for 5 times so as to detect all metabolic compounds in the urine as far as possible. A blank is inserted into each 10 samples in the detection to prevent cross contamination, and a quality control sample is inserted for quality control. The temperature of the sample chamber was maintained at 4 ℃ during the analytical test.

1.4 data processing and preliminary screening of biomarkers

Analyzing a detection sample by using a liquid chromatography-mass spectrometer to obtain 35GB detection data, performing statistical analysis processing by using metabonomics data processing professional software Progenetics QI, wherein the statistical analysis processing comprises data alignment, peak extraction, grouping by using simulated aircraft driving as a processing mode for inducing mild fatigue, performing pairing grouping on the sample before and after processing, performing partial least square method OPLS-DA grouping analysis, and primarily screening potential biomarkers by using P less than or equal to 0.05, CV less than or equal to 30%, VIP greater than 1.0 and maximum change multiple more than or equal to 1.2 as screening thresholds. Wherein the maximum fold change is selected to take into account that fatigue is a recoverable physiological change, the value is set differently from the value set to 2.0 or even to 3.0 or 4.0 in a disease study, and to a smaller value of 1.2.

Processing urine sample detection data according to the above steps, detecting 4847 compounds in polar component in plasma by using polar HILIC column positive ion mode, and detecting with weak polar C ₁₈ 6916 compounds of weak polarity component in urine are detected by column positive ion mode, and weak polarity C is utilized ₁₈ In the data of 4012 compounds of polar lipid components in plasma detected by a column negative ion mode, 9221 compounds of nonpolar components in urine are detected by a nonpolar PFPP column positive ion mode, and 5074 compounds of nonpolar components in urine are detected by a nonpolar PFPP column negative ion mode, so that biomarkers meeting conditions cannot be screened.

According to the results of the 3 test examples, when the tested person does not feel fatigue, the biomarker meeting the conditions is not screened out; when the tested person works (drives in a simulation mode) for 3.5 hours, urocanic acid is expressed as a biomarker, and the content of urocanic acid is up-regulated by 1.4 times relative to a non-fatigue sample; more biomarkers are detected along with the extension of the working time, for example, after 8 hours of work of an administrative worker with light workload, three biomarkers of urocanic acid, 5-hydroxytryptophan and acetylcytosine are expressed and respectively reduced by 1.4, 1.4 and 1.3 times; after 8 hours of work, the controller with high workload and high safety duty risk expresses six biomarkers, wherein the urocanic acid, 5-hydroxytryptophan, acetylcytosine, dimethylguanosine, acetanilide and Alpha-CEHC have the first 5 down-regulation times of 1.4, 1.3, 1.4 and 1.4 respectively, and the Alpha-CEHC content is increased by 1.3.

The detection results and changes of the 6 biomarkers are shown in the following table 6:

TABLE 6 biomarkers associated with fatigue

Example 1 fatigue detection for a simulated civil aircraft driver team

1.1 volunteer recruitment and sample collection:

volunteers 99 were recruited, cohort conditions: the health is good, no medicine is taken, and the age is 20-55 years, wherein 55 men and 44 women need to be in the menstrual period, and female volunteers need not to be in the menstrual period.

The volunteers were scheduled to perform simulated aircraft piloting maneuvers for 3.5 hours continuously, inducing mild fatigue.

Collecting a urine sample: urine samples are collected before and after the volunteer carries out the simulated driving operation, and the urine samples are collected by using a sterile urine cup and are subpackaged in a sterile tube for storage.

Human urine samples are stored, and the urine samples are subpackaged in sterile centrifuge tubes and stored at-80 ℃.

1.2 pretreatment of human urine samples:

the urine sample pretreatment steps are as follows: before assay, the urine sample was taken out and left at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant was diluted with 100. mu.L of water.

1.3 analyzing and detecting the urine sample by adopting a liquid chromatography-time-of-flight mass spectrometry method:

the urine sample is detected by using polar chromatographic column HILIC and weak polar chromatographic column C ₁₈ And the non-polar column PFPP is used for determining the polarity of urine,And (4) respectively carrying out separation detection on the weak polar component and the nonpolar component.

The liquid phase conditions using a polar HILIC column were: UPLC BEH Amide HILIC column (2.1mm × 100mm,1.7 μm), mobile phase A is 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B is 0.1% formic acid; the column temperature was 40 ℃, the sample injection amount was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: positive ion ionization mode detection, mass range was set to 50-1200m/z full scan mode. The optimum capillary voltage of the electrospray ionizer was 3000V, and the cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

Using weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1mm × 100mm,1.7 μm), mobile phase A is aqueous solution containing 0.1% formic acid, and phase B is acetonitrile; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

The liquid phase conditions using a non-polar PFPP chromatography column were: UPLC HSS PFPP column (2.1mm × 100mm,1.7 μm), the mobile phase is aqueous solution containing 0.1% formic acid as phase A, and methanol as phase B; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. Electrospray ionizationThe optimum capillary voltage for the ionizer was 3000V (positive ions) or 2200V (negative ions), and Cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

Each urine sample is respectively detected by 3 chromatographic columns for polar, weakly polar and nonpolar components, wherein the polar component is only detected in a positive ion mode, and the weakly polar and nonpolar components are detected in a positive ion mode and a negative ion mode, namely each urine sample is detected for 5 times, so that all metabolic compounds in the urine can be detected as far as possible. A blank is inserted into each 10 samples in the detection to prevent cross contamination, and a quality control sample is inserted for quality control. The temperature of the sample chamber was maintained at 4 ℃ during the analytical test.

1.4 data processing and preliminary screening of biomarkers

The method comprises the steps of analyzing a detection sample by using a liquid chromatography-mass spectrometer to obtain 435GB detection data, performing statistical analysis and processing by using a professional metabonomics data processing software Progenetics QI, aligning data, extracting peaks by using simulated aircraft driving as a processing mode for inducing mild fatigue, analyzing by using a partial least square method OPLS-DA, and primarily screening potential biomarkers by using P less than or equal to 0.05, CV less than or equal to 30%, VIP greater than 1.0 and maximum change multiple more than or equal to 1.2 as a screening threshold. Wherein the maximum fold change is selected to take into account that fatigue is a recoverable physiological change, the value is set differently from the value set to 2.0 or even to 3.0 or 4.0 in a disease study, and to a smaller value of 1.2.

Processing urine sample detection data according to the above steps while using weak polarity C ₁₈ In the data of 12282 compounds of weak polar components in the urine detected by the positive ion mode of the column, 1 compound is analyzed and screened as a potential biomarker; 9490 compounds in urine are detected by using a polar HILIC column positive ion mode and weak polar C ₁₈ Detection of weak polarity in urine by negative ion mode of columnAnd in the data of 24363 compounds, 13054 compounds in the nonpolar component in the urine detected by the nonpolar PFPP column positive ion mode and 7702 compounds in the urine detected by the nonpolar PFPP column negative ion mode, the biomarkers meeting the conditions can not be screened.

1.5 biomarker metabolic pathway retrieval and Structure confirmation

1 of the potential biomarkers initially selected in step 1.4 are at C ₁₈ The column retention time was: 3.0 min, the precise mass number m/z is 139.0508. The mass deviation was set to 5ppm and the retention time deviation was set to 0.5min, comparing the potential biomarker chromatographic retention behavior and mass number with urocanic acid compared to the fatigue level biomarkers of table 6. Further adopting a urocanic acid standard substance, comparing the standard substance with the compound to be detected by adding the standard substance, wherein the standard substance and the compound to be detected have the same retention time, and the detected accurate mass number is the same, thereby determining that the potential biomarker is urocanic acid.

The comparative urocanic acid fold change was up-regulated by 1.48 fold before and after the simulated driving. The simulated civil aircraft pilot team member experiences light fatigue. And advising the members of the team to leave the post and rest for 20-30 minutes before going on the post.

Example 2 detection of fatigue level of a team of civil aviation air traffic controllers

2.1 volunteer enrollment and sample collection:

volunteer recruitment: 25 volunteers of civil aviation air traffic controllers are recruited in an airport in a country, and the group entering conditions are as follows: healthy body, male, no medicine taking, age 20-35 years old. The civil aviation air traffic controller is responsible for commanding safe operation of the aircraft on the air traffic route, and colloquially speaking, the civil aviation air traffic controller is used for commanding the aircraft and comprehensively managing all aircrafts in the whole airspace by referring to information such as radar and the like. During work, controllers often command the operation of a plurality of airplanes simultaneously, and the abilities of concentration, accurate judgment, emergency treatment and the like are needed, so that fatigue is very easy, and the maximum time of each controller for commanding the airplanes in the seats is clear and not more than 2 hours by relevant regulations of the civil aviation bureau. The fatigue produced during the work is mainly caused by mental labor.

Collecting a urine sample: the urine sample is collected once before the volunteer of the controller in white duty goes on duty as a non-fatigue sample, and the urine sample is collected once before the volunteer of the controller goes off duty after the volunteer goes off duty in white duty as a moderate fatigue sample. The sample collection is carried out in 2016, 10 months and autumn, and the working time of a controller team in white class reaches 8 hours.

Urine samples were collected using sterile urine cups and stored in sterile tubes at-80 ℃.

2.2 pretreatment of urine samples:

the urine sample pretreatment step comprises: before assay, the urine sample was taken out and left at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant was diluted with 100. mu.L of water.

2.3 analyzing and detecting the urine sample by adopting a liquid chromatography-time-of-flight mass spectrometry method:

the urine sample is detected by using polar chromatographic column HILIC and weak polar chromatographic column C ₁₈ And the non-polar chromatographic column PFPP is used for separating and detecting polar, weak-polar and non-polar components in the urine respectively.

The liquid phase conditions using a polar HILIC chromatography column were: UPLC BEH Amide HILIC column (2.1mm × 100mm,1.7 μm), mobile phase A is 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B is 0.1% formic acid; the column temperature was 40 ℃, the sample injection amount was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: positive ion ionization mode detection, mass range was set to 50-1200m/z full scan mode. The optimum capillary voltage for the electrospray ionizer was 3000V, and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ )。

Using weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ column (2.1mm × 100mm,1.7 μm), mobile phase A comprising 0.1% formic acid in water, and phase B comprising acetonitrile; the column temperature was 40 ℃, the sample injection amount was 2.0 μ L, and the mobile phase flow wasThe speed is 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage of the electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and the cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

The liquid phase conditions using a non-polar PFPP chromatographic column were: UPLC HSS PFPP column (2.1mm × 100mm,1.7 μm), the mobile phase is aqueous solution containing 0.1% formic acid as phase A, and methanol as phase B; the column temperature was 40 ℃, the sample size was 2.0. mu.L, and the mobile phase flow rate was 0.3 mL/min. The mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode. The optimum capillary voltage for electrospray ionizer was 3000V (positive ions) or 2200V (negative ions), and cone voltage was 30V. The drying gas was nitrogen, the desolvation flow rate was 800L/h, and the cone gas flow rate was 30L/h. The desolvation temperature was 400 ℃ and the ion source temperature was 100 ℃. Leuconeeenkephalin (leucine enkephalin) with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da ([ M + H ]] ⁺ ) Or 554.2615Da ([ M-H)] ^- )。

Each urine sample is respectively detected by 3 chromatographic columns for polar, weakly polar and nonpolar components, wherein the polar component only detects a positive ion mode, and the weakly polar and nonpolar components detect a positive ion mode and a negative ion mode, namely, each urine sample is detected for 5 times so as to detect all metabolic compounds in the urine as far as possible. A blank is inserted into each 10 samples in the detection to prevent cross contamination, and a quality control sample is inserted for quality control. The temperature of the sample chamber was maintained at 4 ℃ during the analytical test.

2.4 data processing and preliminary screening of biomarkers

Analyzing a detection sample by using a liquid chromatography/mass spectrometer to obtain 65GB detection data, performing statistical analysis processing by using a professional metabonomics data processing software Progenetics QI, performing data alignment and peak extraction, analyzing the sample before and after processing, analyzing by using a partial least square method OPLS-DA, and primarily screening out potential biomarkers by using P less than or equal to 0.05, CV less than or equal to 30%, VIP greater than 1.0 and maximum change multiple more than or equal to 1.2 as screening thresholds. Wherein the maximum fold change is selected to take into account that fatigue is a recoverable physiological change, the value is set differently from the value set to 2.0 or even to 3.0 or 4.0 in a disease study, and to a smaller value of 1.2.

Processing the detection data of the urine samples of the controller group according to the steps (see table 7), and analyzing and screening 4 compounds as potential biomarkers from the data of 7903 compounds of the polar components in the urine by using a polar HILIC column positive ion mode; in the presence of weak polarity C ₁₈ In the data of 10463 compounds of weak polar components in the urine detected by the positive ion mode of the column, 5 compounds are analyzed and screened as potential biomarkers; using weak polarity C ₁₈ 1 compound is analyzed and screened as a potential biomarker in data of 6014 compounds of weak polar components in urine detected in a column anion mode; analyzing and screening 4 compounds as potential biomarkers in the data of 9739 compounds for detecting the nonpolar component in the urine by using the nonpolar PFPP column positive ion mode; in the data of 5996 compounds of the nonpolar component in the urine detected by the nonpolar PFPP column negative ion mode, potential biomarkers meeting the conditions cannot be analyzed and screened.

TABLE 7 biomarker related to potential fatigue screened in urine samples from a panel of controllers

2.5 biomarker Metabolic pathway retrieval and Structure confirmation

The 14 potential biomarkers preliminarily selected in step 2.4 were confirmed by setting the mass deviation to 5ppm and the retention time deviation to 0.5min by using a chromatographic column, retention time and accurate mass number, and comparing the first 6 potential biomarkers with the information of urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide and Alpha-CEHC of items 2 to 7 in Table 6. And (3) comparing by adding the urocanic acid standard, wherein the retention time of the standard and the retention time of the compound to be detected are consistent, and in addition, the accurate molecular weight is consistent through mass spectrometry, so that the first potential biomarker is determined to be urocanic acid.

Further comparing the fold change of the 6 biomarkers, urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide were down-regulated by 1.44, 1.38, 1.62, 1.5, 1.78, respectively, and Alpha-CEHC was up-regulated by 1.33-fold.

In conclusion, the controller was working for 8 hours on a white shift with moderate fatigue.

The embodiments of the present invention have been described above. However, the present invention is not limited to the above embodiment. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (16)

1. A method for detecting the fatigue degree of a team based on human urine is characterized by comprising the following steps:

step 1, collecting urine samples of team members; after the urine sample is collected, the sample is stored at a low temperature of not higher than-20 ℃;

step 2, preprocessing the sample collected in the step 1; the pretreatment step comprises the following steps: centrifuging the urine sample, taking the supernatant and optionally diluting the supernatant into an aqueous solution with a concentration suitable for analysis and detection in the subsequent steps;

step 3, detecting the sample pretreated in the step 2 by adopting a liquid chromatography-mass spectrometry method; the liquid chromatography-mass spectrometry is liquid chromatography-time of flight mass spectrometry; the urine sample is detected by using polar chromatographic column HILIC and weak polar chromatographic column C ₁₈ And the non-polar chromatographic column PFPP separates and detects the polar, weak polar and non-polar components in the urine respectively;

using polar HILIC coloursThe liquid phase conditions of the column are: UPLC BEH Amide HILIC column 2.1mm x 100mm,1.7 μm, mobile phase A is 95% acetonitrile and 5% aqueous solution containing 0.1% formic acid, and phase B is 0.1% formic acid; the column temperature is 40 ℃, the sample injection amount is 2.0 mu L, and the flow rate of the mobile phase is 0.3 mL/min; the mass spectrum conditions are as follows: detecting in positive ion ionization mode, setting the mass range to be 50-1200m/z full scanning mode; the optimal capillary voltage of the electrospray ionizer is 3000V, and the cone voltage is 30V; the drying gas is nitrogen, the desolvation flow rate is 800L/h, and the cone gas flow rate is 30L/h; desolvation temperature is 400 ℃, and ion source temperature is 100 ℃; leuconeeenkephalin with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da [ M + H ]] ⁺ ；

Using weak polarity C ₁₈ The liquid phase conditions of the chromatographic column are as follows: UPLC CSH C ₁₈ column 2.1mm gamma 100mm at 1.7 μm, mobile phase A containing 0.1% formic acid water solution, and phase B containing acetonitrile; the column temperature is 40 ℃, the sample injection amount is 2.0 mu L, and the flow rate of the mobile phase is 0.3 mL/min; the mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full-scanning mode; the optimal capillary voltage of the electrospray ionizer is 3000V or 2200V, and the cone voltage is 30V; the drying gas is nitrogen, the desolvation flow rate is 800L/h, and the cone gas flow rate is 30L/h; the desolvation temperature is 400 ℃, and the ion source temperature is 100 ℃; leuconeeenkephalin with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da [ M + H ]] ⁺ Or 554.2615Da [ M-H [ ]] ^- ；

The liquid phase conditions using a non-polar PFPP chromatographic column were: UPLC HSS PFPP column 2.1mm gamma 100mm,1.7 μm, mobile phase A is aqueous solution containing 0.1% formic acid, and phase B is methanol; the column temperature is 40 ℃, the sample injection amount is 2.0 mu L, and the flow rate of the mobile phase is 0.3 mL/min; the mass spectrum conditions are as follows: detecting positive ions and negative ions in two ionization modes, and setting the mass range to be 50-1200m/z full scanning mode; the optimal capillary voltage of the electrospray ionizer is 3000V or 2200V, and the cone voltage is 30V; the drying gas is nitrogen and the desolvation flow rate is800L/h, cone gas flow rate 30L/h; the desolvation temperature is 400 ℃, and the ion source temperature is 100 ℃; leuconeeenkephalin with the concentration of 0.2ng/mL is used as a mass number calibration internal standard, and the mass of a calibration ion is 556.2771Da [ M + H ]] ⁺ Or 554.2615Da [ M-H [ ]] ^- ；

Step 4, processing and threshold setting are carried out on the data obtained by detection in the step 3, and potential biomarkers are screened out;

step 5, comparing the potential biomarkers screened out in the step 4 with fatigue degree markers, and judging the fatigue degree of the detected team members;

in the step 1, the collecting step comprises collecting a non-fatigue sample and a fatigue degree sample; the step of collecting the sample comprises: collecting urine samples of members of a team before working or before fatigue is induced by simulation operation as non-fatigue samples; collecting urine samples of the members of the team as fatigue degree samples after the members work or simulate operation to induce fatigue according to the fatigue degree; the continuous working time, the working posts, the working loads and the scheduling conditions of all the members in the team are the same or similar;

the team is formed by a driver and a controller;

in step 4, the data separated and detected in step 3 is subjected to statistical analysis processing by adopting data processing software; the analysis processing method comprises the steps of data alignment, peak extraction, partial least square method OPLS-DA analysis, and screening out potential biomarkers by using P less than or equal to 0.05, CV less than or equal to 30%, VIP greater than 1.0, and maximum change multiple greater than or equal to 1.2 and less than 2 as screening thresholds;

in step 5, the markers of fatigue degree are selected from: (1) urocanic acid; (2) acetylcytosine; (3) 5-hydroxytryptophan; (4) dimethyl guanosine; (5) acetanilide; and (6) Alpha-CEHC;

when the detection result of the urine sample collected by the members of the team after working for 2-4 hours shows that the urocanic acid content is increased by 1.4 times, namely the fatigue degree sample is increased by 1.4 times relative to the urocanic acid content in the non-fatigue sample, the members of the team can be judged to have slight fatigue;

when the detection result of the urine sample collected by the team member within 5-8 hours of working time shows that the content reduction multiples of urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine and acetanilide in the fatigue degree sample are respectively more than 1.4, more than 1.3, more than 1.4 and more than 1.4 in comparison with the non-fatigue sample, and the content increase multiple of Alpha-CEHC reaches more than 1.3, the team member can be judged to have moderate fatigue.

2. The method of claim 1, wherein in step 1, the urine sample is from a healthy class member who, when a woman, is not menstrual.

3. The method of claim 1, wherein the group is a sample size group of 5 or more people, or a sample size group of 8-20 people, or a sample size group of 8-10 people.

4. The method of claim 1, wherein in step 1, the urine sample is dispensed into a sterile centrifuge tube and stored at-80 ℃.

5. The method according to any one of claims 1 to 4, wherein an appropriate amount of antibiotic is also added to the sample during cryopreservation to avoid decomposition of part of the metabolites by the bacteria.

6. The method of claim 5, wherein the sodium azide is added to the sample at a mass concentration of 0.05-0.1%.

7. The method of any one of claims 1 to 4, wherein the sample is diluted with 1 to 3 volumes of water.

8. The method of claim 7, wherein the urine sample is pre-treated by: before assay, the urine sample was taken out and left at room temperature, centrifuged at 12000rpm for 5 minutes at 4 ℃ and 100. mu.L of the supernatant was diluted with 100. mu.L of water.

9. The method of claim 1, wherein in separating the sample of the test body fluid, 1 blank is inserted every 5 samples to prevent cross contamination, and one quality control sample is also inserted to perform quality control;

the temperature of the sample chamber is kept between 0 and 4 ℃ during the separation and detection process.

10. The method according to any one of claims 1 to 4, wherein in step 4, the data separated and detected in step 3 is subjected to statistical analysis by using metabonomic data processing-related software.

11. The method of claim 10, wherein the data is analyzed using the data processing professional software Progenesis QI to obtain the potential biomarkers.

12. The method of any one of claims 1 to 4, wherein in step 4, the potential biomarker is screened by determining the precise molecular weight of the potential biomarker by liquid chromatography-mass spectrometry to infer its molecular formula, and comparing the spectral characteristics and mass spectral characteristics exhibited by chromatographic retention times against a database of human urine fractions from one or more of HMDB, METLIN, Chempipder, MZedDB or KEGG to determine the potential biomarker with a mass deviation set at 5 ppm.

13. The method of claim 12, wherein the marker metabolic pathway query is performed using a MetabioAnalyst online database and compared to a standard; the metabolic pathway is related to human sleep, and the detection result of the metabolic pathway is consistent with the measurement result of the retention time and the mass number of the standard substance in a liquid chromatography-mass spectrometer, and the metabolic pathway is used as a fatigue degree marker.

14. The method of claim 13, wherein the unknown potential biomarkers that recur and change consistently across multiple fatigue level panels but are not retrieved from the HMDB and METLIN databases are purified to produce a purified product and the purified product is subjected to mass spectrometry, uv, ir and/or nuclear magnetic data for structural identification as a fatigue level marker.

15. A workload assessment method, or before the post, whether the post can be performed or not, or in the post, a method for detecting and assessing the workload of the post for finding the fatigue risk and adjusting the fatigue risk in time, or after the post, is characterized by comprising the following steps:

1) when the fatigue degree samples collected in the post of 2-4 hours of work of the members of the team judge that the members of the team have slight fatigue by using the method of any one of claims 1-14, the members of the team are recommended to leave the post for rest and then carry out post-working for the posts which are sensitive to the safety production of drivers and controllers;

2) if the fatigue samples collected over 5 hours of working have detected urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide and Alpha-CEHC in urine samples by the method according to any one of claims 1 to 14, and the decrease factors of urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine and acetanilide relative to the non-fatigue samples are 1.4 or more, 1.3 or more, 1.4 or more and 1.4 or more, respectively, and the increase factor of Alpha-CEHC content is 1.3 or more, the work load of the team member is brought to full load, and the rest is recommended or the work load is reduced.

16. A method for shift schedule system assessment, characterized in that, by using the method of any one of claims 1 to 14,

a1) when the fatigue degree samples collected when the team members work for 2-4 hours judge that the team members have slight fatigue by using the detection method, for the safety sensitive posts, the team members need to have a rest;

when the fatigue degree samples collected when the members of the team work for 2-4 hours are judged to have no light fatigue by using the detection method, the working load of the members of the team is appropriate; or the like, or, alternatively,

2) for the work of safety sensitive posts needing high attention, urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethyl guanosine, acetanilide and Alpha-CEHC are screened from collected fatigue degree samples after the work of the members of the team is carried out for 5-7 hours, the down-regulation multiples of the fatigue degree samples relative to non-fatigue samples are respectively more than 1.4, more than 1.3, more than 1.4 and more than 1.4, and when the increase multiple of the content of Alpha-CEHC reaches more than 1.3, the members of the team are proved to have moderate fatigue, the workload of the members of the team is overloaded, the work is recommended to be stopped, the members of the team have a longer rest time after leaving the work, or the members are increased to reduce the workload; when the work is carried out for 8 hours, the working time or the working load needs to be reduced, and the safety production risk is reduced; or the like, or, alternatively,

a3) and when the work is finished for 8 hours, screening urocanic acid, acetylcytosine, 5-hydroxytryptophan, dimethylguanosine, acetanilide and Alpha-CEHC from the collected fatigue degree samples, wherein the reduction multiples of the fatigue degree samples relative to the non-fatigue samples are respectively more than 1.4, more than 1.3, more than 1.4 and more than 1.4, and when the increase multiples of the content of the Alpha-CEHC reach more than 1.3, the members of the team are indicated to have moderate fatigue, and the members of the team of the shift system work at full load.

Images