Method and kit for determining amount of coenzyme Q10 in biological sample

Abstract

Methods and kits for determining the amount of coenzyme Q10 in a biological sample are provided. Relates to the technical field of medical biology. The method comprises the following steps: taking a biological sample to be determined, adding a 1, 4-benzoquinone solution and an internal standard substance, adding an extracting agent, extracting, taking an extracting solution, filtering, and performing liquid chromatography-tandem mass spectrometry determination, wherein the chromatographic conditions are as follows: a Waters C18 chromatographic column is adopted, and a 100% B phase is used as a mobile phase for elution; the mobile phase comprises 0.1% by volume of a component 1 and 99.9% by volume of a component 2, the component 1 is formic acid, and the component 2 is composed of methanol and isopropanol in a ratio of (7-9): (3-1). According to the embodiment of the invention, parameters are optimized through fuzzy logic, the efficient, accurate, sensitive and low-cost method for measuring the amount of the coenzyme Q10 in the biological sample is established, the mobile phase selection of LC-MS / MS detection of the CoQ10 is optimized by virtue of the capability of processing uncertain data through the fuzzy logic, and the precision of the method is remarkably improved compared with that of similar researches.

Description

Technical Field

[0001] The present invention relates to the field of pharmaceutical biotechnology, and more particularly to a method and a kit for determining the amount of coenzyme Q10 in a biological sample. Background Art

[0002] Coenzyme Q10 (CoQ10), also known as ubiquinone, has a chemical structure consisting of a benzoquinone ring and a side chain composed of isoprene. It is a fat-soluble compound naturally present in humans and animals, and is mainly distributed in organs that require a lot of energy, such as the heart, liver, and kidneys. In recent years, many studies have shown that CoQ10 has potential benefits in various health areas. For example, low endogenous CoQ10 levels are significantly associated with cardiovascular disease (CVD), neurodegenerative diseases, diabetes, and cancer. Clinical studies have shown that CoQ10 supplementation can significantly reduce CVD and stress-related mortality. CoQ10 is synthesized in the human body through a complex process and can be ingested through diet. It is mainly found in foods such as fish, pork, beef, and peanuts [4]. Although the proportion of healthy people with CoQ10 levels below the normal range is only about 4% [5], it is closely related to a variety of diseases, and individual CoQ10 levels vary significantly due to factors such as age, region, living standards, and health status. Therefore, monitoring CoQ10 levels is of great significance.

[0003] The application of liquid chromatography tandem mass spectrometry (LC-MS / MS) in laboratory testing has shown an upward trend in recent years, and it has shown significant advantages in the detection of fat-soluble substances due to its high precision and high sensitivity. Currently, there are relatively few studies on the LC-MS / MS detection of human CoQ10, and existing studies have quantified the oxidized and reduced forms of CoQ10 separately. The reduced form is easily oxidized during sample storage and pretreatment, resulting in poor stability, which may affect the accuracy of detection. Some commercial CoQ10 detection kits have certain limitations under specific conditions. For example, the lack of stability of the standard curve may lead to increased quantitative errors. In order to overcome these technical problems and further enrich the detection methods of CoQ10, it is particularly necessary to establish new methods with greater stability, sensitivity and accuracy. Summary of the Invention

[0004] The embodiments of the present invention provide a method and a kit for determining the amount of coenzyme Q10 in a biological sample. This method can not only improve the reliability of detection, but also provide more diverse technical options for experiments and research under different conditions.

[0005] A first aspect of an embodiment of the present invention provides a method for determining the amount of coenzyme Q10 in a biological sample, the method comprising:

[0006] A biological sample to be measured is taken, a 1,4-benzoquinone solution and an internal standard are added, an extractant is added, extraction is performed, the extract is taken, filtered, and subjected to liquid chromatography tandem mass spectrometry determination;

[0007] The chromatographic conditions are:

[0008] A Waters C18 chromatographic column was used, and 100% B phase was used as the mobile phase for elution; the mobile phase included 0.01% to 0.1% component 1 and 99.9% to 99.99% component 2 in a volume ratio, wherein the component 1 was formic acid and the component 2 was methanol:isopropanol = 7-9:3-1.

[0009] Optionally, during the liquid chromatography detection process, the column oven temperature is 35-50° C., and the mobile phase flow rate is 0.3-0.6 mL / min.

[0010] Optionally, mass spectrometry analysis uses an APCI ion source;

[0011] APCI parameters included: curtain gas CUR of 35 Psi, CAD of 7, needle current NC of 3 mA, TEM of 450°C, and spray gas GS1 of 45 Psi;

[0012] The auxiliary heating gas GS2 (Ion Source Gas2) is 50Psi.

[0013] Optionally, the following steps are used to optimize the composition ratio of the component 2:

[0014] The ratio of methanol to isopropanol was used as the input variable of the model, and the elution time was used as the output;

[0015] The output membership function adopts equidistant triangular membership function, the fuzzy rule adopts IF-THEN structure, and the fuzzy reasoning logic adopts AND mode;

[0016] According to the fuzzy reasoning results, the optimal mobile phase ratio was selected within the effective range of the optimal peak elution time to achieve the optimal balance among signal intensity, retention time and background noise.

[0017] Optionally, the component 2 is methanol:isopropanol=8:2.

[0018] Optionally, the extractant is isopropanol.

[0019] Optionally, the method further includes:

[0020] Prepare 2 mg / mL 1,4-benzoquinone solution with methanol; prepare 1000 ng / mL internal standard CoQ10-d9 with 5% BSA solution;

[0021] The method comprises taking a biological sample to be measured, adding a 1,4-benzoquinone solution and an internal standard, adding an extractant, extracting, taking an extract, and filtering, including:

[0022] Take 50ul of serum, add 50ul of the benzoquinone solution, add 50ul of the internal standard, shake and mix for 10 minutes, add 500ul of the extractant, shake and mix for 5 minutes, centrifuge for 5 minutes, and take 200ul of the supernatant.

[0023] Optionally, the method further includes:

[0024] CoQ10 standard substance was prepared in 5% BSA solution to prepare a series of concentrations of 50, 100, 500, 1000, 2000 and 5000 ng / mL for drawing a standard curve.

[0025] The second aspect of the present invention provides a kit for implementing the method for determining the amount of coenzyme Q10 in a biological sample as described in any one of the first aspects.

[0026] The embodiment of the present invention successfully established a new detection method by improving the accuracy and sensitivity of LC-MS / MS detection of CoQ10 and applying fuzzy logic to optimize key parameters. The quantitative lower limit of this method is 0.1 ng / mL. The optimal ratio of mobile phase (methanol and isopropanol) is determined to be 8:2 through fuzzy reasoning, and the actual retention time is 1.749±0.119 min, which provides a scientific basis for the optimization of fuzzy logic in detection methods and its extension to other detection substances and methods. While significantly improving accuracy and sensitivity, the embodiment of the present invention significantly reduces research costs with the help of cutting-edge AI technology, laying a solid foundation for large-scale CoQ10 detection and medical cost control.

[0027] The embodiment of the present invention uses fuzzy logic to optimize parameters to establish an efficient, accurate, sensitive and cost-effective method for determining the amount of coenzyme Q10 in biological samples. The results of the study showed that the precision of this method was significantly improved compared with similar studies. Both inter-batch and intra-batch CVs were controlled within 10%, which meets the requirements of the European Medicines Agency (EMA) "Guidelines for Validation of Bioanalytical Methods" and the Clinical Laboratory Standards Institute (CLSI) C62-A standard for high precision (imprecision <10%). This method has made significant progress in precision. In low-concentration detection, the lower limit of quantification of the method provided by the embodiment of the present invention reached 0.1 ng / mL, and the sensitivity was significantly improved compared with existing results, laying a solid foundation for improving the reliability of CoQ10 detection.

[0028] Specifically, the present invention leverages fuzzy logic's ability to process uncertain data to optimize mobile phase selection for LC-MS / MS detection of CoQ10. Validation results show that the deviation between the average peak time and the predicted time is only 0.63%. The effective application of fuzzy logic significantly reduces experimental time and resource consumption, improves research efficiency, and highlights its potential for application in the biomedical field. The present invention not only enhances the LC-MS / MS detection capabilities of CoQ10 but also provides valuable insights for applying fuzzy logic to the detection of other fat-soluble substances and optimizing the precision and reliability of LC-MS / MS technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the description of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 The standard curve of coenzyme Q10 obtained in the embodiment of the present invention is shown;

[0031] Figure 2 The LC-MS / MS total ion chromatogram with a detection limit of 0.1 ng / mL in an embodiment of the present invention is shown;

[0032] Figure 3 The membership function for CoQ10 detection in mobile phase optimization in the practice of the present invention is shown. DETAILED DESCRIPTION

[0033] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] In the development of LC-MS / MS methodology, there are often uncertainties such as the optimal ratio of mobile phase, which may lead to a large amount of waste of experimental resources. In recent years, the application of artificial intelligence (AI) in laboratory testing has increased significantly. Among them, fuzzy logic is good at dealing with uncertainty problems in the biomedical field, and is therefore expected to optimize the screening of some parameters in methodology development, thereby improving the overall efficiency of the research. Therefore, the embodiment of the present invention aims to solve the uncertainty of some parameters through fuzzy logic, thereby establishing a more stable, accurate and sensitive detection technology. Accordingly, in the embodiment of the present invention, a series of exploratory studies were carried out to establish a method for determining the amount of coenzyme Q10 in biological samples, as follows:

[0035] In this example, LC-MS / MS analysis was performed using a 1000 ng / mL standard and a randomly selected clinical serum sample extract to identify the optimal mobile phase combination. Factors considered during screening included detection efficiency (elution capacity), half-peak width, retention capacity, signal strength, background noise, signal-to-noise ratio (S / N), and detection cost. The formulations of the various mobile phases are detailed in Table 1.

[0036] Table 1 Mobile phase combination grouping information

[0037] Grouping Component 1 (volume ratio 0.1%) Component 2 (99.9% by volume) 1 Formic acid Methanol 2 Formic acid Acetonitrile 3 Formic acid Methanol:isopropanol=7:3 4 Formic acid Methanol: ethanol = 5:5 5 Formic acid Methanol:acetonitrile = 5:5 6 Formic acid Ethanol: acetonitrile = 5:5 7 Formic acid ethanol 8 Formic acid Isopropyl alcohol

[0038] Atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) are two commonly used ionization techniques, suitable for different compound types and analytical requirements. The most suitable ion source can be selected by comparison. Table 2 shows the mass spectrometry acquisition conditions for analyzing standards and matrix samples using APCI and ESI ion sources, respectively. The selection was made based on multiple criteria, including sensitivity, signal-to-noise ratio, and interferences.

[0039] Table 2 Mass spectrometry acquisition conditions

[0040]

[0041] The mass spectrometry conditions used in the present embodiment include: APCI parameters: Curtain Gas (CUR) of 35 psi, Collision Gas (CAD) of 7, Nebulizer Current (NC) of 3 mA, TEM (temperature) of 450°C, and Ion Source Gas (GS1) of 45 psi; ESI parameters: Curtain Gas (CUR) of 25 psi, Collision Gas (CAD) of 7, ionization Voltage (IS) of 5500 V, TEM (temperature) of 450°C, and Ion Source Gas (GS1) of 45 psi. Auxiliary Heating Gas (GS2) of 50 psi; Liquid Phase Conditions: Because coenzyme CoQ10 has multiple hydrophobic isoprene units, it binds tightly to the reversed-phase column in LC-MS / MS analysis, exhibiting strong retention characteristics. To achieve efficient separation and elution of CoQ10, the present invention uses 100% Phase B as the mobile phase, ensuring rapid and complete elution of CoQ10 from the chromatographic column while optimizing the sensitivity and accuracy of mass spectrometry detection. The column oven temperature is 45°C, and the flow rate is 0.5 mL / min.

[0042] In the present example, a concentration series was prepared using 5% BSA, and a Coenzyme Q10 standard curve was plotted to verify linearity and accuracy. This was repeated three times. A third-party quality control product was also used for method validation, and the test was repeated three times. Ten serum and plasma samples were also selected to evaluate the consistency of Coenzyme Q10 test results across the two sample types. High- and low-concentration samples were also selected from these 10 samples to prepare low-concentration quality control (LQC) and high-concentration quality control (HQC) samples. To identify the optimal extraction solution, average recoveries were calculated for comparison. One clinical serum sample was selected and assayed six times using different extraction solutions: methanol in Group A, acetonitrile in Group B, ethanol in Group C, isopropanol in Group D, and 5:5 hexane:isopropanol in Group E. The extraction method is as follows: take 50ul of serum, add 50ul of benzoquinone (2mg / ml), add 50ul of internal standard (1ug / ml), add 500ul of extraction reagent, shake and mix for 5 minutes, centrifuge for 5 minutes (127000r / min), take 200ul of supernatant, and detect on the machine.

[0043] In the implementation of this invention, the limit of quantification and limit of detection (LOD) of Coenzyme Q10 in LC-MS / MS were determined through methodological validation. The LOD was assessed by processing 10 samples at the lower limit of quantification (LLQ), requiring a signal-to-noise ratio (S / N) ≥ 10:1, imprecision (CV) < 15%, and accuracy deviation < 20%. The LOD was assessed by serially diluting the standard sample using 5% BSA as a blank matrix, creating a 3–5-step low-concentration gradient with three replicates at each concentration. After pre-treatment, LC-MS / MS analysis was performed. The lowest concentration at which the signal-to-noise ratio (S / N) reached ≥ 3:1 was determined as the LOD.

[0044] To verify the matrix effect, in the present embodiment, 5 clinical samples were used as group A, the pure solution of the analyte at the middle concentration of the mark line was taken as group B, and a 1:1 mixture of group A and group B solution was taken as group C. The above 3 groups of samples were pre-treated separately and the measurement was repeated 5 times. The spiked recovery rate was calculated by dividing the clinical sample into three equal parts, two of which were added with different concentrations and equal volumes (≦10% of the total volume) of the analyte standard solution to prepare low and high concentration recovery samples; the third part was added with an equal volume of deionized water as the basic sample. Each sample was measured 3 times, and the recovery rate was calculated according to the following formula: spiked recovery rate = (specified value of spiked sample - determined value of basic sample) / spiked amount × 100%.

[0045] After determining the upper limit of the quantification (HLOQ) concentration of the standard curve, a blank sample was measured to determine carryover. This test was repeated five times, and the peak areas were averaged. Clinical samples were then selected and spiked with the analyte to a concentration of approximately 80% of the HLOQ. The volume of the added standard should not exceed 10% of the total volume. The sample was then diluted with deionized water, and five replicates were prepared for each dilution factor to assess carryover and the clinical reporting range.

[0046] To verify the random error of the test result of the method for the embodiment of the present invention and the stability of the sample, 15 samples of three concentration levels of low (80-110ng / mL), medium (800-1100ng / mL) and high (>2000ng / mL) were used, and 1 analysis batch was detected every day. Each batch of samples with 3 levels was tested, and each sample was repeated five times for 3 consecutive days. The high, medium and low concentration samples of 72 people were stored under room temperature, 4°C, -20°C and -80°C, and detected on the same day, 1 day, 2 days, 4 days, 1 week, 2 weeks, 3 weeks and 4 weeks respectively (room temperature was only tested to 1 week), and each determination was repeated 3 times, and the average value was taken. At the same time, 1 person was taken for each sample of the three concentration levels, and repeated freezing and thawing 8 times was performed, and each determination was repeated 3 times.

[0047] To verify the effects of jaundice (bilirubin simulation), hemolysis (hemoglobin simulation) and lipemia samples (triglyceride simulation) on the detection of CoQ10. In the embodiment of the present invention, five experimental groups were set up in low, medium and high concentration samples, including a control group, a low, medium and high concentration group (interfering substance) and a solvent control group. Deionized water, interfering substances (bilirubin, hemoglobin, triglycerides) and interfering substance solvent (methanol) were added in sequence. The configuration system was 950ul sample + 50ul added components. The low, medium and high concentrations of interfering substances dissolved in the sample were 0.05mg / mL, 0.1mg / mL and 0.2mg / mL, respectively. Each concentration sample was tested 5 times in each group.

[0048] The optimal elution time of LC-MS / MS should be between 1 / 3 and 2 / 3 of the single injection time. In the embodiment of the present invention, the optimal mobile phase elution time is set as the zero point range of the output membership function, and the ratio of the mobile phase is used as the input variable of the model. The output membership function adopts the equidistant triangular membership function commonly used in biomedicine, the fuzzy rule adopts the "IF-THEN" structure, and the fuzzy reasoning logic adopts the "AND" mode. The basic formula of fuzzy reasoning is as follows:

[0049] μA∩B(x) = min [μA(x), μB(x)] (1)

[0050] According to the fuzzy reasoning results, the optimal mobile phase ratio is selected within the effective range of the optimal peak time to achieve the optimal balance between signal intensity, retention time and background noise.

[0051] In the present embodiment, the detection was performed using an AB Sciex QTRAP 6500 liquid chromatography tandem mass spectrometry (LC-MS / MS), which has been certified by the China National Medical Products Administration (NMPA).

[0052] The detection kit used in the embodiment of the present invention is provided by Guangdong Zhongke Qingzi Medical Technology Co., Ltd.

[0053] In the examples of the present invention, the three-party quality control used Clin-Check (batch number: 2364) produced by Recipe, Germany, as well as CoQ10 standard substance (BePure-21434) and CoQ10 internal standard d9 (MD-8056-1 mg), all provided by Beijing Manhag Biotechnology Co., Ltd.

[0054] A Waters column (BEH C18 2.5 μm × 2.1 mm × 50 mm) and 1,4-benzoquinone 1G (Cat. No. PHR1028) were purchased from Sichuan Little Squirrel Instrument Co., Ltd. Bovine plasma albumin (BSA) was provided by Sigma; methanol, ethanol, acetonitrile, isopropanol, and formic acid were purchased from Fisher. Hemoglobin, bilirubin, and triglycerides were provided by Shanghai MacLean Biochemical Technology Co., Ltd. CoQ10 standards were prepared in 5% BSA at concentrations of 50, 100, 500, 1000, 2000, and 5000 ng / mL for the calibration curve. The internal standard, CoQ10-d9, was also prepared in 5% BSA at a concentration of 1000 ng / mL. 1,4-Benzoquinone was prepared in methanol at a concentration of 2 mg / mL.

[0055] During the exploratory study, the embodiment of the present invention eliminated the mobile phase solutions of groups 1, 2, 5, 7, and 8 based on a comprehensive evaluation of multiple indicators such as elution ability, half-peak width, retention ability, signal intensity, background noise, and S / N. The toxicity and cost factors of the selected groups 3, 4, and 6 were further compared. The toxicity levels were in the order of acetonitrile > methanol > isopropanol > ethanol; the prices were in the order of ethanol > acetonitrile > isopropanol > methanol. Taking into account the toxicity and cost, group 3 (0.1% formic acid, methanol: isopropanol = 7:3) was finally determined to be the optimal mobile phase combination. Since the S / N of ACPI is significantly higher than that of ESI, ACPI is preferably used as the ion source in the embodiment of the present invention. The relative deviation between serum and plasma was -5.5-10.11%, and both positive and negative deviations were <15%, indicating that there was no significant difference between plasma and serum as samples to be tested.

[0056] The extraction recoveries for each extraction solution ranged from 36.86% to 89.13%, with Group A having the lowest recovery and Group E having the highest. The two groups with the best recovery rates were Groups D (80.87%) and E (89.13%). However, due to the lower signal intensity after extraction with Group E (n-hexane:isopropanol = 5:5), Group D (isopropanol) was ultimately selected as the optimal extraction solution. Figure 1 The standard curve of coenzyme Q10 obtained in the embodiment of the present invention is shown. The horizontal axis represents the concentration ratio and the vertical axis represents the area ratio. The three repeated standard curves show high consistency. The fitting curves superimpose well, showing a good linear relationship (y=0.00116x+0.01975). The total linear regression R2>0.99, indicating that the method established in the embodiment of the present invention has good fit and repeatability.

[0057] The results show that the signal-to-noise ratio (S / N) of the method established in the embodiment of the present invention for 10 samples is greater than 10:1, the accuracy is higher than 80%, the average CV is 5.83%, and the average accuracy is 90.66%, which meets the evaluation criteria for the limit of quantification. The detection limit of the method is 0.1 ng / mL. Figure 2 As shown, it shows the LC-MS / MS total ion current diagram of 0.1 ng / mL detection limit in an embodiment of the present invention, wherein the abscissa represents time and the ordinate represents intensity.

[0058] In the method established in this embodiment, the response ratios of the analyte to internal standard in 1:1 mixed solutions and the response ratios of the analyte to internal standard in biological matrix and pure solution samples were all less than 10% across five replicates, meeting the requirements for matrix effect assessment. The average spiked recovery for low-concentration samples was 88.6%, and the spiked recovery for high-concentration samples was 99.42%, both meeting the spiked recovery requirement of 85% to 115%.

[0059] In the method established in this embodiment of the present invention, the average carryover rate across five replicate tests was 11.31%, meeting the criteria for carryover. For samples diluted 5x and 10x, the mean accuracy was 95.64% and 105.07%, respectively, with CVs both less than 5%. Therefore, the upper limit of the clinically reportable range for the method established in this embodiment of the present invention can be defined as: maximum dilution factor × upper limit of linear range concentration, i.e., 10 × 5000 ng / mL = 50,000 ng / mL.

[0060] The results in Table 3 show that the intra-batch CV and inter-batch CV of the method established in the embodiment of the present invention are both less than 10%, indicating that the method has good precision. The average CV of the three concentration samples after 8 freeze-thaw cycles was 2.25%-6.84%, indicating that freeze-thaw of the samples had no significant effect on the analyte concentration test. The inter-batch CV of the samples stored at -20°C and -80°C within 4 weeks was 1.07%-5.56%, indicating that the samples can be stored for a long time under these conditions. When stored at 4°C, there was no significant difference in the concentration determination of low and medium concentration samples, and the measurement values ​​of high concentration samples began to show a downward trend after 3 weeks. When stored at room temperature, the concentration measurement values ​​of high concentration samples began to show a downward trend from the 4th day, and there was no significant change in the other concentration samples.

[0061] Table 3 Results of inter-batch and intra-batch imprecision tests

[0062]

[0063] In the method established in the examples of the present invention, high concentrations of hemoglobin and triglycerides significantly interfered with the determination of CoQ10 in samples of different concentrations (low, medium, and high), with biases exceeding 15% compared to the control group (hemoglobin: 16.8%, 15.81%, and 28.89%; triglycerides: 38.89%, 29.82%, and 23.94%), indicating that hemolysis and lipemia may affect the accuracy of CoQ10 detection. In contrast, bilirubin had no significant effect on the determination of CoQ10 in serum, with biases below 10% (1.07%-6.09%).

[0064] In the present embodiment, the optimal mobile phase (isopropanol:methanol ratio of 3:7) was experimentally determined to have an elution time of 1.16 minutes, representing approximately 33.33%-66.66% of the single injection time. To optimize elution time and reduce experimental costs, this study used a fuzzy inference model to screen the mobile phase ratio. Figure 3 The membership function of CoQ10 detection in the mobile phase optimization in the embodiment of the present invention is shown, wherein the blue line, green line and red line represent low, medium and high levels respectively. Figure 3 Part A) and isopropyl alcohol (as Figure 3 The input was the ratio of 70% methanol and 30% isopropanol (as described in Section B), and the initial condition was set to 70% methanol and 30% isopropanol (y-axis value = 1). The output was the elution time, with an initial value of 1.16 min (y-axis value = 1). The midpoint was set to the median of the single injection time of 1.75 min, and the end points were determined to be 1.455 min and 2.045 min based on the principle of equidistant distribution (equal intersection area) (as shown in Figure 2). Figure 3(As described in Section C of the previous section). The model predicted elution times of 1.76 min, 2.29 min, and 3.2 min for methanol to isopropanol ratios of 8:2, 8.5:1.5, and 9:1, respectively. Of these, 3.2 min was discarded because it was close to the upper limit of a single injection time; while 2.29 min was within the optimal range, it was close to the lower limit and susceptible to experimental error. Therefore, after comprehensive consideration, an 8:2 ratio was selected as the mobile phase concentration ratio. To verify the effectiveness of fuzzy reasoning, 10 mobile phases were prepared with an 8:2 ratio, and the peak times of 5 samples from the same batch were tested. The results showed that the average peak time was 1.749 ± 0.119 min, with a coefficient of variation (CV) of 6.8%, and a deviation of only 0.63% from the model-predicted value (1.76 min), indicating that fuzzy reasoning has high accuracy and application value in optimizing mobile phase selection.

[0065] Based on the above research results, an embodiment of the present invention provides a method for determining the amount of Coenzyme Q10 in a biological sample. The method comprises the following steps:

[0066] A biological sample to be measured is taken, a 1,4-benzoquinone solution and an internal standard are added, an extractant is added, extraction is performed, the extract is taken, filtered, and liquid chromatography tandem mass spectrometry is performed for determination.

[0067] The chromatographic conditions are:

[0068] A Waters C18 chromatographic column was used, and 100% B phase was used as the mobile phase for elution; the mobile phase comprised 0.01% to 0.1% component 1 and 99.9% to 99.99% component 2 in a volume ratio, wherein the component 1 was formic acid and the component 2 was methanol:isopropanol = 7-9:3-1.

[0069] Preferably, the mobile phase comprises 0.1% component 1 and 99.9% component 2 by volume.

[0070] In the embodiments of the present invention, considering that the oxidized and reduced forms of CoQ10 are in dynamic equilibrium in the body, that is, the total amount of oxidized and reduced CoQ10 in the body is constant, the reduced CoQ10 is completely oxidized to oxidized CoQ10 using 1.4-benzoquinone, thereby achieving the detection of the total amount of oxidized CoQ10 and reduced CoQ10, thereby reducing the requirements for sample transportation and storage.

[0071] In the embodiment of the present invention, the analyte is extracted by a one-step method, thereby improving the detection efficiency while ensuring a high recovery rate.

[0072] In the embodiment of the present invention, the column oven temperature during the liquid chromatography detection process is 35-50° C., and the mobile phase flow rate is 0.3-0.6 mL / min.

[0073] Preferably, during the liquid chromatography detection process, the column oven temperature is 45° C. and the mobile phase flow rate is 0.5 mL / min.

[0074] In the embodiment of the present invention, the mass spectrometry analysis preferably uses an APCI ion source;

[0075] APCI parameters include: curtain gas CUR of 35 Psi, CAD of 7, needle current NC of 3 mA, TEM of 450° C., spray gas GS1 of 45 Psi, and auxiliary heating gas GS2 (Ion Source Gas 2) of 50 Psi.

[0076] In an embodiment of the present invention, a logical reasoning method can be used to optimize the composition ratio of the mobile phase, specifically including:

[0077] The ratio of methanol to isopropanol was used as the input variable of the model, and the elution time was used as the output;

[0078] The output membership function adopts equidistant triangular membership function, the fuzzy rule adopts IF-THEN structure, and the fuzzy reasoning logic adopts AND mode;

[0079] According to the fuzzy reasoning results, the optimal mobile phase ratio was selected within the effective range of the optimal peak elution time to achieve the optimal balance among signal intensity, retention time and background noise.

[0080] In the above exploratory experiment, the optimal mobile phase parameters determined according to the fuzzy reasoning results include: component 2 is methanol:isopropanol = 8:2.

[0081] In practical applications, the fuzzy reasoning method can be used to optimize the composition ratio of the mobile phase in combination with different actual conditions to obtain optimized parameters that meet the actual conditions.

[0082] In the embodiment of the present invention, after research and exploration, it was determined that the most preferred extractant is: isopropyl alcohol.

[0083] Specifically, in an embodiment of the present invention, before performing the assay on the biological sample, the method further includes: preparing a 2 mg / mL 1,4-benzoquinone solution with methanol; and preparing a 1000 ng / mL internal standard CoQ10-d9 with a 5% BSA solution.

[0084] Specifically, in an embodiment of the present invention, the step of extracting the analyte includes:

[0085] Take 50ul of serum, add 50ul of the benzoquinone solution, add 50ul of the internal standard, add 500ul of the extractant, shake and mix for 5 minutes, centrifuge for 5 minutes, and take 200ul of the supernatant.

[0086] In the embodiment of the present invention, an isotope internal standard (CoQ10-d9) method is used for calibration and quantitative analysis, thereby improving the anti-interference ability of the detection method to the complex matrix of clinical samples.

[0087] In a method for determining the amount of Coenzyme Q10 in biological samples, provided by an embodiment of the present invention, the standard curve exhibited excellent linearity (R² > 0.99), an average accuracy of 90.66%, and a limit of detection of 0.1 ng / mL. Recovery rates ranged from 88.6% to 99.42%, with a clinically reportable range of 50,000 ng / mL and inter- and intra-assay imprecision of <10%. Sample concentrations were stable for 3 days at room temperature, 2 weeks at 4°C, and 4 weeks at -20°C and -80°C. High concentrations of hemoglobin (0.2 mg / mL) and triglycerides (0.2 mg / mL) significantly interfered with the assay.

[0088] The embodiment of the present invention uses fuzzy logic to optimize parameters to establish an efficient, accurate, sensitive and cost-effective detection method, which can comprehensively improve the ability of LC-MS / MS to detect CoQ10. The results of the exploratory study show that the precision of the method provided by the embodiment of the present invention is significantly improved compared with similar studies. The inter-batch and intra-batch CVs are both controlled within 10%, which meets the requirements of the European Medicines Agency (EMA) "Guidelines for Validation of Bioanalytical Methods" and the Clinical Laboratory Standards Institute (CLSI) C62-A standard for high precision (imprecision <10%). This method has made significant progress in precision. In low-concentration detection, in the embodiment of the present invention, the lower limit of quantification reached 0.1 ng / mL, and the sensitivity was significantly improved compared with existing results, laying a solid foundation for improving the reliability of CoQ10 detection.

[0089] In this embodiment of the present invention, fuzzy logic's ability to process uncertain data was leveraged to optimize mobile phase selection for LC-MS / MS detection of CoQ10. Validation results showed that the deviation between the average peak time and the predicted time was only 0.63%. The effective application of fuzzy logic significantly reduced experimental time and resource consumption, improved research efficiency, and highlighted its potential for application in the biomedical field. This embodiment of the present invention not only enhances the LC-MS / MS detection capabilities of CoQ10 but also provides valuable insights for applying fuzzy logic to the detection of other fat-soluble substances and optimizing the precision and reliability of LC-MS / MS technology.

[0090] This study successfully established a new detection method by improving the accuracy and sensitivity of LC-MS / MS detection of CoQ10 and applying fuzzy logic to optimize key parameters. The method has a lower limit of quantification of 0.1 ng / mL. The optimal mobile phase (methanol and isopropanol) ratio was determined to be 8:2 through fuzzy reasoning, and the actual retention time was 1.749±0.119 min, providing a scientific basis for the optimization of fuzzy logic in detection methods and its expansion to other detection substances and methods. While significantly improving accuracy and sensitivity, this study significantly reduced research costs with the help of cutting-edge AI technology, laying a solid foundation for large-scale CoQ10 testing and medical cost control.

[0091] In combination with the above embodiments, an embodiment of the present invention further provides a kit for implementing the method for determining the amount of Coenzyme Q10 in a biological sample provided in the above embodiments.

[0092] The kit may include: 1,4-benzoquinone solution, internal standard, extractant, formic acid, methanol, isopropanol and CoQ10 standard substance.

[0093] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0094] The above describes in detail the method and kit for determining the amount of Coenzyme Q10 in a biological sample provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above examples is intended only to facilitate understanding of the method and core concept of the present invention. Furthermore, those skilled in the art will appreciate that variations in the specific implementation methods and scope of application are possible based on the concepts of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for determining the amount of coenzyme Q10 in a biological sample, characterized in that The method comprises: A biological sample to be measured is taken, a 1,4-benzoquinone solution and an internal standard are added, an extractant is added, extraction is performed, the extract is taken, filtered, and subjected to liquid chromatography tandem mass spectrometry determination; The chromatographic conditions are: A Waters C18 chromatographic column was used, and 100% B phase was used as the mobile phase for elution; the mobile phase comprised 0.01% to 0.1% component 1 and 99.9% to 99.99% component 2 in a volume ratio, wherein the component 1 was formic acid and the component 2 was methanol:isopropanol = 7-9:3-1.

2. The method for determining the amount of coenzyme Q10 in a biological sample according to claim 1, wherein During the liquid chromatography detection process, the column oven temperature is 35-50° C., and the mobile phase flow rate is 0.3-0.6 mL / min.

3. The method for determining the amount of coenzyme Q10 in a biological sample according to claim 1, wherein Mass spectrometry analysis used an APCI ion source; APCI parameters included: curtain gas CUR of 35 Psi, CAD of 7, needle current NC of 3 mA, TEM of 450°C, and spray gas GS1 of 45 Psi; The auxiliary heating gas GS2 (Ion Source Gas2) is 50Psi.

4. The method for determining the amount of coenzyme Q10 in a biological sample according to claim 1, wherein The following steps were used to optimize the ratio of components 2: The ratio of methanol to isopropanol was used as the input variable of the model, and the elution time was used as the output; The output membership function adopts equidistant triangular membership function, the fuzzy rule adopts IF-THEN structure, and the fuzzy reasoning logic adopts AND mode; According to the fuzzy reasoning results, the optimal mobile phase ratio was selected within the effective range of the optimal peak elution time to achieve the optimal balance among signal intensity, retention time and background noise.

5. The method for determining the amount of coenzyme Q10 in a biological sample according to claim 1, wherein The component 2 is methanol:isopropanol=8:

2.

6. The method for determining the amount of coenzyme Q10 in a biological sample according to claim 1, wherein The extractant is isopropyl alcohol.

7. The method for determining the amount of coenzyme Q10 in a biological sample according to any one of claims 1 to 6, characterized in that: The method further comprises: Prepare 2 mg / mL 1,4-benzoquinone solution with methanol; prepare 1000 ng / mL internal standard CoQ10-d9 with 5% BSA solution; The method comprises taking a biological sample to be measured, adding a 1,4-benzoquinone solution and an internal standard, adding an extractant, extracting, taking an extract, and filtering, including: Take 50ul of serum, add 50ul of the benzoquinone solution, add 50ul of the internal standard, shake and mix for 10 minutes, add 500ul of the extractant, shake and mix for 5 minutes, centrifuge for 5 minutes, and take 200ul of the supernatant.

8. The method for determining the amount of coenzyme Q10 in a biological sample according to claim 1, wherein The method further comprises: CoQ10 standard substance was prepared in 5% BSA solution to prepare a series of concentrations of 50, 100, 500, 1000, 2000 and 5000 ng / mL for drawing a standard curve.

9. A kit for implementing the method for determining the amount of Coenzyme Q10 in a biological sample according to any one of the preceding claims 1 to 8.

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