Method for detecting scorpion venom-induced cardiotoxicity by fusing metabonomics and ultrasonic electrocardiogram

Abstract

The invention discloses a method for detecting scorpion venom-induced cardiotoxicity by fusing metabonomics and an ultrasonic electrocardiogram, the ultrasonic electrocardiogram proves that scorpion venom has cardiotoxicity, then the change of metabolites related to cardiotoxicity is researched through serum metabonomics, and 37 different metabolites are screened out. The kit can find potential damage of scorpion venom to the heart at an early stage, has relatively high sensitivity and specificity, solves the technical problems of high sampling difficulty in traditional pathology, low sensitivity, poor specificity and long period of conventional markers, remarkably improves the timeliness and reliability of scorpion venom cardiotoxicity prediction, and has a good application prospect. And a scientific basis is provided for subsequent preclinical safety evaluation and clinical medication monitoring of scorpion venom preparations.

Description

Technical Field

[0001] This invention relates to the field of scorpion venom toxicity assessment, specifically to a method for assessing scorpion venom cardiotoxicity using metabolomics combined with echocardiography. Background Technology

[0002] Scorpion venom is a biological toxin second only to snake venom in toxicity. It is mainly composed of non-protein and protein components and possesses complex physiological and pharmacological activities. Clinically, scorpion venom can be used to treat tumors and pain, and it also has anti-epileptic, anti-thrombotic, anti-inflammatory, and anti-rheumatic effects.

[0003] The safety of scorpion venom remains a core evaluation indicator that must be addressed for its clinical application. Both clinical and experimental studies have confirmed that the neurotoxins, cytotoxic peptides, and enzymes in scorpion venom can directly act on ion channels in myocardial cell membranes, inducing arrhythmias, decreased contractility, and even cardiogenic shock. Literature reports that early perfusion of isolated guinea pig hearts with scorpion venom can increase myocardial contractility, accompanied by arrhythmias; subsequently, fluctuations in heart rate, myocardial contractility, and coronary blood flow occur; and in the late stage, bradycardia develops.

[0004] Therefore, it is necessary to accurately assess the cardiotoxicity of scorpion venom to improve the safety of medication use.

[0005] Current technologies for assessing the cardiotoxicity of scorpion venom primarily rely on traditional pathology or single biomarker detection. Pathological examination depends on biopsy or autopsy, which is difficult, invasive, and cannot achieve rapid, dynamic tracking. Serum cardiac enzyme detection can determine myocardial ischemia and necrosis or cell membrane permeability. Cardiac troponin T (cTnT) and cTnI are commonly used to evaluate myocardial injury, while BNP, NT-proBNP, and ANP are mainly used to evaluate heart failure.

[0006] However, traditional cardiotoxicity indicators mostly only change significantly after severe cardiac damage has occurred. Utilizing high-throughput technologies to detect drug-induced cardiotoxicity earlier is crucial for early prediction. Metabolomics techniques offer high sensitivity and specificity for identifying early biomarkers, but currently lack standardized analytical procedures and specific combinations of metabolic biomarkers for scorpion venom cardiotoxicity.

[0007] It is necessary to develop a standardized process that integrates dynamic monitoring of small animal echocardiography with serum metabolomics analysis to screen for specific metabolic biomarkers of scorpion venom cardiotoxicity and improve the timeliness and sensitivity of predictions. Summary of the Invention

[0008] The purpose of this invention is to provide a method for detecting scorpion venom cardiotoxicity by integrating metabolomics and echocardiography, to screen differential metabolites, and to achieve early, accurate, and non-invasive assessment of scorpion venom cardiotoxicity.

[0009] The technical solution adopted in this invention is: A method for detecting cardiotoxicity caused by scorpion venom by integrating metabolomics and echocardiography, the method comprising the following steps: (1) Scorpion venom preparations were administered to mice to establish a mouse model of scorpion venom cardiotoxicity, and scorpion venom model group and blank control group were constructed respectively; (2) After administration, mice were subjected to echocardiography to measure heart rate (HR), left ventricular end-diastolic interventricular septum thickness (IVSd), left ventricular posterior wall end-diastolic thickness (LVPWd), fractional shortening (FS), and ejection fraction (EF). The scorpion venom model group and the blank control group were statistically compared, and P < 0.05 was considered to be significant. (3) Take serum samples from the scorpion venom model group and the blank control group, perform metabolomics analysis, and screen for significantly different metabolites.

[0010] Furthermore, the metabolomics analysis in step (3) includes: using UPLC-TOF / MS detection, performing multidimensional statistical analysis on the detection data, including PCA, PLS-DA and OPLS-DA, and screening for significantly differential metabolites.

[0011] Furthermore, step (1) can be performed as follows: C57BL / 6 SPF grade mice were used as experimental subjects, with half males and half females. After acclimatization, they were administered scorpion venom orally as the scorpion venom model group, while the blank control group was given an equal amount of physiological saline.

[0012] Furthermore, the dosage is usually 10-20 mg / kg, preferably 16 mg / kg.

[0013] Step (2) is preferably performed as follows: Two hours after administration, mice were anesthetized with inhaled isoflurane. Using a ZC3 SC1 small animal ultrasound imaging system, heart rate (HR), left ventricular end-diastolic interventricular septum thickness (IVSd), left ventricular posterior wall end-diastolic thickness (LVPWd), fractional shortening (FS), and ejection fraction (EF) were measured continuously for at least three cardiac cycles, and the average values ​​were taken. The scorpion venom model group and the blank control group were statistically compared, and a p-value < 0.05 was considered statistically significant.

[0014] Preferably, in step (3), the serum sample is processed according to the following steps before being subjected to UPLC-TOF / MS detection: Serum samples were added to a mixture of methanol and acetonitrile at low temperature, vortexed, centrifuged, and the supernatant was lyophilized. The supernatant was then reconstituted with a mixture of acetonitrile, methanol, and water, centrifuged again, and the supernatant was used for UPLC-TOF / MS detection.

[0015] Preferred serum samples were processed according to the following steps before UPLC-TOF / MS detection: Take 100 μL of serum and add it to 600 μL of a solvent with a methanol-acetonitrile volume ratio of 1:1 at -20 ℃. Vortex and centrifuge, take the supernatant and freeze dry. Reconstitute with a mixed solvent with an acetonitrile-methanol-water volume ratio of 80:20:100. Centrifuge and take the supernatant for UPLC-TOF / MS detection.

[0016] The parameters of the UPLC-TOF / MS are: Chromatographic conditions: ACQUITY UPLC BEH C18 column; injection plate temperature: 8 ℃; column temperature: 40 ℃; mobile phase: A: 0.1% formic acid in acetonitrile solution, B: 0.1% formic acid in aqueous solution; injection volume: 3 μL; Gradient elution: 0–1 min, 95% B; 1–5 min, 95%–55% B; 5–8 min, 8–15 min, 55%–35% B; 15–18 min, 0% B; Time-of-flight mass spectrometry was performed using a TurboIonSpray ion source in ESI positive and negative ion scanning mode. Specific conditions were: Gas1: 55 psi, Gas2: 55 psi, CUR: 35 psi, ion source temperature: 500 ℃, and ion spray voltage fluctuation (ISVF): 5500 V / -4500 V (both positive and negative ion modes).

[0017] Preferably, the multidimensional statistical analysis is performed according to the following steps: Raw mass spectrometry data were imported into metabolomics processing software, and baseline filtering, peak identification, peak integration, retention time correction, peak alignment, and normalization were performed sequentially to obtain a data matrix containing retention time, mass-to-charge ratio, and peak intensity information. SIMCA-P 14.0 software was used to perform multidimensional statistical analysis on the data matrix, including PCA, PLS-DA, and OPLS-DA. Ions that simultaneously met the criteria of VIP>1.0 and p<0.05 were selected as significantly differentially expressed ions. Significantly differentially expressed ions were analyzed and identified using OSI / SMMS and HMDB, with a mass error set to be less than 5 ppm, and differentially expressed metabolites were identified. These differentially expressed metabolites were then imported into MetaboAnalyst 5.0 for metabolic pathway analysis.

[0018] Furthermore, QC samples are typically prepared during multidimensional statistical analysis. Equal volumes of mixed serum are used to prepare QC samples for system stability monitoring, requiring that the RSD of each ion peak area in the QC sample be <5%.

[0019] Following the above method, 37 differential metabolites were obtained through screening, of which 27 were in positive ion mode and 10 were in negative ion mode.

[0020] Furthermore, metabolic pathway analysis revealed that the differentially metabolites involved pathways such as α-linolenic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, steroid hormone biosynthesis and linoleic acid metabolism, among which α-linolenic acid was a key early warning biomarker.

[0021] The present invention also provides differential metabolites for evaluating the cardiotoxicity of scorpion venom, said differential metabolites including one or more differential metabolites as shown in Tables 1 and 2, preferably α-linolenic acid.

[0022] The present invention also provides the application of the differential metabolites in the preparation of an in vitro diagnostic kit for detecting scorpion venom-induced cardiotoxicity.

[0023] Table 1. List of differentially metabolites under positive ion mode

[0024] Table 2. List of differentially metabolites under negative ion mode

[0025] The beneficial effects of this invention are as follows: This invention integrates small animal echocardiography with serum metabolomics to establish a standardized evaluation process for scorpion venom cardiotoxicity. Echocardiography can non-invasively detect cardiac function parameters such as heart rate (HR), intravenous systolic blood pressure (IVSd), latent pulse wave (LVPWd), heart failure (FS), and ejection fraction (EF), allowing for real-time monitoring of changes in cardiac structure and function. This invention utilizes echocardiography to confirm the cardiotoxicity of scorpion venom, and then studies changes in cardiotoxicity-related metabolites through serum metabolomics: serum samples were collected for UPLC-TOF / MS analysis, and 37 differentially expressed metabolites were screened using PCA, PLS-DA, and OPLS-DA, with α-linolenic acid identified as a key early warning biomarker. This invention can detect potential cardiac damage caused by scorpion venom at an early stage, exhibiting high sensitivity and specificity, significantly improving the timeliness and reliability of predicting scorpion venom cardiotoxicity.

[0026] This invention addresses the technical challenges of traditional pathological sampling, such as high difficulty, low sensitivity, poor specificity, and long processing times of conventional biomarkers. It enables early, accurate, and non-invasive detection of cardiotoxicity caused by scorpion venom, providing a scientific basis for the preclinical safety evaluation and clinical drug monitoring of subsequent scorpion venom preparations. Attached Figure Description

[0027] Figure 1 This is a TIC chromatogram under LC1 gradient elution conditions in positive ion mode.

[0028] Figure 2 This is a TIC chromatogram under LC2 gradient elution conditions in positive ion mode.

[0029] Figure 3This is a TIC chromatogram under LC3 gradient elution conditions in positive ion mode.

[0030] Figure 4 This is a TIC chromatogram under LC1 gradient elution conditions in negative ion mode.

[0031] Figure 5 This is a TIC chromatogram under LC2 gradient elution conditions in negative ion mode.

[0032] Figure 6 This is a TIC chromatogram under LC3 gradient elution conditions in negative ion mode.

[0033] Figure 7 Comparison of echocardiogram results of mice.

[0034] Figure 8 The figures show the metabolomics results of mouse serum in the blank group and scorpion venom group under different modes. Figure A is the PCA figure, Figure B is the PLS-DA figure, Figure C is the OPLS-DA figure, and Figure D is the permutation test result figure. POS represents the positive ion mode and NEG represents the negative ion mode.

[0035] Figure 9 A diagram showing the results of enriching differential metabolites into metabolic pathways. Detailed Implementation

[0036] The technical solution of the present invention will be further described below with reference to specific embodiments, but the scope of protection of the present invention is not limited thereto.

[0037] The instruments and equipment selected in this embodiment The instruments and equipment selected in this embodiment include: LC3600N, pump, autosampler, column oven, nanoliter liquid chromatography workstation software, quadrupole time-of-flight mass spectrometer, low-temperature high-speed centrifuge, vacuum centrifuge concentrator, electronic balance, IKA micro vortex mixer, small animal ultrasound imaging system, etc.

[0038] 2. Experimental methods used in this embodiment 2.1 Animal model construction.

[0039] A standardized cardiotoxicity model was established using C57BL / 6 mice (half male and half female) orally administered with 16 mg / kg scorpion venom (suspended in 0.05% CMC-Na).

[0040] The specific steps are as follows: Twenty SPF-grade C57BL / 6 mice, half male and half female, weighing 18-20 g.

[0041] Lighting: 12 h / 12 ​​h alternation of light and dark, ambient temperature 20~24℃, relative humidity 50%~65%, free access to food and water during the rearing period.

[0042] Two days after acclimatization, 10 mice (half male and half female) were given toad venom at 16 mg / kg. The remaining 10 mice served as the control group and were given an equal volume of physiological saline.

[0043] Fasting is allowed for 12 hours before administration, but water is permitted. The dosage is prepared into a suspension of the corresponding concentration using 0.05% sodium carboxymethyl cellulose (CMC-Na) solution. Shake well before administration. Administer the same volume of the suspension by gavage according to different concentrations. The minimum dosage of toad venom is calculated from the clinical dosage.

[0044] Two and a half hours after administration of the drug, the patient was anesthetized with isoflurane. Blood was collected from the posterior orbital venous plexus. After collection, the blood samples were placed at room temperature and allowed to coagulate. The samples were then centrifuged at 3500 r / min for 10 min at 4°C to separate the supernatant serum, which was then stored at -80°C. The serum was analyzed by UPLC-TOF / MS.

[0045] 2.2 Echocardiography of the mouse heart Two hours after administration, mice were anesthetized with isoflurane, their left anterior chest was shaved, and they were fixed in a supine position. The following values ​​were measured using the ZC3-SCI small animal ultrasound imaging system: heart rate (HR), left ventricular end-systolic interventricular septal thickness (IVSs), left ventricular end-diastolic interventricular septal thickness (IVSd), left ventricular end-diastolic diameter (LVIDd), left ventricular posterior wall end-diastolic thickness (LVPWd), left ventricular posterior wall end-systolic thickness (LVPWs), left ventricular end-diastolic volume (LVEDV), left ventricular systolic volume (LVESV), short axis ratio (FS), and ejection fraction (EF). The values ​​of each index were measured for three consecutive cardiac cycles and the average value was taken.

[0046] The corresponding formula is as follows: FS = (LVIDd - LVDIDs) / LVIDd × 100%; EF = (LVEDV - LVESV) / ​​LVEDV × 100%; LVEDV = 7 × Dd³ / (2.4 + Dd); LVESV = 7 × Ds³ / (2.4 + Ds). Echocardiography and cardiac function were recorded in mice after drug administration.

[0047] 2.3 Serum Sample Pretreatment Methods Sample Information: This project uses two groups of samples, each with 10 biological replicates, for a total of 20 medical (animal) metabolomics tests and analyses. Quality Control (QC) Samples: Equal volumes of samples are mixed to prepare QC samples. QC samples are used to determine the instrument status and balance the chromatography-mass spectrometry system before sample injection, and to evaluate system stability throughout the experiment.

[0048] Take 100 μL of the aliquoted sample, thaw it on ice, add 600 μL of methanol / acetonitrile (1:1) pre-chilled at -20 ℃, vortex for 60 s, and centrifuge at 14000 r for 20 min at 4 ℃. Transfer the supernatant to a 1.5 mL centrifuge tube and freeze-dry using a FreeZone freeze-drying apparatus. Reconstitute the dried sample powder with 1:1 (v / v) acetonitrile / methanol (80 / 20, v / v) and ultrapure water, and centrifuge at 14000 r for 20 min at 4 ℃. Transfer the supernatant to a sample vial for LC-MS analysis.

[0049] 2.4 Data Processing and Analysis The raw mass spectrometry data were imported into metabolomics processing software, and baseline filtering, peak identification, peak integration, retention time correction, peak alignment, and normalization were performed sequentially to obtain a data matrix containing retention time, mass-to-charge ratio, and peak intensity information. The data matrix was then subjected to multidimensional statistical analysis using SIMCA-P 14.0 (Umetrics, Umea, Sweden), including unsupervised principal component analysis (PCA), supervised partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) to obtain variable importance projection values ​​(VIPs).

[0050] 2.5 Metabolite identification and metabolic pathway enrichment Unidimensional statistical tests were performed on each variable, and ions that simultaneously satisfied VIP>1.0 and p<0.05 were selected as significantly differentially expressed ions. These significantly differentially expressed ions were then identified and characterized using the small molecule metabolite rapid identification software OSI / SMMS and HMDB, with a mass error set to less than 5 ppm. The differentially expressed metabolites were then imported into MetaboAnalyst 5.0 for metabolic pathway analysis.

[0051] 3. Experimental Results 3.1 Optimization of chromatographic conditions Chromatographic conditions: ACQUITY UPLC BEH C18 (100×2.1 mm, 1.7 μm) column injection plate temperature: 8℃; column temperature: 40℃; mobile phase: 0.1% formic acid acetonitrile (A) - 0.1% formic acid water (B); injection volume: 3 μL.

[0052] Time-of-flight mass spectrometry was performed using a TurboIonSpray ion source in ESI positive and negative ion scanning mode. Specific conditions were: Gas1: 55 psi, Gas2: 55 psi, CUR: 35 psi, ion source temperature: 500 ℃, and ion spray voltage fluctuation (ISVF): 5500 V / -4500 V (both positive and negative ion modes).

[0053] The separation conditions were optimized using QC total ion chromatogram (TIC) of samples for the separation and detection of metabolic components. LC1 gradient elution conditions: 0–1 min, 95% B; 1–6 min, 95%–55% B; 6–8 min, 8–16 min, 55%–35% B; 16–18 min, 0% B; LC2 gradient elution conditions: 0–1 min, 95% B; 1–4 min, 95%–55% B; 4–8 min, 8–16 min, 55%–35% B; 16–18 min, 0% B; LC3 gradient elution conditions: 0–1 min, 95% B; 1–5 min, 95%–55% B; 5–8 min, 8–15 min, 55%–35% B; 15–18 min, 0% B.

[0054] The results are as follows Figure 1-6 As shown, the LC3 gradient elution condition has better separation than the LC1 and LC2 gradient elution conditions.

[0055] Ultimately, LC3 gradient elution was chosen as the sample detection condition.

[0056] 3.2 Results of echocardiography of the mouse heart The results of mouse echocardiogram parameters are shown in Table 3 and Figure 7 As shown, the results indicated that compared with the blank control group, the left ventricular heart rate (HR) was significantly decreased in the scorpion venom model group, indicating that the scorpion venom model group exhibited heart failure; the left ventricular intraventricular systolic blood volume (IVSd) was significantly increased. P <0.05), IVSd / LVPWd and IVSs / LVPWs increased significantly ( P <0.01), indicating that the scorpion venom model group had myocardial hypertrophy.

[0057] HR / Bpm (Heart Rate): Heart rate, measured in beats per minute.

[0058] IVSs / cm (Interventricular Septum thickness at end-Systole / centimeter): End-systolic septal thickness (cm) IVSd / cm (Interventricular Septum thickness at end-Diastole / centimeter): End-diastolic interventricular septum thickness (cm) LVIDd / cm (Left Ventricular Internal Dimension at end-Diastole / centimeter): Left ventricular diameter at end-diastole (cm) LVPWd / cm (Left Ventricular Posterior Wall thickness at end-Diastole / centimeter): Thickness of the left ventricular posterior wall at end-diastole (in centimeters). LVPWs / cm (Left Ventricular Posterior Wall thickness at end-Systole / centimeter): Thickness of the left ventricular posterior wall at end-systole (cm) LVEDV(Teich) / ml (Left Ventricular End-Diastolic Volume by Teichholzmethod / milliliter): Teichholz method left ventricular end-diastolic volume (ml). LVESV(Teich) / ml (Left Ventricular End-Systolic Volume by Teichholzmethod / milliliter): Teichholz method left ventricular end-systolic volume (ml). FS% (Fractional Shortening / percent): A basic indicator for assessing left ventricular systolic function by the percentage of shortening. Calculation formula: FS% = [(LVIDd - LVIDs) / LVIDd] × 100%. It represents the percentage reduction in left ventricular diameter during systole relative to diastole. Normal values ​​are generally between 25-45%. A decreased value suggests weakened systolic function.

[0059] EF (Teichholz Ejection Fraction / percent): The most important indicator for assessing overall left ventricular systolic function. It represents the percentage of blood pumped by the left ventricle during each heartbeat relative to its total end-diastolic volume. Calculation formula: EF% = [(LVEDV - LVESV) / ​​LVEDV] × 100%. Here, LVEDV and LVESV are calculated using the Teichholz formula. Normal values ​​are typically ≥55%. A decrease (e.g., <50% or <40%) suggests heart failure.

[0060] IVSd / LVPWd (Ratio of IVSd to LVPWd): The ratio of end-diastolic interventricular septal thickness to end-diastolic left ventricular posterior wall thickness. This ratio is used to assess whether the thickening of the interventricular septum and the left ventricular posterior wall is symmetrical. In concentric hypertrophy caused by hypertension, the ratio is usually close to 1 (e.g., 0.9-1.1). A ratio significantly greater than 1.3 (e.g., ≥1.5) is one of the important criteria for diagnosing hypertrophic cardiomyopathy (especially asymmetric interventricular septal hypertrophy).

[0061] IVSs / LVPWs (Ratio of IVSs to LVPWs): The ratio of the thickness of the interventricular septum at end-systole to the thickness of the left ventricular posterior wall at end-systole.

[0062] This invention first uses echocardiography to confirm that scorpion venom has cardiotoxicity, and then uses metabolomics to reveal changes in metabolites related to cardiotoxicity.

[0063] Table 3. Echocardiographic parameters of mice ( x ± s (n=10)

[0064] 3.3 Metabolomics Data Analysis of Scorpion Venom Serum Samples 3.3.1 Principal Component Analysis (PCA) Principal Component Analysis (PCA) is an unsupervised data analysis method that linearly recombines all identified metabolites to form a new set of composite variables. Several composite variables are then selected based on the problem being analyzed to reflect as much information as possible from the original variables, thus achieving dimensionality reduction. Furthermore, PCA on metabolites can also reflect the overall variability between and within sample groups.

[0065] PCA was used to observe the overall distribution trend among all samples and identify potential points of dispersion. PCA analysis was performed using the control group and the disease group as example groups. The PCA score plot is shown below. Figure 8 A. Data obtained from UHPLC chromatographic separation of samples showed a clear separation trend between samples in both positive and negative ion modes on PC1 and PC2 plots, indicating significant differences between the control group and the model group at the metabolic level.

[0066] 3.3.2 Partial Least Squares Discriminant Analysis (PLS-DA) Partial Least Squares Discriminant Analysis (PLS-DA) is a statistical method related to principal component regression, but instead of finding the hyperplane that maximizes the variance between the response and independent variables, it projects the predictor and observed variables into a new space to find a linear regression model. The results are shown in [link to results]. Figure 8 B.

[0067] 3.3.3 Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) Unlike Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) is a supervised statistical method for discriminant analysis. This method uses partial least squares regression to establish a model relating metabolite expression levels to sample categories, thereby predicting sample categories. This method modifies partial least squares discriminant analysis (PLS-DA) by filtering out noise irrelevant to classification information, improving the model's analytical power and effectiveness. Results are shown in [Figure / Reference]. Figure 8 C.

[0068] The permutation test is a nonparametric method used to assess the significance of a statistical model. It assesses the significance of observed statistical results by randomly rearranging the data to simulate the distribution of the null hypothesis (i.e., no association between variables). The results are shown in [Figure number missing]. Figure 8 D 3.3.4 Identification of metabolites showing significant differences between the control group and the model group In this experiment, metabolites with a p-value < 0.05 and a p-value > 1 were considered to have significant differences using univariate statistical analysis. The OSI / SMMS software was used for metabolite structure identification, and the specific identification results are shown in Tables 4 and 5. A total of 37 differentially expressed metabolites were identified in this study, including 27 in the positive ion mode and 10 in the negative ion mode.

[0069] 3.3.5 Differential Metabolite KEGG Pathway Analysis Metabolic pathway analysis was performed on the differentially metabolites obtained. Figure 9 Table 6 shows the relevant metabolic pathways and their specific information. Combined with Raw p < 0.05 and Impact > 0.1, the results indicate that the differentially metabolites mainly involve metabolic pathways such as α-linolenic acid metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, steroid hormone biosynthesis, and linoleic acid metabolism. Based on the metabolic pathway analysis, α-linolenic acid is a key early warning differentially metabolite.

[0070] Table 4. List of differentially metabolites under positive ion mode

[0071] Table 5. List of Differential Metabolites under Negative Ion Mode

[0072] Table 6 Results of differential metabolite enrichment in metabolic pathways

Claims

1. A method for detecting scorpion venom-induced cardiotoxicity by integrating metabolomics and echocardiography, characterized in that... The method includes the following steps: (1) Scorpion venom preparations were administered to mice to establish a mouse model of scorpion venom cardiotoxicity, and scorpion venom model group and blank control group were constructed respectively; (2) After administration, mice were subjected to echocardiography to measure heart rate (HR), left ventricular end-diastolic interventricular septum thickness (IVSd), left ventricular posterior wall end-diastolic thickness (LVPWd), fractional shortening (FS), and ejection fraction (EF). The scorpion venom model group and the blank control group were statistically compared, and a P < 0.05 was considered statistically significant. (3) Take serum samples from the scorpion venom model group and the blank control group, perform metabolomics analysis, and screen for significantly different metabolites.

2. The method as described in claim 1, characterized in that: The metabolomics analysis in step (3) includes: using UPLC-TOF / MS to detect serum samples, performing multidimensional statistical analysis on the detection data, and screening for significantly different metabolites.

3. The method as described in claim 2, characterized in that: In step (3), the serum sample is processed according to the following steps and then subjected to UPLC-TOF / MS detection: Serum samples were added to a mixture of methanol and acetonitrile at low temperature, vortexed, centrifuged, and the supernatant was lyophilized. The supernatant was then reconstituted with a mixture of acetonitrile, methanol, and water, centrifuged again, and the supernatant was used for UPLC-TOF / MS detection.

4. The method as described in claim 2, characterized in that... The parameters of the UPLC-TOF / MS are: Chromatographic conditions: ACQUITY UPLC BEH C18 column; mobile phase: A: 0.1% formic acid in acetonitrile solution, B: 0.1% formic acid in aqueous solution; Gradient elution: 0–1 min, 95% B; 1–5 min, 95%–55% B; 5–8 min, 8–15 min, 55%–35% B; 15–18 min, 0% B; Time-of-flight mass spectrometry was performed using a TurboIonSpray ion source in ESI positive and negative ion scanning mode; ISVF: 5500 V / -4500 V.

5. The method as described in claim 2, characterized in that: The multidimensional statistical analysis was performed according to the following steps: The raw mass spectrometry data were imported into metabolomics processing software, and baseline filtering, peak identification, peak integration, retention time correction, peak alignment, and normalization were performed sequentially to obtain a data matrix containing retention time, mass-to-charge ratio, and peak intensity information. PCA, PLS-DA, and OPLS-DA were then performed on the data matrix, and ions that simultaneously met the criteria of VIP > 1.0 and p < 0.05 were selected as significantly differentially expressed ions. Significantly different ions were analyzed and identified, with a mass error set to be less than 5 ppm, and differential metabolites were identified; metabolic pathway analysis was performed on the differential metabolites.

6. The method as described in claim 1, characterized in that: Alpha-linolenic acid is a warning marker for cardiotoxicity caused by scorpion venom.

7. Evaluate differentially metabolites of scorpion venom that induce cardiotoxicity, characterized by: The differential metabolites include one or more of the differential metabolites listed in Tables 1 and 2: Table 1. List of differentially metabolites under positive ion mode Table 2. List of differentially metabolites under negative ion mode 8. The differential metabolites for evaluating the cardiotoxicity of scorpion venom as described in claim 7, characterized in that: The differential metabolite is α-linolenic acid.

9. The use of the differential metabolites as described in claim 7 or 8 in the preparation of an in vitro diagnostic kit for detecting scorpion venom-induced cardiotoxicity.

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