Method for detecting saxitoxin biological activity based on the effect of binding to receptors of nerve cells

Abstract

The application discloses a saxitoxin bioactivity detection method based on a nerve cell receptor binding effect, and belongs to the technical field of bioactivity detection. The application can effectively deduct background interference and system error, establish a stable standard product protection rate-concentration dose-effect curve, and realize accurate quantification of the saxitoxin bioactivity equivalent, by setting a multiple control system and a standardized calculation formula. Through dynamic correction of a cell damage model, unified collection of multi-dimensional activity signals, multi-level background deduction, and strict data verification rules, the detection fluctuation is significantly reduced, the high repeatability of batches is ensured, the method has strong reliability, and the quality control requirements of bioactivity detection can be met. The application overcomes the defects of low standardization, poor reproducibility, inaccurate quantification and dependence on animal experiments in the prior art, and provides an efficient, accurate and environmentally-friendly standardized scheme for saxitoxin bioactivity detection.

Description

Technical Field

[0001] This invention relates to the field of bioactivity detection technology, and in particular to a method for detecting the bioactivity of scutellarin based on the receptor binding effect of nerve cells. Background Technology

[0002] Paralytic shellfish toxins, primarily produced by dinoflagellates and cyanobacteria, can accumulate in shellfish and other aquatic products, and are transmitted to humans through the food chain, causing severe neurological paralysis and even death. For example, Chinese patent application CN201410369789.8 discloses a method for detecting paralytic shellfish toxins. This method utilizes a mouse neuroma cell impedance sensor. First, neuro2a cells are seeded into the cell culture wells of the sensor chip for culture. Then, the test solutions are added to the cell culture wells containing ouabain and veratrine solutions. By detecting the CI value of each cell culture well after adding the test solutions, the content of paralytic shellfish toxins in the test solutions is determined based on the change in CI value. This method directly uses cells as the detection carrier, is simple to operate, and is inexpensive.

[0003] However, although the aforementioned patent represents a significant improvement over the current national standard detection method, the mouse biological method, in terms of detection limit, the following problems still exist: In existing technologies, the standardization of cell damage models is insufficient, and the differences in cell states between different batches lead to poor reproducibility of results; there is a lack of systematic sample purification steps, and matrix interference can easily cause false positives or false negatives; and no standardized dose-response fitting model has been established, making it impossible to accurately quantify the bioactivity equivalent of toxins. Summary of the Invention

[0004] The purpose of this invention is to provide a method for detecting the bioactivity of salicornin based on the receptor binding effect of nerve cells, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: Methods for detecting the bioactivity of shifanatoxin based on the receptor binding effect of neural cells include: Collect the original sample to be tested and perform low-temperature homogenization and crushing treatment to obtain a homogenized slurry; The homogenized slurry was subjected to centrifugation, extraction, buffer replacement, and osmotic pressure calibration in sequence to obtain purified toxin components; Neurons expressing voltage-gated sodium channels were cultured to form a monolayer of neuron cells, and sodium channel activators and sodium pump inhibitors were added sequentially for incubation to construct a neuron cell response system. The purified toxin components were sequentially and quantitatively added to the nerve cell reaction system, and a control group was set up simultaneously. Based on the specific targeting binding characteristics of the toxin to nerve cell voltage-gated sodium ion channel receptor, a dose-response relationship between toxin concentration and cell activity was established. Cell activity was detected in each group of neural cell systems that completed the specific binding reaction, and activity characterization signals of each group of neural cell systems were obtained. Cell viability and the specific protective rate of salicornin were calculated to obtain standardized quantitative data characterizing the protective effect of the toxin. Cell viability and specific protective rate were calculated using the following formulas:

[0006] in, Cell viability; The absorbance of the cell pores in the experimental group of the toxin to be tested; The absorbance of the negative control blank well is used to subtract background interference from the solution itself; The absorbance of the activated damage control group was used as a baseline for total cell damage.

[0007] in, The specific protective rate of scleroderma toxin; Cell viability of the toxin group to be tested; To improve cell viability in the damage control group; Based on the dose-response relationship between standardized quantitative data and toxin concentration, a dose-response model of standard protection rate-concentration curve was constructed to calculate the bioactivity equivalent of sparganin in the test sample. The calculation results are compared with the preset activity determination threshold to determine the biological activity level of the shifang clam toxin and generate a test report.

[0008] Furthermore, the specific preparation process for obtaining the purified toxin component includes: Collect the original sample to be tested, classify and process it according to the sample morphology, and obtain a homogeneous slurry or liquid initial test solution. The homogeneous slurry or initial liquid test solution is subjected to segmented gradient centrifugation. The supernatant after low-speed centrifugation is collected, and the supernatant is then subjected to high-speed centrifugation to obtain the original clear liquid phase. Add an equal volume of polar extraction system to the clear liquid stock solution, and selectively extract based on the strong polarity and water solubility of scimitar toxin. Repeat the extraction operation 1-2 times to obtain crude purified toxin extract. The crude purified toxin extract was subjected to ultrafiltration replacement treatment to replace it with a physiological buffer system adapted to the in vitro culture of nerve cells; The pH value and osmolality of the retentate from the physiological buffer system after replacement were measured, and the pH value and osmolality of the retentate were adjusted to the preset target range using the corresponding buffer solution. The physiologically calibrated toxin stock solution was serially diluted using cell reaction buffer, and the serially diluted samples were stored at low temperature and protected from light to obtain purified toxin components.

[0009] Furthermore, the construction of the neural cell response system also includes: after incubation, detecting the degree of damage to the neural cell response system, measuring the actual cell damage rate, and if the actual cell damage rate deviates from the preset standard damage range, adjusting the incubation parameters according to the deviation, and reconstructing the neural cell response system until the actual cell damage rate is within the preset standard damage range.

[0010] Furthermore, the incubation parameters are adjusted based on the deviation, specifically including: When the actual cell damage rate is higher than the upper limit of the preset standard damage range, it indicates excessive damage. In this case, the incubation time should be shortened or the incubation temperature should be lowered. When the actual cell damage rate is lower than the lower limit of the preset standard damage range, it indicates insufficient damage, and the incubation time should be extended or the incubation temperature increased. The larger the deviation, the greater the corresponding correction magnitude. The deviation is characterized by the ratio of the difference between the actual cell damage rate and the center value of the preset standard damage interval to the interval width. The correction magnitude is expressed as a proportion of the original duration or original temperature. The duration correction proportion is positively correlated with the deviation proportion, and the absolute value of the temperature correction is positively correlated with the deviation proportion. After each correction, the damage level is re-detected. If the current actual cell damage rate still deviates, it is corrected again until the damage rate falls within the preset standard damage range.

[0011] Furthermore, the control group includes: an activation damage control, a total damage control, a standard toxin gradient control, a negative control, and a positive control; wherein, the activation damage control is a cell system containing sodium channel activators and sodium pump inhibitors but without salivarius toxin; the total damage control is a cell system containing only sodium pump inhibitors and without sodium channel activators; the standard toxin gradient control is a cell system containing salivarius toxin standards at known concentration gradients; the negative control is a blank well containing only the highest concentration of the test sample working solution without cells; and the positive control is a cell system containing a fixed concentration of salivarius toxin standards.

[0012] Furthermore, the specific process for cell viability testing includes: All groups of neural cell systems that completed the specific binding reaction were uniformly cleaned and balanced, and the signal acquisition environment temperature, acquisition time, signal gain and sampling range were uniformly set to obtain activity characterization signals. Simultaneously collect blank and damage background signals of the neural cell system in each group, distinguish toxin-specific protective signals from environmental noise and cellular background fluctuation signals, and subtract interference signals in turn based on the distinction results; Based on the activity characterization signal after interference calibration, a standardized raw dataset is obtained. According to the preset data processing rules, baseline calibration, outlier data removal, and global normalization are performed to generate a standardized activity signal dataset.

[0013] Furthermore, the generation of the standardized active signal dataset also includes: Based on the preset gradient response matching and intra-group dispersion dual data verification rules, the collected multi-dimensional activity signals are subjected to secondary screening. Each signal data is compared with a preset normal fluctuation range, gradient response pattern, and discrete coefficient threshold to determine the validity of the data and filter out valid signal data. The standardized active signal dataset is updated based on effective signal data and used for calculating cell viability, the specific protection rate of salicornin, and dose-response model fitting.

[0014] Furthermore, the construction of the standard protection rate-concentration curve dose-effect model specifically includes: Based on the updated standardized active signal dataset, and by combining the gradient concentrations of the shifang jiu toxin standard with the corresponding specific protection rates, a dose-response curve of the standard protection rate versus the toxin concentration was constructed. Extract the curve fitting correlation coefficient and residual distribution parameters, and compare them with the preset model qualification threshold to judge the model fitting effectiveness. When the model fitting effectiveness meets the preset fitting standard, determine the upper and lower plateau values ​​of the curve, the half effective concentration and the Hill slope as key target parameters, and generate a standardized dose-response fitting model. The standardized specific protection rate of the test samples corresponding to each dilution gradient is input into the standardized dose-response fitting model, and the apparent half-effective concentration of scimitar toxin in the test samples is obtained by inverse solution. Obtain the standard activity value of the same batch of salicornin standard, and combine it with the sample pretreatment dilution factor and extraction enrichment factor to obtain the bioactivity equivalent of salicornin for each dilution gradient of the test sample.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention constructs a multiple control system including activation damage control, total damage control, standard toxin gradient control, negative control, and positive control. Combined with standardized calculation formulas for cell viability and specific protection rate, it effectively eliminates systematic errors caused by differences in cell state between different experimental batches and interference from sample matrix. At the same time, it uses four-parameter logistic nonlinear fitting to construct a standard protection rate-concentration curve, establishing a stable dose-response relationship, which can accurately quantify the bioactive equivalent of salicornin in the test sample.

[0016] 2. This invention significantly reduces intra- and inter-batch detection fluctuations by standardizing the regulation of cell damage state, and by uniformly acquiring multi-dimensional activity signals, subtracting background data at multiple levels, removing abnormal data, and performing dual data verification. This ensures the repeatability and intermediate precision of the method. Furthermore, the spiked recovery verification further demonstrates that this method has high accuracy and can meet the stringent quality control requirements of bioactivity detection methods.

[0017] 3. This invention uses in vitro cultured nerve cells as a detection carrier. It is also applicable to various environmental sample matrices such as shellfish tissue, water, and sediment. The pretreatment process is highly standardized and easy to promote and standardize in different laboratories. Attached Figure Description

[0018] Figure 1 This is a flowchart of the bioactivity detection method for safflower toxin of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 The present invention provides the following technical solutions: Methods for detecting the bioactivity of shifanatoxin based on the receptor binding effect of neural cells include: Raw samples of shellfish water, shellfish tissue, or water sediments awaiting testing are collected and subjected to low-temperature homogenization and crushing to obtain a homogenized slurry; The homogenized slurry was subjected to centrifugation, extraction, buffer replacement, and osmotic pressure calibration in sequence to remove interfering components and obtain purified toxin components; Neurons expressing voltage-gated sodium channels were cultured to form a monolayer of neurons. Sodium channel activators and sodium pump inhibitors were added sequentially for incubation. The first incubation was performed at a first temperature to induce the sodium channels to enter a continuously open state. The incubation temperature was then lowered to a second temperature for a second incubation to homogenize the degree of cell damage and maintain it within a preset standardized damage range. This allowed the cells to be in a standardized and stable damage state, thus constructing a neuronal response system that is stably viable in vitro and has intact receptor function. The purified toxin components were sequentially and quantitatively added to the nerve cell reaction system, and a control group was set up simultaneously. Based on the specific targeting binding characteristics of the clam toxin to the voltage-gated sodium ion channel receptor of nerve cells, the influx of sodium ions was blocked and the cell damage induced by the activator was antagonized, and the dose-response relationship between toxin concentration and cell activity was established. Cell activity was detected in each group of neural cell systems that completed the specific binding reaction. Activity characterization signals of each group of neural cell systems were obtained, including cell survival status signals, cell membrane integrity signals, cell physiological impedance signals and ion channel function response signals to detect cell activity. Cell viability and the specific protective rate of salicornin toxin were calculated to obtain standardized quantitative data characterizing the toxin's protective effect. The following formula was used for calculation:

[0021] in, Cell viability; The absorbance of the cell pores in the experimental group of the toxin to be tested; The absorbance of the negative control blank well is used to subtract background interference from the solution itself; The absorbance of the activated damage control group was used as a baseline for total cell damage.

[0022] in, The specific protective rate of scleroderma toxin; Cell viability of the toxin group to be tested; To improve cell viability in the damage control group; Based on the dose-response relationship between standardized quantitative data and toxin concentration, a dose-response model of standard protection rate-concentration curve was constructed to calculate the bioactivity equivalent of sparganin in the test sample. The calculation results are compared with the preset activity determination threshold to determine the biological activity level of the shifang clam toxin, and a test report is generated, including the sample number, measured activity equivalent, activity level, specificity verification conclusion, standard curve parameters, intra-batch coefficient of variation, and determination of the validity of this experiment.

[0023] In this embodiment, by using the calculation formulas for cell survival rate and specific protection rate, the interference from solution background and basic damage signals can be accurately deducted, and the protective effect of salicornin on nerve cells can be standardized and quantified. This eliminates the systematic error caused by differences in cell state between different experimental batches, and significantly improves the comparability and repeatability of the detection results.

[0024] In this embodiment, the specific preparation process for obtaining the purified toxin component includes: Collect raw samples of shellfish water, shellfish tissue, or water sediments, and classify them according to their morphology to obtain homogeneous slurry or liquid initial test solution. For solid and semi-solid samples such as shellfish tissues and sediments, an extraction buffer pre-cooled to 4°C was added at a sample-to-extraction-solution mass-to-volume ratio of 1:3 to 1:5. The buffer consisted of 50 mM ammonium acetate, 0.1% Triton X-100, and pH 4.5. The samples were then homogenized using a high-speed dispersion homogenizer at 8000–12000 rpm for 3–5 minutes under ice bath conditions until the samples were completely dispersed into a lumpy homogenous slurry. The entire process was carried out at 4°C in the dark to release bound and free safaritoxins and prevent activity decay. For liquid samples such as shellfish water, they are directly used as the initial test solution, avoiding high temperature and strong light environments throughout the process to prevent the inactivation of toxin biological activity; The homogenized slurry or initial liquid test solution is subjected to segmented gradient centrifugation at 2000–4000×g for 10–15 minutes at 4°C to remove insoluble impurities such as large solid particles, tissue fragments, and suspended sediment. The supernatant after low-speed centrifugation is collected and then centrifuged at 10000–15000×g for 20–30 minutes to precipitate interfering components such as large molecular proteins and lipid polymers, and to completely separate solid impurities from toxin-containing liquid components. The supernatant is then centrifuged at high speed, and the clear liquid phase is collected as the original solution. This avoids the problem of solid impurities clogging the cell reaction system and causing non-specific cell stress responses. Add an equal volume of a polar extraction system, such as water-saturated n-butanol or ethyl acetate, to the clarified liquid stock solution. Based on the strong polarity and water solubility of salicornin, selective extraction is performed by vortexing for 5-10 minutes. After standing and separating the layers, discard the organic phase containing lipophilic impurities and hydrophobic interfering substances, and retain the aqueous phase. Repeat the extraction operation 1-2 times to improve the toxin enrichment purity and remove lipophilic antagonistic impurities that can interfere with sodium ion channel function and non-specifically bind to nerve receptors, to obtain a crude purified toxin extract. The crude purified toxin extract was transferred to an ultrafiltration centrifuge tube with a molecular weight cutoff of 3 kDa. 5–10 times the volume of cell reaction buffer was added, consisting of 140 mM NaCl, 5.4 mM KCl, 1.8 mM CaCl2, 1 mM MgCl2, 10 mM HEPES, and 5 mM glucose, pH 7.4. Ultrafiltration was then performed to completely remove the original sample matrix system and replace it with a physiological buffer system suitable for in vitro culture of nerve cells. After extraction and replacement, the pH value (should be 7.3–7.5) and osmolality (should be 290–320 mOsmol / L) of the retentate from the physiological buffer system were measured. The pH value and osmolality of the retentate were then adjusted to the preset target range using the corresponding buffer solution. The acidity, alkalinity, ion concentration and osmolality parameters of the extract were precisely adjusted to make them completely match the physiological adaptation range for nerve cell survival, eliminate non-specific cell damage caused by acid-base imbalance and abnormal osmolality, and avoid interfering with the subsequent construction of standardized cell damage models. The toxin stock solution, after physiological parameter calibration, was serially diluted using cell reaction buffer. The dilution ratio was set as a semi-logarithmic gradient (interval between adjacent concentrations of 0.5 to 1.0 log units) based on the linear response range determined in the preliminary experiment. Working solutions of the test samples with at least 6 concentration gradients (such as 0.1, 0.3, 1, 3, 10, 30 nM, etc.) were prepared, while the stock solution was retained for later use. Each group of test samples after gradient dilution was stored at low temperature and protected from light to ensure stable toxin activity and consistent matrix environment in each working solution, thereby obtaining purified toxin components.

[0025] In this embodiment, the construction of the neural cell reaction system further includes: after incubation, detecting the degree of damage to the neural cell reaction system and determining the actual cell damage rate; If the actual cell damage rate deviates from the preset standard damage range, the duration or temperature parameters of the first incubation and / or the second incubation will be adjusted according to the amount of deviation. When the actual cell damage rate is higher than the upper limit of the preset standard damage range, it indicates excessive damage. In this case, the duration of the first or second incubation should be shortened, or the temperature of the first or second incubation should be reduced. When the actual cell damage rate is lower than the lower limit of the preset standard damage range, it indicates insufficient damage. In this case, the duration of the first or second incubation should be extended, or the temperature of the first or second incubation should be increased; the greater the deviation, the better. The larger the corresponding correction magnitude, the greater the deviation, which is characterized by the ratio of the difference between the actual cell damage rate and the center value of the preset standard damage interval to the interval width. The correction magnitude is expressed as a proportion of the original duration or original temperature. The duration correction proportion is positively correlated with the deviation proportion, and the absolute value of the temperature correction is positively correlated with the deviation proportion. After each correction, the damage level is re-detected. If the current actual cell damage rate still deviates, it is corrected again until the damage rate falls within the preset standard damage range. If the damage rate deviates in opposite directions after two consecutive corrections, the dichotomy method should be used to reduce the correction range before readjusting.

[0026] In this embodiment, the control group includes: an activation damage control, a total damage control, a standard toxin gradient control, a negative control, and a positive control. The activated damage control was a cell system containing sodium channel activators and sodium pump inhibitors but without salicornin, used to define the basic damage signal; The total damage control was a cell system containing only sodium pump inhibitors and no sodium channel activators, with cell viability defined as 0%, used to calculate maximum cell activity. The standard toxin gradient control is a cell system containing a known concentration gradient of salicornin standard, used to construct a dose-response model; The negative control consists of blank wells containing only the highest concentration of the working solution of the test sample and no cells, used to subtract background interference from the sample itself. The positive control was a cell system with a fixed concentration of salicornin standard added, used to verify the effectiveness of the experimental system.

[0027] In this embodiment, a purification process combining segmented gradient centrifugation, polar extraction, ultrafiltration replacement, and osmotic pressure calibration can efficiently remove solid impurities, lipid-soluble interfering substances, and large molecular proteins from the sample. Simultaneously, the toxin component is replaced with a physiological buffer system perfectly suited for nerve cell culture, avoiding non-specific cell stress responses caused by differences in the sample matrix. This ensures the stability of the subsequent nerve cell response system and the reliability of the detection results. Furthermore, by setting up a multiple control system including activation damage control, total damage control, standard toxin gradient control, negative control, and positive control, the basic cellular damage state, sample matrix interference, standard response consistency, and system effectiveness can be comprehensively monitored during the experiment. This effectively distinguishes between the specific protective signal of *Staphylococcus aureus* toxin and non-specific background noise, significantly improving the accuracy, traceability, and quality control reliability of the detection results.

[0028] In this embodiment, the specific process for detecting cell viability includes: All groups of neural cell systems that have completed the specific binding reaction are uniformly cleaned and balanced, and the signal acquisition environment temperature, acquisition time, signal gain and sampling range are uniformly set to obtain activity characterization signals, so as to achieve synchronous and homogeneous acquisition of multi-dimensional signals. Among them, the cell survival status signal uses the cell mitochondrial activity response level as the detection benchmark to characterize the overall cell survival and proliferation activity; Cell membrane integrity signals are measured using the level of leakage of intracellular landmark macromolecules as a benchmark, characterizing the degree of membrane structural integrity after toxin antagonistic damage. Cellular physiological impedance signals are used as the detection benchmarks for cell adhesion state and cell membrane dynamic impedance to characterize the overall physiological and metabolic homeostasis of cells. The ion channel functional response signal is based on the dynamic response fluctuation of the opening and closing of voltage-gated sodium ion channels, which accurately corresponds to the channel blocking specific effect of safflower toxin. Simultaneously collect blank background signals and damage background signals of the neural cell system of each group, distinguish between toxin-specific protective signals and environmental noise and cellular background fluctuation signals, and subtract interference signals in sequence based on the distinction results. First, subtract the inherent system background noise of the detection equipment, then subtract the blank cell background physiological noise, and finally subtract the matrix noise introduced by the buffer and drug system. Based on the activity characterization signal after interference calibration, a standardized raw dataset is obtained. According to the preset data processing rules, baseline calibration, outlier data removal, and global normalization are performed to eliminate detection system errors and random errors, and generate a standardized activity signal dataset that is comparable between groups and has uniform dimensions. Based on the preset gradient response matching and intra-group dispersion dual data verification rules, the collected multi-dimensional activity signals are subjected to secondary screening. Each signal data is compared with the preset normal fluctuation range, gradient response law, and discrete coefficient threshold to determine the validity of the data, and abnormal signals are traced, marked and precisely removed. Based on the classification criteria for the causes of abnormal data, it distinguishes between problems such as equipment signal fluctuations, human operation errors, reaction system contamination, and abnormal cell growth status, and presets and retains complete data screening and rejection criteria. Once the data verification is complete, select effective signal data that has good gradient correlation, low dispersion, and high repeatability. The standardized active signal dataset is updated based on the effective signal data and used for subsequent calculations of cell survival rate, specific protection rate of salicornin, and dose-effect model fitting, ensuring the accuracy, traceability, and reproducibility of the quantitative detection results.

[0029] In this embodiment, by unifying signal acquisition conditions, multi-level background subtraction, baseline calibration, outlier data removal, and dual data verification rules, it is possible to effectively eliminate equipment noise, cell background fluctuations, and matrix interference, generating a standardized active signal dataset with high signal-to-noise ratio and high repeatability, which significantly improves the sensitivity, precision, and data reliability of the detection method.

[0030] In this embodiment, the construction of the standard protection rate-concentration curve dose-effect model specifically includes: Based on the updated standardized active signal dataset, and combined with the gradient concentration of the shifang ji toxin standard and the corresponding specific protection rate, a four-parameter logistic nonlinear fitting algorithm was used to construct the standard protection rate-toxin concentration dose-response curve. Extract the curve fitting correlation coefficient and residual distribution parameters, and compare them with the preset model qualification threshold to judge the model fitting effectiveness. When the model fitting effectiveness meets the preset fitting standard, determine the upper and lower plateau values ​​of the curve, the half effective concentration and the Hill slope as key target parameters, and generate a standardized dose-response fitting model. The standardized specific protection rate of the test samples corresponding to each dilution gradient is input into the standardized dose-response fitting model, and the apparent half-effective concentration of scimitar toxin in the test samples is obtained by inverse solution. The specific activity values ​​of the same batch of salicylic acid standards were obtained by mouse biocalibration. Based on the activity equivalent conversion formula, and combined with the sample pretreatment dilution factor and extraction enrichment factor, the bioactivity equivalent of salicylic acid corresponding to each dilution gradient of the test sample was obtained, achieving absolute quantification of the toxin's bioactivity. When the coefficient of variation of the activity equivalent value calculated for the test sample at at least three consecutive dilution gradients is ≤15%, the arithmetic mean is taken as the final test result. If the coefficient of variation exceeds 15%, it is determined that there is non-specific interference in the sample, and the sample preprocessing and retesting are required. The calculated activity equivalent value is compared with the preset food safety limit standard, and a qualified or unqualified conclusion is output.

[0031] To further verify the effectiveness, accuracy, and applicability of the method of the present invention, the following experimental examples were conducted, which are illustrated below: Experimental Example 1: Establishment of the protection rate-concentration curve of the sclerotoxin standard To verify the dose-response relationship of the neural cell response system constructed in this invention to salicornin, according to the method described in this invention, concentration gradients of salicornin standard were set at 0.1, 0.3, 1, 3, 10, and 30 nM, and added to the neural cell response system respectively. The cell viability and specific protection rate at each concentration were measured, and the results are shown in Table 1. Table 1. Specific protection rates of different concentrations of salicornin standard. ; As the concentration of salicornin increased, the cell survival rate gradually increased, and the specific protection rate showed a typical S-shaped dose-response curve. After fitting with a four-parameter logistic curve, the following key parameters were obtained: upper plateau value 92.8%, lower plateau value 8.2%, half effective concentration 1.82 nM, Hill slope 1.08, and correlation coefficient 0.998.

[0032] The above results show that the protection rate-concentration curve of the standard constructed in this invention exhibits a typical S-type dose-response relationship in the range of 0.1~30 nM, with extremely high goodness of fit and an EC50 value that is stable at around 1.8 nM. This indicates that the system can sensitively and accurately reflect the receptor binding activity of salicornin and is suitable for quantitative analysis of the bioactivity of salicornin in the test samples.

[0033] Experimental Example 2: Detection of bioactivity equivalent of sclerotoxin in actual shellfish samples Mussel samples were collected from a coastal area and homogenized, centrifuged, extracted, ultrafiltered, and osmotic pressure calibrated according to the pretreatment method described in this invention to obtain purified toxin components.

[0034] The stock toxin solution was serially diluted with cell reaction buffer at dilution ratios of 1:5, 1:10, and 1:20. Each dilution was added to the nerve cell reaction system, and the specific protective rate was measured. The activity equivalent was then calculated by substituting the values ​​into the standard curve established in Example 1. A spiked recovery experiment was also performed, adding 10 nM salicornin standard to negative shellfish samples to verify accuracy. The results are shown in Table 2. Table 2. Detection and Spiked Recovery Results of Actual Shellfish Samples ; The results above show that the method of the present invention has good quantitative ability for salicornin in real shellfish samples. The activity equivalents measured under three consecutive dilution gradients are highly consistent, indicating that the sample matrix does not significantly interfere with the detection. The spiked recovery rate reaches 96.0%, which further verifies the accuracy of the method.

[0035] Experimental Example 3: Method Precision Validation Extracts from the same batch of shellfish samples, with a known activity equivalent of approximately 12 nM, were repeatedly tested 6 times on the same day according to the method of this invention, and then repeatedly tested twice daily for 3 different days, for a total of 6 tests. Intra-batch and inter-batch coefficients of variation were calculated. Simultaneously, standard working solutions at low, medium, and high concentrations were repeatedly tested 6 times to verify the precision at different concentrations. The results are shown in Table 3. Table 3. Results of Intra-batch and Inter-batch Precision Validation ; As shown in Table 3, the intra-batch CV is between 3.0% and 5.6%, and the inter-batch CV is between 4.8% and 7.7%, both of which are below the industry standard of 10%, indicating that the method of the present invention has excellent repeatability and intermediate precision, and can meet the quality control requirements of bioactivity detection methods.

[0036] Experiment Example 4: Method Specificity Validation To verify the specificity of the method of the present invention against sclerotoxin, common marine toxins, namely ootanacin, fin algae toxin-1, bryophyte toxin, tetrodotoxin, and decarbamoyl sclerotoxin, were selected and their specific protective rates were measured under the same experimental conditions at a concentration of 10 nM. The results were compared with those of sclerotoxin at the same concentration. The results are shown in Table 4. Table 4. Specific protection rate of the method of the present invention against different toxins. ; The results showed that the method of this invention has high specificity for tetrodotoxin. It exhibits some cross-reactivity with tetrodotoxin, which has a similar mechanism of action and is a sodium channel blocker; this is an inherent characteristic of receptor-binding methods but does not affect the evaluation of the total activity of tetrodotoxin. It showed approximately 48% cross-reactivity with decarbamoyl tetrodotoxin, as expected. However, it showed almost no response with toxins such as OA, DTX-1, and BTX, which do not act on voltage-gated sodium channels. Therefore, the method of this invention can specifically detect tetrodotoxin and some of its analogues with sodium channel blocking activity, and is suitable for the comprehensive toxicity evaluation of paralytic shellfish poisoning.

[0037] Experiment Example 5: Applicability Verification under Different Sample Matrices Three typical matrices were selected: shellfish tissues (mussels, scallops, and oysters), water samples (from marine aquaculture areas), and sediments. Toxin standards for salicornin were added to each matrix to a final concentration of 10 nM (shellfish tissue samples were converted to wet weight). Pretreatment and detection were performed according to the method of this invention, and the recovery rate and coefficient of variation were calculated. The results are shown in Table 5. Table 5 Spike recoveries and precision in different matrices ; As can be seen from Table 5, the method of the present invention exhibits good recovery rate and precision in various environmental sample matrices such as shellfish tissue, seawater and sediment, indicating that the method has broad matrix adaptability and can be directly used for the detection of schizotoxin bioactivity in different types of samples.

[0038] In the above embodiments, the present invention achieves specific, sensitive, accurate, and reproducible quantification of the bioactivity of salicornin by constructing a detection system based on the receptor binding effect of neural cells. Experimental data fully demonstrate that the method of the present invention has advantages over existing technologies, such as mouse biological methods and conventional cytotoxicity methods, including higher standardization, lower detection costs, better reproducibility, and compliance with the 3R principle of animal experiments.

[0039] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells, characterized in that, include: Collect the original sample to be tested and perform low-temperature homogenization and crushing treatment to obtain a homogenized slurry; The homogenized slurry was subjected to centrifugation, extraction, buffer replacement, and osmotic pressure calibration in sequence to obtain purified toxin components; Neurons expressing voltage-gated sodium channels were cultured to form a monolayer of neuron cells, and sodium channel activators and sodium pump inhibitors were added sequentially for incubation to construct a neuron cell response system. The purified toxin components were sequentially and quantitatively added to the nerve cell reaction system, and a control group was set up simultaneously. Based on the specific targeting binding characteristics of the toxin to nerve cell voltage-gated sodium ion channel receptor, a dose-response relationship between toxin concentration and cell activity was established. Cell activity was detected in each group of neural cell systems that completed the specific binding reaction, and activity characterization signals of each group of neural cell systems were obtained. Cell viability and the specific protective rate of salicornin were calculated to obtain standardized quantitative data characterizing the protective effect of the toxin. Cell viability and specific protective rate were calculated using the following formulas: ， in, Cell viability; The absorbance of the cell pores in the experimental group of the toxin to be tested; The absorbance of the negative control blank well is used to subtract background interference from the solution itself; The absorbance of the activated damage control group was used as a baseline for total cell damage. ， in, The specific protective rate of scleroderma toxin; Cell viability of the toxin group to be tested; To improve cell viability in the damage control group; Based on the dose-response relationship between standardized quantitative data and toxin concentration, a dose-response model of standard protection rate-concentration curve was constructed to calculate the bioactivity equivalent of sparganin in the test sample. The calculation results are compared with the preset activity determination threshold to determine the biological activity level of the shifang clam toxin and generate a test report.

2. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 1, characterized in that, The specific preparation process for obtaining the purified toxin component includes: Collect the original sample to be tested, classify and process it according to the sample morphology, and obtain a homogeneous slurry or liquid initial test solution. The homogeneous slurry or initial liquid test solution is subjected to segmented gradient centrifugation. The supernatant after low-speed centrifugation is collected, and the supernatant is then subjected to high-speed centrifugation to obtain the original clear liquid phase. Add an equal volume of polar extraction system to the clear liquid stock solution, and selectively extract based on the strong polarity and water solubility of scimitar toxin. Repeat the extraction operation 1-2 times to obtain crude purified toxin extract. The crude purified toxin extract was subjected to ultrafiltration replacement treatment to replace it with a physiological buffer system adapted to the in vitro culture of nerve cells; The pH value and osmolality of the retentate from the physiological buffer system after replacement were measured, and the pH value and osmolality of the retentate were adjusted to the preset target range using the corresponding buffer solution. The physiologically calibrated toxin stock solution was serially diluted using cell reaction buffer, and the serially diluted samples were stored at low temperature and protected from light to obtain purified toxin components.

3. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 1, characterized in that, The construction of the neural cell response system further includes: after incubation, detecting the degree of damage to the neural cell response system and determining the actual cell damage rate; if the actual cell damage rate deviates from the preset standard damage range, then adjusting the incubation parameters according to the deviation and reconstructing the neural cell response system until the actual cell damage rate is within the preset standard damage range.

4. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 3, characterized in that, Adjusting incubation parameters based on deviations includes: When the actual cell damage rate is higher than the upper limit of the preset standard damage range, it indicates excessive damage. In this case, the incubation time should be shortened or the incubation temperature should be lowered. When the actual cell damage rate is lower than the lower limit of the preset standard damage range, it indicates insufficient damage, and the incubation time should be extended or the incubation temperature increased. The larger the deviation, the greater the corresponding correction magnitude. The deviation is characterized by the ratio of the difference between the actual cell damage rate and the center value of the preset standard damage interval to the interval width. The correction magnitude is expressed as a proportion of the original duration or original temperature. The duration correction proportion is positively correlated with the deviation proportion, and the absolute value of the temperature correction is positively correlated with the deviation proportion. After each correction, the damage level is re-detected. If the current actual cell damage rate still deviates, it is corrected again until the damage rate falls within the preset standard damage range.

5. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 1, characterized in that, The control group includes: an activation damage control, a total damage control, a standard toxin gradient control, a negative control, and a positive control. The activation damage control is a cell system containing sodium channel activators and sodium pump inhibitors but without salivarius toxin; the total damage control is a cell system containing only sodium pump inhibitors and no sodium channel activators; the standard toxin gradient control is a cell system containing salivarius toxin standards at known concentration gradients; the negative control is a blank well containing only the highest concentration of the test sample working solution and no cells; and the positive control is a cell system containing a fixed concentration of salivarius toxin standards.

6. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 1, characterized in that, The specific process for cell viability testing includes: All groups of neural cell systems that completed the specific binding reaction were uniformly cleaned and balanced, and the signal acquisition environment temperature, acquisition time, signal gain and sampling range were uniformly set to obtain activity characterization signals. Simultaneously collect blank and damage background signals of the neural cell system in each group, distinguish toxin-specific protective signals from environmental noise and cellular background fluctuation signals, and subtract interference signals in turn based on the distinction results; Based on the activity characterization signal after interference calibration, a standardized raw dataset is obtained. According to the preset data processing rules, baseline calibration, outlier data removal, and global normalization are performed to generate a standardized activity signal dataset.

7. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 6, characterized in that, The generation of the standardized active signal dataset also includes: Based on the preset gradient response matching and intra-group dispersion dual data verification rules, the collected multi-dimensional activity signals are subjected to secondary screening. Each signal data is compared with a preset normal fluctuation range, gradient response pattern, and discrete coefficient threshold to determine the validity of the data and filter out valid signal data. The standardized active signal dataset is updated based on effective signal data and used for calculating cell viability, the specific protection rate of salicornin, and dose-response model fitting.

8. The method for detecting the bioactivity of scutellarin based on the receptor binding effect of neural cells as described in claim 7, characterized in that, The construction of the standard protection rate-concentration curve dose-effect model specifically includes: Based on the updated standardized active signal dataset, and by combining the gradient concentrations of the shifang jiu toxin standard with the corresponding specific protection rates, a dose-response curve of the standard protection rate versus the toxin concentration was constructed. Extract the curve fitting correlation coefficient and residual distribution parameters, and compare them with the preset model qualification threshold to judge the model fitting effectiveness. When the model fitting effectiveness meets the preset fitting standard, determine the upper and lower plateau values ​​of the curve, the half effective concentration and the Hill slope as key target parameters, and generate a standardized dose-response fitting model. The standardized specific protection rate of the test samples corresponding to each dilution gradient is input into the standardized dose-response fitting model, and the apparent half-effective concentration of scimitar toxin in the test samples is obtained by inverse solution. Obtain the standard activity value of the same batch of salicornin standard, and combine it with the sample pretreatment dilution factor and extraction enrichment factor to obtain the bioactivity equivalent of salicornin for each dilution gradient of the test sample.

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