A multi-toxicity assessment method for pollutants based on high-throughput detection in Caenorhabditis elegans

Abstract

The present invention discloses a method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans. Based on high-definition perspective scanning technology and an improved MPO-YOLO deep learning model, high-throughput automated identification and detection of Caenorhabditis elegans and its eggs are achieved, which can greatly improve data acquisition efficiency and recognition accuracy. Compared with traditional image analysis methods, the present invention can not only synchronously evaluate the growth, reproduction, survival rate and movement ability of nematodes, but also introduce a microfluidic chip with a tilt adjustment structure to conduct electrotaxis experiments. By setting a certain tilt angle, the chip introduces a gravity component force field in the microchannel, which couples with the electric field force to amplify the behavioral changes of nematodes under nerve and muscle function damage, making electrotaxis as a toxic effect indicator more sensitive and multidimensional. This structure is particularly suitable for detecting weak neurotoxicity or motor coordination disorders, and improving the resolution of behavioral parameters in toxicity analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental toxicology, and in particular to a method for evaluating the multi-toxicity of pollutants based on high-throughput detection of Caenorhabditis elegans. Background Art

[0002] Emerging pollutants harm the ecological environment and human health, and are a global environmental issue. With deepening understanding and the continuous development of environmental monitoring technology, the types and quantities of emerging pollutants will continue to change. It is widely believed that emerging pollutants are gradually becoming a new obstacle to the continued improvement of air, water, and soil environmental quality. They are also a "hard nut to crack" in ecological and environmental protection, following haze and black and smelly water bodies.

[0003] In recent years, the application of Caenorhabditis elegans in environmental toxicology has gradually gained momentum. As a classic model organism, C. elegans boasts significant advantages, including a short life cycle, low cultivation costs, and a well-sequenced genome. Its wide distribution, diverse ecological origins, and rich behavioral responses have made it widely used in toxicology and environmental science.

[0004] In existing toxicity studies, researchers have constructed a variety of biological indicator systems based on the movement ability, reproductive ability and lifespan of Caenorhabditis elegans. Combined with fluorescent labeling, transgenic technology and molecular biology methods, they can deeply explore the toxicity mechanism and biological targets of new pollutants. Existing research evidence shows that a considerable number of new pollutants exist in the environment in the form of low-dose, long-term exposure, causing potential interference to the nervous system, sensory system and motor system of organisms. However, research on the impact mechanism of such new pollutants on the neuro-behavioral level is still in its infancy, especially in terms of evaluation methods and toxicity endpoint indicators. There is a lack of high-throughput evaluation schemes that can reflect changes in neural function. In addition, the existing evaluation schemes also have the following shortcomings:

[0005] 1) The traditional Ludox solution used as the separation medium during the transfer of C. elegans results in low separation efficiency and purity.

[0006] 2) The multi-dimensional movement response of C. elegans under the coupling of electric field force and gravity components is not reflected, and the corresponding behavioral parameters are missing, resulting in low accuracy of toxicity assessment.

[0007] 3) The recognition model used cannot accurately segment and classify nematodes of different morphologies in toxicity analysis based on C. elegans, and the data cannot show the performance of C. elegans with different toxicity levels.

[0008] 4) It is only suitable for liquid environments and supports only a single pollutant exposure experiment, which is not suitable for actual ecological exposure scenarios. Summary of the Invention

[0009] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for evaluating the multi-toxicity of pollutants based on high-throughput detection of Caenorhabditis elegans.

[0010] To achieve the above objectives, the technical solutions provided by the present invention are:

[0011] A method for evaluating the multi-toxicity of pollutants based on high-throughput detection in Caenorhabditis elegans, comprising:

[0012] Based on the environmental concentration and component ratio of the pollutants, the Caenorhabditis elegans is exposed to environmental pollutants in liquid culture medium or simulated environmental culture medium by single exposure or combined exposure; the simulated environment includes soil environment and sediment environment; according to different exposure methods, the exposed Caenorhabditis elegans and its eggs are transferred to the prepared sodium alginate culture dish by different methods; after the liquid in the sodium alginate culture dish is naturally dried to no obvious liquid film, the nematodes and their eggs in the sodium alginate culture dish are scanned twice in succession using a high-definition fluoroscopic scanner, and the time interval between the two scans is set for a set number of minutes, and the same culture dish is obtained. two scanning images of C. elegans after exposure and the control C. elegans were transferred to a microfluidic chip with a tilt adjustment structure, and galvanotaxis experiments were carried out to obtain galvanotaxis images; a toxic effect index recognition model was established and trained; the acquired scanning images and galvanotaxis images were recognized by the trained toxic effect index recognition model to obtain five toxic effect indicators of C. elegans, which are growth, reproduction, motility, survival rate and galvanotaxis; based on the fuzzy weight evaluation method and the information dispersion weighted method, the five toxic effect indicators were integrated to realize the multi-toxicity assessment of pollutants.

[0013] Furthermore, in the case of exposure of C. elegans to environmental pollutants in a simulated environmental medium, a modified sodium alginate solution was used as a separation medium during the transfer of C. elegans. The transfer process was as follows:

[0014] First, add 3 ml of M9 buffer to each simulated environment culture medium, and use a Pasteur pipette to transfer the Caenorhabditis elegans, pollutants, sediments or soil in each simulated environment culture medium to a separate centrifuge tube, and repeat twice; then place the centrifuge tube on a swing-out stand and let it settle naturally for 20 minutes; then, aspirate part of the supernatant of the centrifuge tube and discard it; next, add 2 ml of modified sodium alginate solution to the centrifuge tube containing nematodes, pollutants, sediments or soil, and mix them thoroughly using a test tube mixer; then use the swing-out adapter to centrifuge the sample at 200 g for 2 minutes again; after centrifugation, the supernatant of the modified sodium alginate solution in the centrifuge tube contains Caenorhabditis elegans and eggs; then, transfer the supernatant in the centrifuge tube to a new centrifuge tube; add 10 ml of M9 buffer to the new centrifuge tube to wash the Caenorhabditis elegans and centrifuge, then aspirate the supernatant and discard it, repeat three times; finally, transfer the washed Caenorhabditis elegans to a sodium alginate culture dish.

[0015] Furthermore, the preparation method of the improved sodium alginate solution includes:

[0016] First, slowly add sodium alginate to deionized water and stir at a constant temperature of 25-30℃ to prepare a 0.2-0.4% solution; adjust the pH to 4.5-5.5 with acid and stir at 300-500r / min for 30 minutes; then add EDC・HCl at a rate of 5-10% of the mass of sodium alginate and 2-5% of natural polyphenols, activate with 200-300W ultrasound at room temperature for 0.3-0.8h and continue stirring; then slowly add PEG600 solution with a concentration of 0.02-0.04g / ml, and after 10-15 minutes, The reaction was continued under 150-200W ultrasound for 1-2 hours, and the stirring speed was reduced to 200-300r / min; after the reaction was completed, the pH was adjusted to 7.0±0.2 with an alkaline solution to terminate the reaction; then, the solution was purified with an ultrafiltration membrane with a molecular weight cutoff of 10,000 until the conductivity of the permeate was less than 10μS / cm; finally, the solution was pre-frozen at -40-30°C for 12-13 hours, and freeze-dried at a vacuum degree of less than 10Pa and a sublimation temperature of -20-10°C for 24-36 hours. The dried solid was re-prepared into a 1-2% modified sodium alginate solution.

[0017] Furthermore, the microfluidic chip is provided with two experimental areas, both of which use the same sample inlet, and a microvalve is provided at the sample inlet;

[0018] The process of conducting a galvanotaxis experiment using the microfluidic chip includes:

[0019] The scanned C. elegans were transferred into centrifuge tubes in groups using M9 buffer, named control group and experimental group respectively. The centrifuge tubes of the control group and experimental group were shaken until the C. elegans were evenly distributed in the M9 buffer.

[0020] Adjust the tilt angle of the microfluidic chip as needed; open the microvalve in the microfluidic chip, connect the injection port and peristaltic pump connector of the chip, and connect the electrode of the chip and the electrophoresis instrument interface; turn on the electrochemical workstation and apply a 10V electric field voltage to the two ends of the electrode; start the peristaltic pump to transport the control and experimental groups of Caenorhabditis elegans to the chip at a rate of 0.5L / min; after observing the appearance of the target Caenorhabditis elegans in the microfluidic chip, close the microvalve and peristaltic pump, and place the entire experimental device in a high-definition scanner for scanning to obtain galvanotaxis experimental image data; after obtaining the galvanotaxis experimental image data, open the microvalve and peristaltic pump to transport the remaining Caenorhabditis elegans in the chip to the waste liquid bottle.

[0021] Furthermore, the establishment of a toxic effect index identification model includes:

[0022] Establish the initial model YOLO11;

[0023] Add a detection head to the initial model YOLO11, and its calculation formula is:

[0024]

[0025] in Represents input, To extract features, To process the aggregation part of the features, is the final output prediction, Represents the added detection head;

[0026] Modify the Neck part and adjust the output structure of the Head to obtain the improved model MPO YOLO, whose calculation formula is:

[0027]

[0028]

[0029]

[0030] in, To add the new feature fusion layer to the Neck part, To extract additional sources of information, is the operation function of the Neck part, For the adjusted Head structure, Indicates a connection operation. For the final improved model;

[0031] Using IoU loss and perceptual loss The weighted combination of , as the new positioning regression loss function , and its calculation formula is:

[0032]

[0033]

[0034]

[0035] in, To control the contribution weight of IoU loss and perceptual loss to the total loss, is the prediction box, is the real frame, The first Layer output, is the weighted coefficient of each layer feature, and are the image features of the predicted area and the true area respectively.

[0036] Furthermore, the toxic effect index recognition model was used to identify the two scanned images and galvanotaxis images of the same culture dish, and five toxic effect indices of Caenorhabditis elegans were obtained. The process included:

[0037] Construct a quantification module for toxic effect indicators;

[0038] Generate mask and annotation files of Caenorhabditis elegans images through the toxic effect index quantification module;

[0039] Based on the generated mask image of the C. elegans image, the connected domains of the mask image were marked to obtain all connected regions. Each connected region corresponds to a C. elegans. Subsequently, the pixel perimeter C of each connected region was calculated, and the pixel length of each nematode was approximated as C / 2. Finally, the pixel length was proportionally converted to the actual length to obtain the true length of each nematode. The average length of the C. elegans was calculated and compared to obtain the overall growth index.

[0040] Generate an annotation file for the C. elegans image and obtain the number of C. elegans in the first scan , and a second scan of Caenorhabditis elegans and number of eggs , calculate the reproduction index, where the calculation formula of the reproduction index is:

[0041]

[0042] in Represents reproductive indicators;

[0043] Calculate the intersection-over-union ratio of each C. elegans according to the generated annotation file of the first scanned C. elegans image and the mask image of the second scanned C. elegans image to obtain the overall survival rate;

[0044] elegans image mask was used to calculate the centroid of the block areas of the two images before and after. The displacement of the centroid of each area was then calculated, the average value was taken, and the normalization was performed to obtain the overall movement ability.

[0045] Based on the mechanical model of the behavior of C. elegans in the experimental area of ​​the microfluidic chip equipped with a tilt adjustment structure, the movement rate of C. elegans in the experimental area was calculated and used as an indicator of the overall electrotaxis effect.

[0046] Furthermore, the process of obtaining the overall survival rate includes:

[0047] Based on the first scan of the same culture dish, the C. elegans image and its annotation file are used to extract the polygonal segmentation area of ​​each nematode, and generate the corresponding mask map in the second scanned image; then, the intersection of the two scans of the same nematode is calculated. Evaluate its survival status, where the intersection and union ratio The calculation formula is:

[0048] in, Segment the nematode region for the first scan, is the nematode mask area for the second scan, represents the intersection area of ​​the two. represents the union area of ​​the two; if a nematode The value is greater than the preset survival threshold , the nematode is considered to have survived the pollutant exposure process, otherwise it is considered to have died; finally, the overall survival rate is calculated. , which is the ratio of the number of surviving nematodes to the total number of nematodes marked in the first scan image.

[0049] Furthermore, the process of obtaining overall athletic ability includes:

[0050] First, the mask image of the C. elegans image is divided into blocks, the contours of each area are extracted based on the image segmentation algorithm, and the centroid coordinates of each block area are calculated. and ,in are the centroid abscissa and ordinate of the block area of ​​the image mask image scanned for the first time, are the centroid abscissa and ordinate of the block area of ​​the second scanned image mask; then, calculate the centroid of each block area in the time interval Center of mass displacement within , average the centroid displacement of all block areas to obtain the overall average displacement ; Normalization is performed to eliminate the scale effect and obtain the normalized motion ability index .

[0051] Furthermore, the process of obtaining the overall galvanotaxis index includes:

[0052] First, the force analysis of Caenorhabditis elegans was performed to obtain the force parameters along the slope, including the component of gravity along the slope. , the component of gravity perpendicular to the inclined plane , electric field driving force , liquid viscous resistance and friction , the calculation formula is as follows:

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] Caenorhabditis elegans moves in a tilted microfluidic chip, exhibiting a multi-dimensional motion response under the coupling of electric field and gravity components. This allows for more behavioral parameters and chip geometry parameters to be used for toxicity assessment, including the nematode's own locomotion ability. ;

[0059] Next, we conducted a dynamic analysis of the movement of C. elegans in the microfluidic chip. Since it satisfies Newton's second law, the following equation of motion is derived:

[0060]

[0061] During steady-state exercise:

[0062]

[0063]

[0064] Solve for the motion rate :

[0065]

[0066] Among them, sliding along the inclined plane is positive, The sign is determined by the direction of the electric field, is the tilt angle of the microfluidic chip, For the quality of Caenorhabditis elegans, For exercise time, is the acceleration due to gravity, is the electric field strength, is the liquid viscous resistance coefficient, is the friction coefficient, is the equivalent charge, is the net external force acting on C. elegans;

[0067] Finally, the movement rate of C. elegans was used as the overall indicator of electrotaxis.

[0068] Furthermore, based on the fuzzy weight evaluation method and the information dispersion weighted method, the process of integrating five toxic effect indicators to achieve multi-toxicity assessment of pollutants includes:

[0069] Establish a set of toxic effect indicators and a set of toxicity evaluation levels:

[0070]

[0071]

[0072] in, is a set of toxic effect indicators, is a set of toxicity evaluation grades, They are growth, reproduction, motility, survival rate and galvanotaxis, They are low toxicity, moderate toxicity, and high toxicity respectively;

[0073] S7-2, data preprocessing:

[0074] The raw value is converted into a relative toxicity value:

[0075] in, For the The pollutants in The experimental group data of the indicators, The data are for the control group; is the relative toxicity value after conversion, the smaller the value, the greater the toxicity;

[0076] Constructing the triangle membership function: Setting The toxicity range of (low toxicity) is , The toxicity range is , (Highly toxic) has a toxicity range of , the toxicity value is mapped to fuzzy membership, and the triangle membership function is constructed respectively;

[0077] Low toxicity membership:

[0078]

[0079] Toxic membership:

[0080]

[0081] High toxicity membership:

[0082]

[0083] in, For the Among the pollutants The degree of membership of an indicator;

[0084] Constructing the fuzzy membership matrix :

[0085] Based on the Pollutant exposure experimental data, construct the Fuzzy membership matrix :

[0086]

[0087] For example: When When the exposure pollutant is PFOS, the membership degree of Caenorhabditis elegans in the "low toxicity" level in the "growth" indicator is 0.8, that is, =0.8;

[0088] The weight vector is calculated using the information dispersion weighting method

[0089] Construct the original data matrix:

[0090] Original data matrix: ;

[0091] is the number of samples with different pollutants at different concentrations; is the number of indicators;

[0092] Data standardization:

[0093]

[0094] in, and For the The minimum and maximum values ​​of the indicators, are the standard values ​​of five types of toxic effect indicators;

[0095] Calculation ratio (contribution):

[0096]

[0097] in, The contribution of each indicator;

[0098] Calculate entropy:

[0099]

[0100] in, is the entropy value of each indicator, if ,but ;

[0101] Calculate weights:

[0102]

[0103] in, Assign a value to each indicator's weight; weight vector satisfy ;

[0104] Fuzzy comprehensive operation:

[0105] Through fuzzy matrix operation and comprehensive membership of each index, the membership distribution of the overall toxicity status is obtained:

[0106]

[0107]

[0108] in is the entropy method weight vector, is a fuzzy operator, is the comprehensive membership of “low toxicity”, is the comprehensive membership of “toxicity”, The comprehensive membership degree is “high toxicity”;

[0109] Final toxicity level determination: Determine the final toxicity level based on the maximum membership principle :

[0110] .

[0111] Compared with the existing technology, the principles and advantages of this technical solution are as follows:

[0112] 1. Based on high-definition fluoroscopic scanning technology and an improved MPO-YOLO deep learning model, high-throughput automated identification and detection of Caenorhabditis elegans and its eggs can be achieved, which can greatly improve data acquisition efficiency and identification accuracy, and significantly enhance the repeatability and standardization of experimental processes.

[0113] 2. Compared to traditional image analysis methods, this invention not only simultaneously assesses nematode growth, reproduction, survival, and motility, but also incorporates a tilt-adjustable microfluidic chip for galvanotaxis experiments. By setting a specific tilt angle, this chip introduces a gravity component within the microchannel. This, coupled with the electric field, amplifies behavioral changes in nematodes affected by nerve and muscle damage, making galvanotaxis a more sensitive and multidimensional indicator of toxic effects. This structure is particularly suitable for detecting mild neurotoxicity or motor coordination disorders, enhancing the resolution of behavioral parameters in toxicity analysis.

[0114] 3. The chip is adaptable to both liquid and simulated soil environments, supporting both single and combined pollutant exposure experiments, more closely resembling actual ecological exposure scenarios. Using an improved YOLOv11 model, enhanced with a small object detection head and the introduction of a PIoU loss function, it accurately identifies individual nematodes and their behavioral pathways even under conditions of high sample density and overlap. Combined with high-resolution dynamic image acquisition, it can capture pollutant-induced toxic reactions in real time.

[0115] 4. Introducing a fuzzy weighted assessment method during the comprehensive evaluation phase can objectively integrate multi-dimensional toxicity information to enhance the scientificity and accuracy of pollutant toxicity risk assessments. This strategy, based on information entropy theory and using a weighted information dispersion method, automatically analyzes the degree of variation of each toxic effect indicator under different pollutant conditions and, based on this, determines its relative importance in the comprehensive evaluation.

[0116] 5. A modified sodium alginate solution was used instead of the traditional Ludox solution as the separation medium. Its excellent biocompatibility and mild separation environment were utilized, combined with density adjustment and multi-step separation strategies, to effectively improve the efficiency and purity of nematodes separation from the simulated environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0117] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions will be briefly introduced below. 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.

[0118] Figure 1 This is a principle flow chart of a method for evaluating the multi-toxicity of pollutants based on high-throughput detection of Caenorhabditis elegans according to the present invention;

[0119] Figure 2 This is a scanned image of the nematode of the present invention;

[0120] Figure 3 The labeled image of Caenorhabditis elegans in the training set of the present invention;

[0121] Figure 4 is a black and white binary image of the training set of the present invention;

[0122] Figure 5 This is a schematic diagram of the structure of the original YOLO11 model;

[0123] Figure 6 This is a schematic diagram of the structure of the MPO YOLO model used in the present invention;

[0124] Figure 7 Schematic diagram of the galvanotaxis experiment;

[0125] Figure 8 Schematic diagram of the microfluidic chip (tilt adjustment structure omitted);

[0126] Figure 9 Schematic diagram showing the details of the microfluidic chip;

[0127] Figure 10 Schematic diagram of force analysis of Caenorhabditis elegans in a tilted microfluidic chip; DETAILED DESCRIPTION

[0128] The present invention will be further described below in conjunction with specific embodiments:

[0129] like Figure 1 As shown, the method for evaluating the multi-toxicity of pollutants based on high-throughput detection of Caenorhabditis elegans described in this embodiment includes the following steps:

[0130] S1. Based on the environmental concentration and component ratio of the pollutants, Caenorhabditis elegans is exposed to environmental pollutants in liquid culture medium or simulated environment (soil, sediment) culture medium using either single exposure or combined exposure. The simulated environment includes soil environment and sediment environment.

[0131] S2. Depending on the exposure method, the exposed C. elegans and its eggs are transferred to a prepared sodium alginate culture dish using different methods;

[0132] S3. After the liquid in the sodium alginate culture dish has dried naturally until no obvious liquid film remains, a high-definition fluoroscopic scanner is used to scan the nematodes and their eggs in the sodium alginate culture dish twice in succession. The two scans are separated by a 4-minute interval to obtain two scanned images of the same culture dish.

[0133] S4. Transferring the exposed C. elegans and the control C. elegans to a microfluidic chip equipped with a tilt adjustment structure, conducting a galvanotaxis experiment, and acquiring galvanotaxis images;

[0134] S5. Establish and train a toxic effect indicator identification model;

[0135] S6. Identify the acquired scanned image and galvanotaxis image using the trained toxicity effect index recognition model to obtain five toxicity effect indices of Caenorhabditis elegans, the five toxicity effect indices being growth, reproduction, motility, survival rate, and galvanotaxis;

[0136] S7. Based on the fuzzy weight evaluation method and information dispersion weighting method, five toxic effect indicators are integrated to realize the multi-toxicity assessment of pollutants.

[0137] In step S1, the exposure methods of C. elegans include single exposure and combined exposure. Single exposure means that the nematodes are exposed to only one pollutant or environmental factor, while combined exposure means that the nematodes are exposed to multiple pollutants or environmental factors at the same time. The concentration of pollutant exposure and the proportion of multiple pollutants in combined exposure are set according to the environmental concentration and components, and a concentration gradient is set based on the environmental concentration to ensure that the general pollution level and extreme pollution level in the environment are covered. If the environmental concentration has no obvious toxic effect, the exposure concentration is gradually increased until a toxic effect is produced on the nematodes and their eggs.

[0138] In step S1, based on the physicochemical properties of the contaminant (e.g., solubility, stability) and the experimental requirements of the exposure system, suitable exposure environments are selected, including liquid exposure and simulated environmental exposure. Simulated environmental exposure includes soil exposure and sediment exposure.

[0139] In step S1, the transfer method of C. elegans depends on the exposure environment. Liquid exposure uses a liquid washing method, and simulated environment exposure uses a sediment transfer method.

[0140] In step S1, the present invention uses a sodium hypochlorite lysis solution (1% by mass NaClO solution, 0.5 mol·L-1 NaOH solution) to lyse adult worms to obtain synchronized eggs, which are then transferred to NGM medium (agar content of 1.7%, peptone content of 0.25%, sodium chloride content of 0.3%, and phosphate buffer content of 0.3%). The eggs are then placed in a sterile biochemical chamber and cultured for 48 hours to the L4 stage to obtain Caenorhabditis elegans to be exposed.

[0141] In step S1, an exposure control group must be established for the experimental group, using a group of Caenorhabditis elegans that has not been exposed to any pollutants as a baseline reference for comparative analysis with the exposure group.

[0142] In step S1, liquid exposure environment: M9 buffer is used as a basic culture medium to provide a suitable osmotic pressure and microenvironment.

[0143] In step S1, E. coli OP50 was added as a food source for C. elegans. OP50 bacterial suspension was directly added to the culture dish. The bacterial concentration was controlled at 5×10 8CFU / ml to ensure the normal growth of Caenorhabditis elegans.

[0144] In step S1, the soil exposure environment includes: an organic carbon content of 2.0% ± 0.5%, a pH (CaCl2) of 5.5 ± 0.5, a cation exchange capacity of 10.0 ± 0.4 mmol / 100g, a water holding capacity of 48.2% ± 5.0%, and various particle sizes of sand, silt, and clay. This medium serves as a negative control soil to ensure the accuracy of the test results.

[0145] Two key points to note when considering soil exposure: First, soils with clay contents exceeding 30% may affect nematode growth and reproduction, so additional testing of reference soils with similar clay contents is necessary. Second, soils with kaolin contents exceeding 5% by mass may have adverse effects on nematodes, so when selecting soil, the kaolin content should be controlled to ≤5%. Through strict data specifications and operational standards, this medium ensures experimental reliability and reproducibility.

[0146] In step S1, the sediment was exposed to an environment containing 20% ​​aluminum oxide (Al2O3), 1% calcium carbonate (CaCO3), 0.5% dolomite (clay), 4.5% iron oxide (Fe2O3), 30% silica sand (particle size 0.063 mm), 40% silica sand (particle size 0.1 mm to 0.4 mm), and 4% peat (decomposed peat from high bogs, finely ground and sieved to <1 mm). The dried sediment can be stored long-term and serves as a negative control for sediment testing.

[0147] Two points need to be noted in the sediment exposure environment: First, if the kaolin content in the sediment exceeds 5%, it may have an adverse effect on the growth, fertility and reproduction of nematodes, so the kaolin content should be strictly controlled to ≤5%; second, it is recommended to use specific site reference sediments with similar characteristics to the test samples when possible to ensure the accuracy and reliability of the test.

[0148] For sediment exposure, prepare at least four replicates for each exposure pollutant and control group. Prepare a blank replicate (without C. elegans) to estimate the number of native nematodes in the sample. For exposure pollutants with a water content ≥ 40% (based on total mass), transfer (0.500 ± 0.010) g (wet weight) of the exposure pollutant to each sediment culture medium. For exposure pollutants and sediments with a water content < 40% (based on total mass), transfer m ± 0.010 g to each sediment culture medium and add (0.500-m) ml of M9 culture medium and stir with a spatula to obtain a uniform suspension. Calculate according to the formula Grams:

[0149]

[0150] in, Dry weight is a measure of exposure to pollutants.

[0151] To avoid moisture loss, store it in a refrigerator at (4±3)°C.

[0152] For the soil exposure environment, prepare at least four replicates for each type of exposed C. elegans and eggs and control soil, and prepare an additional blank replicate (without C. elegans) to estimate the number of C. elegans in the sample. First, dry an appropriate amount of soil at room temperature. Then, transfer (0.500 ± 0.010) g (dry weight) of the exposed pollutant to each soil culture medium and add 1 ml of M9 culture medium to adjust the soil moisture to 80% of the maximum water holding capacity (WHCmax). Stir with a spatula to obtain a uniform material. Calculate the required (ml):

[0153] (0.8 WHCmax) -0.1

[0154] To avoid moisture loss, store it in a refrigerator at (4±3)°C.

[0155] In step S2, the following procedure is used to transfer C. elegans to simulate environmental exposure: First, add 3 ml of M9 buffer to each test well. Using a Pasteur pipette, carefully transfer the C. elegans and sediment, soil, or exposed contaminant from each test well to a separate centrifuge tube (centrifuge tube #1; 10 to 15 ml). Repeat two times. Place the sample on a swing-out stand and allow it to settle for 20 minutes. Then, carefully aspirate a portion of the supernatant from the centrifuge tube and discard it. Next, add 2 ml of the modified sodium alginate solution to the centrifuge tube containing the nematodes and sediment, soil, or contaminant particles. Mix thoroughly using a test tube mixer. Centrifuge the sample again at 200 g for 2 minutes using a swing-out adapter. After centrifugation, the supernatant of the modified sodium alginate solution in the centrifuge tube contains the C. elegans and eggs. Transfer the supernatant from the centrifuge tube to a new centrifuge tube (centrifuge tube #2; 10 to 15 ml). Add 10 ml of M9 buffer to centrifuge tube #2 to wash the C. elegans and centrifuge, then aspirate and discard the supernatant. Repeat three times. Finally, the washed C. elegans were transferred to a sodium alginate culture dish for subsequent analysis.

[0156] In the C. elegans transfer method for simulated environmental exposure, the steps for preparing the modified sodium alginate solution are as follows: first, slowly add sodium alginate to deionized water and stir at a constant temperature of 25-30°C to prepare a 0.2-0.4% (preferably 0.3%) solution; adjust the pH to 4.5-5.5 with acid and stir at 300-500 r / min for 30 minutes; then add EDC・HCl at a rate of 5-10% of the mass of the sodium alginate and 2-5% of natural polyphenols (such as tannic acid); activate the solution with ultrasound at 200-300W for 0.3-0.8 hours at room temperature with continuous stirring; then add PE at a concentration of 0.02-0.04g / ml. The G600 solution is slowly added dropwise. After 10-15 minutes of addition, the reaction is continued with 150-200W ultrasound for 1-2 hours, and the stirring speed is reduced to 200-300r / min. After the reaction is completed, the pH is adjusted to 7.0±0.2 with an alkaline solution to terminate the reaction. Subsequently, it is purified with an ultrafiltration membrane with a molecular weight cutoff of 10,000 until the conductivity of the permeate is less than 10μS / cm. Finally, the solution is pre-frozen at -40-30℃ for 12-13 hours, and freeze-dried for 24-36 hours under vacuum degree <10Pa and sublimation temperature of -20-10℃. The dried solid can be re-prepared into a 1-2% improved sodium alginate solution.

[0157] A modified sodium alginate solution was used instead of the traditional Ludox solution as the separation medium. Its excellent biocompatibility and mild separation environment were utilized, combined with density adjustment and multi-step separation strategies, to effectively improve the efficiency and purity of nematodes separation from the simulated environment.

[0158] In step S2, a sodium alginate culture dish is prepared by first preparing a standard sodium alginate solution at a concentration of 0.3 g / ml and pouring 2-3 ml of the solution into a blank culture dish. The solution is then solidified through temperature-induced gelation or calcium ion-induced gelation (e.g., by adding a calcium chloride solution). After solidification, the observation plate can be stored in a refrigerator at 4°C until further experimental use. The present invention incorporates sodium alginate culture dishes as a support substrate for capturing images of C. elegans and its eggs. The gel film formed after natural drying exhibits excellent transparency and mild fixation, helping to preserve the original state of the nematode and prevent displacement or deformation during scanning. This structure facilitates the acquisition of images with a clean background and sharp edges, improving the accuracy of identifying indicators such as nematode length, area, and egg count. This culture dish is simple to prepare, low-cost, and suitable for batch processing, meeting the practical needs of high-throughput, multi-indicator environmental toxicity assessment.

[0159] In step S2, for liquid-exposed C. elegans transfer, maintain a sterile environment by gently eluting the C. elegans by adding M9 buffer (or PBS or saline) to the liquid culture medium and transferring the nematodes to a centrifuge tube using a pipette. Subsequently, centrifuge at 3000 rpm (~600g) for 1-2 minutes to pellet the nematodes. Remove the supernatant, resuspend the nematodes in fresh buffer, and then add the nematodes dropwise to the sodium alginate culture dish.

[0160] In step S2, the M9 buffer solution is prepared by adding 3 g of KH2PO4, 15.14 g of Na2HPO4·12H2O (or 6 g of Na2HPO4), 5 g of NaCl, and 1 ml of MMgSO4 to a volumetric flask, then adding water to make up to 1 L, and finally sterilizing by high pressure for 20 minutes.

[0161] In step S3, the method uses a transmission scanner (Epson V850 Pro) to continuously scan the culture dish at high frequency. The method also incorporates a dynamic time series acquisition strategy, continuously scanning the same culture dish throughout the experiment with a 3-minute interval between scans to generate a high-temporal-resolution data stream.

[0162] In step S4, the microfluidic chip used is provided with two experimental areas, both of which use the same sample inlet, and a microvalve is provided at the sample inlet;

[0163] The process of conducting a galvanotaxis experiment using the microfluidic chip includes:

[0164] S4-1. The scanned C. elegans were transferred into centrifuge tubes using M9 buffer, and the tubes were named control group and experimental group respectively. The centrifuge tubes of the control group and experimental group were shaken until the C. elegans were evenly distributed in the M9 buffer.

[0165] S4-2. Adjust the tilt angle of the microfluidic chip as needed;

[0166] S4-3, opening the microvalve in the microfluidic chip, connecting the injection port of the chip to the peristaltic pump connector, and connecting the electrode of the chip to the electrophoresis instrument interface;

[0167] S4-4, turn on the electrochemical workstation and apply a 10V electric field voltage across the electrodes;

[0168] S4-5, start the peristaltic pump to deliver C. elegans in the control group and the experimental group to the chip at a rate of 0.5 L / min;

[0169] S4-6. After observing the target C. elegans in the microfluidic chip, close the microvalve and peristaltic pump, and place the entire experimental device in a high-definition scanner for scanning to obtain galvanotaxis experimental image data;

[0170] S4-7. After acquiring the image data of the galvanotaxis experiment, open the microvalve and peristaltic pump to transfer the remaining C. elegans in the chip to the waste liquid bottle.

[0171] In the above steps, the microvalve enables on-off control and time-sequencing of the flow of liquids or biological samples (such as a suspension of Caenorhabditis elegans). Before the valve is opened, the inlet area is closed, facilitating preloading and system preparation. Once opened, the sample enters the chip smoothly at a set rate, ensuring consistent sample quantity and uniform distribution, improving experimental reproducibility and accuracy. Furthermore, the valve forms a fluid barrier between the two experimental zones, effectively preventing backflow and diffusion of the solution or nematodes within the microfluidic channel, and avoiding interference between control and experimental groups. This significantly improves the independence of grouped experiments and the comparability of data compared to traditional valveless chips. Finally, combined with the funnel-shaped structure at the inlet, the microvalve enables "first concentration, then dispersion" of the sample. When the valve is closed, the sample is concentrated at the inlet. When opened, the nematodes are guided smoothly into the main channel, avoiding channel blockage caused by the sudden influx of a large number of nematodes.

[0172] In step S5, Labelme software is used to perform polygonal annotation on the Petri dish image, generating a training set in JSON format. This annotation method involves selecting and annotating the C. elegans nematodes and eggs in the Petri dish image, naming them "worm" and "egg," respectively, to ensure that each nematode and egg is accurately identified and assigned a corresponding bounding box. Furthermore, to reduce interference from impurities in the Petri dish and improve model accuracy, overlapping nematodes and large areas of impurities are individually selected and labeled "wrong" during the annotation process. These areas are then excluded from the model training data to optimize training results.

[0173] In step S5, the MPO YOLO model (toxic effect indicator recognition model) is trained on the preprocessed training set. The initial YOLO11 model is improved to obtain the MPO YOLO model to enhance detection of C. elegans and its eggs. Specifically, a lightweight tiny objects detection head is added to the original YOLO11 detection head to enhance the recognition of small objects. Furthermore, the improved model uses a weighted combination of IoU loss and perception loss as a new localization regression loss function, Perception-IoULoss (PIoULoss), to improve detection accuracy and robustness. Model training begins with supervised learning using a training set labeled with C. elegans and its eggs to fully learn target features. Subsequently, the trained MPO YOLO model (toxic effect indicator recognition model) is evaluated on a validation set to optimize detection performance and ensure generalization, ultimately resulting in a high-precision detection model suitable for toxicity analysis.

[0174] Establishing a toxic effect indicator identification model includes:

[0175] Establish the initial model YOLO11;

[0176] Add a detection head to the initial model YOLO11, and its calculation formula is:

[0177]

[0178] in Represents input, To extract features, To process the aggregation part of the features, is the final output prediction, Represents the added detection head;

[0179] Modify the Neck part and adjust the output structure of the Head to obtain the improved model MPO YOLO, whose calculation formula is:

[0180]

[0181]

[0182]

[0183] in, To add the new feature fusion layer to the Neck part, To extract additional sources of information, is the operation function of the Neck part, For the adjusted Head structure, Indicates a connection operation. For the final improved model;

[0184] Using IoU loss and perceptual loss The weighted combination of , as the new positioning regression loss function , and its calculation formula is:

[0185]

[0186]

[0187]

[0188] in, To control the contribution weight of IoU loss and perceptual loss to the total loss, is the prediction box, is the real frame, The first Layer output, is the weighted coefficient of each layer feature, and are the image features of the predicted area and the true area respectively.

[0189] By adding an additional detection head, the MPO YOLO model becomes more flexible, adapting to requirements such as multi-task learning and multi-scale detection. By weighted optimization of the model's loss function, the MPO YOLO model not only focuses on segmentation accuracy but also improves its ability to identify subtle targets and optimizes their feature representation. This approach enables more precise segmentation and classification of nematodes of varying morphologies in toxicity analysis based on the nematode Caenorhabditis elegans. The data can then reveal the behavior of nematodes at varying levels of toxicity, providing more accurate data for subsequent detection and analysis to aid in toxicity quantification.

[0190] Step S6 uses the toxic effect index recognition model to identify the two scanned images and galvanotaxis images of the same culture dish, and the specific process of obtaining the five toxic effect indicators of Caenorhabditis elegans includes:

[0191] S6-1. Construct a quantification module for toxicity effect indicators;

[0192] S6-2. Generate a mask image and annotation file of the Caenorhabditis elegans image using the toxicity effect index quantification module;

[0193] S6-3. Based on the generated mask image of the C. elegans image, mark the connected regions of the mask image to obtain all connected regions, where each connected region corresponds to a C. elegans worm. Subsequently, calculate the pixel perimeter C of each connected region and approximate the pixel length of each nematode as C / 2. Finally, proportionally convert the pixel length to the actual length to obtain the true length of each nematode. Calculate the average length of the C. elegans worm and compare them to obtain the overall growth index.

[0194] S6-4. Generate an annotation file for the C. elegans image and obtain the number of C. elegans in the first scan , and a second scan of Caenorhabditis elegans and number of eggs , calculate the reproduction index, where the calculation formula of the reproduction index is:

[0195]

[0196] in Represents reproductive indicators;

[0197] S6-5. Calculating the intersection-over-union ratio of each C. elegans according to the generated annotation file of the first scanned C. elegans image and the mask image of the second scanned C. elegans image to obtain the overall survival rate;

[0198] The process of finding the overall survival rate includes:

[0199] Based on the first scan of the same culture dish, the C. elegans image and its annotation file are used to extract the polygonal segmentation area of ​​each nematode, and generate the corresponding mask map in the second scanned image; then, the intersection of the two scans of the same nematode is calculated. Evaluate its survival status, where the intersection and union ratio The calculation formula is:

[0200] in, Segment the nematode region for the first scan, is the nematode mask area for the second scan, represents the intersection area of ​​the two. represents the union area of ​​the two; if a nematode The value is greater than the preset survival threshold , the nematode is considered to have survived the pollutant exposure process, otherwise it is considered to have died; finally, the overall survival rate is calculated. , which is the ratio of the number of surviving nematodes to the total number of nematodes marked in the first scan image.

[0201] S6-6. Calculate the centroids of the block areas of the two images before and after the generated mask image of C. elegans. Then calculate the displacement of the centroid of each area, take the average, and normalize it to obtain the overall movement ability.

[0202] The specific process of obtaining overall athletic ability includes:

[0203] First, the mask image of the C. elegans image is divided into blocks, the contours of each area are extracted based on the image segmentation algorithm, and the centroid coordinates of each block area are calculated. and ,in are the centroid abscissa and ordinate of the block area of ​​the image mask image scanned for the first time, are the centroid abscissa and ordinate of the block area of ​​the second scanned image mask; then, calculate the centroid of each block area in the time interval Center of mass displacement within , average the centroid displacement of all block areas to obtain the overall average displacement ; Normalization is performed to eliminate the scale effect and obtain the normalized motion ability index .

[0204] S6-7. Based on the mechanical model of the behavior of C. elegans in the experimental area of ​​the microfluidic chip equipped with a tilt adjustment structure, the movement rate of C. elegans in the experimental area is calculated and used as the overall electrotaxis effect indicator.

[0205] The process of obtaining the overall galvanotaxis index includes:

[0206] First, the force analysis of Caenorhabditis elegans was performed to obtain the force parameters along the slope, including the component of gravity along the slope. The component of gravity perpendicular to the inclined plane , electric field driving force 、 and friction , the calculation formula is as follows:

[0207]

[0208]

[0209]

[0210]

[0211]

[0212] Caenorhabditis elegans moves in a tilted microfluidic chip, exhibiting a multi-dimensional motion response under the coupling of electric field and gravity components. This allows for more behavioral parameters and chip geometry parameters to be used for toxicity assessment, including the nematode's own locomotion ability. ;

[0213] Next, we conducted a dynamic analysis of the movement of C. elegans in the microfluidic chip. Since it satisfies Newton's second law, the following equation of motion is derived:

[0214]

[0215] During steady-state exercise:

[0216]

[0217]

[0218] Solve for the motion rate :

[0219]

[0220] Among them, sliding along the inclined plane is positive, The sign is determined by the direction of the electric field, is the tilt angle of the microfluidic chip, For the quality of Caenorhabditis elegans, For exercise time, is the acceleration due to gravity, is the electric field strength, is the liquid viscous resistance coefficient, is the friction coefficient, is the equivalent charge, is the net external force acting on C. elegans;

[0221] Finally, the movement rate of C. elegans was used as the overall indicator of electrotaxis.

[0222] In step S7, based on the fuzzy weight evaluation method and the information dispersion weighted method, five toxic effect indicators are integrated to achieve multi-toxicity assessment of pollutants:

[0223] S7-1. Establish a set of toxic effect indicators and a set of toxicity evaluation levels:

[0224]

[0225]

[0226] in, is a set of toxic effect indicators, is a set of toxicity evaluation grades, Toxic effect index ( They are ), Toxicity evaluation level ( low toxicity, moderate toxicity, and high toxicity, respectively);

[0227] S7-2, data preprocessing:

[0228] The raw value is converted into a relative toxicity value:

[0229]

[0230] in, For the The pollutants in The experimental group data of the indicators, The data are for the control group; is the relative toxicity value after conversion, the smaller the value, the greater the toxicity;

[0231] S7-3. Constructing triangle membership function: Setting The toxicity range of (low toxicity) is , The toxicity range is , (Highly toxic) has a toxicity range of , the toxicity value is mapped to fuzzy membership, and the triangle membership function is constructed respectively.

[0232] Low toxicity membership:

[0233]

[0234] Toxic membership:

[0235]

[0236] High toxicity membership:

[0237]

[0238] in, For the Among the pollutants The degree of membership of an indicator;

[0239] S7-4. Constructing the fuzzy membership matrix :

[0240] Based on the Pollutant exposure experimental data, construct the Fuzzy membership matrix .

[0241]

[0242] For example: When When the exposure pollutant is PFOS, the membership degree of Caenorhabditis elegans in the "low toxicity" level in the "growth" indicator is 0.8, that is, =0.8.

[0243] S7-5. Calculate the weight vector using the information dispersion weighting method

[0244] Construct the original data matrix:

[0245] Original data matrix: ;

[0246] is the number of samples with different pollutants at different concentrations; is the number of indicators;

[0247] Data standardization:

[0248]

[0249] in, and For the The minimum and maximum values ​​of the indicators, are the standard values ​​of five types of toxic effect indicators;

[0250] Calculation ratio (contribution):

[0251]

[0252] in, The contribution of each indicator;

[0253] Calculate entropy:

[0254]

[0255] in, is the entropy value of each indicator, if ,but ;

[0256] Calculate weights:

[0257]

[0258] in, Assign a value to each indicator's weight; weight vector satisfy ;

[0259] S7-6, fuzzy comprehensive operation:

[0260] Through fuzzy matrix operation and comprehensive membership of each index, the membership distribution of the overall toxicity status is obtained:

[0261]

[0262]

[0263] in is the entropy method weight vector, is a fuzzy operator, is the comprehensive membership of “low toxicity”, is the comprehensive membership of “toxicity”, The comprehensive membership degree is “high toxicity”.

[0264] S7-7. Final toxicity level determination: Determine the final toxicity level based on the maximum membership principle. :

[0265] ).

[0266] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, any changes made based on the shape and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating the multi-toxicity of pollutants based on high-throughput detection of Caenorhabditis elegans, characterized in that: include: Based on the environmental concentration and component ratio of the pollutants, the Caenorhabditis elegans is exposed to environmental pollutants in liquid culture medium or simulated environmental culture medium using a single exposure or combined exposure method; The simulated environment includes soil environment and sediment environment; According to different exposure methods, the exposed C. elegans and its eggs were transferred to the prepared sodium alginate culture dish by different methods; After the liquid in the alginate dish has dried naturally until no visible liquid film remains, a high-definition fluoroscopic scanner is used to scan the nematodes and their eggs twice in a row. The interval between the two scans is a set number of minutes, and two scanned images of the same dish are obtained. The exposed C. elegans and the control C. elegans were transferred to a microfluidic chip equipped with a tilt adjustment structure to conduct galvanotaxis experiments and obtain galvanotaxis images. Establish and train a toxic effect indicator identification model; The trained toxicity effect index recognition model was used to identify the acquired scanned images and galvanotaxis images, and five toxicity effect indicators of C. elegans were obtained. These five toxicity effect indicators are growth, reproduction, motility, survival rate, and galvanotaxis. Based on the fuzzy weight evaluation method and information dispersion weighting method, five toxic effect indicators are integrated to achieve multi-toxicity assessment of pollutants; Establishing a toxic effect indicator identification model includes: Establish the initial model YOLO11; Add a detection head to the initial model YOLO11, and its calculation formula is: f head_new =f head (f neck (f backbone (X))) Where X represents the input, f backbone For extracting features, f neck To process the aggregation part of the feature, f head is the final output prediction, f head_new Represents the added detection head; By modifying the Neck part and adjusting the output structure of the Head, we get the improved model MPOYOLO, whose calculation formula is: f′ neck (f backbone (X))=g(f neck (f backbone (X),f extra_features X))) f′ head (f′ neck (f backbone (X)))=concat(f head ,f head_new ) f final (X)=f′ head (f′ neck (f backbone (X))) Among them, f' neck For the Neck part after adding the new feature fusion layer, f extra_features To extract additional information sources, g is the operation function of the Neck part, f' head is the adjusted Head structure, concat represents the connection operation, f final For the final improved model; Using IoU loss L IoU and perceptual loss L perception The weighted combination of is used as the new positioning regression loss function L PIoU , and its calculation formula is: THE PIoU =λL IoU +(1-λ)L perception Among them, λ is the weight of controlling the contribution of IoU loss and perceptual loss to the total loss, B is the predicted box, and B g is the real frame, Ф i is the i-th layer output of the model network, w i is the weighted coefficient of each layer feature, I pred and I gt are the image features of the predicted area and the true area respectively.

2. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 1, characterized in that: For exposure of C. elegans to environmental pollutants in simulated environmental medium, a modified sodium alginate solution was used as the separation medium during the transfer of C. elegans. The transfer process was as follows: First, add 3 ml of M9 buffer to each simulated environment medium, and use a Pasteur pipette to transfer the Caenorhabditis elegans, pollutants, sediments, or soil in each simulated environment medium to a separate centrifuge tube, repeat twice; then place the centrifuge tube on a swing-out stand and let it settle naturally for 20 minutes; Afterwards, a portion of the supernatant from the centrifuge tube was aspirated and discarded; Next, add 2 ml of the modified sodium alginate solution to the centrifuge tube containing the nematodes, pollutants, sediment, or soil and mix thoroughly using a test tube mixer. Then, place the centrifuge tube in a centrifuge and centrifuge at 3000 rpm for 2 minutes. After centrifugation, the supernatant of the modified sodium alginate solution in the centrifuge tube contains the C. elegans and eggs. Then, transfer the supernatant in the centrifuge tube to a new centrifuge tube. Add 10 ml of M9 buffer to the new centrifuge tube to wash the C. elegans and centrifuge it. Then, aspirate and discard the supernatant, repeating three times. Finally, transfer the washed C. elegans to a sodium alginate culture dish. The preparation method of the improved sodium alginate solution comprises: First, slowly add sodium alginate into deionized water and stir at a constant temperature of 25-30℃ to prepare a 0.2-0.4% solution; Adjust the pH to 4.5-5.5 with acid and stir at 300-500 r / min for 30 minutes; then add 5-10% of EDC·HCl and 2-5% of natural polyphenols based on the mass of sodium alginate, activate with 200-300W ultrasound at room temperature for 0.3-0.8 hours while stirring continuously; then slowly dropwise add 0.02-0.04g / ml PEG600 solution for 10-15 minutes, and continue the reaction with 150-200W ultrasound for 1-2 hours. The stirring speed is reduced to 200-300 r / min; after the reaction is completed, the pH is adjusted to 7.0±0.2 with an alkaline solution to terminate the reaction; then, the solution is purified using an ultrafiltration membrane with a molecular weight cutoff of 10,000 until the conductivity of the permeate is less than 10 μS / cm; finally, the solution is pre-frozen at -40-30°C for 12-13 hours, freeze-dried at a vacuum degree of less than 10 Pa and a sublimation temperature of -20-10°C for 24-36 hours, and the dried solid is re-prepared into a 1-2% modified sodium alginate solution.

3. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 1, characterized in that: The microfluidic chip is provided with two experimental areas, both of which use the same sample inlet, and a microvalve is provided at the sample inlet; The process of conducting a galvanotaxis experiment using the microfluidic chip includes: The scanned C. elegans were transferred into centrifuge tubes in groups using M9 buffer, named control group and experimental group respectively. The centrifuge tubes of the control group and experimental group were shaken until the C. elegans were evenly distributed in the M9 buffer. Adjust the tilt angle of the microfluidic chip as needed; Open the microvalve in the microfluidic chip, connect the chip's injection port and peristaltic pump connector, and connect the chip's electrode and electrophoresis instrument interface; Turn on the electrochemical workstation and apply a 10V electric field voltage across the electrodes; Start the peristaltic pump to deliver C. elegans in the control and experimental groups to the chip at a rate of 0.5 L / min; After observing the target C. elegans in the microfluidic chip, the microvalve and peristaltic pump were closed, and the entire experimental device was placed in a high-definition scanner for scanning to obtain galvanotaxis experimental image data; After acquiring the image data of the galvanotaxis experiment, the microvalve and peristaltic pump are opened to transfer the remaining Caenorhabditis elegans in the chip to the waste bottle.

4. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 1, characterized in that: The toxic effect index recognition model was used to identify the two scanned images and galvanotaxis images of the same culture dish, and five toxic effect indices of Caenorhabditis elegans were obtained. The process included: Construct a quantification module for toxic effect indicators; Generate mask and annotation files of Caenorhabditis elegans images through the toxic effect index quantification module; Based on the generated mask image of the C. elegans image, the connected domains of the mask image were marked to obtain all connected regions. Each connected region corresponds to a C. elegans. Subsequently, the pixel perimeter C of each connected region was calculated, and the pixel length of each nematode was approximated as C / 2. Finally, the pixel length was proportionally converted to the actual length to obtain the true length of each nematode. The average length of the C. elegans was calculated and compared to obtain the overall growth index. Generate an annotation file for the C. elegans image, obtain the number of C. elegans N1 in the first scan, the number of C. elegans N2 and the number of eggs Q in the second scan, and calculate the reproductive index. The calculation formula for the reproductive index is: Among them, P i Represents reproductive indicators; Calculate the intersection-over-union ratio of each C. elegans according to the generated annotation file of the first scanned C. elegans image and the mask image of the second scanned C. elegans image to obtain the overall survival rate; elegans image mask was used to calculate the centroid of the block areas of the two images before and after. The displacement of the centroid of each area was then calculated, the average value was taken, and the normalization was performed to obtain the overall movement ability. Based on the mechanical model of the behavior of C. elegans in the experimental area of ​​the microfluidic chip equipped with a tilt adjustment structure, the movement rate of C. elegans in the experimental area was calculated and used as an indicator of the overall electrotaxis effect.

5. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 4, characterized in that: The process of finding the overall survival rate includes: Based on the first scan of the C. elegans image and its annotation file of the same culture dish, the polygonal segmentation region of each nematode is extracted, and the corresponding mask map is generated in the second scan image. Subsequently, the survival status of the same nematode is evaluated by calculating the intersection over union (IoU) of the two scans. The IoU calculation formula is: Among them, A is the nematode segmentation area of ​​the first scan, B is the nematode mask area of ​​the second scan, |A∩B| represents the intersection area of ​​the two, and |A∪B| represents the union area of ​​the two. If the IoU value of a nematode is greater than the preset survival judgment threshold T s , the nematode is considered to have survived the pollutant exposure process, otherwise it is considered to have died; finally, the overall survival rate R s , which is the ratio of the number of surviving nematodes to the total number of nematodes marked in the first scan image.

6. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 4, characterized in that: The process of determining overall athletic ability includes: First, the mask image of the C. elegans image is divided into blocks, the contours of each area are extracted based on the image segmentation algorithm, and the centroid coordinates C of each block area are calculated. t =(x t ,y t ) and C t+Δt =(x t+Δt ,y t+Δt ), where x t and y t are the centroid abscissa and ordinate of the block area of ​​the image mask image scanned for the first time, x t+Δt and y t+Δt are the horizontal and vertical coordinates of the centroid of the block area of ​​the second scanned image mask image; then, the centroid displacement d of each block area within the time interval Δt is calculated. i , the centroid displacements of all block areas are averaged to obtain the overall average displacement D; finally, D is normalized to eliminate the scale effect and obtain the normalized motion ability index M.

7. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 4, characterized in that: The process of obtaining the overall galvanotaxis index includes: First, the force analysis of Caenorhabditis elegans was performed to obtain the force parameters along the inclined plane, including the component of gravity along the inclined plane F. g , the component of gravity perpendicular to the inclined plane F gy , electric field driving force F e , liquid viscous resistance F d and the friction force F f , the calculation formula is as follows: F g =mgsinθ F gy =mgcosθ F e =qE F d =bv F f =μF gy =μmgcosθ Caenorhabditis elegans moves in a tilted microfluidic chip, exhibiting multi-dimensional motion responses under the coupling of electric and gravitational forces. This allows for the generation of additional behavioral parameters and chip geometry for toxicity assessment, including the nematode's own locomotion capacity (F0). Next, we conducted a dynamic analysis of the movement of C. elegans in the microfluidic chip. Since it satisfies Newton's second law, the following equation of motion is derived: During steady-state exercise: (F0±qE)-mgsinθ-bv-μmgcosθ=0 dv / dt=0 Solve for the velocity v: Where sliding along the inclined plane is positive, the "±" sign is determined by the direction of the electric field, θ is the inclination angle of the microfluidic chip, m is the mass of C. elegans, t is the movement time, g is the acceleration of gravity, E is the electric field intensity, b is the viscous resistance coefficient of the liquid, μ is the friction coefficient, q is the equivalent charge, and F total is the net external force acting on C. elegans; Finally, the movement rate of C. elegans was used as the overall indicator of electrotaxis.

8. The method for multi-toxicity assessment of pollutants based on high-throughput detection of Caenorhabditis elegans according to claim 1, characterized in that: Based on the fuzzy weight evaluation method and the information dispersion weighted method, the process of integrating five toxic effect indicators to achieve multi-toxicity assessment of pollutants includes: Establish a set of toxic effect indicators and a set of toxicity evaluation levels: U={u1,u2,u3,u4,u5}={growth, reproduction, motility, survival rate, galvanotaxis} V={v1,v2,v3}={low toxicity, medium toxicity, high toxicity} Among them, U is the toxic effect index set, V is the toxicity evaluation level set, u1, u2, u3, u4, u5 are growth, reproduction, motility, survival rate and galvanotaxis, respectively, v1, v2, v3 are low toxicity, medium toxicity and high toxicity, respectively; Data preprocessing: The raw value is converted into a relative toxicity value: Among them, x ij is the experimental group data of the i-th pollutant in the j-th index, x 0j The data of the control group; T ij is the relative toxicity value after conversion, the smaller the value, the greater the toxicity; Construct the triangle membership function: The toxicity range of v1 is set to [50%-100%], the toxicity range of v2 is set to [25%-50%], and the toxicity range of v3 is set to [0%-25%]. The toxicity values ​​are mapped to fuzzy membership, and triangular membership functions are constructed respectively. Low toxicity membership: Toxic membership: High toxicity membership: Among them, μ ij is the membership degree of the jth indicator in the i-th pollutant; Construct the fuzzy membership matrix R i : Based on the i-th pollutant exposure experimental data, construct the i-th fuzzy membership matrix R i : The information dispersion weighted method is used to calculate the weight vector W: Construct the original data matrix: Original data matrix: X = [x ij ] m×n ; m is the number of samples with different pollutants at different concentrations; n is the number of indicators; Data standardization: Among them, min(x j ) and max(x j ) is the minimum and maximum value of the jth index, r ij are the standard values ​​of five types of toxic effect indicators; Calculate contribution: Among them, p ij The contribution of each indicator; Calculate entropy: Among them, e j Is the entropy value of each indicator, if p ij =0, then p ij ln(p ij )=0; Calculate weights: Among them, w j Assign a value to each indicator weight; the weight vector W = [w1,w2,w3,w4,w5] satisfies Fuzzy comprehensive operation: Through fuzzy matrix operation and comprehensive membership of each index, the membership distribution of the overall toxicity status is obtained: Where W = [w1, w2, w3, w4, w5] is the entropy weight vector, ° is the fuzzy operator, b1 is the comprehensive membership of "low toxicity", b2 is the comprehensive membership of "medium toxicity", and b3 is the comprehensive membership of "high toxicity". Final toxicity level determination: According to the maximum membership principle, the final toxicity level v is determined. k :

Images