Method and device for predicting bioequivalent concentration of environmental endocrine disrupter

Abstract

The embodiment of the invention provides a method and a device for predicting the bioequivalent concentration of an environmental endocrine disrupter. The method comprises the following steps: receiving living body exposure data when fish is exposed to environmental endocrine disrupters and in-vitro exposure data related to a toxic action pathway, which are sent by data acquisition equipment; wherein the living body exposure data comprises an external exposure concentration; inputting the external exposure concentration into a pre-constructed physiological toxicokinetic model to output the maximum steady-state plasma concentration; acquiring dose-effect curve data according to the in-vitro exposure data related to the toxic action pathway; acquiring in-vitro biological activity concentration from the dose-effect curve data; calculating a bioequivalent concentration according to the maximum steady-state plasma concentration and the in-vitro biological activity concentration; and sending the bio-equivalent concentration to a display terminal for display. According to the method, the bioequivalent concentration can be accurately predicted, so that the toxic effect of the target site concentration of the environmental endocrine disrupter on the fish is accurately evaluated.

Description

Technical Field

[0001] The present application relates to the field of aquatic ecology, and in particular to a method and device for predicting the bioequivalent concentration of environmental endocrine disruptors. Background Art

[0002] Bioequivalent concentration refers to the maximum environmental concentration threshold at which a compound does not produce toxic effects on the target biological receptor. Environmental endocrine disruptors are a class of exogenous compounds that can interfere with the normal endocrine function of organisms. They have been widely detected in environmental water bodies and threaten the normal growth and survival of fish. In order to accurately assess the toxic effects of the target site concentration of environmental endocrine disruptors on fish, it is necessary to convert the external exposure concentration of environmental endocrine disruptors into the bioequivalent concentration of fish receptors.

[0003] Currently, existing technologies use the external exposure concentrations of environmental endocrine disruptors measured directly in environmental samples as the bioequivalent concentrations of fish receptors to evaluate toxic effects.

[0004] However, not all of the directly measured external exposure concentrations of environmental endocrine disruptors enter the fish body, making it impossible to accurately assess the toxic effects of target site concentrations of environmental endocrine disruptors on fish. Summary of the invention

[0005] The embodiments of the present application provide a method and device for predicting the bioequivalent concentration of environmental endocrine disruptors, so as to improve the accuracy of predicting the bioequivalent concentration of environmental endocrine disruptors and accurately evaluate the toxic effects of the target site concentration of environmental endocrine disruptors on fish.

[0006] In a first aspect, an embodiment of the present application provides a method for predicting the bioequivalent concentration of an environmental endocrine disruptor, comprising: receiving in vivo exposure data for fish exposed to environmental endocrine disruptors and in vitro exposure data related to toxic action pathways sent by a data acquisition device; wherein the in vivo exposure data includes external exposure concentrations; inputting the external exposure concentrations into a pre-constructed physiological toxicokinetic model so that the pre-constructed physiological toxicokinetic model outputs a maximum steady-state plasma concentration; obtaining dose-effect curve data based on the in vitro exposure data related to the toxic action pathway; obtaining an in vitro bioactive concentration from the dose-effect curve data; calculating a bioequivalent concentration based on the maximum steady-state plasma concentration and the in vitro bioactive concentration; wherein the bioequivalent concentration is the maximum environmental concentration threshold that does not produce toxic effects when fish are exposed to environmental endocrine disruptors; and sending the bioequivalent concentration to a display terminal so that the display terminal displays the bioequivalent concentration.

[0007] In one possible embodiment, based on in vitro exposure data related to the toxic action pathway, obtaining dose-effect curve data includes: obtaining multiple dosing concentrations and multiple effect strengths from the in vitro exposure data related to the toxic action pathway, wherein one dosing concentration corresponds to one effect strength; and obtaining the dose-effect curve data by using a data processing tool with the logarithm of the dosing concentration as the horizontal axis and the effect strength as the vertical axis.

[0008] In one possible embodiment, the bioequivalent concentration is calculated based on the maximum steady-state plasma concentration and the in vitro biological activity concentration, and the formula is:

[0009]

[0010] In the formula, represents the bioequivalent concentration, Indicates the in vitro bioactive concentration, represents the maximum steady-state plasma concentration.

[0011] In a possible implementation, after calculating the bioequivalent concentration, the method further includes: receiving multiple in vivo effect concentrations sent by a data acquisition device, and multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations; obtaining the predicted no-effect concentration corresponding to each bioequivalent concentration according to the multiple bioequivalent concentrations to obtain multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations; comparing the multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations with the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations to obtain a comparison result; and sending the comparison result to a display terminal so that the display terminal displays the comparison result.

[0012] In a possible embodiment, according to multiple bioequivalent concentrations, obtaining a predicted no-effect concentration corresponding to each bioequivalent concentration includes: sorting the multiple bioequivalent concentrations according to the Weibull distribution to obtain a plurality of sorted bioequivalent concentrations; based on the sorted multiple bioequivalent concentrations, according to the sorting sequence number of each bioequivalent concentration, obtaining a percentage sorting parameter of each bioequivalent concentration; performing linear regression with each bioequivalent concentration after logarithmic transformation as the abscissa and the percentage sorting parameter of each bioequivalent concentration as the ordinate to obtain linear regression data; using the slope and intercept of each bioequivalent concentration in the linear regression data to obtain the predicted no-effect concentration corresponding to each bioequivalent concentration.

[0013] In a possible implementation, based on the sorted multiple bioequivalent concentrations, according to the sorting sequence number of each bioequivalent concentration, the percentage sorting parameter of each bioequivalent concentration is obtained, and the formula is:

[0014]

[0015] In the formula, represents the percentage ranking parameter for each bioequivalence concentration, Indicates the ranking number of each bioequivalence concentration, Represents the number of ranked multiple bioequivalence concentrations.

[0016] In one possible implementation, the slope and intercept of each bioequivalent concentration in the linear regression data are used to obtain the predicted no-effect concentration corresponding to each bioequivalent concentration, and the formula is:

[0017]

[0018] In the formula, represents the predicted no-effect concentration corresponding to each bioequivalence concentration, represents the probability value of the desired protection level, represents the slope, represents the intercept.

[0019] In a second aspect, an embodiment of the present application provides a device for predicting the bioequivalent concentration of environmental endocrine disruptors, comprising:

[0020] The receiving module is used to receive the in vivo exposure data of fish exposed to environmental endocrine disruptors and the in vitro exposure data related to the toxic action pathway sent by the data acquisition device; wherein the in vivo exposure data includes the external exposure concentration.

[0021] The output module is used to input the external exposure concentration into the pre-built physiological toxicokinetic model, so that the pre-built physiological toxicokinetic model outputs the maximum steady-state plasma concentration.

[0022] The first acquisition module is used to acquire dose-effect curve data based on in vitro exposure data related to the toxic action pathway.

[0023] The second acquisition module is used to obtain in vitro bioactive concentration from the dose-effect curve data.

[0024] The calculation module is used to calculate the bioequivalent concentration based on the maximum steady-state plasma concentration and the in vitro biological activity concentration; the bioequivalent concentration is the maximum environmental concentration threshold that does not produce toxic effects when fish are exposed to environmental endocrine disruptors.

[0025] The sending module is used to send the bioequivalent concentration to the display terminal so that the display terminal can display the bioequivalent concentration.

[0026] In a third aspect, an embodiment of the present application provides a server, including: a memory, a processor;

[0027] The memory stores computer-executable instructions;

[0028] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0029] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0030] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0031] The method and device for predicting the bioequivalent concentration of environmental endocrine disruptors provided in the embodiment of the present application obtain the maximum steady-state plasma concentration corresponding to different external exposure concentrations through a pre-constructed physiological toxicokinetic model; wherein the maximum steady-state plasma concentration is the real-time concentration of the substance in the fish. According to the in vitro exposure data related to the toxic action pathway, the dose-effect curve data is obtained to obtain the administration concentration that produces different effect strengths, that is, the in vitro bioactive concentration; according to the in vitro bioactive concentration, the bioequivalent concentration of fish exposed to the external exposure concentration of environmental endocrine disruptors can be accurately predicted. The bioequivalent concentration is the parameter most directly related to the toxic effect, so as to accurately evaluate the toxic effect of the target site concentration of environmental endocrine disruptors on fish. In addition, on the one hand, the formulation of traditional water quality benchmarks usually only considers the death endpoint of organisms, resulting in the ecological risks of many environmental endocrine disruptors being ignored. According to the in vitro bioactive concentration, the bioequivalent concentration obtained when fish are exposed to the external exposure concentration of environmental endocrine disruptors can identify the sensitive toxicity endpoint and the tolerant toxicity endpoint, so as to accurately evaluate the chronic toxicity of the target site concentration of environmental endocrine disruptors on aquatic organisms. On the other hand, in the formulation of traditional water quality standards for compounds, it is usually based on experimental data from a large number of organisms. The bioequivalent concentration obtained by the method of the embodiment of the present application can avoid the consumption of a large number of experimental organisms, and the experimental principles of reduction, substitution and optimization advocated by the compound can reduce the consumption of a large amount of manpower, material resources and financial resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0033] Figure 1 A schematic diagram of a scenario for predicting the bioequivalent concentration of environmental endocrine disruptors provided in an embodiment of the present application;

[0034] Figure 2 A schematic diagram of a process for predicting the bioequivalent concentration of environmental endocrine disruptors provided in an embodiment of the present application;

[0035] Figure 3 A result schematic diagram of the logarithmic value of the difference multiple between the bioequivalent concentration and the in vivo effect concentration provided in the examples of the present application;

[0036] Figure 4 A schematic diagram of the division structure of the physiological tissue compartments of fish provided in an embodiment of the present application;

[0037] Figure 5 A schematic diagram of the structure of a device for predicting the bioequivalent concentration of environmental endocrine disruptors provided in an embodiment of the present application;

[0038] Figure 6 A schematic diagram of the structure of a server provided in an embodiment of the present application.

[0039] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0040] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0041] Figure 1 A schematic diagram of a scenario of a method for predicting the bioequivalent concentration of environmental endocrine disruptors provided in an embodiment of the present application, such as Figure 1 As shown, the application scenario includes: a data acquisition device 101 , a server 102 and a display terminal 103 .

[0042] The data acquisition device 101 is used to collect in vivo exposure data and in vitro exposure data related to toxic action pathways of fish exposed to environmental endocrine disruptors, and send them to the server 101; the server 101 can be a single server or a cluster of multiple servers. It is used to predict the bioequivalent concentration and send the bioequivalent concentration to the display terminal 103; the display terminal 103 is used to display the bioequivalent concentration.

[0043] Bioequivalent concentration refers to the maximum environmental concentration threshold at which a compound does not produce toxic effects on the target biological receptor. Environmental endocrine disruptors are a class of exogenous compounds that can interfere with the normal endocrine function in organisms. They have been widely detected in environmental water bodies, threatening the normal growth and survival of fish. In order to accurately assess the toxic effects of the target site concentrations of environmental endocrine disruptors on fish, it is necessary to convert the external exposure concentrations of environmental endocrine disruptors into the bioequivalent concentrations of fish receptors. At present, the existing technology uses the external exposure concentrations of environmental endocrine disruptors directly measured in environmental samples as the bioequivalent concentrations of fish receptors to evaluate toxic effects. However, the directly measured external exposure concentrations of environmental endocrine disruptors will not all enter the fish body, resulting in the inability to accurately assess the toxic effects of the target site concentrations of environmental endocrine disruptors on fish.

[0044] In response to the above technical problems, the present application proposes the following technical concept: Considering that the directly measured external exposure concentration of environmental endocrine disruptors will not all enter the fish body, the inventors have considered forward applications on the one hand, and obtained the maximum steady-state plasma concentration of the external exposure concentration entering the fish body through a pre-constructed physiological toxicokinetic model; on the other hand, reverse applications are considered. After the external exposure concentration enters the fish body, the fish tissues are tested in vitro to obtain in vitro exposure data related to the toxic action pathway, and the in vitro bioactive concentration is obtained from the in vitro exposure data. Therefore, the in vitro bioactive concentration is equivalent to the maximum steady-state plasma concentration. Combining the pre-constructed physiological toxicokinetic model and the in vitro-in vivo extrapolation relationship, the in vitro bioactive concentration and the maximum steady-state plasma concentration are obtained, and then the bioequivalent concentration of the environmental endocrine disruptor is obtained. The bioequivalent concentration is the parameter most directly related to the toxic effect. The bioequivalent concentration can accurately evaluate the toxic effect of the target site concentration of environmental endocrine disruptors on fish.

[0045] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0046] Figure 2 A schematic diagram of a method for predicting the bioequivalent concentration of environmental endocrine disruptors provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the method includes:

[0047] S201: Receive in vivo exposure data for fish exposed to environmental endocrine disruptors and in vitro exposure data related to toxic action pathways sent by a data acquisition device; wherein the in vivo exposure data includes external exposure concentrations. Among them, the in vivo exposure data are exposure scenario parameters and toxicity experimental data related to water exposure to environmental endocrine disruptors collected by the data acquisition device through literature and databases. Optionally, the in vivo exposure data include exposure scenario parameters including external exposure concentrations, such as water temperature, exposure water volume, fish species, body weight, exposure time, toxicity assessment endpoints, and toxic effect trigger values. The screening criteria for in vivo exposure data are as follows: from aqueous solution exposure, including at least three treatment concentrations and one control group, and explaining the experimental conditions, namely water temperature, body weight, growth stage, and sex of the fish.

[0048] Among them, the in vitro exposure data related to the toxic action pathway are in vitro exposure data obtained from in vitro tests on fish tissues or cells, taking into account data from at least three treatment concentrations. Since the in vitro toxicity data of some compounds are only available for limited species, the intrinsic sensitivity of the compounds is extrapolated across species.

[0049] Optionally, the in vitro exposure data related to the toxic effect pathway includes: in vitro exposure data related to the estrogen receptor pathway.

[0050] Alternatively, the fish tissue may be fish hepatocytes.

[0051] S202: Inputting the external exposure concentration into a pre-constructed physiological toxicokinetic model, so that the pre-constructed physiological toxicokinetic model outputs a maximum steady-state plasma concentration.

[0052] Among them, the in vivo exposure data includes multiple different external exposure concentrations.

[0053] Optionally, the external exposure concentration can be 0.5 mg / L, 1 mg / L, 1.5 mg / L, 2 mg / L, etc.

[0054] Exemplarily, the external exposure concentration is 1 mg / L, and the external exposure concentration is input into the pre-constructed physiological toxicokinetic model so that the pre-constructed physiological toxicokinetic model outputs a maximum steady-state concentration value.

[0055] S203: Obtain dose-effect curve data based on in vitro exposure data related to toxic action pathways.

[0056] Among them, in toxicology or pharmacology research, the strength of the toxic or pharmacological effect is related to the concentration of the poison or the drug, that is, the dose-effect curve data, the vertical axis is the effect intensity, and the horizontal axis is the drug concentration.

[0057] Specifically, multiple dosing concentrations and multiple effect strengths are obtained from in vitro exposure data related to the toxic action pathway, where one dosing concentration corresponds to one effect strength; the logarithm of the dosing concentration is used as the horizontal axis and the effect strength is used as the vertical axis, and the dose-effect curve data is obtained through data processing tools.

[0058] S204: Obtain in vitro bioactive concentration from dose-effect curve data.

[0059] In this example, the dose-effect curve data showed an S-shape.

[0060] Alternatively, the administration concentrations producing different effect strengths can be selected as the in vitro bioactive concentrations. For example, the administration concentration producing 50% effect strength, i.e., AC50, is obtained from the dose-effect curve data.

[0061] S205: Calculate the bioequivalent concentration based on the maximum steady-state plasma concentration and the in vitro biological activity concentration; the bioequivalent concentration is the maximum environmental concentration threshold that does not produce toxic effects when fish are exposed to environmental endocrine disruptors.

[0062] Specifically, the bioequivalent concentration is calculated based on the maximum steady-state plasma concentration and the in vitro bioactive concentration, using the formula:

[0063]

[0064] In the formula, represents the bioequivalent concentration, Indicates the in vitro bioactive concentration, represents the maximum steady-state plasma concentration.

[0065] In this example, the bioequivalent concentration is positively correlated with the in vitro bioactive concentration, and the bioequivalent concentration is negatively correlated with the maximum steady-state plasma concentration.

[0066] S206: Send the bioequivalent concentration to the display terminal so that the display terminal displays the bioequivalent concentration.

[0067] In summary, the maximum steady-state plasma concentration corresponding to different external exposure concentrations can be obtained through the pre-constructed physiological toxicokinetic model; the maximum steady-state plasma concentration is the real-time concentration of the substance in the fish. According to the in vitro exposure data related to the toxic action pathway, the dose-effect curve data can be obtained, and the administration concentration that produces different effect strengths, that is, the in vitro bioactive concentration, can be obtained; according to the in vitro bioactive concentration, the bioequivalent concentration when fish are exposed to the external exposure concentration of environmental endocrine disruptors can be accurately predicted. The bioequivalent concentration is the parameter most directly related to the toxic effect, and can accurately evaluate the toxic effect of the target site concentration of environmental endocrine disruptors on fish. In addition, on the one hand, the formulation of traditional water quality benchmarks usually only considers the death endpoint of organisms, resulting in the ecological risks of many environmental endocrine disruptors being ignored. According to the in vitro bioactive concentration, the bioequivalent concentration obtained when fish are exposed to the external exposure concentration of environmental endocrine disruptors can identify sensitive toxicity endpoints and tolerant toxicity endpoints, and can accurately evaluate the chronic toxic effects of environmental endocrine disruptors on aquatic organisms. On the other hand, in the formulation of traditional water quality benchmarks for compounds, it is usually based on experimental data from a large number of organisms. The bioequivalent concentration obtained by the method of the embodiment of the present application can avoid the consumption of a large number of experimental organisms, and compound the experimental principles of reduction, substitution and optimization, and reduce a large amount of manpower, material and financial resources.

[0068] Optionally, the accuracy of the predicted bioequivalent concentration can be verified by calculating the difference multiple between the bioequivalent concentration and the in vivo effect concentration, wherein a difference multiple within 10 times indicates good prediction accuracy, and a smaller difference multiple indicates better prediction accuracy.

[0069] For example, Figure 3 This is a result diagram of the logarithmic value of the difference multiple between the bioequivalent concentration and the in vivo effect concentration provided in the examples of this application. Figure 3 As shown, the horizontal axis is the species, including zebrafish, fathead minnow, stickleback, rainbow trout and carp, and the vertical axis is the logarithm of the difference multiple.

[0070] Based on the above examples, in this example, the accuracy of the calculated bioequivalent concentration was evaluated, as detailed below:

[0071] S301: receiving a plurality of in vivo effect concentrations sent by a data acquisition device, and a plurality of predicted no-effect concentrations corresponding to the plurality of in vivo effect concentrations.

[0072] Among them, the multiple in vivo effect concentrations are measured data obtained through experiments; the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations are obtained by computer based on the measured in vivo effect concentrations.

[0073] S302: According to the multiple bioequivalent concentrations, a predicted no-effect concentration corresponding to each bioequivalent concentration is obtained to obtain multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations.

[0074] In this embodiment, multiple bioequivalent concentrations of different external exposure concentrations are obtained.

[0075] Optionally, the predicted no-effect concentration corresponding to each bioequivalent concentration is obtained by the chemical toxicity distribution probability method.

[0076] Among them, the chemical toxicity distribution probability method uses the available toxicity data of chemicals with similar modes of action or chemical categories to calculate environmental safety values ​​based on the probability distribution of toxicity values ​​for specific endpoints in ecological receptors. The 5th percentile of the output of the chemical toxicity distribution probability method is selected to calculate the predicted no-effect concentration. If the 5th percentile is selected in the calculation of the chemical toxicity distribution probability method, then the safety threshold representing 95% of the compounds with the same mode of action will be higher than the concentration corresponding to the 5th percentile.

[0077] Specifically, step S302 includes S3021 to S3024:

[0078] S3021: Sort multiple bioequivalent concentrations according to Weibull distribution to obtain multiple sorted bioequivalent concentrations.

[0079] S3022: Based on the sorted multiple bioequivalent concentrations, obtain the percentage sorting parameter of each bioequivalent concentration according to the sorting sequence number of each bioequivalent concentration.

[0080] Specifically, based on the sorted multiple bioequivalent concentrations, according to the sorting sequence number of each bioequivalent concentration, the percentage sorting parameter of each bioequivalent concentration is obtained, and the formula is:

[0081]

[0082] In the formula, represents the percentage ranking parameter for each bioequivalence concentration, Indicates the ranking number of each bioequivalence concentration, Represents the number of ranked multiple bioequivalence concentrations.

[0083] S3023: Perform linear regression with each bioequivalent concentration after logarithmic transformation as the horizontal axis and the percentage ranking parameter of each bioequivalent concentration as the vertical axis to obtain linear regression data.

[0084] Optionally, each bioequivalent concentration after Log10 transformation is used as the abscissa.

[0085] S3024: Use the slope and intercept of each bioequivalence concentration in the linear regression data to obtain the predicted no-effect concentration corresponding to each bioequivalence concentration.

[0086] Specifically, the slope and intercept of each bioequivalent concentration in the linear regression data are used to obtain the predicted no-effect concentration corresponding to each bioequivalent concentration. The formula is:

[0087]

[0088] In the formula, represents the predicted no-effect concentration corresponding to each bioequivalence concentration, represents the probability value of the desired protection level, represents the slope, represents the intercept.

[0089] Optionally, the actual exposure concentration measured in the environment is compared with the predicted no-effect concentration. If the ratio is greater than 1, it means that the environmental concentration has reached the biological tolerance threshold and the organism will be at risk; if the ratio is less than 1, it means that the environmental concentration has not reached the biological tolerance threshold.

[0090] S303: Compare the multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations with the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations to obtain a comparison result.

[0091] In this embodiment, the multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations are calculated based on the method of the embodiment of the present application; the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations are measured data. The multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations are compared with the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations to determine whether the multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations are within the preset error range of the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations. If they are within the preset error range, it means that the comparison results are consistent; if they are not within the preset error range, it means that the comparison results are inconsistent.

[0092] S304: Send the comparison result to the display terminal so that the display terminal displays the comparison result.

[0093] In summary, multiple predicted no-effect concentrations corresponding to multiple bioequivalent concentrations are obtained. By comparing multiple predicted no-effect concentrations corresponding to multiple bioequivalent concentrations with multiple predicted no-effect concentrations corresponding to multiple in vivo effect concentrations, if the comparison results are consistent, it means that the above embodiment can accurately predict the bioequivalent concentration. In addition, the predicted no-effect concentration corresponding to the bioequivalent concentration is compared with the actual exposure concentration measured in the environment. According to the ratio of the predicted no-effect concentration to the actual exposure concentration measured in the environment, it can be judged whether the biological tolerance threshold has been reached, and then it can be judged whether the environmental endocrine disruptors currently pose an ecological risk to fish.

[0094] On the basis of the above-mentioned embodiments, in this embodiment, the process of obtaining a pre-constructed physiological toxicokinetic model is introduced, as detailed as follows:

[0095] Sa: The fish were divided into compartments by an initial physiological toxicokinetic model of fish.

[0096] Figure 4 This is a schematic diagram of the division structure of the physiological tissue compartments of fish provided in the embodiment of the present application. Figure 4 The physiological tissue compartments of the fish shown contain a total of 12 compartments: brain, gonads, fat, well-perfused tissues, poorly perfused tissues, skin, arterial blood, gastrointestinal tract, kidneys, liver, venous blood and gills. Among them, the gills are important respiratory organs, as well as organs for water transport and food filtration. The absorption and removal of environmental endocrine disruptors through the gills are considered to be a reversible exchange process, which is limited by the environmental endocrine disruptor transport capacity of blood and water flow. Environmental endocrine disruptors are mainly absorbed through gill respiration and are considered to be mixed instantaneously in the compartments. The distribution of environmental endocrine disruptors in various tissues is determined by the blood flow to each compartment and the distribution coefficient between each compartment and the blood. Venous blood flowing out of well-perfused tissues and gonads converges into the portal vein and enters the liver; a portion of venous blood outside the skin and poorly perfused tissues is considered to enter the kidneys directly.

[0097] Sb: Determine the mass balance differential equations of environmental endocrine disruptors in each compartment.

[0098] In this embodiment, the total mass balance differential equation for each compartment is a universal equation for each compartment, and is also applicable to the brain, gonads, fat, fully perfused tissue, insufficiently perfused tissue and skin; the mass balance differential equations for arterial blood, gastrointestinal tract, kidneys, venous blood and liver are modified based on the universal equation according to the characteristics of each compartment to characterize the physiological processes in each compartment.

[0099] Sc: Receive species-specific physiological parameters, compound-specific physicochemical parameters and toxicometabolism parameters sent by data acquisition equipment.

[0100] Optionally, the species-specific physiological parameters include specific physiological parameters of zebrafish, rainbow trout, fathead minnow, stickleback and carp.

[0101] Optionally, the compound-specific physicochemical parameters include specific physicochemical parameters of organophosphates, pesticides, and pharmaceuticals and personal care products.

[0102] Sd: Optimize multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters.

[0103] Optionally, the plurality of model parameters include unbound fraction of the compound, lipid-water distribution coefficient, and liver clearance.

[0104] Se: Correct the exchange coefficient of the fish gill chemical flux to obtain the corrected exchange coefficient of the fish gill chemical flux.

[0105] Sf: The temperature prediction equation and the growth equation are nested into the initial physiological toxicokinetic model to obtain the first physiological toxicokinetic model.

[0106] Optionally, the temperature prediction equation is the Arrhenius equation; and the growth equation is the von Bertalanffy growth equation.

[0107] Sg: According to the mass balance differential equations of each compartment, species-specific physiological parameters, compound-specific physicochemical parameters, toxicokinetic parameters, multiple optimized model parameters and the exchange coefficient of corrected fish gill chemical flux, the first physiological toxicokinetic model is optimized to obtain the second physiological toxicokinetic model; wherein the second physiological toxicokinetic model is a pre-constructed physiological toxicokinetic model.

[0108] In summary, the pre-constructed physiological toxicokinetic model divides fish into different compartments, simulates the absorption, distribution, metabolism, and excretion of environmental endocrine disruptors in each compartment, and can accurately convert the external exposure concentration of environmental endocrine disruptors into the maximum steady-state plasma concentration in fish, thereby improving the accuracy of the bioequivalent concentration. In addition, by changing the species-specific physiological parameters, compound-specific physicochemical parameters, and toxicometabolism parameters of the pre-constructed physiological toxicokinetic model, cross-species and cross-compound ecological risk assessment can be achieved.

[0109] Figure 5 The schematic diagram of the structure of the bioequivalent concentration prediction device for environmental endocrine disruptors provided in the embodiment of the present application is as follows: Figure 5 As shown, the bioequivalent concentration prediction device for environmental endocrine disruptors provided in this embodiment includes: a receiving module 501, an output module 502, a first acquisition module 503, a second acquisition module 504, a calculation module 505 and a sending module 506.

[0110] The receiving module 501 is used to receive the in vivo exposure data of fish exposed to environmental endocrine disruptors and the in vitro exposure data related to the toxic action pathway sent by the data acquisition device; wherein the in vivo exposure data includes the external exposure concentration;

[0111] An output module 502, for inputting the external exposure concentration into a pre-constructed physiological toxicokinetic model, so that the pre-constructed physiological toxicokinetic model outputs a maximum steady-state plasma concentration;

[0112] A first acquisition module 503 is used to acquire dose-effect curve data according to in vitro exposure data related to the toxic action pathway;

[0113] The second acquisition module 504 is used to obtain the in vitro biological activity concentration from the dose-effect curve data;

[0114] A calculation module 505 is used to calculate a bioequivalent concentration according to the maximum steady-state plasma concentration and the in vitro biological activity concentration; wherein the bioequivalent concentration is a maximum environmental concentration threshold that does not produce toxic effects when fish are exposed to environmental endocrine disruptors;

[0115] The sending module 506 is used to send the bioequivalent concentration to the display terminal so that the display terminal displays the bioequivalent concentration.

[0116] In a possible embodiment, the first acquisition module 503 is specifically used to: obtain multiple dosing concentrations and multiple effect strengths from in vitro exposure data related to the toxic action pathway, where one dosing concentration corresponds to one effect strength; and obtain dose-effect curve data through a data processing tool using the logarithm of the dosing concentration as the horizontal axis and the effect strength as the vertical axis.

[0117] In a possible implementation, the calculation module 505 has the formula:

[0118]

[0119] In the formula, represents the bioequivalent concentration, Indicates the in vitro bioactive concentration, represents the maximum steady-state plasma concentration.

[0120] In a possible embodiment, the bioequivalent concentration prediction device for environmental endocrine disruptors also includes: a comparison module, which is used to receive multiple in vivo effect concentrations sent by a data acquisition device, and multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations; according to the multiple bioequivalent concentrations, obtain the predicted no-effect concentration corresponding to each bioequivalent concentration to obtain multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations; compare the multiple predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations with the multiple predicted no-effect concentrations corresponding to the multiple in vivo effect concentrations to obtain a comparison result; and send the comparison result to a display terminal so that the display terminal displays the comparison result.

[0121] In a possible embodiment, the comparison module also includes an acquisition unit, which is used to sort the multiple bioequivalent concentrations according to the Weibull distribution to obtain the sorted multiple bioequivalent concentrations; based on the sorted multiple bioequivalent concentrations, according to the sorting sequence number of each bioequivalent concentration, obtain the percentage sorting parameter of each bioequivalent concentration; perform linear regression with each bioequivalent concentration after logarithmic transformation as the horizontal axis and the percentage sorting parameter of each bioequivalent concentration as the vertical axis to obtain linear regression data; use the slope and intercept of each bioequivalent concentration in the linear regression data to obtain the predicted no-effect concentration corresponding to each bioequivalent concentration.

[0122] In a possible implementation, the acquisition unit formula is:

[0123]

[0124] In the formula, represents the percentage ranking parameter for each bioequivalence concentration, Indicates the ranking number of each bioequivalence concentration, Represents the number of ranked multiple bioequivalence concentrations.

[0125] In a possible implementation, the acquisition unit formula is:

[0126]

[0127] In the formula, represents the predicted no-effect concentration corresponding to each bioequivalence concentration, represents the probability value of the desired protection level, represents the slope, represents the intercept.

[0128] The device for predicting the bioequivalent concentration of environmental endocrine disruptors provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be described in detail here.

[0129] Figure 6 This is a schematic diagram of the structure of the server provided in the embodiment of the present application. Figure 6 As shown, the server provided in this embodiment includes: at least one processor 601 and a memory 602. Optionally, the server also includes a communication component 603. The processor 601, the memory 602 and the communication component 603 are connected via a bus 604.

[0130] In a specific implementation process, at least one processor 601 executes the computer execution instructions stored in the memory 602, so that at least one processor 601 executes the above method.

[0131] The specific implementation process of the processor 601 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0132] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0133] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0134] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0135] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0136] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0137] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0138] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0139] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0140] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0141] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0142] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0143] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0144] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for predicting the bioequivalent concentration of environmental endocrine disruptors, characterized in that: Applicable to servers, including: Receiving in vivo exposure data and in vitro exposure data related to toxic action pathways of fish exposed to environmental endocrine disruptors sent by a data acquisition device; wherein the in vivo exposure data includes external exposure concentrations; Inputting the external exposure concentration into a pre-constructed physiological toxicokinetic model, so that the pre-constructed physiological toxicokinetic model outputs a maximum steady-state plasma concentration; Obtaining dose-effect curve data based on the in vitro exposure data associated with the toxic action pathway; Obtaining in vitro bioactive concentrations from the dose-effect curve data; Calculate the bioequivalent concentration according to the maximum steady-state plasma concentration and the in vitro biological activity concentration; wherein the bioequivalent concentration is the maximum environmental concentration threshold that does not produce toxic effects when fish are exposed to the environmental endocrine disruptor; The bioequivalent concentration is sent to a display terminal so that the display terminal displays the bioequivalent concentration.

2. The method according to claim 1, characterized in that The step of obtaining dose-effect curve data based on the in vitro exposure data related to the toxic action pathway comprises: Obtaining multiple dosing concentrations and multiple effect strengths from the in vitro exposure data related to the toxic action pathway, wherein one dosing concentration corresponds to one effect strength; The dose-effect curve data are obtained by using the logarithm of the administration concentration as the abscissa and the effect intensity as the ordinate through data processing tools.

3. The method according to claim 1, characterized in that The bioequivalent concentration is calculated based on the maximum steady-state plasma concentration and the in vitro biological activity concentration, and the formula is: In the formula, represents the bioequivalent concentration, represents the in vitro biological activity concentration, represents the maximum steady-state plasma concentration.

4. The method according to any one of claims 1 to 3, characterized in that: After calculating the bioequivalent concentration, it also includes: receiving a plurality of in vivo effect concentrations sent by the data acquisition device, and a plurality of predicted no-effect concentrations corresponding to the plurality of in vivo effect concentrations; According to the multiple bioequivalent concentrations, obtaining a predicted no-effect concentration corresponding to each bioequivalent concentration, so as to obtain a plurality of predicted no-effect concentrations corresponding to the multiple bioequivalent concentrations; Comparing a plurality of predicted no-effect concentrations corresponding to the plurality of bioequivalent concentrations with a plurality of predicted no-effect concentrations corresponding to the plurality of in vivo effect concentrations to obtain a comparison result; The comparison result is sent to a display terminal so that the display terminal displays the comparison result.

5. The method according to claim 4, characterized in that The step of obtaining a predicted no-effect concentration corresponding to each bioequivalent concentration according to the multiple bioequivalent concentrations includes: sorting the multiple bioequivalent concentrations according to Weibull distribution to obtain a plurality of sorted bioequivalent concentrations; Based on the sorted multiple bioequivalent concentrations, according to the sorting sequence number of each bioequivalent concentration, obtaining the percentage sorting parameter of each bioequivalent concentration; Perform linear regression using each bioequivalent concentration after logarithmic transformation as the abscissa and the percentage ranking parameter of each bioequivalent concentration as the ordinate to obtain linear regression data; The predicted no-effect concentration corresponding to each bioequivalent concentration is obtained by using the slope and intercept of each bioequivalent concentration in the linear regression data.

6. The method according to claim 5, characterized in that Based on the sorted multiple bioequivalent concentrations, according to the sorting sequence number of each bioequivalent concentration, the percentage sorting parameter of each bioequivalent concentration is obtained, and the formula is: In the formula, represents the percentage ranking parameter for each bioequivalence concentration, Indicates the ranking number of each bioequivalence concentration, Represents the number of ranked multiple bioequivalence concentrations.

7. The method according to claim 5, characterized in that The slope and intercept of each bioequivalent concentration in the linear regression data are used to obtain the predicted no-effect concentration corresponding to each bioequivalent concentration, and the formula is: In the formula, represents the predicted no-effect concentration corresponding to each bioequivalence concentration, represents the probability value of the desired protection level, represents the slope, represents the intercept.

8. A device for predicting the bioequivalent concentration of environmental endocrine disruptors, characterized in that: Applicable to servers, including: A receiving module, used for receiving in vivo exposure data and in vitro exposure data related to toxic action pathways of fish exposed to environmental endocrine disruptors sent by a data acquisition device; wherein the in vivo exposure data includes external exposure concentrations; An output module, used for inputting the external exposure concentration into a pre-built physiological toxicokinetic model, so that the pre-built physiological toxicokinetic model outputs a maximum steady-state plasma concentration; A first acquisition module is used to acquire dose-effect curve data according to the in vitro exposure data related to the toxic action pathway; A second acquisition module is used to obtain in vitro biological activity concentration from the dose-effect curve data; A calculation module, for calculating a bioequivalent concentration according to the maximum steady-state plasma concentration and the in vitro biological activity concentration; wherein the bioequivalent concentration is a maximum environmental concentration threshold value for fish that does not produce toxic effects when exposed to the environmental endocrine disruptor; The sending module is used to send the bioequivalent concentration to a display terminal so that the display terminal displays the bioequivalent concentration.

9. A server, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 7 when being executed by a processor.

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