Method and device for predicting concentration of environmental endocrine disrupter in fish body

Abstract

The invention provides a method and a device for predicting the concentration of an environmental endocrine disrupter in a fish body. The method comprises the following steps: dividing fish into a plurality of compartments by using an initial physiological toxicokinetic model, and determining a mass balance differential equation of the environmental endocrine disrupter in each compartment; optimizing a plurality of model parameters, and correcting the exchange coefficient of the gill chemical flux; nesting the temperature prediction equation and the growth equation into the model to obtain a first physiological toxicokinetic model; according to the mass balance differential equation of each compartment, the species-specific physiological parameters, the compound-specific physicochemical parameters, the toxicokinetic parameters, the multiple optimized model parameters and the corrected exchange coefficient of the gill chemical flux, the model is optimized, and a second physiological toxicokinetic model is obtained; the concentration of the environmental endocrine disrupter in the fish body is predicted. The method provided by the invention improves the accuracy of concentration prediction, and further accurately evaluates the toxic effect of the target site concentration of the environmental endocrine disrupter on fish.

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 concentration of environmental endocrine disruptors in fish. Background Art

[0002] Environmental endocrine disruptors are a class of exogenous chemicals that can interfere with the normal endocrine function of organisms. The endocrine system of fish exposed to environmental endocrine disruptors will be seriously disrupted. In order to evaluate the toxic effects of target site concentrations of environmental endocrine disruptors on fish, it is necessary to predict the concentration of environmental endocrine disruptors entering the fish body.

[0003] Currently, existing technologies mainly rely on external exposure concentrations of environmental endocrine disruptors measured directly in environmental samples to assess toxic effects on fish.

[0004] However, existing technologies rely only on the external exposure concentrations of environmental endocrine disruptors directly measured in environmental samples and are unable 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 concentration of environmental endocrine disruptors in fish, so as to improve the accuracy of assessing the toxic effects of target site concentrations of environmental endocrine disruptors on fish.

[0006] In a first aspect, an embodiment of the present application provides a method for predicting the concentration of environmental endocrine disruptors in fish, comprising: dividing the fish into multiple compartments through an initial physiological toxicokinetic model of the fish; determining the mass balance differential equation of the environmental endocrine disruptors in each compartment; receiving species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters sent by a data acquisition device; optimizing multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters; correcting the exchange coefficient of the fish gill chemical flux to obtain the corrected exchange coefficient of the fish gill chemical flux; embedding the temperature prediction equation and the growth equation into the initial physiological toxicokinetic model to obtain a first physiological toxicokinetic model; optimizing the first physiological toxicokinetic model according to the mass balance differential equation of each compartment, species-specific physiological parameters, compound-specific physicochemical parameters, toxicokinetic parameters, multiple optimized model parameters and the corrected exchange coefficient of the fish gill chemical flux to obtain a second physiological toxicokinetic model; wherein the second physiological toxicokinetic model is used to predict the concentration of environmental endocrine disruptors in fish.

[0007] In one possible embodiment, the multiple compartments include brain, gonads, fat, well-perfused tissue, poorly perfused tissue, skin, arterial blood, gastrointestinal tract, kidneys, liver, venous blood and gills; accordingly, the mass balance differential equations of environmental endocrine disruptors in each compartment are determined, including: determining the mass balance differential equations of environmental endocrine disruptors in the brain, gonads, fat, well-perfused tissue, poorly perfused tissue and skin; determining the mass balance differential equations of environmental endocrine disruptors in arterial blood; determining the mass balance differential equations of environmental endocrine disruptors in the gastrointestinal tract; determining the mass balance differential equations of environmental endocrine disruptors in the kidneys; determining the mass balance differential equations of environmental endocrine disruptors in the liver; determining the mass balance differential equations of environmental endocrine disruptors in venous blood; determining the mass balance differential equations of environmental endocrine disruptors in the gills.

[0008] In one possible embodiment, the mass balance differential equation for determining environmental endocrine disruptors in the brain, gonads, fat, well-perfused tissues, poorly perfused tissues, and skin is:

[0009]

[0010] In the formula, Q i Indicates the amount of substance in each compartment, F i represents the blood flow in each compartment, C art Indicates the concentration of a substance in arterial blood, C i Indicates the concentration of the substance in each compartment, PC i Indicates the compartment-blood partition coefficient.

[0011] In one possible implementation, the differential equation for determining the mass balance of environmental endocrine disruptors in arterial blood is:

[0012]

[0013] In the formula, Q art Indicates the amount of substance in arterial blood, F card represents cardiac output, C ven Indicates the concentration of a substance in venous blood, C art Indicates the concentration of a substance in arterial blood.

[0014] In one possible embodiment, the mass balance differential equation for determining environmental endocrine disruptors in the gastrointestinal tract is:

[0015]

[0016] In the formula, Indicates the amount of material in the lumen of the gastrointestinal tract, Frac abs represents the absorption ratio, Qingest Indicates the amount of substance absorbed by the gastrointestinal tract, K u represents the absorption diffusion coefficient, Ke feces represents the fecal excretion rate constant, K BG represents the transfer rate of bile into the gastrointestinal tract, Q bile represents the amount of bile, Qfeces represents the amount of substances excreted through feces, and Q GIT Indicates the amount of material in the gastrointestinal tissue, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C art Indicates the concentration of a substance in arterial blood, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT Represents the tissue-blood partition coefficient of the gastrointestinal tract.

[0017] In one possible embodiment, the mass balance differential equation for determining environmental endocrine disruptors in the kidney is:

[0018]

[0019] In the formula, Q k Indicates the amount of substance in the kidney, F k represents the blood flow in the kidney, C art Indicates the concentration of a substance in arterial blood, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp Indicates blood flow to inadequately perfused tissues, C pp The concentration of a substance in poorly perfused tissue, PC pp Indicates the poorly perfused tissue-blood partition coefficient, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C s Indicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, C k Indicates the concentration of a substance in the kidney, PC k represents the kidney-blood distribution coefficient, Qurine represents the amount of substance in urine, Ke urine represents the urine excretion rate constant.

[0020] In one possible embodiment, the mass balance differential equation for determining environmental endocrine disruptors in the liver is:

[0021]

[0022] In the formula, Q l Indicates the amount of substance in the liver, F l represents the blood flow in the liver, Cart Indicates the concentration of a substance in arterial blood, F rp Indicates the blood flow to fully perfuse the tissue, C rp Indicates the concentration of a substance in a well-perfused tissue, PC rp represents the fully perfused tissue-blood partition coefficient, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT represents the gastrointestinal tissue-blood partition coefficient, F go represents the blood flow in the gonads, C go Indicates the concentration of a substance in the gonads, PC go represents the gonad-blood partition coefficient, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, Ke bile represents the bile excretion rate constant, Q Ml Indicates the amount of substances metabolized by the liver.

[0023] In one possible implementation, the mass balance differential equation for determining environmental endocrine disruptors in venous blood is:

[0024]

[0025] In the formula, Q ven Indicates the amount of substance in venous blood, F b Represents the blood flow in the brain, C b Indicates the concentration of a substance in the brain, PC b represents the brain-blood partition coefficient, F f represents the blood flow in fat, C f Indicates the concentration of a substance in fat, PC f represents the fat-blood partition coefficient, F l represents the blood flow in the liver, F rp Indicates the blood flow to fully perfuse the tissue, F go represents the blood flow in the gonads, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, F k represents the blood flow in the kidney, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp represents the blood flow to inadequately perfused tissues, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, Ck Indicates the concentration of the substance in the kidney, C pp The concentration of a substance in poorly perfused tissue, PC pp Indicates the insufficiently perfused tissue-blood partition coefficient, C s Indicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, F card represents cardiac output, C ven Indicates the concentration of a substance in venous blood, Q admin_gill Indicates the amount of material in the gills, Q Mp Indicates the amount of metabolites in the blood, Q excret_gill Indicates the amount of material excreted through the gills.

[0026] In one possible embodiment, the mass balance differential equation for determining environmental endocrine disruptors in the gills is:

[0027]

[0028] In the formula, Q admin_gill Indicates the amount of material in the gills, K x The exchange coefficient representing the chemical flux through the gills, C water Indicates the concentration of a substance in water.

[0029] In a possible embodiment, the multiple model parameters include the unbound ratio of the compound, the lipid-water distribution coefficient and the liver clearance rate; accordingly, the multiple model parameters of the initial physiological toxicokinetic model are optimized to obtain multiple optimized model parameters, including: optimizing the unbound ratio of the compound to obtain an optimized unbound ratio of the compound; optimizing the lipid-water distribution coefficient to obtain an optimized lipid-water distribution coefficient; optimizing the liver clearance rate to obtain an optimized liver clearance rate.

[0030] In a possible implementation, the unbound ratio of the compound is optimized to obtain an optimized unbound ratio of the compound, and the optimization formula is:

[0031]

[0032] In the formula, f u1 represents the optimized unbound fraction of the compound for the non-dissociable chemical, f u2 represents the unbound ratio of the optimized compound for the dissociable chemical species; v wbl Indicates water content, P bw represents the blood-water partition coefficient, logKow represents the octanol-water partition coefficient for an indissociable chemical substance, and logDow represents the octanol-water partition coefficient for a dissociable chemical substance.

[0033] In a possible implementation, the fat-water distribution coefficient is optimized to obtain an optimized fat-water distribution coefficient, and the optimization formula is:

[0034] D ow =f n,fish ×K ow +(1-f n,fish )×K ow,ion

[0035]

[0036] Where D ow represents the optimized fat-water distribution coefficient, f n,fish Indicates the proportion of neutral molecules in the fish body, K ow represents the n-octanol-water partition coefficient, K ow,ion is the octanol-water partition coefficient of the ionic molecule, pKa represents the acid dissociation constant, and j represents the coefficient.

[0037] In a possible implementation, the liver clearance rate is optimized to obtain an optimized liver clearance rate, and the optimization formula is:

[0038] Cl hepatic =K M,X ×V D

[0039]

[0040] In the formula, Cl hepatic represents the optimized liver clearance, K M,X represents the mass- and temperature-dependent rate constant, V D represents the apparent volume of distribution, K M,N represents the standard rate constant, BM represents the weight of the fish, T represents the temperature, V i Indicates the volume of each compartment; f nl,i represents the proportion of neutral lipids in each compartment, f pl,i represents the proportion of polar lipids in each compartment, f nlom,i represents the proportion of non-lipid organic matter in each compartment, f w,i Indicates the proportion of water in each compartment, D ow represents the optimized lipid-water distribution coefficient, P bw It represents the blood-water partition coefficient.

[0041] In a possible implementation, the exchange coefficient of the fish gill chemical flux is corrected to obtain a corrected exchange coefficient of the fish gill chemical flux, and the correction formula is:

[0042]

[0043] In the formula, K x ′ represents the exchange coefficient of the corrected gill chemical flux, F water Indicates the effective breathing volume, F card represents cardiac output, P bw It represents blood-water partition coefficient, VO2 represents oxygen consumption rate, OEE represents oxygen uptake efficiency, and Cox represents dissolved oxygen concentration.

[0044] In a possible implementation, the temperature prediction equation is:

[0045]

[0046] In the formula, represents the temperature reaction rate, Indicates the temperature reaction rate at the preset temperature. represents the characteristic constant, T A represents the Arrhenius temperature, T r Indicates the preset temperature, and T indicates the absolute temperature of water.

[0047] In one possible implementation, the growth equation is:

[0048]

[0049] Where L represents the structural length of the fish. represents the energy consumption rate, f represents the relative density of food, g represents the energy input ratio, L m Indicates the maximum structural length of the fish.

[0050] In a possible embodiment, after obtaining the second physiological toxicokinetic model, it also includes: inputting the specific physiological parameters of the target fish, the specific physicochemical parameters and toxicokinetic parameters of the target compound into the second physiological toxicokinetic model to output the predicted concentration of the target compound in each compartment of the fish; and evaluating the second physiological toxicokinetic model based on the predicted concentration and the measured concentration.

[0051] In a possible implementation, after obtaining the second physiological toxicokinetic model, the method further includes: obtaining, through sensitivity analysis, normalized dimensionless sensitivity coefficients of various parameters in the second physiological toxicokinetic model after changes have occurred.

[0052] In a possible implementation, the sensitivity analysis formula is:

[0053]

[0054] In the formula, S ij represents the normalized dimensionless sensitivity coefficient, Represents the output variable value, represents the input parameter value, Δθ j Indicates the input parameter change value, Δy i Indicates the change value of the output variable.

[0055] In a second aspect, the present application provides a device for predicting the concentration of environmental endocrine disruptors in fish, comprising:

[0056] A partitioning module is used to partition the fish into compartments using an initial physiological toxicokinetic model of the fish.

[0057] The determination module is used to determine the mass balance differential equation of environmental endocrine disruptors in each compartment.

[0058] The receiving module is used to receive species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters sent by the data acquisition device.

[0059] The optimization module is used to optimize multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters.

[0060] The correction module is used to correct the exchange coefficient of the fish gill chemical flux to obtain the corrected exchange coefficient of the fish gill chemical flux.

[0061] The acquisition module is used to embed the temperature prediction equation and the growth equation into the initial physiological toxicokinetic model to obtain the first physiological toxicokinetic model.

[0062] The prediction module is used to optimize the first physiological toxicokinetic model 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 the corrected fish gill chemical flux to obtain a second physiological toxicokinetic model; wherein the second physiological toxicokinetic model is used to predict the concentration of environmental endocrine disruptors in fish.

[0063] In a third aspect, an embodiment of the present application provides a server, including: a memory, a processor;

[0064] The memory stores computer-executable instructions;

[0065] 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.

[0066] 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.

[0067] 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.

[0068] The method and device for predicting the concentration of environmental endocrine disruptors in fish provided in the embodiment of the present application divide the fish into multiple compartments, and modify the general mass balance differential equation to determine the mass balance differential equation of environmental endocrine disruptors in different compartments to characterize the physiological processes in different compartments; the temperature prediction equation corresponding to the temperature fluctuation factor and the growth equation corresponding to the growth dilution effect are nested into the first physiological toxicokinetic model to obtain the second physiological toxicokinetic model. The second physiological toxicokinetic model is enabled to dynamically simulate the concentration changes of environmental endocrine disruptors in fish, thereby accurately predicting the concentration of environmental endocrine disruptors in fish, and then accurately evaluating the toxic effects of the target site concentration of environmental endocrine disruptors on fish. In addition, there are many species of fish distributed globally, and laboratory live fish experiments are costly, have long experimental cycles, and have large uncertainties. Under the principles of reducing, replacing, and optimizing experimental animals, large-scale whole fish experiments cannot be carried out. Therefore, by simulating the absorption, distribution, metabolism and excretion processes of compounds in different fish based on species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters, while replacing laboratory fish experiments, it also takes into account the differences in species sensitivity, as well as the main biological pathways and target tissues of a variety of different compounds, further improving the accuracy of predicting the concentration of environmental endocrine disruptors in fish. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] 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.

[0070] Figure 1 A schematic diagram of a scenario of a method for predicting the concentration of environmental endocrine disruptors in fish provided in an embodiment of the present application;

[0071] Figure 2 A schematic diagram of a method for predicting the concentration of environmental endocrine disruptors in fish provided in an embodiment of the present application;

[0072] Figure 3 A schematic diagram of the division structure of the physiological tissue compartments of fish provided in an embodiment of the present application;

[0073] Figure 4a A schematic diagram showing the comparison of the predicted concentrations of dissociable chemicals in the brain using the initial physiological toxicokinetic model with the measured concentrations;

[0074] Figure 4b A schematic diagram showing the comparison between the predicted concentrations of the dissociable chemical substances in the brain predicted by the second physiological toxicokinetic model and the measured concentrations;

[0075] Figure 5a A schematic diagram showing the comparison between the predicted concentrations of dissociable chemicals in the gastrointestinal tract predicted by the initial physiological toxicokinetic model and the measured concentrations;

[0076] Figure 5b A schematic diagram showing the comparison between the predicted concentrations of the dissociable chemical substances in the gastrointestinal tract predicted by the second physiological toxicokinetic model and the measured concentrations;

[0077] Figure 6a A schematic diagram showing the comparison between the predicted concentrations of the dissociable chemical substances in the liver using the predicted concentrations of the initial physiological toxicokinetic model and the measured concentrations;

[0078] Figure 6b A schematic diagram showing the comparison between the predicted concentration of the dissociable chemical substance in the liver and the measured concentration by the second physiological toxicokinetic model;

[0079] Figure 7 A schematic diagram of the structure of a device for predicting the concentration of environmental endocrine disruptors in fish provided in an embodiment of the present application;

[0080] Figure 8 A schematic diagram of the structure of a server provided in an embodiment of the present application.

[0081] 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

[0082] 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.

[0083] Figure 1A schematic diagram of a scenario of a method for predicting the concentration of environmental endocrine disruptors in fish provided in an embodiment of the present application. Figure 1 As shown, the application scenario includes: a data acquisition device 101 , a server 102 and a display terminal 103 .

[0084] The data acquisition device 101 is used to send species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters to the server 101; the server 101 can be a single server or a cluster of multiple servers. It is used to predict the concentration of environmental endocrine disruptors in fish and send the concentration of environmental endocrine disruptors in fish to the display terminal 103; the display terminal 103 is used to display the concentration of environmental endocrine disruptors in fish.

[0085] Environmental endocrine disruptors are a class of exogenous chemicals that can interfere with the normal endocrine function of organisms. The endocrine system of fish exposed to environmental endocrine disruptors will be seriously disrupted. In order to evaluate the toxic effects of the target site concentrations of environmental endocrine disruptors on fish, it is necessary to predict the concentration of environmental endocrine disruptors entering the fish body. At present, the existing technology mainly relies on the external exposure concentration of environmental endocrine disruptors directly measured in environmental samples to evaluate the toxic effects on fish. However, the existing technology only relies on the external exposure concentration of environmental endocrine disruptors directly measured in environmental samples, and cannot accurately evaluate the toxic effects of the target site concentrations of environmental endocrine disruptors on fish.

[0086] In response to the above technical problems, the present application proposes the following technical concept: Considering that it is impossible to accurately evaluate the toxic effects of the target site concentration of environmental endocrine disruptors on fish by relying solely on the external exposure concentration of environmental endocrine disruptors directly measured in environmental samples. The inventors thought of determining the mass balance differential equations of environmental endocrine disruptors in different compartments according to the characteristics of different compartments of fish to characterize the physiological processes in different compartments; the influence of temperature fluctuation factors and growth dilution effects were also considered, and the temperature prediction equation corresponding to the temperature fluctuation factor and the growth equation corresponding to the growth dilution effect were nested into the first physiological toxicokinetic model to obtain the second physiological toxicokinetic model. The second physiological toxicokinetic model is able to dynamically simulate the concentration changes of environmental endocrine disruptors in fish, thereby accurately predicting the concentration of environmental endocrine disruptors in fish, so as to accurately evaluate the toxic effects of the target site concentration of environmental endocrine disruptors on fish.

[0087] 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.

[0088] Figure 2 A schematic diagram of a method for predicting the concentration of environmental endocrine disruptors in fish provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the method includes:

[0089] S201: Fish were divided into compartments using an initial physiological toxicokinetic model of fish.

[0090] In this embodiment, Figure 3 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 3 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.

[0091] S202: Determine the mass balance differential equation of environmental endocrine disruptors in each compartment.

[0092] Among them, the distribution process of environmental endocrine disruptors in fish is described by the mass balance differential equation.

[0093] Among them, multiple compartments include brain, gonads, fat, well-perfused tissue, poorly perfused tissue, skin, arterial blood, gastrointestinal tract, kidney, liver, venous blood, and gills;

[0094] Specifically, the mass balance differential equations of environmental endocrine disruptors in each compartment are determined, including: determining the mass balance differential equations of environmental endocrine disruptors in the brain, gonads, fat, fully perfused tissues, insufficiently perfused tissues and skin; determining the mass balance differential equations of environmental endocrine disruptors in arterial blood; determining the mass balance differential equations of environmental endocrine disruptors in the gastrointestinal tract; determining the mass balance differential equations of environmental endocrine disruptors in the kidneys; determining the mass balance differential equations of environmental endocrine disruptors in the liver; determining the mass balance differential equations of environmental endocrine disruptors in venous blood; determining the mass balance differential equations of environmental endocrine disruptors in gills.

[0095] 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.

[0096] Specifically, the mass balance differential equations for determining environmental endocrine disruptors in the brain, gonads, fat, well-perfused tissues, poorly perfused tissues, and skin are:

[0097]

[0098] In the formula, Q i Indicates the amount of substance in each compartment, F i represents the blood flow in each compartment, C art Indicates the concentration of a substance in arterial blood, C i Indicates the concentration of the substance in each compartment, PC i Indicates the compartment-blood partition coefficient.

[0099] Specifically, the mass balance differential equation for environmental endocrine disruptors in arterial blood is determined as:

[0100]

[0101] In the formula, Q art Indicates the amount of substance in arterial blood, F card represents cardiac output, C ven Indicates the concentration of a substance in venous blood, C art Indicates the concentration of a substance in arterial blood.

[0102] Specifically, the mass balance differential equation for environmental endocrine disruptors in the gastrointestinal tract is:

[0103]

[0104]

[0105] In the formula, Indicates the amount of material in the lumen of the gastrointestinal tract, Frac abs represents the absorption ratio, Q ingest Indicates the amount of substance absorbed by the gastrointestinal tract, K u represents the absorption diffusion coefficient, Ke feces represents the fecal excretion rate constant, K BG represents the transfer rate of bile into the gastrointestinal tract, Q bile represents the amount of bile, Qfeces represents the amount of substances excreted through feces, and QGIT Indicates the amount of material in the gastrointestinal tissue, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C art Indicates the concentration of a substance in arterial blood, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT Represents the tissue-blood partition coefficient of the gastrointestinal tract.

[0106] Specifically, the mass balance differential equation for environmental endocrine disruptors in the kidney is:

[0107]

[0108] In the formula, Q k Indicates the amount of substance in the kidney, F k represents the blood flow in the kidney, C art Indicates the concentration of a substance in arterial blood, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp Indicates blood flow to inadequately perfused tissues, C pp The concentration of a substance in poorly perfused tissue, PC pp Indicates the poorly perfused tissue-blood partition coefficient, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C s Indicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, C k Indicates the concentration of a substance in the kidney, PC k represents the kidney-blood distribution coefficient, Qurine represents the amount of substance in urine, Ke urine represents the urine excretion rate constant.

[0109] Among them, the metabolism of environmental endocrine disruptors mainly occurs in the liver and is eliminated through exhaled water, urine and feces.

[0110] Specifically, the mass balance differential equation for environmental endocrine disruptors in the liver is:

[0111]

[0112] In the formula, Q l Indicates the amount of substance in the liver, F l represents the blood flow in the liver, C art Indicates the concentration of a substance in arterial blood, F rp Indicates the blood flow to fully perfuse the tissue, C rp Indicates the concentration of a substance in a well-perfused tissue, PC rprepresents the fully perfused tissue-blood partition coefficient, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT represents the gastrointestinal tissue-blood partition coefficient, F go represents the blood flow in the gonads, C go Indicates the concentration of a substance in the gonads, PC go represents the gonad-blood partition coefficient, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, Ke bile represents the bile excretion rate constant, Q Ml Indicates the amount of substances metabolized by the liver.

[0113] Specifically, the mass balance differential equation for environmental endocrine disruptors in venous blood is determined as:

[0114]

[0115] In the formula, Q ven Indicates the amount of substance in venous blood, F b Represents the blood flow in the brain, C b Indicates the concentration of a substance in the brain, PC b represents the brain-blood partition coefficient, F f represents the blood flow in fat, C f Indicates the concentration of a substance in fat, PC f represents the fat-blood partition coefficient, F l represents the blood flow in the liver, F rp Indicates the blood flow to fully perfuse the tissue, F go represents the blood flow in the gonads, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, F k represents the blood flow in the kidney, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp represents the blood flow to inadequately perfused tissues, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C k Indicates the concentration of the substance in the kidney, C pp The concentration of a substance in poorly perfused tissue, PC pp Indicates the insufficiently perfused tissue-blood partition coefficient, C sIndicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, F card represents cardiac output, C ven Indicates the concentration of a substance in venous blood, Q admin_gill Indicates the amount of material in the gills, Indicates the amount of metabolites in the blood, Q excret_gill Indicates the amount of material excreted through the gills.

[0116] Specifically, the mass balance differential equation for environmental endocrine disruptors in the gills is determined as:

[0117]

[0118] In the formula, Q admin_gill Indicates the amount of material in the gills, K x The exchange coefficient representing the chemical flux through the gills, C water Indicates the concentration of a substance in water.

[0119] S203: receiving species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters sent by a data acquisition device.

[0120] Optionally, the species-specific physiological parameters include species-specific physiological parameters of zebrafish, rainbow trout, fathead minnow, stickleback and carp, etc.

[0121] Optionally, the compound-specific physicochemical parameters include compound-specific physicochemical parameters of organophosphates, pesticides, and drugs and personal care products.

[0122] Optionally, the scope of data acquisition by the data acquisition device includes but is not limited to FishBase database, literature, research data and CompTox Dashboard. The physicochemical properties of chemical substances are collected on CompTox Dashboard, including molecular weight, octanol-water partition coefficient and acid dissociation constant. Its free fraction, octanol-water distribution coefficient and liver clearance are calculated according to existing empirical equations. The blood-water partition coefficient and tissue-blood partition coefficient are estimated using a QSAR model, which depends on the octanol-water partition coefficient of the compound and the water content and lipid content of the exposed species.

[0123] Among them, Table 1 shows species-specific physiological parameters; Table 2 shows compound-specific physicochemical parameters.

[0124] Table 1 Species-specific physiological parameters

[0125] Physiological parameters symbol unit weight BM(t) g Relative weight of each compartment <![CDATA[V i C]]> Relative blood flow in each compartment <![CDATA[Q i C]]> Relative water content of each compartment <![CDATA[W i C]]> Relative lipid content of each compartment <![CDATA[L i C]]> Cardiac output <![CDATA[F card (t)]]> mL / d / g Dissolved oxygen concentration Cox(t) <![CDATA[mg O2 / mL]]> Blood flow into each compartment <![CDATA[F i (t)]]> mL / d The concentration of the substance in each compartment <![CDATA[C i (t)]]> μg / mL Effective breathing volume Fwater(t) mL / d Exchange coefficients of chemical fluxes through fish gills <![CDATA[K x (t)]]> mL / d Saturated dissolved oxygen ratio S - Oxygen uptake efficiency OEE - Distribution of venous blood to inadequately perfused tissues αFpp - Distribution ratio of venous blood in the skin αFs - The amount of material in each compartment <![CDATA[Q i (t)]]> μg Oxygen consumption rate <![CDATA[VO2(t)]]> mg O2 / d The volume of each compartment <![CDATA[V i (t)]]> mL

[0126] Table 2 Compound-specific physicochemical parameters

[0127]

[0128]

[0129] S204: Optimizing multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters.

[0130] In the subsequent embodiments, the process of optimizing multiple model parameters will be introduced.

[0131] S205: Correcting the exchange coefficient of the fish gill chemical flux to obtain a corrected exchange coefficient of the fish gill chemical flux.

[0132] Due to the dissociation of the chemical species, the dissociable fraction generally exhibits lower membrane permeability than the neutral fraction, resulting in lower lipophilicity. Therefore, the exchange coefficients for chemical fluxes through the gills were corrected.

[0133] Specifically, the exchange coefficient of the fish gill chemical flux is corrected to obtain the corrected exchange coefficient of the fish gill chemical flux, and the correction formula is:

[0134]

[0135] In the formula, K x ′ represents the exchange coefficient of the corrected gill chemical flux, F water Indicates the effective breathing volume, F card represents cardiac output, P bw It represents blood-water partition coefficient, VO2 represents oxygen consumption rate, OEE represents oxygen uptake efficiency, and Cox represents dissolved oxygen concentration.

[0136] S206: embedding the temperature prediction equation and the growth equation into the initial physiological toxicokinetic model to obtain a first physiological toxicokinetic model.

[0137] Optionally, the temperature prediction equation is the Arrhenius equation; and the growth equation is the von Bertalanffy growth equation.

[0138] In this embodiment, in order to characterize the effect of water temperature on metabolic rate, the Arrhenius equation was used to predict the effect of increased water temperature on the rate of physiological processes of various species.

[0139] Specifically, the temperature prediction equation is:

[0140]

[0141] In the formula, represents the temperature reaction rate, Indicates the temperature reaction rate at the preset temperature. represents the characteristic constant, T A represents the Arrhenius temperature, T r Indicates the preset temperature, and T indicates the absolute temperature of water.

[0142] Optionally, It can be a characteristic constant for a given reaction.

[0143] In this example, the growth equation was embedded into the initial physiological toxicokinetic model to reflect the growth dilution effect.

[0144] Specifically, the growth equation is:

[0145]

[0146] Where L represents the structural length of the fish. represents the energy consumption rate, f represents the relative density of food, g represents the energy input ratio, L m Indicates the maximum structural length of the fish.

[0147] In this embodiment, according to the allometric scaling hypothesis of DEB theory, the volume length is the cube root of the volume and is independent of the body size of the organism. The physical length of a specific shape is converted to the structural length through the shape coefficient. Specifically, the conversion formula is:

[0148]

[0149] Where V is the volume of the structure; L is the length of the structure; δ M is the shape factor; L ω It is the standard body length.

[0150] In this embodiment, body weight is described by the mass-body length equation, which is:

[0151]

[0152] In the formula, a BW and b BW represents the allometric scaling parameter. BM represents the weight of the fish, L ω Indicates standard body length.

[0153] S207: Optimize the first physiological toxicokinetic model 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 to obtain a second physiological toxicokinetic model. The second physiological toxicokinetic model is used to predict the concentration of environmental endocrine disruptors in fish.

[0154] In this embodiment, 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 the corrected gill chemical flux, the first physiological toxicokinetic model was optimized by R language to obtain the second physiological toxicokinetic model.

[0155] In summary, by dividing the fish into multiple compartments, the mass balance differential equations of environmental endocrine disruptors in different compartments were modified to characterize the physiological processes in different compartments; the temperature prediction equation corresponding to the temperature fluctuation factor and the growth equation corresponding to the growth dilution effect were embedded in the first physiological toxicokinetic model to obtain the second physiological toxicokinetic model. The second physiological toxicokinetic model can dynamically simulate the concentration changes of environmental endocrine disruptors in fish, thereby accurately predicting the concentration of environmental endocrine disruptors in fish, and then accurately evaluating the toxic effects of the target site concentration of environmental endocrine disruptors on fish. In addition, there are many species of fish distributed globally, and laboratory live fish experiments are costly, have long experimental cycles, and have large uncertainties. Under the principles of reducing, replacing, and optimizing experimental animals, large-scale whole fish experiments cannot be carried out. Therefore, by simulating the absorption, distribution, metabolism and excretion processes of compounds in different fish based on species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters, while replacing laboratory fish experiments, it also takes into account the differences in species sensitivity, as well as the main biological pathways and target tissues of a variety of different compounds, further improving the accuracy of predicting the concentration of environmental endocrine disruptors in fish.

[0156] On the basis of the above-mentioned embodiment, in this embodiment, the process of optimizing multiple model parameters of the initial physiological toxicokinetic model and obtaining multiple optimized model parameters is introduced in detail, as described in detail as follows:

[0157] Among them, multiple model parameters include the unbound proportion of the compound, the lipid-water distribution coefficient and the liver clearance rate.

[0158] Specifically, the unbound ratio of the compound is optimized to obtain an optimized unbound ratio of the compound; the lipid-water distribution coefficient is optimized to obtain an optimized lipid-water distribution coefficient; and the liver clearance rate is optimized to obtain an optimized liver clearance rate.

[0159] Specifically, the unbound ratio of the compound is optimized to obtain an optimized unbound ratio of the compound, and the optimization formula is:

[0160]

[0161] In the formula, f u1represents the optimized unbound fraction of the compound for the non-dissociable chemical, f u2 represents the unbound ratio of the optimized compound for the dissociable chemical species; v wbl Indicates water content, P bw represents the blood-water partition coefficient, logKow represents the octanol-water partition coefficient for an imdissociable chemical substance, and logDow represents the octanol-water partition coefficient for a dissociable chemical substance.

[0162] Among them, logKow and logDow in chemistry are two different parameters. Since the pH value range of natural water bodies is very wide, the fate and toxicity of dissociable chemicals in fish bodies vary greatly, so it is expressed by the combined distribution coefficient Dow. logDow depends on the form of the chemical, that is, the valence state of the chemical, the acid dissociation constant, and the external pH value. Dissociated components usually show lower membrane permeability than neutral components, so Kow is replaced by Dow to calculate the exchange coefficient of fish gill chemical flux.

[0163] Specifically, the fat-water distribution coefficient is optimized to obtain the optimized fat-water distribution coefficient. The optimization formula is:

[0164] D ow =f n,fish ×K ow +(1-f n,fish )×K ow,ion

[0165]

[0166] Where D ow represents the optimized fat-water distribution coefficient, f n,fish Indicates the proportion of neutral molecules in the fish body, K ow represents the n-octanol-water partition coefficient, K ow,ion is the octanol-water partition coefficient of the ionic molecule, pKa represents the acid dissociation constant, and j represents the coefficient.

[0167] Alternatively, for dissociable compounds, the pH-dependent lipid-water distribution coefficient Dow is used instead of Kow to better reflect the dissociation behavior of the chemical species.

[0168] Optionally, f n,fish It represents the proportion of neutral molecules in the fish body. For acid, j=1, and for base, j=-1.

[0169] Each tissue is divided into three parts: lipid, non-lipid organic matter and water. The tissue-water partition coefficient is the sum of the distribution of substances between different fish components and the exposure water.

[0170]

[0171] Where P iw represents the tissue-water partition coefficient, f n,l represents the proportion of neutral lipids, f p,l represents the proportion of polar lipids, f nlom represents the proportion of non-lipid organic matter, f w represents the proportion of water; parameters a and b are the regression coefficient and slope of each tissue, respectively; among them, the tissue-blood distribution coefficient is P iw and P bw The ratio between .

[0172] To better compare with other exposure scenarios and for use in mass balance models, the standard rate constants were converted to mass- and temperature-dependent rate constants. Hepatic clearance was then calculated by multiplying the mass- and temperature-dependent rate constants by the apparent volume of distribution.

[0173] Specifically, the liver clearance rate is optimized to obtain an optimized liver clearance rate, and the optimization formula is:

[0174] Cl hepatic =K M,X ×V D

[0175]

[0176] In the formula, Cl hepatic represents the optimized liver clearance, K M,X represents the mass- and temperature-dependent rate constant, V D represents the apparent volume of distribution, K M,N represents the standard rate constant, BM represents the weight of the fish, T represents the temperature, V i Indicates the volume of each compartment; f nl,i represents the proportion of neutral lipids in each compartment, f pl,i represents the proportion of polar lipids in each compartment, f nlom,i represents the proportion of non-lipid organic matter in each compartment, f w,i Indicates the proportion of water in each compartment, D ow represents the optimized lipid-water distribution coefficient, P bw It represents the blood-water partition coefficient.

[0177] In this embodiment, the gills are not included in the calculation of the apparent distribution volume, and arterial blood and venous blood are combined into a unified blood compartment.

[0178] In summary, multiple model parameters were optimized, including the unbound proportion of the compound, the lipid-water distribution coefficient, and the liver clearance. On the one hand, by optimizing the unbound ratio of compounds, ignoring the inert components of environmental endocrine disruptors that bind to plasma proteins, and only considering the active components that are not bound to plasma proteins after entering the fish, the toxic effects of the target site concentration of environmental endocrine disruptors on fish can be accurately simulated, further improving the accuracy of predicting the concentration of environmental endocrine disruptors in fish; on the other hand, by optimizing the lipid-water distribution coefficient, dissociable and non-dissociable environmental endocrine disruptors are considered separately. For dissociable compounds, the pH-dependent lipid-water distribution coefficient is used instead of the general n-octanol-water distribution coefficient, which can clearly reflect the dissociation behavior of chemical substances, further improving the accuracy of predicting the concentration of environmental endocrine disruptors in fish; on the other hand, it is very difficult to carry out extensive experiments on the determination of the liver clearance rate of chemical substances, and the liver clearance rate of most chemical substances in fish is still unclear. Based on the product of the rate constant related to mass and temperature and the apparent distribution volume, the liver clearance rate is optimized, which can avoid a large number of in vitro metabolism experiments and accurately characterize the metabolism of substances in the liver.

[0179] On the basis of the above-mentioned embodiment, in this embodiment, the process of evaluating the second physiological toxicokinetic model is introduced in detail, as follows:

[0180] S301: Input the specific physiological parameters of the target fish, the specific physicochemical parameters of the target compound and the toxicokinetic parameters into the second physiological toxicokinetic model to output the predicted concentration of the target compound in each compartment of the fish.

[0181] Specifically, specific physiological parameters of the target fish, specific physicochemical parameters of the target compound, and toxicokinetic parameters are input into the second physiological toxicokinetic model, and the predicted concentration of the target compound in each compartment of the fish is output.

[0182] S302: Evaluate the second physiological toxicokinetic model based on the predicted concentration and the measured concentration.

[0183] In this example, the second physiological toxicokinetic model was evaluated by the root mean square error and the coefficient of determination based on the logarithmic values ​​of the predicted concentration and the measured concentration.

[0184] Alternatively, an acceptable standard for model validation performance may be considered, that is, the deviation multiple of the predicted concentration and the measured concentration is within 10. The deviation multiple refers to the ratio of the predicted concentration to the measured concentration. In the field of physiological toxicokinetic models, a deviation multiple within 10 times the deviation indicates that the model prediction effect is good, and the smaller the deviation multiple, the better the model prediction effect.

[0185] In this embodiment, the predicted concentration of the second physiological toxicokinetic model is compared with the in vivo experimental data of various chemical substances published in the ecotoxicology database and literature to perform the forward dosimetry model validation. Specifically, in the forward dosimetry validation, the second physiological toxicokinetic model is evaluated by comparing the measured concentrations of non-dissociable chemical substances, dissociable chemical substances, and pesticides with the predicted concentrations.

[0186] refer to Figure 4a , 4b , 5a, 5b, 6a, 6b, the predicted concentrations of dissociable chemical substances in different compartments are compared with the measured concentrations, and are presented in the form of a coordinate graph, where the horizontal axis represents the logarithm of the measured concentration and the vertical axis represents the logarithm of the predicted concentration. Among them, line A indicates that the predicted concentration of the dissociable chemical substance deviates by 10 times from the measured concentration, line B indicates that the predicted concentration of the dissociable chemical substance deviates by 5 times from the measured concentration, and line C indicates that the predicted concentration of the dissociable chemical substance is the same as the measured concentration.

[0187] Figure 4a Schematic diagram showing the comparison between the predicted concentrations of dissociable chemicals in the brain predicted by the initial physiological toxicokinetic model and the measured concentrations; Figure 4a As shown, the deviation multiples between the predicted concentrations and the measured concentrations of 21.43% of the dissociable chemical substances are within 10 times. Figure 4b The figure is a comparison diagram of the predicted concentration of the dissociable chemical substance in the brain by the second physiological toxicokinetic model and the measured concentration; Figure 4b As shown in the figure, the deviation multiples between the predicted concentrations and the measured concentrations of 92.86% of the dissociable chemical substances are within 5 times. Therefore, it can be seen that the prediction effect of the second physiological toxicokinetic model is better.

[0188] Figure 5a Schematic diagram showing the comparison between the predicted concentrations of dissociable chemicals in the gastrointestinal tract predicted by the initial physiological toxicokinetic model and the measured concentrations; Figure 5a As shown, the deviation between the predicted concentration and the measured concentration of 28.57% of the dissociable chemical substances is within 10 times. Figure 5b The figure is a comparison diagram of the predicted concentration of the dissociable chemical substance in the gastrointestinal tract by the second physiological toxicokinetic model and the measured concentration; Figure 5b As shown, the deviation multiples between the predicted concentrations and the measured concentrations of 85.71% of the dissociable chemical substances are within 5 times. Therefore, it can be seen that the prediction effect of the second physiological toxicokinetic model is better.

[0189] Figure 6aSchematic diagram showing the comparison between the predicted concentrations of the dissociable chemical substances in the liver and the measured concentrations predicted by the initial physiological toxicokinetic model; Figure 6a As shown, the deviation between the predicted concentration and the measured concentration of 28.57% of the dissociable chemical substances is within 10 times. Figure 6b The figure is a comparison diagram of the predicted concentration of the dissociable chemical substance in the liver by the predicted concentration of the second physiological toxicokinetic model and the measured concentration; Figure 6b As shown, the deviation multiples between the predicted concentrations and the measured concentrations of 85.71% of the dissociable chemical substances are within 5 times. Therefore, it can be seen that the prediction effect of the second physiological toxicokinetic model is better.

[0190] In this embodiment, the deviation multiple between the predicted concentration and the measured concentration of the non-dissociable chemical substance by the second physiological toxicokinetic model is within 5 times, the determination coefficient is high, which is 0.88, and the root mean square error is low, which is 0.09.

[0191] In summary, by comparing the predicted concentrations using the initial physiological toxicokinetic model with the measured concentrations, and by comparing the predicted concentrations using the second physiological toxicokinetic model with the measured concentrations, it can be seen that the performance of the second physiological toxicokinetic model is better, thereby further improving the accuracy of the concentrations predicted by the second physiological toxicokinetic model.

[0192] On the basis of the above-mentioned embodiment, in this embodiment, the parameter sensitivity of the second physiological toxicokinetic model is introduced in detail, as follows:

[0193] In this embodiment, through sensitivity analysis, the normalized dimensionless sensitivity coefficients after the parameters in the second physiological toxicokinetic model change are obtained.

[0194] Among them, the normalized dimensionless sensitivity coefficient is mainly used in the sensitivity analysis of the second physiological toxicokinetic model. Through sensitivity analysis, the parameters that have the greatest impact on the accuracy of the second physiological toxicokinetic model can be identified to ensure the accuracy of the parameter as much as possible when collecting parameters.

[0195] Optionally, a local sensitivity analysis of multiple parameters is performed using the FME (Fast Model Evaluation) package of the R language to evaluate the effect of parameter perturbations on the output of the second physiological toxicokinetic model. Chemical substances with different n-octanol-water partition coefficient values, 0.89≤logKow≤5.48, are run through the second physiological toxicokinetic model using zebrafish to obtain differences in sensitivity parameters of different chemicals of the same species.

[0196] Optionally, TNBP and BPA are selected as target compounds, and the second physiological toxicokinetic model is run on different compounds to obtain the differences in sensitivity parameters of different species for the same compound.

[0197] Specifically, the sensitivity analysis formula is:

[0198]

[0199] In the formula, S ij represents the normalized dimensionless sensitivity coefficient, Represents the output variable value, represents the input parameter value, Δθ j Indicates the input parameter change value, Δy i Indicates the change value of the output variable.

[0200] In summary, by obtaining the normalized dimensionless sensitivity coefficients of the parameters in the second physiological toxicokinetic model after changes in them through sensitivity analysis, the parameters that have the greatest impact on the accuracy of the second physiological toxicokinetic model can be identified to ensure that the accuracy of the parameters is guaranteed as much as possible when the parameters are collected, thereby further improving the accuracy of the predicted concentrations of the second physiological toxicokinetic model.

[0201] Figure 7 The schematic diagram of the structure of the device for predicting the concentration of environmental endocrine disruptors in fish provided in the embodiment of the present application is as follows: Figure 7 As shown, the device for predicting the concentration of environmental endocrine disruptors in fish provided in this embodiment includes: a division module 701, a determination module 702, a receiving module 703, an optimization module 704, a correction module 705, an acquisition module 706 and a prediction module 707.

[0202] The partitioning module 701 is used to partition the fish into multiple compartments according to the initial physiological toxicokinetic model of the fish.

[0203] The determination module 702 is used to determine the mass balance differential equation of environmental endocrine disruptors in each compartment.

[0204] The receiving module 703 is used to receive species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters sent by the data acquisition device.

[0205] The optimization module 704 is used to optimize multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters.

[0206] The correction module 705 is used to correct the exchange coefficient of the fish gill chemical flux to obtain the corrected exchange coefficient of the fish gill chemical flux.

[0207] The acquisition module 706 is used to embed the temperature prediction equation and the growth equation into the initial physiological toxicokinetic model to obtain a first physiological toxicokinetic model.

[0208] The prediction module 707 is used to optimize the first physiological toxicokinetic model 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 the corrected fish gill chemical flux to obtain a second physiological toxicokinetic model; wherein the second physiological toxicokinetic model is used to predict the concentration of environmental endocrine disruptors in fish.

[0209] In one possible embodiment, the multiple compartments include brain, gonads, fat, well-perfused tissue, poorly perfused tissue, skin, arterial blood, gastrointestinal tract, kidneys, liver, venous blood and gills; accordingly, determination module 702 is specifically used to: determine the mass balance differential equations of environmental endocrine disruptors in the brain, gonads, fat, well-perfused tissue, poorly perfused tissue and skin; determine the mass balance differential equations of environmental endocrine disruptors in arterial blood; determine the mass balance differential equations of environmental endocrine disruptors in the gastrointestinal tract; determine the mass balance differential equations of environmental endocrine disruptors in the kidneys; determine the mass balance differential equations of environmental endocrine disruptors in the liver; determine the mass balance differential equations of environmental endocrine disruptors in venous blood; determine the mass balance differential equations of environmental endocrine disruptors in the gills.

[0210] In a possible implementation, the determination module 702 includes a first determination unit, and the mass balance differential equation of the first determination unit is:

[0211]

[0212] In the formula, Q i Indicates the amount of substance in each compartment, F i represents the blood flow in each compartment, C art Indicates the concentration of a substance in arterial blood, C i Indicates the concentration of the substance in each compartment, PC i Indicates the compartment-blood partition coefficient.

[0213] In a possible implementation, the determination module 702 includes a second determination unit, and the mass balance differential equation of the second determination unit is:

[0214]

[0215] In the formula, Q art Indicates the amount of substance in arterial blood, F card represents cardiac output, C venIndicates the concentration of a substance in venous blood, C art Indicates the concentration of a substance in arterial blood.

[0216] In a possible implementation, the determination module 702 includes a third determination unit, and the mass balance differential equation of the third determination unit is:

[0217]

[0218] In the formula, Indicates the amount of material in the lumen of the gastrointestinal tract, Frac abs represents the absorption ratio, Q ingest Indicates the amount of substance absorbed by the gastrointestinal tract, K u represents the absorption diffusion coefficient, Ke feces represents the fecal excretion rate constant, K BG represents the transfer rate of bile into the gastrointestinal tract, Q bile represents the amount of bile, Qfeces represents the amount of substances excreted through feces, and Q GIT Indicates the amount of material in the gastrointestinal tissue, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C art Indicates the concentration of a substance in arterial blood, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT Represents the tissue-blood partition coefficient of the gastrointestinal tract.

[0219] In a possible implementation, the determination module 702 includes a fourth determination unit, and the mass balance differential equation of the fourth determination unit is:

[0220]

[0221]

[0222] In the formula, Q k Indicates the amount of substance in the kidney, F k represents the blood flow in the kidney, C art Indicates the concentration of a substance in arterial blood, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp Indicates blood flow to inadequately perfused tissues, C pp The concentration of a substance in poorly perfused tissue, PC pp Indicates the poorly perfused tissue-blood partition coefficient, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C s Indicates the concentration of a substance in the skin, PC srepresents the skin-blood partition coefficient, C k Indicates the concentration of a substance in the kidney, PC k represents the kidney-blood distribution coefficient, Qurine represents the amount of substance in urine, Ke urine represents the urine excretion rate constant.

[0223] In a possible implementation, the determination module 702 includes a fifth determination unit, and the mass balance differential equation of the fifth determination unit is:

[0224]

[0225] In the formula, Q l Indicates the amount of substance in the liver, F l represents the blood flow in the liver, C art Indicates the concentration of a substance in arterial blood, F rp Indicates the blood flow to fully perfuse the tissue, C rp Indicates the concentration of a substance in a well-perfused tissue, PC rp represents the fully perfused tissue-blood partition coefficient, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT represents the gastrointestinal tissue-blood partition coefficient, F go represents the blood flow in the gonads, C go Indicates the concentration of a substance in the gonads, PC go represents the gonad-blood partition coefficient, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, Ke bile represents the bile excretion rate constant, Q Ml Indicates the amount of substances metabolized by the liver.

[0226] In a possible implementation, the determination module 702 includes a sixth determination unit, and the mass balance differential equation of the sixth determination unit is:

[0227]

[0228] In the formula, Q ven Indicates the amount of substance in venous blood, F b Represents the blood flow in the brain, C b Indicates the concentration of a substance in the brain, PC b represents the brain-blood partition coefficient, F f represents the blood flow in fat, C f Indicates the concentration of a substance in fat, PC frepresents the fat-blood partition coefficient, F l represents the blood flow in the liver, F rp Indicates the blood flow to fully perfuse the tissue, F go represents the blood flow in the gonads, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, F k represents the blood flow in the kidney, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp represents the blood flow to inadequately perfused tissues, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C k Indicates the concentration of the substance in the kidney, C pp The concentration of a substance in poorly perfused tissue, PC pp Indicates the insufficiently perfused tissue-blood partition coefficient, C s Indicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, F card represents cardiac output, C ven Indicates the concentration of a substance in venous blood, Q admin_gill Indicates the amount of material in the gills, Indicates the amount of metabolites in the blood, Q excret_gill Indicates the amount of material excreted through the gills.

[0229] In a possible implementation, the determination module 702 includes a seventh determination unit, and the mass balance differential equation of the seventh determination unit is:

[0230]

[0231] In the formula, Q admin_gill Indicates the amount of material in the gills, K x The exchange coefficient representing the chemical flux through the gills, C water Indicates the concentration of a substance in water.

[0232] In a possible embodiment, the multiple model parameters include the unbound ratio of the compound, the lipid-water distribution coefficient and the liver clearance rate; accordingly, the optimization module 704 is specifically used to: optimize the unbound ratio of the compound to obtain an optimized unbound ratio of the compound; optimize the lipid-water distribution coefficient to obtain an optimized lipid-water distribution coefficient; optimize the liver clearance rate to obtain an optimized liver clearance rate.

[0233] In a possible implementation, the optimization module 704 includes a first optimization unit, and the optimization formula of the first optimization unit is:

[0234]

[0235] In the formula, f u1 represents the optimized unbound fraction of the compound for the non-dissociable chemical, f u2 represents the unbound ratio of the optimized compound for the dissociable chemical species; v wbl Indicates water content, P bw represents the blood-water partition coefficient, logKow represents the octanol-water partition coefficient for an imdissociable chemical substance, and logDow represents the octanol-water partition coefficient for a dissociable chemical substance.

[0236] In a possible implementation, the optimization module 704 includes a second optimization unit, and the optimization formula of the second optimization unit is:

[0237] D ow =f n,fish ×K ow +(1-f n,fish )×K ow,ion

[0238]

[0239] Where D ow represents the optimized fat-water distribution coefficient, f n,fish Indicates the proportion of neutral molecules in the fish body, K ow represents the n-octanol-water partition coefficient, K ow,ion is the octanol-water partition coefficient of the ionic molecule, pKa represents the acid dissociation constant, and j represents the coefficient.

[0240] In a possible implementation, the optimization module 704 includes a third optimization unit, and the optimization formula of the third optimization unit is:

[0241] Cl hepatic =K M,X ×V D

[0242]

[0243] In the formula, Cl hepatic represents the optimized liver clearance, K M,X represents the mass- and temperature-dependent rate constant, V D represents the apparent volume of distribution, K M,N represents the standard rate constant, BM represents the weight of the fish, T represents the temperature, V iIndicates the volume of each compartment; f nl,i represents the proportion of neutral lipids in each compartment, f pl,i represents the proportion of polar lipids in each compartment, f nlom,i represents the proportion of non-lipid organic matter in each compartment, f w,i Indicates the proportion of water in each compartment, D ow represents the optimized lipid-water distribution coefficient, P bw It represents the blood-water partition coefficient.

[0244] In a possible implementation, in the correction module 705, the correction formula is:

[0245]

[0246] In the formula, K x ′ represents the exchange coefficient of the corrected gill chemical flux, F water Indicates the effective breathing volume, F card represents cardiac output, P bw It represents blood-water partition coefficient, VO2 represents oxygen consumption rate, OEE represents oxygen uptake efficiency, and Cox represents dissolved oxygen concentration.

[0247] In a possible implementation, the temperature prediction equation is:

[0248]

[0249] In the formula, represents the temperature reaction rate, Indicates the temperature reaction rate at the preset temperature. represents the characteristic constant, T A represents the Arrhenius temperature, T r Indicates the preset temperature, and T indicates the absolute temperature of water.

[0250] In one possible implementation, the growth equation is:

[0251]

[0252] Where L represents the structural length of the fish. represents the energy consumption rate, f represents the relative density of food, g represents the energy input ratio, L m Indicates the maximum structural length of the fish.

[0253] In a possible embodiment, the device for predicting the concentration of environmental endocrine disruptors in fish also includes: an evaluation module, which is used to input the specific physiological parameters of the target fish, the specific physicochemical parameters and toxicokinetic parameters of the target compound into a second physiological toxicokinetic model to output the predicted concentration of the target compound in each compartment of the fish; and evaluate the second physiological toxicokinetic model based on the predicted concentration and the measured concentration.

[0254] In a possible implementation, the device for predicting the concentration of environmental endocrine disruptors in fish further includes: a sensitivity analysis module for obtaining, through sensitivity analysis, normalized dimensionless sensitivity coefficients of various parameters in the second physiological toxicokinetic model after changes have occurred.

[0255] In a possible implementation, the sensitivity analysis formula is:

[0256]

[0257] In the formula, S ij represents the normalized dimensionless sensitivity coefficient, Represents the output variable value, represents the input parameter value, Δθ j Indicates the input parameter change value, Δy i Indicates the change value of the output variable.

[0258] The device for predicting the concentration of environmental endocrine disruptors in fish provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar, and this embodiment will not be described in detail here.

[0259] Figure 8 A schematic diagram of the structure of a server provided in an embodiment of the present application. As shown in the figure, the server provided in this embodiment includes: at least one processor 801 and a memory 802. Optionally, the server also includes a communication component 803. The processor 801, the memory 802 and the communication component 803 are connected via a bus 804.

[0260] In a specific implementation process, at least one processor 801 executes the computer-executable instructions stored in the memory 802, so that at least one processor 801 executes the above method.

[0261] The specific implementation process of the processor 801 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.

[0262] In the above embodiments, it should be understood that the processor may 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 may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0263] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0264] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0265] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0266] 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.

[0267] 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.

[0268] 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.

[0269] 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.

[0270] 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.

[0271] 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.

[0272] 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.

[0273] 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.

[0274] 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 concentration of environmental endocrine disruptors in fish, characterized in that: Applicable to servers, including: The fish were divided into compartments through an initial physiological toxicokinetic model of the fish; Determine the mass balance differential equations of environmental endocrine disruptors in each compartment; Receive species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters sent by data acquisition equipment; Optimizing multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters; Correcting the exchange coefficient of the fish gill chemical flux to obtain a corrected exchange coefficient of the fish gill chemical flux; Embedding the temperature prediction equation and the growth equation into the initial physiological toxicokinetic model to obtain a first physiological toxicokinetic model; According to the mass balance differential equations of each compartment, the species-specific physiological parameters, the compound-specific physicochemical parameters, the toxicokinetic parameters, the multiple optimized model parameters and the corrected exchange coefficient of the fish gill chemical flux, the first physiological toxicokinetic model is optimized to obtain a second physiological toxicokinetic model; wherein the second physiological toxicokinetic model is used to predict the concentration of environmental endocrine disruptors in fish.

2. The method according to claim 1, characterized in that The plurality of compartments include brain, gonads, fat, well-perfused tissue, poorly perfused tissue, skin, arterial blood, gastrointestinal tract, kidneys, liver, venous blood, and gills; Accordingly, the mass balance differential equation for determining the environmental endocrine disruptors in each compartment includes: determining a mass balance differential equation of an environmental endocrine disruptor in the brain, the gonads, the fat, the well-perfused tissue, the poorly perfused tissue, and the skin; Determining the mass balance differential equation of environmental endocrine disruptors in the arterial blood; Determine the differential equation for mass balance of environmental endocrine disruptors in the gastrointestinal tract; Determine the differential equation for the mass balance of environmental endocrine disruptors in the kidney; Determining the differential equation for the mass balance of environmental endocrine disruptors in the liver; Determining a differential equation for the mass balance of environmental endocrine disruptors in the venous blood; Determine the mass balance differential equations of environmental endocrine disruptors in the gills.

3. The method according to claim 2, characterized in that The mass balance differential equation for determining the environmental endocrine disruptors in the brain, the gonads, the fat, the well-perfused tissue, the poorly perfused tissue, and the skin is: In the formula, Q i Indicates the amount of substance in each compartment, F i represents the blood flow in each compartment, C art Indicates the concentration of a substance in arterial blood, C i Indicates the concentration of the substance in each compartment, PC i Indicates the compartment-blood partition coefficient.

4. The method according to claim 2, characterized in that: The mass balance differential equation for determining environmental endocrine disruptors in the arterial blood is: In the formula, Q art Indicates the amount of the substance in the arterial blood, F card represents cardiac output, C ven Indicates the concentration of a substance in venous blood, C art Indicates the concentration of a substance in arterial blood.

5. The method according to claim 2, characterized in that: The mass balance differential equation for determining environmental endocrine disruptors in the gastrointestinal tract is: In the formula, Indicates the amount of material in the lumen of the gastrointestinal tract, Frac abs represents the absorption ratio, Q ingest Indicates the amount of gastrointestinal absorption, K u represents the absorption diffusion coefficient, Ke feces represents the fecal excretion rate constant, K BG represents the delivery rate of bile into the gastrointestinal tract, Q bile represents the amount of bile, Qfeces represents the amount of substances excreted through feces, and Q GIT Indicates the amount of material in the gastrointestinal tissue, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C art Indicates the concentration of a substance in arterial blood, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT Represents the tissue-blood partition coefficient of the gastrointestinal tract.

6. The method according to claim 2, characterized in that The mass balance differential equation for determining environmental endocrine disruptors in the kidney is: In the formula, Q k Indicates the amount of substance in the kidney, F k represents the blood flow in the kidney, C art Indicates the concentration of a substance in arterial blood, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp represents the blood flow to the inadequately perfused tissue, C pp represents the concentration of a substance in the poorly perfused tissue, PC pp Indicates the poorly perfused tissue-blood partition coefficient, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C s Indicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, C k Indicates the concentration of a substance in the kidney, PC k represents the kidney-blood partition coefficient, Qurine represents the amount of substance in urine, Ke urine represents the urine excretion rate constant.

7. The method according to claim 2, characterized in that The mass balance differential equation for determining environmental endocrine disruptors in the liver is: In the formula, Q l Indicates the amount of substance in the liver, F l represents the blood flow in the liver, C art Indicates the concentration of a substance in arterial blood, F rp Indicates the blood flow to fully perfuse the tissue, C rp represents the concentration of a substance in the well-perfused tissue, PC rp represents the fully perfused tissue-blood partition coefficient, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C GIT Indicates the concentration of a substance in the tissues of the gastrointestinal tract, PC GIT represents the gastrointestinal tissue-blood partition coefficient, F go represents the blood flow in the gonads, C go represents the concentration of a substance in the gonad, PC go represents the gonad-blood partition coefficient, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, Ke bile represents the bile excretion rate constant, It indicates the amount of substances metabolized by the liver.

8. The method according to claim 2, characterized in that: The mass balance differential equation for determining environmental endocrine disruptors in the venous blood is: In the formula, Q ven Indicates the amount of the substance in the venous blood, F b Represents the blood flow in the brain, C b Indicates the concentration of a substance in the brain, PC b represents the brain-blood partition coefficient, F f represents the blood flow in fat, C f Indicates the concentration of a substance in the fat, PC f represents the fat-blood partition coefficient, F l represents the blood flow in the liver, F rp Indicates the blood flow to fully perfuse the tissue, F go represents the blood flow in the gonads, F GIT represents the blood flow in the tissues of the gastrointestinal tract, C l Indicates the concentration of the substance in the liver, PC l represents the liver-blood partition coefficient, F k represents the blood flow in the kidney, α Fpp Indicates the distribution ratio of venous blood in insufficiently perfused tissues, F pp represents the blood flow of the insufficiently perfused tissue, α Fs Indicates the distribution ratio of venous blood in the skin, F s represents the blood flow in the skin, C k represents the concentration of the substance in the kidney, C pp represents the concentration of a substance in the poorly perfused tissue, PC pp Indicates insufficient perfusion tissue-blood partition coefficient, C s Indicates the concentration of a substance in the skin, PC s represents the skin-blood partition coefficient, F card represents cardiac output, C ven represents the concentration of the substance in the venous blood, Q admin_gill Indicates the amount of material in the gills, Indicates the amount of metabolites in the blood, Q excret_gill Represents the amount of material excreted through the gills.

9. The method according to claim 2, characterized in that: The mass balance differential equation for determining environmental endocrine disruptors in the gills is: In the formula, Q admin_gill represents the amount of material in the gill, K x The exchange coefficient representing the chemical flux through the gills, C water Indicates the concentration of a substance in water.

10. The method according to claim 1, characterized in that The multiple model parameters include unbound proportion of the compound, lipid-water distribution coefficient and liver clearance rate; Accordingly, the multiple model parameters of the initial physiological toxicokinetic model are optimized to obtain multiple optimized model parameters, including: Optimizing the unbound ratio of the compound to obtain an optimized unbound ratio of the compound; Optimizing the fat-water distribution coefficient to obtain an optimized fat-water distribution coefficient; The liver clearance rate is optimized to obtain an optimized liver clearance rate.

11. The method according to claim 10, characterized in that The unbound ratio of the compound is optimized to obtain an optimized unbound ratio of the compound, and the optimization formula is: In the formula, f u1 represents the optimized unbound fraction of the compound for the non-dissociable chemical, f u2 represents the unbound ratio of the optimized compound for the dissociable chemical species; v wbl Indicates water content, P bw represents the blood-water partition coefficient, logKow represents the octanol-water partition coefficient for an imdissociable chemical substance, and logDow represents the octanol-water partition coefficient for a dissociable chemical substance.

12. The method according to claim 10, characterized in that The fat-water distribution coefficient is optimized to obtain an optimized fat-water distribution coefficient, and the optimization formula is: D ow =f n,fish ×K ow +(1-f n,fish )×K ow,ion Where D ow represents the optimized fat-water distribution coefficient, f n,fish Indicates the proportion of neutral molecules in the fish body, K ow represents the n-octanol-water partition coefficient, K ow,ion is the octanol-water partition coefficient of the ionic molecule, pKa represents the acid dissociation constant, and j represents the coefficient.

13. The method according to claim 12, characterized in that The liver clearance rate is optimized to obtain an optimized liver clearance rate, and the optimization formula is: Cl hepatic =K M,X ×V D In the formula, Cl hepatic represents the optimized liver clearance, K M,X represents the mass- and temperature-dependent rate constant, V D represents the apparent volume of distribution, K M,N represents the standard rate constant, BM represents the weight of the fish, T represents the temperature, V i Indicates the volume of each compartment; f nl,i represents the proportion of neutral lipids in each compartment, f pl,i represents the proportion of polar lipids in each compartment, f nlom,i represents the proportion of non-lipid organic matter in each compartment, f w,i Indicates the proportion of water in each compartment, D ow represents the optimized lipid-water distribution coefficient, P bw It represents the blood-water partition coefficient.

14. The method according to claim 1, characterized in that The exchange coefficient of the fish gill chemical flux is corrected to obtain the corrected exchange coefficient of the fish gill chemical flux, and the correction formula is: In the formula, K x ′ represents the exchange coefficient of the corrected gill chemical flux, F water Indicates the effective breathing volume, F card represents cardiac output, P bw It represents blood-water partition coefficient, VO2 represents oxygen consumption rate, OEE represents oxygen uptake efficiency, and Cox represents dissolved oxygen concentration.

15. The method according to claim 1, characterized in that The temperature prediction equation is: In the formula, represents the temperature reaction rate, Indicates the temperature reaction rate at the preset temperature. represents the characteristic constant, T A represents the Arrhenius temperature, T r Indicates the preset temperature, and T indicates the absolute temperature of water.

16. The method according to claim 1, characterized in that The growth equation is: Where L represents the structural length of the fish. represents the energy consumption rate, f represents the relative density of food, g represents the energy input ratio, L m Indicates the maximum structural length of the fish.

17. The method according to any one of claims 1 to 16, characterized in that: After obtaining the second physiological toxicokinetic model, the method further comprises: Inputting specific physiological parameters of the target fish, specific physicochemical parameters of the target compound, and toxicokinetic parameters into the second physiological toxicokinetic model to output predicted concentrations of the target compound in each compartment of the fish; The second physiological toxicokinetic model is evaluated based on the predicted concentration and the measured concentration.

18. The method according to any one of claims 1 to 16, characterized in that: After obtaining the second physiological toxicokinetic model, the method further comprises: Through sensitivity analysis, the normalized dimensionless sensitivity coefficients of the parameters in the second physiological toxicokinetic model after changes are obtained.

19. The method according to claim 18, characterized in that The sensitivity analysis formula is: In the formula, S ij represents the normalized dimensionless sensitivity coefficient, Represents the output variable value, represents the input parameter value, Δθ j Indicates the input parameter change value, Δy i Indicates the change value of the output variable.

20. A device for predicting the concentration of environmental endocrine disruptors in fish, characterized in that: Applicable to servers, including: a partitioning module for partitioning fish into compartments using an initial physiological toxicokinetic model of fish; A determination module for determining a mass balance differential equation of environmental endocrine disruptors in each compartment; A receiving module, used for receiving species-specific physiological parameters, compound-specific physicochemical parameters and toxicokinetic parameters sent by a data acquisition device; An optimization module, used to optimize multiple model parameters of the initial physiological toxicokinetic model to obtain multiple optimized model parameters; A correction module, used for correcting the exchange coefficient of the fish gill chemical flux to obtain a corrected exchange coefficient of the fish gill chemical flux; An acquisition module, used for embedding the temperature prediction equation and the growth equation into the initial physiological toxicokinetic model to obtain a first physiological toxicokinetic model; A prediction module is used to optimize the first physiological toxicokinetic model according to the mass balance differential equations of each compartment, the species-specific physiological parameters, the compound-specific physicochemical parameters, the toxicokinetic parameters, the multiple optimized model parameters and the corrected exchange coefficient of the fish gill chemical flux to obtain a second physiological toxicokinetic model; wherein the second physiological toxicokinetic model is used to predict the concentration of environmental endocrine disruptors in fish.

21. 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 1-19.

22. 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 19 when executed by a processor.

23. 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 19 when being executed by a processor.

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