Method for synergistic application of cell therapy and hydrogen-oxygen anions in endocrine system conditioning

Abstract

This invention specifically relates to a method for the synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation, involving the field of medical informatics technology. The method includes: calculating the initial transmembrane electrochemical potential difference, correcting the transmembrane potential equation, and solving for the target potential shift; constructing a nonlinear model of permeability evolution based on cell therapy intervention markers, and establishing a resonance criterion for matching resonance. In this invention, a digital twin model of the electrophysiology of endocrine target cells is constructed to achieve deep matching of cell therapy and hydrogen-oxygen negative ion intervention in terms of timing, permeability, and resonance frequency, thereby improving the synergistic regulatory efficacy. The system relies on EIT impedance acquisition, adaptive Wiener filtering, and Cole-Cole model fitting to characterize core physiological features such as cell membrane capacitance and resting potential. Combined with the dynamic evolution model of permeability after cell therapy intervention, the optimal window period for ion intervention is locked, enabling hydrogen-oxygen negative ions to efficiently penetrate the cell membrane and act on target cells.

Description

Technical Field

[0001] This invention relates to the field of medical informatics technology, and in particular to a method for the synergistic application of cell therapy and hydrogen-oxygen negative ions in the regulation of the endocrine system. Background Technology

[0002] Cell therapy, as a cutting-edge technology in the field of regenerative medicine, can achieve the replacement and repair of damaged endocrine cells, paracrine nutritional support, and local microenvironment regulation by targeted transplantation of functional cells or stem cells. It has shown good application prospects in the treatment and management of various endocrine diseases such as diabetes, thyroid dysfunction, and adrenal diseases. However, the colonization, survival, activity maintenance, and function of transplanted cells are highly dependent on the appropriate physiological microenvironment of the target area.

[0003] Currently, the combined application of cell therapy and hydrogen-oxygen negative ion intervention is mainly implemented in stages in clinical practice, and it has shown certain synergistic potential in the treatment of some endocrine diseases.

[0004] The electrophysiological properties and ion permeability of endocrine target cell membranes undergo dynamic temporal changes with the intervention of cell therapy. The intervention effect of hydrogen and oxygen negative ions is closely related to the real-time physiological state of target cells, the spatiotemporal matching degree of intervention parameters, and energy synergy efficiency. In current applications, a full-process collaborative technology system covering real-time perception of the physiological state of target cells, precise modeling of personalized intervention parameters, and dynamic regulation has not yet been formed, making it difficult to fully realize the synergistic potential of the two.

[0005] Based on this, developing a precise regulation method that can achieve deep synergy between cell therapy and hydrogen-oxygen negative ion intervention has important clinical value and technical significance for improving the conditioning effect of endocrine diseases. Summary of the Invention

[0006] The purpose of this invention is to address the aforementioned problems by proposing a method for the synergistic application of cell therapy and hydrogen-oxygen negative ions in the regulation of the endocrine system.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: The synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation includes: The complex impedance spectrum of the endocrine target area tissue was obtained and the equivalent cell membrane capacitance was extracted by fitting. The observed voltage signal was subjected to adaptive Wiener filtering to extract the resting potential reference value. The absolute temperature and initial ion concentration were collected simultaneously to construct the environmental background vector matrix. The initial transmembrane electrochemical potential difference was calculated, the transmembrane potential equation was corrected, and the target potential offset was solved. A nonlinear model of permeability evolution was constructed based on cell therapy intervention markers, and a resonance criterion for matching resonance was established. The initial convection velocity vector and the optimal initial concentration baseline are calculated by using the target potential offset and a nonlinear model of permeability evolution; pulse width modulation control commands are generated based on the resonance criterion. Substitute the predicted ion concentration that penetrates into the cell into the mitochondrial transmembrane proton dynamic potential correction equation, and combine catalytic kinetics to solve the instantaneous adenosine triphosphate synthesis rate. The observation state vector containing the cooperative energy conversion efficiency function is optimally estimated based on the unscented Kalman filter. The optimal estimated state vector is then used for rolling optimization and sent down to the hydrogen-oxygen negative ion device for execution. When the residual meets the exit threshold, an exponentially decaying adaptive smooth exit is performed.

[0008] Preferably, the step of obtaining the target region complex impedance spectrum to extract the equivalent cell membrane capacitance includes: A broadband swept AC excitation current was applied to the endocrine target area, and the voltage response signal at different frequencies was extracted to calculate the complex impedance spectrum. Based on the relaxation model, the DC equivalent resistance of extracellular fluid and the ultra-high frequency equivalent resistance of fluid penetrating inside and outside the cell are separated. By combining the characteristic relaxation time constant extracted from the fitting with the difference between the DC equivalent resistance and the ultra-high frequency equivalent resistance, the equivalent cell membrane capacitance characterizing the cell's energy storage properties is derived.

[0009] Preferably, the extraction of the resting potential reference value through adaptive Wiener filtering specifically includes: The autocorrelation function and cross-correlation function matrix of the observed signal are continuously calculated within the sliding time window; By minimizing the mean square error between the real signal and the filtered output signal, the discrete Wiener-Hough matrix equation is solved in real time to dynamically update the filter coefficients. The low-frequency DC component, which eliminates environmental thermal noise and has a stable baseline, is extracted and used as the resting potential reference value.

[0010] Preferably, the process of calculating the initial transmembrane electrochemical potential difference, correcting the transmembrane potential equation, and solving for the target potential shift is as follows: The system allocates a three-dimensional grid matrix in memory, defining the state parameter in the matrix as the total electrochemical potential difference across the cell membrane. ; The system performs the following discretized thermodynamic energy equation for each virtual grid node: ; in, The ideal gas constant is preset. The absolute temperature of a local tissue; The valence state of the intervening ions involved in the simulation; The Faraday constant is a preset value. and These are the initial estimated values ​​of ion molar concentrations for the interstitial fluid grid on the outer side of the cell membrane and the cytoplasmic grid on the inner side of the cell membrane, respectively, in the three-dimensional grid network established by the system. Equivalent to the resting potential reference value ; By using a cyclic calculation equation, the initial potential energy baseline of the current endocrine cell membrane when it is not interfered with by external physical equipment is obtained; The following modified nonlinear equations are executed in parallel: ; in, This is the dynamic equilibrium potential value; The relative permeability static constant weighting coefficients of the natural channels for potassium, sodium, and chloride ions in endocrine cells are pre-set in the system. and A scalar matrix of steady-state transmembrane background concentrations in the microenvironment pre-configured for the database; This is the functional of forced diffusion flux outside the membrane; The membrane forced permeation flux functional is constructed for the system.

[0011] Preferably, the construction of a nonlinear model of permeability evolution based on cell therapy intervention markers, and the establishment of a resonance criterion for matching resonances, specifically includes: By introducing nonlinear evolution compensation in the time dimension, a nonlinear model of permeability evolution is calculated: ; in, The basic permeability constant; A continuous timestamp variable; It is the reciprocal of the negative physiological time constant; This represents the limiting saturation value of the permeability increment coefficient. The reciprocal of the positive time constant for channel reconstruction; Continuous computation The function allows the system to obtain a reference control curve that dynamically fluctuates over time in the digital space, ensuring that the parameters of the ion device output can be acquired and matched to the dynamic opening and closing window of the cell membrane. The system extracts the equivalent cell membrane capacitance obtained in step one. And combined with preset film equivalent inductance parameters The theoretical spontaneous oscillation frequency of endocrine cells was calculated using the LC oscillation model. This establishes the pulse frequency to be sent to external devices. Resonance criterion to be satisfied: ; in, The minimum positive real frequency tolerance threshold is forcibly constrained in the system register; the optimal center frequency that allows external hydrogen-oxygen negative ion devices to emit high-voltage square wave pulses is derived by using algebraic transformation. And store it in the buffer sequence queue of control commands to be sent.

[0012] Preferably, the process of calculating the initial convection velocity vector and the optimal initial occurrence concentration baseline by using the target potential offset and the nonlinear model of permeability evolution is as follows: To reverse-engineer the required forced wind speed and background ion concentration at the initial nozzle of the generator, a three-dimensional Nernst-Planck spacetime partial differential equation system was built into the calculator: ; in, For a point within a 3D spatial grid At any moment The total diffusion flux vector matrix of a specific anion; For Fick's natural diffusion term; For directional electric field migration term, where This is a digital parameter for ion mobility; For convection transport terms, The core velocity vector; The system discretizes the spatial region from the device nozzle to the endocrine target area into a three-dimensional mesh, and substitutes the following calculation boundary conditions: Starting Dirichlet boundary: at the origin of the generator hardware nozzle coordinates Location, concentration Constrained to the desired generator concentration baseline ; Terminal Neumann boundary: On the virtual uptake surface of targeted endocrine cells, the microscopic normal flux gradient is defined as equal to... The dot product with the local discrete concentration; Iterative calculations yield the initial convective velocity vector that ensures the flux at the end-absorber surface meets the target value. Baseline of optimal initial occurrence concentration .

[0013] Preferably, the step of generating pulse width modulation control commands based on resonance criteria specifically includes: To match the resonant frequency At the same time, without inducing oxidative stress, the system's computing module needs to calculate the precise proportion of high-level time in each pulse cycle, i.e., the dynamic duty cycle. ; The system executes a nonlinear exponential compensation control equation that conforms to the threshold response characteristics of biofilms: ; in, This is the absolute value of the error between the predicted target membrane potential and the filtered actual resting potential within the current system sampling and observation period; This is the resting potential reference constant stored in the system. and These correspond to the minimum effective corona discharge arc ignition duty cycle and the maximum physical safety limit duty cycle to prevent overheating and breakdown of the equipment cavity, respectively. For the adaptive gain-damping hyperparameter of the control system; After multidimensional tensor computation and mapping logic, the system will obtain the control parameter tuple. The data is packaged into a digital communication frame sequence and periodically sent to the underlying microcontroller of the external physical hydrogen-oxygen negative ion device.

[0014] Preferably, the step of determining the adenosine triphosphate synthesis rate includes: The basal transmembrane potential difference and pH difference of the inner mitochondrial membrane are extracted and superimposed with the integral term of the predicted ion concentration entering the cell by the binding energy coupling weighting coefficient to obtain the total proton dynamic potential. By substituting the total proton driving potential as the substrate driving force into the catalytic kinetic model, and limiting the linear increase of the synthesis rate to avoid the risk of oxidative stress when the total proton driving potential approaches the Michaelis constant corresponding to the maximum catalytic rate limit of the cell.

[0015] Preferably, the optimal estimation of the observed state vector containing the cooperative energy conversion efficiency function based on unscented Kalman filtering includes: Multiple sampling points are calculated in a deterministic distribution within the neighborhood of the current state estimate; The sampling points are substituted into the nonlinear mapping equation and weighted summation is performed by combining the covariance matrices of process noise and observation noise. The optimal mean and covariance matrix of the state vector are reconstructed to eliminate the linearization truncation error of the Jacobian matrix of the nonlinear system, and the optimal estimated state vector is output.

[0016] Preferably, the step of substituting the output optimal estimated state vector into the cost function of the nonlinear model predictive control for rolling optimization, sending it down to the hydrogen-oxygen negative ion device for execution, and performing an exponentially decaying adaptive smooth exit when the residual meets the exit threshold includes: Introduce a state error weight matrix and a control increment weight matrix to limit drastic hardware changes into the cost function; When the predicted total ion concentration entering the cell exceeds the biological tolerance safety threshold, a boundary penalty mechanism that grows in a cubic order is triggered to forcibly reduce the control duty cycle. When the residual of the evaluation is less than the exit threshold for several consecutive cycles, the direct power-off command is blocked, and the device output is slowly down-modulated according to the exponential decay function until the device is powered off.

[0017] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention constructs a digital twin model of the electrophysiology of endocrine target cells to achieve deep matching of cell therapy and hydrogen-oxygen negative ion intervention in terms of timing, permeability, and resonant frequency, thereby enhancing the synergistic conditioning efficacy. The system relies on EIT impedance acquisition, adaptive Wiener filtering, and Cole-Cole model fitting to characterize core physiological features such as cell membrane capacitance and resting potential. Combined with the dynamic evolution model of permeability after cell therapy intervention, the optimal window period for ion intervention is locked, enabling hydrogen-oxygen negative ions to efficiently penetrate the cell membrane and act on target cells.

[0018] 2. This invention reduces the energy barrier of ion transmembrane delivery and improves the efficiency of targeted delivery by designing pulse excitation based on LC resonance criterion; it uses the real-time physiological state of cells as the driving force for personalized regulation, which not only provides a stable and suitable metabolic microenvironment for transplanted cells, enhancing their colonization survival and paracrine function, but also avoids ineffective intervention and energy waste, so that cell repair and physical conditioning form a positive gain, improving the effect and stability of endocrine system function reconstruction. Attached Figure Description

[0019] Further details, features, and advantages of this application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0020] Several embodiments of this application will now be described in more detail with reference to the accompanying drawings to enable those skilled in the art to implement this application. This application may be embodied in many different forms and for various purposes and should not be limited to the embodiments set forth herein. These embodiments are provided to make this application thorough and complete, and to fully convey the scope of this application to those skilled in the art. The embodiments described do not limit this application.

[0021] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having a meaning consistent with their meaning in the relevant field and / or the context of this specification, and shall not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0022] Example 1 Its specific implementation method is combined with the appendix Figure 1 Please provide a detailed explanation.

[0023] Appendix Figure 1 The flowchart of the method for the synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation provided in the embodiments of the present invention shows the complete steps from obtaining the complex impedance spectrum of the endocrine target area tissue and fitting and extracting the equivalent cell membrane capacitance to performing an exponentially decaying adaptive smooth exit.

[0024] In this embodiment, it includes: Step 1: Cell membrane potential data acquisition and benchmark establishment, configured as follows: acquire the complex impedance spectrum of endocrine target tissue and fit to extract equivalent cell membrane capacitance, perform adaptive Wiener filtering on the observed voltage signal to extract the resting potential benchmark value, and simultaneously acquire absolute temperature and initial ion concentration to construct an environmental background vector matrix; This step forms the data foundation for constructing the entire nonlinear dynamic digital twin model. The system uses rigorous physical detection methods to acquire the current electrophysiological microenvironment state of the cell population in the endocrine lesion target area in real time, and applies pure mathematical signal processing techniques for high-dimensional feature extraction and background noise removal.

[0025] The system's underlying firmware drives the EIT patch electrode array to apply a wide-frequency swept AC excitation current (with a constant amplitude between 10μA and 50μA) at the microampere level, conforming to human safety standards and having a preset time envelope, to the target endocrine region. The system simultaneously and at high speed acquires the voltage response signals of the target tissue to currents of different frequencies, and uses a Fast Fourier Transform (FFT) algorithm to calculate the complex impedance spectrum of the target tissue. Complex impedance in the complex plane consists of a real part (characterizing pure resistive dissipation) and an imaginary part (characterizing capacitive energy storage).

[0026] To accurately separate the independent physical contributions of extracellular fluid, intracellular fluid, and the cellular lipid bilayer, the system not only extracts the impedance modulus but also substitutes the collected discrete complex impedance data point sequence into the improved Cole-Cole classical relaxation model equation for curve space fitting: ; In this formula: To achieve the preset AC excitation frequency The complex impedance measured by the lower system is expressed in ohms. ); DC (i.e., extremely low frequency, frequency) The tissue equivalent resistance (approaching 0). This parameter is crucial because low-frequency currents are hindered from penetrating the cell membrane by the high capacitive reactance of the membrane capacitance. Therefore, this value purely characterizes the ionic conductivity state of the extracellular fluid, and its unit is... ; This is the equivalent resistance at extremely high frequencies. High-frequency currents can penetrate completely into and outside the cell without obstruction by membrane capacitance. This value characterizes the total resistance of the parallel network of intracellular and extracellular fluids, and is measured in units of... ; This is the characteristic relaxation time constant of the cell membrane, expressed in seconds. This value exhibits a highly nonlinear mapping relationship with the average geometric radius and membrane dielectric constant of the endocrine cell population in the target area. The dimensionless distribution coefficient of relaxation time is introduced into the system, and its value range is strictly defined between (0,1]. This coefficient directly reflects the degree of heterogeneity in the morphology and size distribution of cell populations at endocrine lesions; The system invokes the built-in damped least squares nonlinear optimization algorithm to solve for the four core unknown parameters in the multidimensional parameter space. .

[0027] Based on this, in order to obtain the key physical quantities that can characterize the energy storage properties of cells, the system uses the electrical equivalent network transformation formula. Accurately derive the current equivalent cell membrane capacitance baseline value of the target cell population. The unit is farad (Faraday) This parameter It is the absolute core parameter for deriving the resonant frequency of the transmembrane potential fluctuation in subsequent steps.

[0028] Because the natural resting potential of endocrine cell populations is extremely weak (typically distributed in the deep water range of -40mV to -90mV), they are easily overwhelmed by electromyographic (EMG) interference, 50Hz / 60Hz power frequency interference, and ambient thermal white noise during epidermal sampling. To avoid phase distortion and unreliable predictions that may be caused by conventional neural network filtering, the system employs an adaptive Wiener filtering algorithm based purely on statistical signal processing.

[0029] The system is configured to acquire the original noisy observed voltage signal discrete sequence via analog-to-digital converter as follows: .

[0030] in This is the sequence of real endocrine cell membrane electrophysiological signals to be recovered. The superposition assumption is that the environmental thermal noise sequence is a generalized stationary process.

[0031] The system continuously calculates the autocorrelation function of the observed signal within a sliding time window. Estimation matrix of cross-correlation function The optimization objective of the system is to automatically design a finite-length unit impulse response (FIR) digital filter, with its coefficient weight vector as follows: .

[0032] The system requires the output of this filter. With unknown real signals Expected value of statistical mean square error between To achieve the global minimum.

[0033] Therefore, the system's central processing unit solves the following discrete Wiener-Hough matrix equations in each sampling clock cycle: ; By continuously inverting and iterating the matrix The system dynamically updates the filter coefficient vector in real time. After rigorous cleaning by the phase-distortion-free filter, the system extracts the DC voltage component with an absolutely stable baseline and retains its low-frequency, slow-fluctuation characteristics. This component is then defined as the current resting potential reference value for the endocrine target cell population. Unit precision is retained to the microvolt (µV). ).

[0034] To establish absolutely accurate initial boundary conditions and environmental perturbation parameters in the nonlinear partial differential equations of steps two and three, the system must quantitatively acquire the macroscopic physical environment state at the time of intervention. The system uses a high-precision front-end thermal and gas sensor network to collect and construct the environmental background vector matrix in real time. .

[0035] The physical definitions of each element are as follows: and These represent the baseline molar concentrations of initial background oxygen and hydrogen ions in the air of the treatment microenvironment before physical intervention, in units of... This provides a baseline deduction for the absolute increment that needs to be added to the ion equipment in subsequent calculations.

[0036] The absolute temperature of the patient's local tissues is collected in real time, and the unit is Kelvin (K). It must be emphasized that this temperature parameter is not merely used to monitor whether a patient has a fever; it is directly substituted as a core independent variable into the subsequent Straumann-Einstein equation to dynamically and in real-time correct the diffusion coefficient of ions in body fluids. In reality, the range of variation is usually precisely between 308.15K and 315.15K, which highly reflects the intensity of microvascular contraction and dilation and metabolic heat production in the local endocrine glands.

[0037] The relative humidity of the environment is expressed as a percentage ( ). This parameter is indicated by (). The system will use this parameter to look up and correct the dielectric constant attenuation rate and aerosol dissolution rate of ions penetrating the air / stratum corneum interface.

[0038] At this point, the system has successfully transformed the previously vague, invisible, and highly individualized biological states of endocrine cells into a comprehensive understanding. A series of rigorous, quantitative, and interference-resistant physical digital reference matrices.

[0039] These baseline tensor matrices have been securely stored in the CPU's cache, ready to serve as the basis for triggering subsequent deep nonlinear electrochemical mapping and coupled solutions.

[0040] Step 2: Nonlinear modeling of cell membrane electrochemical gradient, configured as follows: calculate the initial transmembrane electrochemical potential difference based on the resting potential benchmark, introduce the external forced diffusion flux functional and the internal forced permeation flux functional to correct the transmembrane potential equation, and solve for the target potential offset; construct a nonlinear model of permeability evolution based on cell therapy intervention markers, and establish a resonance criterion for matching resonance by combining the equivalent cell membrane capacitance; The core purpose of this step is to have the system's central processing unit and hardware floating-point unit (FPU) receive the physical reference matrix output to the cache in step one. Furthermore, a dynamic digital twin model representing the transmembrane energy state of the endocrine target cell population is constructed in a digital logical space. This process is entirely completed within an electronic computing architecture through parallel computing, without involving direct physical contact with the human body.

[0041] The system first accesses a pre-stored database of thermodynamic and electrochemical standard constants in read-only memory (ROM). The system then allocates a three-dimensional raster matrix in memory, defining the state parameter within this matrix as the total electrochemical potential difference across the cell membrane. This tensor matrix physically reflects the baseline of ion migration potential energy driven by both the microscopic chemical concentration gradient and the macroscopic electric field gradient.

[0042] The system performs the following discretized thermodynamic energy equation for each virtual grid node: ; In this formula, all parameters have a strict numerical mapping in system memory addressing: The ideal gas constant is preset, and the system strictly takes the value of 8.314 J / (mol·K); The absolute temperature of the local tissue, updated in real time from step one to the memory (RAM), is measured in units of... ; The valence state of the intervening ions involved in the simulation. Since the system primarily calculates the externally sourced hydrogen anions (… ) and oxygen negative ions ( The underlying penetration dynamics of ) will be discussed in the logical branches of the system. It is strictly and consistently assigned the value -1; The preset Faraday constant is a system constant with a value of 96485 C / mol. and : These are the initial estimated ion molar concentration matrices representing the interstitial fluid grid on the outer side of the cell membrane and the cytoplasmic grid on the inner side, respectively, within the three-dimensional raster network established by the system. These initial values ​​are preloaded based on physiological constants from different endocrine sites (such as pancreatic islet tissue or thyroid tissue), and the units are 1200 ppm. ; This voltage difference term is directly substituted into the resting potential reference value obtained after adaptive Wiener filtering in step one. ; The system calculates this equation iteratively to obtain the "initial potential energy baseline" of the endocrine cell membrane when it is not interfered with by external physical devices. This baseline is the only reference for subsequently determining the absolute value of the energy gap.

[0043] Traditional transmembrane potential equations are only applicable to the natural physiological homeostasis under absolutely closed conditions without external interference. In order to accurately calculate the "target potential shift" that the cell membrane can achieve after the intervention of an external hydrogen-oxygen negative ion device, the system introduces nonlinear perturbation functionals of forced convection and microscopic diffusion into the pure mathematical model; The system's multi-core processors execute the following modified nonlinear equations in parallel: ; The numerical meanings and physical constraints of each element in the equation are as follows: The dynamic equilibrium potential value that the system attempts to predict, under the pre-set external high concentration of ion intervention, will be forced to the cell membrane; The relative permeability static constant weighting coefficients of the natural channels for potassium, sodium, and chloride ions in endocrine cells are pre-set for the system (pre-set as prior ratios of 1.0:0.04:0.45, etc.). and A scalar matrix of steady-state transmembrane background concentrations in the microenvironment pre-configured for the database; This is the functional of forced diffusion flux outside the membrane. The system is calculated using the formula... Perform real-time evaluation calculations; in The dimensionless collision probability coefficient is set by the system based on the extracellular matrix density; For local temperature Diffusion coefficient dynamically corrected according to Einstein's relation (units) ); The system's preset physical device ion release pulse interval period (unit) ).

[0044] The forced permeate flux functional within the membrane is constructed for the system. The system performs calculations based on the transmembrane dissipation barrier theory: ; here This represents the digital empirical constant for ligand binding within the membrane; The activation free energy required for ions to cross the core hydrophobic region of a pre-defined endocrine cell lipid bilayer, as preset in the database, is expressed in units of... .

[0045] Because the equation contains highly nonlinear transcendental characteristics, the system's main control chip calls the Newton-Raphson iterative root-finding algorithm to continuously approximate and finally output the theoretically optimal external ion concentration threshold matrix that balances both sides of the above equation within the set computational domain.

[0046] When the system receives a digital flag signal (Flag=1) indicating that "cell therapy has been implemented" (e.g., mesenchymal stem cell suspension has been injected) through the human-computer interaction interface or hospital information system (HIS) interface, the physicochemical properties (such as lipid fluidity) of the cell membrane of the in situ endocrine lesion will undergo temporal remodeling for up to several weeks due to the fusion of exogenous target cells or the release of paracrine microvesicles from stem cells.

[0047] The system must incorporate nonlinear evolution compensation in the time dimension. A high-precision microsecond-level timer is activated within the system to calculate the nonlinear model of the transparency evolution in real time. ; In this time function: The current time predicted by the system The absolute co-permeability of endocrine cell membranes to external negative ions, in units of ; This represents the baseline permeability constant of cells under standard, uninterrupted conditions. This is a continuous timestamp variable recorded by the system after the cell therapy flag is triggered; This is the reciprocal of the negative physiological time constant for the temporary closure of channels caused by initial cell fusion stress, in units of ; The permeability increment coefficient limit saturation value determined by the preset dose of the input cell therapy, in units. ; The inverse of the positive time constant of channel remodeling caused by the later effects of paracrine signaling and increased membrane porosity, in units of ; Through continuous calculation The system obtains a reference control curve in the digital space that fluctuates dynamically over time, which ensures that the parameters of the ion device output can accurately "track" and match the slow dynamic opening and closing window of the cell membrane.

[0048] To maximize the coupling conversion rate between the physical device's intervention energy and the underlying biological electrochemical processes, and to avoid ineffective irradiation, the system has established strict resonant frequency domain matching conditions.

[0049] The system extracts the equivalent cell membrane capacitance obtained in step one. And combined with preset film equivalent inductance parameters (This parameter is based on a priori digital model of the endocrine target tissue type and characterizes the inertial delay effect of ion channels under electric field force.) The theoretical spontaneous oscillation frequency of endocrine cells is calculated using the classical LC oscillation model.

[0050] The system thus establishes the pulse frequency to be sent to external devices. The resonance criterion absolute value inequality that must be satisfied is: ; in, The minimum positive real frequency tolerance threshold, forcibly constrained in the system register, is strictly limited to the range [0.01Hz, 0.5Hz]. Based on this equation, the system computing unit uses algebraic transformations to derive the optimal center frequency that allows the external hydrogen-oxygen negative ion device to emit high-voltage square wave pulses. And store it in the buffer sequence queue of control commands to be sent.

[0051] Step 3: Ion pulse spatiotemporal dynamics control mapping, configured as follows: by substituting the target potential offset and the nonlinear model of permeability evolution into the three-dimensional Nernst-Planck partial differential equation, the initial convection velocity vector and the optimal initial occurrence concentration baseline are solved; based on the resonance criterion, a pulse width modulation control command containing instantaneous pulse frequency and dynamic duty cycle is generated. This step transforms the ideal calculation results (membrane potential offset and resonant frequency) in digital space into mixed digital / analog commands (including PWM duty cycle signals to control motor speed and DAC reference voltage signals to control the high-voltage ionization module) sent to the external hardware controller. The system establishes a four-dimensional (4D) precise mapping control model on three-dimensional Euclidean space and a one-dimensional time axis.

[0052] After high-concentration hydrogen and oxygen negative ions escape from the nozzle of the generator, they penetrate the air medium and the stratum corneum skin barrier, eventually reaching the deep target area of ​​the endocrine lesion. This process involves significant fluid dynamics and electrodynamic attenuation. To inversely calculate the required forced wind speed and background ion concentration at the initial nozzle of the generator, the system incorporates a three-dimensional Nernst-Planck spacetime partial differential equation system in its arithmetic unit: ; In this vector differential equation: : Represents a point within a three-dimensional spatial grid At any moment Preset anion (such as The total diffusion flux vector matrix (units) ; : Characterizes the Fick natural diffusion term driven purely by the spatial concentration gradient; : Characterizes the directional electric field migration term applied by the low-frequency micro-electric field emitter attached to the system generator. This is a digital parameter for ion mobility, in units of... ; : Characterizes the convective transport term induced by the initial macroscopic fluid momentum provided by the equipment's air pump. Here This refers to the core velocity vector that the system needs to solve in reverse and ultimately map to the rotational speed of the centrifugal fan's brushless DC motor (BLDC). (Unit: ...) .

[0053] The system discretizes the spatial region from the device nozzle to the endocrine target area into a three-dimensional mesh with a mesh step size of millimeters. The system incorporates the following two stringent computational boundary conditions: Starting Dirichlet boundary: at the origin of the generator hardware nozzle coordinates Location, concentration Constrained to the desired generator concentration baseline .

[0054] Terminal Neumann boundary: On the virtual uptake surface of the targeted endocrine cell, the microscopic normal flux gradient is defined as equal to the time-varying permeability calculated in step two. The dot product with the local discrete concentration.

[0055] The central processing unit calls a pre-built large sparse matrix solver (such as the generalized minimum residual method GMRES) to iteratively calculate the initial convective velocity vector that ensures the flux at the end-cap absorber precisely meets the target value. Baseline of optimal initial occurrence concentration Both of these will be packaged and compiled.

[0056] After the spatial flow flux requirement is theoretically satisfied, the system begins to handle pulse width control over extremely short timescales. This is to match the resonant frequency obtained in step two. At the same time, without inducing oxidative stress, the system's computing module needs to calculate the precise proportion of time occupied by the high level (i.e., the discharge conduction of the ionization chamber) within each microsecond-level pulse cycle, i.e., the dynamic duty cycle. .

[0057] Instead of using simple linear scaling, the system executes a nonlinear exponential compensation control equation that better reflects the threshold response characteristics of biofilms. ; During the solution of this parameter tensor: This is the absolute value of the error between the target membrane potential predicted in step two and the actual resting potential after filtering within the current system sampling and observation period. This value represents the transmembrane energy gap that the system still needs to "pump in" through the equipment. This is the resting potential reference constant stored in the system. and These are the hardware safety limiting parameters soldered into the digital controller firmware, corresponding to the minimum effective corona discharge arc initiation duty cycle (e.g., 12%) and the maximum physical safety limit duty cycle (e.g., 88%) to prevent the device cavity from overheating and breaking down. To optimize the adaptive gain-damping hyperparameter of the control system, the system will monitor the convergence rate of the error sequence over the first few time periods. If the system determines that the convergence is too slow (in an underdamped response state), it will automatically increase the hyperparameter in memory. Value; if potential overshoot oscillation occurs (in an overdamped response state), then decrease. The value is set, and the system's logic limiter will strictly clamp its value within [0.5, 2.0].

[0058] After the rigorous multidimensional tensor calculation and mapping logic described above, the system will obtain the control parameter tuple. The data is packaged into a series of digital communication frames conforming to industry standards (such as via an RS-485 serial communication bus) and periodically sent to the underlying microcontroller of an external physical hydrogen-oxygen negative ion device. The external hardware only needs to passively parse and execute these precise digital instructions, thereby achieving non-contact spatiotemporal intervention and coordination of the endocrine cell microenvironment in the target area without completely abandoning human experience.

[0059] Step 4: Cell-ion co-energy coupling calculation, configured as follows: Substitute the integral of the predicted ion concentration penetrating into the cell into the mitochondrial transmembrane proton dynamic potential correction equation, combine catalytic kinetics to solve the instantaneous adenosine triphosphate synthesis rate, and combine the total power consumption of the device's instantaneous electrical output to construct a dimensionless co-energy conversion efficiency function.

[0060] After completing the front-end mapping based on electrochemistry and fluid dynamics in steps two and three, this step enters the biocomputation energy logic layer.

[0061] The system's central processing unit must use purely digital modeling to quantify the extent to which the physical energy output by the hydrogen-oxygen negative ion device can be converted into the actual chemical energy (ATP) of the colonized cell mitochondria. This is the core technology to ensure that the issued control commands not only meet the requirements of "spatial arrival" but also "energy resonance".

[0062] The system's central processing unit invokes the mitochondrial bioenergetics digital model in parallel computing threads. Based on Peter Mitchell's chemiosmotic hypothesis, the system abstracts the driving force of intracellular ATP synthesis as the proton kinetic potential across the inner mitochondrial membrane. .

[0063] The system executes the following physicochemically corrected integral equation: ; in: The total proton dynamic potential scalar calculated by the system at the current moment, in millivolts (mV). This value directly determines the motor speed of subsequent ATP synthase; The basal natural transmembrane potential difference of the mitochondrial inner membrane. During system initialization, it is assigned a default value of a Gaussian distribution function with a mean of 160mV and a variance of 15mV, and real-time reference drift correction is performed based on the complex impedance phase angle extracted in step one. : A scalar value for the pH difference between the mitochondrial matrix and the intermembrane space (typically a digital parameter of about 0.5 to 1.0). and : Dimensionless energy coupling weighting coefficients preset in the system ROM register. These two coefficients represent the absolute physical efficiency of exogenous hydrogen and oxygen anions per unit molar concentration being captured by the mitochondrial respiratory chain (such as complex I and complex IV) and converted into a transmembrane proton gradient; This is the numerical integration term executed by the system. The system performs the integration on the value calculated in step two within the time window. Discrete ion concentration sequences that penetrate the cell membrane and enter the cytoplasm and Perform high-precision numerical integration using Simpson's rule. This step mathematically settles the "total account of exogenous physical energy" accumulated in the cell.

[0064] The system will use the proton dynamic potential obtained above. Substituting this substrate-driven force into the nonlinear catalytic kinetics model of ATP synthase, the system microprocessor executes the following rational fractional algebraic equation: ; In this equation: The instantaneous energy synthesis rate of the target endocrine cell population obtained virtually by the system, in units of ; This is the maximum theoretical catalytic rate limiting constant of ATP synthase, pre-set in the system database for different endocrine cells (such as pancreatic islet cells, which have extremely high energy requirements); The Michaelis constant is the physical meaning of the rate at which the synthesis rate reaches a certain value. The critical value of the proton dynamic potential corresponding to half of the value.

[0065] The non-obvious innovation of this step lies in the fact that the system no longer blindly and linearly increases the input power of external ions as in existing technologies. The system discovers through this nonlinear fractional calculation that when... Approaching the saturation point (i.e.) When ), the value of the fraction will approach the extreme value. At this point, the system determines that continuing to increase the input of hydrogen and oxygen negative ions will encounter "diminishing marginal returns," thus naturally avoiding energy waste and the potential risk of intracellular reactive oxygen species (ROS) overload at the algorithm level.

[0066] To provide an absolutely objective optimization target for subsequent control, the system defines a dimensionless efficiency index function to evaluate the compatibility between external physical electrical energy and internal biochemical energy conversion: ; In this global discriminant: The standard Gibbs free energy constant for ATP hydrolysis, with the system strictly taking the value as . This constant converts the synthesis rate of the previous step into absolute Joule heat level power.

[0067] : The total instantaneous power consumption of the device during the current millisecond-level observation period. Obtained by integrating the product of the driving voltage and current acquired by the system's underlying ADC, in watts (W). ).

[0068] The estimated resting thermodynamic energy consumption required for the cell to maintain the basic operation of the sodium-potassium pump.

[0069] The system monitors in memory in real time. The ultimate goal of numerical fluctuations in a sequence is to find and lock onto the system state attractor in a high-dimensional parameter space that maximizes the function value (i.e., energy cooperative optimization).

[0070] Step 5: Dynamic feedback control of equipment output parameters, configured as follows: Based on unscented Kalman filtering, the observed state vector containing the cooperative energy conversion efficiency function is optimally estimated, the optimal estimated state vector is substituted into the cost function of nonlinear model predictive control for rolling optimization, and sent down to the hydrogen-oxygen negative ion device for execution, and when the residual meets the exit threshold, an exponentially decaying adaptive smooth exit is performed. This step enables the entire system to transition from "static model solving" to "dynamic adaptive control".

[0071] The endocrine system exhibits strong time lag and nonlinear physiological resistance. To ensure the absolute robustness of control commands, the system abandons the commonly used PID linear control algorithm in industry and instead adopts a cascaded architecture of unscented Kalman filtering and nonlinear model predictive control, which is used in the attitude control of high-end spacecraft.

[0072] Given that baseline drift is inevitable in the acquisition of weak electrophysiological signals from living organisms, the system incorporates a UKF processing module in the main control loop.

[0073] The system defines a high-dimensional observation state vector. .

[0074] Faced with a large number of nonlinear transcendental equations (such as logarithmic and exponential functions) in steps two and four, conventional extended Kalman filtering requires solving the Jacobian matrix, which consumes a great deal of computational resources, and the linearization truncation error is extremely large.

[0075] This system uses unscented transformation: The system calculates, according to a deterministic distribution, within the neighborhood of the current state estimate. Sigma sampling points ( (For the state vector dimension). The system sequentially passes these Sigma points through all the nonlinear mapping equations in this case, and then uses a preset process noise covariance matrix. and observation noise covariance matrix (The system dynamically initializes the signal-to-noise ratio as a diagonal matrix based on the signal-to-noise ratio during the device's power-on self-test.) The optimal mean and covariance matrix of the state vector are reconstructed through weighted summation.

[0076] When the system performs weighted summation, the specific allocation model for the mean weight and covariance weight is as follows: First, the system is based on the state vector dimension. Define scaling parameters : ; in, The scaling factor (usually taken as a minimum value) is used to control the distribution range of Sigma points. This is a secondary scaling parameter that ensures the positive semidefiniteness of the matrix.

[0077] Subsequently, the system calculated Each Sigma sampling point is assigned a weight for reconstructing the optimal mean. Weights used to reconstruct covariance .

[0078] For the central sampling point ( Its weight is defined as: ; ; in, The non-negative weighting coefficients are those that incorporate prior knowledge of the state distribution (usually 2 for Gaussian distributions).

[0079] For the remaining surrounding sampling points ( Its mean weight and covariance weight are equal, and are defined as follows: ; Finally, the system uses the rigorously defined weight set to perform a weighted summation of the Sigma points and their residuals after nonlinear mapping, thereby reconstructing the optimal mean and covariance matrix of the state vector without loss.

[0080] The final output is the optimal estimated state vector. The smoothing process filters out high-frequency jitter, providing an absolutely reliable digital foundation for subsequent optimization.

[0081] The system establishes a framework within the digital domain that covers the prediction time domain. (Typically corresponding to several second-level cycles of endocrine cell metabolism) and control time domain A scrolling optimization engine.

[0082] Define the control input vector for the current cycle of the system. .

[0083] The system "pre-simulates" physiological feedback over a future period in a digital simulation space, with the goal of finding a set of control sequences that satisfy the following complex quadratic integral cost function. Reaching the minimum value: ; In this cost function logic: That is, the ideal reference state vector at the point of highest energy co-efficiency determined in step four; : The stable physical device output vector required to maintain the reference state; The system-defined positive semi-definite weight matrix for state errors. The maxima of the diagonal elements in this matrix signify that the system severely penalizes any behavior that deviates from the optimal physiological state. : Positive definite weighting matrix that controls the increment. This term exists to limit drastic changes in the output parameters of the hydrogen-oxygen negative ion device (such as a sudden increase in fan speed or a voltage surge), preventing mechanical and electrical physical shocks to fragile cells; The terminal Lyapunov penalty weight matrix is ​​the core constraint that ensures the global asymptotic stability of the entire NMPC control system at a purely mathematical level.

[0084] The system calls the interior-point algorithm of Sequence Quadratic Programming (SQP) to solve for the solution in real time within each millisecond-level control cycle. Minimum optimal control input The signal is then transmitted to the actuator motor and ionization chamber via a hardware digital-to-analog converter circuit.

[0085] To ensure absolute safety, the system forcibly embeds a boundary penalty formula at the algorithm's underlying level. .

[0086] The system monitors the total predicted concentration of intracellular ions in real time. Once this value exceeds the preset biological tolerance safety threshold... The system immediately triggers the following strongly nonlinear penalty mechanism: ; in This results in a significant penalty for the multiplier. Because the function employs a cubic (or cubic) exponential model, exceeding the limit will cause the cost function to... The explosive growth forces the system to immediately reduce the control duty cycle of the device in terms of algorithmic mathematical structure, triggering hardware-level pulse cutoff and blocking protection.

[0087] After the system has been running for a long period, it is detected that the residual between the state vector and the target state is less than the minimum exit threshold for several consecutive periods. At that time, the system determined that the endocrine cell population had passed the energy depletion period and entered the "stable therapeutic plateau period".

[0088] At this point, the system strictly prohibits directly cutting off the device's power supply to prevent a precipitous rebound of the cell membrane potential (physiological withdrawal effect). Instead, the system executes an adaptive smooth decay command: controlling the input vector... It must strictly follow the exponential decay function Downlink modulation is performed. Among them... The set slow-release decay time constant, The initial timestamp triggered by the exit procedure until the device shuts down smoothly.

[0089] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0090] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely for distinguishing one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0091] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0092] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0093] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for the synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation, characterized in that, include: The complex impedance spectrum of the endocrine target area tissue was obtained and the equivalent cell membrane capacitance was extracted by fitting. The observed voltage signal was subjected to adaptive Wiener filtering to extract the resting potential reference value. The absolute temperature and initial ion concentration were collected simultaneously to construct the environmental background vector matrix. Calculate the initial transmembrane electrochemical potential difference, correct the transmembrane potential equation, and solve for the target potential offset. A nonlinear model of permeability evolution was constructed based on cell therapy intervention markers, and a resonance criterion was established for matching resonances. The initial convection velocity vector and the optimal initial concentration baseline are calculated by using the target potential offset and a nonlinear model of permeability evolution; pulse width modulation control commands are generated based on the resonance criterion. Substitute the predicted ion concentration that penetrates into the cell into the mitochondrial transmembrane proton dynamic potential correction equation, and combine catalytic kinetics to solve the instantaneous adenosine triphosphate synthesis rate. The observation state vector containing the cooperative energy conversion efficiency function is optimally estimated based on the unscented Kalman filter. The optimal estimated state vector is then used for rolling optimization and sent down to the hydrogen-oxygen negative ion device for execution. When the residual meets the exit threshold, an exponentially decaying adaptive smooth exit is performed.

2. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 1, characterized in that, Obtaining the target region complex impedance spectrum to extract the equivalent cell membrane capacitance includes: A broadband swept AC excitation current was applied to the endocrine target area, and the voltage response signal at different frequencies was extracted to calculate the complex impedance spectrum. Based on the relaxation model, the DC equivalent resistance of extracellular fluid and the ultra-high frequency equivalent resistance of fluid penetrating inside and outside the cell are separated. By combining the characteristic relaxation time constant extracted from the fitting with the difference between the DC equivalent resistance and the ultra-high frequency equivalent resistance, the equivalent cell membrane capacitance characterizing the cell's energy storage properties is derived.

3. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 2, characterized in that, The resting potential reference value is extracted through adaptive Wiener filtering, specifically including: The autocorrelation function and cross-correlation function matrix of the observed signal are continuously calculated within the sliding time window; By minimizing the mean square error between the real signal and the filtered output signal, the discrete Wiener-Hough matrix equation is solved in real time to dynamically update the filter coefficients. The low-frequency DC component, which eliminates environmental thermal noise and has a stable baseline, is extracted and used as the resting potential reference value.

4. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 1, characterized in that, The process of calculating the initial transmembrane electrochemical potential difference, correcting the transmembrane potential equation, and solving for the target potential shift is as follows: The system allocates a three-dimensional grid matrix in memory, defining the state parameter in the matrix as the total electrochemical potential difference across the cell membrane. ; The system performs the following discretized thermodynamic energy equation for each virtual grid node: ； in, The ideal gas constant is preset. The absolute temperature of a local tissue; The valence state of the intervening ions involved in the simulation; The Faraday constant is a preset value. and These are the initial estimated values ​​of ion molar concentrations for the interstitial fluid grid on the outer side of the cell membrane and the cytoplasmic grid on the inner side, respectively, in the three-dimensional grid network established by the system. Equivalent to the resting potential reference value ; By using a cyclic calculation equation, the initial potential energy baseline of the current endocrine cell membrane when it is not interfered with by external physical equipment is obtained; The following modified nonlinear equations are executed in parallel: ； in, This is the dynamic equilibrium potential value; The relative permeability static constant weighting coefficients of the natural channels for potassium, sodium, and chloride ions in endocrine cells are pre-set in the system. and A scalar matrix of steady-state transmembrane background concentrations in the microenvironment pre-configured for the database; This is the functional of forced diffusion flux outside the membrane; The membrane forced permeation flux functional is constructed for the system.

5. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 4, characterized in that, A nonlinear model of permeability evolution was constructed based on cell therapy intervention markers, and a resonance criterion for matching resonances was established, specifically including: By introducing nonlinear evolution compensation in the time dimension, a nonlinear model of permeability evolution is calculated: ; in, The basic permeability constant; A continuous timestamp variable; It is the reciprocal of the negative physiological time constant; This represents the limiting saturation value of the permeability increment coefficient. The reciprocal of the positive time constant for channel reconstruction; Continuous computation The function allows the system to obtain a reference control curve that dynamically fluctuates over time in the digital space, ensuring that the parameters of the ion device output can be acquired and matched to the dynamic opening and closing window of the cell membrane. The system extracts the equivalent cell membrane capacitance obtained in step one. And combined with preset film equivalent inductance parameters The theoretical spontaneous oscillation frequency of endocrine cells was calculated using the LC oscillation model. This establishes the pulse frequency to be sent to external devices. Resonance criterion to be satisfied: ； in, The minimum positive real frequency tolerance threshold is forcibly constrained in the system register; the optimal center frequency that allows external hydrogen-oxygen negative ion devices to emit high-voltage square wave pulses is derived by using algebraic transformation. And store it in the buffer sequence queue of control commands to be sent.

6. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 1, characterized in that, The initial convective velocity vector and the optimal initial occurrence concentration baseline are calculated using a nonlinear model of target potential offset and permeability evolution, as follows: To reverse-engineer the required forced wind speed and background ion concentration at the initial nozzle of the generator, a three-dimensional Nernst-Planck spacetime partial differential equation system was built into the calculator: ； in, For a point within a 3D spatial grid At any moment The total diffusion flux vector matrix of a specific anion; For Fick's natural diffusion term; For directional electric field migration term, where This is a digital parameter for ion mobility; For convection transport terms, The core velocity vector; The system discretizes the spatial region from the device nozzle to the endocrine target area into a three-dimensional mesh, and substitutes the following calculation boundary conditions: Starting Dirichlet boundary: at the origin of the generator hardware nozzle coordinates Location, concentration Constrained to the desired generator concentration baseline ; Terminal Neumann boundary: On the virtual uptake surface of targeted endocrine cells, the microscopic normal flux gradient is defined as equal to... The dot product with the local discrete concentration; Iterative calculations yield the initial convective velocity vector that ensures the flux at the end-absorber surface meets the target value. Baseline of optimal initial occurrence concentration .

7. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 6, characterized in that, Based on the resonance criterion, pulse width modulation control commands are generated, specifically as follows: To match the resonant frequency At the same time, without inducing oxidative stress, the system's computing module needs to calculate the precise proportion of high-level time in each pulse cycle, i.e., the dynamic duty cycle. ; The system executes a nonlinear exponential compensation control equation that conforms to the threshold response characteristics of biofilms: ； in, This is the absolute value of the error between the predicted target membrane potential and the filtered actual resting potential within the current system sampling and observation period; This is the resting potential reference constant stored in the system. and These correspond to the minimum effective corona discharge arc ignition duty cycle and the maximum physical safety limit duty cycle to prevent overheating and breakdown of the equipment cavity, respectively. For the adaptive gain-damping hyperparameter of the control system; After multidimensional tensor computation and mapping logic, the system will obtain the control parameter tuple. The data is packaged into a digital communication frame sequence and periodically sent to the underlying microcontroller of the external physical hydrogen-oxygen negative ion device.

8. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 1, characterized in that, The steps for determining the rate of adenosine triphosphate (ATP) synthesis include: The basal transmembrane potential difference and pH difference of the inner mitochondrial membrane are extracted and superimposed with the integral term of the predicted ion concentration entering the cell by the binding energy coupling weighting coefficient to obtain the total proton dynamic potential. By substituting the total proton driving potential as the substrate driving force into the catalytic kinetic model, and limiting the linear increase of the synthesis rate to avoid the risk of oxidative stress when the total proton driving potential approaches the Michaelis constant corresponding to the maximum catalytic rate limit of the cell.

9. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 1, characterized in that, Optimal estimation of the observed state vector containing the cooperative energy conversion efficiency function based on unscented Kalman filtering includes: Multiple sampling points are calculated in a deterministic distribution within the neighborhood of the current state estimate; The sampling points are substituted into the nonlinear mapping equation and weighted summation is performed by combining the covariance matrices of process noise and observation noise. The optimal mean and covariance matrix of the state vector are reconstructed to eliminate the linearization truncation error of the Jacobian matrix of the nonlinear system, and the optimal estimated state vector is output.

10. The method for synergistic application of cell therapy and hydrogen-oxygen negative ions in endocrine system regulation according to claim 9, characterized in that, The optimal estimated state vector is substituted into the cost function of the nonlinear model predictive control for rolling optimization, then sent down to the hydrogen-oxygen negative ion device for execution. When the residual meets the exit threshold, an exponentially decaying adaptive smooth exit is performed, including: Introduce a state error weight matrix and a control increment weight matrix to limit drastic hardware changes into the cost function; When the predicted total ion concentration entering the cell exceeds the biological tolerance safety threshold, a boundary penalty mechanism that grows in a cubic order is triggered to forcibly reduce the control duty cycle. When the residual of the evaluation is less than the exit threshold for several consecutive cycles, the direct power-off command is blocked, and the device output is slowly down-modulated according to the exponential decay function until the device is powered off.

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