A material analysis method for screening a diabetic core flora

Abstract

The application relates to the technical field of material analysis, and discloses a material analysis method for screening a diabetes core bacterial group, which comprises the following steps: depositing a dielectric gradient film with a dielectric relaxation time gradient on the surface of an analysis base to construct a non-equilibrium state analysis surface; placing a complex biological medium sample to be measured on the analysis surface and applying a sweep-frequency alternating current signal; triggering a cooperative polarization response of deep polarons of the analysis base by utilizing the mismatch relationship between the polarization response time constant of the film and the ion migration rate of the sample, and shielding background interference signals; extracting a polarization signal generated by target analyte microparticles according to the change characteristics of the imaginary part of a complex impedance; and calculating a quantitative parameter based on the correlation relationship between a phase shift amount and the complex impedance, so that physical level separation of a target signal and high-conductivity background noise is realized, the determined physical response characteristics are ensured under a low-abundance condition, and the physical state characterization precision of intestinal microecology is improved.

Description

Technical Field

[0001] This invention belongs to the field of materials analysis technology, and in particular relates to a materials analysis method for screening core bacterial communities in diabetes. Background Technology

[0002] Currently, in biological sample analysis, measuring changes in the physical properties of the substrate interface using electrochemical impedance spectroscopy is a routine technique. Existing methods typically involve modifying a sensitive membrane layer on the surface of a homogeneous electrode to capture the interfacial impedance shift caused by the specific binding of the target analyte to the sensitive membrane layer. For the analytical environment of intestinal core flora extracts, the sample exhibits high intrinsic conductivity and contains sodium salts and various organic acid components with concentrations ranging from 100 to 150 mM. This strong electrolyte environment generates a double-layer charge shield with high polarization intensity at the analytical substrate interface. The current fluctuations generated by the random thermal motion of background ions overwhelm the weak polarization signal caused by the binding of the target analyte to the analytical substrate with a non-equilibrium analytical surface.

[0003] Industry experts have adopted strategies such as increasing the excitation voltage amplitude or extending the signal sampling period to attempt to extract impedance characteristics. However, increasing the excitation voltage induces the electrolysis of water molecules and introduces nonlinear noise, while extending the sampling period leads to the accumulation of nonspecific polarization charges at the interface. This reduces the resolution and effective detection limit of the analytical method for extracting weak signals of the target analyte. Furthermore, due to the charge fluctuations in the background environment, the physical properties of homogeneous materials in existing technologies exhibit linear distribution characteristics, making it impossible to achieve selective responses to specific biophysical characteristics under strong polarization backgrounds. For example, Chinese invention patent application publication number CN113413148A... A signal processing method and device for improving the performance of impedance biosensors are proposed. The method utilizes machine learning algorithms such as principal component analysis and support vector machine to extract feature points from the real part, imaginary part, amplitude, and phase of impedance in a multi-dimensional mode for classification. The back-end algorithm compensation technology is based on the underlying logic of non-ideal operating conditions such as linear measurement mode in electrical equilibrium and intestinal extracts. The background ion fast polarization response and the target signal are deeply overlapped in the frequency domain, making it impossible to decouple the signal from the noise at the physical interface layer. The feature extraction relying on software algorithms is prone to capturing physical artifacts caused by background fluctuations, resulting in reference drift and false positives in the quantization results in complex matrices.

[0004] Therefore, how to utilize the non-equilibrium polarization distribution mechanism of the substrate material to extract the specific dielectric relaxation characteristics of the target bacterial community under strong electrolyte interference environment has become the technical problem to be solved by this invention. Summary of the Invention

[0005] This invention provides a material analysis method for screening core gut microbiota in diabetic patients, comprising the following steps:

[0006] Step S1: Deposit a dielectric gradient thin film on the surface of the analysis substrate. By adjusting the evolution curve of sputtering power over time, construct a polarization response interval with a gradient continuous distribution of polarization response time constant from 500 μs at the surface to 10 μs at the bottom layer inside the dielectric gradient thin film. This constructs an overall time window covering the polarization response interval to form a non-equilibrium analysis surface with dielectric relaxation time gradient.

[0007] Step S2: Place the complex biological medium sample containing the core bacterial extract of diabetes on the non-equilibrium analytical surface and apply a swept AC signal. Adjust the polarization frequency window of the dielectric gradient film so that the polarization frequency window overlaps with the dielectric loss peak of the target analyte particles. Utilize the mismatch between the polarization response time constant and the migration rate of ions in the complex biological medium sample to trigger the cooperative polarization response of deep polarons in the analytical substrate, so as to shield the background interference signal generated by ions.

[0008] Step S3: Under the cooperative polarization response environment, the imaginary part change characteristics of the complex impedance are extracted synchronously by the measurement channel and the reference channel, and the polarization response value of the reference channel is used to offset the background conductivity fluctuation of the complex biological medium sample to be tested, so as to extract the polarization signal generated by the combination of the target analyte particles and the non-equilibrium analytical surface.

[0009] Step S4: Input the polarization signal into the identification model of the physical fingerprint of the target analyte particles, and calculate the quantitative parameters characterizing the physical response of the target analyte particles based on the multidimensional parameter correlation between phase offset and complex impedance.

[0010] Preferably, in step S1, when depositing the dielectric gradient film, the non-uniform deposition rate of high-energy particles on the surface of the analytical substrate is controlled, so that the dielectric gradient film generates an electric potential energy step perpendicular to the direction of the analytical substrate, so as to guide the charge to the binding site of the target analyte particles at the microscale; wherein, the polarization response time constant decreases non-linearly from the surface layer to the bottom layer of the dielectric gradient film, and the polarization response time constant of the surface layer is limited to 50 times the polarization response time constant of the bottom layer.

[0011] Preferably, when a swept-frequency AC signal is applied in step S2, the local electric field distortion generated by the dielectric elliptic thin film is used to enhance the double-layer polarization effect at the interface between the target analyte particles and the non-equilibrium analytical surface, and the change in phase angle within a specific frequency window is monitored to identify the microscopic evolution of the interface electrolyte capacitance properties.

[0012] Preferably, the specific frequency window is set according to the polarization relaxation time of a specific membrane protein in the target analyte particle, and the target analyte particle is identified by filtering out the physical artifacts caused by the adsorption of non-specific proteins in the complex biological media sample to be tested.

[0013] Preferably, when extracting the imaginary part change characteristics of complex impedance in step S3, the high dielectric component of the bottom layer of the dielectric constant film and the low dielectric component of the surface layer are used to construct signal amplification logic so that the polarization signal intensity is not less than 3 times the intrinsic electromagnetic shielding noise intensity of the complex biological medium sample under test.

[0014] Preferably, in step S4, when calculating the quantization parameters characterizing the physical response features of the target analyte particles, a reference phase reference is introduced, the polarization state of the target analyte particles is determined based on the phase offset, and the initial quantization value determined by the complex impedance is corrected using a preset nonlinear compensation factor to obtain the quantization parameters, so as to compensate for the reference drift caused by the fluctuation of salt concentration on the surface of the analysis substrate.

[0015] Preferably, the calculation of quantization parameters follows this logic: Where P is the quantization parameter, and ΔZ″ is the difference in the imaginary part of the complex impedance of the measurement channel relative to the reference channel. Δθ is the real part of the complex impedance of the reference channel, α is the phase offset, and β is the preset sensitivity adjustment coefficient and phase correction factor, respectively.

[0016] Preferably, the substrate is monitored in real time using complex impedance spectroscopy. By adjusting the excitation voltage amplitude of the swept frequency AC signal, the electrolytic reaction of the complex biological medium sample under test is suppressed. The upper limit of the excitation voltage amplitude is set to 800mV.

[0017] Preferably, step S1 further includes: performing surface functionalization treatment on the analytical substrate before depositing the dielectric gradient film, and using a silane coupling agent to construct a molecular-level hydrophobic barrier on the non-equilibrium analytical surface to inhibit the penetration of non-target ions into the interior of the dielectric gradient film.

[0018] Preferably, the material analysis method for screening the core microbiota of diabetes is used to characterize the physical properties of the complex biological media samples to be tested, and the calculated quantitative parameters are used as technical indicators to characterize the evolution of the physical state of the gut microbiota.

[0019] Compared with existing technologies, the material analysis method for screening core gut microbiota in diabetes of the present invention has the following advantages:

[0020] 1. In the screening of core microbial communities in diabetes, a frequency-domain physical gating mechanism for the target analyte is established by constructing a non-equilibrium analytical surface with a dielectric relaxation time gradient on the surface of the analytical substrate. Utilizing the overall time window of the polarization response time constant continuously distributed from 500 μs at the surface to 10 μs at the bottom within the dielectric gradient film, it is matched with the characteristic relaxation time of the target microbial cell membrane. When the target analyte comes into contact with the analytical substrate with the non-equilibrium analytical surface, a synergistic coupling response between the polarons on the surface of the dielectric gradient film and the transmembrane potential of the microbial community is triggered. Since the polarization rate of the abundant salt ions in the sample background is on the picosecond scale, its response characteristics are essentially decoupled from the polarization window of the dielectric gradient film on a physical scale, causing the background ions to only produce a linear reference drift. This mechanism achieves physical-level separation of the target signal from the environmental background noise at the material property level, freeing the analytical process from the spatial shielding limitation of weak electrical characteristics by high conductivity media, and ensuring that highly deterministic physical response characteristics can still be obtained under low abundance sample conditions.

[0021] 2. This invention combines the local electric field distortion generated at the capture site by the dielectric gradient thin film with differential signal processing logic. This combined mechanism constructs a self-compensating analysis system with native anti-interference capability. The analysis substrate forms a potential energy ladder perpendicular to the substrate direction through non-uniform deposition of a high-dielectric component at the bottom layer and a low-dielectric component at the surface layer. This guides the charge flow to the target binding site for directional accumulation at the microscale. Combined with the synchronous analysis of the measurement channel and the reference channel under a swept-frequency AC signal, the imaginary part variation characteristics of the complex impedance are extracted in real time. The polarization response value of the reference channel is used to offset the fluctuation of the sample background conductivity. This combined effect of the local enhancement effect caused by the material physical gradient and the differential compensation logic significantly improves the adaptability of the method to salt concentration fluctuations. Without the need for additional environmental compensation sensors, it ensures the logical consistency of the analysis results under complex acidity and alkalinity and high-salt backgrounds. Attached Figure Description

[0022] Figure 1 This is a flowchart of a material analysis method for screening core gut microbiota in diabetes according to the present invention;

[0023] Figure 2 This is a logic diagram for calculating the multidimensional quantization parameters of the target particle polarization characteristics in this invention. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0025] In the description of this specification, references to the terms "an embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0026] A material analysis method for screening core gut microbiota in diabetic patients includes the following steps:

[0027] Step S1: Deposit a dielectric gradient thin film on the surface of the analysis substrate. By adjusting the evolution curve of sputtering power over time, construct a polarization response interval with a gradient continuous distribution of polarization response time constant from 500 μs at the surface to 10 μs at the bottom layer inside the dielectric gradient thin film. This constructs an overall time window covering the polarization response interval to form a non-equilibrium analysis surface with dielectric relaxation time gradient.

[0028] Step S2: Place the complex biological medium sample containing the core bacterial extract of diabetes on the non-equilibrium analytical surface and apply a swept AC signal. Adjust the polarization frequency window of the dielectric gradient film so that the polarization frequency window overlaps with the dielectric loss peak of the target analyte particles. Utilize the mismatch between the polarization response time constant and the migration rate of ions in the complex biological medium sample to trigger the cooperative polarization response of deep polarons in the analytical substrate, so as to shield the background interference signal generated by ions.

[0029] Step S3: Under the cooperative polarization response environment, the imaginary part change characteristics of the complex impedance are extracted synchronously by the measurement channel and the reference channel, and the polarization response value of the reference channel is used to offset the background conductivity fluctuation of the complex biological medium sample to be tested, so as to extract the polarization signal generated by the combination of the target analyte particles and the non-equilibrium analytical surface.

[0030] Step S4: Input the polarization signal into the identification model of the physical fingerprint of the target analyte particles, and calculate the quantitative parameters characterizing the physical response of the target analyte particles based on the multidimensional parameter correlation between phase offset and complex impedance.

[0031] Preferably, in step S1, when depositing the dielectric gradient film, the non-uniform deposition rate of high-energy particles on the surface of the analytical substrate is controlled, so that the dielectric gradient film generates an electric potential energy step perpendicular to the direction of the analytical substrate, so as to guide the charge to the binding site of the target analyte particles at the microscale; wherein, the polarization response time constant decreases non-linearly from the surface layer to the bottom layer of the dielectric gradient film, and the polarization response time constant of the surface layer is limited to 50 times the polarization response time constant of the bottom layer.

[0032] Preferably, when a swept-frequency AC signal is applied in step S2, the local electric field distortion generated by the dielectric elliptic thin film is used to enhance the double-layer polarization effect at the interface between the target analyte particles and the non-equilibrium analytical surface, and the change in phase angle within a specific frequency window is monitored to identify the microscopic evolution of the interface electrolyte capacitance properties.

[0033] Preferably, the specific frequency window is set according to the polarization relaxation time of a specific membrane protein in the target analyte particle, and the target analyte particle is identified by filtering out the physical artifacts caused by the adsorption of non-specific proteins in the complex biological media sample to be tested.

[0034] Preferably, when extracting the imaginary part change characteristics of complex impedance in step S3, the high dielectric component of the bottom layer of the dielectric constant film and the low dielectric component of the surface layer are used to construct signal amplification logic so that the polarization signal intensity is not less than 3 times the intrinsic electromagnetic shielding noise intensity of the complex biological medium sample under test.

[0035] Preferably, in step S4, when calculating the quantization parameters characterizing the physical response features of the target analyte particles, a reference phase reference is introduced, the polarization state of the target analyte particles is determined based on the phase offset, and the initial quantization value determined by the complex impedance is corrected using a preset nonlinear compensation factor to obtain the quantization parameters, so as to compensate for the reference drift caused by the fluctuation of salt concentration on the surface of the analysis substrate.

[0036] Preferably, the calculation of quantization parameters follows this logic: Where P is the quantization parameter, and ΔZ″ is the difference in the imaginary part of the complex impedance between the measurement channel and the reference channel. Δθ is the real part of the complex impedance of the reference channel, α is the phase offset, and β is the preset sensitivity adjustment coefficient and phase correction factor, respectively.

[0037] Preferably, the substrate is monitored in real time using complex impedance spectroscopy. By adjusting the excitation voltage amplitude of the swept frequency AC signal, the electrolytic reaction of the complex biological medium sample under test is suppressed. The upper limit of the excitation voltage amplitude is set to 800mV.

[0038] Preferably, step S1 further includes: performing surface functionalization treatment on the analytical substrate before depositing the dielectric gradient film, and using a silane coupling agent to construct a molecular-level hydrophobic barrier on the non-equilibrium analytical surface to inhibit the penetration of non-target ions into the interior of the dielectric gradient film.

[0039] Preferably, the material analysis method for screening the core microbiota of diabetes is used to characterize the physical properties of the complex biological media samples to be tested, and the calculated quantitative parameters are used as technical indicators to characterize the evolution of the physical state of the gut microbiota.

[0040] Example 1: Current in vitro electrochemical screening of core diabetic microbiota clinical samples involves processing intestinal extract samples with extremely high intrinsic conductivity and fluctuating background ion concentrations. This strong electrolyte environment generates a double-layer charge shield at the analytical substrate interface, causing the polarization signal induced by the binding of target analyte particles to the analytical substrate to be overlaid by the current fluctuations generated by the random thermal motion of background ions. This paper provides a materials analysis method for screening core diabetic microbiota in complex biological media analysis scenarios. Traditional methods increase the AC excitation voltage amplitude or extend the signal sampling period to induce nonlinear electrolytic noise in water molecules. To address the accumulation of non-specific polarization charges at the interface, this analytical method deposits a dielectric gradient thin film on the substrate surface. By adjusting the evolution curve of sputtering power over time, a continuous time window is constructed within the dielectric gradient thin film, with the polarization response time constant continuously distributed from 500 μs at the surface to 10 μs at the bottom. This forms a non-equilibrium analytical surface with a dielectric relaxation time gradient. The complex biological medium sample to be tested is placed on the non-equilibrium analytical surface, and a swept AC signal is applied. The polarization frequency window of the dielectric gradient thin film is adjusted so that it overlaps with the dielectric loss peak of the target analyte particles.

[0041] The polarization rate of salt ions in the complex biological medium sample is on the picosecond scale. Utilizing the mismatch between the polarization response time constant and the migration rate of ions in the complex biological medium sample, when the target analyte particles come into contact with the analytical substrate with a non-equilibrium analytical surface, a cooperative polarization response of deep polarons in the analytical substrate is triggered. The high-frequency fluctuations of background ions cannot couple with the microsecond-level thin-film polarization, only producing a linear reference drift, thus shielding the background interference signal generated by ions. Under the cooperative polarization response environment, the imaginary part change characteristics of the complex impedance are extracted synchronously using the measurement channel and the reference channel, and the polarization response value of the reference channel is used to offset the background conductivity fluctuations of the complex biological medium sample, extracting the polarization signal generated by the combination of the target analyte particles and the non-equilibrium analytical surface.

[0042] The polarization signal is input into the identification model of the physical fingerprint of the target analyte particles. Based on the multidimensional parameter correlation between phase shift and complex impedance, the quantization parameters characterizing the physical response of the target analyte particles are calculated. The specific quantization parameters follow the formula. The calculation is performed, where P is the quantization parameter and ΔZ″ is the difference in the imaginary part of the complex impedance between the measurement channel and the reference channel. The real part of the complex impedance of the reference channel is denoted as Δθ, the phase offset is α, and β are the preset sensitivity adjustment coefficient and phase correction factor, respectively. The analysis method uses the mismatch between the polarization response time constant and the ion migration rate to extract the polarization signal. The imaginary part of the complex impedance is extracted in the complex biological medium sample environment where the salt concentration fluctuates up to 50 mM. The output quantization parameters have a linear mapping relationship with the abundance of the target analyte particles. The output quantization parameters serve as technical indicators to characterize the evolution of the physical state of the intestinal microecology.

[0043] Example 2: Current intestinal biological media samples contain inorganic salt ions and electroactive metabolites with fluctuating concentrations. Their intrinsic conductivity fluctuates in both time and space. The testing process uses an impedance analyzer with 0.01° phase resolution and a 1MHz sampling rate as the basic data acquisition hardware. A frequency range for the swept AC signal is set. This parameter balances the characteristic dispersive frequency band of the target analyte particles with the relaxation frequency limit of the background ions. When the concentration disturbance of the electrolyte background ions causes the low-frequency region double-layer capacitance to dominate the interfacial impedance, the method of this invention sets the lower limit frequency of the excitation signal to 10kHz to avoid electrode polarization saturation and limits its upper limit frequency to 10MHz to cover the color of the target cell membrane. In a dispersed region, an AC excitation signal source was constructed, and three types of analytical substrates with different physical configurations were constructed. The first group was set as the sample group of the present invention, which was a thin film with a continuous distribution of polarization response time constant from 500 μs on the surface to 10 μs on the bottom layer. The second group was set as the control sample group with a thin film with a uniform polarization response time constant. The third group was set as the control group with an out-of-range distribution of polarization response time constant from 100 μs on the surface to 10 μs on the bottom layer. The present invention injected clinical intestinal extract samples containing target analyte particles with preset abundance into each of the prepared analytical substrates, and superimposed Gaussian white noise with a signal-to-noise ratio of 20 dB and power frequency interference harmonics with a frequency of 50 Hz onto the AC excitation signal source to reproduce the electromagnetic interference environment of industrial and clinical testing.

[0044] During the frequency sweep test, the imaginary part of the original complex impedance output of the comparison sample group oscillated. Its interface polarization capacitance was affected by the random thermal motion of environmental ions, generating a fluctuating noise floor of 45Ω. The weak polarization characteristics induced by the target analyte particles could not be identified in this background noise. Under the same operating conditions, the sample group of this invention used the mismatch mechanism between the dielectric constant thin film polarization response time constant and the ion migration rate to shield the background fluctuations. The picosecond-level high-frequency response of the background ions did not coordinate with the microsecond-level polarization of the thin film. The baseline noise floor extracted by the method of this invention was suppressed to 2.1Ω. When the target analyte particles combined to induce the reconstruction of the interface double layer, this method recorded intermediate state data. The difference ΔZ″ of the imaginary part of the complex impedance of the measurement channel relative to the reference channel was 15.6Ω, and the phase offset Δθ was extracted as 1.25°. This method is based on the formula The output quantization parameter P is 0.85, and this output value maps to the preset target particle abundance.

[0045] For the out-of-range control group, the test data exhibited a nonlinear response because the ratio of the time constant between the surface and the bottom layer decreased from 50 times to 10 times. Its phase offset dropped to around 0.15° and showed random jump characteristics, failing to establish a relaxation time mismatch barrier, which caused the judgment parameters output by this method to deviate. Concentration gradient tests showed that when the background salt ion concentration increased and exceeded a certain threshold, the signal-to-noise ratio growth rate of the quantitative parameters of the sample group of this invention showed a gentle saturation inflection point, proving that the time constant distribution gradient from 500 μs on the surface to 10 μs on the bottom layer can balance the interface signal amplification and charge shielding capacity. Multi-dimensional comparative data and nonlinear evolution trends showed that the dielectric relaxation time gradient configuration cut off the coupling path between the thermal motion of background ions and the interface polarization measurement, transforming the signal extraction under high salt background into a frequency domain feature filtering process. The quantitative parameters output by the method of this invention under strong electrolyte and electromagnetic disturbance environments are reproducible.

[0046] Example 3: In the engineering environment for characterizing the physical state of the intestinal microecology, when preparing a non-equilibrium analytical surface with a specified polarization response time constant gradient, a technical challenge arises in controlling the deposition rate of high-energy particles. The method of this invention uses barium strontium titanate as the sputtering target. A thin film is deposited in a magnetron sputtering device with a chamber background vacuum of 0.0005 Pa and a working pressure maintained at 1.0 Pa. The control module adjusts the sputtering power of the RF power supply according to a nonlinear decay function, so that the sputtering power continuously increases from 200 W within a 60-minute deposition cycle. The power is reduced to 50W, and the power decay is controlled to increase the size of barium strontium titanate grains deposited on the substrate surface from the bottom layer to the surface layer, generating a dielectric physical structure with a nonlinear gradient in internal grain boundary density. This physical structure determines the relaxation time distribution of internal polarons, and outputs a polarization response time constant window that is continuously distributed from 500μs at the surface layer to 10μs at the bottom layer. In step S1, the dielectric gradient thin film deposition process is implemented by adjusting the output power W of the RF magnetron sputtering power supply. During a continuous deposition cycle of 60 minutes, the output power W is controlled to increase from the initial power. according to The linearly decreasing function decreases to the termination power, and the initial power... The power was set to 200W, the termination power was set to 50W, k was the attenuation coefficient, and t was the deposition time. As the output power W decreased continuously, the size of the barium strontium titanate grains deposited on the surface of the analysis substrate gradually evolved from an average of 20nm in the bottom layer to an average of 85nm in the surface layer. This formed a gradient distribution structure in which the grain boundary density increased with the depth of the film, resulting in a non-equilibrium analysis surface with a polarization response time constant that was continuously distributed from 500μs in the surface layer to 10μs in the bottom layer.

[0047] Before deployment, a standardized offline calibration procedure is initiated. A microfluidic pump sequentially injects standard bacterial suspensions with target particle abundances of 1000 CFU / mL, 100000 CFU / mL, and 10000000 CFU / mL into a test channel equipped with a non-equilibrium analytical surface. After applying a swept-frequency AC signal from a lower limit frequency of 10 kHz to an upper limit frequency of 10 MHz, the impedance analyzer simultaneously records the set of imaginary part differences in the complex impedance of the measurement channel relative to the reference channel and the set of real part values ​​of the complex impedance of the reference channel at each abundance node. And the set of phase offsets; the processor extracts steady-state measurement data of each abundance node at the characteristic frequency of the dielectric loss peak, constructs an overdetermined system of equations with the preset abundance value as the dependent variable and the normalized impedance offset and phase offset as independent variables, solves the overdetermined system of equations by the least squares method and extracts the coefficient solution with the minimum sum of squared residuals, outputs the sensitivity adjustment coefficient α with a value of 2.35 and the phase correction factor with a value of 0.12, and directly writes the coefficients into the identification model of the physical fingerprint of the target analyte particles, eliminating undefined variables in the multidimensional parameter correlation relationship, according to the formula The calculated quantization parameter P is reproducible in engineering. The sensitivity adjustment coefficient and phase correction factor involved in the calculation of quantization parameter P are determined as follows: The target analyte particle concentrations are pre-configured as follows... CFU / mL CFU / mL and For a standard suspension at CFU / mL, the imaginary part difference ΔZ″ of the complex impedance relative to the reference channel and the real part of the complex impedance of the reference channel were recorded at each concentration node under the same testing environment. With the phase offset Δθ as the target variable and the known concentration value as the objective variable, the least squares method is used to perform regression calculation on the aforementioned measurement data to solve for the coefficient value when the sum of squared residuals reaches the minimum value. The obtained regression coefficients are then confirmed as the sensitivity adjustment coefficient and the phase correction factor to eliminate the quantization benchmark deviation caused by differences in sensor batches.

[0048] Example 4: In the engineering environment for characterizing the physical state of the intestinal microecology, when this method faces the objective condition that the intrinsic conductivity baseline of different batches of clinical extracts exhibits physical drift, the testing process involves connecting a non-equilibrium analytical surface with a medium-elasticity film to an impedance analyzer and initiating a field pre-calibration procedure. A matrix buffer without target analyte particles is injected into the test channel using a microfluidic pump. The impedance analyzer applies a swept-frequency AC signal in a logarithmically spaced step manner within the frequency range of 10 kHz to 10 MHz. The measurement channel and reference channel synchronously and continuously acquire the background complex impedance spectrum of the matrix buffer. The processor extracts the real part of the complex impedance of the reference channel from the background complex impedance spectrum. Based on the extracted values ​​and the corresponding imaginary reference values, a baseline impedance data matrix characterizing the ion distribution characteristics of the current batch of biological media is constructed.

[0049] This method uses a constructed baseline impedance data matrix to filter the linear drift component in the input signal. A microfluidic pump injects a suspension containing standard electroactive microparticles into the test channel. The processor tracks the derivative sequence of the imaginary part difference ΔZ″ of the complex impedance in the measurement channel as a function of frequency, locates the peak frequency corresponding to the zero-crossing point of the positive and negative flip of the derivative sequence, sets this peak frequency as the center frequency of the polarization frequency window, and delineates the absolute physical boundary using the frequency coordinates corresponding to the point where the power attenuation is half at this center frequency. In step S2, the specific frequency window is set based on the characteristic response peak of the target analyte microparticle in the imaginary part of the complex impedance spectrum. Within a frequency sweep range of 10 kHz to 10 MHz, the evolution trend of the imaginary part difference ΔZ″ of the complex impedance as a function of frequency is monitored in real time, and the frequency corresponding to the peak value of ΔZ″ is located. Set the center frequency of the polarization frequency window to The frequency is extended to both sides from this center, and the frequency coordinate corresponding to the point where ΔZ″ drops to half of the peak value is selected as the physical boundary of a specific frequency window. By limiting the frequency window, the cooperative polarization response of the dielectric gradient film is concentrated in the transmembrane potential relaxation frequency band of the target bacterial community. At the physical level, the reference drift interference caused by background salt ions with response time on the picosecond scale is shielded. The control module writes the parameters of this absolute physical boundary into the AC excitation signal source. The control panel of this invention outputs the test environment initialization command and adjusts the AC excitation signal source so that the polarization frequency window of the dielectric gradient film overlaps with the dielectric loss peak of the target analyte particles.

[0050] Example 5: Under the long-term characterization of the physical state of the intestinal microecology, the polarization characteristics of the dielectric constant film are limited by the physical decay of the polarization characteristics with the increase of the number of uses. The test process adopts an adaptive reconstruction procedure with an internally loaded polarization frequency window. The method of the present invention maintains a working pressure of 1.0 Pa in the test channel and injects a reference verification solution containing standard electroactive microparticles. The impedance analyzer applies a swept frequency AC signal of 10 kHz to 10 MHz to the analysis substrate. The processor periodically extracts the peak value of the difference between the imaginary part of the complex impedance of the measurement channel and the reference channel, ΔZ″, and sets it as a quantitative monitoring index of the physical state of the film.

[0051] The processor compares the peak value of the extracted complex impedance imaginary part difference ΔZ″ with the pre-stored initial calibration value. After determining that the peak value is below 85% of the initial calibration value for three consecutive sampling periods, a reconstruction command is generated. The control module receives this reconstruction command and adjusts the upper limit frequency of the AC excitation signal source. Based on the linear compensation relationship that a 5% decrease in the peak impedance difference corresponds to a 2% increase in the upper limit frequency, the upper limit frequency of the sweep frequency range is widened from 10MHz to 10.5MHz. The widened polarization frequency window re-covers the dielectric loss peak of the target analyte particles that has shifted to higher frequencies due to thin film attenuation. In this compensated state, the method of this invention extracts the phase shift Δθ, combined with the real part of the complex impedance of the reference channel. And specific sensitivity adjustment coefficients α and phase correction factors β, according to the formula The quantization parameter P is obtained through calculation, and the consistency of the calculation benchmark of this method is maintained under boundary conditions where material properties deviate.

[0052] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A material analysis method for screening core gut microbiota in diabetic patients, characterized in that, Includes the following steps: Step S1: Deposit a dielectric gradient thin film on the surface of the analysis substrate. By adjusting the evolution curve of sputtering power over time, construct a polarization response interval with a gradient continuous distribution of polarization response time constant from 500 μs at the surface to 10 μs at the bottom layer inside the dielectric gradient thin film. This constructs an overall time window covering the polarization response interval to form a non-equilibrium analysis surface with dielectric relaxation time gradient. Step S2: Place the complex biological medium sample containing the core bacterial extract of diabetes on the non-equilibrium analytical surface and apply a swept AC signal. Adjust the polarization frequency window of the dielectric gradient film so that the polarization frequency window overlaps with the dielectric loss peak of the target analyte particles. Utilize the mismatch between the polarization response time constant and the migration rate of ions in the complex biological medium sample to trigger the cooperative polarization response of deep polarons in the analytical substrate, so as to shield the background interference signal generated by ions. Step S3: Under the cooperative polarization response environment, the imaginary part change characteristics of the complex impedance are extracted synchronously by the measurement channel and the reference channel, and the polarization response value of the reference channel is used to offset the background conductivity fluctuation of the complex biological medium sample to be tested, so as to extract the polarization signal generated by the combination of the target analyte particles and the non-equilibrium analytical surface. Step S4: Input the polarization signal into the identification model of the physical fingerprint of the target analyte particles, and calculate the quantitative parameters characterizing the physical response of the target analyte particles based on the multidimensional parameter correlation between phase offset and complex impedance.

2. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, In step S1, during the deposition of the dielectric gradient thin film, the non-uniform deposition rate of high-energy particles on the surface of the analytical substrate is controlled to generate an electric potential energy step perpendicular to the direction of the analytical substrate in the dielectric gradient thin film, so as to guide the charge to the binding site of the target analyte particles at the microscale. The polarization response time constant is distributed non-linearly from the surface layer to the bottom layer of the dielectric gradient thin film, and the polarization response time constant of the surface layer is limited to 50 times that of the bottom layer.

3. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, In step S2, when a swept-frequency AC signal is applied, the local electric field distortion generated by the dielectric gradation thin film is used to enhance the double-layer polarization effect at the interface between the target analyte particles and the non-equilibrium analytical surface, and the change in phase angle within a specific frequency window is monitored to identify the microscopic evolution of the interface electrolyte capacitance properties.

4. The material analysis method for screening core gut microbiota in diabetes according to claim 3, characterized in that, The specific frequency window is set according to the polarization relaxation time of specific membrane proteins in the target analyte particles. By filtering out physical artifacts caused by non-specific protein adsorption in the complex biological media sample to be tested, the target analyte particles can be identified.

5. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, When extracting the imaginary part change characteristics of complex impedance in step S3, the high dielectric component of the bottom layer of the dielectric constant film and the low dielectric component of the surface layer are used to construct the signal amplification logic so that the polarization signal intensity is not less than 3 times the intrinsic electromagnetic shielding noise intensity of the complex biological medium sample under test.

6. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, In step S4, when calculating the quantization parameters characterizing the physical response of the target analyte particles, a reference phase reference is introduced. The polarization state of the target analyte particles is determined based on the phase offset. The initial quantization value determined by the complex impedance is corrected using a preset nonlinear compensation factor to obtain the quantization parameters, thereby compensating for the reference drift caused by the fluctuation of salt concentration on the surface of the analysis substrate.

7. The material analysis method for screening core gut microbiota in diabetes according to claim 6, characterized in that, The calculation of quantization parameters follows this logic: Where P is the quantization parameter, and ΔZ″ is the difference in the imaginary part of the complex impedance between the measurement channel and the reference channel. Δθ is the real part of the complex impedance of the reference channel, α is the phase offset, and β is the preset sensitivity adjustment coefficient and phase correction factor, respectively.

8. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, The substrate was analyzed using complex impedance spectroscopy for real-time monitoring. By adjusting the excitation voltage amplitude of the swept frequency AC signal, the electrolytic reaction of the complex biological medium sample under test was suppressed. The upper limit of the excitation voltage amplitude was set to 800mV.

9. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, Step S1 further includes: performing surface functionalization treatment on the analytical substrate before depositing the dielectric elliptic membrane; and constructing a molecular-level hydrophobic barrier on the non-equilibrium analytical surface using a silane coupling agent to inhibit the penetration of non-target ions into the interior of the dielectric elliptic membrane.

10. The material analysis method for screening core gut microbiota in diabetes according to claim 1, characterized in that, The material analysis method for screening the core microbiota of diabetes is used to characterize the physical properties of complex biological media samples to be tested, and the calculated quantitative parameters serve as technical indicators to characterize the evolution of the physical state of the gut microbiota.

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