Multi-mode nerve disease diagnosis chip and method based on space-time controllable immune response

Abstract

The invention discloses a multi-mode nerve disease diagnosis chip based on space-time controllable immune response, and relates to the technical field of in vitro diagnos.The chip comprises a light-operated antibody switch module, a three-dimensional fluorescent probe, a multi-omics detection channel and an intelligent temperature control system.The chip can synchronously detect GFAP, NfL, p-tau217, miR-132, miR-124 and metabolic markers; the affinity regulation range of the light-operated antibody switch module is larger than or equal to 100 times, and the signal enhancement factor of the three-dimensional fluorescent probe is larger than or equal to 20 times. The chip system is scientific and reasonable in structure and safe and convenient to use, combines a plurality of innovative technologies, brings a remarkable clinical application effect, not only improves the detection efficiency, but also reduces the detection cost. The precise control of immunoreaction, signal enhancement and marker separation process is also ensured, and the standardization and consistency of diagnosis are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of in vitro diagnostic technology, specifically to a multimodal neurological disease diagnostic chip and method based on spatiotemporally controllable immune responses. Background Technology

[0002] While existing immunoassay technologies are widely used in clinical diagnosis, they still have some significant limitations that restrict their application in more efficient and accurate detection. For example, the traditional enzyme-linked immunosorbent assay (ELISA) technology suffers from insufficient sensitivity, with a detection limit typically of 50 pg / mL, which cannot meet the demand for high-sensitivity detection of low-concentration biomarkers. In addition, the ELISA testing process is lengthy, usually requiring more than 4 hours, making it difficult to meet the clinical needs for rapid diagnosis. Furthermore, the antibodies have poor specificity and a high cross-reactivity rate (over 8%), which further affects the accuracy and reliability of the test results. Therefore, existing technologies have significant shortcomings in terms of sensitivity, speed, and specificity. Furthermore, existing multi-indicator detection technologies often rely on complex and expensive equipment, such as electrochemiluminescence analyzers. These devices are not only costly, with each test typically costing around 200 yuan, but also complex to operate, making it difficult to meet the immediate and convenient needs of point-of-care testing. With the continuous advancement of medical diagnostic technology, there is an urgent need to develop a new diagnostic platform that combines the advantages of high sensitivity, low cost, and rapid detection, while also exhibiting good antibody specificity. In addition, current technologies have not yet achieved dynamic control of the detection process and fusion analysis of multi-omics data, lacking the ability to comprehensively analyze complex biological information. Therefore, there is an urgent need to develop a more advanced multimodal diagnostic platform that can achieve more accurate and efficient detection to better serve clinical needs. Summary of the Invention

[0003] This invention provides a multimodal neurological disease diagnostic chip and method based on spatiotemporally controllable immune response, which can effectively solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response, the chip comprising a light-controlled antibody switch module, a three-dimensional fluorescent probe, a multi-omics detection channel, and an intelligent temperature control system; The chip can simultaneously detect GFAP, NfL, p-tau217, miR-132, miR-124, and metabolic markers.

[0005] According to the above technical solution, the affinity modulation range of the photocontrolled antibody switch module is greater than or equal to 100 times, and the signal enhancement factor of the three-dimensional fluorescent probe is greater than or equal to 20 times. The chip also includes a microfluidic chip integrated pneumatic valve control system, which can realize fully automated processing of 10μL of plasma.

[0006] According to the above technical solution, the detection area includes three protein detection lines (T1-T3), two nucleic acid detection lines (T4-T5), and a metabolite sensor to supplement it, so as to realize the detection of biomarkers related to neurological diseases; The surface of the chip is covered with a nitrocellulose film and gold nanoparticles are coated by a vapor deposition process. The size and distribution uniformity of the gold nanoparticles are optimized to maximize the SPR effect and improve the stability and sensitivity of the fluorescence signal. SPR enhances fluorescence signal by 18.5 times.

[0007] According to the above technical solution, the density and distribution of gold nanoparticles deposited on the surface of the nitrocellulose membrane can be adjusted according to different detection requirements.

[0008] According to the above technical solution, the intelligent temperature control system monitors the internal temperature changes of the chip in real time through a built-in temperature sensor and automatically adjusts the temperature according to the needs of the immune response. The temperature control system uses intelligent algorithms to precisely regulate the temperature at different detection stages, ensuring that the immune response takes place within the optimal temperature range, thereby improving detection sensitivity and accuracy. By working in conjunction with other modules on the chip, the intelligent temperature control system can automatically start or stop the heating function according to actual needs, achieving energy saving and efficient control.

[0009] According to the above technical solution, the intelligent temperature control system further includes a heating unit, a cooling unit, and a temperature feedback adjustment unit, which can intelligently adjust the heating and cooling mechanisms according to the temperature control requirements of each detection module in the chip. The heating unit uses high-efficiency thermoelectric materials, which can provide a uniform and stable temperature in a short time; The cooling unit uses miniature cooling components, which can rapidly reduce the temperature of the chip surface to prevent excessively high temperatures from affecting the immune response and the sample. The temperature feedback regulation unit precisely controls the timing of heating and cooling switching by real-time temperature monitoring and combining it with the chip's operating status.

[0010] Based on the above technical solution, the chip can provide effective early warning three years before the onset of Alzheimer's disease by detecting biomarkers related to Alzheimer's disease. According to the above technical solution, the multimodal diagnostic method for neurological diseases based on spatiotemporally controllable immune responses includes the following steps: Step 1: Mix 10 μL of plasma sample with 90 μL of diluent, and then use a microfluidic system to mix them evenly to ensure that the sample and diluent are fully mixed; Step 2: Add the light-controlled antibody-3D probe complex to the mixture and incubate the mixture at 37°C for 5 minutes to ensure that the complex fully binds to and reacts with the target molecule; Step 3: Activate the photocontrolled antibody complex with 365nm light to initiate an immune response. During this process, the conformational change of the antibody triggered by light will enhance the binding ability of the antibody to the target molecule. Step 4: Use 450nm light to terminate the immune reaction, prevent the reaction from continuing and ensure the controllability of the reaction. After the immune reaction is completed, the sample is processed by chromatography for 10 minutes to separate the reaction products and remove unbound substances, thereby further improving the specificity of the detection. Step 5: Perform time-resolved fluorescence detection. Excite the target molecule using 340nm wavelength excitation light and simultaneously measure the fluorescence signals at wavelengths of 545nm, 615nm, and 660nm. Changes in the fluorescence signals can be used as a quantitative basis for the concentration of the target molecule. Step 6: Input the collected multi-omics data into the AI ​​system for analysis. The AI ​​system, based on fluorescence signals and other detection results, combined with big data analysis and algorithm models, performs comprehensive analysis on the data of different biomarkers and finally outputs diagnostic results.

[0011] Compared with existing technologies, the beneficial effects of this invention are as follows: The invention has a scientifically sound and reasonable structure, is safe and convenient to use, and the chip system combines multiple innovative technologies, resulting in significant clinical application effects. First, the world's first light-controlled immune response system achieves spatiotemporal specific regulation of antibody activity, significantly improving the accuracy and sensitivity of the immune response. Second, the integrated multi-omics detection chip can simultaneously detect three types of biomarkers: proteins, nucleic acids, and metabolites, providing richer information for comprehensive disease diagnosis. Furthermore, the AI ​​early warning model breaks through the limitation of existing technologies that can only diagnose existing cases. By analyzing multi-omics data, it can achieve intelligent early warning of diseases, providing support for early intervention. The system's ultra-sensitive detection performance increases the detection limit of traditional methods by 5000 times (GFAP can reach 0.01 pg / mL), significantly enhancing the detection capability for low-concentration biomarkers and achieving earlier, more accurate diagnosis. Finally, the world's first intelligent microfluidic system integrating light control, temperature control, and flow control not only improves detection efficiency but also ensures precise control of the immune response, signal enhancement, and biomarker separation processes, greatly improving the standardization and consistency of diagnosis. Simultaneously, the detection sensitivity and accuracy of neurological disease biomarkers are significantly improved. The photocontrolled antibody switch module uses a formula to adjust the affinity constant, making the binding between the antibody and the target molecule precise and controllable, avoiding the cross-reaction problem in traditional detection, and improving the specificity of the immune response. The signal enhancement factor formula of the three-dimensional fluorescent probe greatly enhances the fluorescence signal through the synergistic effect of gold nanoparticles, which can effectively detect low concentrations of biomarkers and greatly improve the detection sensitivity. The intelligent temperature control system ensures that the immune response takes place within the optimal temperature range by precisely adjusting the temperature, further improving the accuracy and stability of the reaction. The application of the time-resolved fluorescence detection formula makes the relationship between the fluorescence signal and the concentration of the target molecule more accurate, providing reliable quantitative analysis. The AI ​​analysis system improves the accuracy and intelligence of early warning by integrating multi-omics data and combining weighted summation, enabling the chip to achieve early and accurate diagnosis of neurological diseases, especially Alzheimer's disease. Overall, the design and application of these formulas effectively enhance the performance of the chip in actual diagnosis, providing clinicians with an efficient, sensitive, and intelligent diagnostic tool. Attached Figure Description

[0012] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0013] In the attached diagram: Figure 1 This is a flowchart illustrating the method steps of the present invention; Figure 2 This is a diagram of the reagent kit of the present invention; Figure 3 This is a diagram of the detection equipment of the present invention. Detailed Implementation

[0014] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0015] Example 1: like Figure 1 As shown, the present invention provides a technical solution: a multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response. The chip includes a light-controlled antibody switch module, a three-dimensional fluorescent probe, a multi-omics detection channel, and an intelligent temperature control system. The chip can simultaneously detect GFAP, NfL, p-tau217, miR-132, miR-124, and metabolic markers.

[0016] According to the above technical solution, the affinity regulation range of the photocontrolled antibody switch module is greater than or equal to 100 times, and the signal enhancement factor of the three-dimensional fluorescent probe is greater than or equal to 20 times. The chip also includes a microfluidic chip integrated with a pneumatic valve control system, which can achieve fully automated processing of 10μL of plasma.

[0017] During the operation of the photosensitive antibody switch module, the affinity is adjusted by changing the wavelength of light, and the affinity constant is... The affinity regulation adjusts with changes in light wavelength, thereby affecting the binding strength between the antibody and the target molecule. The following formula illustrates the specific relationship of affinity regulation:

[0018] in: wavelength of light The affinity constant at the given time; The initial affinity constant before illumination; It is an affinity modulation coefficient related to changes in light wavelength; The optimal wavelength for illumination; λ is the wavelength of light, which controls the regulation of antibody affinity; The three-dimensional fluorescent probe used in the chip achieves significant signal enhancement through the action of gold nanoparticles. The enhancement factor is closely related to the density and number of gold nanoparticles. The following formula shows the relationship between signal enhancement and the number of gold nanoparticles:

[0019] in: The enhanced signal strength; The original signal strength; The enhancement factor is related to the density of gold nanoparticles; The number of gold nanoparticles; β is an enhancement factor related to the density of gold nanoparticles, which determines the intensity of signal enhancement; The intelligent temperature control system ensures that the immune response occurs within the optimal range by dynamically adjusting the temperature. This adjustment process is based on feedback from real-time monitoring results. The following formula illustrates how the temperature control system adjusts the temperature over time to ensure precise control:

[0020] in: The temperature at time t; The initial temperature; The range of temperature change; γ is the time constant of the temperature control system response, describing the system's response speed to temperature changes; Time-resolved fluorescence detection technology is used for the quantitative analysis of target molecule concentration. In this process, the change in fluorescence signal is related to the concentration of the target molecule. The following formula shows the quantitative relationship between fluorescence signal and target concentration:

[0021] in: The fluorescence intensity at time t; The initial fluorescence intensity is given by , and C is the concentration of the target molecule. The attenuation coefficient is related to the target molecule concentration C; C represents the concentration of the target molecule; In multimodal diagnostic systems, AI systems comprehensively analyze data from multiple biomarkers to provide more accurate diagnostic results. The weights and detection values ​​of different biomarkers are weighted and summed using the following formula:

[0022] in: The diagnostic results after AI analysis; Let i be the weight of the i-th marker. This is the detection value of the marker; n represents the number of biomarkers involved in the analysis; The design of microfluidic systems can ensure efficient and uniform processing. The flow efficiency of fluids directly affects the accuracy and time of sample processing. The following formula describes the efficiency of fluid processing in the chip:

[0023] in: For fluid handling efficiency; This represents the actual volume processed. This represents the total volume of the sample. The fluid flow rate (volume / time); For processing time; The introduction of gold nanoparticles significantly enhances the surface plasmon resonance (SPR) effect, thereby improving the sensitivity of the fluorescence signal. The formula illustrates how the size, distribution, and relationship between the gold nanoparticles and the target molecules affect the SPR signal enhancement:

[0024] in: The degree of SPR signal enhancement; It is a constant (dependent on experimental conditions); d is the diameter of the gold nanoparticle; D is the size of the surface reflection area; r is the distance between the gold nanoparticle and the target molecule; R is the size of the SPR sensitive area; To accurately detect the concentration of target molecules, changes in time-resolved fluorescence signals are used for quantitative analysis. The amount of signal change is related to background fluorescence and the size of the time window. The following formula describes the quantification of fluorescence signal sensitivity:

[0025] in: The sensitivity of the fluorescence signal; Changes in fluorescence signal; Background fluorescence; For example, the time window (e.g., the time interval between each fluorescence sampling); Under light activation, the effects of the immune response change, and the relationship between the light wavelength and the response efficiency is expressed by the following formula:

[0026] in: This represents the change in immune response efficiency under light wavelength λ. To achieve maximum reaction efficiency; The response gain factor is related to wavelength change; The wavelength of light is used to control the precision of the immune response; To ensure precise control of the immune response, the intelligent temperature control system uses a temperature regulation rate coefficient. The system automatically adjusts the temperature. The following formula describes how the temperature changes over time and reflects the system's response to temperature control requirements at different stages:

[0027] in: The adjusted temperature at time t; The initial temperature; The target temperature (the temperature required for the immune response); This is the temperature control regulation rate coefficient, used to describe the response speed of the temperature control system; t represents time; For the portion of the chip used for nucleic acid detection, the detection sensitivity can be expressed by the following formula:

[0028] in: To improve the sensitivity of nucleic acid testing; The concentration of the target nucleic acid to be tested; This is the lowest detectable concentration of nucleic acid.

[0029] According to the above technical solution, the detection area includes three protein detection lines (T1-T3), two nucleic acid detection lines (T4-T5), and a metabolite sensor to supplement it, so as to realize the detection of biomarkers related to neurological diseases; The chip surface is covered with a nitrocellulose film and gold nanoparticles are deposited through a vapor deposition process. The size and distribution uniformity of the gold nanoparticles are optimized to maximize the SPR effect and improve the stability and sensitivity of the fluorescence signal. SPR enhances fluorescence signal by 18.5 times.

[0030] According to the above technical solution, the density and distribution of gold nanoparticles deposited on the surface of nitrocellulose membrane can be adjusted according to different detection requirements.

[0031] According to the above technical solution, the intelligent temperature control system monitors the internal temperature changes of the chip in real time through the built-in temperature sensor and automatically adjusts the temperature according to the needs of the immune response. The temperature control system uses intelligent algorithms to precisely regulate the temperature at different detection stages, ensuring that the immune response takes place within the optimal temperature range, thereby improving detection sensitivity and accuracy. By working in conjunction with other modules on the chip, the intelligent temperature control system can automatically start or stop the heating function according to actual needs, achieving energy saving and efficient control.

[0032] According to the above technical solution, the intelligent temperature control system further includes a heating unit, a cooling unit, and a temperature feedback adjustment unit, which can intelligently adjust the heating and cooling mechanisms according to the temperature control requirements of each detection module in the chip. The heating unit uses high-efficiency thermoelectric materials, which can provide a uniform and stable temperature in a short time; The cooling unit uses miniature cooling components, which can rapidly reduce the temperature of the chip surface to prevent excessively high temperatures from affecting the immune response and the sample. The temperature feedback regulation unit precisely controls the timing of heating and cooling switching by real-time temperature monitoring and combining it with the chip's operating status.

[0033] Based on the above technical solution, the chip can provide effective early warning three years before the onset of Alzheimer's disease by detecting biomarkers related to Alzheimer's disease. According to the above technical solution, the multimodal neurological disease diagnosis method based on spatiotemporally controllable immune response includes the following steps: Step 1: Mix 10 μL of plasma sample with 90 μL of diluent, and then use a microfluidic system to mix them evenly to ensure that the sample and diluent are fully mixed; Step 2: Add the light-controlled antibody-3D probe complex to the mixture and incubate the mixture at 37°C for 5 minutes to ensure that the complex fully binds to and reacts with the target molecule; Step 3: Activate the photocontrolled antibody complex with 365nm light to initiate an immune response. During this process, the conformational change of the antibody triggered by light will enhance the binding ability of the antibody to the target molecule. Step 4: Use 450nm light to terminate the immune reaction, prevent the reaction from continuing and ensure the controllability of the reaction. After the immune reaction is completed, the sample is processed by chromatography for 10 minutes to separate the reaction products and remove unbound substances, thereby further improving the specificity of the detection. Step 5: Perform time-resolved fluorescence detection. Excite the target molecule using 340nm wavelength excitation light and simultaneously measure the fluorescence signals at wavelengths of 545nm, 615nm, and 660nm. Changes in the fluorescence signals can be used as a quantitative basis for the concentration of the target molecule. Step 6: Input the collected multi-omics data into the AI ​​system for analysis. The AI ​​system, based on fluorescence signals and other detection results, combined with big data analysis and algorithm models, performs comprehensive analysis on the data of different biomarkers and finally outputs diagnostic results.

[0034] Example 2: Preparation of light-controlled antibody switches: Materials: Mouse anti-human GFAP monoclonal antibody (clone number 5G8), azobenzene-succinimide ester, SPDP; step: An azophenyl group was introduced into the antibody hinge region, and the photoisomerization efficiency was verified to be >95% by UV-Vis spectroscopy. SPR testing showed that the affinity changed by up to 120 times before and after photocontrol (KD value from 8.5×10). -10 M decreased to 7.1×10 -13 M).

[0035] Example 3: Synthesis of three-dimensional fluorescent probes: Materials: Fifth-generation PAMAM, Eu 3+ -EDTA, SMCC; step: 100 Eu load 3+ -EDTA to the surface of PAMAM, conjugated with antibody (conjugation rate 92%). Dynamic light scattering detection of particle size is 120±15nm, and fluorescence lifetime is extended to 1.2ms.

[0036] Example 4: Multimodal chip performance testing: result: Detection time: 8 minutes (240 minutes for traditional methods); Limit of detection: GFAP 0.01 pg / mL (conventional ELISA 50 pg / mL); Batch consistency: CV < 2.0% (traditional method CV > 10%).

[0037] Example 5: AI diagnostic model training: Data: 10,000 clinical samples (2,000 in the AD group, 1,800 in the TBI group, and 6,200 in the healthy group); result: The early prediction accuracy of AD is 98.7% (early warning 3 years before onset). The combined diagnosis using multiple omics methods had an AUC of 0.995 (the AUC for a single protein marker was 0.98).

[0038] Example 6: To verify the performance of the multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune responses, a 10 μL plasma sample was used for the experiment. The goal was to detect biomarkers related to neurological diseases, including GFAP (glial fibrillary acidic protein), NfL (neurofilament light chain protein), and p-tau217 (phosphorylated tau protein). In the experiment, sensitive detection and accurate diagnosis were achieved by combining various modules of the chip with formulas and data.

[0039] Experimental steps and calculation process: Applications of affinity modulation and light-controlled antibody switching modules: Initial affinity constant =10 -10 M, the wavelength of light from =365nm was adjusted to λ=370nm, with an adjustment coefficient α=1.5; After adjusting the light wavelength, the calculated affinity constant is as follows: =1.176×10 -11 M, compared to the initial value of 10 -10 M, with an affinity increase of approximately 11.76%, enhances the binding strength between the antibody and the target molecule.

[0040] Signal enhancement: Applications of three-dimensional fluorescent probes: Number of gold nanoparticles =10 6 Particle density coefficient β=0.05, initial signal strength =100AU.

[0041] Through the action of gold nanoparticles, the signal enhancement factor is =5,000100AU, the signal is enhanced by 5,000 times, which greatly improves the detection sensitivity of low-concentration markers.

[0042] Temperature control and regulation: Application of intelligent temperature control systems: initial temperature =37℃, temperature change range =5℃, temperature control rate coefficient γ=0.2min -1 The measurement time was t = 5 min.

[0043] The temperature is adjusted to 40.16℃ after 5 minutes by the temperature control system, ensuring that the immune response takes place at the optimal temperature, thus maximizing the accuracy and stability of the response.

[0044] Quantitative analysis of fluorescence signals: Initial fluorescence intensity =100AU, attenuation coefficient α=0.1perpg / mL, target molecule concentration C=2pg / mL, time t=5min.

[0045] Five minutes later, the fluorescence intensity decayed to 36.79 AU, demonstrating the accurate relationship between the target molecule concentration and the fluorescence intensity, ensuring precise quantification of the concentration.

[0046] AI analysis and multi-omics data processing: The first marker w1=0.5, the detection value B1=30AU; the second marker w2=0.3, the detection value B2=40AU; the third marker w3=0.2, the detection value B3=50AU.

[0047] The AI ​​diagnostic result is calculated as follows: =37AU. The AI ​​system uses a weighted summation method to comprehensively evaluate the impact of each marker and output the final diagnostic value.

[0048] Fluid handling efficiency of microfluidic chips: flow =0.5μL / min, processing time =10min, total sample size =10μL; The microfluidic system has a fluid handling efficiency of 50%, ensuring uniform mixing and precise processing of plasma samples.

[0049] The contribution of gold nanoparticles to the SPR effect: The diameter of the gold nanoparticles is d=2nm, the size of the SPR sensitive region is D=200nm, the distance between the gold particles and the target molecules is r=10nm, and the size of the sensitive region is R=30nm. The SPR enhancement signal was increased by 18.5 times, significantly enhancing the fluorescence signal and making the detection of low-concentration biomarkers more sensitive.

[0050] Time-resolved fluorescence detection sensitivity: Background fluorescence =5AU, signal change =50AU, sampling time window Δt=1min.

[0051] The sensitivity is calculated to be 10 AU / min, ensuring the chip's efficient detection of trace markers.

[0052] Changes in light-controlled immune response: Maximum reaction efficiency =100AU, reaction gain factor κ=0.0per nm, illumination wavelength change is =20nm.

[0053] The light-induced immune response gain was 63.21 AU, which significantly improved the efficiency of the immune response and enhanced the stability of biomarker detection.

[0054] Temperature change prediction by intelligent temperature control system: initial temperature =3737℃, target temperature =40℃, temperature control rate coefficient =0.2min -1 The temperature was adjusted to 39.2℃ within 5 minutes, ensuring the reaction proceeded stably.

[0055] Nucleic acid detection sensitivity: Target nucleic acid concentration =5pg / mL, the lowest detectable nucleic acid concentration =0.01 pg / mL.

[0056] The nucleic acid test has a sensitivity of 99.8%, ensuring efficient detection of low-concentration nucleic acids.

[0057] Experimental results: (1) Lowest detection line (LoD) Using the kit described in Example 6, the following samples were tested: Sample 1 (GFAP, NfL, and p-Tau217 concentrations were 0.006 pg / mL, 0.010 pg / mL, and 0.010 pg / mL, respectively); Sample 2 (GFAP, NfL, and p-Tau217 concentrations were 0.008 pg / mL, 0.030 pg / mL, and 0.015 pg / mL, respectively); Sample 3 (GFAP, NfL, and p-Tau217 concentrations were 0.010 pg / mL, 0.050 pg / mL, and 0.020 pg / mL, respectively); Sample 4 (GFAP, NfL, and p-Tau217 concentrations were 0.015 pg / mL, 0.070 pg / mL, and 0.030 pg / mL, respectively); and Sample 5 (GFAP, NfL, and p-Tau217 concentrations were 0.020 pg / mL, 0.020 pg / mL, and 0.020 pg / mL, respectively). The samples were tested at concentrations of 0.090 pg / mL, 0.040 pg / mL, and 0.090 pg / mL. Each sample was measured four times, and the tests were conducted for three consecutive days to obtain 60 test results. The results were calculated using the formula: LoD = LoB + kSDz (where SDz is the pooled standard deviation of the low concentration sample test values, and the calculation formulas are shown in formulas (1) and (2).

[0058] In the formula: ni is the number of results for the i-th low concentration level sample; SDi is the standard deviation of the i-th low-concentration level sample; k is the multiplier of the 95th percentile of the normal distribution; N is the number of samples at the low concentration level; L is the total number of results from all low-concentration level samples; Table 1 Detection limit test results

[0059]

[0060] (2) Precision testing The kit from Example 6 was used to detect the following samples: Sample 5 (GFAP, NfL, and p-Tau217 concentrations were 0.100 pg / mL, 0.500 pg / mL, and 0.200 pg / mL, respectively), Sample 6 (GFAP, NfL, and p-Tau217 concentrations were 1.000 pg / mL, 5.000 pg / mL, and 2.000 pg / mL, respectively), and Sample 7 (GFAP, NfL, and p-Tau217 concentrations were 10.000 pg / mL, 50.000 pg / mL, and 20.000 pg / mL, respectively). The tests were repeated 10 times, and the average value and coefficient of variation (CV) of the test results were calculated. The test results are shown in Table 2 below.

[0061] Table 2 Precision Test Results

[0062] (3) Results Analysis: GFAP detection: The detection limit of the traditional ELISA method is 50 pg / mL, while the detection limit of this chip is increased to 0.01 pg / mL, the sensitivity is increased by 5000 times, the experimental time is 8 minutes, compared with 240 minutes of the traditional ELISA method, the detection time is significantly shortened, and the batch consistency (CV value) is less than 2.0%, which is significantly higher than the traditional method (CV value > 10%).

[0063] NfL detection: By enhancing the fluorescence signal with gold nanoparticles, the detection limit was increased to 0.05 pg / mL (compared to 10 pg / mL for the traditional method). The signal enhancement made the detection of low-concentration biomarkers more sensitive, and the batch-to-batch consistency (CV value) was less than 2.0%, which was significantly higher than that of the traditional method (CV value > 10%).

[0064] p-tau217 detection: This chip can detect p-tau217 at a concentration of 0.02 pg / mL, far below the detection limit of 5 pg / mL for traditional methods, representing a 250-fold increase in sensitivity. The enhanced signal makes the detection of low-concentration biomarkers more stable, with batch-to-batch consistency (CV) below 2.0%, significantly higher than traditional methods (CV > 10%).

[0065] Early warning from AI systems: In the early prediction of Alzheimer's disease (AD), the AI ​​diagnostic model achieved an accuracy rate of 98.7%, providing effective early warning up to 3 years before the onset of AD, thus supporting early intervention.

[0066] Conclusion: This embodiment verifies the significant advantages of a multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune responses in detecting neurological disease-related biomarkers. Through optimized affinity modulation, signal enhancement, temperature control system, and AI analysis, the performance of multi-biomarker detection has been comprehensively improved, providing strong support for the early diagnosis of neurological diseases.

[0067] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response, characterized in that: The chip includes a light-controlled antibody switch module, a three-dimensional fluorescent probe, a multi-omics detection channel, and an intelligent temperature control system; The chip can simultaneously detect GFAP, NfL, p-tau217, miR-132, miR-124, and metabolic markers.

2. The multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response according to claim 1, characterized in that, The affinity modulation range of the photocontrolled antibody switch module is greater than or equal to 100 times, and the signal enhancement factor of the three-dimensional fluorescent probe is greater than or equal to 20 times. The chip also includes a microfluidic chip integrated pneumatic valve control system, which can realize fully automated processing of 10μL of plasma.

3. The multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response according to claim 1, characterized in that, The detection area includes three protein detection lines (T1-T3), two nucleic acid detection lines (T4-T5), and a metabolite sensor to supplement the detection of biomarkers related to neurological diseases. The surface of the chip is covered with a nitrocellulose film and gold nanoparticles are coated by a vapor deposition process. The size and distribution uniformity of the gold nanoparticles are optimized to maximize the SPR effect and improve the stability and sensitivity of the fluorescence signal. SPR enhances fluorescence signal by 18.5 times.

4. The multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response according to claim 3, characterized in that, The density and distribution of gold nanoparticles deposited on the surface of the nitrocellulose membrane can be adjusted according to different detection requirements.

5. The multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response according to claim 1, characterized in that, The intelligent temperature control system monitors the internal temperature changes of the chip in real time through a built-in temperature sensor and automatically adjusts the temperature according to the needs of the immune response. The temperature control system uses intelligent algorithms to precisely regulate the temperature at different detection stages, ensuring that the immune response proceeds within the specified range. By working in conjunction with other modules on the chip, the intelligent temperature control system can automatically start or stop the heating function according to actual needs.

6. The multimodal neurological disease diagnostic chip based on spatiotemporally controllable immune response according to claim 5, characterized in that, The intelligent temperature control system further includes a heating unit, a cooling unit, and a temperature feedback adjustment unit, which can intelligently adjust the heating and cooling mechanisms according to the temperature control requirements of each detection module in the chip. The heating unit uses high-efficiency thermoelectric materials to provide a uniform and stable temperature; The cooling unit uses miniature refrigeration components; The temperature feedback regulation unit controls the timing of heating and cooling switching by real-time temperature monitoring and combining it with the chip's operating status.

7. The application of the chip according to claim 1 in the preparation of early warning products for Alzheimer's disease, characterized in that: The chip can provide effective early warning up to 3 years before the onset of Alzheimer's disease by detecting biomarkers associated with Alzheimer's disease.

8. The diagnostic method for multimodal neurological disease diagnostic chips based on spatiotemporally controllable immune responses according to claim 1, characterized in that, Includes the following steps: Step 1: Mix 10 μL of plasma sample with 90 μL of diluent, and then use a microfluidic system to mix them evenly to ensure that the sample and diluent are fully mixed; Step 2: Add the light-controlled antibody-3D probe complex to the mixture and incubate the mixture at 37°C for 5 minutes to ensure that the complex fully binds to and reacts with the target molecule; Step 3: Activate the photocontrolled antibody complex with 365nm light to initiate an immune response. During this process, the conformational change of the antibody triggered by light will enhance the binding ability of the antibody to the target molecule. Step 4: Use 450nm light to terminate the immune reaction, prevent the reaction from continuing and ensure the controllability of the reaction. After the immune reaction is completed, the sample is processed by chromatography for 10 minutes to separate the reaction products and remove unbound substances, thereby further improving the specificity of the detection. Step 5: Perform time-resolved fluorescence detection. Excite the target molecule using 340nm wavelength excitation light and simultaneously measure the fluorescence signals at wavelengths of 545nm, 615nm, and 660nm. Changes in the fluorescence signals can be used as a quantitative basis for the concentration of the target molecule. Step 6: Input the collected multi-omics data into the AI ​​system for analysis. The AI ​​system, based on fluorescence signals and other detection results, combined with big data analysis and algorithm models, performs comprehensive analysis on the data of different biomarkers and finally outputs diagnostic results.

Images