Electrochemical sensor capable of monitoring hs-cTnT data in real time and monitoring device comprising electrochemical sensor

Abstract

The invention discloses an electrochemical sensor capable of monitoring hs-cTnT data in real time and a monitoring device comprising the electrochemical sensor. The invention discloses an electrochemical sensor capable of monitoring hs-cTnT data in real time. The electrochemical sensor comprises a monitoring electrode and a masking agent, the monitoring electrode takes a laser-induced graphene electrode as a substrate, and a cTnT aptamer is fixed on the surface; the masking agent is used for masking the surface of the electrode. A flexible wearable integrated self-powered cTnT monitoring device comprises an electrochemical sensor, a self-powered system and a data transmission unit. The flexible wearable integrated self-powered cTnT detection nucleic acid aptamer sensor can diagnose AMI in an early stage, rapidly and accurately, and provides a diagnosis basis for optimization of a clinical decision path.

Description

Technical Field

[0001] The present invention belongs to the field of medical monitoring devices, and in particular relates to an electrochemical sensor capable of monitoring hs-cTnT data in real time and a monitoring device comprising the same. Background Art

[0002] Acute myocardial infarction (AMI) is the most common cause of death in the world. There are 3 million new AMI patients every year in the world. In June 2023, the National Center for Cardiovascular Diseases released the latest "China Cardiovascular Health and Disease Report 2022", pointing out that the AMI mortality rate in my country from 2002 to 2020 has generally increased, and since 2005, the AMI mortality rate has shown a rapid upward trend. In 2020, the total hospitalization cost of cardiovascular and cerebrovascular diseases in my country was 270.901 billion yuan. Among them, the hospitalization cost of AMI was 34.685 billion yuan.

[0003] Among the emergency patients who visit the hospital every year, about 10% of them have AMI-related symptoms. Therefore, early and clear diagnosis is of great significance for the timely and standardized treatment of AMI patients. Every 1 minute of delay will directly affect the one-year mortality rate, and every 30 minutes of delay will increase the relative risk of death by 7.5%. Clinical symptoms, electrocardiogram results and cardiac troponin (cTn) level determination are the key to the early diagnosis of AMI. Thanks to the development of high-sensitivity cardiac troponin (hs-cTn) detection technology, the European Society of Cardiology (ESC) gave the highest level of Class I recommendation to the "0h / 1h diagnostic process" for AMI in the recently updated guidelines. However, the "0h / 1h diagnostic process" does not have a sufficiently high negative predictive value in the diagnosis of AMI. The cTn content is dynamic and will change over time. Therefore, continuous and dynamic monitoring of cTn is of particular clinical significance for the diagnosis and risk stratification of AMI.

[0004] In myocardial cells, cTn has three subunits: troponin T (cTn T), troponin I (cTn I) and troponin C (cTn C). cTn T and cTn I are specifically expressed in the heart. When myocardial cells are damaged, cTn located in the cytoplasm is rapidly released into the blood, becoming a marker for early detection of myocardial injury. In AMI patients, cTn will begin to be released within 3-6 hours, reach a peak within 10-24 hours, and return to normal in 10-15 days for cTnT and 5-7 days for cTnI. hs-cTn and cTn both detect the same substance, and hs-cTn mainly emphasizes accuracy and sensitivity. The European Society of Cardiology (ESC), the American College of Cardiology (ACC), the American Heart Association (AHA), the World Heart Federation (WHF) and the Chinese Society of Cardiology (CSC) have fully affirmed the importance of hs-cTn in the diagnosis and differentiation of ACS. As one of the best cTn detection methods currently available, hs-cTn detection has been widely used in clinical practice due to its optimal sensitivity and specificity.

[0005] The limitations of hs-cTn in clinical applications are becoming increasingly prominent. First, the detection threshold uses a fixed threshold without considering factors that may affect age and gender; second, the detection time node is relatively fixed (0 / 1 hour), which is prone to misdiagnosis and missed diagnosis; third, the interpretation of the test results is not combined with electrocardiogram and clinical data. Therefore, exploring ways to improve the hs-cTn detection process to meet the growing demand for AMI diagnosis and treatment has become an urgent problem to be solved. Summary of the invention

[0006] The purpose of the present invention is to address the defects of the prior art and provide an electrochemical sensor capable of monitoring hs-cTnT data in real time and a monitoring device comprising the same.

[0007] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: an electrochemical sensor capable of real-time monitoring of hs-cTnT data, comprising a monitoring electrode and a masking agent; the monitoring electrode is based on a laser-induced graphene electrode, and a cTnT aptamer is fixed on the surface; the masking agent is used to mask the electrode surface.

[0008] Furthermore, the laser induced graphene electrode is a laser induced graphene electrode constructed on a polyimide film using a laser engraving technique.

[0009] Furthermore, the cTnT aptamer is modified on the surface of the laser-induced graphene electrode by depositing noble metal nanoparticles on the surface of the laser-induced graphene electrode, and the cTnT aptamer is modified by the noble metal nanoparticles.

[0010] Furthermore, the noble metal is Au or Ag.

[0011] Furthermore, the masking agent is 6-mercapto-1-hexanol or bovine serum albumin.

[0012] A method for preparing the electrochemical sensor capable of real-time monitoring of hs-cTnT data comprises the following steps:

[0013] (1) Constructing laser-induced graphene electrodes based on laser engraving technology. The parameters of the laser cutting machine are: speed 6.8%-50%, power 5.5%-25%, and engraving the electrode shape on the polyimide film. The electrode shape is a rod electrode or a three-electrode;

[0014] (2) Using an electrochemical workstation to provide power, electrochemically deposit noble metal nanoparticles on the surface of the laser-induced graphene electrode to construct a laser-induced graphene / noble metal electrode; the electrochemical deposition reaction process is as follows: immerse the laser-induced graphene electrode prepared in (1) in a mixed solution of 0.1~0.2mM sodium sulfate and 1~2mM chloroauric acid, apply a deposition potential of -0.2~-0.4V to electro-deposit nanogold particles, and the deposition time is 400~600s;

[0015] (3) Self-assembling nucleic acid aptamers on the surface of laser-induced graphene / noble metal electrode, the specific process is as follows: dripping aptamer solution with a concentration of 2-10uM and a volume of 10-15uL on the surface of laser-induced graphene / noble metal electrode prepared in step (2), covering the electrode cap, incubating at room temperature for 12-24h to form a stable noble metal-S chemical bond, and fixing the cTnT aptamer on the surface of laser-induced graphene / noble metal electrode;

[0016] (4) Add 6-mercapto-1-hexanol solution with a concentration of 5 to 10 uM and a volume of 10 to 15 uL to the surface of the electrode prepared in step (3), cover the electrode cap, and incubate at room temperature for 1 to 3 hours to block the active sites on the electrode surface that are not fixed by the aptamer.

[0017] A flexible wearable integrated self-powered cTnT monitoring device, comprising: the above-mentioned electrochemical sensor, a self-powered system and a data transmission unit;

[0018] The electrochemical sensor is used to detect the hs-cTnT data of the wearer's fingertips in real time;

[0019] The self-powered system is used to collect low-level heat energy from the wearer's body and convert it into electrical energy for storage to power the sensor;

[0020] The data transmission unit is used to transmit the patient's hs-cTnT data obtained in real time to an external platform for analysis and evaluation.

[0021] Furthermore, the self-powered system uses a polyvinyl alcohol-based thermoelectric composite hydrogel based on a three-dimensional interconnected porous network.

[0022] Furthermore, the polyvinyl alcohol-based thermoelectric composite hydrogel based on the three-dimensional interconnected porous network is prepared by the following steps:

[0023] (1) Prepare tellurium nanowires by a hydrothermal reaction method. Dissolve polyvinyl pyrrolidone in ultrapure water and then add sodium tellurite. Then add a precursor solution formed by hydrazine hydrate and ammonia monohydrate. Perform a hydrothermal reaction at 180-200°C for 10-12 hours. Wash the obtained product with ultrapure water. Finally, dry the product in a vacuum oven to obtain tellurium nanowires.

[0024] (2) PVA and polyethylene dioxythiophene-polystyrene sulfonate aqueous solution are mixed in a three-necked flask, and then placed in an oil bath at 80-90°C and stirred continuously. During the stirring process, the tellurium nanowires prepared in step (1) are slowly added, and then the prepolymer solution is frozen at -15--20°C for 1 hour to solidify. The solid is placed in a sealed culture dish and allowed to stand at room temperature for 10 hours. The freeze-thaw cycle is repeated 5-10 times to obtain a polyvinyl alcohol-based thermoelectric composite hydrogel.

[0025] Furthermore, the data transmission unit uses Bluetooth technology to send data to an external platform.

[0026] This research group consists of the AMI clinical research team, the multimodal big data team, the flexible electronics and sensing R&D team, and the nanogenerator and self-driving system research team. The clinical research team verified the value and mode of hs-cTnT in the differential diagnosis of AMI in a large sample cohort study and constructed multi-center AMI cohort data; the multimodal big data team constructed a cross-modal communication system architecture for multimodal services, designed a semantic-based cross-modal encoding scheme, proposed a semantic-driven cross-modal code stream scheduling and transmission method, and built a remote operation platform based on cross-modal communication; the flexible electronics and sensing R&D team developed a flexible sensing material with excellent electrical and mechanical properties and the performance of strain sensors, and developed an independently developed wireless sensing signal acquisition and testing system, which records and displays motion signals through mobile phone APP, providing good prospects for the commercialization of sensing equipment; the nanogenerator and self-driving system research team developed a 3D printed acoustic friction nanogenerator (A-TENG), which has the characteristics of controllable structure, one-time molding, simple production, and low cost. It uses wet spinning to construct a two-dimensional Ti-based 3 C 2Stretchable n-type thermoelectric MP fibers composited with TxMXene nanosheets and polyurethane PU. The proposed fibers adopt a 3D interconnected porous network design, which can simultaneously achieve satisfactory electrical conductivity (σ), thermal conductivity (κ) and wearable stretchability. The most important thing is that our research group has successfully constructed gold nanoparticle-modified electrodes LIG / Au based on cTn nucleic acid aptamers, which can be verified in the future.

[0027] Flexible Wearable and Self-powered Aptasensors for Continuous High-sensitivity Cardiac Troponin T Monitoring (FWSAT) can diagnose AMI early, quickly and accurately, and provide a diagnostic basis for the optimization of clinical decision-making pathways. Its mechanism is as follows: FWSAT uses aptamers to detect hs-cTnT in the wearer's subcutaneous capillaries. The device sends signals via Bluetooth to a cloud system, where machine learning algorithms link the information with training data to dynamically and continuously assess the wearer's hs-cTnT levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flow chart of wearing FWSAT test in an embodiment.

[0029] Figure 2 The following are examples of evaluating the measurement results of the test method and the measurement results of the comparable method in the form of scatter plots: (A) Error grid plot (B) Clarke error grid plot (C) Consensus error grid plot.

[0030] Figure 3 It is a test flow chart for evaluating the safety and effectiveness of a flexible wearable integrated self-powered hs-cTnT detection system according to an embodiment.

[0031] Figure 4 The embodiment is a flowchart of an experiment for verifying the clinical value of FWSAT in AMI diagnosis by multimodality. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0033] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or apparatuses.

[0034] 1. Construction of FWSAT

[0035] The design of FWSAT includes three parts: sensor construction, self-powered system and data processing system.

[0036] 1. Construction of an electrochemical sensor for detecting hs-cTnT based on nucleic acid aptamers: This experiment uses PI membrane, LIG, AuNPs, cTnT aptamers and electrochemical sensors to construct an electrochemical method that can specifically detect hs-cTnT. The AuNPs are modified on the electrode surface by constant potential deposition; the aptamer is fixed on the AuNPs-modified electrode surface with the help of Au-S bonds; MCH (6-mercapto-1-hexanol) is used as a masking agent to mask the electrode surface to reduce nonspecific adsorption on the electrode surface; after binding to cTnT, the spatial position of the cTnT aptamer on the electrode surface changes, the current increases, and the detection of cTnT is achieved.

[0037] 2. Self-powered system: Based on a three-dimensional interconnected porous network of stretchable thermoelectric fibers, a textile thermoelectric generator is constructed to collect low-level thermal energy from the body and convert it into electrical energy stored in supercapacitors to power sensors.

[0038] 3. Data processing system: FWSAT uses nucleic acid aptamers to detect hs-cTnT in the wearer's subcutaneous capillaries. The device sends signals via Bluetooth to a cloud system where machine learning algorithms link the information with training data to dynamically and continuously assess the wearer's hs-cTnT levels.

[0039]

Experimental methods

[0040] (1) Electrode preparation: ① Construction of LIG electrode based on laser engraving technology; ② Electrochemical deposition of AuNPs to construct LIG / Au electrode; ③ Self-assembly of nucleic acid aptamers on the surface of LIG / Au electrode, including aptamer selection, aptamer precursor solution preparation and self-assembly steps; ④ Characterization of electrodes at different modification stages using an electrochemical workstation.

[0041] (2) Preparation of textile thermoelectric generators: ① Wet spinning is used to construct a two-dimensional Ti 3 C 21. Stretchable n-type thermoelectric MP fibers composited with TxMXene nanosheets and polyurethane PU; 2. Optimize the thermoelectric and mechanical properties of MP fibers; 3. Construct a textile thermoelectric generator based on MP-60 fibers.

[0042]

Key technologies

[0043] Aptamer precursor solution configuration and self-assembly: TCEP configuration: 1* M 20mL 0.05734g; Aptamer configuration: 2 uL aptamer (concentration is 100 uM) +2 uL (TCEP)+96 uL(TE)= 100 uL 1uM aptamer solution; The prepared aptamer solution was added dropwise to the surface of the gold nanoparticle modified electrode, the electrode cap was covered and placed in a refrigerator at 4 ℃ for 12 h to obtain the aptamer-modified electrode; After taking it out, it was thoroughly rinsed with ultrapure water, placed in 6-mercapto-1-hexanol (MCH, MCH configuration: 20 mL 1 mM requires 2.7 uL of stock solution) at room temperature for 1 h to obtain the masked electrode.

[0044] 2. Clinical Validation of FWSAT

[0045] FWSAT monitors the wearer's subcutaneous interstitial fluid hs-cTnT concentration and draws a curve to reflect the fluctuation trend of the patient's hs-cTnT level, achieving continuous dynamic monitoring. A multicenter clinical trial aimed to evaluate the performance, ease of use and safety of FWSAT in Chinese adult patients with chest pain.

[0046]

Experimental methods

[0047] 1. Study design: A prospective, multi-center, single-group target value design clinical trial. The hs-cTnT values ​​measured by the subjects FWSAT were compared with the venous hs-cTnT. The main indicators included 20% consistency of the reference value (standard requirement> 65%), mean absolute relative error (MARD%, standard requirement < 18%), percentage of Clarke error grid A+B area (standard requirement> 95%), percentage of Consensus error grid A+B area (standard requirement> 95%), and consistency of reference value Bland-Altman bias analysis (standard requirement> 95%).

[0048] 2. Subject inclusion and exclusion criteria

[0049] Inclusion Criteria:

[0050] (1) Aged 18 and above;

[0051] (2) Subjects with chest pain suspected of AMI or other cardiac diseases (heart failure, myocarditis, pericarditis, Takotsubo syndrome, etc.);

[0052] (3) Volunteer to participate in this clinical trial and sign the subject informed consent form.

[0053] Exclusion criteria:

[0054] (1) Sequelae of hemiplegia caused by previous stroke;

[0055] (2) Cognitive impairment or mental illness;

[0056] (3) Skin scars or skin diseases;

[0057] (4) Pregnant or breastfeeding women, or those planning to become pregnant during the trial;

[0058] (5) Those who have participated in other interventional device clinical trials within 1 month before this trial or have participated in drug clinical trials within 5 half-lives of the last medication;

[0059] (6) Those who the researchers consider unsuitable to participate in this clinical trial.

[0060] 3. After the qualified subjects were enrolled, they wore one FWSAT on each arm for 15 consecutive days. During the wearing period, one day was randomly selected for intensive venous blood sampling in the "1st to 2nd day after initialization", "7th to 9th day during wearing" and "last 24 hours of wearing", and venous blood was collected every 30 minutes for 7 consecutive hours. Venous blood hs-cTnT was measured by Roche analyzer, using Elecsys Troponin T hs STAT detection, comparing the sensor detection value with the analyzer hs-cTnT value, and statistically analyzing the results.

[0061] 4. Sample size calculation:

[0062] (1) Based on the 20% standard of consistency with the reference value, assuming that the consistency between the hs-cTnT value measured by FWSAT and the venous hs-cTnT value (20% standard) is 65%, and the target value is set at 60%, then when the bilateral significance level is 0.05 and a 20% dropout rate is taken into account, 1200 measurement points will be able to provide more than 80% confidence (considering that there is a certain correlation between multiple measurements from the same subject) to prove that the performance of the test product meets the needs of clinical application. If it is conservatively estimated that each subject can provide results of at least 12 measurement points during the trial, then at least 100 subjects will be selected to meet the above sample size (measurement point) requirements. Paired FWSAT hs-cTnT values ​​and venous hs-cTnT values ​​of different concentrations are required, with at least 360 measurement points for high-concentration hs-cTnT values ​​greater than or equal to 100 ng / L and at least 60 measurement points for low-concentration hs-cTnT values ​​below 14 ng / L.

[0063] (2) The expected results of the proportion of points falling in the A+B zone in the Clarke or Consensus error grid analysis are consistent with the target value (both are 95% and 90%), and the consistency of the reference value Bland-Altman bias analysis is consistent with the target value (both are 95% and 90%). Therefore, the above sample size can provide sufficient confidence to prove that the product meets the requirements.

[0064] (3) For the MARD% value, assuming that the actual observation result is 18%±5% (patient level), with a bilateral significance level of 0.05 and taking into account 20% dropout, 100 subjects can provide about 80% confidence to prove that the MARD% value at the subject level is less than 20%.

[0065] In summary, in order to simultaneously meet the sample size requirements of the four main indicators, the total number of subjects included was finally determined to be 100.

[0066] In the above calculations, the sample size calculation formula used in (1) and (2) is:

[0067]

[0068] The expected efficacy level of the corresponding test group in the formula corresponds to the target value level, represents the quantile corresponding to the standard normal distribution, corresponds to the type I error level of the statistical test, which is 0.025 here, and the type II error level of the corresponding test is 0.2 when calculated.

[0069] Calculation formula:

[0070]

[0071] Used for MARD% value calculation.

[0072] 5. Test flow chart:

[0073] See the flowchart Figure 1 and Table 1.

[0074] Table 1

[0075]

[0076] 6. Experimental plan table: A prospective, multi-center, single-group target value designed clinical trial with a sample size of 100 (Table 2)

[0077] Table 2

[0078]

[0079]

Key technologies

[0080] 1. Mean absolute relative error (MARD%) evaluation

[0081] MARD (Mean Absolute Relative Difference) is to use two methods to measure the same set of samples, obtain the difference level between multiple pairs of data, and then take the average. In this evaluation indicator, MARD is the average absolute relative error between the detection value of the wearable integrated self-powered hs-cTnT detection system and the venous hs-cTnT value.

[0082] •MARD=Avg[{abs(method A - method B) / method B} x100%]

[0083] •The smaller the MARD value, the closer the reading of the wearable integrated self-powered hs-cTnT detection system is to the venous hs-cTnT value and the higher the accuracy.

[0084] 2. Reference value 20% consistency rate

[0085] The hs-cTnT value measured by the wearable integrated self-powered hs-cTnT detection system was compared with the venous hs-cTnT value measured by the Roche detector (i.e., the reference value) to reflect the overall consistency of the wearable integrated self-powered hs-cTnT detection system value relative to the venous hs-cTnT value.

[0086] A=(wearable integrated self-powered hs-cTnT detection system value - the number of pairs with venous blood hs-cTnT value deviation within ±20% / total number of pairs with full concentration) × 100%.

[0087] The higher the consistency rate, the closer the reading of the wearable integrated self-powered hs-cTnT detection system is to the venous blood hs-cTnT value, and the higher the accuracy.

[0088] 3. Error Grid

[0089] The measurement results of the test method and the measurement results of the comparable method are evaluated in the form of a scatter plot, thereby visually displaying the possibility of harm to patients caused by the test error ( Figure 2 ).

[0090] X represents the “true value” of the measurement, which in this case is the venous hs-cTnT value.

[0091] Y represents the measured value, that is, the value of the wearable integrated self-powered hs-cTnT detection system. The difference between Y and X may have a certain impact on the clinical results.

[0092] • Zone A: Both values ​​produce the same or nearly the same clinical decision, and the measurement error of Y has no clinical impact

[0093] • Zone B: Y and X lead to slightly different clinical decisions, but the likelihood of causing harm to the patient is low

[0094] • Zone C: When Y leads to a clinical decision that is completely different from X and may cause great danger to the patient

[0095] (If necessary, higher risk levels may be added, such as D and E zones. D zone may represent permanent injury, E zone may represent death, etc.)

[0096] 4. Index Analysis – Clarke Error Grid

[0097] Calculate the number of data points that fall in each area and the percentage they occupy, as well as the sum of area A and area B.

[0098] •Zone A is clinically absolutely accurate;

[0099] •Zone B is clinically acceptable and accurate;

[0100] •The remaining areas C, D, and E will cause clinical operation errors to varying degrees.

[0101] 5. Indicator Analysis – Consensus Error Grid (CEG)

[0102] Calculate the number of data points that fall in each area and the percentage they occupy, as well as the sum of area A and area B.

[0103] •Area A has no effect on clinical outcomes;

[0104] • Zone B: little or no effect on clinical outcomes;

[0105] •Zone C is likely to affect clinical outcomes;

[0106] •The remaining D and E areas have a greater impact on clinical outcomes or may cause danger.

[0107] 6. Index analysis – consistency of reference value Bland-Altman bias analysis

[0108] The consistency limit LoA (mean ± 1.96 standard deviation) was calculated using the values ​​determined by the two measurement methods, and a Bland-Alman plot was made to observe and analyze the bias distribution of each point.

[0109] 3. Multimodal validation of the clinical value of FWSAT in the diagnosis of AMI

[0110]

Experimental methods

[0111] 1. Multicenter cohort population establishment: 300 patients with suspected AMI were enrolled in six centers to form three cohorts, with 50 patients in each center. The development cohort, the external biochemical validation cohort, and the external phenotypic validation cohort were composed of patients from three, one, and two centers, respectively. The subjects included in the study had a detailed medical history, physical examination, 12-lead electrocardiogram, and laboratory tests recorded. All subjects underwent echocardiography and coronary angiography evaluation. After enrollment, the subjects wore one FWSAT on each arm, and venous blood was collected from the hospital on the first day and one day from the second to the 14th day. Venous blood was collected every 30 minutes for 7 consecutive hours. Venous blood hs-cTnT was measured by Roche analyzer. The sensor detection value was compared with the analyzer hs-cTnT value. Discharged patients were followed up for 1 month through the patient's clinical information system to check for cardiac symptoms or adverse clinical events (death due to cardiac causes and readmission).

[0112] 2. External biochemical validation: sensor data was used as input to distinguish patients with elevated and non-elevated hs-cTnT levels. The development cohort data was incorporated into the final model development and internal evaluation using a cross-validation approach, and the external biochemical validation cohort was used to evaluate the performance and generalizability of the development model. This analysis was used to train the Transformer machine learning model using data from 3 sites and to perform external model testing on the external biochemical validation cohort.

[0113] 3. External phenotypic validation by echocardiogram: External phenotypic validation was performed using echocardiogram (at 2 centers). The data extracted from the echocardiogram reports included left ventricular ejection fraction and regional wall motion abnormalities. Using the data from two external test sites, a Logistic regression model was used to analyze the relationship between the sensor data and the echocardiogram data.

[0114] 4. External phenotypic validation by coronary angiography: External phenotypic validation was performed using the results of coronary angiography (at 2 centers). The data of the coronary angiography results included the visible degree of stenosis and the type of intervention (such as balloon angioplasty and / or stent implantation). During invasive coronary angiography, the presence of significant stenosis in ≥1 major coronary artery trunk (left main, left anterior descending, left circumflex, and right coronary arteries), defined as a ≥90% stenosis of the lumen diameter. Using the data from two external test sites, a Logistic regression model was used to analyze the relationship between the sensor data and the coronary angiography (the process is shown in Figure 4 ).

[0115]

Key Technologies

[0116] A cross-modal masked autoencoder cloud pre-training method was proposed. By self-supervised learning of the semantic associations of non-masked features in each modality, the representation and generalization ability of E(·) was improved. Specifically, different modality signals V, A, H were randomly masked according to the ratio a (0 < a < 1) to be divided into regular masked blocks MV, MA, MH and non-masked blocks SV, SA, SH; {SV, SA, SH} were transformed into embedding vectors with the same dimension, and corresponding position encoding and modality type encoding were added, and then input into the Transformer block to extract features {EV, EA, EH}; after the encoder, {FV, FA, FH} were input into D(·) to perform local reconstruction on the masked part, and the mean squared error (MAE) function between the reconstructed data and the original data was used for optimization.

[0117] IV. Building a "hs-cTnT" one-network based on a flexible wearable integrated self-powered sensor

[0118] Based on the flexible wearable integrated self-powered hs-cTnT sensor, a "hs-cTnT" one-network was built with the patient and the community as the centers respectively.

[0119] 1. With the patient as the center, based on the flexible wearable integrated self-powered sensor, a "hs-cTnT" one-network was built. After AMI patients are discharged, they wear the integrated self-powered hs-cTnT sensor and upload the real-time signals to the cloud. Through background monitoring, the hs-cTnT status of the patients can be dynamically monitored, and critical values can be timely reminded and processed, and medical intervention can be carried out as early as possible.

[0120] 2. With the community as the center and flexible wearable integrated self-powered sensors as the basis, we will build a "hs-cTnT" network. For people at high risk of cardiovascular disease in the community, they can wear integrated self-powered hs-cTnT sensors and upload real-time signals to the cloud. Through background monitoring, the patient's hs-cTnT status can be dynamically monitored, and critical values ​​can be promptly reminded and processed, so that medical intervention can be given as soon as possible.

[0121]

Experimental methods

[0122] The diagnostic criteria for the cardiovascular high-risk population include any of the following: (1) aged over 69 years; (2) hypertensive patients; (3) diabetic patients; (4) patients with a history of cardiovascular and cerebrovascular diseases; (5) others who need hs-cTnT monitoring.

[0123]

Key technologies

[0124] Data transmission between sensors and cloud servers.

[0125] Phase 1: The sensor communicates with the mobile phone via Bluetooth and transmits the collected sensor data over a short distance with extremely low power consumption.

[0126] The steps of data transmission are:

[0127] (1) Establishing a connection: Before Bluetooth transmission, a Bluetooth connection needs to be established. This process is called pairing, in which the two Bluetooth devices will perform authentication and encryption operations to ensure data security. After successful pairing, a virtual communication link is established between the devices;

[0128] (2) Data encoding: converting raw data into a specific binary encoding format so that it can be accurately transmitted and reconstructed during transmission;

[0129] (3) Frame encapsulation: data is divided into smaller packets (frames), each of which usually contains some control information for error detection and correction, such as checksum or redundant coding;

[0130] (4) Modulation / demodulation: In wireless transmission, the sender uses modulation technology to convert digital signals into analog signals for transmission through the wireless channel. The receiver uses demodulation technology to convert the analog signals back into digital signals;

[0131] (5) Transmission medium: Bluetooth technology uses frequency division multiple access technology to share the 2.4 GHz frequency band, divides the frequency band into 79 channels, and uses fast switching to transmit between these channels to avoid interference with other Bluetooth devices;

[0132] (6) Error detection and correction: The receiver usually performs error detection and correction on the received data to ensure the integrity and accuracy of the data. Common technologies include checksum, cyclic redundancy check, etc.

[0133] (7) Data decoding: The receiver decodes the received data and restores it to its original data format.

[0134] The second stage: The mobile phone and the cloud server conduct 5G wireless communication, and the collected sensor data is transmitted through the 5G link with low latency, high reliability and large capacity.

[0135] (1) Initial connection between user equipment and base station: The user equipment initiates a communication request through a 5G modem, using 5G NR technology (New Radio technology) to achieve high-speed data transmission and low latency. The signal is sent to the nearest base station via millimeter wave (mmWave) or sub-6 GHz frequency band. The base station uses beamforming technology to concentrate signal energy, improve reception efficiency, and reduce interference. This step is the starting point of 5G communication and establishes the initial connection between the user equipment and the network.

[0136] (2) Signal transmission and routing planning in the core network: The base station transmits the signal to the 5G core network. The core network adopts a service-based architecture (SBA) to provide high modularity and flexibility. Network slicing technology dynamically allocates resources according to service requirements to ensure the quality and performance of different services. The core network uses software-defined networking (SDN) technology to achieve efficient signal routing and transmit data quickly and accurately to the base station of the target user. This step is a key link to ensure data transmission efficiency and accuracy.

[0137] (3) High-quality signal reception: After the target base station receives the signal, it uses Multiple Input Multiple Output (MIMO) technology to improve data throughput, and uses Dynamic Spectrum Sharing (DSS) technology to flexibly share spectrum resources between 4G and 5G to optimize signal transmission. After the target user's 5G device receives the signal, it uses advanced decoding technologies such as Low-Density Parity-Check (LDPC) or Turbo coding to quickly and accurately decode the data. This step is the final link in achieving data exchange, ensuring that users can receive high-quality communication services.

[0138] (4) Network optimization and maintenance after communication: After communication, 5G devices and networks optimize resource usage through intelligent algorithms, such as Network Function Virtualization (NFV) and Dynamic Spectrum Sharing (DSS), to improve resource utilization. Artificial Intelligence (AI) and Machine Learning (ML) technologies are used to continuously optimize the network, predict network traffic patterns, and automatically adjust network configurations. Edge computing technology places data processing and storage tasks close to the data source to reduce latency. This step is the guarantee for the long-term stable operation of the 5G network and the provision of high-quality services.

[0139] 3.3 Feasibility Analysis

[0140] (1) The project has sufficient basis and the subject design is reasonable

[0141] Our research group has been engaged in the prevention, diagnosis and treatment of AMI for a long time, and has long used the results of venous hs-cTnT to guide the diagnosis and treatment of AMI. Our research group intends to use gold nanoparticles, cTnT aptamers and electrochemical sensors to construct a flexible, wearable, self-powered electrochemical method that can specifically detect hs-cTnT, so as to achieve continuous and dynamic monitoring of patients with chest pain, and provide more accurate laboratory basis for the diagnosis and treatment of AMI. Therefore, the project has sufficient basis and reasonable design.

[0142] (2) This topic has a solid foundation of preliminary work

[0143] The relevant preliminary experiments of this project have been carried out smoothly and achieved preliminary results. The value and mode of cTn in the differential diagnosis of AMI have been verified, and multi-center AMI cohort data have been constructed; gold nanoparticles, cTnT aptamers, and electrochemical sensors have been used to preliminarily construct an electrochemical method that can specifically detect hs-cTnT; wet spinning has been used to construct a two-dimensional Ti 3 C 2 The stretchable n-type thermoelectric MP fiber composed of TxMXene nanosheets and polyurethane PU can simultaneously achieve satisfactory electrical conductivity (σ), thermal conductivity (κ) and wearable stretchability. The previous foundation of this project combined with the latest international literature derived the hypothesis of this project, so this project is theoretically feasible.

[0144] (3) This project is highly technically feasible

[0145] The applicant has accumulated technology through the molecular biology research of AMI with the support of four National Natural Science Foundations in the early stage. The project team members have mastered the necessary experimental capabilities and technologies to implement this project. There are sufficient clinical cases to meet the sample requirements of the clinical part of this project. They have mastered the technologies of sensors, self-function, data transmission and clinical trials. This project is technically feasible.

[0146] (4) This topic has superior research strength

[0147] This research group is composed of the AMI clinical research team (Department of Cardiovascular Medicine, the First Affiliated Hospital of Nanjing Medical University / Key discipline of the Ministry of Education and key specialty of the National Industry and Health Commission), the multimodal big data team (School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications / Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing University of Posts and Telecommunications), the flexible electronics and sensor R&D team and the nanogenerator and self-driving system research team (School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications). The joint composition of professional and technical personnel, professional complementarity, and medical and engineering crossover have laid a solid foundation for the implementation of this project.

[0148] Features and innovations of this project;

[0149] (1) hs-cTn can be continuously and dynamically monitored.

[0150] The current "0h / 1h diagnostic process" of hs-cTn monitoring does not have a sufficiently high negative predictive value in the diagnosis of AMI. The hs-cTn content is dynamic, and continuous and dynamic monitoring of hs-cTn is of particular clinical significance for the diagnosis and risk stratification of AMI. Currently, there is no flexible, wearable, integrated hs-cTnT detection sensor in clinical application. This research project can achieve flexible, wearable, continuous and dynamic monitoring of hs-cTn.

[0151] (2) The sensor developed in this project is a self-powered sensor based on the principle of thermoelectric power generation and driven by a temperature gradient.

[0152] At present, most flexible wearable sensors need to be equipped with an additional energy supply system, which inevitably increases the probability of system failure and affects the wearing comfort and aesthetics. 3 C 2 The stretchable n-type thermoelectric MP fiber made of TxMXene nanosheets and polyurethane PU has excellent electrical conductivity (σ), thermal conductivity (κ) and wearable stretchability. It can collect low-level thermal energy from the wearer's body and apply it to the driving of biosensors. This project develops a flexible sensor with integrated self-powered energy.

[0153] (3) With the help of this project, all-round dynamic management of AMI patients can be achieved.

[0154] AMI is one of the leading causes of death worldwide. With the help of the flexible wearable integrated hs-cTnT detection sensor developed in this project, dynamic management of AMI patients can be achieved from multiple levels such as hospitals (outpatient clinics, emergency departments, wards), families, schools, institutions and communities. Build a "hs-cTnT One Network" platform to collect, monitor and analyze the hs-cTnT data of people who use flexible wearable integrated hs-cTnT detection sensors to collect data and successfully upload it to the ECG cloud platform, so as to intervene in high-risk groups in advance.

[0155] It should be understood that the present invention is described by way of example only and can be modified within the scope and spirit of the present invention. The preferred specific embodiments of the present invention are described in detail above. It should be understood that ordinary skills in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, all technical solutions that can be obtained by technicians in the technical field through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. An electrochemical sensor capable of real-time monitoring of hs-cTnT data, characterized in that: It comprises a monitoring electrode and a masking agent; the monitoring electrode takes a laser-induced graphene electrode as a substrate, and a cTnT aptamer is fixed on the surface; the masking agent is used for masking the electrode surface.

2. The electrochemical sensor capable of real-time monitoring of hs-cTnT data according to claim 1, characterized in that: The laser induced graphene electrode is a laser induced graphene electrode constructed on a polyimide film by using a laser engraving technology.

3. The electrochemical sensor capable of real-time monitoring of hs-cTnT data according to claim 2, characterized in that: The laser-induced graphene electrode surface is modified with a cTnT aptamer by depositing noble metal nanoparticles on the surface of the laser-induced graphene electrode to modify the cTnT aptamer with the noble metal nanoparticles.

4. The electrochemical sensor capable of real-time monitoring of hs-cTnT data according to claim 3, characterized in that: The noble metal is Au or Ag.

5. The electrochemical sensor capable of real-time monitoring of hs-cTnT data according to claim 1, characterized in that: The masking agent is 6-mercapto-1-hexanol or bovine serum albumin.

6. A method for preparing an electrochemical sensor capable of real-time monitoring of hs-cTnT data according to any one of claims 1 to 5, characterized in that The following steps are involved: (1) Constructing laser-induced graphene electrodes based on laser engraving technology. The parameters of the laser cutting machine are: speed 6.8%-50%, power 5.5%-25%, and engraving the electrode shape on the polyimide film. The electrode shape is a rod electrode or a three-electrode; (2) Using an electrochemical workstation to provide power, electrochemically deposit noble metal nanoparticles on the surface of the laser-induced graphene electrode to construct a laser-induced graphene / noble metal electrode; the electrochemical deposition reaction process is as follows: immerse the laser-induced graphene electrode prepared in (1) in a mixed solution of 0.1~0.2mM sodium sulfate and 1~2mM chloroauric acid, apply a deposition potential of -0.2~-0.4V to electro-deposit nanogold particles, and the deposition time is 400~600s; (3) Self-assembling nucleic acid aptamers on the surface of laser-induced graphene / noble metal electrode, the specific process is as follows: dripping aptamer solution with a concentration of 2-10uM and a volume of 10-15uL on the surface of laser-induced graphene / noble metal electrode prepared in step (2), covering the electrode cap, incubating at room temperature for 12-24h to form a stable noble metal-S chemical bond, and fixing the cTnT aptamer on the surface of laser-induced graphene / noble metal electrode; (4) Add 6-mercapto-1-hexanol solution with a concentration of 5 to 10 uM and a volume of 10 to 15 uL to the surface of the electrode prepared in step (3), cover the electrode cap, and incubate at room temperature for 1 to 3 hours to block the active sites on the electrode surface that are not fixed by the aptamer.

7. A flexible wearable integrated self-powered cTnT monitoring device, characterized in that include: The electrochemical sensor, self-powered system and data transmission unit according to any one of claims 1 to 5; The electrochemical sensor is used to detect the hs-cTnT data of the wearer's fingertips in real time; The self-powered system is used to collect low-level heat energy from the wearer's body and convert it into electrical energy for storage to power the sensor; The data transmission unit is used to transmit the patient's hs-cTnT data obtained in real time to an external platform for analysis and evaluation.

8. The flexible wearable integrated self-powered cTnT monitoring device according to claim 7 is characterized in that: The self-powered system adopts a polyvinyl alcohol-based thermoelectric composite hydrogel based on a three-dimensional interconnected porous network.

9. The flexible wearable integrated self-powered cTnT monitoring device according to claim 8, characterized in that: The polyvinyl alcohol-based thermoelectric composite hydrogel based on a three-dimensional interconnected porous network is prepared by the following steps: (1) Prepare tellurium nanowires by a hydrothermal reaction method. Dissolve polyvinyl pyrrolidone in ultrapure water and then add sodium tellurite. Then add a precursor solution formed by hydrazine hydrate and ammonia monohydrate. Perform a hydrothermal reaction at 180-200°C for 10-12 hours. Wash the obtained product with ultrapure water. Finally, dry the product in a vacuum oven to obtain tellurium nanowires. (2) PVA and polyethylene dioxythiophene-polystyrene sulfonate aqueous solution are mixed in a three-necked flask, and then placed in an oil bath at 80-90°C and stirred continuously. During the stirring process, the tellurium nanowires prepared in step (1) are slowly added, and then the prepolymer solution is frozen at -15--20°C for 1 hour to solidify. The solid is placed in a sealed culture dish and allowed to stand at room temperature for 10 hours. The freeze-thaw cycle is repeated 5-10 times to obtain a polyvinyl alcohol-based thermoelectric composite hydrogel.

10. The flexible wearable integrated self-powered cTnT monitoring device according to claim 7, characterized in that: The data transmission unit uses Bluetooth technology to send data to the external platform.

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