Fully Automated High-Efficiency Capillary Electrophoresis Clinical Biochemical Abnormal Protein Typing Detection System

Abstract

This invention relates to the field of clinical biochemical testing technology, specifically a fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system. It includes a fully automated sample processing module, an intelligent capillary separation module, a composite signal detection module, a data processing and control module, and a result output module. These modules work together to automate the entire process from sample loading to typing report output. By employing bioaffinity modification-microfluidic coupling pretreatment technology, the system addresses sample matrix interference. An innovative gradient-modified capillary column design, combined with an adaptive buffer mixing unit, improves the efficiency and resolution of abnormal protein separation. Furthermore, by integrating Raman enhancement spectroscopy and fluorescence detection technology, a dual-signal complementary detection system is constructed, enhancing detection sensitivity and specificity. The system requires no manual intervention, has a short detection cycle, and provides accurate typing, effectively identifying abnormal immunoglobulins, protein fragments, and other target components in serum, urine, and other samples.

Description

Technical Field

[0001] This invention relates to the field of clinical biochemical testing technology, specifically a fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing system. Background Technology

[0002] Capillary electrophoresis, with its advantages of high separation efficiency, small sample volume, and fast analysis speed, has been widely used in clinical biochemical testing, especially in the detection of abnormal proteins. Abnormal proteins refer to proteins with abnormal structure, function, or expression levels produced by the body under pathological conditions. Their types, levels, and typing results are closely related to the occurrence and development of various diseases. For example, the serum of patients with multiple myeloma will show characteristic M proteins, and the urine of patients with nephrotic syndrome will show large amounts of albumin and other abnormal protein components. Therefore, accurate abnormal protein typing is of great clinical significance for the early diagnosis, differential diagnosis, and prognostic assessment of diseases.

[0003] While existing capillary electrophoresis systems for detecting abnormal proteins have achieved partial automation, several technical bottlenecks remain in practical clinical applications, hindering the development of efficient, accurate, and fully automated detection processes. Firstly, the sample pretreatment stage is significantly inadequate. Clinical samples (such as serum and urine) have complex matrices containing numerous interfering components such as proteins, lipids, and carbohydrates. Existing systems often employ simple dilution or filtration methods, failing to effectively remove these interfering components and resulting in poor enrichment of the target abnormal protein. This leads to peak overlap and baseline drift issues during subsequent separation and detection, affecting genotyping accuracy. Secondly, some systems require manual sample pretreatment, increasing operator workload, introducing human error, and failing to achieve fully automated detection, thus reducing efficiency.

[0004] Secondly, the separation performance of capillary separation modules needs improvement. Existing capillary columns mostly employ a single coating modification, resulting in limited selectivity for separating abnormal proteins with different charges and molecular weights. This is particularly true for structurally similar abnormal protein components (such as fragments of different immunoglobulin subtypes), making effective separation difficult and leading to low typing resolution. Furthermore, buffer systems are often fixed ratios, unable to be adaptively adjusted according to different sample types (such as serum and urine) and the specific types of target abnormal proteins, further limiting separation efficiency. In addition, the cleaning and regeneration processes for capillary columns are inadequate, leading to rapid column efficiency decay after long-term use and increasing detection costs.

[0005] Secondly, the sensitivity and specificity of the detection signals are insufficient. Existing systems mostly employ single fluorescence detection or ultraviolet detection techniques. While fluorescence detection has high sensitivity, it is easily interfered with by the fluorescence of the sample matrix, leading to false positive results. Ultraviolet detection has poor specificity and limited ability to detect low-concentration abnormal proteins, making it difficult to meet the detection needs of low-concentration abnormal proteins in early disease diagnosis. Furthermore, the signal acquisition and processing algorithms are relatively simple, failing to effectively distinguish between target signals and interference signals, further affecting the accuracy of the detection results.

[0006] Furthermore, the existing systems have low levels of automation and poor coordination between modules (sample processing, separation, detection, and data processing), resulting in issues such as mismatched detection timing and data transmission delays. This leads to long detection cycles, typically exceeding 60 minutes for a single sample, making it difficult to meet the rapid detection needs of large batches of clinical samples. Additionally, some systems have limited data processing capabilities, only outputting simple electrophoresis patterns and failing to automatically perform genotyping and clinical alerts. This necessitates manual analysis by operators, increasing the clinical workload and increasing the risk of result bias due to human judgment.

[0007] To address the aforementioned issues, several improved solutions have emerged in existing technologies. For example, immunoaffinity chromatography is used for sample pretreatment, which improves the enrichment of target proteins, but it is complex, costly, and difficult to automate with capillary electrophoresis systems. Some solutions employ novel coated capillary columns to enhance separation efficiency, but single modification methods cannot simultaneously meet the separation requirements of multiple abnormal proteins. Other solutions utilize dual-signal detection technology, but the signal fusion and complementation algorithms are imperfect, failing to fully leverage the advantages of dual-detection technology. Therefore, developing a fully automated capillary electrophoresis abnormal protein typing detection system with high separation efficiency, strong detection sensitivity and specificity, and accurate typing has become an urgent need in the field of clinical biochemical testing. Summary of the Invention

[0008] To address the shortcomings of existing capillary electrophoresis abnormal protein typing detection systems, such as poor sample pretreatment, low separation efficiency, insufficient detection sensitivity and specificity, low automation integration, and long detection cycles, this paper presents a fully automated and efficient capillary electrophoresis clinical biochemical abnormal protein typing detection system. This system achieves full automation of sample processing, separation, detection, and data processing through multi-module collaborative design and cross-disciplinary technology integration. It improves the resolution and accuracy of abnormal protein separation, shortens the detection cycle, reduces detection costs and human error, and meets the needs of efficient and accurate detection of large batches of clinical samples.

[0009] The technical solution adopted by this invention to solve its technical problem is: a fully automated and efficient capillary electrophoresis clinical biochemical abnormal protein typing detection system, comprising: a fully automated sample processing module, which integrates a bioaffinity-modified microfluidic chip and a constant-temperature incubation unit. Specific affinity ligands are immobilized within the microfluidic chip, enabling the removal of impurity proteins and enrichment of target abnormal proteins in the sample. The constant-temperature incubation unit has a temperature adjustment range of 35-39℃ and is linked with the sample delivery channel to achieve continuous pretreatment; and an intelligent capillary separation module, comprising a gradient-modified capillary column, an adaptive buffer ratio unit, and a pressure control component. The inner wall of the gradient-modified capillary column is modified with an amino-carboxyl composite, the column length is 30-50 cm, and the inner diameter is 50-75 μm. The buffer solution preparation unit automatically adjusts the buffer pH and additive concentration according to the sample type, while the pressure control component achieves precise closed-loop control of injection and separation pressures. The composite signal detection module integrates a Raman enhancement detection unit and a fluorescence detection unit. The Raman enhancement unit uses gold nanoparticles to modify the detection window, and the fluorescence detection unit is equipped with a switchable excitation wavelength light source. The two units simultaneously acquire signals and perform complementary verification. The data processing and control module has a built-in abnormal protein typing algorithm, which can perform fusion analysis, baseline correction, and peak identification on the dual detection signals. It also controls the operation sequence of each module to achieve full-process automation. The result output module can generate typing maps, quantitative results, and clinical prompt reports, and supports data storage and traceability.

[0010] Specifically, in the bioaffinity-modified microfluidic chip of the fully automated sample processing module, the specific affinity ligand is modified dextran or recombinant protein A / G, and the ligand fixation density is 1-5 mg / cm³. 2 The chip channel width is 100-200μm and the depth is 50-100μm.

[0011] Specifically, the adaptive buffer mixing unit of the intelligent capillary separation module has at least three basic buffer solutions and two additives. The pH adjustment range of the buffer solution is 3.5-9.0, and the additives are sodium dodecyl sulfate or β-cyclodextrin with a concentration adjustment range of 0.01-0.1 mol / L.

[0012] Specifically, in the composite signal detection module, the excitation wavelength of the Raman enhancement detection unit is 785nm, and the excitation wavelength of the fluorescence detection unit can be switched between 488nm, 532nm, and 633nm, with a dual-unit detection window overlap of ≥95%.

[0013] Specifically, the abnormal protein typing algorithm of the data processing and control module uses wavelet transform for baseline correction and combines it with support vector machine algorithm to achieve peak identification and typing, with a typing accuracy of ≥98%.

[0014] Specifically, the fully automated sample processing module also integrates a sample dilution and mixing unit, with the dilution factor automatically adjustable from 1 to 10 times, the mixing speed at 500-1000 r / min, and the mixing time at 10-30 s.

[0015] Specifically, the intelligent capillary separation module also includes a capillary column cleaning and regeneration unit, which can automatically clean the column sequentially with acid, alkali, pure water and buffer solution, and the regeneration cycle is once for every 5-10 samples tested.

[0016] Specifically, the composite signal detection module is also equipped with a signal amplification unit, which uses immune nanoprobes to assist in signal enhancement, with a probe particle size of 50-100nm.

[0017] Specifically, the data processing and control module supports interface with the hospital's LIS system, enabling real-time uploading and sharing of test data.

[0018] Specifically, the overall detection cycle of the system is ≤40min / sample, and the detection limit for abnormal proteins is ≤0.1mg / dL.

[0019] The beneficial effects of this invention are: (1) The fully automated and efficient capillary electrophoresis clinical biochemical abnormal protein typing detection system of the present invention is fully automated and integrated. Through the linkage control of each module, it realizes the absence of human intervention from sample loading to result output, significantly reduces human error, improves detection efficiency, and the single sample detection cycle is ≤40min, which meets the clinical batch sample detection needs.

[0020] (2) The fully automated high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system of the present invention has excellent sample pretreatment effect. The bio-affinity modified microfluidic chip combined with constant temperature incubation technology can achieve efficient enrichment of target abnormal proteins and removal of impurity proteins, thereby improving the accuracy of subsequent separation and detection.

[0021] (3) The fully automated high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system of the present invention has high separation resolution. The gradient modified capillary column and the adaptive buffer ratio unit work together to match the optimal separation conditions according to the sample characteristics, realize the effective separation of structurally similar abnormal proteins, and significantly improve the typing accuracy.

[0022] (4) The fully automated high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system described in this invention has both detection sensitivity and specificity. The composite signal detection system complements Raman enhancement and fluorescence detection, and combines immune nanoprobe signal amplification to effectively reduce interference. The detection limit is as low as 0.1 mg / dL, and the typing accuracy is high.

[0023] (5) The fully automated high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system of the present invention has a long service life and low cost. The automatic cleaning and regeneration unit of the capillary column can maintain column efficiency and extend the service life of the capillary. At the same time, the automated operation reduces reagent waste and labor costs, and is easy to promote and apply in clinical practice. Attached Figure Description

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] Figure 1 This is an architecture diagram of the fully automated and efficient capillary electrophoresis clinical biochemical abnormal protein typing detection system provided by the present invention. Detailed Implementation

[0026] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0027] like Figure 1 As shown, the fully automated and efficient capillary electrophoresis clinical biochemical abnormal protein typing detection system of the present invention includes a fully automated sample processing module, an intelligent capillary separation module, a composite signal detection module, a data processing and control module, and a result output module. Each module is connected in conjunction with the circuit and data line to achieve closed-loop operation of the entire process.

[0028] The fully automated sample processing module integrates a bioaffinity-modified microfluidic chip, a constant-temperature incubation unit, a sample dilution and mixing unit, and a sample transfer unit. The bioaffinity-modified microfluidic chip is the core component. Specific affinity ligands (modified dextran or recombinant protein A / G) are immobilized within the chip channels. These ligands specifically bind to the target abnormal protein through affinity interactions, while simultaneously removing interfering components such as impurities and lipids, achieving enrichment and purification of the target protein. The ligands are covalently fixed to the inner wall of the chip channels, and the immobilization density can be adjusted according to detection requirements to ensure enrichment efficiency and specificity. The constant-temperature incubation unit is integrated with the microfluidic chip, with a temperature adjustment range of 35-39℃, simulating the human physiological environment to maintain the activity of the target protein and promote affinity reactions. The incubation time can be automatically adjusted according to sample type (1-5 min). The sample dilution and mixing unit automatically adjusts the dilution factor (1-10 times) according to the sample concentration. Sample mixing is achieved through magnetic stirring, and the mixing speed and time can be precisely controlled to avoid detection deviations caused by uneven sample concentration. The sample transfer unit uses a micro peristaltic pump and a solenoid valve in linkage control to accurately deliver the processed sample to the intelligent capillary separation module, realizing the automated connection between sample processing and separation.

[0029] The intelligent capillary separation module includes a gradient-modified capillary column, an adaptive buffer mixing unit, a pressure control component, and a capillary column cleaning and regeneration unit. The gradient-modified capillary column utilizes an amino-carboxyl composite modification process, creating a gradient charge distribution on the inner wall. This allows for efficient separation based on differences in the charge properties and molecular weight of abnormal proteins, making it particularly suitable for separating structurally similar abnormal protein subtypes. The column length and inner diameter can be selected according to detection requirements, with core parameters ranging from 30-50 cm in length and 50-75 μm in inner diameter, balancing separation efficiency and detection speed. The adaptive buffer mixing unit incorporates three basic buffers (citric acid buffer, Tris-HCl buffer, and phosphate buffer) and two additives (sodium dodecyl sulfate and β-cyclodextrin). A high-precision metering pump and mixing chamber automatically adjust the buffer pH (3.5-9.0) and additive concentration (0.01-0.1 mol / L), matching the optimal buffer system based on sample type (serum, urine) and the target abnormal protein. The pressure control component employs a precision pressure sensor and a closed-loop control system to achieve precise control of the injection pressure (0.1-0.5 MPa) and separation pressure (0.05-0.3 MPa), avoiding peak distortion caused by pressure fluctuations. The capillary column cleaning and regeneration unit can automatically clean the column sequentially with acid (0.1 mol / L hydrochloric acid), alkali (0.1 mol / L sodium hydroxide), pure water, and buffer solution. The regeneration cycle can be automatically set according to the number of samples tested (5-10 samples / cycle), maintaining capillary column efficiency and extending its service life.

[0030] The composite signal detection module integrates a Raman enhancement detection unit, a fluorescence detection unit, a signal amplification unit, and a detection window calibration unit. The Raman enhancement detection unit uses gold nanoparticles to modify the detection window. These gold nanoparticles generate a surface-enhanced Raman effect, significantly increasing the Raman signal intensity of the target protein. The excitation wavelength is selected as 785nm near-infrared light to reduce fluorescence interference from the sample matrix. The fluorescence detection unit is equipped with a switchable excitation wavelength light source (488nm, 532nm, 633nm), allowing selection of the optimal excitation wavelength based on the fluorescence labeling characteristics of the target abnormal protein, thus improving fluorescence detection sensitivity. The dual detection units simultaneously acquire signals, enabling complementary verification of Raman and fluorescence signals. The Raman signal is used to eliminate matrix interference and improve specificity, while the fluorescence signal is used to improve sensitivity. Fusion analysis of both effectively reduces false positive and false negative rates. The signal amplification unit uses immunoassay nanoprobes for enhancement. The probes consist of nanocarriers (silica nanospheres), specific antibodies, and signal molecules, which can specifically bind to the target abnormal protein, further amplifying the detection signal and reducing the detection limit to 0.1 mg / dL. The detection window calibration unit uses laser positioning technology to achieve precise alignment of the detection windows of the dual detection units, with an overlap of ≥95%, ensuring the consistency of signal acquisition.

[0031] Data Processing and Control Module: This module includes a built-in abnormal protein typing algorithm, a timing control unit, and a data storage and transmission unit. The abnormal protein typing algorithm uses wavelet transform for baseline correction, effectively removing baseline drift interference. Combined with a support vector machine algorithm, it achieves automatic identification, qualitative and quantitative analysis of electrophoresis peaks, accurately identifying various abnormal protein components such as M protein, immunoglobulin fragments, and glycosylated abnormal proteins, with a typing accuracy of ≥98%. The timing control unit uses a PLC controller to coordinate the operation of each module, achieving full automation of the entire process from sample loading, pretreatment, injection, separation, detection, data processing, and result output, without manual intervention. The data storage and transmission unit can store at least 100,000 test data sets, supports data traceability, and has LIS system integration capabilities, enabling real-time uploading and sharing of test data for convenient clinical case management.

[0032] The results output module includes a display unit, a printing unit, and an alarm unit. The display unit can display the detection process, electrophoresis patterns, genotyping results, and quantitative data in real time; the printing unit can generate a standardized detection report, including genotyping patterns, target protein types, concentrations, clinical prompts, and other information; the alarm unit automatically issues an audible and visual alarm when detection abnormalities occur (such as sample contamination, capillary column blockage, or signal abnormalities), and indicates the cause of the fault and provides handling suggestions.

[0033] Example 1: M protein typing detection in serum samples. This example uses the fully automated high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system described in this invention to perform M protein typing detection on serum samples from suspected multiple myeloma patients. The specific steps are as follows: 1. System Preparation: Start the fully automated high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system and perform a self-test, including the interoperability of each module, capillary column integrity, buffer level, and detection light source stability. After passing the self-test, install the gradient-modified capillary column (40cm long, 60μm inner diameter, amine-carboxyl complex modified) into the intelligent capillary separation module. The capillary column cleaning and regeneration unit automatically cleans the capillary column sequentially with 0.1mol / L hydrochloric acid, 0.1mol / L sodium hydroxide, pure water, and Tris-HCl buffer (pH 8.0), each for 2 minutes, to complete column activation. The adaptive buffer mixing unit automatically prepares the buffer system according to the serum sample detection requirements: based on Tris-HCl buffer, adjust the pH to 8.2, add 0.05mol / L sodium dodecyl sulfate as an additive, stir evenly, and then transfer it to the separation channel to equilibrate the capillary column for 10 minutes.

[0034] 2. Sample Processing: A 200 μL serum sample from a suspected multiple myeloma patient is placed into the system via the sample loading unit. The fully automated sample processing module automatically aspirates 50 μL of sample into the dilution and mixing unit. Based on the initial sample concentration (pre-determined through rapid system detection), the dilution factor is automatically adjusted to 5 times. After dilution with physiological saline, the sample is magnetically mixed at 800 rpm for 20 seconds. The mixed sample is then delivered to a bioaffinity-modified microfluidic chip, where recombinant protein A / G ligands are immobilized (immobilized density 3 mg / cm³). 2 The isothermal incubation unit adjusts the temperature to 37℃ and incubates for 3 minutes, allowing the ligands to specifically bind to immunoglobulins (including M protein) in the sample. Simultaneously, interfering components such as extraneous proteins and lipids are discharged through the chip's waste liquid channel. Subsequently, the chip automatically introduces elution buffer (0.02 mol / L glycine-hydrochloric acid buffer, pH 2.8) to elute the bound target protein. The elution buffer volume is 100 μL. The eluted sample is then transferred by the sample transfer unit via a micro-peristaltic pump to the inlet of the intelligent capillary separation module. The injection pressure is set to 0.3 MPa, and the injection time is 5 seconds, completing the sample injection.

[0035] 3. Separation and Detection: The data processing and control module initiates the separation program. The pressure control component adjusts the separation pressure to 0.2 MPa, maintaining a constant pressure for capillary electrophoresis separation. The separation temperature is controlled at 25℃ by the system's thermostat. Simultaneously, the composite signal detection module is activated. The detection window calibration unit calibrates the Raman detection window and fluorescence detection window using laser positioning to ensure an overlap of ≥95%. The Raman enhancement detection unit uses a 785 nm excitation wavelength to acquire the Raman signal of the target protein; the fluorescence detection unit uses a 532 nm excitation wavelength to simultaneously acquire the fluorescence signal. An immunoassay nanoprobe (silica nanosphere carrier, 80 nm in diameter, linked to an anti-human immunoglobulin antibody) is added to the elution buffer beforehand to specifically bind to the target M protein, amplifying the signal. The dual detection units acquire signals synchronously, and the signal data is transmitted to the data processing and control module in real time.

[0036] 4. Data Processing and Result Output: The data processing module uses a wavelet transform algorithm to perform baseline correction on the acquired dual signals, removing baseline drift and noise interference. Subsequently, a support vector machine algorithm is used to identify and analyze the electrophoretic peaks. Combining the characteristic peak positions, Raman spectral characteristics, and fluorescence intensity of the M protein, the type of the M protein (IgG type) is automatically determined, and its content is calculated to be 2.8 mg / dL. The result output module displays the electrophoresis pattern, typing results, and quantitative data. The printing unit generates a test report, clearly indicating the M protein type, content, and a clinical suggestion to "further confirm multiple myeloma by bone marrow aspiration." Simultaneously, the data is automatically uploaded to the hospital's LIS system.

[0037] 5. System Cleaning: After testing, the cleaning and regeneration unit of the intelligent capillary separation module automatically cleans and regenerates the capillary column, sequentially introducing acid, alkali, pure water, and buffer solution, each for 3 minutes, to remove residual sample and protein from the column. The system then enters standby mode, awaiting the next sample test. In this embodiment, the single-sample testing cycle is 35 minutes, the typing results are accurate, and verified by bone marrow aspiration, consistent with the clinical diagnosis, with no false positives or false negatives.

[0038] Example 2: Detection of albumin and abnormal protein fragments in urine samples. This example uses the system described in this invention to detect albumin and abnormal protein fragments in urine samples from patients with nephrotic syndrome. The specific steps are as follows: 1. System Preparation: Power on the system and complete the self-test. Select a gradient-modified capillary column with a length of 35 cm and an inner diameter of 50 μm. After installation, perform column cleaning and regeneration, following the same cleaning procedure as in Example 1. The adaptive buffer preparation unit automatically prepares the buffer system based on the characteristics of the urine sample: using phosphate buffer as a base, adjust the pH to 7.4, add 0.03 mol / L β-cyclodextrin as an additive, and equilibrate the capillary column for 8 min. The composite signal detection module calibrates the detection window, maintaining the Raman excitation wavelength at 785 nm, and the fluorescence detection unit selects an excitation wavelength of 488 nm to match the fluorescent labeling characteristics of albumin in the urine sample.

[0039] 2. Sample Processing: A 300 μL urine sample was collected from a patient with nephrotic syndrome. After loading, the fully automated sample processing module automatically aspirated 80 μL of the sample into the dilution unit. Due to the low concentration of the urine sample, the dilution factor was automatically adjusted to 2:1. Physiological saline was added for dilution, and the sample was mixed at 600 rpm for 15 seconds. The sample was then fed into a bioaffinity-modified microfluidic chip. The chip ligand was modified dextran (fixed density 2 mg / cm³). 2 The sample specifically binds to albumin and abnormal protein fragments. The temperature of the isothermal incubation unit is adjusted to 36℃ and incubated for 4 minutes to remove interfering components such as urea and electrolytes from the urine. A 0.01 mol / L Tris-HCl buffer (pH 7.5) is used as the elution buffer to elute the target protein. The elution volume is 120 μL. After elution, the sample is transferred to the injection port at an injection pressure of 0.25 MPa for 6 seconds.

[0040] 3. Separation and Detection: The separation pressure is set to 0.15 MPa and the separation temperature to 24℃. Capillary electrophoresis separation is initiated. The composite signal detection unit simultaneously acquires Raman and fluorescence signals. The Raman signal is used to eliminate fluorescence interference from urea in the urine, while the fluorescence signal is used to accurately detect the content of albumin and abnormal protein fragments. The immunonanoprobe uses bispecific antibodies against albumin and protein fragments to further enhance the signal intensity and ensure the effective detection of low concentrations of abnormal protein fragments.

[0041] 4. Data Processing and Result Output: The data processing module performs fusion analysis on the two signals. After baseline correction, it identifies the albumin peak and two abnormal protein fragment peaks (molecular weights of 25kDa and 35kDa, respectively). It automatically calculates the albumin content as 350mg / L and the abnormal protein fragment contents as 42mg / L and 38mg / L, respectively. The result output module generates a report containing electrophoresis patterns and quantitative results for each component. The clinical suggestion is "consistent with proteinuria characteristics of nephrotic syndrome; monitoring of renal function is recommended." The data is then uploaded to the LIS system.

[0042] 5. System cleaning: After the test is completed, the capillary column is cleaned and regenerated according to the standard procedure. The test cycle is 38 minutes. The typing results are compared with the results of high performance liquid chromatography. The consistency is ≥99%, which proves that this system has high accuracy in typing abnormal proteins in urine samples.

[0043] Example 3: Detection of Abnormally Glycated Proteins in Serum Samples. This example uses the system described in this invention to detect and classify abnormally glycosylated albumin in serum samples from patients with diabetic nephropathy. The specific steps are as follows: 1. System Preparation: Power on the system and ensure it passes self-test. Select a gradient-modified capillary column with a length of 45 cm and an inner diameter of 70 μm. After installation, clean and regenerate the column. Prepare the buffer system using the adaptive buffer mixing unit: Based on citrate-phosphate buffer, adjust the pH to 6.0, add 0.04 mol / L sodium dodecyl sulfate, and equilibrate the capillary column for 12 min. Calibrate the detection window of the composite signal detection module. Select a 633 nm excitation wavelength for the fluorescence detection unit, using a fluorescent labeling reagent compatible with glycosylated abnormal albumin. Ensure the Raman detection unit is functioning correctly, achieving dual-signal complementarity.

[0044] 2. Sample Processing: 250 μL of serum sample from a patient with diabetic nephropathy was loaded into the system. The automated sample processing module then aspirated 60 μL of the sample, adjusted the dilution factor to 3, and mixed it at 700 rpm for 25 seconds. The sample was then introduced into a bioaffinity-modified microfluidic chip. The chip ligand was modified dextran (fixed density 4 mg / cm³). 2 The sample specifically binds to albumin (including abnormally glycosylated albumin and normal albumin), and is incubated at 38°C for 3.5 min to remove other contaminating proteins and interfering components from the serum. A 0.03 mol / L acetate-sodium acetate buffer (pH 5.0) is used as the elution buffer to elute the target protein. The elution volume is 110 μL. After elution, the sample is transferred to the injection port at an injection pressure of 0.35 MPa for 4 s.

[0045] 3. Separation and Detection: The separation pressure is set to 0.22 MPa and the separation temperature to 26℃. Electrophoretic separation is initiated. The composite signal detection unit simultaneously acquires Raman and fluorescence signals. Due to the differences in Raman spectral characteristics between abnormally glycosylated albumin and normal albumin, the Raman detection unit can accurately distinguish between the two components. The fluorescence signal is used for quantitative analysis. The immunoassay nanoprobe specifically binds to abnormally glycosylated albumin, enhancing its signal intensity and ensuring the detection of low-content components.

[0046] 4. Data Processing and Result Output: The data processing module corrects the baseline using wavelet transform, identifies electrophoretic peaks using a support vector machine algorithm, and distinguishes between abnormally glycosylated albumin and normal albumin based on Raman spectral characteristics. The calculated abnormally glycosylated albumin content is 180 mg / L, accounting for 12.5% ​​of total albumin. The result output module displays the genotyping spectrum and quantitative data, prints a report indicating "Elevated abnormally glycosylated albumin content suggests a risk of diabetic nephropathy progression," and uploads the data to the LIS system.

[0047] 5. System cleaning: After the detection is completed, the capillary column is cleaned and regenerated. The detection cycle is 36 minutes. Compared with the mass spectrometry detection results, the typing accuracy and quantitative consistency are both ≥98.5%, proving that this system can effectively achieve accurate typing detection of abnormal glycosylation proteins.

[0048] Comparative Example 1 used a single-coated capillary column detection system. This comparative example used the same detection system as Example 1, except that the gradient-modified capillary column was replaced with a single-amine-modified capillary column. All other parameters and operating procedures were consistent with Example 1. M protein typing was performed on serum samples from the same suspected multiple myeloma patient. Results showed that the single-amine-modified capillary column had poor separation performance for M protein from other immunoglobulins, with overlapping electrophoretic peaks, significant baseline drift, and the typing algorithm failing to accurately identify the M protein type. The quantification error exceeded 15%, the detection cycle was extended to 55 minutes, and the column efficiency significantly decreased after using 5 samples, requiring column replacement and significantly increasing detection costs.

[0049] Control Example 2 used a single fluorescence detection system. This control example used the same detection system as Example 2, but the Raman enhancement detection unit was turned off, and only the single fluorescence detection unit was used. All other parameters and operating procedures were consistent with Example 2. Urine samples from the same patient with nephrotic syndrome were tested. The results showed that single fluorescence detection was severely affected by fluorescence interference from urea and impurities in the urine, resulting in false positive peaks. It could not accurately distinguish between albumin and abnormal protein fragments, with a detection limit of only 0.5 mg / dL. Low levels of abnormal protein fragments were not detected, and the typing accuracy was only 82%, which could not meet clinical testing needs.

[0050] The control example used the same detection system as Example 3, but the sample pretreatment was performed manually. This involved manually diluting the sample, manually performing immunoaffinity chromatography to enrich the target protein, and then adding the treated sample to the system for subsequent separation and detection. All other parameters and operating procedures were consistent with Example 3. The results showed that manual pretreatment was time-consuming, with a single sample pretreatment time of 20 minutes, extending the overall detection cycle to 60 minutes. Furthermore, manual operation introduced errors; the quantitative error for glycosylated abnormal albumin was 10%. The results showed poor consistency between samples processed by different operators, insufficient reproducibility, and an inability to achieve efficient detection of batch samples.

[0051] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system, characterized in that, include: The fully automated sample processing module integrates a bio-affinity-modified microfluidic chip and a constant-temperature incubation unit. The microfluidic chip is immobilized with specific affinity ligands, which can remove impurities and enrich target abnormal proteins in the sample. The constant-temperature incubation unit has a temperature adjustment range of 35-39℃ and is linked with the sample delivery channel to achieve continuous pretreatment. The intelligent capillary separation module includes a gradient-modified capillary column, an adaptive buffer mixing unit, and a pressure control component. The inner wall of the gradient-modified capillary column is modified with an amino-carboxyl composite. The column length is 30-50 cm and the inner diameter is 50-75 μm. The adaptive buffer mixing unit can automatically adjust the pH value of the buffer and the concentration of additives according to the sample type. The pressure control component realizes precise closed-loop control of the injection pressure and separation pressure. The composite signal detection module integrates a Raman enhancement detection unit and a fluorescence detection unit. The Raman enhancement unit uses gold nanoparticles to modify the detection window, and the fluorescence detection unit is equipped with a switchable excitation wavelength light source. The two units simultaneously acquire signals and perform complementary verification. The data processing and control module has a built-in abnormal protein typing algorithm, which can perform fusion analysis, baseline correction and peak identification on dual detection signals, and simultaneously control the operation sequence of each module to achieve full-process automation. The results output module can generate genotyping maps, quantitative results, and clinical prompts reports, and supports data storage and traceability.

2. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: In the bioaffinity-modified microfluidic chip of the fully automated sample processing module, the specific affinity ligand is modified dextran or recombinant protein A / G, and the ligand fixation density is 1-5 mg / cm³. 2 The chip channel width is 100-200μm and the depth is 50-100μm.

3. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The adaptive buffer mixing unit of the intelligent capillary separation module has at least three basic buffer solutions and two additives. The pH adjustment range of the buffer solution is 3.5-9.0, and the additives are sodium dodecyl sulfate or β-cyclodextrin with a concentration adjustment range of 0.01-0.1 mol / L.

4. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: In the composite signal detection module, the excitation wavelength of the Raman enhancement detection unit is 785nm, and the excitation wavelength of the fluorescence detection unit can be switched between 488nm, 532nm, and 633nm.

5. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The abnormal protein typing algorithm of the data processing and control module uses wavelet transform for baseline correction and combines it with support vector machine algorithm to achieve peak identification and typing.

6. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The fully automated sample processing module also integrates a sample dilution and mixing unit, which can automatically adjust the dilution factor to 1-10 times, the mixing speed to 500-1000 r / min, and the mixing time to 10-30 s.

7. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The intelligent capillary separation module also includes a capillary column cleaning and regeneration unit, which can automatically clean the column sequentially with acid, alkali, pure water and buffer solution, and the regeneration cycle is once for every 5-10 samples tested.

8. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The composite signal detection module is also equipped with a signal amplification unit, which uses immune nanoprobes to assist in signal enhancement, with a probe particle size of 50-100nm.

9. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The data processing and control module supports interface with the hospital's LIS system, enabling real-time uploading and sharing of test data.

10. The fully automated, high-efficiency capillary electrophoresis clinical biochemical abnormal protein typing detection system according to claim 1, characterized in that: The overall detection cycle of the system is ≤40min / sample, and the detection limit for abnormal proteins is ≤0.1mg / dL.

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