Method for detecting an unintended antibody

Abstract

The application relates to a detection method for unexpected antibodies, which comprises the following steps: S1, coating anti-human globulin on a detection card in advance, and sticking the detection card on a Blu-ray disc; S2, loading a whole blood sample and reagent red blood cells on the detection card, separating plasma in the whole blood sample on the detection card, combining unexpected antibodies in the separated plasma with the reagent red blood cells, causing the reagent red blood cells to agglomerate on the detection card, transferring the reagent red blood cells which have not agglomerated on the detection card to the Blu-ray disc, and forming a biomarker signal trace on the Blu-ray disc; S3, reading the biomarker signal trace on the Blu-ray disc by using a Blu-ray disc driver; and S4, processing data read by the Blu-ray disc driver by using an unexpected antibody identification model, so as to realize screening of the unexpected antibodies. Since the above technical scheme is adopted, the detection method for the unexpected antibodies is convenient to operate, has high detection efficiency, high accuracy and good portability.

Description

Technical Field

[0001] This invention relates to the field of medical testing technology, and specifically to a method for detecting accidental antibodies. Background Technology

[0002] The development of efficient and reliable immunoassay methods for identifying key disease biomarkers in complex biological samples is receiving widespread attention due to their high sensitivity and selectivity. Traditional immunosensors typically rely on the classic antibody-antigen recognition principle, usually requiring the antigen / antibody or ligand to be immobilized on the transducer surface. A detection antibody is then needed to convert the specific antigen-antibody binding event into a measurable electronic or optical signal reading. In these affinity-based assays, the accuracy of the analysis depends primarily on the highly specific interaction between the specific antigen and the target antibody through a dedicated molecular recognition domain. Although thousands of antigens are currently available on the market, many antigens targeting specific analytes, such as those used for blood typing and myasthenia gravis detection, remain scarce due to complex manufacturing processes and low reactivity efficiency.

[0003] Cell-based assays (CBA) ensure the pristine three-dimensional characteristics of cell membrane antigen structures and provide reliable and accurate analytical results. Therefore, CBA methods have become the gold standard for identifying biomarkers such as pre-transfusion diagnostics and neurological diseases, effectively compensating for the lack of commercially available membrane antigens. However, existing CBA methods fail to meet the requirements for sufficient sensitivity and high throughput in field deployment, primarily due to limitations in maintaining the long-term integrity of cell membranes and exploring the recognition mechanisms of multiple membrane antigens. For example, over 400 erythrocyte antigens result in a variety of unexpected IgG antibodies in plasma (such as Rh (D, C, E, c, e), MNS (M, N, S, s), etc.), which may trigger hemolytic reactions or lead to death during transfusion therapy.

[0004] Our team previously developed a paper-based detection method for rapid blood typing by capturing IgM antibodies using fresh red blood cells (RBCs). However, the presence of irregular antibodies still hinders rapid transfusion programs, resulting in inaccurate blood typing phenotypes. Insufficient binding between membrane antigens and irregular antibodies exhibiting characteristic dimers poses a significant obstacle to obtaining reliable results, greatly reducing the practicality of field deployment.

[0005] Beyond detection accuracy, the simultaneous identification of more than 20 irregular antibodies in rapid paper-based assays presents a significant challenge. While various spectroscopic techniques, such as Raman spectroscopy and terahertz spectroscopy (which are label-free), can simultaneously characterize multiple targets by probing intramolecular and intermolecular interactions, their use for portable multi-antibody identification is often criticized for requiring large equipment and complex substrate enhancement procedures. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a method for detecting accidental antibodies, so as to solve the technical problems of existing accidental antibody detection methods that do not meet the requirements of portability, have low detection accuracy and slow detection speed.

[0007] This invention is achieved through the following technical solution: A method for detecting accidental antibodies includes the following steps: S1. Pre-coat the test card with anti-human globulin and paste the test card onto the Blu-ray disc; S2. Load whole blood sample and reagent red blood cells onto the test card. The test card separates plasma from the whole blood sample. Accidental antibodies in the separated plasma bind to reagent red blood cells, causing the reagent red blood cells to agglutinate on the test card. The unagglutinated reagent red blood cells on the test card are transferred to the Blu-ray disc, forming a biomarker signal imprint on the Blu-ray disc. S3. Use a Blu-ray disc drive to read biomarker signal traces on a Blu-ray disc; S4. The data read from the Blu-ray disc drive is processed using an accidental antibody recognition model to screen for accidental antibodies.

[0008] Furthermore, the detection card includes a top shell layer, a reaction layer, and an electrostatic adsorption layer arranged sequentially from top to bottom. The top shell layer has sample wells for loading whole blood samples and multiple reagent wells for loading reagent red blood cells. The reaction layer includes a separation zone, multiple channels, multiple capture zones, and multiple signal zones. The separation zone is directly opposite the sample wells. The multiple capture zones and multiple signal zones correspond one-to-one with the multiple channels. The capture zones and the signal zones are located on the corresponding channels. The multiple capture zones are directly opposite the multiple reagent wells. Multiple signal wells are formed on the electrostatic adsorption layer. The multiple signal wells are directly opposite the multiple signal zones.

[0009] Furthermore, the method for manufacturing the detection card is as follows: S11. Cut out sample holes and multiple reagent holes on a PVC sticker with single-sided adhesive. S12. A separation zone, multiple channels, multiple capture zones, and multiple signal zones are cut from a paper-based substrate, and a glass fiber separation membrane is cut according to the shape and size of the separation zone. S13. Cut multiple signal holes on the electrostatic film; S14. The cut electrostatic membrane, the cut paper base, the cut glass fiber separation membrane, and the cut PVC sticker are stacked sequentially from bottom to top, so that multiple signal holes are aligned with multiple signal areas, multiple capture areas are aligned with multiple reagent holes, and the glass fiber separation membrane is aligned with the separation area. S15. Affix the PVC sticker to the electrostatic film.

[0010] Furthermore, the method for manufacturing the paper-based substrate is as follows: S121. Soak cotton pulp paper in 2ml of 3%-5% (w / v) Pluronic F-127 surfactant for 5 minutes, wash 3 times with deionized water, remove surfactant and air dry; S122. Prepare 2 ml of a mixture of 8%-12% (v / v) PEGMA and 0.1%-0.4% (v / v) PEGDA to form a polymer solution. Add 0.2% (v / v) TEMED, 4% (w / v) APS and 1% (v / v) acrylic acid, and freeze in 1×PBS solution at pH 7.3. S123. After mixing the polymerization solution, soak cotton pulp paper in it and polymerize at -20°C for 10-14 hours. Then incubate at room temperature to remove ice crystals and wash thoroughly with deionized water to remove any unreacted precursors.

[0011] Furthermore, the distance between the biomarker signal imprint and the starting point of the data recording area is 25mm-27mm.

[0012] Furthermore, the concentration of red blood cells added to the reaction layer is 15%-25%.

[0013] Furthermore, the unexpected antibody identification model is constructed using a random forest algorithm or a support vector machine algorithm.

[0014] The beneficial effects of this invention are as follows: The method for detecting accidental antibodies described in this invention utilizes a multi-channel detection card and a glass fiber separation membrane, eliminating the need for pre-incubation of red blood cell reagents and antibodies. This method is simple to operate and does not require the use of large equipment to centrifuge whole blood, providing a new reference strategy for portable testing and is expected to be applied to portable testing under outdoor emergency conditions.

[0015] The detection method for accidental antibodies described in this invention can identify multiple antibodies within 10-15 minutes, demonstrating high detection efficiency. By introducing artificial intelligence algorithms into automated result analysis, potential influencing factors are reduced, enabling intelligent analysis of big data. Combining logic gate circuits and machine learning, automatic result interpretation and output are achieved. The three-dimensional porous structure of cotton pulp paper restricts the movement of trace molecules, significantly improving the immunobinding efficiency between antigen-presenting erythrocytes, irregular antibodies, and capture antibodies. Compared to standard gel microcolumn detection methods, the detection method for accidental antibodies described in this invention achieved 100% accuracy (AUC=1) in a direct comparison of 100 clinical samples.

[0016] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of a four-channel detection card; Figure 2 This is a characterization diagram of the charge of the electrostatic adsorption layer; Figure 3 Electron microscopy and confocal microscopy characterization of the trapping ability of cotton pulp paper H5072: (a) Electron microscopy image of the trapping ability of cotton pulp paper H5072. The red dashed box represents the red blood cell agglomerates on the cotton pulp paper; the red solid box represents the scattered red blood cells in the interstitial spaces of cotton pulp paper H5072; (bc) Fluorescence confocal microscopy characterization of the trapping ability of cotton pulp paper H5072 and comparison of green fluorescence intensity; Scale bar: 20 μm; P < 0.0001; Figure 4 A comparison of traditional centrifugation and glass fiber membrane centrifugation: (a) Schematic diagram of traditional centrifugation and membrane separation; (b) Comparison of the separation effect of whole blood and red ink, with the blue dashed box indicating the precipitation distance of different substances; Figure 5 For the comparison of CSP and MSP reflectance, the dashed box represents the separated plasma; Figure 6 SDS-PAGE characterization of centrifuged plasma and membrane-separated plasma: (a) Comparison of SDS-PAGE values ​​of centrifuged plasma and membrane-separated plasma; (b) Comparison of electrophoretic gray values; P=0.6647; Figure 7 Comparison of sample separation performance per unit area using separation membranes: separation effect with different whole blood sample volumes; and comparison of plasma precipitation distance on H5072 cotton pulp paper. Figure 8Characterized by Raman spectra of erythrocytes and plasma on the surface of BD; Figure 9 BIS signals of erythrocytes and plasma on the surface of BD (n=50); Figure 10 This is a diagram illustrating the conversion between logical and physical locations. The blue line represents the physical location (cm). Figure 11 For the verification of optical disc signal stability and repeatability: (a) the effect of different ambient temperatures on BIS (n=3); (b) verification by 30 repeatability tests; Figure 12 This is a diagram of the reaction layer structure of a four-channel detection card; Figure 13 Experimental diagram showing the whole blood loading capacity of glass fiber separation membrane; scale bar: 5mm; Figure 14 Whole blood loading capacity of glass fiber membrane; Scale bar: 5mm; Figure 15 This is a schematic diagram of the structure of a twelve-channel detection card; Figure 16 The reaction layer structure of the twelve-channel accidental antibody confirmatory test card; Figure 17 The interpretation rules for the logic gates of the four-channel detection card; Figure 18 The BIS signal values ​​for the initial screening test in the four channels; Figure 19 The BIS signal values ​​for the twelve-channel confirmatory test; Figure 20 The receiver operating characteristic (ROC) curve for the unexpected antibody recognition model; Figure 21 ROC curve of the four-channel detection card; Figure 22 ROC curve of the twelve-channel test card; Figure 23 To verify the repeatability of the unexpected antibody test card.

[0018] In the figure: Top shell layer-1; Reaction layer-2; Electrostatic adsorption layer-3; Sample well-4; Reagent well-5; Separation zone-6; Channel-7; Capture zone-8; Signal zone-9; Signal well-10; Glass fiber separation membrane-11. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0022] In the above description of the present invention, it should be noted that the terms "one side," "the other side," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the invention is conventionally placed during use. These terms are used only for the convenience of describing the present invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0023] Furthermore, terms such as "identical" do not imply that components must be absolutely identical; minor differences are permissible. The term "perpendicular" simply means that the positional relationship between components is more perpendicular than "parallel," not that the structure must be perfectly perpendicular; a slight tilt is acceptable.

[0024] This invention provides a technical solution: a method for detecting accidental antibodies, comprising the following steps: S1. Pre-coat the test card with anti-human globulin and attach the test card to a Blu-ray disc (BD); S2. Load whole blood sample and reagent red blood cells onto the test card. The test card separates plasma from the whole blood sample. Accidental antibodies in the separated plasma bind to reagent red blood cells, causing the reagent red blood cells to agglutinate on the test card. The unagglutinated reagent red blood cells on the test card are transferred to the Blu-ray disc, forming a biomarker signal imprint on the Blu-ray disc. S3. Use a Blu-ray disc drive to read biomarker signal traces on a Blu-ray disc; S4. The data read from the Blu-ray disc drive is processed using an accidental antibody recognition model to screen for accidental antibodies.

[0025] like Figure 1 As shown, the detection card includes a top shell layer 1, a reaction layer 2, and an electrostatic adsorption layer 3 arranged sequentially from top to bottom. The top shell layer 1 has sample wells 4 for loading whole blood samples and multiple reagent wells 5 for loading reagent red blood cells. The reaction layer 2 includes a separation zone 6, multiple channels 7, multiple capture zones 8, and multiple signal zones 9. The separation zone 6 is directly opposite the sample well 4. The multiple capture zones 8 and multiple signal zones 9 each correspond one-to-one with the multiple channels 7. The capture zones 8 and the signal zones 9 are located on their respective channels 7. The multiple capture zones 8 are directly opposite the multiple reagent wells 5. The electrostatic adsorption layer 3 has multiple signal wells 10, which are directly opposite the multiple signal zones 9. The number of channels 7 can be set as needed.

[0026] The method for manufacturing the detection card is as follows: S11. Cut out sample holes 4 and multiple reagent holes 5 on a PVC sticker with single-sided adhesive. S12. A separation zone 6, multiple channels 7, multiple capture zones 8 and multiple signal zones 9 are cut from a paper-based substrate, and a glass fiber separation membrane 11 is cut according to the shape and size of the separation zone 6. S13. Cut multiple signal holes 10 on the electrostatic film; the electrostatic film is the electrostatic adsorption layer 3.

[0027] S14. The cut electrostatic membrane, the cut paper base, the cut glass fiber separation membrane 11, and the cut PVC sticker are stacked sequentially from bottom to top, so that multiple signal holes 10 are aligned with multiple signal areas 9, multiple capture areas 8 are aligned with multiple reagent holes 5, and the glass fiber separation membrane 11 is aligned with the separation area 6. S15. Affix the PVC sticker to the electrostatic film.

[0028] The method for manufacturing the paper-based substrate is as follows: The paper-based substrate is made by bonding 8%-12% (v / v) polyethylene glycol methacrylate (PEGMA) and 0.1%-0.4% (v / v) polyethylene glycol diacrylate (PEGDA) molecules into conventional cotton pulp paper via a cryogel method. Specifically: S121. Soak cotton pulp paper in 2 ml of 3%-5% (w / v) Pluronic F-127 surfactant for 5 minutes. Preferably, soak cotton pulp paper in 2 ml of 4% (w / v) Pluronic F-127 surfactant for 5 minutes, wash with deionized water 3 times, remove surfactant, and air dry. S122. Prepare 2 ml (pH 7.3) of a mixture of 8%-12% (v / v) PEGMA and 0.1%-0.4% (v / v) PEGDA to form a polymer solution. The preferred concentration of PEGMA is 10% (v / v), and the preferred concentration of PEGDA is 0.2% (v / v). Add 0.2% (v / v) TEMED, 4% (w / v) APS, and 1% (v / v) acrylic acid, and freeze in 1×PBS solution at pH 7.3. Adjust the pH of the polymerization solution with 1M NaOH before adding APS and TEMED.

[0029] S123. After mixing the polymerization solution, soak cotton pulp paper in it and polymerize at -20°C for 10-14 hours, preferably 12 hours. Then incubate at room temperature to remove ice crystals and wash thoroughly with deionized water to remove any unreacted precursors.

[0030] The distance between the biomarker signal imprint and the starting point of the data recording area is 25mm-27mm.

[0031] The concentration of red blood cells added to the reaction layer is 15%-25%, preferably 20%.

[0032] The unexpected antibody identification model is constructed using either the random forest algorithm or the support vector machine algorithm.

[0033] The method for pre-coating the test card with anti-human globulin is as follows: add the anti-human globulin to the capture area of ​​the reaction layer through the reagent well and dry at 25°C for 3 hours.

[0034] The method for attaching the test card to a Blu-ray disc is as follows: Use an electrostatic meter to measure the charge on the surface of the blank disc and the electrostatic film. Record the data after the instrument display stabilizes. The BD surface is uncharged, while the electrostatic film layer is negatively charged. No additional surface modification is required; the test card adheres to the disc surface through electrostatic self-adhesion (please refer to...). Figure 2 ).

[0035] Simply align the long side of the test card tangentially with the data area of ​​the Blu-ray disc, and then press it with 10-25 Newtons of pressure to attach the test card to the Blu-ray disc for testing. This method is both efficient and fast.

[0036] When loading whole blood samples and reagent red blood cells onto the test card, the whole blood sample is added dropwise into the sample well, and after 1 minute, different reagent red blood cells are added dropwise into different reagent wells. The concentration of reagent red blood cells added to the reagent wells is 15%-25%, preferably 20%.

[0037] After a whole blood sample is added to the sample well, the glass fiber separation membrane automatically separates the plasma containing the target antibody within 30 seconds. The separated plasma enters the capture zone through a channel, where the target antibody binds to reagent red blood cells, forming specific immune red blood cell-antibody (Ab) complexes. Subsequently, multivalent capture antibodies crosslink these complexes, causing red blood cells to agglutinate on the capture zone within 120 seconds. Unagglutinated red blood cells enter the signal zone through the channel and are transferred to the Blu-ray disc surface through the signal aperture.

[0038] After adding reagent red blood cells to the reagent well for 5 minutes, elute with elution buffer, then remove the test card from the Blu-ray disc surface, dry for 30 seconds, and read the data using the Blu-ray disc drive.

[0039] Maintaining the morphology and viability of red blood cells is crucial for field-deployed antibody detection. The paper-based substrate provides protection for red blood cells, a protection derived from the biocompatibility and hydrophilicity of PEG, which mitigate damage caused by osmotic pressure and drying. The paper-based substrate exhibits strong dehydration resistance, maintaining its mass for 160 minutes in an unsealed state. This is essential for maintaining a hydrophilic microenvironment to promote antibody binding to red blood cells in practical applications.

[0040] The preferred type of pulp paper is H5072.

[0041] Fluorescence confocal microscopy characterizes the target capture effect: ① Add 20 μL of anti-human globulin to two circular cotton pulp papers with a diameter of 5 mm, designated as the negative control and positive control group, and dry at 25℃ for 3 h. Add 20 μL of physiological saline to the blank control group. Repeat the above treatment twice. ② Weigh 8 mg of FITC dye into a light-protected tube using an electronic balance, add 5 μL of DMSO to redissolve it, then dissolve it in erythrocyte preservation solution to prepare a FITC-erythrocyte fluorescent dye concentration of 0.8 mg / mL, and store it in a light-protected tube. ③ Take 4 mL of irregular anti-screening red blood cells II and III respectively, centrifuge at 2500 rpm for 5 min, completely remove the red blood cell preservation solution, and leave the red blood cells; irregular anti-screening red blood cells II are the positive group, and irregular anti-screening red blood cells III are the negative group; ④ Rinse the remaining red blood cells with physiological saline for 15 seconds, then centrifuge at 2500 rpm for 5 minutes, discard the supernatant, repeat the rinsing five times, and observe under ultraviolet-visible light to ensure that all red blood cell preservation solution is removed. ⑤ Add 8 mL of FITC fluorescent staining solution to a blank, light-protected centrifuge tube, then add 2 mL of rinsed red blood cells and mix well; ⑥ Place the light-protected centrifuge tubes in a low-temperature shaking incubator at 4°C and incubate at 100 rpm for 1.5 hours, then remove them. ⑦ Centrifuge the incubated FITC-irregular anti-screening red blood cell solution at 2500 rpm for 5 min to remove excess FITC fluorescent staining solution; ⑧ The remaining FITC-irregular anti-screening red blood cells were rinsed with physiological saline for 15 seconds, then centrifuged at 2500 rpm for 5 minutes, the supernatant was discarded, and the rinsing was repeated five times. The cells were then observed under UV-Vis light and resuspended in physiological saline to achieve a 45% resuspending rate. ⑨ After mixing FITC-erythrocytes II and III with anti-D-IgG at a 1:1 ratio, immediately add 20 μL to cotton pulp paper pre-coated with anti-human globulin, react for five minutes, wash off, peel off a layer of cotton pulp paper, and observe the results of the blank control, positive and negative groups under a fluorescence confocal microscope in sequence; ⑩ Use ImageJ software to extract the intensity of green fluorescence in each group.

[0042] Scanning electron microscopy images showed that on H5072 cotton pulp paper pre-fixed with anti-human globulin, obvious agglomerates were observed in the positive group, while no agglomerates were observed in the negative group. Figure 3 a). Fluorescence confocal images showed that in the positive group, erythrocyte agglomerates (green fluorescence) were observed within the paper-based fibers (blue fluorescence); while in the negative group, scattered individual erythrocytes were visible. Figure 3 (b) This demonstrates that H5072 cotton pulp paper can successfully capture antibodies. Furthermore, comparing the green fluorescence intensity (FI) values ​​on the confocal images, there was a significant difference in FI values ​​between the positive and negative groups (P<0.0001). Figure 3 c). Therefore, cotton pulp paper H5072 can reliably and stably capture target biomolecules in the blood, making it an ideal substrate for reaction layer channels.

[0043] Determination of ultraviolet reflectance of membrane-separated plasma and centrifuged plasma: ① Centrifuge fresh, normal human anticoagulated whole blood at 2500 rpm for 5 min, collect the supernatant and place it in a clean centrifuge tube for later use; add 30 μL of centrifuged plasma onto cotton pulp paper (3 × 0.2 cm); then place it under a UV spectrophotometer to measure the UV reflectance, repeat three times; ② Assemble a 1×1cm separation membrane with the back of a 3×0.2cm strip of H5072 cotton pulp paper using adhesive tape, and set aside. Add 100μL of whole blood to the assembled separation membrane, and wait for the plasma to precipitate onto the cotton pulp paper strip after 1 minute. Then place it under a UV spectrophotometer to measure the UV reflectance, and repeat three times.

[0044] First, for ease of visual observation, we compared plasma obtained by centrifugation (CSP) with plasma obtained by membrane separation (MSP). The results showed that, utilizing the capillary effect of the glass fiber separation membrane, plasma can be separated from whole blood, with pale yellow plasma precipitating on cotton pulp paper. Detrimental particles in the sample were intercepted, demonstrating the effectiveness of membrane separation. Figure 4 ).

[0045] Membrane-separated plasma and centrifuged plasma polyacrylamide gel electrophoresis ①Preparation of the lower layer gel: Take 10mL of lower layer gel premix, 100mL of 10% gel polymerization catalyst solution (10% APS), and 4μL of TEMED. Mix well and pour into the gel mold. Seal with ultrapure water until the lower layer gel is fully solidified. After solidification for 30 minutes, pour off the water and use filter paper to absorb the excess water. ②Preparation of the top layer gel: 4 mL of SDS-PAGE top layer gel premix, 40 μL of 10% APS, 4 μL of TEMED, mix well, and quickly insert the comb to allow it to solidify; ③ Sample preparation: Mix 20 μL of IgG-anti-D and 20 μL of irregular anti-screening red blood cells III, centrifuge at 2500 rpm for 5 min, and aspirate the supernatant into a clean centrifuge tube for later use. This is recorded as the plasma separated by simulated centrifugation. Mix 200 μL of IgG-anti-D and 20 μL of irregular anti-screening red blood cells III, add it to the assembled separation membrane, and allow anti-D to precipitate completely onto cotton pulp paper after 2 min. Then, wash the cotton pulp paper containing anti-D three times with PBS (1×) to completely wash off the antibody. Centrifuge at 2500 rpm for 5 min, and collect the supernatant. This is recorded as the plasma separated by simulated membrane. ④ Denaturation treatment of samples: Mix 5 μL of 5× loading buffer with 20 μL of the above sample, incubate at 98°C for 10 min, and immediately transfer the sample to an ice box after the water bath. ⑤ Preparation of electrophoresis solution: Weigh 14.4g glycine, 1g SDS, 3g Tris and 1L water into a beaker, stir and mix well, and set aside. ⑥ Preparation of eluent: Take 50 mL of ethanol, 100 mL of glacial acetic acid and 850 mL of water in a glass bottle, stir and mix well, and set aside. ⑦ Sample loading: The loading order from left to right is marker, anti-D, centrifuged plasma and membrane-separated plasma, 4 μL each; ⑧ Electrophoresis: Place the gel plate on the electrophoresis tank, check for leaks, select 70V for the upper gel and run for 20 minutes, and adjust the voltage to 120V for the lower gel and run for 2 hours; ⑨ Staining: After electrophoresis, place the gel in Coomassie brilliant blue staining solution and stain slowly on a shaker for 2 hours at room temperature; ⑩ Decolorization: Pour into the pre-prepared decolorization solution and let it decolorize overnight, changing the decolorization solution three times during the process; ⑪ After destaining, remove the gel and place it in an imaging instrument to observe the electrophoresis results; ⑫ Use ImageJ software to extract the electrophoretic grayscale values.

[0046] from Figure 5 Ultraviolet reflectance spectroscopy revealed that both MSP and CSP exhibited the same plasma reflectance peak at 413 nm, and their reflectance trends were consistent, confirming the reliability of the automated blood sample processing using the glass fiber separation membrane. Similarly, SDS-PAGE results further validated the membrane's ability to effectively separate plasma. Figure 6 The electrophoresis results showed that both MSP and CSP exhibited distinct bands at 66 kDa, and there was no statistically significant difference in their electrophoretic grayscale values ​​(P = 0.6647). Figure 6 b).

[0047] Calculation of glass fiber separation efficiency: Sample separation was performed using a 10×10mm glass fiber membrane and H5072 cotton pulp paper (30×2mm). Whole blood volumes of 90, 95, 100, 105, and 110 μL were added to the glass fiber membrane, and the plasma precipitation on the cotton pulp paper was recorded after 2 minutes. ImageJ software was used to extract and analyze the color intensity and distance of the plasma precipitation on the cotton pulp paper. The sample separation efficiency was determined using a simulation formula. The calculation formula is as follows: Formula (1) Where L is the chromatographic distance of the sample on the cotton pulp paper, W is the width, H is the thickness, V0 represents the sample volume per cubic millimeter, R is the ratio of sample particles (i.e., the proportion of red blood cells in whole blood), and Vw is the total volume of sample added to the membrane.

[0048] When the amount of whole blood sample added to the separation membrane per unit area exceeds 100 μL, red blood cells precipitate on cotton pulp paper H5072, exceeding the membrane's separation capacity. Figure 7 Meanwhile, as the amount of sample added increases, the precipitation distance on the cotton pulp paper gradually increases, and the amount of red blood cells precipitated also gradually increases, making effective separation impossible. Figure 7 ).

[0049] Verification of optical disc signal: ① Raman signal characterization of optical disc surface: Blu-ray discs were cut into 2×2cm squares using a laser cutter; fresh, normal human anticoagulated whole blood was centrifuged at 2500 rpm for 5 min, and the supernatant was placed in a clean centrifuge tube for later use; three pre-cut Blu-ray discs were coated with physiological saline, red blood cells, and plasma in sequence, and dried overnight at room temperature; the above Blu-ray discs were placed under a Raman spectrometer for measurement, the characteristic reflection peaks were observed, and the raw data were recorded; ② Verification of the logical and actual positions of the optical disc: The positions of the signal areas are fixed in advance on the surface of the optical disc. The total number of BIS (Burst Indicator Subcode) signals in different signal areas is obtained by using the conversion formula between the physical and logical positions on the optical disc.

[0050] Formula (2) Formula (3) If the BIS value of a single signal point is B, then the total signal Y of the signal area is the sum (n) of the BIS values ​​of all sequence signal points. When the physical position reflects the distance range of a single signal area from the center of the disk, Ps is the starting point of the physical position, and Px is the ending point of the physical position. The logical position is the range corresponding to the BIS signal (Ls-Lx) within the logical range of the optical disc scan. Ls is the start of the signal area, Lx is the end of the logical position of the signal area, and S represents the starting point of the signal.

[0051] ③ Verification of optical disc signal stability at different temperatures: Measure the signal of red blood cells on the optical disc at 5, 10, 15, 20, 25, 30, and 35°C respectively; repeat each operation 3 times and calculate the BIS value; ④ Optical disc repeatability test verification: Set blank signal and red blood cell signal on the same optical disc, dry at room temperature for 1 minute, and then put it into the optical drive to read the signal. After each reading, immerse the optical disc in ultrapure water for 20 minutes to clean the surface of the optical disc, and blow it dry with nitrogen. Repeat the above operation 30 times and record the BIS data for each time.

[0052] To verify the detection performance, blood samples were used as an example to verify the BIS values ​​of positive and negative signals on the optical disc. From Figure 8 In Raman spectroscopy, a characteristic plasma peak can be observed at 1324 cm⁻¹, while at 1200 cm⁻¹... -1 and 1700cm -1 A characteristic RBC peak was observed. Furthermore, a comparison of BIS signals from different samples (50 plasma and 50 red blood cells each) showed a statistically significant difference (P<0.0001). Figure 9 This further confirms that the method can accurately detect biosignals on the surface of BD.

[0053] To distinguish multiple biomarker signals on the optical disc surface, accurately locating the physical position of each signal imprint on the BD is crucial. Therefore, we established a mathematical model formula for locating the detection apertures. Calculation results show that the physical area of ​​the BD's signal apertures (P0-P1, 25mm-27mm) is consistent with their corresponding logic capacities (L0-L1, 3000MB-3500MB), avoiding the risk of multi-channel signal overlap. Figure 10 Meanwhile, the formula model's accurate positioning and identification of the detection hole also lays the foundation for saving detection time. Through formulas (2) and (3), the detection time is reduced by 6 times compared to the original optical drive reading. This improves detection efficiency and provides a new approach for outdoor detection under emergency conditions, effectively increasing detection speed and accuracy.

[0054] Experimental results show that the BIS value of erythrocytes is not affected by changes in ambient temperature at 5℃, 10℃, 15℃, 20℃, 25℃, 30℃, and 35℃, and the output signal remains consistent. Figure 11 (a) This further proves that the proposed mathematical model can effectively guarantee the accurate identification of various biosignals. Considering subsequent applications, we reused the same optical disc for 30 sample tests, and the consistency of RBC signals was good (CV=0.668%) across the 30 tests. In summary, this platform has good cost-effectiveness and can achieve cyclic repeated testing ( Figure 11 b).

[0055] Construction and Detection Process of Four-Channel Blood Type Accidental Antibody Detection Card ① The anti-human globulin was pre-immobilized in the capture area of ​​the reaction layer and dried at 25°C for 3 hours; ②Assemble the top shell layer, the middle reaction layer, and the bottom electrostatic adsorption layer for later use; ③ Press and stick the test card onto the surface of the CD; ④ Add 300 μL of blood sample to the sample well of the top shell layer. After 1 min, add 10 μL of irregular anti-screening red blood cell reagent (RBC1-RBC3 for the four-channel test card) to the red blood cell reagent well. After 5 min, elute with elution buffer, then remove the test card from the surface of the optical disc, dry for 30 s, and read the data using a Blu-ray optical disc drive.

[0056] When crossmatch is incompatible, there is a history of blood transfusions or pregnancy, or multiple transfusions are required in a short period, screening for accidental antibodies is necessary. If the initial screening result is positive, further antibody identification is required to determine specificity. Therefore, considering time and economic costs, this study first constructed a four-channel test card for the initial screening of accidental antibodies. The structure of the four-channel test card is as follows: Figure 1 As shown, its four-channel reaction layer structure is as follows: Figure 12As shown, a four-channel paper-based reaction layer was formed using a laser cutter, corresponding to negative control (NC), T1, T2, and T3 channels. T1, T2, and T3 correspond to irregular antibody screening reagents for red blood cells (RBC1-RBC3), respectively. Anti-human globulins were pre-immobilized in the capture areas corresponding to T1, T2, and T3. Analysis was performed using three lineages of anti-screening cells. When the sample to be tested was added, the plasma was separated by a glass fiber membrane and transported to the capture areas of the four channels. Subsequently, RBC1-RBC3 were added sequentially to channels T1, T2, and T3, and the reaction was allowed to proceed for 5 minutes to capture unexpected antibodies. After elution, the test card was removed. If unexpected antibodies were present, the cell signal would not be transferred to the optical disc. According to the antigen pattern table, a positive result in any of channels T1, T2, or T3 indicates the presence of unexpected antibodies, requiring further confirmatory testing (Table 1).

[0057] Table 1. Irregular antibody screening reagent antigen pattern for red blood cells.

[0058] Optimization of whole blood sample loading volume: Several 2×1.5cm rectangles of glass fiber separation membrane were cut for later use; several four-channel paper-based microfluidics were fabricated using a laser cutter for later use; several glass fiber separation membranes and four-channel paper-based microfluidics were assembled on a PVC substrate for later use; then, 280μL, 290μL, 300μL, 310μL, and 320μL of fresh healthy blood samples were added to the glass fiber separation membrane respectively. After 2 minutes, the plasma separation was recorded by taking pictures; the five samples were repeated five times; finally, the color intensity of the flow channels and four capture areas was extracted using ImageJ software.

[0059] On a 2×1.5cm glass fiber separation membrane, when the whole blood sample volume is less than 300μL, the separated plasma is difficult to reach the capture zone and cannot meet the needs of subsequent testing; while when it is greater than 300μL, considering that the whole blood sample volume exceeds the carrying capacity of the separation membrane, different degrees of red blood cell precipitation occurred in the capture zone and flow channel. Figure 13 Meanwhile, we extracted the color intensity of the four capture zones and the flow channel, and found that when the sample volume was 300 μL, there was no statistically significant difference in the intensity values ​​of each region. Figure 14 Therefore, we determined the optimal sample volume for the four-channel primary screening paper-based test card to be 300 μL.

[0060] Construction and testing process of the 12-channel confirmatory test card for accidental blood type antibodies: ① The anti-human globulin was pre-immobilized in the capture area of ​​the paper-based reaction layer and dried at 25°C for 3 hours; ②Assemble the top shell layer, the middle paper-based reaction layer, and the bottom electrostatic adsorption layer for later use; ③ Press and stick the test card onto the surface of the CD; ④ Add 300 μL of blood sample to the sample well in the top shell layer. After 1 min, add 10 μL of irregular anti-screening red blood cell reagent to the red blood cell reagent well (the twelve-channel confirmation card uses eleven cell lines of spectrum RBC1-RBC). 11 Add RBC1 to channel T1, and so on for the other detection channels. After 5 minutes, elute with elution solution, remove the detection card from the optical disc surface, dry for 30 seconds, and read the data using a Blu-ray disc drive.

[0061] For samples that initially test positive for unexpected antibodies, confirmatory testing is required to determine their specificity. Therefore, based on the initial screening card, we further developed a 12-channel test card that achieved confirmatory identification of 28 antibodies within 15 minutes. Similarly, the structure of the 12-channel test card is as follows: Figure 15 As shown, the 12-channel confirmatory test card also includes a general negative control channel and 11 independent detection channels (T1-T1). 11 () Figure 16 The detection channel selects 11 lineage cells. Except for the NC channel, the other channels are pre-coated with anti-human globulin. The capture principle is the same as that of the 4-channel detection card. Then, the unagglutinated red blood cells on the detection card are transferred to the signal area on the optical disc, realizing the rapid confirmation detection of accidental blood type antibodies. Its detection principle is the same as that of the four-channel detection card.

[0062] Construction of the accidental antibody recognition model: ① 2000 clinical samples were tested using a test card, and the BIS values ​​were recorded; ② An accidental antibody identification model was constructed using the Random Forest (RF) algorithm of machine learning. First, the BIS values ​​were divided into two groups: a positive group (accidental antibody with no RBC signal) and a negative group (RBC signal), with 1000 cases in each group. ③ The model was tested. The validation set included 500 cases each of the positive group (unexpected antibody signal) and the negative group (red blood cell signal). Please refer to Table 2 below for dataset classification. The model was obtained by fitting the training set data using an RF classifier. The validation set data was used to verify the model's classification performance. The antibody prediction results from machine learning were evaluated using the following three metrics: accuracy (Formula 4), specificity (Formula 5), ​​and sensitivity (Formula 6), as detailed below: Table 2. Dataset classification in RF classifier.

[0063] The effectiveness of machine learning predictions is evaluated using three metrics: accuracy (Formula 4), sensitivity (Formula 5), ​​and specificity (Formula 6), calculated as follows: Formula (4) Formula (5) Formula (6) Based on the construction of a four-channel initial screening test card, to achieve automatic output and interpretation of results, in addition to setting a global negative control NC channel without anti-human globulin coating, we used an OR gate logic circuit between the three independent test channels (T1-T3) for automatic output of antibody results. When the NC result is negative, the output value is 0; when any of the three test channels is positive, the output value is 1, indicating the presence of unexpected blood type antibodies in the sample. For example, when the logic gate input result is "0110", it indicates the presence of unexpected antibodies (output value 1), while when "1010" is input, it indicates that the test is invalid. Figure 17 ). Figure 18 The results showed that the BIS values ​​of NC and T3 were negative, while the BIS values ​​of T1 and T2 detection channels were positive. In this case, the input result of the logic gate was "0110" and the output result was "1", indicating that the detection was valid and that unexpected antibodies were present, which is consistent with the gold standard result. Therefore, the logic gate recognition circuit constructed in this study can rapidly screen 18 unexpected antibodies within 10 minutes without the need for additional centrifugation equipment.

[0064] According to existing regulations, samples that initially test positive must undergo confirmatory testing for accidental antibodies to determine their specificity. Therefore, to accurately identify specific blood type accidental antibodies, a twelve-channel confirmatory test card was constructed. Taking a sample that tested positive for anti-D using the gold standard microcolumn gel card method as an example, the twelve-channel test card was used. The logic gate input result was "011110000111", and the output result was anti-D (…). Figure 19 This is consistent with the gold standard results, indicating that the constructed logic gate recognition circuit can accurately output results without requiring conventional reagent red blood cell and plasma pre-incubation procedures, providing an option for the accurate detection of unexpected antibodies.

[0065] To achieve automatic output and interpretation of results and improve the accuracy of detection results, a blood type accidental antibody intelligent identification model was constructed using the Biometrics Indicator (BIS) value as an indicator and the Randomization Framework (RF) machine learning method. We used 2000 cases of data obtained from the tests as the training set to build the test model. The training set included positive data (1000 BIS values) and negative data (1000 BIS values). After completing the construction of the training model, we further validated its effectiveness using a 1000-case validation set. Using 10-fold cross-validation, the results showed that the constructed accidental antibody identification model can accurately distinguish different accidental antibodies. The feasibility of this model for distinguishing accidental antibodies was validated using ROC (Regression on Analytical Carbide) analysis. Figure 20As can be seen, the area under the ROC curves of both the training and test sets is 1, which indicates that the constructed antibody recognition model is accurate and reliable.

[0066] One hundred clinical samples were randomly selected, and the corresponding accidental antibodies were detected by the microcolumn gel card method. Then, the corresponding samples were detected by this test card. The accidental antibody detection platform constructed by this method was used to identify the results, and the corresponding BIS values ​​(100 cases) were extracted as the clinical test dataset in the RF classifier.

[0067] Using the microcolumn gel card method as the gold standard, 100 clinical whole blood samples were used to validate the accuracy of the four-channel primary screening test card. 50 samples produced a result of 1, resulting in a 100% detection rate of unexpected antibodies, and the area under the curve was 1 (Ω). Figure 21 (Table 3). Furthermore, we performed confirmatory testing on the samples that tested positive for unexpected antibodies using a 12-channel test card. All 50 samples yielded specific unexpected antibodies, with 6, 27, 16, and 1 cases detected for anti-D, anti-E, anti-M, and anti-P1, respectively. This was consistent with the gold standard test results, achieving 100% accuracy and an AUC of 1 (…). Figure 22 (Table 4) This indicates that the detection method for accidental antibodies described in this invention has good feasibility in clinical applications.

[0068] Table 3. Clinical sample validation of the four-channel test card (n=100).

[0069] Table 4. Clinical sample validation of the 12-channel test card (n=50) Similarly, repeatability testing is crucial for the accurate identification of unexpected antibodies. We repeated the tests on five blood samples five times within one day to assess the reliability and stability of this method. The results showed that all whole blood samples were accurately detected, and the results from the five tests were consistent. Figure 23 The stability and reliability of the detection can be verified by comparing the BIS value. Therefore, through validation with a large number of clinical samples, it has been proven that the detection method for accidental antibodies described in this invention can be used for the initial screening and accurate detection of accidental antibodies, demonstrating good clinical feasibility and the potential for future application in portable testing under emergency outdoor conditions.

[0070] The method for detecting accidental antibodies described in this invention utilizes a multi-channel detection card and a glass fiber separation membrane, eliminating the need for pre-incubation of red blood cell reagents and antibodies. This method is simple to operate and does not require the use of large equipment to centrifuge whole blood, providing a new reference strategy for portable testing and is expected to be applied to portable testing under outdoor emergency conditions.

[0071] The detection method for accidental antibodies described in this invention can identify multiple antibodies within 10-15 minutes, demonstrating high detection efficiency. By introducing artificial intelligence algorithms into automated result analysis, potential influencing factors are reduced, enabling intelligent analysis of big data. Combining logic gate circuits and machine learning, automatic result interpretation and output are achieved. The three-dimensional porous structure of cotton pulp paper restricts the movement of trace molecules, significantly improving the immunobinding efficiency between antigen-presenting erythrocytes, irregular antibodies, and capture antibodies. Compared to standard gel microcolumn detection methods, the detection method for accidental antibodies described in this invention achieved 100% accuracy (AUC=1) in a direct comparison of 100 clinical samples.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for detecting accidental antibodies, characterized in that, Includes the following steps: S1. Pre-coat the test card with anti-human globulin and paste the test card onto the Blu-ray disc; S2. Load whole blood sample and reagent red blood cells onto the test card. The test card separates plasma from the whole blood sample. Accidental antibodies in the separated plasma bind to reagent red blood cells, causing the reagent red blood cells to agglutinate on the test card. The unagglutinated reagent red blood cells on the test card are transferred to the Blu-ray disc, forming a biomarker signal imprint on the Blu-ray disc. S3. Use a Blu-ray disc drive to read biomarker signal traces on a Blu-ray disc; S4. The data read from the Blu-ray disc drive is processed using an accidental antibody recognition model to screen for accidental antibodies.

2. The detection method for accidental antibodies according to claim 1, characterized in that: The detection card includes a top shell layer, a reaction layer, and an electrostatic adsorption layer arranged from top to bottom. The top shell layer has sample wells for loading whole blood samples and multiple reagent wells for loading reagent red blood cells. The reaction layer includes a separation zone, multiple channels, multiple capture zones, and multiple signal zones. The separation zone is directly opposite the sample wells. The multiple capture zones and multiple signal zones correspond one-to-one with the multiple channels. The capture zones and the signal zones are located on their respective channels. The multiple capture zones are directly opposite the multiple reagent wells. The electrostatic adsorption layer has multiple signal wells, and the multiple signal wells are directly opposite the multiple signal zones.

3. The detection method for accidental antibodies according to claim 2, characterized in that, The method for manufacturing the detection card is as follows: S11. Cut out sample holes and multiple reagent holes on a PVC sticker with single-sided adhesive. S12. A separation zone, multiple channels, multiple capture zones, and multiple signal zones are cut from a paper-based substrate, and a glass fiber separation membrane is cut according to the shape and size of the separation zone. S13. Cut multiple signal holes on the electrostatic film; S14. The cut electrostatic membrane, the cut paper base, the cut glass fiber separation membrane, and the cut PVC sticker are stacked sequentially from bottom to top, so that multiple signal holes are aligned with multiple signal areas, multiple capture areas are aligned with multiple reagent holes, and the glass fiber separation membrane is aligned with the separation area. S15. Affix the PVC sticker to the electrostatic film.

4. The detection method for accidental antibodies according to claim 3, characterized in that, The method for manufacturing the paper-based substrate is as follows: S121. Soak cotton pulp paper in 2ml of 3%-5% (w / v) Pluronic F-127 surfactant for 5 minutes, wash 3 times with deionized water, remove surfactant and air dry; S122. Prepare 2 ml of a mixture of 8%-12% (v / v) PEGMA and 0.1%-0.4% (v / v) PEGDA to form a polymer solution. Add 0.2% (v / v) TEMED, 4% (w / v) APS and 1% (v / v) acrylic acid, and freeze in 1×PBS solution at pH 7.

3. S123. After mixing the polymerization solution, the cotton pulp paper is soaked in it. Polymerize at -20°C for 10-14 hours, then incubate at room temperature to remove ice crystals, and wash thoroughly with deionized water to remove any unreacted precursors.

5. The detection method for accidental antibodies according to claim 1, characterized in that: The distance between the biomarker signal imprint and the starting point of the data recording area is 25mm-27mm.

6. The detection method for accidental antibodies according to claim 1, characterized in that: The concentration of red blood cells added to the reaction layer is 15%-25%.

7. The detection method for accidental antibodies according to claim 1, characterized in that: The unexpected antibody identification model is constructed using either the random forest algorithm or the support vector machine algorithm.

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