Visual detection test paper for intestinal tract cleanliness before gynecological operation

Abstract

The invention relates to the technical field of chemical or physical analysis, and provides gynecological preoperative intestinal cleanliness visual detection test paper, compared with an existing gynecological preoperative intestinal cleanliness detection technology which is subjected to single-index detection, susceptible to interference and depends on subjective evaluation, synchronous detection of multiple indexes such as cholate and cholecystin is achieved through a double-response nanoprobe, and the detection accuracy is high. The omission ratio is reduced from 18% to 3%, and the detection limit is as low as 2 [mu] mol / L of cholate and 3 ng / mL of cholecystin; the nano-particle wrapping and micro-fluidic technology is adopted, so that the retention rate of the enzyme activity under the interference of antibiotics reaches 85%, and the operation error rate is reduced from 15% to 5%; aI image recognition and an intelligent algorithm are combined, five-color gradient quantitative scoring is achieved, the interpretation efficiency is improved by 20 times, the functions of postoperative infection early warning, home remote detection and the like are expanded, a complete system from detection to clinical decision is constructed, intestinal tract preparation evaluation is promoted to develop towards the precise and intelligent direction, and remarkable creativity and clinical application value are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of chemical or physical analysis, in particular to a visual detection test paper for intestinal cleanliness before gynecological surgery. Background Art

[0002] In the field of gynecological surgery, accurate assessment of preoperative intestinal cleanliness is crucial to reducing the incidence of complications such as postoperative infection and anastomotic fistula. Currently, traditional detection technologies have significant flaws: First, the detection index is single. Existing pH test strips can only detect acidity and alkalinity and cannot identify hidden fecal residue, resulting in a missed detection rate of up to 18%. Key indicators such as stercobilin residue are not included in the detection range. Second, the anti-interference ability is poor. Antibiotics commonly used during intestinal preparation (such as metronidazole) inhibit the enzyme activity in traditional test strips, resulting in a retention rate of only 60%, which is prone to false negative results. Third, the operational error is large. Traditional test strips that rely on naked eye observation are affected by uneven sample diffusion, with an operational error rate of 15%, and the misinterpretation rate of people with color blindness is as high as 22%. Fourth, the function is limited. Existing methods can only assess cleanliness and lack the ability to detect mucosal damage and pathogens, which cannot meet the clinical needs for a comprehensive assessment of surgical risks.

[0003] These technical problems seriously affect the safety and effectiveness of gynecological surgery. Therefore, a visual test strip for intestinal cleanliness before gynecological surgery was proposed. Through nanoprobes, microfluidics, AI recognition and other technologies, multi-indicator collaborative detection, precise quantitative evaluation and risk warning can be achieved, filling the existing technological gaps and providing more reliable technical support for preoperative preparation for gynecological surgery. Summary of the Invention

[0004] Technical problems solved

[0005] In view of the deficiencies of the existing technology, the present invention provides a visual detection test paper for intestinal cleanliness before gynecological surgery.

[0006] Technical Solution

[0007] To achieve the above-mentioned solution, the present invention provides the following technical solution: a visual detection test strip for intestinal cleanliness before gynecological surgery, which includes a substrate layer, a reagent layer, a color development layer, a quality control module and an intelligent interaction layer.

[0008] The substrate layer is a composite film of nanocellulose and polylactic acid with a thickness of 0.15±0.02mm. 0.5% graphene oxide nanosheets are dispersed in the composite film. The substrate layer has three built-in arc-shaped guide channels with an angle of 60°. The width of a single channel is 0.5mm and the depth is 0.2mm. The inner wall of the guide channel is sprayed with a polytetrafluoroethylene hydrophobic coating, and the contact angle reaches 120±5°.

[0009] The reagent layer is arranged on the substrate layer and includes a dual-responsive nanoprobe area, a mucosal injury detection area, and a pathogenic bacteria screening area; the dual-responsive nanoprobe area is loaded with silica@gold core-shell nanoparticles, and the particle surface is coupled with β-glucuronidase and anti-stercobilin monoclonal antibody; the mucosal injury detection area is based on the sandwich ELISA principle, immobilizes diamine oxidase capture antibody and is labeled with detection antibody; the pathogenic bacteria screening area is immobilized with specific aptamers for Escherichia coli O157:H7 and Klebsiella pneumoniae.

[0010] The color development layer covers the reagent layer and includes an acid-base color development strip and a fluorescent quantum dot array; the acid-base color development strip is composed of an ethanol solution of bromocresol green and methyl red, and the fluorescent quantum dot array includes QDs-520 for bile salt detection, QDs-560 for stercobilin detection, and QDs-610 for mucosal injury detection.

[0011] The quality control module includes a sample quantity detection strip and an enzyme activity calibration strip; the sample quantity detection strip is composed of sodium polyacrylate hydrophilic gel and bromocresol purple color developer, and the enzyme activity calibration strip is fixed with horseradish peroxidase and 3,3',5,5'-tetramethylbenzidine substrate.

[0012] The intelligent interactive layer includes a two-dimensional code recognition area and a graphene conductive electrode; the two-dimensional code recognition area adopts DataMatrix encoding, and the graphene conductive electrode is used for quantitative collection of fluorescence signals.

[0013] Preferably, the nanocellulose composite substrate is composited with nanocellulose and polylactic acid in a mass ratio of 3:7, has a thickness of 0.15±0.02 mm, and is dispersed with 0.5% graphene oxide nanosheets.

[0014] Preferably, the preparation method of the silica@gold core-shell nanoparticles is: first, 10 mL of 0.01% chloroauric acid solution is reacted with 1 mL of 1% sodium citrate to prepare a 20 nm gold core, then ammonia water and ethyl orthosilicate are added to form a 40 nm silica shell, and finally carboxyl groups are introduced by modification with 3-mercaptopropionic acid.

[0015] Preferably, the β-glucuronidase is coupled to silica@gold core-shell nanoparticles by the EDC / NHS method, with a coupling efficiency of ≥90% and an enzyme activity retention rate of ≥85%; the loading amount of the anti-stercobilin monoclonal antibody is 200 μg / mg, and the KD value for specific recognition of stercobilin is 5×10 -9 M.

[0016] Preferably, the color developing layer comprises: acid-base color developing zone, 0.4 mg / mL bromocresol green and 0.15 mg / mL methyl red ethanol solution, showing a pH gradient of 5.0-7.0; quantum dot array, containing CdSe / ZnS quantum dots with emission wavelengths of 520 nm, 560 nm and 610 nm, arranged at intervals of 1 mm by inkjet printing technology.

[0017] Preferably, the QDs-520 is synthesized by hydrothermal reaction at 120°C for 2 hours, with an emission wavelength of 520 nm; the QDs-560 is synthesized by reaction at 150°C for 3 hours, with surface modification of polyethylene glycol; and the QDs-610 is synthesized by reaction at 180°C for 4 hours, and is coupled with diaminooxidase detection antibody by EDC / NHS method.

[0018] Preferably, the sample volume detection strip is a sodium polyacrylate hydrophilic gel, and bromocresol purple developing agent is added, which shows blue color when the sample volume is greater than or equal to 0.8 mL; the enzyme activity calibration strip is fixed with horseradish peroxidase and TMB substrate, and shows blue color within 1 minute.

[0019] Preferably, the graphene conductive electrode is prepared by chemical vapor deposition method, with a thickness of 0.34 nm and a conductivity of greater than or equal to 10 4 S / cm, and an external fluorescence reader is used to realize quantitative collection of fluorescence signals with a collection accuracy of ±2%.

[0020] The detection method of the gynecological preoperative intestinal cleanliness visual detection test paper, the method is applied to the above-mentioned gynecological preoperative intestinal cleanliness visual detection test paper, and the method comprises the following steps:

[0021] Sample collection and pretreatment: a sterilized plastic swab is used to collect rectal midsection excrement, and a suspension liquid with a concentration of 10-50 mg / mL is prepared, 100 μL of the suspension liquid is filtered, and a sample treatment liquid containing Triton X-100 is added for incubation.

[0022] Microfluidic reaction and signal triggering: the treated sample is added to the sample inlet of the test paper, the sample diffuses to each detection zone along the flow guide channel under capillary action, and the detection of bile salts, fecal porphyrin, mucosal injury markers and pathogenic bacteria preliminary screening is performed.

[0023] Multi-modal signal collection and analysis: the color value of the acid-base color developing zone is obtained by a camera, and is compared with an internal colorimetric card; the fluorescence intensities at 520 nm, 560 nm and 610 nm are collected by an external fluorescence reader; the impedance change of the pathogenic bacteria preliminary screening zone is monitored by an electrochemical workstation; and the cleanliness score is calculated by using a Logistic regression model.

[0024] Result output and clinical application: Display cleanliness level and quantitative test results, issue risk warning for Score ≥ 4 or positive pathogens, and store the test results in the hospital information system.

[0025] Beneficial effects

[0026] Compared with the prior art, the present invention provides a visual test strip for intestinal cleanliness before gynecological surgery, which has the following beneficial effects:

[0027] 1. This visual test strip for intestinal cleanliness before gynecological surgery uses dual-response nanoprobes and multimodal signal conversion technology to achieve simultaneous detection of bile salt concentration, stercobilin residue, mucosal damage markers and pathogenic bacteria, reducing the missed detection rate from 18% to 3%, and the detection limit as low as 2μmol / L bile salt and 3ng / mL stercobilin, solving the problem of missed detection of hidden fecal residue.

[0028] 2. This visual test strip for intestinal cleanliness before gynecological surgery protects enzyme activity through nanoparticle encapsulation. The enzyme activity retention rate in samples containing metronidazole reaches 85%, far exceeding the 60% level of traditional test strips. Combined with the microfluidic anti-pollution structure, the operating error rate is reduced from 15% to 5%, and it still maintains good performance after being stored at 40°C for 6 months.

[0029] 3. This visual test strip for intestinal cleanliness before gynecological surgery integrates AI image recognition and intelligent algorithms to achieve five-color gradient quantitative scoring of cleanliness, increasing interpretation efficiency by 20 times. It also has postoperative infection risk warning and home self-examination telemedicine functions, building a complete system from detection to clinical decision-making, and promoting the development of precise and intelligent intestinal preparation before gynecological surgery. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a schematic diagram of the test strip operation process of the present invention;

[0031] Figure 2 The figure is a schematic diagram of the preparation process of the test paper of the present invention. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0033] See also Figures 1 and 2 The present invention proposes a visual detection test strip for intestinal cleanliness before gynecological surgery, which includes the following contents:

[0034] 1. Test paper structure and function

[0035] 1.1 Substrate layer

[0036] 1.1.1 Material composition and properties

[0037] Substrate material: Nanocellulose (CNF) and polylactic acid (PLA) composite film with a mass ratio of 3:7 and a thickness of 0.15 ± 0.02 mm. The nanocellulose is derived from cotton linters (prepared by acid hydrolysis, with an average diameter of 20-50 nm), which imparts high strength (tensile strength ≥ 80 MPa) and high water absorption (water absorption rate 150 μL / cm 2 ) to the substrate, while PLA provides biodegradability (degradation period under composting conditions 6-12 months).

[0038] Functional modification: 0.5% (w / w) graphene oxide nanoplatelets are uniformly dispersed in the composite film to form a conductive network through ultrasonic treatment (power 200 W, time 30 minutes), with a conductivity of 5 S / cm, which is used to enhance the stability of subsequent fluorescence signal acquisition.

[0039] 1.1.2 Microfluidic flow guide structure

[0040] Channel design: Three arc-shaped flow guide channels with an included angle of 60° are built in, with a single channel width of 0.5 mm and a depth of 0.2 mm. SU-8 photoresist (thickness 50 μm) is used as a mold, and the channel structure is formed on the PDMS layer by soft lithography technology, and then bonded to the nanocellulose film by hot pressing (pressure 50 kPa, temperature 80 °C).

[0041] Anti-pollution treatment: The inner wall of the channel is sprayed with a polytetrafluoroethylene (PTFE) hydrophobic coating, and a 50 nm thick film is formed by vapor deposition (temperature 150 °C, time 2 hours), with a contact angle of 120 ± 5°, to ensure that the sample flows along the preset path with a diffusion coefficient of variation (CV) ≤ 8%.

[0042] 1.2 Reagent layer

[0043] 1.2.1 Dual-responsive nanoprobes region

[0044] Core material: Silica@gold core-shell nanoparticles (SiO2@AuNPs) prepared by seed growth method:

[0045] Gold core synthesis: 10 mL of 0.01% chloroauric acid solution is boiled, 1 mL of 1% sodium citrate is quickly added, and stirring is carried out for 30 minutes to obtain 20 nm gold cores;

[0046] Silicon shell coating: Ammonia (25%) is added to the gold core solution to adjust the pH to 10, and tetraethyl orthosilicate (TEOS) is added dropwise, and the reaction is carried out at room temperature for 2 hours to form a 40 nm silica shell layer;

[0047] Surface modification: modification by 3-mercaptopropionic acid (1 mM) to introduce carboxyl groups for subsequent antibody coupling.

[0048] Biofunctionalization:

[0049] β-glucuronidase (25 U / mL) was coupled by 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) / N-hydroxysuccinimide (NHS) method, coupling efficiency ≥ 90%, enzyme activity retention rate ≥ 85%;

[0050] Anti-stercobilin monoclonal antibody (10 μg / mL) was coupled in the same way, and the antibody loading reached 200 μg / mg, specifically recognizing stercobilin (KD=5 x 10 -9 M).

[0051] 1.2.2 Mucosal damage detection zone

[0052] Detection principle: based on the sandwich ELISA principle, the fixed diamine oxidase (DAO) capture antibody (5 μg / mL) on the nitrocellulose membrane, the detection antibody labeled with AlexaFluor488 (10 μg / mL), forming an "antibody-antigen-fluorescent antibody" complex, and the fluorescence intensity is positively correlated with the DAO concentration (normal range < 15 U / L).

[0053] Matrix formula: phosphate buffer solution (PBS, pH 7.4) containing 0.1% bovine serum albumin (BSA) and 0.05% Tween-20, to reduce non-specific adsorption.

[0054] 1.2.3 Pathogenic bacteria primary screening zone

[0055] Recognition element: specific aptamer (sequence screened by SELEX technology) against Escherichia coli O157:H7 and Klebsiella pneumoniae, concentration 5 μM, immobilized on the surface of graphene conductive electrode through amino modification;

[0056] Signal conversion: pathogenic bacteria binding leads to changes in electrode impedance values, monitored by an electrochemical workstation (frequency range 10 Hz-100 kHz), and impedance changes ≥ 10% are determined as positive.

[0057] 1.3 Color development layer: multi-modal signal conversion system

[0058] 1.3.1 Acid-base color development band

[0059] Indicator formula: bromocresol green (0.4 mg / mL) and methyl red (0.15 mg / mL) in ethanol solution (ethanol volume fraction 70%), pH sensitive range 5.0-7.0, color gradient:

[0060] pH 5.0-5.4: bright green (RGB: 0, 220, 100)

[0061] pH 5.5-6.2: yellow-green (RGB: 180, 220, 50)

[0062] pH 6.3-6.8: Yellow (RGB: 255, 200, 0)

[0063] pH 6.9-7.0: orange-yellow (RGB: 255, 150, 0)

[0064] 1.3.2 Fluorescent Quantum Dot Arrays

[0065] Preparation method:

[0066] QDs-520 (bile salt detection): CdSe / ZnS quantum dots were synthesized by hydrothermal method at 120°C for 2 hours. The emission wavelength was 520 nm and the half-peak width was ≤30 nm.

[0067] QDs-560 (stercobilin detection): 150°C, 3 hours reaction, emission wavelength 560 nm, surface modified with polyethylene glycol (PEG, MW = 2000) to improve water solubility;

[0068] QDs-610 (mucosal injury detection): 180°C, 4 hours reaction, emission wavelength 610 nm, DAO detection antibody conjugated via EDC / NHS method.

[0069] Array layout: Three types of quantum dots are arranged in the color development layer at intervals of 1 mm. Inkjet printing technology (nozzle diameter 50 μm) is used to precisely control the placement of dots, and the coefficient of variation (CV) of fluorescence intensity is ≤5%.

[0070] 1.4 Quality Control Module: Ensuring the Reliability of the Testing Process

[0071] 1.4.1 Sample volume test strips

[0072] Materials: Sodium polyacrylate hydrophilic gel (concentration 3% w / v), with bromocresol purple added as a color developer (0.05 mg / mL). When the sample volume is ≥0.8 mL, it absorbs water and swells, and the pH value changes, causing the color to change from colorless to blue (pH ≥6.0).

[0073] 1.4.2 Enzyme activity calibration strips

[0074] Calibration principle: Horseradish peroxidase (HRP, 10 U / mL) and 3,3',5,5'-tetramethylbenzidine (TMB) substrate are immobilized. Water in the sample activates HRP to catalyze the oxidation of TMB, and a blue color appears within 1 minute, indicating normal enzyme activity in the detection system.

[0075] 1.5 Intelligent Interaction Layer

[0076] 1.5.1 QR code recognition area

[0077] Coding content: including test strip batch number, production time, detection parameters (such as quantum dot excitation wavelength, colorimetric card threshold), using DataMatrix coding, scanning recognition rate ≥ 99.9%;

[0078] Function linkage: After scanning the code, the built-in convolutional neural network (CNN) is activated. The model is trained based on 5,000 clinical samples, with a validation set accuracy of 99.2%, and supports real-time updates of detection algorithms.

[0079] 1.5.2 Graphene Conductive Electrode

[0080] Preparation process: Single-layer graphene is grown on the substrate surface by chemical vapor deposition (CVD) with a thickness of 0.34nm and a conductivity of ≥10 4 S / cm;

[0081] Signal acquisition: with external fluorescence reader (excitation light intensity 200mW / cm 2 , bandpass filters 520 / 560 / 610nm±10nm) to achieve quantitative acquisition of fluorescence signals with an accuracy of ±2%.

[0082] 2. Analysis of the entire preparation process

[0083] 2.1 Preparation of nanocellulose composite substrate

[0084] 2.1.1 Nanocellulose extraction

[0085] Cotton linters were hydrolyzed with 64% sulfuric acid (solid-to-liquid ratio 1:10, reaction at 50°C for 2 hours), centrifuged (10,000 rpm, 15 minutes) and dialyzed to remove the acid solution, obtaining a nanocellulose hydrosol with an average diameter of 30 nm (solid content 2%).

[0086] 2.1.2 Composite membrane preparation

[0087] The nanocellulose sol and PLA acetone solution (concentration 10% w / w) were mixed in a volume ratio of 3:7, ultrasonically dispersed for 30 minutes, cast onto a glass substrate, dried at 60°C for 12 hours, and peeled off to obtain a composite film with a thickness of 0.15 mm.

[0088] 2.1.3 Microfluidic Channel Integration

[0089] The silicon wafer surface was spin-coated with SU-8 photoresist (rotation speed 2000 rpm, thickness 50 μm) and exposed to UV light (dose 200 mJ / cm 2 ) and then developed to form a channel mold;

[0090] PDMS prepolymer was mixed with curing agent (10:1), poured into the mold, cured at 65 °C for 2 h, peeled off and hot-pressed bonded to the composite membrane, and the inner wall of the channel was sprayed with PTFE hydrophobic coating.

[0091] 2.2 Preparation of dual-responsive nanoprobes

[0092] 2.2.1 Synthesis of silica@gold core-shell particles

[0093] Gold nucleus growth: Boil 10 mL of 0.01% HAuCl4 solution, quickly add 1 mL of 1% sodium citrate, and stir vigorously for 30 minutes to obtain a wine-red 20 nm gold sol;

[0094] Silica shell coating: 5 mL of gold sol was added to 0.5 mL of 25% ammonia water. After stirring for 5 minutes, 0.2 mL of LTEOS was added dropwise. The mixture was reacted at room temperature for 2 hours. The particles were collected by centrifugation (15,000 rpm, 30 minutes) and washed twice with ethanol.

[0095] Surface modification: The particles were dispersed in 10 mL of 1 mM 3-mercaptopropionic acid solution, stirred at room temperature for 12 hours, centrifuged and resuspended in PBS (pH 7.4).

[0096] 2.2.2 Biomolecule Conjugation

[0097] Take 1 mg of SiO2@AuNPs, add 50 μL of LEDC (10 mg / mL) and 50 μL of NHS (5 mg / mL), and activate for 30 minutes;

[0098] β-glucuronidase (25 U / mL, 100 μL) or anti-stercobilin antibody (10 μg / mL, 100 μL) were added, incubated overnight at 4°C, centrifuged to remove unbound proteins, and resuspended in PBS to 1 mg / mL.

[0099] 2.3 Functional layer coating process

[0100] 2.3.1 Preparation of reagent layer

[0101] Dual-responsive nanoprobe area: The probe solution was applied to the middle of the substrate using a film sprayer (nozzle diameter 100 μm, pressure 0.3 MPa) to form a circular area with a diameter of 5 mm. Drying conditions: 37°C, humidity ≤ 30%, and time of 1 hour.

[0102] Mucosal injury detection area: DAO capture antibody solution was spotted on nitrocellulose membrane using a contact spotter (accuracy ±10 μm), with a spot volume of 1 μL / spot and a spacing of 2 mm;

[0103] Pathogen screening area: The aptamer solution (5 μM) was fixed on the graphene electrode surface by electrochemical deposition with a deposition voltage of 0.5 V and a time of 30 seconds.

[0104] 2.3.2 Preparation of color development layer

[0105] Acid-base color ribbon: Bromocresol green-methyl red mixture is coated by gravure printing process, printing speed is 50mm / s, coating thickness is 10μm;

[0106] Fluorescent quantum dot array: Three quantum dot solutions were printed at preset positions using inkjet printing technology (resolution 600 dpi), and after drying, they were covered with a 0.1 mm thick polyacrylate moisture-proof layer.

[0107] 2.4 Packaging and sterilization

[0108] Inner packaging: A single test strip is placed in an aluminum foil bag with a built-in silica gel desiccant (moisture absorption ≥ 15% of its own weight), filled with nitrogen (oxygen content ≤ 1%), heat-sealed at 180°C for 2 seconds;

[0109] Sterilization: After packaging, sterilize with ethylene oxide (EO) (concentration 600 mg / L, temperature 55°C, time 6 hours), and analyze for 48 hours to ensure the sterility level reaches 10 -6 SAL.

[0110] 3. Detailed explanation of the entire detection process

[0111] 3.1 Sample collection and pretreatment

[0112] 3.1.1 Collection methods

[0113] Use a sterile plastic swab to insert into the middle part of the rectum (depth of about 5 cm), rotate it 3 times to collect feces, immediately place it in a sterile test tube containing 2 mL of normal saline, add 0.1% sodium azide (to inhibit bacterial growth), vortex and oscillate for 1 minute to prepare a 10-50 mg / mL suspension.

[0114] 3.1.2 Sample processing

[0115] 100 μL of the suspension was filtered through a 0.45 μm filter membrane (to remove particulate impurities), and 10 μL of sample treatment solution (containing 0.5% Triton X-100 to lyse cells and release intracellular components) was added to the filtrate. After incubation at room temperature for 5 minutes, the sample was added to the test paper injection port.

[0116] 3.2 Microfluidic reaction and signal triggering

[0117] 3.2.1 Sample diversion

[0118] The sample diffuses rapidly along the three flow channels under capillary action (reverse capillary force generated by a contact angle of 120°) and reaches all detection areas within 90 seconds. The flow uniformity of each channel is ≥95%.

[0119] 3.2.2 Biochemical reactions

[0120] Bile salt detection: Bile salt hydrolysis catalyzed by β-glucuronidase generates 4-methyl umbelliferone (4-MU), which emits 520 nm fluorescence under 365 nm excitation light, reaction kinetics equation: V = V max max x [S] / (K m + [S])

[0121] (V0 = initial reaction rate, Vmax = maximum reaction rate = 25 μM / min, Km = Michaelis constant = 10 μM)

[0122] Stool Bilirubin detection: Stool Bilirubin binds to antibody, leading to gold nanoparticle agglomeration, solution absorbance A550nm value increases with concentration, consistent with Lambert-Beer law (linear range 0-20 μmol / L, R 2 = 0.998);

[0123] Mucosal damage detection: DAO forms sandwich structure with capture antibody, fluorescent antibody, quantum dot QDs-560 fluorescence intensity (I 560 ) is linearly related to DAO concentration (regression equation: I 560 = 100 + 50 x [DAO], R 2 = 0.995).

[0124] 3.3 Multi-modal signal acquisition and analysis

[0125] 3.3.1 Color signal acquisition

[0126] The camera (resolution 1200 million pixels, aperture f / 1.8) takes the color layer, and the color value is obtained through the RGB-D sensor, compared with the built-in color card (five color gradients: 1st grade bright green, 2nd grade yellow green, 3rd grade yellow, 4th grade orange, 5th grade red), and the color difference value ΔE (CIELAB space) is calculated, ΔE≤3 is determined as effective matching.

[0127] 3.3.2 Fluorescence signal acquisition

[0128] The external fluorescence reader (volume 10 cm x 8 cm x 5 cm, weight 200 g) emits 405 nm excitation light, and the fluorescence intensities (I 520 , I 560 , I 610 ) at 520 / 560 / 610 nm are collected through filters, and the data is transmitted to the report.

[0129] 3.3.3 Intelligent algorithm analysis

[0130] Cleanliness score model: Logistic regression model is used, and the weight coefficient is determined by training 5000 clinical samples, and the calculation formula is: Score = 0.6 x (I520 / I 520_max )+0.3×(I 560 / I 560_max )-0.1×(I 610 / I 610_min )

[0131] (I 520_max is the maximum fluorescence intensity of the cleanliness level 1 sample, I 560_max is the upper limit fluorescence value of stercobilin detection, I 610_min is the minimum fluorescence intensity of normal mucosa)

[0132] Initial screening for pathogenic bacteria: The electrochemical workstation monitors the impedance spectrum in real time. When the impedance change at a frequency of 10 kHz is ≥10%, it is determined to be pathogen-positive (Escherichia coli O157:H7 or Klebsiella pneumoniae).

[0133] 3.4 Result Output and Clinical Application

[0134] 3.4.1 Visual Report

[0135] Display content:

[0136] Cleanliness level (1-5, 1 being the best) and the corresponding Boston and Ottawa scores;

[0137] Quantitative test results: bile salt concentration (μmol / L), stercobilin residue (μmol / L), diamine oxidase (U / L);

[0138] Risk warning: Red mark Score ≥ 4 or pathogenic bacteria positive, recommended supplementary plan (such as increasing the dose of PEG electrolyte powder by 250mL, or extending the enema interval by 1 hour).

[0139] 3.4.2 Data Management

[0140] The test results are encrypted and stored in the hospital information system (HIS), support connection with the electronic medical record (EMR), and automatically generate a preoperative evaluation report including the test time, operator, and quality control results (sample volume / enzyme activity calibration status).

[0141] 4. Detection method validation and performance parameters

[0142] 4.1 Core Detection Performance Verification

[0143] 4.1.1 Sensitivity and detection limit

[0144]

[0145]

[0146] 4.1.2 Specificity and anti-interference ability

[0147] Cross-reactivity:

[0148] Bile salt detection: bilirubin (10-fold concentration) interference rate ≤5%, non-specific binding is inhibited by nano-probe steric hindrance effect;

[0149] Stercobilin detection: cross-reactivity with bilirubin and cholic acid is 8% and 6%, respectively, and the antibody affinity (KD=5x10 -9 M) is significantly higher than that of the interferent (KD>1x10 -7 M).

[0150] Antibiotic resistance: in metronidazole (10 μg / mL) containing samples, the retention rate of β-glucuronidase activity is ≥80% (only 60% for traditional test paper), thanks to the shielding effect of the nano-particle protective layer on the enzyme active center.

[0151] 4.2 Operation performance verification

[0152] 4.2.1 Reproducibility and repeatability

[0153] Intra-batch repeatability: the same batch of test paper detects the same sample (bile salt 10 μmol / L, stercobilin 5 μmol / L), cleanliness score RSD=7.2% (n=10);

[0154] Inter-batch repeatability: different batches (n=5) of test paper detect the same sample, score RSD=8.5%, quantum dot fluorescence intensity RSD=6.8%, both of which meet the requirements of clinical detection (RSD≤10%).

[0155] 4.2.2 Operation convenience

[0156] Detection time: the whole process from sample addition to result output is ≤5 minutes, which is significantly better than traditional endoscopy (30 minutes) and ELISA method (2 hours);

[0157] Learning curve: the operation accuracy rate of nurses trained for 10 minutes reaches 98%, and there is no significant difference in the accuracy rate of color weak people in judging fluorescence signals compared with normal people (P>0.05).

[0158] 4.3 Environmental adaptability verification

[0159] 4.3.1 Temperature and humidity stability

[0160] Accelerated aging test:

[0161] Storage at 40℃ / 75% RH for 3 months: the retention rate of β-glucuronidase activity is 85%, and the attenuation of quantum dot fluorescence intensity is ≤15%;

[0162] -20℃ frozen storage for 6 months: The nanoprobe structure was intact and the reaction rate did not decrease significantly after reconstitution (P>0.05).

[0163] Extreme environment testing:

[0164] High temperature and high humidity (35°C / 85% RH): Continuously tested 50 samples, with a detection limit stable at 2μmol / L and a pathogen identification rate of 97%;

[0165] Low-temperature drying (5°C / 20% RH): The sample diffusion time was extended to 120 seconds, and the scoring accuracy was still ≥95%.

[0166] 4.3.2 Storage validity period

[0167] According to the Arrhenius model prediction, the test paper has a shelf life of 24 months under refrigerated conditions at 2-8°C and 18 months at room temperature (25°C / 60% RH), which is significantly better than traditional enzyme test paper (shelf life of 12 months).

[0168] 4.4 Clinical multicenter validation

[0169] 4.4.1 Experimental Design

[0170] Sample size: A total of 500 patients undergoing gynecological surgery from three tertiary hospitals, aged 25-65 years, were enrolled. Bowel preparation regimens included polyethylene glycol (PEG) group (n=300) and sodium phosphate group (n=200).

[0171] The gold standard was colonoscopy (Boston score), and the Kappa test was used to analyze the consistency of cleanliness grading.

[0172] 4.4.2 Key Results

[0173]

[0174]

[0175] 4.4.3 Clinical Value

[0176] Successfully identified 23 cases of occult fecal samples (stercobilin 3-5 μmol / L) that were missed by endoscopy, avoiding surgical delays due to insufficient cleanliness assessment;

[0177] The postoperative infection rate of patients with positive pathogen screening (n=18) (8.3%) was significantly higher than that of negative patients (1.2%), suggesting the need for prophylactic use of antibiotics.

[0178] Case 1: Basic nanoprobe test paper

[0179] Technical Parameters

[0180] Substrate: nanocellulose composite membrane (CNF:PLA = 3:7), thickness 0.15 mm, 3 microfluidic channels (width 0.5 mm, angle 60°)

[0181] Dual-responsive probe: SiO2@Au NPs (particle size 60 nm), loaded with β-glucuronidase (25 U / mL) and anti-stercobilin antibody (10 μg / mL)

[0182] Color development system: bromocresol green-methyl red acid-base indicator + QDs-520 / 560 fluorescence array

[0183] Preparation points

[0184] Nanocellulose was extracted by sulfuric acid hydrolysis method and blended with PLA to flow cast into a film

[0185] Microfluidic channels were prepared using soft lithography technology, and the inner wall was sprayed with PTFE hydrophobic coating (contact angle 120°)

[0186] Probes were coupled with biomolecules by EDC / NHS method, with a loading capacity of 200 μg / mg

[0187] Detection performance

[0188] Bile salt detection limit: 2 μmol / L (HPLC-MS / MS verified recovery rate 98%)

[0189] Stercobilin specificity: 5% cross-reactivity with bilirubin (competitive binding experiment)

[0190] Batch repeatability: RSD = 7.8% (n = 20 batches of the same sample detection)

[0191] Note: This case uses a nanocellulose composite substrate, integrating 3 microfluidic channels and silica@gold core-shell nanoprobe, loaded with β-glucuronidase and anti-stercobilin antibody, combined with acid-base indicator and fluorescent quantum dots to achieve dual-index detection. The preparation process covers nanomaterial synthesis, microfluidic processing and biomolecule coupling, with a detection limit of 2 μmol / L bile salt and a batch repeatability RSD = 7.8%.

[0192] Case 2: Economic polypropylene substrate test paper

[0193] Technical parameters

[0194] Substrate: polypropylene (PP) material, thickness 0.2 mm, 5 microfluidic channels (width 0.3 mm, angle 45°)

[0195] Dual-responsive probe: SiO2@Ag core-shell particles (particle size 50 nm), loaded with β-galactosidase (20 U / mL) and anti-cholic acid antibody

[0196] Color development system: bromothymol blue indicator + rhodamine B fluorescent dye

[0197] Innovation

[0198] Use of silver-based nanoparticles to reduce costs (material costs down 30%)

[0199] Increase the number of channels to improve sample diversion efficiency (reaction time shortened to 3 minutes)

[0200] Detection performance

[0201] Bile acid detection limit: 3 μmol / L (LC-MS / MS verification)

[0202] Environmental adaptability: Enzyme activity retention rate is 80% after 6 months storage at 40℃

[0203] Convenient operation: the color development time of the sample detection strip is shortened to 30 seconds

[0204] Description: The microfluidic system utilizes a polypropylene substrate, five microfluidic channels, and silica@silver core-shell particles to reduce costs. β-galactosidase and anti-cholic acid antibodies are loaded, and rhodamine B replaces quantum dots to simplify the fluorescence system. Assay time is shortened to 3 minutes, and enzyme activity retention is 80% after six months of storage at 40°C, reducing material costs by 30%.

[0205] Case 3: Degradable paper-based test strips

[0206] Technical Parameters

[0207] Substrate: Polylactic acid (PLA) and wood cellulose composite film (thickness 0.2mm)

[0208] Microfluidic structure: open design without channels, surface coated with super-hydrophobic nanocoating (contact angle 115°) Probe system: carbon quantum dots (CQDs) labeled β-glucuronidase, detect bile salt concentration Preparation points

[0209] The composite film is formed by hot pressing and has a degradation cycle of 12 months (composting conditions)

[0210] Carbon quantum dots were synthesized by microwave method (emission wavelength 520nm, quantum yield 40%)

[0211] Detection performance

[0212] Detection time: 4 minutes (open structure accelerates sample diffusion)

[0213] Biocompatibility: Cytotoxicity test (L929 cells) survival rate ≥ 95%

[0214] Clinical verification: 96% consistency with the test strip in Case 1 (n=100)

[0215] Note: The composite substrate is made of polylactic acid and lignocellulose, and has no channel opening design with a super-hydrophobic coating. Carbon quantum dots are used to label beta-glucuronidase to detect bile salts. The degradation period is 12 months (under composting conditions), the cell survival rate is ≥95%, and the consistency with the basic test paper is 96%.

[0216] Case 4: Intelligent interpretation system

[0217] System architecture

[0218] Hardware: 1200 megapixel mobile phone camera + 405 nm portable excitation light source

[0219] Software: CNN algorithm (ResNet-18 model, training set 3000 cases, verification set accuracy 99.1%)

[0220] Interaction: Scan test paper two-dimensional code to automatically match detection parameters, generate five-color score within 5 seconds

[0221] Interpretation process

[0222] Take color development layer image (resolution 1920x1080)

[0223] Image preprocessing: remove background noise, locate fluorescent array area

[0224] Feature extraction: extract RGB value and fluorescence intensity (I 520 / I 560 )

[0225] Model inference: adapt different batches of test paper through transfer learning

[0226] Performance data

[0227] Color weak population interpretation accuracy: 98% (traditional method 75%)

[0228] Scoring time: 3 seconds / time (manual interpretation requires 60 seconds)

[0229] Anti-light interference: △E≤3 under 500-5000 lux light intensity

[0230] Note: The 1200 megapixel camera and CNN algorithm (ResNet-18 model) are integrated, the parameters are automatically matched by scanning the two-dimensional code, the five-color score is completed within 5 seconds, the color weak population interpretation accuracy reaches 98%, and the anti-light interference ability is strong (△E≤3 under 500-5000 lux).

[0231] Case 5: Portable fluorescence reader detection

[0232] Device parameters

[0233] Excitation light source: 405nm LED (power 200mW / cm 2 )

[0234] Detection module: 3-channel spectrometer (wavelength range 400-700nm, resolution 1nm)

[0235] Data interface: Bluetooth 5.0 transmission, support HIS system docking

[0236] Detection steps

[0237] Insert the test paper into the reading instrument detection slot (positioning accuracy ±0.1mm)

[0238] Automatic calibration: read the fluorescence background value of the quality control module

[0239] Quantitative detection: Collect QDs-520 / 560 / 610 fluorescence intensity (integration time 500ms)

[0240] Result calculation: Output cleanliness score (1-5) through Logistic regression model

[0241] Clinical Application

[0242] Emergency surgery scenario: from sampling to results ≤ 3 minutes

[0243] Data traceability: The test results automatically generate a PDF report, including the quality control status and the original spectrum image

[0244] Accuracy verification: consistency with laboratory ELISA method R 2 =0.992(n=200)

[0245] Description: Equipped with 405nm excitation light source and 3-channel spectrometer, supports Bluetooth transmission and HIS system docking, can produce results within 3 minutes in emergency scenarios, and the detection accuracy is consistent with ELISA method. 2 =0.992, automatically generate a PDF report containing the original spectrum.

[0246] Case 6: Evaluation of the effect of PEG bowel preparation

[0247] Patient Information

[0248] A 45-year-old female patient undergoing myomectomy was treated with PEG electrolyte powder (2L) for bowel preparation.

[0249] Sampling time: 2 hours after enema, the stool is yellow watery (no fecal residue observed by naked eye)

[0250] Test results

[0251] Acid-base color band: yellow-green (pH 5.8, corresponding to Boston score level 2)

[0252] Fluorescent signal: I 520 = 800, I 560 = 300 (stool bile residue 4 μmol / L)

[0253] Intelligent score: Score = 0.6 x (800 / 1000) + 0.3 x (300 / 500) = 0.6 + 0.18 = 0.78 (converted to level 2)

[0254] Clinical decision: Because the stool bile residue is > 3 μmol / L, it is recommended to add 500 mL of PEG solution, and the Score is 0.92 (level 1) after 2 hours of retesting.

[0255] Note: For patients with watery stool after PEG enema, the presence of hidden stool bile residue (4 μmol / L) is detected by fluorescent signal detection, the intelligent score corrects the misjudgment of visual observation (from level 1 to level 2), and the addition of intestinal preparation is guided to meet the requirements.

[0256] Case 7: Postoperative infection risk warning

[0257] Patient information

[0258] Female, 58 years old, radical resection of ovarian cancer, excrement after sodium phosphate enema is paste

[0259] Test results:

[0260] Cleanliness score: level 3 (yellow color band, stool bile 8 μmol / L)

[0261] Mucosal injury index: diamine oxidase 25 U / L (normal < 15 U / L)

[0262] Pathogenic bacteria screening: Escherichia coli O157:H7 positive (impedance change 15%)

[0263] Clinical intervention

[0264] Postpone surgery for 24 hours, and use PEG + probiotic intestinal preparation scheme

[0265] Prophylactic use of ceftriaxone sodium (2g, iv, q12h)

[0266] Postoperative monitoring: no anastomotic fistula or abdominal infection occurred, and the hospitalization time was shortened by 2 days compared with similar patients

[0267] Note: When testing patients with paste stool, cleanliness level 3, mucosal injury (DAO = 25 U / L), and Escherichia coli positive are found simultaneously, the risk warning is used to postpone surgery and adjust the scheme, avoid postoperative infection, and shorten the hospitalization time by 2 days.

[0268] Case 8: Home self-testing and remote medical care linkage

[0269] System composition

[0270] Test paper: built-in low-power Bluetooth module (transmission distance 10m)

[0271] Terminal: Home health management device (5.5-inch screen, 12-hour battery life)

[0272] Platform: Hospital cloud server (data encryption transmission, compliant with HIPAA standards)

[0273] Operation process

[0274] Patients collect samples at home and insert test strips

[0275] The terminal automatically identifies the test strip batch and starts the detection program

[0276] Generate reports within 5 minutes and synchronize to the attending physician's workstation

[0277] Doctors remotely confirm: If cleanliness level is level 1, the patient will be notified to be admitted as planned.

[0278] Verify data

[0279] Home testing accuracy: 97% (n=50, compared with hospital testing)

[0280] Process optimization: Reduced outpatient visits by 1.2 times per patient, saving an average of 3 hours

[0281] Description: Patients use Bluetooth test strips for testing at home, and the terminal automatically uploads the results to the hospital cloud platform. Doctors remotely confirm the cleanliness level 1 and notify the patient for admission. The process optimization saves 3 hours per patient and has an accuracy rate of 97%.

[0282] Case 9: Comparative test with traditional pH test paper

[0283] Detection object: Hidden fecal samples containing 5μmol / L stercobilin

[0284] index Traditional test strips Test paper of the present invention (Case 1) Color rendering method Single pH indicator (bromocresol green) Dual-responsive nanoprobe + fluorescence Stercobilin test Unrecognizable Positive (A550nm↑15%) Cleanliness score Mistakenly diagnosed as level 1 (normal pH) Correctly judged as level 2 Operational error rate 22% (uneven sample diffusion) 5% (microfluidic diversion)

[0285] Description: For samples containing 5μmol / L stercobilin, the traditional test paper misjudged it as level 1 due to the missed detection of the single pH indicator. The test paper of the present invention recognized stercobilin through the dual-response probe and correctly judged it as level 2, reducing the operating error rate from 22% to 5%.

[0286] Case 10: Comparative test of single indicator test strips

[0287] Detection object: Antibiotic interference sample (containing metronidazole 10μg / mL)

[0288] index Single enzyme test strips (β-glucuronidase) Test paper of the present invention (Case 2) Enzyme activity retention 60% (40°C / 3 months) 85% (nano protective layer) Detection limit 5 μmol / L 2 μmol / L False negative rate 18％ 3％

[0289] Description: In interfering samples containing metronidazole, the enzyme activity retention rate of a single enzyme test paper is only 60%, the detection limit is 5 μmol / L, and the false negative rate is 18%; the test paper of the present invention increases the activity retention rate to 85% through the nano protective layer, reduces the detection limit to 2 μmol / L, and the false negative rate is 3%.

[0290] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. Visual test strip for intestinal cleanliness before gynecological surgery, characterized by: It includes substrate layer, reagent layer, color development layer, quality control module and intelligent interaction layer; A substrate layer comprising a composite film of nanocellulose and polylactic acid, with a thickness of 0.15 ± 0.02 mm and dispersed with 0.5% graphene oxide nanosheets. The substrate layer has three built-in curved flow channels at a 60° angle, with a single channel width of 0.5 mm and a depth of 0.2 mm. The inner wall of the flow channel is sprayed with a polytetrafluoroethylene hydrophobic coating, resulting in a contact angle of 120 ± 5°. The reagent layer is provided on the substrate layer and includes a dual-responsive nanoprobe area, a mucosal injury detection area, and a pathogen screening area; the dual-responsive nanoprobe area is loaded with silica@gold core-shell nanoparticles, the particle surfaces of which are coupled with β-glucuronidase and anti-stercobilin monoclonal antibodies; the mucosal injury detection area is based on the sandwich ELISA principle, immobilizing a diamine oxidase capture antibody and labeling it with a detection antibody; and the pathogen screening area is immobilized with specific aptamers for Escherichia coli O157:H7 and Klebsiella pneumoniae; a color development layer covering the reagent layer, comprising an acid-base color development ribbon and a fluorescent quantum dot array; the acid-base color development ribbon is composed of an ethanol solution of bromocresol green and methyl red, and the fluorescent quantum dot array includes QDs-520 for bile salt detection, QDs-560 for stercobilin detection, and QDs-610 for mucosal injury detection; The quality control module includes a sample quantity detection strip and an enzyme activity calibration strip; the sample quantity detection strip is composed of sodium polyacrylate hydrophilic gel and bromocresol purple color developer, and the enzyme activity calibration strip is immobilized with horseradish peroxidase and 3,3',5,5'-tetramethylbenzidine substrate; The intelligent interactive layer includes a two-dimensional code recognition area and a graphene conductive electrode; the two-dimensional code recognition area adopts DataMatrix encoding, and the graphene conductive electrode is used for quantitative collection of fluorescence signals.

2. The visual detection test paper for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The nanocellulose composite substrate is composited with nanocellulose and polylactic acid in a mass ratio of 3:7, has a thickness of 0.15±0.02 mm, and is dispersed with 0.5% graphene oxide nanosheets.

3. The visual detection test paper for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The silica@gold core-shell nanoparticles were prepared by reacting 10 mL of 0.01% chloroauric acid solution with 1 mL of 1% sodium citrate to produce a 20 nm gold core. Ammonia and ethyl orthosilicate were then added to form a 40 nm silica shell. Finally, carboxyl groups were introduced through modification with 3-mercaptopropionic acid.

4. The visual detection test paper for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The β-glucuronidase was coupled to silica@gold core-shell nanoparticles via the EDC / NHS method, with a coupling efficiency of ≥90% and an enzyme activity retention rate of ≥85%. The loading capacity of the anti-stercobilin monoclonal antibody reached 200 μg / mg, and the KD value for specific recognition of stercobilin was 5×10 -9 M.

5. The visual detection test paper for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The color development layer includes: an acid-base color development ribbon, an ethanol solution loaded with 0.4 mg / mL bromocresol green and 0.15 mg / mL methyl red, showing a gradient color change from pH 5.0 to 7.0; a quantum dot array, including CdSe / ZnS quantum dots with emission wavelengths of 520 nm, 560 nm, and 610 nm, arranged at intervals of 1 mm using inkjet printing technology.

6. The visual detection test paper for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The QDs-520 was synthesized by a hydrothermal reaction at 120°C for 2 hours, with an emission wavelength of 520 nm; the QDs-560 was synthesized by a reaction at 150°C for 3 hours, and its surface was modified with polyethylene glycol; the QDs-610 was synthesized by a reaction at 180°C for 4 hours, and was coupled to a diamine oxidase detection antibody by the EDC / NHS method.

7. The visual detection test paper for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The sample volume detection strip is a sodium polyacrylate hydrophilic gel, which is added with bromocresol purple color developer and turns blue when the sample volume is ≥0.8 mL; the enzyme activity calibration strip is fixed with horseradish peroxidase and TMB substrate and turns blue within 1 minute.

8. The visual detection test strip for intestinal cleanliness before gynecological surgery according to claim 1, characterized in that: The graphene conductive electrode is prepared by chemical vapor deposition, has a thickness of 0.34 nm, and a conductivity of ≥10 4 S / cm, and cooperate with an external fluorescence reader to realize quantitative collection of fluorescence signals with an acquisition accuracy of ±2%.

9. A method for visually detecting intestinal cleanliness before gynecological surgery using a test strip, characterized by: The method is applied to the visual detection test paper for intestinal cleanliness before gynecological surgery according to any one of claims 1 to 8, and the method comprises the following steps: Sample collection and pretreatment: Use a sterile plastic swab to collect mid-rectal feces and prepare a 10-50 mg / mL suspension. Take 100 μL of the suspension, filter it, and incubate it in a sample treatment solution containing Triton X-100. Microfluidic reaction and signal triggering: The processed sample is added to the test strip inlet. Under capillary action, the sample diffuses along the diversion channel to each detection area, and bile salts, stercobilin, mucosal damage markers and pathogenic bacteria are detected respectively; Multimodal signal acquisition and analysis: The color value of the acid-base colorimetric strip is acquired through a camera and compared with the built-in colorimetric card; the fluorescence intensity at 520 / 560 / 610 nm is acquired through an external fluorescence reader; the impedance change in the pathogen screening area is monitored through an electrochemical workstation; and the cleanliness score is calculated using a logistic regression model. Result output and clinical application: Display cleanliness level and quantitative test results, issue risk warning for Score ≥ 4 or positive pathogens, and store the test results in the hospital information system.

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