WO2020000598A1 - 一种汞离子检测产品、方法及智能手机成像分析系统 - Google Patents

一种汞离子检测产品、方法及智能手机成像分析系统 Download PDF

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WO2020000598A1
WO2020000598A1 PCT/CN2018/100985 CN2018100985W WO2020000598A1 WO 2020000598 A1 WO2020000598 A1 WO 2020000598A1 CN 2018100985 W CN2018100985 W CN 2018100985W WO 2020000598 A1 WO2020000598 A1 WO 2020000598A1
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value
detection
gray
image
nucleotide sequence
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PCT/CN2018/100985
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English (en)
French (fr)
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罗云波
许文涛
程楠
黄昆仑
徐瑗聪
杨湛森
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中国农业大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/75—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
    • G01N21/77—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
    • G01N21/78—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a change of colour
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/8483—Investigating reagent band
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/8483—Investigating reagent band
    • G01N2021/8494—Measuring or storing parameters of the band

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  • the invention belongs to the technical field of biological detection, and particularly relates to a mercury ion detection product and method, and a smart phone imaging analysis system.
  • Water-soluble divalent mercury ion is a more common heavy metal risk factor in food safety and drinking water safety. It has strong biological enrichment and is harmful to the human body. It can damage nerves even at very low concentrations. System, digestive system, brain and kidney tissue. Many countries and organizations have adjusted the maximum allowable limit of mercury ions in drinking water samples. For example, the World Health Organization (WHO) stipulates that the maximum allowable limit of mercury ions in drinking water does not exceed 6ng mL -1 (30nM).
  • WHO World Health Organization
  • the Environmental Protection Agency has set an acceptable limit for mercury ions in drinking water of 2ng mL -1 (10nM), the European Union (EU) drinking water standard, and the Chinese Ministry of Health have set the maximum allowable limit for mercury ions No more than 1ng mL -1 (5nM). Therefore, the detection of trace mercury ions is a common concern worldwide.
  • most of these sensors face the dilemma of relatively complicated systems and difficult to quantitative detection.
  • lateral flow tomography sensor is fast, simple, specific, accurate and sensitive.
  • the current lateral flow chromatography sensors can only achieve qualitative or semi-quantitative detection. Additional special instruments are required for quantitative detection, and there is currently no one that can simply and conveniently read quantitative detection data directly from the lateral flow chromatography sensor Technical or portable instruments.
  • the invention provides a mercury ion detection product, a method and a smart phone imaging analysis system, which can convert the detection result displayed on a side flow chromatography sensor into a mercury ion concentration value through a mobile phone, so as to achieve at least a simple and efficient quantitative detection.
  • the concentration of mercury ions in the sample are very suitable for on-site testing by untrained personnel, and provide on-site testing such as food safety and environmental safety. Great convenience.
  • composition including at least one of the following 1) -3):
  • nucleotide sequence shown in 1 undergoes substitution and / or deletion and / or addition of one or several nucleotides and is identical to SEQ ID in the Sequence Listing
  • the nucleotide sequence shown in 1 has a nucleotide sequence having the same function; specifically, the function includes at least one of the following (1) to (4): (1) can specifically recognize or bind to SEQ in the sequence listing ID The nucleotide sequence shown in 3; (2) can specifically recognize or combine the SEQ ID in the sequence listing The nucleotide sequence shown in 3 has been substituted and / or deleted and / or added by one or several nucleotides; (3) When mercury is present, it can be linked with mercury and SEQ ID
  • the nucleotide sequence shown in 2 forms a T-Hg (II) -T structure; (4) When mercury is present, the The T-Hg (II) -T structure is formed by the
  • nucleotide sequence shown in 2 has been substituted and / or deleted and / or added by one or several nucleotides and is identical to the SEQ ID in the Sequence Listing
  • the nucleotide sequence shown in 2 has a nucleotide sequence having the same function; specifically, the function includes at least one of the following (1) to (2): (1) When mercury is present, it can interact with mercury, SEQ ID in the Sequence Listing
  • the nucleotide sequence shown in 1 forms a T-Hg (II) -T structure; (2) When mercury is present, the The T-Hg (II) -T structure is formed by the nucleotide sequence shown in 1 through substitution and / or deletion and / or addition of one or several nucleotides;
  • nucleotide sequence shown in 3 has been substituted and / or deleted and / or added by one or several nucleotides and is identical to the SEQ ID in the Sequence Listing
  • the nucleotide sequence shown in 3 has a nucleotide sequence having the same function. Specifically, the function includes at least one of the following (1) to (2): (1) can specifically recognize or bind to SEQ ID in the sequence listing The nucleotide sequence shown in 1; (2) can specifically recognize or combine the SEQ ID in the sequence listing The nucleotide sequence shown in 1 is subjected to substitution and / or deletion and / or addition of one or several nucleotides.
  • Yet another object of the present invention is to provide a method for detecting mercury and / or mercury ions.
  • the method includes detection using the composition described above or a lateral flow chromatography sensor.
  • Yet another object of the present invention is to provide a method for obtaining the concentration of an object to be measured from any of the lateral flow chromatography sensors of the present invention. After the detection result is displayed on the detection line of the flow chromatography sensor, a quantitative analysis is performed to obtain the concentration of the analyte, and the method further includes:
  • step 4 Substituting the peak area S value obtained in step 2) into the quantitative detection standard curve in step 3), calculating and outputting the concentration value of the test substance in the test sample to complete the detection work;
  • the method for calculating a gray intensity value formed by a detection line region of a flow measurement tomographic sensor in the detection image and the peak area S value includes:
  • the ordinate is perpendicular to the abscissa, and all the ordinates in the detection image having the same abscissa x
  • the average value of the gray value Y is recorded as the gray level intensity value y of the column, and a gray level intensity P (x) function curve is established based on the gray level intensity value y and the abscissa value x of the obtained column;
  • the gray intensity function curve of the detection image with a resolution of m ⁇ n is:
  • Y is a gray value
  • x is an abscissa value
  • y is an ordinate value
  • m and n are resolutions of a detected image
  • the peak surface of the gray intensity function curve in the detection line region is selected, and the peak area is integrated to calculate the peak area S.
  • Yet another object of the present invention is to provide a storage medium including a stored program, wherein a processor executes the method according to any one of the present invention when the program runs.
  • Another object of the present invention is to provide a quantitative detection and analysis system, including:
  • An image acquisition module an image acquisition module, an area image processing module, and a standard curve module
  • the image acquisition module is used to call a camera for image capture or read an image from a mobile phone storage device
  • the image acquisition module is used to intercept the image
  • the area image processing module is used to calculate the pixel gray value of the part, construct a gray intensity function, select a peak surface and calculate the peak surface area S according to the gray intensity function
  • the standard The curve module is used to input the standard curve and calculate and / or output the concentration of the test product;
  • the method for calculating the gray intensity function and the peak area S includes:
  • the flow direction of the sample to be measured on the flow-based paper-based tomographic sensor in the image is the direction of the abscissa, the ordinate is perpendicular to the abscissa, and gray in all the ordinates having the same abscissa x in the image
  • the average value of the degree value Y is recorded as the gray level intensity value y of the column, and the gray level intensity function curve of the obtained column is used to establish a gray level intensity function curve;
  • the gray intensity function curve of the image with a resolution of m ⁇ n is:
  • Y is a gray value
  • x is an abscissa value
  • y is an ordinate value
  • m and n are image resolutions
  • the peak area of the gray intensity function curve in the detection line region on the flow-based paper-based tomographic sensor in the image is selected and the peak area S is calculated by integrating and calculating the peak area.
  • the method for obtaining the standard curve includes:
  • each of the plurality of standard samples is detected by using a lateral flow paper-based tomographic sensor, and detection images of the detection results of the lateral flow paper-based tomographic sensor are respectively acquired and / or displayed by a mobile phone;
  • step 4) Take the concentration value C of the analyte in multiple standard samples or the logarithmic value lgC of the concentration value C of the analyte as the abscissa, and use the multiple obtained in step 3) to correspond to different concentrations of the analyte.
  • the value of the peak area S is plotted on the ordinate, and multiple discrete points are obtained.
  • the multiple discrete points are connected into a straight line.
  • the slope value a, the intercept between the straight line and the abscissa axis is the intercept value b, where C is the concentration of the analyte and S is the peak area S.
  • Another object of the present invention is to provide a composition of any one of the present invention, a lateral flow chromatography sensor of any one of the invention, a method of any one of the invention, a storage medium of any one of the invention, and a system of any one of the invention. application.
  • the application includes qualitative or quantitative detection of mercury ions
  • the detection method of the present invention has at least the following advantages:
  • Nucleic acid base mismatch side flow chromatography sensor Using gold nanoparticles as a signal, the thymine base (T) -rich nucleic acid sequence that can specifically recognize mercury ions is formed with mercury ions in the water sample to be tested "T-Hg (II) -T" structure, showing red lines recognizable to the naked eye on the detection line. The depth of the line color is positively correlated with the concentration of mercury ions. At least it solves the rapid identification of mercury ions in water and its concentration is rapid. Problems that translate into reliable optical signals.
  • Smart phone imaging analysis system It is developed based on the Android system, including two parts: human-computer interaction interface and image processing algorithm design. It is used to achieve rapid quantitative detection of lateral flow tomographic sensors. Users can directly read the side through this system.
  • the concentration value of the target substance detected by the flow chromatography sensor at least solves the problem that the traditional quantitative method needs to use an extra large, expensive, and unmovable instrument.
  • the nucleic acid base mismatch-based lateral flow chromatography sensor provided by the present invention and / or a smartphone imaging and analysis system used in conjunction with the present invention only generate a signal response to mercury ions, and the detection specificity is good; the lowest achievable
  • the detection line is 10nM of mercury ions, and the mercury ion in liquid can be quantitatively detected in a linear range of 10nM to 1mM, and the detection sensitivity is high.
  • Nucleic acid base mismatch-based lateral flow chromatography sensors and / or smartphone imaging analysis systems provided by the present invention are very suitable for on-site testing by untrained personnel, for food safety, environmental safety, etc. On-site testing provides great convenience.
  • FIG. 1 is a schematic diagram of a lateral flow chromatography sensor based on a nucleic acid base mismatch, wherein serial numbers 1-5 represent a plastic low liner, an NC membrane, a binding pad, a water absorption pad (paper), and a sample pad in this order.
  • FIG. 2 is a specific experiment result of a lateral flow chromatography sensor based on a nucleic acid base mismatch, wherein serial numbers 1 to 13 represent Hg (II), Zn (II), Mg (II), and Pb (II), respectively. , Fe (III), Fe (II), Cu (II), K (I), Ca (II), Mn (II), Ag (I), Au (III), Ni (II) solutions.
  • FIG. 3 is a photograph of the detection result displayed by the lateral flow chromatography sensor.
  • FIG. 4 is a graph of optical density distribution.
  • Figure 5 is a photo of the detection result displayed by the side flow chromatography sensor, in which the serial numbers 0-9 respectively represent the detection of negative mercury ion concentration, 1nM, 10nM, 100nM, 1 ⁇ M, 10 ⁇ M, 100 ⁇ M, 1mM, 10mM, 100mM result.
  • FIG. 6 is a graph of optical density distribution, wherein serial numbers 0-9 respectively represent optical density distribution curves when the mercury ion concentration is negative, 1nM, 10nM, 100nM, 1 ⁇ M, 10 ⁇ M, 100 ⁇ M, 1 mM, 10 mM, and 100 mM.
  • FIG. 7 is a graph showing a correspondence relationship between a peak area and a mercury ion concentration in a mercury standard solution.
  • FIG. 8 is a standard curve diagram of peak area and mercury ion concentration.
  • FIG. 9 is a schematic structural diagram of a quantitative detection and analysis system.
  • Example 1 Preparation of a lateral flow chromatography sensor based on nucleic acid base mismatch
  • Sequence 1 (nucleotide sequence on gold nanoparticles): 5’-ThioMC6-GGTGGTGGTGGTGG-3 ’
  • Sequence 2 (nucleotide sequence on the detection line): 5'-Biotin-CCCCCCCTCCTCCTCCTCC-3 '
  • Sequence 3 (nucleotide sequence on quality control line): 5'-Biotin-CCCCCCCACCACCACCACCACCACCACCACCACCACC-3 '
  • Sequence 1 is the SEQ ID in the sequence listing The 5 ′ end of the nucleotide sequence shown in 1 is obtained by ThioMC6 thiol modification;
  • Sequence 2 is the SEQ ID in the Sequence Listing The 5 'end of the nucleotide sequence shown in 2 is obtained after biotin labeling;
  • Sequence 3 is obtained by adding SEQ ID in the Sequence Listing Biotinylated at the 5 'end of the nucleotide sequence shown in 3.
  • the nucleic acid sequence coupled with the gold nanoparticle is fixed on the binding pad.
  • a specific fixing process refer to the reference described in step 1 above.
  • the above-prepared NC membrane and the bonding pad are prepared into a lateral flow chromatography sensor according to the existing method. Specifically, as shown in FIG. 1, the prepared NC membrane is fixed to the middle of the plastic low lining 1; The prepared bonding pad covers one end of the NC film 2 so that the bonding pad 3 and the NC film 2 partially overlap; the other end of the NC film 2 is covered with a water-absorbing pad (paper) 4 so that the NC film 2 and the water-absorbing pad (paper) 4 partially overlap; cover the sample pad 5 to the end of the bonding pad 3 away from the NC membrane 2 and partially overlap the bonding pad 3 and the sample pad 5; finally cover the protective film to prepare a side flow chromatography sensor for later use.
  • paper water-absorbing pad
  • the materials used for the NC film 2, the bonding pad 3, the sample pad 5, and the water-absorbing pad (paper) 4 are respectively a nitrocellulose film, a glass fiber film, a glass fiber film, and a water-absorbing paper.
  • the detection principle of a nucleic acid base mismatch side flow chromatography sensor is based on a sandwich structure (thymidine-rich nucleic acid sequence-mercury ion-thymidine-rich nucleic acid sequence), as shown in Figure 1, a section rich in The thymine base nucleic acid sequence is fixed on the detection line. Another thymine base-rich nucleic acid sequence is coupled to the gold nanoparticles and fixed on the binding pad. The adenine base-rich nucleic acid sequence is fixed on the quality control. on-line.
  • a sample containing a certain concentration of mercury ions is first dropped on the sample pad, and then the solution will move up to the binding pad in the direction of the chromatography sensor due to the capillary force (that is, the suction force of the water absorption pad or paper); and
  • the complexes on the binding pad that are rich in thymine base nucleic acid sequences and coupled with gold nanoparticles continue to move up to the detection line along the direction of the chromatography sensor; on the detection line, a certain concentration of mercury ions in the sample and two segments are rich in Thymine base nucleic acid sequences are combined to form a "T-Hg (II) -T" structure, allowing gold nanoparticles to be captured and deposited on the test line.
  • Red lines visible to the naked eye appear on the test line, and mercury ions in the sample The greater the concentration, the deeper the red; the excess of complexes rich in thymine base nucleic acid sequences and gold nanoparticles continues to move up to the quality control line, making the gold through the complementary pairing of thymine and adenine to make gold The nanoparticles were captured and accumulated on the quality control line, and red lines visible to the naked eye appeared on the quality control line. If the sample does not contain a certain concentration of mercury ions, the "T-Hg (II) -T" structure cannot be formed on the test line, and no gold nanoparticles are accumulated, so no red line that can be recognized by the naked eye will appear on the test line. .
  • Nucleic acid base mismatch-based lateral flow chromatography sensors prepared in Example 1 were used to detect different metal ion solutions, and the specificity of the sensor was tested, in which the Hg (II) concentration was 1 ⁇ M. Other metal ions The concentration is 1 mM.
  • Example 3 Quantitative detection of lateral flow tomographic sensors through a smartphone imaging analysis system
  • the lateral flow chromatography sensor described in Example 1 detects a mercury ion, a red line appears on the detection line and / or the quality control line. Therefore, by using an image containing red lines, and by establishing a standard curve corresponding to the mercury ion concentration in the mobile phone, the captured image containing red lines (or an image stored in the mobile phone in advance or an image downloaded through the mobile phone) can be used to detect mercury. Quantitative detection of ion concentration.
  • a series of mercury standard solutions of known concentration diluted by multiples were prepared.
  • the mercury ion concentrations in different mercury standard solutions were 0, 1nM, 10nM, 100nM, 1 ⁇ M, 10 ⁇ M, 100 ⁇ M, 1mM, 10mM, and 100mM.
  • the prepared mercury standard solutions of different concentrations were dropped on the sample pads of the side flow chromatography sensor based on the nucleic acid base mismatch prepared in Example 1. After about 5 minutes, the side flow chromatography sensor displayed Out of the test results.
  • an image showing a red line on the quality control line and / or the measured line as shown in FIG. 3 can be obtained, and the image can also be stored in advance Images on mobile phones, or images obtained through mobile phone downloads.
  • the optical density distribution curves shown in FIG. 6 are obtained.
  • different mercury ion concentration values for example, 0, 1 nM, 10 nM, 100 nM, 1 ⁇ M, 10 ⁇ M, 100 ⁇ M, 1 mM, 10 mM, 100 mM.
  • a curve is prepared by using the obtained peak area against the concentration value of mercury ions in a known mercury standard solution.
  • the lateral flow chromatography sensor will display the test result.
  • the test result is taken by the camera of the mobile phone to obtain a test image.
  • the photo result can be stored in the mobile phone or directly use;
  • the calculation method of the gray intensity value and peak area S value in the detection image is:
  • the ordinate is perpendicular to the abscissa, and all the ordinates in the detection image having the same abscissa x
  • the average value of the gray value Y is recorded as the gray level intensity value y of the column, and a gray level intensity P (x) function curve is established based on the gray level intensity value y and the abscissa value x of the obtained column;
  • the gray intensity function curve of the detection image with a resolution of m ⁇ n is:
  • Y is a gray value
  • x is an abscissa value
  • y is an ordinate value
  • m and n are resolutions of a detected image
  • the peak surface of the gray intensity function curve in the detection line region is selected, and the peak area is integrated to calculate the peak area S.
  • the obtained peak area S is input into the built-in standard curve, and the output concentration value C is calculated, that is, the concentration value corresponding to the detection line in the photograph of the detection result is output.
  • the smartphone imaging analysis system of this embodiment may be developed and designed based on the Android system.
  • the peak area obtained by using the smartphone imaging analysis system described in this embodiment has a good correlation with the mercury ion concentration; the side flow chromatography based on nucleic acid base mismatch prepared in Example 1
  • the minimum detection line that the sensor and the smartphone imaging analysis system described in this embodiment can achieve is 10 nM of mercury ions, with high sensitivity; the linear range is 10 nM to 1 mM, and the mercury ion in water can be quantitatively detected in this range.
  • FIG. 9 shows a schematic structural diagram of a quantitative detection and analysis system, including:
  • An image acquisition module an image acquisition module, an area image processing module, and a standard curve module
  • the image acquisition module is used to call a camera for image capture or read an image from a mobile phone storage device
  • the image acquisition module is used to intercept the image
  • the area image processing module is used to calculate the pixel gray value of the part, construct a gray intensity function, select a peak surface and calculate the peak surface area S according to the gray intensity function
  • the standard The curve module is used to input the standard curve and calculate and / or output the concentration of the test product;
  • the method for calculating the gray intensity function and the peak area S includes:
  • the flow direction of the sample to be measured on the flow-based paper-based tomographic sensor in the image is the direction of the abscissa, the ordinate is perpendicular to the abscissa, and gray in all the ordinates having the same abscissa x in the image
  • the average value of the degree value Y is recorded as the gray level intensity value y of the column, and the gray level intensity function curve of the obtained column is used to establish a gray level intensity function curve;
  • the gray intensity function curve of the image with a resolution of m ⁇ n is:
  • Y is a gray value
  • x is an abscissa value
  • y is an ordinate value
  • m and n are image resolutions
  • the peak area of the gray intensity function curve in the detection line region on the flow-based paper-based tomographic sensor in the image is selected and the peak area S is calculated by integrating and calculating the peak area.
  • the method for obtaining the standard curve includes:
  • each of the plurality of standard samples is detected by using a lateral flow paper-based tomographic sensor, and detection images of the detection results of the lateral flow paper-based tomographic sensor are respectively acquired and / or displayed by a mobile phone;
  • step 4) Take the concentration value C of the analyte in multiple standard samples or the logarithmic value lgC of the concentration value C of the analyte as the abscissa, and use the multiple obtained in step 3) to correspond to different concentrations of the analyte.
  • the value of the peak area S is plotted on the ordinate, and multiple discrete points are obtained.
  • the multiple discrete points are connected into a straight line.
  • the slope value a, the intercept between the straight line and the abscissa axis is the intercept value b, where C is the concentration of the analyte and S is the peak area S.

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Abstract

一种汞离子检测产品、方法及智能手机成像分析系统。一种基于核酸碱基错配的侧流层析传感器，包括序列1-3所示至少一种核苷酸序列，具有检测特异性和灵敏度。一种配合所述侧流层析传感器使用的智能手机成像分析系统，通过手机将侧流层析传感器上显示的检测结果转换为汞离子的浓度值，实现样品中汞离子的定量检测。上述汞离子检测产品、方法及智能手机成像分析系统，适合于未经培训的人员进行现场测试，对于食品安全、环境安全等现场检测提供便利。

Description

一种汞离子检测产品、方法及智能手机成像分析系统
本申请要求于2018年06月28日提交中国专利局、申请号为201810688361.8、发明名称为“一种汞离子检测产品、方法及智能手机成像分析系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明属于生物检测技术领域，具体涉及一种汞离子检测产品、方法及智能手机成像分析系统。
背景技术
水溶性二价汞离子是食品安全和饮用水安全中较为常见的重金属类风险因子，具有较强的生物富集性，对人体的危害较大，即使在极低浓度的情况下也会损害神经系统、消化系统、脑组织和肾组织。许多国家和组织调整了饮用水样本中汞离子的最大允许上限，例如世界卫生组织(World Health Organization,WH O)规定饮用水汞离子的最大允许限量不超过6ng mL -1(30nM)、美国环境保护局(Environmental Protection Agency,EPA)规定饮用水中汞离子的可接受限量为2ng mL -1(10nM)、欧盟(European Union,EU)饮用水标准和中国卫生部都规定汞离子的最高允许限量不超过1ng mL -1(5nM)。因此，痕量汞离子的检测是全球共同关注的问题。目前，基于“核酸碱基错配”识别体系构建传感器检测汞离子是主流的研究趋势，是指DNA的两个胸腺嘧啶碱可以错配结合一个汞离子形成稳定的“T-Hg(II)-T”结构。但是，这些传感器大多面临着体系较为复杂、不易定量检测的窘境。
侧流层析传感器作为一种新兴的快速检测平台，拥有快速、简单、专一、准确及灵敏等特点。但目前的侧流层析传感器只能实现定性或半定量检测，定量检测时需要额外的专用仪器,且目前还没有一种可以简单方便的从侧流层析传感器上直接读取定量检测数据的技术或便携的仪器。
发明内容
本发明提供了一种汞离子检测产品、方法及智能手机成像分析系统，可以通过手机将侧流层析传感器上显示的检测结果转换为汞离子的浓度值，以至少实现 了简单高效的定量检测样品中汞离子的浓度。本发明提供的基于核酸碱基错配的侧流层析传感器和/或配合使用的智能手机成像分析系统，非常适合于未经培训的人员进行现场测试，对于食品安全、环境安全等现场检测提供了很大的便利。
本发明的一个目的是提供组合物，组合物包括下述1)-3)中的至少一种：
1)序列表中SEQ ID
Figure PCTCN2018100985-appb-000001
1所示核苷酸序列；或将序列表中SEQ ID
Figure PCTCN2018100985-appb-000002
1所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加且与序列表中SEQ ID
Figure PCTCN2018100985-appb-000003
1所示核苷酸序列具有相同功能的核苷酸序列；具体的，所述功能包括下述(1)-(4)中的至少一种：(1)可特异识别或结合序列表中SEQ ID
Figure PCTCN2018100985-appb-000004
3所示核苷酸序列；(2)可特异识别或结合将序列表中SEQ ID
Figure PCTCN2018100985-appb-000005
3所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加的核苷酸序列；(3)当汞存在时，可与汞、序列表中SEQ ID
Figure PCTCN2018100985-appb-000006
2所示核苷酸序列形成T-Hg(II)-T结构；(4)当汞存在时，可与汞、将序列表中SEQ ID
Figure PCTCN2018100985-appb-000007
2所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加的核苷酸序列形成T-Hg(II)-T结构；
2)序列表中SEQ ID
Figure PCTCN2018100985-appb-000008
2所示核苷酸序列；或将序列表中SEQ ID
Figure PCTCN2018100985-appb-000009
2所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加且与序列表中SEQ ID
Figure PCTCN2018100985-appb-000010
2所示核苷酸序列具有相同功能的核苷酸序列；具体的，所述功能包括下述(1)-(2)中的至少一种：(1)当汞存在时，可与汞、序列表中SEQ ID
Figure PCTCN2018100985-appb-000011
1所示核苷酸序列形成T-Hg(II)-T结构；(2)当汞存在时，可与汞、将序列表中SEQ ID
Figure PCTCN2018100985-appb-000012
1所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加的核苷酸序列形成T-Hg(II)-T结构；
3)序列表中SEQ ID
Figure PCTCN2018100985-appb-000013
3所示核苷酸序列；或将序列表中SEQ ID
Figure PCTCN2018100985-appb-000014
3所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加且与序列表中SEQ ID
Figure PCTCN2018100985-appb-000015
3所示核苷酸序列具有相同功能的核苷酸序列。具体的，所述功能包括下述(1)-(2)中的至少一种：(1)可特异识别或结合序列表中SEQ ID
Figure PCTCN2018100985-appb-000016
1所示核苷酸序列；(2)可特异识别或结合将序列表中SEQ ID
Figure PCTCN2018100985-appb-000017
1所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加的核苷酸序列。
本发明的又一个目的是提供一种侧流层析传感器，该传感器包括以上任一项所述的组合物。
本发明的又一个目的是提供一种检测汞和/或汞离子的方法。该方法包括使用上面所述的所述组合物或侧流层析传感器进行检测。
本发明的又一个目的是提供一种从本发明任一所述侧流层析传感器上获取待测物浓度的方法，先将待测样品滴于测流层析传感器的样品垫区域，待测流层析传感器的检测线上显示检测结果后，进行定量分析获取待测物浓度，所述方法还包括：
1)通过手机获取和/或显示侧流层析传感器的检测结果的检测图像；
2)计算和/或输出所述检测图像中的测流层析传感器的检测线区域形成的灰度强度值和峰面积S；
3)手动向手机软件中输入所述侧流层析传感器的定量检测标准曲线S＝693.71lgC-1360.4，R 2＝0.9868，其中lgC为待测物浓度的对数值，S为步骤2)所述的峰面积S；
4)将步骤2)所得峰面积S值代入步骤3)所述定量检测标准曲线，计算并输出待测样品中待测物的浓度值，完成检测工作；
其中，所述检测图像中的测流层析传感器的检测线区域形成的灰度强度值和所述峰面积S值的计算方法包括：
以所述检测图像中待测样品在测流层析传感器上的流动方向为横坐标的方向，纵坐标与所述横坐标垂直，所述检测图像中具有相同横坐标x的所有纵坐标处的灰度值Y的平均值记为列的灰度强度值y，以所得列的灰度强度值y和横坐标值x建立灰度强度P(x)函数曲线；
所述灰度值Y计算方法为：Y＝0.299R+0.587G+0.114B，其中R、G、B为像素点的R、G、B值；
所述分辨率为m×n的检测图像的灰度强度函数曲线为：
[根据细则26改正19.10.2018]　
Figure WO-DOC-FIGURE-1
所述灰度强度函数曲线中，Y为灰度值，x为横坐标值，y为纵坐标值，m、n为检测图像的分辨率；
选择检测线区域内所述灰度强度函数曲线的峰面，积分计算其峰面积，即得峰面积S。
本发明的还一个目的是提供一种存储介质，所述存储介质包括存储的程序，其中，在所述程序运行时由处理器执行本发明任一所述的方法。
本发明的还一个目的是提供一种定量检测分析系统，包括：
图像采集模块，图像截取模块，区域图像处理模块，标准曲线模块，所述图像采集模块用于调用摄像头进行图像拍摄或从手机储存装置中读取图像，所述图像截取模块用于截取所述图像中需要检测的部分，所述区域图像处理模块用于计算所述部分的像素灰度值，构建灰度强度函数，根据所述灰度强度函数选择峰面并计算峰面面积S；所述标准曲线模块用于输入标准曲线和计算和/或输出待测品浓度；
其中，所述灰度强度函数、峰面积S的计算方法包括：
以所述图像中待测样品在测流纸基层析传感器上的流动方向为横坐标的方向，纵坐标与所述横坐标垂直，所述图像中具有相同横坐标x的所有纵坐标处的灰度值Y的平均值记为列的灰度强度值y，以所得列的灰度强度值y和横坐标值x建立灰度强度函数曲线；
所述灰度值Y计算方法为：Y＝0.299R+0.587G+0.114B，其中R、G、B为像素点的R、G、B值；
所述分辨率为m×n的图像的灰度强度函数曲线为：
[根据细则26改正19.10.2018]　
Figure WO-DOC-FIGURE-1
所述灰度强度函数曲线中，Y为灰度值，x为横坐标值，y为纵坐标值，m、n为图像的分辨率；
选择图像中测流纸基层析传感器上的检测线区域内所述灰度强度函数曲线的峰面，积分计算其峰面积，即得峰面积S。
具体的，所述标准曲线的的获得方法包括：
1)提供多个标准品样本，其中将多个标准品样本中的待测物的浓度按相同的倍数稀释；
2)利用侧流纸基层析传感器分别对所述多个标准品样本进行检测，通过手机分别获取和/或显示侧流纸基层析传感器的检测结果的检测图像；
3)计算和/或输出所述多个标准品样本的检测图像中的测流纸基层析传感器的检测线区域形成的多个峰面积S；
4)以多个标准品样本中的待测物浓度值C或待测物浓度值C的对数值lgC为横坐标，以步骤3)所得的多个与不同待测物浓度值对应的多个峰面积S值为纵坐标做图，得多个离散的点，将多个离散的点连接成直线，直线的斜率即为标 准曲线S＝a×C+b或S＝a×lgC+b中的斜率值a，直线与横坐标轴的截距即为截距值b，其中C为待测物浓度，S为峰面积S。
本发明的再一个目的是提供本发明任一所述组合物、发明任一所述侧流层析传感器、发明任一所述方法、发明任一所述存储介质、发明任一所述系统的应用。
具体的，所述应用包括定性检测或定量检测汞离子
本发明检测方法同其它检测技术相比，至少具有以下优点：
(1)核酸碱基错配侧流层析传感器：以金纳米颗粒为信号，利用可以特异性识别汞离子的富含胸腺嘧啶碱基(T)核酸序列与待测水样中的汞离子形成“T-Hg(II)-T”结构，在检测线上呈现肉眼可辨识的红色线条，线条颜色的深浅与汞离子的浓度呈正相关，至少解决了水中汞离子的快速识别并将其浓度迅速转化为可靠的光学信号的问题。
(2)智能手机成像分析系统：基于安卓系统进行开发，包括人机交互界面和图像处理算法设计两部分，用以实现侧流层析传感器的快速定量检测，用户可通过该系统直接读取侧流层析传感器检测出的待测目标物的浓度数值，至少解决了传统定量方法需额外使用体积大、价格昂贵、无法移动的仪器的问题。
(3)本发明提供的基于核酸碱基错配的侧流层析传感器和/或配合使用的智能手机成像分析系统，只对汞离子产生了信号响应，检测的特异性好；可以实现的最低检测线为10nM的汞离子，可以在10nM到1mM的线性范围内对液体中汞离子进行定量检测，检测的灵敏度高。
(4)本发明提供的基于核酸碱基错配的侧流层析传感器和/或配合使用的智能手机成像分析系统，非常适合于未经培训的人员进行现场测试，对于食品安全、环境安全等现场检测提供了很大的便利。
附图说明
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，并不构成对本申请的不当限定。在附图中：
图1为基于核酸碱基错配的侧流层析传感器的原理图，其中，序号1-5依次代表塑料低衬、NC膜、结合垫、吸水垫(纸)、样品垫。
图2为基于核酸碱基错配的侧流层析传感器的特异性实验结果图，其中，序号1-13分别依次代表Hg(II)、Zn(II)、Mg(II)、Pb(II)、Fe(III)、Fe(II)、Cu(II)、K(I)、Ca(II)、Mn(II)、Ag(I)、Au(III)、Ni(II)溶液的检测结果。
图3为侧流层析传感器显示出的检测结果的照片。
图4为光密度分布曲线图。
图5为侧流层析传感器显示出的检测结果的照片，其中，序号0-9分别依次代表汞离子浓度为阴性、1nM、10nM、100nM、1μM、10μM、100μM、1mM、10mM、100mM的检测结果。
图6为光密度分布曲线图，其中，序号0-9分别依次代表汞离子浓度为阴性、1nM、10nM、100nM、1μM、10μM、100μM、1mM、10mM、100mM时的光密度分布曲线图。
图7为峰面积与汞标准溶液中汞离子浓度的对应关系曲线图。
图8为峰面积与汞离子浓度的标准曲线图。
图9为一种定量检测分析系统的结构示意图。
具体实施方式
下述实施例中所使，用的实验方法如无特殊说明，均为常规方法。
下述实施例中未作具体说明的分子生物学实验方法，均参照《分子克隆实验指南》(第三版)J.萨姆布鲁克一书中所列的具体方法进行，或者按照试剂盒和产品说明书进行。
下述实施例中所用的材料、试剂等，如无特殊说明，均可从商业途径得到。
下述实施例及其具体说明用于解释和理解本申请，并不构成对本申请的不当限定。
实施例1、基于核酸碱基错配的侧流层析传感器的制备
(一)用于检测的核苷酸序列的设计
序列1(金纳米颗粒上核苷酸序列)：5’-ThioMC6-GGTGGTGGTGGTGG-3’
序列2(检测线上核苷酸序列)：5’-Biotin-CCCCCCCTCCTCCTCCTCC-3’
序列3(质控线上核苷酸序列)：5’-Biotin-CCCCCCCACCACCACCACC-3’
上述设计的所有核苷酸序列均通过人工合成获得。其中序列1为将序列表中SEQ ID
Figure PCTCN2018100985-appb-000020
1所示核苷酸序列的5’端进行ThioMC6巯基修饰后得到的；序列2为将序列表中SEQ ID
Figure PCTCN2018100985-appb-000021
2所示核苷酸序列的5’端进行生物素标记后得到的；序列3为将序列表中SEQ ID
Figure PCTCN2018100985-appb-000022
3所示核苷酸序列的5’端进行生物素标记后得到的。
(二)基于核酸碱基错配的侧流层析传感器的制备
1、将上述设计的命名为序列2的富含胸腺嘧啶碱基的核酸序列固定在NC 膜的检测线(Test Line，T线)上，具体固定过程可参考文献Nan Cheng,Yuancong Xu,Kunlun Huang,Yuting Chen,Zhanshen Yang,Yunbo Luo,Wentao Xu.One-step competitive lateral flow biosensor running on an independent quantification system for smart phones based in-situ detection of trace Hg(II)in water.Food Chemistry,2017,214:169-175.
2、将上述设计的命名为序列1的富含胸腺嘧啶碱基的核酸序列与金纳米颗粒偶联在一起；金纳米颗粒的制备及偶联过程均可参考上述步骤1所述参考文献。
3、将上述偶联有金纳米颗粒的核酸序列固定在结合垫上，具体固定过程可参考上述步骤1所述参考文献。
4、将上述设计的命名为序列3的富含腺嘌呤碱基的核酸序列固定在NC膜的质控线(Control Line,C线)上，具体固定过程也可参考上述步骤1所述参考文献。
5、将上述制备好的NC膜和结合垫按照现有方法制备成侧流层析传感器，具体可选：如图1所示，将制备好的NC膜固定到塑料低衬1的中部；将制备好的结合垫覆盖到NC膜2的一端，使得结合垫3与NC膜2部分重叠；将吸水垫(纸)4覆盖到NC膜2的另一端，使得NC膜2与吸水垫(纸)4部分重叠；将样品垫5覆盖到结合垫3远离NC膜2的一端，并使得结合垫3与样品垫5部分重叠；最后覆盖保护膜，制备成侧流层析传感器备用。
所述NC膜2、结合垫3、样品垫5、吸水垫(纸)4所使用的材料分别依次为硝酸纤维素膜、玻璃纤维膜、玻璃纤维膜、吸水纸。
(三)基于核酸碱基错配的侧流层析传感器的检测原理及过程
核酸碱基错配侧流层析传感器的检测原理是基于三明治结构(富含胸腺嘧啶碱基核酸序列-汞离子-富含胸腺嘧啶碱基核酸序列)，如图1所示，将一段富含胸腺嘧啶碱基核酸序列固定在检测线上，将另一段富含胸腺嘧啶碱基核酸序列与金纳米颗粒偶联在一起固定在结合垫上，将一段富含腺嘌呤碱基核酸序列固定在质控线上。在一个标准的检测中，含有一定浓度汞离子的样品首先被滴于样品垫上，之后溶液由于毛细管力(即吸水垫或纸的吸力)会随着层析传感器的方向向上移动到达结合垫；与结合垫上富含胸腺嘧啶碱基核酸序列与金纳米颗粒偶联的复合物一起继续随着层析传感器的方向向上移动到达检测线；在检测线上，样品中一定浓度汞离子与两段富含胸腺嘧啶碱基核酸序列结合，形成“T-Hg(II)-T” 结构，使金纳米颗粒被抓取并堆积于检测线上，检测线上出现肉眼可辨识的红色线条，样品中汞离子浓度越大，红色越深；过量的富含胸腺嘧啶碱基核酸序列与金纳米颗粒偶联的复合物继续向上移动到达质控线，通过胸腺嘧啶和腺嘌呤的碱基互补配对结合，使金纳米颗粒被抓取并堆积于质控线，质控线上出现肉眼可辨识的红色线条。若样品中不含有一定浓度汞离子，则在检测线上无法形成“T-Hg(II)-T”结构，也没有金纳米颗粒的堆积，因此检测线上不会出现肉眼可辨识的红色线条。
实施例2、基于核酸碱基错配的侧流层析传感器的特异性实验
利用实施例1所制备得到的基于核酸碱基错配的侧流层析传感器对不同的金属离子溶液进行了检测，测试该传感器的特异性，其中，Hg(II)浓度为1μM.其他金属离子浓度为1mM。
将待测样品滴于样品垫上，约5分钟后，侧流层析传感器会显示出检测结果。特异性实验结果如图2所示，该基于核酸碱基错配的侧流层析传感器只对汞离子产生了信号响应，说明该方法特异性良好。
实施例3、通过智能手机成像分析系统实现侧流层析传感器的定量检测
根据本公开具体实施方式即实施例1所述的侧流层析传感器对汞离子进行检测时，会在检测线和/或质控线上呈现出红色线条。因此利用包含红色线条的图像，通过在手机中建立与汞离子浓度对应的标准曲线，即可利用拍摄的包含红色线条的图像(或者是预先在手机存储的，或者通过手机下载的图像)对汞离子浓度进行定量检测。
(一)标准曲线的建立
配制一系列按倍数稀释的已知浓度的汞标准溶液，不同汞标准溶液中汞离子浓度依次为0、1nM、10nM、100nM、1μM、10μM、100μM、1mM、10mM、100mM。
将上述配制好的不同浓度的汞标准溶液分别滴于10个实施例1所制备的基于核酸碱基错配的侧流层析传感器的样品垫上，约5分钟后，侧流层析传感器会显示出检测结果。
通过手机的摄像头分别对上述侧流层析传感器显示出的检测结果拍照，即可获得如图3所示的在质控线和/或实测线呈现红色线条的图像，该图像也可以是预先存储在手机上的图像，或者是通过手机下载获得的图像。
然后，以侧流层析传感器的纵向延伸方向为横坐标，以每个横坐标对应的列的平均灰度值为纵坐标，即可得到如图4所示的曲线图像(即光密度分布曲线)。
选取检测线所在位置的曲线，计算该处曲线的峰面积(即对该曲线进行积分运算)，即可得到与特定的汞离子浓度对应的峰面积值。
通过以上方式，根据如图5所示的拍照结果，得到如图6所示的光密度分布曲线，根据所得曲线，分别计算出不同的汞离子浓度值(例如，0、1nM、10nM、100nM、1μM、10μM、100μM、1mM、10mM、100mM)对应的峰面积值。如图7所示，利用所得到的峰面积对已知的汞标准溶液中汞离子的浓度值制作曲线。最后通过Excel人工拟合计算得到如图8所示的标准曲线：S＝693.71lgC-1360.4，R 2＝0.9868，其中lgC为待测物汞离子浓度的对数值，S代表峰面积值。
(二)智能手机成像分析系统的建立
将上述拟合计算得到标准曲线：S＝693.71lgC-1360.4(R 2＝0.9868)内置到智能手机成像分析系统中；
将待测样品滴于样品垫上，约5分钟后，侧流层析传感器会显示出检测结果，通过手机的摄像头对该检测结果拍照，得检测图像，拍照结果可储存到手机中，也可直接使用；
检测图像中的灰度强度值和峰面积S值的计算方法为：
以所述检测图像中待测样品在测流层析传感器上的流动方向为横坐标的方向，纵坐标与所述横坐标垂直，所述检测图像中具有相同横坐标x的所有纵坐标处的灰度值Y的平均值记为列的灰度强度值y，以所得列的灰度强度值y和横坐标值x建立灰度强度P(x)函数曲线；
所述灰度值Y计算方法为：Y＝0.299R+0.587G+0.114B，其中R、G、B为像素点的R、G、B值；
所述分辨率为m×n的检测图像的灰度强度函数曲线为：
[根据细则26改正19.10.2018]　
Figure WO-DOC-FIGURE-1
所述灰度强度函数曲线中，Y为灰度值，x为横坐标值，y为纵坐标值，m、n为检测图像的分辨率；
选择检测线区域内所述灰度强度函数曲线的峰面，积分计算其峰面积，即得峰面积S。
将所得峰面积S输入所内置的标准曲线，计算输出浓度值C，即输出了所拍摄的检测结果照片中的检测线所对应的浓度值。
在一个具体的实施方案中，本实施例智能手机成像分析系统可基于安卓系统进行开发，设计。
(三)基于核酸碱基错配的侧流层析传感器和智能手机成像分析系统的汞离子定量检测的灵敏度
如图7、图8所示，利用本实施例所述的智能手机成像分析系统所得峰面积与汞离子浓度具有良好的相关性；实施例1制备的基于核酸碱基错配的侧流层析传感器和本实施例所述的智能手机成像分析系统可以实现的最低检测线为10nM的汞离子，灵敏度高；线性范围为10nM到1mM，可以在这个范围对水中汞离子进行定量检测。
此外，图9示出了一种定量检测分析系统的结构示意图，包括：
图像采集模块，图像截取模块，区域图像处理模块，标准曲线模块，所述图像采集模块用于调用摄像头进行图像拍摄或从手机储存装置中读取图像，所述图像截取模块用于截取所述图像中需要检测的部分，所述区域图像处理模块用于计算所述部分的像素灰度值，构建灰度强度函数，根据所述灰度强度函数选择峰面并计算峰面面积S；所述标准曲线模块用于输入标准曲线和计算和/或输出待测品浓度；
其中，所述灰度强度函数、峰面积S的计算方法包括：
以所述图像中待测样品在测流纸基层析传感器上的流动方向为横坐标的方向，纵坐标与所述横坐标垂直，所述图像中具有相同横坐标x的所有纵坐标处的灰度值Y的平均值记为列的灰度强度值y，以所得列的灰度强度值y和横坐标值x建立灰度强度函数曲线；
所述灰度值Y计算方法为：Y＝0.299R+0.587G+0.114B，其中R、G、B为像素点的R、G、B值；
所述分辨率为m×n的图像的灰度强度函数曲线为：
[根据细则26改正19.10.2018]　
Figure WO-DOC-FIGURE-1
所述灰度强度函数曲线中，Y为灰度值，x为横坐标值，y为纵坐标值，m、n为图像的分辨率；
选择图像中测流纸基层析传感器上的检测线区域内所述灰度强度函数曲线的峰面，积分计算其峰面积，即得峰面积S。
所述标准曲线的的获得方法包括：
1)提供多个标准品样本，其中将多个标准品样本中的待测物的浓度按相同的倍数稀释；
2)利用侧流纸基层析传感器分别对所述多个标准品样本进行检测，通过手机分别获取和/或显示侧流纸基层析传感器的检测结果的检测图像；
3)计算和/或输出所述多个标准品样本的检测图像中的测流纸基层析传感器的检测线区域形成的多个峰面积S；
4)以多个标准品样本中的待测物浓度值C或待测物浓度值C的对数值lgC为横坐标，以步骤3)所得的多个与不同待测物浓度值对应的多个峰面积S值为纵坐标做图，得多个离散的点，将多个离散的点连接成直线，直线的斜率即为标准曲线S＝a×C+b或S＝a×lgC+b中的斜率值a，直线与横坐标轴的截距即为截距值b，其中C为待测物浓度，S为峰面积S。

Claims (10)

  1. 一种组合物，其特征在于，所述组合物包括下述1)-3)中的至少一种：
    1)序列表中SEQ ID №：1所示核苷酸序列；或将序列表中SEQ ID №：1所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加且与序列表中SEQ ID №：1所示核苷酸序列具有相同功能的核苷酸序列；
    2)序列表中SEQ ID №：2所示核苷酸序列；或将序列表中SEQ ID №：2所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加且与序列表中SEQ ID №：2所示核苷酸序列具有相同功能的核苷酸序列；
    3)序列表中SEQ ID №：3所示核苷酸序列；或将序列表中SEQ ID №：3所示核苷酸序列经过一个或几个核苷酸的取代和/或缺失和/或添加且与序列表中SEQ ID №：3所示核苷酸序列具有相同功能的核苷酸序列。
  2. 根据权利要求1所述的组合物，其特征在于，所述组合物还包括下述1)-3)中的至少一种：
    1)所述序列表中SEQ ID №：1所示核苷酸序列的5’端修饰有巯基；
    2)所述序列表中SEQ ID №：2所示核苷酸序列的5’端标记有生物素；
    3)所述序列表中SEQ ID №：3所示核苷酸序列的5’端标记有生物素。
  3. 一种侧流层析传感器，其特征在于，所述侧流层析传感器包括权利要求1和/或2任一所述组合物。
  4. 根据权利要求3所述的侧流层析传感器，所述传感器包括质控线和检测线，其特征在于，所述侧流层析传感器还包括下述1)-4)中的至少一种：
    1)所述序列表中SEQ ID №：2所示核苷酸序列位于检测线上；
    2)所述侧流层析传感器还包括结合垫，所述序列表中SEQ ID №：1所示核苷酸序列与金纳米颗粒偶联在一起并位于结合垫上；
    3)所述序列表中SEQ ID №：3所示核苷酸序列位于质控线上；
    4)所述侧流层析传感器还包括低衬、NC膜、结合垫、吸水垫或纸、样品垫；所述NC膜位于低衬的中部；所述结合垫与NC膜的一端部分重叠，所述吸水垫或纸与NC膜的另一端部分重叠；所述样品垫与结合垫远离NC膜的一端部分重叠；所述质控线和检测线均位于所述NC膜上，其中，质控线位于靠近吸水垫或纸的一端，检测线位于靠近结合垫的一端。
  5. 一种检测汞和/或汞离子的方法，其特征在于，所述方法包括使用权利要 求1和/或2所述组合物，或使用权利要求3和/或4所述侧流层析传感器进行检测。
  6. [根据细则26改正19.10.2018]　
    一种从权利要求3和/或4所述侧流层析传感器上获取待测物浓度的方法，先将待测样品滴于测流层析传感器的样品垫区域，待测流层析传感器的检测线上显示检测结果后，进行定量分析获取待测物浓度，其特征在于，所述方法还包括：
    1)通过手机获取和/或显示侧流层析传感器的检测结果的检测图像；
    2)计算和/或输出所述检测图像中的测流层析传感器的检测线区域形成的灰度强度值和峰面积S；
    3)手动向手机软件中输入所述侧流层析传感器的定量检测标准曲线S＝693.71lgC-1360.4，R 2＝0.9868，其中lgC为待测物浓度的对数值，S为步骤2)所述的峰面积S；
    4)将步骤2)所得峰面积S值代入步骤3)所述定量检测标准曲线，计算并输出待测样品中待测物的浓度值，完成检测工作；
    其中，所述检测图像中的测流层析传感器的检测线区域形成的灰度强度值和所述峰面积S值的计算方法包括：
    以所述检测图像中待测样品在测流层析传感器上的流动方向为横坐标的方向，纵坐标与所述横坐标垂直，所述检测图像中具有相同横坐标x的所有纵坐标处的灰度值Y的平均值记为列的灰度强度值y，以所得列的灰度强度值y和横坐标值x建立灰度强度P(x)函数曲线；
    所述灰度值Y计算方法为：Y＝0.299R+0.587G+0.114B，其中R、G、B为像素点的R、G、B值；
    所述分辨率为m×n的检测图像的灰度强度函数曲线为：
    Figure WO-DOC-FIGURE-1

    所述灰度强度函数曲线中，Y为灰度值，x为横坐标值，y为纵坐标值，m、n为检测图像的分辨率；
    选择检测线区域内所述灰度强度函数曲线的峰面，积分计算其峰面积，即得峰面积S。
  7. 一种存储介质，所述存储介质包括存储的程序，其中，在所述程序运行时由处理器执行权利要求6所述的方法。
  8. [根据细则26改正19.10.2018]　
    一种定量检测分析系统，其特征在于，包括：
    图像采集模块，图像截取模块，区域图像处理模块，标准曲线模块，所述图像采集模块用于调用摄像头进行图像拍摄或从手机储存装置中读取图像，所述图像截取模块用于截取所述图像中需要检测的部分，所述区域图像处理模块用于计算所述部分的像素灰度值，构建灰度强度函数，根据所述灰度强度函数选择峰面并计算峰面面积S；所述标准曲线模块用于输入标准曲线和计算和/或输出待测品浓度；
    其中，所述灰度强度函数、峰面积S的计算方法包括：
    以所述图像中待测样品在测流纸基层析传感器上的流动方向为横坐标的方向，纵坐标与所述横坐标垂直，所述图像中具有相同横坐标x的所有纵坐标处的灰度值Y的平均值记为列的灰度强度值y，以所得列的灰度强度值y和横坐标值x建立灰度强度函数曲线；
    所述灰度值Y计算方法为：Y＝0.299R+0.587G+0.114B，其中R、G、B为像素点的R、G、B值；
    所述分辨率为m×n的图像的灰度强度函数曲线为：
    Figure WO-DOC-FIGURE-1

    所述灰度强度函数曲线中，Y为灰度值，x为横坐标值，y为纵坐标值，m、n为图像的分辨率；
    选择图像中测流纸基层析传感器上的检测线区域内所述灰度强度函数曲线的峰面，积分计算其峰面积，即得峰面积S。
  9. 根据权利要求8所述的系统，其特征在于，所述标准曲线的的获得方法包括：
    1)提供多个标准品样本，其中将多个标准品样本中的待测物的浓度按相同的倍数稀释；
    2)利用侧流纸基层析传感器分别对所述多个标准品样本进行检测，通过手机分别获取和/或显示侧流纸基层析传感器的检测结果的检测图像；
    3)计算和/或输出所述多个标准品样本的检测图像中的测流纸基层析传感器的检测线区域形成的多个峰面积S；
    4)以多个标准品样本中的待测物浓度值C或待测物浓度值C的对数值lgC 为横坐标，以步骤3)所得的多个与不同待测物浓度值对应的多个峰面积S值为纵坐标做图，得多个离散的点，将多个离散的点连接成直线，直线的斜率即为标准曲线S＝a×C+b或S＝a×lgC+b中的斜率值a，直线与横坐标轴的截距即为截距值b，其中C为待测物浓度，S为峰面积S。
  10. 权利要求1和/或2所述组合物、权利要求3和/或4所述侧流层析传感器、权利要求5或6所述方法、权利要求7所述存储介质、权利要求8和/或9所述系统的应用。
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