CN113960146B - Lipoprotein subtyping detection method and system - Google Patents
Lipoprotein subtyping detection method and system Download PDFInfo
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- 102000004895 Lipoproteins Human genes 0.000 title claims abstract description 83
- 108090001030 Lipoproteins Proteins 0.000 title claims abstract description 83
- 238000001514 detection method Methods 0.000 title claims abstract description 25
- HVYWMOMLDIMFJA-DPAQBDIFSA-N cholesterol Chemical compound C1C=C2C[C@@H](O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2 HVYWMOMLDIMFJA-DPAQBDIFSA-N 0.000 claims abstract description 38
- 235000012000 cholesterol Nutrition 0.000 claims abstract description 18
- 238000012545 processing Methods 0.000 claims abstract description 17
- 230000003287 optical effect Effects 0.000 claims abstract description 13
- 238000000034 method Methods 0.000 claims abstract description 12
- 238000001502 gel electrophoresis Methods 0.000 claims abstract description 7
- 238000007781 pre-processing Methods 0.000 claims abstract description 7
- 238000012360 testing method Methods 0.000 claims description 21
- 238000004458 analytical method Methods 0.000 claims description 20
- 238000001962 electrophoresis Methods 0.000 claims description 8
- 108010007622 LDL Lipoproteins Proteins 0.000 description 13
- 102000007330 LDL Lipoproteins Human genes 0.000 description 13
- 238000010586 diagram Methods 0.000 description 8
- 239000002245 particle Substances 0.000 description 6
- 108010010234 HDL Lipoproteins Proteins 0.000 description 3
- 102000015779 HDL Lipoproteins Human genes 0.000 description 3
- 108010062497 VLDL Lipoproteins Proteins 0.000 description 3
- 102000004190 Enzymes Human genes 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 208000029078 coronary artery disease Diseases 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 210000000497 foam cell Anatomy 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000037356 lipid metabolism Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002808 molecular sieve Substances 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 210000002966 serum Anatomy 0.000 description 1
- URGAHOPLAPQHLN-UHFFFAOYSA-N sodium aluminosilicate Chemical compound [Na+].[Al+3].[O-][Si]([O-])=O.[O-][Si]([O-])=O URGAHOPLAPQHLN-UHFFFAOYSA-N 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/26—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
- G01N27/416—Systems
- G01N27/447—Systems using electrophoresis
- G01N27/44704—Details; Accessories
- G01N27/44717—Arrangements for investigating the separated zones, e.g. localising zones
- G01N27/44721—Arrangements for investigating the separated zones, e.g. localising zones by optical means
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- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
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- Investigating Or Analysing Materials By Optical Means (AREA)
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Abstract
The application discloses lipoprotein subtyping detecting system and method, the system includes: the device comprises a scanning module, a calibration module, a processing module and a deriving module; the scanning module is used for scanning the lipoprotein optical density map obtained based on the gel electrophoresis method and obtaining a scanning image; the calibration module is used for preprocessing the scanned image to obtain a calibration image; the processing module is used for calculating and obtaining the cholesterol value of each lipoprotein subtype based on the calibration image; the export module is used for exporting the processing result obtained by the processing module. The invention can realize accurate detection of cholesterol content of each subtype of lipoprotein.
Description
Technical Field
The invention relates to the technical field of biological detection, in particular to a lipoprotein subtyping detection method and a lipoprotein subtyping detection system.
Background
Elevated Low Density Lipoprotein (LDL) cholesterol levels are one of the major risk factors for coronary heart disease. Low density lipoproteins can be divided into up to 7 subtypes, from the largest particle to the smallest particle, designated LDL-1 to LDL-7, respectively. The larger particle size low density lipoproteins subtyped LDL-1 and LDL-2 are designated as type A, while the smaller particle size subtyped LDL-3 to LDL-7 are designated as type B. Meanwhile, large and light LDL (lbLDL) and small and dense LDL (sdLDL) are classified according to the particle diameter and density. In the prior art, the lipoprotein content is detected mainly by an enzyme method. The problem with this assay is that the specific levels of each subtype of lipoprotein are not available. Whereas studies have shown that in all lipoprotein subtypes: sdLDL is more prone to oxidation and is cleared slowly and more easily into the arterial wall, promoting foam cell formation. Therefore, how to design a novel lipoprotein subtype detection device to overcome the problems of the existing detection methods and more accurately obtain the specific content of each lipoprotein subtype is the direction that the skilled person needs to study.
Disclosure of Invention
The application discloses a lipoprotein subtype detection method, which can realize accurate detection of cholesterol content of each lipoprotein subtype.
A lipoprotein subtyping detection method comprising the steps of:
step 1: scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method, and obtaining an optical density map;
step 2: preprocessing the optical density map to obtain a calibration image;
step 3: calculating the cholesterol value of each lipoprotein subtype based on the calibration image;
step 4: and (3) deriving the processing result obtained in the step (3).
Preferably, in the above lipoprotein subtype detection method, the step 2 includes:
step 21: acquiring a contour area of a test tube image in a scanning image, and splitting the scanning image into images to be cut corresponding to a single test tube based on the contour area of the test tube image;
step 22: analyzing the image to be cut, and automatically positioning the analysis starting position and the analysis ending position of the image to be cut:
step 23: and performing secondary cropping on the image to be cropped based on the analysis starting position and the analysis ending position to obtain a calibration image.
More preferably, in the above lipoprotein subtype detection method, the step 22 includes:
step 221: respectively taking the long side of each image to be cut as an X axis, and respectively taking pixels as units to calculate the total average of the pixel values in the short sides of each image to be cut;
step 222: respectively storing the obtained pixel values in the same numerical axis;
step 223: representing the number axis as a graph of curves;
step 224: taking the front hillside of the second crest from the left side of the curve graph as an analysis starting position; and taking the front hillside of the first crest on the right side of the curve graph as an analysis ending position.
Wherein: the threshold of the peak is a configurable parameter used to ignore small peak interference terms below this threshold. It is also a configurable threshold parameter to detect how high the peak will stop when the analysis start position and the analysis end position are acquired. All of the final determinations of the configurable threshold parameters are one of the empirical parameters that are determined by repeated experimentation.
Further preferably, in the above lipoprotein subtype detection method, step 3 includes:
step 31: respectively obtaining the average value of pixels of each lipoprotein parting region in the test tube in the calibration image, and forming an array by the average value of each pixel;
step 32: normalizing the array;
step 33: taking the average value of pixels of each lipoprotein type in the array as a Y-axis coordinate, taking the index value of each lipoprotein type in the array as an X-axis coordinate, and performing curve fitting on each tracing point in a secondary quadrant to obtain a lipoprotein subtyping peak pattern corresponding to each lipoprotein subtyping;
step 34: obtaining the area of each lipoprotein subtyping peak pattern;
step 35: accumulating the areas of the peak pattern images of the subtyping of each lipoprotein to obtain the total area;
step 36: obtaining the ratio of the area of each lipoprotein subtyping peak pattern to the total area;
step 37: based on the total cholesterol value input from the outside and the ratio obtained in step 36, the cholesterol value of each lipoprotein subtype is obtained.
By adopting the technical scheme: the quantitative analysis and the imaging display of each subtype of the lipoprotein are realized, and the concentration and the size of each subtype of the lipoprotein can be quickly obtained by an experimenter.
In order to realize the lipoprotein subtyping detection method, the application also discloses a lipoprotein subtyping detection system, which adopts the following technical scheme:
a lipoprotein subtyping detection system comprising: the device comprises a scanning module, a calibration module, a processing module and a deriving module; the scanning module is used for scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method and obtaining an optical density map; the calibration module is used for preprocessing the optical density map to obtain a calibration image; the processing module is used for calculating and obtaining the cholesterol value of each lipoprotein subtype based on the calibration image; the export module is used for exporting the processing result obtained by the processing module.
Preferably, the lipoprotein subtyping detection system further comprises: the setting module is used for setting system parameters.
Compared with the prior art, the novel device is simple in structure and easy to realize. The following technical progress is achieved:
by the technical scheme, quantitative detection and data analysis of each subtype of lipoprotein can be realized, and the method can be used for assessing lipid metabolism.
Drawings
FIG. 1 is a block diagram of a module of embodiment 1;
FIG. 2 is a workflow diagram of example 1;
FIG. 3 is an image of a test tube obtained by the scan of step 1 of example 1;
FIG. 4 is a schematic representation of the conversion of the image to be cropped into a lipoprotein subtyping peak pattern in example 1;
FIG. 5 is a diagram showing the subtyping peaks of lipoproteins converted from the images to be cut corresponding to the test tube No. 03 in FIG. 3;
FIG. 6 is a diagram showing the subtyping peaks of lipoproteins converted from the images to be cut corresponding to the test tube No. 04 in FIG. 3;
FIG. 7 is a diagram showing the subtyping peaks of lipoproteins converted from the images to be cut corresponding to the test tube No. 05 in FIG. 3;
FIG. 8 is a diagram showing the subtyping peaks of lipoproteins converted from images to be cut corresponding to the test tube No. 06 in FIG. 3;
FIG. 9 is a diagram showing the subtyping peaks of lipoproteins converted from images to be cut corresponding to the test tube No. 08 in FIG. 3;
FIG. 10 is a diagram showing the subtyping peaks of lipoproteins converted from images to be cut corresponding to the test tube No. 09 in FIG. 3;
the correspondence between each reference number and the component name is as follows:
1. a scanning module; 2. a calibration module; 3. a processing module; 4. a derivation module; 5. and setting a module.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1:
a lipoprotein subtyping detection system comprising: a scanning module 1, a calibration module 2, a processing module 3, a deriving module 4 and a setting module 5.
The scanning module 1 is used for scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method and obtaining an optical density map; the calibration module 2 is used for preprocessing the optical density map to obtain a calibration image; the processing module 3 is used for obtaining the cholesterol value of each lipoprotein subtype in the calibration image, and comparing the cholesterol value of each lipoprotein subtype with a preset standard value to obtain a comparison result; the deriving module 4 is configured to derive the comparison result. The setting module 5 is configured to set system parameters.
As shown in fig. 2-3, example 1:
based on the lipoprotein subtyping detection system, lipoprotein subtyping detection is carried out, and the method comprises the following steps:
the lipoprotein in the serum or the plasma is added to a gel column after being dyed;
under the action of an electric field in the electrophoresis tank, each subtype of lipoprotein is separated according to the particle size in sequence by virtue of the molecular sieve effect of gel;
step 1: scanning lipoprotein electrophoresis bands obtained based on gel electrophoresis, and obtaining an optical density map shown in figure 2;
step 2: preprocessing the optical density map to obtain a calibration image;
specifically, the step 2 includes:
step 21: acquiring a contour area of a test tube image in a scanning image, and splitting the scanning image into images to be cut corresponding to a single test tube based on the contour area of the test tube image;
step 22: analyzing the image to be cut, and automatically positioning the analysis starting position and the analysis ending position of the image to be cut:
step 23: and performing secondary cropping on the image to be cropped based on the analysis starting position and the analysis ending position to obtain a calibration image.
Wherein, the step 22 includes:
step 221: respectively taking the long side of each image to be cut as an X axis, and respectively taking pixels as units to calculate the total average of the pixel values in the short sides of each image to be cut;
step 222: respectively storing the obtained pixel values in the same numerical axis;
step 223: representing the number axis as a graph of curves;
step 224: taking the front hillside of the second crest from the left side of the curve graph as an analysis starting position; and taking the front hillside of the first crest on the right side of the curve graph as an analysis ending position.
Step 3: calculating the cholesterol value of each lipoprotein subtype based on the 6 calibration images;
specifically, step 3 includes:
step 31: respectively obtaining the average value of pixels of each lipoprotein parting region in the test tube in the calibration image, and forming an array by the average value of each pixel;
step 32: normalizing the array;
step 33: taking the average value of pixels of each lipoprotein type in the array as a Y-axis coordinate, taking the index value of each lipoprotein type in the array as an X-axis coordinate, and performing curve fitting on each tracing point in a secondary quadrant to obtain a lipoprotein subtyping peak pattern corresponding to each lipoprotein subtyping;
as shown in fig. 4, in the above steps, the process of converting the image to be cropped into the calibration image is specifically as follows: the direction of the arrow is taken as the electrophoresis direction of the gel column, the lower part of the arrow is taken as the scanning image of the gel column, wherein the starting point is very low density lipoprotein, and the end point is high density lipoprotein. The gel column is divided into areas of each subgroup according to the mobility of each subtype of lipoprotein and the transverse direction of the test tube image, the average value of pixels in each longitudinal pixel area of the gel column is calculated, so that a pixel average value array is obtained, a dense point set is formed in the area, and then the data are connected, so that a curve graph is formed.
Step 34: obtaining the area of each lipoprotein subtyping peak pattern;
step 35: accumulating the areas of the peak pattern images of the subtyping of each lipoprotein to obtain the total area;
step 36: obtaining the ratio of the area of each lipoprotein subtyping peak pattern to the total area;
step 37: based on the total cholesterol value input from the outside and the ratio obtained in step 36, the cholesterol value of each lipoprotein subtype is obtained.
The total cholesterol value obtained by the measurement was 3.63mmol/L, and was 140mg/dl in terms of the total cholesterol value.
Exemplified by the lipoprotein subtyping peak pattern converted into test tube No. 03 shown in fig. 5:
it can be seen that: the areas of VLDL, MID-C, MID-B, MID-A, LDL-1, LDL-2, LDL-3, LDL-4, LDL-5, LDL-6, LDL-7 and HDL were 15%, 2.9%, 4.3%, 8.1%, 13%, 13.9%, 11.7%, 11%, 3.9%, 0% and 16.2%, respectively.
So their concentration is calculated as:
VLDL＝140*15％＝21mg/dl；
MID-C＝140*2.9％＝4mg/dl；
MID-B＝140*4.3％＝6.02mg/dl≈6mg/dl；
MID-A＝140*8.1％＝11.34mg/dl≈11mg/dl。
LDL-1＝140*13％＝18.2mg/dl≈18mg/dl
LDL-2＝140*13.9％＝19.46mg/dl≈20mg/dl
LDL-3＝140*11.7％＝16.38mg/dl≈16mg/dl
LDL-4＝140*11％＝15.4mg/dl≈15mg/dl
LDL-5＝140*3.9％＝5.46mg/dl≈5mg/dl
LDL-6＝140*0％＝0mg/dl
LDL-7＝140*0％＝0mg/dl
HDL＝140*16.2％＝22.68mg/dl≈23mg/dl
although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A lipoprotein subtyping detection method, comprising the steps of:
step 1: scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method, and obtaining an optical density map;
step 2: preprocessing the optical density map to obtain a calibration image;
step 3: calculating the cholesterol value of each lipoprotein subtype based on the calibration image;
step 4: exporting the processing result obtained in the step 3; wherein, the step 2 comprises the following steps:
step 21: acquiring a contour area of a test tube image in a scanning image, and splitting the scanning image into images to be cut corresponding to a single test tube based on the contour area of the test tube image;
step 22: analyzing the image to be cut, and automatically positioning the analysis starting position and the analysis ending position of the image to be cut:
step 23: performing secondary cropping on the image to be cropped based on the analysis starting position and the analysis ending position to obtain a calibration image;
wherein, the step 22 includes:
step 221: respectively taking the long side of each image to be cut as an X axis, and respectively taking pixels as units to calculate the total average of the pixel values in the short sides of each image to be cut;
step 222: respectively storing the obtained pixel values in the same numerical axis;
step 223: representing the number axis as a graph of curves;
step 224: taking the front hillside of the second crest from the left side of the curve graph as an analysis starting position; taking the front hillside of the first crest on the right side of the curve graph as an analysis ending position;
the step 3 comprises the following steps:
step 31: respectively obtaining the average value of pixels of each lipoprotein parting region in the test tube in the calibration image, and forming an array by the average value of each pixel;
step 32: normalizing the array;
step 33: taking the average value of pixels of each lipoprotein type in the array as a Y-axis coordinate, taking the index value of each lipoprotein type in the array as an X-axis coordinate, and performing curve fitting on each tracing point in a secondary quadrant to obtain a lipoprotein subtyping peak pattern corresponding to each lipoprotein subtyping;
step 34: obtaining the area of each lipoprotein subtyping peak pattern;
step 35: accumulating the areas of the peak pattern images of the subtyping of each lipoprotein to obtain the total area;
step 36: obtaining the ratio of the area of each lipoprotein subtyping peak pattern to the total area;
step 37: based on the total cholesterol value input from the outside and the ratio obtained in step 36, the cholesterol value of each lipoprotein subtype is obtained.
2. A lipoprotein subtyping detection system based on the method of claim 1, comprising: the device comprises a scanning module, a calibration module, a processing module and a deriving module;
the scanning module is used for scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method and obtaining an optical density map;
the calibration module is used for preprocessing the optical density map to obtain a calibration image;
the processing module is used for calculating and obtaining the cholesterol value of each lipoprotein subtype based on the calibration image;
the export module is used for exporting the processing result obtained by the processing module.
3. The lipoprotein subtyping detection system of claim 2 further comprising: the setting module is used for setting system parameters.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US8031925B2 (en) * | 2007-01-09 | 2011-10-04 | The Board Of Regents Of The University Of Texas System | Method and computer-program product for detecting and quantifying protein spots |
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| JP2010127856A (en) * | 2008-11-28 | 2010-06-10 | National Institute Of Advanced Industrial Science & Technology | Method for detection and analysis using protein array |
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