CN113960146A - Method and system for detecting sub-typing of lipoprotein - Google Patents
Method and system for detecting sub-typing of lipoprotein Download PDFInfo
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- 102000004895 Lipoproteins Human genes 0.000 title claims abstract description 86
- 108090001030 Lipoproteins Proteins 0.000 title claims abstract description 86
- 238000000034 method Methods 0.000 title claims abstract description 22
- 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 36
- 238000012545 processing Methods 0.000 claims abstract description 20
- 235000012000 cholesterol Nutrition 0.000 claims abstract description 17
- 230000003287 optical effect Effects 0.000 claims abstract description 13
- 238000001502 gel electrophoresis Methods 0.000 claims abstract description 7
- 238000007781 pre-processing Methods 0.000 claims abstract description 7
- 238000009795 derivation Methods 0.000 claims abstract description 6
- 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
- 238000010606 normalization Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract description 13
- 108010007622 LDL Lipoproteins Proteins 0.000 description 12
- 102000007330 LDL Lipoproteins Human genes 0.000 description 12
- 239000002245 particle Substances 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 4
- 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
- 238000010586 diagram Methods 0.000 description 3
- 108091008012 small dense LDL 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
- 230000015572 biosynthetic process Effects 0.000 description 1
- 208000029078 coronary artery disease Diseases 0.000 description 1
- 238000007405 data analysis 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
- 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
- 238000011160 research 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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- 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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- General Health & Medical Sciences (AREA)
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Abstract
The application discloses a lipoprotein subtyping detection system and a method, wherein the system comprises: the device comprises a scanning module, a calibration module, a processing module and a derivation module; the scanning module is used for scanning the lipoprotein optical density map obtained based on the gel electrophoresis method to obtain a scanned image; the calibration module is used for preprocessing the scanning image to obtain a calibration image; the processing module is used for calculating and solving 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 classified into up to 7 sub-classifications, from largest to smallest particles, designated LDL-1 to LDL-7, respectively. Low-density lipoprotein subtyping LDL-1 and LDL-2 with larger particle size was designated as type A, while LDL-3 to LDL-7 with smaller particle size was designated as type B. Meanwhile, large light LDL (lbLDL) and small dense LDL (sdLDL) are classified according to the particle diameter and density. In the prior art, the lipoprotein is detected mainly by an enzyme method. This detection method has a problem that specific contents of each of the lipoprotein subtypes cannot be obtained. However, studies have shown that, in all lipoprotein subtypes: sdLDL is more prone to oxidation, and is slowly cleared, more easily enters the arterial wall, promoting foam cell formation. Therefore, it is a necessary research direction for those skilled in the art to design a novel apparatus for detecting lipoprotein subtyping to overcome the problems of the existing detection methods and to obtain the specific content of each lipoprotein subtype more accurately.
Disclosure of Invention
The application discloses a method for detecting the subtyping of lipoprotein, which can realize the accurate detection of the cholesterol content of each subtyping of the lipoprotein.
A method for detecting the subtyping of lipoprotein, which comprises the following steps:
step 1: scanning a lipoprotein electrophoresis strip obtained based on a gel electrophoresis method to obtain an optical density map;
step 2: preprocessing the optical density map to obtain a calibration image;
and step 3: calculating and solving the cholesterol value of each lipoprotein subtype based on the calibration image;
and 4, step 4: and (4) deriving the processing result obtained in the step (3).
Preferably, in the method for detecting a subtyping of lipoprotein, the step 2 comprises:
step 21: acquiring a contour area of a test tube image in a scanned image, and splitting the scanned image into images to be cut corresponding to single test tubes 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 cutting on the image to be cut based on the analysis starting position and the analysis ending position to obtain a calibration image.
More preferably, in the method for detecting a subtyping of lipoprotein, the step 22 comprises:
step 221: respectively taking the long side of each image to be cut as an X axis and taking a pixel as a unit, and respectively calculating the pixel values in the short side of each image to be cut to be summed up and averaged;
step 222: respectively storing the obtained pixel values in the same numerical axis;
step 223: representing the axes as a curve graph;
step 224: taking a front slope of a second peak from the left side of the curve graph as an analysis starting position; and taking the front slope of the first peak from the right side of the curve graph as an analysis ending position.
Wherein: the threshold of the peak is a configurable parameter for omitting the wavelet peak interference term under the threshold. It is also a configurable threshold parameter how much height the detected peak will stop when the analysis start position and the analysis end position are obtained. The final determination of all configurable threshold parameters is an empirical parameter that is finally determined by trial and error.
More preferably, in the method for detecting a subtyping of lipoprotein, step 3 comprises:
step 31: respectively obtaining the pixel average value of each lipoprotein parting area in the test tube in the calibration image, and forming an array by using each pixel average value;
step 32: carrying out normalization processing on the array;
step 33: taking the average pixel value of each lipoprotein type in the array as a Y-axis coordinate and the index value of each lipoprotein type in the array as an X-axis coordinate, and performing curve fitting on each trace 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 sub-typing peak patterns of each lipoprotein to obtain a total area;
step 36: obtaining the ratio of the area of each lipoprotein subtyping peak pattern in the total area;
step 37: and (4) calculating the cholesterol value of each lipoprotein subtype based on the total cholesterol value input from the outside and the ratio obtained in the step (36).
By adopting the technical scheme: the quantitative analysis and the imaging display of each subparticle of the lipoprotein are realized, and experimenters are helped to quickly obtain the concentration and the size of each subparticle of the lipoprotein.
In order to realize the method for detecting the sub-typing of the lipoprotein, the application also discloses a system for detecting the sub-typing of the lipoprotein, 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 derivation module; the scanning module is used for scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method to obtain 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 solving the cholesterol value of each lipoprotein subtype based on the calibration image; and the export module is used for exporting the processing result obtained by the processing module.
Preferably, the system for detecting a subtyping of lipoprotein further comprises: the setting module is used for setting system parameters.
Compared with the prior art, the device is simple in structure and easy to realize. The following technical progress is achieved:
by adopting the technical scheme, quantitative detection and data analysis of each sub-type of the lipoprotein can be realized, and the method can be used for evaluating lipid metabolism.
Drawings
FIG. 1 is a block diagram of the modules of embodiment 1;
FIG. 2 is a flowchart of the operation of example 1;
FIG. 3 is an image of the test tube obtained by the scanning in step 1 of example 1;
FIG. 4 is a schematic diagram of the conversion of an image to be clipped into a lipoprotein subtyping peak pattern diagram in example 1;
FIG. 5 is a chart of the sub-typing peaks of lipoproteins in the test tube No. 03 of FIG. 3 corresponding to the conversion of the image to be cut;
FIG. 6 is a chart of the sub-typing peaks of lipoproteins in the test tube No. 04 in FIG. 3 corresponding to the conversion of the image to be cut;
FIG. 7 is a chart of the sub-typing peaks of lipoproteins in the test tube No. 05 corresponding to the cut image in FIG. 3;
FIG. 8 is a chart of the sub-typing peaks of lipoproteins into which the test tube No. 06 in FIG. 3 is converted;
FIG. 9 is a chart of the sub-typing peaks of lipoproteins in the test tube No. 08 in FIG. 3 corresponding to the conversion of the image to be cut;
FIG. 10 is a chart of the sub-typing peaks of lipoproteins into which the test tube No. 09 in FIG. 3 is converted from the images to be cut;
the correspondence between each reference numeral and the part 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 technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1:
a lipoprotein subtyping detection system comprising: the device comprises a scanning module 1, a calibration module 2, a processing module 3, a derivation module 4 and a setting module 5.
The scanning module 1 is used for scanning a lipoprotein electrophoresis strip obtained based on a gel electrophoresis method to obtain 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 cholesterol values of all lipoprotein subtypes in the calibration image, and comparing the cholesterol values of all lipoprotein subtypes with a preset standard value to obtain a comparison result; the derivation module 4 is configured to derive the comparison result. The setting module 5 is used for setting system parameters.
As shown in fig. 2 to 3, example 1:
the detection system for the subtyping of the lipoprotein is used for the subtyping detection of the lipoprotein, and comprises the following steps:
the lipoprotein in the serum or the plasma is stained and then is added to a gel column;
under the action of an electric field in an electrophoresis tank, various sub-types of the lipoprotein are sequentially separated according to the particle size by the molecular sieve effect of gel;
step 1: scanning lipoprotein electrophoresis bands obtained by gel electrophoresis to obtain optical density map shown in FIG. 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 scanned image, and splitting the scanned image into images to be cut corresponding to single test tubes 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 cutting on the image to be cut based on the analysis starting position and the analysis ending position to obtain a calibration image.
Wherein the step 22 comprises:
step 221: respectively taking the long side of each image to be cut as an X axis and taking a pixel as a unit, and respectively calculating the pixel values in the short side of each image to be cut to be summed up and averaged;
step 222: respectively storing the obtained pixel values in the same numerical axis;
step 223: representing the axes as a curve graph;
step 224: taking a front slope of a second peak from the left side of the curve graph as an analysis starting position; and taking the front slope of the first peak from the right side of the curve graph as an analysis ending position.
And step 3: calculating and obtaining the cholesterol value of each lipoprotein subtype based on the 6 calibration images;
specifically, step 3 includes:
step 31: respectively obtaining the pixel average value of each lipoprotein parting area in the test tube in the calibration image, and forming an array by using each pixel average value;
step 32: carrying out normalization processing on the array;
step 33: taking the average pixel value of each lipoprotein type in the array as a Y-axis coordinate and the index value of each lipoprotein type in the array as an X-axis coordinate, and performing curve fitting on each trace 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 specifically is as follows: taking the arrow direction as the electrophoresis direction of the gel column, and taking the scanning image of the gel column below the arrow, wherein the starting point is the very low density lipoprotein, and the end point is the high density lipoprotein. Dividing the gel column into sub-component areas according to the transverse direction of a test tube image according to the mobility of each subtype of lipoprotein, calculating the average value of pixels in each longitudinal pixel area of the gel column, obtaining a pixel average value array, forming a dense point set in the area, and then connecting the data to form a curve graph.
Step 34: obtaining the area of each lipoprotein subtyping peak pattern;
step 35: accumulating the areas of the sub-typing peak patterns of each lipoprotein to obtain a total area;
step 36: obtaining the ratio of the area of each lipoprotein subtyping peak pattern in the total area;
step 37: and (4) calculating the cholesterol value of each lipoprotein subtype based on the total cholesterol value input from the outside and the ratio obtained in the step (36).
The value of total cholesterol was found to be 3.63mmol/L, which was converted to 140 mg/dl.
The sub-typing peak pattern of lipoprotein converted in test tube No. 03 shown in FIG. 5 is exemplified:
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 concentrations were 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 appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A method for detecting the subtyping of lipoprotein, which is characterized by comprising the following steps:
step 1: scanning a lipoprotein electrophoresis strip obtained based on a gel electrophoresis method to obtain an optical density map;
step 2: preprocessing the optical density map to obtain a calibration image;
and step 3: calculating and solving the cholesterol value of each lipoprotein subtype based on the calibration image;
and 4, step 4: and (4) deriving the processing result obtained in the step (3).
2. The method for detecting lipoprotein subtyping according to claim 1, wherein the step 2 comprises:
step 21: acquiring a contour area of a test tube image in a scanned image, and splitting the scanned image into images to be cut corresponding to single test tubes 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 cutting on the image to be cut based on the analysis starting position and the analysis ending position to obtain a calibration image.
3. The method for detecting lipoprotein subtyping according to claim 2, wherein the step 22 comprises:
step 221: respectively taking the long side of each image to be cut as an X axis and taking a pixel as a unit, and respectively calculating the pixel values in the short side of each image to be cut to be summed up and averaged;
step 222: respectively storing the obtained pixel values in the same numerical axis;
step 223: representing the axes as a curve graph;
step 224: taking a front slope of a second peak from the left side of the curve graph as an analysis starting position; and taking the front slope of the first peak from the right side of the curve graph as an analysis ending position.
4. The method for detecting lipoprotein subtyping according to claim 1, wherein the step 3 comprises:
step 31: respectively obtaining the pixel average value of each lipoprotein parting area in the test tube in the calibration image, and forming an array by using each pixel average value;
step 32: carrying out normalization processing on the array;
step 33: taking the average pixel value of each lipoprotein type in the array as a Y-axis coordinate and the index value of each lipoprotein type in the array as an X-axis coordinate, and performing curve fitting on each trace 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 sub-typing peak patterns of each lipoprotein to obtain a total area;
step 36: obtaining the ratio of the area of each lipoprotein subtyping peak pattern in the total area;
step 37: and (4) calculating the cholesterol value of each lipoprotein subtype based on the total cholesterol value input from the outside and the ratio obtained in the step (36).
5. A system for detecting a subtyping of a lipoprotein, comprising: the device comprises a scanning module, a calibration module, a processing module and a derivation module;
the scanning module is used for scanning lipoprotein electrophoresis strips obtained based on a gel electrophoresis method to obtain 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 solving the cholesterol value of each lipoprotein subtype based on the calibration image;
and the export module is used for exporting the processing result obtained by the processing module.
6. The system for detecting lipoprotein subtyping according to claim 5, further comprising: the setting module is used for setting system parameters.
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