CN104266954A - DSP (diarrhetic shellfish poison) detection and analysis method based on cell image sensor - Google Patents
DSP (diarrhetic shellfish poison) detection and analysis method based on cell image sensor Download PDFInfo
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Abstract
The invention discloses a DSP (diarrhetic shellfish poison) detection and analysis method based on a cell image sensor. The method is characterized by comprising the following steps: establishing the cell image sensor which is high in performance and low in cost, acquiring an image, converting an acquired RGB (red green blue) image to a grayscale image, binaryzating the image, matriculating the image, detecting a peak value, detecting the variation of a pulse image of a myocardial cell when in mechanical pulse, and detecting the mechanical pulse rate, pulse range and pulse interval of the myocardial cell; establishing a standard graph by detecting the response of the cell image sensor to different standard sample working solutions of the shellfish diarrhetic poisons in different concentrations; and detecting the response of the cell image sensor to the shellfish diarrhetic poisons of unknown concentration, comparing the detected response result with the standard graph, and semi-quantitatively calculating the concentration of the poisons. Compared with the existing shellfish diarrhetic poison detection and analysis method, the method is low in cost, simple in operation and capable of directly evaluating the toxicity of the poisons for a long time.
Description
Technical field
The present invention relates to the diarrhoeal Mycotoxin identification analytical technology of shellfish, particularly relate to the diarrhoeal Mycotoxin identification analytical approach of a kind of shellfish based on cell image sensor.
Background technology
The diarrhoeal toxin of marine aquatic product is the non-protein toxin that a class toxicity is very strong, and to be shellfish be gathered in enrichment in body by predation planktonic algae forms harmful organic substances.People can cause poisoning after consumption, even dead.The diarrhoeal toxins checking method of current domestic marine aquatic product uses mouse Bioexperiment method (MBA) usually, HPLC-MS (HPLC-MS) and enzyme linked immunosorbent detection technology (ELISA) etc.Experimental amount needed for MBA method is huge and there is very large individual difference, and the virulence level of toxin may be underestimated.Although HPLC-MS has the wide advantage of sensing range, its equipment is huge and expensive.There is the expensive and high deficiency of testing cost equally in the enzyme linked immunosorbent detection technology such as ELISA.Cell image sensor adopts in vitro myocardial cells culture, builds high-performance and cell image sensor with low cost, for the detection analysis of the diarrhoeal toxin of marine aquatic product.In addition, the detection method of graphical analysis is adopted, can be directly perceived, the effect of endotoxins on cells is observed on long-time and unicity ground.
Summary of the invention
The object of the invention is to for the deficiencies in the prior art, provide a kind of shellfish based on cell image sensor diarrhoeal Mycotoxin identification analytical approach.
The object of the invention is to be achieved through the following technical solutions: the diarrhoeal Mycotoxin identification analytical approach of a kind of shellfish based on cell image sensor, the method realizes in the diarrhoeal Mycotoxin identification analytic system of shellfish, and the diarrhoeal Mycotoxin identification analytic system of described shellfish comprises: CCD camera, cardiac muscle cell's sensor culture plate, inverted microscope and computing machine; Wherein, cardiac muscle cell's sensor culture plate is fixed on the objective table of inverted microscope; CCD camera is fixed on above inverted microscope; CCD camera is connected with computing machine by USB connecting line; The method comprises the following steps:
(1) cultivation of cardiac muscle cell: obtain cardiac muscle cell to be measured, cultivate in high glucose medium, make cell suspension; After viable count, archaeocyte suspension is mixed with 170, the cell suspension of 000/ml; Last selection arbitrarily in cardiac muscle cell's sensor culture plate adds 100 μ l cell suspensions in a hole, cell quantity in hole is made to be 17000/hole, cardiac muscle cell's sensor culture plate is placed in incubator and cultivates 96 hours, cardiac muscle cell is well attached on cardiac muscle cell's sensor culture plate, constructs cell image sensor;
(2) prepare the working fluid of diarrhoeal toxin to be measured: the standard model solution storage liquid being mixed with 200 μ g/L with dimethyl sulfoxide (DMSO) (DMSO), dilute storage liquid successively with high glucose medium, obtain the working fluid of at least three variable concentrations gradients;
(3) control group scheming cell machinery pulsatile status detect: first cardiac muscle cell's sensor culture plate is placed on inverted microscope on objective table, use 40 times of object lens and 10 times of eyepieces, the position of adjustment inverted microscope objective table and focusing knob, clearly can see cardiac muscle cell in the visual field; Carry out scheming cellular beating image acquisition by computing machine control CCD camera, then calculate scheming cell mechanical beats curve; Calculate control group beat rates, pulsatile range and gap state parameter of beating finally by scheming cell mechanical beats opisometer, specifically comprise following sub-step:
(3.1) cardiac muscle cell of collection to be beaten the first frame two field picture in contrast of image;
(3.2) contrast two field picture is carried out gray processing, the gray processing formula of employing is:
Gray=R×0.299+G×0.587+B×0.114
Wherein, Gray refers to the gray-scale value after image pixel binaryzation, and R, G and B refer to the value of original image pixels red, green and blue passage respectively;
(3.3) adopt large law to carry out binaryzation to the image after step 3.2 gray processing, T is designated as the segmentation threshold of display foreground and background, w
0be designated as foreground pixel to count the ratio of with image total pixel number, display foreground average gray is u
0; w
1for background pixel is counted the ratio of with image total pixel number, image background average gray is u1; U is designated as the overall average gray scale of image, computing formula is u=w
0× u
0+ w
1× u
1; G is designated as maximum between-cluster variance, from minimal gray to maximum gradation value, travel through T, according to computing formula G=w
0× (u
0-u)
2+ w1 × (u
1-u)
2, when T makes G maximum, the T got now is best segmentation threshold; Then according to T, what image pixel gray level value is less than T is taken as 0, and what image pixel gray level value was greater than T is taken as 1, realizes the binaryzation of gray level image;
(3.4) gather cardiac muscle cell subsequently and beat the sequence frame image of image as real-time frame image, according to step (3.2) and (3.3), gray processing and binary conversion treatment are carried out to real-time frame image;
(3.5) the real-time frame image after gray processing is done image subtraction with the two field picture that contrasts after gray processing, obtain subtraction image; Then subtraction image is carried out the matrixing of image slices vegetarian refreshments, obtain image array, now matrix element value be-1,0 and 1 three one of them;
(3.6) absolute value is carried out to image matrix element, then element summation is carried out to the image array after absolute value, itself and be image difference value of beating;
(3.7) take time as horizontal ordinate, the image difference value of beating of the real-time frame image that step 3.6 calculates is ordinate curve plotting, and this curve is cardiac muscle cell's mechanical beats curve;
(3.8) wavelet transformation is carried out to cardiac muscle cell's mechanical beats curve, adopt 7 layers of multiscale analysis method;
(3.9) the approximation component A7 in 7 layers of multiscale analysis result, details coefficients D1, D2 and D3 are carried out zero setting, then adopt wavelet inverse transformation reconstruct cardiac muscle cell mechanical beats curve, namely remove the cardiac muscle cell's mechanical beats curve after baseline noise reduction;
(3.10) mean square deviation of the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction is calculated, and be decided to be threshold value: the site being greater than threshold value in the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction is designated as 1, the site being less than threshold value is designated as 0, and then carrying out difference, Dependence Results numerical value is 1,0 and-1 thrin; The wherein left hand edge in curve values to be the site of 1 be crest site, curve values be-1 site be the right hand edge in crest site;
(3.11) according to step (3.10) left hand edge that draws and right hand edge site, obtain in its interval the maximal value of the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction, maximal value site is crest site; Obtain the minimum value that the cardiac muscle cell's mechanical beats curve after baseline noise reduction is removed in its interval, minimum value site is trough site; The difference of maxima and minima is cardiac muscle cell's mechanical beats amplitude; Time interval ratio between continuous print crest site, is cardiac muscle cell's mechanical beats gap;
(3.12) every 30 seconds statistics crest site numbers, pulsatile range and gaps of beating, statistics crest site number is designated as the mean speed of 30 seconds myocardium cellular beatings; Take time as x-axis, the mean speed that cardiac muscle cell is beaten is y-axis, builds cardiac muscle cell and to beat mean speed curve; Take time as x-axis, pulsatile range is y-axis, builds cardiac muscle cell's pulsatile range curve; Take time as x-axis, cardiac muscle cell gap of beating is y-axis, builds cardiac muscle cell and to beat gap curve;
(4) standard diagram of toxin to be measured is built: the volume after step (2) being diluted is that the working fluid of the variable concentrations gradient of 20 μ l adds in cardiac muscle cell's sensor culture plate respectively, repeat step (3), detect the beat curve of cardiac muscle cell under the working fluid effect of variable concentrations gradient, beat rates, pulsatile range and gap state parameter of beating; The identical parameters of the beat rates of gained, pulsatile range and beat gap and step (3) control group gained is adopted normalized, namely using the state parameter of each time point of control group as benchmark, state parameter under drug effect, compared with the benchmark of synchronization control group, is normalized calculating; The standard diagram in cardiac muscle cell's beat rates of toxin to be measured, pulsatile range and gap of beating is built by normalization result of calculation;
(5) prepare the diarrhoeal toxin sample solution of marine aquatic product shellfish to be measured: prepare sample solution according to GB GB/T 5009.212-200, the diarrhoeal toxin contained in described 1ml sample solution is equivalent to the diarrhoeal toxin contained by marine aquatic product to be measured that 20g shells;
(6) virulence analyzing the diarrhoeal toxin of marine aquatic product shellfish to be measured is detected: repeat step (3), obtain beat rates, the pulsatile range of sample solution and gap curve of beating, the standard diagram comparison of setting up with step (4), can draw the concentration ranges of sample solution; Then the diarrhoeal toxin contained by the 1ml sample solution of step (5) is equivalent to the relation of the diarrhoeal toxin contained by marine aquatic product to be measured that 20g shells, draw the diarrhoeal content of toxins of shellfish, by beat rates, pulsatile range and gap curvilinear motion of beating, analyze shellfish diarrhoeal toxin toxicity to the time dependent impact of cardiac muscle cell.
The invention has the beneficial effects as follows: the inventive method have with low cost and can for a long time, observe to visualize the effect change of endotoxins on cells thus the advantages such as assessment toxin virulence.In the diarrhoeal Mycotoxin identification analytical approach of the more existing shellfish of the present invention, there is operation steps simple, when cost is low and long, the advantages such as shellfish diarrhoeal toxin toxicity action change are observed on visualize ground, without the need to other steps except easy steps such as preparation standard solution and inoculating cell etc.According to above advantage, the inventive method can become the new tool of ocean Mycotoxin identification analysis field, and is widely used in this field.
Accompanying drawing explanation
Fig. 1 is the detection system one-piece construction figure that the inventive method uses;
Fig. 2 is the inventive method process flow diagram;
Fig. 3 is the Dependence Results figure of beating that cell image sensor of the present invention detects okadaic acid (OA);
Fig. 4 is the beat rates result figure of OA oxicity analysis of the present invention;
Fig. 5 is the pulsatile range result figure of OA oxicity analysis of the present invention;
Fig. 6 is the gap result figure of beating of OA oxicity analysis of the present invention;
In figure: CCD camera 1, cell image sensor 2, inverted microscope 3, USB connecting line 4, computing machine 5.
Embodiment
Below in conjunction with drawings and the specific embodiments, the present invention is described in detail, but be not restriction the present invention.
The present invention is based on the diarrhoeal Mycotoxin identification analytical approach of shellfish of cell image sensor, the method realizes in the diarrhoeal Mycotoxin identification analytic system of shellfish, as shown in Figure 1, the diarrhoeal Mycotoxin identification analytic system of shellfish comprises: CCD camera 1, cardiac muscle cell's sensor, inverted microscope 3 and computing machine 5; Wherein, cell image sensor 2 is fixed on the objective table of inverted microscope 3; CCD camera 1 is fixed on above inverted microscope 3, thus gathers cell image sensor culture plate 1 picture signal; CCD camera 1 is connected with computing machine 5 by USB connecting line 4, thus collection signal is transferred to computing machine 5 and carries out aftertreatment; The method comprises the following steps:
(1) cultivation of cardiac muscle cell: the high glucose medium (DMEM) rat heart apex being placed in precooling; Then the apex of the heart after rinsing is organized in the DMEM of precooling and removes atrium and vascular tissue; In 5ml vial, add the balanced salt solution (HBSS) of 2ml precooling afterwards, the apex of the heart is transferred in HBSS, be cut into 1mm
3fritter, add collagenase solution, this collagenase solution is 0.07% trypsase and massfraction by massfraction is that 0.05% mouse collagen enzyme II mixes in HBSS; In vial, add the DMEM nutrient culture media that 5ml contains percent by volume 10% hyclone (FBS) in collagenase solution postdigestive remnant tissue block, collection supernatant is placed in the DMEM nutrient culture media containing percent by volume 10%FBS; By the centrifugal 5min of mixed supernatant 800rpm, in precipitation, add 5ml high glucose medium blow and beat gently with re-suspended cell; Resuspended cardiac muscle cell is crossed 200 order cell sieves, and by cell harvesting to 5ml high glucose medium, form new cell suspension and put into 50ml centrifuge tube; Cell suspension is collected in culture flask, carry out differential velocity adherent 2 times, each 45min, to remove fibrocyte and other cell; Afterwards the myocardial cell suspensions after differential velocity adherent is transferred in 50ml centrifuge tube and carry out cell count; Then draw 100 μ l cell suspensions, mixing adds 100 μ l trypan blue dye liquors and under being placed in room temperature, carries out viable count after 1min; After counting, the cell suspension in culture flask is mixed with 170, the cell suspension of 000/ml; Last selection arbitrarily in cardiac muscle cell's sensor culture plate 1 adds 100 μ l cell suspensions in a hole, cell quantity in hole is made to be 17000/hole, cardiac muscle cell's sensor culture plate 1 is placed in incubator and cultivates 96 hours, cardiac muscle cell is well attached on cardiac muscle cell's sensor culture plate 1, constructs cell image sensor.
(2) prepare the working fluid of diarrhoeal toxin to be measured: the standard model solution storage liquid being mixed with 200 μ g/L with dimethyl sulfoxide (DMSO) (DMSO), dilute storage liquid successively with high glucose medium, obtain the working fluid of at least three variable concentrations gradients.
(3) control group scheming cell machinery pulsatile status detect: first cardiac muscle cell's sensor culture plate 1 is placed on inverted microscope 3 on objective table, use 40 times of object lens and 10 times of eyepieces, the position of adjustment inverted microscope 3 objective table and focusing knob, clearly can see cardiac muscle cell in the visual field; The frame per second of CCD camera 1 is set to 24fps; Carry out scheming cellular beating image acquisition by computing machine 5 control CCD camera 1, then calculate scheming cell mechanical beats curve, as shown in Figure 2; Calculate control group beat rates, pulsatile range and gap state parameter of beating finally by scheming cell mechanical beats opisometer, specifically comprise following sub-step:
(3.1) cardiac muscle cell of collection to be beaten the first frame two field picture in contrast of image;
(3.2) contrast two field picture is carried out gray processing, the gray processing formula of employing is:
Gray=R×0.299+G×0.587+B×0.114
Wherein, Gray refers to the gray-scale value after image pixel binaryzation, and R, G and B refer to the value of original image pixels red, green and blue passage respectively;
(3.3) adopt large law to carry out binaryzation to the image after step 3.2 gray processing, T is designated as the segmentation threshold of display foreground and background, w
0be designated as foreground pixel to count the ratio of with image total pixel number, display foreground average gray is u
0; w
1for background pixel is counted the ratio of with image total pixel number, image background average gray is u1; U is designated as the overall average gray scale of image, computing formula is u=w
0× u
0+ w
1× u
1; G is designated as maximum between-cluster variance, from minimal gray to maximum gradation value, travel through T, according to computing formula G=w
0× (u
0-u)
2+ w1 × (u
1-u)
2, when T makes G maximum, the T got now is best segmentation threshold; Then according to T, what image pixel gray level value is less than T is taken as 0, and what image pixel gray level value was greater than T is taken as 1, realizes the binaryzation of gray level image;
(3.4) gather cardiac muscle cell subsequently and beat the sequence frame image of image as real-time frame image, according to step (3.2) and (3.3), gray processing and binary conversion treatment are carried out to real-time frame image;
(3.5) the real-time frame image after gray processing is done image subtraction with the two field picture that contrasts after gray processing, obtain subtraction image; Then subtraction image is carried out the matrixing of image slices vegetarian refreshments, obtain image array, now matrix element value be-1,0 and 1 three one of them;
(3.6) absolute value is carried out to image matrix element, then element summation is carried out to the image array after absolute value, itself and be image difference value of beating;
(3.7) take time as horizontal ordinate, the image difference value of beating of the real-time frame image that step 3.6 calculates is ordinate curve plotting, and this curve is cardiac muscle cell's mechanical beats curve;
(3.8) wavelet transformation is carried out to cardiac muscle cell's mechanical beats curve, adopt 7 layers of multiscale analysis method;
(3.9) the approximation component A7 in 7 layers of multiscale analysis result, details coefficients D1, D2 and D3 are carried out zero setting, then adopt wavelet inverse transformation reconstruct cardiac muscle cell mechanical beats curve, namely remove the cardiac muscle cell's mechanical beats curve after baseline noise reduction;
(3.10) mean square deviation of the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction is calculated, and be decided to be threshold value: the site being greater than threshold value in the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction is designated as 1, the site being less than threshold value is designated as 0, and then carrying out difference, Dependence Results numerical value is 1,0 and-1 thrin; The wherein left hand edge in curve values to be the site of 1 be crest site, curve values be-1 site be the right hand edge in crest site;
(3.11) according to the left hand edge drawn in sub-step (3.10) and right hand edge site, obtain in its interval the maximal value of the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction, maximal value site is crest site; Obtain the minimum value that the cardiac muscle cell's mechanical beats curve after baseline noise reduction is removed in its interval, minimum value site is trough site; The difference of maxima and minima is cardiac muscle cell's mechanical beats amplitude; Time interval ratio between continuous print crest site, is cardiac muscle cell's mechanical beats gap;
(3.12) every 30 seconds statistics crest site numbers, pulsatile range and gaps of beating, statistics crest site number is designated as the mean speed of 30 seconds myocardium cellular beatings; Take time as x-axis, the mean speed that cardiac muscle cell is beaten is y-axis, builds cardiac muscle cell and to beat mean speed curve; Take time as x-axis, pulsatile range is y-axis, builds cardiac muscle cell's pulsatile range curve; Take time as x-axis, cardiac muscle cell gap of beating is y-axis, builds cardiac muscle cell and to beat gap curve.
(4) standard diagram of toxin to be measured is built: the volume after step (2) being diluted is that the working fluid of the variable concentrations gradient of 20 μ l adds in cardiac muscle cell's sensor culture plate 1 respectively, repeat step (3), detect the beat curve of cardiac muscle cell under the working fluid effect of variable concentrations gradient, beat rates, pulsatile range and gap state parameter of beating; As shown in Figure 3, when being 10 minutes, control group, 10ng/ml, 40ng/ml and 160ng/ml standard model Solution Cell imageing sensor are beaten curve map; The identical parameters of the beat rates of gained, pulsatile range and beat gap and step (3) control group gained is adopted normalized, namely using the state parameter of each time point of control group as benchmark, state parameter under drug effect, compared with the benchmark of synchronization control group, is normalized calculating; The standard diagram in cardiac muscle cell's beat rates of toxin to be measured, pulsatile range and gap of beating is built by normalization result of calculation; As shown in Fig. 4,5 and 6, be respectively the standard diagram that beat rates, pulsatile range and gap parameter of beating are set up;
(5) prepare marine aquatic product shellfish to be measured diarrhoeal toxin sample solution: prepare sample solution according to GB GB/T 5009.212-2008: be placed in homogeneous cup by foreign-water product to be measured, add 3 times of volume acetone and stir at least 5min; Pour the potpourri be stirred in Buchner funnel suction filtration, collect extract; Moved into by extract in the round-bottomed flask of 500ml, adjustment rotary evaporator, bath temperature is 56 DEG C ± 1 DEG C, and reduced pressure concentration removes acetone until isolate grease at liquid surface; Concentrate is moved in separating funnel, wash lower sticky wall portion with 100ml ~ 200ml ether, vibrate (can not emulsion be generated) gently, after stratification, remove water layer (lower floor); With the distillation washing ether layer twice of suitable ether half amount volume, then move in the round-bottomed flask of 250ml or 500ml by ether layer, reduced pressure concentration (rotary evaporator, 35 DEG C ± 1 DEG C) removes ether; Be that whole concentrate is diluted to 10ml, shake well by the cell culture media solution of the dimethyl sulfoxide (DMSO) (DMSO) of 0.1% in scale test tube with massfraction, make even DSP-0.1%DMSO cell culture media solution, i.e. testing sample solution; The diarrhoeal toxin that 1ml sample solution contains is equivalent to the diarrhoeal toxin contained by marine aquatic product to be measured that 20g shells;
(6) virulence analyzing the diarrhoeal toxin of marine aquatic product shellfish to be measured is detected: repeat step (3), obtain beat rates, the pulsatile range of sample solution and gap curve of beating, the standard diagram comparison of setting up with step (4), can draw the concentration ranges of sample solution; Then the diarrhoeal toxin contained by the 1ml sample solution of step (5) is equivalent to the relation of the diarrhoeal toxin contained by marine aquatic product to be measured that 20g shells, draw the diarrhoeal content of toxins of shellfish, by beat rates, pulsatile range and gap curvilinear motion of beating, analyze shellfish diarrhoeal toxin toxicity to the time dependent impact of cardiac muscle cell.
Claims (1)
1. the diarrhoeal Mycotoxin identification of the shellfish based on a cell image sensor analytical approach, the method realizes in the diarrhoeal Mycotoxin identification analytic system of shellfish, and the diarrhoeal Mycotoxin identification analytic system of described shellfish comprises: CCD camera (1), cardiac muscle cell's sensor culture plate (1), inverted microscope (3) and computing machine (5); Wherein, cardiac muscle cell's sensor culture plate (1) is fixed on the objective table of inverted microscope (3); CCD camera (1) is fixed on inverted microscope (3) top; CCD camera (1) is connected with computing machine (5) by USB connecting line (4); It is characterized in that, the method comprises the following steps:
(1) cultivation of cardiac muscle cell: obtain cardiac muscle cell to be measured, cultivate in high glucose medium, make cell suspension; After viable count, archaeocyte suspension is mixed with 170, the cell suspension of 000/ml; Last selection arbitrarily in cardiac muscle cell's sensor culture plate (1) adds 100 μ l cell suspensions in a hole, cell quantity in hole is made to be 17000/hole, cardiac muscle cell's sensor culture plate (1) is placed in incubator and cultivates 96 hours, cardiac muscle cell is well attached on cardiac muscle cell's sensor culture plate (1), constructs cell image sensor;
(2) prepare the working fluid of diarrhoeal toxin to be measured: the standard model solution storage liquid being mixed with 200 μ g/L with dimethyl sulfoxide (DMSO) (DMSO), dilute storage liquid successively with high glucose medium, obtain the working fluid of at least three variable concentrations gradients;
(3) control group scheming cell machinery pulsatile status detect: first cardiac muscle cell's sensor culture plate 1 is placed on inverted microscope (3) on objective table, use 40 times of object lens and 10 times of eyepieces, the position of adjustment inverted microscope (3) objective table and focusing knob, clearly can see cardiac muscle cell in the visual field; Carry out scheming cellular beating image acquisition by computing machine (5) control CCD camera (1), then calculate scheming cell mechanical beats curve; Calculate control group beat rates, pulsatile range and gap state parameter of beating finally by scheming cell mechanical beats opisometer, specifically comprise following sub-step:
(3.1) cardiac muscle cell of collection to be beaten the first frame two field picture in contrast of image;
(3.2) contrast two field picture is carried out gray processing, the gray processing formula of employing is:
Gray=R×0.299+G×0.587+B×0.114
Wherein, Gray refers to the gray-scale value after image pixel binaryzation, and R, G and B refer to the value of original image pixels red, green and blue passage respectively;
(3.3) adopt large law to carry out binaryzation to the image after step 3.2 gray processing, T is designated as the segmentation threshold of display foreground and background, w
0be designated as foreground pixel to count the ratio of with image total pixel number, display foreground average gray is u
0; w
1for background pixel is counted the ratio of with image total pixel number, image background average gray is u1; U is designated as the overall average gray scale of image, computing formula is u=w
0× u
0+ w
1× u
1; G is designated as maximum between-cluster variance, from minimal gray to maximum gradation value, travel through T, according to computing formula G=w
0× (u
0-u)
2+ w1 × (u
1-u)
2, when T makes G maximum, the T got now is best segmentation threshold; Then according to T, what image pixel gray level value is less than T is taken as 0, and what image pixel gray level value was greater than T is taken as 1, realizes the binaryzation of gray level image;
(3.4) gather cardiac muscle cell subsequently and beat the sequence frame image of image as real-time frame image, according to step (3.2) and (3.3), gray processing and binary conversion treatment are carried out to real-time frame image;
(3.5) the real-time frame image after gray processing is done image subtraction with the two field picture that contrasts after gray processing, obtain subtraction image; Then subtraction image is carried out the matrixing of image slices vegetarian refreshments, obtain image array, now matrix element value be-1,0 and 1 three one of them;
(3.6) absolute value is carried out to image matrix element, then element summation is carried out to the image array after absolute value, itself and be image difference value of beating;
(3.7) take time as horizontal ordinate, the image difference value of beating of the real-time frame image that step 3.6 calculates is ordinate curve plotting, and this curve is cardiac muscle cell's mechanical beats curve;
(3.8) wavelet transformation is carried out to cardiac muscle cell's mechanical beats curve, adopt 7 layers of multiscale analysis method;
(3.9) the approximation component A7 in 7 layers of multiscale analysis result, details coefficients D1, D2 and D3 are carried out zero setting, then adopt wavelet inverse transformation reconstruct cardiac muscle cell mechanical beats curve, namely remove the cardiac muscle cell's mechanical beats curve after baseline noise reduction;
(3.10) mean square deviation of the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction is calculated, and be decided to be threshold value: the site being greater than threshold value in the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction is designated as 1, the site being less than threshold value is designated as 0, and then carrying out difference, Dependence Results numerical value is 1,0 and-1 thrin; The wherein left hand edge in curve values to be the site of 1 be crest site, curve values be-1 site be the right hand edge in crest site;
(3.11) according to step (3.10) left hand edge that draws and right hand edge site, obtain in its interval the maximal value of the cardiac muscle cell's mechanical beats curve after removing baseline noise reduction, maximal value site is crest site; Obtain the minimum value that the cardiac muscle cell's mechanical beats curve after baseline noise reduction is removed in its interval, minimum value site is trough site; The difference of maxima and minima is cardiac muscle cell's mechanical beats amplitude; Time interval ratio between continuous print crest site, is cardiac muscle cell's mechanical beats gap;
(3.12) every 30 seconds statistics crest site numbers, pulsatile range and gaps of beating, statistics crest site number is designated as the mean speed of 30 seconds myocardium cellular beatings; Take time as x-axis, the mean speed that cardiac muscle cell is beaten is y-axis, builds cardiac muscle cell and to beat mean speed curve; Take time as x-axis, pulsatile range is y-axis, builds cardiac muscle cell's pulsatile range curve; Take time as x-axis, cardiac muscle cell gap of beating is y-axis, builds cardiac muscle cell and to beat gap curve;
(4) standard diagram of toxin to be measured is built: the volume after step (2) being diluted is that the working fluid of the variable concentrations gradient of 20 μ l adds in cardiac muscle cell's sensor culture plate (1) respectively, repeat step (3), detect the beat curve of cardiac muscle cell under the working fluid effect of variable concentrations gradient, beat rates, pulsatile range and gap state parameter of beating; The identical parameters of the beat rates of gained, pulsatile range and beat gap and step (3) control group gained is adopted normalized, namely using the state parameter of each time point of control group as benchmark, state parameter under drug effect, compared with the benchmark of synchronization control group, is normalized calculating; The standard diagram in cardiac muscle cell's beat rates of toxin to be measured, pulsatile range and gap of beating is built by normalization result of calculation;
(5) prepare the diarrhoeal toxin sample solution of marine aquatic product shellfish to be measured: prepare sample solution according to GB GB/T 5009.212-200, the diarrhoeal toxin contained in described 1ml sample solution is equivalent to the diarrhoeal toxin contained by marine aquatic product to be measured that 20g shells;
(6) virulence analyzing the diarrhoeal toxin of marine aquatic product shellfish to be measured is detected: repeat step (3), obtain beat rates, the pulsatile range of sample solution and gap curve of beating, the standard diagram comparison of setting up with step (4), can draw the concentration ranges of sample solution; Then the diarrhoeal toxin contained by the 1ml sample solution of step (5) is equivalent to the relation of the diarrhoeal toxin contained by marine aquatic product to be measured that 20g shells, draw the diarrhoeal content of toxins of shellfish, by beat rates, pulsatile range and gap curvilinear motion of beating, analyze shellfish diarrhoeal toxin toxicity to the time dependent impact of cardiac muscle cell.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104777299A (en) * | 2015-03-13 | 2015-07-15 | 浙江大学 | Diarrhetic shellfish toxin high throughput detection device and method based on image analysis |
| CN104777159A (en) * | 2015-03-13 | 2015-07-15 | 浙江大学 | Paralytic shellfish toxin detection method based on image analysis |
| CN105954505A (en) * | 2016-05-04 | 2016-09-21 | 浙江大学 | Cell viability sensor-based diarrhetic shellfish poison detection apparatus and method thereof |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001037192A1 (en) * | 1999-11-18 | 2001-05-25 | Ikonisys, Inc. | Method and apparatus for computer controlled cell based diagnosis |
| US20070243523A1 (en) * | 2006-03-31 | 2007-10-18 | Fluxion Biosciences Inc. | Methods and Apparatus for the Manipulation of Particle Suspensions and Testing Thereof |
| CN101975768A (en) * | 2010-08-27 | 2011-02-16 | 深圳市疾病预防控制中心 | Method for detecting diarrhea shellfish toxin |
| CN103473751A (en) * | 2013-08-14 | 2013-12-25 | 西安理工大学 | CMOS sensor cell image super-resolution reconstruction method based on multiple objects |
| CN103575893A (en) * | 2013-10-14 | 2014-02-12 | 广州市疾病预防控制中心 | Method for rapidly detecting shellfish toxin |
-
2014
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001037192A1 (en) * | 1999-11-18 | 2001-05-25 | Ikonisys, Inc. | Method and apparatus for computer controlled cell based diagnosis |
| US20070243523A1 (en) * | 2006-03-31 | 2007-10-18 | Fluxion Biosciences Inc. | Methods and Apparatus for the Manipulation of Particle Suspensions and Testing Thereof |
| CN101975768A (en) * | 2010-08-27 | 2011-02-16 | 深圳市疾病预防控制中心 | Method for detecting diarrhea shellfish toxin |
| CN103473751A (en) * | 2013-08-14 | 2013-12-25 | 西安理工大学 | CMOS sensor cell image super-resolution reconstruction method based on multiple objects |
| CN103575893A (en) * | 2013-10-14 | 2014-02-12 | 广州市疾病预防控制中心 | Method for rapidly detecting shellfish toxin |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104777299A (en) * | 2015-03-13 | 2015-07-15 | 浙江大学 | Diarrhetic shellfish toxin high throughput detection device and method based on image analysis |
| CN104777159A (en) * | 2015-03-13 | 2015-07-15 | 浙江大学 | Paralytic shellfish toxin detection method based on image analysis |
| CN105954505A (en) * | 2016-05-04 | 2016-09-21 | 浙江大学 | Cell viability sensor-based diarrhetic shellfish poison detection apparatus and method thereof |
| CN105954505B (en) * | 2016-05-04 | 2018-06-15 | 浙江大学 | The detection device and method of the diarrhoeal toxin of shellfish based on cell activity sensor |
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