Mediterranean anemia detection system and kit

Abstract

The invention belongs to the technical field of biological medicine, and particularly relates to a thalassemia detection system and kit.The thalassemia detection system comprises a collection module used for collecting a to-be-detected blood sample, an acid elution and dyeing module used for conducting acid elution and dyeing treatment on the to-be-detected blood sample, and an image collection module used for collecting images of the to-be-detected blood sample. The image acquisition module is used for carrying out image acquisition on a dyeing processing result, the image processing module is used for converting an image acquired by the image acquisition module into data information, the calculation module is used for calculating the number proportion of dyed red blood cells and the dyeing depth according to the data information, and the output module is used for displaying a calculation result. The acquisition module is connected with the acid elution and dyeing module, the acid elution and dyeing module is connected with the image acquisition module, the invention develops the thalassemia detection system, can realize rapid detection of thalassemia, and has important clinical application value.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to a thalassemia detection system and a kit. Background Art

[0002] Thalassemia is a disease of abnormal hemoglobin, a hereditary disease caused by autosomal gene defects. Due to the deletion or mutation of the gene that regulates globin synthesis, the synthesis ratio of α-chain and β-chain globin that constitute hemoglobin is unbalanced, resulting in a shortened lifespan of red blood cells and hemolytic anemia. The pathogenesis of thalassemia is different from that of common anemia. Common anemia is caused by a lack of iron in the diet, which leads to too few red blood cells and insufficient oxygen transport by red blood cells, while thalassemia is caused by defects in the red blood cells themselves, not a lack of red blood cells. Carriers of the thalassemia gene do not develop the disease, and their appearance and body functions are no different from those of ordinary people. Only severe patients will show symptoms, and the possibility of cure is low.

[0003] The clinical symptoms of thalassemia can be manifested in three types: mild, moderate, and severe. In a pair of genes, if one gene is defective and the other gene is normal, it is heterozygous thalassemia. Most of these patients are mild thalassemia patients with no obvious symptoms. It is not easy for the patients themselves to detect it, and it is often discovered during physical examinations or family disease analysis. However, heterozygous thalassemia may also suffer from moderate anemia. Patients have symptoms such as fatigue, pale complexion, indigestion and loss of appetite, mild bone changes and delayed sexual development. If both genes are defective, that is, homozygous or severe thalassemia, this patient will be accompanied by anemia, pale complexion, developmental delay, hepatosplenomegaly and other symptoms, and the symptoms will become increasingly obvious with age, and severe cases will be life-threatening.

[0004] The current detection method of thalassemia is relatively complicated and requires high skill level of the operator. Therefore, a thalassemia detection system and a kit are invented to achieve rapid detection of thalassemia. Summary of the invention

[0005] In view of the above-mentioned and / or existing problems in a thalassemia detection system and kit, the present invention is proposed.

[0006] Therefore, the object of the present invention is to provide a thalassemia detection system and kit, which can solve the above-mentioned existing problems.

[0007] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

[0008] A thalassemia detection system, comprising:

[0009] A collection module, used for collecting blood samples to be tested;

[0010] An acid elution and staining module, used for performing acid elution and staining treatment on the blood sample to be tested;

[0011] An image acquisition module is used to acquire images of the staining treatment results;

[0012] An image processing module, used for converting the image acquired by the image acquisition module into data information;

[0013] A calculation module, used to calculate the percentage of stained red blood cells and the depth of staining according to the data information;

[0014] Output module, used to display calculation results;

[0015] The acquisition module is connected to the acid elution and staining module, the acid elution and staining module is connected to the image acquisition module, the image acquisition module is connected to the image processing module, the image processing module is connected to the calculation module, and the calculation module is connected to the output module.

[0016] As a preferred embodiment of the thalassemia detection system described in the present invention, the acid elution uses an acidic eluent.

[0017] As a preferred embodiment of the thalassemia detection system described in the present invention, the raw materials of the acidic eluent include: 4-6 g / L hematoxylin, 800 mL / L ethanol, 5-7 g / L ferric chloride, 4-5 mL / L 25% hydrochloric acid solution, 0.001-0.003 g / L polytrifluorochloroethylene and 0.003-0.005 g / L methylpentanol.

[0018] As a preferred embodiment of the thalassemia detection system of the present invention, the preparation process of the acidic eluent is as follows:

[0019] Process 1: Dissolve hematoxylin fully in ethanol to obtain solution A;

[0020] Process 2: After dissolving ferric chloride in hydrochloric acid solution, add distilled water to make up the volume, mix well, and obtain solution B;

[0021] Process three: After mixing solution A and solution B, add polytrifluorochloroethylene and methylpentanol, mix well, and obtain an acidic eluent.

[0022] As a preferred embodiment of the thalassemia detection system described in the present invention, the staining treatment uses eosin staining solution.

[0023] As a preferred embodiment of the thalassemia detection system described in the present invention, the eosin staining solution includes eosin Y 10g / L and 100mL / L of a saturated aqueous solution of picric acid.

[0024] As a preferred embodiment of the thalassemia detection system of the present invention, the preparation process of the eosin staining solution is as follows:

[0025] Process 1: Add Eosin Y to distilled water;

[0026] Process 2: Add saturated aqueous solution of picric acid into distilled water and mix well to obtain eosin staining solution.

[0027] As a preferred solution of the thalassemia detection system described in the present invention, the data information includes category prediction probability.

[0028] As a preferred solution of the thalassemia detection system described in the present invention, the calculation formula of the category prediction probability is as follows:

[0029] P i =softmax(z i1 ,z i2 ,...,z iC )

[0030] Among them, Z ij It is the original score output by the network, which is normalized by the softmax function to obtain the category prediction probability.

[0031] A thalassemia detection kit comprises the above-mentioned acidic eluent and eosin staining solution.

[0032] Compared with existing technologies:

[0033] 1. The present invention develops a thalassemia detection system, which can realize the rapid detection of thalassemia and has important clinical application value.

[0034] 2. The acidic eluent provided by the present invention can greatly improve the elution effect of red blood cells, and is particularly useful for distinguishing red blood cells containing and not containing hemoglobin F, thereby improving the detection accuracy. Some components (polychlorotrifluoroethylene, methylpentanol) in the acidic eluent of the present invention can enter the gaps between adherent cells, lubricate the interface between cells, and thus disperse red blood cells, thereby improving the defect of inaccurate judgment caused by red blood cell aggregation, thereby improving the detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the process of the present invention.

[0036] In the figure: acquisition module 1, acid elution and staining module 2, image acquisition module 3, image processing module 4, calculation module 5, output module 6. DETAILED DESCRIPTION

[0037] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0038] Embodiment 1:

[0039] The present invention provides a thalassemia detection system, please refer to Figure 1 ,include:

[0040] Collection module 1, used for collecting blood samples to be tested;

[0041] Acid elution and staining module 2, used for performing acid elution and staining treatment on the blood sample to be tested;

[0042] Image acquisition module 3, used for acquiring images of the dyeing treatment results;

[0043] The image processing module 4 is used to convert the image acquired by the image acquisition module into data information;

[0044] A calculation module 5 is used to calculate the percentage of stained red blood cells and the depth of staining according to the data information;

[0045] Output module 6, used for displaying calculation results;

[0046] The acquisition module 1 is connected to the acid elution and staining module 2, the acid elution and staining module 2 is connected to the image acquisition module 3, the image acquisition module 3 is connected to the image processing module 4, the image processing module 4 is connected to the calculation module 5, and the calculation module 5 is connected to the output module 6.

[0047] The acid elution uses an acidic eluent;

[0048] The raw materials of the acidic eluent include: 6 g / L hematoxylin, 800 mL / L ethanol, 5 g / L ferric chloride, 4 mL / L 25% hydrochloric acid solution, 0.001 g / L polychlorotrifluoroethylene and 0.005 g / L methyl amyl alcohol;

[0049] The preparation process of the acidic eluent is as follows:

[0050] Process 1: Dissolve 6 g of hematoxylin in 800 mL of ethanol to obtain solution A;

[0051] Step 2: Dissolve 5 g of ferric chloride in 4 mL of 25% hydrochloric acid solution, add distilled water to make up to 200 mL, mix well, and obtain solution B;

[0052] Process three: After mixing solution A and solution B, add 0.001g of polytrifluorochloroethylene and 0.005g of methylpentanol and mix well to obtain an acidic eluent.

[0053] The staining process uses eosin staining solution;

[0054] The eosin staining solution includes eosin Y 10g / L and picric acid saturated aqueous solution 100mL / L;

[0055] The preparation process of the eosin staining solution is as follows:

[0056] Process 1: Add Eosin Y to distilled water;

[0057] Process 2: Add saturated aqueous solution of picric acid into distilled water and mix well to obtain eosin staining solution.

[0058] The data information includes the category prediction probability, and the calculation formula of the category prediction probability is as follows:

[0059] P i =softmax(z i1 ,z i2 ,...,z iC )

[0060] Among them, Z ij It is the original score output by the network, which is normalized by the softmax function to obtain the category prediction probability.

[0061] A thalassemia detection kit comprises the above-mentioned acidic eluent and eosin staining solution.

[0062] Embodiment 2:

[0063] The present invention provides a thalassemia detection system, please refer to Figure 1 ,include:

[0064] Collection module 1, used for collecting blood samples to be tested;

[0065] Acid elution and staining module 2, used for performing acid elution and staining treatment on the blood sample to be tested;

[0066] Image acquisition module 3, used for acquiring images of the dyeing treatment results;

[0067] The image processing module 4 is used to convert the image acquired by the image acquisition module into data information;

[0068] A calculation module 5 is used to calculate the percentage of stained red blood cells and the depth of staining according to the data information;

[0069] Output module 6, used for displaying calculation results;

[0070] The acquisition module 1 is connected to the acid elution and staining module 2, the acid elution and staining module 2 is connected to the image acquisition module 3, the image acquisition module 3 is connected to the image processing module 4, the image processing module 4 is connected to the calculation module 5, and the calculation module 5 is connected to the output module 6.

[0071] The acid elution uses an acidic eluent;

[0072] The raw materials of the acidic eluent include: 5 g / L hematoxylin, 800 mL / L ethanol, 6 g / L ferric chloride, 5 mL / L 25% hydrochloric acid solution, 0.002 g / L polychlorotrifluoroethylene and 0.003 g / L methyl amyl alcohol;

[0073] The preparation process of the acidic eluent is as follows:

[0074] Process 1: Dissolve 5 g of hematoxylin in 800 mL of ethanol to obtain solution A;

[0075] Step 2: Dissolve 6 g of ferric chloride in 5 mL of 25% hydrochloric acid solution, add distilled water to make up to 200 mL, mix well, and obtain solution B;

[0076] Process 3: After mixing solution A and solution B, add 0.002g of polytrifluorochloroethylene and 0.003g of methylpentanol and mix well to obtain an acidic eluent.

[0077] The staining process uses eosin staining solution;

[0078] The eosin staining solution includes eosin Y 10g / L and picric acid saturated aqueous solution 100mL / L;

[0079] The preparation process of the eosin staining solution is as follows:

[0080] Process 1: Add Eosin Y to distilled water;

[0081] Process 2: Add saturated aqueous solution of picric acid into distilled water and mix well to obtain eosin staining solution.

[0082] The data information includes the category prediction probability, and the calculation formula of the category prediction probability is as follows:

[0083] P i =softmax(z i1 ,z i2,...,z iC )

[0084] Among them, Z ij It is the original score output by the network, which is normalized by the softmax function to obtain the category prediction probability.

[0085] A thalassemia detection kit comprises the above-mentioned acidic eluent and eosin staining solution.

[0086] Embodiment 3:

[0087] The present invention provides a thalassemia detection system, please refer to Figure 1 ,include:

[0088] Collection module 1, used for collecting blood samples to be tested;

[0089] Acid elution and staining module 2, used for performing acid elution and staining treatment on the blood sample to be tested;

[0090] Image acquisition module 3, used for acquiring images of the dyeing treatment results;

[0091] The image processing module 4 is used to convert the image acquired by the image acquisition module into data information;

[0092] A calculation module 5 is used to calculate the percentage of stained red blood cells and the depth of staining according to the data information;

[0093] Output module 6, used for displaying calculation results;

[0094] The acquisition module 1 is connected to the acid elution and staining module 2, the acid elution and staining module 2 is connected to the image acquisition module 3, the image acquisition module 3 is connected to the image processing module 4, the image processing module 4 is connected to the calculation module 5, and the calculation module 5 is connected to the output module 6.

[0095] The acid elution uses an acidic eluent;

[0096] The raw materials of the acidic eluent include: 4 g / L hematoxylin, 800 mL / L ethanol, 7 g / L ferric chloride, 4 mL / L 25% hydrochloric acid solution, 0.003 g / L polychlorotrifluoroethylene and 0.004 g / L methylpentanol;

[0097] The preparation process of the acidic eluent is as follows:

[0098] Process 1: Dissolve 4 g of hematoxylin in 800 mL of ethanol to obtain solution A;

[0099] Step 2: Dissolve 7g of ferric chloride in 4mL of 25% hydrochloric acid solution, add distilled water to make up to 200mL, mix well, and obtain solution B;

[0100] Process three: After mixing solution A and solution B, add 0.003g of polytrifluorochloroethylene and 0.004g of methylpentanol and mix well to obtain an acidic eluent.

[0101] The staining process uses eosin staining solution;

[0102] The eosin staining solution includes eosin Y 10g / L and picric acid saturated aqueous solution 100mL / L;

[0103] The preparation process of the eosin staining solution is as follows:

[0104] Process 1: Add Eosin Y to distilled water;

[0105] Process 2: Add saturated aqueous solution of picric acid into distilled water and mix well to obtain eosin staining solution.

[0106] The data information includes the category prediction probability, and the calculation formula of the category prediction probability is as follows:

[0107] P i =softmax(z i1 ,z i2 ,...,z iC )

[0108] Among them, Z ij It is the original score output by the network, which is normalized by the softmax function to obtain the category prediction probability.

[0109] A thalassemia detection kit comprises the above-mentioned acidic eluent and eosin staining solution.

[0110] Comparative Example 1:

[0111] Same as Example 1, except that polychlorotrifluoroethylene is not added to the acidic eluent.

[0112] Comparative Example 2:

[0113] Same as Example 1, except that methyl amyl alcohol is not added to the acidic eluent.

[0114] Comparative Example 3:

[0115] Same as Example 1, except that the methyl amyl alcohol in the acidic eluent is replaced by sodium pyrophosphate.

[0116] Embodiment 4:

[0117] This embodiment takes the acidic eluent prepared in Example 1 as an example (the acidic eluents prepared in Examples 2 and 3 can achieve the same effect), and uses the thalassemia detection system to perform blood sample detection:

[0118] Step 1: Collecting a blood sample to be tested through the collection module 1;

[0119] Step 2: After the blood sample to be tested is made into a blood smear, the acid elution and staining module 2 is used for acid elution and staining treatment; wherein the acid elution and staining treatment is to immerse the blood smear in the acid elution solution prepared in Example 1 at 37° C. for 60 seconds, and then stain it with eosin staining solution for 60 seconds after drying;

[0120] The preparation method of eosin staining solution is as follows: add 1g of eosin Y to 90mL of distilled water, then add 10mL of saturated aqueous solution of picric acid, and mix well;

[0121] Step 3: After the stained blood film is dried again, the image is collected by the image acquisition module 3, and converted into data information by the image processing module 4, and then the number and proportion of stained red blood cells and the depth of staining are calculated by the calculation module 5, and finally the calculation result is displayed by the output module 6;

[0122] Step 4: According to the calculation results, judge the test results according to the following standards:

[0123] ① Most red blood cells are stained red: severe type of β-thalassemia.

[0124] ② A small number of red blood cells are stained red: mild form of β-thalassemia, aplastic anemia, and hemolytic anemia.

[0125] ③ Dark staining: homozygous type of hereditary HbF hyperplasia.

[0126] ④Light staining: heterozygous type of hereditary HbF hyperplasia.

[0127] Comparative Example 4:

[0128] The same as Example 4, except that the acidic eluent prepared in Example 1 is replaced by the acidic eluent prepared in Comparative Example 1.

[0129] Comparative Example 5:

[0130] The same as Example 4, the only difference is that the acidic eluent prepared in Example 1 is replaced by the acidic eluent prepared in Comparative Example 2.

[0131] Comparative Example 6:

[0132] The same as Example 4, except that the acidic eluent prepared in Example 1 is replaced by the acidic eluent prepared in Comparative Example 3.

[0133] The dyeing treatment conditions of Example 4 and Comparative Examples 4-6 were statistically analyzed, and the results are shown in Table 1.

[0134] Table 1 Dyeing treatment of Example 4 and Comparative Examples 4-6

[0135] Example / Comparative Example Is the dyeing clear? Cellular level Example 4 yes Clearly legible Comparative Example 4 no Partially discernible Comparative Example 5 no Unidentifiable Comparative Example 6 no Unidentifiable

[0136] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A thalassemia detection system, characterized in that: include: A collection module (1), used for collecting a blood sample to be tested; An acid elution and staining module (2), used for performing acid elution and staining treatment on the blood sample to be tested; An image acquisition module (3) is used to acquire images of the dyeing treatment results; An image processing module (4) is used to convert the image acquired by the image acquisition module into data information; A calculation module (5), used for calculating the percentage of stained red blood cells and the depth of staining according to the data information; An output module (6), used for displaying the calculation results; The acquisition module (1) is connected to the acid elution and staining module (2), the acid elution and staining module (2) is connected to the image acquisition module (3), the image acquisition module (3) is connected to the image processing module (4), the image processing module (4) is connected to the calculation module (5), and the calculation module (5) is connected to the output module (6).

2. A thalassemia detection system according to claim 1, characterized in that: The acid elution uses an acidic eluent.

3. A thalassemia detection system according to claim 2, characterized in that: The raw materials of the acidic eluent include: 4-6 g / L hematoxylin, 800 mL / L ethanol, 5-7 g / L ferric chloride, 4-5 mL / L 25% hydrochloric acid solution, 0.001-0.003 g / L polychlorotrifluoroethylene and 0.003-0.005 g / L methyl amyl alcohol.

4. A thalassemia detection system according to claim 3, characterized in that: The preparation process of the acidic eluent is as follows: Process 1: Dissolve hematoxylin fully in ethanol to obtain solution A; Process 2: After dissolving ferric chloride in hydrochloric acid solution, add distilled water to make up the volume, mix well, and obtain solution B; Process three: After mixing solution A and solution B, add polytrifluorochloroethylene and methylpentanol, mix well, and obtain an acidic eluent.

5. The thalassemia detection system according to claim 1, characterized in that: The staining treatment uses eosin staining solution.

6. A thalassemia detection system according to claim 5, characterized in that: The eosin staining solution includes eosin Y 10g / L and 100mL / L of saturated aqueous solution of picric acid.

7. A thalassemia detection system according to claim 6, characterized in that: The preparation process of the eosin staining solution is as follows: Process 1: Add Eosin Y to distilled water; Process 2: Add saturated aqueous solution of picric acid into distilled water and mix well to obtain eosin staining solution.

8. The thalassemia detection system according to claim 1, characterized in that: The data information includes category prediction probabilities.

9. A thalassemia detection system according to claim 8, characterized in that: The calculation formula for the category prediction probability is as follows: P i =softmax(z i1 ,z i2 ,...,z iC ) Among them, Z ij It is the original score output by the network, which is normalized by the softmax function to obtain the category prediction probability.

10. A thalassemia detection kit, characterized in that: The method comprises the acidic elution solution and eosin staining solution as described in claims 1-9.

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