CN117701740A - Portable intelligent detection micro-platform and method for accurate and rapid fluorescence quantification of target concentration - Google Patents

Abstract

The invention discloses a portable intelligent detection micro-platform and method for accurate and rapid fluorescence quantification of target concentration. The micro-platform includes a micro-fluidic chip, a nucleic acid fluorescence quantitative reaction system, and a quantitative detection system; the quantitative detection system includes a method for obtaining nucleic acid-based fluorescence Image acquisition module and image optimization module for the fluorescence image of the microreactor chamber after the quantitative reaction system completes the target nucleic acid fluorescence reaction, and a microreactor chamber identification module for identifying the microreactor chamber in the fluorescence image of the microreactor chamber and obtaining its RGB intensity. A quantitative module for quantitative detection of target nucleic acids based on the RGB intensity of the microreactor chamber and the pre-constructed linear relationship between RGB and target concentration. In the present invention, only a mobile terminal is needed to obtain the microreaction fluorescence image, and the image analysis is performed to obtain the detection result, which greatly reduces the burden of expensive and non-portable instruments, simplifies the experimental requirements and accelerates the detection process, and can be used in clinical practice. rapid screening and accurate quantification.

Description

Portable intelligent detection micro-platform and method for accurate and rapid fluorescence quantification of target concentration

Technical field

The invention belongs to the technical field of cell biological detection, and in particular relates to a portable intelligent detection micro-platform and method for accurate and rapid fluorescence quantification of target concentration.

Background technique

Bacterial infections are the cause of a variety of diseases in humans, animals and plants. Severe pathogenic bacterial infections can cause a variety of symptoms, especially posing a threat to patients with immune deficiencies or antibiotic medications. Since there are many types of bacteria, and different bacteria can contain multiple subtypes, causing different symptoms, each symptom needs to be diagnosed and identified before an appropriate/personalized treatment strategy can be formulated, which brings challenges to clinical diagnosis and treatment. A lot of burden. Rapid identification of bacterial subtype infections and accurate quantification of their bacterial content are important means for timely treatment and control of infections. Traditional detection technology relies heavily on expensive professional instruments, which greatly reduces its applicability in large-scale population screening. Traditional bacterial infection analysis methods, taking Cryptococcus as an example, usually need to be based on real-time quantitative polymerase chain reaction (RT-qPCR), which is highly specific. However, this technology relies heavily on expensive qPCR instruments/procedures for precise temperature control and result readout, and is therefore limited in large-scale clinical screening applications. The new CRISPR-Cas system can provide endonucleases, probes, etc. for specific detection of different bacteria to detect bacteria. This isothermal amplification-based probe avoids reliance on expensive temperature-controlled instrumentation. However, in current technology, quantifying fluorescence signals still requires specialized instruments or procedures, such as fluorescence spectrometers, which also restricts the popularity and wide-scale application of this technology.

Contents of the invention

The purpose of the present invention is to provide a portable intelligent detection micro-platform and method for accurate and rapid fluorescence quantification of target concentration, which can quickly and accurately quantify bacterial infection without relying on professional instruments (for example, high-pixel image acquisition equipment such as microscopes or electron microscopes), and Easy to carry.

In order to solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions: a portable intelligent detection micro-platform for accurate and rapid fluorescence quantitative target concentration, including a micro-fluidic chip, a nucleic acid fluorescence quantitative reaction system, and a quantitative detection system; The microfluidic chip includes a substrate and a central liquid inlet hole on the substrate; it also includes a positive control area and a negative control area and several detection areas arranged around the central liquid inlet hole; each area is provided with a microfluidic channel and a central liquid inlet hole. The holes are connected, and each area is provided with several micro-reaction chambers connected to the micro-channel; the end of the micro-channel is provided with a liquid outlet hole; the quantitative detection system includes a method for obtaining a quantitative reaction based on the nucleic acid fluorescence An image acquisition module for the fluorescence image of the microreactor chamber after the target nucleic acid fluorescence reaction has been completed by the system, an image optimization module for optimizing the fluorescence image of the microreactor chamber, and an image acquisition module for identifying each microreaction in the fluorescence image of the microreactor chamber. micro-reaction chamber identification module that obtains the RGB intensity of the chamber and obtains its RGB intensity, and is used to calculate the RGB intensity mean value based on the RGB intensity of all micro-reaction chambers in the current detection area, and establish the RGB intensity mean value and the corresponding known target concentration based on the two. The linear relationship between, and the quantitative module for quantitatively detecting the target nucleic acid based on the linear relationship;

The micro-reaction chamber identification module includes: a grayscale threshold setting module, used to set the threshold range 0 to N and the threshold step n, thereby obtaining several grayscale thresholds; a binary image acquisition module, used to gray out the pixels. The grayscale values are compared with several grayscale thresholds respectively, and pixels whose grayscale value is greater than the grayscale threshold are set to white, while pixels whose grayscale value is less than or equal to the grayscale threshold are set to black, thereby obtaining several binary images; The spot group merging module is used to extract connected white pixels in each binary image as spots, and merge the spots with overlapping geometric centers in all binary images into spot groups; the spot group selection module is used to Filter the spot group by the number of pixels, concavity, inertia ratio, and roundness to select the spot group representing the micro-reaction chamber; (that is, one spot group corresponds to one micro-reaction chamber); the micro-reaction chamber position marking module is used to Record the position of the spot group, and mark the position of the corresponding micro-reaction chamber on the optimized fluorescence image of the micro-reaction chamber according to the position of the spot group; the RGB intensity acquisition module is used to measure the optimized micro-reaction chamber. The pixels in the micro-reaction chamber in the fluorescence image of the reaction chamber are weighted by RGB values and averaged to obtain the RGB intensity of each representative micro-reaction chamber.

As an improvement, the detection area includes a subtype I detection area and a subtype II detection area; the subtype I detection area, the subtype II detection area, the positive control area, and the negative control area are along the The central liquid inlet hole is arranged symmetrically with respect to the center.

As an improvement, the nucleic acid fluorescence quantitative reaction system is a CRISPR system, including one of CRISPR-Cas9, CRISPR-Cas12 or CRISPR-Cas13 systems.

As an improvement, the CRISPR system includes Cas-12a protein, primer crRNA, fluorescent reporter molecule and reaction buffer; the fluorescent reporter (Reporter) is connected with a quenching group (BHQ-1) and carboxyl fluorescence Fluorescein Amidite (FAM).

As an improvement, each reagent in the nucleic acid fluorescence quantitative reaction system is placed in the microfluidic chip in a freeze-dried form.

As an improvement, the image acquisition module includes an ultraviolet lamp and a smart mobile terminal integrated with a camera.

The invention also provides a method for accurate and rapid fluorescence quantification of target concentration, which is applied to the portable detection micro-platform for accurate and rapid fluorescence quantification of target concentration. The target is a bacterial target gene, including:

S01: Use the preset freeze-dried nucleic acid fluorescence quantitative reaction system to react with known sample nucleic acids in the microfluidic chip; the target concentration calculated by the known sample is known; S02: Use ultraviolet lamp to perform nucleic acid fluorescence quantitative reaction The final microfluidic chip is irradiated, and a smart mobile terminal is used to collect the fluorescence image of the microreactor chamber; S03: Optimize the collected fluorescence image of the microreactor chamber; S04: Identify the microorganisms in the fluorescence image of the microreactor chamber. reaction chamber and obtain the RGB intensity corresponding to the micro-reaction chamber in the fluorescence image of the micro-reaction chamber; S05: Calculate the RGB mean value of all micro-reaction chambers in the current detection area, and calculate the RGB intensity value based on the RGB intensity mean value and the known sample nucleic acid value. The known target concentration establishes a linear equation between the two; S06: Add the sample to be tested in the microfluidic chip to react with the preset freeze-dried nucleic acid fluorescence quantitative reaction system; the target concentration of the sample to be tested is unknown; S07 : Use ultraviolet light to illuminate the microfluidic chip after the nucleic acid fluorescence quantitative reaction, and use a smart mobile terminal to collect the fluorescence image of the microreaction chamber; S08: Optimize the collected fluorescence image of the microreaction chamber; S09: Recognition The micro-reaction chamber in the fluorescence image of the micro-reaction chamber is obtained, and the RGB intensity corresponding to the micro-reaction chamber in the fluorescence image of the micro-reaction chamber is obtained, and the average RGB value of all micro-reaction chambers in the current detection area is calculated; S10: The obtained said to be The average RGB intensity of the test sample is brought into the linear equation to calculate the nucleic acid content of the test sample.

As an improvement, the step of optimizing the collected micro-reactor chamber image includes: using a bilinear interpolation algorithm to expand the pixels of the collected micro-reactor chamber fluorescence image to a preset value; using Gaussian filtering Reduce the brightness difference between each pixel and surrounding pixels.

As an improvement, the step of identifying the micro-reaction chamber in the fluorescence image of the micro-reaction chamber and obtaining the RGB intensity of the micro-reaction chamber in the fluorescence image of the micro-reaction chamber includes: setting a threshold range of 0 to N and a threshold step n , thereby obtaining several grayscale thresholds; compare the grayscale value of the pixel with several grayscale thresholds respectively, and set the pixels with a grayscale value greater than the threshold as white, and set the pixels with a grayscale value less than or equal to the threshold as black. Thus, several binary images are obtained; connected white pixels in each binary image are extracted as spots, and spots with overlapping geometric centers in all binary images are merged into spot groups; through the number of pixels, concavity and convexity, , inertia ratio, and roundness to screen the spot group to select the spot group representing the micro-reaction chamber; record the position of the spot group, and mark the micro-spot group on the optimized fluorescence image of the micro-reactor chamber according to the position of the spot group. The position of the reaction chamber; the pixels in the micro-reaction chamber in the optimized fluorescence image of the micro-reaction chamber are weighted by RGB values and averaged to obtain the RGB intensity of each representative micro-reaction chamber.

As an improvement, the specific steps of using the preset freeze-dried nucleic acid fluorescence quantitative reaction system to react with sample nucleic acid are as follows: S01: Take the sample to be tested, lyse the cells to expose the DNA, and the sample is cryptococcus; S02: Add the sample containing The sample solution containing exposed DNA is added from the central inlet hole of the chip, and at the same time, a negative pressure is applied outside the chip to evacuate, so that the sample solution containing exposed DNA fully enters the chip and fluoresces with the preset freeze-dried nucleic acid. The quantitative reaction system reacts; S03: After the Cas12a protein in the nucleic acid fluorescence quantitative reaction system is combined with the target sample-specific crRNA, the non-specific endonuclease activity is released, and the quenching group and carboxyl group on the fluorescent reporter molecule are Fluorescein is cut off to release fluorescence; the sequence of the target sample-specific crRNA is shown in SEQ ID NO. 1, SEQ ID NO. 2 or SEQ ID NO. 3.

The crRNA sequences involved in the method of the present invention are shown in the table below.

Table 1

The benefit of the present invention is that: the present invention detects samples through a microfluidic chip and a nucleic acid fluorescence quantitative reaction system (such as a CRISPR system) preset in the microfluidic chip, and then uses non-professional equipment such as mobile smart terminals to To obtain fluorescence images, and use the quantitative detection system to perform image analysis and processing to quickly and quantitatively obtain detection results, and the micro-platform is easy to carry. When target DNA is present in the sample solution, the Cas12a-crRNA conjugate is activated by reporter gene cleavage at 37°C, resulting in separation between the quencher group (BHQ-1) and the reporter gene carboxyfluorescein (Fluorescein Amidite, FAM). and emits an amplified fluorescent signal fluorescein. In contrast, no fluorescent signal is generated in the negative area or in the microreactor chamber without target DNA. Specific subtypes of Cryptococcus can be identified using a handheld UV lamp (480nm), and the corresponding fluorescence image is captured by an intelligent mobile terminal, such as a smartphone.

The invention integrates the portability of microfluidic array biochips, the high specificity of CRIPSR-Cas12a technology and the accuracy of intelligent imaging procedures. The detection results only need to be obtained through expensive professional equipment such as personal smartphones, which do not have the same pixels as professional cameras or microscopes, and are detected through image processing, which greatly reduces the burden of expensive and non-portable instruments, simplifies experimental requirements and accelerates the detection process. for rapid screening and accurate quantification in clinical practice.

In the present invention, the number of detection areas can be adjusted according to needs, and multiple bacterial subtypes can be detected simultaneously, thereby improving detection efficiency.

The nucleic acid fluorescence quantitative detection system is pre-installed in the microfluidic chip in a freeze-dried form, which improves the product's portability and ease of use. You only need to inject the sample to obtain the results, without the need to configure the nucleic acid fluorescence quantitative detection system on site. . During the transportation process, the lyophilized form of the nucleic acid fluorescence quantitative detection system will remain in the preset position due to lack of fluidity and will not flow around and cause failure.

The detection area, negative and positive control areas are arranged symmetrically along the center of the central liquid inlet hole, ensuring the consistency of solution flow in each area and improving the accuracy of the entire test result.

During the process of quantitative detection, the present invention optimizes the image and uses a bilinear interpolation algorithm to expand the pixels of the collected image to a preset value such as a width of 1000 pixels. The purpose is to eliminate low pixels and inconsistencies in different images. Pixel interference. Gaussian filtering is used to reduce the brightness difference between each pixel and surrounding pixels, minimizing the impact of high-frequency noise. In addition, by identifying the micro-reaction chamber in the image and obtaining the RGB intensity of the micro-reaction chamber in the image, the present invention first performs binarization processing to obtain the binary image, and then identifies spots from the image and combines the spots to identify the micro-reaction The location of the room. Due to the small size of the microfluidic chip and the limited shooting accuracy of existing smartphone cameras, it is difficult to accurately segment the microreaction chamber directly from the image using existing instance segmentation and other methods. Therefore, in order to improve the robustness of the present invention, the micro-reaction chamber is segmented through the above steps in the present invention, and the requirements for image shooting are greatly reduced.

Finally, by pre-constructing the linear equation between different target concentrations and RGB intensity of each sample, that is, through a large number of preliminary experiments, a database containing linear relationships between various samples with known different target concentrations and RGB intensity was constructed, where, Use RGB intensity as the independent variable and target concentration as the dependent variable. After obtaining the RGB intensity of each micro-reaction chamber in the detection area corresponding to the sample to be detected, calculate the RGB mean value of the detection area (that is, the RGB intensity corresponding to the sample), and bring its value into the linear equation. Finding the target concentration corresponding to the sample further improves the convenience of use of the present invention.

Description of the drawings

In order to more clearly explain the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to describe the embodiments or the prior art will be briefly introduced below. Throughout the drawings, similar elements or portions are generally identified by similar reference numerals. In the drawings, elements or parts are not necessarily drawn to actual scale. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting any creative effort.

Figure 1 is a schematic diagram of a detection micro-platform according to an exemplary embodiment of the present invention;

Figure 2A is a schematic dimensional view of a chip system constructed based on a microfluidic chip according to an exemplary embodiment of the present invention;

Figure 2B is a schematic diagram of the dimensions of a single microfluidic chip shown in Figure 2A;

Figure 2C shows the partial micro-reaction chamber in Figure 2B;

Figure 3 is a flow chart of a detection method according to an exemplary embodiment of the present invention;

Figure 4 is an experimental result diagram of the detection results of the embodiment of the present invention;

Figure 5A is a diagram showing a microfluidic chip according to an embodiment of the present invention;

Figure 5B shows the fluorescence image of the microreactor chamber for detecting different bacterial subtypes and the corresponding RBG intensity;

Figure 5C shows the RGB values corresponding to different target concentrations reflecting the same bacterial subtype;

Figure 5D is a linear relationship constructed based on different target concentrations and corresponding RGB intensities of the same bacterial subtype;

Figure 6 is a schematic flow chart of the quantitative detection system in the present invention;

Figure 7 shows the corresponding time and sensitivity results of the CRISPR system detecting Cryptococcus target DNA in the embodiment of the present invention;

Figure 8 shows the reaction time of the CRISPR-Cas12a system in detecting Cryptococcus subtype DNA samples in the embodiment of the present invention;

Figure 9 is a representation of the purity of the targets used in the embodiments of the present invention (each target is not contaminated), and each target is not contaminated;

Figure 10 shows an embodiment of the present invention using a known concentration target for measurement to establish a linear relationship between the target concentration and the average RGB intensity of the micro-reaction chamber.

Marked in the figure: central inlet hole 1, microfluidic channel 2, outlet hole 3, micro reaction chamber 4, negative control area 5, subtype Ⅰ detection area 6, subtype Ⅱ detection area 7, positive control area 8, ultraviolet light Lamp 9, smartphone 10.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention. Herein, suffixes such as "module", "component" or "unit" used to represent elements are used only to facilitate the description of the present invention and have no specific meaning in themselves. Therefore, "module", "component" or "unit" may be used interchangeably. In this article, the terms "upper", "lower", "inner", "outer", "front", "back", "one end", "other end", etc. indicate the orientation or positional relationship based on the orientation shown in the drawings. or positional relationships are only for the convenience of describing the present invention and simplifying the description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance. In this article, unless otherwise expressly stipulated and limited, the terms "installed", "provided with", "connected", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection or a detachable connection, or Integrated connection; it can be mechanical connection, direct connection, indirect connection through an intermediary, or internal connection between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood on a case-by-case basis. As used herein, "and/or" includes any and all combinations of one or more of the associated listed items. "Plural" in this article means two or more, that is, it includes two, three, four, five, etc. As used in this specification, the term "about" typically means +/-5% of the stated value, more typically +/-4% of the stated value, and more typically + /-3%, more typically +/-2% of the stated value, even more typically +/-1% of the stated value, even more typically +/-0.5% of the stated value. In this specification, certain embodiments may be disclosed in a format that falls within a range. It should be understood that this "within a range" description is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosure. Accordingly, descriptions of ranges should be considered to have specifically disclosed all possible subranges and individual numerical values within such ranges. For example, range The description of Individual numbers such as 1, 2, 3, 4, 5 and 6. The above rules apply regardless of the breadth of the scope.

Example 1: As shown in Figure 1, the present invention provides a portable intelligent detection micro-platform for accurate and rapid fluorescence quantitative target concentration, including a microfluidic chip, a nucleic acid fluorescence quantitative reaction system, and a quantitative detection system. Among them, the microfluidic chip includes a base and a central liquid inlet hole 1 opened on the base; it also includes a positive control area 8, a negative control area 5 and several detection areas arranged around the central liquid inlet hole 1; each area is provided with a micro The flow channel 2 is connected with the central liquid inlet hole 1, and each area is provided with a number of micro-reaction chambers 4 connected with the micro-channel 2; the end of the micro-channel 2 is provided with a liquid outlet hole 3. Among them, the nucleic acid fluorescence quantitative reaction system is a CRISPR system, specifically one of the CRISPR-Cas9, CRISPR-Cas12 or CRISPR-Cas13 systems; the CRISPR system contains a fluorescent reporter molecule connected with a fluorescent group and a fluorescence quenching group. In the present invention, the CRISPR system is a freeze-dried reagent system preset in a micro-reaction chamber, specifically including Cas-12a protein, primer crRNA, fluorescent reporter molecules and reaction buffer. Among them, the quantitative detection system includes an image acquisition module for acquiring fluorescence images of micro-reactor chambers, an image optimization module for optimizing fluorescence images of micro-reactor chambers, and an image acquisition module for identifying micro-reactor chambers in fluorescence images of micro-reactor chambers, and acquiring micro-reactor chambers. The micro-reaction chamber identification module for the RGB intensity of the micro-reaction chamber in the fluorescence image of the reaction chamber is used to establish a linear relationship between the average RGB intensity of all micro-reaction chambers in each area and the target concentration, and based on the linear relationship, the target nucleic acid (such as , bacterial infection amount) quantitative module for quantification.

The present invention detects samples through a microfluidic chip and a CRISPR system preset in the microfluidic chip, and then quickly and quantitatively obtains detection results through a quantitative detection system using image analysis and processing. When target DNA is present in the sample solution, the Cas12a-crRNA conjugate is activated by reporter gene cleavage at 37°C, resulting in separation between the quencher group (BHQ-1) and the reporter gene carboxyfluorescein (FAM). , and emits an amplified fluorescent signal fluorescein. In contrast, no fluorescent signal is generated in the negative area or in the microreactor chamber without target DNA. Specific subtypes of Cryptococcus can be identified using a handheld ultraviolet lamp (480nm), and the corresponding fluorescent images are captured by smart mobile terminals such as smartphones. That is, the present invention integrates the portability of the microfluidic array biochip, the high specificity of CRIPSR-Cas12a technology and the accuracy of the intelligent imaging program. The test results only need to be read through a personal smartphone, which greatly reduces the burden of expensive, non-portable instruments, simplifies experimental requirements and accelerates the testing process, and is used for rapid screening and accurate quantification in clinical practice.

In the present invention, the detection area includes a subtype I detection area 6 and a subtype II detection area 7; among which the subtype I detection area 6, subtype II detection area 7, positive control area 8, and negative control area 5 are along the central liquid inlet hole 1 The centrally symmetrical setting ensures the consistency of solution flow in each area and improves the accuracy of the entire detection result. In this embodiment, two detection areas are used to pair the two most common cryptococcal subtypes, namely Cryptococcus neoformans (NEO) and Cryptococcus gattii (GAT). Of course, more subtypes can also be paired, and the number of detection areas can be specifically adjusted as needed, which is not limited in the present invention. In order to eliminate signal differences between devices, a positive control area and a negative control area are specially set up in the present invention to standardize the fluorescence intensity from the detection area. For example, the microreactor chamber in the positive control area contains 5nM target DNA and the CRISPR-Cas12a system, and the microreactor chamber in the negative area contains Cas12a, Reporter, and crRNA with scrambled DNA sequence.

As shown in Figures 2A to 2C, more specifically, the micro reaction chamber 4 is circular, with a diameter D3 of 780 microns to 820 microns, and a depth of 78 microns to 82 microns; the width W1 of the microchannel 2 is 95 microns to 105 microns. microns, the depth H1 is 38 microns to 42 microns; the microchannel 2 is arranged in a serpentine shape, and each area includes 26 to 34 micro reaction chambers, which are symmetrically arranged on both sides of the microchannel 2. The depth of the microreaction chamber 4 is approximately twice that of the microfluidic channel, ensuring that the sample solution is fully filled in the microreaction chamber. The four areas are connected to the central liquid inlet hole 1 through the microfluidic channel 2, and the diameter D1 of the central liquid inlet hole 1 is 1900 microns to 2100 microns; the microfluidic channels 2 in each area end at the liquid outlet hole 3, and the diameter of the liquid outlet hole 3 is D2 is 1400 microns to 1600 microns. The length L3 of each area is 6.5 microns to 7 mm, and the width L4 is 5.4 microns to 6.0 microns. In addition, the microfluidic chip can also be several blocks integrated together to provide high usage efficiency. Among them, the length L2 of a single chip is 16 microns to 20 mm, while the length L1 of the system integrated together is 56 mm to 60 mm.

The image acquisition module used to acquire fluorescence images of the microreactor chamber in the present invention includes an ultraviolet lamp 9 and a smartphone 10 integrated with a camera. The ultraviolet lamp 9 and camera are used to obtain the fluorescence image of the microfluidic chip, while the microreaction chamber identification module and quantitative module can be built into the smartphone 10 as a mobile APP, and the microreactor chamber identification can be realized by running the smartphone 10 processor and infection quantification functions.

More specifically, the micro-reaction chamber identification module includes: a grayscale threshold setting module, used to set the threshold range 0 ~ N and the threshold step n, so as to obtain several grayscale thresholds; a binary image acquisition module, used to The gray value of the pixel is compared with several gray thresholds respectively, and the pixels whose gray value is greater than the threshold are set to white, while the pixels whose gray value is less than or equal to the threshold are set to black, thereby obtaining several binary images; spots The group merging module is used to extract connected white pixels in each binary image as spots, and merge the spots with overlapping geometric centers in all binary images into spot groups; the spot group selection module is used to pass The number of pixels, concavity and convexity, inertia ratio, and roundness are used to screen the spot group to select the spot group representing the micro-reaction chamber; the micro-reaction chamber position marking module is used to record the position of the spot group, and is optimized according to the position of the spot group. The processed fluorescence image is marked with the position of each micro-reaction chamber in the detection area; the RGB intensity acquisition module is used to weight and average the RGB values of the pixels in the micro-reaction chamber in the optimized fluorescence image to obtain each Represents the RGB intensity of the microreactor chamber.

As shown in Figure 3, the present invention also provides a method for accurate and rapid fluorescence quantification of target concentration, which is applied to the above-mentioned portable intelligent detection micro-platform for accurate and rapid fluorescence quantification of target concentration. This embodiment still quantifies Cryptococcus subtypes, that is, neonatal Cryptococcus (NEO) and Cryptococcus gattii (GAT) are taken as examples, but this does not mean that the present invention is limited thereto. Specifically, it includes the following steps:

S11 performs vacuum treatment on the microfluidic chip, and injects four mixtures of Cas12a, crRNA, Reporter, and 1× reaction buffer from the outlet holes in the four areas. The purpose of vacuum treatment is to keep the microfluidic channels on the microfluidic chip and the microreaction chamber in a vacuum state to ensure that the solution is filled and no bubbles are generated when the CRISPR-Cas12a system is added. In this embodiment, the vacuum treatment time is 25 to 35 minutes. The four areas on the microfluidic chip, namely the subtype I detection area, subtype II detection area, positive control area, and negative control area, need to be arranged with the corresponding CRISPR-Cas12a system, which are Cas12a, crRNA, Reporter, and 1× reaction buffer. liquid.

S12 freezes the microfluidic chip until the mixture becomes dry powder, and vacuums the microfluidic chip again. The purpose of vacuuming the microfluidic chip again is to keep the inside of the microfluidic chip in a vacuum state. The processing time is 25min to 35min. After the processing is completed, it is sealed and stored for use.

S13 extracts DNA samples from bacterial samples and identifies them by qPCR.

S14 Inject a single sample and a mixture of at least two samples into the central inlet hole and incubate at 37°C for 25 to 35 minutes.

S15 uses ultraviolet light to illuminate the microfluidic chip and collects fluorescence images of the microreaction chamber in 4 areas (or detection areas). Specifically, images of each area can be used separately, or images including all areas can be collected at once.

As shown in Figure 6, the following steps are the specific steps for quantitative detection by the quantitative detection system.

S16 optimizes the collected fluorescence images of the microreactor chamber. In this embodiment, the specific method of optimizing the image includes: S161 uses a bilinear interpolation algorithm to expand the pixels of the collected fluorescence image of the micro-reactor chamber to a preset value, such as a width of 1000 pixels, with the purpose of eliminating pixels of different images. Interference from low and inconsistent pixels. S162 uses Gaussian filtering to reduce the brightness difference between each pixel and surrounding pixels, minimizing the impact of high-frequency noise.

S17 identifies the microreaction chambers in the fluorescence image of the microreaction chamber and obtains the RGB intensity of each microreaction chamber in the fluorescence image of the microreaction chamber. The micro-reaction chamber is cylindrical, which appears as a "spot" in the top view photo. This step identifies the location of the micro-reaction chamber by finding the boundary of the spot, including: S171 setting the threshold range 0 to N and the threshold step n , thereby obtaining several grayscale thresholds. The gray value range is 0 to 255. In order to ensure the accuracy of the final result, in this implementation, the gray threshold range is also set to 0 to 255, and the threshold step is set to 1, so that a total of 0 to 255 can be obtained 256 grayscale thresholds. S172 compares the grayscale value of the pixel with several grayscale thresholds, and sets the pixels whose grayscale value is greater than the threshold to 1 (white), while the pixels whose grayscale value is less than or equal to the threshold are set to 0 (black), thereby obtaining Several binary images. The purpose of this step is to independently binarize the image. The so-called image independent binarization (Independent Binary Segmentation) refers to the process of dividing a grayscale image into black and white parts. A certain threshold is usually used as the black-white dividing point, and pixels are classified as black or white based on the relationship between the pixel gray value and the threshold. The purpose of independent binarization is to distinguish the subject and background in the image and facilitate subsequent image processing and analysis. In other words, after independent binarization processing, all pixels in the image are either black or white. Since 256 grayscale thresholds are set in this embodiment, 256 binary images will eventually be obtained. Compared with the traditional method of directly converting an image to be tested into a grayscale value image of 0 or 255, setting multiple grayscale thresholds is actually to obtain more data, and it is a logic that one would rather catch by mistake than let it go. Avoid missing a large amount of data; of course, obtaining a lot of data may lead to duplicate or redundant spots in the spots that are subsequently identified. Therefore, suitable spots are screened out through corresponding filtering conditions (see the following for specific filtering methods) part). S173 extracts the connected white pixels in each binary image as spots respectively, and merges the spots with overlapping geometric centers in all binary images into a spot group. The connected white pixels in 256 binary images are extracted to form spots through the findContours function. Since the position and number of black and white pixels in each binary image are different, the shape of the spots extracted in each binary image is different. Also different. After extracting the spots, the spots need to be fused to form a spot group representing the microreaction chamber. The principle of splicing is to splice spots with overlapping geometric centers into a spot group. Since the spots representing the same micro-reaction chamber in each binary image have different shapes, it is possible that the same micro-reaction chamber will form several spot groups. In order to select the most representative spot group, the spot group also needs to be screened. S174 filters the spot group based on the number of pixels, concavity and convexity, inertia ratio, and roundness to select the spot group representing the micro-reaction chamber. In the present invention, the spot group is screened through the above four aspects to select a most suitable spot group. Specifically, first, filter the number of pixels, for example, 9,000 to 13,000. By normalizing the number of pixels, you can filter out spot groups of appropriate sizes. Second, filter the concavity and convexity, that is, Groups of spots with smoother, more continuous borders, no concave features, and no sharp corners can be filtered out. Third, filter the inertia ratio/> Stretched blob groups can be eliminated. Fourth, filter the roundness/> Approximately circular spot groups can be filtered out. S175 records the position of the spot group, and marks the position of the micro-reaction chamber on the optimized original image based on the position of the spot group. After selecting the most appropriate spot group to represent a certain microreactor chamber, record the position of the spot group, and then mark the position of the microreactor chamber at the corresponding position in the optimized original image. Through the processing of the above steps, the position of the micro-reaction chamber in the image can be found very accurately, thereby improving the subsequent detection accuracy. Due to the small size of the microfluidic chip and the limited shooting accuracy of existing smartphone cameras, it is difficult to accurately segment the microreaction chamber directly from the image using existing instance segmentation and other methods. Therefore, in order to improve the robustness of the present invention, the micro-reaction chamber is segmented through the above steps in the present invention, and the requirements for image shooting are greatly reduced. S176 weights the RGB values of the pixels in the micro-reactor chamber in the optimized fluorescence image of the micro-reactor chamber and averages the RGB intensity of each representative micro-reactor chamber. After selecting the spot group representing the microreactor chamber, the RGB values of the pixels in the spot group need to be weighted and averaged to obtain the RGB intensity for subsequent use.

S18 calculates the mean RGB intensity of all microreactor chambers in each detection area, and establishes a linear equation between the mean RGB intensity and the corresponding target concentration to quantify cryptococcal infection (ie, target nucleic acid). There is a certain linear relationship between the RGB intensity of the microreactor chamber and the target concentration. The linear equation of the two can be constructed through a large number of preliminary experiments in advance, and then the RGB intensity of the microreactor chamber is used as the independent variable and the target concentration is used as the dependent variable. After obtaining the RGB intensity of a certain micro-reactor chamber, calculate the RGB average value of all micro-reactor chambers in the same detection area, and put its value into the linear equation to calculate the corresponding target concentration.

Figures 5A to 5D illustrate the above-described embodiment of the present invention. Among them, Figure 5A shows the actual microfluidic chip. Figure 5B shows the fluorescence photos of the chip after adding sample NEO with known target concentration, the fluorescence photos of the chip after adding sample GAT with known target concentration, and the fluorescence photos of the chip after adding mixed samples with known target concentration. The upper left of the chip is the negative control area, the upper right is the positive control area, the lower left is the subtype I detection area, and the lower right is the subtype II detection area; the lower row in Figure 5B shows the RGB intensities corresponding to the fluorescence photos (in each figure The thin solid line is the RGB mean value of the corresponding area. When the sample NEO is detected alone, the corresponding RGB mean value is: 148.27; when the sample GAT is detected alone, the corresponding RGB mean value is 153.97; when the mixed sample of NEO and GAT is detected separately , its corresponding RGB mean value is: 136.60). Figure 5C exemplarily shows the RGB intensity of each microreaction chamber corresponding to known different target concentrations of sample NEO. Figure 5D shows the linear relationship between the RGB intensity (that is, the RGB mean value of multiple micro-reaction chambers in the corresponding detection area) and the target concentration constructed in advance based on the different target concentrations of the sample NEO and the RGB mean value obtained by image processing.

In addition, in the present invention, in order to further improve the convenience of use, the linear relationship between RGB intensity and target concentration is actually established in advance. As shown in Figure 10, several groups of samples with known target concentration are detected and obtained in advance. The relationship between the fluorescence value and the RGB value is shown, and the fluorescence value actually reflects the target concentration. Therefore, a linear equation between the RGB value and the target concentration can be constructed by and. When detecting the sample to be tested , after detecting the RGB value through image analysis, directly enter the linear equation between RGB and target concentration to calculate the target concentration of the sample to be detected.

Chinese patent application CN202211064842.4 discloses a portable uranyl ion fluorescence detection method based on RGB analysis, including: combining a uranyl ion in-situ monitoring probe with corn peptide-sensitized curcumin fluorescence and solutions containing uranyl ions with different concentrations. Mix to obtain a mixed solution; use a purple flashlight to illuminate the mixed solution under dark conditions, and use a camera to capture the image; use a color picker to read the R, G, and B values of the image, and draw three different standard curves; add the uranium content to be measured The acyl ion solution is illuminated with a purple flashlight under dark conditions, and a camera is used to take an image of the uranyl ion-containing solution to be measured; a color picker is used to read the R, G, and B values of the image, and the corresponding standards in step 4 are taken. From the curve, the concentration of the solution containing uranyl ions to be measured is calculated. In the above-mentioned prior art, although the physical and chemical values are also measured through the RGB values of the solution fluorescence image, according to the original description, it is necessary to "adjust the camera parameters to ISO 4000, shutter speed 1/125 second, aperture f/7.1, focal length is 22mm". It shows that the above-mentioned prior art has high requirements for captured images, and not only requires a more professional camera, but also requires specific parameters to achieve better recognition results. In the present invention, through the above series of processing steps, the requirements for image quality during detection are greatly reduced, which improves the universal applicability of the present invention.

Example 2: This example provides a method for preparing a microchannel chip, which specifically includes: Step 1: Preparation of a silicon-based mold. Step 1.1: Use AutoCAD to draw the photolithography mask model and make the mask. The specific dimensions are: the diameter of the central liquid inlet hole is 2000 μm; the width of the microchannel is 100 μm; the length of the side channel is 200 μm and the width is 200 μm; the diameter of the reaction micropore is 800 μm; the diameter of the outlet hole is 1500 μm. As shown in Figure 8. In order to prevent the liquid from flowing out after adding liquid, a "deep reaction chamber" structure is designed: the chip is composed of two layers of PDMS, and masks are designed respectively. Become mask plate I and mask plate II. The first layer has a flow channel structure and a reaction chamber structure, and the second layer only has a reaction chamber structure. Two layers of PDMS are bonded together to form a morphological feature of "shallow flow channel and deep reaction chamber" to store liquid. Two-layer structure, the thickness of each layer is 40 (±3) μm. Step 1.2: Rinse the silicon wafer. First wipe the silicon wafer with acetone, then clean it with acetone, alcohol, and ultrapure water to remove organic impurities and particulate impurities. After cleaning, blow dry with nitrogen and bake in an oven to remove moisture adsorption. Step 1.3: Add oxygen. The silicon wafer is further cleaned in a plasma cleaning machine to ashes organic impurities. And oxygen is added to temporarily form free -OH groups on the surface of the silicon wafer to enhance its adhesion to the photoresist. Step 1.4: Throw glue 1. The photoresist is coated by spin coating (also known as "resist rejection"). You can refer to the spin coating curve to obtain the coating conditions of a glue. Place the silicon wafer on the glue leveling machine, apply vacuum to fix the silicon wafer, and spin-coat the photoresist SU-8 2025 at a rotation speed of 1700 rpm to obtain a 40 μm thick photoresist. Step 1.5: Pre-bake 1. During the pre-bake or soft-bake process, place the silicon wafer on the hot plate on the right side of the glue spinner, bake at 65°C for 3 minutes, then at 80°C for 3 minutes, and then at 95°C for baking. Bake for 6 minutes, then cool to room temperature and take out. Step 1.6: Photolithography. Exposure is completed through an exposure mask and exposure system. Place the silicon wafer on the UV lithography machine, and after sucking it with negative pressure, place the mask on top of the silicon wafer so that they fit together as much as possible without squeezing. Then suck the mask with negative pressure, and expose for 14 seconds. . Step 1.7: Post-baking 1. Place the silicon wafer on the hot plate, bake and fix, heat to 65°C for 2 minutes, then heat to 80°C and bake for 1 minute, then heat to 95°C and bake for 5.5 minutes, cool to room temperature and take out. Step 1.8: Throw glue 2. Repeat the step of glue spinning 1, place the silicon wafer on the glue leveling machine, vacuum to fix the silicon wafer, and spin-coat photoresist SU-8 2025 at a rotation speed of 1700 rpm to obtain a second layer of 40 μm thick photoresist. Step 1.9: Pre-bake 2. Repeat step 1 before baking. Place the silicon wafer on the hot plate on the right side of the glue spinner, heat it to 65°C and bake for 3 minutes, then heat it to 80°C and bake it for 3 minutes, then heat it to 95°C and bake it for 6 minutes, then cool it to room temperature and take it out. Step 1.10: Overlay. Exposure is performed on the second layer of photoresist. Place the silicon wafer on the UV lithography machine, and after sucking it with negative pressure, place the mask on top of the silicon wafer, suck the mask with negative pressure, and raise the silicon wafer to bring the two closer together. Next, adjust the declination micro-ruler and the two horizontal and vertical spiral micro-rulers to make the positioning mark of the second layer of mask coincide with the positioning mark of the first layer of photolithography, and then raise the silicon wafer to make the two as close as possible. No squeezing. Exposure for 14 seconds, be careful not to look directly. Step 1.11: Post-baking 2. After the second exposure, repeat the post-bake 1 operation. Place the silicon wafer on the hot plate, bake and fix, heat to 65°C for 2 minutes, then heat to 80°C and bake for 1 minute, then heat to 95°C and bake for 5.5 minutes, cool to room temperature and take out. Step 1.12: Develop. Immerse the silicon wafer into a developer using propylene glycol monomethyl ether acetate, shake slowly and fully for reaction, and develop for 3 minutes. Then wash with ultrapure water for 30 seconds, blow dry with nitrogen, and then bake and fix in an oven at 120°C. Step 1.13: Surface modification. Place the silicon wafer membrane and 3 μL of trichloro(1H, 1H, 2H, 2H)-perfluorooctylsilane in a vacuum desiccator, set the pressure to 100 mbar, and leave it overnight to perform silanization treatment to form a hydrophobic surface. Step 2: Invert molding. Step 2.1: Mix the polydimethylsiloxane (PDMS) matrix and curing agent (referred to as mixed glue) at a mass ratio of 10:1. Place in a vacuum dish and vacuum to remove air bubbles. Step 2.2: Mix the glue in step 2.1. Pour the mixed glue into a flat mold and vacuum it again to ensure there are no bubbles. Step 2.3: Place the PDMS in step 2.2 into a high-temperature oven at 80 degrees Celsius and heat for cross-linking and solidification. Step 2.4: Peel off the PDMS layer cured in step 2.3 from the mold. Step 2.5: Prepare the liquid inlet and outlet holes by punching holes in the cured PDMS layer. Step 3: Assembly of microfluidic chip. Step 3.1: Treat the PDMS with microchannels and the glass slide separately with plasma. Step 3.2: Take out the two in step 3.1 and align them for bonding. A strong Si0 bond is formed between the glass sheet and the silicone base of PDMS, thereby completing the irreversible bonding between the two to form a microfluidic chip.

Example 3: This example provides an investigation of the rapidity, accuracy, stability and sensitivity of typing detection of various subtypes of Cryptococcus.

S01: DNA samples were incubated with the CRISPR-Cas12a system at 37°C. The fluorescence intensity of each group was measured every 1 min (Fig. 4a). In the presence of the target sequence, the three CRISPR-Cas12a systems significantly enhanced the fluorescence signal, reaching saturation within 20 minutes (Figure 4b-c, Figure 7, Figure 8a-c).

S02: The high specificity of the CRISPR-Cas12a system was demonstrated by adding disordered DNA. The disordered DNA resulted in a lower fluorescence signal line, which was comparable to the no-template control (NTC) group (Figure 4d).

S03: Further explore the sensitivity of the CRISPR-Cas12a system in DNA sample detection. The calibration curve results show that the three detection systems have a linear relationship in the range of 0.1nM to 4nM, and the limit of detection (LOD) is 0.1nM (Figure 4e-f). Considering that the concentration of clinical samples is often higher than 0.1nM, the LOD results of the detection are satisfactory.

Accuracy evaluation: Carry out CRISPR typing detection on rotational combinations of DNA sequences specific to each subtype of Cryptococcus and DNA sequences common to Cryptococcus, set up three sets of parallel experiments, and compare the real-time fluorescence PCR detection results with the chip detection results of the present invention. Yes, evaluate the accuracy of the method of the present invention. The experimental results are shown in Figure 4d. Only when the type of CRISPR system corresponds to the type of the handle, there is a detection signal, indicating that the present invention shows good specificity, the accuracy is 100%, and the experimental time is 30 minutes.

Stability evaluation: Carry out CRISPR typing testing on the specific DNA sequences of each subtype of Cryptococcus and the DNA sequences shared by Cryptococcus. Carry out 3 tests on each sample, compare the consistency between the 3 results, and evaluate the stability of the kit. sex. The experimental results are shown in Figures 4b-f and Figures 7-8. The error limit in the results shows that the system has strong stability, and the experimental time is 37 minutes.

Sensitivity evaluation: The specific DNA sequences of each subtype of Cryptococcus and the DNA sequence shared by Cryptococcus were gradient diluted to 0.1nM, and CRISPR typing detection was performed on them respectively. Record the test results and evaluate the sensitivity of the kit. The experimental results are shown in Figure 4e-f and Table 2. The detection sensitivity is high, the detection limit is 0.1nM, and the detection time is 42min.

Rapidity evaluation: Record the time from sample addition to completion of detection in the above experiment. The results show that the detection can be completed within 50 minutes, which is a rapid detection.

Table 2 Sensitivity evaluation detection structure

Detection concentration Repeat 1 Repeat 2 Repeat 3 0.05nM - - - 0.1nM + + + 0.25nM + + + 0.5nM + + + 1nM + + + 2nM + + + 5nM + + +

"+" means it can be detected by typing; "-" means there is no significant difference.

This example uses DNA sequences specific to each subtype of Cryptococcus that have been sequenced, as well as DNA sequence samples shared by Cryptococcus, and is diluted in a concentration gradient. As well as crRNA and PCR primers designed separately for each DNA sequence. Used to test the speed, accuracy, stability and sensitivity of the detection system.

The nucleotide sequences of crRNA probe, target DNA, Reporter and PCR involved in this example are shown in Table 3.

Table 3 Sequences of crRNA probe, target DNA, Reporter and PCR nucleotides

Target recognition regions in the crRNA sequence are bolded. CRY,Cryptococcus.NEO,Cryptococcusneoformans.GAT,Cryptococcus gattii.Neg,negative control.F,forward.R,reverse.

After pre-experimental exploration, it was determined that the specific DNA sequences of each subtype of Cryptococcus and the DNA sequences shared by Cryptococcus were designed. The optimal CRISPR-Cas12a reaction system is shown in Table 4.

Table 4 CRISPR-Cas12a optimal reaction system

It can be understood that the sequences of the crRNA probe, target DNA, Reporter and PCR nucleotides in the present invention, as well as the reaction conditions in the present invention, are not limited to the above enumeration.

Figure 9 is a representation of the purity of the targets used in the examples of the present invention (each target is uncontaminated). The Ct value represents the number of cycles experienced when the fluorescence signal reaches the set threshold (the concentration of the "amplified object" reaches the threshold). When the ct value is greater than 40, 40 is taken and the "amplified object" is considered not to exist in the solution.

It should be noted that, in this document, the terms "comprising", "comprises" or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or device that includes a series of elements not only includes those elements, It also includes other elements not expressly listed or inherent in the process, method, article or apparatus. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of additional identical elements in a process, method, article or apparatus that includes that element.

Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product in essence or the part that contributes to the existing technology. The computer software product is stored in a storage medium (such as ROM/RAM, disk, CD), including several instructions to cause a computer terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention. The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above-mentioned specific implementations. The above-mentioned specific implementations are only illustrative and not restrictive. Those of ordinary skill in the art will Under the inspiration of the present invention, many forms can be made without departing from the spirit of the present invention and the scope protected by the claims, and these all fall within the protection of the present invention.

Claims (10)

1. A portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of a target by fluorescence is characterized in that: comprises a micro-flow channel chip, a nucleic acid fluorescence quantitative reaction system and a quantitative detection system;

the micro-channel chip comprises a substrate and a central liquid inlet hole arranged on the substrate; the device also comprises a positive control area, a negative control area and a plurality of detection areas, wherein the positive control area, the negative control area and the detection areas are arranged around the central liquid inlet hole; each zone is provided with a micro-channel communicated with the central liquid inlet, and a plurality of micro-reaction chambers communicated with the micro-channel are arranged in each zone; the tail end of the micro-channel is provided with a liquid outlet hole;

the quantitative detection system comprises an image acquisition module, an image optimization module, a micro reaction chamber identification module and a quantitative determination module, wherein the image acquisition module is used for acquiring a micro reaction chamber fluorescence image after the fluorescent reaction of the target nucleic acid is completed based on the nucleic acid fluorescent quantitative reaction system, the image optimization module is used for optimizing the micro reaction chamber fluorescence image, the micro reaction chamber identification module is used for identifying each micro reaction chamber in the micro reaction chamber fluorescence image and acquiring RGB intensity of the micro reaction chamber in the micro reaction fluorescence image, and the quantitative determination module is used for calculating RGB intensity average values according to RGB intensity of all the micro reaction chambers in a current detection area, and establishing a linear relation between the RGB intensity average values and target concentration so as to quantitatively detect the target nucleic acid based on the linear relation;

The micro-reaction chamber identification module comprises:

the gray threshold setting module is used for setting threshold ranges 0-N and threshold step length N so as to obtain a plurality of gray thresholds;

the binarization image acquisition module is used for comparing the gray values of the pixel points with a plurality of gray threshold values respectively, setting the pixel points with the gray values larger than the gray threshold values as white and setting the pixel points smaller than or equal to the gray threshold values as black, so as to obtain a plurality of binarization images;

the spot combining module is used for respectively extracting the white pixels communicated in each binarized image as spots, and combining the spots overlapped in the geometric centers in all the binarized images into a spot group;

the spot group selecting module is used for selecting spot groups according to the number of pixels, the convexity, the inertia ratio and the roundness so as to select the spot groups representing the micro-reaction chamber;

the micro-reaction chamber position marking module is used for recording the positions of the spot groups and marking the positions of the corresponding micro-reaction chambers on the optimized micro-reaction chamber fluorescent images according to the positions of the spot groups; and the RGB intensity acquisition module is used for weighting RGB values of pixel points in the micro-reaction chamber fluorescent image and averaging to acquire the RGB intensity corresponding to each micro-reaction chamber.

2. The portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of a fluorescent target according to claim 1, wherein the portable intelligent detection micro-platform is characterized in that: the detection zone comprises a subtype I detection zone and a subtype II detection zone; the subtype I detection area, the subtype II detection area, the positive control area and the negative control area are symmetrically arranged along the center of the central liquid inlet hole.

3. The portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of a fluorescent target according to claim 1, wherein the portable intelligent detection micro-platform is characterized in that: the nucleic acid fluorescent quantitative reaction system is a CRISPR system, comprising CRISPR-Cas9, CRISPR-Cas12 or CRISPR-Cas13.

4. The portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of a fluorescent target according to claim 3, wherein the CRISPR system comprises Cas-12a protein, primer crRNA, fluorescent reporter and reaction buffer; the fluorescent reporter molecule is connected with a quenching group and carboxyfluorescein.

5. The portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of a fluorescent target according to claim 4, wherein the portable intelligent detection micro-platform is characterized in that: each reagent in the nucleic acid fluorescence quantitative reaction system is pre-arranged in the micro-channel chip in a freeze-dried mode.

6. The portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of a fluorescent target according to claim 1, wherein the portable intelligent detection micro-platform is characterized in that: the image acquisition module comprises an ultraviolet lamp and an intelligent mobile terminal integrated with a camera.

7. A method for accurately and rapidly quantifying the concentration of a fluorescent quantitative target, which is applied to a portable intelligent detection micro-platform for accurately and rapidly quantifying the concentration of the fluorescent quantitative target according to any one of claims 1 to 6, wherein the target is a bacterial target gene, and is characterized by comprising the following steps:

s01: the method comprises the steps of reacting a preset freeze-dried nucleic acid fluorescence quantitative reaction system with nucleic acid of a known sample in a micro-channel chip; the target concentration of the known sample nucleic acid is known;

s02: irradiating the micro-channel chip after nucleic acid fluorescence quantitative reaction by using an ultraviolet lamp, and collecting a fluorescence image of a micro-reaction chamber by using an intelligent mobile terminal;

s03: optimizing the acquired fluorescence image of the micro-reaction chamber;

s04: identifying the micro-reaction chambers in the optimized micro-reaction chamber fluorescent image, acquiring the RGB intensities corresponding to each micro-reaction chamber in the micro-reaction chamber fluorescent image, and calculating the RGB average value of all the micro-reaction chambers in the current detection area;

S05: establishing a linear equation according to the RGB intensity mean value and the known target concentration of the known sample nucleic acid;

s06: adding a sample to be detected into the micro-channel chip to react with a preset freeze-dried nucleic acid fluorescent quantitative reaction system;

s07: irradiating the micro-channel chip subjected to nucleic acid fluorescence quantitative reaction by using an ultraviolet lamp, and collecting a fluorescence image of a micro-reaction chamber by using an intelligent mobile terminal;

s08: optimizing the acquired fluorescence image of the micro-reaction chamber;

s09: identifying micro-reaction chambers in a micro-reaction chamber fluorescence image, acquiring RGB intensity corresponding to each micro-reaction chamber in the micro-reaction chamber fluorescence image, and calculating RGB average values of all the micro-reaction chambers in a current detection area;

s10: and carrying the RGB intensity mean value of the sample to be detected into the linear equation so as to calculate the nucleic acid content of the sample to be detected.

8. The method for accurate and rapid fluorescence quantification of a target concentration of claim 7, wherein the step of optimizing the acquired micro-chamber fluorescence image comprises:

expanding the pixels of the acquired micro-reaction chamber fluorescent image to a preset value by adopting a bilinear interpolation algorithm;

The difference in brightness between each pixel and surrounding pixels is reduced using gaussian filtering.

9. The method for precisely and rapidly quantifying the target concentration by fluorescence according to claim 7, wherein the steps of identifying the micro-reaction chambers in the micro-reaction chamber fluorescence image and obtaining the corresponding RGB intensities of each micro-reaction chamber in the micro-reaction chamber fluorescence image comprise:

setting a threshold range of 0-N and a threshold step length of N, thereby obtaining a plurality of gray thresholds;

respectively comparing the gray values of the pixel points with a plurality of gray threshold values, and setting the pixel points with the gray values larger than the threshold value as white and the pixel points smaller than or equal to the threshold value as black so as to obtain a plurality of binarized images;

respectively extracting white pixels communicated in each binarized image as spots, and merging the spots overlapped in the geometric centers in all the binarized images into a spot group;

selecting a spot group representing the micro-reaction chamber by screening the spot group according to the number of pixels, the convexity, the inertia ratio and the roundness;

recording the positions of the spot groups, and marking the positions of the corresponding micro-reaction chambers on the optimized micro-reaction chamber fluorescent images according to the positions of the spot groups;

And carrying out RGB value weighting and average on pixel points in the micro-reaction chamber in the optimized micro-reaction chamber fluorescent image to obtain the RGB intensity of each representative micro-reaction chamber.

10. The method for accurate and rapid fluorescence quantification of a target concentration of claim 7, wherein: the specific steps of reacting the sample nucleic acid with the preset freeze-dried nucleic acid fluorescence quantitative reaction system are as follows:

s01: taking a sample to be detected, and lysing cells to expose DNA, wherein the sample is cryptococcus;

s02: adding a sample solution containing exposed DNA from a central liquid inlet hole of the micro-channel chip, and simultaneously applying negative pressure and vacuumizing outside the micro-channel chip to enable the sample solution containing exposed DNA to fully enter the micro-channel chip and react with a preset freeze-dried nucleic acid fluorescence quantitative reaction system;

s03: after Cas12a protein in the nucleic acid fluorescence quantitative reaction system is combined with target sample specific crRNA, releasing nonspecific endonuclease activity, cutting off a quenching group and carboxyfluorescein on a fluorescence reporter molecule, and releasing fluorescence; the sequence of the target sample specific crRNA is shown as SEQ ID NO.1, SEQ ID NO.2 or SEQ ID NO. 3.