A SPR anti-interference dual-reference differential enhancement device and method based on kinetics

Abstract

This invention discloses a kinetic-based SPR anti-interference dual-reference differential enhancement method. First, a three-channel microfluidic device is provided. Then, according to a preset constant-pressure measurement method, a correction factor r value characterizing the relationship between the detection channel and the second reference channel is pre-determined. The detection process is executed using the three-channel microfluidic device, and the correction factor r value is used to correct the three-channel microfluidic device, thereby acquiring the adsorption signals of the corresponding channels. Differential processing is performed on the acquired adsorption signals to obtain the net non-specific adsorption signal increment. Finally, by performing kinetic analysis on the net non-specific adsorption signal increment, the non-specific adsorption component in the mixed adsorption signal of the detection channel is calculated and subtracted, thereby extracting the specific adsorption signal of the detection channel. This method can effectively improve the detection reliability, sensitivity, and applicability in complex biological samples or highly interfering environments.

Description

Technical Field

[0001] This invention relates to the field of SPR detection technology, specifically a dynamic SPR anti-interference dual-reference differential enhancement device and method. Background Technology

[0002] Surface plasmon resonance (SPR) technology is a real-time, label-free biomolecular interaction analysis method based on optical principles. It is widely used in drug screening, immunoassay, protein-protein interaction studies, and trace substance analysis. The corresponding instruments are often referred to as molecular interaction analyzers, belonging to the category of high-end scientific research and diagnostic instruments. SPR technology dynamically tracks molecular binding and dissociation processes by monitoring minute changes in the refractive index of the sensor surface, offering advantages such as high sensitivity, good real-time performance, and label-free operation.

[0003] However, in actual detection processes, especially when analyzing the interactions of biomolecules with weak affinity and low concentrations, non-specific adsorption (NSA) often becomes a major interfering factor affecting the accuracy and sensitivity of detection. Non-specific adsorption typically refers to the non-selective binding of analytes or impurities to the sensor surface through physical means such as hydrophobic interactions and electrostatic adsorption. The resulting signal is superimposed on the target-specific binding signal, and in severe cases, it can even completely mask the latter, leading to distorted detection results or failure to detect the substance.

[0004] Currently, common strategies for addressing the non-specific adsorption problem in SPR detection mainly include: classifying non-specific adsorption into physical adsorption and chemical adsorption based on kinetic characteristics, and then using a dual-channel (one detection channel and one reference channel) differential method to subtract common-mode interference.

[0005] Then, in actual detection, because physical adsorption and chemical adsorption exhibit different attenuation function parameters during dissociation, the dual-channel (single reference channel) method struggles to separate non-specific adsorption attenuation functions, leading to the masking of specific adsorption signals. Particularly for weakly interacting systems, the intensity of non-specific adsorption signals can reach or even exceed that of specific signals by several to tens of times. Traditional methods often fail to achieve effective signal separation, resulting in increased detection limits and narrowed dynamic ranges, severely limiting the application of SPR technology in low-abundance, low-affinity organisms.

[0006] Therefore, there is an urgent need for a dynamic SPR anti-interference dual-reference differential enhancement device and method that can effectively improve the detection reliability, sensitivity and applicability in complex biological samples or high-interference environments. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and propose a dynamic SPR anti-interference dual-reference differential enhancement device and method, which can effectively improve the detection reliability, sensitivity and applicability in complex biological samples or high interference environments.

[0008] To achieve the above objectives, the technical solution specifically adopted by the present invention is as follows: A dynamic-based SPR anti-interference dual-parameter differential enhancement method includes the following steps: Step 1: Set up a three-channel microfluidic device, which includes a first reference channel, a second reference channel, and a detection channel; Step 2: Perform channel pretreatment and calibration: After injecting a sample carrier liquid or solvent without sample into the first reference channel, seal the channel so that there is no liquid flow during subsequent detection; according to the preset constant pressure measurement method, pre-determine the correction factor r value that characterizes the flow ratio relationship between the detection channel and the second reference channel determined by the mechanical structure. Step 3: Execute the detection process: The sample carrier or solvent and the sample to be tested flow simultaneously through the second reference channel and the detection channel, while maintaining a constant total flow rate Q; wherein, the sensitive surface of the second reference channel only undergoes non-specific adsorption, while the sensitive surface of the detection channel undergoes both specific and non-specific adsorption. Step 4: Acquisition and processing of surface plasmon resonance signals: Under constant flow conditions, real-time signals of the first reference channel, the second reference channel, and the detection channel as a function of time are acquired simultaneously; Step 5: Extract and correct the differential signal. (5.1) Based on the measured r value and total flow rate Q, calculate the real-time flow rate of the second reference channel and the detection channel respectively; (5.2) The signal value of the second reference channel is compared with the signal value of the first reference channel to obtain the signal increment containing the flow velocity difference. Non-specific adsorption signal increment Combination signals; (5.3) Calculate the second difference between the signal value of the detection channel and the signal value of the first reference channel to remove inherent differences in the system and obtain the signal increment containing the flow velocity difference. Non-specific adsorption signal increment and specific adsorption signal increment Combination signals; (5.4) Separate the velocity difference signal increment from the combined signal of the first difference. This allows for the acquisition of the non-specific adsorption signal increment of the second reference channel. ; Step 6: Non-specific adsorption reduction based on kinetic model: (6.1) Increment of non-specific adsorption signal for the second reference channel Kinetic analysis was performed to obtain the kinetic parameters of the non-specific adsorption-dissociation process dominated by physical adsorption, including the initial adsorption amount parameter and the dissociation rate parameter related to the flow rate. ; (6.2) Based on the flow rate relationship between the second reference channel and the detection channel, and the theoretical relationship between the initial adsorption capacity parameter and the flow rate, calculate the initial non-specific adsorption capacity of the detection channel; (6.3) Using the calculated initial adsorption amount and dissociation rate parameters of the detection channel for non-specific adsorption. Construct a decay function of the non-specific adsorption signal in the detection channel as a function of time; Step 7, Specific signal extraction: From the combined signal of the second difference obtained in step (5.3), subtract the calculated velocity difference signal increment in sequence. And using the decay function constructed in step (6.3) to calculate the non-specific adsorption signal at any time, the signal characterizing the specific intermolecular interaction is finally obtained. This refers to the specific adsorption signal detected by the detection channel.

[0009] Preferably, in step (2), the method for determining the value of the correction factor r includes: In the three-channel microfluidic device, pure water is filled into the second reference channel and the detection channel respectively; one channel is closed, and fluid is pushed into the other channel under a constant pressure difference. The volume of fluid flowing out per unit time is measured to obtain its flow rate; the closed channels are exchanged, and the above operation is repeated to obtain the flow rate of the other channel; the ratio of the flow rates of the two channels is calculated as the r value.

[0010] Preferably, the determination of the correction factor r value needs to be repeated multiple times, and the average value is taken as the r value for subsequent calculations.

[0011] Preferably, in step (5.4), the velocity difference signal increment It is obtained through one of the following methods: Before or after the formal sample testing begins, a calibration phase is arranged where a sample-free pure sample solution or solvent flows through the second reference channel. During this phase, the signal baselines of the first and second reference channels stabilize. The average of the first difference during this phase is calculated and taken as the calibration result. ;or, The test, conducted beforehand at a total flow rate Q, involves passing a sample-free pure sample solution or solvent through the second reference channel, accurately measuring and storing the corresponding flow rate. value.

[0012] Preferably, in step (6.1), the kinetic model of the non-specific adsorption and dissociation process is an exponential decay model.

[0013] Preferably, when the three-channel microfluidic device is in laminar flow and the correction factor r is less than 1.05, the dissociation rate parameter is... Treat it as a constant.

[0014] Preferably, in the three-channel microfluidic device, the first reference channel is provided with a valve body structure that can control its on / off state.

[0015] The present invention also provides a three-channel differential enhancement device for reducing non-specific adsorption effects based on kinetics, comprising: The microfluidic chip integrates three independent microfluidic channels: a first reference channel, a second reference channel, and a detection channel. A flow drive and control system is used to provide and maintain a constant total flow rate to the second reference channel and the detection channel, and to control the on / off state of the first reference channel; The surface plasmon resonance sensing unit has its sensing surface optically coupled to the detection area of ​​the three microfluidic channels to acquire the resonance signal of each channel in real time. The data processing unit is used to receive the signal from the surface plasmon resonance sensing unit and execute the signal processing and calculation process including steps (5) to (7).

[0016] Preferably, the channel structure of the microfluidic chip is as follows: It includes a main fluid inlet, which is connected to the inlets of the second reference channel and the detection channel simultaneously through a flow splitting structure; the first reference channel has an independent fluid inlet, and the valve body structure is provided at its inlet.

[0017] Preferably, the channel structure of the microfluidic chip is as follows: It includes an upper unit for sample detection and a shared lower reference unit; The upper unit includes at least one detection group, each detection group containing a second reference channel and a detection channel, and sharing a liquid inlet; The lower reference unit includes one or more parallel first reference channels, each first reference channel having an independent valve body structure for providing a static reference signal to the corresponding upper detection group.

[0018] Preferably, the flow drive and control system includes an injection pump or a pressure pump, and a sensor or controller for measuring or controlling the flow rate.

[0019] Preferably, the data processing unit also stores a pre-determined correction factor r value for the microfluidic chip, as well as the incremental flow velocity difference signal measured at different flow rates. Values ​​and nonspecific adsorption-dissociation rate parameters value.

[0020] This invention has the following characteristics and beneficial effects: (1) By adding a static reference channel (channel A) and controlling its non-flowing state during the sample injection stage, combined with a flowing reference channel (channel B), the signal component (S_AB) caused purely by the flow rate difference can be obtained, thereby effectively separating the non-specific adsorption signal from the system common-mode noise. Furthermore, by utilizing the non-specific adsorption kinetic data of channel B under pure solvent conditions, an exponential decay model based on the mass transfer process is established to achieve dynamic prediction and subtraction of the non-specific adsorption signal in channel C, thereby upgrading the traditional passive suppression strategy to active signal analysis and separation, significantly enhancing the ability to extract weakly specific adsorption signals.

[0021] (2) Even under interference conditions where the intensity of the non-specific adsorption signal does not exceed 10 times that of the specific signal, this method can still effectively extract the target signal, and its signal enhancement factor is better than the common 1–1.5 times level. By performing kinetic modeling and differential subtraction on non-specific adsorption, the apparent detection limit can be effectively reduced, and the detection reliability of the system in low concentration and low affinity systems can be improved.

[0022] (3) This method is specifically applicable to constant flow detection processes. It normalizes the flow differences between channels using pre-determined r values, ensuring the consistency of model parameters. The system design supports two microfluidic configurations: Figure 2 Suitable for high consistency detection of single samples; Figure 3 By modularly replicating the "one-to-two" liquid inlet channel, multiple detection units can be constructed and a static reference channel can be shared, significantly increasing the equipment's detection throughput without affecting signal resolution accuracy.

[0023] (4) The r value is introduced as a quantitative parameter for the difference in fluid resistance between channels, and a clear constant pressure measurement method and periodic calibration steps are provided. This can effectively offset the channel performance drift caused by processing tolerance, material aging or blockage, and ensure the accuracy of the signal processing model in long-term use.

[0024] (5) In laminar flow and when the resistance difference between channels is small (r < 1.05), the non-specific adsorption dissociation parameter It can be treated as a constant, eliminating the need to distinguish between the dynamic differences between channels, greatly simplifying the computational complexity of real-time signal processing. Combined with a preset r value and The system can achieve fully automated signal extraction and is suitable for integration into high-throughput SPR detection platforms.

[0025] In summary, this invention achieves systematic suppression and signal enhancement of non-specific adsorption interference through a systematic approach combining three-channel microfluidic design, process control, and kinetic modeling. It is particularly suitable for detecting weak molecular interactions under high background interference, providing reliable methodological support for the precise application of SPR technology in drug screening, biomarker discovery, and other fields. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of a dynamic SPR anti-interference dual-parameter differential enhancement method according to an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram of one embodiment of the three-channel microfluidic device of the present invention.

[0028] Figure 3 This is a schematic diagram of another embodiment of the three-channel microfluidic device in this invention. Detailed Implementation

[0029] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0030] Example 1: A dynamic-based SPR anti-interference dual-parameter differential enhancement method This embodiment provides a dynamic SPR anti-interference dual-parameter differential enhancement method, such as... Figure 1 As shown, the method relies on a three-channel microfluidic device (the structure of which can be seen in Embodiment 2 or 3) and a corresponding control system.

[0031] Step S101: Apparatus preparation and determination of correction factor r Provide such as Figure 2 or Figure 3 The three-channel microfluidic chip shown integrates a first reference channel (channel A), a second reference channel (channel B), and a detection channel (channel C). Before performing formal biological detection, the flow ratio correction factor r between channel B and channel C must be determined and calibrated in advance. This value characterizes the inherent fluid resistance ratio determined by the microscopic differences in the mechanical structure and surface properties (such as length, cross-section, and roughness) of the two channels.

[0032] The specific procedure for determining the r value is as follows: (1) Fill channels B and C with pure water (or the sample carrier solution used) to ensure that there are no air bubbles.

[0033] (2) Connect to the chip inlet via a flow drive system (such as an injection pump) and close the outlet of channel C. Based on the relationship between pressure drop and flow rate, ,in These are the pressure drop, resistance coefficient, and flow rate at both ends of the channel, respectively.

[0034] It should be noted that the resistance coefficients of channels B and C are respectively... ,definition Typically, the measurement channel C is chosen to be the channel with the lowest resistance, i.e. Therefore, in this embodiment, based on Please elaborate.

[0035] The system is set with a constant pressure differential. (Instead of constant flow) mode, fluid is pushed into channel B. The volume of fluid flowing out of channel B within a set time t (e.g., 60 seconds) is collected and measured. Calculate its flow rate .

[0036] (3) Exchange channel, close the outlet of channel B, and under the same constant pressure difference, push fluid into channel C for the same time t, and measure the outflow volume. Calculate flow .

[0037] (4) Calculate the r value for this measurement: .

[0038] (5) Repeat steps (2)-(4) at least 6 times to calculate the arithmetic mean of all r values, and use this mean as the correction factor r for all subsequent calculations. This calibration step can be performed periodically to correct for performance drift caused by material aging or slight blockage of microchannels.

[0039] Step S102: Initialization of detection process and setting of channel status Static first reference channel (A) setup: Inject pure sample carrier solution (or buffer solvent) without the test sample into the independent inlet of channel A. Subsequently, completely seal channel A by controlling the shut-off valve (such as a solenoid valve) at its inlet or outlet, maintaining it in a statically closed state with no liquid flow throughout the subsequent detection process. At this time, the SPR signal of channel A will provide a stable system baseline reference.

[0040] Preparation of the flow-through second reference channel (B) and detection channel (C): The sensing surfaces of channel B and detection channel C are differentiated. The sensing surface of channel B is modified or treated to allow only non-specific adsorption (e.g., coated only with inert proteins or blocking agents, without immobilizing target capture molecules). The sensing surface of detection channel C, on the other hand, is immobilized with specific capture molecules (e.g., antibodies, receptors), enabling target-specific adsorption while still allowing for non-specific adsorption.

[0041] Flow control: The sample solution (or a mixture of sample and carrier solution) is introduced into channels B and C simultaneously through a shared inlet splitter structure. The flow drive and control system (such as a high-precision syringe pump) operates in constant flow mode, maintaining a constant total flow rate Q through channels B and C. Based on the r value measured in step S101, the real-time flow rates of the two channels can be calculated as follows: .

[0042] Step S103: Synchronous acquisition of SPR signal Under constant flow rate Q, the surface plasmon resonance sensing unit is activated to synchronously and in real time acquire SPR response signals (such as resonance angular displacement Δθ or wavelength displacement Δλ) of channels A (static baseline signal), B (non-specific adsorption signal only), and C (mixed adsorption, where the mixed adsorption signal includes both non-specific and specific adsorption signals) at the same sampling frequency, and record them as a time-varying signal sequence. , , .

[0043] Step S104: Primary differential processing to remove inherent system differences To eliminate common-mode noise from light source fluctuations, temperature drift, and other factors, as well as differences in initial optical coupling, inter-channel differential is first performed: Calculate the first difference signal This signal consists of two parts: one is the velocity difference signal component caused solely by the flow in channel B and the absence of flow in channel A. (Theoretically constant); secondly, the signal increment generated by channel B due to non-specific adsorption. .

[0044] Calculate the second difference signal This signal consists of three parts: the flow velocity difference signal component. (Constant) Non-specific adsorption signal increment And the specific adsorption signal increment that needs to be extracted ultimately. .

[0045] Step S105: Determination and stripping of flow velocity difference signal components Before the formal sample injection or after the dissociation phase, a "pure solvent rinse" step is performed: using a pure sample carrier solution without the sample, it flows through channels B and C at the same total flow rate Q as the formal assay, while channel A remains closed. During this period, no non-specific adsorption occurs in channel B, and its signal is stable. The first differential signal of this phase is recorded. The average value, i.e., the accurate value under the current flow Q, is obtained. Value. Similarly, we can obtain Value (or by r value and) (Relationship deduction).

[0046] Subsequently, the flow rate effect was removed from the first difference signal to obtain the net non-specific adsorption signal of channel B: .

[0047] Similarly, for detection channel C, it can also be removed. The signal increment formed by the specific-nonspecific adsorption of detection channel C is obtained. .

[0048] Step S106: Kinetic-based nonspecific adsorption modeling and extrapolation Model fitting: During the dissociation phase, after sample injection and rinsing with the pure sample carrier solution, non-specifically adsorbed molecules gradually dissociate. The decay curve during the dissociation phase is fitted.

[0049] Understandable. , They exhibit different kinetic characteristics under the flushing action of the sample carrier / solvent: Primarily driven by chemisorption, while Primarily driven by physical adsorption, it exhibits typical exponential decay characteristics, which can be described as a decremental decay function. ,in, This represents the initial non-specific adsorption concentration.

[0050] and and Since they are formed from the same substance, they are expected to exhibit the same exponential decay with the same characteristic parameters under the flushing action of the sample carrier / solvent. The only difference between the two is the initial concentration, i.e., the maximum equilibrium adsorption amount formed during the injection process, denoted as […]. , . The calculation method is as follows:

[0051] in , These are the mass transfer parameters and the concentration of non-specific adsorbed substances in the sample carrier / solvent, respectively, which can be considered constants during the detection process.

[0052] Typically, nonspecific adsorption-dissociation processes dominated by physical adsorption can be described by an exponential decay model: ,in Here, t is the initial value, and t is the dissociation start time. These are the dissociation parameters. The initial adsorption equilibrium value can be obtained through fitting. and dissociation rate constant The rate constant Related to flow rate (i.e., mass transfer rate), it can be denoted as: .

[0053] Furthermore, since channel C and channel B experience the same non-specific adsorbed material environment and their dissociation kinetics are dominated by the same physical adsorption mechanism, it can be assumed that the non-specific adsorption in the two channels has the same dissociation rate constant. The difference in non-specific adsorption capacity between the two channels mainly stems from the difference in mass transfer process caused by the different flow rates. According to the mass transfer model, the initial adsorption equilibrium... With traffic There is a theoretical relationship (e.g., proportional to Q^(-2 / 3)). Combining the measured r value and... The initial amount of non-specific adsorption in detection channel C can be calculated. .

[0054] It should be further noted that when the resistance difference between channels is very small (r < 1.05) and laminar flow is in effect, it can be simplified to consider... Alternatively, the proportional relationship can be determined directly through experiments.

[0055] Constructing the decay function: Therefore, a prediction function for the decay of the non-specific adsorption signal in detection channel C over time can be constructed. .

[0056] Step S107: Final extraction of specific signals From the second difference signal In the middle, the determined velocity difference components are subtracted sequentially. and the non-specific adsorption signal calculated using the prediction function constructed in step S106. This allows for the final extraction of a pure, specific adsorption signal.

[0057] Should The signal is the true kinetic curve characterizing the interaction between target molecules after removing non-specific adsorption interference, and can be used to calculate parameters such as binding rate, dissociation rate and affinity.

[0058] Example 2: Device Example (Single Sample Detection Type Three-Channel Microfluidic Device) This embodiment provides a specific apparatus for implementing the method described in Embodiment 1, the structure of which corresponds to... Figure 2 The device mainly includes the following parts: Microfluidic chip: It is manufactured using a one-piece process (such as glass-PDMS bonding or plastic injection molding). The chip integrates three parallel microchannels as detection channels.

[0059] Fluid Layout: A main body inlet 1 is provided for introducing the sample or sample carrier liquid. Downstream of inlet 1 is a "Y"-shaped diversion structure that divides the fluid into two equal paths, which are respectively introduced into the second reference channel B and the detection channel C. The first reference channel A is provided with an independent fluid inlet 3, which integrates a shut-off valve 2 (e.g., a PDMS diaphragm valve or piezoelectric valve that can be driven by an external electromagnet).

[0060] Sensing regions: Identical SPR sensing films (such as gold films) are prepared below the detection regions (i.e., the middle sections of the channels) of the three channels. The sensing surface of channel B is inertized and sealed, while the sensing surface of channel C is immobilized with specific trapping molecules.

[0061] Liquid outlet: Each of the three channels has an independent fluid outlet, which facilitates waste liquid collection or connection to a pressure sensor.

[0062] Flow drive and control system: Includes a high-precision dual-channel syringe pump (or pressure pump). One channel of the pump is connected via tubing to the main fluid inlet 1, used to deliver the sample / load solution mixture to channels B and C in a constant flow mode. The other channel of the pump is connected to an independent inlet 3, which injects solvent into channel A only during the initialization phase, after which the shut-off valve 2 is closed by a control signal.

[0063] The system controller is electrically connected to the injection pump and shut-off valve 2, and coordinates the injection, shut-off, and flushing processes according to a preset program, while ensuring that the total flow rate Q remains constant.

[0064] The surface plasmon resonance sensing unit includes a light source (such as an LED or laser diode), an optical prism (whose bottom surface is optically coupled to the sensing surface of the microfluidic chip), and a photodetector array (such as a CCD or CMOS camera). The optical system is designed to simultaneously measure the SPR resonance angle changes above the sensing surfaces of the three channels, enabling synchronous real-time signal acquisition.

[0065] Data processing unit: This is an embedded computer or a connected host computer with built-in signal processing software. It is configured to perform the following operations: a. Receive and store the three-channel raw signals from the detector. , , .

[0066] b. Store the pre-determined correction factor r value for the chip.

[0067] c. Automatically perform the difference calculations described in steps S104 to S107 of Example 1. Determination, dynamic fitting (e.g., using the Levenberg-Marquardt algorithm to fit exponential decay), nonspecific signal prediction, and final specific signal. The complete algorithm flow for extraction.

[0068] d. Visualize the original signal, intermediate differential signal, and the final extracted specific dynamic curve.

[0069] This structure ( Figure 2 The characteristics of this system are a simple flow path, with the fluid source of channels B and C being completely consistent, and good flow symmetry, making it very suitable for high-precision and high-consistency detection and analysis of a single sample.

[0070] Example 3: Device Example (High-throughput Detection Type Three-Channel Microfluidic Device) This embodiment provides another device implementation, the structure of which corresponds to Figure 3 This aims to increase testing throughput. For example... Figure 3 As shown, the device adopts a modular design and mainly includes: Microfluidic chip: The chip can be structurally divided into an upper detection unit and a lower reference unit.

[0071] Upper detection unit: contains at least two ( Figure 3 (Taking two examples) The two detection groups are identical. Each detection group adopts a "one-to-two" liquid inlet design, with one group inlet 3. After the fluid is split within the group, it enters a second reference channel B and a detection channel C. The sensing surface treatment of channels B and C in different detection groups can be the same as in Example 2. The group inlets 3 of each detection group can be connected in parallel to the sample dispensing system, thereby realizing the simultaneous detection of multiple samples.

[0072] The lower reference unit contains the same number of first reference channels A as the upper detection groups. These channels A are connected in parallel and share a common reference liquid inlet 3. Each channel A has an integrated independent inlet at its inlet. When conducting experiments for a certain detection group n, solvent is injected into its channel A and then closed, making it the static reference channel for that detection group. The valves of other channels A remain closed.

[0073] Flow drive and control system: A multi-channel fluid drive scheme (such as a multi-channel injection pump or rotary valve switching system) is adopted to independently control the sample flow to each upper detection group inlet 3.

[0074] The reference solution inlet 3 is connected to an independent solvent pump, which is used to inject solution into each channel A before the experiment begins.

[0075] The central controller precisely controls the opening and closing sequence of each valve, synchronizing it with the experimental process of the corresponding upper detection group.

[0076] Surface plasmon resonance sensing unit and data processing unit: The optical sensing unit needs to be able to monitor all channels simultaneously (e.g., 6 channels in 2 detection groups), and can adopt a wide beam illumination combined with multi-area detection.

[0077] The data processing unit needs to independently store the corresponding correction factor r for each detection group n (because there may be slight differences in the processing of different groups), and run multiple instantiated signal processing algorithms in parallel to extract the specific signal for each detection group. .

[0078] This structure, through the reuse of static reference units and modular design, significantly improves the instrument's detection throughput without substantially increasing the complexity of the optical and fluid systems, making it suitable for applications requiring high efficiency and parallelism, such as drug screening and simultaneous detection of multiple indicators.

[0079] Based on the above embodiments, compared with the prior art, the present invention does not reduce the actual detection limit, but it can enhance extraction within 10 times the intensity of the non-specific adsorption signal, exceeding the common 1 to 1.5 times. Therefore, it can achieve higher detection capability in strong substance interference environment.

[0080] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic-based SPR anti-interference dual-parameter differential enhancement method, characterized in that, Includes the following steps: Step 1: Provide a three-channel microfluidic device, which includes a first reference channel, a second reference channel, and a detection channel; Step 2: Based on the preset constant pressure measurement method, pre-determine the correction factor r value of the flow ratio relationship between the detection channel and the second reference channel, which is determined by the microscopic differences in mechanical structure and surface properties. Step 3: Execute the detection process using a three-channel microfluidic device, and calibrate the three-channel microfluidic device using a calibration factor r value, thereby obtaining the static baseline signal of the first reference channel, the non-specific adsorption signal of the second reference channel, and the mixed adsorption signal of the detection channel, wherein the mixed adsorption signal includes non-specific adsorption signal and specific adsorption signal; Step 4: Based on the static baseline signal of the first reference channel, perform differential processing on the signals of the second reference channel and the detection channel respectively to obtain the net nonspecific adsorption signal increment; Step 5: By performing kinetic analysis on the net nonspecific adsorption signal increment, the nonspecific adsorption component in the mixed adsorption signal of the detection channel is calculated and subtracted, thereby extracting the specific adsorption signal of the detection channel.

2. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 1, characterized in that, In step 3, the detection process is as follows: the first reference channel is kept in a static reference state with no liquid flow; the same sample carrier liquid or solvent and the sample to be tested flow through the second reference channel and the detection channel simultaneously; wherein, the sensing surface of the second reference channel is set to only undergo non-specific adsorption, and the sensing surface of the detection channel is set to undergo both specific and non-specific adsorption.

3. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 2, characterized in that, Before the detection process, a flow relationship calibration step is also included: the flow rate difference between the second reference channel and the detection channel is corrected using the correction factor r value.

4. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 2, characterized in that, The method for determining the correction factor r value is as follows: in the three-channel microfluidic device, pure water is filled into the second reference channel and the detection channel respectively; one channel is closed, and fluid is pushed into the other channel under a constant pressure difference; the volume of fluid flowing out per unit time is measured to obtain its flow rate. By swapping the closed channels and repeating the above operation, the flow of the other channel can be obtained; Calculate the ratio of the traffic flow of the two channels, and use it as the r value.

5. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 1, characterized in that, In step 4, the signal processing method includes: The difference between the signal of the second reference channel and the signal of the first reference channel is calculated to obtain a first difference signal, which includes the flow rate difference signal and the non-specific adsorption signal of the second reference channel; The difference between the signal of the detection channel and the signal of the first reference channel is calculated to obtain a second difference signal. The second difference signal includes the flow rate difference signal, the non-specific adsorption signal of the detection channel, and the specific adsorption signal. The flow rate difference signal is separated from the first difference signal to obtain the net nonspecific adsorption signal increment of the second reference channel.

6. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 5, characterized in that, The kinetic analysis of the nonspecific adsorption signal of the second reference channel includes: fitting the decay process of the net nonspecific adsorption signal increment during the dissociation stage to obtain the dissociation kinetic parameters of nonspecific adsorption.

7. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 6, characterized in that, The step of calculating and subtracting the non-specific adsorption component in the mixed adsorption signal of the detection channel includes: converting the dissociation kinetic parameters and non-specific adsorption amount information obtained from the second reference channel into a non-specific adsorption decay function applicable to the detection channel based on the flow relationship between the second reference channel and the detection channel, and subtracting the signal component characterized by the non-specific adsorption decay function from the second difference signal.

8. The dynamic-based SPR anti-interference dual-parameter differential enhancement method according to claim 1, characterized in that, The detection process is performed under a constant total flow rate.

9. An apparatus for implementing the dynamics-based SPR anti-interference dual-parameter differential enhancement method according to any one of claims 1 to 8, characterized in that, include: The microfluidic chip integrates three independent microfluidic channels: a first reference channel, a second reference channel, and a detection channel. The first reference channel is equipped with a valve structure that keeps it closed and static. A flow drive and control system is used to drive the liquid flow through the second reference channel and the detection channel; A surface plasmon resonance sensing unit is used to monitor the signal changes of the three sensing surfaces in real time. The data processing unit is configured to perform the signal processing, differential and dynamic reduction steps.

10. The apparatus according to claim 9, characterized in that, The microfluidic chip has the following channel structure: the second reference channel and the detection channel share a liquid inlet split structure, and the first reference channel has an independent liquid inlet.

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