Microfluidic neutralizing antibody detection method and system based on quantum dot fluorescent probe

Abstract

The application discloses a kind of microfluidic neutralizing antibody detection method and system based on quantum dot fluorescent probe, belong to biological detection technical field.The method includes: obtaining the donor channel fluorescence signal time series of microfluidic chip detection area under the irradiation of continuous excitation light;Double exponential decay fitting is carried out to time series, and first decay component and second decay component are obtained, wherein the first rate constant is greater than the second rate constant, and the first amplitude is negative;The ratio of the absolute value of first amplitude and second amplitude is calculated;According to the ratio and the preset calibration relationship, the surface coverage of detection area and the concentration of target analyte are determined.The system includes microfluidic chip, optical excitation module, fluorescence detection module and data processing module.Through the application, the problem that only fluorescence resonance energy transfer efficiency is used as static measurement in the prior art without utilizing system time evolution dynamics information is solved, and high-precision, wide dynamic range detection of neutralizing antibody is realized.

Description

Technical Field

[0001] This invention relates to a microfluidic method and system for detecting neutralizing antibodies based on quantum dot fluorescent probes, belonging to the field of biodetection technology. Background Technology

[0002] The detection of virus-neutralizing antibodies is of great significance for infectious disease diagnosis, evaluation of vaccine efficacy, and development of therapeutic antibodies. With the development of nanotechnology and microfluidics, microfluidic detection technology based on quantum dot fluorescent probes has become a research hotspot in the field of immunoassay due to its high sensitivity, high throughput, and miniaturization advantages. In particular, by utilizing the excellent photostability, high quantum yield, and wide Stokes shift of quantum dots, a homogeneous immunoassay system based on fluorescence resonance energy transfer (FRET) can be constructed, enabling real-time monitoring of the antigen-antibody specific binding process.

[0003] In existing technologies, immunoassay methods based on fluorescence resonance energy transfer (FRET) primarily focus on measuring steady-state signals. Typically, fluorescence intensity is acquired within a specific time window after excitation, and the ratio of donor to acceptor fluorescence intensity or FRET efficiency is calculated as the basis for quantification. This static measurement mode treats the FRET process as a static physical state, focusing only on instantaneous signal intensity changes while ignoring the dynamic evolution of the photophysical properties of the fluorescent probe over time under continuous excitation light irradiation. For example, under continuous illumination, donors in the FRET state and unpaired donors often exhibit different photobleaching kinetics; this temporal difference is completely discarded in static measurements.

[0004] Therefore, the core technical problem with the aforementioned existing technology lies in the fact that it only uses fluorescence resonance energy transfer efficiency as a static quantity for measurement, failing to utilize the time evolution dynamics information of the fluorescence resonance energy transfer system. This lack of information leads to two problems: firstly, the detection dynamic range is limited by the static signal-to-noise ratio, and it is difficult to distinguish background fluorescence generated by non-specific adsorption, making it susceptible to interference; secondly, due to the lack of inherent constraints from kinetic parameters, the detection system cannot establish an effective self-verification mechanism, making it difficult to identify anomalies caused by probe aggregation or environmental fluctuations, thus limiting the accuracy and reliability of the detection results. Summary of the Invention

[0005] The technical problem to be solved by this invention is to provide a microfluidic method and system for detecting neutralizing antibodies based on quantum dot fluorescent probes. It solves the problem in the prior art that only fluorescence resonance energy transfer efficiency is measured as a static quantity and the dynamic information of system time evolution is not utilized, thus realizing high-precision and wide dynamic range detection of neutralizing antibodies.

[0006] The technical problem to be solved by this invention is achieved by the following technical solution:

[0007] A microfluidic method and system for detecting neutralizing antibodies based on quantum dot fluorescent probes includes the following steps:

[0008] Obtain the time series of donor channel fluorescence signals in the detection area of ​​a microfluidic chip under continuous excitation light irradiation;

[0009] The time series of the donor channel fluorescence signal is fitted with a double exponential decay to obtain a first decay component and a second decay component, wherein the first decay component corresponds to a first rate constant and a first amplitude, and the second decay component corresponds to a second rate constant and a second amplitude; the first rate constant is greater than the second rate constant, and the first amplitude is negative.

[0010] Calculate the ratio of the absolute value of the first amplitude to the second amplitude;

[0011] Based on the ratio, the surface coverage of the detection area is determined by a preset ratio-surface coverage calibration curve; based on the preset negative correlation calibration relationship between the surface coverage and the target analyte concentration, the concentration of the target analyte in the sample to be tested is determined.

[0012] Optionally, before acquiring the time series of the donor channel fluorescence signal, a spatial normalization step is further included:

[0013] Before the continuous excitation light is turned on, the initial fluorescence intensity spatial distribution map of the detection area is acquired;

[0014] During the acquisition of the time series of fluorescence signals in the donor channel, the real-time fluorescence signal at each spatial location in the detection area is divided by the initial intensity value corresponding to that spatial location in the initial fluorescence intensity spatial distribution map to obtain the normalized fluorescence signal.

[0015] Spatially average the normalized fluorescence signal to obtain the donor channel fluorescence signal time series for subsequent double exponential decay fitting.

[0016] Optionally, the continuous excitation light is a flat-top distributed beam shaped by a beam homogenizer, and the excitation power density deviation in the detection area does not exceed ±5%.

[0017] Optionally, the double exponential decay fitting employs a two-step decoupling fitting strategy, specifically including:

[0018] The second rate constant and the second amplitude are determined by performing a single exponential fit on the tail time segment data of the donor channel fluorescence signal time series;

[0019] The attenuation tail baseline is calculated based on the second rate constant and the second amplitude, and the attenuation tail baseline is subtracted from the donor channel fluorescence signal time series to obtain the residual signal;

[0020] The residual signal is subjected to single-exponential fitting to determine the first rate constant and the first amplitude.

[0021] Optionally, the first amplitude being negative is determined by the following physical condition: the total bleaching rate of the acceptor fluorescent nanoprobe is greater than the product of the intrinsic bleaching rate of the donor fluorescent nanoprobe and the efficiency of a single FRET pair, so that the donor paired with the acceptor disappears at a faster rate than the unpaired donor.

[0022] Optionally, a solid-phase recognition element labeled with a donor fluorescent nanoprobe is immobilized in the detection area, and the sample to be tested also contains a label conjugate labeled with a receptor fluorescent nanoprobe; the target analyte is a neutralizing antibody, which competes with the label conjugate for binding to the solid-phase recognition element; the surface coverage characterizes the amount of the label conjugate labeled with the receptor fluorescent nanoprobe on the detection area; the surface density of the donor fluorescent nanoprobe is configured such that the donor-receptor pairing follows a Poisson distribution and the Poisson parameter does not exceed 0.3.

[0023] Optionally, the donor fluorescent nanoprobe is fixed to the solid-phase recognition element via a rigid connecting arm, and the acceptor fluorescent nanoprobe is marked on the marker-binding body via a flexible connecting arm; the sum of the lengths of the rigid connecting arm and the flexible connecting arm makes the ratio of the distance between the donor fluorescent nanoprobe and the acceptor fluorescent nanoprobe to a preset Förster radius between 0.8 and 1.2.

[0024] Optionally, after the double exponential decay fitting, a model validity verification step is also included:

[0025] A single exponential decay model and a double exponential decay model were constructed to fit the time series of fluorescence signals in the donor channel, respectively.

[0026] The goodness of fit between the double exponential decay model and the single exponential decay model is compared by the F-test. When the statistic of the F-test is greater than a preset critical value, the double exponential decay model is confirmed to be effective.

[0027] Optionally, it further includes synchronously acquiring the time series of receptor channel fluorescence signals, wherein the time series of receptor channel fluorescence signals includes a first receptor attenuation component and a second receptor attenuation component, wherein the first receptor attenuation component corresponds to the total receptor bleaching rate constant, and the second receptor attenuation component corresponds to the first rate constant.

[0028] It also includes dynamic parameter verification steps and dual-channel cross-verification steps;

[0029] The kinetic parameter verification step includes: calculating the ratio of the first rate constant to the second rate constant, and determining whether the ratio falls within a preset effective range. The lower limit of the effective range is 5, and the upper limit is the upper limit of the intrinsic parameters of the detection system. The upper limit of the intrinsic parameters is jointly determined by the intrinsic bleaching rate of the donor fluorescent nanoprobe, the total bleaching rate of the acceptor fluorescent nanoprobe, and the single-pair FRET efficiency, and does not change with the concentration of the target analyte. If the ratio is not within the preset effective range, the detection is determined to be abnormal.

[0030] The dual-channel cross-validation step includes: extracting the rate constant corresponding to the second receptor decay component from the receptor channel fluorescence signal time series, comparing the consistency between the first rate constant extracted from the donor channel fluorescence signal time series and the rate constant corresponding to the second receptor decay component extracted from the receptor channel fluorescence signal time series, and determining an abnormality if the difference exceeds a preset threshold.

[0031] A microfluidic neutralizing antibody detection system based on quantum dot fluorescent probes, comprising:

[0032] A microfluidic chip has a detection area in which a solid-phase recognition element labeled with a donor fluorescent nanoprobe is fixed. The surface density of the donor fluorescent nanoprobe is configured such that the donor-acceptor pairing follows a Poisson distribution and the Poisson parameter does not exceed 0.3.

[0033] An optical excitation module is used to generate continuous excitation light with a uniform power density distribution in the detection area;

[0034] The fluorescence detection module is used to simultaneously acquire the time series of fluorescence signals from the donor channel and the acceptor channel;

[0035] The data processing module is used in the above method to process the time series of fluorescence signals from the donor channel and output the concentration of the target analyte.

[0036] The beneficial effects of this invention are as follows: By acquiring the time series of donor channel fluorescence signals under continuous excitation light irradiation, a fast decay component (first decay component) reflecting the FRET kinetic process and a slow decay component (second decay component) reflecting intrinsic bleaching are extracted using double exponential decay fitting. Furthermore, the ratio of the absolute value of the negative amplitude of the fast component to the amplitude of the slow component is innovatively used as a quantitative indicator. This method fully utilizes the time evolution kinetic information of the FRET system, establishes a direct correlation between the ratio and surface coverage, and effectively broadens the detection dynamic range. In addition, this method constructs a complete detection self-verification system through effective range verification of the kinetic parameter ratio and consistency cross-verification of the dual-channel rate constants, significantly improving the anti-interference ability and result reliability of the detection system in complex sample environments. Attached Figure Description

[0037] Figure 1 This is the main flowchart of the present invention.

[0038] Figure 2 This is a flowchart of the double exponential decay fitting process in this invention.

[0039] Figure 3 This is a flowchart of the model validity verification and dynamic parameter verification process in this invention.

[0040] Figure 4 This is the system architecture diagram of the present invention.

[0041] Figure 5 This is a schematic diagram of the microfluidic chip structure of the present invention. Detailed Implementation

[0042] To facilitate a clear understanding of the technical means, creative features, objectives, and effects of this invention, the invention will be further described below in conjunction with specific illustrations.

[0043] To address the shortcomings of existing immunoassay techniques that utilize fluorescence resonance energy transfer (FRET) and only measure FRET efficiency as a static quantity, failing to leverage the time-varying dynamics of the FRET system and resulting in a narrow detection dynamic range, susceptibility to non-specific adsorption interference, and a lack of self-verification capabilities, this application provides a microfluidic neutralizing antibody detection method based on quantum dot fluorescent probes. Figure 1 As shown, it includes the following steps.

[0044] The Förster radius described in this invention is a characteristic distance parameter characterizing fluorescence resonance energy transfer efficiency. It means that when the spatial distance between the donor fluorescent probe and the acceptor fluorescent probe is exactly equal to this radius, the efficiency of a single FRET pair is 50%. The specific value of this radius is determined by the fluorescence quantum yield of the donor, the molar extinction coefficient of the acceptor, and the spectral overlap integral of the two probes.

[0045] S1: The sample to be tested is mixed with the label conjugate labeled with the acceptor fluorescent nanoprobe and added to the detection area of ​​a microfluidic chip with a solid-phase recognition element immobilized with the donor fluorescent nanoprobe label, so that the target analyte in the sample competes with the label conjugate to bind to the solid-phase recognition element, forming a donor-acceptor fluorescent nanoprobe pair.

[0046] In this embodiment, the target analyte is a SARS-CoV-2 neutralizing antibody. The test sample is a serum, plasma, or whole blood sample suspected of containing the target analyte. The receptor fluorescent nanoprobe in the label conjugate is a lead sulfide / cadmium sulfide core-shell quantum dot with an emission wavelength of 800 nm. This receptor fluorescent nanoprobe is labeled onto the label conjugate via a flexible linker arm, which is a short polyethylene glycol chain with a length of 2.5 nm. The donor fluorescent nanoprobe is a cadmium selenide / cadmium sulfide core-shell quantum dot with an emission wavelength of 580 nm. This donor fluorescent nanoprobe is fixed to a solid-phase recognition element via a rigid linker arm, which is a 9-base-pair double-stranded deoxyribonucleic acid protein with a length of 3 nm. The solid-phase recognition element is the SARS-CoV-2 spike protein receptor-binding domain protein.

[0047] The surface density of the donor fluorescent nanoprobes is configured such that donor-acceptor pairing follows a Poisson distribution with a Poisson parameter not exceeding 0.3. In this embodiment, the surface density of the donor fluorescent nanoprobes is 200 nanoprobes per square micrometer. This surface density is chosen because, with a detection area of ​​2 square millimeters, the total number of donors is approximately 4 × 10⁻⁶. 5 This ensures that the fluorescence signal intensity meets the detection requirements. Simultaneously, at this density, the spacing between adjacent donors is approximately 70 nanometers, far exceeding the Förster radius of 9.5 nanometers, indicating no energy transfer between donors and satisfying the independent donor hypothesis. By controlling the concentration of the label-binding complex of the acceptor fluorescent nanoprobe and the incubation time, a Poisson parameter of 0.3 was achieved.

[0048] The implementation method is as follows: Under a fixed donor surface density, the label-binding complex labeled with the receptor fluorescent nanoprobe is incubated with a solid-phase recognition element at five concentration gradients of 0.5 nmol / L, 1 nmol / L, 2 nmol / L, 5 nmol / L, and 10 nmol / L for 15 minutes, 30 minutes, 45 minutes, and 60 minutes, respectively. The surface coverage under each condition is measured, and the corresponding Poisson parameter is calculated. The lowest receptor probe concentration and the shortest incubation time with a Poisson parameter not exceeding 0.3 and a signal intensity meeting the detection requirements are selected as the optimal conditions. In this embodiment, the preferred conditions are a receptor probe concentration of 2 nmol / L and an incubation time of 30 minutes.

[0049] To eliminate interference from quantum dot aggregates, the donor fluorescent nanoprobes were purified by size exclusion chromatography (SUC) before immobilization to remove aggregates. SUC was performed using a Sepharose CL-4B gel column with phosphate buffer as the mobile phase. The first elution peak (corresponding to monodisperse quantum dots) was collected, and subsequent elution peaks (corresponding to aggregates) were discarded. Surface immobilization employed a dilution method: the quantum dot solution was diluted to 0.1 nanomolars / L and incubated at 4°C for 12 hours to ensure that each immobilization site bound to at most one quantum dot, thus reducing the probability of multiple quantum dots occupying the same site.

[0050] The sum of the lengths of the rigid and flexible connecting arms ensures that the ratio of the distance between the donor and acceptor fluorescent nanoprobes to the preset Förster radius is between 0.8 and 1.2. In this embodiment, the donor-acceptor distance is 9.2 nm, which is contributed by the rigid connecting arm length of 3 nm, the flexible connecting arm length of 2.5 nm, the donor fluorescent nanoprobe radius of approximately 1.5 nm, the acceptor fluorescent nanoprobe radius of approximately 1.2 nm, and the labeled binding protein size of approximately 1 nm. With a preset Förster radius of 9.5 nm, the ratio of the donor-acceptor distance to the preset Förster radius is 0.968, corresponding to a single-pair fluorescence resonance energy transfer efficiency of 0.55, which meets the requirement that the single-pair fluorescence resonance energy transfer efficiency falls within the range of 0.45 to 0.65. The ratio of the donor-acceptor distance distribution width to the preset Förster radius is less than 0.3, and the donor-acceptor distance distribution width is approximately 1.8 nm. This value is determined by combining the length distribution width of the rigid connector arm (approximately 1.5 nm) and the length distribution width of the flexible connector arm (approximately 1.0 nm) using the square root of the sum of their squares. The preset Förster radius is 9.5 nanometers, and the ratio between the two is approximately 0.19, which meets the requirement of being less than 0.3.

[0051] The above mixture was statically incubated at 37 degrees Celsius for 30 minutes to allow the competitive binding to reach equilibrium.

[0052] S2: Before the continuous excitation light is turned on, the initial fluorescence intensity spatial distribution map of the detection area is acquired.

[0053] In a preferred embodiment of the present invention, this step is performed before acquiring the time series of the donor channel fluorescence signal during spatial normalization using imaging detection. Before the excitation light is turned on, or under conditions of extremely low power and negligible bleaching, an initial fluorescence intensity spatial distribution map of the donor channel is acquired using a charge-coupled device or a complementary metal-oxide-semiconductor camera in the auxiliary imaging module for subsequent spatial normalization. In a preferred embodiment, an initial fluorescence intensity spatial distribution map of the acceptor channel is also acquired simultaneously for spatial normalization of the acceptor channel signal.

[0054] S3: Obtain the time series of donor channel fluorescence signals in the detection area of ​​the microfluidic chip under continuous excitation light irradiation.

[0055] A continuous excitation beam is activated. This beam is a flat-top distribution beam shaped by a beam homogenizer, and the excitation power density deviation within the detection area does not exceed ±5%. In this embodiment, the excitation source is a 470 nm wavelength light-emitting diode with an output power of 5 mW, an effective detection area of ​​2 square millimeters, and a power density of 2.5 mW / m². The beam homogenizer uses a microlens array homogenizer to convert the Gaussian beam into a flat-top distribution, ensuring that the power density variation within the detection area is less than ±3%. Simultaneously, constant current drive and photoelectric feedback control are employed to ensure that the root mean square value of the excitation beam power fluctuation is less than 0.1%.

[0056] Under continuous excitation light irradiation, the time series of fluorescence signals from the donor channel is acquired. Acquiring the time series of fluorescence signals from the donor channel is a fundamental step. In a preferred embodiment, the time series of fluorescence signals from the acceptor channel is acquired simultaneously for dual-channel cross-validation in subsequent step S6. The donor channel is detected using a 580 nm bandpass filter in conjunction with a photomultiplier tube, and the acceptor channel is detected using an 800 nm bandpass filter in conjunction with an indium gallium arsenide detector. The acquisition time window is 1800 seconds, and the sampling interval is 1 second. During the acquisition process, a reference photodiode is used to monitor the excitation power in real time for subsequent light source fluctuation correction.

[0057] The acquisition of the donor channel fluorescence signal time series also includes a spatial normalization operation. The real-time fluorescence signal at each spatial location in the detection area is divided by the initial intensity value corresponding to that location in the initial fluorescence intensity spatial distribution map to obtain the normalized fluorescence signal. This normalized fluorescence signal is then spatially averaged to obtain the donor channel fluorescence signal time series used for subsequent double exponential decay fitting. The residual inhomogeneity remaining after homogenization of the excitation light field has a negligible impact on the amplitude ratio.

[0058] As an optional optimization method in this step, an adaptive acquisition time strategy is adopted based on the actual concentration of the sample. When the concentration of the target analyte in the sample is high, the surface coverage is small, the amplitude of the fast component is small, and a longer acquisition time is required to accumulate sufficient signal-to-noise ratio. During the acquisition process, the semi-logarithmic slope of the fluorescence signal in the donor channel is monitored in real time. When the change of this slope within a preset time period is less than a preset threshold, it is determined that the slow component has been fully manifested, and the acquisition can be terminated early.

[0059] S4: Perform double exponential decay fitting on the time series of the donor channel fluorescence signal to obtain a first decay component and a second decay component, wherein the first decay component corresponds to a first rate constant and a first amplitude, and the second decay component corresponds to a second rate constant and a second amplitude; the first rate constant is greater than the second rate constant, and the first amplitude is a negative value.

[0060] Before fitting, the acquired donor channel fluorescence signal time series is preprocessed. Preprocessing includes dark current subtraction, background subtraction, and source fluctuation correction. Source fluctuation correction divides the donor channel fluorescence signal by the ratio of real-time excitation power to initial excitation power to eliminate the influence of excitation power fluctuations on the signal. The double exponential decay model is as follows: in, It is the first amplitude and is negative. The first rate constant is... For the second amplitude, The second rate constant, The background fluorescence intensity is denoted as .

[0061] like Figure 2 As shown, the dual-exponential decay fitting employs a two-step decoupled fitting strategy. First, a single-exponential fit is performed on the tail segment data of the donor channel fluorescence signal time series to determine the second rate constant and the second amplitude. The tail segment data represents the time region after the fast component has essentially decayed; in this region, the signal is mainly contributed by the slow component. The tail segment single-exponential fitting is a fitting problem with uniquely determined parameters, resulting in robustness. Second, the decay tail baseline is calculated based on the second rate constant and the second amplitude. This decay tail baseline is subtracted from the donor channel fluorescence signal time series to obtain the residual signal. A single-exponential fit is then performed on this residual signal to determine the first rate constant and the first amplitude. At this point, the contribution of the slow component in the residual signal has been subtracted, leaving only the contribution of the fast component. The single-exponential fitting is again a fitting problem with uniquely determined parameters, thus decomposing the four-parameter coupled nonlinear fitting problem into two independent two-parameter fitting problems, eliminating the coupling effect between parameters.

[0062] The physical origin of the double-exponential decay in this step is as follows: the donor paired with the surviving acceptor is in a fluorescence resonance energy transfer state, and its apparent decay rate... Unpaired or recipient-bleached donors are in a free state, and their bleaching rate... in, The donor intrinsic bleaching rate constant, For single-pair fluorescence resonance energy transfer efficiency, This represents the total bleaching rate constant of the receptor. It comprises two parts: the contribution from direct photobleaching and the contribution from fluorescence resonance energy transfer-sensitized bleaching. This is due to the total bleaching rate constant of the acceptor. Greater than the donor's intrinsic bleaching rate constant Compared with single-pair fluorescence resonance energy transfer efficiency The product of, i.e. The disappearance rate of fluorescence resonance energy transfer state donors is faster than that of free state donors, resulting in fast component decay; therefore, the first rate constant... Greater than the second rate constant .

[0063] The above model is based on the premise of surface coverage. The test remains constant throughout the detection process. The reasoning for this premise is as follows: The competitive binding equilibrium is established during the incubation phase of S1. In the subsequent photobleaching process, the photobleaching of the acceptor fluorescent nanoprobe does not alter the binding state between the labeled conjugate and the solid-phase recognition element; that is, the bound labeled conjugate does not dissociate due to acceptor bleaching. Therefore, the donor-acceptor pairing remains unchanged during detection. It is a constant.

[0064] In this embodiment, the total bleaching rate constant of the receptor for Donor intrinsic bleaching rate constant per second for per second, single-pair fluorescence resonance energy transfer efficiency It is 0.55. for Every second, Much larger Ensure the first rate constant Greater than the second rate constant .

[0065] First amplitude The physical rationale for negative values ​​is explained as follows: At that moment, the sum of the first and second amplitudes is positive, equal to... As time goes by Increase, due to The fast component term, containing the first negative amplitude, gradually approaches zero from its negative value, while the slow component term remains positive and decays more slowly. Therefore, the fluorescence signal intensity of the donor channel is positive at any given time, satisfying physical realizability. The negative first amplitude reflects the physical process of the system's average fluorescence emission efficiency increasing after the fluorescence resonance energy transfer state donor rapidly disappears due to acceptor bleaching.

[0066] Following the double exponential decay fitting, model validity verification is also performed. Single and double exponential decay models are constructed and fitted to the time series of fluorescence signals from the donor channel, respectively. The goodness of fit between the double and single exponential decay models is compared using an F-test. The F-test is a standard statistical method for comparing the goodness of fit between two nested models; its statistic is calculated from the sum of squared residuals and degrees of freedom of the two models. When the F-test statistic is greater than a preset critical value, the double exponential decay model is considered valid. In this embodiment, the number of data points... F critical value If the calculated F-statistic is greater than the critical value, the double-exponential model is significantly better than the single-exponential model at a 99% confidence level. If the p-value of the F-test is less than 0.01, the existence of fluorescence resonance energy transfer state transition kinetics is confirmed, and subsequent steps are performed; otherwise, it is determined that there is no effective fluorescence resonance energy transfer signal at this detection point.

[0067] As an optional optimization method, a global fitting strategy is adopted to improve fitting accuracy when the same sample is repeatedly measured multiple times. Assuming multiple repeated measurements (no less than 3 times) are performed on the same sample, multiple donor channel fluorescence signal time series are obtained, and a global fitting model is constructed. The first and second rate constants are globally shared parameters, used by all repeated measurements; the first amplitude, second amplitude, and background are local parameters, independent of each measurement. During global fitting, the shared parameters are constrained by multiple curves, improving accuracy. Changes in local parameters reflect measurement noise and can be used to estimate uncertainty. During the fitting process, Bayesian regularization constraints are applied using the prior distributions of the first and second rate constants determined in the calibration experiment. That is, a prior constraint term is added to the fitting objective function to ensure that the fitting result does not deviate from the reasonable range of parameters determined in the calibration experiment. The calibration experiment uses standards of known concentrations for multiple measurements to obtain the mean and standard deviation of the first and second rate constants. This prior information is added as a regularization term to the fitting objective function, ensuring that even when the quality of a single measurement is poor, the prior constraint guarantees that the fitting result remains within a physically reasonable range.

[0068] After fitting, the process includes residual analysis and anomaly detection. The fitting residuals are calculated; these residuals should have no systematic structure, meaning there is no autocorrelation between them. An autocorrelation test is performed on the residuals. If the residuals exhibit a systematic structure, such as oscillations or trends, it indicates that the model is insufficient and that there are interfering factors such as multiple pairings or clusters. This point is then marked as an anomaly.

[0069] To verify the feasibility of the above method under typical noise levels, typical parameter conditions in the embodiments ( Every second, Every second, , Poisson parameters Monte Carlo numerical simulations were performed, repeated 1000 times, using shot noise (Poisson noise) as the noise model. The results show that within a 1800-second acquisition time, the amplitude is... The relative standard deviation is less than 6%, and the rate constant is greater than that of the standard deviation ... The relative standard deviation is less than 4%, indicating that the method has sufficient parameter extraction accuracy under experimentally feasible signal-to-noise ratio conditions.

[0070] S5: Calculate the ratio of the absolute value of the first amplitude to the second amplitude.

[0071] Calculate the ratio This amplitude is greater than Surface coverage Monotonically increasing function: The larger the value, the more donors are in the fluorescence resonance energy transfer state, and the greater the amplitude of the fast component. The larger.

[0072] After calculating the ratio, the Poisson multiple-pairing effect is corrected. Donor-receptor binding follows a Poisson distribution. When the effective Poisson parameter is greater than 0.1, the case where a single donor site binds to multiple receptors needs to be considered. In this embodiment, the effective Poisson parameter is 0.3, and the multiple-pairing probability is calculated from the Poisson distribution. The multiple pairing effect introduces a systematic bias into the amplitude ratio, which is corrected using a correction formula. The multiple pairing effect can also be automatically included when establishing the calibration curve using a triple-exponential model that incorporates multiple pairing components. This triple-exponential model adds a third attenuation component corresponding to a 2:1 pairing to the double-exponential model. The effective Poisson parameter can be predetermined through calibration experiments or estimated by combining the amplitude ratio obtained from the double-exponential fitting with the half-maximum inhibition concentration of the calibration curve. The amplitude ratio after Poisson correction is denoted as... This is used for determining surface coverage and concentration in subsequent step S7.

[0073] S6: Perform dynamic parameter verification and dual-channel cross-validation.

[0074] like Figure 3 As shown, the dynamic parameter verification specifically involves: calculating the first rate constant. With the second rate constant ratio Determine whether the ratio falls within a preset valid range. The lower limit of this valid range is 5, and the upper limit is the upper limit of the inherent parameters of the detection system. .

[0075] The upper limit of the intrinsic parameter is determined by the intrinsic bleaching rate of the donor fluorescent nanoprobe, the total bleaching rate of the acceptor fluorescent nanoprobe, and the single-pair fluorescence resonance energy transfer efficiency. The calculation formula is as follows: in For single-pair fluorescence resonance energy transfer efficiency, The total bleaching rate constant of the receptor is . This is the intrinsic bleaching rate constant of the donor. The upper limit of this intrinsic parameter does not change with the concentration of the target analyte. In this embodiment, the upper limit of the intrinsic parameter is based on the parameters given in S4. therefore The effective range is In actual testing, when the concentration of the target analyte is within the effective detection range, the measured... Falling within the effective range If the ratio is within the preset valid range, the test is considered abnormal.

[0076] The dual-channel cross-validation specifically involves extracting the rate constant corresponding to the second receptor decay component from the receptor channel fluorescence signal time series. The receptor channel fluorescence signal contains two exponential decay components: the first receptor decay component corresponds to the total receptor bleaching rate constant. The second receptor attenuation component corresponds to the first rate constant, derived from direct photobleaching of the receptor fluorescent nanoprobe. This originates from fluorescence resonance energy transfer (FRET) sensitized bleaching. Free, unbound acceptor fluorescent nanoprobes do not form FRET pairs and exhibit single-exponential decay in the acceptor channel, which can be separated from the signal of the bound probe by fitting the signal. The first rate constant obtained from fitting the acceptor channel is denoted as... The first rate constant obtained from fitting the donor channel is denoted as .Compare and Consistency. Non-specific adsorption and background fluorescence do not exhibit this dual-channel consistency and can be automatically identified. If the difference exceeds a preset threshold, an anomaly is determined.

[0077] S7: Based on the ratio, determine the surface coverage of the detection area through a preset ratio-surface coverage calibration curve; determine the concentration of the target analyte in the sample to be tested based on the preset negative correlation calibration relationship between the surface coverage and the target analyte concentration.

[0078] Based on the amplitude ratio after Poisson correction in step S5 The surface coverage is determined by a preset ratio-surface coverage calibration curve. Surface coverage Defined as the ratio of the number of paired donor fluorescent nanoprobes to the total number of donor fluorescent nanoprobes within the detection area. The ratio-surface coverage calibration curve can be established using the following theoretical model: in, The total bleaching rate constant of the receptor is . The first rate constant is... The second rate constant, For single-pair fluorescence resonance energy transfer efficiency, For surface coverage. This formula shows the amplitude ratio. With surface coverage There is a one-to-one correspondence between them, and Follow Monotonically increasing.

[0079] The relationship between surface coverage and target analyte concentration is determined by competitive binding equilibrium, and can be expressed as: in, The Poisson parameter is the parameter when there is no competition. To label the dissociation constant of the complex and the solid-phase recognition element, Let be the concentration of the target analyte. From the above formula, we can see that... Follow The increase leads to a decrease, showing a negative correlation. The values ​​determined in the preceding steps... Substituting the values ​​into the above formula, the concentration of the target analyte can be deduced. The calibration curve is preferably established using the theoretical model described above.

[0080] When parameters in the theoretical model (such as single-pair fluorescence resonance energy transfer efficiency, total acceptor bleaching rate constant, and donor intrinsic bleaching rate constant) are difficult to determine accurately through independent experiments, the following empirical model can be used as an alternative. The calibration curve can be established empirically beforehand by measuring standards of known concentrations. A series of standards with target analyte concentrations of 0, 0.5 nmol / L, 1 nmol / L, 2 nmol / L, 5 nmol / L, 10 nmol / L, 20 nmol / L, 50 nmol / L, 100 nmol / L, and 200 nmol / L are taken and tested according to steps S1 to S6, obtaining the amplitude ratio corresponding to each concentration. A four-parameter Logistic model is used to perform nonlinear fitting on the concentration and amplitude ratio. After determining the model parameters, the empirical calibration curve is obtained. For the sample to be tested, the amplitude ratio after Poisson correction is substituted into the above calibration curve model to inversely deduce the target analyte concentration.

[0081] like Figure 4 As shown, the present invention also provides a microfluidic neutralizing antibody detection system based on quantum dot fluorescent probes, for implementing the above-mentioned microfluidic neutralizing antibody detection method based on quantum dot fluorescent probes, including a microfluidic chip, an optical excitation module, a fluorescence detection module and a data processing module.

[0082] The microfluidic chip has a detection region in which a solid-phase recognition element labeled with a donor fluorescent nanoprobe is fixed. The surface density of the donor fluorescent nanoprobe is configured such that the donor-acceptor pairing follows a Poisson distribution with a Poisson parameter not exceeding 0.3.

[0083] like Figure 5As shown, the microfluidic chip also includes a sample introduction channel, a reaction chamber, and a waste liquid channel. The sample introduction channel is used to introduce a mixture of the test sample and the label-bound polymer of the acceptor fluorescent nanoprobe. The reaction chamber is located in the detection area. The waste liquid channel is used to discharge unbound free probes. The chip substrate is made of glass and has undergone silanization treatment. The optical window is made of quartz glass. The microfluidic chip is also equipped with a temperature control module, which includes a heating film and a temperature sensor located below the chip, as well as a proportional-integral-differential temperature control circuit, used to control the temperature of the detection area within the range of 37±0.5℃ to eliminate the influence of temperature changes on the intrinsic bleaching rate constant of the donor and the total bleaching rate constant of the acceptor. As an optional component, the system may also include a sample introduction module for introducing the mixture into the detection area and completing the incubation.

[0084] The optical excitation module generates continuous excitation light with a uniform power density distribution within the detection area. This module includes an excitation source (a 470 nm wavelength light-emitting diode) and a beam homogenizer (a microlens array homogenizer that converts the Gaussian beam into a flat-top distribution, ensuring that the excitation power density deviation within the detection area does not exceed ±3%). The module also includes a constant current drive circuit and a photoelectric feedback control circuit to ensure the power stability of the excitation light. A reference photodiode is also included for real-time monitoring of excitation power fluctuations.

[0085] The fluorescence detection module is used to acquire the time series of fluorescence signals from the donor channel. As a preferred configuration, the fluorescence detection module is also used to simultaneously acquire the time series of fluorescence signals from the acceptor channel for dual-channel cross-validation. This fluorescence detection module includes a donor channel detector and an acceptor channel detector. The donor channel detector is a photomultiplier tube with a 580 nm bandpass filter at its front end, and the acceptor channel detector is an indium gallium arsenide detector with an 800 nm bandpass filter at its front end.

[0086] To prevent fluorescence crosstalk from the donor channel to the acceptor channel, a 580 / 40 nm bandpass filter (40 nm FW-50) is used in the donor channel, and an 800 / 50 nm bandpass filter (50 nm FW-50) is used in the acceptor channel. The spectral isolation between the two channels is greater than [missing value]. After installing the filter, the crosstalk rate is assessed by measuring the residual signal of the pure donor sample in the acceptor channel, ensuring that the crosstalk rate is less than 1%. The fluorescence detection module also includes an auxiliary imaging module, which is a charge-coupled device or complementary metal-oxide-semiconductor camera, configured to acquire an initial fluorescence image before excitation begins for spatial normalization correction.

[0087] As an optional enhancement scheme, the fluorescence detection module can also adopt a time-gated detection mode: the excitation source uses pulse excitation with a pulse width of 100 nanoseconds and a repetition frequency of 1 MHz, and the detector uses gated detection with a gate delay of 5 nanoseconds and a gate width of 50 nanoseconds to eliminate short-lived background fluorescence, thereby improving the signal-to-noise ratio by 3 to 5 times.

[0088] The data processing module is used to fit the time series of donor channel fluorescence signals into a double exponential decay model using a two-step fitting method, extract the amplitude ratio and rate constant, perform kinetic parameter verification and dual-channel cross-validation, and determine the concentration through the preset calibration relationship between the amplitude ratio and the concentration of the target analyte.

[0089] Specifically, the data processing module is configured to perform a double-exponential decay fitting on the time series of the donor channel fluorescence signal to obtain a first decay component and a second decay component. The first decay component corresponds to a first rate constant and a first amplitude, while the second decay component corresponds to a second rate constant and a second amplitude. The first rate constant is greater than the second rate constant, and the first amplitude is negative. The ratio of the absolute value of the first amplitude to the second amplitude is calculated. Based on this ratio, the surface coverage of the detection area is determined using a preset ratio-surface coverage calibration curve. The concentration of the target analyte in the sample is determined based on a preset negative correlation calibration relationship between surface coverage and target analyte concentration. Furthermore, the data processing module is also configured to perform global fitting on multiple repeated measurements of the same sample, where the first and second rate constants are globally shared parameters, and the first and second amplitudes are local parameters for each measurement. Bayesian regularization constraints are applied to the fitting process using the prior distributions of the first and second rate constants determined by calibration experiments.

[0090] The aforementioned optical excitation module is positioned opposite the optical window of the microfluidic chip, and the fluorescence detection module is positioned on the detection optical path of the microfluidic chip's optical window. The data processing module is communicatively connected to the fluorescence detection module, receiving electrical signals output from the donor channel detector and the acceptor channel detector. In terms of timing, the fluorescence detection module acquires an initial fluorescence image before the optical excitation module is activated. Subsequently, the optical excitation module activates continuous excitation light, and the fluorescence detection module simultaneously acquires time-series signals from the donor and acceptor channels. The data processing module performs data processing after acquisition is complete.

[0091] 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, and various changes and modifications can be made without departing from the spirit and scope of the invention, all of which fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A microfluidic method for detecting neutralizing antibodies based on quantum dot fluorescent probes, characterized in that, Includes the following steps: Obtain the time series of donor channel fluorescence signals in the detection area of ​​a microfluidic chip under continuous excitation light irradiation; The time series of the donor channel fluorescence signal is fitted with a double exponential decay to obtain a first decay component and a second decay component, wherein the first decay component corresponds to a first rate constant and a first amplitude, and the second decay component corresponds to a second rate constant and a second amplitude; the first rate constant is greater than the second rate constant, and the first amplitude is negative. Calculate the ratio of the absolute value of the first amplitude to the second amplitude; Based on the ratio, the surface coverage of the detection area is determined by a preset ratio-surface coverage calibration curve; based on the preset negative correlation calibration relationship between the surface coverage and the target analyte concentration, the concentration of the target analyte in the sample to be tested is determined.

2. The method according to claim 1, characterized in that, Before acquiring the time series of the donor channel fluorescence signal, a spatial normalization step is also included: Before the continuous excitation light is turned on, the initial fluorescence intensity spatial distribution map of the detection area is acquired; During the acquisition of the time series of fluorescence signals in the donor channel, the real-time fluorescence signal at each spatial location in the detection area is divided by the initial intensity value corresponding to that spatial location in the initial fluorescence intensity spatial distribution map to obtain the normalized fluorescence signal. Spatially average the normalized fluorescence signal to obtain the donor channel fluorescence signal time series for subsequent double exponential decay fitting.

3. The method according to claim 1, characterized in that, The continuous excitation light is a flat-top distributed beam shaped by a beam homogenizer, and the excitation power density deviation in the detection area does not exceed ±5%.

4. The method according to claim 1, characterized in that, The double exponential decay fitting employs a two-step decoupling fitting strategy, specifically including: The second rate constant and the second amplitude are determined by performing a single exponential fit on the tail time segment data of the donor channel fluorescence signal time series; The attenuation tail baseline is calculated based on the second rate constant and the second amplitude, and the attenuation tail baseline is subtracted from the donor channel fluorescence signal time series to obtain the residual signal; The residual signal is subjected to single-exponential fitting to determine the first rate constant and the first amplitude.

5. The method according to claim 1, characterized in that, The first amplitude being negative is determined by the following physical condition: the total bleaching rate of the acceptor fluorescent nanoprobe is greater than the product of the intrinsic bleaching rate of the donor fluorescent nanoprobe and the efficiency of a single FRET pair, so that the donor paired with the acceptor disappears at a faster rate than the unpaired donor.

6. The method according to claim 1, characterized in that, The detection area contains a solid-phase recognition element labeled with a donor fluorescent nanoprobe, and the sample to be tested also contains a label conjugate labeled with a receptor fluorescent nanoprobe. The target analyte is a neutralizing antibody, which competes with the label conjugate for binding to the solid-phase recognition element. The surface coverage characterizes the amount of the label conjugate labeled with the receptor fluorescent nanoprobe bound to the detection area. The surface density of the donor fluorescent nanoprobe is configured such that the donor-receptor pairing follows a Poisson distribution with a Poisson parameter not exceeding 0.

3.

7. The method according to claim 6, characterized in that, The donor fluorescent nanoprobe is fixed to the solid-phase recognition element by a rigid connecting arm, and the acceptor fluorescent nanoprobe is marked on the marker conjugate by a flexible connecting arm; the sum of the lengths of the rigid connecting arm and the flexible connecting arm makes the ratio of the distance between the donor fluorescent nanoprobe and the acceptor fluorescent nanoprobe to the preset Förster radius between 0.8 and 1.

2.

8. The method according to claim 1, characterized in that, Following the double exponential decay fitting, a model validity verification step is also included: A single exponential decay model and a double exponential decay model were constructed to fit the time series of fluorescence signals in the donor channel, respectively. The goodness of fit between the double exponential decay model and the single exponential decay model is compared by the F-test. When the statistic of the F-test is greater than a preset critical value, the double exponential decay model is confirmed to be effective.

9. The method according to claim 1, characterized in that, It also includes the synchronous acquisition of receptor channel fluorescence signal time series, wherein the receptor channel fluorescence signal time series includes a first receptor attenuation component and a second receptor attenuation component, the first receptor attenuation component corresponds to the total receptor bleaching rate constant, and the second receptor attenuation component corresponds to the first rate constant. It also includes dynamic parameter verification steps and dual-channel cross-verification steps; The kinetic parameter verification step includes: calculating the ratio of the first rate constant to the second rate constant, and determining whether the ratio falls within a preset effective range. The lower limit of the effective range is 5, and the upper limit is the upper limit of the intrinsic parameters of the detection system. The upper limit of the intrinsic parameters is jointly determined by the intrinsic bleaching rate of the donor fluorescent nanoprobe, the total bleaching rate of the acceptor fluorescent nanoprobe, and the single-pair FRET efficiency, and does not change with the concentration of the target analyte. If the ratio is not within the preset effective range, the detection is determined to be abnormal. The dual-channel cross-validation step includes: extracting the rate constant corresponding to the second receptor decay component from the receptor channel fluorescence signal time series, comparing the consistency between the first rate constant extracted from the donor channel fluorescence signal time series and the rate constant corresponding to the second receptor decay component extracted from the receptor channel fluorescence signal time series, and determining an abnormality if the difference exceeds a preset threshold.

10. A microfluidic neutralizing antibody detection system based on quantum dot fluorescent probes, characterized in that, include: A microfluidic chip has a detection area in which a solid-phase recognition element labeled with a donor fluorescent nanoprobe is fixed. The surface density of the donor fluorescent nanoprobe is configured such that the donor-acceptor pairing follows a Poisson distribution and the Poisson parameter does not exceed 0.

3. An optical excitation module is used to generate continuous excitation light with a uniform power density distribution in the detection area; The fluorescence detection module is used to simultaneously acquire the time series of fluorescence signals from the donor channel and the acceptor channel; The data processing module is used to execute the method according to any one of claims 1 to 9, process the time series of the donor channel fluorescence signal and output the concentration of the target analyte.

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