An event-guided high-targeting fluorescence correlation spectroscopy method and device thereof

Abstract

This invention provides an event-guided, highly targeted fluorescence correlation spectroscopy method and apparatus. It includes the following steps: S1, an excitation light source in a wide-field module illuminates the sample to collect signals, achieving rapid wide-field imaging; S2, the obtained wide-field image is processed in real-time by a dynamic event discrimination module specifically designed for event types. This module returns a set of coordinates for any detected event. If an event is detected, wide-field imaging is stopped, and FCS acquisition begins around the detection coordinates with predetermined acquisition parameters. Compared with traditional FCS technology, the event-guided, highly targeted fluorescence correlation spectroscopy method and apparatus provided by this invention can quickly and highly target the region of interest where the event occurs and perform FCS data acquisition, greatly improving the targeting and efficiency of FCS experimental acquisition.

Description

Technical Field

[0001] This invention relates to the field of optical microscopy, and more particularly to an event-guided, highly targeted fluorescence correlation spectroscopy method and apparatus thereof. Background Technology

[0002] Molecular dynamics in biological systems is fundamental to life events. Fluorescence correlation spectroscopy (FCS) is a powerful tool for detecting molecular dynamics by analyzing the intensity fluctuations emitted by biomolecules as they diffuse within a focused observation volume. FCS can accurately measure local concentrations, hydrodynamic radii, diffusion coefficients, and interactions between different biomolecules. Compared to other dynamics-oriented methods, FCS has a wider range of measurable events, from ns to s, and higher sensitivity, reaching the single-molecule level. Confocal microscopy provides a very limited observation volume (approximately 0.5 fl), which significantly improves the signal-to-noise ratio of FCS.

[0003] When studying various dynamic processes in living biological systems, fractional coherence scintillation (FCS) is inevitably affected by many factors, such as cell movement, photobleaching of fluorophores, and anomalous dynamics in the sub-diffraction region. To overcome these difficulties, much work has been done over the past two decades to expand the capabilities of FCS. For example, two-color FCS has been proposed for measuring the interactions of different molecules, and spatial multiplexing techniques allow FCS to probe dynamic processes at different locations. For static FCS, the observation volume is fixed at a specific location in the sample, making it unsuitable for studying the slower diffusion dynamics in biological membranes. In such cases, the frequency of fluorophore appearance in the focal spot is low, posing sampling problems. Obtaining sufficient data often requires long acquisition times, and the long dwell time of the focal volume increases the possibility of photodegradation. Scanning FCS, by rapidly scanning the sample, calculates and... The autocorrelation of combined intensity trajectories associated with one or more locations is used, and then a fitting model is applied to obtain kinetic information. Parallel scanning FCS scans focused light along one, two, or a circle on the membrane plane, acquiring and assembling photons with time and pixel information. Then, the intensity of each pixel is extracted from the scanned line or circle and binned into an image intensity trajectory. The autocorrelation of the image intensity trajectory can provide information such as the concentration and diffusion coefficient of the target biomolecule. At the same time, the intensity of two pixels at a known distance between two scan lines or scan circles can also be autocorrelated and cross-correlated. Global fitting of the obtained autocorrelation and cross-correlation relationships can obtain information such as the size, concentration, and diffusion coefficient of the measured biomolecule. Repeated sampling of a portion of the sample by scanning FCS can ensure reduced photobleaching of fluorophores and improve statistical accuracy, which helps to examine the dynamic behavior and concentration in live cell applications.

[0004] Whether using single-point FCS or scanning FCS to detect events, it is necessary to manually select the region of interest (ROI) before data acquisition. The selection of the ROI greatly affects the experimental results. A poor ROI can lead to less data acquisition or even failure to detect the event signal. The problem of ROI selection is more pronounced in live cells against a large background. ROI selection often relies on the experimenter's experience, which makes the experiment inefficient.

[0005] Therefore, it is necessary to provide an event-guided, highly targeted fluorescence correlation spectroscopy method and apparatus to solve the above-mentioned technical problems. Summary of the Invention

[0006] This invention provides an event-guided, highly targeted fluorescence correlation spectroscopy method and apparatus, which solves the problems mentioned above.

[0007] To address the aforementioned technical problems, this invention provides an event-guided, highly targeted fluorescence correlation spectroscopy method, comprising the following steps:

[0008] S1. In the wide-field module, the light source generates excitation light to illuminate the sample and collect signals, thus achieving fast wide-field imaging.

[0009] S2. The obtained wide-field image is processed in real time by a dynamic event discrimination module specifically designed for event types. This module returns a set of coordinates for any detected event. If an event is detected, wide-field imaging is stopped and FCS acquisition begins around the detection coordinates with predetermined acquisition parameters.

[0010] S3 and FCS modules perform FCS data acquisition;

[0011] S4. When FCS data is obtained, comprehensive data about the event can be saved, including the wide field-of-view time interval that caused the detected event, the scan data, and the log file summarizing the parameters and timing of event detection and scanning. In the post-collection analysis, the saved auxiliary data is used to confirm the validity of the event and to assist in the FCS analysis of each event.

[0012] S5. Then the microscope returns to the previous settings, and another continuous wide field of view recording begins immediately. This method can run indefinitely, and the focus-locking module keeps the sample stable throughout the experiment, preventing axial drift.

[0013] Furthermore, in step S1, the laser in the wide-field module outputs the first laser beam, which is focused onto the fluorescent material by a high numerical aperture objective lens. The fluorescent material emits fluorescence through spontaneous electron emission transition. The signal emitted by the fluorescent material is collected by the high numerical aperture objective lens, filtered by a filtering system, and detected by a CCD to obtain a wide-field image.

[0014] Furthermore, in step S2, real-time event analysis, coordinate transformation, and real-time visual feedback are performed in the control components implemented in the microscope control software;

[0015] A third-order polynomial coordinate transformation is used between the wide-field space and the scan space to achieve accurate coordinate transformation throughout the entire field of view.

[0016] The transformation is calibrated by detecting the coefficient fit of the fluorescent beads in two imaging modes and polynomial transformation by transforming the wide field-of-view coordinates of all detected beads to the scan space and comparing them with the wide field-of-view coordinates of the detected beads in the scan image.

[0017] The transition between wide field and FCS occurs within a time window of tens of milliseconds after the event occurs, and the event is recorded in real time;

[0018] Event-triggered pattern switching works through eight main steps:

[0019] 1. Initialize the event triggering method; 2. Record the fast imaging image; 3. Run the dynamic event discrimination module; 4. If coordinates are detected: continue; if coordinates are not detected: repeat from step 2; 5. Convert the detected coordinates into the scan space; 6. Prepare for scanning and calculate the scan curve; 7. Run the scan; 8. Save the data and log file;

[0020] Finally, you can choose to repeat steps 2-8 in an infinite loop to achieve fully automatic acquisition of many events;

[0021] The final data saved in step 8 includes not only FCS recorded data, but also the fast imaging frame stack that caused the event, and a log file containing, for example, the coordinates of the triggered event, the transformation coordinates, the parameters of the event discrimination module, and the timestamps during different steps in the process.

[0022] Further, in step S3, the laser outputs a second laser beam as the excitation light for the FCS module. After passing through the filtering module, it is focused onto the fluorescent material by a high numerical aperture objective lens. Fluorescence is emitted through spontaneous electron emission transitions. The signal emitted by the fluorescent material is collected by the objective lens, filtered by a filter, and detected by an avalanche photodiode through a pinhole to obtain the fluorescence intensity signal at the focal point and record the fluorescence time trajectory.

[0023] Furthermore, the confirmation of the validity of the event in step S4 requires the FCS signal, the N wide-field frames that caused the event, and the log file describing the event.

[0024] These frames are used for post-acquisition analysis to determine whether the triggering event is actually a real target event or caused by other factors;

[0025] To classify events, we can study the N wide-field frames preceding the event. By using the trigger coordinates saved in the log file, we can extract the signal trajectory around the trigger coordinates. Real events typically show a significant increase in the last frame, while false events caused by something moving quickly into the detection pixel in the frame will show a relatively flat response.

[0026] Furthermore, event detection requires detecting signal intensity peaks in a wide field-of-view image. The detection of peaks can be divided into two parts: preprocessing using masks of the current frame, the previous frame, and the region of interest; and peak detection algorithm.

[0027] Before initiating the method and running the module, a binary mask is generated to represent the region to be considered in the field of view, typically a cell, which is created by intensity thresholding and Gaussian smoothing of the average image intensity of several consecutive frames.

[0028] This mask is input into the detection channel to limit any irrelevant background noise, including large-scale changes from frame to frame, to avoid affecting the results;

[0029] In the event discrimination module, the initial preprocessing converts the wide-field image into a pixel percentage intensity change map compared to the previous image. It first subtracts the previous frame from the current frame and divides it by the previous frame to generate a proportional image of pixel-level intensity percentage change.

[0030] Then the image is multiplied by a pre-calculated mask to obtain only the changes within the region of interest and discard the background.

[0031] The image is Gaussian smoothed to reduce the impact of noise-based fluorescence intensity fluctuations. The pre-processed image is then used as input in the subsequent peak detection and compared with its own maximum filtered version. Local maxima are then found where the two images are equal.

[0032] The peak value is put into a Boolean mask, and then the mask is multiplied by two threshold versions of the preprocessed image: one with a high threshold and one with a low threshold.

[0033] Extract the coordinates of the remaining peaks in the Boolean peak mask, remove peaks near the edge of the field of view, extract the intensity of the small region around each peak, and then use the input parameters to limit the number of peaks used in the rest of the channel;

[0034] Peak location and intensity are stored and form an additional information parameter. The channel connects the trajectory from the peak location, and these trajectories are analyzed to determine when a trajectory first appears and how the intensity of the peak develops over time.

[0035] When the intensity of an event increases proportionally above a certain threshold within 10 frames, the event is considered to have occurred, and the tracking coordinates of the last frame are considered to be the event coordinates.

[0036] An event-guided, highly targeted fluorescence correlation spectroscopy device includes a wide-field module, an FCS module, a focus-locking module, and a control window;

[0037] The emitting part of the wide field module includes, in sequence along the light propagation direction, a wide field imaging light source, a Gaussian beam expanding collimating lens group, and a first dichroic mirror. The detection part of the wide field module includes, in sequence along the light propagation direction, a first dichroic mirror, a first lens, a first adjustable reflector, a second lens, a first bandwidth filter, a first notch filter, and a wide field CCD camera.

[0038] The excitation module includes, in sequence along the light propagation direction, a first excitation light source, an acousto-optic tunable harmonic filter, a Gaussian beam expanding collimating lens group, a second adjustable reflector, a second dichroic mirror, and a third adjustable reflector.

[0039] The scanning module includes a third lens, a Y-axis scanning galvanometer, a spherical mirror, an X-axis scanning galvanometer, a scanning lens, and a third dichroic mirror along the direction of light propagation.

[0040] The detection module, along the direction of light propagation, includes, in sequence, a fourth lens, a pinhole, a fifth lens, a sixth lens, a second bandwidth filter, a second notch filter, and an avalanche photodiode;

[0041] The focus locking module includes, in sequence along the light propagation direction, a second laser source, a fourth adjustable mirror, a beam expander, a fifth adjustable mirror, a seventh lens, a sixth adjustable mirror, a seventh adjustable mirror, a third notch filter, and a focus locking CCD camera;

[0042] The sample detection module includes, in sequence along the direction of light propagation, a fourth dichroic mirror, an eighth lens, an eighth adjustable mirror, a high numerical aperture objective lens, a stage, and a piezoelectric moving platform.

[0043] Compared with related technologies, the event-guided highly targeted fluorescence correlation spectroscopy method and apparatus provided by this invention have the following advantages:

[0044] This invention provides an event-guided, highly targeted fluorescence correlation spectroscopy method and apparatus. Compared with traditional FCS technology, this invention can quickly and highly target the region of interest where the event occurs and perform FCS data acquisition, which greatly improves the efficiency of FCS for event detection experiments on membranes. Attached Figure Description

[0045] Figure 1 This is a flowchart of an event-guided, highly targeted fluorescence correlation spectroscopy method;

[0046] Figure 2 This is a schematic diagram of an event-guided, highly targeted fluorescence correlation spectroscopy method.

[0047] Figure 3 This is a structural diagram of the device of the present invention;

[0048] Figure 4 This is a schematic diagram of the signal for a slow event on the membrane.

[0049] The diagram is labeled as follows: 1. Wide-field imaging light source; 2. Gaussian beam expanding and collimating lens group; 3. First dichroic mirror; 4. First lens; 5. First adjustable mirror; 6. Second lens; 7. First bandwidth filter; 8. First notch filter; 9. Wide-field CCD camera; 10. First excitation light source; 11. Acousto-optic tunable harmonic filter; 12. Gaussian beam expanding and collimating lens group; 13. Second adjustable mirror; 14. Second dichroic mirror; 15. Third adjustable mirror; 16. Third lens; 17. Y-axis scanning galvanometer; 18. Spherical mirror; 19. X-axis scanning galvanometer; 20. Scanning lens; 21. 22. Third dichroic mirror, 23. Fourth lens, 24. Pinhole, 25. Fifth lens, 26. Sixth lens, 27. Second bandwidth filter, 28. Second notch filter, 29. Avalanche photodiode, 30. Second laser source, 31. Fourth adjustable mirror, 32. Beam expander, 33. Fifth adjustable mirror, 34. Seventh lens, 35. Sixth adjustable mirror, 36. Seventh adjustable mirror, 37. Third notch filter, 38. Focus-locked CCD camera, 39. Fourth dichroic mirror, 40. Eighth lens, 41. Eighth adjustable mirror, 42. High numerical aperture objective lens, 43. Piezoelectric moving platform. Detailed Implementation

[0050] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0051] Please refer to the following: Figure 1-4 As shown, an event-guided highly targeted fluorescence correlation spectroscopy device includes a wide-field module, an FCS module, a focus-locking module, and a control window;

[0052] The emitting part of the wide-field module includes, in sequence along the light propagation direction, a wide-field imaging light source 1, a Gaussian beam expanding collimating lens group 2, and a first dichroic mirror 3. The detection part of the wide-field module includes, in sequence along the light propagation direction, a first dichroic mirror 3, a first lens 4, a first adjustable reflector 5, a second lens 6, a first bandwidth filter 7, a first notch filter 8, and a wide-field CCD camera 9. The fluorescence signal excited by the wide-field laser source is collected and returned by the objective lens, passes through the dichroic mirror 3, is reflected by the first adjustable reflector 5 and then through the lens 6. After that, it is filtered and screened by the first bandwidth filter 7 and the first notch filter 8, and finally collected by the wide-field CCD camera 9 to obtain a wide-field image.

[0053] The excitation module, along the light propagation direction, sequentially includes a first excitation light source 10, an acousto-optic tunable harmonic filter 11, a Gaussian beam-expanding collimating lens group 12, a second adjustable reflector 13, a second dichroic mirror 14, and a third adjustable reflector 15. The light beam emitted by the first excitation light source 10 is a Gaussian beam. After passing through the acousto-optic tunable harmonic filter 11 and the beam expander 12, it is reflected by the second reflector 13, then by the second dichroic mirror 14, and finally by the third adjustable reflector 15 before entering the scanning module.

[0054] The scanning module includes a third lens 16, a Y-axis scanning galvanometer 17, a spherical mirror 18, an X-axis scanning galvanometer 19, a scanning lens 20, and a third dichroic mirror 21 along the direction of light propagation.

[0055] The detection module includes, in sequence along the direction of light propagation, a fourth lens 22, a pinhole 23, a fifth lens 24, a sixth lens 25, a second bandwidth filter 26, a second notch filter 27, and an avalanche photodiode 28; the fluorescence signal is collected by the avalanche photodiode 28 to obtain the fluorescence intensity and time information of the pixel, which is used for subsequent FCS analysis.

[0056] The focus locking module includes, in sequence along the direction of light propagation, a second laser source 29, a fourth adjustable mirror 30, a beam expander 31, a fifth adjustable mirror 32, a seventh lens 33, a sixth adjustable mirror 34, a seventh adjustable mirror 35, a third notch filter 36, and a focus locking CCD camera 37.

[0057] The sample detection module includes, in sequence along the direction of light propagation, a fourth dichroic mirror 38, an eighth lens 39, an eighth adjustable mirror 40, a high numerical aperture objective lens 41, a stage, and a piezoelectric moving platform 42.

[0058] An event-guided, highly targeted fluorescence correlation spectroscopy method includes the following steps:

[0059] S1. In the wide-field module, the laser outputs the first continuous laser beam, which is focused onto the fluorescent material through a high numerical aperture objective lens, emitting fluorescence through spontaneous electron emission transitions. The signal emitted by the fluorescent material is collected by the objective lens, filtered by a filtering system, and detected by a CCD to obtain a wide-field image;

[0060] S2. The obtained wide-field image is processed in real time by a dynamic event discrimination module specifically designed for event types. This module returns a set of coordinates for any detected event. If an event is detected, wide-field imaging is stopped and FCS acquisition begins around the detection coordinates with predetermined acquisition parameters.

[0061] S3. The laser outputs a second continuous laser beam as the excitation light for the FCS module. After passing through the filter module, it is focused onto the fluorescent material by the high numerical aperture objective lens. The fluorescent material emits fluorescence through spontaneous electron emission transition. The signal emitted by the fluorescent material is collected by the objective lens, filtered by the filter, and detected by the avalanche photodiode 28 through the pinhole to obtain the fluorescence intensity signal at the focal point and record the fluorescence time trajectory.

[0062] S4. When FCS data is obtained, comprehensive data about the event can be saved, including the wide field-of-view time interval that caused the detected event, the scan data, and the log file summarizing the parameters and timing of event detection and scanning. In the post-collection analysis, the saved auxiliary data is used to confirm the validity of the event and to assist in the FCS analysis of each event.

[0063] S5. Then the microscope returns to the previous settings, and another continuous wide field of view recording begins immediately. This method can run indefinitely, and the focus-locking module keeps the sample stable throughout the experiment, preventing axial drift.

[0064] In step S1 of this invention, the laser in the wide-field module outputs the first laser beam, which is focused onto the fluorescent material by the high numerical aperture objective lens 41. The fluorescent material emits fluorescence through spontaneous electron emission transition. The signal emitted by the fluorescent material is collected by the high numerical aperture objective lens 41, filtered by the filtering system, and detected by the CCD to obtain a wide-field image.

[0065] In step S2 of this invention, real-time event analysis, coordinate transformation, and real-time visual feedback are performed in the control component implemented in the microscope control software.

[0066] A third-order polynomial coordinate transformation is used between the wide-field space and the scan space to achieve accurate coordinate transformation throughout the entire field of view.

[0067] The transformation is calibrated by detecting the coefficient fit of the fluorescent beads in two imaging modes and polynomial transformation by transforming the wide field-of-view coordinates of all detected beads to the scan space and comparing them with the wide field-of-view coordinates of the detected beads in the scan image.

[0068] The transition between wide field and FCS occurs within a time window of tens of milliseconds after the event occurs, and the event is recorded in real time;

[0069] Event-triggered pattern switching works through eight main steps:

[0070] 1. Initialize the event triggering method; 2. Record the fast imaging image; 3. Run the dynamic event discrimination module; 4. If coordinates are detected: continue; if coordinates are not detected: repeat from step 2; 5. Convert the detected coordinates into the scan space; 6. Prepare for scanning and calculate the scan curve; 7. Run the scan; 8. Save the data and log file;

[0071] Finally, you can choose to repeat steps 2-8 in an infinite loop to achieve fully automatic acquisition of many events;

[0072] The final data saved in step 8 includes not only FCS recorded data, but also the fast imaging frame stack that caused the event, and a log file containing, for example, the coordinates of the triggered event, the transformation coordinates, the parameters of the event discrimination module, and the timestamps during different steps in the process.

[0073] In step S3 of this invention, the laser outputs a second laser beam as the excitation light for the FCS module. After passing through the filtering module, it is focused onto the fluorescent material by a high numerical aperture objective lens. Fluorescence is emitted through spontaneous electron emission transitions. The signal emitted by the fluorescent material is collected by the objective lens, filtered by a filter, and detected by an avalanche photodiode 28 through a pinhole to obtain the fluorescence intensity signal at the focal point and record the fluorescence time trajectory.

[0074] In step S4 of this invention, the confirmation of the validity of the event needs to be based on the FCS signal, the N wide-field frames that caused the event, and a log file describing the coordinates, timing, etc. of the triggering event.

[0075] These frames are used for post-acquisition analysis to determine whether the triggering event is actually a real target event or caused by other factors;

[0076] To classify events, we can study the N wide-field frames preceding the event. By using the trigger coordinates saved in the log file, we can extract the signal trajectory around the trigger coordinates. Real events typically show a significant increase in the last frame, while false events caused by something moving quickly into the detection pixel in the frame will show a relatively flat response.

[0077] Event detection requires detecting signal intensity peaks in a wide field-of-view image. The detection of peaks can be divided into two parts: preprocessing using masks of the current frame, the previous frame, and the region of interest; and peak detection algorithm.

[0078] Before initiating the method and running the module, a binary mask is generated to represent the area to be considered in the field of view, usually a cell, which is created by intensity thresholding and Gaussian smoothing of the average image intensity of several consecutive frames, such as 10 frames.

[0079] This mask is input into the detection channel to limit any irrelevant background noise, including large-scale changes from frame to frame, to avoid affecting the results;

[0080] In the event discrimination module, the initial preprocessing converts the wide-field image into a pixel percentage intensity change map compared to the previous image. It first subtracts the previous frame from the current frame and divides it by the previous frame to generate a proportional image of pixel-level intensity percentage change.

[0081] Then the image is multiplied by a pre-calculated mask to obtain only the changes within the region of interest and discard the background.

[0082] The image is Gaussian smoothed to reduce the impact of noise-based fluorescence intensity fluctuations. The pre-processed image is then used as input for peak detection, compared to its own maximum filtered version, and local maxima are found where the two images are equal.

[0083] The peak value is put into a Boolean mask, and then the mask is multiplied by two threshold versions of the preprocessed image: one with a high threshold and one with a low threshold.

[0084] Extract the coordinates of the remaining peaks in the Boolean peak mask, remove peaks near the edge of the field of view, extract the intensity of the small region around each peak, and then use the input parameters to limit the number of peaks used in the rest of the channel;

[0085] Peak location and intensity are stored and form an additional information parameter. The channel connects the trajectory from the peak location, and these trajectories are analyzed to determine when a trajectory first appears and how the intensity of the peak develops over time.

[0086] When the intensity of an event increases proportionally above a certain threshold within 10 frames, the event is considered to have occurred, and the tracking coordinates of the last frame are considered to be the event coordinates.

[0087] Example

[0088] NaYF4:Yb / Tm rare earth nanoparticles were excited using continuous near-infrared excitation light. In this example, a wavelength of 980 nm was selected. Under the excitation of a 980 nm near-infrared laser with a certain power, rapid imaging was performed in a wide-field module to obtain a wide-field image. After preprocessing, the wide-field image was input into the dynamic event discrimination module for real-time analysis. When an event occurs, the dynamic event discrimination module responds quickly, obtains the specific coordinates of the event in FCS mode, and quickly completes the mode conversion. FCS acquisition is performed at the event coordinates, and comprehensive data about the event is saved, including the wide field-of-view time interval that led to the detected event, the scan data, and a log file summarizing the parameters and timing of event detection and scanning.

[0089] After the first round of FCS acquisition is completed, the system quickly returns to its initial position and resumes wide-field imaging mode to continue detecting event signals. Upon detecting a new event signal, it switches back to FCS mode and moves to the vicinity of the event coordinates for the next round of FCS acquisition, thus repeating this cycle to achieve automatic data acquisition. The cycle can be manually terminated once sufficient data has been obtained.

[0090] An external computer analyzes the collected data using a time autocorrelation function to obtain multiple FCS curves, each representing information about events in different regions. By combining these FCS curves with the data saved during FCS acquisition, the validity of the events can be analyzed, eliminating false positive events with significant interference.

[0091] The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An event-guided, high-targeting fluorescence-related spectroscopy method, characterized in that, Includes the following steps: S1. In the wide-field module, the light source generates excitation light to illuminate the sample and collect signals, thus achieving fast wide-field imaging. S2. The obtained wide-field image is processed in real time by a dynamic event discrimination module specifically designed for event types. This module returns a set of coordinates for any detected event. If an event is detected, wide-field imaging is stopped and FCS acquisition begins around the detection coordinates with predetermined acquisition parameters. S3 and FCS modules perform FCS data acquisition; S4. When FCS data is obtained, comprehensive data about the event can be saved, including the wide field-of-view time interval that caused the detected event, the scan data, and the log file summarizing the parameters and timing of event detection and scanning. In the post-collection analysis, the saved auxiliary data is used to confirm the validity of the event and to assist in the FCS analysis of each event. S5. Then the microscope returns to the previous settings, and another continuous wide field of view recording begins immediately. This method can run indefinitely, and the focus locking module keeps the sample stable throughout the experiment, preventing axial drift. In step S2, real-time event analysis, coordinate transformation, and real-time visual feedback are performed in the control components implemented in the microscope control software. A third-order polynomial coordinate transformation is used between the wide-field space and the scan space to achieve accurate coordinate transformation throughout the entire field of view. The transformation is calibrated by detecting the coefficient fit of the fluorescent beads in two imaging modes and polynomial transformation by transforming the wide field-of-view coordinates of all detected beads to the scan space and comparing them with the wide field-of-view coordinates of the detected beads in the scan image. The transition between wide field and FCS occurs within a time window of tens of milliseconds after the event occurs, and the event is recorded in real time.

2. The event-guided high-targeting fluorescence related spectroscopy method according to claim 1, wherein, In step S1, the laser in the wide field module outputs the first laser beam, which is focused onto the fluorescent material by the high numerical aperture objective (41). The fluorescent material emits fluorescence through spontaneous electron emission transition. The signal emitted by the fluorescent material is collected by the high numerical aperture objective (41), filtered by the filtering system, and detected by the CCD to obtain a wide field image.

3. The event-guided, highly targeted fluorescence correlation spectroscopy method according to claim 2, characterized in that, Event-triggered pattern switching works through eight main steps:

1. Initialize the event triggering method; 2. Record the fast imaging image; 3. Run the dynamic event discrimination module; 4. If coordinates are detected: continue; if coordinates are not detected: repeat from step 2; 5. Convert the detected coordinates into the scan space; 6. Prepare for scanning and calculate the scan curve; 7. Run the scan; 8. Save data and log files; Finally, you can choose to repeat steps 2-8 in an infinite loop to achieve fully automatic acquisition of many events; The final data saved in step 8 includes not only FCS recorded data, but also the fast imaging frame stack that caused the event, as well as a log file containing the coordinates of the triggered event, the transformation coordinates, the parameters of the event discrimination module, and the timestamps during different steps in the process.

4. The event-guided high-targeting fluorescence related spectroscopy method according to claim 3, wherein, In step S3, the laser outputs a second laser beam as the excitation light for the FCS module. After passing through the filter module, it is focused onto the fluorescent material by the high numerical aperture objective lens. The fluorescent material emits fluorescence through spontaneous electron emission transition. The signal emitted by the fluorescent material is collected by the objective lens, filtered by the filter, and detected by the avalanche photodiode (28) through the pinhole to obtain the fluorescence intensity signal at the focal point and record the fluorescence time trajectory.

5. The event-guided high-targeting fluorescence related spectroscopy method according to claim 4, wherein, In step S4, the confirmation of the validity of the event needs to be based on the FCS signal, the N wide-field frames that caused the event, and the log file describing the event. These frames are used for post-acquisition analysis to determine whether the triggering event is actually a real target event or caused by other factors; To classify events, we can study the N wide-field frames preceding the event. By using the trigger coordinates saved in the log file, we can extract the signal trajectory around the trigger coordinates. Real events will show a significant increase in the last frame, while false events caused by something moving quickly in the frame to the detection pixel will show a relatively flat response.

6. According to the event-guided high-targeting fluorescence correlation spectroscopy method described in claim 5, event detection requires detecting signal intensity peaks in a wide field-of-view image. The detection of peaks can be divided into two parts: preprocessing using masks of the current frame, the previous frame, and the region of interest. And peak detection algorithms; Before initiating the method and running the module, a binary mask is generated to represent the area to be considered in the field of view, in cells, which is created by intensity thresholding and Gaussian smoothing of the average image intensity of several consecutive frames; This mask is input into the detection channel to limit any irrelevant background noise, including large-scale changes from frame to frame, to avoid affecting the results; In the event discrimination module, the initial preprocessing converts the wide-field image into a pixel percentage intensity change map compared to the previous image. It first subtracts the previous frame from the current frame and divides it by the previous frame to generate a proportional image of pixel-level intensity percentage change. Then the image is multiplied by a pre-calculated mask to obtain only the changes within the region of interest and discard the background; The image is Gaussian smoothed to reduce the impact of noise-based fluorescence intensity fluctuations. The pre-processed image is then used as input in the subsequent peak detection and compared with its own maximum filtered version. Local maxima are then found where the two images are equal. The peak value is put into a Boolean mask, and then the mask is multiplied by two threshold versions of the preprocessed image: one with a high threshold and one with a low threshold. Extract the coordinates of the remaining peaks in the Boolean peak mask, remove peaks near the edge of the field of view, extract the intensity of the small region around each peak, and then use the input parameters to limit the number of peaks used in the rest of the channel; Peak location and intensity are stored and form an additional information parameter. The channel connects the trajectory from the peak location, and these trajectories are analyzed to determine when a trajectory first appears and how the intensity of the peak develops over time. When the intensity of an event increases proportionally above a certain threshold within 10 frames, the event is considered to have occurred, and the tracking coordinates of the last frame are considered to be the event coordinates.

7. A high-targeting fluorescence related spectroscopy device based on event-guiding, using the method of claim 6, characterized in that, Includes a wide field module, an FCS module, a focus lock module, and a control window; The emitting part of the wide field module includes, in sequence along the direction of light propagation, a wide field imaging light source (1), a Gaussian beam expanding collimating lens group (2), and a first dichroic mirror (3). The detection part of the wide field module includes, in sequence along the direction of light propagation, a first dichroic mirror (3), a first lens (4), a first adjustable reflector (5), a second lens (6), a first bandwidth filter (7), a first notch filter (8), and a wide field CCD camera (9). The excitation module includes, in sequence along the direction of light propagation, a first excitation light source (10), an acousto-optic tunable harmonic filter (11), a Gaussian beam expanding collimating lens group (12), a second adjustable reflector (13), a second dichroic mirror (14), and a third adjustable reflector (15). The scanning module includes a third lens (16), a Y-axis scanning galvanometer (17), a spherical mirror (18), an X-axis scanning galvanometer (19), a scanning lens (20), and a third dichroic mirror (21) along the direction of light propagation. The detection module includes, in sequence along the direction of light propagation, a fourth lens (22), a pinhole (23), a fifth lens (24), a sixth lens (25), a second bandwidth filter (26), a second notch filter (27), and an avalanche photodiode (28). The focus locking module includes, in sequence along the light propagation direction, a second laser source (29), a fourth adjustable mirror (30), a beam expander (31), a fifth adjustable mirror (32), a seventh lens (33), a sixth adjustable mirror (34), a seventh adjustable mirror (35), a third notch filter (36), and a focus locking CCD camera (37). The sample detection module includes, in sequence along the direction of light propagation, a fourth dichroic mirror (38), an eighth lens (39), an eighth adjustable mirror (40), a high numerical aperture objective lens (41), a stage, and a piezoelectric moving platform (42).

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