Second harmonic imaging method for analyzing living hippocampus collagen structure of depression model mouse

Abstract

The invention discloses a secondary harmonic imaging method for analyzing a depression model mouse living body hippocampus collagen structure, and belongs to the technical field of neuropathology and tissue imaging, and the method comprises the following steps: (1) sample preparation: tissue acquisition and pretreatment, and sample fixation and mounting; (2) unmarked two-photon imaging and image acquisition, including imaging system configuration and image acquisition parameter setting; (3) image analysis: a second harmonic imaging technology is adopted to directly capture inherent signals of collagenous fibers through a nonlinear optical effect, and a three-dimensional reconstruction algorithm is combined, so that the following breakthroughs are realized: unmarked imaging: a coloring agent or an antibody is not needed, and signal interference is avoided; performing high-resolution three-dimensional analysis: obtaining the spatial orientation and density distribution of collagenous fibers through two-photon laser layer scanning and Z-axis stacking; the method is used for accurately analyzing the collagen structure in the brain sea horse tissue of the depression model mouse, and overcomes the defects in three-dimensional presentation and resolution in the prior art.

Description

Technical Field

[0001] The present invention belongs to the technical fields of neuropathology and tissue imaging, and particularly relates to a second harmonic imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse. Background Art

[0002] Depression is a complex mental disorder, and its pathological mechanism is closely related to the structural and functional changes in multiple regions of the brain. Research shows that abnormal changes in the collagen structure of the hippocampal region of depression model animals (such as disordered spatial distribution) may further affect the efficiency of nerve signal transmission and tissue repair ability by disrupting the function of the extracellular matrix. Therefore, developing a technology that can accurately analyze the three-dimensional structure of collagen is crucial for elucidating the pathological mechanism of depression.

[0003] Existing technologies for studying brain tissue collagen mainly include histological staining, immunofluorescence staining, and related microscopic imaging technologies. However, the core defects of existing technologies are: (1) unable to non-invasively obtain the three-dimensional spatial distribution information of collagen fibers (such as branching angle, density gradient); (2) overly dependent on staining agents or antibody labeling, resulting in poor detection stability and limited application range.

[0004] Aiming at the above technical defects, based on the second harmonic microscopy technology, the present invention proposes a label-free and high-resolution three-dimensional collagen imaging method, which can achieve accurate quantitative analysis of the fresh hippocampal collagen structure of a depression model mouse. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide, in view of the deficiencies of the background art, a high-resolution and label-free imaging technology for accurately analyzing the collagen structure in the hippocampal tissue of a depression model mouse, and overcoming the deficiencies of existing technologies in three-dimensional presentation and resolution.

[0006] The present invention adopts the following technical solutions to solve the above technical problems:

[0007] A second harmonic imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse, characterized by specifically comprising the following steps;

[0008] Step 1, sample preparation:

[0009] Step 1.1, tissue acquisition and pretreatment: The anesthetized mouse is quickly decapitated and sacrificed, the brain tissue is completely removed and placed in pre-cooled artificial cerebrospinal fluid aCSF, and the bilateral hippocampi are separated along the coronal section, and the complete morphology of the hippocampus is retained;

[0010] Step 1.2, sample fixation and mounting;

[0011] Step 2, Label-free Two-photon Imaging and Image Acquisition: including imaging system configuration and image acquisition parameter settings;

[0012] Step 3, Image Analysis, specifically including the following steps;

[0013] Step 3.1, Image preprocessing includes background correction and intensity normalization;

[0014] Step 3.2, Construct the Gray-Level Co-occurrence Matrix (GLCM): including the number of gray levels, distance d, and direction φ;

[0015] Step 3.3, Count the frequency of pixel pairs with gray values i and j in the image co-occurring at a specific distance d and direction φ, and generate the GLCM matrix P(i,j);

[0016] Normalize the GLCM matrix P(i,j) to a probability distribution p(i,j);

[0017] Specific calculation: p(i,j) = P(i,j) / ΣP(i,j);

[0018] Calculate the entropy Entropy:

[0019] Calculate the inverse difference moment IDM:

[0020] Take the average of the calculation results of the gray-level co-occurrence matrices GLCM in four directions to enhance the direction robustness;

[0021] Use MATLAB to implement the calculation of the first-order and second-order directional derivatives based on the Steger algorithm:

[0022] Calculate the gradient of the image I(x,y); where, (x,y) represents the two-dimensional spatial coordinates in the image; I represents the intensity Intensity of the image, that is, the gray value of the pixel; I(x,y) corresponds to the actual pixel matrix, representing the brightness value of the pixel at the position (x,y);

[0023] Formula:

[0024] Among them, Gx and Gy respectively represent the gradient components in the x direction and y direction, that is, Gx is the change rate of the image on the horizontal x-axis, and Gy is the change rate on the vertical y-axis;

[0025] Gradient magnitude

[0026] Gradient direction: θgrad = arctan(G y / G x );

[0027] Construct the Hessian matrix H:

[0028] Solve for the eigenvalues λ1 and λ2 of the Hessian matrix, assuming |λ1| ≥ |λ2|, which is used to detect linear structures, i.e., collagen; when |λ1| >> |λ2|, the current position is the center line of the collagen;

[0029] Collagen thickness: Along the cross-section perpendicular to the collagen direction, i.e., the gradient direction, measure the full width at half maximum (FWHM) of the gray-scale distribution;

[0030]

[0031] where is the standard deviation of Gaussian fitting;

[0032] Collagen overlap: The density of collagen cross-points per unit area or the proportion of the overlapping area. Detect collagen cross-points through local Hessian feature analysis or morphological operations;

[0033] where, collagen overlap = number of cross-points / area of the image region;

[0034] Collagen overlap = number of cross-points / area of the image region.

[0035] As a further preferred embodiment of the second harmonic imaging method for analyzing the collagen structure of the living hippocampus of a depressive model mouse in the present invention, in step 1.1, the formula of the artificial cerebrospinal fluid aCSF is: NaCl 100 - 126 mM, KCl 2 - 3 mM, CaCl2 1 - 2 mM, MgCl 0.5 - 1 mM, glucose 5 - 10 mM.

[0036] As a further preferred embodiment of the second harmonic imaging method for analyzing the collagen structure of the living hippocampus of a depressive model mouse in the present invention, in step 1.2, drop biocompatible cyanoacrylate glue in the central area of the glass slide, and gently place the unilateral hippocampus in the center of the glue droplet; evenly apply low-melting-point hot melt glue on both sides of the glass slide, and gently press the cover glass until the hot melt glue completely solidifies, ensuring that the distance between the hippocampus sample and the cover glass is constant, i.e., 100 ± 10 μm, to avoid tissue compression and deformation. Immerse the sealed sample in ACSF and take pictures as soon as possible to ensure the morphological stability of the collagen fibers.

[0037] As a further preferred embodiment of the second harmonic generation imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse in the present invention, in step 2, the imaging system configuration specifically includes: using a STELLARIS 8DIVE two-photon laser confocal microscope, configuring an adjustable infrared femtosecond pulsed laser with a wavelength range of 680 - 1300 nm; setting the laser wavelength to 916 nm according to the SHG excitation characteristics of mouse hippocampal collagen and the wavelength scanning results of preliminary experiments to maximize the signal intensity; focusing through a 25× multi-photon water immersion objective lens with NA 0.95. After the SHG signal is separated by a dichroic mirror, it is collected by a high-sensitivity detector in the 448 nm band.

[0038] As a further preferred embodiment of the second harmonic generation imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse in the present invention, in step 2, the image acquisition parameter settings specifically include: three-dimensional preview after single-layer preview to check fiber continuity, and slide along the Z-axis to confirm full-layer coverage; manually define the starting and ending points of the Z-axis to ensure full coverage of the hippocampal full-layer collagen thickness, where the range is 200 - 300 μm; optimize according to the objective lens numerical aperture and SHG light penetration depth, where the objective lens numerical aperture NA = 1.2, balance resolution and data volume, and select a step size of 1 μm; enable the automatic optimization of laser power, scanning speed, and signal gain mode, dynamically adjust the laser power, add depth compensation, and gradually increase the PMT gain by 2 - 5% / 10 μm as the Z-axis deepens, with an initial value of 5 - 10% of the titanium sapphire laser output to avoid optical damage, and automatically calibrate based on the signal intensity, with the highest gray value ≈ 80% of the dynamic range; the objective lens magnification is 25×, combined with 2× digital zoom, and two-way scanning, and images are acquired at a resolution of 1024×1024 pixels.

[0039] Compared with the prior art, the present invention adopts the above technical solutions and has the following technical effects:

[0040] 1. To overcome the problems of lack of three-dimensional information and antibody dependence in the prior art, the present invention adopts the second harmonic generation imaging technology (Second Harmonic Generation Imaging, SHG), directly captures the inherent signal of collagen fibers through non-linear optical effects, and combines three-dimensional reconstruction algorithms to achieve the following breakthroughs:

[0041] Label-free imaging: No staining agents or antibodies are required, avoiding signal interference;

[0042] High-resolution three-dimensional analysis: Through two-photon laser layer scanning and Z-axis stacking, the spatial orientation and density distribution of collagen fibers are obtained;

[0043] 2. The present invention provides a high-resolution, label-free imaging technique that can directly present the spatial distribution and morphology of collagen fibers, making up for the deficiencies of immunofluorescence staining and histological staining in terms of resolution and morphological recognition. At the same time, this technique does not rely on antibody labeling and is applicable to various pathological studies. In a preferred embodiment, three-dimensional observation of collagen fibers in the hippocampal tissue of mice with a depression model can be achieved by adjusting the parameters of second harmonic generation microscopy. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 shows the detection results of depressive-like behaviors of the present invention;

[0045] Figure 2 is the statistical result graph of the collagen thickness of the present invention

[0046] Figure 3 is the statistical result graph of the collagen overlap degree of the present invention;

[0047] Figure 4 is the experimental timeline of the present invention;

[0048] Figure 5 is the schematic diagram of sample preparation of the present invention;

[0049] Figure 6 is the image acquisition interface of the present invention;

[0050] Figure 7 is the collagen image collected by the present invention;

[0051] Figure 8 is the partial analysis result graph of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The technical solutions of the present invention will be further described in detail below with reference to the accompanying drawings:

[0053] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. The present invention will be described in detail below according to the accompanying drawings and preferred embodiments, and the purpose and effect of the present invention will become more apparent. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] As Figures 1 to 8 shown, the second harmonic generation imaging method for analyzing the collagen structure of the living hippocampus of mice with a depression model specifically includes the following steps;

[0055] Step 1. Sample preparation:

[0056] Step 1.1. Tissue acquisition and preprocessing:

[0057] After the establishment of the Chronic Social Defeat Stress (CSDS) depression model, the depressive-like behaviors of mice were evaluated (social interaction experiment and sucrose preference rate). The anesthetized mice were quickly decapitated, and the whole brain tissue was removed and placed in pre-cooled (4°C) artificial cerebrospinal fluid (aCSF, formula: 126 mM NaCl, 3 mM KCl, 2 mM CaCl2, 1 mM MgCl, 10 mM glucose). The bilateral hippocampi were separated along the coronal section, and the complete morphology of the hippocampus was preserved.

[0058] Step 1.2. Sample fixation and mounting:

[0059] Add 5 μL of biocompatible cyanoacrylate glue to the central area of the glass slide, and gently place the unilateral hippocampus in the center of the glue droplet. Subsequently, evenly apply low-melting-point hot melt glue (melting point: 50°C) on both sides of the edge of the glass slide, and gently press the coverslip until the hot melt glue is completely solidified, ensuring a constant distance (100 ± 10 μm) between the hippocampal sample and the coverslip to avoid tissue compression and deformation. Finally, immerse the mounted sample in ACSF and take pictures as soon as possible to ensure the morphological stability of the collagen fibers, Figure 1 as shown.

[0060] The experimental timeline is as Figure 4 shown, and the schematic diagram of sample preparation is as Figure 5 shown.

[0061] The image acquisition interface is as Figure 6 shown, and the acquired collagen images are as Figure 7 shown.

[0062] Step 2, label-free two-photon imaging and image acquisition:

[0063] Step 2.1, imaging system configuration:

[0064] Use a STELLARIS 8 DIVE two-photon laser confocal microscope, configured with an adjustable infrared femtosecond pulsed laser (wavelength range 680 - 1300 nm). According to the SHG excitation characteristics of mouse hippocampal collagen and the wavelength scanning results of the preliminary experiment (see Chart 7), the laser wavelength was set to 916 nm to maximize the signal intensity. Focus through a 25× multi-photon water immersion objective (NA 0.95), and after the SHG signal is separated by a dichroic mirror, it is collected by a high-sensitivity detector in the 448 nm band.

[0065] Step 2.2. Image acquisition parameter settings:

[0066] After single-layer preview to check fiber continuity (avoid oversaturation or undersampling), perform three-dimensional preview. Slide along the Z-axis to confirm full-layer coverage. Manually define the starting and ending points of the Z-axis to ensure coverage of the entire hippocampal collagen thickness (range: 200 - 300 μm). Optimize according to the objective lens numerical aperture (NA = 1.2) and the SHG light penetration depth, balance resolution and data volume, and select a step size of 1 μm. Enable the "System Optimized" mode (automatically optimize laser power, scanning speed, and signal gain), dynamically adjust the laser power, add depth compensation (gradually increase the PMT gain by 2 - 5% / 10 μm as the Z-axis deepens), with a starting value of 5 - 10% of the titanium sapphire laser output to avoid light damage, and automatically calibrate based on signal intensity, with the highest gray value ≈ 80% of the dynamic range. The objective lens magnification is 25×, combined with 2× digital zoom, and two-way scanning, and images are acquired at a resolution of 1024×1024 pixels.

[0067] Step 3. Image analysis:

[0068] Use Fiji (Background Subtraction plugin) for image preprocessing (background correction, intensity normalization)

[0069] Use a MATLAB custom toolbox (based on the graycomatrix function) to construct a gray-level co-occurrence matrix (GLCM):

[0070] Number of gray levels (usually reduced to 16 or 32 levels to reduce the computational load);

[0071] Distance (d, commonly 1 pixel) and direction (φ, taking four directions of 0°, 45°, 90°, 135°);

[0072] Statistically calculate the frequency of pixel pairs with gray values of i and j co-occurring at a specific distance d and direction φ, and generate the GLCM matrix P(i,j);

[0073] Normalize the GLCM matrix P(i,j) to a probability distribution p(i,j);

[0074] Specific calculation: p(i,j) = P(i,j) / ΣP(i,j);

[0075] Calculate entropy Entropy:

[0076] Calculate the inverse difference moment IDM:

[0077] Take the mean of the calculation results of the gray-level co-occurrence matrix GLCM in four directions to enhance the direction robustness;

[0078] Use MATLAB to implement the calculation of the first-order and second-order directional derivatives based on the Steger algorithm:

[0079] Calculate the gradient of the image I(x, y): (x, y) represents the two-dimensional spatial coordinates in the image; I represents the intensity of the image, that is, the grayscale value of the pixel.

[0080] I(x, y) corresponds to the actual pixel matrix and represents the brightness value of the pixel at the position (x, y). In a grayscale image, the pixel brightness value range is usually 0 to 255.

[0081] Formula:

[0082] Where Gx and Gy represent the gradient components in the x-direction and y-direction respectively. That is, Gx is the rate of change of the image in the horizontal direction (x-axis), and Gy is the rate of change in the vertical direction (y-axis).

[0083] Gradient magnitude

[0084] Gradient direction: θgrad = arctan(G y / G x );

[0085] Construct the Hessian matrix H:

[0086] Solve the eigenvalues λ1 and λ2 of the Hessian matrix, assuming |λ1| ≥ |λ2|, which is used to detect linear structures, i.e., collagen; when |λ1| >> |λ2|, the current position is the collagen center line;

[0087] As Figure 2 and Figure 3 shown, the collagen thickness: Measure the full width at half maximum (FWHM) of the grayscale distribution along the profile perpendicular to the collagen direction, i.e., the gradient direction;

[0088]

[0089] where is the standard deviation of Gaussian fitting;

[0090] Collagen overlap degree: The density of collagen intersection points per unit area or the proportion of the overlapping area. Detect collagen intersection points through local Hessian feature analysis or morphological operations;

[0091] Where the collagen overlap degree = the number of intersection points / the area of the image region;

[0092] The collagen overlap degree = the number of intersection points / the area of the image region.

[0093] As Figure 8 shown, Fourier spectrum analysis:

[0094] Convert the SHG image to grayscale using the Fiji tool and perform background correction

[0095] Perform a two-dimensional fast Fourier transform (FFT) on the image I(x,y) using MATLAB (fft2, angle, pol2cart functions) to obtain the spectrum F(u,v)

[0096] Center the spectrum (Shift DC component) and calculate the magnitude spectrum |F(u,v)|

[0097] Convert the spectrum to polar coordinates (r,θ) and calculate the energy integral at different angles θ:

[0098] Formula:

[0099] Find the peak angle of E(θ) as the collagen-dominated direction. Calculate the variance or entropy of the energy distribution to quantify the direction consistency.

[0100] 4. Statistical results:

[0101] Figure 1 Calculate the social interaction ratio (SIR) for the detection results of depressive-like behavior (left figure), SIR = cumulative time with strange targets in the social area / cumulative time without strange targets in the social area; (right figure) calculate the sucrose preference rate (SPT, Sucrose Preference Test), SPI = (sucrose intake / total intake) * 100%.

[0102] Those of ordinary skill in the art can understand that the above are only preferred examples of the invention and are not used to limit the invention. Although the invention has been described in detail with reference to the foregoing examples, for those skilled in the art, they can still modify the technical solutions described in the foregoing examples, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, etc. made within the spirit and principle of the invention shall be included within the protection scope of the invention. All technical features in this embodiment can be freely combined according to actual needs.

[0103] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A second harmonic imaging method for analyzing the collagen structure in the living hippocampus of a depression model mouse, characterized in that: Specifically, it includes the following steps; Step 1, sample preparation: Step 1.1, tissue acquisition and pretreatment: The anesthetized mice were quickly decapitated, and the brain tissues were completely removed and placed in pre-cooled artificial cerebrospinal fluid aCSF. The bilateral hippocampi were separated along the coronal section, and the intact morphology of the hippocampus was preserved; Step 1.2, sample fixation and mounting; Step 2, label-free two-photon imaging and image acquisition: It includes imaging system configuration and image acquisition parameter settings; Step 3, image analysis, specifically including the following steps; Step 3.1, image preprocessing includes background correction and intensity normalization; Step 3.2, constructing the gray-level co-occurrence matrix GLCM: It includes the number of gray levels, distance d, and direction φ; Step 3.3, statistically calculating the frequency of co-occurrence of pixel pairs with gray values i and j in the image at a specific distance d and direction φ, and generating the GLCM matrix P(i,j); Normalize the GLCM matrix P(i,j) to the probability distribution p(i,j); Specific calculation: p(i,j) = P(i,j) / ΣP(i,j); Calculate Entropy: Calculate the Inverse Difference Moment (IDM): Take the average of the calculation results of the gray-level co-occurrence matrices GLCM in four directions to enhance the direction robustness; Use MATLAB to implement the calculation of the first-order and second-order directional derivatives based on the Steger algorithm: Calculate the gradient of the image I(x,y); where, (x,y) represents the two-dimensional spatial coordinates in the image; I represents the intensity Intensity of the image, that is, the gray value of the pixel; I(x,y) corresponds to the actual pixel matrix and represents the brightness value of the pixel at the position (x,y); Among them, Gx and Gy respectively represent the gradient components in the x direction and y direction, that is, Gx is the change rate of the image on the horizontal x-axis, and Gy is the change rate on the vertical y-axis; Gradient magnitude Gradient direction: θgrad = arctan(G y / G x ); Construct the Hessian matrix H: Solve the eigenvalues λ1 and λ2 of the Hessian matrix, and assume |λ1|≥|λ2|, which is used to detect linear structures, that is, collagen; when |λ1| >> |λ2|, the current position is the center line of the collagen; Collagen thickness: Along the profile perpendicular to the collagen direction, that is, the gradient direction, measure the full width at half maximum FWHM of the gray-level distribution; Among them, is the standard deviation of Gaussian fitting; Collagen overlap degree: The density of collagen cross points or the proportion of the overlapping area per unit area. Detect collagen cross points through local Hessian feature analysis or morphological operations; Among them, collagen overlap degree = number of cross points / image area; Collagen overlap degree = number of cross points / image area.

2. The second harmonic imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse according to claim 1, characterized in that: In step 1.1, the formula of the artificial cerebrospinal fluid aCSF is: NaCl 100 - 126 mM, KCl 2 - 3 mM, CaCl2 1 - 2 mM, MgCl 0.5 - 1 mM, glucose 5 - 10 mM.

3. The second harmonic imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse according to claim 1, wherein: In step 1.2, drop biocompatible cyanoacrylate glue in the central area of the glass slide, and gently place the unilateral hippocampus in the center of the glue droplet; evenly apply low-melting-point hot melt glue on both sides of the glass slide, and gently press the coverslip until the hot melt glue completely solidifies, ensuring that the distance between the hippocampus sample and the coverslip is constant, that is, 100 ± 10 μm, to avoid tissue compression and deformation. Immerse the mounted sample in ACSF and take pictures as soon as possible to ensure the morphological stability of the collagen fibers.

4. The second harmonic imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse according to claim 1, wherein: In step 2, the imaging system is configured, specifically including: using a STELLARIS 8DIVE two-photon laser confocal microscope, configuring an adjustable infrared femtosecond pulsed laser with a wavelength range of 680 - 1300 nm; setting the laser wavelength to 916 nm to maximize the signal intensity according to the SHG excitation characteristics of mouse hippocampal collagen and the wavelength scanning results of preliminary experiments; focusing through a 25× multi-photon water immersion objective lens with NA 0.95, and after the SHG signal is separated by a dichroic mirror, it is collected by a high-sensitivity detector in the 448 nm band.

5. The second harmonic imaging method for analyzing the in vivo hippocampal collagen structure of a depression model mouse according to claim 1, characterized in that: In step 2, the image acquisition parameters are set, specifically including: three-dimensional preview after single-layer preview to check fiber continuity, and sliding along the Z-axis to confirm full-layer coverage; manually defining the starting and ending points of the Z-axis to ensure coverage of the entire thickness of hippocampal collagen, with a range of 200 - 300 μm; optimizing according to the objective lens numerical aperture and the SHG light penetration depth, where the objective lens numerical aperture NA = 1.2, balancing resolution and data volume, and selecting a step size of 1 μm; enabling the automatic optimization of laser power, scanning speed, and signal gain mode, dynamically adjusting the laser power, adding depth compensation, gradually increasing the PMT gain by 2 - 5% / 10 μm as the Z-axis deepens, with an initial value of 5 - 10% of the titanium sapphire laser output, avoiding light damage, automatically calibrating based on signal intensity, and the highest gray value ≈ 80% of the dynamic range; the objective lens magnification is 25×, combined with 2× digital zoom, and two-way scanning, and images are acquired at a resolution of 1024×1024 pixels.

Images