Experimental study on deantigenization and trabecular structure effects on bovine cancellous bone compression

Abstract

De-antigenization treatments in allogeneic bone grafting affect the compressive properties of bone materials, while synthetic 3D-printed scaffolds often overlook trabecular structural influences. This study investigates how de-antigenization impacts the hardness and compressive strength of bovine cancellous bone and explores the relationship between trabecular structural parameters and mechanical properties, aiming to optimize antigen removal while preserving mechanical integrity and guiding synthetic bone design. In this study, the hardness, compressive strength, and elastic modulus of bovine cancellous bone were analyzed after degreasing and deproteinization. Structural parameters (porosity, trabecular anisotropy, fractal dimensions) were obtained via CT scanning, and their effects on compressive properties were evaluated. The study yielded three findings:1. Deproteinization weakened the mechanical properties of bovine cancellous bone more significantly than degreasing. 2. When both deproteinization and degreasing are required, conducting degreasing before deproteinization can reduce the loss of mechanical properties. 3. Compressive strength is positively correlated with trabecular anisotropy and negatively correlated with trabecular thickness. To preserve the compressive strength and hardness of xenograft bone materials, degreasing should be performed before deproteinization during de-antigenization. In the design of 3D-printed bone scaffolds, the compressive strength can be modulated by adjusting the anisotropy of scaffold units. This approach enables personalized scaffold design tailored to the specific needs of individual patients, improving clinical outcomes.

Keywords

bovine femoral cancellous bone compressive strength properties heterogeneity of the trabeculae

Introduction

In clinical medicine, bone grafting is a primary treatment for traumatic orthopedics and joint revision, categorized into autologous, allogeneic, and synthetic bone grafts based on the source of the graft material.¹ The ideal bone implant should exhibit stable biocompatibility, mechanical strength, osteogenic, osteoinductive, and osteoconductive properties, minimal antigenicity, cost-effectiveness, and safety.² However, autologous bone grafts are limited by donor site morbidity and availability, restricting their clinical use. Bovine cancellous bone, a natural material with excellent biocompatibility and osteoinductive potential, is widely utilized in bone tissue engineering.^3,4 Untreated or inadequately processed allograft bone materials often trigger immune rejection due to residual antigenic components within the trabecular structure. Thus, de-antigenization of bovine cancellous bone is critical to enhancing its clinical safety and efficacy.^5,6 Lipoproteins and fat-soluble glycopeptides in bone fat and cell membranes are key antigenic components, as lipid and protein residues can induce immune rejection and reduce grafting success rates.^7,8

The effects of different degreasing methods on the degreasing of bovine cancellous bone were compared by visual observation, and it was found that the degreasing effect of the supercritical extraction method was similar to that of the chemical method.⁹ By comparing the effects of compressive mechanical properties of porcine rib bones degreased in different temperatures and environments, it was found that the biomechanical effects of deep cryogenic freezing on the xenograft bone were relatively small.¹⁰ Researchers analyzed the impact of antigen removal treatment on porcine cancellous bone and found that the method of antigen removal was able to effectively remove the antigenic components of xenograft bone while preserving the natural structural framework of the xenograft bone, and the matrix scaffold of the xenograft bone after treatment had good physicochemical properties and was able to satisfy the basic requirements for the repair of bone defects.¹ In vitro decalcification can be used to simulate cancellous bone with varying degrees of osteoporosis and to study its tensile fracture properties.¹¹

With advancements in 3D printing and additive manufacturing, synthetic materials have gained prominence in bone defect repair. These materials serve as scaffolds for bone regeneration, supporting osteoblast attachment and promoting osteoclast activity, which enhances graft resorption and new bone formation.¹² The customizable nature of 3D-printed bone scaffolds addresses the challenges of traditional manufacturing methods in accommodating diverse bone defect geometries.¹³ The mechanical properties of synthetic bone scaffolds, particularly compressive strength, are critical for providing adequate mechanical support.

Current research on allograft bone grafts primarily focuses on the effects of de-antigenization treatments and the mechanical impacts of isolated degreasing or deproteinization. However, there is limited exploration into the combined effects of degreasing and deproteinization on the compressive strength of cancellous bone. Additionally, structural optimization of bone scaffolds often relies on finite-element simulations, neglecting the influence of natural cancellous bone's structural parameters. This study aims to investigate the variations in hardness and compressive properties of bovine cancellous bone following degreasing and deproteinization, providing a scientific basis for optimizing allograft bone preparation. Furthermore, it explores the influence of trabecular anisotropy and fractal dimension on compressive strength, offering valuable insights into the mechanical design of orthopedic implants.

Method

Samples and preparation

Fresh bovine femur bones, slaughtered on the same day, were procured from a local market. After removing the periosteum and surrounding soft tissues, the bones were immediately stored in a −35 °C freezer for 24 h. While frozen, the femurs were sectioned, focusing on areas with a high concentration of cancellous bone. Cylindrical samples were extracted from the mid-region of the femoral head using a hollow drill with an inner diameter of 5 mm. A total of 25 cylindrical samples were randomly punched from the cancellous bone region above the bone scale line, ensuring uniform sampling by avoiding the ligamentous fossa at the femoral head's apex. Post-punching, the samples were trimmed and polished to achieve cylindrical dimensions of Ø4 × 8 mm (Figure 1).

Degreasing and deproteinization

Due to slight variations in the mechanical properties of femoral head cancellous bone based on positional distribution, and to mitigate the influence of cortical bone effects, the 25 cylindrical samples were randomly divided into five groups (A, B, C, D and E), each containing five samples. Group A served as the control group and remained untreated.

Methanol has polarity and penetration-enhancing effects, and together with chloroform's strong non-polar solubility, it can efficiently extract lipids, 1:1 volume ratio mixture of methanol and chloroform is a well-known and classic method for degreasing. 30% H₂O₂ solution, as a strong oxidizing agent, can oxidize and degrade bone collagen, while also destroying other organic components. It is a commonly used deproteinization method in the field of biochemistry.

Figure 1.

Samples preparation steps.

Group B samples were degreased by soaking in methanol/ chloroform solution for 24 h. Group C samples were degreased by immersion in a 30% H₂O₂ solution for 24 h, with the solution replaced every 12 h. Group D samples underwent a combined treatment: first, they were degreased by soaking in a 1:1 methanol /chloroform solution for 24 h, followed by deproteinization in a 30% H₂O₂ solution for two 12-h intervals, with the solution refreshed after the first 12 h. Group E samples were treated in the reverse order of Group D, with deproteinization first followed by degreasing (Figure 2).

Figure 2.

Samples de-antigenization steps.

After the respective chemical treatments, all samples were immersed in anhydrous ethanol for 10 h to remove residual reagents and surface antigens.

Structural characterization of cancellous bone

Micro-CT scanning, a nondestructive 3D imaging technique, utilizes X-rays to irradiate samples and records the intensity distribution of transmitted X-rays via a detector. This process enables the reconstruction of high-resolution 3D internal structural images using computer algorithms, making it particularly suitable for imaging and analyzing fine and intricate structures. In this experiment, five groups of samples were placed separately on the stage (nano voxel-3000D Sanying Precision Instruments), and the scanner performed imaging scans at a resolution of 500 nm, an exposure time of 0.4 s per projection, an energy of 90 kV, and a current of 66.5 ± 0.2 µA. Reconstruction was performed using the instrument's proprietary software (New Recon). The resulting slices were exported for analysis, and parameters such as trabecular bone volume fraction, average trabecular thickness, trabecular anisotropy, and fractal dimension were calculated using specialized software plugins .

Figure 3.

Anisotropic evaluation schematic.14

Figure 4.

Fractal dimension box-counting method evaluation schematic.¹⁵

Figure 5.

Slicing effect after fitting calculation of bone trabecular thickness and trabecular spacing. (a) binarized slice, (b) trabecular thickness, (c) trabecular spacing.

Figure 6.

Electronic universal testing machine and loading process of compression experiment.

To minimize the impact of surface densification artifacts introduced during sample preparation, the region of interest (ROI) was carefully selected within the scanned volume using the software. A cylindrical region, one size smaller than the original sample and centered within the cylinder, was defined as the ROI for export and subsequent analysis. This approach ensured the accuracy and reliability of the structural parameter measurements.

Specific volume fraction of cancellous bone

The sample slices were binarized, and the bone volume fraction (BV/TV) was calculated using the BoneJ plugin. BV/TV represents the ratio of the volume of mineralized bone (BV) to the total volume of the sample (TV) within the analyzed region.

Anisotropy of the trabecular of cancellous bone

BoneJ computes trabecular anisotropy by plotting numerous vectors of equal length on sample slices. The mean intercept length (MIL) of these vectors is determined by dividing the vector length by the number of intersections, representing the average distance between interfaces. A point cloud is generated, with each point corresponding to a vector multiplied by its MIL. The MIL tensor is derived by fitting an ellipsoid to the orientation data, and the anisotropy tensor and eigenvalues are calculated. The degree of anisotropy (DA) is defined as $1 - \frac{m i n i m u m e i g e n v a l u e}{m a x i m u m e i g e n v a l u e}$ , where the longest axis corresponds to the smallest eigenvalue due to the inverse square relationship (Figure 3). The process iteratively samples new random points with the same vectors, updating the DA using the MIL technique until the minimum number of sampled points is reached or the coefficient of variation of the DA falls below a threshold.

Cancellous bone is an anisotropic, viscoelastic material. While many studies simplify it as isotropic for research and calculations, the microstructure of trabecular bone significantly influences its mechanical properties. In this study, the slice sequence was imported into ImageJ and binarized. The 2D slices were reconstructed into a 3D model, which was then purified to remove non-maximal volume particles and background noise, enhancing the accuracy of anisotropy computation. For the analysis, the following parameters were set:

Directions: 2000 (number of sampling directions),

Lines per direction: 10,000 (number of parallel lines drawn in each direction),

Sampling increment: 1.73 (distance between sampling points along the lines).

Fractal dimension of cancellous bone

Fractal dimension (FD) is a metric used to quantify the irregularity and complexity of a structure. Higher FD values indicate greater structural complexity and disorder, making it a useful parameter for analyzing the self-similarity of trabecular bone distribution. By studying the relationship between the fractal dimension of trabecular bone and its mechanical properties, insights can be gained to optimize the mechanical performance of cancellous bone scaffolds in three-dimensional modeling.

In this study, the fractal dimension of trabecular bone was calculated using the BoneJ plugin in ImageJ software. The plugin employs the box-counting algorithm to estimate the FD of the image. Box-counting is an empirical method used to estimate the fractal dimension of an object, image, or set. It is based on a simple concept: covering the object with boxes of progressively smaller sizes and then counting the number of boxes required to cover the object at each corresponding scale (Figure 4). The parameters used for the calculation were as follows:

Starting box size: 48 (size of the box in the sampling grid during the first iteration),

Smallest box size: 6 (minimum size of the box in the grid),

Box scaling factor: 1.2 (factor by which the box size is reduced after each iteration).

Trabecular thickness and trabecular spacing

Trabecular thickness (Tb.Th) and trabecular spacing (Tb.Sp) are key parameters for evaluating the spatial morphology and structure of trabecular bone. The BoneJ plugin employs the sphere-fitting method to calculate these metrics. For trabecular thickness, spheres are fitted to the trabeculae, while for trabecular spacing, spheres are fitted to the gaps between the trabeculae. The calculation process follows a maximization principle, where the maximum sphere diameter is measured from each voxel, and the average of all diameters is computed to determine Tb. Th and Tb.Sp (Figure 5).

This method provides a robust and accurate quantification of trabecular bone microstructure, enabling detailed analysis of its structural characteristics and their relationship to mechanical properties. The results of these calculations are essential for understanding the biomechanical behavior of cancellous bone and optimizing the design of bone scaffold materials.

Hardness test

The cylindrical specimens were thawed at room temperature for 2 h while immersed in physiological saline, the lower end of each sample was fixed. A Shore hardness tester was employed to measure the hardness of the samples. To minimize measurement error, hardness values were recorded at five distinct positions on each sample: upper left, lower left, upper right, lower right, and the center. The highest and lowest values were excluded, and the average of the remaining three measurements was calculated and recorded as the hardness value for that sample.

Compressive strength test

Compression tests were conducted on cancellous bone samples subjected to different de-antigenization treatments. Before testing, the samples were thawed at room temperature for 2 h. The experiments were performed using a universal electronic testing machine (Hegewald & Peschke, Inspekt Table Blue 5 kN) with two kinds of load capacity, 500 N and 5 KN, for this test 500 N load capacity will be used. Displacement-controlled loading was applied at a rate of 1 mm/min, and a preload of approximately 0.5 N was uniformly applied at the onset of loading.Due to the small cross-sectional area of the sample, no lubrication is applied between the sample and the fixture. The tests were carried out at room temperature (23 ± 1 °C, 50 ± 5%RH), with the samples subjected to axial strain up to 25% (Figure 6). Throughout the loading process, the testing machine collected real-time data, including time, load, and displacement. The load-displacement curve was plotted using Origin software based on the load and displacement data obtained from the universal testing machine during the experiment.

σ_{s} = \frac{F}{A}

(1)

The stress values corresponding to each data point on the force-displacement curve can be calculated.

ε = \frac{δ}{L_{0}}

(2)

The strain values corresponding to each data point were calculated. By plotting the stress and strain values of all data points as a line graph, the stress-strain curve was obtained.

Young's modulus describes a material's ability to resist elastic deformation. Given the pronounced viscoelasticity of cancellous bone, Young's modulus serves as a critical parameter for characterizing its mechanical properties. This value is obtained by calculating the slope of the linear region in the stress-strain curve. The yield strength is defined as the stress at which a material begins to deform plastically, it corresponds to the peak stress at which plastic deformation initiates on the stress-strain curve. Compressive strength represents the maximum stress a material can endure under compressive loading. For certain elastoplastic materials, yield strength may serve as a reasonable approximation of compressive strength. Given the discernible yield point observed in the experimental stress-strain curve, yield strength was employed to characterize the compressive strength of trabecular bone.

Statistical analysis

One-way analysis of variance was used on the obtained hardness data to determine the significance of the correlation between different de-antigenization methods and treatment sequences with bone hardness differences, and then Tukey's test was selected for multiple post-hoc comparisons based on the results of the homogeneity of variance assumption. One-way ANOVA was applied to yield strength and Young's modulus, with ANOVA or Welch's tests performed based on the reported homogeneity of variance. Bivariate correlation analysis was conducted between the computed bone structural parameters and compressive performance parameters, and parameters with significant effects were selected for further multiple linear regression analysis based on the Pearson's and corresponding p-values.

Results

Cancellous bone hardness

The hardness values of five groups are presented in the table below:

Pairwise comparisons across five sample groups, including de-antigenization versus controls, are presented in Table 1 (P -values and confidence intervals). Results indicated that defatting alone did not significantly alter bone hardness (P = 0.843). In contrast, deproteinization significantly reduced material hardness. Furthermore, a synergistic effect was observed when defatting followed deproteinization (Group B/E, P = 0.032), yielding a greater softening effect compared to single or reverse-ordered treatments. No additional hardness reduction occurred when defatting preceded deproteinization (Group C/D, P = 1.000). The effect size $η^{2} = \frac{S S_{b e t w e e n}}{S S_{t o t a l}}$ = 0.539 was large, which falls within the range of a large effect in biomedicine. These findings demonstrate that de-antigenization exerts both statistically and clinically meaningful effects on bone material hardness.

Table 1.

Sample hardness of the five ABCDE groups.

Group	Average hardness value (HB)	Mean difference	P	95% confidence interval
A (Control Group)	63.750 ± 4.802	-	-	-
B (Degreased Group)	60.333 ± 4.446	3.417	0.843	−6.592,13.426
C (Deproteinized Group)	53.633 ± 6.607	10.117	0.047	0.108–20.126
D (Degreased & Deproteinized Group)	53.599 ± 5.728	10.151	0.046	0.142–20.160
E (Deproteinized & Degreased Group)	49.600 ± 4.535	14.150	0.003	4.141–24.159

Table 2.

Yield strength and Young's modulus of five groups.

Group	Yield strength ( $σ_{s}$ , MPa)	Average Young's modulus (E,GPa)
Control Group (A)	27.346 ± 2.257	0.564 ± 0.252
Degreased Group (B)	24.552 ± 6.769	0.397 ± 0.047
Deproteinized Group (C)	25.615 ± 6.595	0.362 ± 0.061
Degreased & Deproteinized Group (D)	20.240 ± 6.590	0.350 ± 0.104
Deproteinized & Degreased Group (E)	17.561 ± 8.507	0.263 ± 0.136

Compressive strength of cancellous bone

After obtaining the displacement-load curves of the specimens, the stress-strain data of all 25 samples were calculated according to equations (1) and (2). The stress-strain curves of individual samples were plotted as line graphs in Origin, and the average curves for the five sample groups were calculated (Figure 7).

Figure 7.

Load-displacement curves (a) and strength-strain curves (b) of five groups of specimens.

Peak identification was performed using Origin to determine the yield strength( $σ_{s}$ ) of all 25 specimens, then calculated the slope of the linear elastic region in the stress-strain curves of 25 samples to obtain the corresponding Young's modulus(E), and calculated the average of the computed data presented in the Table 2.

Structural parameters of cancellous bone

The trabecular structural parameters for all 25 specimens were calculated from sample sections using BoneJ, with the results presented in Figure 8 :

Figure 8.

Structural parameters of five groups.

Figure 9.

Scatter plots and linear regression of trabecular bone structural parameters with yield strength and Young's modulus of cancellous bone.

Correlation between compressive strength and structural parameters

Plot the compression performance and structural parameters of each sample as a scatter plot, to show the trend of changes between the yield strength and Young's modulus of each specimen and the structural parameters of trabecular bone (Figure 9).

A bivariate correlation analysis was conducted between the four structural parameters and the compression performance parameters. The results are shown in Figure 10.

Figure 10.

Bivariate correlation analysis between bone structural parameters and compressive properties. (* P < 0.05, - negative correlation).

It can be seen that Tb.Th, DA, and FD are negatively, positively, and positively correlated with yield strength, respectively, while BV/TV has no significant effect on yield strength (P = 0.415 > 0.05). All four structural parameters have a statistically significant effect on Young's modulus, among which the P -value of DA (0.064) is close to 0.05, indicating that DA has a relatively larger impact on E compared to the other three parameters. At the same time, the P < 0.01 and r = 0.713 of $σ_{s}$ /E are extremely positively correlated, which is in line with the basic laws of material mechanics, and also means that the two may share similar parameter influence mechanisms. Since the results indicate that the structural parameters do not have a significant effect on the Young's modulus, the following will focus solely on performing multiple linear regression on the yield strength based on the parameters with significant effects. The calculated correlations of various parameters are shown in Figure 11.

Figure 11.

The effect of multivariate linear regression structural parameters on yield strength(* P ≤ 0.05).

According to the ANOVA results: F(3,21) = 8.667, P < 0.001, the overall significance of the model is extremely high. The adjusted $R^{2}$ = 0.489, indicating that the three parameters Tb.Th, DA, and FD together explain 48.9% of the variation in yield strength, suggesting that these parameters are key determinants of yield strength. Tb.Th and FD have nearly equal importance (P = 0.05) and effect magnitude (absolute Beta approximately 0.5) on yield strength, but in opposite directions, with significant negative and positive predictions, respectively. In addition, collinearity diagnostics were performed on the model, revealing that the VIF values of all variables were well below 10 and all tolerance values were above 0.1, indicating no serious collinearity issues and demonstrating that the model is stable and reliable.

Discussion

The surgical treatment of bone defects remains a significant challenge in modern clinical medicine. Heterogeneous bone materials, due to their low cost, ease of acquisition, natural porous structure, suitable porosity, and excellent biocompatibility, hold great potential as ideal bone graft materials. However, current de-antigenization treatments for heterogeneous bone inevitably weaken its mechanical properties to some extent. Synthetic bone scaffold materials, while not fully replicating natural cancellous bone, benefit from advancements in additive manufacturing, which allows precise control over size, pore size, porosity, and structural characteristics. These materials can be personalized to match the bone quality and defect morphology of individual patients, thereby improving surgical success rates, reducing patient discomfort, and shortening recovery times.

In addition, cortical bone accounts for 80% of the total bone mass. It has high density and strength, serving as an important supporting tissue and a key part of bone mechanics research. Future studies will continue to investigate the effects of de-antigenization treatment on cortical-cancellous bone composites. This study remains limited by modest statistical power for detecting treatment effects on yield strength and Young's modulus. The non-significant ANOVA results (P = 0.513 and P = 0.249, respectively) may reflect true absence of treatment effects or insufficient power to detect smaller effect sizes. Future studies with larger sample sizes (n ≥ 8–10 per group) would provide definitive answers regarding these mechanical properties.

Effect of deantigenization on the hardness of cancellous bone

A comparison between groups A and B indicates that the degreasing treatment of cancellous bone using a methanol /chloroform solution resulted in merely a 5% reduction in sample hardness, compared with other control groups, its effect on sample hardness was not statistically significant (Table 1). In comparisons among groups A and C, after immersion in H₂O₂ solution, the cancellous bone specimens exhibited a 15.87% reduction in hardness, demonstrating that deproteinization treatment significantly compromises the mechanical integrity of trabecular tissue. Comparing groups C and D, it was found that performing defatting treatment before deproteinization does not increase the degree of reduction in hardness, but comparing Group D and Group E, it was found that deproteinization before defatting the damage to the hardness of the trabeculae.

Therefore, when employing H₂O₂ solution for degreasing cancellous bone, it is crucial to control the processing time and solution concentration to avoid excessive reduction in sample hardness, which could compromise the mechanical properties of the bone. Simultaneously, when deproteinization and degreasing of the bone are required, degreasing should be performed first to minimize damage to the bone's hardness.

Effect of deantigenization on the compressive strength of cancellous bone

Based on the compression experiment data obtained from the universal testing machine generated compression load-displacement curves, and strength-strain curves for each group. The compression curves of bovine cancellous bone exhibited an overall trend of initial increase, followed by a decrease, and then a continuous rise, with a distinct elastic-plastic phase observed in the material's behavior (Figure 7).

The comparisons between groups A/B and A/C respectively revealed that the degreasing treatment reduced the yield strength of cancellous bone by approximately 10.2% and 6.3%. The comparisons between groups A/D and A/E respectively revealed that the degreasing treatment reduced the yield strength of cancellous bone by approximately 26.0% and 35.8%. Although statistical analysis did not detect significant differences among groups (P = 0.513), potentially due to limited statistical power, descriptive trends suggest that there is still a trend similar to the changes observed in hardness. At the same time, statistical analysis indicates that yield strength exhibits a significantly similar trend to that of the Young's modulus.

Effect of structural parameters of bone trabeculae on compressive strength of cancellous bone

The results indicate that the yield strength of trabecular bone is significantly negatively correlated with Tb.Th and significantly positively correlated with FD (Figure 11), the corresponding trend can also be seen in Figure 8(c) and (e). Although DA is simply positively correlated with yield strength, its effect in the regression model is overshadowed by Tb.Th and FD (or due to their shared influence).

Based on the data obtained from Figure 11, a multiple regression equation for yield strength was formulated:

σ_{s} = - 86.843 - 15.012 T b . T h + 8.556 D A + 39.862 F D

Since the Young's modulus is highly correlated with the yield strength (P < 0.01, r = 0.713), its trend is considered to be consistent with that of the yield strength. These findings highlight the importance of trabecular structural parameters in determining the mechanical properties of cancellous bone, providing valuable insights for optimizing bone scaffold design and clinical applications.

Conclusions

Currently, the design of bone scaffolds primarily relies on finite element simulations, resulting in structures that are relatively simplistic and uniform compared to the complex trabecular architecture of natural cancellous bone. Future optimization of bone scaffolds, inspired by the structural parameters of natural trabecular bone, can significantly enhance the biomechanical properties of synthetic bone implants. This approach will facilitate the broader clinical application of synthetic bone materials, ultimately improving patient outcomes.

The de-antigenization reagents used in this experiment are standard solutions, which are readily available, easier to operate compared to other de-antigenization methods, and have a broader range of applications.

By examining the microstructure of natural bovine cancellous bone, this study investigates the relationship between structural parameters—such as trabecular bone volume fraction, trabecular thickness, trabecular anisotropy, and trabecular fractal dimension—and the compressive strength and elastic modulus of cancellous bone. These findings contribute to the optimization of artificial bone scaffold materials.

By considering these parameters, bone scaffold structures can be tailored to meet the specific mechanical needs of individual patients, optimizing clinical outcomes.

Footnotes

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China [grant numbers 52175386, 51805091]; and the Natural Science Foundation of Guangdong Province [grant numbers 2018A030313713].

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

ORCID iD

Jian-Bo Sui

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