Variation Patterns and Correlation Between BTMs and Microparameters of Trabecular Bone and Macro－mechanical Strength of Lumbar Vertebrae

Variation Patterns and Correlation Between BTMs and Microparameters of Trabecular Bone and Macro－mechanical Strength of Lumbar Vertebrae | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Variation Patterns and Correlation Between BTMs and Microparameters of Trabecular Bone and Macro－mechanical Strength of Lumbar Vertebrae Yuhao Jia, Ning Xia, Jian Zhao, Wei Xu, Wei Wang, hailong Yu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6161804/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Summary: This 4-month study was conducted in 64 white rabbits.The correlation between the microstructure, micro-mechanical properties and macroscopic mechanical strength of BTMs, bone trabeculae was investigated. CTX-I showed the strongest correlation with microstructure and micromechanical properties, while OC showed the strongest correlation with macroscopic mechanical strength. Objective: To investigate the variation patterns and correlations among serum bone turnover markers (BTMs), microstructure of trabecular bone, micro-mechanical properties, and macro-mechanical strength during the process of osteoporosis, and to identify BTMs that show strong correlations with all three. Methods: A total of 64 female New Zealand white rabbits were randomly divided into a sham surgery group (Sham group, n=32) and an osteoporosis model group (OP group, n=32). Rabbits in both groups were further randomly assigned to baseline (Pre-ovx), and three subsequent groups at 1, 2, and 4 months (n=8 each). Bone mineral density (BMD) was measured at Pre-ovx, and 1, 2, and 4 months post-surgery. Serum BTMs were collected from arterial blood, and lumbar vertebrae specimens were obtained to measure the microstructure, micro-mechanical properties, and macro-mechanical strength of trabecular bone. Results: BMD, maximum load (L max ), elastic modulus of trabecular bone, hardness, trabecular thickness (Tb.Th, mm), trabecular number (Tb.N, 1/mm), and bone volume fraction (BV/TV, %) gradually decreased, while trabecular space (Tb.Sp, mm), osteocalcin (OC), type I procollagen N-terminal propeptide (PⅠNP), and C-terminal telopeptide of type I collagen (CTX-I) gradually increased. Multiple linear regression showed that Tb.Th (β=0.369, P=0.038) and the elastic modulus of trabecular bone (β=0.594, P=0.002) were positively correlated with Lmax, while CTX-I was negatively correlated with both Tb.Th (β=-0.953, P=0.002) and the elastic modulus of trabecular bone (β=-0.963, P=0.000). OC was negatively correlated with L max (β=-0.966, P=0.000). Conclusion: The elastic modulus of trabecular bone has the most significant impact on macro-mechanical strength. CTX-I showed the strongest correlation with microstructure and micromechanical properties, while OC showed the strongest correlation with macroscopic mechanical strength. Rabbit Osteoporosis Micro-mechanics Microstructure Macro-mechanics Bone turnover markers Figures Figure 1 Figure 2 1. Introduction Osteoporosis (OP) is a skeletal disease characterized by a reduction in bone mass and degradation of bone tissue microstructure, leading to increased bone fragility and fracture risk 1 . Osteoporotic fractures represent a significant complication of OP, with an incidence rate of 13% in China. It is projected that by 2035, the annual number of fractures related to OP will reach 4.83 million, incurring an estimated cost of approximately $ 19.92 billion annually 2 . Vertebral compression fractures (VCFs) are the most common type of osteoporotic fracture, as spinal bone mineral density (BMD) progressively declines with age, making the disease particularly prevalent among the elderly 3 , 4 . Symptomatic vertebral OP fractures often result in severe spinal pain, spinal deformities, reduced mobility, and decreased pulmonary function, thereby increasing mortality risk with advancing age 5 . Thus, exploring the micro-mechanisms underlying spinal OP fractures could be instrumental in effectively preventing the occurrence of spinal OP. Dual-energy X-ray absorptiometry (DXA) is currently the gold standard for measuring BMD and diagnosing OP; however, it has certain limitations. Firstly, DXA does not exhibit significant changes in early BMD fluctuations, as it can only detect alterations in bone loss once it reaches a certain threshold 6 . Secondly, BMD alone does not fully account for variations in bone strength and fracture risk observed in clinical treatment 7 . Therefore, it is necessary to employ additional imaging techniques, such as micro-computed tomography (Micro-CT) and nanoindentation, to further validate BMD measurements and bone structure 8 . Research has indicated that changes in the spatial structure of trabecular bone during the process of OP can significantly impact the overall mechanical strength of bone 9 . 10 . Micro-mechanical properties of trabecular bone, such as microhardness and micro-elastic modulus, also exert a substantial influence on bone strength 11 . However, the alterations in the micro-mechanical properties of spinal trabecular bone throughout the OP process, as well as the interactions and degrees of influence between these changes, microstructural parameters, and macro-mechanical strength, remain unclear. Bone turnover markers (BTMs) are products of the bone tissue's own metabolism and can dynamically reflect the status of bone remodeling. Nonetheless, the variety of markers, along with their susceptibility to environmental and methodological influences, has resulted in controversy regarding which specific BTMs can more sensitively indicate fracture risk. Overall, current research primarily focuses on the macroscopic level, particularly the correlation between BMD and macro-mechanical strength, lacking a systematic investigation of microparameters (microstructure and micro-mechanics) of bone. Furthermore, the interactions between microstructural parameters and micro-mechanical properties during the OP process remain poorly understood, as does their weighting in relation to macro-mechanical strength. There is also a notable deficiency in studies exploring the correlations between BTMs, microstructural parameters, micro-mechanical properties, and macro-mechanical strength. Consequently, the aim of this study is to investigate the weighting of microstructural parameters and micro-mechanical characteristics in relation to Lmax, and to further analyze their correlations with BTMs. This research seeks to identify BTMs that exhibit strong correlations with both macro-mechanical strength and microstructural and micro-mechanical properties, providing a theoretical basis for the prevention and treatment of OP and osteoporotic fractures. 2. Materials and Methods 2.1 Animal Source Sixty-four 7-month-old (3.12 ± 0.25 kg) female New Zealand white rabbits were provided by Chengdu Enswier Biotechnology Co., Ltd. All experimental procedures were approved by the Animal Ethics Committee of the General Hospital of the Western Theater Command of the Chinese People's Liberation Army (2022EC2-ky045) and adhered to guidelines for animal care and use. Each rabbit was housed individually in stainless steel cages within standard animal facilities, maintaining a room temperature of 21–24°C and relative humidity of 40–60%. A 12-hour light-dark cycle was implemented, with the lighting period synchronized with daytime, and standard commercial rabbit feed (Chengdu Enswier Biotechnology Co., Ltd.) and tap water were provided ad libitum. 2.2 Osteoporotic Rabbit Model Grouping and Establishment After a two-week acclimatization period to their new environment, all animals were randomly divided into a sham surgery group (Sham group, n = 32) and an osteoporosis model group (OP group, n = 32). Prior to modeling, eight rabbits from each group were randomly selected for euthanasia via air embolism through the marginal ear vein to obtain Pre-ovx data. The animals in the OP group were fasted for 12 hours before surgery. Under isoflurane anesthesia (provided by Shenzhen Reward Life Science and Technology Co., Ltd., China), a midline incision was made on the abdomen to cut through the skin and muscles for bilateral ovariectomy surgery (OVX). For the Sham group, the bilateral ovaries were exposed during the procedure and then returned and sutured without further intervention. All animals received an intramuscular injection of gentamicin at a dose of 10,000 U/kg (Beijing Soleybo Co., Ltd.) twice daily for three days post-surgery. Two weeks postoperatively, animals in the OP group were administered dexamethasone at a dose of 0.5 mg/kg (Shanxi Yiduoli Co., Ltd.) twice weekly for four weeks. Following the designated time periods, animals were classified into 1-month, 2-month, and 4-month groups, with eight rabbits in each group. Postoperatively, the animals were divided into groups based on the duration of time: 1-month group, 2-month group, 4-month group, each consisting of 8 animals. At 1, 2, and 4 months post-surgery, lumbar spine bone mineral density (BMD) was measured using DXA. Subsequently, rabbits were euthanized via ear vein injection of excess air and lumbar spine (L1-L5) samples were collected and stored frozen at -80°C. 2.3 Lumbar Spine BMD Measurement BMD values of the lumbar spine were measured for each group of rabbits prior to euthanasia at designated time points (Pre-ovx, 1 month, 2 months, 4 months) using DXA (Lunar Prodigy Advance; GE Lunar, Madison, WI, USA). During measurement, the rabbits were placed in a prone position on the testing platform under isoflurane anesthesia, and analysis was performed using dedicated small animal software (GE Medical Systems, enCOREv17). Osteoporosis was diagnosed when the BMD value in the OP group was lower than the mean value of the Sham group at the same time point minus 2.5 SD, in conjunction with changes in bone microstructure 12 . 2.4 Micro-CT Scanning and Reconstruction Analysis The lumbar vertebrae were removed from the − 80°C freezer and thawed at room temperature. Muscle, intervertebral discs, and fascia were dissected, and accessory structures such as transverse and spinous processes were removed. The L5 vertebra was scanned using a Quantum GX Micro-CT scanner (PerkinElmer, USA). Scanning parameters were set as follows: energy/intensity of 80 kV, 100 µA, 8 W, angle increment of 0.5°, and a scanning time of 4 minutes, starting from 0° rotation. Post-scan, reconstructed images were obtained. The entire trabecular region of the complete vertebra was defined as the region of interest (ROI), and analysis was conducted using Avatar software (version 2.0.0.1, PINGSENG Healthcare Inc.), with parameters including Tb.Th, Tb.Sp, Tb.N, and BV/TV. 2.5 Nanoindentation Testing Lumbar specimens that had undergone Micro-CT scanning were stored frozen at -80°C and retrieved for testing, thawing at room temperature until fully defrosted. Initially, the bone surface was polished using 120-grit sandpaper, followed by sequential polishing with 600, 800, and 1200-grit sandpapers. The polished samples were then placed on a PG-2DA dual-disk variable-speed polishing machine (Shanghai Guangmi Instrument Co., Ltd.) for polishing while being rinsed with sterile deionized water. After polishing, samples were cleaned using an ultrasonic bath. Following the calibration of the TI 750 TriboIndenter nanoindentation testing system (Hysitron, USA), the polished samples were affixed to the testing stage of the nanoindenter, ensuring that the indenter tip remained perpendicular to the sample surface. The surface of the vertebral specimen, featuring a trabecular mesh structure, was verified through atomic force microscopy to ensure that indentations were conducted on trabecular regions. Given the random distribution of trabecular bone, ten random compressions were performed for each group of specimens, and indentation measurements were taken using the Basic method. Testing parameters were set to a loading rate of 0.1 µN/s, unloading rate of 0.1 mN/s, a maximum displacement of 200 nm, and a load hold time of 60 seconds to eliminate the viscoelastic effects on measurements. The resulting load-displacement curves were utilized to calculate micro-mechanical indices, including elastic modulus and hardness, with the average values taken as statistical data for each specimen. 2.6 Compression Testing L4 vertebrae were selected and fully thawed at room temperature, with muscle, intervertebral discs, and fascia removed. Low-speed precision diamond saws with continuous irrigation were used to excise the endplates of the vertebra, removing accessory structures such as transverse and spinous processes, and the superior and inferior surfaces were polished to be parallel, resulting in a vertebral body composed of a central trabecular core and a compact shell. Compression testing was conducted using an MTS809 axial/torsion materials testing machine (MTS, USA). The MTS machine was equipped with an axial hydraulic actuator with a capacity of 200 kN. The sample was placed in the testing chamber, preloaded with a static force of -10 N for 30 seconds, followed by a compression test at a rate of 0.02 mm/s until a clear peak was observed, after which L max was automatically determined using the accompanying software. All experimental procedures were performed at a room temperature of 23 ± 0.2°C. 2.7 Serum BTMs Testing Fasting blood samples were collected from the central ear marginal artery of the rabbits at designated time points (Pre-ovx, 1 month, 2 months, 4 months) between 7:00 and 10:00 AM, following a night of fasting. All samples were centrifuged at 4°C at 3000 g for 15 minutes, and the supernatant was collected. Subsequently, serum samples were stored in a deep freezer at -80°C until analysis. For analysis, samples were thawed at room temperature, and 50 µL of each sample and standard were added to a 96-well plate. Serum levels of osteocalcin (OC), N-terminal propeptide of type I procollagen (PINP), and C-terminal telopeptide of type I collagen (CTX) were measured using an enzyme-linked immunosorbent assay (ELISA). Analysis was conducted using a Multiskan GO microplate reader (Thermo Fisher Scientific, USA), and all samples were processed using the same detection method unless repeat measurements of individual values were required. All procedures were conducted in accordance with the instructions provided with the assay kits. 3. Statistical Methods Statistical analyses were performed using SPSS version 26.0. All data were normally distributed and presented as mean ± standard deviation. Comparisons of relevant parameters between the Sham and OP groups at the same time points were conducted using independent samples t-tests. Comparisons of different time points within the same group were performed using one-way analysis of variance (ANOVA). Pearson correlation analysis was used to evaluate the relationships between microstructural parameters, micro-mechanical properties, and macro-mechanical strength, identifying the indices most strongly correlated with macro-mechanical strength among microstructural and micro-mechanical parameters. Subsequently, Pearson correlation analysis was conducted between these identified indices and BTMs to determine which BTMs exhibited the strongest correlations with microstructural and micro-mechanical properties. Finally, Pearson correlation analysis was performed between the identified BTMs and macro-mechanical strength to ascertain which BTMs were most strongly correlated with macro-mechanical strength. Multivariate linear regression analyses were then conducted to identify BTMs that had the greatest influence on macro-mechanical strength, microstructural parameters, and micro-mechanical properties. Statistical significance was set at P < 0.05. 4. Results 4.1 BMD and L max As shown in Table 1 , both BMD and L max values in the OP group exhibited a gradual decline over the modeling period. At 2 months and 4 months post-surgery, BMD and L max values in the OP group were significantly lower than those in the Sham group (P < 0.001). Additionally, BMD and L max values in the OP group at 2 months and 4 months post-surgery showed significant decreases compared to Pre-ovx (P 0.05). Table 1 BMD and L max results parameter Group Pre-ovx 1 mouth 2 mouths 4 mouths BMD (g/cm²) Sham 0.277 ± 0.06 0.278 ± 0.04 0.279 ± 0.04 0.282 ± 0.03 OP 0.275 ± 0.08 0.273 ± 0.05 0.232 ± 0.08 *# 0.172 ± 0.06 *# L max (N) Sham 677 ± 51 685 ± 39 691 ± 28 691 ± 57 OP 667 ± 44 632 ± 18 490 ± 34 *# 331 ± 34 *# Values are expressed as the mean ± standard deviation (n = 8). Compared to the Sham group at the same time point, * P < 0.001; Compared to Pre-ovx in the same treatment group, # P < 0.001. 4.2 Microstructural and Micro-mechanical Parameters As shown in Table 2 , notable changes in microstructural parameters of the OP group began to occur at 2 months post-surgery, except for Tb.N, which significantly declined starting from 1 month post-surgery (P = 0.004). At 2 and 4 months post-surgery, the OP group exhibited significantly decreased Tb.Th and BV/TV and significantly increased Tb.Sp compared to the Sham group at the same time points (P < 0.01). Compared to Pre-ovx, the OP group showed significant reductions in Tb.Th, Tb.N, and BV/TV and a significant increase in Tb.Sp at both 2 months and 4 months (P 0.05). In terms of micro-mechanical parameters, both elastic modulus and hardness in the OP group demonstrated a gradual decline. At 1, 2, and 4 months post-surgery, the OP group exhibited significantly lower elastic modulus and hardness compared to the Sham group at the same time points (P < 0.01). When compared to Pre-ovx, the OP group showed significant decreases in both elastic modulus and hardness (P < 0.01). Table 2 Microstructural and Micro-mechanical Parameter Results parameter Group Pre-ovx 1 mouth 2 mouths 4 mouths Tb.Th (mm) Sham 0.233 ± 0.014 0.227 ± 0.015 0.235 ± 0.016 0.232 ± 0.018 OP 0.228 ± 0.014 0.212 ± 0.004 0.184 ± 0.005 *# 0.147 ± 0.012 *# Tb.N (1/mm) Sham 1.013 ± 0.061 0.974 ± 0.077 0.995 ± 0.086 1.003 ± 0.079 OP 0.999 ± 0.068 0.865 ± 0.022 &△ 0.823 ± 0.013 &△ 0.689 ± 0.043 &# Tb.Sp (mm) Sham 0.769 ± 0.047 0.788 ± 0.057 0.789 ± 0.080 0.784 ± 0.072 OP 0.781 ± 0.062 0.860 ± 0.041 1.002 ± 0.002 *# 1.243 ± 0.085 *# BV/TV (%) Sham OP 0.303 ± 0.030 0.299 ± 0.024 0.295 ± 0.034 0.276 ± 0.007 0.303 ± 0.035 0.221 ± 0.008 *# 0.313 ± 0.022 0.174 ± 0.023 *# Elastic modulus (Gpa) Sham 22.920 ± 1.014 23.016 ± 1.035 23.284 ± 0.977 23.160 ± 1.191 OP 23.131 ± 1.072 20.413 ± 0.679 *# 17.886 ± 0.624 *# 15.260 ± 0.866 *# Hardness (Gpa) Sham 0.823 ± 0.052 0.813 ± 0.048 0.810 ± 0.081 0.833 ± 0.075 OP 0.800 ± 0.058 0.716 ± 0.056 &△ 0.614 ± 0.027 *# 0.460 ± 0.034 *# Values are expressed as the mean ± standard deviation (n = 8). Compared to the Sham group at the same time point, & P < 0.01; Compared to the Sham group at the same time point, * P < 0.001; Compared to Pre-ovx in the same treatment group, △ P < 0.01; Compared to Pre-ovx in the same treatment group, # P < 0.001. BV/TV, bone volume fraction; Tb.Th, trabecular thickness; Tb.Sp, trabecular spacing; Tb.N, number of trabeculae. 4.3 Micro-CT Imaging of Lumbar Trabecular Bone As illustrated in Fig. 1 , panels a-d depict the trabecular architecture in the Sham group, characterized by a rich and densely interconnected trabecular network with stable structure. In contrast, panels e-h demonstrate the progressive deterioration of the trabecular structure over time in the OP group, with a noticeable reduction in trabecular quantity, an increase in trabecular spacing, a decrease in trabecular thickness, and discontinuity in structure. 4.4 Serum BTMs Analysis As shown in Table 3 , the levels of bone turnover markers (BTMs) in the OP group exhibited a gradual increase over time. Compared to the Sham group at the same time points, levels of PINP and CTX-I showed significant elevation starting from 1 month post-surgery, while OC levels significantly increased from 2 months post-surgery (P < 0.001). When compared to Pre-ovx, the OP group demonstrated significant increases in PINP and CTX-I from 1 month post-surgery (P 0.05). Table 3 Serum BTMs Analysis Results (ng/mL) parameter Group Pre-ovx 1 mouth 2 mouths 4 mouths OC Sham 1.41 ± 0.07 1.42 ± 0.05 1.41 ± 0.04 1.42 ± 0.05 OP 1.42 ± 0.05 1.48 ± 0.07 2.86 ± 0.31 *# 4.07 ± 0.24 *# PINP Sham 2.91 ± 0.16 2.93 ± 0.15 2.94 ± 0.13 2.90 ± 0.15 OP 2.92 ± 0.07 3.59 ± 0.22 *# 5.80 ± 0.32 *# 7.77 ± 0.34 *# CTX-I Sham 0.23 ± 0.04 0.24 ± 0.03 0.22 ± 0.02 0.23 ± 0.02 OP 0.23 ± 0.03 0.40 ± 0.02 *# 0.60 ± 0.03 *# 0.80 ± 0.03 *# Values are expressed as the mean ± standard deviation (n = 8). Compared to the Sham group at the same time point, * P < 0.001; Compared to Pre-ovx in the same treatment group, # P < 0.001. 4.5 Pearson Correlation Analysis Among Parameters in the OP Group As shown in Fig. 2 , there were positive correlations between Tb.Th, Tb.N, BV/TV and the elastic modulus and hardness of trabecular bone, while Tb.Sp exhibited negative correlations with these parameters. The strongest correlation was found between Tb.Th and elastic modulus (r = 0.938, P = 0.000) and hardness (r = 0.921, P = 0.000). Moreover, Tb.Th, Tb.N, BV/TV, elastic modulus, and hardness were positively correlated with lumbar L max , while Tb.Sp showed a negative correlation with L max . The strongest correlation was observed between trabecular elastic modulus and lumbar L max (r = 0.940, P = 0.000). OC, PINP, and CTX-I all exhibited negative correlations with lumbar Lmax, with OC showing the strongest correlation (r = -0.966, P = 0.000). Additionally, OC, PINP, and CTX-I were negatively correlated with Tb.Th and elastic modulus, with the strongest correlations seen between CTX-I and elastic modulus (r = -0.963, P = 0.000) and Tb.Th (r = -0.954, P = 0.000). 4.6 Multiple Linear Regression The results of the multiple linear regression analysis among parameters are presented in Tables 4 , 5 , and 6 . Both Tb.Th and the elastic modulus of trabecular bone showed positive correlations with L max , with the strongest correlation between elastic modulus and L max (β = 0.594, P = 0.002). CTX-I exhibited negative correlations with both Tb.Th and the elastic modulus, with the strongest correlation observed between CTX-I and elastic modulus (β = -0.963, P = 0.000). OC also showed a negative correlation with L max (β = -0.966, P = 0.000). Table 4 Multiple Linear Regression Analysis of Microstructural Parameters with L max Parameter L max Standard Error Standardized Coefficient P Tb.Th 715.881 0.369 0.038 Elastic Modulus 7.642 0.594 0.002 Table 5 Multiple Linear Regression Analysis of OC with L max Parameter L max Standard Error Standardized Coefficient P OC 5.779 -0.966 0.000 Table 6 Multiple Linear Regression Analysis of CTX-I with Tb.Th and Elastic Modulus Parameter Tb.Th Elastic Modulus Standard Error Standardized Coefficient P Standard Error Standardized Coefficient P CTX-I 0.008 -0.953 0.000 0.695 -0.963 0.000 5. Discussion As age increases, bone loss may occur, leading to an increased incidence of osteoporosis (OP). Therefore, as a chronic, long-term bone disorder, OP is more common among the elderly, typically affecting males over the age of 65 and females over the age of 55 13 . Patients with vertebral compression fractures (VCF) face a significantly increased risk of subsequent fractures, making OP fractures a strong and independent risk factor 14 . These fractures severely impact quality of life and safety. This study primarily investigates the changes in bone turnover markers (BTMs), microstructural properties of lumbar trabecular bone, micro-mechanical characteristics, and their correlation with macro-mechanical strength throughout the OP process. We successfully established an OP rabbit model using the traditional ovariectomy (OVX) and glucocorticoid (GC) method, examining the temporal variations in BMD, microstructural properties, micro-mechanical characteristics, BTMs, and macro-mechanical strength over a four-month postoperative period. The observed progressive changes in the OP group indicate worsening osteoporosis. The longer the duration of OVX and GC treatment, the more severe the osteoporosis. Currently, ovariectomized rats are the most commonly used animal model for OP 15 . However, this model has limitations: rats do not experience natural menopause and cannot achieve true skeletal maturity. Additionally, their small size limits complete epiphyseal closure and Haversian remodeling 16 . In contrast, rabbits exhibit active Haversian remodeling, reach skeletal maturity within a shorter period of six to eight months, and are easier to feed and manage compared to larger animals. Therefore, rabbits were chosen for our OP model 17 . Research indicates that the impact of OP progression on trabecular microstructure is greater than that on cortical bone 18 , with trabecular bone being crucial for microstructural studies. Currently, with the increased availability of high-resolution imaging technologies such as Micro-CT, measuring trabecular spatial structure has become a routine method. The main indicators for observing trabecular structure include BV/TV, Tb.Th, Tb.Sp, and Tb.N 19 . In the study, we used Micro-CT to scan the lumbar vertebrae and measured the changes in these four linear indicators BV/TV, Tb.Th, Tb.Sp, Tb.N as OP progressed. As OP advanced, BV/TV, Tb.Th, and Tb.N showed significant declines, while Tb.Sp significantly increased, which is consistent with the findings of Divya et al 20 . In our study, compared to the Sham group, there was a significant difference in BMD in the OP group at two months post-surgery, while the Micro-CT measurement of Tb.N showed significant differences from the Sham group as early as one month post-surgery. This indicates that Micro-CT has higher sensitivity for detecting changes in trabecular bone mass. Additionally, compared to Tb.N, BV/TV, Tb.Th, and Tb.Sp only began to show significant changes at two months post-surgery, indicating that early changes in the spatial structure of trabecular bone during the OP process were primarily characterized by a reduction in trabecular number, while later changes were mainly reflected in decreases in volume, thinning of trabeculae, and widening of trabecular spacing. Nanoindentation is currently the only method available for accurate micro-mechanical analysis of trabecular bone 21 . The elastic modulus is a critical indicator of bone strength, reflecting the ability of bone to resist elastic deformation under load 22 . Our study found significant declines in both elastic modulus and hardness starting 1 month post-surgery, corroborating findings from other researchers like Li et al. 23 , indicating early significant declines in microstructural strength and hardness in OP. It is worth mentioning that in the study by Wen et al. 24 , the nanoindentation method was found to detect changes in bone quality in osteoporotic rabbit models earlier than other conventional methods (Micro-CT, BMD), which differs from our findings. In our study, both Tb.N measured by Micro-CT and the elastic modulus and hardness of trabecular bone measured by nanoindentation showed significant changes starting from 1 month post-surgery. This indicates that the timing of changes in microstructural properties and micro-mechanical characteristics at the microscopic level is similar, suggesting that nanoindentation does not demonstrate greater sensitivity than Micro-CT in detecting changes in the quality of lumbar trabecular bone. In the study by Li et al., analysis of the femoral condyle revealed that the elastic modulus and hardness of cortical bone trabeculae showed significant changes starting at 4 weeks, while their microstructural properties and BMD only changed significantly after 6 weeks. We believe the differences may arise from the different anatomical sites studied, indicating that the timing of changes in trabecular bone may vary across different anatomical locations, which requires further validation. OP significantly increases overall bone brittleness, raising fracture risk. Lumbar L max represents the maximum force the vertebra can withstand before fracturing, serving as a key indicator of macro-mechanical performance 25 . Our findings demonstrate a significant reduction in L max as OP progressed, consistent with previous studies 26 . Notably, while elastic modulus, hardness, and Tb.N showed significant changes at 1 month post-surgery, L max did not decline until 2 months post-surgery, suggesting that early macro-mechanical strength changes are primarily driven by alterations in trabecular thickness, spacing, and volume—areas warranting further investigation. While we explored changes in microstructural properties, micro-mechanical characteristics, and macro-mechanical strength, the interplay between these factors remains unclear. Studies suggest that the relationship between trabecular microstructure and its elastic modulus and hardness depends on one or more microstructural features 27 . We conducted correlation analyses between BV/TV, Tb.Th, Tb.Sp, Tb.N and L max , as well as trabecular elastic modulus and hardness. As shown in Fig. 2 , Tb.Th has the strongest correlation with L max (r = 0.926, P = 0.000), trabecular elastic modulus (r = 0.938, P = 0.000), and hardness (r = 0.921, P = 0.000). When analyzing the correlation between trabecular elastic modulus and hardness with L max , as shown in Fig. 2 , the elastic modulus (r = 0.940, P = 0.000) was found to be the strongest correlated factor. These results indicate that among the micro-mechanical properties of bone, changes in elastic modulus are most closely associated with macro-mechanical strength, while Tb.Th is the factor most strongly correlated with both micro-mechanical properties and macro-mechanical strength. However, it remains unclear whether these two factors influence macro-mechanical strength and which indicator better reflects changes in bone strength. Therefore, we conducted further analysis. As shown in Table 4 , multiple linear regression reveals that both Tb.Th (β = 0.369, P = 0.038) and trabecular elastic modulus (β = 0.594, P = 0.002) are positively correlated with L max , indicating that both Tb.Th and trabecular elastic modulus correlate strongly with macroscopic mechanical strength. Additionally, the impact of trabecular elastic modulus on macro-mechanical strength is greater than that of Tb.Th; the higher the elastic modulus, the greater the bone strength and the lower the risk of fractures. BTMs are biomarkers used to detect dynamic bone remodeling in blood or urine 28 , reflecting the status of bone resorption and bone formation 29 . Current research focuses on the differences between BMD and BTMs; however, BMD explains only about 60%-70% of bone strength variability 30 , indicating that analyzing BTMs in isolation from microstructural and mechanical properties may not accurately reflect changes in bone strength. Further integration of BTMs with microstructural and mechanical analyses is essential for a comprehensive understanding of bone health. OC is one of the bone formation markers and a specific indicator reflecting bone formation. CTX-I and PINP are highly sensitive markers of bone turnover metabolism 31 , with CTX-I being more sensitive 6 to differences in femoral neck bone mass and strength. PINP reflects the rate of type I collagen synthesis and the state of bone turnover; higher levels of PINP indicate more active bone turnover 32 , 33 . This study shows that serum levels of OC, CTX-I, and PINP in the OP group are significantly higher than in the Sham group, consistent with previous findings 34 . This indicates that serum OC, CTX-I, and PINP can reflect changes in bone metabolism and mass, aiding in the early diagnosis and treatment of OP. In our study, both CTX-I and PINP began to increase significantly from 1 month post-surgery, while OC showed significant changes starting from the second month post-surgery. The delayed response of OC may be related to the use of dexamethasone. Studies have shown that prolonged use of glucocorticoids (GC) can impair osteoblast function, leading to decreased osteocalcin (OC) levels. This is due to targeted disruption of GC signaling in osteoblasts, weakening the inhibition of OC synthesis and halting OC production. Research by Dovio 36 et al. indicated that high-dose, short-term GC use in humans immediately reduces OC and PINP levels while rapidly and briefly increasing CTX-I levels, which appears somewhat different from our results. Upon analyzing the reasons for these differences, we believe that firstly, the GC dosage used in their study was 15 mg/kg per day, significantly higher than the dosage we utilized. Studies have suggested that GC doses ranging between 0.5 and 1 mg/(kg·d) are effective only for bone turnover without affecting inflammation, necrosis, or subchondral bone changes, while doses below 0.5 mg/(kg·d) do not significantly impact bone alterations 37 . Furthermore, Dovio et al. measured OC, CTX-I, and PINP daily during treatment (10 days) and three months later. The results indicated that during treatment, OC and PINP immediately decreased starting from the second day, while CTX-I continued to significantly increase. Three months later, the levels of all bone turnover markers (BTMs) showed a significant increase. In our study, the first postoperative measurement was taken one month later, so we are uncertain if OC and PINP decreased during this period. However, three months later, all BTMs showed a significant increase, which is somewhat consistent with our results. Although serum BTMs can reflect changes in bone metabolism and bone mass, it is still unclear which marker best reflects their correlation with bone quality and strength. As shown in Fig. 2 , we conducted a correlation analysis between OC, CTX-I, PINP, and lumbar spine Lmax. The results showed that OC had the strongest negative correlation with L max (r=-0.966, P = 0.000), indicating that OC could serve as a representative marker for assessing bone quality in macroscopic mechanics. We further analyzed the correlations of OC, CTX-I, and PINP with microstructural parameters and micro-mechanical properties that are strongly related to macroscopic mechanical strength, such as Tb.Th and trabecular elastic modulus. The results showed that CTX-I had the strongest correlation with trabecular elastic modulus (r=-0.963, P = 0.000) and Tb.Th (r=-0.954, P = 0.000). Subsequently, we performed multiple linear regression analyses of OC with L max , CTX-I with Tb.Th, and trabecular elastic modulus. As shown in Tables 5 and 6 , the correlation between CTX-I and trabecular elastic modulus (β=-0.963, P = 0.000) was the strongest. OC had a negative correlation with L max (β=-0.966, P = 0.000), indicating that OC was the most influential factor related to macroscopic mechanical strength, while CTX-I was the most influential factor related to microstructural properties and micro-mechanical characteristics. Therefore, from a macroscopic perspective, in the process of OP, a higher OC value corresponds to lower L max in the lumbar spine, suggesting a more severe degree of OP. From a microscopic analysis, a higher CTX-I value correlates with thinner trabeculae, lower elastic modulus, and hardness. The limitations of our experiment include the discussion of only linear indices for microstructural parameters and the lack of further discussion on nonlinear indices, as well as the absence of discussion on microchemical composition. Additionally, our study was limited to animal models without clinical validation. There are limitations to the generalization of the findings to human osteoporosis due to physiological differences between humans and rabbits. First, the bone metabolic rate in rabbits is much higher than that in humans, leading to the possibility that the short-term effects of pharmacological interventions may be magnified without accurately reflecting the pathological process of chronic osteoporosis in humans 38 . Second, rabbits have a 15–20% higher cortical bone porosity than humans and a different pattern of cancellous bone density distribution, affecting the comparability of drug diffusion kinetics 39 . In addition, the distribution of mechanical loads in quadrupeds results in the distal femur, rather than the femoral neck, being the main load-bearing area, which is an anatomical deviation from the high prevalence of osteoporotic fractures in humans 40 . Therefore, in future research, we will incorporate non-linear parameters and clinical serum data for further exploration to improve our findings. 6. Conclusion In the process of OP, lumbar BMD, L max , trabecular elastic modulus, hardness, BV/TV, Tb.Th, Tb.N, and BTMs gradually decrease over time, while Tb.Sp gradually increases. Early changes in trabecular spatial structure are primarily characterized by a significant reduction in trabecular number, later accompanied by significant decreases in trabecular thickness, increased spacing, and reduced volume. Tb.Th shows the strongest correlation with micro-mechanical properties. Trabecular elastic modulus has the most significant impact on macro-mechanical strength. We hypothesize that the elastic modulus of lumbar trabecular bone can be a predictive factor for vertebral OP fractures. For BTMs, CTX-I shows the strongest correlation with microstructure and micromechanical properties of the lumbar spine, while OC shows the strongest correlation with macro-mechanical strength. Early detection of CTX-I helps us understand changes in the microstructural and micro-mechanical properties of lumbar trabecular bone during the process of OP, while early detection of OC assists in understanding changes in macro-mechanical strength. These findings provide new research ideas and theoretical foundations for more comprehensive clinical assessments of spinal OP severity and the prevention of spinal OP fractures. Abbreviations ANOVA: Analysis of variance; BMD: Bone mineral density; CTX-I: C-terminal telopeptide of type I collagen; DXA: Dual energy X-ray absorptiometry; ELISA: Enzyme-linked immunosorbent assay; OC: Osteocalcin; OP: Osteoporosis; PINP: Type I procollagen N-terminal propeptide; BTMs: Bone turnover markers; BV/TV: bone volume fraction; Tb.Th: trabecular thickness; Tb.Sp: trabecular spacing; Tb.N: number of trabeculae; OVX: ovariectomy. Declarations All methods are reported in accordance with ARRIVE guidelines. Ethics approval statement The animal experiments were approved by the Animal Ethics Committee of the General Hospital of Western Theater Command (2022EC2-ky045) . Moreover, all applicable rules and regulation of the organization and government were followed regarding the ethical use of experimental animal. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author Da Liu on reasonable request. Funding This study was supported by the Cadre health committee Program of China (21BJZ40) and 、 (2022NSFSC0664) . Conflict of interest disclosure Yuhao Jia, Ning Xia, Jian Zhao, Wei Xu, Wei Wang, hailong Yu, Da Liu and Yingbo Zhang declare that they have no conflict of interest Patient consent statement Not applicable. Permission to reproduce material from other sources Not applicable. Clinical trial registration Not applicable. Acknowledgements Not applicable. References 1 Chai H, Ge J, Li L, Li J, Ye Y. Hypertension is associated with osteoporosis: a case-control study in Chinese postmenopausal women. BMC Musculoskelet Disord . 2021;22(1):253. doi:10.1186/s12891-021-04124-9 Zeng Q, Li N, Wang Q, et al. The Prevalence of Osteoporosis in China, a Nationwide, Multicenter DXA Survey. J Bone Miner Res . 2019;34(10):1789-1797. doi:10.1002/jbmr.3757 Pcs P, Cg M, Rz M, L M, Ml F. An overview of clinical guidelines for the management of vertebral compression fracture: a systematic review. 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The definition of spine bone mineral density (BMD)-classified osteoporosis and the much inflated prevalence of spine osteoporosis in older Chinese women when using the conventional cutpoint T-score of −2.5. Ann Transl Med . 2022;10(24):1421. doi:10.21037/atm-22-4559 Compston JE, McClung MR, Leslie WD. Osteoporosis. Lancet . 2019;393(10169):364-376. doi:10.1016/S0140-6736(18)32112-3 Kutsal FY, Ergin Ergani GO. Vertebral compression fractures: Still an unpredictable aspect of osteoporosis. Turk J Med Sci . 2021;51(2):393-399. doi:10.3906/sag-2005-315 Komori T. Animal models for osteoporosis. Eur J Pharmacol . 2015;759:287-294. doi:10.1016/j.ejphar.2015.03.028 Dai L, Wu H, Yu S, et al. Effects of OsteoKing on osteoporotic rabbits. Molecular Medicine Reports . 2015;12(1):1066-1074. doi:10.3892/mmr.2015.3551 Permuy M, López-Peña M, Muñoz F, González-Cantalapiedra A. Rabbit as model for osteoporosis research. J Bone Miner Metab . 2019;37(4):573-583. doi:10.1007/s00774-019-01007-x Xie F, Zhou B, Wang J, et al. Microstructural properties of trabecular bone autografts: comparison of men and women with and without osteoporosis. Arch Osteoporos . 2018;13(1):18. doi:10.1007/s11657-018-0422-z Morgan EF, Unnikrisnan GU, Hussein AI. Bone Mechanical Properties in Healthy and Diseased States. Annu Rev Biomed Eng . 2018;20:119-143. doi:10.1146/annurev-bioeng-062117-121139 Sharma D, Larriera AI, Palacio-Mancheno PE, et al. The effects of estrogen deficiency on cortical bone microporosity and mineralization. Bone . 2018;110:1-10. doi:10.1016/j.bone.2018.01.019 Kimmel DB, Vennin S, Desyatova A, et al. Bone architecture, bone material properties, and bone turnover in non-osteoporotic post-menopausal women with fragility fracture. Osteoporos Int . 2022;33(5):1125-1136. doi:10.1007/s00198-022-06308-y Mora-Macías J, García-Florencio P, Pajares A, Miranda P, Domínguez J, Reina-Romo E. Elastic Modulus of Woven Bone: Correlation with Evolution of Porosity and X-ray Greyscale. Ann Biomed Eng . 2021;49(1):180-190. doi:10.1007/s10439-020-02529-6 Xi L, Song Y, Wu W, et al. Investigation of bone matrix composition, architecture and mechanical properties reflect structure-function relationship of cortical bone in glucocorticoid induced osteoporosis. Bone . 2020;136:115334. doi:10.1016/j.bone.2020.115334 Wen XX, Xu C, Wang FQ, et al. Temporal changes of microarchitectural and mechanical parameters of cancellous bone in the osteoporotic rabbit. Biomed Res Int . 2015;2015:263434. doi:10.1155/2015/263434 Sopon M, Oleksik V, Roman M, et al. Biomechanical Study of the Osteoporotic Spine Fracture: Optical Approach. J Pers Med . 2021;11(9):907. doi:10.3390/jpm11090907 Quan R, Ni Y, Zhang L, Xu J, Zheng X, Yang D. Short- and long-term effects of vertebroplastic bone cement on cancellous bone. J Mech Behav Biomed Mater . 2014;35:102-110. doi:10.1016/j.jmbbm.2014.03.007 Giner M, Miranda C, Vázquez-Gámez MA, et al. Microstructural and Strength Changes in Trabecular Bone in Elderly Patients with Type 2 Diabetes Mellitus. Diagnostics (Basel) . 2021;11(3):577. doi:10.3390/diagnostics11030577 Jain S. Role of Bone Turnover Markers in Osteoporosis Therapy. Endocrinology and Metabolism Clinics of North America . 2021;50(2):223-237. doi:10.1016/j.ecl.2021.03.007 Brown JP, Don-Wauchope A, Douville P, Albert C, Vasikaran SD. Current use of bone turnover markers in the management of osteoporosis. Clin Biochem . 2022;109-110:1-10. doi:10.1016/j.clinbiochem.2022.09.002 Pumberger M, Issever AS, Diekhoff T, et al. Bone structure determined by HR-MDCT does not correlate with micro-CT of lumbar vertebral biopsies: a prospective cross-sectional human in vivo study. J Orthop Surg Res . 2020;15(1):398. doi:10.1186/s13018-020-01895-0 Eastell R, Szulc P. Use of bone turnover markers in postmenopausal osteoporosis. Lancet Diabetes Endocrinol . 2017;5(11):908-923. doi:10.1016/S2213-8587(17)30184-5 Wheater G, Elshahaly M, Tuck SP, Datta HK, van Laar JM. The clinical utility of bone marker measurements in osteoporosis. J Transl Med . 2013;11:201. doi:10.1186/1479-5876-11-201 Williams C, Sapra A. Osteoporosis Markers. In: StatPearls . StatPearls Publishing; 2023. Accessed December 17, 2023. http://www.ncbi.nlm.nih.gov/books/NBK559306/ Bhattoa HP. Laboratory aspects and clinical utility of bone turnover markers. EJIFCC . 2018;29(2):117-128. Florez H, Hernández-Rodríguez J, Carrasco JL, et al. Low serum osteocalcin levels are associated with diabetes mellitus in glucocorticoid treated patients. Osteoporos Int . 2022;33(3):745-750. doi:10.1007/s00198-021-06167-z Dovio A, Perazzolo L, Osella G, et al. Immediate fall of bone formation and transient increase of bone resorption in the course of high-dose, short-term glucocorticoid therapy in young patients with multiple sclerosis. J Clin Endocrinol Metab . 2004;89(10):4923-4928. doi:10.1210/jc.2004-0164 Eberhardt AW, Yeager-Jones A, Blair HC. Regional trabecular bone matrix degeneration and osteocyte death in femora of glucocorticoid- treated rabbits. Endocrinology . 2001;142(3):1333-1340. doi:10.1210/endo.142.3.8048 Duggal D, Nagwekar J, Rich R, et al. Phosphorylation of myosin regulatory light chain has minimal effect on kinetics and distribution of orientations of cross bridges of rabbit skeletal muscle. Am J Physiol Regul Integr Comp Physiol . Harrison KD, Hiebert BD, Panahifar A, et al. Cortical Bone Porosity in Rabbit Models of Osteoporosis. J Bone Miner Res . 2020;35(11):2211-2228. Kimura M, Nakase J, Takata Y, et al. Regeneration Using Adipose-Derived Stem Cell Sheets in a Rabbit Meniscal Defect Model Improves Tensile Strength and Load Distribution Function of the Meniscus at 12 Weeks. Arthroscopy . References 2 Baofeng L, Zhi Y, Bei C, Guolin M, Qingshui Y, Jian L. Characterization of a rabbit osteoporosis model induced by ovariectomy and glucocorticoid. Acta Orthop . 2010;81(3):396-401. Oki Y, Doi K, Kobatake R, et al. Histological and histomorphometric aspects of continual intermittent parathyroid hormone administration on osseointegration in osteoporosis rabbit model. PLoS One . 2022;17(6):e0269040. Permuy M, López-Peña M, Muñoz F, González-Cantalapiedra A. Rabbit as model for osteoporosis research. J Bone Miner Metab . 2019;37(4):573-583. Duggal D, Nagwekar J, Rich R, et al. Phosphorylation of myosin regulatory light chain has minimal effect on kinetics and distribution of orientations of cross bridges of rabbit skeletal muscle. Am J Physiol Regul Integr Comp Physiol . Harrison KD, Hiebert BD, Panahifar A, et al. Cortical Bone Porosity in Rabbit Models of Osteoporosis. J Bone Miner Res . 2020;35(11):2211-2228. Kimura M, Nakase J, Takata Y, et al. Regeneration Using Adipose-Derived Stem Cell Sheets in a Rabbit Meniscal Defect Model Improves Tensile Strength and Load Distribution Function of the Meniscus at 12 Weeks. Arthroscopy . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6161804","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":433380488,"identity":"ede83cdf-ac95-41b3-a29e-c4171c8bf0dc","order_by":0,"name":"Yuhao Jia","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yuhao","middleName":"","lastName":"Jia","suffix":""},{"id":433380489,"identity":"91b0b18f-585e-40da-8414-63d418b7bb47","order_by":1,"name":"Ning Xia","email":"","orcid":"","institution":"The Fifth People's Hospital of Sichuan Province","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Xia","suffix":""},{"id":433380491,"identity":"5533c879-03d2-4195-9236-2c6018622e1c","order_by":2,"name":"Jian Zhao","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhao","suffix":""},{"id":433380494,"identity":"800cf182-fff9-4425-9535-7632f4889730","order_by":3,"name":"Wei Xu","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Xu","suffix":""},{"id":433380496,"identity":"ac64dffe-b908-49d3-870c-29db9b00535c","order_by":4,"name":"Wei Wang","email":"","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wang","suffix":""},{"id":433380498,"identity":"81f6e8d9-bcb2-4e0b-ad02-405b7fbb9d27","order_by":5,"name":"hailong Yu","email":"","orcid":"","institution":"General Hospital of Northern Theater Command of Chinese PLA","correspondingAuthor":false,"prefix":"","firstName":"hailong","middleName":"","lastName":"Yu","suffix":""},{"id":433380500,"identity":"47636f02-91b4-471b-ba30-bd12e2dd1229","order_by":6,"name":"Yingbo Zhang","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yingbo","middleName":"","lastName":"Zhang","suffix":""},{"id":433380503,"identity":"cbc104bf-051a-4d4f-a86e-b173e07053e3","order_by":7,"name":"Da Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYBACPmYGBgmGHxJ2/MzMhx8QpYUNpIWxxyJZsp0tzYA4LQwgW9gqGDec51GQIE4LO4/hjR88EszGh3kYDBhqbKKJcBiPsWWPhQSf2WHeAw8YjqXlNhChxUyCB2iL2WG+BAPGhsPEaZH8wybBuLmZx0CCaC3SPEAtG5iJ18JWbC3bI5EscRgYyAnE+IWf//DGm29+1Nnx9x8+/OBDjQ1hLagggTTlo2AUjIJRMApwAQCwijD7b+dlUgAAAABJRU5ErkJggg==","orcid":"","institution":"The General Hospital of Western Theater Command","correspondingAuthor":true,"prefix":"","firstName":"Da","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-03-05 10:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6161804/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6161804/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79552363,"identity":"8fc318ec-1b17-4e02-8ebc-1b25f7765ecd","added_by":"auto","created_at":"2025-03-31 06:49:45","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":516660,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional reconstruction images from Micro-CT scans of the L5 vertebra. Panels A-D represent the Sham group at Pre-ovx, 1 month, 2 months, and 4 months, respectively. Panels E-H represent the OP group at Pre-ovx, 1 month, 2 months, and 4 months, respectively.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6161804/v1/3b8b270efa203e334c5c66ac.jpeg"},{"id":79552368,"identity":"e6ee54dc-c057-47f9-be26-5749518ed88a","added_by":"auto","created_at":"2025-03-31 06:49:45","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":608740,"visible":true,"origin":"","legend":"\u003cp\u003ePearson Correlation Analysis Among Parameters in the OP Group\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6161804/v1/6a51960a957caba8c555c300.jpeg"},{"id":79553800,"identity":"3057c1aa-a1ab-451a-be20-20bc46f95449","added_by":"auto","created_at":"2025-03-31 07:05:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2166015,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6161804/v1/747fb296-f281-49bf-b0c5-fd81e70ee180.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Variation Patterns and Correlation Between BTMs and Microparameters of Trabecular Bone and Macro－mechanical Strength of Lumbar Vertebrae","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOsteoporosis (OP) is a skeletal disease characterized by a reduction in bone mass and degradation of bone tissue microstructure, leading to increased bone fragility and fracture risk\u003csup\u003e \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1\u003c/span\u003e \u003c/sup\u003e. Osteoporotic fractures represent a significant complication of OP, with an incidence rate of 13% in China. It is projected that by 2035, the annual number of fractures related to OP will reach 4.83\u0026nbsp;million, incurring an estimated cost of approximately \u003cspan\u003e$\u003c/span\u003e19.92\u0026nbsp;billion annually\u003csup\u003e \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e \u003c/sup\u003e. Vertebral compression fractures (VCFs) are the most common type of osteoporotic fracture, as spinal bone mineral density (BMD) progressively declines with age, making the disease particularly prevalent among the elderly\u003csup\u003e \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e4\u003c/span\u003e \u003c/sup\u003e. Symptomatic vertebral OP fractures often result in severe spinal pain, spinal deformities, reduced mobility, and decreased pulmonary function, thereby increasing mortality risk with advancing age\u003csup\u003e \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e \u003c/sup\u003e. Thus, exploring the micro-mechanisms underlying spinal OP fractures could be instrumental in effectively preventing the occurrence of spinal OP.\u003c/p\u003e \u003cp\u003eDual-energy X-ray absorptiometry (DXA) is currently the gold standard for measuring BMD and diagnosing OP; however, it has certain limitations. Firstly, DXA does not exhibit significant changes in early BMD fluctuations, as it can only detect alterations in bone loss once it reaches a certain threshold\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Secondly, BMD alone does not fully account for variations in bone strength and fracture risk observed in clinical treatment\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Therefore, it is necessary to employ additional imaging techniques, such as micro-computed tomography (Micro-CT) and nanoindentation, to further validate BMD measurements and bone structure\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Research has indicated that changes in the spatial structure of trabecular bone during the process of OP can significantly impact the overall mechanical strength of bone\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e.\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Micro-mechanical properties of trabecular bone, such as microhardness and micro-elastic modulus, also exert a substantial influence on bone strength\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, the alterations in the micro-mechanical properties of spinal trabecular bone throughout the OP process, as well as the interactions and degrees of influence between these changes, microstructural parameters, and macro-mechanical strength, remain unclear. Bone turnover markers (BTMs) are products of the bone tissue's own metabolism and can dynamically reflect the status of bone remodeling. Nonetheless, the variety of markers, along with their susceptibility to environmental and methodological influences, has resulted in controversy regarding which specific BTMs can more sensitively indicate fracture risk. Overall, current research primarily focuses on the macroscopic level, particularly the correlation between BMD and macro-mechanical strength, lacking a systematic investigation of microparameters (microstructure and micro-mechanics) of bone. Furthermore, the interactions between microstructural parameters and micro-mechanical properties during the OP process remain poorly understood, as does their weighting in relation to macro-mechanical strength. There is also a notable deficiency in studies exploring the correlations between BTMs, microstructural parameters, micro-mechanical properties, and macro-mechanical strength.\u003c/p\u003e \u003cp\u003eConsequently, the aim of this study is to investigate the weighting of microstructural parameters and micro-mechanical characteristics in relation to Lmax, and to further analyze their correlations with BTMs. This research seeks to identify BTMs that exhibit strong correlations with both macro-mechanical strength and microstructural and micro-mechanical properties, providing a theoretical basis for the prevention and treatment of OP and osteoporotic fractures.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Animal Source\u003c/h2\u003e \u003cp\u003e Sixty-four 7-month-old (3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25 kg) female New Zealand white rabbits were provided by Chengdu Enswier Biotechnology Co., Ltd. All experimental procedures were approved by the Animal Ethics Committee of the General Hospital of the Western Theater Command of the Chinese People's Liberation Army (2022EC2-ky045) and adhered to guidelines for animal care and use. Each rabbit was housed individually in stainless steel cages within standard animal facilities, maintaining a room temperature of 21\u0026ndash;24\u0026deg;C and relative humidity of 40\u0026ndash;60%. A 12-hour light-dark cycle was implemented, with the lighting period synchronized with daytime, and standard commercial rabbit feed (Chengdu Enswier Biotechnology Co., Ltd.) and tap water were provided ad libitum.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Osteoporotic Rabbit Model Grouping and Establishment\u003c/h2\u003e \u003cp\u003eAfter a two-week acclimatization period to their new environment, all animals were randomly divided into a sham surgery group (Sham group, n\u0026thinsp;=\u0026thinsp;32) and an osteoporosis model group (OP group, n\u0026thinsp;=\u0026thinsp;32). Prior to modeling, eight rabbits from each group were randomly selected for euthanasia via air embolism through the marginal ear vein to obtain Pre-ovx data. The animals in the OP group were fasted for 12 hours before surgery. Under isoflurane anesthesia (provided by Shenzhen Reward Life Science and Technology Co., Ltd., China), a midline incision was made on the abdomen to cut through the skin and muscles for bilateral ovariectomy surgery (OVX). For the Sham group, the bilateral ovaries were exposed during the procedure and then returned and sutured without further intervention. All animals received an intramuscular injection of gentamicin at a dose of 10,000 U/kg (Beijing Soleybo Co., Ltd.) twice daily for three days post-surgery. Two weeks postoperatively, animals in the OP group were administered dexamethasone at a dose of 0.5 mg/kg (Shanxi Yiduoli Co., Ltd.) twice weekly for four weeks. Following the designated time periods, animals were classified into 1-month, 2-month, and 4-month groups, with eight rabbits in each group. Postoperatively, the animals were divided into groups based on the duration of time: 1-month group, 2-month group, 4-month group, each consisting of 8 animals. At 1, 2, and 4 months post-surgery, lumbar spine bone mineral density (BMD) was measured using DXA. Subsequently, rabbits were euthanized via ear vein injection of excess air and lumbar spine (L1-L5) samples were collected and stored frozen at -80\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Lumbar Spine BMD Measurement\u003c/h2\u003e \u003cp\u003eBMD values of the lumbar spine were measured for each group of rabbits prior to euthanasia at designated time points (Pre-ovx, 1 month, 2 months, 4 months) using DXA (Lunar Prodigy Advance; GE Lunar, Madison, WI, USA). During measurement, the rabbits were placed in a prone position on the testing platform under isoflurane anesthesia, and analysis was performed using dedicated small animal software (GE Medical Systems, enCOREv17). Osteoporosis was diagnosed when the BMD value in the OP group was lower than the mean value of the Sham group at the same time point minus 2.5 SD, in conjunction with changes in bone microstructure\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Micro-CT Scanning and Reconstruction Analysis\u003c/h2\u003e \u003cp\u003eThe lumbar vertebrae were removed from the \u0026minus;\u0026thinsp;80\u0026deg;C freezer and thawed at room temperature. Muscle, intervertebral discs, and fascia were dissected, and accessory structures such as transverse and spinous processes were removed. The L5 vertebra was scanned using a Quantum GX Micro-CT scanner (PerkinElmer, USA). Scanning parameters were set as follows: energy/intensity of 80 kV, 100 \u0026micro;A, 8 W, angle increment of 0.5\u0026deg;, and a scanning time of 4 minutes, starting from 0\u0026deg; rotation. Post-scan, reconstructed images were obtained. The entire trabecular region of the complete vertebra was defined as the region of interest (ROI), and analysis was conducted using Avatar software (version 2.0.0.1, PINGSENG Healthcare Inc.), with parameters including Tb.Th, Tb.Sp, Tb.N, and BV/TV.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Nanoindentation Testing\u003c/h2\u003e \u003cp\u003eLumbar specimens that had undergone Micro-CT scanning were stored frozen at -80\u0026deg;C and retrieved for testing, thawing at room temperature until fully defrosted. Initially, the bone surface was polished using 120-grit sandpaper, followed by sequential polishing with 600, 800, and 1200-grit sandpapers. The polished samples were then placed on a PG-2DA dual-disk variable-speed polishing machine (Shanghai Guangmi Instrument Co., Ltd.) for polishing while being rinsed with sterile deionized water. After polishing, samples were cleaned using an ultrasonic bath. Following the calibration of the TI 750 TriboIndenter nanoindentation testing system (Hysitron, USA), the polished samples were affixed to the testing stage of the nanoindenter, ensuring that the indenter tip remained perpendicular to the sample surface. The surface of the vertebral specimen, featuring a trabecular mesh structure, was verified through atomic force microscopy to ensure that indentations were conducted on trabecular regions. Given the random distribution of trabecular bone, ten random compressions were performed for each group of specimens, and indentation measurements were taken using the Basic method. Testing parameters were set to a loading rate of 0.1 \u0026micro;N/s, unloading rate of 0.1 mN/s, a maximum displacement of 200 nm, and a load hold time of 60 seconds to eliminate the viscoelastic effects on measurements. The resulting load-displacement curves were utilized to calculate micro-mechanical indices, including elastic modulus and hardness, with the average values taken as statistical data for each specimen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Compression Testing\u003c/h2\u003e \u003cp\u003eL4 vertebrae were selected and fully thawed at room temperature, with muscle, intervertebral discs, and fascia removed. Low-speed precision diamond saws with continuous irrigation were used to excise the endplates of the vertebra, removing accessory structures such as transverse and spinous processes, and the superior and inferior surfaces were polished to be parallel, resulting in a vertebral body composed of a central trabecular core and a compact shell. Compression testing was conducted using an MTS809 axial/torsion materials testing machine (MTS, USA). The MTS machine was equipped with an axial hydraulic actuator with a capacity of 200 kN. The sample was placed in the testing chamber, preloaded with a static force of -10 N for 30 seconds, followed by a compression test at a rate of 0.02 mm/s until a clear peak was observed, after which L\u003csub\u003emax\u003c/sub\u003e was automatically determined using the accompanying software. All experimental procedures were performed at a room temperature of 23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Serum BTMs Testing\u003c/h2\u003e \u003cp\u003eFasting blood samples were collected from the central ear marginal artery of the rabbits at designated time points (Pre-ovx, 1 month, 2 months, 4 months) between 7:00 and 10:00 AM, following a night of fasting. All samples were centrifuged at 4\u0026deg;C at 3000 g for 15 minutes, and the supernatant was collected. Subsequently, serum samples were stored in a deep freezer at -80\u0026deg;C until analysis. For analysis, samples were thawed at room temperature, and 50 \u0026micro;L of each sample and standard were added to a 96-well plate. Serum levels of osteocalcin (OC), N-terminal propeptide of type I procollagen (PINP), and C-terminal telopeptide of type I collagen (CTX) were measured using an enzyme-linked immunosorbent assay (ELISA). Analysis was conducted using a Multiskan GO microplate reader (Thermo Fisher Scientific, USA), and all samples were processed using the same detection method unless repeat measurements of individual values were required. All procedures were conducted in accordance with the instructions provided with the assay kits.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Statistical Methods","content":"\u003cp\u003eStatistical analyses were performed using SPSS version 26.0. All data were normally distributed and presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Comparisons of relevant parameters between the Sham and OP groups at the same time points were conducted using independent samples t-tests. Comparisons of different time points within the same group were performed using one-way analysis of variance (ANOVA). Pearson correlation analysis was used to evaluate the relationships between microstructural parameters, micro-mechanical properties, and macro-mechanical strength, identifying the indices most strongly correlated with macro-mechanical strength among microstructural and micro-mechanical parameters. Subsequently, Pearson correlation analysis was conducted between these identified indices and BTMs to determine which BTMs exhibited the strongest correlations with microstructural and micro-mechanical properties. Finally, Pearson correlation analysis was performed between the identified BTMs and macro-mechanical strength to ascertain which BTMs were most strongly correlated with macro-mechanical strength. Multivariate linear regression analyses were then conducted to identify BTMs that had the greatest influence on macro-mechanical strength, microstructural parameters, and micro-mechanical properties. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1 BMD and L\u003csub\u003emax\u003c/sub\u003e\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, both BMD and L\u003csub\u003emax\u003c/sub\u003e values in the OP group exhibited a gradual decline over the modeling period. At 2 months and 4 months post-surgery, BMD and L\u003csub\u003emax\u003c/sub\u003e values in the OP group were significantly lower than those in the Sham group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, BMD and L\u003csub\u003emax\u003c/sub\u003e values in the OP group at 2 months and 4 months post-surgery showed significant decreases compared to Pre-ovx (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No statistically significant differences were observed among the Sham group at different time points (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBMD and L\u003csub\u003emax\u003c/sub\u003e results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eparameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePre-ovx\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 mouth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 mouths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 mouths\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMD (g/cm\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.277\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.278\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.279\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.282\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.275\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.273\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.232\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.172\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL\u003csub\u003emax\u003c/sub\u003e (N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e677\u0026thinsp;\u0026plusmn;\u0026thinsp;51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e685\u0026thinsp;\u0026plusmn;\u0026thinsp;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e691\u0026thinsp;\u0026plusmn;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e691\u0026thinsp;\u0026plusmn;\u0026thinsp;57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e667\u0026thinsp;\u0026plusmn;\u0026thinsp;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e632\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e490\u0026thinsp;\u0026plusmn;\u0026thinsp;34\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e331\u0026thinsp;\u0026plusmn;\u0026thinsp;34\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (n\u0026thinsp;=\u0026thinsp;8). Compared to the Sham group at the same time point, \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Compared to Pre-ovx in the same treatment group, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Microstructural and Micro-mechanical Parameters\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, notable changes in microstructural parameters of the OP group began to occur at 2 months post-surgery, except for Tb.N, which significantly declined starting from 1 month post-surgery (P\u0026thinsp;=\u0026thinsp;0.004). At 2 and 4 months post-surgery, the OP group exhibited significantly decreased Tb.Th and BV/TV and significantly increased Tb.Sp compared to the Sham group at the same time points (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Compared to Pre-ovx, the OP group showed significant reductions in Tb.Th, Tb.N, and BV/TV and a significant increase in Tb.Sp at both 2 months and 4 months (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). No statistically significant differences were observed among the Sham group at different time points (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In terms of micro-mechanical parameters, both elastic modulus and hardness in the OP group demonstrated a gradual decline. At 1, 2, and 4 months post-surgery, the OP group exhibited significantly lower elastic modulus and hardness compared to the Sham group at the same time points (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). When compared to Pre-ovx, the OP group showed significant decreases in both elastic modulus and hardness (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMicrostructural and Micro-mechanical Parameter Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eparameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-ovx\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 mouth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 mouths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 mouths\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTb.Th (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.233\u0026thinsp;\u0026plusmn;\u0026thinsp;0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.227\u0026thinsp;\u0026plusmn;\u0026thinsp;0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.235\u0026thinsp;\u0026plusmn;\u0026thinsp;0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.232\u0026thinsp;\u0026plusmn;\u0026thinsp;0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.228\u0026thinsp;\u0026plusmn;\u0026thinsp;0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.212\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.184\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.147\u0026thinsp;\u0026plusmn;\u0026thinsp;0.012\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTb.N (1/mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.013\u0026thinsp;\u0026plusmn;\u0026thinsp;0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.974\u0026thinsp;\u0026plusmn;\u0026thinsp;0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.995\u0026thinsp;\u0026plusmn;\u0026thinsp;0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.003\u0026thinsp;\u0026plusmn;\u0026thinsp;0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.999\u0026thinsp;\u0026plusmn;\u0026thinsp;0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.865\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022\u003csup\u003e\u0026amp;△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.823\u0026thinsp;\u0026plusmn;\u0026thinsp;0.013\u003csup\u003e\u0026amp;△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.689\u0026thinsp;\u0026plusmn;\u0026thinsp;0.043\u003csup\u003e\u0026amp;#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTb.Sp (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.769\u0026thinsp;\u0026plusmn;\u0026thinsp;0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.788\u0026thinsp;\u0026plusmn;\u0026thinsp;0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.789\u0026thinsp;\u0026plusmn;\u0026thinsp;0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.784\u0026thinsp;\u0026plusmn;\u0026thinsp;0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.781\u0026thinsp;\u0026plusmn;\u0026thinsp;0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.860\u0026thinsp;\u0026plusmn;\u0026thinsp;0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.243\u0026thinsp;\u0026plusmn;\u0026thinsp;0.085\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBV/TV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.303\u0026thinsp;\u0026plusmn;\u0026thinsp;0.030\u003c/p\u003e \u003cp\u003e0.299\u0026thinsp;\u0026plusmn;\u0026thinsp;0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.295\u0026thinsp;\u0026plusmn;\u0026thinsp;0.034\u003c/p\u003e \u003cp\u003e0.276\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.303\u0026thinsp;\u0026plusmn;\u0026thinsp;0.035\u003c/p\u003e \u003cp\u003e0.221\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.313\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022\u003c/p\u003e \u003cp\u003e0.174\u0026thinsp;\u0026plusmn;\u0026thinsp;0.023\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElastic modulus (Gpa)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.920\u0026thinsp;\u0026plusmn;\u0026thinsp;1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.016\u0026thinsp;\u0026plusmn;\u0026thinsp;1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.284\u0026thinsp;\u0026plusmn;\u0026thinsp;0.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.160\u0026thinsp;\u0026plusmn;\u0026thinsp;1.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.131\u0026thinsp;\u0026plusmn;\u0026thinsp;1.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.413\u0026thinsp;\u0026plusmn;\u0026thinsp;0.679\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.886\u0026thinsp;\u0026plusmn;\u0026thinsp;0.624\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.260\u0026thinsp;\u0026plusmn;\u0026thinsp;0.866\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHardness (Gpa)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.823\u0026thinsp;\u0026plusmn;\u0026thinsp;0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.813\u0026thinsp;\u0026plusmn;\u0026thinsp;0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.810\u0026thinsp;\u0026plusmn;\u0026thinsp;0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.833\u0026thinsp;\u0026plusmn;\u0026thinsp;0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.800\u0026thinsp;\u0026plusmn;\u0026thinsp;0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.716\u0026thinsp;\u0026plusmn;\u0026thinsp;0.056\u003csup\u003e\u0026amp;△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u0026thinsp;\u0026plusmn;\u0026thinsp;0.027\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.460\u0026thinsp;\u0026plusmn;\u0026thinsp;0.034\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (n\u0026thinsp;=\u0026thinsp;8). Compared to the Sham group at the same time point, \u003csup\u003e\u0026amp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Compared to the Sham group at the same time point, \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Compared to Pre-ovx in the same treatment group, \u003csup\u003e△\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Compared to Pre-ovx in the same treatment group, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001. BV/TV, bone volume fraction; Tb.Th, trabecular thickness; Tb.Sp, trabecular spacing; Tb.N, number of trabeculae.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Micro-CT Imaging of Lumbar Trabecular Bone\u003c/h2\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panels a-d depict the trabecular architecture in the Sham group, characterized by a rich and densely interconnected trabecular network with stable structure. In contrast, panels e-h demonstrate the progressive deterioration of the trabecular structure over time in the OP group, with a noticeable reduction in trabecular quantity, an increase in trabecular spacing, a decrease in trabecular thickness, and discontinuity in structure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Serum BTMs Analysis\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the levels of bone turnover markers (BTMs) in the OP group exhibited a gradual increase over time. Compared to the Sham group at the same time points, levels of PINP and CTX-I showed significant elevation starting from 1 month post-surgery, while OC levels significantly increased from 2 months post-surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When compared to Pre-ovx, the OP group demonstrated significant increases in PINP and CTX-I from 1 month post-surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and OC from 2 months post-surgery. No statistically significant differences were observed among the Sham group at different time points (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSerum BTMs Analysis Results (ng/mL)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eparameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-ovx\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 mouth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 mouths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 mouths\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePINP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTX-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (n\u0026thinsp;=\u0026thinsp;8). Compared to the Sham group at the same time point, \u003csup\u003e*\u003c/sup\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Compared to Pre-ovx in the same treatment group, \u003csup\u003e#\u003c/sup\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Pearson Correlation Analysis Among Parameters in the OP Group\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, there were positive correlations between Tb.Th, Tb.N, BV/TV and the elastic modulus and hardness of trabecular bone, while Tb.Sp exhibited negative correlations with these parameters. The strongest correlation was found between Tb.Th and elastic modulus (r\u0026thinsp;=\u0026thinsp;0.938, P\u0026thinsp;=\u0026thinsp;0.000) and hardness (r\u0026thinsp;=\u0026thinsp;0.921, P\u0026thinsp;=\u0026thinsp;0.000). Moreover, Tb.Th, Tb.N, BV/TV, elastic modulus, and hardness were positively correlated with lumbar L\u003csub\u003emax\u003c/sub\u003e, while Tb.Sp showed a negative correlation with L\u003csub\u003emax\u003c/sub\u003e. The strongest correlation was observed between trabecular elastic modulus and lumbar L\u003csub\u003emax\u003c/sub\u003e (r\u0026thinsp;=\u0026thinsp;0.940, P\u0026thinsp;=\u0026thinsp;0.000). OC, PINP, and CTX-I all exhibited negative correlations with lumbar Lmax, with OC showing the strongest correlation (r = -0.966, P\u0026thinsp;=\u0026thinsp;0.000). Additionally, OC, PINP, and CTX-I were negatively correlated with Tb.Th and elastic modulus, with the strongest correlations seen between CTX-I and elastic modulus (r = -0.963, P\u0026thinsp;=\u0026thinsp;0.000) and Tb.Th (r = -0.954, P\u0026thinsp;=\u0026thinsp;0.000).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Multiple Linear Regression\u003c/h2\u003e \u003cp\u003eThe results of the multiple linear regression analysis among parameters are presented in Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Both Tb.Th and the elastic modulus of trabecular bone showed positive correlations with L\u003csub\u003emax\u003c/sub\u003e, with the strongest correlation between elastic modulus and L\u003csub\u003emax\u003c/sub\u003e (β\u0026thinsp;=\u0026thinsp;0.594, P\u0026thinsp;=\u0026thinsp;0.002). CTX-I exhibited negative correlations with both Tb.Th and the elastic modulus, with the strongest correlation observed between CTX-I and elastic modulus (β = -0.963, P\u0026thinsp;=\u0026thinsp;0.000). OC also showed a negative correlation with L\u003csub\u003emax\u003c/sub\u003e (β = -0.966, P\u0026thinsp;=\u0026thinsp;0.000).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression Analysis of Microstructural Parameters with L\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandardized Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTb.Th\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e715.881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElastic Modulus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression Analysis of OC with L\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandardized Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression Analysis of CTX-I with Tb.Th and Elastic Modulus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTb.Th\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eElastic Modulus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandardized Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStandardized Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTX-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eAs age increases, bone loss may occur, leading to an increased incidence of osteoporosis (OP). Therefore, as a chronic, long-term bone disorder, OP is more common among the elderly, typically affecting males over the age of 65 and females over the age of 55\u003csup\u003e13\u003c/sup\u003e. Patients with vertebral compression fractures (VCF) face a significantly increased risk of subsequent fractures, making OP fractures a strong and independent risk factor\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These fractures severely impact quality of life and safety.\u003c/p\u003e \u003cp\u003eThis study primarily investigates the changes in bone turnover markers (BTMs), microstructural properties of lumbar trabecular bone, micro-mechanical characteristics, and their correlation with macro-mechanical strength throughout the OP process. We successfully established an OP rabbit model using the traditional ovariectomy (OVX) and glucocorticoid (GC) method, examining the temporal variations in BMD, microstructural properties, micro-mechanical characteristics, BTMs, and macro-mechanical strength over a four-month postoperative period. The observed progressive changes in the OP group indicate worsening osteoporosis. The longer the duration of OVX and GC treatment, the more severe the osteoporosis.\u003c/p\u003e \u003cp\u003eCurrently, ovariectomized rats are the most commonly used animal model for OP\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, this model has limitations: rats do not experience natural menopause and cannot achieve true skeletal maturity. Additionally, their small size limits complete epiphyseal closure and Haversian remodeling\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In contrast, rabbits exhibit active Haversian remodeling, reach skeletal maturity within a shorter period of six to eight months, and are easier to feed and manage compared to larger animals. Therefore, rabbits were chosen for our OP model\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eResearch indicates that the impact of OP progression on trabecular microstructure is greater than that on cortical bone\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, with trabecular bone being crucial for microstructural studies. Currently, with the increased availability of high-resolution imaging technologies such as Micro-CT, measuring trabecular spatial structure has become a routine method. The main indicators for observing trabecular structure include BV/TV, Tb.Th, Tb.Sp, and Tb.N\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In the study, we used Micro-CT to scan the lumbar vertebrae and measured the changes in these four linear indicators BV/TV, Tb.Th, Tb.Sp, Tb.N as OP progressed. As OP advanced, BV/TV, Tb.Th, and Tb.N showed significant declines, while Tb.Sp significantly increased, which is consistent with the findings of Divya et al\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In our study, compared to the Sham group, there was a significant difference in BMD in the OP group at two months post-surgery, while the Micro-CT measurement of Tb.N showed significant differences from the Sham group as early as one month post-surgery. This indicates that Micro-CT has higher sensitivity for detecting changes in trabecular bone mass. Additionally, compared to Tb.N, BV/TV, Tb.Th, and Tb.Sp only began to show significant changes at two months post-surgery, indicating that early changes in the spatial structure of trabecular bone during the OP process were primarily characterized by a reduction in trabecular number, while later changes were mainly reflected in decreases in volume, thinning of trabeculae, and widening of trabecular spacing.\u003c/p\u003e \u003cp\u003eNanoindentation is currently the only method available for accurate micro-mechanical analysis of trabecular bone\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The elastic modulus is a critical indicator of bone strength, reflecting the ability of bone to resist elastic deformation under load\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Our study found significant declines in both elastic modulus and hardness starting 1 month post-surgery, corroborating findings from other researchers like Li et al.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, indicating early significant declines in microstructural strength and hardness in OP. It is worth mentioning that in the study by Wen et al.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, the nanoindentation method was found to detect changes in bone quality in osteoporotic rabbit models earlier than other conventional methods (Micro-CT, BMD), which differs from our findings. In our study, both Tb.N measured by Micro-CT and the elastic modulus and hardness of trabecular bone measured by nanoindentation showed significant changes starting from 1 month post-surgery. This indicates that the timing of changes in microstructural properties and micro-mechanical characteristics at the microscopic level is similar, suggesting that nanoindentation does not demonstrate greater sensitivity than Micro-CT in detecting changes in the quality of lumbar trabecular bone. In the study by Li et al., analysis of the femoral condyle revealed that the elastic modulus and hardness of cortical bone trabeculae showed significant changes starting at 4 weeks, while their microstructural properties and BMD only changed significantly after 6 weeks. We believe the differences may arise from the different anatomical sites studied, indicating that the timing of changes in trabecular bone may vary across different anatomical locations, which requires further validation.\u003c/p\u003e \u003cp\u003eOP significantly increases overall bone brittleness, raising fracture risk. Lumbar L\u003csub\u003emax\u003c/sub\u003e represents the maximum force the vertebra can withstand before fracturing, serving as a key indicator of macro-mechanical performance\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Our findings demonstrate a significant reduction in L\u003csub\u003emax\u003c/sub\u003e as OP progressed, consistent with previous studies\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Notably, while elastic modulus, hardness, and Tb.N showed significant changes at 1 month post-surgery, L\u003csub\u003emax\u003c/sub\u003e did not decline until 2 months post-surgery, suggesting that early macro-mechanical strength changes are primarily driven by alterations in trabecular thickness, spacing, and volume\u0026mdash;areas warranting further investigation.\u003c/p\u003e \u003cp\u003eWhile we explored changes in microstructural properties, micro-mechanical characteristics, and macro-mechanical strength, the interplay between these factors remains unclear. Studies suggest that the relationship between trabecular microstructure and its elastic modulus and hardness depends on one or more microstructural features\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. We conducted correlation analyses between BV/TV, Tb.Th, Tb.Sp, Tb.N and L\u003csub\u003emax\u003c/sub\u003e, as well as trabecular elastic modulus and hardness. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Tb.Th has the strongest correlation with L\u003csub\u003emax\u003c/sub\u003e (r\u0026thinsp;=\u0026thinsp;0.926, P\u0026thinsp;=\u0026thinsp;0.000), trabecular elastic modulus (r\u0026thinsp;=\u0026thinsp;0.938, P\u0026thinsp;=\u0026thinsp;0.000), and hardness (r\u0026thinsp;=\u0026thinsp;0.921, P\u0026thinsp;=\u0026thinsp;0.000). When analyzing the correlation between trabecular elastic modulus and hardness with L\u003csub\u003emax\u003c/sub\u003e, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the elastic modulus (r\u0026thinsp;=\u0026thinsp;0.940, P\u0026thinsp;=\u0026thinsp;0.000) was found to be the strongest correlated factor. These results indicate that among the micro-mechanical properties of bone, changes in elastic modulus are most closely associated with macro-mechanical strength, while Tb.Th is the factor most strongly correlated with both micro-mechanical properties and macro-mechanical strength. However, it remains unclear whether these two factors influence macro-mechanical strength and which indicator better reflects changes in bone strength. Therefore, we conducted further analysis. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, multiple linear regression reveals that both Tb.Th (β\u0026thinsp;=\u0026thinsp;0.369, P\u0026thinsp;=\u0026thinsp;0.038) and trabecular elastic modulus (β\u0026thinsp;=\u0026thinsp;0.594, P\u0026thinsp;=\u0026thinsp;0.002) are positively correlated with L\u003csub\u003emax\u003c/sub\u003e, indicating that both Tb.Th and trabecular elastic modulus correlate strongly with macroscopic mechanical strength. Additionally, the impact of trabecular elastic modulus on macro-mechanical strength is greater than that of Tb.Th; the higher the elastic modulus, the greater the bone strength and the lower the risk of fractures.\u003c/p\u003e \u003cp\u003eBTMs are biomarkers used to detect dynamic bone remodeling in blood or urine\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, reflecting the status of bone resorption and bone formation\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Current research focuses on the differences between BMD and BTMs; however, BMD explains only about 60%-70% of bone strength variability\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, indicating that analyzing BTMs in isolation from microstructural and mechanical properties may not accurately reflect changes in bone strength. Further integration of BTMs with microstructural and mechanical analyses is essential for a comprehensive understanding of bone health.\u003c/p\u003e \u003cp\u003eOC is one of the bone formation markers and a specific indicator reflecting bone formation. CTX-I and PINP are highly sensitive markers of bone turnover metabolism\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, with CTX-I being more sensitive\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e to differences in femoral neck bone mass and strength. PINP reflects the rate of type I collagen synthesis and the state of bone turnover; higher levels of PINP indicate more active bone turnover\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This study shows that serum levels of OC, CTX-I, and PINP in the OP group are significantly higher than in the Sham group, consistent with previous findings\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. This indicates that serum OC, CTX-I, and PINP can reflect changes in bone metabolism and mass, aiding in the early diagnosis and treatment of OP. In our study, both CTX-I and PINP began to increase significantly from 1 month post-surgery, while OC showed significant changes starting from the second month post-surgery. The delayed response of OC may be related to the use of dexamethasone. Studies have shown that prolonged use of glucocorticoids (GC) can impair osteoblast function, leading to decreased osteocalcin (OC) levels. This is due to targeted disruption of GC signaling in osteoblasts, weakening the inhibition of OC synthesis and halting OC production. Research by Dovio\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e et al. indicated that high-dose, short-term GC use in humans immediately reduces OC and PINP levels while rapidly and briefly increasing CTX-I levels, which appears somewhat different from our results. Upon analyzing the reasons for these differences, we believe that firstly, the GC dosage used in their study was 15 mg/kg per day, significantly higher than the dosage we utilized. Studies have suggested that GC doses ranging between 0.5 and 1 mg/(kg\u0026middot;d) are effective only for bone turnover without affecting inflammation, necrosis, or subchondral bone changes, while doses below 0.5 mg/(kg\u0026middot;d) do not significantly impact bone alterations\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Furthermore, Dovio et al. measured OC, CTX-I, and PINP daily during treatment (10 days) and three months later. The results indicated that during treatment, OC and PINP immediately decreased starting from the second day, while CTX-I continued to significantly increase. Three months later, the levels of all bone turnover markers (BTMs) showed a significant increase. In our study, the first postoperative measurement was taken one month later, so we are uncertain if OC and PINP decreased during this period. However, three months later, all BTMs showed a significant increase, which is somewhat consistent with our results.\u003c/p\u003e \u003cp\u003eAlthough serum BTMs can reflect changes in bone metabolism and bone mass, it is still unclear which marker best reflects their correlation with bone quality and strength. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, we conducted a correlation analysis between OC, CTX-I, PINP, and lumbar spine Lmax. The results showed that OC had the strongest negative correlation with L\u003csub\u003emax\u003c/sub\u003e (r=-0.966, P\u0026thinsp;=\u0026thinsp;0.000), indicating that OC could serve as a representative marker for assessing bone quality in macroscopic mechanics. We further analyzed the correlations of OC, CTX-I, and PINP with microstructural parameters and micro-mechanical properties that are strongly related to macroscopic mechanical strength, such as Tb.Th and trabecular elastic modulus. The results showed that CTX-I had the strongest correlation with trabecular elastic modulus (r=-0.963, P\u0026thinsp;=\u0026thinsp;0.000) and Tb.Th (r=-0.954, P\u0026thinsp;=\u0026thinsp;0.000). Subsequently, we performed multiple linear regression analyses of OC with L\u003csub\u003emax\u003c/sub\u003e, CTX-I with Tb.Th, and trabecular elastic modulus. As shown in Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the correlation between CTX-I and trabecular elastic modulus (β=-0.963, P\u0026thinsp;=\u0026thinsp;0.000) was the strongest. OC had a negative correlation with L\u003csub\u003emax\u003c/sub\u003e (β=-0.966, P\u0026thinsp;=\u0026thinsp;0.000), indicating that OC was the most influential factor related to macroscopic mechanical strength, while CTX-I was the most influential factor related to microstructural properties and micro-mechanical characteristics. Therefore, from a macroscopic perspective, in the process of OP, a higher OC value corresponds to lower L\u003csub\u003emax\u003c/sub\u003e in the lumbar spine, suggesting a more severe degree of OP. From a microscopic analysis, a higher CTX-I value correlates with thinner trabeculae, lower elastic modulus, and hardness. The limitations of our experiment include the discussion of only linear indices for microstructural parameters and the lack of further discussion on nonlinear indices, as well as the absence of discussion on microchemical composition. Additionally, our study was limited to animal models without clinical validation. There are limitations to the generalization of the findings to human osteoporosis due to physiological differences between humans and rabbits. First, the bone metabolic rate in rabbits is much higher than that in humans, leading to the possibility that the short-term effects of pharmacological interventions may be magnified without accurately reflecting the pathological process of chronic osteoporosis in humans\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Second, rabbits have a 15\u0026ndash;20% higher cortical bone porosity than humans and a different pattern of cancellous bone density distribution, affecting the comparability of drug diffusion kinetics\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In addition, the distribution of mechanical loads in quadrupeds results in the distal femur, rather than the femoral neck, being the main load-bearing area, which is an anatomical deviation from the high prevalence of osteoporotic fractures in humans\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Therefore, in future research, we will incorporate non-linear parameters and clinical serum data for further exploration to improve our findings.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn the process of OP, lumbar BMD, L\u003csub\u003emax\u003c/sub\u003e, trabecular elastic modulus, hardness, BV/TV, Tb.Th, Tb.N, and BTMs gradually decrease over time, while Tb.Sp gradually increases. Early changes in trabecular spatial structure are primarily characterized by a significant reduction in trabecular number, later accompanied by significant decreases in trabecular thickness, increased spacing, and reduced volume. Tb.Th shows the strongest correlation with micro-mechanical properties. Trabecular elastic modulus has the most significant impact on macro-mechanical strength. We hypothesize that the elastic modulus of lumbar trabecular bone can be a predictive factor for vertebral OP fractures. For BTMs, CTX-I shows the strongest correlation with microstructure and micromechanical properties of the lumbar spine, while OC shows the strongest correlation with macro-mechanical strength. Early detection of CTX-I helps us understand changes in the microstructural and micro-mechanical properties of lumbar trabecular bone during the process of OP, while early detection of OC assists in understanding changes in macro-mechanical strength. These findings provide new research ideas and theoretical foundations for more comprehensive clinical assessments of spinal OP severity and the prevention of spinal OP fractures.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANOVA: Analysis of variance; BMD: Bone mineral density; CTX-I: C-terminal telopeptide of type I collagen; DXA: Dual energy X-ray absorptiometry; ELISA: Enzyme-linked immunosorbent assay; OC: Osteocalcin; OP: Osteoporosis; PINP: Type I procollagen N-terminal propeptide; BTMs: Bone turnover markers; BV/TV: bone volume fraction; Tb.Th: trabecular thickness; Tb.Sp: trabecular spacing; Tb.N: number of trabeculae; OVX: ovariectomy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAll methods are reported in accordance with ARRIVE guidelines.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal experiments were approved by the Animal Ethics Committee of the General Hospital of Western Theater Command (2022EC2-ky045) . Moreover, all applicable rules and regulation of the organization and government were followed regarding the ethical use of experimental animal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author Da Liu on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Cadre health committee Program of China (21BJZ40) and\u0026nbsp;、\u0026nbsp;(2022NSFSC0664) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYuhao Jia, Ning Xia, Jian Zhao, Wei Xu, Wei Wang, hailong Yu, Da Liu and Yingbo Zhang\u003c/p\u003e\n\u003cp\u003edeclare that they have no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermission to reproduce material from other sources\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References 1","content":"\u003col\u003e\n\u003cli\u003eChai H, Ge J, Li L, Li J, Ye Y. 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Laboratory aspects and clinical utility of bone turnover markers. \u003cem\u003eEJIFCC\u003c/em\u003e. 2018;29(2):117-128.\u003c/li\u003e\n\u003cli\u003eFlorez H, Hern\u0026aacute;ndez-Rodr\u0026iacute;guez J, Carrasco JL, et al. Low serum osteocalcin levels are associated with diabetes mellitus in glucocorticoid treated patients. \u003cem\u003eOsteoporos Int\u003c/em\u003e. 2022;33(3):745-750. doi:10.1007/s00198-021-06167-z\u003c/li\u003e\n\u003cli\u003eDovio A, Perazzolo L, Osella G, et al. Immediate fall of bone formation and transient increase of bone resorption in the course of high-dose, short-term glucocorticoid therapy in young patients with multiple sclerosis. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e. 2004;89(10):4923-4928. doi:10.1210/jc.2004-0164\u003c/li\u003e\n\u003cli\u003eEberhardt AW, Yeager-Jones A, Blair HC. Regional trabecular bone matrix degeneration and osteocyte death in femora of glucocorticoid- treated rabbits. \u003cem\u003eEndocrinology\u003c/em\u003e. 2001;142(3):1333-1340. doi:10.1210/endo.142.3.8048\u003c/li\u003e\n\u003cli\u003eDuggal D, Nagwekar J, Rich R, et al. Phosphorylation of myosin regulatory light chain has minimal effect on kinetics and distribution of orientations of cross bridges of rabbit skeletal muscle. \u003cem\u003eAm J Physiol Regul Integr Comp Physiol\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eHarrison KD, Hiebert BD, Panahifar A, et al. Cortical Bone Porosity in Rabbit Models of Osteoporosis. \u003cem\u003eJ Bone Miner Res\u003c/em\u003e. 2020;35(11):2211-2228.\u003c/li\u003e\n\u003cli\u003eKimura M, Nakase J, Takata Y, et al. Regeneration Using Adipose-Derived Stem Cell Sheets in a Rabbit Meniscal Defect Model Improves Tensile Strength and Load Distribution Function of the Meniscus at 12 Weeks. \u003cem\u003eArthroscopy\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"References 2","content":"\u003col\u003e\n\u003cli\u003eBaofeng L, Zhi Y, Bei C, Guolin M, Qingshui Y, Jian L. Characterization of a rabbit osteoporosis model induced by ovariectomy and glucocorticoid. \u003cem\u003eActa Orthop\u003c/em\u003e. 2010;81(3):396-401.\u003c/li\u003e\n\u003cli\u003eOki Y, Doi K, Kobatake R, et al. Histological and histomorphometric aspects of continual intermittent parathyroid hormone administration on osseointegration in osteoporosis rabbit model. \u003cem\u003ePLoS One\u003c/em\u003e. 2022;17(6):e0269040.\u003c/li\u003e\n\u003cli\u003ePermuy M, L\u0026oacute;pez-Pe\u0026ntilde;a M, Mu\u0026ntilde;oz F, Gonz\u0026aacute;lez-Cantalapiedra A. Rabbit as model for osteoporosis research. \u003cem\u003eJ Bone Miner Metab\u003c/em\u003e. 2019;37(4):573-583.\u003c/li\u003e\n\u003cli\u003eDuggal D, Nagwekar J, Rich R, et al. Phosphorylation of myosin regulatory light chain has minimal effect on kinetics and distribution of orientations of cross bridges of rabbit skeletal muscle. \u003cem\u003eAm J Physiol Regul Integr Comp Physiol\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eHarrison KD, Hiebert BD, Panahifar A, et al. Cortical Bone Porosity in Rabbit Models of Osteoporosis. \u003cem\u003eJ Bone Miner Res\u003c/em\u003e. 2020;35(11):2211-2228.\u003c/li\u003e\n\u003cli\u003eKimura M, Nakase J, Takata Y, et al. Regeneration Using Adipose-Derived Stem Cell Sheets in a Rabbit Meniscal Defect Model Improves Tensile Strength and Load Distribution Function of the Meniscus at 12 Weeks. \u003cem\u003eArthroscopy\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rabbit, Osteoporosis, Micro-mechanics, Microstructure, Macro-mechanics, Bone turnover markers","lastPublishedDoi":"10.21203/rs.3.rs-6161804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6161804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eSummary: \u003c/strong\u003eThis 4-month study was conducted in 64 white rabbits.The correlation between the microstructure, micro-mechanical properties and macroscopic mechanical strength of BTMs, bone trabeculae was investigated. CTX-I showed the strongest correlation with microstructure and micromechanical properties, while OC showed the strongest correlation with macroscopic mechanical strength.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To investigate the variation patterns and correlations among serum bone turnover markers (BTMs), microstructure of trabecular bone, micro-mechanical properties, and macro-mechanical strength during the process of osteoporosis, and to identify BTMs that show strong correlations with all three.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 64 female New Zealand white rabbits were randomly divided into a sham surgery group (Sham group, n=32) and an osteoporosis model group (OP group, n=32). Rabbits in both groups were further randomly assigned to baseline (Pre-ovx), and three subsequent groups at 1, 2, and 4 months (n=8 each). Bone mineral density (BMD) was measured at Pre-ovx, and 1, 2, and 4 months post-surgery. Serum BTMs were collected from arterial blood, and lumbar vertebrae specimens were obtained to measure the microstructure, micro-mechanical properties, and macro-mechanical strength of trabecular bone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eBMD, maximum load (L\u003csub\u003emax\u003c/sub\u003e), elastic modulus of trabecular bone, hardness, trabecular thickness (Tb.Th, mm), trabecular number (Tb.N, 1/mm), and bone volume fraction (BV/TV, %) gradually decreased, while trabecular space (Tb.Sp, mm), osteocalcin (OC), type I procollagen N-terminal propeptide (PⅠNP), and C-terminal telopeptide of type I collagen (CTX-I) gradually increased. Multiple linear regression showed that Tb.Th (β=0.369, P=0.038) and the elastic modulus of trabecular bone (β=0.594, P=0.002) were positively correlated with Lmax, while CTX-I was negatively correlated with both Tb.Th (β=-0.953, P=0.002) and the elastic modulus of trabecular bone (β=-0.963, P=0.000). OC was negatively correlated with L\u003csub\u003emax\u003c/sub\u003e (β=-0.966, P=0.000).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The elastic modulus of trabecular bone has the most significant impact on macro-mechanical strength. CTX-I showed the strongest correlation with microstructure and micromechanical properties, while OC showed the strongest correlation with macroscopic mechanical strength.\u003c/p\u003e","manuscriptTitle":"Variation Patterns and Correlation Between BTMs and Microparameters of Trabecular Bone and Macro－mechanical Strength of Lumbar Vertebrae","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 06:49:40","doi":"10.21203/rs.3.rs-6161804/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-22T04:29:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T21:21:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T07:18:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230292126487523176982440607202035820547","date":"2025-03-24T19:40:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296583453177940140903146530050363280895","date":"2025-03-24T15:55:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-18T08:59:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-18T06:00:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-18T02:37:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-18T02:32:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Musculoskeletal Disorders","date":"2025-03-05T10:39:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"991acd3d-b48f-4fc0-9f31-32fbeb48dc24","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-06T15:10:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-31 06:49:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6161804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6161804","identity":"rs-6161804","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}