Correlation of serum bone turnover markers with microstructure and macroscopic mechanical strength of lumbar cancellous bone during progression of osteoporosis

Correlation of serum bone turnover markers with microstructure and macroscopic mechanical strength of lumbar cancellous bone during progression of osteoporosis | 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 Correlation of serum bone turnover markers with microstructure and macroscopic mechanical strength of lumbar cancellous bone during progression of osteoporosis Yuhao Jia, Ning Xia, Wei Xu, Wei Wang, Jian Zhao, Ling Wang, Da Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3863396/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper established an osteoporotic rabbit model by depopulation and the glucocorticoid method, investigated the weights of bone micro-parameters in macro-mechanics during OP progression, preliminary elucidated micro-mechanisms, and screened out bone turnover markers (BTMs) that have a strong correlation with bone macro-mechanical strength and microscopic spatial structure to provide the theoretical basis for OP and OP fracture. Methods: 64 female White rabbits were chosen and assigned to two groups: one that underwent a sham operation (Sham group, n = 32) and the other that served as an osteoporosis model (OP group, n = 32). At four different postoperative time points (T = 0, 1, 2, and 4 months), respectively. The white rabbits in the Sham group and the OP group were randomly divided into four groups (n = 8) each. Dual-energy X-ray absorptiometry (DXA) was used to determine the lumbar bone mineral density (BMD) at various time intervals (T = 0, 1, 2, and 4 months), and serum BTMs were found using an ELISA test after blood was drawn and the animals were put to death. Axial compression testing and micro-CT were used to assess and characterise the cancellous bone in the lumbar spine specimens. Results: Lumbar BMD, lumbar Lmax, Tb.Th, Tb.N, and BV/TV all steadily declined as OP progressed, while OC, PINP, CTX, and Tb.Sp all gradually rose. All bone microspatial characteristics were strongly linked with Lmax (p = 0.000) according to a person linear correlation analysis, with the best association found between Tb.Th and lumbar Lmax (r = 0.924, p = 0.000). PINP and OC had the strongest connections with lumbar Lmax (r = -0.958, p = 0.000), whereas CTX had the strongest correlation with Tb.Th (r = -0.955, p = 0.000), according to a correlation analysis of serum BTMs with bone strength and sensitive microspatial measures. Conclusion: All lumbar cancellous bone microspatial parameters were correlated with macroscopic mechanical strength during OP progression, with Tb.Th having the strongest correlation. For BTMs, CTX had the strongest correlation with microspatial structure, and PINP and OC had the strongest correlation with macroscopic mechanical strength. Rabbit Osteoporosis Spinal osteoporotic fracture Macromechanics Microspatial structure Bone turnover markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Osteoporosis (OP) is a skeletal condition marked by a loss of bone mass and deterioration of the bone's microstructure, which increases bone fragility and fracture risk. 1 Osteoporotic fracture is a severe complication of OP and a major health concern for the world's ageing population. In China, the incidence of osteoporotic fractures is 13%. By 2035, the number of osteoporosis-related fractures is projected to reach 4.83 million, at a cost of approximately $19.92 billion annually. 2 Vertebral compression fractures (VCF) are the most common form of osteoporotic fracture because vertebral bone density decreases with age, and they are more prevalent in the elderly. 3,4 In China, the incidence of vertebral fracture is approximately 15% in women over 50 and 36.6% in women over 80. 5 Symptomatic osteoporotic fractures of the spine frequently result in severe back pain, spinal deformity, decreased mobility and lung function, and an increased risk of mortality with advancing age. 6 Consequently, investigating the microscopic mechanism of spinal osteoporotic fracture can prevent the development of spinal osteoporosis. Changes in the spatial structure of cancellous trabeculae during the OP process can substantially affect the overall mechanical strength of bone, according to previous research. 7,8 Currently, scholars at home and abroad mainly use high-resolution imaging techniques such as micro-CT to study the microspatial structure of bone trabeculae, 9,10 and relevant studies have shown that bone turnover markers (BTMs) can dynamically reflect bone remodelling. However, the conclusions of these studies are controversial because of the wide variety of markers and the susceptibility of the assay to environmental and methodological factors. Moreover, it is still unclear which specific BTMs are more sensitive to indicating fracture risk. Furthermore, current studies have focused more on the macroscopic level, i.e., the correlation between BMD (or bone mineral content) and the macroscopic mechanical strength of bone, while there is a lack of research on the study of microscopic parameters and BMD, as well as the weighting of microscopic parameters in the role of macroscopic mechanical strength. Therefore, the aim of the present study was to establish a rabbit model of osteoporosis by depopulation combined with the glucocorticoid method and to investigate the weights of bone microstructural parameters in the lumbar spine maximum load (L max ), to describe the microscopic mechanism of spinal osteoporosis, and, through further study and correlation analysis with bone turnover markers (BTMs), to select bone turnover markers with a strong correlation with bone mineral density. Materials and methods Animals Byrness Weil Biotech Ltd. (Chengdu, China) provided 64 female New Zealand white rabbits of pure breed and 7 months of age for this study. Their body weight ranged from 2.87 to 3.37 kg. These experiments were approved by the General Hospital of Western Theatre Ethics Committee and adhered to the Animal Care and Use Guidelines by housing the rabbits individually in stainless steel cages in a standard animal facility with room temperature maintained between 21 and 24 degrees Celsius, relative humidity between 40 and 60 percent, a 12-hour light/dark cycle, with a light cycle consistent with daytime, and diet (standard commercial rabbit food) and running water provided ad libitum. Establishment of osteoporotic rabbit model After the rabbits had acclimated to their new environment for 2 weeks, each animal was randomly assigned to either the sham operation group (n = 32) or the osteoporosis model group (n = 32). To obtain baseline data (pre-ovx), including BMD, PINP, OC, CTX-I, Tb.N., Tb.Th., Tb.Sp., BV/TV, and biomechanical assays, eight rabbits from each group were randomly selected and executed via air embolisation of the marginal ear vein. Animals in the OP group were starved for 12 hours prior to surgery and underwent bilateral ovariectomy (OVX) with isoflurane (Reward, Shenyang, China). During the operation, both ovaries were exposed in the Sham group, and the abdomen was then closed and sutured. All animals were administered 10,000 U/kg of intramuscular gentamicin (Solarbio, Beijing, China) twice per day for three days to prevent infection. Two weeks after surgery, animals in the OP group received intramuscular dexamethasone 0.5 mg/kg (Yiduoli, Shanxi, China) twice a week for four weeks. The animals were divided into 1-month, 2-month, and 4-month groups, with 8 animals in each group. Lumbar BMD was measured by dual-energy X-ray absorptiometry (DXA) at 1, 2, and 4 months postoperatively, after which the rabbits were euthanized by intravenous injection of excess air into the ear margins, and specimens of lumbar vertebrae (L1–L5) were collected and frozen at -80 °C. Lumbar Bone Density Test Lumbar spine BMD was determined utilizing a DXA (Lunar Prodigy Advance; GE Lunar, Madison, WI, USA), and DXA scans were analyzed at the corresponding time points (pre-ovx, 1 month, 2 months, and 4 months) prior to the execution of each group of animals. Each rodent was placed in the prone position on a DEXA table under general anaesthesia for BMD measurement. OP was diagnosed by a BMD value in the OP group that was lower than the mean value in the Sham group at the same time point minus 2.5 SD and combined with bone microstructural alterations. 11 Micro-CT scanning and reconstruction analysis The lumbar vertebrae of rabbits were removed from the refrigerator at -80°C, thawed at room temperature, and the muscles, intervertebral discs, and fascia were removed, along with the transverse processes and spinous processes. L5 vertebrae were selected, scanned, and analysed using a Quantum GX Micro-CT scanner (PerkinElmer, USA). Utilise the following image retrieval parameters: Energy/intensity was 80 kV, 100 μA, 8 W, angular increment was 0.5°, and scantime was 4 minutes. Scanning is performed by rotating from 0°, and a reorganisation image is obtained after scanning is complete. Tb.N, Tb.Th, Tb.Sp, and BV/TV were analysed using Avatar software (version 2.0.0.1, PINGSENG Healthcare lnc). Biomechanical testing The lumbar vertebrae were thawed at room temperature, and the L4 vertebral body was selected, followed by the removal of the musculature, intervertebral discs, and fascia. The two endplates of the vertebral body were removed using a low-speed precision diamond saw with continuous irrigation, as well as the transverse processes and spinous processes. By grinding the upper and lower planes parallel to each other, the central portion of the vertebral body with parallel ends was obtained; this central section consists of a central trabecular core and a compact housing. Utilising the MTS Model 809 axial/torsional testing system (MTS Systems Corp., USA), tensile experiments were conducted. The MTS testing machine was equipped with an axial hydraulic actuator with a 200 kN axial capacity. The sample is deposited in the test stand and statically preloaded for 30 seconds with a force of 10N. Subsequently, the compression test was conducted at a speed of 0.02 mm/s until a clear peak appeared, after which the maximal load (L max ) was automatically determined by the software included with the apparatus. All phases of this investigation were conducted at a temperature of 23 ± 0.2°C. Serum BTMs test Blood samples were collected from the central auricular artery one week prior to the respective time points (pre-ovx, 1 month, 2 months, and 4 months). Collect blood samples between 7 a.m. and 10 a.m. the next morning after fasting the rabbit overnight before blood collection. Centrifuged immediately, and the serum was separated and stored at -80 °C until analysis. For analysis, samples were thawed at room temperature, 50 μL of samples and standards were added to 96-well plates, and an enzyme-linked immunosorbent assay (R&D Systems, Minneapolis, MN) was used to detect serum levels of OC, PINP, and CTX. Unless duplicate measurements of individual values were required, all samples were processed using the same assay. All procedures were carried out according to the kit's instructions. Statistical analysis Statistical analyses were performed using SPSS 26.0, and all data conformed to a normal distribution and were expressed as mean ± standard deviation. Comparisons of the relevant parameters between the Sham and OP groups within the same time point were performed using an independent samples t test (indent-pendent-samples t test). While comparisons between different time points within the same group were performed using one-way ANOVA, the LSD method was used if the variance was homogeneous, and the Tammany method was used if the variance was not homogeneous. Pearson linear correlation analysis was used to analyse the microspatial parameters and macroscopic mechanical strength of cancellous bone, and the strongest correlation between microspatial parameters and macroscopic mechanical strength was identified, the resulting metrics were then analysed by Pearson linear correlation analysis with bone turnover markers, and the bone turnover markers with the strongest correlation with microstructure were identified, finally, Pearson linear correlation analysis was performed between the bone turnover markers and the macroscopic mechanical strength, and the bone turnover markers with the strongest correlation with the macroscopic mechanical strength were identified. Differences were considered statistically significant at p < 0.05. Results Lumbar spine BMD Table 1 Results of lumbar BMD (g / cm²) Groups Pre - ovx 1 months 2 months 4months Sham (n = 8) 0.277 ± 0.06 0.278 ± 0.04 0.279 ± 0.04 0.282 ± 0.03 OP (n = 8) 0.275 ± 0.08 0.273 ± 0.05 0.232 ± 0.08 *** 0.172 ± 0.06 *** Data are expressed as mean ± standard deviation of BMD (n = 8). *** P < 0.0001, the difference was statistically significant. As shown in Table 1, the values of BMD in the OP group showed a gradual decrease with increasing time, there was a statistical difference between all time points in the OP group, except for no statistical difference between the pre-ovx and 1 months groups (p < 0.0001), there was a significant difference in lumbar BMD values between the OP group and the Sham group at the same time point at 2 and 4 months postoperatively (p < 0.0001), the difference was statistically significant, but only at postoperative month 4, the BMD value in the OP group was smaller than that in the Sham group minus 2.5 SD in the same period, the lumbar spine BMD values in the OP group decreased by 39 % compared to the sham group. The difference was not statistically significant in the sham group (p > 0.05). Biomechanical testing Table 2 Results of biomechanical parameters of lumbar spine (N) Groups Pre-ovx 1 months 2 months 4 months Sham(n=8) 677 ± 51 685 ± 39 691 ± 28 691 ± 57 OP (n=8) 667 ± 44 613 ± 23 * 490 ± 34 *** 331 ± 34 *** Data are expressed as mean ± standard deviation of Maximum load (n=8). * P < 0.05, the difference was statistically significant, ** P < 0.001, the difference was statistically significant, *** P < 0.0001, the difference was statistically significant. As shown in Table 2, with the exception of the pre-ovx group, the maximal loads of the OP group were significantly lower than those of the Sham group at all time points, decreasing by 10.5% (p < 0.05), 29% (p < 0.0001), and 52.2% (p < 0.0001), respectively, compared with those of the Sham group 1 month, 2 months, and 4 months after the operation and at the same time point. The Lmax of the OP group decreased gradually with time (Fig. 5), and the differences between OP groups at different time points were statistically significant (p 0.05). Serum BTMs test Table 3 Results of serum BTMs parameters (ng / mL) Times Groups OC PINP CTX Pre-ovx Sham 1.41 ± 0.07 2.91 ± 0.16 0.23 ± 0.03 op 1.42 ± 0.09 2.92 ± 0.07 0.23 ± 0.03 1 months Sham 1.42 ± 0.05 2.93 ± 0.15 0.24 ± 0.03 op 1.49 ± 0.07 3.59 ± 0.22 * 0.40 ± 0.02 *** 2 months Sham 1.41 ± 0.04 2.93 ± 0.13 0.22 ± 0.02 op 2.80 ± 0.37 *** 5.80 ± 0.32 *** 0.60 ± 0.03 *** 4 months Sham 1.42 ± 0.05 2.90 ± 0.15 0.23 ± 0.02 op 4.07 ± 0.24 *** 7.77 ± 0.34 *** 0.80 ± 0.03 *** Data are expressed as mean ± standard deviation of BTMs (n=8). * P < 0.05, the difference was statistically significant, ** P < 0.001, the difference was statistically significant, *** P < 0.0001, the difference was statistically significan. As shown in Table 3, PINP and CTX were significantly different between the OP group and the Sham group in all time periods except pre-ovx, in which PINP increased by 22.5 % (p < 0.05), 97.9 % (p < 0.0001), and 167.9 % (p < 0.0001) in each of the parameters in the postoperative months of 1, 2, and 4, respectively, compared with the Sham group in the same time period, and CTX increased by 66.7 % (p < 0.0001), 172.7 % (p < 0.0001), and 247.8 % (p < 0.0001), respectively. increased by 66.7% (p < 0.0001), 172.7% (p < 0.0001), and 247.8% (p < 0.0001), respectively. OC changed significantly from 2 months postoperatively, increasing by 98.6% (p < 0.0001) and 186.6% (p < 0.0001) at 2 and 4 months postoperatively, respectively. With the increase in time, the serum parameters of OC, PINP, and CTX in the OP group showed a gradual increase (Fig. 6), and the differences among the Sham groups were not statistically significant (p > 0.05). Micro-CT Testing Table 4 Results of micro-CT microstructural parameters of lumbar cancellous bone Times Groups BV/TV (%) Tb.Th (mm) Tb.N(1/mm) Tb.Sp(mm) Pre-ovx Sham 0.303 ± 0.030 0.233 ± 0.014 1.013 ± 0.061 0.769 ± 0.047 op 0.299 ± 0.024 0.228 ± 0.014 0.999 ± 0.068 0.781 ± 0.062 1 months Sham 0.295 ± 0.034 0.227 ± 0.015 0.974 ± 0.077 0.788 ± 0.057 op 0.236 ± 0.008 * 0.210 ± 0.003 * 0.865 ± 0.022 * 0.935 ± 0.023 *** 2 months Sham 0.303 ± 0.035 0.235 ± 0.016 0.995 ± 0.086 0.789 ± 0.080 op 0.221 ± 0.008 * 0.184 ± 0.005 *** 0.823± 0.013* 1.002 ± 0.002 *** 4 months Sham 0.313 ± 0.022 0.232 ± 0.018 1.003 ± 0.079 0.784 ± 0.072 op 0.174 ± 0.023 *** 0.147 ± 0.012 *** 0.689± 0.043 *** 1.243 ± 0.085 *** Data are expressed as mean ± standard deviation of Maximum load (n=8). * P < 0.05, the difference was statistically significant, ** P < 0.001, the difference was statistically significant, *** P < 0.0001, the difference was statistically significant. As shown in Table 4, except for pre-ovx, the parameters of the OP group were significantly different from those of the Sham group at all time periods, in which BV/TV decreased by 20% (p < 0.05), 27.1% (p < 0.05), and 44.4% (p < 0.0001), Tb.N decreased by 11.2% (p < 0.05), 17.3% (p < 0.05), and 31.3% (p < 0.0001), respectively, in the OP group, as compared with that of the Sham group at the same time. 11.2 % (p < 0.05), 17.3 % (p < 0.05), 31.3 % (p < 0.0001), and Tb.Th decreased by 7.5 % (p < 0.05), 21.7 % (p < 0.0001), and 36.6 % (p < 0.0001), respectively, while Tb.Sp increased by 15.7 %, 21.3 %, and 36.9% (p < 0.0001). With the increase in time, the BV/TV, Tb.Th, and Tb.N showed a decreasing trend, and Tb.Sp showed an increasing trend (Fig. 7). Differences between OP groups at different time points were statistically significant (p 0.05). Microstructural analysis of the lumbar spine As shown in Fig. 8, the (a)-(d) trabeculae were more abundant, tightly connected with each other to form a mesh, and structurally stable. In (e)-(h) , the spongy structure becomes more and more spongy as time progresses, the number of trabeculae decreases, the trabecular intervals increase, and the thickness becomes progressively thinner and more structurally discontinuous. Pearson correlation coefficients between parameters Table 5 Pearson's linear correlation analysis of microscopic parameters with BMD and lumbar L max Parameters BMD Lumbar L max Tb.Th r 0.936 0.924 p 0.000 0.000 Tb.Sp r -0.898 -0.891 p 0.000 0.000 Tb.N r 0.852 0.896 p 0.000 0.000 BV/TV r 0.816 0.846 p 0.000 0.000 BV/TV, bone volume fraction; Tb.Th, trabecular thickness; Tb.Sp, trabecular spacing; Tb.N, number of trabeculae As shown in Table 5, Tb.Th, Tb.N, and BV/TV were positively correlated with lumbar BMD and Lmax, and Tb.Sp was negatively correlated with lumbar BMD and Lmax. The strongest correlations were found between Tb.Th and lumbar BMD (r = 0.936, p = 0.000) and L max (r = 0.924, p = 0.000). Table 6 Pearson's linear correlation analysis of BTMs with L max of lumbar spine Parameters Lumbar L max OC r -0.958 p 0.000 CTX r -0.943 p 0.000 PINP r -0.958 p 0.000 OC, Osteocalcin; CTX, type I collagen cross-linked C-terminal peptide; PINP, type I procollagen N-terminal prepeptide As shown in Table 6, OC, CTX, and PINP were all negatively correlated with lumbar L max , with PINP and OC having the strongest correlation with lumbar L max (r = -0.958, p = 0.000). Table 7 Pearson's linear correlation analysis of BTMs and Tb.Th of bone Parameters Tb.Th OC r -0.918 p 0.000 CTX r -0.955 p 0.000 PINP r -0.935 p 0.000 OC, Osteocalcin; CTX, type I collagen cross-linked C-terminal peptide; PINP, type I procollagen N-terminal prepeptide As shown in Table 7, OC, CTX, and PINP were all negatively correlated with Tb.Th, with CTX having the strongest correlation with Tb.Th (r = -0.955, p = 0.000). Discussion In this study, we concentrated on the strength of the correlation between the lumbar cancellous bone's microspatial structure, macroscopic mechanical strength, and bone conversion indicators in the development of OP. The entire postoperative study observation process took place over a period of four months. We were successful in creating an osteoporosis model using the OVX combined with the GC method and investigated the micro-spatial structure of BMD, lumbar cancellous bone, macroscopic mechanical properties, and the changes of bone turnover markers over time. We find that Tb.Th has the strongest correlation with macroscopic mechanical strength, and for BTMs, CTX is the strongest correlate of microspatial structure, while PINP and OC are the strongest correlates of macroscopic mechanical strength. The most well-liked animal models for postmenopausal osteoporosis have been chosen by OVX in mice, rats, sheep, and nonhuman primates. On the other hand, the most widely used animal model for osteoporosis is ovariectomized rats. 12 The model does have several limitations, though, including the fact that rats lack a natural menopause and are unable to reach true skeletal maturity, as well as the fact that they are too tiny to fully close the epiphyseal plate and do not undergo Haversian remodelling. 13 Rabbits, on the other hand, are easier to grow and handle than other models and show active Haversian remodelling. They also have a shorter maturation time than larger animals, attaining full skeletal maturity in about six to eight months. 14 As a result, we decided to create an animal model of osteoporosis using rabbits. Although DXA is now the gold standard for measuring BMD and diagnosing OP, it has certain limitations. For example, DXA does not detect substantial changes in early BMD and only detects changes in bone loss when it reaches a particular level, 15 and secondly, changes in bone strength and fracture risk after clinical treatment cannot be adequately explained by BMD alone. 16 With the help of additional techniques, such as micro-computed tomography, biomechanics, and biomarkers of bone turnover, we may further validate BMD values and bone structure. 17 Living bones are mostly made of bone tissue, which is an organ whose quality as an organ is primarily determined by its macrostructure and whose quality as bone tissue is primarily determined by its composition and microstructure. By assessing a bone's biomechanics, we can often express the bone's mass. 18 Lumbar spine L max is the maximum force it can withstand before a fracture occurs and is an important measure of its biomechanical properties. 19 In our study, it was found that with the progression of OP, lumbar L max was significantly reduced, which is consistent with the results of previous studies. 20 However, current studies have focused more on the macroscopic level, i.e., the correlation between BMD (or bone tissue mineral content) and the macroscopic mechanical strength of bone, while there is a lack of research on the microscopic parameters and BMD. Studies have shown that cancellous bone microarchitecture is more affected than cortical bone during OP progression. 21 In the study of the microstructure of cancellous bone, the study of trabeculae is important. Previous studies have found that changes in the spatial structure of the trabecular space of cancellous bone during the development of OP can significantly affect the overall mechanical strength of the bone. 7,8 The spatial arrangement of bone trabeculae is known as trabecular architecture, and measurement of the spatial structure of bone trabeculae has become routine with the increased availability of high-resolution imaging techniques such as micro-CT. The main metrics for structural observation of bone trabeculae include Tb.Th, Tb.Sp, Tb.N, BV/TV, BS/BV, connection density, structural modelling index (SMI), and degree of anisotropy. 22 In this study, firstly, we scanned the lumbar spine by micro-CT and measured the relationship of the four linear indexes, Tb.Th, Tb.Sp, Tb.N, and BV/TV, with the progression of OP. After measuring the relationship of the four linear indexes with the progression of OP, we found that a significant decrease in Tb.Th, Tb.N, and BV/TV occurred as OP progressed, while Tb.Sp increased significantly, which is consistent with the findings of Divya et al. . 23 At the same time, we can find that the four indexes of Tb.Sp, Tb.N, and BV/TV changed significantly (p < 0.05) from the first month of postoperative period, while BMD changed significantly from the second month of postoperative period, this suggests that the four metrics, Tb.Th, Tb.Sp, Tb.N, and BV/TV, are more reflective of early OP changes than BMD. However, we still wanted to know which of these four indicators was more strongly correlated with BMD, so we correlated Tb.Th, Tb.Sp, Tb.N, and BV/TV with BMD, and the correlation between Tb.Th, Tb.N, and BV/TV and BMD was analysed. As shown in Table 5, we found the strongest correlation between Tb.Th and BMD (r = 0.936, p = 0.000). It is worth mentioning that in the experiment of Qiu et al. , 24 the changes of BMD, BV/TV, Tb.N, Tb.Th, Tb.Sp, and SMI in the femur of white rabbits over time were investigated. The results showed that Tb.Sp and BV/TV changed significantly from month 2 onwards and earlier than BMD. This suggests that Tb.Sp and BV/TV are the most sensitive predictors of early OP. This is a departure from our results. In our study, Tb.Th, Tb.Sp, Tb.N, and BV/TV changed significantly from 1 month postoperatively. This may be due to differences in the sites studied and the fact that all parameters in the study by Qiu Y et al. were determined by micro-CT, whereas we used DXA to determine BMD. Differences in detection methods may also contribute to the discrepancy. We looked at macromechanics, microstructure, and BMD variations separately, but it's still unclear how much of a role microstructure plays in bone's macromechanical strength. As a result, we'd like to first investigate the most important microstructural parameters for macroscopic mechanical strength. Four microscopic measures, Tb.Th, Tb.Sp, Tb.N, and BV/TV, were each correlated with the lumbar spine Lmax using Pearson's correlation analysis. The strongest association between Tb.Th and lumbar Lmax was discovered, as indicated in Table 7 (r = 0.924, p = 0.000). This suggests that the lumbar spine's maximal loading force increases with trabecular thickness. The aforementioned studies have helped us understand how macromechanics weighs microspatial characteristics, but more research is still needed to determine how strongly these two variables are related to markers of bone turnover. Markers of bone turnover are biomarkers used to detect dynamic bone remodelling in blood or urine, 25 which reflect bone resorption and bone formation. 26 Currently, bone turnover markers are extensively used in clinical practise; however, they are more frequently employed to elucidate the pharmacodynamics and efficacy of osteoporosis medications than to reflect changes in bone mass and strength, 27 current research has focused on the difference in change between bone mineral density (BMD) and bone turnover markers, with BMD explaining 60% to 70% of the change in bone strength, 28 therefore, the correlation analysis between bone turnover markers and BMD alone does not adequately reflect the changes in bone strength; we must combine the bone turnover markers with the microscopic spatial structure and macroscopic mechanical strength to analyse the most relevant bone turnover markers, which will be more useful in guiding clinical work and providing the foundation for fracture prevention. OC is one of the markers and specific indicators of bone formation; CTX and PINP are both extremely sensitive indicators of bone turnover. 29 Of these, CTX is more sensitive to variations in bone volume and bone integrity of the femoral neck than the others. 15 PINP reflects the rate of type I collagen synthesis and bone turnover; the greater the PINP concentration, the more active the bone turnover. 30,31 We must be especially mindful of the potential impact of BTM variability on test outcomes when detecting them. Sources of pre-analytic variability in BTM measurements mainly include age, sex, circadian rhythms, and food intake or fasting status. We chose seven-month-old rabbits that are sexually mature since research has shown that BTMs stay stable and follow typical levels of sex steroids throughout adulthood. The largest variations in the circadian rhythm effect on CTX were seen in research by Schini et al. 32 with minimums between 11:00 and 15:00 p.m. and peaks between 1:30 and 4:30 a.m. The patterns of OC and PINP's rhythms were comparable, with higher levels at night and lower levels in the afternoon. However, there was not much variance, with PINP exhibiting the least amount of change. The majority of research indicates that both men and women's PINP lack a circadian rhythm. 33 Furthermore, BTM was significantly impacted by food consumption and fasting state. Eating in the morning decreased PINP, CTX, and OC, with CTX having the biggest impact; fasting decreased the diurnal variation in CTX from 35% to 40% to 9% to 16%. 32 As a result, we fasted the rabbits overnight and collected blood samples the next morning between 7 and 10 a.m. 34 Consistent with previous findings, our study revealed that serum OC, CTX, and PINP were markedly higher in the OP group than in the Sham group. 35 This suggests that serum OC, CTX, and PINP can reflect changes in bone metabolism and bone mass and assist in the early diagnosis and treatment of osteoporosis. It is worth highlighting that in our study, both CTX and PINP underwent a large increase from the 1st postoperative month, whereas OC changed dramatically from the 2nd postoperative month, and the explanation of the delayed response to OC may be related to the use of dexamethasone. It has been shown that prolonged use of GC leads to impaired osteoblast function and reduced OC levels, which is attributed to osteoblast-targeted disruption of GC signaling, thereby attenuating the inhibition of OC synthesis and blocking OC synthesis. 36 Additionally, during the first few months of GC use, there is a significant loss of bone because GC causes mature osteoblasts and bone cell to undergo apoptosis, which reduces the production of new bone. GC also results in enhanced osteoclastogenesis, an increased lifespan and number of mature osteoclasts, and decreased osteoclast apoptosis, leading to increased bone resorption. 37–39 In addition, because the loss of osteoblasts prevents the damaged osteocyte-tubule network from responding to bone damage, this leads to reduced bone strength. GC can also inhibit this pathway of osteoblast differentiation by stimulating the production of Wnt pathway inhibitors, thereby inhibiting bone formation. 40 In a study by Dovio et al., 41 it was shown that in humans, high-dose, short-term use of GC causes an immediate decrease in OC and PINP and a rapid and transient increase in CTX. This seems to differ somewhat from our results. We reached the following conclusion after analyzing the causes of the discrepancy: First, the dose of GC utilized in their study was 15 mg/kg per day, which is significantly higher than the dose we administered. Research has demonstrated that GC exhibits its effects exclusively on bone turnover, devoid of induction of inflammation, necrosis, or alterations in subarticular bone, when administered at a dose ranging from 0.5 to 1 mg/kg/day. Doses falling below 0.5 mg/kg/day fail to elicit substantial effects on bone changes. 42 Therefore, we use small doses of continuous dosing. Secondly, Dovio et al. measured OC, CTX, and PINP on a daily basis during the treatment period (10 days) and after approximately three months, respectively. Their findings demonstrated that during the treatment period, OC and PINP immediately decreased from day 2, while CTX remained significantly elevated throughout the treatment period. After three months, all BTM levels were significantly elevated. Initial postoperative measurements in our study were conducted one month later. Consequently, we cannot definitively ascertain whether OC and PINP levels decreased during this time period. However, after three months, all BTM levels substantially increased, which is partially consistent with our findings. Additionally, physiological distinctions between humans and rabbits may contribute to the differences. An illustration of this can be observed in the comparatively rapid bone growth and regeneration processes of rabbits, which also possess a heightened metabolic rate and biological activity. Therefore, the aforementioned factors may account for a portion of the distinctions between rabbit and human bone remodeling. Serum CTX-I levels were found to be adversely connected with body weight in a study by Ryszard et al., 43 although BMD was positively correlated with body weight. This finding may be related to the mechanical loading of bone by fat mass.Serum CTX-I levels were found to be adversely connected with body weight in a study by Ryszard et al., although BMD was positively correlated with body weight. This finding may be related to the mechanical loading of bone by fat mass. In a study by Cheng et al., 44 it was also shown that bariatric surgery increases bone turnover and causes bone loss, with CTX-1, OC, and PINP all being elevated to varying degrees postoperatively. In our study, we observed a lower magnitude of weight loss in rabbits in the OP group during this four-month period, but there was no significant difference compared to the Sham group (p > 0.05). A study by Liu et al. 45 showed no significant difference (p > 0.05) in OC levels between men with primary OP and age-matched non-OP controls. The reason for the difference in results may be due to the difference in the study population; bone loss is slower in men, and the pattern of bone conversion of OC in men with primary OP remains unclear, with results to be further validated. Although serum BTMs can reflect changes in bone metabolism and bone mass, it is unclear which index reflects its correlation with bone mass and bone strength more accurately. Therefore, we conducted further analyses. According to Table 6, we correlated OC, CTX, and PINP with lumbar Lmax, and the results showed that PINP and OC had the strongest and most significant negative correlation with it (r = -0.958, p = 0.000). This suggests that PINP and OC can be used as representative markers for assessing bone quality in macromechanics. Subsequently, we correlated OC, CTX, and PINP with Tb.Th, the microscopic parameter with the greatest influence on macroscopic mechanical strength, and found that CTX had the strongest correlation (r = -0.955, p = 0.000). Through the above analysis, we found that at the macroscopic spatial level, the greater the values of PINP and OC in the OP process, the lower the Lmax of the lumbar vertebrae and the more severe the osteoporosis, while at the microscopic spatial level, the greater the value of CTX, the thinner the trabeculae of the bone. Our analysis of the reasons for the discrepancy may be due to the fact that PINP and OC serve as markers of bone formation, that the bone formation period is characterized by matrix synthesis and mineralization, and that PINP and OC are protein fragments and proteins released by osteoblastic cells. OC, also originally known as bone Gla-protein, is produced by bone mineralization, and Gla-protein in bone plays an important role in bone strength; therefore, PINP and OC can be used as an important indicator to represent macroscopic mechanical strength. 32 Our findings are somewhat supported by a study by Berezovska et al. 46 that compared osteocalcin knock-out mice with wild-type mice and found that OC levels were linked to fractures and bone fragility. Notably, OC increases bone density and promotes mineralization and bone formation, thereby contributing to bone mechanical strength. However, in our study, the mechanical strength of the lumbar spine decreased as PINP and OC values increased, likely because elevated markers of bone formation typically indicate an active bone formation process. Nonetheless, bone resorption remains active throughout the course of osteoporosis progression; consequently, bone loss may persist, and ongoing bone resorption undermines the structural integrity and stability of the skeleton, ultimately resulting in diminished bone mechanical strength. In addition, elevated markers of bone formation may suggest that the process of bone formation is especially active at specific sites; if the rate of bone formation surpasses the rate of bone mineralization, insufficient mineralization will occur within the bone, resulting in a heterogeneous internal structure. Such heterogeneous bone formation can potentially compromise the mechanical strength of the bone and contribute to its fragility. 47 Thus, elevated bone formation markers may contribute to increased BMD and bone mechanical strength within the normal range. On the contrary, an increase in bone formation markers throughout the course of osteoporosis progression leads to a reduction in the mechanical strength of the bone. CTX is a bone resorption marker and is secreted by osteoclasts. The process of bone resorption is that osteoclasts cause the destruction and degradation of bone trabeculae through contact with them, which leads to an increase in CTX levels. This process contributes to the stabilization of bone microstructure; therefore, we can use the change in CTX levels to reflect the change in trabecular density and the stability of bone microstructure. These three indicators can be used for clinical observation in order to prevent osteoporotic spine fractures. Obviously, there are some flaws in our investigation. First, during the discussion of microscopic parameters, only the microscopic spatial structure and not the micromechanical strength were discussed. Second, the discussion of the microspace structure is limited to four linear indicators, and we have not investigated the nonlinear parameters. In addition, our study was limited to an animal model and was not validated in a clinical setting; consequently, we will include nanoindentation experiments in future research to further investigate this in conjunction with nonlinear parameters and clinical patient specimens. Conclusions In conclusion, there is a correlation between bone turnover markers, bone microspace structure, and bone macromechanics. In the OP progression, each microspatial parameter of lumbar cancellous bone was correlated with macroscopic mechanical strength, with Tb.Th showing the strongest correlation. CTX was the most significant correlate of microspace structure for BTMs, whereas PINP and OC were the most significant correlates of macroscopic mechanical strength. Therefore, early detection of CTX can help us to understand the microstructural changes of vertebral cancellous bone in the progression of OP, and early detection of PINP and OC can help us to understand the changes of macroscopic mechanical strength of vertebral cancellous bone in the progression of OP, thereby providing a theoretical basis for a more comprehensive assessment of the severity of spinal osteoporosis and the prevention of spinal osteoporotic fracture in the clinic. Abbreviations ANOVA: Analysis of variance; BMD: Bone mineral density; CTX: 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 Acknowledgements Not applicable. Authors’ contributions LD, ZYB designed the study. WW, WL, and ZJ performed the statistical analysis. JYH drafted the manuscript. XW, XN and JYH were responsible for data collection and outcomes evaluation. LD and ZYB reviewed and edited the manuscript. All authors read and approved the fnal manuscript. Funding This study was supported by the Cadre health committee Program of China (21BJZ40) and Science and Technology Plan Project of Sichuan Province (2023NSFSC0664) . Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author Yuhao Jia on reasonable request. Ethics approval and consent to participate All participants signed a written informed consent form, and the study protocol was approved by the Ethics Committee of the General Hospital of Western Theater Command. All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication Not applicable. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References 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. 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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-3863396","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268367836,"identity":"d609335c-1b76-4799-816a-06bc01108531","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":268367837,"identity":"4ea26831-caaf-4102-ad33-8934f73bf32e","order_by":1,"name":"Ning Xia","email":"","orcid":"","institution":"The General Hospital of Western Theater 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establishment, Figure \u003cstrong\u003e(a)\u003c/strong\u003eshows the intraoperative exposed ovary, \u003cstrong\u003e(b)\u003c/strong\u003e shows the resected ovary\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/a321cc854ed7a18949789a5b.png"},{"id":49977205,"identity":"31f2833d-4ad4-416e-8c5a-4f949d9d6598","added_by":"auto","created_at":"2024-01-22 14:53:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":470406,"visible":true,"origin":"","legend":"\u003cp\u003eDXA test analysis, Figure \u003cstrong\u003e(a)\u003c/strong\u003e shows the test bench and body position placement,\u003cstrong\u003e(b)\u003c/strong\u003e shows the test results.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/4b06cbe7c273a174931bad2f.png"},{"id":49978372,"identity":"730a8976-b408-43ac-aa32-67c82186ac9a","added_by":"auto","created_at":"2024-01-22 15:01:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":730848,"visible":true,"origin":"","legend":"\u003cp\u003eMicro-CT scanning and reconstruction analysis Figure\u003cstrong\u003e (a)\u003c/strong\u003e shows the micro-CT scanning process, and the yellow area in \u003cstrong\u003e(b) \u003c/strong\u003eshows the distribution of bone trabeculae.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/e41b799a19afbc29f1cec414.png"},{"id":49977211,"identity":"becedf04-f6c9-4e20-9cdb-d51ca2d01782","added_by":"auto","created_at":"2024-01-22 14:53:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1746624,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental test of lumbar compression\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/87459e778ee4dafe482cafbe.png"},{"id":49977210,"identity":"5d05188b-fdee-4f18-b9d6-de268838e8fe","added_by":"auto","created_at":"2024-01-22 14:53:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":32132,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of lumbar spine subjected to Maximum load (N) between the two groups at different time points after surgery.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/02b08574e7d4b6e04ee8753d.png"},{"id":49977208,"identity":"3a966aa4-d7c4-41b8-9390-f4ed08f1a074","added_by":"auto","created_at":"2024-01-22 14:53:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":99184,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of serum BTMs parameters (ng / mL) between the two groups at different postoperative time points, with \u003cstrong\u003e(a), (b),\u003c/strong\u003e and\u003cstrong\u003e (c) \u003c/strong\u003ein the figure showing the trends of OC, PINP, and CTX, respectively.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/fdaa9ff9bd8ade615907d9e7.png"},{"id":49977206,"identity":"dd640dc4-47d4-436b-87de-8c71c3b3d366","added_by":"auto","created_at":"2024-01-22 14:53:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":116784,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of microstructural parameters of lumbar spine micro-CT between the two groups at different time points after surgery, with \u003cstrong\u003e(a), (b), (c),\u003c/strong\u003e and \u003cstrong\u003e(d)\u003c/strong\u003ein the figure showing the trends of BV/TV, Tb.Th , Tb.N, and Tb.Sp, respectively.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/6feb94838c2a7ac424aa0036.png"},{"id":49977212,"identity":"410412b1-db43-4859-993b-dc1be9987c66","added_by":"auto","created_at":"2024-01-22 14:53:23","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":495653,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional reconstruction of L5 vertebrae Micro-CT scan, where\u003cstrong\u003e (a)-(d)\u003c/strong\u003e are schematic diagrams of Sham group at pre-ovx, 1, 2, and 4 months, and\u003cstrong\u003e (e)-(h) \u003c/strong\u003eare schematic diagrams of OP group at pre-ovx, 1, 2, and 4 months, respectively.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/5b5901115791975664ed02b9.png"},{"id":62002138,"identity":"51bd009e-295e-4cff-9af6-304afcb49e05","added_by":"auto","created_at":"2024-08-08 06:07:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6953196,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3863396/v1/9ed557b6-fac2-4744-893c-22adbc25b5ae.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation of serum bone turnover markers with microstructure and macroscopic mechanical strength of lumbar cancellous bone during progression of osteoporosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoporosis (OP) is a skeletal condition marked by a loss of bone mass and deterioration of the bone\u0026apos;s microstructure, which increases bone fragility and fracture risk.\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e Osteoporotic fracture is a severe complication of OP and a major health concern for the world\u0026apos;s ageing population. In China, the incidence of osteoporotic fractures is 13%. By 2035, the number of osteoporosis-related fractures is projected to reach 4.83 million, at a cost of approximately $19.92 billion annually.\u0026nbsp;\u003csup\u003e2\u003c/sup\u003e Vertebral compression fractures (VCF) are the most common form of osteoporotic fracture because vertebral bone density decreases with age, and they are more prevalent in the elderly.\u0026nbsp;\u003csup\u003e3,4\u003c/sup\u003e In China, the incidence of vertebral fracture is approximately 15% in women over 50 and 36.6% in women over 80.\u0026nbsp;\u003csup\u003e5\u003c/sup\u003e Symptomatic osteoporotic fractures of the spine frequently result in severe back pain, spinal deformity, decreased mobility and lung function, and an increased risk of mortality with advancing age.\u0026nbsp;\u003csup\u003e6\u003c/sup\u003e Consequently, investigating the microscopic mechanism of spinal osteoporotic fracture can prevent the development of spinal osteoporosis.\u003c/p\u003e\n\u003cp\u003eChanges in the spatial structure of cancellous trabeculae during the OP process can substantially affect the overall mechanical strength of bone, according to previous research.\u0026nbsp;\u003csup\u003e7,8\u003c/sup\u003e Currently, scholars at home and abroad mainly use high-resolution imaging techniques such as micro-CT to study the microspatial structure of bone trabeculae,\u0026nbsp;\u003csup\u003e9,10\u003c/sup\u003e and relevant studies have shown that bone turnover markers (BTMs) can dynamically reflect bone remodelling. However, the conclusions of these studies are controversial because of the wide variety of markers and the susceptibility of the assay to environmental and methodological factors. Moreover, it is still unclear which specific BTMs are more sensitive to indicating fracture risk. Furthermore, current studies have focused more on the macroscopic level, i.e., the correlation between BMD (or bone mineral content) and the macroscopic mechanical strength of bone, while there is a lack of research on the study of microscopic parameters and BMD, as well as the weighting of microscopic parameters in the role of macroscopic mechanical strength.\u003c/p\u003e\n\u003cp\u003eTherefore, the aim of the present study was to establish a rabbit model of osteoporosis by depopulation combined with the glucocorticoid method and to investigate the weights of bone microstructural parameters in the lumbar spine maximum load (L\u003csub\u003emax\u003c/sub\u003e), to describe the microscopic mechanism of spinal osteoporosis, and, through further study and correlation analysis with bone turnover markers (BTMs), to select bone turnover markers with a strong correlation with bone mineral density.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eAnimals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eByrness Weil Biotech Ltd. (Chengdu, China) provided 64 female New Zealand white rabbits of pure breed and 7 months of age for this study. Their body weight ranged from 2.87 to 3.37 kg. These experiments were approved by the General Hospital of Western Theatre Ethics Committee and adhered to the Animal Care and Use Guidelines by housing the rabbits individually in stainless steel cages in a standard animal facility with room temperature maintained between 21 and 24 degrees Celsius, relative humidity between 40 and 60 percent, a 12-hour light/dark cycle, with a light cycle consistent with daytime, and diet (standard commercial rabbit food) and running water provided ad libitum.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of osteoporotic rabbit model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the rabbits had acclimated to their new environment for 2 weeks, each animal was randomly assigned to either the sham operation group (n = 32) or the osteoporosis model group (n = 32). To obtain baseline data (pre-ovx), including BMD, PINP, OC, CTX-I, Tb.N., Tb.Th., Tb.Sp., BV/TV, and biomechanical assays, eight rabbits from each group were randomly selected and executed via air embolisation of the marginal ear vein. Animals in the OP group were starved for 12 hours prior to surgery and underwent bilateral ovariectomy (OVX) with isoflurane (Reward, Shenyang, China). During the operation, both ovaries were exposed in the Sham group, and the abdomen was then closed and sutured. All animals were administered 10,000 U/kg of intramuscular gentamicin (Solarbio, Beijing, China) twice per day for three days to prevent infection. Two weeks after surgery, animals in the OP group received intramuscular dexamethasone 0.5 mg/kg (Yiduoli, Shanxi, China) \u0026nbsp;twice a week for four weeks. The animals were divided into 1-month, 2-month, and 4-month groups, with 8 animals in each group. Lumbar BMD was measured by dual-energy X-ray absorptiometry (DXA) at 1, 2, and 4 months postoperatively, after which the rabbits were euthanized by intravenous injection of excess air into the ear margins, and specimens of lumbar vertebrae (L1\u0026ndash;L5) were collected and frozen at -80 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLumbar Bone Density Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLumbar spine BMD was determined utilizing a DXA (Lunar Prodigy Advance; GE Lunar, Madison, WI, USA), and DXA scans were analyzed at the corresponding time points (pre-ovx, 1 month, 2 months, and 4 months) prior to the execution of each group of animals. Each rodent was placed in the prone position on a DEXA table under general anaesthesia for BMD measurement. OP was diagnosed by a BMD value in the OP group that was lower than the mean value in the Sham group at the same time point minus 2.5 SD and combined with bone microstructural alterations. \u003csup\u003e11\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicro-CT scanning and reconstruction analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe lumbar vertebrae of rabbits were removed from the refrigerator at -80\u0026deg;C, thawed at room temperature, and the muscles, intervertebral discs, and fascia were removed, along with the transverse processes and spinous processes. L5 vertebrae were selected, scanned, and analysed using a Quantum GX Micro-CT scanner (PerkinElmer, USA). Utilise the following image retrieval parameters: Energy/intensity was 80 kV, 100 \u0026mu;A, 8 W, angular increment was 0.5\u0026deg;, and scantime was 4 minutes. Scanning is performed by rotating from 0\u0026deg;, and a reorganisation image is obtained after scanning is complete. Tb.N, Tb.Th, Tb.Sp, and BV/TV were analysed using Avatar software (version 2.0.0.1, PINGSENG Healthcare lnc).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiomechanical testing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe lumbar vertebrae were thawed at room temperature, and the L4 vertebral body was selected, followed by the removal of the musculature, intervertebral discs, and fascia. The two endplates of the vertebral body were removed using a low-speed precision diamond saw with continuous irrigation, as well as the transverse processes and spinous processes. By grinding the upper and lower planes parallel to each other, the central portion of the vertebral body with parallel ends was obtained; this central section consists of a central trabecular core and a compact housing. Utilising the MTS Model 809 axial/torsional testing system (MTS Systems Corp., USA), tensile experiments were conducted. The MTS testing machine was equipped with an axial hydraulic actuator with a 200 kN axial capacity. The sample is deposited in the test stand and statically preloaded for 30 seconds with a force of 10N. Subsequently, the compression test was conducted at a speed of 0.02 mm/s until a clear peak appeared, after which the maximal load (L\u003csub\u003emax\u003c/sub\u003e) was automatically determined by the software included with the apparatus. All phases of this investigation were conducted at a temperature of 23 \u0026plusmn; 0.2\u0026deg;C.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerum BTMs test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples were collected from the central auricular artery one week prior to the respective time points (pre-ovx, 1 month, 2 months, and 4 months). Collect blood samples between 7 a.m. and 10 a.m. the next morning after fasting the rabbit overnight before blood collection. Centrifuged immediately, and the serum was separated and stored at -80 \u0026deg;C until analysis. For analysis, samples were thawed at room temperature, 50 \u0026mu;L of samples and standards were added to 96-well plates, and an enzyme-linked immunosorbent assay (R\u0026amp;D Systems, Minneapolis, MN) was used to detect serum levels of OC, PINP, and CTX. Unless duplicate measurements of individual values were required, all samples were processed using the same assay. All procedures were carried out according to the kit\u0026apos;s instructions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS 26.0, and all data conformed to a normal distribution and were expressed as mean \u0026plusmn; standard deviation. Comparisons of the relevant parameters between the Sham and OP groups within the same time point were performed using an independent samples t test (indent-pendent-samples t test). While comparisons between different time points within the same group were performed using one-way ANOVA, the LSD method was used if the variance was homogeneous, and the Tammany method was used if the variance was not homogeneous. Pearson linear correlation analysis was used to analyse the microspatial parameters and macroscopic mechanical strength of cancellous bone, and the strongest correlation between microspatial parameters and macroscopic mechanical strength was identified, the resulting metrics were then analysed by Pearson linear correlation analysis with bone turnover markers, and the bone turnover markers with the strongest correlation with microstructure were identified, finally, Pearson linear correlation analysis was performed between the bone turnover markers and the macroscopic mechanical strength, and the bone turnover markers with the strongest correlation with the macroscopic mechanical strength were identified. Differences were considered statistically significant at p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eLumbar spine BMD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 Results of lumbar BMD (g / cm\u0026sup2;)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"587\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.546848381601365%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.45315161839864%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003ePre - ovx \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2 months \u0026nbsp; \u0026nbsp; \u0026nbsp; 4months\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.546848381601365%\" valign=\"top\"\u003e\n \u003cp\u003eSham (n = 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.277 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.278 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.279 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.282 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.546848381601365%\" valign=\"top\"\u003e\n \u003cp\u003eOP (n = 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.275 \u0026plusmn; 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.273 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.232 \u0026plusmn; 0.08\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61328790459966%\" valign=\"top\"\u003e\n \u003cp\u003e0.172 \u0026plusmn; 0.06\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are expressed as mean \u0026plusmn; standard deviation of BMD (n = 8). \u003csup\u003e***\u003c/sup\u003eP \u0026lt; 0.0001, the difference was statistically significant.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 1, the values of BMD in the OP group showed a gradual decrease with increasing time, there was a statistical difference between all time points in the OP group, except for no statistical difference between the pre-ovx and 1 months groups (p \u0026lt; 0.0001), there was a significant difference in lumbar BMD values between the OP group and the Sham group at the same time point at 2 and 4 months postoperatively (p \u0026lt; 0.0001), the difference was statistically significant, but only at postoperative month 4, the BMD value in the OP group was smaller than that in the Sham group minus 2.5 SD in the same period, the lumbar spine BMD values in the OP group decreased by 39 % compared to the sham group. The difference was not statistically significant in the sham group (p \u0026gt; 0.05). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiomechanical testing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 Results of biomechanical parameters of lumbar spine (N)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003ePre-ovx \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e2 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e4 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eSham(n=8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e677 \u0026plusmn; 51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e685 \u0026plusmn; 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e691 \u0026plusmn; 28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e691 \u0026plusmn; 57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eOP (n=8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e667 \u0026plusmn; 44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e613 \u0026plusmn; 23\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e490 \u0026plusmn; 34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e331 \u0026plusmn; 34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are expressed as mean \u0026plusmn; standard deviation of Maximum load (n=8). \u003csup\u003e*\u003c/sup\u003eP \u0026lt; 0.05, the difference was statistically significant, \u003csup\u003e**\u003c/sup\u003eP \u0026lt; 0.001, the difference was statistically significant, \u003csup\u003e***\u003c/sup\u003e P \u0026lt; 0.0001, the difference was statistically significant.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2, with the exception of the pre-ovx group, the maximal loads of the OP group were significantly lower than those of the Sham group at all time points, decreasing by 10.5% (p \u0026lt; 0.05), 29% (p \u0026lt; \u0026nbsp;0.0001), and 52.2% (p \u0026lt; 0.0001), respectively, compared with those of the Sham group 1 month, 2 months, and 4 months after the operation and at the same time point. The Lmax of the OP group decreased gradually with time (Fig. 5), and the differences between OP groups at different time points were statistically significant (p \u0026lt; 0.0001), whereas the differences between Sham groups were not statistically significant at all time points (p \u0026gt; 0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerum BTMs test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 Results of serum BTMs parameters (ng / mL)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"560\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003eTimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003eOC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003ePINP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003eCTX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003ePre-ovx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e1.41 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e2.91 \u0026plusmn; 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.23 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e1.42 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e2.92 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.23 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e1 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e1.42 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e2.93 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.24 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e1.49 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e3.59 \u0026plusmn; 0.22\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.40 \u0026plusmn; 0.02\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e2 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e1.41 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e2.93 \u0026plusmn; 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.22 \u0026plusmn; 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e2.80 \u0026plusmn; 0.37\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e5.80 \u0026plusmn; 0.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.60 \u0026plusmn; 0.03\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e4 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e1.42 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e2.90 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.23 \u0026plusmn; 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.75579322638146%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.795008912655971%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10338680926916%\" valign=\"top\"\u003e\n \u003cp\u003e4.07 \u0026plusmn; 0.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.529411764705884%\" valign=\"top\"\u003e\n \u003cp\u003e7.77 \u0026plusmn; 0.34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.816399286987522%\" valign=\"top\"\u003e\n \u003cp\u003e0.80 \u0026plusmn; 0.03\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are expressed as mean \u0026plusmn; standard deviation of BTMs (n=8). \u003csup\u003e*\u003c/sup\u003eP \u0026lt; 0.05, the difference was statistically significant, \u003csup\u003e**\u003c/sup\u003eP \u0026lt; 0.001, the difference was statistically significant, \u003csup\u003e***\u003c/sup\u003e P \u0026lt; 0.0001, the difference was statistically significan.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 3, PINP and CTX were significantly different between the OP group and the Sham group in all time periods except pre-ovx, in which PINP increased by 22.5 % (p \u0026lt; 0.05), 97.9 % (p \u0026lt; 0.0001), and 167.9 % (p \u0026lt; 0.0001) in each of the parameters in the postoperative months of 1, 2, and 4, respectively, compared with the Sham group in the same time period, and CTX increased by 66.7 % (p \u0026lt; 0.0001), 172.7 % (p \u0026lt; 0.0001), and 247.8 % (p \u0026lt; 0.0001), respectively. increased by 66.7% (p \u0026lt; 0.0001), 172.7% (p \u0026lt; 0.0001), and 247.8% (p \u0026lt; 0.0001), respectively. OC changed significantly from 2 months postoperatively, increasing by 98.6% (p \u0026lt; 0.0001) and 186.6% (p \u0026lt; 0.0001) at 2 and 4 months postoperatively, respectively. With the increase in time, the serum parameters of OC, PINP, and CTX in the OP group showed a gradual increase (Fig. 6), and the differences among the Sham groups were not statistically significant (p \u0026gt; 0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicro-CT Testing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 Results of micro-CT microstructural parameters of lumbar cancellous bone\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"660\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003eTimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003eBV/TV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003eTb.Th (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003eTb.N(1/mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003eTb.Sp(mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003ePre-ovx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.303 \u0026plusmn; 0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.233 \u0026plusmn; 0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e1.013 \u0026plusmn; 0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e0.769 \u0026plusmn; 0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.299 \u0026plusmn; 0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.228 \u0026plusmn; 0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e0.999 \u0026plusmn; 0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e0.781 \u0026plusmn; 0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e1 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.295 \u0026plusmn; 0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.227 \u0026plusmn; 0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e0.974 \u0026plusmn; 0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e0.788 \u0026plusmn; 0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.236 \u0026plusmn; 0.008\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.210 \u0026plusmn; 0.003\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e0.865 \u0026plusmn; 0.022\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e0.935 \u0026plusmn; 0.023\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e2 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.303 \u0026plusmn; 0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.235 \u0026plusmn; 0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e0.995 \u0026plusmn; 0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e0.789 \u0026plusmn; 0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.221 \u0026plusmn; 0.008\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.184 \u0026plusmn; 0.005\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e0.823\u0026plusmn; 0.013*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e1.002 \u0026plusmn; 0.002\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e4 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.313 \u0026plusmn; 0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.232 \u0026plusmn; 0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e1.003 \u0026plusmn; 0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e0.784 \u0026plusmn; 0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.380880121396055%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.559939301972685%\" valign=\"top\"\u003e\n \u003cp\u003eop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.271623672230653%\" valign=\"top\"\u003e\n \u003cp\u003e0.174 \u0026plusmn; 0.023\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11987860394537%\" valign=\"top\"\u003e\n \u003cp\u003e0.147 \u0026plusmn; 0.012\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.96813353566009%\" valign=\"top\"\u003e\n \u003cp\u003e0.689\u0026plusmn; 0.043\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.699544764795146%\" valign=\"top\"\u003e\n \u003cp\u003e1.243 \u0026plusmn; 0.085\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are expressed as mean \u0026plusmn; standard deviation of Maximum load (n=8). \u003csup\u003e*\u003c/sup\u003eP \u0026lt; 0.05, the difference was statistically significant, \u003csup\u003e**\u003c/sup\u003eP \u0026lt; 0.001, the difference was statistically significant, \u003csup\u003e***\u003c/sup\u003e P \u0026lt; 0.0001, the difference was statistically significant.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 4, except for pre-ovx, the parameters of the OP group were significantly different from those of the Sham group at all time periods, in which BV/TV decreased by 20% (p \u0026lt; 0.05), 27.1% (p \u0026lt; 0.05), and 44.4% (p \u0026lt; 0.0001), Tb.N decreased by 11.2% (p \u0026lt; 0.05), 17.3% (p \u0026lt; 0.05), and 31.3% (p \u0026lt; 0.0001), respectively, in the OP group, as compared with that of the Sham group at the same time. 11.2 % (p \u0026lt; 0.05), 17.3 % (p \u0026lt; 0.05), 31.3 % (p \u0026lt; 0.0001), and Tb.Th decreased by 7.5 % (p \u0026lt; 0.05), 21.7 % (p \u0026lt; 0.0001), and 36.6 % (p \u0026lt; 0.0001), respectively, while Tb.Sp increased by 15.7 %, 21.3 %, and 36.9% (p \u0026lt; 0.0001). With the increase in time, the BV/TV, Tb.Th, and Tb.N showed a decreasing trend, and Tb.Sp showed an increasing trend (Fig. 7). Differences between OP groups at different time points were statistically significant (p \u0026lt; 0.0001), and differences between Sham groups at all time points were not statistically significant (p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicrostructural analysis of the lumbar spine\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 8, the \u003cstrong\u003e(a)-(d)\u003c/strong\u003e trabeculae were more abundant, tightly connected with each other to form a mesh, and structurally stable. In\u003cstrong\u003e\u0026nbsp;(e)-(h)\u003c/strong\u003e, the spongy structure becomes more and more spongy as time progresses, the number of trabeculae decreases, the trabecular intervals increase, and the thickness becomes progressively thinner and more structurally discontinuous.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePearson correlation coefficients between parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 \u0026nbsp; Pearson\u0026apos;s linear correlation analysis of microscopic parameters with BMD and lumbar L\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"569\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003eBMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003eLumbar L\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003eTb.Th \u0026nbsp; \u0026nbsp; r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003eTb.Sp \u0026nbsp; \u0026nbsp; r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e-0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e-0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003eTb.N \u0026nbsp; \u0026nbsp; \u0026nbsp;r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003eBV/TV \u0026nbsp; \u0026nbsp;r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.956063268892795%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.08787346221441%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBV/TV, bone volume fraction; Tb.Th, trabecular thickness; Tb.Sp, trabecular spacing; Tb.N, number of trabeculae\u003c/p\u003e\n\u003cp\u003eAs shown in Table 5, Tb.Th, Tb.N, and BV/TV were positively correlated with lumbar BMD and Lmax, and Tb.Sp was negatively correlated with lumbar BMD and Lmax. The strongest correlations were found between Tb.Th and lumbar BMD (r = 0.936, p = 0.000) and L\u003csub\u003emax\u003c/sub\u003e (r = 0.924, p = 0.000).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6 Pearson\u0026apos;s linear correlation analysis of BTMs with L\u003csub\u003emax\u003c/sub\u003e of lumbar spine\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"376\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003eLumbar L\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003eOC \u0026nbsp; \u0026nbsp; r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003e-0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003eCTX \u0026nbsp; \u0026nbsp;r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003e-0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003ePINP \u0026nbsp; \u0026nbsp;r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003e-0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.4%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.6%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOC, Osteocalcin; CTX, type I collagen cross-linked C-terminal peptide; PINP, type I procollagen N-terminal prepeptide\u003c/p\u003e\n\u003cp\u003eAs shown in Table 6, OC, CTX, and PINP were all negatively correlated with lumbar L\u003csub\u003emax\u003c/sub\u003e, with PINP and OC having the strongest correlation with lumbar L\u003csub\u003emax\u003c/sub\u003e (r = -0.958, p = 0.000).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7 Pearson\u0026apos;s linear correlation analysis of BTMs and Tb.Th of bone\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003eTb.Th\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003eOC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003e-0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003eCTX \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003e-0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003ePINP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003e-0.935\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.347258485639685%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.652741514360315%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOC, Osteocalcin; CTX, type I collagen cross-linked C-terminal peptide; PINP, type I procollagen N-terminal prepeptide\u003c/p\u003e\n\u003cp\u003eAs shown in Table 7, OC, CTX, and PINP were all negatively correlated with Tb.Th, with CTX having the strongest correlation with Tb.Th (r = -0.955, p = 0.000).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we concentrated on the strength of the correlation between the lumbar cancellous bone\u0026apos;s microspatial structure, macroscopic mechanical strength, and bone conversion indicators in the development of OP. The entire postoperative study observation process took place over a period of four months. We were successful in creating an osteoporosis model using the OVX combined with the GC method and investigated the micro-spatial structure of BMD, lumbar cancellous bone, macroscopic mechanical properties, and the changes of bone turnover markers over time. We find that Tb.Th has the strongest correlation with macroscopic mechanical strength, and for BTMs, CTX is the strongest correlate of microspatial structure, while PINP and OC are the strongest correlates of macroscopic mechanical strength.\u003c/p\u003e\n\u003cp\u003eThe most well-liked animal models for postmenopausal osteoporosis have been chosen by OVX in mice, rats, sheep, and nonhuman primates. On the other hand, the most widely used animal model for osteoporosis is ovariectomized rats.\u0026nbsp;\u003csup\u003e12\u003c/sup\u003e The model does have several limitations, though, including the fact that rats lack a natural menopause and are unable to reach true skeletal maturity, as well as the fact that they are too tiny to fully close the epiphyseal plate and do not undergo Haversian remodelling.\u0026nbsp;\u003csup\u003e13\u003c/sup\u003e Rabbits, on the other hand, are easier to grow and handle than other models and show active Haversian remodelling. They also have a shorter maturation time than larger animals, attaining full skeletal maturity in about six to eight months.\u0026nbsp;\u003csup\u003e14\u003c/sup\u003e As a result, we decided to create an animal model of osteoporosis using rabbits.\u003c/p\u003e\n\u003cp\u003eAlthough DXA is now the gold standard for measuring BMD and diagnosing OP, it has certain limitations. For example, DXA does not detect substantial changes in early BMD and only detects changes in bone loss when it reaches a particular level,\u0026nbsp;\u003csup\u003e15\u003c/sup\u003e and secondly, changes in bone strength and fracture risk after clinical treatment cannot be adequately explained by BMD alone.\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e With the help of additional techniques, such as micro-computed tomography, biomechanics, and biomarkers of bone turnover, we may further validate BMD values and bone structure.\u0026nbsp;\u003csup\u003e17\u003c/sup\u003e Living bones are mostly made of bone tissue, which is an organ whose quality as an organ is primarily determined by its macrostructure and whose quality as bone tissue is primarily determined by its composition and microstructure. By assessing a bone\u0026apos;s biomechanics, we can often express the bone\u0026apos;s mass.\u0026nbsp;\u003csup\u003e18\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLumbar spine L\u003csub\u003emax\u003c/sub\u003e is the maximum force it can withstand before a fracture occurs and is an important measure of its biomechanical properties.\u0026nbsp;\u003csup\u003e19\u003c/sup\u003e In our study, it was found that with the progression of OP, lumbar L\u003csub\u003emax\u003c/sub\u003e was significantly reduced, which is consistent with the results of previous studies.\u0026nbsp;\u003csup\u003e20\u003c/sup\u003e However, current studies have focused more on the macroscopic level, i.e., the correlation between BMD (or bone tissue mineral content) and the macroscopic mechanical strength of bone, while there is a lack of research on the microscopic parameters and BMD.\u003c/p\u003e\n\u003cp\u003eStudies have shown that cancellous bone microarchitecture is more affected than cortical bone during OP progression.\u0026nbsp;\u003csup\u003e21\u003c/sup\u003e In the study of the microstructure of cancellous bone, the study of trabeculae is important. Previous studies have found that changes in the spatial structure of the trabecular space of cancellous bone during the development of OP can significantly affect the overall mechanical strength of the bone.\u0026nbsp;\u003csup\u003e7,8\u003c/sup\u003e The spatial arrangement of bone trabeculae is known as trabecular architecture, and measurement of the spatial structure of bone trabeculae has become routine with the increased availability of high-resolution imaging techniques such as micro-CT. The main metrics for structural observation of bone trabeculae include Tb.Th, Tb.Sp, Tb.N, BV/TV, BS/BV, connection density, structural modelling index (SMI), and degree of anisotropy.\u0026nbsp;\u003csup\u003e22\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, firstly, we scanned the lumbar spine by micro-CT and measured the relationship of the four linear indexes, Tb.Th, Tb.Sp, Tb.N, and BV/TV, with the progression of OP. After measuring the relationship of the four linear indexes with the progression of OP, we found that a significant decrease in Tb.Th, Tb.N, and BV/TV occurred as OP progressed, while Tb.Sp increased significantly, which is consistent with the findings of Divya et al. .\u003csup\u003e23\u003c/sup\u003e At the same time, we can find that the four indexes of Tb.Sp, Tb.N, and BV/TV changed significantly (p \u0026lt; 0.05) from the first month of postoperative period, while BMD changed significantly from the second month of postoperative period, this suggests that the four metrics, Tb.Th, Tb.Sp, Tb.N, and BV/TV, are more reflective of early OP changes than BMD. However, we still wanted to know which of these four indicators was more strongly correlated with BMD, so we correlated Tb.Th, Tb.Sp, Tb.N, and BV/TV with BMD, and the correlation between Tb.Th, Tb.N, and BV/TV and BMD was analysed. As shown in Table 5, we found the strongest correlation between Tb.Th and BMD (r = 0.936, p = 0.000). It is worth mentioning that in the experiment of Qiu et al. ,\u0026nbsp;\u003csup\u003e24\u003c/sup\u003e the changes of BMD, BV/TV, Tb.N, Tb.Th, Tb.Sp, and SMI in the femur of white rabbits over time were investigated. The results showed that Tb.Sp and BV/TV changed significantly from month 2 onwards and earlier than BMD. This suggests that Tb.Sp and BV/TV are the most sensitive predictors of early OP. This is a departure from our results. In our study, Tb.Th, Tb.Sp, Tb.N, and BV/TV changed significantly from 1 month postoperatively. This may be due to differences in the sites studied and the fact that all parameters in the study by Qiu Y et al. were determined by micro-CT, whereas we used DXA to determine BMD. Differences in detection methods may also contribute to the discrepancy. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe looked at macromechanics, microstructure, and BMD variations separately, but it\u0026apos;s still unclear how much of a role microstructure plays in bone\u0026apos;s macromechanical strength. As a result, we\u0026apos;d like to first investigate the most important microstructural parameters for macroscopic mechanical strength. Four microscopic measures, Tb.Th, Tb.Sp, Tb.N, and BV/TV, were each correlated with the lumbar spine Lmax using Pearson\u0026apos;s correlation analysis. The strongest association between Tb.Th and lumbar Lmax was discovered, as indicated in Table 7 (r\u0026nbsp;= 0.924, p = 0.000). This suggests that the lumbar spine\u0026apos;s maximal loading force increases with trabecular thickness. The aforementioned studies have helped us understand how macromechanics weighs microspatial characteristics, but more research is still needed to determine how strongly these two variables are related to markers of bone turnover.\u003c/p\u003e\n\u003cp\u003eMarkers of bone turnover are biomarkers used to detect dynamic bone remodelling in blood or urine,\u0026nbsp;\u003csup\u003e25\u003c/sup\u003e which reflect bone resorption and bone formation.\u0026nbsp;\u003csup\u003e26\u003c/sup\u003e Currently, bone turnover markers are extensively used in clinical practise; however, they are more frequently employed to elucidate the pharmacodynamics and efficacy of osteoporosis medications than to reflect changes in bone mass and strength,\u0026nbsp;\u003csup\u003e27\u003c/sup\u003e current research has focused on the difference in change between bone mineral density (BMD) and bone turnover markers, with BMD explaining 60% to 70% of the change in bone strength,\u0026nbsp;\u003csup\u003e28\u003c/sup\u003e therefore, the correlation analysis between bone turnover markers and BMD alone does not adequately reflect the changes in bone strength; we must combine the bone turnover markers with the microscopic spatial structure and macroscopic mechanical strength to analyse the most relevant bone turnover markers, which will be more useful in guiding clinical work and providing the foundation for fracture prevention.\u003c/p\u003e\n\u003cp\u003eOC is one of the markers and specific indicators of bone formation; CTX and PINP are both extremely sensitive indicators of bone turnover.\u0026nbsp;\u003csup\u003e29\u003c/sup\u003e Of these, CTX is more sensitive to variations in bone volume and bone integrity of the femoral neck than the others.\u0026nbsp;\u003csup\u003e15\u003c/sup\u003e PINP reflects the rate of type I collagen synthesis and bone turnover; the greater the PINP concentration, the more active the bone turnover.\u0026nbsp;\u003csup\u003e30,31\u003c/sup\u003e We must be especially mindful of the potential impact of BTM variability on test outcomes when detecting them. Sources of pre-analytic variability in BTM measurements mainly include age, sex, circadian rhythms, and food intake or fasting status. We chose seven-month-old rabbits that are sexually mature since research has shown that BTMs stay stable and follow typical levels of sex steroids throughout adulthood. The largest variations in the circadian rhythm effect on CTX were seen in research by Schini et al.\u0026nbsp;\u003csup\u003e32\u003c/sup\u003e with minimums between 11:00 and 15:00 p.m. and peaks between 1:30 and 4:30 a.m. The patterns of OC and PINP\u0026apos;s rhythms were comparable, with higher levels at night and lower levels in the afternoon. However, there was not much variance, with PINP exhibiting the least amount of change. The majority of research indicates that both men and women\u0026apos;s PINP lack a circadian rhythm.\u0026nbsp;\u003csup\u003e33\u003c/sup\u003e Furthermore, BTM was significantly impacted by food consumption and fasting state. Eating in the morning decreased PINP, CTX, and OC, with CTX having the biggest impact; fasting decreased the diurnal variation in CTX from 35% to 40% to 9% to 16%.\u0026nbsp;\u003csup\u003e32\u003c/sup\u003e As a result, we fasted the rabbits overnight and collected blood samples the next morning between 7 and 10 a.m.\u0026nbsp;\u003csup\u003e34\u003c/sup\u003e Consistent with previous findings, our study revealed that serum OC, CTX, and PINP were markedly higher in the OP group than in the Sham group.\u0026nbsp;\u003csup\u003e35\u003c/sup\u003e This suggests that serum OC, CTX, and PINP can reflect changes in bone metabolism and bone mass and assist in the early diagnosis and treatment of osteoporosis. It is worth highlighting that in our study, both CTX and PINP underwent a large increase from the 1st postoperative month, whereas OC changed dramatically from the 2nd postoperative month, and the explanation of the delayed response to OC may be related to the use of dexamethasone. It has been shown that prolonged use of GC leads to impaired osteoblast function and reduced OC levels, which is attributed to osteoblast-targeted disruption of GC signaling, thereby attenuating the inhibition of OC synthesis and blocking OC synthesis.\u0026nbsp;\u003csup\u003e36\u003c/sup\u003e Additionally, during the first few months of GC use, there is a significant loss of bone because GC causes mature osteoblasts and bone cell to undergo apoptosis, which reduces the production of new bone. GC also results in enhanced osteoclastogenesis, an increased lifespan and number of mature osteoclasts, and decreased osteoclast apoptosis, leading to increased bone resorption.\u0026nbsp;\u003csup\u003e37\u0026ndash;39\u003c/sup\u003e In addition, because the loss of osteoblasts prevents the damaged osteocyte-tubule network from responding to bone damage, this leads to reduced bone strength. GC can also inhibit this pathway of osteoblast differentiation by stimulating the production of Wnt pathway inhibitors, thereby inhibiting bone formation.\u0026nbsp;\u003csup\u003e40\u003c/sup\u003e In a study by Dovio et al.,\u0026nbsp;\u003csup\u003e41\u003c/sup\u003e it was shown that in humans, high-dose, short-term use of GC causes an immediate decrease in OC and PINP and a rapid and transient increase in CTX. This seems to differ somewhat from our results. We reached the following conclusion after analyzing the causes of the discrepancy: First, the dose of GC utilized in their study was 15 mg/kg per day, which is significantly higher than the dose we administered. Research has demonstrated that GC exhibits its effects exclusively on bone turnover, devoid of induction of inflammation, necrosis, or alterations in subarticular bone, when administered at a dose ranging from 0.5 to 1 mg/kg/day. Doses falling below 0.5 mg/kg/day fail to elicit substantial effects on bone changes.\u0026nbsp;\u003csup\u003e42\u003c/sup\u003e Therefore, we use small doses of continuous dosing. Secondly, Dovio et al. measured OC, CTX, and PINP on a daily basis during the treatment period (10 days) and after approximately three months, respectively. Their findings demonstrated that during the treatment period, OC and PINP immediately decreased from day 2, while CTX remained significantly elevated throughout the treatment period. After three months, all BTM levels were significantly elevated. Initial postoperative measurements in our study were conducted one month later. Consequently, we cannot definitively ascertain whether OC and PINP levels decreased during this time period. However, after three months, all BTM levels substantially increased, which is partially consistent with our findings. Additionally, physiological distinctions between humans and rabbits may contribute to the differences. An illustration of this can be observed in the comparatively rapid bone growth and regeneration processes of rabbits, which also possess a heightened metabolic rate and biological activity. Therefore, the aforementioned factors may account for a portion of the distinctions between rabbit and human bone remodeling. Serum CTX-I levels were found to be adversely connected with body weight in a study by Ryszard et al.,\u0026nbsp;\u003csup\u003e43\u003c/sup\u003e although BMD was positively correlated with body weight. This finding may be related to the mechanical loading of bone by fat mass.Serum CTX-I levels were found to be adversely connected with body weight in a study by Ryszard et al., although BMD was positively correlated with body weight. This finding may be related to the mechanical loading of bone by fat mass. In a study by Cheng et al.,\u0026nbsp;\u003csup\u003e44\u003c/sup\u003e it was also shown that bariatric surgery increases bone turnover and causes bone loss, with CTX-1, OC, and PINP all being elevated to varying degrees postoperatively. In our study, we observed a lower magnitude of weight loss in rabbits in the OP group during this four-month period, but there was no significant difference compared to the Sham group (p \u0026gt; 0.05). A study by Liu et al.\u0026nbsp;\u003csup\u003e45\u003c/sup\u003e showed no significant difference (p \u0026gt; 0.05) in OC levels between men with primary OP and age-matched non-OP controls. The reason for the difference in results may be due to the difference in the study population; bone loss is slower in men, and the pattern of bone conversion of OC in men with primary OP remains unclear, with results to be further validated.\u003c/p\u003e\n\u003cp\u003eAlthough serum BTMs can reflect changes in bone metabolism and bone mass, it is unclear which index reflects its correlation with bone mass and bone strength more accurately. Therefore, we conducted further analyses. According to Table 6, we correlated OC, CTX, and PINP with lumbar Lmax, and the results showed that PINP and OC had the strongest and most significant negative correlation with it (r\u0026nbsp;= -0.958, p\u0026nbsp;= 0.000). This suggests that PINP and OC can be used as representative markers for assessing bone quality in macromechanics. Subsequently, we correlated OC, CTX, and PINP with Tb.Th, the microscopic parameter with the greatest influence on macroscopic mechanical strength, and found that CTX had the strongest correlation (r\u0026nbsp;= -0.955, p = 0.000).\u003c/p\u003e\n\u003cp\u003eThrough the above analysis, we found that at the macroscopic spatial level, the greater the values of PINP and OC in the OP process, the lower the Lmax of the lumbar vertebrae and the more severe the osteoporosis, while at the microscopic spatial level, the greater the value of CTX, the thinner the trabeculae of the bone. Our analysis of the reasons for the discrepancy may be due to the fact that PINP and OC serve as markers of bone formation, that the bone formation period is characterized by matrix synthesis and mineralization, and that PINP and OC are protein fragments and proteins released by osteoblastic cells. OC, also originally known as bone Gla-protein, is produced by bone mineralization, and Gla-protein in bone plays an important role in bone strength; therefore, PINP and OC can be used as an important indicator to represent macroscopic mechanical strength.\u0026nbsp;\u003csup\u003e32\u003c/sup\u003e Our findings are somewhat supported by a study by Berezovska et al.\u0026nbsp;\u003csup\u003e46\u003c/sup\u003e that compared osteocalcin knock-out mice with wild-type mice and found that OC levels were linked to fractures and bone fragility. Notably, OC increases bone density and promotes mineralization and bone formation, thereby contributing to bone mechanical strength. However, in our study, the mechanical strength of the lumbar spine decreased as PINP and OC values increased, likely because elevated markers of bone formation typically indicate an active bone formation process. Nonetheless, bone resorption remains active throughout the course of osteoporosis progression; consequently, bone loss may persist, and ongoing bone resorption undermines the structural integrity and stability of the skeleton, ultimately resulting in diminished bone mechanical strength. In addition, elevated markers of bone formation may suggest that the process of bone formation is especially active at specific sites; if the rate of bone formation surpasses the rate of bone mineralization, insufficient mineralization will occur within the bone, resulting in a heterogeneous internal structure. Such heterogeneous bone formation can potentially compromise the mechanical strength of the bone and contribute to its fragility.\u0026nbsp;\u003csup\u003e47\u003c/sup\u003e Thus, elevated bone formation markers may contribute to increased BMD and bone mechanical strength within the normal range. On the contrary, an increase in bone formation markers throughout the course of osteoporosis progression leads to a reduction in the mechanical strength of the bone. CTX is a bone resorption marker and is secreted by osteoclasts. The process of bone resorption is that osteoclasts cause the destruction and degradation of bone trabeculae through contact with them, which leads to an increase in CTX levels. This process contributes to the stabilization of bone microstructure; therefore, we can use the change in CTX levels to reflect the change in trabecular density and the stability of bone microstructure. These three indicators can be used for clinical observation in order to prevent osteoporotic spine fractures.\u003c/p\u003e\n\u003cp\u003eObviously, there are some flaws in our investigation. First, during the discussion of microscopic parameters, only the microscopic spatial structure and not the micromechanical strength were discussed. Second, the discussion of the microspace structure is limited to four linear indicators, and we have not investigated the nonlinear parameters. In addition, our study was limited to an animal model and was not validated in a clinical setting; consequently, we will include nanoindentation experiments in future research to further investigate this in conjunction with nonlinear parameters and clinical patient specimens.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, there is a correlation between bone turnover markers, bone microspace structure, and bone macromechanics. In the OP progression, each microspatial parameter of lumbar cancellous bone was correlated with macroscopic mechanical strength, with Tb.Th showing the strongest correlation. CTX was the most significant correlate of microspace structure for BTMs, whereas PINP and OC were the most significant correlates of macroscopic mechanical strength. Therefore, early detection of CTX can help us to understand the microstructural changes of vertebral cancellous bone in the progression of OP, and early detection of PINP and OC can help us to understand the changes of macroscopic mechanical strength of vertebral cancellous bone in the progression of OP, thereby providing a theoretical basis for a more comprehensive assessment of the severity of spinal osteoporosis and the prevention of spinal osteoporotic fracture in the clinic.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANOVA: Analysis of variance; BMD: Bone mineral density; CTX: 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\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLD, ZYB designed the study. WW, WL, and ZJ performed the statistical analysis. JYH drafted the manuscript. XW, XN and JYH were responsible for data collection and outcomes evaluation. LD and ZYB reviewed and edited the manuscript. All authors read and approved the fnal manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Cadre health committee Program of China (21BJZ40) and Science and Technology Plan Project of Sichuan Province (2023NSFSC0664) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author Yuhao Jia on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll participants signed a written informed consent form, and the study protocol was approved by the Ethics Committee of the General Hospital of Western Theater Command. All methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChai H, Ge J, Li L, Li J, Ye Y. Hypertension is associated with osteoporosis: a case-control study in Chinese postmenopausal women. \u003cem\u003eBMC Musculoskelet Disord\u003c/em\u003e. 2021;22(1):253. doi:10.1186/s12891-021-04124-9\u003c/li\u003e\n\u003cli\u003eZeng Q, Li N, Wang Q, et al. 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Bone quality: the determinants of bone strength and fragility. \u003cem\u003eSports Med Auckl NZ\u003c/em\u003e. 2014;44(1):37-53. doi:10.1007/s40279-013-0100-7\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rabbit, Osteoporosis, Spinal osteoporotic fracture, Macromechanics, Microspatial structure, Bone turnover markers","lastPublishedDoi":"10.21203/rs.3.rs-3863396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3863396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper established an osteoporotic rabbit model by depopulation and the glucocorticoid method, investigated the weights of bone micro-parameters in macro-mechanics during OP progression, preliminary elucidated micro-mechanisms, and screened out bone turnover markers (BTMs) that have a strong correlation with bone macro-mechanical strength and microscopic spatial structure to provide the theoretical basis for OP and OP fracture.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: 64 female White rabbits were chosen and assigned to two groups: one that underwent a sham operation (Sham group, n = 32) and the other that served as an osteoporosis model (OP group, n = 32). At four different postoperative time points (T = 0, 1, 2, and 4 months), respectively. The white rabbits in the Sham group and the OP group were randomly divided into four groups (n = 8) each. Dual-energy X-ray absorptiometry (DXA) was used to determine the lumbar bone mineral density (BMD) at various time intervals (T = 0, 1, 2, and 4 months), and serum BTMs were found using an ELISA test after blood was drawn and the animals were put to death. Axial compression testing and micro-CT were used to assess and characterise the cancellous bone in the lumbar spine specimens.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Lumbar BMD, lumbar Lmax, Tb.Th, Tb.N, and BV/TV all steadily declined as OP progressed, while OC, PINP, CTX, and Tb.Sp all gradually rose. All bone microspatial characteristics were strongly linked with Lmax (p = 0.000) according to a person linear correlation analysis, with the best association found between Tb.Th and lumbar Lmax (r = 0.924, p = 0.000). PINP and OC had the strongest connections with lumbar Lmax (r = -0.958, p = 0.000), whereas CTX had the strongest correlation with Tb.Th (r = -0.955, p = 0.000), according to a correlation analysis of serum BTMs with bone strength and sensitive microspatial measures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion: All lumbar cancellous bone microspatial parameters were correlated with macroscopic mechanical strength during OP progression, with Tb.Th having the strongest correlation. For BTMs, CTX had the strongest correlation with microspatial structure, and PINP and OC had the strongest correlation with macroscopic mechanical strength.\u003c/p\u003e","manuscriptTitle":"Correlation of serum bone turnover markers with microstructure and macroscopic mechanical strength of lumbar cancellous bone during progression of osteoporosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-22 14:53:19","doi":"10.21203/rs.3.rs-3863396/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"991acd3d-b48f-4fc0-9f31-32fbeb48dc24","owner":[],"postedDate":"January 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-08T05:58:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-22 14:53:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3863396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3863396","identity":"rs-3863396","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}