Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Objective:To predict Chinese materia medica that may prevent and treat coronary microvascular dysfunction (CMD) by identifying disease core targets.Methods:CMD- related targets were obtained through GeneCards and OMIM databases. Subnetworks were extracted by using MCODE plugin in Cytoscape 3.9.1. Core targets of subnetworks were obtained by using cytoNCA plugin. GO function and KEGG pathway enrichment analysis for core targets were performed by using Metascape. Coremine Medical database was used to match targets with Chinese materia medica. Obtained Chinese materia medica was screened, and their properties and tastes, meridians and efficacy categories were under statistics.Results:Totally 3 859 disease-related targets were screened and five subnetworks were obtained. An in-depth study of MCODE1 yielded ten core targets, including IL-1β, IL6, TNF, STAT3, AKT1, ACTB, VEGFA, GAPDH, TP53, and ALB. GO functional enrichment analysis showed that these core targets were mainly involved in biological processes, such as positive regulation of gene expression, positive regulation of transcription, DNA template, and negative regulation of gene expression. KEGG pathway enrichment analysis identified 67 signaling pathways, including the AGEs-RAGE signaling pathway, HIF-1 signaling pathway, adipocytokine signaling pathway, fluid shear stress, and atherosclerosis. The researchers identified 36 kinds of Chinese materia medica associated with the ten core targets, including Salviea Miltiorrhizae Radix et Rhizoma, Chuanxiaong Rhizoma, Carthami Flos, Paeoniae Radix Rubra, Coptidis Rhizoma, Ginseng Radix et Rhizoma, Ophiopogonis Radix, Schisandrae Chinensis Fructus, Cinnamomi Cortex, Nelumbinis Semen, and Valerianae Jatamansi Rhizoma et Radix among 880 herbs.Conclusion:This study predicts 36 kinds of Chinese materia medica that have the effect of preventing and treating CMD, which can provide research ideas for the development of new drugs.

The present study aims to screen and evaluate the early clinical predictors for type 2 diabetes mellitus (T2DM) patients with mild cognitive impairment (MCI) and dementia in Hunan province. A cross-sectional study was conducted from May 2023 to October 2023 to collect data on long-term T2DM patients who settled in Hunan province and were treated in the Department of Geriatrology at Xiangya Hospital of Central South University. The patients were grouped according to the Montreal Cognitive Assessment (MoCA) scale. Basic patient information and multiple serum markers were collected, and differences between groups were compared using one-way ANOVA or Kruskal-Wallis (KW) tests. The multivariate logistic regression analysis was utilized to assess risk factors and Nomogram models were constructed. The logistic regression analysis showed that years of education and serum levels of 1, 5-AG were related factors for the progression of T2DM to T2DM with MCI, and body weight, years of education and FPN levels affected the progression of T2DM with MCI to T2DM with dementia. Based on this, two Nomogram risk prediction models were established. The area under the curve (AUC) of the Nomogram model predicting T2DM progression to T2DM combined with MCI was 0.741, and the AUC of the Nomogram model predicting T2DM combined with MCI progression to T2DM combined with dementia was 0.734. The calibration curves (DCA) of the two models in the training and validation sets were symmetrically distributed near the diagonal line, indicating that the models in the training and validation sets could match each other. In summary, body weight, years of education, and serum HDL-3, FPN, and 1, 5-AG levels are associated with the development of MCI and dementia in T2DM patients. The Nomogram models constructed based on these factors can predict the risk of MCI and dementia in T2DM patients, providing a basis for clinical decision-making.

The present study aims to screen and evaluate the early clinical predictors for type 2 diabetes mellitus (T2DM) patients with mild cognitive impairment (MCI) and dementia in Hunan province. A cross-sectional study was conducted from May 2023 to October 2023 to collect data on long-term T2DM patients who settled in Hunan province and were treated in the Department of Geriatrology at Xiangya Hospital of Central South University. The patients were grouped according to the Montreal Cognitive Assessment (MoCA) scale. Basic patient information and multiple serum markers were collected, and differences between groups were compared using one-way ANOVA or Kruskal-Wallis (KW) tests. The multivariate logistic regression analysis was utilized to assess risk factors and Nomogram models were constructed. The logistic regression analysis showed that years of education and serum levels of 1, 5-AG were related factors for the progression of T2DM to T2DM with MCI, and body weight, years of education and FPN levels affected the progression of T2DM with MCI to T2DM with dementia. Based on this, two Nomogram risk prediction models were established. The area under the curve (AUC) of the Nomogram model predicting T2DM progression to T2DM combined with MCI was 0.741, and the AUC of the Nomogram model predicting T2DM combined with MCI progression to T2DM combined with dementia was 0.734. The calibration curves (DCA) of the two models in the training and validation sets were symmetrically distributed near the diagonal line, indicating that the models in the training and validation sets could match each other. In summary, body weight, years of education, and serum HDL-3, FPN, and 1, 5-AG levels are associated with the development of MCI and dementia in T2DM patients. The Nomogram models constructed based on these factors can predict the risk of MCI and dementia in T2DM patients, providing a basis for clinical decision-making.

OBJECTIVE: To introduce a scout view scanning technique of back-forward bending CT (BFB-CT) in simulated surgical position for evaluating the remaining real angle and flexibility of thoracolumbar kyphosis secondary to old osteoporotic vertebral compression fracture. METHODS: A total of 28 patients with thoracolumbar kyphosis secondary to old osteoporotic vertebral compression fracture who met the selection criteria between June 2018 and December 2021 were included in the study. There were 6 males and 22 females with an average age of 69.5 years (range, 56-92 years). The injured vertebra were located at T ₁₀-L ₂, including 11 cases of single thoracic fracture, 11 cases of single lumbar fracture, and 6 cases of multiple thoracolumbar fractures. The disease duration ranged from 3 weeks to 36 months, with a median of 5 months. All patients received examinations of BFB-CT and standing lateral full-spine X-ray (SLFSX). The thoracic kyphosis (TK), thoracolumbar kyphosis (TLK), local kyphosis of injured vertebra (LKIV), lumbar lordosis (LL), and the sagittal vertical axis (SVA) were measured. Referring to the calculation method of scoliosis flexibility, the kyphosis flexibility of thoracic, thoracolumbar, and injured vertebra were calculated respectively. The sagittal parameters measured by the two methods were compared, and the correlation of the parameters measured by the two methods was analyzed by Pearson correlation. RESULTS: Except LL ( P>0.05), TK, TLK, LKIV, and SVA measured by BFB-CT were significantly lower than those measured by SLFSX ( P<0.05). The flexibilities of thoracic, thoracolumbar, and injured vertebra were 34.1%±18.8%, 36.2%±13.8%, and 39.3%±18.6%, respectively. Correlation analysis showed that the sagittal parameters measured by the two methods were positively correlated ( P<0.001), and the correlation coefficients of TK, TLK, LKIV, and SVA were 0.900, 0.730, 0.700, and 0.680, respectively. CONCLUSION Thoracolumbar kyphosis secondary to old osteoporotic vertebral compression fracture shows an excellent flexibility and BFB-CT in simulated surgical position can obtain the remaining real angle which need to be corrected surgically.
Male ; Female ; Humans ; Aged ; Fractures, Compression/surgery* ; Spinal Fractures/diagnostic imaging* ; Lumbar Vertebrae/surgery* ; Thoracic Vertebrae/surgery* ; Kyphosis/surgery* ; Osteoporotic Fractures/surgery* ; Lordosis ; Tomography, X-Ray Computed ; Retrospective Studies

OBJECTIVE: To investigate the changes in spinal-pelvic sagittal parameters from preoperative standing to prone position in old traumatic spinal fractures with kyphosis. METHODS: The clinical data of 36 patients admitted between December 2016 and June 2021 for surgical treatment of old traumatic spinal fractures with kyphosis, including 7 males and 29 females, aged from 50 to 79 years (mean, 63.9 years), were retrospectively analyzed. Lesion segments included 2 cases of T ₁₁, 12 cases of T ₁₂, 2 cases of T _{11, 12}, 4 cases of T ₁₂ and L ₁, 12 cases of L ₁, 2 cases of L ₂, 1 case of L _{2, 3}, and 1 case of L ₃. The disease duration ranged from 4 to 120 months, with an average of 19.6 months. Surgical procedures included Smith-Petersen osteotomy in 4 cases, Ponte osteotomy in 6 cases, pedicle subtraction osteotomy in 2 cases, and improved fourth level osteotomy in 18 cases; the remaining 6 cases were not osteotomized. The bone mineral density ranged from -3.0 to 0.5 T, with a mean of -1.62 T. The spinal-pelvic sagittal parameters from preoperative standing to prone positions were measured, including local kyphosis Cobb angle (LKCA), thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), and PI and LL mismatch (PI-LL). The kyphotic flexibility=(preoperative standing LKCA-preoperative prone LKCA)/preoperative standing LKCA×100%. Spinal-pelvic sagittal parameters were compared between standing position and prone position before operation, and Pearson correlation was used to judge the correlation between the parameters of standing position and prone position before operation. RESULTS: When the position changed from standing to prone, LKCA and TK decreased significantly ( P<0.05), while SS, LL, PT, and PI-LL had no significant difference ( P>0.05). Pearson correlation analysis showed that LL was significantly correlated with SS and PI-LL in both standing and prone positions ( P<0.05), and the correlation strength between LL and SS in prone position was higher than that in standing position. In the standing position, LKCA was significantly correlated with SS and PT ( P<0.05). However, when the position changed from standing to prone, the correlation between LKCA and SS and PT disappeared, while PT and PI-LL was positive correlation ( P<0.05). The kyphotic flexibility was 25.13%-78.79%, with an average of 33.85%. CONCLUSION For the patients of old traumatic spinal fractures with kyphosis, the preoperative LKCA and TK decrease significantly from standing position to prone position, and the correlation between spinal and pelvic parameters also changed, which should be taken into account in the formulation of preoperative surgical plan.
Male ; Female ; Humans ; Spinal Fractures/surgery* ; Standing Position ; Retrospective Studies ; Lumbar Vertebrae/surgery* ; Kyphosis/surgery* ; Lordosis/surgery*

Objective To compare the biomechanical effects of contiguous three-level cervical Hybrid surgery[anterior cervical discectomy and fusion (ACDF) + cervical disc arthroplasty ( CDA)] and three-level ACDF. Methods The finite element model of C1-T1 cervical-thoracic spine was developed based on CT data. Three models were simulated by the implantation of Prestige LP and Zero-P prostheses, including two Hybrid models (AFA, Prestige LP implanted at C3-4 and C5-6 segments and Zero-P implanted at C4-5 segment; FAF, Zero-P implanted at C3-4 and C5-6 segments and Prestige LP implanted at C4-5 segment) and three-level ACDF model(FFF). The changes in range of motion (ROM) of adjacent levels during flexion, extension, lateral bending and axial rotation, the overall ROM, as well as the intradiscal pressure ( IDP) and facet contact force ( FCF) of adjacent levels were compared. Results The ROM in adjacent levels and the overall ROM of the AFA modelwere closer to the intact model, and the maximum increases in the ROM of the adjacent levels for the FAF and FFF models were 15. 0% and 23. 4% , respectively. For AFA, FAF and FFF models, the maximum increases in the maximum IDP of adjacent levels were 19. 0% , 66. 7% , 147. 6% , and the maximum increases in FCF were 17. 4% , 55. 7% , 80. 1% , respectively. Conclusions This study provides biomechanical basis for three-level cervical Hybrid surgery in treating patients with the contiguous three-level cervical degenerative disc disease.