BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Space medicine,as a comprehensive discipline ensuring the safety,health,and efficient performance of astronauts during manned space missions,focuses on elucidating the underlying mechanisms of multi-system physiological effects induced by extreme space environments and developing corresponding protective strategies.With China's space program transitioning into an application and development phase,space medical experiments—a critical domain within space applications—face significant opportunities and challenges.This paper reviews the international development trend in the field of medical experiments and the progress in China from perspectives including platform system construction,utilization of novel technologies,and scientific discoveries.It further outlines the engineering framework,guiding ideology,and key research directions for space medical experiments under China's Space Station Application and Development Project.Deliberations and prospects center on the in-depth analysis of the adaptation law of life in space flight,the application of big data and artificial intelligence technology,the emerging challenges it faces,and the scientific research organization models.This work aims to provide a reference for the development of space medical experiment field in China.

Objective To explore the effect of different post-processing methods of total spinal CT angiography(CTA)for displaying spinal dural arteriovenous fistula(SDAVF).Methods Total spinal CTA data of 55 patients with SDAVF were retrospectively analyzed.Traditional post-processing of original CTA images(modified tissue growth boneless volume rendering[VR]and full-range axial maximum intensity projection[MIP])were performed,while the axial,sagittal and coronal MIP reconstructions,axial,sagittal and coronal VR reconstructions,as well as axial,sagittal and coronal MIP+VR reconstructions of original CTA images on lesion layers were completed,respectively.Taken digital subtraction angiography(DSA)as the gold standards,a 5-point scale was used to subjectively evaluate the effect of displaying the location,the range and feeding artery of fistula shown on CTA images based on different post-processing methods.Results No significant difference of subjective score of location nor feeding artery of fistula was found among axial MIP,VR and MIP+VR images(all P＞0.05),which were all higher than that of CTA images reconstructed using other post-processing methods(all P＜0.05).Meanwhile,no significant difference of subjective scores of the range of SDAVF was detected among sagittal MIP,VR and MIP+VR images(all P＞0.05),which were all higher than that of CTA images obtained using other post-processing methods(all P＜0.05).Conclusion The location and feeding artery of SDAVF could be observed based on axial MIP,VR and MIP+VR reconstructions of the total spinal CTA,while sagittal MIP,VR and MIP+VR reconstructions were conducive to display the range of SDAVF.Combination of multiple post-processing methods was helpful for comprehensive understanding the composition and range of SDAVF.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Objective To explore the effect of different post-processing methods of total spinal CT angiography(CTA)for displaying spinal dural arteriovenous fistula(SDAVF).Methods Total spinal CTA data of 55 patients with SDAVF were retrospectively analyzed.Traditional post-processing of original CTA images(modified tissue growth boneless volume rendering[VR]and full-range axial maximum intensity projection[MIP])were performed,while the axial,sagittal and coronal MIP reconstructions,axial,sagittal and coronal VR reconstructions,as well as axial,sagittal and coronal MIP+VR reconstructions of original CTA images on lesion layers were completed,respectively.Taken digital subtraction angiography(DSA)as the gold standards,a 5-point scale was used to subjectively evaluate the effect of displaying the location,the range and feeding artery of fistula shown on CTA images based on different post-processing methods.Results No significant difference of subjective score of location nor feeding artery of fistula was found among axial MIP,VR and MIP+VR images(all P＞0.05),which were all higher than that of CTA images reconstructed using other post-processing methods(all P＜0.05).Meanwhile,no significant difference of subjective scores of the range of SDAVF was detected among sagittal MIP,VR and MIP+VR images(all P＞0.05),which were all higher than that of CTA images obtained using other post-processing methods(all P＜0.05).Conclusion The location and feeding artery of SDAVF could be observed based on axial MIP,VR and MIP+VR reconstructions of the total spinal CTA,while sagittal MIP,VR and MIP+VR reconstructions were conducive to display the range of SDAVF.Combination of multiple post-processing methods was helpful for comprehensive understanding the composition and range of SDAVF.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective Explore a non-contact physiological and psychological detection model based on facial video in simulations of weightlessness effects,research new methods for non-contact heart rate and negative mood state detection in long-term simulations of weightlessness effect analysis.Methods Construct a non-contact physiological and psychological data collection system for fusion analysis of visible light and thermal infrared videos.Collect physiological and psychological data of volunteers in the"Earth Star-Ⅱ"90-day head-down bed rest experiment.A non-contact heart rate detection model based on GCN facial multi-region feature fusion and a non-contact negative mood state detection model considering data reliability were constructed,and the effectiveness of the models were validated with finger clip heart rate and POMS-SF scale as labels.Results The experimental results show that the average difference in the Bland-Altman plot of the non-contact heart rate detection model is-1.26 bpm,and 96.3%of value error detection data falls within the 95%confidence interval,indicating a high consistency between the model detected heart rate and the finger clip heart rate.The non-contact negative mood state detection model achieves an accuracy of>0.85 for detecting tension,depression,anger,and fatigue.Features such as heart rate,AU06,eye gaze,and head pose were observed to be important to mood state detection.Conclusion Non-contact physiological and psychological detection methods not only can be utilized for long-term physiological analysis in simulations of weightlessness effects,but also provide a novel technical approach for on-orbit astronauts health assurance during long-term space flight in the future.