Objective To explore the related risk factors of osteosarcopenia (OS) in elderly patients with type 2 diabetes mellitus (T2DM) and to evaluate their predictive value. Methods We selected 409 elderly patients with T2DM from our hospital between June 2021 and December 2024 as the study subjects, and divided them into an OS occurrence group and a non-occurrence group based on whether they were diagnosed with OS. Results Among the 409 elderly patients with T2DM included, 93 were diagnosed with OS, yielding a prevalence rate of 22.73%. Spearman correlation analysis revealed a significant association between lumbar spine BMD and T-scores with age, history of previous fractures, fasting plasma glucose (FPG), procollagen type I N-terminal propeptide (PINP), osteocalcin (OC), and 25-hydroxyvitamin D (25(OH)D). Gender (OR=0.193), Body Mass Index (BMI) (OR=0.254), history of previous fractures (OR=8.883), FPG (OR=0.543), Total Cholesterol (TC) (OR=3.684), High-Density Lipoprotein Cholesterol (HDL-C) (OR=86.024), PINP (OR=0.818), and OC (OR=0.526) are identified as influential factors for the occurrence of OS in elderly patients with T2DM. The combined prediction of these variables yields a sensitivity of 96.5%, a specificity of 97.8%, and an area under the curve (AUC) of 0.992 for the occurrence of OS in elderly patients with T2DM, indicating an excellent predictive performance. Conclusion The following factors—gender, BMI, history of previous fractures, FPG, TC, HDL-C, PINP, and OC—are influential in the occurrence of OS among elderly patients with T2DM. Formulating intervention measures based on these influencing factors can provide assistance in preventing and treating the occurrence of OS.

Background The contamination of public baths with Legionella pneumophila contamination has become a growing public health concern in recent years. However, research on its association with bacterial community characteristics in water samples remains limited. The integration of 16S rRNA sequencing and random forest modeling provides a new approach to elucidate the bacterial community characteristics of public bath water and their association with Legionella pneumophila contamination. Objective To investigate the bacterial community structure and diversity of public bath water in Shanghai, explore the association between Legionella pneumophila contamination and bacterial community characteristics, and identify key bacterial genera associated with contamination, thereby providing a scientific basis for formulating hygiene management regulations for public bath water. Methods From February to March 2023, water samples were collected from ten public baths in Shanghai which were selected based on business scale, regional distribution, and functional differences. Water quality parameters were evaluated, and the samples were categorized into Legionella-positive and Legionella-negative groups based on the detection results of Legionella pneumophila. The bacterial community structure, α-diversity, and β-diversity were analyzed using 16S rRNA sequencing. Redundancy analysis (RDA) was employed to examine the relationship between physicochemical factors and bacterial community diversity. A random forest model was employed to identify key bacterial genera distinguishing the two groups, with the importance of genera being evaluated based on the mean decrease accuracy (MDA). Results The oxygen consumption in the Legionella-positive group was significantly lower than that in the Legionella-negative group (mean values: 1.85 mg·L⁻¹ vs. 6.81 mg·L⁻¹, P< 0.05), while no significant differences were observed in other physicochemical indicators. The sequencing results revealed a total of 27 bacterial phyla and 454 bacterial genera, with Proteobacteria (63.00%) being the dominant phylum. The dominant genera included Pelomonas (8.50%), Acidovorax (8.13%), Mycobacterium (7.93%), and Acinetobacter (6.59%). The α-diversity analysis indicated that bacterial community richness (Chao1 and ACE indices) was significantly higher in the Legionella-positive group than in the Legionella-negative group (P<0.01). The β-diversity analysis showed no significant difference in the bacterial community structure between the two groups (P>0.05). The RDA analysis demonstrated that the bacterial community diversity was positively correlated with pH and negatively correlated with oxygen consumption and free residual chlorine. The RDA1 and RDA2 explained 23.92% and 21.30% of the bacterial community diversity, respectively. The random forest model identified 20 key genera significantly influencing the microbial community distribution between the two groups, including unclassified_Bradyrhizobiaceae (MDA=2.42), Meiothermus (MDA=2.37), and Flavihumibacter (MDA=2.26). Conclusion The diversity of bacterial communities in public bath water is influenced by pH, oxygen consumption, and free residual chlorine. Samples contaminated with Legionella pneumophila exhibit greater microbial richness and contain characteristic key bacterial genera that contribute to community differences. Machine learning random forest technology helps identify these distinctive key bacterial genera. The findings provide a basis for carrying out risk early warning strategies in such settings.

Objective: To investigate the association between brain and muscle Arnt like protein 1( BMAL 1) gene and ambulatory blood pressure (ABP) parameters in college students, and to explore the influence of the interaction between the gene and weight status on the ABP levels, so as to provide reference for early prevention of chronic cardiovascular diseases related to hypertension. Methods: During September 2022 to June 2024, a total of 510 college students were recruited from a university in Changsha, China for on site questionnaire investigation, physical examination, ABP monitoring and genotyping testing. Multiple linear regression method was used to explore the association between the BMAL 1 gene and ABP indicators. An interaction term was included in the general linear model of multiple linear regression to analyze the interactive effects of BMAL 1 gene polymorphisms and weight status on ABP levels. Results: The prevalence of abnormal 24 hour blood pressure, abnormal daytime blood pressure, and abnormal nighttime blood pressure were 3.3%, 3.1%, and 3.9%, respectively. Multiple linear regression analysis showed that the BMAL 1/rs7950226 polymorphism was positively correlated with the 24 hour diastolic blood pressure(DBP) and the daytime DBP level after adjusting for gender, age, and body mass index( β =0.87,0.99, both P <0.05). Also, interaction between BMAL 1/ rs 11022775 and weight status on the nighttime DBP level ( P interaction =0.03) was found. The CC genotype carriers had significantly higher nighttime DBP level ( β =3.52, P <0.05) among overweight/obesity college students, but no differences in nocturnal DBP levels were observed between CC genotype carriers and TT+CT genotype carriers among college students with normal body weight( P > 0.05). Conclusions The rs 7950226 polymorphism is associated with 24 hours DBP and daytime DBP levels. Significant interaction between rs 11022775 with weight status on the nighttime DBP level is found among college students.

Objective: To investigate the heritability of axial length (AL) by comparing the consistency of AL in monozygotic (MZ) and dizygotic (DZ) twins, thereby providing data support for research on the genetic mechanisms and prevention and control practices of myopia in children and adolescents. Methods: A total of 137 twin pairs aged 3 to 16 years who attended the Optometry Center of the First Affiliated Hospital of Anhui Medical University from January 2021 to December 2024 were enrolled, comprising 79 DZ pairs and 58 MZ pairs. Biometry was used to measure children s axial length, and structural equation modeling within the OpenMx package was applied to calculate the heritability of axial length. Results: The overall mean axial length of the twin cohort was (23.7±1.5) mm. The intraclass correlation coefficient (ICC) for axial length in all twins was 0.82 (95% CI =0.76-0.87) ( P < 0.05 ). The ICC for MZ twins was 0.97 (95% CI =0.94-0.98), which was higher than that for DZ twins ( ICC =0.71, 95% CI =0.58-0.80) (both P <0.05). Maximum likelihood estimation using OpenMx revealed that the additive genetic plus unique environmental (AE) model provided the best fit. Specifically, additive genetic factors (A) accounted for 93.63% (95% CI =90.31%-95.69%) of the total variance, while unique environmental factors (E) accounted for 6.37% (95% CI =4.31%-9.69%). Conclusion Axial length in children is predominantly influenced by genetic factors, while unique environmental factors also play a contributory role.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

To address the scarcity of annotated data for pediatric abdominal CT imaging and the insufficient generalization capability of existing models, we constructed a self-supervised pretraining architecture tailored for pediatric CT domain adaptation based on the visual foundation model DINOv3, and validated its performance in the task of pediatric abdominal multi-organ segmentation.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

Objective To investigate the relationship between the radial-ulnar ratio,lateral lunate angle of radius and height loss of radius after palmar locking plate internal fixation for distal radius fractures.Methods A total of 158 patients with distal radius fractures treated with palmar locking plate internal fixation in our hospital from March 2020 to September 2023 were selected.According to the height of radius loss after operation,the patients were divided into non-radius loss group(41 cases,<2 mm),mild to moderate radius loss group(32 cases,2 to 5 mm)and severe radius loss group(85 cases,>5 mm),and the clinical data of patients in the three groups were compared.Multivariate Logistic regression analysis was used to analyze the risk factors affecting height loss of radius.Locally weighted scatterplot smoothing(LOWESS)method was used to analyze the two-dimensional curve relationship of continuous variables.Restricted cubic spline(RCS)and threshold effect were used to analyze the relationship between the radial-ulnar ratio,lateral lunate angle of radius and height loss of radius after operation.Results The age of patients in the severe radius loss group was significantly higher than those in the non-radius loss group and the mild to moderate radius loss group(P<0.05),and the age of patients in the mild to moderate radius loss group was significantly higher than that in the non-radius loss group(P<0.05).Female patients and patients with osteoporosis and fracture type C were more likely to have height loss of radius(P<0.05).There were significant differences in patient-rated wrist evaluation(PRWE)score,disabilities of the arm,shoulder and hand(DASH)score,dorsal extension,palmar curvature,ulnar deviation,radial deviation,radial-ulnar ratio,and lateral lunate angle of radius of patients at 3 and 6 months after operation among three groups(P<0.001).The first prediction model based on age,gender,osteoporosis,fracture type,PRWE score,DASH score,dorsal extension,palmar curvature,ulnar deviation,and radial deviation and the second prediction model based on age,gender,osteoporosis,fracture type,PRWE score,DASH score,dorsal extension,palmar curvature,ulnar deviation,radial deviation,radial-ulnar ratio,and lateral lunate angle of radius were subjected to Hosmer-Lemeshow test showed good goodness of fit.LOWESS analysis showed that age,PRWE score,DASH score,dorsal extension,palmar curvature,ulnar deviation,radial deviation,radial-ulnar ratio,and lateral lunate angle of radius had a certain nonlinear relationship with the height loss of radius.RCS and threshold effect analysis showed that the probability of postoperative radius loss increased with the increase of radial-ulnar ratio in patients with distal radius fractures and radial-ulnar ratio≥13.254(P<0.001).The probability of postoperative radius loss decreased with the increase of the lateral lunate angle of radius in patients with distal radius fractures and lateral lunate angle of radius≤11.068°(P<0.001).Conclusion There was a positive correlation between the radial-ulnar ratio and the height loss of radius,and a negative correlation between the lateral lunate angle of radius and the height loss of radius after palmar locking plate internal fixation for distal radius fractures.

AIM:To determine the concentration of ARV-471(a representative PROTAC drug)in mice plasma by establishing an HPLC-MS/MS method and to apply this method in pharmacokinetic studies in mice.METHODS:Verapamil was taken as the inter-nal standard,the mice plasma samples were extract-ed by methanol.After centrifugation,the superna-tant was analyzed by liquid chromatography-mass spectroscopy(LC-MS/MS).Chromatographic col-umn:ACQUITY UPLC HSS T3(1.8 μm,2.1 mm × 50 mm);The mobile phase consists of acetonitrile(containing 0.1％formic acid)and 2 mmol/L ammoni-um formate aqueous solution(containing 0.1％for-mic acid)for gradient elution;flow-rate of 0.6 mL/min;injection volume:2 μL.The electrospray ioniza-tion(ESI)is employed,operating in positive ion scan-ning mode with multiple reaction monitoring(MRM)detection.The specificity,standard curve and quanti-fication limit,precision and accuracy,recovery rate and matrix effect,stability and dilution reliability of this method were examined.Furthermore,the plas-ma concentration and pharmacokinetic parameters of ARV-471 in mice after intravenous injection of 5 mg/kg and oral gavage of 30 mg/kg were deter-mined and calculated.RESULTS:The results dem-onstrate that ARV-471 exhibits a good linear rela-tionship within the concentration range of 2.0 to 2 000.0 ng/mL.The intra-and inter-accuracy were between 80.0％and 120.0％,with the intra-and in-ter-precision less than 15％.The results of method-ological study of specificity,matrix effect,stability conformed to the requirements of the guideline.Pharmacokinetic parameters reveal that after oral administration of 30 mg/kg ARV-471 to male and fe-male mice,Cmax were(2 947.19±454.77)and(2 682.02±342.23)ng·mL-1;AUC0-twere(23 357.37±3 488.00)and(20 161.23±1 871.32)ng·h·mL-1;T1/2were(3.11±0.18)and(2.93±0.62)h.Tmax were(1.83±0.41)and(2.00±0.00)h for male and fe-male mice,respectively.After intravenous adminis-tration of 5 mg/kg ARV-471 to male and female mice,the AUC0-t values were found to be(18 219.07±2 059.41)and(17 238.01±2 380.55)ng·h·mL-1;T1/2 values were(2.76±0.23)and(2.73±0.20)h;The absolute bio-availability of ARV-471 were deter-mined to be(19.49±1.81)％and(21.37±3.19)％for male and female mice,respectively.CONCLU-SION:This study establishes a rapid and effective method for the pharmacokinetic research of ARV-471,laying the foundation for the pharmacokinetic studies of PROTAC drugs.