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.

High mobility group box protein 1(HMGB1)is one of the most widely expressed protein member in the HMGs family,which is well known for its involvement in the body inflammatory response.Previous researches have found that it plays a significant role in cell migration,immune identification and neuroprotection.Spinal cord injury is a disease that causes severe damage to the nervous system,and neural circuits are disrupted after a spinal cord injury,which leads to many conditions including ischemia and hypoxia,inflammatory responses,demyelinating lesions,and glial scar formation that are detrimental to nerve regeneration and repair,making it one of the most difficult diseases to treat in the modern spinal surgery field.HMGB1 is upregulated after spinal cord injury,thereby regulating neuroinflam-matory responses,and participating in the neuronal apoptosis,promoting neuronal regeneration,and inducing neural stem cell differentiation and migration,which plays an important role in the process of neural function recovery.This paper summarizes the structure and function of HMGB1,as well as its role in spinal cord injury,in order to provide direction for founding therapeutic target for neurological function recovery after spinal cord injury.

Given the lack of annotations for key lung organs and tissues in existing public datasets,this study collected 863 cases of chest CT scan images and constructed the first comprehensive dataset containing annotations of pulmonary vessels,airways,and nodules using a semi-automated method that combines computer vision algorithms with manual corrections by radiologists.On this basis,a lung nodule segmentation model based on multi-task learning is proposed.By incorporating annotations of pulmonary vessels(pulmonary arteries and veins)and the trachea to enhance model's ability to learn lung features,the proposed model reduces the false discovery rate in lung nodule detection,and improves generalization ability.Additionally,the use of larger image patches further optimizes model performance.The trained VAAN_128 model achieves the best performance,with a Dice coefficient of 0.694 and a false discovery rate of 0.210 for lung nodule segmentation.Moreover,it simultaneously provides accurate segmentation results of pulmonary vessels and the trachea,assisting in the formulation of more precise diagnosis and treatment plans.Based on the VAAN_128 model,a software system for navigation and localization in biopsy procedures is developed.In clinical practice,this system can assist physicians in accurately locating lung nodules,distinguishing critical tissues,and improving preoperative planning efficiency.This provides precise and efficient technical support for early diagnosis and disease monitoring of lung diseases,and is of great significance for path planning in clinical navigation system and future lung imaging research.

With the widespread application of nuclear technology,the prevention and treatment of radiation damage have become significant issues in the fields of public health and medicine.This article reviews the adverse drug reactions and their monitoring for radioprotective drugs,and discusses their post-marketing re-evaluation in terms of safety,efficacy,economics,and quality standards.Research indicates that while there is a wide variety of radioprotective drugs,safety concerns are prevalent.Future efforts should focus on strengthening the monitoring and management of adverse drug reactions,optimizing drug safety,and exploring the potential of combined drug applications through multidisciplinary collaboration to enhance anti-radiation efficacy.

Objective:To investigate the clinical value of dynamic AI ultrasonic intelligent assisted diagnosis system for preoperative evaluation of thyroid nodules with diameter ≤1.0 cm.Methods:From Apr. 1, 2023, to Dec. 30, 2023, 742 thyroid nodules with diameter ≤1.0 cm were removed from 532 patients with thyroid nodule disease who received surgical treatment in the Department of Thyroid (hernia) of the First Medical Center of the Chinese People’s Liberation Army General Hospital. Among them, 423 were d≤0.5 cm. 319 cases (235 males and 507 females) with 0.5

Objective To explore the therapeutic effect of picroside Ⅱ(P Ⅱ)on diabetes nephropathy(DN)rats by regulating fatty acid synthase(Fas)/fatty acid synthase ligand(FasL)signaling pathway.Methods A DN rat model was constructed by combining high sugar and high-fat diet with streptozotocin(STZ)injection.DN rats were grouped into model group(DN group),low,medium and high dose picroside Ⅱ groups(P-L group,P-M group,P-H group),and high dose picroside Ⅱ+Fas recombinant protein group(P-H+rh-Fas group),with healthy rats as control group,and 18 rats in each group.Fasting blood glucose(FBG),body mass,24-hour urinary protein(24h UTP),and renal function(SCr,BUN)were measured in rats.Hematoxylin-eosin(HE)staining and Masson staining were applied to observe the pathological changes in renal tissue of rats;immunohistochemistry and Western blot were applied to detect the expression of RAGE,COL-Ⅳ and pathway proteins,respectively.Results Compared with the control group,rats in DN group showed thickening of the glomerular basement membrane,mesangial proliferation,tubular degeneration,dilation,atrophy,fatty degeneration,obvious collagen deposition,higher levels of FBG,24h UTP,SCr,BUN,TNF-α,IL-6 and IL-1β,body mass loss,and higher expression of RAGE,COL-Ⅳ,Fas and FasL(P＜0.05).Compared with the DN group,the glomerular and tubular lesions were reduced and collagen deposition was decreased in the P-L,P-M and P-H groups,furthermore,the FBG,24h UTP,SCr,BUN,TNF-α,IL-6,IL-1β levels were lower,body mass was higher,and the RAGE,COL-Ⅳ,Fas,FasL expression was lower(P＜0.05).Compared with the P-H group,the renal tissue lesions in the P-H+rh-Fas group worsened,the FBG,24 h UTP,SCr,BUN,TNF-α,IL-6,IL-1β levels were higher,body mass was lower,and the RAGE,COL-Ⅳ,Fas,FasL expression was higher(P＜0.05).Conclusion Picroside Ⅱ exerts therapeutic effects on DN rats by inhibiting the Fas/FasL signaling pathway.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.