Objective To analyze the prevalence characteristics and influencing factors of metabolic syndrome (MS) in people aged 35-75 years in Hubei Province. Methods The follow-up data from 2016 to 2022 in the early screening and comprehensive intervention project for high-risk cardiovascular population in Hubei Province were collected. SAS 9.4 software was used to conduct 2-test and multivariate logistic regression to analyze the prevalence of MS and its influencing factors. Results Among the 89 199 subjects, 24 757 were affected by MS, with a prevalence rate of 27.75% and a standardized rate of 23.55%. Among the various components of MS, the prevalence of abnormal blood pressure was the highest, at 70.88%, and the standardized rate was 59.32%. Secondly, abnormal blood glucose was 36.26%, and the standardized rate was 30.04%. Central obesity was 33.12%, and the standardized rate was 30.28%. Hypertriglyceridemia was 32.90%, and the standardized prevalence rate was 32.70%. The rate of low HDL-C syndrome was 10.25%, and the standardized rate was 11.67%. The results of multivariate logistic regression analysis showed that the risk of MS increased with age, and the risk of MS in urban residents was lower than that in rural residents (OR=0.835, 95%CI: 0.77-0.886). Administrative and professional workers had a higher risk of MS than farmers (OR=1.313, 95%CI:1.194-1.445). Overweight, obesity, central obesity, history of self-reported hypertension, history of self-reported diabetes, and history of self-reported dyslipidemia were associated with a higher risk of MS, and the differences were statistically significant (P < 0.001). Conclusion The prevalence of MS is high in people aged 35-75 years in Hubei Province. On the basis of comprehensive intervention, focus monitoring should be strengthened to control the risk factors of MS and reduce the risk of cardiovascular and cerebrovascular diseases.

ObjectiveTo investigate the role of interleukin （IL）-17A in acute inhalational pneumonia induced by the highly drug-resistant and hypervirulent Staphylococcus aureus strain USA300-R in mice. MethodsAn acute inhalational pneumonia model was established in mice using an aerosolized pulmonary delivery technique. RNA sequencing （RNA-seq） and enzyme-linked immunosorbent assay （ELISA） were employed to examine the expression dynamics of Il17a mRNA and IL-17A protein， respectively， in the lungs of infected mice. Il17a knockout （Il17a^-/-） mice were generated using CRISPR/Cas9 gene editing technology. The survival rate， body weight， bacterial load in lung tissue， and histopathological changes were compared between Il17a^-/- and wild-type （WT） mice following inhalational infection with USA300-R. Results12 hours after USA300-R infection， compared to pre-infection， the expression level of Il17a mRNA in lung tissue and the level of IL-17A protein in bronchoalveolar lavage fluid （BALF） increased by approximately 50-fold （P<0.01） and 6-fold （P<0.001）， respectively. Compared to WT mice， Il17a^-/- mice exhibited approximately 10-fold higher bacterial loads in lung tissue at both 12 and 24 hours post-infection （P<0.001， P<0.05）. However， they showed significantly attenuated lung histopathological injury， reduced alveolar wall thickening， markedly decreased neutrophil infiltration， and an approximately 50% improvement in survival rate （P<0.05）. ConclusionIn acute Staphylococcus aureus USA300-R inhalational pneumonia， IL-17A contributes to bacterial clearance by recruiting neutrophils； however， excessive neutrophil infiltration exacerbates pulmonary inflammation and injury， reduces survival rates， and represents a potential therapeutic target.

Objective To identify potential immunosenescence markers in benign prostatic hyperplasia(BPH)and to explore BPH-related senescent phenotypes. Methods Three transcriptome datasets and one single-cell RNA-sequencing(scRNA-seq)dataset for BPH and normal prostate tissues were obtained from the Gene Expression Omnibus(GEO)database. The GSE7307 and GSE119195 were combined to analyze differentially expressed genes(DEGs). Enrichment analysis and immune infiltration analysis were used to explore aging-related changes in the immune microenvironment. Weighted gene coexpression network analysis(WGCNA)was applied to identify immune-related genes in GSE132714. ScRNA-seq data were employed to investigate the transcriptomic landscape, luminal cell heterogeneity, and aging-related alterations in BPH through cell-cell communication and pseudotime analysis. Finally, the results were validated with in vitro experiments. Results A total of 1202 DEGs and 627 immune-related genes were identified in BPH and normal prostate tissues. Enrichment analysis indicated that the vascular endothelial growth factor(VEGF)signaling pathway exhibited a downregulated aging phenotype in BPH. In scRNA-seq analysis, 9 cell types were identified. The VEGF signaling pathway in BPH exhibited an aging-related expression pattern, characterized by decreased vascular endothelial growth factor A(VEGFA)in luminal cells. Conclusion Our study identified VEGFA as a marker of immunosenescence in BPH, with changes of the VEGF pathway. Meanwhile, low expression of VEGFA, coupled with high expression of placental growth factor(PlGF)and vascular endothelial growth factor receptor(VEGFR), represented a senescent phenotype of the prostate.

Objective:To evaluate the effectiveness of entrustable professional activities (EPAs) in the general practice internship of undergraduate clinical medicine students, identify issues that need improvement in the internship, and enhance medical students' competence.Methods:A total of 75 students in the five-year (English class) clinical medicine program enrolled in 2018 and 2019 who participated in general practice internship in Renji Hospital affiliated to Shanghai Jiao Tong University School of Medicine from October 2021 to October 2023 were selected as study subjects. The design of core EPAs was adopted to assess the correlation among different EPA dimensions and to analyze the qualified rates.Results:The evaluation of EPAs showed that EPA2 (practicing respect, understanding and teamwork) had the highest mean score of 9.33, and EPA10 (chronic disease management and management of key populations) had the lowest mean score of 8.08. A supervision level of 3a and above was used as the criterion for qualification. The supervision levels of the students' EPAs were mostly concentrated at levels 3a and 3b. The highest qualified rate was for EPA2 (practicing respect, understanding and teamwork) at 85.33%, followed by EPA1 (complying with the rules of the profession and demonstrating professionalism) at 80.00% and EPA8 (reviewing information and solving clinical problems) at 72.00%. The lowest qualified rate was for EPA10 (chronic disease management and management of key populations) at 33.33%, followed by EPA4 (analyzing and interpreting test results) at 57.33%.Conclusions:EPAs concretize competency evaluation, which can effectively reflect the "competency-oriented" training objectives encompassing multiple elements such as knowledge, skills, values, and attitudes, while maintaining professional specificity. Undergraduates demonstrated strengths in professionalism and academics, but showed deficiencies in community chronic disease management and management of key populations. These findings suggest the need to strengthen the training in health and social care to better align with the competencies required during standardized residency training.

Objective:To describe the body mass index (BMI) level and long-term trends of Chinese older adults aged 65 and above.Methods:Older adults aged 65 and above from six waves (2002-2018) of the China Longitudinal Healthy Longevity Survey were selected as the study population. Multiple cross-sectional design with six survey waves conducted in 2002, 2005, 2008, 2011, 2014, and 2018 was adopted, enrolling 15 647, 15 358, 15 622, 9 166, 6 302, and 12 417 participants, respectively. Additionally, a total of 13, 755 participants were included in the cohort study design. Relevant information was collected through questionnaires and physical examinations. The χ2 trend test was used to compare the changes in the rates of underweight and overweight/obesity over the years, and the linear mixed-e?ects model (LMM) was used to fit trajectory curves of BMI changes with advancing age in older adults. Results:The baseline ages of the participants included in 2002, 2005, 2008, 2011, 2014, and 2018 were (85.16±11.26), (84.23±11.83), (84.99±12.16), (81.10±11.86), (78.89±11.30), and (83.08±12.42) years, respectively, with a relatively high proportion of females and rural residents. In the cohort study, the 13 755 participants had a median ( Q1, Q3) follow-up time of 6.5 (5.2, 10.0) years, with a cumulative follow-up duration of 109 041 person-years. In each wave, males had higher BMI than females, urban residents had higher BMI than rural residents, and BMI gradually decreased with increasing age (all P<0.001). The mean BMI of older adults in China increased from (19.37±3.80) kg/m2 in 2002 to (22.04±4.01) kg/m2 in 2018 ( P<0.001). Across all survey years, the prevalence of underweight was consistently higher in women than in men and in rural areas than in urban areas, with an upward trend as age increased (all P<0.001). In 2018, the underweight rates in the 65-79, 80-89, 90-99, and ≥100-year-old age groups were 8.0%, 16.7%, 26.2%, and 35.5%, respectively. Meanwhile, the prevalence of overweight/obesity was higher in men than in women and in urban areas than in rural areas, showing a declining trend with advancing age (all P<0.001). The prevalence of underweight among the older adults decreased significantly from 45.2% in 2002 to 18.9% in 2018 ( P<0.001), while the prevalence of overweight/obesity increased from 11.0% in 1998 to 29.6% in 2018 ( P<0.001). The trajectory curves fitted by the LMM model showed that individuals born in later decades had higher BMI levels at the same age compared to earlier cohorts. Conclusion:From 2002 to 2018, the BMI level among Chinese older adults showed an increasing trend. The prevalence of underweight showed a declining trend, while the rates of obesity and overweight increased. However, the underweight rate remained notably high among the oldest old.

Objective To design an individually portable oral treatment device to solve the problems of oral diagnosis and treatment under field conditions in alpine regions.Methods The individually portable oral treatment device had a trolley box structure and consisted of an outer box,an inner framework and an operation panel.The outer box was made of low-density polyethylene material and formed by by one-time rotational moulding process;the inner framework integrated a plateau com-pressor,an independent negative-pressure compressor,an integrated control system for programmable logic controller(PLC),an individually portable respiratory synchronized pulsed oxygen supply module for plateau application;there were several curative devices equipped in the operation panel,including a 3-way syringe,a high-speed turbine handpiece,an electric variable-speed handpiece,a water control switch,a light curing machine and an ultrasonic dental cleaning handpiece.Trials were carried out with the test-phase prototype in alpine regions so as to verify the performance of the device.Results Trials proved that the prototype gained advantages in mobility,multifunctionality and pressure supply facilitating continuous operation of power gas source for oral diagnosis and treatment in alpine regions.Conclusion The device developed solves the problems in pressure insufficiency and instability,control system integration,portability and oxygen supply for medical staffs,improves the mobility of oral diagnosis and treatment in alpine regions and enhances the oral support service and equipment effectively.[Chinese Medical Equipment Journal,2025,46(1):108-113]

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective:To construct a classification management model on the basis of Kraljic matrix for electrocardiogram(ECG)monitoring equipment in emergency intensive care unit(ICU),so as to explore its application value in the management for ECG monitoring equipment in emergency ICU.Methods:The classification management model on the basis of index for ECG monitoring equipment in emergency ICU was constructed.According to two classification dimensions included the market supply risk and the self-value,an indicator system of classification management,which aimed at strategic materials with high value and high risk,leverage materials with high value and low risk,bottleneck materials with low value and high risk,and conventional materials with low value and low risk,was constructed.A total of fifty-one ECG monitoring equipment in the emergency ICU of The People's Hospital of Longhua of Shenzhen from January to December 2023 were selected,and they were managed respectively by conventional management mode(25 sets)and classification management mode(26 sets)according to different management modes.The standardization level of operation management for equipment,the occurrence of safety risk and the level of management for equipment of the two management modes were compared,and the satisfaction of 30 relative personnel,who used and managed these equipment,for classification management of equipment also were compared.Results:The average values of the percentage of standardization level of normality of equipment operation,disinfection and sterilization,maintenance and fault repair of using classification management mode were respectively(91.58±4.33)%,(92.1±3.28)%,(91.49±3.54)%and(92.58±3.32)%,all of which were higher than those of conventional management mode,and the differences were statistically significant(t=12.537,15.706,14.196,18.946,P<0.05),repsectively.The average incidences of the risk of pressure injury,electrical injury and body fluid extravasation of adopting classification management mode were respectively(2.54±0.87)%,(3.02±0.82)%and(1.29±0.65)%,all of which were lower than those of adopting conventional management mode,and the differences were statistically significant(t=22.825,17.453,24.424,P<0.05),respectively.The satisfaction scores of 30 relative management personnel,who used equipment on the process rationality,system standardization and quality effectiveness,of adopting classification management mode were respectively(94.26±3.54),(92.57±4.36)and(91.87±3.69),all of which were higher than those of conventional management mode,and the differences were statistically significant(t=14.052,13.991,13.551,P<0.05),respectively.The reasonable placement rate,recording rate of standardization,and intact rate of equipment in the 26 equipment by adopting classification management mode were respectively 92.31%,92.31%and 88.46%,all of which were significantly higher than those by adopting conventional management mode,and the differences were statistical significant(x2=12.052,10.398,11.338,P<0.05).Conclusion:The classification management model of ECG monitoring equipment in emergency ICU can increase the management efficiency for the equipment in operating room of hospital,and improve the operation quality of equipment,and enhance the safety of equipment in clinical use,and the standardization of operation management for equipment.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.