ObjectiveTo clarify the graded quantitative diagnostic characteristics of lung qi deficiency syndrome in chronic obstructive pulmonary disease （COPD） based on latent class analysis combined with a hidden structure model. MethodsClinical data， including the four diagnostic methods of traditional Chinese medicine （TCM）， were collected from 745 COPD patients with lung qi deficiency syndrome. Latent class modeling was performed using R 4.1.2 software， and each patient was classified into one of three severity categories （mild， moderate， or severe） based on probabilistic parameterization， parameter estimation， and model fitting. A database was established for different severity levels of lung qi deficiency syndrome. Based on this， Lantern 5.0 software was used to construct hidden structure models for mild， moderate， and severe lung qi deficiency syndrome， and syndrome differentiation rules were developed through comprehensive clustering. ResultsA latent class model was constructed using 28 symptoms and signs with a frequency greater than 10%. Considering TCM theory and model simplicity， the optimal model was determined when the number of latent classes was three， categorizing lung qi deficiency syndrome into mild （298 cases）， moderate （164 cases）， and severe （283 cases）. Hidden structure models were separately developed for each severity level， and syndrome differentiation rules were established. A comparison of common symptoms in the syndrome differentiation rules for mild and moderate lung qi deficiency syndrome showed no statistically significant differences in diagnostic values and weights （P＞0.05）， leading to their combined analysis and the development of a unified syndrome differentiation rule. Value and weight of quantitative diagnosis of mild-to-moderate lung qi deficiency syndrome were as followed： shortness of breath （diagnostic value 9.3， diagnostic weight 86.92%）， dyspnea on exertion （8.2， 76.64%）， low voice and reluctance to speak （6.7， 62.62%）， poor appetite （4.0， 37.38%）， loose stools （4.0， 37.38%）， weak cough sound （2.9， 27.10%）， wheezing （2.3， 21.50%）， fatigue （1.8， 16.82%）， spontaneous sweating （1.7， 15.89%）， susceptibility to colds （1.6， 14.95%）， swollen tongue （1.4， 13.08%）， teeth marks on the tongue edge （1.2， 11.21%）， deep pulse （1.6， 14.95%）， with a diagnostic threshold of 10.3. Value and weight of quantitative diagnosis of severe lung qi deficiency syndrome were as followed： weak cough sound （15.1， 61.13%）， soreness and weakness of the waist and knees （12.6， 51.01%）， shortness of breath （11.1， 44.94%）， low voice and reluctance to speak （8.3， 33.60%）， frequent nocturia （6.1， 24.70%）， spontaneous sweating （3.7， 14.98%）， susceptibility to colds （3.5， 14.17%）， teeth marks on the tongue edge （7.8， 31.58%）， pale tongue body （1.9， 7.69%）， white tongue coating （5.5， 22.27%）， thin pulse （1.5， 6.07%）， with a diagnostic threshold of 23.7. ConclusionThe combination of latent class analysis and a hideen structure model effectively clarified the graded quantitative diagnostic characteristics of lung qi deficiency syndrome， providing a reference for the quantitative diagnosis of other fundamental syndromes in TCM.

Background During urbanization, the passenger load on urban public transport systems continues to increase, exposing bus drivers to a high risk of musculoskeletal disorders (MSDs). This occupational health issue may also potentially compromise public transport safety. Objective To investigate the prevalence of MSDs among bus drivers in a first-tier city and to explore associated influencing factors. Methods A self-administered questionnaire survey was conducted from December 2024 to March 2025 among 1300 bus drivers in a bus company. Data were collected on general demographic information, occupational activities, and MSDs indicators. A total of 1268 valid questionnaires were returned, yielding a response rate of 97.5%. Descriptive statistics were used to analyze the distribution characteristics of MSDs. Pearson χ² tests were employed to examine the association between MSDs prevalence and individual/occupational characteristics. Logistic regression was performed to identify the influencing factors of MSDs. Results The survey revealed that the prevalence of MSDs among the bus drivers was 28.5%, with the highest prevalence in the 41–50 years age group (30.5%). The conditions primarily affected the cervical spine (60.5%) and lumbar spine (61.9%), with some cases involving multiple sites. The logistic regression model indicated that the following factors were associated with a higher risk of MSDs: frequent smoking (OR=1.477), poor or moderate self-reported health status (OR=4.422), 11–20 years of service (OR=1.749), daily cumulative driving time ≥361 min (OR=1.616), frequent whole-body fatigue during driving (OR=2.077), occasional whole-body fatigue during driving (OR=1.873), feeling tense during driving (OR=1.518), fatigue after work (OR=2.485), work-related stress (OR=1.882), and prolonged smartphone use with head-down posture (OR=1.671). Conversely, occasional exercise (OR=0.713)/frequent exercise (OR=0.569), driving intervals ≥21 min per round (OR=0.645), and perceiving the driving seat comfortable (OR=0.429) were associated with a lower risk of MSDs. Conclusion Physical exercise, smoking, years of service, daily cumulative driving time, driving intervals per round, prolonged smartphone use with head-down posture, self-reported health status, and psychological factors such as work-related stress are influencing factors for MSDs among bus drivers. Drivers should increase physical exercise and change unhealthy living habits. Employers should optimize working conditions, arrange reasonable driving schedules, and foster a positive work environment to reduce MSDs prevalence.

Objective To assess the current state and influencing factors of multi-site work-related musculoskeletal disorders (WMSDs) among front-line employees in the assembly workshop of an automobile manufacturing enterprise. Methods A total of 394 front-line workers in the assembly workshop of an automobile manufacturing enterprise in Beijing City were selected as the research subjects using the judgmental sampling method. The Chinese version Musculoskeletal Disorders Questionnaire was used to assess the presence of WMSDs over the past 12 months in nine body regions: neck, shoulders, upper back, lower back, elbows, wrists, hips and thighs, knees, ankles and feet. The multivariable logistic regression was employed to investigate the influencing factors. Results The detection rate of overall WMSDs was 32.7% (129/394), with the top three single-site WMSDs being in the neck, shoulders, and lower back, and their detection rates were 14.0%, 12.7% and 9.6%, respectively. The detection rate of multi-site WMSDs was 17.8% (70/394). The result of multivariable logistic regression analysis revealed that workers who turned or bent their upper body while keeping their legs stationary, frequently performed wrist flexion/extension/lateral bending/rotation, or stood for prolonged period of time had significantly higher risks of developing multi-site WMSDs compared with those who did not (all P<0.05). Workers who perceived uncomfortable workplace lighting had higher risk of multi-site WMSDs than those who perceived it as comfortable (P<0.01). Conclusion The development of multi-site WMSDs among workers in the assembly workshop of this automobile manufacturing enterprise is strongly related to poor working postures at work.

Objective To investigate the effect of total paeony glycoside(TPG)on cerebral ischemia-reperfusion injury(CI/RI)of rats.Methods The rats were randomly divided into sham surgery(sham)group,CI/RI model group(simple CI/RI group),positive control group(nimodipine group,5 mg/kg),low-dose TPG group(TPG-L group,27 mg/kg),a high-dose TPG group(TPG-H group,54 mg/kg)and a high-dose TPG+NOD-like receptor thermal protein domain associated protein 3(NLRP3)activator diethyl dithiocarbamate(DDC)group(TPG-H+DDC group,54 mg/kg TPG and 30 mg/kg DDC),with 18 rats in each,administered once a day for 7 consecutive days.After the administration,the neurological deficit score of the rats was evaluated.Nissl staining microscopy was applied to observe neuronal activity in brain tissue.2,3,5-triphenyltetrazolium chloride(TTC)staining microscopy was applied to detect the area of cerebral infarction in rats.The level of interleukin-1β and IL-18 in brain tissue was measured by ELISA method.Western blot was applied to detect the expression of purinergic receptor P2X ligand-gated ion channel 7(P2X7R)/NLRP3 signaling pathway related proteins and pyroptosis related proteins such as apoptosis associated speck like protein containing a CARD(ASC)and cysteine protease 1(caspase-1)proteins in brain tissue.Results Compared with the sham group,the neurological deficit score,infarct area,level of IL-1β and IL-18 in brain tissue and protein expression of P2X7R,NLRP3,ASC,and caspase-1 in brain tissue of rats in the simple CI/RI group were significantly increased(P<0.05),while the proportion of Nissl body positive cells in brain tissue was significantly reduced(P<0.05).The change in corresponding indicators of rats in the nimodipine group,TPG-L group,and TPG-H group was opposite to those in the simple CI/RI group(P<0.05).NLRP3 acti-vator DDC antagonized the inhibitory effect of TPG on cell pyroptosis in CI/RI rats.Conclusions TPG may inhibit brain injury in CI/RI rats by down-regulating the P2X7R/NLRP3 pathway.

Background During urbanization, the passenger load on urban public transport systems continues to increase, exposing bus drivers to a high risk of musculoskeletal disorders (MSDs). This occupational health issue may also potentially compromise public transport safety. Objective To investigate the prevalence of MSDs among bus drivers in a first-tier city and to explore associated influencing factors. Methods A self-administered questionnaire survey was conducted from December 2024 to March 2025 among 1300 bus drivers in a bus company. Data were collected on general demographic information, occupational activities, and MSDs indicators. A total of 1268 valid questionnaires were returned, yielding a response rate of 97.5%. Descriptive statistics were used to analyze the distribution characteristics of MSDs. Pearson χ² tests were employed to examine the association between MSDs prevalence and individual/occupational characteristics. Logistic regression was performed to identify the influencing factors of MSDs. Results The survey revealed that the prevalence of MSDs among the bus drivers was 28.5%, with the highest prevalence in the 41–50 years age group (30.5%). The conditions primarily affected the cervical spine (60.5%) and lumbar spine (61.9%), with some cases involving multiple sites. The logistic regression model indicated that the following factors were associated with a higher risk of MSDs: frequent smoking (OR=1.477), poor or moderate self-reported health status (OR=4.422), 11–20 years of service (OR=1.749), daily cumulative driving time ≥361 min (OR=1.616), frequent whole-body fatigue during driving (OR=2.077), occasional whole-body fatigue during driving (OR=1.873), feeling tense during driving (OR=1.518), fatigue after work (OR=2.485), work-related stress (OR=1.882), and prolonged smartphone use with head-down posture (OR=1.671). Conversely, occasional exercise (OR=0.713)/frequent exercise (OR=0.569), driving intervals ≥21 min per round (OR=0.645), and perceiving the driving seat comfortable (OR=0.429) were associated with a lower risk of MSDs. Conclusion Physical exercise, smoking, years of service, daily cumulative driving time, driving intervals per round, prolonged smartphone use with head-down posture, self-reported health status, and psychological factors such as work-related stress are influencing factors for MSDs among bus drivers. Drivers should increase physical exercise and change unhealthy living habits. Employers should optimize working conditions, arrange reasonable driving schedules, and foster a positive work environment to reduce MSDs prevalence.

Objective To evaluate the clinical value of loop-mediated isothermal amplification(LAMP)for rapid detection of neonatal infectious pathogens.Methods Biological samples(cord blood and neonatal blood or sputum within 48 hours of birth)of 167 suspected neonates and premature infants delivered in Jinhua Maternal and Child Health Hospital from June 2021 to December 2022 were collected and tested by LAMP method and bacterial culture method respectively.The results of the two methods were compared consistent-ly.Using the bacterial culture method as the standard,the positive rate of LAMP method was evaluated in de-tecting common pathogens in neonatal infections.Results Among the 167 specimens,the positive rate of pathogen detection by LAMP method(24.0％)was higher than that by bacterial culture method(15.0％),and the difference was statistically significant(x2=4.30,P＜0.05).The positive rate of LAMP method for detecting methicillin-resistant Staphylococcus aureus was higher than that of bacterial culture method,and the difference was statistically significant(x2=15.59,P＜0.01).Conclusion Compared with bacterial culture method,LAMP method has a higher positive rate for detecting methicillin-resistant Staphylococcus aureus,and can quickly and accurately diagnose the pathogenic bacteria of neonatal infections,providing a basis for the rapid development of clinical diagnosis and treatment strategies.

Objective To systematic evaluate the impact of applying the clinical nursing pathway(CNP)on epidural anesthetic analgesia natural delivery.Methods The randomized controlled trial(RCT)and quasi-experimental researches on the application of CNP in epidural anesthetic analgesia natural delivery were retrieved from PubMed,Cochrane Library,Embase,Web of Science,China Knowledge Network database,Wanfang database,VIP and the Chinese Biomedical Literature Database.The retrieval time limit was from January 1,2014,to July 31,2024 with no language limitation.The meta analysis on the included studies was performed by applying RevMan5.4.1.Results A total of 5 RCTs and 2 quasi-experimental studies were in-cluded,involving 979 parturients with deliveries.The meta analysis showed that compared with the conven-tional nursing,CNP could shorten the duration of the first stage of labor(MD=—1.06,95％CI:—1.95——0.17,P=0.02)and the duration of the second stage of labor(MD=—0.12,95％CI:—0.21——0.03,P=0.006);decreased the rate of perineal lateral incision(RR=0.73,95％CI:0.65-0.83,P＜0.001)and inci-dence rate of postpartum urinary retention(RR=0.35,95％CI:0.20-0.63,P＜0.001);and shortened the time to lactation initiation(SMD=—1.52,95％CI:—2.38——0.66,P＜0.001).There was no influence on reducing postpartum 24 h hemorrhage amount(SMD=—0.51,95％CI:—1.23-0.21,P=0.16).The study subjects were divided into the primipara women subgroup and unclassified parturients subgroup.Compared with the conventional nursing group,compared with the conventional nursing,CNP had no impact on the dura-tion of the first stage of labor(MD=—0.32,95％CI:—0.61-0.98,P=0.63)and the duration of the second stage of labor(MD=—0.11,95％CI:—0.25-0.04,P=0.15)in the primipara women subgroup.CNP could reduce the postpartum 24 h hemorrhage volume in the unclassified parturients subgroup(SMD=—1.47,95％CI:—1.72——1.21,P＜0.001).Conclusion Application of CNP in parturients labor analgesia could reduce the perineal lateral incision rate and incidence rate of postpartum urinary retention and shorten the time to lac-tation initiation.Due to the heterogeneity among studies,the impact of CNP on the labor duration and the bleeding amount within postpartum 24 h still requires more high-quality studies to be conducted in the future for verification.

In the era of big data,artificial intelligence(AI)technology has developed rapidly,with medical field being one of its most deeply penetrated application domains.Leveraging the advantages of big data and AI requires the sharing and integration of medical data,yet balancing privacy protection and data sharing poses significant challenges.This paper analyzes the focus issues of patient privacy and data security in medical AI from a global perspective across 6 dimensions:challenges in data sovereignty and cross-border flow compliance,technical vulnerabilities in de-anonymization and re-identification risks,failure of informed consent mechanisms and dynamic authorization needs,regulatory gaps in algorithmic"black boxes"and data misuse,technological dependency and supply chain security risks,and the dilemma of balancing privacy protection with public health interests.Corresponding solutions and strategies are also proposed.

Objective:To construct a diagnostic prediction model for childhood asthma and conduct a preliminary evaluation based on the test results of specific IgE (sIgE) for airborne allergens and in combination with clinical data.Methods:This study is a case-control study. A total of 4 338 cases that completed the sIgE test for airborne allergens in the Allergy Department of Beijing Children′s Hospital Affiliated to Capital Medical University from January to December 2023 were selected as the research subjects. They were divided into the asthma group and the non-asthma group based on the diagnostic information. Age, gender, cough and wheezing symptoms, and the classification results of sIgE concentrations of 15 airborne allergens were collected as the predictor variables of the asthma diagnostic prediction model. Differential analysis and LASSO regression were employed for the screening of predictor variables. The multivariate logistic regression method was applied to construct the nomogram prediction model. The data set was randomly split at a ratio of 7∶3 into a training set (3 036 cases) for constructing the prediction model and a validation set (1 302 cases) for testing the predictive efficacy of the model. The area under the receiver operating characteristic (ROC) curve (AUC), the Hosmer-Lemeshow calibration curve were utilized to assess the discrimination and goodness of fit of the model, and the clinical decision curve (DCA) was adopted to evaluate the clinical application value of the model.Results:Among 4 338 pediatric cases, children aged 0 to <3 years accounted for 10.17% (441 cases), those aged 3 to <6 years accounted for 36.49% (1 583 cases), those aged 6 to <12 years accounted for 46.98% (2 038 cases), and those aged 12 to 18 years accounted for 6.36% (276 cases). Males constituted 65.17% (2 827 cases), and females 34.83% (1 511 cases). The proportion of children without wheezing symptoms was 41.47% (1 799 cases), while those with wheezing symptoms was 58.53% (2 539 cases). The asthma group accounted for 41.77% (1 812 cases), and the non-asthma group for 58.23% (2 526 cases). Statistically significant differences were observed between the asthma group and the non-asthma group in 18 predictive variables including age, gender, wheezing symptoms, d1, d2, e1, e5, g2, g6, m6, t11, t3, t6, w1, w22, w6, wx5, and m3 ( P<0.05). LASSO regression analysis identified six predictor variables: age (calculated in months), cough and wheezing symptoms, and sIgE of four airborne allergens, namely, Dermatophagoides pteronyssinus (d1), Canis familiaris dander (e5), Aspergillus fumigatus (m3), and Artemisia vulgaris pollen (w6).Multifactorial regression analysis revealed that the contribution degrees of the above-mentioned predictor variables to the asthma diagnosis prediction model were ranked as follows: cough and wheezing symptoms ( OR=24.37, P<0.001), m3 ( OR=1.34, P<0.001), d1 ( OR=1.22, P<0.001), e5 ( OR=1.12, P=0.028), w6 ( OR=1.11, P<0.001), and age ( OR=1.01, P<0.001).The AUCs of the nomogram prediction model for the training set and the validation set were 0.853 (95% CI: 0.840-0.866) and 0.838 (95% CI: 0.817-0.860), respectively. The Hosmer-Lemeshow calibration curve indicated a good fit ( P=0.215 for the training set; P=0.352 for the validation set). The DCA of the validation set demonstrated that when the probability threshold for predicting the occurrence of childhood asthma was 8%-92%, the model had the best applicability. Conclusion:By combining age, cough and wheezing symptoms, and sIgE of the four airborne allergens (d1, e5, m3, and w6) selected from 15 airborne allergens, a childhood asthma diagnosis prediction model with good predictive performance and clinical practicability was constructed. It can serve as a simple and convenient tool for accurately identifying asthma and provides a practical basis for the application of artificial intelligence big data analysis models in the prevention, treatment, and management of childhood asthma.

Objective To explore the short-term prognosis and risk factors for in-hospital mortality in patients with fulminant myocarditis induced refractory cardiogenic shock(FM-RCS)receiving veno-arterial extracorporeal membrane oxygenation(VA-ECMO)treatment,and to construct an early prognosis prediction model using relevant indicators.Methods A total of 61 FM-RCS patients treatment by VA-ECMO in the department of intensive care unit of the Second Affiliated Hospital of Zhengzhou University from January 2017 to February 2024,excluding 15 cases with age less than 18 years and 3 cases with ECMO treatment duration less than 24 hours,a total of 43 patients were finally included.Participants were stratified into survival(n=19)and mortality(n=24)groups according to discharge outcomes.Demographic data,chronic disease history,early laboratory indicators,left ventricular function indicators,and basic reference values of hemodynamics were systematically compared between the two groups.Variable selection was performed using LASSO regression,followed by multivariate COX regression analysis to screen independent risk factors for in-hospital mortality in ECMO-treatment FM-RCS patients.A nomogram prediction model was subsequently developed using R software and validated through calibration curves,concordance index(C-index),and receiver operator characteristic curve(ROC curve)analysis.Results The overall survival rate of the 43 enrolled patients was 44.2%,with 19 cases in the survival group and 24 cases in the mortality group.In early laboratory indicators,the survival group exhibited significantly lower levels of initial lactic acid(Lac),24-hour Lac(Lac 24 h),24-hour MB isoenzyme of creatine kinase(CK-MB 24 h),24-hour cardiac troponin T(cTnT 24 h),24-hour total bilirubin(TBil 24 h),24-hour serum creatinine(SCr 24 h),and lactate albumin ratio(LAR)compared to the mortality group[initial Lac(mmol/L):2.7(1.3,7.6)vs.9.2(5.9,14.0),Lac 24 h(mmol/L):2.4(2.0,3.6)vs.5.4(3.3,9.2),CK-MB 24 h(U/L):58.0(28.0,115.0)vs.167.7(68.5,280.3),cTnT 24 h(μg/L):0.53(0.37,2.41)vs.3.92(3.10,8.86),TBil 24h(μmol/L):18.3(9.9,37.8)vs.40.2(24.6,67.0),SCr 24 h(μmol/L):90.63±42.49 vs.177.76±70.76,LAR:0.09(0.04,0.23)vs.0.31(0.20,0.38),all P<0.05],serum albumin(Alb)levels were significantly higher in the survival group[g/L:36.0(31.9,39.2)vs.31.7(26.4,34.4),P<0.05].The mortality group had a higher incidence of malignant arrhythmias[66.7%(16/24)vs.31.6%(6/19),P<0.05].The LASSO regression model identified four non-zero coefficient variables-Lac 24 h,CK-MB 24 h,cTnT 24 h,and SCr 24 h-which were included in the subsequent multivariate COX regression analysis.The results demonstrated that Lac 24 h[hazard ratio(HR)and 95%confidence interval(95%CI)was 1.186(1.074-1.310),P<0.001]and cTnT 24 h(HR=1.230,95%CIwas 1.078-1.404,P=0.002)were independent risk factors for in-hospital mortality in VA-ECMO treatment FM-RCS patients.A predictive model constructed using these two indicators showed a C-index of 0.812,area under the curve(AUC)=0.941,with 91.7%sensitivity and 94.7%specificity.Furthermore,compared to the survival group,the mortality group exhibited significantly higher incidences of acute kidney injury[91.7%(22/24)vs.36.8%(7/19)]and hypoxic-ischemic encephalopathy[62.5%(15/24)vs.10.5%(2/19),both P<0.05].The mortality group also required greater transfusion volumes[mL:3 800(1 420,8 515)vs.1 200(400,3 020),P<0.05],but had shorter total hospitalization durations[days:7(3,13)vs.23(20,44),P<0.05].Conclusion For FM-RCS patients receiving VA-ECMO treatment,Lac 24 h and cTnT 24 h after ECMO initiation are independent predictors of in-hospital mortality.Clinicians should be vigilant about poor prognosis in FM-RCS patients with high Lac 24 h hours(>2.5 mmol/L)and cTnT 24 hours(>3.01 μg/L)after ECMO treatment.