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.

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.

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.

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 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.

Parkinson's disease(PD)is a common progressive neurodegenerative disease mainly affecting the motor system.Various genetic factors and cellular mechanisms underlying PD have recently been discovered.Emerging evidence suggests that epigenetic modifications play a very important role in the pathogenesis,prevention,and treatment of PD.Epigenetic modification mediates genetic and environmental interactions mainly through complex interactions of DNA methylation,histone modification,and non-coding RNA,thereby affecting expression in the absence of changes in DNA sequence.In this review,we summarize the epigenetic modification mechanisms involved in the pathogenesis of Parkinson's disease.In this review,we summarize the epigenetic modification mechanisms involved in the pathogenesis of Parkinson's disease.Recent studies have found that traditional Chinese medicine can participate in the regulation of abnormal epigenetic modifications in the treatment of PD.Traditional Chinese medicine benefits from its multi-level and multi-target regulatory effects,and various traditional Chinese medicine monomers,compound prescriptions,and techniques have been evaluated,confirming that this is a promising approach for improving symptoms in PD.This review summarizes the mechanisms by which epigenetic modifications contribute to P D,explores the role of traditional Chinese medicine,and provides new ideas for clinical treatment and drug development in PD through epigenetic intervention.

Objective:To analyze the distribution of allergen components of dust mite in children with airway allergic diseases.Methods:This was a cross-sectional study. The clinical data of children with dust mite-induced allergic asthma (AA) complicated with allergic rhinitis (AR) or allergic rhinitis who were treated in Department of Allergy,Beijing Children′s Hospital from January 2019 to October 2022 were retrospectively analyzed. The spedific IgE (sIgE) levels to Der p1,Der p2,Der p5,Der p7,Der p10,Der p21,Der p23 and Der f1,Der f2 were detected by protein chip method. The distribution of dust mite sensitized components and the sIgE levels in children with different airway allergic diseases and different ages were compared.Results:Among 138 children with airway allergic diseases,there were 97 boys and 41 girls,age (6.86±2.61) years old,and there were 106 cases of AA combined AR (AAAR group) and 32 cases of AR alone (AR group). The sensitization rates of Der p2 was the highest (75.4%,104/138),followed by Der f2 (74.6%,103/138),Der f1 (73.9%,102/138),Der p1 (71.7%,99/138),Der p21 (19.6%,27/138),Der p5 (16.7%,23/138),Der p23 (14.5%,20/138),Der p7 (11.6%,16/138) and Der p10 (2.9%,4/138). The co-sensitization rate of Der p1,Der p2,Der f1 and Der f2 was the highest (31.2%,43/138). There was no significant difference in sensitization rate of dust mites components between AAAR group and AR group(all P>0.05). AAAR group had higher levels of sIgE to Der p23 than AR group [0.1 (0,0.1) IU/ml vs. 0 (0,0.1) IU/ml,Z=-2.819, P=0.005]. There were no significant differences in the positive rate of dust mite components and sIgE levels between children aged≤6 and>6 years old with airway allergic diseases(all P>0.05). Conclusions:Der p1,Der p2,Der f1 and Der f2 are the major components of dust mites sensitizing airway allergic diseases in children. Der p1,Der p2,Der f1 and Der f2 are the main co-sensitizing components in children with dust mite-induced airway allergic diseases. Compared with AR,the sIgE level to Der p23 in children with AAAR is higher.

Objective To provide methodological examples for related research,the influencing factors of the evolution of Qi deficiency syndrome in chronic obstructive pulmonary disease(COPD)based on a nonlinear mixed effects model was explored.Methods A research questionnaire on the influencing factors of the evolution of Qi deficiency syndrome in chronic obstructive pulmonary disease was developed,and clinical data of 650 COPD patients on the 1st and 14th day of acute exacerbation,the 1st and 28th day of risk window,the first day of stable period,and the 90th day were dynamically collected from 10 tertiary hospitals across the country.8 baseline data including gender and age were collected through the PROC NLMIXED process by SAS 9.4 software.Coronary heart disease,diabetes and hypertension accounted for the highest proportion.Nine concurrent syndromes including wind cold syndrome and phlegm heat syndrome were used as fixed effects,and individual level was used as random effects to gradually fit the model and screen the influencing factors of Qi deficiency syndrome in the entire process of disease occurrence and development.Results A total of 637 eligible cases were included,and clinical datas were dynamically collected on the 1st and 14th day of acute exacerbation,the 1st and 28th day of the risk window,the 1st and 90th day of the stable period.It was found that the number of acute exacerbations,alcohol consumption,concomitant hypertension,coronary heart disease,blood stasis syndrome,yin deficiency syndrome,yang deficiency syndrome,6-minute walking distance,and the modified Medical Research Council Dyspnea Questionnaire(mMRC)had an impact on the evolution of Qi deficiency syndrome in the previous year(P<0.05).Conclusion The use of a nonlinear mixed effects model revealed the relevant factors affecting the evolution of Qi deficiency syndrome from complex multi temporal dynamic data,providing methodological references for other related studies.