ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

ObjectiveTo investigate the infection characteristics of respiratory syncytial virus (RSV) in children with acute respiratory tract infection (ARI) in Pudong New Area, Shanghai, from 2013 to 2023, so as to provide an evidence for the prevention and control of RSV in Shanghai. MethodsChildren who sought medical care at sentinel healthcare facilities in Pudong New Area, Shanghai, between January 2013 and December 2023 and met the case definition of ARI were included in the study. Nasopharyngeal swab samples were collected and tested for viral pathogens using real-time fluorescene PCR, and the clinical information of whom was collected simultaneously. ResultsA total of 4 980 children were included in the ARI surveillance, among whom 231 tested positive for RSV, with an overall detection rate of 4.64%. Of these, 106 cases were type A and 125 were type B. From 2013 to 2023, the detection rate of RSV in children showed an overall trend of initial increase followed by a decline, with higher detection rates in autumn and winter and lower rates in spring and summer. The RSV detection rate gradually decreased with age, with the highest rate observed in children <1 year old, accounting for 16.33% (80/490) of RSV-detection cases. Cough was the most common clinical symptom. Among the RSV-positive cases, 36 involved co-infection with another virus, 6 co-infected with three viruses, and 1 with mixed infection of four viruses. The most frequent co-infection was RSV and human coronavirus. ConclusionChildren under 1 year of age are more susceptible to RSV infection, with cough being the predominant symptom. RSV infection in Pudong New Area, Shanghai, mainly occurs in winter. Targeted prevention and control measures should be taken for children under 1 year old during the winter season to reduce the risk of both RSV infection and co-infection with human coronavirus and influenza virus.

Objective:To analyze the gene mutation type and clinical phenotype of patients with PRRT2 mutation, and explore their relations with prognosis. Methods:A total of 18 patients with PRRT2 gene mutation (1 patient with novel mutation in PRRT2 gene, and 17 probands in 17 families with PRRT2 gene mutation) were enrolled in Department of Neurology, First Affiliated Hospital of Air Force Medical University from January 2018 to July 2023. Serum of the patients was collected for whole exon sequencing, and mutation sites and types of PRRT2 gene were analyzed. SWISS-MODEL website was used to predict the changes in protein structure caused by PRRT2 gene mutation. The relations of gene mutation type and clinical phenotype with prognosis of these patients were analyzed. Results:(1) All 18 patients with PRRT2 gene mutation were heterozygous mutation, including 12 frameshift mutations, 5 missense mutations, and 1 integer mutation. The clinical phenotype included benign familial infantile epilepsy (BFIE) in 5 patients, epilepsy in 6 patients, exercise-induced paroxysmal kinesigenic dyskinesia (PKD) in 5 patients, and infantile convulsion and choreoathetosis (ICCA) in 2 patients. A total of 8 mutation sites were found in 18 patients with PRRT2 gene mutation, of which 3 mutation sites have been reported, and 5 mutation sites have not been reported, including c.647(exon2)C>A, c.647(exon2)C>G, c.170(exon2)delC, c.981(exon3)C>G, and lossl(EXON: 2)(all). (2) Eighteen patients mainly accepted oxcarbazepine, levetiracetam, and sodium valproate in combination or monotherapy. Among them, 5 BFIE patients, 2 ICCA patients and 3 epilepsy patients were seizure-free after treatment. PKD patients did not respond well to oxcarbazepine. (3) Three frameshift mutations (mutation sites: c.649 [exon2]_c.650 [exon2] insC, c.640 [exon2]_c.641 [exon2] insC, and c.170 [exon2] delC) led to premature termination of protein translation, resulting in significant changes in protein structure. Four missense mutations (mutation sites: c.640[exo2]G>C, c.647[exon2]C>A, c.647[exon2]C>G, and c.981[exon3]C>G) had little effect on protein structure changes. No relation was found between changes of protein structure caused by different mutation types and prognosis. Conclusion:PRRT2 gene mutation patients with clinical phenotypes of BFIE and ICCA have good prognosis, but the mutation type is not related with the prognosis of patients.

ObjectiveTo identify the rate， population characteristics， and vaccination history of repeat infections among previously infected people in the current epidemic based on the rate of repeat infection and population characteristics of different mutant strains at different times in Pudong New Area of Shanghai， and to provide reference for the prevention and control strategies of novel coronavirus repeat infections. MethodsA total of 9 250 investigated subjects were randomly selected from the new cases of asymptomatic infection and confirmed cases reported by Pudong New Area from March to May 2022. The investigation mainly focused on demographic characteristics， nucleic acid or antigen test results， and symptoms after infection. The repeat infection rates among different populations were compared， and logistic regression was used to analyze the impact of gender， age， and vaccination status on repeat infections. ResultsThe survey sample of 9 250 people had a response rate of 81.85%. There were 4 043 males （53.40%） and 3 528 females （46.60%）， with a median age of 34 years old （P₂₅， P₇₅： 7， 61）. The overall vaccine uptake rate was 59.44% （4 500/7 571）. In December of 2022， there were 563 cases of repeat infection， with an infection rate of 7.44%. The lowest rate of repeat infection was seen in the 3‒ year-old group （2.86%） and the highest rate in the 30‒ year-old group （12.42%）， with significant differences between different age groups. The repeated infection rate for those who had completed their vaccinations was significantly lower （6.57%） compared to those who had not （7.11%）. The age groups of 3‒ years， 70‒79 years， as well as individuals who completed full vaccination and received booster shots were protective factors against repeat infections. ConclusionThe overall rate of reinfection among the infected in Shanghai during the spring of 2022 was low in the outbreak of the Omicron variant， and the rate of reinfection in the 3‒ year-old group was significantly lower than in other age groups. Completing the full course of vaccination significantly reduces the risk of reinfection. Although the reinfection rate is high in individuals who received booster shots， it remains a mitigating factor compared to those who do not receive the vaccine. It is recommended to continue monitoring reinfections in key populations and further strengthen immunization efforts.

Objective:To investigate the rates of low disease activity and clinical remission in patients with systemic lupus erythematosus(SLE)in a real-world setting,and to analyze the related factors of low disease activity and clinical remission.Methods:One thousand patients with SLE were enrolled from 11 teaching hospitals.Demographic,clinical and laboratory data,as well as treatment regimes were collec-ted by self-completed questionnaire.The rates of low disease activity and remission were calculated based on the lupus low disease activity state(LLDAS)and definitions of remission in SLE(DORIS).Charac-teristics of patients with LLDAS and DORIS were analyzed.Multivariate Logistic regression analysis was used to evaluate the related factors of LLDAS and DORIS remission.Results:20.7％of patients met the criteria of LLDAS,while 10.4％of patients achieved remission defined by DORIS.Patients who met LLDAS or DORIS remission had significantly higher proportion of patients with high income and longer disease duration,compared with non-remission group.Moreover,the rates of anemia,creatinine eleva-tion,increased erythrocyte sedimentation rate(ESR)and hypoalbuminemia was significantly lower in the LLDAS or DORIS group than in the non-remission group.Patients who received hydroxychloroquine for more than 12 months or immunosuppressant therapy for no less than 6 months earned higher rates of LLDAS and DORIS remission.The results of Logistic regression analysis showed that increased ESR,positive anti-dsDNA antibodies,low level of complement(C3 and C4),proteinuria,low household in-come were negatively related with LLDAS and DORIS remission.However,hydroxychloroquine usage for longer than 12 months were positively related with LLDAS and DORIS remission.Conclusion:LLDAS and DORIS remission of SLE patients remain to be improved.Treatment-to-target strategy and standar-dized application of hydroxychloroquine and immunosuppressants in SLE are recommended.

Objective:To establish an indicator system for surveillance of data sources to provide a theoretical basis for respiratory infectious disease surveillance and early warning.Methods:Indicators for data sources in the surveillance of acute respiratory infectious diseases were initially compiled through a literature search. Subsequently, two rounds of expert consultations were conducted with 22 experts using the Delphi method to refine the indicators.Results:The questionnaire recovery rates for the two rounds of expert consultation were 100.00% and 86.36%, respectively. The authority coefficient of the experts was 0.83. The coordination coefficient of the second round of Delphi expert consultation was 0.32, and the coefficient of variation of each indicator was less than 0.25. Finally, the indicators system of data source for the surveillance of acute respiratory infectious diseases includes 4 first-level indicators, 10 second-level indicators, and 26 third-level indicators.Conclusion:The indicator system of data sources for the surveillance of acute respiratory infectious diseases constructed in this study is reasonable and reliable, providing a valuable reference for surveillance, early warning and policy formulation of acute respiratory infectious diseases.

Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.

Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.

Objective:To explore the medication law of gilles de la Tourette syndrome (TS) in ancient TCM books through data mining.Methods:TS related disease information was searched by searching Chinese Medicine Collection Database 4.0 and Chinese Medical Classics 5.0 about liver wind, convulsion, infantile convulsion, slow infantile convulsion, Chi Zong, Jin Ti Rou Yu, chronic spleen wind. Excel 2022 software was used to input the main symptoms, etiology and pathogenesis, treatment methods and prescriptions of each disease, and the frequency, property and taste, meridian tropism and efficacy of medication were analyzed. Gephi 0.9.2 software was used to analyze the complex network of Chinese materia medica data to find out the core drugs. SPSS Statistic 25.0 software was used for clustering analysis of high-frequency Chinese materia medica (top 50 in frequency ). SPSS Modeler 14.2 software was used to analyze the association rules of high-frequency Chinese materia medica based on Apriori algorithm. Results:Totally 692 ancient prescriptions were included, involving 436 kinds of Chinese materia medica. The top five in terms of frequency were: Scorpio, Cinnabaris, Moschus, Typhonii Rhizoma, Gastrodiae Rhizoma appeared the most frequently. The main property was cold, the main taste was pungent, and mainly into the liver, spleen, and heart meridians; the core drugs were Bombyx Batryticatus, Pinelliae Rhizoma, and Glycyrrhizae Radix et Rhizoma. Clustering analysis could be divided into 8 categories. Correlation analysis showed that Scorpio→Bombyx mori Linnaeus and Cinnabaris had the highest support, while Cinnabaris→Bovis Calculus→Moschus→Scorpio had the highest confidence.Conclusions:Ancient doctors believed that the disease location of TS-related diseases are mainly liver, heart, spleen and kidney, and the pathogenic factors were mainly wind, fire, phlegm, blood stasis and deficiency. The insect snakes used in prescription drugs are used to search for wind and eliminate pathogenic factors, the epigraphy is used to calm the nerves and calm the wind, and the herbs are used to soothe the wind, clear heat, calm the liver and dispel phlegm.

Humans ; Aminoquinolines/therapeutic use* ; Carcinoma, Non-Small-Cell Lung/genetics* ; Lung Neoplasms/genetics* ; Mutation/genetics* ; Standard of Care