Objective:To explore the non-bacterial pathogen distribution, epidemiological characteristics, and clinical features of acute respiratory infections in children in Sichuan Province.Methods:Using a retrospective cohort study method, this study selected hospitalized children diagnosed with acute respiratory infections at West China Second Hospital of Sichuan University from February 2019 to January 2021, and tested 13 pathogens using polymerase chain reaction (PCR)-fragment analysis. The children were divided into infant group (<1 year old), toddler group (1 year old ≤ age <3 years old), preschool group (3 years old ≤ age <6 years old) and school-age group (6 years old ≤ age <18 years old). The distribution of pathogen positive rates, seasonal epidemic characteristics, clinical characteristics, and some laboratory test indicators were analyzed in children. Statistical analysis was performed on the results using SPSS 22.0 software, with count data expressed as percentages and inter group comparisons using SPSS 22.0 software χ2 Inspection. Results:A total of 2 922 pediatric patients were included in this study, with 1 748 (59.8%) positive for pathogens detected. Among them, 1 391 (79.6%) were detected as a single pathogen, and 357 (20.4%) were detected as a mixture of two or more pathogens. The most commonly detected pathogens were rhinovirus (HRV) (39.7%), syncytial virus (RSV) (22.8%), and parainfluenza virus (PIV) (12.5%). Pathogen positivity is more common in children under 6 years old ( χ2=146.59, P<0.001), with a slightly higher positivity rate in male children (61.3%, 1 047/1 707) than in female children (57.7%, 701/1 215) ( χ2=3.91, P=0.048), and compared with pathogen negative children, positive children are more prone to symptoms such as cough, wheezing, and shortness of breath ( χ2=259.15, 366.06, 12.48, P<0.001). The distribution of different pathogens varies among children of different age groups, and HRV is more common in children aged 1-3 and 3-6 years old ( χ2=9.74, P<0.001), while RSV is more common in children under 1 year old ( χ2=178.63, P<0.001), while mycoplasma pneumoniae (MP) and influenza virus (InfA/B) are less common in children under 1 year old ( χ2=92.54, 12.90,22.21, P<0.01). The prevalence of multiple pathogens showed seasonal changes. HRV showed a high prevalence trend in spring and autumn, while the prevalence of RSV infection was mainly seen in autumn and winter festivals. The positive rate of different pathogens after the outbreak of novel coronavirus pneumonia was significantly lower than that before the outbreak ( χ2=252.68, P<0.001). Conclusion:The detection rate of non-bacterial respiratory pathogens in children in Sichuan Province from 2019 to 2021 is high, which is prone to symptoms such as cough, wheezing, and shortness of breath, with HRV and RSV being the main types. The positive rate of respiratory pathogens varies among different age groups, genders, and seasons.

Objective:To explore the non-bacterial pathogen distribution, epidemiological characteristics, and clinical features of acute respiratory infections in children in Sichuan Province.Methods:Using a retrospective cohort study method, this study selected hospitalized children diagnosed with acute respiratory infections at West China Second Hospital of Sichuan University from February 2019 to January 2021, and tested 13 pathogens using polymerase chain reaction (PCR)-fragment analysis. The children were divided into infant group (<1 year old), toddler group (1 year old ≤ age <3 years old), preschool group (3 years old ≤ age <6 years old) and school-age group (6 years old ≤ age <18 years old). The distribution of pathogen positive rates, seasonal epidemic characteristics, clinical characteristics, and some laboratory test indicators were analyzed in children. Statistical analysis was performed on the results using SPSS 22.0 software, with count data expressed as percentages and inter group comparisons using SPSS 22.0 software χ2 Inspection. Results:A total of 2 922 pediatric patients were included in this study, with 1 748 (59.8%) positive for pathogens detected. Among them, 1 391 (79.6%) were detected as a single pathogen, and 357 (20.4%) were detected as a mixture of two or more pathogens. The most commonly detected pathogens were rhinovirus (HRV) (39.7%), syncytial virus (RSV) (22.8%), and parainfluenza virus (PIV) (12.5%). Pathogen positivity is more common in children under 6 years old ( χ2=146.59, P<0.001), with a slightly higher positivity rate in male children (61.3%, 1 047/1 707) than in female children (57.7%, 701/1 215) ( χ2=3.91, P=0.048), and compared with pathogen negative children, positive children are more prone to symptoms such as cough, wheezing, and shortness of breath ( χ2=259.15, 366.06, 12.48, P<0.001). The distribution of different pathogens varies among children of different age groups, and HRV is more common in children aged 1-3 and 3-6 years old ( χ2=9.74, P<0.001), while RSV is more common in children under 1 year old ( χ2=178.63, P<0.001), while mycoplasma pneumoniae (MP) and influenza virus (InfA/B) are less common in children under 1 year old ( χ2=92.54, 12.90,22.21, P<0.01). The prevalence of multiple pathogens showed seasonal changes. HRV showed a high prevalence trend in spring and autumn, while the prevalence of RSV infection was mainly seen in autumn and winter festivals. The positive rate of different pathogens after the outbreak of novel coronavirus pneumonia was significantly lower than that before the outbreak ( χ2=252.68, P<0.001). Conclusion:The detection rate of non-bacterial respiratory pathogens in children in Sichuan Province from 2019 to 2021 is high, which is prone to symptoms such as cough, wheezing, and shortness of breath, with HRV and RSV being the main types. The positive rate of respiratory pathogens varies among different age groups, genders, and seasons.

Background: Ziziphi Spinosae Semen (ZSS) contains a wide range of active components. Because existing methods cannot fully evaluate these components, a new quantitative method needs to be established for component characterization. Objective: Ziziphi Spinosae Semen has gained increasing attention in recent years, primarily as a medicinal and edible plant. The content determination of ZSS is not specified in the Chinese Pharmacopeia (2020 edition). Environmental conditions in different production areas can influence the quality of ZSS. This study aims to identify ZSS collected from various geographical origins in China. Materials and methods: High-performance liquid chromatography (HPLC) fingerprints were established using optimized HPLC-photo-diode array methods. Subsequently, similarity analysis and quantification of ZSS from different sources were conducted. Metabolites of ZSS were identified and evaluated using the UHPLC-Q Exactive HF Orbitrap MS system. Principal component analysis, hierarchical cluster analysis, and orthogonal partial least squares discriminant analysis were performed based on all peak areas. Results: In this study, the components of ZSS against insomnia were screened through network pharmacology. As revealed by the results of protein-protein interaction network analysis, Gene Ontology analysis, and Kyoto Encyclopedia of Genes and Genomes pathway analysis, 14 core components, 10 core targets, and 25 pathways were identified. Thirty-four batches of ZSS fingerprints were established through the HPLC method, which identified 12 characteristic peaks, with 6 being qualitatively identified. An identification method for assessing differences in the chemical composition of ZSS from different origins was developed by using UHPLC-Q Exactive HF Orbitrap MS. Differential markers from various origins were screened and identified. Through multiple analyses such as principal component analysis and orthogonal partial least squares discriminant analysis, it was concluded that there were differences in ZSS metabolites from Hebei, Shandong, and Shaanxi provinces. Seventeen differential metabolites of different origins were identified. Conclusions: This study confirmed that ZSS played a synergistic role in improving insomnia through multiple components, targets, and pathways. The content of all 5 components was high, except for jujuboside B. In addition, 6 compounds in ZSS extracts from different origins differed in content, indicating that different growth environments might impact the quality of ZSS.