ObjectiveTo investigate the intervention effects and mechanisms of the flavonoid hyperoside （Hyp） on lipopolysaccharide （LPS）-induced inflammation in the zebrafish model. MethodsZebrafish larvae were either microinjected with 0.5 g·L^-1 LPS or immersed in 1 g·L^-1 LPS for the modeling of inflammation. The larvae were then treated with Hyp at 25， 50， and 100 mg·L^-1 through immersion for four consecutive days. The inflammatory phenotypes were assessed by analyzing the mortality rate， malformation rate， body length， and yolk sac area ratio. Behavioral tests were conducted to evaluate the inflammatory stress responses， and macrophage migration was observed by fluorescence microscopy. Additionally， the mRNA levels of inflammation-related genes， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， chemokine C-C motif ligand 2 （CCL2）， chemokine C-X3-C motif receptor 1 （CX3CR1）， chemokine C-C motif receptor 2 （CCR2）， and genes associated with the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-kappa B （NF-κB） signaling pathway， were measured by Real-time quantitative polymerase chain reaction（Real-time PCR）. ResultsCompared with the pure water injection group， the model group exhibited increased mortality， malformation rates and yolk sac area ratio （P0.01）， reduced body length （P0.01）， increased total swimming distance and high-speed swimming duration （P0.01）， and up-regulated mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.01）. Hyp at low， medium and high doses， as well as aspirin， reduced the mortality and malformation rates （P0.05，P0.01）， increased the body length （P0.05，P0.01）， decreased the yolk sac area ratio （P0.01）， reduced the high-speed swimming duration （P0.01）， and down-regulated the mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.05，P0.01） compared with the model group. ConclusionHyp may modulate the TLR4/MyD88/NF-κB pathway to ameliorate inflammatory phenotypes and alleviate stress conditions in zebrafish， thereby exerting the anti-inflammatory effect.

Objective:To investigate the clinical characteristics of children with severe human metapneumovirus (HMPV) infection and identify the risk factors associated with critical illness.Methods:A retrospective cohort study was conducted, enrolling 157 hospitalized children with severe HMPV infection, who tested positive for HMPV nucleic acid via PCR-capillary electrophoresis fragment analysis of nasopharyngeal secretions at Shanghai Children′s Hospital from January 2021 to December 2023.Clinical features, co-infections, treatment, and outcomes were collected. Based on the diagnostic criteria for severe HMPV infection, the patients were categorized into a critical illness group and a non-critical illness group. Intergroup comparisons were performed using the χ2 test or the Mann-Whitney U test. Multivariate Logistic regression analysis was employed to identify risk factors for critical HMPV infection and to establish a predictive model.The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis and calibration curves. Results:Among the 157 cases of severe HMPV infection, there were 67 males and 90 females, with an onset age of 39.0 (20.0, 55.5) months. Single-pathogen infection was observed in 125 cases (79.6%), while mixed infections accounted for 32 cases (20.4%).Severe pneumonia was diagnosed in 136 cases (86.6%).The predominant manifestations of severe HMPV infection included fever 152 cases (96.8%), cough 151 cases (96.2%), and wheezing 94 cases (59.9%).Sixty-eight patients (43.3%) required non-invasive respiratory support, 58 cases (36.9%) were admitted to the intensive care unit, and 22 cases (14.0%) underwent mechanical ventilation. Of the total, 149 cases (94.9%) were discharged with improvement, 8 cases (5.1%) were discharged against medical advice, and there were no fatal cases. The cohort was further stratified into a critical illness group 31 cases and a non-critical illness group 126 cases. Compared to the non-critical illness group, the critical illness group exhibited significantly higher rates of respiratory distress, lethargy, and intercostal retractions, along with a higher proportion of underlying comorbidities, and elevated levels of C-reactive protein and procalcitonin (all P<0.05).Conversely, albumin and hemoglobin levels were significantly lower in the critical illness group (both P<0.05). ROC curve analysis revealed that the optimal cutoff value for the duration of fever in predicting severe HMPV infection was 4.5 days.The multivariate binary Logistic regression analysis revealed that prolonged fever duration (>4.5 days) ( OR=28.00, 95% CI 5.09-153.93, P<0.001), anorexia ( OR=11.72, 95% CI 1.26-108.75, P=0.030), and immune dysfunction ( OR=36.71, 95% CI 1.55-867.31, P=0.026) were independent risk factors for severe HMPV infection. A predictive model for critical illness was constructed based on these independent risk factors. ROC curve analysis demonstrated excellent discriminative ability, with an area under the curve of 0.96 (95% CI 0.92-1.00, P<0.001). The optimal predictive probability threshold was 0.17, yielding a sensitivity of 0.93 and specificity of 0.92. The calibration curve closely approximated the ideal curve, indicating good model calibration ( P=0.157). Conclusions:Severe HMPV infection is predominantly observed as a single infection and is prone to progress to severe pneumonia, with fever, cough, and wheezing as the main clinical manifestations. A subset of cases progresses to critical illness, though the overall prognosis is favorable. Prolonged fever duration (>4.5 days), anorexia, and immune dysfunction were independent risk factors for critical illness.The risk prediction model constructed for pediatric critical HMPV infection demonstrated robust discriminative ability with excellent calibration.

Objective:To analyze the distribution and epidemiological characteristics of non-bacterial pathogens in hospitalized children with acute respiratory infections at a tertiary pediatric hospital in Shanghai during 2023.Methods:A retrospective study was conducted on 10 591 children with acute respiratory tract infections who were hospitalized in Shanghai Children's Hospital from January to December 2023. A multiplex PCR combined with capillary electrophoresis platform was used to detect 11 common non-bacterial respiratory pathogens（including viruses and atypical pathogens）. Statistical analysis was carried out using SPSS 29.0 software. Qualitative data were presented as numbers and percentages，and the Chi-square test was employed to make comparisons between groups，aiming to analyze the differences in the distribution of different pathogens according to gender，age group，and season. Additionally，based on the severity of the disease，patients were calssified into a severe pneumonia group and a non-severe pneumonia group to further explore the characteristics of the pathogen spectrum of severe pneumonia.Results:The total detection rate of pathogens was 54.39%（5 760/10 591），and the proportion of mixed infections was 12.76%（735/5 760）. The dominant pathogens and their proportions were as follows： Mycoplasma pneumoniae（19.20%，2 034/10 591），human rhinovirus（12.16%，1 288/10 591），influenza A virus（8.31%，880/10 591），and respiratory syncytial virus（8.14%，862/10 591）. Epidemiological characteristics showed that：（1）In terms of age： Mycoplasma pneumoniae was more common in older children（29.55%，901/3 049，in the school-age group，χ 2 = 653.67， P<0.001）. Influenza A virus had a high incidence in the adolescent group（11.34%，45/397，χ 2=48.69， P<0.001）. Respiratory syncytial virus was most susceptible in the infant group（20.94%，280/1 337，χ 2=739.92， P<0.001）. Human rhinovirus showed the characteristic of general susceptibility across all ages.（2）Monthly and seasonal distribution： Mycoplasma pneumoniae had a seasonal epidemic in summer and autumn（it began to rise in May and peaked in October at 34.22%，439/1 283）；influenza A virus had a bimodal distribution in spring and winter（the peak was 37.15% in March，315/848）；respiratory syncytial virus had a dominant epidemic in spring and summer（the detection rate was 21.24% in May，206/970），and human rhinovirus was prevalent throughout the year.（3）Clinical correlation：The detection rate of pathogens in the severe pneumonia group was significantly higher than that in the non-severe group：84.19%（426/506） vs 2.89%（5 334/10 085），χ 2=56.23， P<0.001. Conclusions:In 2023，the pathogen spectrum of hospitalized children with acute respiratory infections in the Shanghai area exhibits an epidemic pattern dominated by Mycoplasma pneumoniae，and its transmission dynamics are significantly age-dependent. This study delineates the pathogen-host-environment tripartite interactions，establishing an evidence-based foundation for formulating precision diagnostic-therapeutic algorithms and seasonal nosocomial infection prevention frameworks.

Objective:To analyze the distribution and epidemiological characteristics of non-bacterial pathogens in hospitalized children with acute respiratory infections at a tertiary pediatric hospital in Shanghai during 2023.Methods:A retrospective study was conducted on 10 591 children with acute respiratory tract infections who were hospitalized in Shanghai Children's Hospital from January to December 2023. A multiplex PCR combined with capillary electrophoresis platform was used to detect 11 common non-bacterial respiratory pathogens（including viruses and atypical pathogens）. Statistical analysis was carried out using SPSS 29.0 software. Qualitative data were presented as numbers and percentages，and the Chi-square test was employed to make comparisons between groups，aiming to analyze the differences in the distribution of different pathogens according to gender，age group，and season. Additionally，based on the severity of the disease，patients were calssified into a severe pneumonia group and a non-severe pneumonia group to further explore the characteristics of the pathogen spectrum of severe pneumonia.Results:The total detection rate of pathogens was 54.39%（5 760/10 591），and the proportion of mixed infections was 12.76%（735/5 760）. The dominant pathogens and their proportions were as follows： Mycoplasma pneumoniae（19.20%，2 034/10 591），human rhinovirus（12.16%，1 288/10 591），influenza A virus（8.31%，880/10 591），and respiratory syncytial virus（8.14%，862/10 591）. Epidemiological characteristics showed that：（1）In terms of age： Mycoplasma pneumoniae was more common in older children（29.55%，901/3 049，in the school-age group，χ 2 = 653.67， P<0.001）. Influenza A virus had a high incidence in the adolescent group（11.34%，45/397，χ 2=48.69， P<0.001）. Respiratory syncytial virus was most susceptible in the infant group（20.94%，280/1 337，χ 2=739.92， P<0.001）. Human rhinovirus showed the characteristic of general susceptibility across all ages.（2）Monthly and seasonal distribution： Mycoplasma pneumoniae had a seasonal epidemic in summer and autumn（it began to rise in May and peaked in October at 34.22%，439/1 283）；influenza A virus had a bimodal distribution in spring and winter（the peak was 37.15% in March，315/848）；respiratory syncytial virus had a dominant epidemic in spring and summer（the detection rate was 21.24% in May，206/970），and human rhinovirus was prevalent throughout the year.（3）Clinical correlation：The detection rate of pathogens in the severe pneumonia group was significantly higher than that in the non-severe group：84.19%（426/506） vs 2.89%（5 334/10 085），χ 2=56.23， P<0.001. Conclusions:In 2023，the pathogen spectrum of hospitalized children with acute respiratory infections in the Shanghai area exhibits an epidemic pattern dominated by Mycoplasma pneumoniae，and its transmission dynamics are significantly age-dependent. This study delineates the pathogen-host-environment tripartite interactions，establishing an evidence-based foundation for formulating precision diagnostic-therapeutic algorithms and seasonal nosocomial infection prevention frameworks.

Objective:To investigate the clinical characteristics of children with severe human metapneumovirus (HMPV) infection and identify the risk factors associated with critical illness.Methods:A retrospective cohort study was conducted, enrolling 157 hospitalized children with severe HMPV infection, who tested positive for HMPV nucleic acid via PCR-capillary electrophoresis fragment analysis of nasopharyngeal secretions at Shanghai Children′s Hospital from January 2021 to December 2023.Clinical features, co-infections, treatment, and outcomes were collected. Based on the diagnostic criteria for severe HMPV infection, the patients were categorized into a critical illness group and a non-critical illness group. Intergroup comparisons were performed using the χ2 test or the Mann-Whitney U test. Multivariate Logistic regression analysis was employed to identify risk factors for critical HMPV infection and to establish a predictive model.The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis and calibration curves. Results:Among the 157 cases of severe HMPV infection, there were 67 males and 90 females, with an onset age of 39.0 (20.0, 55.5) months. Single-pathogen infection was observed in 125 cases (79.6%), while mixed infections accounted for 32 cases (20.4%).Severe pneumonia was diagnosed in 136 cases (86.6%).The predominant manifestations of severe HMPV infection included fever 152 cases (96.8%), cough 151 cases (96.2%), and wheezing 94 cases (59.9%).Sixty-eight patients (43.3%) required non-invasive respiratory support, 58 cases (36.9%) were admitted to the intensive care unit, and 22 cases (14.0%) underwent mechanical ventilation. Of the total, 149 cases (94.9%) were discharged with improvement, 8 cases (5.1%) were discharged against medical advice, and there were no fatal cases. The cohort was further stratified into a critical illness group 31 cases and a non-critical illness group 126 cases. Compared to the non-critical illness group, the critical illness group exhibited significantly higher rates of respiratory distress, lethargy, and intercostal retractions, along with a higher proportion of underlying comorbidities, and elevated levels of C-reactive protein and procalcitonin (all P<0.05).Conversely, albumin and hemoglobin levels were significantly lower in the critical illness group (both P<0.05). ROC curve analysis revealed that the optimal cutoff value for the duration of fever in predicting severe HMPV infection was 4.5 days.The multivariate binary Logistic regression analysis revealed that prolonged fever duration (>4.5 days) ( OR=28.00, 95% CI 5.09-153.93, P<0.001), anorexia ( OR=11.72, 95% CI 1.26-108.75, P=0.030), and immune dysfunction ( OR=36.71, 95% CI 1.55-867.31, P=0.026) were independent risk factors for severe HMPV infection. A predictive model for critical illness was constructed based on these independent risk factors. ROC curve analysis demonstrated excellent discriminative ability, with an area under the curve of 0.96 (95% CI 0.92-1.00, P<0.001). The optimal predictive probability threshold was 0.17, yielding a sensitivity of 0.93 and specificity of 0.92. The calibration curve closely approximated the ideal curve, indicating good model calibration ( P=0.157). Conclusions:Severe HMPV infection is predominantly observed as a single infection and is prone to progress to severe pneumonia, with fever, cough, and wheezing as the main clinical manifestations. A subset of cases progresses to critical illness, though the overall prognosis is favorable. Prolonged fever duration (>4.5 days), anorexia, and immune dysfunction were independent risk factors for critical illness.The risk prediction model constructed for pediatric critical HMPV infection demonstrated robust discriminative ability with excellent calibration.

ObjectiveDetection and quantification of RNA synthesis in cells is a widely used technique for monitoring cell viability, health, and metabolic rate.After exposure to environmental stimuli, both the internal reference gene and target gene would be degraded. As a result, it is imperative to consider the accurate capture of nascent RNA and the detection of transcriptional levels of RNA following environmental stimulation. This study aims to create a Click Chemistry method that utilizes its property to capture nascent RNA from total RNA that was stimulated by the environment. MethodsThe new RNA was labeled with 5-ethyluridine (5-EU) instead of uracil, and the azido-biotin medium ligand was connected to the magnetic sphere using a combination of “Click Chemistry” and magnetic bead screening. Then the new RNA was captured and the transcription rate of 16S rRNA was detected by fluorescence molecular beacon (M.B.) and quantitative reverse transcription PCR (qRT-PCR). ResultsThe bacterial nascent RNA captured by “Click Chemistry” screening can be used as a reverse transcription template to form cDNA. Combined with the fluorescent molecular beacon M.B.1, the synthesis rate of rRNA at 37℃ is 1.2 times higher than that at 15℃. The 16S rRNA gene and cspI gene can be detected by fluorescent quantitative PCR,it was found that the measured relative gene expression changes were significantly enhanced at 25℃ and 16℃ when analyzed with nascent RNA rather than total RNA, enabling accurate detection of RNA transcription rates. ConclusionCompared to other article reported experimental methods that utilize screening magnetic columns, the technical scheme employed in this study is more suitable for bacteria, and the operation steps are simple and easy to implement, making it an effective RNA capture method for researchers.

Objective This study aimed to reveal critical genes regulating peri-implantitis during its development and construct a diagnostic model by using random forest(RF)and artificial neural network(ANN).Methods GSE-33774,GSE106090,and GSE57631 datasets were obtained from the GEO database.The GSE33774 and GSE106090 da-tasets were analyzed for differential expression and functional enrichment.The protein-protein interaction networks(PPI)and RF screened vital genes.A diagnostic model for peri-implantitis was established using ANN and validated on the GSE33774 and GSE57631 datasets.A transcription factor-gene interaction network and a transcription factor-micro-RNA(miRNA)regulatory network were also established.Results A total of 124 differentially expressed genes(DEGs)involved in the regulation of peri-implantitis were screened.Enrichment analysis showed that DEGs were mainly associated with immune receptor activity and cytokine receptor activity and were mainly involved in processes such as leukocyte and neutrophil migration.The PPI and RF screened six essential genes,namely,CD38,CYBB,FCGR2A,SELL,TLR4,and CXCL8.The receiver oper-ating characteristic curve(ROC)indicated that the ANN model had an excellent diagnostic performance.FOXC1,GA-TA2,and NF-κB1 may be essential transcription factors in peri-implantitis,and hsa-miR-204 may be a key miRNA.Con-clusion The diagnostic model of peri-implantitis constructed by RF and ANN has high confidence,and CD38,CYBB,FCGR2A,SELL,TLR4,and CXCL8 are potential diagnostic markers.FOXC1,GATA2,and NF-κB1 may be essential transcription factors in peri-implantitis,and hsa-miR-204 plays a vital role as a critical miRNA.

Objective This study aims to investigate the role of genes related to fatty acid metabolism in periodon-titis through machine learning and bioinformatics methods.Methods Periodontitis datasets GSE10334 and GSE-16134 were downloaded from the GEO database,and the fatty acid metabolism-related gene sets were obtained from the GeneCards database.Differentially expressed fatty acid metabolism-related genes(DEFAMRGs)in periodontitis were screened using the"limma"R package.Functional enrichment and pathway analyses were conducted.Recursive Feature Elimination,Least Absolute Shrinkage and Selection Operator,and Boruta algorithm were used to determine hub DEFAMRGs and construct diagnostic models with internal and external validation.Subtypes of periodontitis relat-ed to hub DEFAMRGs were constructed using consis-tency clustering analysis.CIBERSORT was used to ana-lyze immune cell infiltration in gingival tissues and ex-plore the correlation between hub DEFAMRGs and im-mune cells.Results A total of 113 periodontitis DE-FAMRGs were screened out as a result.The enrichment analysis results indicate that DEFAMRGs are mainly associat-ed with immune inflammatory responses and immune cell chemotaxis.Finally,8 hub DEFAMRGs(BTG2,CXCL12,FABP4,CLDN10,PPBP,RGS1,LGALSL,and RIF1)were identified and a diagnostic model(AUC=0.967)was con-structed,based on which periodontitis was divided into two subtypes.In addition,there is a significant correlation be-tween hub DEFAMRGs and different immune cell populations,with mast cells and dendritic cells showing higher cor-relation.Conclusion This study provides new insights and ideas for the occurrence and development mechanism of periodontitis and proposes a diagnostic model based on hub DEFAMRGs to provide new directions for diagnosis and treatment.

Myocarditis is characterized by inflammatory cell infiltration into the myocardium and a high risk of deteriorating cardiac function with a heterogeneous etiology. Both viral- and myosin-induced myocarditis experimental models are used to mimic myocarditis in humans. Here, coxsackie virus B3-induced and non-virus-induced myocarditis models and data obtained in clinical studies were reviewed. Experimental murine myocarditis following immunization with α-myosin together with complete Freund adjuvant represents the classical immune-mediated model. T helper 1 (Th1) and Th2 pathways and important cytokines are involved in the autoimmunity of myocarditis, and the dynamic balance between Th17 and regulatory T cell seems to have an important role in the process of myocarditis. The purpose of this review is to summarize the existing understanding of the immunological mechanisms underlying myocarditis and exploring gaps in knowledge in both animal and human studies, since these mechanistic insights are a critical requirement for the development of novel therapeutic and vaccination strategies.

Myocarditis is characterized by inflammatory cell infiltration into the myocardium and a high risk of deteriorating cardiac function with a heterogeneous etiology. Both viral- and myosin-induced myocarditis experimental models are used to mimic myocarditis in humans. Here, coxsackie virus B3-induced and non-virus-induced myocarditis models and data obtained in clinical studies were reviewed. Experimental murine myocarditis following immunization with α-myosin together with complete Freund adjuvant represents the classical immune-mediated model. T helper 1 (Th1) and Th2 pathways and important cytokines are involved in the autoimmunity of myocarditis, and the dynamic balance between Th17 and regulatory T cell seems to have an important role in the process of myocarditis. The purpose of this review is to summarize the existing understanding of the immunological mechanisms underlying myocarditis and exploring gaps in knowledge in both animal and human studies, since these mechanistic insights are a critical requirement for the development of novel therapeutic and vaccination strategies.