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.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

Objectives:To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods:Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation.Results:A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions:The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.Objectives To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation. Results A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.

Objective To construct a Gabra3 gene knockout cell model and explore transcriptomic and proteomic alterations in murine neuronal cells,in order to investigate the molecular mechanisms underlying the increased depth of slow-wave sleep observed following Gabra3 deletion.Methods Multiple sgRNA sequences were designed,and the CRISPR/Cas9 system was used to knock out the Gabra3 gene in the murine GT1-7 neuronal cell line.Gene sequencing was performed to assess knockout efficiency,and TA cloning was used to validate the knockout results.Protein immunoblotting experiments were conducted to confirm the knockout,while cell proliferation assays were used to validate the knockout phenotype.Total RNA and protein were extracted for transcriptomic and proteomic sequencing,respectively.A range of bioinformatics analyses was conducted to assess the functional consequences of Gabra3 knockout in GT1-7 neuronal cells.Results Following Gabra3 gene knockout,pathways related to cortisol and aldosterone synthesis and secretion,as well as circadian rhythm,were significantly enriched.Three key genes,BMP2,GLI2,and DLL1,were identified.Proteomic profiling revealed widespread disturbances in protein expression following Gabra3 knockout.Conclusion Gabra3 gene knockout may increase slow-wave sleep depth by modulating the expression of hormone secretion-related genes and altering circadian regulatory pathways.

The particularity of children's physiology and pathology determines that doctors should pay special attention to nursing in the process of treating pediatric diseases. This article discussed the dosage form and taking characteristics of pediatric prescriptions in Tai Ping Sheng Hui Fang from the aspects of dosage form and quantity, decoction, dosage, temperature, time, frequency and degree. It has been concluded that Tai Ping Sheng Hui Fang is rich in dosage forms, both internal and external treatment; paying attention to the care of the spleen and stomach, taking medicine in a light and specialized manner, and emphasizing the end of the disease; the way of taking medicine conforms to the physiological and pathological characteristics of children.

ObjectiveTo provide scientific support for the compilation of high-quality anti-nuclear， biological， and chemical （NBC） medical textbooks in China by retrieving books in the field of biological weapons defense in China， summarizing the publication time and distribution of publishing institutions， and categorizing content and key points of related books. MethodsRelevant subject terms in the field of biological weapons defense were searched through the official website of China National Digital Library and other websites， up until December 31， 2023， and were limited to books. Topic analysis was conducted on the introductions and contents of the books using the latent Dirichlet allocation （LDA） model. The number of topics was determined based on perplexity， and topics were identified according to the intertopic distance map， followed by a qualitative description of the core content of each topic. ResultsA total of 104 books were included in this study， among which four were identified as higher educational textbooks. The volume of publications increased during the periods 2002‒2004 and 2020‒2023. Research institutions accounted for the highest percentage of publishers （37.78%）， and 56.67% of the publishers were military institutions. The study identified six topics： "distribution， defense， and response to biological weapons"， "category， diagnosis， and treatment of biological warfare agents"， "response to biological public health emergencies"， "status of nuclear， biological， and chemical weapons internationally"， "biosafety risk management and prevention and control"， and "technologies and equipment related to biological hazard identification". ConclusionThere are few books in the field of biological weapons defense in China and the content is relatively outdated. In the future， the preparation of teaching materials should be aimed at practical emergency handling techniques for biological weapons， enhance the emphasis on biological weapons detection and biological warfare early warning， improve the fundamental theories at different training levels， and timely update the current research status in the field.

Objective:To summarize the best evidence for the management of ovarian hyperstimulation syndrome in patients undergoing assisted reproductive therapy.Methods:Evidence related to the management of ovarian hyperstimulation syndrome in patients undergoing assisted reproductive therapy,including guidelines,clinical decision,best clinical practice,systematic evaluation,expert consensus and evidence summary and related original research were systematically searched in UpToDate,BMJ Best Practice,World Health Organization(WHO)website,Guidelines International Network(GIN),National Institute for Health and Clinical Excellence(NICE)website,National Guidelines website,American Society for Reproductive Medicine(ASRM)website,New York Academy of Sciences(NYAS)website,Joanna Briggs Institute(JBI)database,Cochrane Library,CINAHL,PubMed,Wanfang database,CNKI,and China Biomedical Literature Database from inception to May 31,2024.Two researchers independently evaluated the quality of the literature,and a senior researcher made the final decision for literature inclusion.Results:A total of 15 articles were included in the study.Following quality assessment,one article was excluded.The remaining 14 articles included 5 practice guidelines,3 systematic reviews,2 expert consensuses,1 evidence summary,and 3 from UpToDate.Ultimately,27 pieces of evidence were identified across five key aspects:risk assessment,disease monitoring,early prevention,institutional management and health education.Conclusion:The updated evidence indicates that the monitoring and prevention of ovarian hyperstimulation syndrome should start early,personalized treatment plans should be provided for patients,and the rational allocation of treatment resources needs to be promoted to enhance effective management of ovarian hyper-stimulation syndrome.

Objective:To develop a short-term prognostic model of spontaneous cerebral hemorrhage based on eXtreme Gradient Boosting (XGBoost) machine learning, and to compare its predictive performance with a Logistic regression model.Methods:Patients with sICH admitted to Department of Neurology, Second People's Hospital of Hefei from January 2018 to March 2022 were chosen; their general demographic characteristics, medical history, laboratory indices and cranial imaging data were retrospectively collected. The prognoses of patients 90 d after discharge were evaluated according to modified Rankin Scale (mRS) scores (good prognosis: mRS scores<3; poor prognosis: mRS scores≥3). XGboost and multiple Logistic regression models were used to screen out the factors for prognoses of patients 90 d after discharge, and area under receiver operating characteristic (ROC) curves, sensitivity, specificity and prediction accuracy of the 2 models were analyzed and compared.Results:A total of 413 patients with sICH were included; 180 patients(43.6 %) had poor prognosis and 233 (56.4%) had good prognosis 90 d after discharge. Multivariate Logistic regression results showed that age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, hematoma volume>40 mL and National Institutes of Health Stroke Scale (NIHSS) scores were independent influencing factors for short-term prognoses of sICH ( P<0.05). The variables in the XGBoost model were ranked in order of importance: NIHSS scores, systolic blood pressure at admission, Glasgow coma scale (GCS) scores, age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, and hematoma volume>40 mL. AUC of XGBoost model in predicting the prognosis was 0.895 (95% CI: 0.820-0.947), enjoying sensitivity of 68.89%, specificity of 94.83%, and prediction accuracy of 83.5%. AUC of Logistic regression model in predicting the prognosis was 0.894 (95% CI: 0.818-0.946), enjoying sensitivity of 93.33%, specificity of 70.69%, and prediction accuracy of 80.58%. Conclusion:The short-term prognostic model based on XGboost for sICH patients has high predictive efficacy, whose predictive accuracy is better than traditional Logistic regression.

Objective:To identify differentially expressed genes (DEGs) associated with the progression of synovitis in RA by using bioinformatics analysis and explore the effects of DMARDs such as methotrexate, tocilizumab and rituximab on the DEGs in RA synovium.Methods:RA expression profile microarray data GSE7307、GSE12021、GSE55457、GSE55235、GSE77298、GSE89408 were acquired from the public gene chip database (GEO), including 113 synovial tissue samples from RA and 70 healthy controls (HC). At the same time, synovial expression microarrays GSE45867, GSE24742 and GSE97165 after DMARDs treatment were obtained. These data included 8 samples treated with methotrexate, 12 treated with tocilizumab, 12 treated with rituximab and 19 treated with combined tDMARDs. R software was used to screen DEGs and Venn plots using gene ontology function enrichment and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Hub genes were selected by STRING online analysis tool and Cytoscape software.Results:Compared with HC, 797 DEGs were up-regulated and 434 DEGs were down-regulated in the synovial tissue of RA. These DEGs were mainly enriched in T cell activation, immune response-activating cell surface receptor signaling pathway. Using Cytoscape and cytoHubba to obtain 5 sets of DEGs based on the STRING database model, the degree algorithm screened out 10 hub genes: LCK, SYK, PTPRC, HLA-DRA, LYN, NCAPG, TOP2A, JUN, CXCR4, CCNB1. Methotrexate treatment significantly up-regulated 20 DEGs and down-regulated 30 DEGs. Rituximab treatment up-regulated 100 DEGs and down-regulated 55 DEGs. Tocilizumab treatment up-regulated 91 DEGs and down-regulated 317 DEGs. These altered DEGs were enriched in regulating cell adhesion, leukocyte-cell adhesion, leukocyte transfer, and insulin-like growth factor receptor signaling pathways. It was worth noting that after treatment, a total of 306 high-expressing DEGs were down-regulated, and 36 low-expressing DEGs were up-regulated.Conclusion:LCK, insulin-like growth factor receptor signaling pathway, etc. are the responsible molecular mechanisms and key pivot genes for the occurrence and development of RA, and the treatment of DMARDs, which are closely related to the response of RA to the treatment of DMARDs.

Objective:To investigate Helicobactor pylori (H. pylori) infection status and interfamilial transmission pattern in Zhengzhou area. Methods:A cross-sectional study was conducted from September 2020 to march 2021, among 731 individual from 266 families randomly selected from 9 communities of Zhengzhou area. H. pylori infection status was determined by serum antibody tests, and 13C-urea breath test was performed in the previously eradicated population to clarify the current infection status. The individual and familial infection rate, infection status for couples and children and adolescent were analyzed. Results:Among 731 individuals from 266 families, 397 of them were H. pylori positive. The individual infection rate was 54.31% (397/731); among infected individuals 77.83% (307/397) were infected with type Ⅰ strain, 22.67% (90/397) were infected by type Ⅱ strain. Annual household income ( χ2=0.419, 0.410, 0.213, all P>0.05), smoking history (χ 2=0.071, P>0.05), drinking history ( χ2=0.071, P>0.05), dining place ( χ2=0.009, P>0.05), gastrointestinal symptoms ( χ2=0.047, P>0.05), family history of gastric disease ( χ2=0.069, P>0.05), and history of gastric cancer ( χ2=0.004, P>0.05) had no significant differences between H. pylori-positive and -negative groups, but the infection rate in individuals with higher education level was lower ( χ2=4.449, P<0.05). The infection rate was significantly higher in≥18 age groups compared with<18 age groups ( χ2=6.531, 23.362, 20.671, 24.244, 37.948, 14.597 and 5.170, all P<0.05). The familial H. pylori infection rate was 87.59% (233/266), and in 61 families all member were infected (26.18%, 61/233). The positive rate was 23.08% (6/26) in 50 families with children under 18 years when both parents were infected. Among 231 coupled families, both couples were infected in 78 families (33.76%), one couple was infected in 113 families (48.92%), and both couples were not infected in 40 (17.32%). With the increase of marriage time, the infection rate of both spouses increased significantly ( χ2=7.775, 12.662, 15.487, all P<0.05). Conclusions:The distribution of H. pylori infection presents a family cluster pattern, and intrafamilial infection is an important transmission rout of H. pylori. The type I strain of H. pylori is the dominate strain in this area.