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.

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.

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.

Objective:To investigate the current situation of water-borne endemic fluorosis in Anhui Province, and provide basic data for the adjusting the prevention and control measures.Methods:Using cross-sectional survey method, all villages in the water-borne endemic fluorosis areas were investigated in Anhui Province from 2019 to 2022. In water-borne endemic fluorosis village, the situation of water improvement project and the fluoride level of drinking water were investigated, and dental fluorosis of all children aged 8 - 12 was examined. The criteria for determining the achievement of control targets for water-borne endemic fluorosis in affected counties were based on the "Evaluation Measures for Control and Elimination of Key Endemic Diseases (2019 Edition)".Results:From 2019 to 2022, the rate of water improvement village in water-borne endemic fluorosis areas were 88.47% (1 527/1 726), 100% (1 726/1 726), 100% (1 726/1 726) and 100% (1 726/1 726), respectively. The qualified proportion of water fluoride in water-borne endemic fluorosis villages was 33.84% (584/1 726), 63.09% (1 089/1 726), 70.74% (1 221/1 726) and 74.33% (1 283/1 726), respectively. The prevalence rates of dental fluorosis in children aged 8 - 12 were 25.48% (45 461/178 440), 15.78% (27 959/177 200), 13.68% (23 505/171 880) and 12.66% (23 315/184 200), respectively. The proportion of affected counties that had achieved the control target of water-borne endemic fluorosis was 16% (4/25), 60% (15/25), 36% (9/25) and 40% (10/25), respectively.Conclusions:The water-borne endemic fluorosis areas in Anhui Province have improved the water fluoride qualification rate and reduced the incidence of fluorosis in children through prevention and control measures such as water improvement and fluoride reduction. However, the prevention and control efforts in key areas and counties need to be further improved.

Objective:The differentially expressed genes(DEGs)and activated signaling pathways in systemic sclerosis(SSc)were screened by bioinformatics methods,and Chinese medicines for potential treatment of SSc were explored,providing a new theoretical basis for the study of SSc and the screening of potential markers.Methods:The data sets GSE58095,GSE130953,GSE33463 and GSE58613 were selected from GEO database and divided into skin group and peripheral blood group according to the sample source.The DEGs of SSc patients was analyzed by R language,and the Wayne diagram was drawn to take the intersection of the two groups.Metascape was used for GO enrichment analysis and KEGG pathway enrichment analysis,and STRING and Cytoscape were used for protein interaction network analysis to find key pathways and hub genes.The core genes were mapped to the medical on-tology information retrieval platform,and related Chinese medicines for SSc treatment were screened.The effective components of Chi-nese medicines were obtained through TCMSP and HERB databases,and the target letters of active ingredients were obtained through swiss database.The"drug-active ingredient-target"network was constructed by Cytoscape.Results:Total 218 DEGs were identified from the skin group of patients with SSc,and 283 DEGs were screened from peripheral blood of patients with SSc.Among them,there were 7 DEGs co-upregulated in skin and peripheral blood,namely ISG15,LGALS3BP,BST2,C1QB,IFI27,CEACAM1 and FBP1.CAMK2N1 was up-regulated in skin but down-regulated in peripheral blood,ARG1 was down-regulated in skin but up-regulated in pe-ripheral blood.GO and KEGG analysis of SSc DEGs showed that these genes were significantly enriched in inflammatory response,he-moglobin complex,immune receptor activity and extracellular matrix.The results of protein interaction network suggest that more than 10 genes such as COL1A1,CTGF12,IL1B,IFNG and JUN may be potential markers of SSc and core genes of therapeutic targets.The potential Chinese medicines screened for SSc treatment include ginseng,sanguisorba,convolvula,wolfberry,safflower,etc.The main components of these herbs were β-sitosterol,quercetin,kaempferol,stigmasterol,luteolin,sitosterol,Spinasterol,and the target were AKR1B1,AR,CYP1B1,XDH,etc.Conclusion:This study uses bioinformatics to screen out core genes that may be potential markers and therapeutic targets for SSc,which is expected to be a new target for the early diagnosis and mechanism research of SSc.Meanwhile,the mapped Chinese medicine and its effective components can provide ideas for the research and development of Chinese medicine compounds for the treatment of SSc.

This study characterized the whole-genome sequences of 45 Coxsackievirus A6(CVA6)strains isolated from Pudong District,Shanghai,during 2015-2023,to elucidate regional genetic evolution and recombination patterns.Viral genomes were ampli-fied and sequenced with Illumina MiSeq platforms,and phylogenetic analysis of the VP1 and 3D regions was conducted via MEGA 11(maximum-likelihood method,bootstrap=1 000).Nucleotide/amino acid homology and variation sites were assessed in DNAstar v7.0,and recombination events were identified with SimPlot v3.5.1 and RDP4.All isolates belonged to the D3a subtype,and exhibited intra-strain nucleotide and amino acid homologies of 88.0%-99.9%and 92.4%-100%,respectively,in contrast to lower homologies to the prototype Gdula strain(78.0%-80.5%nucleotide;94.5%-95.1%amino acid).Thirty-six mutation sites were identified in the VP1 re-gion.Recombination analysis revealed frequent cross-serotype events involving CVA4 and EV-A71,with dominant RF-A(84.5%)and minor RF-K(15.5%)patterns localized in the 3D region.This study elucidated the gene recombination and genetic evolution of CVA6 in Pudong District,Shanghai,thereby providing data support to enhance understanding of the evolutionary trends and genetic characteristics of coxsackieviruses,and offering theoretical evidence for the prevention and control of CVA6.

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:The differentially expressed genes(DEGs)and activated signaling pathways in systemic sclerosis(SSc)were screened by bioinformatics methods,and Chinese medicines for potential treatment of SSc were explored,providing a new theoretical basis for the study of SSc and the screening of potential markers.Methods:The data sets GSE58095,GSE130953,GSE33463 and GSE58613 were selected from GEO database and divided into skin group and peripheral blood group according to the sample source.The DEGs of SSc patients was analyzed by R language,and the Wayne diagram was drawn to take the intersection of the two groups.Metascape was used for GO enrichment analysis and KEGG pathway enrichment analysis,and STRING and Cytoscape were used for protein interaction network analysis to find key pathways and hub genes.The core genes were mapped to the medical on-tology information retrieval platform,and related Chinese medicines for SSc treatment were screened.The effective components of Chi-nese medicines were obtained through TCMSP and HERB databases,and the target letters of active ingredients were obtained through swiss database.The"drug-active ingredient-target"network was constructed by Cytoscape.Results:Total 218 DEGs were identified from the skin group of patients with SSc,and 283 DEGs were screened from peripheral blood of patients with SSc.Among them,there were 7 DEGs co-upregulated in skin and peripheral blood,namely ISG15,LGALS3BP,BST2,C1QB,IFI27,CEACAM1 and FBP1.CAMK2N1 was up-regulated in skin but down-regulated in peripheral blood,ARG1 was down-regulated in skin but up-regulated in pe-ripheral blood.GO and KEGG analysis of SSc DEGs showed that these genes were significantly enriched in inflammatory response,he-moglobin complex,immune receptor activity and extracellular matrix.The results of protein interaction network suggest that more than 10 genes such as COL1A1,CTGF12,IL1B,IFNG and JUN may be potential markers of SSc and core genes of therapeutic targets.The potential Chinese medicines screened for SSc treatment include ginseng,sanguisorba,convolvula,wolfberry,safflower,etc.The main components of these herbs were β-sitosterol,quercetin,kaempferol,stigmasterol,luteolin,sitosterol,Spinasterol,and the target were AKR1B1,AR,CYP1B1,XDH,etc.Conclusion:This study uses bioinformatics to screen out core genes that may be potential markers and therapeutic targets for SSc,which is expected to be a new target for the early diagnosis and mechanism research of SSc.Meanwhile,the mapped Chinese medicine and its effective components can provide ideas for the research and development of Chinese medicine compounds for the treatment of SSc.

This study characterized the whole-genome sequences of 45 Coxsackievirus A6(CVA6)strains isolated from Pudong District,Shanghai,during 2015-2023,to elucidate regional genetic evolution and recombination patterns.Viral genomes were ampli-fied and sequenced with Illumina MiSeq platforms,and phylogenetic analysis of the VP1 and 3D regions was conducted via MEGA 11(maximum-likelihood method,bootstrap=1 000).Nucleotide/amino acid homology and variation sites were assessed in DNAstar v7.0,and recombination events were identified with SimPlot v3.5.1 and RDP4.All isolates belonged to the D3a subtype,and exhibited intra-strain nucleotide and amino acid homologies of 88.0%-99.9%and 92.4%-100%,respectively,in contrast to lower homologies to the prototype Gdula strain(78.0%-80.5%nucleotide;94.5%-95.1%amino acid).Thirty-six mutation sites were identified in the VP1 re-gion.Recombination analysis revealed frequent cross-serotype events involving CVA4 and EV-A71,with dominant RF-A(84.5%)and minor RF-K(15.5%)patterns localized in the 3D region.This study elucidated the gene recombination and genetic evolution of CVA6 in Pudong District,Shanghai,thereby providing data support to enhance understanding of the evolutionary trends and genetic characteristics of coxsackieviruses,and offering theoretical evidence for the prevention and control of CVA6.

Objective:To investigate the current situation of water-borne endemic fluorosis in Anhui Province, and provide basic data for the adjusting the prevention and control measures.Methods:Using cross-sectional survey method, all villages in the water-borne endemic fluorosis areas were investigated in Anhui Province from 2019 to 2022. In water-borne endemic fluorosis village, the situation of water improvement project and the fluoride level of drinking water were investigated, and dental fluorosis of all children aged 8 - 12 was examined. The criteria for determining the achievement of control targets for water-borne endemic fluorosis in affected counties were based on the "Evaluation Measures for Control and Elimination of Key Endemic Diseases (2019 Edition)".Results:From 2019 to 2022, the rate of water improvement village in water-borne endemic fluorosis areas were 88.47% (1 527/1 726), 100% (1 726/1 726), 100% (1 726/1 726) and 100% (1 726/1 726), respectively. The qualified proportion of water fluoride in water-borne endemic fluorosis villages was 33.84% (584/1 726), 63.09% (1 089/1 726), 70.74% (1 221/1 726) and 74.33% (1 283/1 726), respectively. The prevalence rates of dental fluorosis in children aged 8 - 12 were 25.48% (45 461/178 440), 15.78% (27 959/177 200), 13.68% (23 505/171 880) and 12.66% (23 315/184 200), respectively. The proportion of affected counties that had achieved the control target of water-borne endemic fluorosis was 16% (4/25), 60% (15/25), 36% (9/25) and 40% (10/25), respectively.Conclusions:The water-borne endemic fluorosis areas in Anhui Province have improved the water fluoride qualification rate and reduced the incidence of fluorosis in children through prevention and control measures such as water improvement and fluoride reduction. However, the prevention and control efforts in key areas and counties need to be further improved.