BACKGROUND:Currently,different methods of model establishment have been derived from different injury modes of spinal cord injury.Traditional physical injury modeling methods have their own advantages and disadvantages,and there is a lack of more effective and stable animal models of spinal cord injury. OBJECTIVE:To establish a reproducible,controllable,trauma-free,low-mortality,more stable,widely applicable,and short-term postoperative care rat model of spinal cord injury. METHODS:Forty Sprague-Dawley rats with similar body mass and ages were randomly divided into a control group and an improved group,with 20 rats in each group.Animal models of spinal cord injury in the control group were constructed using a clip model method,while the improved group used a modified ligation method based on the compression method to make the spinal cord injury models using suture ligation based on fenestration.Postoperative comparisons were made between the two groups,assessing urination behavior,hematuria,pyuria(infection rate),mortality,scoliosis rate and Basso-Beattie-Bresnahan locomotor rating scale scores at 1,3,5,and 7 days after modeling. RESULTS AND CONCLUSION:Compared with the conventional modeling method,the modified ligation method based on the compression method resulted in faster recovery of urination behavior,lower hematuria rate,lower infection rate,lower mortality rate,lower scoliosis rate,and more concentrated and stable Basso-Beattie-Bresnahan scores(all below 2 points within 1 week).This proves that the modified ligation method based on compression is more suitable for the establishment of spinal cord injury models in rats.

Objective To construct and validate a prediction model for urosepsis in patients after upper urinary tract stone surgery using various machine learning algorithms.Methods A total of 7 464 upper urinary tract stone patients who underwent surgery at the Sixth Affiliated Hospital of Guangxi Medical University from Jun.2018 to Jun.2023 were enrolled and randomly assigned to training(5 224 cases)or validation sets(2 240 cases)at a ratio of 7∶3.Among them,622(8.33%)cases developed urosepsis postoperatively.Six machine learning algorithms,including extreme gradient boosting(XGBoost),logistic regression,light gradient boosting machine(LightGBM),random forest(RF),adaptive boosting(AdaBoost),and gradient boosting decision tree(GBDT),were used to construct prediction models for postoperative urosepsis.The model's predictive ability and clinical benefits were evaluated using receiver operating characteristic(ROC)curves,Shapley additive explanation(SHAP)analysis,calibration curves,and decision curve analysis(DCA).Results The clinical features included body mass index(BMI),number of surgeries,heart rate,Barthel index,venous thrombo embolism(VTE)risk assessment,gender,American Society of Anesthesiologists(ASA)grade,urinary nitrite,and urinary leukocyte in the models.In the training set,the XGBoost,LightGBM,and RF models performed excellently,with area under curve(AUC)values of ROC curves reaching 1.00.In the validation set,the logistic regression model performed the best,with an AUC value of ROC curve of 0.76,showing good predictive stability and calibration.The AdaBoost and GBDT models followed with AUC values of 0.74 and 0.75,respectively,while the AUC values of the LightGBM,XGBoost,and RF models were 0.71,0.70,and 0.68.In terms of model interpretability,SHAP analysis showed the contribution of variables in a descending order as:heart rate,urinary leukocytes,gender,BMI,Barthel index,VTE risk assessment,urinary nitrite,number of surgeries,and ASA grade.Conclusion A logistic regression model for early risk prediction of postoperative urosepsis in upper urinary tract stone patients has been successfully constructed.This model has good predictive performance and calibration,and can effectively assist clinical diagnosis.

The application of transseptal puncture(TSP)technology in measuring left atrial pressure began in the late 1950s.With continuous development of cardiac interventional technology,TSP has become a routine procedure for mitral valve intervention,atrial fibrillation catheter ablation,and left atrial appendage closure(LAAC),and it also provides an unconventional pathway for transcatheter aortic valve replacement(TAVR),radiofrequency ablation of premature ventricular contraction,and ventricular septal defect occlusion.The popularity of transesophageal echocardiography(TEE)technology and the application of intracardiac echocardiography(ICE)have improved the accuracy of TSP location.Besides,the emergence of various novel transseptal puncture needles makes the operation of TSP easier and reduces the incidence of TSP complications.Combined with the related research on TSP technology at home and abroad,this paper aims to make a detailed review about the historic evolution and the latest research progress of TSP technology.

Objective: To investigate the prospective effects of intake of each food group on the development of lung function of pupils,so as to provide theoretical basis for promoting the healthy development of lung function and preventing chronic respiratory diseases in Chinese children. Methods: A cluster stratified sampling method was used to select a total of 893 pupils in grades 2-5 from Chengdu in November 2021. Dietary data of respondents were collected using a food frequency questionnaire within the past year,then the food group intake was categorized into T1, T2 and T3 from low to high by the trichotomous method, and anthropometric measurements including lung capacity were obtained in 2022. Logistic regression models and test for trend were used to analyze the prospective effects of intake of each food group on lung function development of pupils. Results: Among male students, consumption of vegetables [118.6(50.5, 188.2)g/d] and milk and dairy products [200.0(73.3, 250.0)g/d] were higher in the excellent lung capacity group than in the non excellent lung capacity group [90.0(37.1, 192.9), and 178.6(35.7, 250.0)g/d],with statistically significant differences ( Z =-1.98, -2.24); among girls, the group with excellent lung capacity consumed less staple food [391.1(273.6, 511.4)g/d] than the group with non excellent lung capacity [407.4(309.5, 594.3)g/d], and the group with excellent lung capacity consumed more aquatic products [31.2(14.6, 69.8)g/d] and milk and dairy products [215.0(107.1, 250.1) g/d ] than that of the non excellent lung capacity [19.4(10.7, 58.3), 114.3(35.7, 250.0)g/d] ( Z =-2.01, -3.33, -5.10)( P < 0.05 ). After adjusting for energy, body mass index Z score(BMI Z ), mother s education level, averge family income monthly, whether presence of smokers in the living environment, and whether participation in physical activities during the past week, among male students, T3 group of vegetable intake ( OR =0.48, 95% CI = 0.27-0.86), T2 group of bean and soy product intake ( OR = 0.52 , 95% CI =0.27-0.96)，T2 and T3 groups of milk and dairy products intake (T2： OR =0.54, 95% CI =0.31-0.93; T3： OR = 0.52 , 95% CI =0.30-0.90) were negatively associated with non excellent lung capacity ( P <0.05). Among girls, T3 group of aquatic product intake( OR =0.52, 95% CI =0.28-0.97), T2 and T3 groups of milk and dairy product (T2: OR =0.44, 95% CI =0.25- 0.76 ;T3: OR =0.33, 95% CI =0.19-0.59) were negatively associated with nonexcellent lung capacity, whereas the T2 group of red meat intake ( OR =2.51, 95% CI =1.37-4.67) was positively associated with non excellent lung capacity. Non excellent lung capacity was found to be negatively associated with vegetable and milk and dairy product intake in boys by test for trend; in girls, milk and dairy products intake was negatively associated with non excellent lung capacity, whereas red meat intake was positively associated with non excellent lung capacity ( t =-1.13，-0.44；-3.03，1.95, P trend <0.05). Conclusions Milk and dariy products intakes reduce the risk of non excellent lung capacity in pupils, vegetables intakes reduce the risk of non excellent lung capacity in boys, and the intake of red meat increases the risk of non excellent lung capacity in girls. Promoting rational food choices is necessary for children to improve healthy lung development.

Background and objective Transcription factor(TF)can bind specific sequences that either promotes or represses the transcription of target genes,and exerts important effects on tumorigenesis,migration,invasion.Staphylococcal nuclease-containing structural domain 1(SND1),which is a transcriptional co-activator,is considered as a promising target for tumor therapy.However,its role in lung adenocarcinoma(LUAD)remains unclear.This study aims to explore the role of SND1 in LUAD.Methods Data from The Cancer Genome Atlas(TCGA),Gene Expression Omnibus(GEO),Clinical Pro-teomic Tumor Analysis Consortium(CPTAC),and Human Protein Atlas(HPA)database was obtained to explore the associa-tion between SND1 and the prognosis,as well as the immune cell infiltration,and subcellular localization in LUAD tissues.Furthermore,the functional role of SND1 in LUAD was verified in vitro.EdU assay,CCK-8 assay,flow cytometry,scratch assay,Transwell assay and Western blot were performed.Results SND1 was found to be upregulated and high expression of SND1 is correlated with poor prognosis of LUAD patients.In addition,SND1 was predominantly present in the cytoplasm of LUAD cells.Enrichment analysis showed that SND1 was closely associated with the cell cycle,as well as DNA replication,and chro-mosome segregation.Immune infiltration analysis showed that SND1 was closely associated with various immune cell popula-tions,including T cells,B cells,cytotoxic cells and dendritic cells.In vitro studies demonstrated that silencing of SND1 inhib-ited cell proliferation,invasion and migration of LUAD cells.Besides,cell cycle was blocked at G,phase by down-regulating SND1.Conclusion SND1 might be an important prognostic biomarker of LUAD and may promote LUAD cells proliferation and migration.

Objectives:To assess the prognostic impact of the neoadjuvant rectal (NAR) score following neoadjuvant short-course radiotherapy and consolidation chemotherapy in locally advanced rectal cancer (LARC), as well as its value in guiding decisions for adjuvant chemotherapy.Methods:Between August 2015 and August 2018, patients were eligible from the STELLAR phase III trial (NCT02533271) who received short-course radiotherapy plus consolidation chemotherapy and for whom the NAR score could be calculated. Based on the NAR score, patients were categorized into low (＜8), intermediate (8-16), and high (＞16) groups. The Kaplan-Meier method, log rank tests, and multivariate Cox proportional hazard regression models were used to evaluate the impact of the NAR score on disease-free survival (DFS).Results:Out of the 232 patients, 24.1%, 48.7%, and 27.2% had low (56 cases), intermediate (113 cases), and high NAR scores (63 cases), respectively. The median follow-up period was 37 months, with 3-year DFS rates of 87.3%, 68.3%, and 53.4% ( P＜0.001) for the low, intermediate, and high NAR score groups. Multivariate analysis demonstrated that the NAR score (intermediate NAR score: HR, 3.10, 95% CI, 1.30-7.37, P=0.011; high NAR scores: HR=5.44, 95% CI, 2.26-13.09, P＜0.001), resection status ( HR, 3.00, 95% CI, 1.64-5.52, P＜0.001), and adjuvant chemotherapy ( HR, 3.25, 95% CI, 2.01-5.27, P＜0.001) were independent prognostic factors for DFS. In patients with R0 resection, the 3-year DFS rates were 97.8% and 78.0% for those with low and intermediate NAR scores who received adjuvant chemotherapy, significantly higher than the 43.2% and 50.6% for those who did not ( P＜0.001, P=0.002). There was no significant difference in the 3-year DFS rate (54.2% vs 53.3%, P=0.214) among high NAR score patients, regardless of adjuvant chemotherapy. Conclusions:The NAR score is a robust prognostic indicator in LARC following neoadjuvant short-course radiotherapy and consolidation chemotherapy, with potential implications for subsequent decisions regarding adjuvant chemotherapy. These findings warrant further validation in studies with larger sample sizes.

Background and objective Lung cancer is a leading cause of cancer-related deaths.Non-small cell lung cancer(NSCLC)is the most common pathological subtype,with adenocarcinoma being the predominant type.FAT atypical cadherin 1(FAT1)is a receptor-like protein with a high frequency of mutations in lung adenocarcinoma.The protein encoded by FAT1 plays a crucial role in processes such as cell adhesion,proliferation,and differentiation.This study aims to investigate the expression of FAT1 in lung adenocarcinoma and its relationship with immune infiltration.Methods Gene expression levels and relevant clinical information of 513 lung adenocarcinoma samples and 397 adjacent lung samples were obtained through The Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression(GTEx)data.The mRNA expression levels of the FAT1 gene in lung adenocarcinoma tissues were analyzed,along with its association with the prognosis of lung adenocarcinoma patients.Pathway enrichment analysis was conducted to explore the signaling pathways regulated by the FAT1 gene.Immu-noblotting was used to detect the differential expression of FAT1 in lung epithelial cells and various lung cancer cell lines,while immunohistochemistry was employed to assess FAT1 expression in lung cancer and adjacent tissues.Results FAT1 gene muta-tions were identified in 14%of lung adenocarcinoma patients.TCGA database data revealed significantly higher FAT1 mRNA expression in lung adenocarcinoma tissues compared to adjacent lung tissues.Kaplan-Meier analysis indicated lower survival rates in lung adenocarcinoma patients with higher FAT gene expression.Pathway enrichment analysis suggested the involve-ment of FAT1 in tumor development pathways,and its expression was closely associated with immune cell infiltration.Immu-nohistochemical validation demonstrated significantly higher expression of FAT1 in cancer tissues compared to adjacent lung tissues.Conclusion FAT1 mRNA is highly expressed in lung adenocarcinoma tissues,and elevated FAT1 mRNA expression is associated with poor prognosis in lung adenocarcinoma patients.FAT1 may serve as a potential biomarker for lung cancer.

Objective To establish a human tonsil organoid model and investigate the immunological effects of this tonsil organoid infected by influenza virus.Methods Human tonsil tissue removed by adenoid hypertrophy surgery were subjected to gradient centrifugation,and then the obtain cells were cultured in vitro with using a 2.5D-Transwell chamber in combination with IL-2 and B cell activating factor(Baff)to construct a human tonsil organoid.Single cell transcriptome sequencing(scRNA-seq)was used to analyze the distribution of influenza virus receptors in different cell subsets of the tonsil organoid.Immunofluorescence assay and flow cytometry were applied to detect the immunological effects of the tonsil organoid in 48 h after influenza virus infection.Results The tonsil organoids were established successfully using this 2.5D-Transwell culture technique.scRNA-seq analysis showed that the receptors for influenza virus were extensively distributed in nearly all of cell subsets of tonsil organoids.In 48 h after influenza virus infection,the tonsil organoids could generate a large amount of plasma cells and memory B cells to produce specific IgG antibodies.In addition,direct infection of the virus promoted the production of TNF-α and IL-2 from CD8+T cells and the secretion of TNF-α,IFN-γ and IL-2 by CD4+T cells.Conclusion The tonsil organoids can be established successfully and reach maturity at about the 6th day after culture.The receptors for influenza virus are widely distributed in human tonsil organoids.Influenza virus directly infects human T cells,leading to T cell activation and cytokine releasing.Moreover,influenza virus infection also promotes B cells differentiate into plasma cells and induce the secretion of IgG as well as the formation of memory B cells.

Objectives:To assess the prognostic impact of the neoadjuvant rectal (NAR) score following neoadjuvant short-course radiotherapy and consolidation chemotherapy in locally advanced rectal cancer (LARC), as well as its value in guiding decisions for adjuvant chemotherapy.Methods:Between August 2015 and August 2018, patients were eligible from the STELLAR phase III trial (NCT02533271) who received short-course radiotherapy plus consolidation chemotherapy and for whom the NAR score could be calculated. Based on the NAR score, patients were categorized into low (＜8), intermediate (8-16), and high (＞16) groups. The Kaplan-Meier method, log rank tests, and multivariate Cox proportional hazard regression models were used to evaluate the impact of the NAR score on disease-free survival (DFS).Results:Out of the 232 patients, 24.1%, 48.7%, and 27.2% had low (56 cases), intermediate (113 cases), and high NAR scores (63 cases), respectively. The median follow-up period was 37 months, with 3-year DFS rates of 87.3%, 68.3%, and 53.4% ( P＜0.001) for the low, intermediate, and high NAR score groups. Multivariate analysis demonstrated that the NAR score (intermediate NAR score: HR, 3.10, 95% CI, 1.30-7.37, P=0.011; high NAR scores: HR=5.44, 95% CI, 2.26-13.09, P＜0.001), resection status ( HR, 3.00, 95% CI, 1.64-5.52, P＜0.001), and adjuvant chemotherapy ( HR, 3.25, 95% CI, 2.01-5.27, P＜0.001) were independent prognostic factors for DFS. In patients with R0 resection, the 3-year DFS rates were 97.8% and 78.0% for those with low and intermediate NAR scores who received adjuvant chemotherapy, significantly higher than the 43.2% and 50.6% for those who did not ( P＜0.001, P=0.002). There was no significant difference in the 3-year DFS rate (54.2% vs 53.3%, P=0.214) among high NAR score patients, regardless of adjuvant chemotherapy. Conclusions:The NAR score is a robust prognostic indicator in LARC following neoadjuvant short-course radiotherapy and consolidation chemotherapy, with potential implications for subsequent decisions regarding adjuvant chemotherapy. These findings warrant further validation in studies with larger sample sizes.

This study was designed to explore the transcription level,genome alteration,potential abnormal expression mechanism,prognostic value and the association with immune cells of the tetraspan MS4A6A(membrane-spanning 4A(MS4A)subfamily protein 6A)in pan-cancer.Public databases,such as UCSC Xena,cBioPortal and Timer2,were used to collect relative data,and thenbioinformatic approaches were used to analyze the correlation of MS4A6A genome and MS4A6A expression with immune infiltration,tumor mutation burden(TMB),microsatellite instability(MSI)etc.TMB and MSI were further calculated by R package maftools.Immune score,stromal score and ESTIMATE score were calculated by R package ESTIMATE.The correlation between immune score and MS4A6A expression was conducted based on Spearman correlation coefficient.Data showed that DNA methylation of MS4A6A in most cancer tissues was negatively correlated with its expression level,suggesting the possible relation of differential MS4A6A expression to the methylation level of its promoter region.Univariate Cox analysis revealed that high expression of MS4A6A was the risk factor for LGG,TGCT,UVM and THYM;MS4A6A expression was positively correlated with the immune score in 32 types of cancer;MS4A6A expression was positively correlated with the infiltration levels of various immune cells,such as tumor associated fibroblasts(CAF),regulatory T cells(Treg),B cells,neutrophils,macrophages,monocytes,and CD8+T cells.In conclusion,MS4A6A may participate in the development of cancer,suggesting it is a potential new biomarker for cancer treatment and prevention.