Objective: To analyze the spatio-temporal distribution of pulmonary tuberculosis (PTB) among students in Suzhou City, Jiangsu Province from 2015 to 2023, so as to provide the evidence for the prevention and control of PTB in schools. Methods: Data of PTB cases among students in Suzhou City from 2015 to 2023 were collected from Chinese Disease Prevention and Control Information System and Suzhou Report of Investigation and Disposal of Tuberculosis in Schools. The seasonal incidence of PTB among students was analyzed using seasonal index (SI). The spatio-temporal clustering characteristics of PTB among students were analyzed using spatial autocorrelation and retrospective spatio-temporal permutation scanning. Results: Totally 1 374 PTB cases among students were reported in Suzhou City from 2015 to 2023. PTB cases were reported in each month, and the SIs were 100.69%, 124.38%, 108.98%, 135.04%, 106.61% and 106.61% in April, May, July, September, October and November, respectively, indicating the prevalence of PTB among students. Spatial autocorrelation analysis showed there was a positive spatial correlation of PTB among students in 2019 and 2020 (Moran's I=0.053 and 0.089, both P<0.05). From 2015 to 2023, there were high-high clustering sites mainly in Hengtang Street and Shishan Street. Retrospective spatio-temporal permutation scanning showed a primary cluster in Hengtang Street, with aggregation time in 2017, and 6 secondary clusters covering 25 towns (streets). Conclusion From 2015 to 2023, the PTB cases among students in Suzhou City were mainly concentrated in summer and autumn, and were predominantly clustered in Hengtang Street and Shishan Street.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective: To understand the association of physical exercise willingness and insomnia with depressive symptoms among college students, so as to provide reference for improving depressive symptoms of college students. Methods: From October 2022 to April 2023, cluster sampling was used to recruit 11 101 college students from four colleges in Anhui Province. The questionnaire survey was conducted to investigate the willingness to engage in physical exercise, insomnia and depressive symptoms of college students. The multivariate Logistic regression model was used to analyze the association of physical exercise willingness and insomnia with depressive symptoms of college students. Results: The prevalence of depressive symptoms among college students was 9.24%. Multivariate Logistic regression analysis showed that college students who were passive participants/non participants in physical activity, or who experienced insomnia, had a higher likelihood of depressive symptoms compared to those who were active participants or did not experience insomnia ( OR =1.84, 2.07, 4.02, all P <0.01). College students who were passive participants or non participants in physical activity and concurrently experienced insomnia had a higher risk of depressive symptoms compared with those who were active participants or did not experience insomnia ( OR =1.87-8.39, all P <0.01). Gender stratified analysis showed that the combined effect of passive physical exercise and insomnia increased the risk of depressive symptoms in both male ( OR = 1.81 -9.87) and female college students ( OR =1.67-7.39) (all P <0.05). Conclusions Both physical exercise willingness and insomnia are associated with depressive symptoms in college students. In order to improve the depressive symptoms of college students, it is necessary to improve the enthusiasm of physical exercise and strengthen the education of sleep health awareness.

Objective: To analyze the relationship between the risk of tuberculosis outbreaks in schools and the visit interval of index cases, so as to provide a scientific reference for predicting the risks of tuberculosis outbreak and making preventive measures. Methods: A total of 630 index cases from school tuberculosis outbreaks were studied during January, 2015 to December, 2022. Data on demographics, consultation history, etiological diagnosis, and methods of detection were collected. Restricted Cubic Splines (RCS), unconditional Logistic regression, and the receiver operating characteristic curve (ROC curve) were used for analysis. Results: The RCS fitted curve showed that the risk of a tuberculosis outbreak linearly increased when the consultation interval for etiologically negative patients exceeded 5.79 days, or for etiologically positive patients exceeded 8.37 days. After multi factor adjustment, for every additional day in the visit interval of the index case, the odds ratio ( OR ) value for a high risk outbreak was 1.10 (95% CI =1.07-1.13)( P <0.05). When analyzed by tertiles of visit intervals, compared to an interval of <14 days, the OR values (95% CI ) for high risk outbreaks in schools with intervals of 14-<28 days and ≥28 days were 10.32(3.04-35.10) and 82.58( 28.42 -239.95), respectively( P <0.01), indicating a trend of increasing outbreak risk with longer visit intervals. Based on the ROC curve analysis, the optimal threshold for predicting a high risk school tuberculosis outbreak was 23.5 days, with an area under the curve ( AUC ) of 0.93 (95% CI =0.89-0.98). Conclusion An extended visit interval of index cases is a good early warning indicator for high risk tuberculosis outbreaks in schools and could be considered a key factor in early intervention and risk control strategies.

Objective To preliminarily investigate the anti-tumor effects of phytosphingosine(PHS)and the involvement of inducing apoptosis of leukemia cells.Methods Cellular model of leukemia was established in leukemia cell lines K562 and SUP-B15.CCK-8 assay and EdU assay were used to measure the viability and DNA synthesis of K562 and SUP-B15 cells.RNA-seq was carried out to verify the differentially expressed genes(DEGs)after PHS treatment.Gene Ontology(GO)enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were applied to analyze the involved functions and signaling pathways.Comparative Toxicogenomics Database(CTD)and Discovery Studio software were employed to predict the underlying targets of PHS and molecular docking.Cell apoptosis was detected by flow cytometry,mitochondrial membrane potential was evaluated by JC-1 probe,and protein expression of key molecules was validated by Western blotting.Results PHS inhibited the proliferation of K562 and SUP-B15 cells in a time-and dose-dependent manner.The half-maximal inhibitory concentration(IC50)of K562 cells was 17.67 and 12.52 pmol/L for 24 and 48 h,respectively,and the IC50 value of SUP-B15 cells was 17.58 and 14.86 μmol/L for 24 and 48 h,respectively.PHS treatment at a dose of 20 μmol/L for 48 h resulted in significant inhibition of DNA synthesis.GO enrichment analysis of the K562 cells showed that PHS might be involved in positive regulation of apoptotic process,plasma membrane and its integral components,and protein kinase binding and activity.Reverse predictive analysis showed that BCL-2 protein was the most likely target of PHS.PHS significantly increased the apoptotic rate of leukemia cells(P＜0.05)in a dose-dependent manner,reduced the mitochondrial membrane potential,and down-regulated BCL-2 level(P＜0.05)and up-regulated the levels of Cleaved caspase-3 and Cleaved caspase-9(P＜0.05).Conclusion PHS may inhibit the proliferation of leukemia cells by inducing mitochondria-dependent apoptosis,possibly through PHS and BCL-2 interaction.

Objective To construct risk prediction models of death or readmission in patients with acute heart failure(AHF)during the vulnerable phase based on machine learning algorithms and screen the optimal model.Methods A total of 651 AHF patients with admitted to Department of Cardiology of the Second Affiliated Hospital of Army Medical University from October 2019 to July 2021 were included.The clinical data consisting of admission vital signs,comorbidities and laboratory results were collected from electronic medical records.The composite endpoint was defined as all-cause death or readmission for worsening heart failure within 3 months after discharge.The patients were divided into a training set(521 patients)and a test set(130 patients)in a ratio of 8:2 through the simple random sampling.Six machine learning models were developed,including logistic regression(LR),random forest(RF),decision tree(DT),light gradient boosting machine(LGBM),extreme gradient boosting(XGBoost)and neural networks(NN).Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the predictive performance and clinical benefit of the models.Shapley additive explanation(SHAP)was used to explain and evaluate the effect of different clinical characteristics on the models.Results A total of 651 AHF patients were included,of whom 203 patients(31.2%)died or were readmitted during the vulnerable phase.ROC curve analysis showed that the AUC values of the LR,RF,DT,LGBM,XGBoost and NN model were 0.707,0.756,0.616,0.677,0.768 and 0.681,respectively.The XGBoost model had the highest AUC value.DCA showed that the XGBoost model exhibited greater clinical net benefit compared with other models,with the best predictive performance.SHAP algorithm analysis showed that the clinical features that had the greatest impact on the output of the model were serum uric acid,D-dimer,mean arterial pressure,B-type natriuretic peptide,left atrial diameter,body mass index,and New York Heart Association(NYHA)classification.Conclusion The XGBoost model has the best predictive performance in predicting the risk of death or readmission of AHF patients during the vulnerable phase.

Pathology is the gold standard for diagnosis of neoplastic diseases.Whole slide imaging turns traditional slides into digital images,and artificial intelligence has shown great potential in pathological image analysis,especially deep learning models.The application of artificial intelligence in whole slide imaging of lung cancer involves many aspects such as histopathological classification,tumor microenvironment analysis,efficacy and survival prediction,etc.,which is expected to assist clinical decision-making of accurate treatment.Limitations in this field include the lack of precisely annotated data and slide quality varying among institutions.Here we summarized recent research in lung cancer pathology image analysis leveraging artificial intelligence and proposed several future directions.

Objective To construct plasmids and knock out HIF-1α gene expression in an naked mole rat skin fibroblasts(NSF)cell line using CRISPR/Cas9 genomic editing technology,to provide an in vitro cell model for studying the mechanism of hypoxia tolerance and the occurrence and development of hypoxia-related diseases in naked mole rats.Methods We designed four pairs of single guide RNA(sgRNA)sequences targeting exons 1～4 of the NSF HIF-1αgene and successfully constructed an expression plasmid.The plasmid with the optimal sgRNA was identified and transfected into 293T cells,and the supernatant was used for detecting the virus titer.Lentivirus particles carrying sgRNAs of HIF-1α were transfected into NSF cells which express Cas9 protein,based on a previous protocol.After transfection,fluorescence signals were observed under a fluorescence microscope,and HIF-1α expression in NSF cells was detected by Western Blot and T7 endonuclease 1(T7E1)analysis.Results Sanger sequencing showed that the designed sgRNA was successfully inserted into pX459 and pKLV2-U6-sgRNA2 vectors,demonstrating successful construction of a recombinant plasmid for transfection.T7E1 digestion successfully removed three bands and the target efficiency of sgRNA was 54％.Western Blot showed that the HIF-1α gene was successfully knocked out and its protein level was significantly reduced in NSF cells from naked mole rats(P=0.0019).There were no obvious morphological changes in HIF-1α-knockout cells under the microscope,and gene knockout had no obvious effect on cell proliferation.Conclusions We successfully constructed an HIF-1α-knockout cell line using CRISPR/Cas9 technology,to provide an experimental basis for further studies of the biological function of HIF-1α,as well as the mechanism of hypoxia tolerance in naked mole rats.The result also provide a theoretical foundation for the prevention and treatment of hypoxia-related diseases.

Objectives:To evaluate the efficacy and safety of the self-fixing and self-detachable drainage stent in pancreaticojejunostomy and to provide supportive data for the follow clinical trials.Methods:This is an experimental research in animals which completed from February 2022 to September 2022. A self-fixing and self-detachable pancreaticojejunostomy drainage stent was designed for Hong′s pancreaticojejunostomy technique based on the theory of “fistula healing” in pancreaticojejunostomy. Ten biocompatibility tests were completed invitro before this study. Twenty-five Bama minipigs were selected and double-ligated in the neck of the pancreas to dilate the distal main pancreatic duct. Twenty-three of them were successfully modelled and divided into three groups by a stratified random method: pancreaticojejunostomy drainage stent group (referred to as stent group) with 11 pigs, pancreatic duct to jejunal mucosa anastomosis group (referred to as manual suture group) with 8 pigs, sham operation group with 4 pigs. The anastomic time,amylase content in postoperative abdominal drainage fluid and the tolerable pressure value of pancreaticojejunostomy were compared between the stent group and the manual suture group. An abdominal X-ray fluoroscopy examination was adopted to detect the detach time of the stent. A postoperative pathological examination was performed to verify the healing time,the type of treatment and the stricture rate of pancreaticojejunostomy. Quantitative data was analyzed by independent sample t-test. The classified data were analyzed by Fisher′s exact test. Results:There were no significant differences in the diameter of the pancreatic duct and pancreatic texture,the time of pancreaticojejunostomy,the amylase content in postoperative peritoneal drainage fluid,and the tolerable pressure value of the pancreaticojejunostomy between the stent group and the manual suture group(all P>0.05). Abdominal X-ray fluoroscopy showed that the stents gradually detached and were removed from the body 21 days after operation,and all stents were detached in the follow 3 months after operation. Pancreaticojejunostomy healed 7 days after operation based on fistula formation in the stent group,and 14 days in the manual suture group. The incidence of anastomotic stricture within 35 days after operation was 2/8 in the stent group and 6/8 in the manual suture group (Fisher′s exact test: P=0.132). Conclusion:The stent method is safer and simpler than the manual suture method in pancreaticojejunostomy of Bama minipigs, with shorter anastomotic healing time and lower stricture rate.

Objectives:To evaluate the efficacy and safety of the self-fixing and self-detachable drainage stent in pancreaticojejunostomy and to provide supportive data for the follow clinical trials.Methods:This is an experimental research in animals which completed from February 2022 to September 2022. A self-fixing and self-detachable pancreaticojejunostomy drainage stent was designed for Hong′s pancreaticojejunostomy technique based on the theory of “fistula healing” in pancreaticojejunostomy. Ten biocompatibility tests were completed invitro before this study. Twenty-five Bama minipigs were selected and double-ligated in the neck of the pancreas to dilate the distal main pancreatic duct. Twenty-three of them were successfully modelled and divided into three groups by a stratified random method: pancreaticojejunostomy drainage stent group (referred to as stent group) with 11 pigs, pancreatic duct to jejunal mucosa anastomosis group (referred to as manual suture group) with 8 pigs, sham operation group with 4 pigs. The anastomic time,amylase content in postoperative abdominal drainage fluid and the tolerable pressure value of pancreaticojejunostomy were compared between the stent group and the manual suture group. An abdominal X-ray fluoroscopy examination was adopted to detect the detach time of the stent. A postoperative pathological examination was performed to verify the healing time,the type of treatment and the stricture rate of pancreaticojejunostomy. Quantitative data was analyzed by independent sample t-test. The classified data were analyzed by Fisher′s exact test. Results:There were no significant differences in the diameter of the pancreatic duct and pancreatic texture,the time of pancreaticojejunostomy,the amylase content in postoperative peritoneal drainage fluid,and the tolerable pressure value of the pancreaticojejunostomy between the stent group and the manual suture group(all P>0.05). Abdominal X-ray fluoroscopy showed that the stents gradually detached and were removed from the body 21 days after operation,and all stents were detached in the follow 3 months after operation. Pancreaticojejunostomy healed 7 days after operation based on fistula formation in the stent group,and 14 days in the manual suture group. The incidence of anastomotic stricture within 35 days after operation was 2/8 in the stent group and 6/8 in the manual suture group (Fisher′s exact test: P=0.132). Conclusion:The stent method is safer and simpler than the manual suture method in pancreaticojejunostomy of Bama minipigs, with shorter anastomotic healing time and lower stricture rate.