Purpose To construct and validate a risk prediction model for in-stent restenosis(ISR)nomogram in patients with superficial femoral artery stent implantation.Materials and Methods 150 cases of superficial femoral artery stent implantation patients who were hospitalized in Department of Cardiovascular Surgery of the Second Affiliated Hospital of Army Medical University from February 2016 to November 2022 were retrospectively analyzed.Risk factors for ISR in patients with superficial femoral artery stent implantation were screened using univariate analysis,least absolute shrinkage and selection operator and multifactorial Logistic regression analysis.Nomograms were produced,Bootstrap method was used for internal validation,consistency index was used for model differentiation assessment,and calibration graphs were used for calibration assessment.Results Fifty-five patients(36.7%)with ISR one year after superficial femoral artery stenting were identified.Univariate analysis,least absolute shrinkage and selection operator and Logistic regression showed a history of stroke(OR=9.152,95%CI 2.957-28.322),chronic kidney disease(OR=14.639,95%CI 2.378-90.115),fibrinogen concentration(OR=8.422,95%CI 3.139-22.594),pre-procedural occlusion(OR=3.604,95%CI 1.446-8.981)and calcified plaque(OR=5.167,95%CI 2.044-13.059)were the best predictors of the occurrence of ISR one year post-procedure in patients with stenting of superficial femoral artery.The consistency index of the prediction model was 0.876(95%CI 0.812-0.939),with specificity and sensitivity of 93.6%and 70.9%,respectively;a Brie score of 0.124,and a consistency index after internal validation of the model of 0.859,respectively.Calibration plots showed that the ideal probability curves and the actual probability curves overlapped with each other well.Conclusion The Nomogram risk prediction model of superficial femoral artery stent restenosis constructed in this study has good differentiation and calibration,and is of good value for clinical prediction of ISR in patients with superficial femoral artery stent implantation.

Objective:To investigate the life expectancy of antiretroviral treatment (ART) HIV-infected patients and its trends in Taizhou City, Zhejiang Province from 2014 to 2023.Methods:The data were obtained from the China Information System for Disease Control and Prevention , and the study subjects were HIV-infected patients received ART in Taizhou City. An abbreviated life expectancy table was prepared based on Chiang's method to analyze the differences in life expectancy of HIV-infected patients receiving ART in Taizhou City with different characteristics in 2023 and to compare the trends in life expectancy of patients with different CD4 +T lymphocytes (CD4) counts at the time of initiation of ART from 2014 to 2023. Results:A total of 4 825 patients were enrolled in this study, with a cumulative follow-up of 276 648.56 person-years, and a case-fatality rate of 18.07 (95% CI: 16.48-19.65) /1 000 person-years. In 2023, male patients had lower life expectancy than females in all age groups, and those who were married had higher life expectancy than those who were unmarried and those who were divorced or widowed; patients who had been transmitted heterosexually had lower life expectancy than those who had been transmitted through homosexual transmission. Patients with different CD4 counts at the time of initiating ART had different life expectancies in all age groups. The life expectancy of patients with CD4 counts ≥350 cells/μl when initiating the treatment was higher than that of patients with CD4 counts <200 cells/μl in all age groups. The life expectancy of HIV-infected patients on ART at age 20 and 50 increased from 39.0 years and 19.1 years in 2014 to 46.0 years and 24.1 years in 2023, respectively, with an average annual percentage change of 2.43% (95% CI: 0.81%-4.07%) and 3.34% (95% CI: 1.17%-5.56%). The change in life expectancy was similar for patients with CD4 counts ≥350 cells/μl and 200-349 cells/μl at the time of initiating treatment in 2016-2023, and was higher than that for patients with CD4 counts <200 cells/μl. The rate of increase in life expectancy for patients at age 50 was higher than that at age 20 for all CD4 counts. Conclusions:The rising trend of life expectancy among HIV-infected patients on ART in Taizhou City is obvious. But the disparity between patients with different characteristics is obvious, especially among patients with baseline CD4 counts <200 cells/μl, suggesting the importance of expanded testing, early diagnosis and timely initiation of ART to improve the life expectancy of HIV-infected patients.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

Objective:To investigate the life expectancy of antiretroviral treatment (ART) HIV-infected patients and its trends in Taizhou City, Zhejiang Province from 2014 to 2023.Methods:The data were obtained from the China Information System for Disease Control and Prevention , and the study subjects were HIV-infected patients received ART in Taizhou City. An abbreviated life expectancy table was prepared based on Chiang's method to analyze the differences in life expectancy of HIV-infected patients receiving ART in Taizhou City with different characteristics in 2023 and to compare the trends in life expectancy of patients with different CD4 +T lymphocytes (CD4) counts at the time of initiation of ART from 2014 to 2023. Results:A total of 4 825 patients were enrolled in this study, with a cumulative follow-up of 276 648.56 person-years, and a case-fatality rate of 18.07 (95% CI: 16.48-19.65) /1 000 person-years. In 2023, male patients had lower life expectancy than females in all age groups, and those who were married had higher life expectancy than those who were unmarried and those who were divorced or widowed; patients who had been transmitted heterosexually had lower life expectancy than those who had been transmitted through homosexual transmission. Patients with different CD4 counts at the time of initiating ART had different life expectancies in all age groups. The life expectancy of patients with CD4 counts ≥350 cells/μl when initiating the treatment was higher than that of patients with CD4 counts <200 cells/μl in all age groups. The life expectancy of HIV-infected patients on ART at age 20 and 50 increased from 39.0 years and 19.1 years in 2014 to 46.0 years and 24.1 years in 2023, respectively, with an average annual percentage change of 2.43% (95% CI: 0.81%-4.07%) and 3.34% (95% CI: 1.17%-5.56%). The change in life expectancy was similar for patients with CD4 counts ≥350 cells/μl and 200-349 cells/μl at the time of initiating treatment in 2016-2023, and was higher than that for patients with CD4 counts <200 cells/μl. The rate of increase in life expectancy for patients at age 50 was higher than that at age 20 for all CD4 counts. Conclusions:The rising trend of life expectancy among HIV-infected patients on ART in Taizhou City is obvious. But the disparity between patients with different characteristics is obvious, especially among patients with baseline CD4 counts <200 cells/μl, suggesting the importance of expanded testing, early diagnosis and timely initiation of ART to improve the life expectancy of HIV-infected patients.

Objective: To investigate whether fibroblast growth factor 18(FGF18) can induce human gingival fibroblasts(HGFs) isolatedin vitroto differentiate into osteoblast-like cells, and to explore the mechanism of osteogenesis. Methods : HGFs were isolated, cultured and identified by tissue block method. The third generation of HGFs were divided into experimental group and control group. FGF18 and L-DMEM was added to the experimental group while L-DMEM was added to the control group.The effects of different concentrations of FGF18(0, 0.01, 0.02, 0.04, 0.06 mg/L) on proliferation of HGFs were detected by Methylthiazolyldiphenyl-tetrazolium bromide(MTT) assay. Alkaline phosphatase(ALP) and alizarin red staining were used to detect the osteogenesis and mineralization ability of the cells after induction. RT-PCR, immunocytochemistry staining, and Western blot were used to detect the expression of genes and proteins related to osteogenesis and BMP2 in the BMP signaling pathway. Results: Compared with the control group, the experimental group could promote the proliferation of HGFs at 3, 5, 7, 9, and 11days(P<0.05),ALP activity and mineral salt deposition increased after induction at 14 and 21 days(P<0.05), and the expressions of ALP, OPN, OCN mRNA and BMP2 mRNA in BMP signaling pathway significantly increased(P<0.01). The expressions of OPN, OCN and BMP2 protein at 21 days were significantly higher than those at 14 days(P<0.01). Conclusion FGF18 can promote the proliferation of HGFs, and induce the differentiation of HGFs into functional osteoblasts. The osteogenic mechanism is related to the upregulation of BMP2.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

Purpose To construct and validate a risk prediction model for in-stent restenosis(ISR)nomogram in patients with superficial femoral artery stent implantation.Materials and Methods 150 cases of superficial femoral artery stent implantation patients who were hospitalized in Department of Cardiovascular Surgery of the Second Affiliated Hospital of Army Medical University from February 2016 to November 2022 were retrospectively analyzed.Risk factors for ISR in patients with superficial femoral artery stent implantation were screened using univariate analysis,least absolute shrinkage and selection operator and multifactorial Logistic regression analysis.Nomograms were produced,Bootstrap method was used for internal validation,consistency index was used for model differentiation assessment,and calibration graphs were used for calibration assessment.Results Fifty-five patients(36.7%)with ISR one year after superficial femoral artery stenting were identified.Univariate analysis,least absolute shrinkage and selection operator and Logistic regression showed a history of stroke(OR=9.152,95%CI 2.957-28.322),chronic kidney disease(OR=14.639,95%CI 2.378-90.115),fibrinogen concentration(OR=8.422,95%CI 3.139-22.594),pre-procedural occlusion(OR=3.604,95%CI 1.446-8.981)and calcified plaque(OR=5.167,95%CI 2.044-13.059)were the best predictors of the occurrence of ISR one year post-procedure in patients with stenting of superficial femoral artery.The consistency index of the prediction model was 0.876(95%CI 0.812-0.939),with specificity and sensitivity of 93.6%and 70.9%,respectively;a Brie score of 0.124,and a consistency index after internal validation of the model of 0.859,respectively.Calibration plots showed that the ideal probability curves and the actual probability curves overlapped with each other well.Conclusion The Nomogram risk prediction model of superficial femoral artery stent restenosis constructed in this study has good differentiation and calibration,and is of good value for clinical prediction of ISR in patients with superficial femoral artery stent implantation.

Purpose To investigate the expression of FUT8-AS1 gene in epithelial ovarian cancer(EOC)tissues and cell lines and its relationship with clinical pathology and progno-sis,to investigate the effect of FUT8-AS on proliferation,inva-sion and EMT of epithelial ovarian cancer cell line and its possi-ble mechanism.Methods Based on GEPIA2 and Kaplan-Meier Plotter database,the expression of FUT8-AS1 in epithelial ovarian cancer and its effect on survival of patients with ovarian cancer were analyzed,the expression levels of FUT8-AS1 miR-142-5p,BCL2,and EMT marker genes were detected by qRT-PCR,CCK-8 and Transwell assays were used to detect the effect of abnormal expression of FUT8-AS1 gene on proliferation and invasion of CAOV3 cells.The interaction between FUT8-AS1 and miR-142-5p was verified by Dual-luciferase reporter assay sys-tem.Results Using GEPIA2 and Kaplan-Meier Plotter data-bases,it was found that the expression of FUT8-AS1 in epitheli-al ovarian cancer tumor tissue was significantly higher than that in normal tissue(P＜0.05),and the overall survival rate of the high expression group of FUT8-AS1 was significantly lower than that of the low expression group of FUT8-AS1(P＜0.01).The expression of FUT8-AS1 gene in 74 cases of epithelial ovarian cancer tissue was significantly higher than that of normal tissue[(2.547±1.370)vs(1.330±0.831),P＜0.01],and was associated with greater omentum metastasis,lymph node metas-tasis,FIGO staging,and survival(P＜0.01).Knocking down the FUT8-AS1 gene can inhibit the in vitro proliferation and in-vasion ability of epithelial ovarian cancer cell line CAOV3(P＜0.01 or P＜0.05).The results of dual luciferase reporter gene detection showed that co transfection with miR-142-5p mimics and FUT8-AS1-WT plasmids significantly reduced the luciferase activity of CAOV3 cells(P＜0.05).Transfection with miR-142-5p mimics could offset the downregulation of BCL2 gene ex-pression caused by knocking down FUT8-AS1 in CAOV3 cells(P＜0.05).Conclusion The FUT8-AS1 gene is highly ex-pressed in EOC and leads to poor prognosis.Knocking down the FUT8-AS1 gene can inhibit the in vitro proliferation,invasion,and EMT of CAOV3 cells.Mechanistically,the FUT8-AS1 gene may promote the progression of EOC by targeting the miR-142-5p/BCL2 molecular axis.

Bowel sounds can reflect the movement and health status of the gastrointestinal tract.However,the traditional manual auscultation method has subjective deviation and is time-consuming and labor-intensive.In order to better assist doctors in diagnosing bowel sounds and improve the reliability and efficiency of bowel sound detection,this study proposed a deep neural network model that combines a residual neural network(ResNet),a bidirectional long short-term memory network(BiLSTM),and an attention mechanism.Firstly,a large number of labeled clinical data was collected using the self-developed multi-channel bowel sound acquisition system,and the multi-scale wavelet decomposition and reconstruction method was used to preprocess the bowel sounds.Then,log Mel spectrogram features were extracted and sent to the network for training.Finally,the performance and effectiveness of the model were evaluated and verified by 10-fold cross-validation and an ablation experiment.The experimental results showed that the precision,recall,and F1 score of the model reached 83%,76%,and 79%,respectively,and it could effectively detect bowel sound segments and locate their start and end times,performing better than previous algorithms.This algorithm can not only provide auxiliary information for doctors in clinical practice but also offer technical support for further analysis and research of bowel sounds.

Objective:To investigate effect of Gehua Jiecheng Decoction on IL-6/JAK2/STAT3 signaling pathway in colon tissue of ulcerative colitis with"inflammatory to cancer transformation"(UC-UCAC)mice of spleen deficiency and damp-heat type.Methods:Ten from 80 SPF C57BL/6 male mice were randomly selected as blank group and other 70 mice were selected as model group.After establishment of spleen deficient damp-heat model,mice were randomly divided into model group(1st,2nd and 3rd cycle),Gehua Jiecheng Decoction high,medium and low doses groups and mesalazine group,with 10 pieces per group.UC-UCAC transformation model was further established with azo methane oxide solution(AOM)/sodium glucan sulfate(DSS).Each group was treated with corresponding drugs for 4 weeks.General state of mice was observed.Score of disease activity index(DAI)was calculated.HE staining was used to observe colonic mucosa pathology of mice.EGFR,IL-6,JAK2,STAT3 and p-STAT3 proteins and genes expressions in mice colon tissues were detected by Western blot,IHC and RT-qPCR,respectively.Results:Compared with blank group,mice in model group(3rd cycle)were generally in a worse state,colon mucosal tissue was cancerous,DAI score,target proteins and genes expressions were significantly increased(P<0.01).Compared with model group(3rd cycle),general state of mice in all treatment groups were restored and colonic tissues pathology were improved to some extent.Target proteins and genes expressions in other treatment groups were significantly decreased except for Gehua Jiecheng Decoction low-dose group(P<0.01).Conclusion:Gehua Jiecheng Decoction may destroy tumor inflammatory microenvironment,repair damaged colonic mucosa tissue,delay inflamma-tion-cancer transformation process and prevent UCAC by inhibiting activation of IL-6/JAK2/STAT3 signaling pathway.