Objective:To construct and validate a predictive model for postoperative pulmonary complications (PPCs) in patients undergoing robot-assisted laparoscopic urological surgery.Methods:This retrospective study included the medical records of 932 patients who underwent robot-assisted laparoscopic urological surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from January 2020 to February 2022. The patients were divided into a training group ( n=559) and a validation group ( n=373) at a 6∶4 ratio. Logistic regression analysis was used to determine the independent risk factors for PPCs, and a nomogram prediction model was constructed based on these factors. The performance of the model was evaluated using the receiver operating characteristic curve and calibration curve, and the clinical benefit was assessed using the clinical decision curve analysis. Results:The independent risk factors for PPCs included advanced age (>60 yr), smoking history, respiratory tract infection within 1 month, preoperative low SpO 2 (<96%), and prolonged length of postoperative hospital stay ( P<0.05), and the body mass index (18.5-<28.0 kg/m 2) was a protective factor. The nomogram prediction model developed based on the aforementioned 6 influencing factors had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.76-0.86) in training group and 0.80 (95% confidence interval 0.75-0.86) in validation group. The calibration curve indicated a good consistency between the predicted and actual occurrence curves, and the clinical decision curve analysis showed good accuracy and net benefit of the prediction model. Conclusions:The predictive model for PPCs is successfully constructed based on age, low body mass index, smoking history, history of respiratory tract infection within 1 month, preoperative low SpO 2 and prolonged length of postoperative hospital stay and has good predictive performance in patients undergoing robot-assisted laparoscopic urological surgery.

Objective:To construct and validate a predictive model for postoperative pulmonary complications (PPCs) in patients undergoing robot-assisted laparoscopic urological surgery.Methods:This retrospective study included the medical records of 932 patients who underwent robot-assisted laparoscopic urological surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from January 2020 to February 2022. The patients were divided into a training group ( n=559) and a validation group ( n=373) at a 6∶4 ratio. Logistic regression analysis was used to determine the independent risk factors for PPCs, and a nomogram prediction model was constructed based on these factors. The performance of the model was evaluated using the receiver operating characteristic curve and calibration curve, and the clinical benefit was assessed using the clinical decision curve analysis. Results:The independent risk factors for PPCs included advanced age (>60 yr), smoking history, respiratory tract infection within 1 month, preoperative low SpO 2 (<96%), and prolonged length of postoperative hospital stay ( P<0.05), and the body mass index (18.5-<28.0 kg/m 2) was a protective factor. The nomogram prediction model developed based on the aforementioned 6 influencing factors had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.76-0.86) in training group and 0.80 (95% confidence interval 0.75-0.86) in validation group. The calibration curve indicated a good consistency between the predicted and actual occurrence curves, and the clinical decision curve analysis showed good accuracy and net benefit of the prediction model. Conclusions:The predictive model for PPCs is successfully constructed based on age, low body mass index, smoking history, history of respiratory tract infection within 1 month, preoperative low SpO 2 and prolonged length of postoperative hospital stay and has good predictive performance in patients undergoing robot-assisted laparoscopic urological surgery.

Objective To explore the risk factors analysis and prediction model establishment of restenosis dysfunction at 1 year after percutaneous transluminal angioplasty(PTA)of internal arteriovenous fistula based on machine learning.Methods A total of 322 patients who underwent PTA of internal arteriovenous fistula in Wenzhou Central Hospital from June 1,2018 to December 31,2023 were enrolled.The operation-related data were collected.Variables were used to construct prediction models using five machine learning algorithms:Random forest(RF),extreme gradient boosting(XGBoost),support vector machine(SVM),gradient boosting decision tree(GBDT)and Logistic regression(LR).The predictive efficacy was evaluated by area under receiver operating characteristic curve.Results There were 97 cases of restenosis dysfunction and 225 cases of non-dysfunction.The incidence of internal fistula restenosis dysfuction was 30.1％1 year after PTA.The age,diabetes,smoking,calcium-phosphorus product,dilatation pressure ≥20mmHg,and balloon diameter ≥6mnm in dysfunction group were higher than those in non-dysfunction group.The difference was statistically significant(P＜0.05).The area under the curve of RF,XGBoost,SVM,GBDT and LR models based on machine learning was 0.908(95％CI:0.836-0.980),0.809(95％CI:0.696-0.922),0.745(95％CI:0.624-0.867),0.711(95％CI:0.576-0.847)and 0.651(95％CI:0.508-0.795),respectively.The sensitivity was 79.1％,70.8％,83.3％,62.5％and 72.3％,respectively.The specificity was 89.0％,81.2％,57.8％,78.9％and 71.0％,respectively.Conclusion Age,diabetes mellitus,smoking,calcium-phosphorus product,expansion pressure ≥20mnmHg,balloon diameter ≥ 6mm are independent risk factors for restenosis failure after PTA in patients with internal arteriovenous fistula,which can be used as an index to predict restenosis failure 1 year after PTA in internal arteriovenous fistula.The random forest prediction model based on machine learning algorithm has good prediction performance and can better predict restenosis failure 1 year after PTA in internal arteriovenous fistula.

Objective To explore the risk factors analysis and prediction model establishment of restenosis dysfunction at 1 year after percutaneous transluminal angioplasty(PTA)of internal arteriovenous fistula based on machine learning.Methods A total of 322 patients who underwent PTA of internal arteriovenous fistula in Wenzhou Central Hospital from June 1,2018 to December 31,2023 were enrolled.The operation-related data were collected.Variables were used to construct prediction models using five machine learning algorithms:Random forest(RF),extreme gradient boosting(XGBoost),support vector machine(SVM),gradient boosting decision tree(GBDT)and Logistic regression(LR).The predictive efficacy was evaluated by area under receiver operating characteristic curve.Results There were 97 cases of restenosis dysfunction and 225 cases of non-dysfunction.The incidence of internal fistula restenosis dysfuction was 30.1％1 year after PTA.The age,diabetes,smoking,calcium-phosphorus product,dilatation pressure ≥20mmHg,and balloon diameter ≥6mnm in dysfunction group were higher than those in non-dysfunction group.The difference was statistically significant(P＜0.05).The area under the curve of RF,XGBoost,SVM,GBDT and LR models based on machine learning was 0.908(95％CI:0.836-0.980),0.809(95％CI:0.696-0.922),0.745(95％CI:0.624-0.867),0.711(95％CI:0.576-0.847)and 0.651(95％CI:0.508-0.795),respectively.The sensitivity was 79.1％,70.8％,83.3％,62.5％and 72.3％,respectively.The specificity was 89.0％,81.2％,57.8％,78.9％and 71.0％,respectively.Conclusion Age,diabetes mellitus,smoking,calcium-phosphorus product,expansion pressure ≥20mnmHg,balloon diameter ≥ 6mm are independent risk factors for restenosis failure after PTA in patients with internal arteriovenous fistula,which can be used as an index to predict restenosis failure 1 year after PTA in internal arteriovenous fistula.The random forest prediction model based on machine learning algorithm has good prediction performance and can better predict restenosis failure 1 year after PTA in internal arteriovenous fistula.

Objective:To investigate the effect of tofacitinib,a pan-Janus kinase(JAK)inhibitor,on transforming growth factor-beta 1(TGF-β1)-induced fibroblast to myofibroblast transition(FMT)and to explore its mechanism.To provide a theoretical basis for the clinical treatment of connective tissue disease-related interstitial lung disease(CTD-ILD).Methods:(1)Human fetal lung fibroblast 1(HFL-1)were cultured in vitro,and 6 groups were established:DMSO blank control group,TGF-β1 in-duction group,and TGF-β1 with different concentrations of tofacitinib(0.5,1.0,2.0,5.0 μmol/L)drug intervention experimental groups.CCK-8 was used to measure the cell viability,and wound-healing assay was performed to measure cell migration ability.After 48 h of combined treatment,quantitative real-time PCR(RT-PCR)and Western blotting were used to detect the gene and protein expression levels of α-smooth muscle actin(α-SMA),fibronectin(FN),and collagen type Ⅰ(COL1).(2)RT-PCR and enzyme-linked immunosorbnent assay(ELISA)were used to detect the interleukin-6(IL-6)gene and protein expression changes,respectively.(3)DMSO carrier controls,1.0 μmol/L and 5.0 μmol/L tofacitinib were added to the cell culture media of different groups for pre-incubation for 30 min,and then TGF-β1 was added to treat for 1 h,6 h and 24 h.The phosphorylation levels of Smad2/3 and signal transducer and activator of transcription 3(STAT3)protein were detected by Western blotting.Results:(1)Tofacitinib inhibited the viability and migration ability of HFL-1 cells after TGF-β1 induction.(2)The expression of α-SMA,COL1A1 and FN1 genes of HFL-1 in the TGF-β1-induced groups was signifi-cantly up-regulated compared with the blank control group(P＜0.05).Compared with the TGF-β1 in-duction group,α-SMA expression in the 5.0 μmol/L tofacitinib intervention group was significantly inhi-bited(P＜0.05).Compared with the TGF-β1-induced group,FN1 gene was significantly inhibited in each intervention group at a concentration of 0.5-5.0 μmol/L(P＜0.05).Compared with the TGF-β1-induced group,the COL1A1 gene expression in each intervention group did not change significantly.(3)Western blotting results showed that the protein levels of α-SMA and FN1 in the TGF-β1-induced group were significantly higher than those in the control group(P＜0.05),and there was no significant difference in the expression of COL1A1.Compared with the TGF-β1-induced group,the α-SMA protein level in the intervention groups with different concentrations decreased.And the differences between the TGF-β1-induced group and 2.0 μmol/L or 5.0 μmol/L intervention groups were statistically significant(P＜0.05).Compared with the TGF-β1-induced group,the FN1 protein levels in the intervention groups with different concentrations showed a downward trend,but the difference was not statistically sig-nificant.There was no difference in COL1A1 protein expression between the intervention groups com-pared with the TGF-β1-induced group.(4)After TGF-β1 acted on HFL-1 cells for 48 h,the gene ex-pression of the IL-6 was up-regulated and IL-6 in culture supernatant was increased,the intervention with tofacitinib partly inhibited the TGF-β1-induced IL-6 gene expression and IL-6 in culture supernatant.TGF-β1 induced the increase of Smad2/3 protein phosphorylation in HFL-1 cells for 1 h and 6 h,STAT3 protein phosphorylation increased at 1 h,6 h and 24 h,the pre-intervention with tofacitinib inhibited the TGF-β1-induced Smad2/3 phosphorylation at 6 h and inhibited TGF-β1-induced STAT3 phosphorylation at 1 h,6 h and 24 h.Conclusion:Tofacitinib can inhibit the transformation of HFL-1 cells into myofi-broblasts induced by TGF-β1,and the mechanism may be through inhibiting the classic Smad2/3 path-way as well as the phosphorylation of STAT3 induced by TGF-β1,thereby protecting the disease progres-sion of pulmonary fibrosis.

Objective To investigate the longitudinal changes in left ventricular(LV)structure and function after bariatric surgery in obese individuals and their relationship with preoperative left ventricular ejection fraction(LVEF)by cardiac magnetic resonance(CMR)imaging.Methods We prospectively enrolled 75 obese subjects scheduled for laparoscopic sleeve gastrectomy and 46 age and sex-matched healthy controls(the control group).All subjects underwent CMR examination to obtain LV structural parameters,LVEF,and strain parameters.According to their preoperative LVEF,the obese subjects were divided into two obesity groups,including the group of patients with LVEF≥60％(n=43)and the group of patients with 50％≤LVEF＜60％(n=32).LV structural and functional differences between the control group and the two obesity groups were compared.Eventually,38 obese subjects completed the CMR follow-up at 1 month and 12 months after bariatric surgery.The longitudinal changes in LV structure and function after surgery in the LVEF ≥ 60％(n=20)group and the 50％≤LVEF＜60％group(n=18)were compared.Results Before bariatric surgery,the global longitudinal strain was significantly lower in the LVEF ≥ 60％group than that in the control group([-18.36±1.86]％vs.[-19.50±1.53]％,P＜0.05).The global radial([27.70±3.52]％vs.[34.44±4.11]％,P＜0.05),circumferential([-17.35±1.46]％vs.[-19.85±1.42]％,P＜0.05),and longitudinal([-16.22±1.81]％vs.[-19.50±1.53]％,P＜0.05)strain in the 50％≤ LVEF＜60％group was significantly lower than that in the control group.At 12 months after bariatric surgery,the global radial([32.52±7.84]％vs.[30.92±4.27]％,P＞0.05),circumferential([-19.02±2.42]％vs.[-18.63±1.49]％,P＞0.05),and longitudinal([-18.18±2.06]％vs.[-17.78±1.66]％,P＞0.05)strain in the LVEF≥60％group showed no significant difference compared with the baseline findings.In the 50％≤ LVEF＜60％group,the global radial([32.73±5.86]％vs.[26.83±4.85]％,P＜0.05)and circumferential([-19.10±2.00]％vs.[-16.91±2.09]％,P＜0.05)strain was significantly higher than that before surgery.Conclusion LV remodeling is reversed after bariatric surgery in obese subjects,and the longitudinal changes in LV structure and function vary with the preoperative LVEF.

Objective:To analyze the clinical characteristics of elderly-onset gouty arthritis and risk factors of tophi.Methods:A total of 1 239 gout patients were retrospective selected in the outpatient department of the Gout Clinical Medical Center of the Affiliated Hospital of Qingdao University from 2016 to 2022. According to age of onset, they were divided into the young and middle-aged group(aged<60) consisted of 826 cases, and the elderly group(aged≥60) consisted of 413 cases. Compare the clinical characteristics of elderly with Young and Middle-aged patients.Results:The systolic blood pressure, fasting blood glucose, creatinine, regular exercise, comorbidities, and tophi in the elderly group was higher than that in the middle-aged and young group. The proportion of diastolic blood pressure, serum triglycerides, eGFR, serum uric acid, alcohol consumption rate, and family history of gout was lower than that of young and middle-aged group( P<0.05); In the elderly-onset group, the initial site of arthritis was commonly observed in the first metatarsophalangeal joint. The proportion of the first attack with the upper limb joint was higher in old age group than in young and middle age group( P<0.05). Renal underexcretion type was the main subtype in the elderly group, and the proportion of overproduction type was higher than that of the young and middle-aged group( P<0.05). The logistic regression analysis showed that age, urea nitrogen, disease duration≥10 years and family history of gout were risk factors for tophi in elderly patients( P<0.05). Conclusion:The elderly-onset gout has unique clinical characteristics, characterized by a higher prevalence of tophi, a higher rate of complications. An initial site of arthritis commonly observed in the first metatarsophalangeal joint and the predominant type of uric acid excretion is renal excretion impairment. Early diagnosis and treatment, control of blood uric acid levels, smoking cessation and alcohol, regular exercise should be applied to prevent or delay the formation of tophi.

This study was to develop a new method for detecting circulating tumor cells (CTCs) with high sensitivity and specificity, therefore to detect the colorectal cancer as early as possible for improving the detection rate of the disease. To this end, we prepared some micro-column structure microchips modified with graphite oxide-streptavidin (GO-SA) on the surface of microchips, further coupled with a broad-spectrum primary antibody (antibody1, Ab₁), anti-epithelial cell adhesion molecule (anti-EpCAM) monoclonal antibody to capture CTCs. Besides, carboxylated multi-walled carbon nanotubes (MWCNTs-COOH) were coupled with colorectal cancer related antibody as specific antibody 2 (Ab₂) to prepare complex. The sandwich structure consisting of Ab₁-CTCs-Ab₂ was constructed by the microchip for capturing CTCs. And the electrochemical workstation was used to detect and verify its high sensitivity and specificity. Results showed that the combination of immunosensor and micro-nano technology has greatly improved the detection sensitivity and specificity of the immunosensor. And we also verified the feasibility of the immunosensor for clinical blood sample detection, and successfully recognitized detection and quantization of CTCs in peripheral blood of colorectal cancer patients by this immunosensor. In conclusion, the super sandwich immunosensor based on micro-nano technology provides a new way for the detection of CTCs, which has potential application value in clinical diagnosis and real-time monitoring of disease.
Humans ; Nanotubes, Carbon/chemistry* ; Neoplastic Cells, Circulating/pathology* ; Biosensing Techniques ; Immunoassay/methods* ; Antibodies ; Colorectal Neoplasms/diagnosis* ; Electrochemical Techniques/methods* ; Gold/chemistry*

OBJECTIVES: This study examined the associations between adverse childhood experiences (ACEs) and diabetes within a social-ecological framework, incorporating personal and environmental unfavorable conditions during childhood from family, school, and community contexts. METHODS: Data were obtained from the China Health and Retirement Longitudinal Study (2014 life history survey and 2015 survey), including 9,179 participants aged ≥45 years. ACEs were collected through self-report questionnaires, and participants were categorized based on the number of distinct ACEs experienced (0, 1, 2, 3, or ≥4 ACEs). Diabetes was defined by biomarkers, self-reported diagnosis, and treatment status. Logistic regression was conducted to explore the associations between ACEs and diabetes. Subgroup analyses were conducted by gender, age, and obesity status. RESULTS: Compared with participants without ACEs, those exposed to any ACE (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.01 to 1.40), 3 ACEs (OR, 1.32; 95% CI, 1.07 to 1.62) and ≥4 ACEs (OR, 1.29; 95% CI, 1.07 to 1.56) had an increased risk of diabetes. For each additional ACE, the risk of diabetes increased by about 5%. Regarding the source of ACEs, those originating from the family (OR, 1.23; 95% CI, 1.08 to 1.41) were associated with diabetes. In terms of specific ACE types, family members with substance abuse (OR, 1.23; 95% CI, 1.01 to 1.52), emotional abuse (OR, 1.28; 95% CI, 1.12 to 1.46), and poor parental relationship (OR, 1.25; 95% CI, 1.09 to 1.43) were associated with diabetes. CONCLUSIONS ACEs, particularly those originating from the family, were associated with diabetes. Interventions aimed at preventing and mitigating ACEs are essential for the early prevention of diabetes.