Objective:To investigate the effect of ginsenoside octanoate(Rh2-O)on inducing immunogenic cell death in hepa-tocellular carcinoma cells and its molecular mechanism.Methods:Effects of ginsenoside caprylate(Rh2-O)and autophagy inhibitor 3-MA on the activity of hepatocellular carcinoma cells were detected by CCK-8 assay.The effect of Rh2-O on CRT membrane eversion in Hepa1-6 cells were detected by immunofluorescence assay.Rh2-O treated mouse hepatocellular carcinoma cells were used to pre-pare a tumor vaccine for in vivo vaccination experiments in mice.Extracellular ATP levels were detected in real-time.The expression of autophagy-related genes and proteins were measured by real-time fluorescence PCR and Western blot,and the mitochondrial morphol-ogy and co-localization with autophagy proteins were observed by laser confocal microscopy.Results:Rh2-O showed strong cytotoxicity to Hepa1-6 cells[cell viability:(58.54±3.56)%]at a concentration of 150 μmol/L,and a large amount of CRT was observed on the surface of the cell membrane.The tumor emergence rate was 36.36%in the vaccinated group and 100%in the control group.The tumor vaccine prepared by Rh2-O effectively protected mice from the same type of tumor attack;Rh2-O induced an increase in the level of cellular secreted ATP(P<0.05),the mRNA of autophagy-related genes ATG3,p62,LC3 expression levels and autophagy-associated proteins LC3A and LC3B expression levels were increased(P<0.05),and co-localization of mitochondria with autophagy proteins was significantly increased(P<0.05).In addition,Rh2-O action on 3-MA pretreated hepatocellular carcinoma cells resulted in a signifi-cant decrease in extracellular ATP levels(P<0.001).Conclusion:Rh2-O may induce immunogenic cell death by inducing autophagy in hepatocellular carcinoma cells.

Carotid artery perivascular adipose tissue (PVAT) can influence plaque formation and progression. Recently, carotid artery PVAT density has emerged as a novel imaging biomarker being capable of reflecting local metabolic and inflammatory states of adipose tissue. It is closely associated with vulnerable plaque characteristics, such as intraplaque hemorrhage, thinning or rupture of the fibrous cap, lipid-rich necrotic core, and calcification. Therefore, carotid artery PVAT density holds promise as a key parameter for early identification of vulnerable carotid plaques and stroke risk prediction. This article reviews the definition and pathophysiological mechanism of PVAT and application of imaging techniques in PVAT, as well as the association between carotid artery PVAT density and vulnerable characteristics of plaques, with the aim of providing references for early identification of asymptomatic high-risk plaques and individualized prevention strategies of ischemic stroke.

Objective:To investigate the impact of receptor-interacting protein kinase 3 (RIPK3) on major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI), as well as the predictive performance of RIPK3 combined with traditional cardiovascular risk factors.Methods:This study was a single-center prospective cohort study. It included patients with AMI who underwent PCI at Peking Union Medical College Hospital between September 2017 and November 2017. Baseline clinical data were collected, and plasma samples were obtained 6 hours after PCI to measure RIPK3 levels. Follow-up was conducted via outpatient visits or phone calls to record the occurrence of MACE, including cardiovascular death, hospitalization for heart failure, and vascular events (recurrent AMI or stroke). The predictive performance of RIPK3, traditional cardiovascular risk factors and their combination for MACE was compared using receiver operating characteristic (ROC) curves. Patients were divided into low- and high-RIPK3 level groups based on the optimal cutoff value of RIPK3. Multivariate Cox proportional hazards regression analysis was used to assess the impact of RIPK3 levels on MACE after PCI in AMI patients. Kaplan-Meier survival curves were plotted, and the log-rank test was used to compare MACE incidence between the low-and high-RIPK3 groups.Results:A total of 103 AMI patients who underwent PCI were included, aged 63.0 (56.0, 69.0) years, and 83 (80.6%) were male. The follow-up time was 5.17 (2.81, 5.17) years, during which 44 patients (42.7%) experienced MACE. The ROC curve analysis showed that the area under the curve ( AUC) for traditional cardiovascular risk factors was 0.68 (95% CI: 0.58-0.78), while the AUC for plasma RIPK3 was 0.72 (95% CI: 0.62-0.82). The combined AUC for traditional risk factors and RIPK3 was 0.75 (95% CI: 0.65-0.85). Multivariate Cox proportional hazards regression analysis indicated that plasma RIPK3 level is greater than or equal to the optimal cutoff value of 440.9 μg/L ( HR=3.31, 95% CI: 1.53-8.30, P=0.005) was an independent risk factor for MACE in AMI patients after PCI. Kaplan-Meier survival analysis demonstrated that the high-RIPK3 group had a significantly higher risk of MACE after PCI compared to the low-RIPK3 group (log-rank P=0.006). Conclusions:Elevated plasma RIPK3 level is an independent risk factor for MACE in AMI patients after PCI. Plasma RIPK3 combined with traditional cardiovascular risk factors can more effectively predict the occurrence of MACE in AMI patients after PCI. AMI patients with RIPK3≥440.9 μg/L have a higher risk of MACE after PCI.

Background The prevalence of hyperuricemia (HUA) among Chinese residents has been increasing annually, with occupational populations facing a higher risk of HUA due to shift work or obesity. Objective To investigate the impact of shift work and obesity on HUA among coal miners, and to provide scientific data for the prevention of HUA in this occupational group. Methods A cross-sectional study was conducted with 25619 workers from a coal mining group in 2023 as the study population, using a questionnaire survey and occupational health check-ups. Workers who were retired or on medical leave, as well as those who provided incomplete responses to the questionnaire or did not complete anthropometric measurements or blood tests, were excluded. A total of 23173 participants were included in the study. An unconditional logistic regression model was used to analyze the association between HUA and selected factors such as shift work status, years of shift work, daily shift work hours, body mass index (BMI), waist-to-height ratio (WHtR), and visceral adiposity index (VAI), as well as the interaction between obesity and shift work on HUA. Restricted cubic spline functions were used to analyze the dose-response relationship between years of shift work, daily shift work hours, and HUA. Results The average age of the included workers was (42.38 ± 9.82) years. A total of 6735 workers reported positive HUA, with a positive rate of 29.1%, and the prevalence was higher in men compared to women (31.8% vs. 13.9%). After adjusting for confounding factors, the restricted cubic spline model revealed a nonlinear dose-response relationship between years of shift work, daily shift work duration, and HUA: ① When the years of shift work exceeded 3.25 years, the risk of HUA in workers gradually increased with longer work duration. At 20 years of shift work, the risk increase showed a "saturation effect," meaning that the risk of HUA no longer increased with additional years of shift work. ② When daily shift work duration was below 10 h, the risk of HUA increased with the length of shift work, but after exceeding 10 h, the risk stabilized. After adjusting for confounding factors, the logistic regression model showed that, compared to non-shift workers, shift workers, those with 10-20 years and over 20 years of shift work experience, as well as those working less than 8 h and more than 8 h per day, had a higher risk of HUA, with odds ratios (OR) of 1.14 (95%CI: 1.06, 1.22), 2.42 (95%CI: 2.20, 2.67), 2.23 (95%CI: 2.00, 2.48), 1.41 (95%CI: 1.29, 1.54), and 1.90 (95%CI: 1.75, 2.06), respectively. Additionally, compared to individuals with normal obesity indices, those with overweight and obesity based on BMI, high and very high VAI and excessive WHtR had a higher risk of HUA, with ORs of 2.01 (95%CI: 1.85, 2.17), 3.51 (95%CI: 3.20, 3.84), 1.42 (95%CI: 1.32, 1.54), 2.10 (95%CI: 1.91, 2.30), and 1.82 (95%CI: 1.69, 1.97), respectively. The interaction analysis showed no interaction between shift work and obesity index (both P_s < 0.001). Conclusion Shift work, longer shift work years, and longer daily shift work hours increase the risk of HUA among coal miners. Additionally, the role of obesity in the development of HUA cannot be ignored.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Objective: To compare peritoneal indexes between transperitoneal approach and retroperitioneal approach of robot-assisted partial nephrectomy (RAPN) for dorsal renal tumors via transperitoneal and retroperitoneal approaches，thereby providing reference for clinical decision-making in managing such neoplasms. Methods: The clinical data of renal cancer patients undergoing RAPN performed by the same surgeon at our hospital during 2017 and 2021 were retrospectively analyzed.A total of 80 patients with complete data of dorsal renal tumors were screened and divided into two groups based on the surgical approaches：50 cases in the transperitoneal group and 30 in the retroperitoneal group.The general information，intraoperative data，positive rate of pathological margins，recovery time of gastrointestinal functions，and incidence of complications were compared between the two groups. Results: All operations were successfully completed, and the surgical margins were negative.There were no statistically significant differences in warm ischemia time [17 (15，18) min vs.16 (14，19) min，P=0.772]，operation time [120 (105，149) min vs.124 (108，152) min，P=0.584]，intraoperative blood loss [100 (50，100) mL vs.100 (50，100) mL，P=0.814]，and incidence of postoperative complications (17% vs.24%，P=0.504) between the two groups (P>0.05).The postoperative recovery time of gastrointestinal functions in the retroperitoneal group was significantly shorter than that in the transperitoneal group [2.0 (2.0，3.0) d vs.3.5 (3.0，4.0) d，P<0.001]. Conclusion: The perioperative outcomes of patients undergoing RAPN via the retroperitoneal approach are similar to those via the transperitoneal approach.However，the retroperitoneal approach has an advantage of faster recovery of gastrointestinal functions.

Background In recent years, the detection rate of thyroid nodules in China's occupational population has shown an upward trend. The prevalence of this disease needs to be taken seriously and targeted measures should be taken to address its influencing factors. Objective To analyze the detection and influencing factors of thyroid nodules among adult male workers in coal mining enterprises in Shanxi Province, and provide a theoretical basis for the prevention of thyroid nodules. Methods A total of 5195 adult male workers from coal mining enterprises who ordered physical examination provided by the Xishan Coal Electricity (Group) Corporation Occupational Disease Prevention and Control Institute in Taiyuan City, Shanxi Province from May 2023 to December 2023 were selected as research subjects. A questionnaire survey, physical examination, ultrasound examination, and biological sample collection and testing were conducted. Thyroid nodules were diagnosed based on ultrasound results, classified and evaluated according to the Chinese-Thyroid Imaging Reporting and Data System (C-TIRADS), and the crude detection rate and standardized detection rate of thyroid nodules in adult male coal mine workers in Shanxi Province wereestimated. Occupational history and occupational exposure information were retrieved from their annual occupational health examination reports provided by the employer. Logistic regression modeling was used to analyze the influencing factors of thyroid nodule. Results A total of 1688 cases of thyroid nodules were detected, with a crude detection rate of 32.49% and an age-standardized detection rate of 31.17%. The cases (constitution ratio) of thyroid nodules by category in the detected cases was as follows: 358 cases (21.21%) were classified as category 2, 1261 cases (74.70%) as category 3, 67 cases (3.97%) as category 4a, and 2 cases (0.12%) as category 4b. The results of logistic regression showed that the duration of exposure to occupational hazards for 11-20 years, 21-30 years, ≥31 years, average monthly working>26 days, and shift work were positively correlated with the detection of thyroid nodules (P<0.05), and the associated ORs (95%CIs) were 1.29 (1.01, 1.65), 1.55 (1.20, 1.99), 1.68 (1.26, 2.55), 1.19 (1.00, 1.40), and 1.15 (1.02, 1.29), respectively. Conclusion The duration of exposure to occupational hazards, average monthly working days, and shift work are influencing factors of thyroid nodules. Intervention measures should be developed based on these influencing factors to prevent the occurrence of thyroid nodules.

Objective:To investigate the efficacy of a predictive model for differentiating benign and malignant renal tumors based on CT radiomic features and clinical features.Methods:A retrospective study was conducted on 1 395 patients with renal tumors admitted to the First Affiliated Hospital of Zhengzhou University from December 2011 to December 2021, including 842 males and 553 females. The median age was 55 (44, 59) years, and the median tumor diameter was 3.6 (2.7, 4.6) cm. All patients underwent contrast-enhanced CT scaning before surgery, and radiomic features were extracted from non-contrast, arterial, and venous phase images. Prediction models for distinguishing benign and malignant renal tumors were constructed using five machine learning algorithms (logistic regression, support vector machine, neural network, random forest, and extreme gradient boosting), and these models were then ensembled to construct a stacking classifier. All patients underwent partial nephrectomy, and they were divided into a training group (941 cases, December 2011 to June 2020) and a validation group (454 cases, July 2020 to December 2021) based on the date of surgery. A clinical-radiomic model was developed by combining the result of stacking classifier, clinical features and CT report results, and its predictive performance was evaluated in the validation group.Results:The radiomic signature based on the combined features and five machine learning algorithms(AUC 0.835-0.844) showed higher accuracy in predicting benign and malignant renal tumors compared to single phases (AUC 0.744-0.831). After integrating the five machine learning algorithms, the AUC of the three-phase combined radiomic model in the validation group improved to 0.847(95% CI 0.802-0.892). The clinical-radiomic model, incorporating radiomic features, clinical features, and CT report results, achieved a significantly higher AUC in the validation group compared to radiologists [0.919(95% CI 0.889-0.950)vs. 0.835(95% CI 0.786-0.883), P<0.01]. Conclusions:The predictive model integrating CT radiomics features, clinical characteristics, and CT report results demonstrates excellent discriminative ability in distinguishing benign and malignant renal tumors.

Objective:To analyze the clinical features associated with pelvic lymph node metastasis(PLNM)in prostate cancer and to construct a preoperative prediction model for PLNM,thereby reducing unnecessary extended pelvic lymph node dissection(ePLND).Methods:Based on predefined inclusion and exclusion criteria,344 patients who underwent radical prostatectomy and ePLND at the First Affilia-ted Hospital of Zhengzhou University between 2014 and 2024 were retrospectively enrolled,among whom,77 patients(22.4％)were pathologically confirmed to have lymph node-positive disease.The clinical characteristics,MRI reports,and pathological results were collected.The data were then randomly divi-ded into a training cohort(241 cases,70％)and a validation cohort(103 cases,30％).Univariate and multivariate Logistic regression analysis were employed to construct a preoperative prediction model for PLNM.Results:Univariate Logistic regression analysis revealed that total prostate specific antigen(tPSA)(P=0.021),free prostate specific antigen(fPSA)(P=0.002),fPSA to tPSA ratio(fPSA/tPSA)(P=0.011),percentage of positive biopsy cores(P＜0.001),prostate imaging reporting and data system(PI-RADS)score(P=0.004),biopsy Gleason score ≥8(P=0.005),clinical T stage(P＜0.001),and MRI-indicated lymph node involvement(MRI-LNI)(P＜0.001)were significant predictors of PLNM.Multivariate Logistic regression analysis demonstrated that the percentage of positive biopsy cores(OR=91.24,95％CI:13.34-968.68),PI-RADS score(OR=7.64,95％ CI:1.78-138.06),and MRI-LNI(OR=4.67,95％ CI:1.74-13.24)were independent risk factors for PLNM.And a novel nomogram for predicting PLNM was developed by integrating all these three variables.Com-pared with the individual predictors:percentage of positive biopsy cores[area under curve(AUC)=0.806],PI-RADS score(AUC=0.679),and MRI-LNI(AUC=0.768),the multivariate model incor-porating all three variables demonstrated significantly superior predictive performance(AUC=0.883).Consistently,calibration curves and decision curve analyses confirmed that the multivariable model had high predictive accuracy and provided significant net clinical benefit relative to single-variable models.And using a cutoff of 6％,the multiparameter model missed only approximately 5.2％of PLNM cases(4/77),while reducing approximately 53％of ePLND procedures(139/267),demonstrating favorable predictive efficacy.Conclusion:Percentage of positive biopsy cores,PI-RADS score and MRI-LNI are independent risk factors for PLNM.The constructed multivariate model significantly improves predictive efficacy,offering a valuable tool to guide clinical decisions on ePLND.

Objective:To analyze the clinical features associated with pelvic lymph node metastasis(PLNM)in prostate cancer and to construct a preoperative prediction model for PLNM,thereby reducing unnecessary extended pelvic lymph node dissection(ePLND).Methods:Based on predefined inclusion and exclusion criteria,344 patients who underwent radical prostatectomy and ePLND at the First Affilia-ted Hospital of Zhengzhou University between 2014 and 2024 were retrospectively enrolled,among whom,77 patients(22.4％)were pathologically confirmed to have lymph node-positive disease.The clinical characteristics,MRI reports,and pathological results were collected.The data were then randomly divi-ded into a training cohort(241 cases,70％)and a validation cohort(103 cases,30％).Univariate and multivariate Logistic regression analysis were employed to construct a preoperative prediction model for PLNM.Results:Univariate Logistic regression analysis revealed that total prostate specific antigen(tPSA)(P=0.021),free prostate specific antigen(fPSA)(P=0.002),fPSA to tPSA ratio(fPSA/tPSA)(P=0.011),percentage of positive biopsy cores(P＜0.001),prostate imaging reporting and data system(PI-RADS)score(P=0.004),biopsy Gleason score ≥8(P=0.005),clinical T stage(P＜0.001),and MRI-indicated lymph node involvement(MRI-LNI)(P＜0.001)were significant predictors of PLNM.Multivariate Logistic regression analysis demonstrated that the percentage of positive biopsy cores(OR=91.24,95％CI:13.34-968.68),PI-RADS score(OR=7.64,95％ CI:1.78-138.06),and MRI-LNI(OR=4.67,95％ CI:1.74-13.24)were independent risk factors for PLNM.And a novel nomogram for predicting PLNM was developed by integrating all these three variables.Com-pared with the individual predictors:percentage of positive biopsy cores[area under curve(AUC)=0.806],PI-RADS score(AUC=0.679),and MRI-LNI(AUC=0.768),the multivariate model incor-porating all three variables demonstrated significantly superior predictive performance(AUC=0.883).Consistently,calibration curves and decision curve analyses confirmed that the multivariable model had high predictive accuracy and provided significant net clinical benefit relative to single-variable models.And using a cutoff of 6％,the multiparameter model missed only approximately 5.2％of PLNM cases(4/77),while reducing approximately 53％of ePLND procedures(139/267),demonstrating favorable predictive efficacy.Conclusion:Percentage of positive biopsy cores,PI-RADS score and MRI-LNI are independent risk factors for PLNM.The constructed multivariate model significantly improves predictive efficacy,offering a valuable tool to guide clinical decisions on ePLND.