Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective To investigate the correlation between glycemic variability metrics and the risk of diabetic foot(DF)in patients with type 2 diabetes mellitus(T2DM)utilizing flash glucose monitoring(FGM)tech-nology.Methods A retrospective analysis was conducted on 233 hospitalized patients with T2DM,with or without DF,who were treated in the Department of Endocrinology at Lianyungang First People's Hospital from January 2021 to May 2022 and monitored using FGM.Patients were categorized into a non-DF group(n=147)and a DF group(n=86)based on the presence of DF.The study compared general clinical characteristics,biochemical parameters,and glycemic variability metrics between the two groups and performed subgroup analyses.Binary logistic regression was employed to identify factors associated with the risk of DF,while receiver operating characteristic(ROC)curves were utilized to assess the predictive value of glycemic variability metrics for DF.Results Compared with the non-DF group,patients in the DF group exhibited significantly longer disease duration,higher body mass index(BMI),glycated hemoglobin(HbA1c),urinary albumin-to-creatinine ratio(UACR),alanine aminotransferase(ALT),serum uric acid(SUA),mean amplitude of glycemic excursions(MAGE),coefficient of variation(CV),mean of daily differences(MODD),and mean blood glucose(MBG),but lower fasting C-peptide(FCP),fasting insulin(FINS),high-density lipoprotein cholesterol(HDL-C),and time in range(TIR),with statistically signifi-cant differences(P<0.05).Subgroup analysis revealed that TIR was associated with the incidence of DF and diabetic retinopathy(DR).Binary logistic regression analysis identified HbA1c,MAGE,MODD,and MBG as risk factors for DF,while TIR was a protective factor(P<0.05).ROC curve analysis demonstrated that the area under the curve(AUC)for predicting DF using HbA1c,TIR,MAGE,MODD,MBG,and their combination were 0.646,0.850,0.868,0.764,0.619,and 0.967,respectively,indicating superior performance of the combined prediction model.Conclusions HbA1c,TIR,MAGE,MODD,and MBG are critical factors associated with the development of DF in patients with T2DM.Targeted early interventions aimed at optimizing these glycemic variability indicators may effectively reduce the incidence of DF.

Objective:To investigate the mechanism of icariin(ICA)on improving cardiac function in mice with chronic heart failure(CHF)and its effect on gene expression of Toll-like receptor 4(TLR4)signaling pathway.Methods:Transverse aortic constric-tion was used to reproduce the CHF mouse model,low(ICA-L)and high(ICA-H)doses of ICA were used to intervent.Lipopolysac-charide(LPS),a TLR4 signal specific agonist,was used as a functional rescue test.High-resolution small animal ultrasound imaging system was used to detect left ventricular end-systolic diameter(LVIDs),left ventricular end-diastolic diameter(LVIDd),left ventric-ular ejection fraction(LVEF)and left ventricular short axis shortening(LVFS).TUNEL staining was used to detect apoptosis of myo-cardial tissue of mice in each group.Immunofluorescence was used to detect expressions of TNF-α and IL-6.qRT-PCR was used to detect mRNA expressions of TLR4,high mobility group box 1(HMGB1),myeloid differentiation factor 88(MyD88)and nuclear factor κB(NF-κB).Western blot was used to detect protein expressions of TLR4,HMGB1,MyD88 and phosphorylated NF-κB(p-NF-κB).Results:Compared with Sham group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expressions of TLR4,HMGB1,MyD88,NF-κB and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly increased,while LVEF and LVFS were significantly decreased in CHF group,ICA-L group,ICA-H group and ICA-H+LPS group.Compared with CHF group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expressions of TLR4,HMGB1,MyD88,NF-κB,and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly decreased,while LVEF and LVFS were significantly increased in ICA-L group,ICA-H group and ICA-H+LPS group.Compared with ICA-L group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expres-sions of TLR4,HMGB1,MyD88,NF-κB,and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly decreased,while LVEF and LVFS were significantly increased in ICA-H group.Compared with ICA-H group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expressions of TLR4,HMGB1,MyD88,NF-κB,and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly increased,while LVEF and LVFS were significantly decreased in ICA-H+LPS group(P<0.05),there was no statistically significant difference in expression of NF-κB in myocardial tissues of mice in each group(P>0.05).Conclusion:ICA can significantly inhibit inflammatory stress and collagen deposition in CHF mice,reduce apoptosis rate of myocardial tissue,and improve the cardiac function of experimental animals,which may be related to the inhibition of TLR4 signaling pathway.

Objective:To investigate the mechanism of icariin(ICA)on improving cardiac function in mice with chronic heart failure(CHF)and its effect on gene expression of Toll-like receptor 4(TLR4)signaling pathway.Methods:Transverse aortic constric-tion was used to reproduce the CHF mouse model,low(ICA-L)and high(ICA-H)doses of ICA were used to intervent.Lipopolysac-charide(LPS),a TLR4 signal specific agonist,was used as a functional rescue test.High-resolution small animal ultrasound imaging system was used to detect left ventricular end-systolic diameter(LVIDs),left ventricular end-diastolic diameter(LVIDd),left ventric-ular ejection fraction(LVEF)and left ventricular short axis shortening(LVFS).TUNEL staining was used to detect apoptosis of myo-cardial tissue of mice in each group.Immunofluorescence was used to detect expressions of TNF-α and IL-6.qRT-PCR was used to detect mRNA expressions of TLR4,high mobility group box 1(HMGB1),myeloid differentiation factor 88(MyD88)and nuclear factor κB(NF-κB).Western blot was used to detect protein expressions of TLR4,HMGB1,MyD88 and phosphorylated NF-κB(p-NF-κB).Results:Compared with Sham group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expressions of TLR4,HMGB1,MyD88,NF-κB and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly increased,while LVEF and LVFS were significantly decreased in CHF group,ICA-L group,ICA-H group and ICA-H+LPS group.Compared with CHF group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expressions of TLR4,HMGB1,MyD88,NF-κB,and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly decreased,while LVEF and LVFS were significantly increased in ICA-L group,ICA-H group and ICA-H+LPS group.Compared with ICA-L group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expres-sions of TLR4,HMGB1,MyD88,NF-κB,and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly decreased,while LVEF and LVFS were significantly increased in ICA-H group.Compared with ICA-H group,LVIDd and LIVDs,apoptosis rate of myocardial tissue,immunofluorescence intensity of TNF-α and IL-6 in myocardial tissue,mRNA expressions of TLR4,HMGB1,MyD88,NF-κB,and protein expressions of TLR4,HMGB1,MyD88 and p-NF-κB in myocardial tissue were significantly increased,while LVEF and LVFS were significantly decreased in ICA-H+LPS group(P<0.05),there was no statistically significant difference in expression of NF-κB in myocardial tissues of mice in each group(P>0.05).Conclusion:ICA can significantly inhibit inflammatory stress and collagen deposition in CHF mice,reduce apoptosis rate of myocardial tissue,and improve the cardiac function of experimental animals,which may be related to the inhibition of TLR4 signaling pathway.

Objective To investigate the correlation between glycemic variability metrics and the risk of diabetic foot(DF)in patients with type 2 diabetes mellitus(T2DM)utilizing flash glucose monitoring(FGM)tech-nology.Methods A retrospective analysis was conducted on 233 hospitalized patients with T2DM,with or without DF,who were treated in the Department of Endocrinology at Lianyungang First People's Hospital from January 2021 to May 2022 and monitored using FGM.Patients were categorized into a non-DF group(n=147)and a DF group(n=86)based on the presence of DF.The study compared general clinical characteristics,biochemical parameters,and glycemic variability metrics between the two groups and performed subgroup analyses.Binary logistic regression was employed to identify factors associated with the risk of DF,while receiver operating characteristic(ROC)curves were utilized to assess the predictive value of glycemic variability metrics for DF.Results Compared with the non-DF group,patients in the DF group exhibited significantly longer disease duration,higher body mass index(BMI),glycated hemoglobin(HbA1c),urinary albumin-to-creatinine ratio(UACR),alanine aminotransferase(ALT),serum uric acid(SUA),mean amplitude of glycemic excursions(MAGE),coefficient of variation(CV),mean of daily differences(MODD),and mean blood glucose(MBG),but lower fasting C-peptide(FCP),fasting insulin(FINS),high-density lipoprotein cholesterol(HDL-C),and time in range(TIR),with statistically signifi-cant differences(P<0.05).Subgroup analysis revealed that TIR was associated with the incidence of DF and diabetic retinopathy(DR).Binary logistic regression analysis identified HbA1c,MAGE,MODD,and MBG as risk factors for DF,while TIR was a protective factor(P<0.05).ROC curve analysis demonstrated that the area under the curve(AUC)for predicting DF using HbA1c,TIR,MAGE,MODD,MBG,and their combination were 0.646,0.850,0.868,0.764,0.619,and 0.967,respectively,indicating superior performance of the combined prediction model.Conclusions HbA1c,TIR,MAGE,MODD,and MBG are critical factors associated with the development of DF in patients with T2DM.Targeted early interventions aimed at optimizing these glycemic variability indicators may effectively reduce the incidence of DF.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective Exploring the clinical application value of long chain non-coding RNA(lncRNA)H19 in peripheral blood mononuclear cells(PBMCs)in type 2 diabetes mellitus(T2DM)patients with osteoporosis(OP).Methods A total of 176 patients with T2DM admitted to the Department of Endocrinology of the First People's Hospital of Lianyungang City from December 2022 to June 2023 were selected.They were divided into OP group(n=100)and simple T2DM group(n=76)according to the results of bone mineral density(BMD)determination by dual-energy X-ray.General data and biochemical indicators were compared between the two groups.The correlation between lncRNA H19 and other clinical indicators was analyzed by Spearman correlation analysis and the influencing factors for T2DM with OP were analyzed by logistic regression.Receiver operating characteristic(ROC)curve was used to evaluate the diagnostic value of lncRNA H19 in T2DM with OP.Results Compared with T2DM group,the proportion of females,age,HbA1c,TC and TGF-β1 were higher(P<0.05),while BMI,SUA,BMD and lncRNA H19 were lower in OP group(P<0.05).Spearman correlation analysis showed that lncRNA H19 expression level was positively correlated with BMI,SUA and BMD(P<0.05),and negatively correlated with age,HbA1c and TGF-β1(P<0.05).Logistic regression analysis showed that age,BMI,TC,TGF-β1 and lncRNA H19 were the influencing factors for T2DM combined with OP(P<0.05).ROC curve analysis showed that the AUC of lncRNA H19 in the diagnosis of T2DM with OP was 0.839,the sensitivity was 76.3%,and the specificity was 86.0%.Multiple linear regression analysis showed that age,TGF-β1 and OP were the influencing factors for lncRNA H19(P<0.05).Conclusion LncRNA H19 expression decreased in PBMCs in patients with T2DM with OP,which may participate in the occurrence and development of T2DM with OP through glucose metabolism and lncRNA H19/TGF-β1 pathway.

Objective To investigate the role of human umbilical cord mesenchymal stem cell-derived extracellular vesicle (hUC-MSC-EV) in the regeneration of fibrotic liver. Methods C57BL/6 mice were randomly divided into the 70% normal liver resection group (Oil+PHx group), 70% liver fibrosis resection group (CCl₄+PHx group) and 70% liver fibrosis resection+mesenchymal stem cell-derived extracellular vesicle (MSC-EV) treatment group (CCl₄+PHx+MSC-EV group), with 8 mice in each group. LX-2 cell lines were assigned into the phosphate buffer solution (PBS) group, transforming growth factor (TGF)-β group and TGF-β+MSC-EV group. The serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) in mice after partial liver resection were detected in each group. The expression levels of liver fibrosis and proliferation-related parameters were analyzed in each group. The messenger RNA (mRNA) expression levels of epidermal growth factor (EGF), fibroblast growth factor (FGF), vascular endothelial growth factor (VEGF) and hepatocyte growth factor (HGF) in LX-2 cells were detected in each group, and their effects on HGF expression in mouse liver were observed. Results Compared with the Oil+PHx group, the serum levels of AST, ALT and LDH were up-regulated, and the degree of fibrosis was more severe, the positive area of Sirius red and α-smooth muscle actin (α-SMA) staining was larger, and the expression level of α-SMA protein was up-regulated in the CCl₄+PHx group. Compared with the CCl₄+PHx group, the serum levels of AST, ALT and LDH were decreased, the degree of fibrosis was slighter, the positive area of Sirius red and α-SMA staining was decreased, and the expression level of α-SMA protein was down-regulated in the CCl₄+PHx+MSC-EV group, and the differences were statistically significant (all P < 0.05). Compared with the Oil+PHx group, the protein expression levels of Ki67 and proliferating cell nuclear antigen (PCNA) were lower in the CCl₄+PHx group. Compared with the CCl₄+PHx group, the protein expression levels of Ki67 and PCNA were increased in the CCl₄+PHx+MSC-EV group, and the differences were statistically significant (all P < 0.05). Compared with the PBS group, the expression level of CollagenⅠ mRNA in LX-2 cells was increased, the expression level of α-SMA protein was up-regulated and the expression level of HGF protein was decreased in the TGF-β group. Compared with the TGF-β group, the expression level of CollagenⅠ mRNA in LX-2 cells was decreased, the expression levels of HGF mRNA and protein were increased, and the expression level of α-SMA protein was decreased in the TGF-β+MSC-EV group, the differences were statistically significant (all P < 0.05). The expression level of HGF protein in the CCl₄+PHx group was lower than that in the Oil+PHx group, whereas the difference was not statistically significant (P > 0.05). The expression level of HGF protein in the CCl₄+PHx+MSC-EV group was higher than that in the CCl₄+PHx group, and the difference was statistically significant (P < 0.05). Conclusions The regenerative capacity of fibrotic liver is weaker than that of normal liver. hUC-MSC-EV may alleviate liver fibrosis and improve liver regeneration by promoting HGF secretion from actived hepatic stellate cells and effectively enhancing the regenerative capacity of fibrotic liver.

Objective:To observe the clinical efficacy of autologous platelet rich gel (APG) in the treatment of type 2 diabetic foot (DF) patients and the effect of APG on the expression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in peripheral blood mononuclear cells (PBMCs).Methods:A total of 62 patients with DF admitted to the Affiliated Hospital of Kangda College of Nanjing Medical University from February 2021 to May 2022 were randomly divided into a control group (30 cases) and an observation group (32 cases) using a random number table method. The control group received ultrasound debridement and dressing change treatment, while the observation group received ultrasound debridement combined with APG treatment. After 6 weeks of treatment, the effective rate, transcutaneous oxygen partial pressure (TcPO 2), and serum tumor necrosis factor- α (TNF-α), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), hypoxia inducible factor α (HIF-1 α)and the level of MALAT1 expression in PBMCs of the two groups of patients were observed. The Pearson correlation analysis was used to investigate the relationship between the expression change of MALAT (△ MALAT1) and the total effective rate of treatment. Results:The total effective rate of the observation group was higher than that of the control group [93.75%(30/32) vs 73.33%(22/30), P<0.05]. After treatment, the systolic blood pressure (SBP), diastolic blood pressure (DBP), cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FPG), glycosylated hemoglobin (HbA 1c), urinary microalbumin/creatinine (UACR), uric acid (UA), white blood cells (WBC), TNF- α and IL-6 of both groups had decreased compared to before; HIF-1 α, VEGF and MALAT1 increased compared to before treatment (all P<0.05); After treatment, there was a statistically significant difference in UA, HIF-1α, VEGF, and MALAT1 between the observation group and the control group (all P<0.05). Pearson correlation analysis showed that Δ MALAT1 in DF patients was negatively correlated with TNF -α ( r=-0.61, P=0.02), IL-6 ( r=-0.52, P=0.04), WBC ( r=-0.53, P=0.03), and positively correlated with VEGF ( r=0.58, P=0.03) and HIF-1α ( r=0.54, P=0.03). The total effective rate of DF treatment was higher in the high change group of△ MALAT [88.37%(38/43) vs 73.68%(14/19), P<0.05]. There was no statistically significant difference in the incidence of adverse reactions between the two groups ( P>0.05). Conclusions:APG can significantly upregulate the expression of MALAT, improve wound tissue blood perfusion, wound angiogenesis, and inflammatory response, promote ulcer healing, and changes in MALAT expression can help determine the prognosis of DF.