Diabetic kidney disease（DKD） is a chronic kidney structural and functional disorder caused by diabetes. With the global prevalence of diabetes continuing to rise， DKD has gradually become a major cause of chronic kidney disease and end-stage renal disease（ESRD）， posing a serious threat to patients' quality of life and long-term health outcomes. Studies have shown that apoptosis plays a pivotal role in the development and progression of DKD， with its mechanisms involving abnormal activation of multiple signaling pathways such as Toll-like receptor 4（TLR4）/nuclear transcription factor-κB（NF-κB）/B-cell lymphoma-2（Bcl-2）/cysteinyl aspartate-specific proteinase（Caspase）-3， protein kinase R-like endoplasmic reticulum kinase（PERK）/eukaryotic initiation factor 2α（eIF2α）/activating transcript factor 4（ATF4）/CCAAT enhancer-binding protein homologous protein（CHOP）， phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β）， Janus kinase 2（JAK2）/signal transducer and activator of transcription 3（STAT3）， adenosine monophosphate-activated protein kinase（AMPK）/mammalian target of rapamycin（mTOR） and silent information regulator 1（SIRT1）/tumor suppressor protein 53（p53）， thereby accelerating renal pathological damage in DKD. Extensive evidence-based medical studies have confirmed that traditional Chinese medicine（TCM）， leveraging its unique therapeutic advantages of multi-target， multi-component and multi-pathway approaches， has demonstrated remarkable efficacy and favorable safety profiles in treating DKD. Recent studies have demonstrated that active components of TCM can specifically target and modulate key effectors in apoptotic signaling pathways. Meanwhile， traditional compound formulations exert synergistic effects through multiple approaches such as replenishing deficiency and activating blood circulation， detoxifying and dredging collaterals， tonifying kidney essence， and removing stasis and purging turbidity， thereby comprehensively regulating critical pathological processes including endoplasmic reticulum stress and mitochondrial apoptosis pathways. This combined therapeutic approach of molecular targeting and holistic regulation provides novel strategies for delaying the progression of DKD. Based on this， this paper provides an in-depth analysis of key apoptotic signaling pathways and their regulatory mechanisms， while systematically summarizing recent research advances regarding the therapeutic effects of TCM active components， compound formulations， and proprietary Chinese medicines on DKD through modulation of these pathways， with particular emphasis on their underlying molecular mechanisms. These findings not only elucidate the modern scientific connotation and theoretical basis of TCM in treating DKD but also establish a solid theoretical and practical foundation for promoting the wider clinical application and further research of TCM in the field of DKD treatment.

Objective:To investigate the predictive value of a machine learning model combining contrast-enhanced ultrasound（CEUS）parameters，radiomics features of ultrasound images，and clinical data for pathological grading in bladder urothelial carcinoma（BUC）.Methods:A retrospective analysis was conducted on 174 BUC patients from Inner Mongolia Autonomous Region People 's Hospital and the First Affiliated Hospital of Baotou Medical College from December 2017 to March 2024. One hundred and thirteen BUC patients from the former hospital were randomly divided into training group and internal test group in a ratio of 7 to 3，while 61 BUC patients from the latter hospital served as an external test group. The patients were stratified into low-grade bladder urothelial carcinoma（LGBUC）and high-grade bladder urothelial carcinoma（HGBUC）groups based on pathology. Two-dimensional grayscale ultrasound images were subjected to super-resolution（SR）reconstruction，followed by extraction and screening of radiomics features in comparison with CEUS video sequences. Selected features were input into a support vector machine（SVM）to build the radiomics model. CEUS parameters，conventional ultrasound metrics and clinical data with statistical significance between LGBUC and HGBUC groups were input into SVM to construct the clinical model. The radiomics and clinical model outputs were fused via multivariate Logistic regression to form a combined model. Model performances were evaluated using ROC curves，calibration curves，and clinical decision curves. Results:Seven radiomics features from SR images were used to build the radiomics model，while CEUS parameters（peak intensity and time-to-peak half），age，tumor-wall interface and tumor-wall angle formed the clinical model. The combined model integrated these outputs. All 3 models exhibited respective strengths，the combined model showed superior robustness. The AUCs of the combined model in the training，internal test and external test groups were 0.92，0.84 and 0.82，respectively.Conclusions:The combined model combining CEUS parameters，ultrasound radiomics features，and clinical data accurately predicts BUC pathological grade，providing a potential tool for clinical diagnosis and treatment.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Objective: To investigate the correlation between peripheral blood CD4 T lymphocyte subsets and delayed graft function (DGF) and short-term prognosis in kidney transplant recipients, so as to help optimize preoperative assessment for kidney transplantation and provide insights into the immune mechanisms of DGF. Methods: A retrospective analysis was conducted on the clinical data of 103 kidney transplant recipients at the First Affiliated Hospital of Soochow University during Jun.2022 and Oct.2023. A total of 61 recipients were finally included in this study, and were categorized into two groups based on postoperative renal function recovery：the DGF group (n=20) and the immediate graft function (IGF) group (n=41).Flow cytometry was used to detect the proportions and absolute counts of various CD4 T lymphocyte subsets in the peripheral blood on postoperative day 7.The clinical data and peripheral blood lymphocyte subsets between the two groups were compared.For the subsets that exhibited significant differences, the correlation between their proportions and absolute counts and serum creatinine (Scr) levels on postoperative day 7 was further analyzed in the DGF group.Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to evaluate the predictive performance of the most strongly correlated CD4 T lymphocyte subset in terms of proportion and absolute count for short-term renal function. Results: There were no statistically significant differences in the proportions and absolute counts of Th1, Th2, Th17, and regulatory T cells (Treg) between the DGF and IGF groups (P>0.05).The proportions and absolute counts of follicular helper T cells (Tfh) and PD-1 Tfh cells were significantly higher in the DGF group than in the IGF group (P＜0.000 1). The Scr levels at 1 month and 1 year postoperatively were significantly higher in the DGF group than in the IGF group (P＜0.01), while the estimated glomerular filtration rate (eGFR) was significantly lower in the DGF group compared with the IGF group (P＜0.01, P=0.02).Spearman correlation analysis showed that the proportions and absolute counts of Tfh and PD-1 Tfh cell subsets were positively correlated with the Scr level on post-operative day 7 in the DGF group (P＜0.05).The ROC curve demonstrated that the AUC for the proportion of PD-1 Tfh cells in predicting Scr and eGFR at 1 month after surgery was 0.73(95%CI:0.61-0.86) and 0.75 (95%CI:0.62-0.88), respectively.Additionally, the AUC for predicting Scr and eGFR at 1 year was 0.72(95%CI:0.59-0.86) and 0.70(95%CI:0.58-0.83), respectively. Conclusion: The increase in the proportions and absolute counts of Tfh and PD-1 Tfh cells is associated with postoperative DGF of renal transplant recipients, and the proportion of PD-1 Tfh cells may help predict the short-term renal function of recipients.

Arsenic (organoarsenic) compound is one of the oldest drugs used by humans to treat various diseases. From its initial application in treating various skin diseases to the 1970s when arsenic trioxide (ATO) was proven to be able to significantly relieve acute promyelocytic leukemia (APL), arsenic (organoarsenic) compounds gradually occupied an important position in the history of medical development. This article reviews the pharmaceutical research progress of inorganic arsenic compounds and organic arsine compounds, covering anticancer, antiparasitic, antiviral and antibiotic aspects. It further explores the potential for developing new arsenic (organoarsenic) drugs with higher efficacy and lower toxicity, aiming to provide new research directions and ideas for the application of arsenic (organoarsenic) compounds in disease treatment.

Objective:To investigate the predictive value of a machine learning model combining contrast-enhanced ultrasound（CEUS）parameters，radiomics features of ultrasound images，and clinical data for pathological grading in bladder urothelial carcinoma（BUC）.Methods:A retrospective analysis was conducted on 174 BUC patients from Inner Mongolia Autonomous Region People 's Hospital and the First Affiliated Hospital of Baotou Medical College from December 2017 to March 2024. One hundred and thirteen BUC patients from the former hospital were randomly divided into training group and internal test group in a ratio of 7 to 3，while 61 BUC patients from the latter hospital served as an external test group. The patients were stratified into low-grade bladder urothelial carcinoma（LGBUC）and high-grade bladder urothelial carcinoma（HGBUC）groups based on pathology. Two-dimensional grayscale ultrasound images were subjected to super-resolution（SR）reconstruction，followed by extraction and screening of radiomics features in comparison with CEUS video sequences. Selected features were input into a support vector machine（SVM）to build the radiomics model. CEUS parameters，conventional ultrasound metrics and clinical data with statistical significance between LGBUC and HGBUC groups were input into SVM to construct the clinical model. The radiomics and clinical model outputs were fused via multivariate Logistic regression to form a combined model. Model performances were evaluated using ROC curves，calibration curves，and clinical decision curves. Results:Seven radiomics features from SR images were used to build the radiomics model，while CEUS parameters（peak intensity and time-to-peak half），age，tumor-wall interface and tumor-wall angle formed the clinical model. The combined model integrated these outputs. All 3 models exhibited respective strengths，the combined model showed superior robustness. The AUCs of the combined model in the training，internal test and external test groups were 0.92，0.84 and 0.82，respectively.Conclusions:The combined model combining CEUS parameters，ultrasound radiomics features，and clinical data accurately predicts BUC pathological grade，providing a potential tool for clinical diagnosis and treatment.

Arsenic (organoarsenic) compound is one of the oldest drugs used by humans to treat various diseases. From its initial application in treating various skin diseases to the 1970s when arsenic trioxide (ATO) was proven to be able to significantly relieve acute promyelocytic leukemia (APL), arsenic (organoarsenic) compounds gradually occupied an important position in the history of medical development. This article reviews the pharmaceutical research progress of inorganic arsenic compounds and organic arsine compounds, covering anticancer, antiparasitic, antiviral and antibiotic aspects. It further explores the potential for developing new arsenic (organoarsenic) drugs with higher efficacy and lower toxicity, aiming to provide new research directions and ideas for the application of arsenic (organoarsenic) compounds in disease treatment.

Objective To explore the application value of a special fence in percutaneous transhepatic cholangial drainage(PTCD)under the guidance of C-arm CT.Methods A total of 43 patients who underwent PTCD were randomly divided into observation group and control group.The intervention operation in the observation group was guided by C-arm CT and located by special fence;in the control group,the intervention operation was only performed under digital subtraction angiography(DSA)fluoroscopy.Respectively,the differences in operation time,number of puncture needles and number of complications between the two groups were compared.Results The operation time,puncture times and complications in the observation group were(39.33±12.96)min,(1.67±0.80)times and 3 cases respectively;in the control group were(86.77±22.70)min,(3.41±1.26)times and 13 cases respectively;There were significant differences between the two groups(P<0.05).Conclusion The application of special fence in PTCD under the guidance of C-arm CT can short the operation time,reduce the number of punctures and reduce complications,which has important clinical application value.

Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.

Primary liver cancer is one of the most common malignant tumors of the digestive system,of which hepatocellular carcinoma(HCC)accounts for more than 90％of the total cases.The patients with early HCC treated by surgical resection generally demonstrate good prognosis.However,due to the insidious onset,HCC in the vast majority of patients has progressed to the mid-to-late stage when being diagnosed.As a result,surgical treatment has unsatisfactory effects,and non-surgical treatment methods generally have severe side effects and low tumor selectivity.Nanoparticles(NP)with small sizes,large specific surface areas,and unique physical and chemical properties have become potential carriers for the delivery of therapeutic agents such as drugs,genes,and cytokines.The nano-delivery systems with NP as the carrier can regulate the metabolism and transformation of drugs,genes,and cytokines in vivo from time,space,and dose via functional modification,showing great potential in the treatment of HCC.This paper introduces the current status and advantages of several common nano-delivery systems,including organic nano-carriers,inorganic nano-carriers,and exosomes,in the treatment of HCC.Furthermore,this paper summarizes the mechanisms of NP-based nano-carriers in treating HCC and provides reference for the development of new nano-delivery systems.