Diabetic kidney disease （DKD）， a common complication of diabetes mellitus， is a leading global cause of end-stage renal disease （ESRD）. Current therapeutic strategies primarily focus on symptomatic management but exhibit limited efficacy in halting disease progression to ESRD， and some drugs carry non-negligible toxic side effects. Traditional Chinese medicine （TCM） has a long history in treating DKD， with single TCM and TCM compounds demonstrating unique advantages in multi-target， multi-pathway， and multi-effect therapeutic interventions. Tripterygium wilfordii （TW）， known for its effects in promoting blood circulation， dredging collaterals， dispelling wind， removing dampness， reducing swelling， and alleviating pain， contains bioactive components such as Tripterygium glycosides （TWG）， triptolide （TPL）， tripdiolide （TPD）， and celastrol （CEL）. The active ingredients possess various functions， including regulating immune-inflammatory balance， ameliorating renal fibrosis and glomerulosclerosis， combating oxidative stress， protecting podocytes， and improving glucose and lipid metabolism， all of which play a significant role in the treatment of DKD. This review summarized the mechanisms underlying the therapeutic effects of T. wilfordii and its active ingredients on DKD， aiming to provide insights for clinical management and novel drug development of DKD.

Hepatocellular carcinoma （HCC）， the predominant subtype of primary liver cancer， ranks among the top in both incidence and mortality rates of malignant tumors in China. In its early stages， the disease may present with subtle or nonspecific symptoms， often leading to poor clinical prognosis and low patient survival rates， which makes it a significant public health concern. The pathogenesis is associated with multiple factors， including hepatitis virus infection， alcohol consumption， obesity， drug-induced liver injury， and immune disorders， which may interact synergistically to promote disease development. Currently， mainstream therapeutic approaches for HCC in modern medicine encompass surgical resection， liver transplantation， radiofrequency ablation， radiotherapy， and chemotherapy， but they all have certain limitations， such as large side effects and poor prognosis， imposing substantial psychological distress and financial strain on affected individuals. With a rich historical background in hepatic malignancy management， traditional Chinese medicine offers therapeutic benefits characterized by multi-targeted mechanisms， multi-level regulation， minimal adverse effects， and reduced likelihood of disease recurrence. It can not only enhance the curative effect， but also reduce the side effects of radiotherapy， chemotherapy， and surgery. Thus， it has attracted widespread attention. Extensive research has demonstrated that traditional Chinese medicine exhibits significant antitumor properties， along with notable anti-inflammatory and oxidative stress-reducing capabilities， and its mechanism may be related to the regulation of nuclear factor-kappa B （NF-κB） signaling pathway， which can affect multiple stages of hepatocarcinogenesis， such as cell proliferation， invasion， metastasis， and apoptosis. The mechanism of NF-κB signaling pathway in traditional Chinese medicine for HCC treatment has emerged as one of the pivotal research directions in current oncology studies. Based on the existing research foundation， a systematic literature review method was adopted to retrieve and analyze relevant Chinese and English literature in recent years. Integrating the molecular regulatory mechanisms of the NF-κB signaling pathway and its pivotal role in HCC pathogenesis and progression helped further explore the latest research advances in traditional Chinese medicine interventions targeting this pathway for HCC treatment. This approach may provide novel theoretical foundations and translational strategies for the prevention and management of HCC using traditional Chinese medicine.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

[摘 要] 目的：构建了一种靶向成纤维细胞活化蛋白（FAP）且能分泌CTLA-4单链抗体（scFv）的CAR-T细胞，并探讨其联合血管靶向药物阿帕替尼对胶质母细胞瘤（GBM）的抗肿瘤效果及机制。方法：构建FAP-CTLA-4 CAR过表达载体，转导至T细胞中制备FAP-CTLA-4 CAR-T细胞。流式细胞术检测FAP-CTLA-4 CAR-T细胞表面分子CD69表达，ELISPOT检测其分泌IFN-γ的能力，细胞增殖实验分析FAP-CTLA-4 CAR-T细胞的增殖情况，杀伤实验分析其联合阿帕替尼处理对人脑星形胶质母细胞瘤U-87 MG细胞治疗效果的影响。建立小鼠U-87 MG细胞异种移植瘤模型。分别用FAP-CTLA-4 CAR-T细胞单独治疗或联合阿帕替尼治疗荷瘤小鼠，命名为FAP-CTLA-4 CAR-T组、阿帕替尼组和FAP-CTLA-4 CAR-T + 阿帕替尼组，观察各组小鼠肿瘤生长情况，免疫组化、TUNEL染色与免疫荧光法检测各组肿瘤组织中Ki-67、CD31表达及细胞凋亡情况，流式细胞术分析FAP-CTLA-4 CAR-T细胞在荷瘤小鼠体内的存活状况，H-E染色和血清生化分析评估联合治疗的安全性。结果：与FAP-CTLA-4 CAR-T组、阿帕替尼组相比，FAP-CTLA-4 CAR-T + 阿帕替尼组中CAR-T细胞的活化水平显著提高，细胞增殖能力明显增强，IFN-γ分泌细胞比例及对靶细胞的杀伤效率均提高（P < 0.01或P < 0.05）。在荷瘤小鼠模型中，联合治疗显著抑制肿瘤生长并延长小鼠生存时间（P < 0.01或P < 0.05），同时抑制肿瘤细胞增殖、降低微血管密度、促进肿瘤细胞凋亡，并延长CAR-T细胞在肿瘤组织中的存活时间（P < 0.01或P < 0.05），且未对主要组织器官造成毒性损伤。结论：FAP-CTLA-4 CAR-T细胞与阿帕替尼联合应用在GBM治疗中显示出协同增效作用与良好的安全性。

ObjectiveTo systematically analyze the differences in therapeutic efficacy between intensity-modulated radiotherapy （IMRT） and stereotactic body radiotherapy （SBRT） for locally advanced pancreatic cancer （LAPC）， and to provide a basis for treatment decision-making. MethodsPubMed， Embase， the Cochrane Library， CNKI， Wanfang Data， and VIP databases were searched for prospective or retrospective cohort studies on IMRT versus SBRT for the treatment of LAPC published up to July 31， 2025. The Newcastle-Ottawa Scale was used to assess the quality of studies， and Review Manager 5.4 was used to perform the Meta-analysis. ResultsA total of 23 studies involving 2 505 patients were included. In terms of local control rate， an analysis of 13 studies with 847 patients showed that the SBRT group had a significantly higher 1-year local control rate than the IMRT group （84.5% vs 66.7%， relative risk ［RR］=1.27， 95% confidence interval ［CI］： 1.03 — 1.56， I²=28%， P=0.026）. In terms of acute toxicity， an analysis of 15 studies showed that the SBRT group had a significantly lower incidence rate of grade≥3 acute toxicity than the IMRT group （3.5% vs 11.0%， RR=0.32， 95%CI： 0.19 — 0.53， I²=18%， P<0.001）. There was no significant difference in overall survival between the SBRT group and the IMRT group （16.8 months vs 16.3 months）. The subgroup analysis of local control rate showed that in the 9 high-quality studies， the SBRT group had a significantly higher local control rate than the IMRT group （RR=1.25， P<0.001）， and a similar result was observed in the 4 moderate-quality studies （RR=1.31， P=0.021）； the stratified analysis based on technique platforms showed that the MR-guided technique group showed the largest effect size （RR=1.40， I²=10%）. The sensitivity analysis showed that the RR value ranged from 1.21 to 1.28， with stable results. The Egger regression analysis showed no significant publication bias （P>0.05）. ConclusionSBRT is superior to IMRT in terms of local control rate and acute toxicity and is a preferred treatment option for LAPC， with the MR-guided techniques showing the best performance.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.

Objective To explore the clinical value of preoperative assessment and intraoperative frozen section pathology in screening patients suitable for testicular preservation surgery, so as to provide reference for reducing unnecessary radical orchiectomy in patients with benign testicular tumors. Methods A retrospective analysis was conducted on 121 patients who underwent surgical treatment for testicular tumors in the First Affiliated Hospital of Xi'an Jiaotong University during Jan. 2021 and Sep. 2025. Data were collected, including demographic information, preoperative imaging, serum tumor markers, surgical procedures, intraoperative frozen section, postoperative pathology, and postoperative testicular volume changes. Results Among the 121 patients, 105 underwent radical orchiectomy, with 91 malignant and 14 benign cases confirmed by postoperative pathology; 16 received testicular tumor enucleation, all confirmed as benign. Benign lesions accounted for 24.79% (30/121) of all cases. In patients undergoing tumor enucleation, intraoperative frozen section results were fully consistent with final pathological findings. Conclusion Preoperative differentiation between benign and malignant testicular tumors is crucial for selecting the appropriate surgical approach. For patients with preoperative findings suggesting benign lesions, testicular tumor enucleation combined with intraoperative frozen section can achieve precise treatment while maximizing testicular preservation.

Objective To analyze the disease burden of chronic kidney diseases (CKD) attributed to high body mass index (BMI) in China from 1992 to 2021 and predict the disease burden for the next decade, and to provide evidence for the prevention and treatment of CKD. Methods Using the Global Burden of Disease (GBD) database and the Joinpoint model, the average annual percentage rate change (AAPC) of the mortality rate and disability-adjusted life year (DALY) rate was calculated to describe and analyze the CKD disease burden attributed to high BMI in China from 1992 to 2021. The ARIMA model was employed to predict and analyze the change trend of the CKD disease burden. Results From 1992 to 2021, the mortality rate and DALY rate attributed to high BMI-induced chronic kidney disease showed an upward trend. Compared to 1992, the attributed number of deaths increased by 324.38%, and DALYs increased by 268.56%; the mortality rate increased by 64.00%, and the DALY rate grew by 51.62%. From 1992 to 2021, the mortality rate and DALY rate for males were lower than those for females, but the growth rate for males exceeded that of females. From 1992 to 2021, the mortality rate and DALY rate of chronic kidney disease attributed to high BMI in China increased with age. The average annual change rate of chronic kidney disease attributed to high BMI in China from 1992 to 2021 (mortality rate: 1.40 per 100,000 (95% CI: 1.04–1.76), DALY rate: 1.43 per 100 000 (95% CI: 1.17–1.70)) was higher than thHuaiyin Normal University, Huai'anher social demographic index (SDI) regions. The ARIMA model predicted that the age-standardized mortality rate increased from 2.91 per 100 000 in 2022 to 3.05 per 100 000 in 2026, and the age-standardized DALY rate increased from 69.65 per 100 000 in 2022 to 73.58 per 100 000 in 2026. Conclusion Chronic kidney disease attributed to high BMI in China is on the rise, and it will continue to grow in the future. The focus of CKD prevention and control should be on males and the elderly, while active measures should be taken to reduce the occurrence and progression of chronic kidney disease.

ObjectiveTo observe the influence and therapeutic effect of quercetin on cuproptosis in rheumatoid arthritis rats and to explore its possible mechanism based on the solute carrier family 31 member 1 （SLC31A1）/ferredoxin 1 （FDX1） pathway. MethodsSixty male SD rats were divided into six groups： A control group， a model group， high- and low-dose quercetin groups （150 and 50 mg·kg^-1）， a cuproptosis inhibitor （tetrathiomolybdate， TTM） group （10 mg·kg^-1）， and a methotrexate group （2 mg·kg^-1）， 10 rats in each group. Except for the control group， the model of rheumatoid arthritis （CIA） rats was established by type Ⅱ collagen induction method. After successful modeling， each drug group was intervened according to the corresponding dose of drugs， and the control group and the model group were given the same amount of normal saline by gavage， once a day， which lasted for 4 weeks. The swelling degree of rats' feet was observed， and the clinical arthritis scores were determined. The levels of serum rheumatoid factor （RF）， matrix metalloproteinase-3 （MMP-3）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， interleukin-10 （IL-10）， and ceruloplasmin （Cp） were detected by enzyme-linked immunosorbent assay （ELISA）. The content of copper ion （Cu）， malondialdehyde （MDA）， superoxide dismutase （SOD）， and glutathione （GSH） in joint tissue was detected. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of joint tissue. The levels of reactive oxygen species （ROS） and dihydrolipoic acid transacetylase （DLAT） were detected by immunofluorescence （IF）. The protein and mRNA expression of SLC31A1， FDX1， lipoic acid synthase （LIAS）， heat shock protein 70 （HSP70）， pyruvate dehydrogenase E1 subunit β （PDHB）， and copper transporting P-type ATPase β （ATP7B） was detected by immunohistochemistry （IHC） and real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared to the control group， the model group exhibited joint swelling and deformity， significantly increased clinical arthritis scores， obvious bone destruction， synovial hyperplasia， and inflammatory cell infiltration in joint tissue. In addition， the serum levels of RF， MMP-3， TNF-α， IL-1β， and Cp showed significant elevation， while the level of IL-10 was significantly reduced. The levels of Cu， MDA， ROS， and DLAT in joint tissue were markedly increased， whereas SOD and GSH content was significantly decreased. The protein and mRNA expression of SLC31A1 and HSP70 was significantly up-regulated， while the protein and mRNA expression of FDX1， LIAS， PDHB， and ATP7B was significantly down-regulated （P<0.01）. Compared to the model group， each treatment group exhibited varying degrees of improvement in joint swelling and deformation as well as clinical arthritis scores in rats. Additionally， there was a reduction in joint bone destruction， inflammatory cell infiltration， and synovial hyperplasia in rats. Furthermore， the serum levels of RF， MMP-3， TNF-α， IL-1β， and Cp significantly decreased， while the level of IL-10 increased significantly. In joint tissue， the levels of Cu， MDA， ROS， and DLAT showed significant decreases， while SOD and GSH content exhibited significant increases. The protein and mRNA expression of SLC31A1 and HSP70 was down-regulated， while the protein and mRNA expression of FDX1， LIAS， PDHB， and ATP7B was up-regulated （P<0.05）. ConclusionQuercetin effectively reduces synovial hyperplasia and inflammatory infiltration in rats with rheumatoid arthritis， thereby alleviating pathological damage to joint tissue. This effect may be attributed to the blockade of the SLC31A1/FDX1 signaling pathway activation and inhibition of excessive cuproptosis.