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.

Objective:To investigate the effect of ribonucleotide reductase regulatory subunit M2 (RRM2) on the malignant biological behavior and aerobic glycolysis of gastric cancer cells by regulating cyclin-dependent kinase (CDK) 1.Methods:Human gastric cancer MKN-45 cells were divided into si-NC group (transfected with blank fragment) , CoCl 2+si-NC group (hypoxia control transfected with blank fragment) , CoCl 2+si-RRM2 group (hypoxia with RRM2 silencing) , CoCl 2+si-RRM2+pcDNA3.1 NC group (hypoxia with RRM2 silencing and blank vector) and CoCl 2+si-RRM2+pcDNA3.1 CDK1 group (hypoxia with RRM2 silencing and CDK1 overexpression) . The mRNA relative expression levels of RRM2 and CDK1 were analyzed by real time fluorescent quantitative reverse transcription PCR. Co-immunoprecipitation (CoIP) was used to analyze the interaction between RRM2 and CDK1 protein. MTT assay was used to analyze the proliferation activity of cells. The cell migration distance was detected by cell scratch assay. Cell apoptosis was detected by flow cytometry. Adenosine triphosphate (ATP) and glucose kit were used to detect ATP production and glucose consumption. The protein expressions of ENO1, RRM2, HK2, PKM2, GLUT1 and p-CDK1/CDK1 were detected by Western blotting. Results:Real time fluorescent quantitative reverse transcription PCR results showed that the relative expression levels of CDK1 mRNA in si-NC group, CoCl 2+si-NC group and CoCl 2+si-RRM2 group were 1.01±0.15, 1.30±0.06 and 0.51±0.18, and the relative expression levels of RRM2 mRNA were 1.03±0.32, 1.59±0.28 and 0.44±0.17, respectively, and there were statistically significant differences ( F=25.52, P=0.001; F=14.47, P=0.005) . The mRNA expressions of RRM2 and CDK1 in CoCl 2+si-NC group were higher than those in si-NC group. Compared with the si-NC group and the CoCl 2+si-NC group, the mRNA expressions of RRM2 and CDK1 were lower in the CoCl 2+si-RRM2 group (all P<0.05) . CoIP results showed that there was interaction between RRM2 and CDK1. MTT assay, cell scratch assay and flow cytometry showed that the cell proliferation activity of si-NC group, CoCl 2+si-NC group, CoCl 2+si-RRM2 group, CoCl 2+si-RRM2+pcDNA3.1 NC group and CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were 1.04±0.01, 1.18±0.04, 0.84±0.03, 0.81±0.03 and 0.93±0.05, respectively. The cell migration distances were (301.83±2.75) , (369.67±0.76) , (176.50±6.38) , (175.83±3.69) , (254.17±1.61) μm, respectively. The apoptosis rates were 8.05%±0.21%, 5.75%± 0.20%, 28.28%±0.04%, 30.18%±1.51% and 17.79%±0.22%, respectively, all with statistically significant differences ( F=73.82, P<0.001; F=1 600.01, P<0.001; F=787.15, P<0.001) . Compared with the si-NC group and CoCl 2+si-NC group, the proliferation and migration ability of cells in the CoCl 2+si-RRM2 group, CoCl 2+si-RRM2+pcDNA3.1 NC group and CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were weaker, and the apoptosis rates were higher (all P<0.05) . Compared with the CoCl 2+si-RRM2+pcDNA3.1 NC group, the proliferation and migration ability of cells in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were stronger, and the apoptosis rate was lower (all P<0.05) . The results of ATP and glucose detection showed that there were statistically significant differences in the amount of ATP production and glucose consumption among the above five groups ( F=12.53, P<0.001; F=19.21, P<0.001) . Compared with the si-NC group, the glucose consumption of cells was lower in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group ( P<0.05) . Compared with the CoCl 2+si-NC group, the ATP production and glucose consumption of cells in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were lower (both P<0.05) . Compared with the CoCl 2+si-RRM2+pcDNA3.1 NC group, the ATP production and glucose consumption of the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were higher (both P<0.05) . Western blotting showed that there were statistically significant differences in the protein expressions of ENO1, RRM2, HK2, PKM2, GLUT1, and p-CDK1/CDK1 among the above five groups (all P<0.001) . Compared with the si-NC group and the CoCl 2+si-NC group, the protein expressions of ENO1, RRM2, HK2, PKM2, GLUT1 and p-CDK1/CDK1 in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were lower (all P<0.05) . Compared with the CoCl 2+si-RRM2+pcDNA3.1 NC group, the protein expressions of ENO1, RRM2, PKM2, GLUT1 and p-CDK1/CDK1 in the CoCl 2+si-RRM2+pcDNA3.1 CDK1 group were higher (all P<0.05) . Conclusions:Silencing RRM2 can inhibit the malignant biological behavior of gastric cancer cells and the occurrence of aerobic glycolysis by regulating CDK1.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.

Immunoglobulin A nephropathy （IgAN） is a common primary glomerular disease and a frequent cause of chronic renal failure. Tripterygium wilfordii is a traditional Chinese herbal medicine， which possesses the effects of promoting blood circulation， relieving swelling and pain， and dispelling wind and dampness. Modern pharmacological studies have shown that T. wilfordii multiglucoside exhibit anti-inflammatory and immunomodulatory effects， inhibit mesangial cell proliferation， protect podocytes， ameliorate endothelial cell injury， and regulate gut microbiota disturbances. Triptolide also possesses anti-inflammatory and immunomodulatory properties， suppresses mesangial cell proliferation， and protects podocytes. Celastrol demonstrates anti- inflammatory and immunomodulatory functions as well as the ability to improve endothelial cell damage. Through these mechanisms， T. wilfordii and its active components can play a role in alleviating clinical symptoms and delaying disease progression in the treatment of IgAN. Future research should focus on in-depth analysis and mechanistic investigation of these active ingredients， promote high-quality clinical studies， systematically evaluate the synergistic effects among them， and emphasize strategies for reducing toxicity and enhancing efficacy， thereby providing more comprehensive and reliable evidence-based foundations for the clinical treatment of IgAN.

Objective To analyze the current status of clinical trial registration in the TCM treatment of diabetic nephropathy(DN);To provide references for the registration and implementation of relevant clinical trials.Methods Clinical trials about TCM treatment for DN registered in the Chinese Clinical Trial Registry(ChiCTR)and the U.S.Clinical Trial Registry(ClinicalTrials.gov)from their inception to August 18,2024 were retrieved.The following information was analyzed:registration year,geographical distribution,funding sources,TCM syndrome patterns of participants,number of research centers,sample size,study type,study design,randomization method,blinding method,intervention measures,outcome indicators and safety indicators.Results A total of 88 clinical trials were included,comprising 79 interventional studies and 9 observational studies.The number of registrations has increased annually.The domestic registered trials were distributed across 17 provincial-level administrative regions in China,with Beijing and Shanghai having the highest number of registrations.The primary sources of funding were local and national government funds.The most common TCM syndrome pattern among participants was qi-yin deficiency with blood stasis.Most trials were single-center studies,with the majority having a sample size between 31 and 60.The predominant study type was interventional,mostly randomized controlled trials(RCTs),with simple randomization being the most frequently used method.31 trials reported blinding methods,with double-blinding being the most common.The intervention measures were mostly oral Chinese patent medicines or TCM compounds,and the outcome indicators were mainly efficacy indicators,with less safety indicators.Conclusion The number of registered clinical trials on TCM treatment for DN has increased annually;however,the overall number remains limited.There is uneven regional distribution and incomplete registration information for various factors such as randomization methods,blinding methods,number of research centers,intervention measures,and outcome indicators.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.

Objective To analyze the current status of clinical trial registration in the TCM treatment of diabetic nephropathy(DN);To provide references for the registration and implementation of relevant clinical trials.Methods Clinical trials about TCM treatment for DN registered in the Chinese Clinical Trial Registry(ChiCTR)and the U.S.Clinical Trial Registry(ClinicalTrials.gov)from their inception to August 18,2024 were retrieved.The following information was analyzed:registration year,geographical distribution,funding sources,TCM syndrome patterns of participants,number of research centers,sample size,study type,study design,randomization method,blinding method,intervention measures,outcome indicators and safety indicators.Results A total of 88 clinical trials were included,comprising 79 interventional studies and 9 observational studies.The number of registrations has increased annually.The domestic registered trials were distributed across 17 provincial-level administrative regions in China,with Beijing and Shanghai having the highest number of registrations.The primary sources of funding were local and national government funds.The most common TCM syndrome pattern among participants was qi-yin deficiency with blood stasis.Most trials were single-center studies,with the majority having a sample size between 31 and 60.The predominant study type was interventional,mostly randomized controlled trials(RCTs),with simple randomization being the most frequently used method.31 trials reported blinding methods,with double-blinding being the most common.The intervention measures were mostly oral Chinese patent medicines or TCM compounds,and the outcome indicators were mainly efficacy indicators,with less safety indicators.Conclusion The number of registered clinical trials on TCM treatment for DN has increased annually;however,the overall number remains limited.There is uneven regional distribution and incomplete registration information for various factors such as randomization methods,blinding methods,number of research centers,intervention measures,and outcome indicators.

OBJECTIVE To evaluate the efficacy and safety of rituximab （RTX） in the treatment of children with refractory nephrotic syndrome （RNS） based on the real world by meta-analysis. METHODS A systematic search was conducted on CNKI， Wanfang， VIP， PubMed， Embase， Web of Science， the Cochrane Library， and CINAHL databases to strictly screen the literature and evaluate their quality. A meta-analysis was performed on the extracted literature data using R 4.2.2 and RStudio software. RESULTS A total of 26 real-world studies were included in this study， involving 996 children with steroid-dependent nephrotic syndrome/frequente-relapse nephrotic syndrome （SDNS/FRNS） and 205 children with steroid-resistant nephrotic syndrome （SRNS）. The results of the meta-analysis showed that the complete remission （CR） rate of RTX treatment for RNS was 46% （95%CI： 37%-56%）， the partial remission （PR） rate was 22% （95%CI： 14%-31%）， and the discontinuation rate was 35% （95%CI： 25%-44%）. The results of subgroup analysis showed that the CR rate of RTX treatment in SDNS/FRNS children was 49% （95%CI： 37%-62%）， PR rate was 25% （95%CI： 0-50%）， discontinuation rate was 41% （95%CI： 29%-52%）； the CR rate in SRNS children was 42% （95%CI： 27%-56%）， PR rate was 22%（95%CI： 12%-32%）， discontinuation rate was 21% （95%CI： 4%-38%）. The recurrence rate in children with SDNS/FRNS was 39% （95%CI： 21%-57%） within 1 year or less， 18% （95%CI： 18%-98%） in 2 years and more. As for safety， the majority of adverse reactions were mild infusion reactions， with an incidence of 13% （95%CI： 8%-22%）. Sensitivity analysis suggested that the results were robust. There was publication bias in mild infusion 20210908-BZ-CACM） reaction rate. CONCLUSIONS RTX is effective and safe in the treatment of RNS in children.

Objective:To explore the mechanism of Eucommiae Cortex- Epimedii Folium herbal pair in the treatment of osteoporosis through network pharmacology, molecular docking, and molecular dynamics methods. Methods:Search the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and relevant literature to screen the active compounds of Eucommiae Cortex- Epimedii Folium herbal pair. Using TargetNet, SwissTargetPrediction, and STITCH databases to predict the target of active compounds. GeneCards, OMIM, TTD and DisGeNET databases were used to screen the related targets of osteoporosis, and the intersection targets were obtained by Venny 2.1.0 online tool. Using STRING database for protein-protein interaction (PPI) network analysis. Construct a network diagram using Cytoscape 3.8.2 software and perform network feature analysis to determine key targets and core compounds. Using R 3.6.3 software for gene ontology (GO) functional annotation and Kyoto Encyclopedia of genes and genomes (KEGG) signaling pathway analysis. Apply SYBYL-X 2.1.1 software to perform molecular docking between core compounds and key targets, and use GROMACS 2021.6 software for molecular dynamics simulation. Results:Totally 47 active compounds, 329 targets related to compounds, 4 604 targets related to osteoporosis, and 210 intersecting targets of Eucommiae Cortex- Epimedii Folium herbal pair were selected. Network feature analysis showed that luteolin, quercetin, kaempferol, caffeic acid, chryseriol, and pinoresinol were core compounds, while protein kinase B1(Akt1), interleukin-6 (IL-6), steroid receptor coactivator (Src), cysteinyl aspartate specific proteinase-3 (CASP3), epidermal growth factor receptor (EGFR), estrogen receptor 1 (ESR1), prostaglandin-endoperoxide synthase 2 (PTGS2), mitogen-activated protein kinase 8 (MAPK8), and JUN were key targets. GO analysis showed that biological process (BP) mainly involve cellular hormone metabolism, intracellular receptor signaling pathways, oxidative stress responses, hormone metabolism processes, etc. Cell component (CC) mainly involved membrane rafts, membrane microregions, membrane regions, transcription factor complexes, etc. Molecular function (MF) mainly involved nuclear receptor activity, transcription factor activity, steroid hormone receptors, hormone binding, etc. KEGG analysis showed that the signaling pathways of Eucommiae Cortex- Epimedii Folium herbal pair in the treatment of osteoporosis mainly included osteoclast differentiation, PI3K-Akt signaling pathway, and MAPK signaling pathway. Molecular docking showed that the core compounds could accurately bind to the active sites of key target proteins, and molecular dynamics analysis further verified the binding stability between the core compounds and key target proteins. Conclusions:The combination of Eucommiae Cortex- Epimedii Folium herbal pair has the characteristics of multiple components, targets, and pathways in the treatment of osteoporosis, laying a theoretical foundation for its clinical use.

BACKGROUND: One of the most important treatment modalities for non-small cell lung cancer (NSCLC) is immune checkpoint inhibitor. Nevertheless, a small percentage of patients do not respond well to these therapies, highlighting the significance of identifying important CD8+ T cell subsets for immunotherapy and creating trustworthy biomarkers. The purpose of this study is to assess the potential utility of TIM3+CD8+ T cells as new biomarkers by examining their expressions in various areas of the NSCLC tumor microenvironment. METHODS: Based on biopsy techniques, tumor tissue samples were obtained from patients with NSCLC and categorized into tumor central and non-central regions. Using flow cytometry, the infiltration of TIM3+CD8+ T cells and the surface expression of programmed cell death 1 (PD-1) on these cells were examined, and their correlations with the effectiveness of immunotherapy were assessed. RESULTS: The non-central region of tumor tissues had considerably larger infiltration of TIM3+CD8+ T lymphocytes compared to the non-central region (P<0.0001). This pattern was found in both subgroups with tumor diameters ≥3 cm or <3 cm (P<0.01). In comparison to TIM3-CD8+ T cells, TIM3+CD8+ T cells showed higher levels of PD-1 (P<0.001), with more PD-1+TIM3+CD8+ T cells invading the non-central region (P<0.01). Clinical responders to immunotherapy had considerably lower infiltration levels of TIM3+CD8+ T cells in the tumor non-central region compared to non-responders, with lower levels correlated with better clinical outcomes (P<0.01), while no correlation was identified in the tumor central region (P>0.05). According to reciever operating characteristic (ROC) curve analysis, TIM3+CD8+ T cells in the tumor non-central region had an area under the curve (AUC) of 0.9375 for predicting the effectiveness of immunotherapy, which was considerably higher than that of TIM3+CD8+ T cells in the tumor central region and programmed cell death ligand 1 (PD-L1) [tumor proportion score (TPS)]. CONCLUSIONS In the tumor microenvironment of NSCLC, TIM3+CD8+ T cells show regional distribution patterns. The expression of this cell population in the non-central region of the tumor microenvironment may be a biomarker for predicting the effectiveness of immunotherapy.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Lung Neoplasms/metabolism* ; Hepatitis A Virus Cellular Receptor 2/immunology* ; Tumor Microenvironment/immunology* ; CD8-Positive T-Lymphocytes/metabolism* ; Male ; Female ; Middle Aged ; Aged ; Adult ; Programmed Cell Death 1 Receptor/metabolism* ; Immunotherapy ; Clinical Relevance