ObjectiveTo establish an animal model of atrial fibrillation（AF） that accurately reflects the phlegm-heat and blood stasis（TRYZ） pathogenesis in traditional Chinese medicine. MethodsForty SPF-grade SD rats were randomly assigned using a random number table to the following groups：the control group， the TRYZ+AF group，the AF group and the TRYZ group， with ten rats in each group. The TRYZ+AF and TRYZ groups underwent a high-fat diet combined with intraperitoneal lipopolysaccharide（LPS） injection to simulate the pathological alterations of TRYZ syndrome. Groups TRYZ+AF and AF were induced with acetylcholine-calcium chloride（Ach-CaCl₂） via caudal vein injection to induce AF. The control group received no intervention and was maintained under normal conditions. The modeling period lasted 3 weeks. Electrocardiography was used to assess AF episodes and duration， echocardiography evaluated left atrial dimensions and cardiac function， fully automated biochemical analyzer measured the levels of total cholesterol（TC）， triglycerides（TG）， high-density lipoprotein cholesterol（HDL-C） and low-density lipoprotein cholesterol（LDL-C）， hemoreometer analyzed the whole blood viscosity， plasma viscosity， and whole blood reduced viscosity， a coagulation analyzer assessed prothrombin time（PT）， activated partial thromboplastin time（APTT）， thrombin time（TT）， and fibrinogen（FIB）， enzyme-linked immunosorbent assay（ELISA） was used to determine the levels of C-reactive protein（CRP）， interleukin（IL）-1β， IL-6， IL-17， tumour necrosis factor（TNF）-α， matrix metalloproteinase-9（MMP-9）， galectin-3（Gal-3）， Collagen Ⅰ， and α-smooth muscle actin（α-SMA）. Hematoxylin-eosin（HE） staining and Masson's trichrome staining were used to analyze pathological changes in atrial myocardium， Western blot was employed to detect MMP-9， Collagen Ⅰ and α-SMA protein expression in myocardial tissue， real-time quantitative polymerase chain reaction（Real-time PCR） evaluated fibrous factor gene expression levels. Changes in the TRYZ syndrome were assessed via body weight， tongue color［red（R）， green（G）， and blue（B）］， and rectal temperature. Ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was employed to detect differential metabolites between the control group and the TRYZ+AF group. ResultsFollowing three weeks of sustained modeling， compared with the control group， rats in the TRYZ+AF and the TRYZ groups exhibited reduced body weight， dry faeces， elevated rectal temperature， dark red tongue， decreased RGB values on the tongue surface， and markedly elevated TC and LDL-C levels（P<0.05， P<0.01）. The TRYZ+AF， TRYZ， and AF groups exhibited significantly decreased TT， APTT and PT， along with markedly elevated whole blood viscosity and FIB（P<0.05， P<0.01）. Rats in the TRYZ+AF and AF groups exhibited AF rhythm， markedly decreased heart rate， prolonged RR intervals， enlarged left atrium， and significantly reduced ejection fraction and shortening fraction（P<0.05， P<0.01）. Serum levels of CRP， IL-1β， IL-6， IL-17， TNF-α， MMP-9， Gal-3， Collagen Ⅰ， and α-SMA were elevated in rats from the TRYZ+AF， TRYZ， and AF groups compared to the control group， with the most pronounced increase observed in the TRYZ+AF group（P<0.05， P<0.01）. Histopathology revealed that the collagen fiber deposition in the atrial of rats in the TRYZ+AF， TRYZ and AF groups was higher than that in the control group（P<0.05， P<0.01）. Western blot and Real-time PCR results further demonstrated that the protein and mRNA expression levels of MMP-9， Collagen Ⅰ and α-SMA in the myocardial tissue of the TRYZ+AF group were higher than those in the other three groups（P<0.05， P<0.01）. Metabolomic analysis revealed 173 differentially expressed metabolites in the TRYZ+AF group and the control group， primarily enriched in pathways such as glycerophospholipid metabolism and glycolysis/gluconeogenesis. ConclusionThis study successfully establishes a rat model of AF integrated with the TRYZ syndrome， demonstrating the pathological process where the interactions of phlegm， heat and stasis jointly trigger tremor， this provides a reliable experimental tool for in-depth research into the biological basis of this disease syndrome.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

Triptolide （TP）， the core active component of the traditional Chinese medicine Tripterygium wilfordii ， exhibits remarkable pharmacological activities including anti-inflammatory， immunosuppressive and anti-tumor effects， and holds broad application prospects in the treatment of major diseases such as autoimmune diseases and malignant tumors. However， TP has a narrow therapeutic window and causes multi-organ toxicities including liver， kidney and reproductive toxicities， which severely restrict its safe clinical application and new drug development. Therefore， toxicity reduction and efficacy enhancement has become a core scientific problem urgently to be solved in this field. This paper systematically reviews the four core strategies for TP toxicity reduction and efficacy enhancement， including structural modification， dosage form improvement， herbal compatibility， and external therapies of traditional Chinese medicine. Among them， structural modification optimizes the toxic and efficacy characteristics of TP from the molecular structure level， with typica l derivatives including （5 R ）-5-hydroxy triptolide， ZT01， PG490-88， etc. Dosage form modification achieves toxicity reduction and efficacy enhancement via targeted and sustained-controlled drug release of diverse delivery systems. It includes triptolide preparations such as nanoparticles， liposomes， microemulsion gels and liquid crystals， possessing favorable clinical transformation potential. The herbal compatibility and external therapies of traditional Chinese medicine conform to the holistic view of traditional Chinese medicine and have a profound clinical application foundation， but their mechanisms of action are insufficiently elucidated， and they lack unified standardized specifications and high-quality evidence-based proof. In the future， we should rely on multi-omics technology to elucidate the toxic and efficacy mechanisms， integrate technologies to optimize preparations， improve the evaluation system and promote clinical transformation.

Objective To investigate the effects and molecular mechanisms of regenerating islet-derived 3-Alpha(REG3A)on the proliferation,apoptosis and cisplatin(DDP)resistance of ovarian cancer(OC)cells.Methods Cancer tissue and adjacent tissue samples of 97 ovarian cancer patients admitted to Qinghai Fifth People's Hospital from January 2021 to December 2022 were collected.Quantitative reverse transcriptase-mediated PCR(qRT-PCR)and immunohis to chemistry(IHC)were used to detect the expression of REG3A in cancer tissues and adjacent tissues,and the relationship between its expression and the clinical pathological characteristics and prognosis of patients was analyzed.QRT-PCR was used to detect the expression of REG3A in human normal ovarian epithelial cell line OSE and human OC cell lines(ES2,HEY,A2780,and SKOV3).SKOV3 and DDP resistant OC cell lines(SKOV3/DDP)were selected and randomly divided into siNC group and siREG3A group.Cell counting kit-8(CCK-8)was used to detect cell proliferation activity.Determination of cell drug resistance by methylthiazolyl tetrazolium(MTT).Flow cytometry was used to detect proliferation cycle and apoptosis.Immunoblotting was used to detect the expression of resistance,proliferation,apoptosis and phsphatidylinostol 3-kinase(PI3K)/protein kinase B(Akt)pathway related proteins in OC cells.Results The expression of REG3A mRNA in ovarian cancer tissues was higher than that in adjacent tissues(1.46±0.43 vs 0.52±0.11),and the difference was statistically significant(t=20.858,P<0.001).The 5-year survival rate of patients with high expression of REG3A was 24.49%(12/49),which was lower than the 91.67%(44/48)of patients with low expression of REG3A,and the difference was statistically significant(χ2=44.841,P<0.001).The proportion of patients with FIGO stages III-IV,moderate to high differentiation and tumor size>3cm in the high expression group of REG3A was higher than that in the low expression group of REG3A,and the differences were statistically significant(χ2=4.537～9.972,all P<0.05).Compared with OSE,the mRNA and protein expression of REG3A in ES2,HKY,A2780 and SKOV3 increased significantly(t=6.725～30.234,all P<0.01).Compared with the siNC group,the expression of REG3A was downregulated in SKOV3 cells in the siREG3A group(0.23±0.02 vs 0.99±0.06),cell activity decreased at 24,48 and 72 hours of transfection,the proportion of G1 phase cells increased,while the proportion of S and G2 phase cells and apoptosis rate,MDR-1,Cyclin D1 and Cleaved caspase 3 protein expression,p-PI3K/PI3K and p-Akt/Akt ratios were decreased,and the differences were statistically significant(t=6.584～22.730,all P<0.01).After treatment with DDP at concentrations of 1.25,2.5,5,7.5 and 15 μg/ml,compared with the siNC group,the survival rates of SKOV3 and SKOV3/DDP cells in the siREG3A group gradually decreased,and the differences were statistically significant(t=2.888～11.135,all P<0.05).Conclusion REG3A is highly expressed in OC tissues and is associated with malignant progression and poor prognosis of OC.Its up-regulation promotes cancer cell proliferation and DDP resistance by activating the PI3K/Akt pathway,and inhibits apoptosis.

Aim To clarify the mechanism by which Qishen Yixin Granules improved microcirculation vas-cular endothelial dysfunction(VED)in mice,through activating the Nrf2/HO-1 signaling pathway to regulate oxidative stress.Methods C57 mice were randomly divided into six groups:blank group,model group,pos-itive drug group,and low-,medium-,and high-dose groups of Qishen Yixin Granules.The VED model was established by long-term infusion of Ang Ⅱ combined with a high-fat diet.Each treatment group received the corresponding drug intervention.After four weeks of drug intervention,cardiac function was assessed by echocardiography.Carstairs staining was used to ob-serve the formation of microthrombi in myocardial tis-sue.The micro vascular ischemia was evaluated by Hei-denhain staining.The ultrastructure of endothelial cells was observed by electron microscopy.The levels of EMPs,ROS,NO,ET-1,TF,TM,VWF,and TXA2 in serum were measured by ELISA.The expression levels of MDA,SOD,and GSH-Px in mouse heart tissue were determined by chemical methods.Cardiac microvascu-lar density and the expression of Nrf2,Keap1,and HO-1 proteins were detected by Immunohistochemical stai-ning.The protein expressions of Keap1,cytoplasmic Nrf2,nuclear Nrf2,and HO-1 in myocardial tissue were detected by Western blot.Results Qishen Yixin Granules could effectively improve the cardiac function of mice,alleviate the damage of endothelial cells and endothelial function.They could up-regulate serum NO levels and the activities of antioxidant enzymes SOD and GSH-Px,while down-regulating the expression of ROS and vascular inflammatory injury factors such as ET-1,VWF,TXA2,TF,TM,and EMPs.Qishen Yixin Granules also increased the positive counts of CD34,Nrf2,and HO-1,as well as microvessel density.Fur-thermore,they inhibited the expression of MDA,Keap1,and cytoplasmic Nrf2 protein in myocardial tis-sue,while increasing the expression of nuclear proteins HO-1 and Nrf2.Conclusions Qishen Yixin Granules may inhibit oxidative stress and inflammatory response by regulating the Nrf2/HO-1 signaling pathway,thereby improving vascular endothelial damage and cardiac function in VED mice.

As the incidence of diabetes in China continues to rise,its complications pose a serious threat to the life health of patients.New hypoglyce-mic agents are constantly emerging,with particular attention being paid to glucagon-like peptide-1 re-ceptor agonists(GLP-1RA)and sodium-glucose co-transporter 2 inhibitor(SGLT2i),which can not only effectively control blood glucose levels,but also sig-nificantly improve the cardiac and renal outcomes of diabetic patients.New technologies for diabetes management based on artificial intelligence(AI)are also developing rapidly,playing a crucial role in the diagnosis of diabetic retinopathy(DR)and insu-lin dose-assisted decision-making.Continuous glu-cose monitoring(CGM)and automated insulin de-livery system(AID)have already been used clinical-ly.This article reviews the progress in drug therapy and new technologies for type 2 diabetes mellitus T2DM,aiming to provide guidance for the treat-ment of T2DM patients.

Objective:To investigate the current status of treatment delay and analyze its influencing factors in patients with breast cancer-related lymphedema.Methods:Using convenience sampling, 218 patients with breast cancer-related lymphedema from The First Affiliated Hospital of Zhengzhou University between April 2024 and January 2025 were enrolled. The General Information Questionnaire, Lymphedema Self-Management Support Scale for Breast Cancer Survivors (LSMS-BCs), Brief Illness Perception Questionnaire for Breast Cancer-related Lymphedema (BIPQ-BCRL), Perceived Barriers to Health Care-Seeking Decision-Chinese (PBHSD-C), and Health Literacy Scale for Chronic Patients (HLSCP) were used to conduct a cross-sectional survey. Logistic regression identified predictors of treatment delay, with model fit assessed by the Hosmer-Lemeshow test. Discriminative ability was evaluated using receiver operating characteristic (ROC) curve analysis.Results:The study included 218 female BCRL patients, aged (58.31 ± 10.54) years. Among 218 patients, 76 experienced treatment delay, the incidence of treatment delay was 34.8% (76/218). Independent risk factors included junior high school education or below, no regular arm circumference measurement, low self-management support scores, low illness perception scores, high perceived barriers to healthcare-seeking scores, and low health literacy scores (Wald χ2 values were 7.75-15.15, all P<0.05). The Hosmer-Lemeshow test indicated good model fit ( χ2=6.21, P>0.05). The combined predictive model demonstrated significantly better discrimination than individual factors, the area under the curve of ROC was 0.846 ( P<0.01). Conclusions:The incidence of treatment delay is relatively high among breast cancer-related lymphedema patients. Nursing staff should pay special attention to patients with a junior high school education or below, no regular arm circumference measurement, low LSMS-BCs scores, low BIPQ-BCRL scores, high PBHSD-C scores and low HLSCP scores, implement timely interventions to reduce treatment delay in lymphedema patients.

Objective:To conduct a systematic review and Meta-analysis of unavoidable pressure injuries (uPI) to provide evidence-based guidance for establishing standardized intervention protocols.Methods:Cross-sectional and cohort studies on uPI were systematically retrieved from PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and China Biology Medicine disc databases up to February 5, 2024. Two researchers independently screened the literature, extracted data, and assessed the risk of bias in the included studies. Meta-analysis was performed using R4.3.2 software.Results:A total of 9 studies involving 10 research items were included. The Meta-analysis showed that the proportion of uPI was 42.92%. Subgroup analysis revealed that the proportions of uPI in acute care hospitals, intensive care units, and long-term care facilities were 53.14%, 33.56%, and 40.97%, respectively. The proportions in North America and Europe were 40.26% and 44.99%, respectively. The proportions of uPI in studies published between 2010-2015, 2016-2020, and 2021-2024 were 63.25%, 37.00%, and 40.61%, respectively. The proportions of uPI assessed using the Pressure Ulcer Prevention Inventory, National Pressure Ulcer Advisory Panel definition, empirical judgment, NHS definition, and end-stage pressure injury definition were 40.38%, 26.17%, 40.00%, 62.07%, and 51.32%, respectively.Conclusions:The incidence of uPI is high, with significant differences across healthcare settings, continents, years, and assessment criteria. A universal definition of uPI should be established, along with unified assessment standards, to optimize uPI care strategies and provide references for standardized prevention and intervention.

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.