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 systematically evaluate the published models in prediction of the risk of lung infections in elderly patients with hip fracture so as to provide a guidance for medical workers in selection or development of suitable risk prediction models.Methods Relevant studies were searched from databases including CNKI,Wanfang Data,VIP,SinoMed,PubMed,Web of Science,Cochrane Library,Embase and CINAHL,from the inception to 31st January,2024.Data were extracted from the selected literature and a bias assessment tool of risk predictive model was used to evaluate the risk of bias and applicability of the included literature.Results A total of 1,035 articles were retrieved,of which seven studies involving 13 predictive models were finally included after screening.The sample sizes ranged from 305 to 2,669 cases and lung infection rates ranged from 5.40%to 20.02%.The repeatedly reported predictors included age,gender,chronic obstructive pulmonary disease,hypoproteinaemia,American Society of Anesthesiologists(ASA)Physical Status Classification and white blood cell count.In the 13 models constructed,the reported area under the curve(AUC)of subjects'job characteristics ranged from 0.667 to 0.996.Five out of seven studies had good overall applicability,but all with high risk of bias.Conclusion The predictive models for lung infections in elderly patients with hip fracture are still in the stage of development.Although the predictive models show some predictive performance,however they are still deficient,and all studies have been found with a high risk in bias.

Objective To explore the distribution characteristics and development trend of TCM prevention and treatment for irritable bowel syndrome(IBS)by analyzing the clinical trials of TCM prevention and treatment for IBS registered in China Clinical Trial Registry(ChiCTR).Methods The ChiCTR database was retrieved to collect and organize clinical trials related to the TCM prevention and treatment of IBS from the establishment of the database to May 1,2024.Characteristics of the included trials were analyzed and summarized using SPSS 25.0 and Excel 2021.Results A total of 73 clinical trials were included,of which 65 were pre-registered.The registered research projects involved 14 provincial-level administrative regions,including Beijing,Jiangsu,Guangdong,Shanghai,and Sichuan,and 46 clinical trial institutions,among which Beijing University of Chinese Medicine(6 items,7.89%)registered a higher number.The top three sources of research funding were,in order,local finance(26 items,35.62%),state finance(20 items,27.40%),and hospital funding(10 items,13.70%).The types of studies were predominantly interventional(68 items,93.15%),and the study designs were predominantly randomized parallel controlled studies(64 items,87.67%),but only 27 studies(36.99%)used a blinded approach.The main interventions included acupuncture and moxibustion,Chinese patent medicines,classic prescriptions/hospital-prepared remedies,etc.Conclusion The number of clinical research registrations in this field has been gradually increasing in recent years,but there are problems such as uneven regional distribution,low use of blinding,and lack of standardization of registration information.

Objective To analyze the clinical trial projects of TCM treatment for psoriasis registered at the China Clinical Trial Registry(ChiCTR);To provide references for clinical research in this field.Methods Clinical trial studies on the TCM treatment for psoriasis were retrieved from the ChiCTR database from the establishment of the database to June 17,2024.Excel 2019 and GraphPad Prism 9.0 were used to organize and analyze the general characteristics included in registered clinical trials.Results Totally 65 TCM-related trials were included,of which 58(89.23%)were prospectively registered,and 55(84.62%)had undergone ethical review.The majority of trials were registered in Guangdong,Beijing and Shanghai,collectively accounting for 78.46%(n=51)of the total.The leading institution,Guangdong Provincial Hospital of Chinese Medicine,contributed 19 trials.Funding was predominantly sourced from governmental bodies,with 72.31%(n=47)supported by national or regional grants.Among the registered studies,interventional trials predominated(n=56),including 46 randomised parallel-controlled designs.Blinding was implemented in 23 trials,and biospecimen collection was reported in 48 studies.40 trials were single-centre studies,and a cumulative sample size was 17 695 participants.Common interventions included oral administration of classical TCM formulations or hospital-prepared remedies,alongside topical applications such as medicated baths and ointments.The primary outcome measure in most trials was the Psoriasis Area and Severity Index.Conclusion While the number of registered clinical trials on TCM for psoriasis in China demonstrates a fluctuating yet upward trend,the overall volume remains modest.Disparities in regional distribution,methodological variability,and incomplete trial registration details highlight areas for improvement.

Type Ⅳ cardiorenal syndrome(CRS)is a subtype of CRS characterized by cardiac structural damage and/or functional decline secondary to chronic kidney disease.Clinically,it often manifests as fatigue,shortness of breath,edema,oliguria,and difficulty lying flat at night,which align with the TCM pattern of"deficiency of primordial qi and excess of yin-pathogenic fire".Li Dongyuan proposed the theory that"yin-pathogenic fire and primordial qi are opposites",emphasizing the dynamic relationship of"mutual growth and decline"between primordial qi and yin fire.From this perspective,the development and progression of Type Ⅳ CRS are believed to correspond to the fluctuations in the balance of primordial qi and yin-pathogenic fire.Based on this theory,the core pathogenesis of Type Ⅳ CRS is summarized as"imbalance between qi and fire",where"deficiency of primordial qi"is the root cause,often attributed to damage to the heart,spleen,and kidney,while"exuberance of yin-pathogenic fire"represents the pathological manifestation.In clinical practice,the treatment should focus on reinforcing primordial qi and subduing yin-pathogenic fire,with tailored approaches according to the stages of disease progression.In the early stage,when primordial qi lacks a foundation for generation and yin-pathogenic fire begins to emerge,the treatment should aim to consolidate the root of primordial qi and suppress the budding of yin-pathogenic fire.In the middle stage,when primordial qi is insufficiently produced and yin-pathogenic fire becomes predominant,the treatment should focus on nourishing the source of primordial qi and curbing the exuberance of yin-pathogenic fire.In the late stage,when primordial qi becomes dispersed and yin-pathogenic fire is unconstrained,the treatment should prioritize consolidating the foundation of primordial qi and restraining the chaotic movement of yin-pathogenic fire.

Objective To investigate the role of matrix GLA protein(MGP)in the pathogenesis of idiopathic calcium oxalate kidney stones(ICOS),and to find potential biomarkers for early diagnosis and disease evaluation.Methods A total of 120 patients admitted to our hospital from September 2021 to September 2023 were prospectively included,of which 60 patients with ICOS were in the calculus group and 60 patients without calculus were in the control group.Serum biochemical indexes and immunohistochemical scores of the two groups were detected,urinary MGP levels were determined by ELISA,and MGP mRNA and protein expression in renal papilla tissues were detected by qPCR and Western blot.The independent risk factors of ICOS were screened by Logistic regression analysis,and the prediction model was drawn by nomogram.Results Compared with control group,urinary MGP content in calculus group was decreased[(1 805.91±244.44)pg/ml vs.(2 014.79±252.14)pg/mnl,P＜0.05).Expression of MGP mRNA and MGP protein in renal papillae decreased(0.89±0.15 vs.1.00±0.00,P=0.001)and decreased(0.87±0.18 vs.1.00±0.00,P＜0.05).MGP immunohistochemical scores of renal tissue were decreased[4(2-6)scores vs.6(4-8)scores,P＜0.001].Multivariate analysis showed that urinary calcium(OR=1.370),urinary MGP(OR=1.127),renal papilla MGP relative expression level(OR=27.532)and renal tissue MGP immunohistochemical score(OR=1.359)were independent risk factors for ICOS.Area under ROC curve of the nomogram prediction model built based on the above factors is 0.839,indicating that the model has good differentiation ability in risk prediction.Conclusion MGP is closely related to the pathogenesis of ICOS.Urinary and renal tissue MGP levels may be potential biomarkers for early diagnosis and disease assessment of ICOS.

Objective To explore the relationship between the degree of compression and shape grading of the cerebral cistern ambiens in hypertensive cerebral hemorrhage(HCH)patients after neural endoscopic intracranial hematoma evacuation(NEIHE)and prognosis.Methods 246 HCH patients who underwent NEIHE surgery from January 2020 to June 2023 were selected as the research subjects.According to the postoperative 6 month Glasgow outcome score(GOS),the patients were divided into good prognosis group(n=158)and poor prognosis group(n=88).Hierarchical regression model was used to analyze the relationship between clinical pathological features and the degree of compression and shape grading of the cerebral cistern ambiens.Multivariate logistic regression model was used to analyze the independent risk factors affecting the poor prognosis of patients with HCH after NEIHE,and a prediction model was constructed.Receiver operating characteristic curve(ROC curve)was drawn with poor prognosis as the outcome variable.Area under the curve(AUC),integrated discrimination improvement(IDI)and net reclassification improvement(NRI)of different prediction models were compared.Hosmer-Lemeshow was used to test the goodness of fit.Generalized additive model(GAM)was used to analyze the relationship between GOS and related factors.Results Compared with the good prognosis group,the poor prognosis group had more preoperative blood loss,lower preoperative Glasgow coma score(GCS),and higher proportion of patients with midline deviation,hypertension history ≥10 years,hemorrhage breaking into the brain ventricle,and operation time in the late stage,the differences were statistically significant(P＜0.05).Compared with the good prognosis group,the proportions of patients with ipsilateral and contralateral cerebral cistern ambiens compression of 3 to 4 points and the morphological classification of cerebral cistern ambiens of grade V in the poor prognosis group were higher,and the differences were statistically significant(P＜0.05).The location of bleeding,midline deviation,and intracranial pressure all had an impact on the degree of compression and morphological grading of the cerebral cistern ambiens,and the differences were statistically significant(P＜0.05).Multivariate Logistic regression analysis(model 2:including the degree of compression and shape grading of the cerebral cistern ambiens)showed that midline deviation,history of hypertension ≥10 years,preoperative bleeding volume＞37 mL,bleeding into the brain ventricles,preoperative GCS＜7 points,late surgical timing,degree of compression of the cerebral cistern ambiens(3 to 4 points on the same side of hematoma,3 to 4 points on the opposite side of hematoma),and grade V morphology were all risk factors influencing the poor prognosis of patients with HCH after NEIHE(P＜0.05).After incorporating the degree of compression and morphological grading of the cerebral cistern ambiens into model 1(excluding the degree of compression and shape grading of the cerebral cistern ambiens),the AUC increased to 0.812(95％CI:0.763～0.872),and both the IDI(0.081,95％CI:0.049～0.095)and NRI(0.611,95％CI:0.510～0.674)of the model improved,with statistically significant differences(P＜0.05).Compared with model 1,model 2 showed an increase in AUC(0.826,95％CI:0.771～0.863),IDI(0.085,95％CI:0.052～0.110),and NRI(0.628,95％CI:0.510～0.709),with statistically significant differences(P＜0.05).The Hosmer-Lemeshow test showed that model 2(P=0.878)had a better fit for predicting poor prognosis than model 1(P=0.691).GAM analysis showed that the higher the degree of compression and morphological grading of the cerebral cistern ambiens,the lower the GOS,and the difference was statistically significant(P＜0.05).ROC curve analysis showed that the combined application of degree of compression and morphological grading of the cerebral cistern ambiens had a high predictive value for poor prognosis,with AUC of 0.935(95％CI:0.890～0.971),sensitivity of 70.26％,and specificity of 93.84％.Conclusion The degree of compression and shape changes of the cerebral cistern ambiens in HCH patients after NEIHE are closely related to prognosis,and the combined application has certain predictive value for poor prognosis.The location of bleeding,midline deviation,intracranial pressure,and other factors significantly affect the compression degree and shape change of the cerebral cistern ambiens.

Objective:To investigate the effect of p38MAPK signaling pathway mediating progesterone regulation on IL-8 protein secretion by decidual stromal cells(DSCs)on early spontaneous miscarriage.Methods:IHC and Western blot were applied to detect protein expressions of p38MAPK and p-p38MAPK in decidual tissues of miscarriage group and control group.Human DSCs in early pregnancy were isolated in vitro and cultured to be treated with different concentrations of progesterone(0.01 μmol/L,0.1 μmol/L,1 μmol/L and 10 μmol/L),with ELISA measuring IL-8 protein secretion from DSCs and Western blot measuring protein expressions of p38MAPK and p-p38MAPK in DSCs.After treatment with p38MAPK inhibitor SB203580,IL-8 protein secretion was detected by ELISA in progesterone+inhibitor group,progesterone group and control group.Results:Protein expression of p-p38MAPK in decidual tissues of miscarriage group was significantly higher than that of control group(P=0.002 3).Protein secretion of IL-8 in DSCs of 0.01 μmol/L progesterone group was lower than that of control group(P=0.027 6),protein expression of p-p38MAPK in DSCs of 0.1 μmol/L proges-terone group was lower than that of control group(P=0.025 3),IL-8 protein expression was significantly lower than that in control group(P=0.007 0),and protein expressions of both IL-8 and p-p38MAPK from DSCs in 1 μmol/L and 10 μmol/L progesterone groups were significantly lower than those in control group(P=0.003 2,P=0.001 9;P=0.002 2,P=0.001 3).IL-8 protein secretion in proges-terone+p38MAPK inhibitor group was further reduced compared to progesterone group(P=0.046 6).Conclusion:Abnormal activation of p38MAPK signaling pathway is involved in early spontaneous miscarriage,and progesterone may down-regulate IL-8 expression in DSCs by inhibiting p38MAPK phosphorylation to correct early spontaneous miscarriage caused by Th1/Th2 cytokine imbalance.

Background and Aims:Extrahepatic cholangiocarcinoma(ECCA)is a malignancy with insidious onset,strong invasiveness,and poor prognosis,characterized by a high postoperative recurrence rate and a 5-year overall survival of less than 20％.Most existing prognostic models are based on the Cox proportional hazards model,which is limited by the proportional hazards assumption and linearity constraints.The random survival forest(RSF)model,a novel machine learning algorithm,can capture complex interactions and nonlinear effects among variables;however,its application in ECCA remains scarce.Therefore,this study developed a prognostic model for ECCA patients after radical resection using the RSF algorithm,aiming to provide precise and individualized prognostic assessments and support clinical decision-making.Methods:A total of 515 postoperative ECCA patients from the SEER database(2016-2021)were retrospectively enrolled and randomly divided into a training set(n=361)and a test set(n=154).Demographic and clinical variables were collected.Cox models were developed using univariate and multivariate regression,while RSF models were constructed using variable importance(VIMP)and minimal depth methods.Model performance was evaluated using the concordance index(C-index),time-dependent area under the curve(AUC),Brier scores,calibration plots,and decision curve analysis.Survival differences were assessed using Kaplan-Meier analysis,and interpretability was enhanced through the use of SurvSHAP and SurvLIME.Results:Multivariate Cox regression identified seven independent prognostic factors:age,race,income,T stage,N stage,tumor size,and chemotherapy.The RSF model selected four key predictors:age,tumor size,lymph node positive rate,and chemotherapy.In the test cohort,the RSF model achieved a C-index of 0.751,outperforming the Cox model(0.711).The RSF model yielded AUCs of 0.843,0.749,and 0.814 at 1,2,and 3 years,respectively,with superior calibration,overall performance,and net clinical benefit.Nonlinear associations were observed for lymph node positive rate,age,and tumor size,while chemotherapy was associated with reduced mortality risk.Stratified survival curves indicated poorer prognosis in patients without chemotherapy,lymph node positive rate＞0.1,age＞70 years,or tumor size＞20 mm.Conclusion:The RSF model,based on only four readily available clinical variables,demonstrated superior predictive performance compared with the Cox model.It provides a reliable tool for individualized prognosis and postoperative management in ECCA patients.The integration of interpretability frameworks further enhances its clinical applicability,offering potential to improve survival outcomes and quality of life.

Background and Aims:Extrahepatic cholangiocarcinoma(ECCA)is a malignancy with insidious onset,strong invasiveness,and poor prognosis,characterized by a high postoperative recurrence rate and a 5-year overall survival of less than 20％.Most existing prognostic models are based on the Cox proportional hazards model,which is limited by the proportional hazards assumption and linearity constraints.The random survival forest(RSF)model,a novel machine learning algorithm,can capture complex interactions and nonlinear effects among variables;however,its application in ECCA remains scarce.Therefore,this study developed a prognostic model for ECCA patients after radical resection using the RSF algorithm,aiming to provide precise and individualized prognostic assessments and support clinical decision-making.Methods:A total of 515 postoperative ECCA patients from the SEER database(2016-2021)were retrospectively enrolled and randomly divided into a training set(n=361)and a test set(n=154).Demographic and clinical variables were collected.Cox models were developed using univariate and multivariate regression,while RSF models were constructed using variable importance(VIMP)and minimal depth methods.Model performance was evaluated using the concordance index(C-index),time-dependent area under the curve(AUC),Brier scores,calibration plots,and decision curve analysis.Survival differences were assessed using Kaplan-Meier analysis,and interpretability was enhanced through the use of SurvSHAP and SurvLIME.Results:Multivariate Cox regression identified seven independent prognostic factors:age,race,income,T stage,N stage,tumor size,and chemotherapy.The RSF model selected four key predictors:age,tumor size,lymph node positive rate,and chemotherapy.In the test cohort,the RSF model achieved a C-index of 0.751,outperforming the Cox model(0.711).The RSF model yielded AUCs of 0.843,0.749,and 0.814 at 1,2,and 3 years,respectively,with superior calibration,overall performance,and net clinical benefit.Nonlinear associations were observed for lymph node positive rate,age,and tumor size,while chemotherapy was associated with reduced mortality risk.Stratified survival curves indicated poorer prognosis in patients without chemotherapy,lymph node positive rate＞0.1,age＞70 years,or tumor size＞20 mm.Conclusion:The RSF model,based on only four readily available clinical variables,demonstrated superior predictive performance compared with the Cox model.It provides a reliable tool for individualized prognosis and postoperative management in ECCA patients.The integration of interpretability frameworks further enhances its clinical applicability,offering potential to improve survival outcomes and quality of life.