To explore the clinical value of a multimodal predictive model based on multiparametric magnetic resonance imaging(MRI) radiomics combined with deep learning(DL) features for the preoperative noninvasive assessment of mismatch repair-deficient(MMRd) status in endometrial cancer(EC).

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.

Objective To elucidate the molecular mechanisms underlying the effects of Kanggan Mixture(KGM)on key targets in rats with acute lung injury,network pharmacology and in vivo micro-CT experiments were employed.Methods Network pharmacology was utilized to forecast the target genes and principal pathways involved in the intervention of KGM in acute lung injury(ALI).Lipopolysaccharide(LPS)-induced ALI rat models were utilized,and micro-computed tomography(micro-CT)was employed to evaluate the extent of lung injury in vivo.Experiments were conducted to verify the intervention mechanism of KGM on ALI rats.Results The findings revealed that 190 chemical constituents were identified from KGM,and 579 potential targets and 204 pathways associated with KGM's impact on ALI were predicted.The principal components of KGM,such as quercetin,luteolin,kaempferol,betulin,and lupenone,exhibit anti-viral,anti-inflammatory,and immunomodulatory properties by targeting TP53,AKT1,SRC,EP300,and STAT3,and modulating the FoxO signaling pathway,TNF signaling pathway,PI3K-Akt signaling pathway,and MAPK signaling pathway,demonstrating an influence on acute lung injury.Micro-CT results suggest that KGM can improve lung texture enhancement and lung injury in ALI rats,with an increase in end-expiratory lung volume(inspiratory phase-expiratory phase).The HE and W/D ratio results indicate that KGM can improve lung tissue injury and reduce the lung tissue wet/dry weight ratio(P<0.01).Blood cell analysis results show that the anti-inflammatory agent can decrease the WBC(white blood cell count)and N%(neutrophil percentage)in ALI rats'blood(P<0.01),and increase lymphocytes(P<0.05).Real-time quantitative PCR,WES,and immunohistochemistry results suggest that KGM can decrease the mRNA expression,protein distribution,and protein expression levels of TP53,AKT1,SRC,EP300,and STAT3 in lung tissue of ALI rats(P<0.05).Conclusion KGM has a certain intervention effect on acute lung injury,mainly achieved through the core targets STAT3,EP300,SRC,AKT1,and TP53.

Objective To explore the effects of Dushu pills on cognitive ability and mitochondrial dynamics related proteins in mouse model of Alzheimer's disease(AD)based on network pharmacology.Methods The corresponding targets of Dushu pills and its related targets with AD were predicted using TCMSP database.The intersection targets of Dushu pills and AD were obtained by Venny website.The protein interaction network and drug-disease-target network were mapped using String database and Cytoscape software,respectively.GO and KEGG enrichment analysis were performed for intersection targets using David database.The mouse model of AD was established by injecting Aβ25-35 into bilateral ventricles.The learning and memory ability of the mice was detected by behavioral tests,the mitochondrial damage of neurons in the hippocampus was observed by transmission electron microscopy,and the expression of proteins related to mitochondrial dynamics was detected by Western blot.Results A total of 311 intersection targets related to drugs and diseases were screened out from the database.GO and KEGG analysis showed that the relevant targets were concentrated in mitochondria and other components,and concentrated in the pathways of ATP binding and positive regulation of MAPK activity.Compared with the normal group,the learning and memory ability of the model group was decreased(P<0.05),mitochondrial ridges appeared swelling and fracture(P<0.0001),decreased expression of MAPK,Mfn2 and OPA1 proteins in hippocampus(P<0.01),the expression of DRP1 protein increased(P<0.01).Compared with the model group,the learning and memory ability of mice in the medium and high dose groups of Dushu pills was improved(P<0.05),mitochondrial damage was significantly improved(P<0.01),increased expression of MAPK,Mfn2 and OPA1 in the hippocampus(P<0.01),DRP1 protein expression decreased(P<0.01).Conclusion Dushu pills can reduce mitochondrial damage,maintain mitochondrial homeostasis,and improve the cognitive and memory ability of AD mice.

Objective:To investigate the influence of genetic and environmental factors on the clinical characteristics of upper urinary tract calculi in pediatric patients.Methods:This study was a retrospective case series. The clinical data of 179 children under the age of 14 with upper urinary tract calculi treated at Beijing Friendship Hospital，Capital Medical University，from August 2014 to February 2023 were analyzed. There were 121 males（67.60%）and 58 females（32.40%），with a median age at onset of 2.10（1.14，5.17）years. Thirty-three cases（18.44%）had a family history of urinary stone disease. Stone characteristics was defined by CT，with a median stone burden（sum of the diameters of all stones）of 1.3（1.00，1.60）cm. Fifty-four（30.17%）children had staghorn calculi. Multiple stones were present in 92 cases（51.40%），and bilateral stones in 52 cases（29.05%），with hydronephrosis was present in 119 children（66.48%）. The median follow-up time was 67 months，and 36 children（20.11%）experienced stone recurrence. Dietary habits and related information were collected by electronic questionnaire，including a total of 115 children（64.25%）with an unbalanced diet，101（56.42%）with insufficient water intake，and 32 children（17.88%）with a preference for a high-protein diet. Tap water was used as the source of drinking water by 128 patients（71.51%），and 107（59.78%）took dietary supplements. Whole-exome sequencing revealed that 55 children（30.73%）carried pathogenic mutations in stone-related genes. Binary logistic regression was used for univariate analysis of above risk factors. Variables with P < 0.1 in univariate analysis and without multicollinearity were included in multivariate logistic regression to further screen for independent risk factors. Results:Multivariate analysis confirmed that carrying stone-related pathogenic gene mutations（ OR = 3.06，95% CI 1.25?7.45， P = 0.014）and insufficient water intake（ OR = 3.28，95% CI 1.14?9.47， P = 0.028）were independent risk factors for higher stone burden. A high-protein diet（ OR = 2.40，95% CI 1.03?5.63， P = 0.044），carrying stone-related pathogenic gene mutations（ OR = 4.57，95% CI 2.21?9.46， P<0.01），and a family history of stones（ OR = 3.18，95% CI 1.28 ~ 7.91， P = 0.013）were independent risk factors for staghorn calculi. Multiple stones were closely associated with a family history of stones（ OR = 2.66，95% CI 1.15-6.17， P = 0.022）and carrying stone-related pathogenic gene mutations（ OR = 3.22，95% CI 1.60-6.48， P = 0.001）. Moreover，carrying stone-related pathogenic gene mutations（ OR = 5.19，95% CI 2.52?13.82， P < 0.01）were an independent risk factor for stone recurrence，whereas dietary supplement intake was a protective factor（ OR = 0.26，95% CI 0.11?0.62， P = 0.002）. Conclusions:Genetic and environmental factors play significant roles in the occurrence and development of pediatric upper urinary tract stones. A high-protein diet as well as a positive family history of stones are independent risk factors for staghorn calculi，and insufficient water intake is a critical environmental factor for stone formation，while appropriate use of dietary supplements may help reduce the risk of stone recurrence. Genetic testing indicates that approximately 30% of children carry stone-related pathogenic gene mutations，and these patients prone to severe stone and an increased risk of recurrence.

Objective To elucidate the molecular mechanisms underlying the effects of Kanggan Mixture(KGM)on key targets in rats with acute lung injury,network pharmacology and in vivo micro-CT experiments were employed.Methods Network pharmacology was utilized to forecast the target genes and principal pathways involved in the intervention of KGM in acute lung injury(ALI).Lipopolysaccharide(LPS)-induced ALI rat models were utilized,and micro-computed tomography(micro-CT)was employed to evaluate the extent of lung injury in vivo.Experiments were conducted to verify the intervention mechanism of KGM on ALI rats.Results The findings revealed that 190 chemical constituents were identified from KGM,and 579 potential targets and 204 pathways associated with KGM's impact on ALI were predicted.The principal components of KGM,such as quercetin,luteolin,kaempferol,betulin,and lupenone,exhibit anti-viral,anti-inflammatory,and immunomodulatory properties by targeting TP53,AKT1,SRC,EP300,and STAT3,and modulating the FoxO signaling pathway,TNF signaling pathway,PI3K-Akt signaling pathway,and MAPK signaling pathway,demonstrating an influence on acute lung injury.Micro-CT results suggest that KGM can improve lung texture enhancement and lung injury in ALI rats,with an increase in end-expiratory lung volume(inspiratory phase-expiratory phase).The HE and W/D ratio results indicate that KGM can improve lung tissue injury and reduce the lung tissue wet/dry weight ratio(P<0.01).Blood cell analysis results show that the anti-inflammatory agent can decrease the WBC(white blood cell count)and N%(neutrophil percentage)in ALI rats'blood(P<0.01),and increase lymphocytes(P<0.05).Real-time quantitative PCR,WES,and immunohistochemistry results suggest that KGM can decrease the mRNA expression,protein distribution,and protein expression levels of TP53,AKT1,SRC,EP300,and STAT3 in lung tissue of ALI rats(P<0.05).Conclusion KGM has a certain intervention effect on acute lung injury,mainly achieved through the core targets STAT3,EP300,SRC,AKT1,and TP53.

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.

Chronic myeloid leukemia (CML) is a malignant hematologic disorder caused by abnormal proliferation of hematopoietic stem cells. In recent years, while the application of tyrosine kinase inhibitors (TKIs) has significantly improved the prognosis of CML patients through in-depth exploration of pathogenesis of CML and advancements in targeted therapies, some patients still face challenges including drug resistance, disease relapse, and failure to achieve treatment-free remission. Imunotherapy, as a complementary or alternative strategy, holds significant potential for overcoming these limitations, and has gradually emerged as a critical research focus in CML treatment. This review aims to summarize the current research status and latest advances in immunotherapy for CML.

Objective: To develop a rapid quantification method for neutrophil extracellular traps (NETs) by quantifying neutrophils forming NETs (NETotic cells) on routine peripheral blood smears, and to evaluate the performance of an early warning model combining NETs with traditional coagulation indicators for risk of sepsis-induced coagulopathy (SIC) in septic patients. Methods: This prospective observational study was conducted in Wuxi People's Hospital Affiliated with Nanjing Medical University between May 2023 and May 2025. A total of 147 patients with sepsis (diagnosed based on Sepsis-3.0 criteria) who had not developed SIC [the international society on thrombosis and haemostasis (ISTH SIC score <4)] were enrolled. Blood samples were collected within 2 hours of admission. Neutrophil smudge cells (NETs%) were counted using an automated cell morphology analyzer. Serum levels of myeloperoxidase-DNA (MPO-DNA) complexes, circulating free DNA (cf-DNA) and sequential organ failure assessment (SOFA) scores were also determined. Based on progression to SIC (ISTH score ≥4) within 72 hours of admission, patients were categorized into a sepsis without SIC group (n=85) and a sepsis with SIC group (n=62). Risk factors were analyzed using binary logistic regression, receiver operating characteristic (ROC) curves were plotted, and the predictive value of NETs%, SOFA, and AT-Ⅲ for coagulation dysfunction was assessed. Results: The NETs% level was significantly higher in the sepsis with SIC group [8.50% (7.00, 11.50)] compared to both the healthy control group [1.00% (0.00, 2.00)] and sepsis without SIC group [4.40%(3.50, 6.50)] (P<0.01). NETs% was identified as an independent risk factor for SIC in sepsis patients. ROC analysis showed that the area under the curve (AUC) for predicting SIC was 0.90 for NETs%, 0.85 for MPO-DNA, and 0.79 for cf-DNA. The combined model of NETs% and SOFA score demonstrated the best performance, with an optimal cut-off value of 0.33, an AUC of 0.92, a sensitivity of 77%, and a specificity of 93%. Conclusion: NETs% shows promise as a novel biomarker for SIC. Peripheral blood smear morphology provides a simple, rapid, and cost-effective method for quantifying NETs%. NETs% enhances the early clinical identification of patients at high risk for SIC, and its combination with the SOFA score facilitates SIC prediction, offering a critical time window for initiating timely preventive interventions.

Objective To investigate the correlations of the expression levels of serum silencing in-formation regulatory factor 2-related enzyme 1(SIRT1),endothelial cell-specific molecule-1(ESM-1),and fibroblast growth factor-21(FGF21)with therapeutic outcome in patients with sepsis-related acute respiratory distress syndrome(ARDS).Methods A total of 140 patients with sepsis-related ARDS were selected and divided into good outcome group(n=96)and poor outcome group(n=44)accord-ing to the therapeutic outcome.The levels of serum SIRT1,ESM-1 and FGF21 were compared between the two groups,and the correlations of serum SIRT1,ESM-1 and FGF21 with the severity of the dis-ease and therapeutic outcome were analyzed.The predictive values of serum SIRT1,ESM-1 and FGF21 for therapeutic outcome were evaluated.Results The serum SIRT1 level in the poor outcome group was significantly lower,while the levels of ESM-1 and FGF21 were significantly higher than those in the good outcome group(P＜0.05).The serum SIRT1 level showed a significant gradual downward trend in mild,moderate,and severe patients,while the ESM-1 and FGF21 levels showed a significant gradual upward trend in mild,moderate,and severe patients(P＜0.05).Spearman corre-lation analysis showed that serum SIRT1 was significantly negatively correlated with disease severity,while ESM-1 and FGF21 were significantly positively correlated with disease severity(P＜0.05).Partial correlation analysis showed that serum SIRT1,ESM-1 and FGF21 were significantly correla-ted with the therapeutic outcome of ARDS patients with sepsis(P＜0.05).The receiver operating characteristic(ROC)curve showed that the area under the curve(AUC)of serum SIRT1,ESM-1 and FGF21 for predicting the treatment outcome of sepsis-related ARDS patients was 0.742,0.838 and 0.796 respectively,with sensitivities of 77.27％,77.27％and 70.45％,and specificities of 64.58％,81.25％and 87.50％.The AUC of the combination of three indexes for predicting the therapeutic outcome of sepsis-related ARDS patients was 0.939,with a sensitivity of 88.64％and a specificity of 83.33％,which was significantly higher than the predictive value of the three indexes alone(P＜0.05).Conclusion The levels of SIRT1,ESM-1 and FGF21 in the serum of sepsis-re-lated ARDS patients are significantly correlated with the severity of the disease and the therapeutic outcome,and have the abilitis to independently predict the therapeutic outcome.The combined pre-dictive value is even higher.