Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

OBJECTIVE To systematically evaluate the effects of supplementation with different doses of vitamin D on maternal and infant outcomes in vitamin D-deficient pregnant women. METHODS Related literature on the effects of supplementing different doses of vitamin D on maternal and infant outcomes was searched in databases including CNKI， Wanfang Data， VIP， PubMed， Medline， the Cochrane Library， Embase from their inception to June 30， 2025. The risk of bias assessment tool from the Cochrane Handbook 5.1 was used to evaluate the quality of included literature. Meta-analysis of outcome indicators was performed by using RevMan 5.4 software. RESULTS A total of 15 studies were included， involving 4 664 patients [2 129 in the experimental group （daily dose ＞2 000 IU）， 2 058 in control group 1 （daily dose ≤1 000 IU） and 477 in control group 2 （daily dose ＞1 000-≤2 000 IU） ] . Meta-analysis results showed that the incidence of preeclampsia （PE） [OR＝0.71， 95%CI （0.53， 0.96）， P ＝0.03 ] ， gestational diabetes mellitus （GDM） [OR＝0.60， 95%CI （0.43， 0.84）， P ＝0.003 ] ， low birth weight of newborn [OR＝0.72， 95%CI （0.53， 0.97）， P ＝0.03 ] and macrosomia [OR＝0.53， 95%CI （0.29， 0.98）， P ＝0.04 ] in the experimental group were significant lower than control group 1； but there was no significant difference in the incidence of premature delivery [OR＝0.86， 95%CI （0.65， 1.13）， P ＝0.28 ] ， cesarean delivery [OR＝0.92， 95%CI （0.74， 1.15）， P ＝0.48 ] or stillbirth rate [OR＝0.77， 95%CI （0.48， 1.24）， P ＝0.29 ] . The incidence of low birth weight of ne wborn [OR＝0.64， 95%CI （0.41， 0.98）， P ＝0.04 ] in the experimental group was significant lower than control group 2； but there was no significant difference in the incidence of PE [OR＝0.61， 95%CI （0.25， 1.49）， P ＝0.28 ] ， the incidence of GDM [OR＝0.73， 95%CI （0.42， 1.24）， P ＝0.24 ] ， premature delivery rate [OR＝0.90， 95%CI （0.59， 1.39）， P ＝0.63 ] ， cesarean delivery rate [OR＝0.92， 95%CI （0.64， 1.33）， P ＝0.66 ] ， or stillbirth rate [OR＝0.68， 95%CI （0.24， 1.94）， P ＝0.48 ] . CONCLUSIONS Different doses of vitamin D supplementation in early pregnancy have a significant impact on maternal and infant pregnancy outcomes in vitamin D-deficient pregnant women； daily doses ＞2 000 IU have significant advantages in reducing the incidence of PE and GDM and improving the outcome of premature delivery.

Objective To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

OBJECTIVE To investigate the clinical characteristics of euglycemic diabetic ketoacidosis （euDKA） induced by empagliflozin， and provide references for safe medication. METHODS Case reports of euDKA induced by empagliflozin were retrieved and analyzed from PubMed， Web of Science， CNKI， and Wanfang Data. The Naranjo’s scale was adopted to assess the causal relationship between empagliflozin and euDKA. RESULTS A total of 29 patients were enrolled， including 16 males and 13 females，with a median age of 58 years. All patients were diagnosed with type 2 diabetes mellitus； 22 patients had at least one comorbidity. The median time to euDKA onset was 60 days after administration， and 7 cases occurred within 2 weeks of treatment. Perioperative periods，fasting，and low-carbohydrate or ketogenic diets were the main predisposing factors. Common presentations included nausea，vomiting， fatigue， tachypnea，and tachycardia. The causal relationship between empagliflozin and euDKA was assessed as “probable” in all cases. According to adverse reaction severity grading， 13 cases were grade 3 （severe） and 16 cases were grade 4 （life-threatening）. All patients discontinued empagliflozin and recovered after corresponding treatment. CONCLUSIONS euDKA is a serious adverse reaction to empagliflozin， which mostly occurs early in treatment. Perioperative periods， fasting， and ketogenic diets are prone to induce euDKA. Elderly patients and those with comorbidities are at higher risk. Risk assessment should be conducted before clinical administration； blood ketones and acid-base monitoring should be strengthened in the early medication period； withhold the drug before elective surgery， avoid prolonged fasting；upon diagnosis， discontinue empagliflozin and initiate intravenous insulin， provide fluid resuscitation promptly， and use other treatments to improve patient prognosis.

ObjectiveTo investigate the protective effect of magnolol ester derivative YW against cisplatin （Cis）-induced acute kidney injury （AKI） and to explore its effect and preliminary mechanisms on Cis-induced AKI. MethodsThe research group designed and synthesized the magnolol ester derivative YW using magnolol as the parent core. Molecular docking was employed to predict the binding interaction between YW and lysine acetyltransferase 7 （KAT7）. A Cis-induced AKI model was established in C57BL/6J mice. Mice were divided into the normal control group， model group， YW low/medium/high dose groups （17.5， 35， 70 mg/kg）， and the positive control amifostine group. Renal function was assessed by measuring serum creatinine （Scr） and blood urea nitrogen （BUN） levels. Pathological changes were evaluated via HE staining and scoring of kidney tissues. Protein expression levels of kidney injury molecule 1 （KIM-1）， lysine acetyltransferase 7 （KAT7）， and cyclin-dependent kinase inhibitor 1A （p21） in kidney tissues were detected by Western blot （WB）. HK-2 cells were treated with different concentrations of YW； cell viability was measured by CCK-8 assay. WB was used to detect the expression levels of the renal injury marker KIM-1， KAT7， and its downstream protein p21. Cellular senescence was assessed by senescence-associated β-galactosidase （SA-β-Gal） staining. ResultsYW could stably bind to KAT7. In vivo experiments showed that， compared with the model group， all YW dose groups， especially the medium and high doses， significantly reduced the elevated levels of Scr and BUN in AKI mice （P<0.001） and effectively ameliorated renal histopathological damage. YW significantly downregulated the protein expression levels of KIM-1， KAT7， and p21 in kidney tissues （P<0.05）. Concentrations of YW≤10 μmol/L had no significant effect on HK-2 cell viability. YW inhibited the Cis-induced decline in HK-2 cell viability （P<0.05）， suppressed the Cis-induced upregulation of KIM-1， KAT7， and p21 proteins （P<0.05）， and significantly decreased the percentage of SA-β-Gal-positive cells （P<0.01）. ConclusionYW suppresses the expression of KAT7 and p21 proteins and inhibits the decline in HK-2 cell viability in cisplatin-induced AKI， significantly mitigates HK-2 cell senescence， and improves renal function， providing preliminary experimental evidence for developing AKI treatment strategies based on structural optimization of natural products.

ObjectiveTo construct and validate a risk assessment model for post-transplant diabetes mellitus （PTDM） using multiple machine learning algorithms， and to realize the early identification of PTDM. MethodsA retrospective analysis was performed for the clinical data of the patients who underwent allogeneic liver transplantation in The First Hospital of Shanxi Medical University from April 1， 2020 to December 31， 2024， and they were randomly divided into a training set and a validation set at a ratio of 7∶3. The LASSO regression analysis combined with 5-fold cross-validation was used for feature selection. Seven machine learning models were developed in the training set， i.e.， logistic regression （LR）， decision tree （DT）， Naive Bayes （NB）， random forest （RF）， K-nearest neighbor （KNN）， extreme gradient boosting （XGBoost）， and adaptive boosting （AdaBoost）. In the validation set， various methods were used to assess the predictive performance of each model， such as accuracy， precision， recall rate， specificity， F1 score， area under the receiver operating characteristic curve （AUROC）， and area under the precision-recall curve （AUPRC）. The Brier score and decision curve analysis were used to assess the calibration and clinical practicability of the models， and the SHAP method was used to analyze feature importance. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsA total of 135 liver transplant recipients were enrolled， among whom 26 developed PTDM， and there were 94 patients in the training set and 41 in the validation set. Feature extraction and screening identified 7 key features of sex， overweight or obesity， anhepatic phase， time of operation， length of hospital stay， early postoperative hypomagnesemia， and impaired fasting glucose （IFG）. In the validation set， the XGBoost model showed the best predictive performance， with an AUROC of 0.907 （95% confidence interval ［CI］： 0.807 — 0.989）， an AUPRC of 0.649 （95%CI： 0.339 — 0.955）， an accuracy of 0.878， a precision of 0.667， a recall rate of 0.750， an F1-score of 0.706， a specificity of 0.909， and a Brier score of 0.104. The decision curve analysis showed that when the threshold probability was below 0.667， application of the XGBoost model in clinical decision-making provided relatively high net benefit. The SHAP analysis showed that the length of hospital stay ranked first in terms of feature importance， followed by time of operation， overweight or obesity， sex， IFG， anhepatic phase， and early postoperative hypomagnesemia. ConclusionThe risk assessment model for PTDM in liver transplant recipients based on XGBoost algorithm has excellent performance and can effectively identify high-risk individuals； however， multicenter large-sample data are needed for further validation.

Objectives:To explore the predictive value of residual Murray's law-based quantitative flow ratio(μQFR)on long-term vessel-oriented composite endpoints(VoCE).Methods:This retrospective study included 3 510 patients from the FAVOR Ⅲ China trial.Offline residual μQFR analysis was performed on all vessels(diameter≥2.5 mm)with 50%-90%stenotic lesions.Patients were stratified into high-,intermediate-,and low-risk groups based on residual μQFR tertiles.The primary endpoint was 3-year VoCE,defined as a composite of cardiac death related to the target vessel,target vessel-related spontaneous myocardial infarction,and ischemia-driven target vessel revascularization.Results:Offline analysis was performed on 5 256 vessels from 3 510 patients.The mean residual μQFR was 0.92±0.75.The high-risk group(residual μQFR≤0.91)with 1 554 patients(1 958 vessels);the intermediate-risk group(residual μQFR 0.92-0.96)with 1 211 patients(1 906 vessels);and the low-risk group(residual μQFR>0.96)with 745 patients(1 392 vessels).Over 3-year follow-up,VoCE occurred in 227 vessels(4.3%).The 3-year VoCE incidence was significantly higher in the high-risk group compared to the intermediate-and low-risk groups(6.2%vs.4.1%vs.2.5%,log-rank P<0.001),primarily driven by ischemia-driven target vessel revascularization(5.0%vs.3.0%vs.1.6%,log-rank P<0.001).Hypertension(OR=0.83,95%CI:0.72-0.96),hypercholesterolemia(OR=0.84,95%CI:0.73-0.97),bifurcation lesions(OR=0.72,95%CI:0.63-0.83),moderate/severe calcification(OR=0.70,95%CI:0.57-0.84),and tandem lesions(OR=0.59,95%CI:0.47-0.75)were independent predictors of lower residual μQFR values.Conclusions:Lower residual μQFR is significantly associated with increased VoCE risk during the 3-year follow up period.

Objective:To investigate the 10-year incidence of reproductive system malignancies and their associated risk factors among overweight and obese women with different metabolic phenotypes aged 40 years and older in Guiyang City.Methods:A total of 6 444 female residents in Yunyan District, Guiyang City were included from the 2011 " Epidemiological Study on the Risk of Malignancy in Chinese Patients with Type 2 Diabetes Mellitus(REACTION)". Based on body mass index(BMI) and the presence or absence of metabolic syndrome(MetS), participants were categorized into four groups: metabolically healthy normal weight(MHNW, n=2 373), metabolically unhealthy normal weight(MUNW, n=1 098), metabolically healthy overweight/obese(MHO, n=2 229), and metabolically unhealthy overweight/obese(MUO, n=744). Baseline data were collected, and participants were followed up for 10 years to document the incidence of female reproductive system malignancies, including breast cancer, ovarian cancer, cervical cancer, and endometrial cancer. Logistic regression models were used to evaluate the association between metabolic phenotype and the 10-year risk of developing reproductive system malignancies. Results:Over a mean follow-up period of (9.89±0.77) years, the overall incidence of reproductive system malignancies was 1.15%(74/6, 444). Baseline characteristics such as age, BMI, high-density lipoprotein-cholesterol(HDL-C), and triglycerides(TG) differed significantly among the groups( P<0.05). The cumulative incidence of reproductive system malignancies in each group was: MHNW 0.93%(22/2 373), MUNW 0.73%(8/1 098), MHO 1.57%(35/2 229), and MUO 1.21%(9/744). There were no statistically significant differences in incidence across the four groups( P>0.05). However, multivariable logistic regression analysis revealed that, compared with the MHNW group, the adjusted HR (95% CI) were: MUNW 0.787(0.349-1.774, P>0.05), MHO 4.835(1.708-13.688, P<0.05), and MUO 3.719(1.144-12.089, P<0.05). Conclusion:Overweight and obesity are significant risk factors for reproductive system malignancies in women aged 40 and above. The presence of metabolic abnormalities in overweight or obese women further increases the risk of developing such malignancies.

In proton therapy,prompt gamma-ray imaging is considered as one of the most promising methods for assessing proton beam range.Prompt gamma-ray imaging detector evaluates the proton beam range based on the prompt gamma-ray distribution obtained by the prompt gamma-ray imaging system,which enables high-precision measurement of the proton beam range.Herein a proton beam range verification algorithm is designed for the newly developed prototype of the range verification detector(pixelated prompt gamma-ray imaging detector),which verifies the range estimation accuracy of the prototype for different phantoms and different energies of homogeneous media through Monte Carlo simulation.The results show that the accuracy of the proton beam range verification algorithm is within 0.5 mm of the safety margin error of the Bragg peak,and the measurement accuracy is significantly improved with the increase of the number of protons,indicating that the prototype algorithm is feasible for proton beam range verification.

Objective To investigate the current status of family resilience of children with cancer and analyze its influencing factors,to provide a basis for medical staff to formulate intervention plans.Methods Using a convenient sampling method,children with cancer who were hospitalized in 2 tertiary hospitals in Henan Province from January to April 2024 were selected for the survey.A general information questionnaire,family resilience assessment scale,quality of life family version,ZBI caregiver burden interview,and social support rating scale were used to understand the current status of family resilience of children with cancer and to explore the related influencing factors by univariate analysis and multiple stepwise linear regression analysis.Results A total of 280 questionnaires were distributed and 265 valid questionnaires were recovered,with a valid questionnaire recovery rate of 94.64％.The total score of family resilience for primary caregivers of children with cancer was(185.63±30.66).The multiple stepwise linear regression analysis results showed that the children's self-care ability,caregiver's work status,family care burden,and social support level were the influencing factors for family resilience of children with cancer(P＜0.05),and the explanatory variance was 51.3％.Conclusion The family resilience of children with cancer is at a medium level.The worse the children's self-care ability and the heavier the family care burden,the worse the family resilience;the caregiver's work status and good social support are helpful for the family resilience of children with cancer.Healthcare workers should develop intervention programs to address these factors to enhance the family resilience of children with cancer.