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 investigate the application value of flexible traction suspension (FTS) strategy in pure single-incision laparoscopic distal gastrectomy (PSILDG).Methods:The retrospective and descriptive study was conducted. The clinicopathological data of 12 patients who underwent PSILDG in The Second Affiliated Hospital of Army Medical University from November 2021 to March 2024 were collected. There were 8 males and 4 females, aged (53±14)years. Observation indicators: (1) intraoperative conditions; (2) postoperative conditions; (3) follow-up. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absolute numbers. Results:(1) Intraoperative conditions. All 12 patients underwent PSILDG with FTS strategy successfully, with the operation time of (260±31) minutes, the volume of intraoperative blood loss of 103.3(37.5,150.0)mL, the length of surgical incision of (3.9±0.6)cm. There was no intra-operative special circumstance or complication. (2) Postoperative conditions. Results of histopatho-logical examination showed that among the 12 patients, there were 10 cases of adenocarcinoma, 1 case of signet ring cell carcinoma, and 1 case of high-grade intraepithelial neoplasia. The distance of the proximal tumor margin was 2.8(2.0,3.4)cm, the distance of distal margin was 5.9(5.0,7.5)cm, the tumor diameter was (2.3±1.0)cm, and the number of lymph node dissected was 34±10. On the post-operative first day, all 12 patients had a visual analog score of 1.0. The time to postoperative removal of gastric tube was 1.25(1.00,1.75)days, the time to postoperative first intake of liquid food was 2.00(1.00,2.00)days, the time to postoperative first out-of-bed activity was 1.67(1.00,2.00)days, the time to postoperative first flatus was 2.40(2.00,3.00)days, the time to postoperative first bowel movement was 3.50(2.00,5.00)days, the duration of postoperative hospital stay was (7.10±1.40) days, and the satisfaction score for the abdominal wall incision was 20.6±2.7. No patient experien-ced postopera-tive complications. (3) Follow-up. All 12 patients completed a 30-day follow-up after surgery, with no complication or need for secondary surgery.Conclusion:Application of FTS strategy in PSILDG is safe and feasible.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Background and Aims:Acute pancreatitis(AP)is an acute inflammatory disease of the pancreas caused by abnormal activation of pancreatic enzymes.Although gallstones,hyperlipidemia,and alcohol use are the most common causes,a subset of patients develop AP secondary to rare etiologies that are often misdiagnosed or diagnosed late,leading to recurrence or inappropriate management.This study aims to summarize the clinical characteristics,diagnostic strategies,and treatment outcomes of four cases of AP caused by uncommon etiologies,supported by a literature review.Methods:Clinical data of 4 patients admitted to the Department of Hepatobiliary and Pancreatic Surgery,the Third Xiangya Hospital of Central South University,between November 2021 and September 2024,were retrospectively analyzed.Their etiological characteristics,diagnostic approaches,and treatment strategies were reviewed in combination with relevant literature.Results:The underlying causes of AP were intraductal papillary mucinous neoplasm,pancreatic neuroendocrine tumor,pancreatic ductal adenocarcinoma,and duodenojejunal intussusception.All cases initially presented as idiopathic AP.Three patients underwent definitive surgical treatment and recovered well,while one patient with pancreatic cancer received only palliative care due to delayed diagnosis and died three months later.Conclusion:AP secondary to rare etiologies often mimics common forms in clinical presentation but poses diagnostic challenges.For patients with recurrent or idiopathic AP,clinicians should emphasize etiological tracing and utilize advanced imaging and endoscopic modalities for early identification.Timely etiological intervention,particularly surgical management when appropriate,is essential for preventing recurrence and improving prognosis.

Objective:To correlate the expression of interleukin-6 (IL-6), CD40 ligand (CD40L), and soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) with regulatory T lymphocyte (Treg)/helper T lymphocyte 17 (Th17) in children with immune thrombocytopenic purpura (ITP) and to assess their combined diagnostic value.Methods:A retrospective study was conducted involving 80 children with ITP (ITP group) and 80 healthy children undergoing routine health screenings (control group) at Jinhua Central Hospital from February 2023 to February 2024. The levels of IL-6, CD40L, and sTREM-1, along with the Treg/Th17 ratio, were compared between the two groups and among children with different degrees of ITP severity. The correlations between IL-6, CD40L, and sTREM-1 and the severity of ITP, as well as the Treg/Th17 ratio were analyzed. Additionally, the diagnostic value of the combined tests was evaluated.Results:The levels of IL-6, CD40L, and sTREM-1 in the ITP group were (46.53 ± 8.69) ng/L, (6.51 ± 1.51), and (18.76 ± 3.72) ng/L, respectively. These values in the ITP group were significantly higher than those in the control group [(11.72 ± 1.58) ng/L, (4.31 ± 1.25), (8.07 ± 1.34) ng/L, t = 35.25, 10.04, 24.18, all P < 0.001]. The Treg/Th17 ratio in the ITP group was (1.34 ± 0.41), which was significantly lower than that in the control group [(13.56 ± 2.87), t = 37.70, P < 0.001]. In children with severe ITP, the levels of IL-6, CD40L, and sTREM-1 were (56.39 ± 11.70) ng/L, (9.62 ± 1.78), and (24.72 ± 4.81) ng/L, respectively. For those with moderate ITP, the levels were (45.41 ± 8.27) ng/L, (6.38 ± 1.40), and (17.69 ± 3.56) ng/L, respectively. In children with mild ITP, the levels were (37.04 ± 6.32) ng/L, (5.11 ± 1.32), and (14.50 ± 3.04) ng/L. The Treg/Th17 ratio in children with mild ITP was (0.95 ± 0.26), which was significantly lower than that in the moderate (1.37 ± 0.40) and severe (2.88 ± 0.56) groups. All differences were statistically significant among the three groups ( F = 23.98, 42.57, 37.15, 122.23, all P < 0.001). The levels of IL-6, CD40L, and sTREM-1 were positively correlated with the severity of ITP ( r = 0.565, 0.542, 0.538) and negatively correlated with the Treg/Th17 ratio ( r = -0.572, -0.536, -0.532), with all correlations being statistically significant (all P < 0.001). The receiver operating characteristic curve analysis indicated that the area under the curve values for the individual diagnoses of IL-6, CD40L, and sTREM-1 were 0.779, 0.750, and 0.763, respectively. In contrast, the area under the curve value for the combined diagnosis was 0.951, which was greater than that for each individual marker ( Z = 1.924, 2.137, 2.015, P = 0.037, 0.026, 0.031). Conclusions:The levels of IL-6, CD40L, and sTREM-1 in children with ITP are substantially correlated with the severity of ITP and the Treg/Th17 ratio, demonstrating notable diagnostic efficacy for ITP. Notably, the combination of IL-6, CD40L, and sTREM-1 greatly enhances diagnostic value.

Aim To investigate the anti-Zika virus(ZIKV)mechanism of diterpenoid compound 9 from Euphorbia helioscopia in vitro.Methods The cytotox-icity of compound 9 was evaluated using the CCK-8 as-say.A ZIKV-infected Vero cell model was established,and the antiviral activity was assessed through RT-qPCR,plaque assay,Western blot,and immunofluores-cence.Furthermore,the mechanism of action was elu-cidated using multi-cell line validation,nanoparticle tracking analysis,cellular thermal shift assay,and mo-lecular docking.Results In Vero cells,compound 9 exhibited an EC50 of(3.95±0.15)μmol·L-1 and a CC50 of(272.12±8.56)μmol·L-1,demonstrating significantly higher antiviral efficacy than the positive control drug ribavirin(RBV).Its virus inactivation effect was time-dependent and could significantly re-duce viral load and plaque formation.Studies revealed that compound 9 altered the physicochemical properties of ZIKV particles,including reducing surface charge and increasing particle size distribution.Additionally,it significantly enhanced the thermal stability of the prM protein.Molecular docking analysis indicated that compound 9 formed a high-affinity interaction with the prM protein(binding energy:-38.52 kJ·mol-1)and stabilized its structure through hydrophobic interac-tions.Conclusion Compound 9 exerts in vitro anti-ZIKV activity by directly inactivating the virus,disrup-ting viral particle integrity,and targeting the prM pro-tein.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective:To study echinococcosis in the population and canine Echinococcus infection in Yushu City, Qinghai Province, and to explore the current epidemic situation and main transmission species of Echinococcus. Methods:In June 2023, a multi-stage sampling method was used to select 2 villages each in Shanglaxiu Township and Longbao Town, Yushu City, Qinghai Province. Each village included at least 100 permanent residents who had lived locally for at least 1 year and were 2 years old or older as the survey subjects. Enzyme-linked immunosorbent assay (ELISA) was used to detect serum antibodies against Echinococcus larvae in the population, and B-mode ultrasound was used for abdominal organ scanning. Meanwhile, on the main roads of Shanglaxiu Township and Longbao Town, canine feces were collected in designated areas at intervals. ELISA was used to detect the antigen of canine fecal Echinococcus, and PCR was used to detect the types of parasites ( Echinococcus multilocularis, Echinococcus granulosus and Echinococcus shiquicus). Results:A total of 511 residents were investigated in Yushu City, and the positive rate of serum Echinococcus larvae antibodies in the population was 26.22% (134/511), and the detection rate of echinococcosis B-mode ultrasound was 1.37% (7/511). Among them, the detection rates of B-mode ultrasound for cystic echinococcosis (CE) and alveolar echinococcosis (AE) were 1.17% (6/511) and 0.20% (1/511), respectively. The positive rate of Echinococcus antigen in 543 canine feces detected by ELISA was 12.89% (70/543). PCR was used to test 497 canine feces, and the detection rate of Echinococcus was 3.02% (15/497). Among them, the detection rate of Echinococcus multilocularis was higher than that of Echinococcus granulosus [2.82% (14/497) vs 0.20% (1/497)], and the difference was statistically significant (χ 2 = 11.44, P < 0.001). No Echinococcus shiquicus was detected. Conclusions:The positive rates of Echinococcus larvae antibodies in the population and canine Echinococcus antigen in Yushu City, Qinghai Province are both relatively high. There is a mixed epidemic of CE and AE, with Echinococcus multilocularis being the main species.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.