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.

Rice (Oryza sativa L.) is an important food crop. The appearance of lesion mimics in rice leads to phytohormone disorders, which affects rice adaptation to environmental stresses and ultimately reduces the yield and quality. To explore whether the changes in the adaptability of rice lesion-mimic mutants to stressful environments are caused by the disorder of phytohormone metabolism in plants. In this study, we screened an ethyl methane sulfonate-treated population of the japonica cultivar 'Taipei 309' for a mutant with rust-like spots on leaves at the early tillering stage and brown-red spots at maturity and named it rsl1 (rust spotted leaf 1). Compared with the wild type, rsl1 showed decreases in plant height, panicle length, primary branch number, secondary branch number, filled grains per panicle, seed-setting rate, and 1 000-grain weight, and an increase in number of effective panicles. Genetic analysis indicated that rsl1 was controlled by a single recessive nuclear gene. RSL1 was localized between two molecular markers, B7-7 and B7-9, on rice chromosome 7 by map-based cloning. PCR sequencing of the annotated genes in this interval revealed a mutation of C1683A on the eighth exon of SPL5 (LOC_Os07g10390) in rsl1, which resulted in premature termination of protein translation. Exogenous phytohormone treatments showed that rsl1 was less sensitive to salicylic acid (SA), abscisic acid (ABA), and indo-3-acetic acid (IAA) and more sensitive to methyl jasmonate (MeJA) and gibberellin acid (GA) than the wild type. In addition, the survival rate of rsl1 was lower than that of the wild type under salt, alkali, drought, and high temperature stresses, and it was higher than that of the wild type under cold stress. Quantitative real-time polymerase chain reaction (qRT-PCR) results showed that RSL1 was involved in the regulation of ABA, SA, MeJA, IAA, and GA-related genes under abiotic stresses. The present study showed that the RSL1 mutation led to the appearance of lesion mimics and affected the growth, development, and stress resistance of rsl1 under abiotic stresses. The study of the functional mechanism of this gene can provide theoretical guidance for the research on rice stress resistance.
Oryza/microbiology* ; Stress, Physiological/genetics* ; Plant Diseases/genetics* ; Cloning, Molecular ; Chromosome Mapping ; Plant Growth Regulators/metabolism* ; Plant Proteins/genetics* ; Mutation ; Cyclopentanes ; Genes, Plant ; Plant Leaves/genetics* ; Oxylipins

The faithful segregation of genetic material to daughter cells is a fundamental biological process and a prerequisite for autonomous construction of robustly self-replicating artificial cells.Artificial cells are mimic cell structures with part or whole functions of normal cells.The complexity of eukaryotic chromosome segregation machinery has limited its applications in the field of synthetic biology.In contrast,the plasmid segregation machineries employed by prokaryotes are relatively simple and can provide valuable approaches for the bottom-up construction of complex artificial cells.This review aimed to comprehensively analyze the origin species and working mechanism of three bacterial plasmid segregation systems,namely ParABS,ParMRC,and TubZRC systems.The current researches on plasmid segregation both in bacterial and artificial cellular systems were summarized,and the future directions of this field were also proposed.

Objective To explore the safety of establishing the veno-arterial extracorporeal membrane oxygenation(VA-ECMO)pipeline through percutaneous puncture and the effectiveness of high-risk percutaneous coronary intervention(HR-PCI)under VA-ECMO assistance.Methods In this single-center retrospective study,patients who underwent HR-PCI assisted by VA-ECMO at Wuhan Asian Heart Hospital from December 2022 to December 2023 were included.The primary endpoint was the safety of establishing the VA-ECMO pipeline through percutaneous puncture,mainly characterized by extracorporeal membrane oxygenation(ECMO)-related complications,including severe bleeding/hematoma at the wound,arteriovenous fistula,pseudoaneurysm,peripheral arterial dissection,etc.The secondary endpoint was the effectiveness of HR-PCI under VA-ECMO assistance,defined as major adverse cardiovascular and cerebrovascular events(MACCE)at 6-month follow-up,including the composite events of all-cause death,non-fatal myocardial infarction,repeat revascularization,and ischemic stroke.Results Among the 189 patients included in the study,15(7.9％)had severe bleeding/hematoma at the puncture wound caused by VA-ECMO,8(4.2％)had wound infection,1(0.5％)had arteriovenous fistula,4(2.1％)had pseudoaneurysm,3(1.6％)had peripheral arterial dissection,8(4.2％)had systemic embolism,8(4.2％)had acute kidney injury,3(1.6％)had acute neurological injury,and 1(0.5％)died.percutaneous coronary intervention(PCI)was successful in 182 cases(96.3％),and a total of 36 cases(19.0％)had PCI-related complications.164 patients completed 6-month follow-up,among which 4(2.4％)had all-cause death,11(6.7％)had non-fatal myocardial infarction,11(6.7％)had unplanned repeat revascularization,and 2(1.2％)had the composite event of ischemic stroke.Conclusions Ultrasound-guided percutaneous puncture for establishing the VA-ECMO pipeline has high safety,and HR-PCI patients assisted by VA-ECMO have good short-term effects.

Objective:To explore the early predictive value of the triglyceride-glucose (TyG) index and the controlling nutritional status (CONUT) score for severe acute pancreatitis (SAP).Methods:Clinical data from 1 050 hospitalized patients with acute pancreatitis (AP) at the General Hospital of Central Theater Command between January 2019 and December 2023 were retrospectively analyzed. Patients were categorized into mild acute pancreatitis (MAP) group ( n=606), moderately severe acute pancreatitis (MSAP) group ( n=320), and SAP group ( n=124) based on AP severity. General clinical data, laboratory parameters, modified computed tomography severity index (MCTSI), bedside index for severity in acute pancreatitis (BISAP), TyG index, and CONUT score were compared among the three groups. Spearman correlation analysis was used to evaluate the relationship between TyG index, CONUT score and AP severity. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for AP severity. Receiver operating characteristic curves (ROC) were plotted to calculate the area under the curve (AUC), sensitivity, and specificity for evaluating the predictive efficacy of TyG index, CONUT score, and their combination for SAP. Results:Significant differences on TyG index and CONUT score were observed among AP patients with varying severity (all P value <0.001). Spearman correlation analysis further revealed positive correlations of TyG index ( r=0.174), CONUT score ( r=0.306) with AP severity (both P<0.001). Multivariate logistic regression identified neutrophil count ( OR=1.076, 95% CI 1.027-1.125), MCTSI ( OR=2.565, 95% CI 2.250-2.921), BISAP ( OR=3.522, 95% CI 2.726-4.549), TyG index ( OR=1.859, 95% CI 1.276-2.707), and CONUT score ( OR=1.155, 95% CI 1.035-1.288) as independent risk factors for AP severity. The combined predictive model equation was: -7.342+0.76×TyG+0.439×CONUT. ROC analysis showed that the AUC values of the TyG index, CONUT score, and the combined index (TyG index+CONUT score) were 0.583 (95% CI 0.529-0.637), 0.701 (95% CI 0.652-0.75), and 0.755 (95% CI 0.710-0.801), with sensitivities of 0.706, 0.677, and 0.742, and specificities of 0.884, 0.629, and 0.657, respectively (all P value <0.05). Conclusions:TyG index and CONUT score are positively correlated with AP severity and may serve as reliable predictors for SAP. Their combination could enhance the predictive accuracy for AP.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

OBJECTIVE: To accurately measure human energy metabolism with high temporal resolution, a respiratory gas analysis system was designed using a breath-by-breath approach. METHODS: Firstly, indirect calorimetry was employed in respiratory gas analysis to measure the respiratory flow and concentration signals in real-time. Secondly, oxygen consumption QO2 and carbon dioxide production QCO2 were calculated through respiratory characteristic alignment and respiratory signal segmentation. Finally, metabolic indexes were calculated according to the Weir formula. Furthermore, a controlled trial was formulated for validation comparisons with the MGC ULTIMA SYSTEM PFX CARDIO2. RESULTS: The results indicate that the data points of metabolic indexes measured by this system all fall within the confidence interval when compared with those of the MGC. CONCLUSION The system has high consistency with the MGC measurement results. Thus, the system can accurately measure metabolism in real-time and provide data support for clinical nutrition assessment and therapy.
Humans ; Energy Metabolism ; Breath Tests/instrumentation* ; Calorimetry, Indirect/instrumentation* ; Equipment Design

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*