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 quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]

Objective To quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]

Objective To explore the application effect of 3D printed individualized model in the treatment of complex ankle fractures(AF).Methods Patients with complex AF admitted to our hospital from July 2021 to October 2022 were selected and divided into the control group and the observation group using a random number table method,with 50 cases in each group.Patients in the control group were received minimally invasive reduction and internal fixation,while these in the observation group were given minimally invasive reduction and internal fixation under the guidance of 3D printed individualized model.The surgical conditions,ankle joint reduction,stress indicators[norepinephrine(NE)and angiotensin Ⅱ(AngⅡ)],ankle function and postoperative complications were compared between the two groups.Results There were 2 patients in the observation group and 3 patients in the control group were lost to follow-up 12 months after surgery.Compared with the control group,the observation group showed a decrease in the intraoperative blood loss,shortened surgical time,hospitalization time,and weight-bearing activity time,and an increase in the anatomical reduction rate(P<0.05).The observation group had lower serum levels of NE and AngⅡ 1 and 3 days after surgery(P<0.05)and higher Kofoed score and American Orthopedic Foot and Ankle Society(AOFAS)scores 1,6,and 12 months after surgery(P<0.05),as well as lower incidence of postoperative complications(P<0.05)than those in the control group.Conclusion For the treatment of complex AF,3D printed individualized model assisted the formulation of minimally invasive reduction and fixation surgical plans before surgery can shorten surgical time,reduce stress injury,decrease the risk of complications,and simultaneously increase the anatomical reduction rate and improve ankle joint function,thereby accelerating postoperative recovery of patients.

Objective To validate the diagnostic performance and risk stratification ability of an AI-based recognition system(PE-AI)for pulmonary embolism(PE)using computed tomography pulmonary angiography(CTPA)so as to analyze its diagnostic value in clinical practice.Methods A total of 416 patients with suspected PE who underwent CTPA from January 1,2023 to December 10,2023 at our hospital were included in this study.Two junior radiologists and PE-AI separately detected and diagnosed emboli in the collected cases by double-blind method,and recorded the diagnosis time respectively.Three senior radiologists reviewing with clinical follow-up results were used as the gold standard in this study.Diagnostic performance was evaluated by using the receiver operating characteristic(ROC)curve analysis and Delong-t test.For positive cases,the pulmonary artery obstruction index(PAOI)calculated by AI and manually were collected respectively and consistency analysis was performed.Results The area under the curve(AUC)of PE-AI,manual and combined diagnosis was 85.6％,90.8％and 95.1％,respectively,which differed significantly(P＜0.05).The reading time of PE-AI[(0.16±0.07)min]was significantly lower than the time of manual[(4.42±1.85)min,P＜0.001]and combined diagnosis[(4.58±1.84)min,P＜0.001].The PAOI measured by PE-AI and manually had high consistency(intraclass correlation efficient,ICC=0.80)in the subgroup analysis of confirmed cases.Conclusion AI can quickly identify pulmonary artery emboli in a short time and assist radiologists to improve diagnostic efficiency.At the same time,through the intelligent detection of PAOI,it is helpful for the risk stratification of patients with PE and optimizing the diagnosis and treatment pathway for pulmonary embolism.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

With the rise of data-intensive research, data literacy has become a critical capability for improving scientific data quality and achieving artificial intelligence (AI) readiness. In the biomedical domain, data are characterized by high complexity and privacy sensitivity, calling for robust and systematic data management skills. This paper reviews current trends in scientific data governance and the evolving policy landscape, highlighting persistent challenges such as inconsistent standards, semantic misalignment, and limited awareness of compliance. These issues are largely rooted in the lack of structured training and practical support for researchers. In response, this study builds on existing data literacy frameworks and integrates the specific demands of biomedical research to propose a comprehensive, lifecycle-oriented data literacy competency model with an emphasis on ethics and regulatory awareness. Furthermore, it outlines a tiered training strategy tailored to different research stages-undergraduate, graduate, and professional, offering theoretical foundations and practical pathways for universities and research institutions to advance data literacy education.
Artificial Intelligence ; Humans ; Biomedical Research

OBJECTIVE: To explore the current research status and hotspots in the field of biomechanics of diabetic foot by bibliometric analysis methods. METHODS: Literatures related to biomechanics of diabetic foot published in the Web of Scienc Core Collection (WoSCC) from 1981 to 2024 were searched. CiteSpace software and R language bibliometrics plugin were used to conduct a visual analysis of annual publication volume of the literature, including publication volume of each country and region, the publication situation of authors and institutions, the citation situation of individual literature, and the co-occurrence network of keywords. RESULTS: Totally 996 literatures were included, and the number of published papers increased steadily. The United States (261 papers) and China (89 papers) were the top two countries in terms of the number of published papers. The mediating centrality of the United States was 0.94, and that of China was 0.01. Scholars such as Cavanagh and institutions like the Cleveland Clinic were at the core of research in this field. High-frequency keywords include plantar pressure (plantar pressure), diabetic foot (diabetic foot), ulceration (ulcer), etc. The research focuses on plantar pressure, ulcer formation and prevention, etc. CONCLUSION Biomechanical research on diabetic foot mainly focuses on the pressure distribution on the sole of the foot, callus formation, mechanical analysis of soft tissues on the sole of the foot, and the study of plantar decompression caused by Achilles tendon elongation. The research trend has gradually shifted from focusing on joint range of motion to gait and the design of braces and assistive devices, and has begun to pay attention to muscle strength, gait imbalance and proprioception abnormalities.
Humans ; Diabetic Foot/physiopathology* ; Biomechanical Phenomena ; Bibliometrics

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

The oxytocin receptor (OXTR) has garnered increasing attention for its role in regulating both mature behaviors and brain development. It has been established that OXTR mediates a range of effects that are region-specific or period-specific. However, the current studies of OXTR expression patterns in mice only provide limited help due to limitations in resolution. Therefore, our objective was to generate a comprehensive, high-resolution spatiotemporal expression map of Oxtr mRNA across the entire developing mouse brain. We applied RNAscope in situ hybridization to investigate the spatiotemporal expression pattern of Oxtr in the brains of male mice at six distinct postnatal developmental stages (P7, P14, P21, P28, P42, P56). We provide detailed descriptions of Oxtr expression patterns in key brain regions, including the cortex, basal forebrain, hippocampus, and amygdaloid complex, with a focus on the precise localization of Oxtr⁺ cells and the variance of expression between different neurons. Furthermore, we identified some neuronal populations with high Oxtr expression levels that have been little studied, including glutamatergic neurons in the ventral dentate gyrus, Vgat⁺Oxtr⁺ cells in the basal forebrain, and GABAergic neurons in layers 4/5 of the cortex. Our study provides a novel perspective for understanding the distribution of Oxtr and encourages further investigations into its functions.
Animals ; Receptors, Oxytocin/metabolism* ; Male ; Brain/growth & development* ; Mice ; Mice, Inbred C57BL ; Neurons/metabolism* ; Single-Cell Analysis ; Gene Expression Regulation, Developmental ; RNA, Messenger/metabolism* ; Animals, Newborn