ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective To explore the technical process and clinical application of laparoscopic combined upper midline incision minimally invasive liver transplantation. Methods A retrospective analysis was conducted on 30 cases of laparoscopic combined upper midline incision minimally invasive liver transplantation. The cases were divided into cirrhosis group (15 cases) and liver failure group (15 cases) based on the primary disease. The surgical and postoperative conditions of the two groups were compared. Results All patients successfully underwent laparoscopic "clockwise" liver resection, with no cases of passive conversion to open surgery or intolerance to pneumoperitoneum. In 6 cases, the right lobe was relatively large, and the right hepatic ligaments could not be completely mobilized. One case required an additional reverse "L" incision during open surgery. All patients successfully completed the liver transplantation, with no major intraoperative bleeding, cardiovascular events, or other occurrences in the 30 patients. The model for end-stage liver disease (MELD) score in the cirrhosis group was lower than that in the liver failure group (P<0.001). There were no statistically significant differences between the two groups in terms of age, surgical time, blood loss, anhepatic phase, or cold ischemia time (all P>0.05). During the perioperative period, there was 1 case of hepatic artery embolism, 1 case of portal vein anastomotic stenosis, no complications of hepatic vein and inferior vena cava, and 3 cases of biliary anastomotic stenosis, all of which occurred in the liver failure group. Conclusions In strictly selected cases, the minimally invasive liver transplantation technique combining laparoscopic hepatectomy with upper midline incision for graft implantation has the advantages of smaller incisions, less bleeding, relatively easier operation, and faster postoperative recovery, which is worthy of clinical promotion and application.

Objective To explore the feasibility and clinical experience of the middle hepatic vein splitting-reconstruction technique in split liver transplantation from low-age donor livers. Methods A retrospective analysis was conducted on the cases of two low-age donor livers that underwent middle hepatic vein splitting-reconstruction, which were transplanted into four child recipients at the Liver Transplantation Center of the Third Affiliated Hospital of Sun Yat-sen University from January 2017 to July 2023. The surgical and postoperative conditions were summarized and analyzed. Results Donor 1 was a 6-year-old and 4-month-old girl with a body weight of 21 kg, and the obtained donor liver weighed 496 g. After splitting, the left and right liver weights were 201 g and 280 g, and transplanted into a 9-month-old boy weighing 6.5 kg and a 9-month-old boy weighing 7.5 kg, respectively. The graft to recipient weight ratio (GRWR) was 3.09% and 3.73%, respectively. Donor 2 was a 5-year-old and 8-month-old boy with a body weight of 19 kg, and the donor liver weighed 673 g. After splitting, the left and right liver weights were 230 g and 400 g, and transplanted into a 13-month-old girl weighing 9.5 kg and a 15-month-old boy weighing 12 kg. The GRWR was 2.42% and 3.33%, respectively. Both donor livers were split ex vivo, with the middle hepatic vein being completely split in the middle and reconstructed using allogeneic iliac vein and iliac artery vascular patches. According to GRWR, none of the 4 transplant livers were reduced in volume. Among the 4 recipients, one died due to postoperative portal vein thrombosis and non-function of the transplant liver, while the other three cases recovered smoothly without early or late complications. Regular follow-up was conducted until July 31, 2023, and liver function recovered well. Conclusions Under the premise of detailed assessment of the donor liver and meticulous intraoperative operation, as well as matching with suitable child recipients, low-age donor livers may be selected for splitting. The complete splitting and reconstruction of the middle hepatic vein in the middle may effectively ensure the adequate venous return of the left and right liver and provide sufficient functional liver volume.

This research aims to construct a stable epithelial cell senescence model for screening and e-valuation of senolytics.We explored the optimal conditions for doxorubicin-induced senescence of non-transformed epithelial cells MCF 10A,including the optimal induction concentration,the optimal inter-vention time,and the optimal senescence duration,and confirmed the feasibility of MCF 10A as an epi-thelial senescence model by multiple ways.The optimal condition for Doxorubicin-induced senescence of MCF 10A cells was treatment with 0.6 μmol/L Doxorubicin for 16 h to achieve the best senescence state on the 8th day.Under the optimal induction conditions,the positive rate of senescence-associated β-gal-actosidase(SA-β-gal)staining in the treated group reached 97％.At the same time,biochemical results of detecting the expression of mRNA,proteins,and immunofluorescence demonstrated that the expression levels of senescence-associated secretory phenotype(SASP),p16,p21 and p53 in the treated group were significantly higher than those in the control cells,and Lamin B1 was significantly decreased(P＜0.001),which were consistent with the specific characteristics of senescence.In summary,an epithelial senescence model was successfully induced in MCF 10A cells by Doxorubicin in this study,which will promote the screening of senolytics for senescent epithelial cells.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective Based on the national drug sampling inspection program,this study aims to comprehensively and systematically evaluate the quality of Xuanmai Ganjie preparations,analyze existing quality issues,and provide references and suggestions for quality control of this variety.Methods A total of 237 batches of Xuanmai Ganjie preparations were tested using legal standards,and methods were established for detecting adulteration of Ophiopogon japonicus with counterfeit varieties,paclobutrazol residue levels,and determining the content of platycodin D in Xuanmai Ganjie preparations.These methods were applied to the quality control and evaluation of Xuanmai Ganjie preparations.Results Through statutory inspection,one batch of Xuanmai Ganjie granules was found non-compliant.Specific batches were identified to contain the following irregularities:adulteration of Ophiopogon japonicus with counterfeit varieties,paclobutrazol residue levels exceeding proposed limits,and platycodin D content below the established threshold.Conclusion The overall quality of Xuanmai Ganjie granules was average,while the overall quality of Xuanmai Ganjie capsules and lozenges was relatively good.Manufacturing enterprises should strengthen their sense of primary responsibility and enhance control over the entire drug production process.

Objective:To discern the association between autism-like behaviors and resilience within the ado-lescent demographic.Methods:A total of 7 063 middle school students were selected to assess ASD-like behaviors and resilience in adolescents using the Autism Spectrum Screening Questionnaire(ASSQ)as well as the Resilience Scale for Chinese Adolescent(RSCA).Subgroups bounded by P5 and P95 of the total ASSQ score,a comparative analysis of the resilience scores between these groups was executed.A correlation evaluation and linear regression a-nalysis was carried out between ASSQ and RSCA scores from all participants.Results:The RSCA scores within the high ASSQ scoring group,were inferior to those in the low scoring group.ASSQ scores were negatively correlated with RSCA scores for the full sample(Ps＜0.01);Social interaction scores on the ASSQ were negatively correlated with the five-factor RSCA scores(β=-0.23,-0.27,-0.11,-0.23,-0.37,Ps＜0.05).Conclusion:There was a negative association between autism spectrum disorder-like behaviors and resilience in adolescents,with more severe social interaction symptoms being associated with poorer resilience.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Acute symptomatic osteoporotic thoracolumbar compression fracture (ASOTLF) can lead to chronic low back pain, kyphosis deformity, pulmonary dysfunction, loss of mobility, and even life-threatening complications. Vertebral augmentation is currently the mainstream treatment method for this condition. In 2019, the Editorial Board of Chinese Journal of Trauma and the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association collaboratively led the development of Clinical guideline for vertebral augmentation for acute symptomatic osteoporotic thoracolumbar compression fractures. Six years later, with advances in clinical diagnosis and treatment techniques as well as accumulating evidence in related fields, the 2019 guideline requires updating. To this end, the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association, the Spinal Health Professional Committee of China Human Health Science and Technology Promotion Association, and the Minimally Invasive Orthopedics Professional Committee of Shaanxi Medical Doctor Association have organized experts in the field to develop the Clinical guideline for vertebral augmentation of acute symptomatic osteoporotic thoracolumbar compression fractures ( version 2025) , based on the latest evidence-based medical researches. This guideline incorporates 3 recommendations retained from the 2019 version with updated strength of evidence, along with 12 new recommendations. It provides recommendations from six aspects of diagnosis, pain management, treatment option selection, prevention of postoperative complications, anti-osteoporosis therapy, and postoperative rehabilitation, aiming to provide a reference for standard treatment of vertebral augmentation for ASOTLF in hospitals at all levels.