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 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:To establish a TaqMan-MGB probe-based method for detecting the polymorphic loci C677T and A1298C of the MTHFR gene.Methods:Specific primers and TaqMan-MGB probes targeting the C677T and A1298C polymorphic loci of the MTHFR gene were designed and optimized based on the gene sequence information.A real-time quantitative PCR detection system was established.Gradient dilution experiments were conducted to determine the limit of detection,and reproducibility experiments were performed to evaluate detection consistency.Specificity was validated using wild-type and mutant plasmid templates.The method was applied to detect 56 clinical samples,and its accuracy and practicality were assessed through comparison with traditional Sanger sequencing.Results:The TaqMan-MGB probe method demonstrated high specificity for detecting the C677T and A1298C loci,with no cross-reactivity between wild-type and mutant probes,enabling accurate genotype differentiation.Sensitivity experiments revealed detection limits of 1.13 × 103 copies/μL for C677T and 8.39 × 101 copies/μL for A1298C.Reproducibility experiments showed coefficients of variation below 1％,indicating stable and reliable results.Among the 56 clinical samples,the overall detection rate for the C677T locus was 86.99％,and for the A1298C locus,it was 97.92％.The TaqMan-MGB method exhibited good concordance with Sanger sequencing results.Conclusion:The TaqMan-MGB method exhibits high specificity,sensitivity,and excellent reproducibility in detecting the polymorphic loci C677T and A1298C of the MTHFR gene,making it suitable for rapid detection in large-scale clinical samples.This method provides an effective molecular diagnostic tool for the early diagnosis and prevention of folate-related diseases.

Objective To develop a novel type of transparent simulation manikin as a surgical training model to meet the surgical treatment demand on the medical train.Methods A transparent manikin was developed with the steps of basic data collection,motherboard design and manufacture and module production and assembly.Firstly,basic data collection was carried out with reference to standardized human anatomy and parameters.Secondly,some software such as UG NX7.5 was used to construct the motherboard of the manikin.Finally,module production and assembly were performed with the materials of acrylic,transparent rubber,silicone and hydrogel and the technology of silicone infusion.Results The transparent manikin developed had its anatomy structure close to that of the real body and high visuality for its internal and external components,which simulated a variety of war wounds and thus could be integrated with the surgical training scenarios on the medical train effectively.Conclusion The transparent manikin developed is characterized by high visuality,modularity and blood flow,and meets the demands for surgical training on the medical train.[Chinese Medical Equipment Journal,2025,46(6):111-115]

Objective To develop a novel type of transparent simulation manikin as a surgical training model to meet the surgical treatment demand on the medical train.Methods A transparent manikin was developed with the steps of basic data collection,motherboard design and manufacture and module production and assembly.Firstly,basic data collection was carried out with reference to standardized human anatomy and parameters.Secondly,some software such as UG NX7.5 was used to construct the motherboard of the manikin.Finally,module production and assembly were performed with the materials of acrylic,transparent rubber,silicone and hydrogel and the technology of silicone infusion.Results The transparent manikin developed had its anatomy structure close to that of the real body and high visuality for its internal and external components,which simulated a variety of war wounds and thus could be integrated with the surgical training scenarios on the medical train effectively.Conclusion The transparent manikin developed is characterized by high visuality,modularity and blood flow,and meets the demands for surgical training on the medical train.[Chinese Medical Equipment Journal,2025,46(6):111-115]

Objective:To investigate the anti-heart failure mechanism of N-acetylcysteine(NAC)in diabetic cardiomyop-athy independent from coronary artery factors.Methods:A total of 40 diabetic mice after heart failure model construction were randomly divided into two groups,NAC group(n=20,NAC 100mg·kg-1·d-1)and control group(n=20,Saline 100 mg·kg-1·d-1).Echocardiography was performed to detect left ventricular end-diastolic volume(LVEDV),left ventricular end-systolic volume(LVESV),left ventricular ejection fraction(LVEF),mitral left ventricular early-dias-tolic peak flow velocity/left ventricular late-diastolic peak flow velocity(E/A),isovolumic relaxation time(IVRT)and cardiac output(CO)after 4 weeks.Terminal uridine nick-end labeling(TUNEL)was performed to detect apoptosis in-dex,and Western Blot was performed to detect the expression of extracellular regulated protein kinases(ERK)1/2 after 6 weeks in two groups.Results:Compared to those in control group,mice in NAC group had significant higher LVEF[(40.5±3.4)％vs.(36.9±3.2)％],E/A[(1.5±0.1)vs.(1.4±0.1)]and CO[(10.3±0.6)ml/min vs.(9.9±0.5)ml/min](P＜0.05 or＜0.01);and significant lower LVESV[(23.1±1.3)μl vs.(24.7±1.5)μl],apoptosis index[(31.2±0.5)％vs.(45.1±0.9)％]and the expression of ERK1/2[(2.2±0.2)vs.(3.9±0.1)](P＜0.001 all).Conclusion:NAC exerts anti-heart failure effect by attenuating apoptosis of cardiomyocytes via regulating ERK1/2 pathway.

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:To establish a TaqMan-MGB probe-based method for detecting the polymorphic loci C677T and A1298C of the MTHFR gene.Methods:Specific primers and TaqMan-MGB probes targeting the C677T and A1298C polymorphic loci of the MTHFR gene were designed and optimized based on the gene sequence information.A real-time quantitative PCR detection system was established.Gradient dilution experiments were conducted to determine the limit of detection,and reproducibility experiments were performed to evaluate detection consistency.Specificity was validated using wild-type and mutant plasmid templates.The method was applied to detect 56 clinical samples,and its accuracy and practicality were assessed through comparison with traditional Sanger sequencing.Results:The TaqMan-MGB probe method demonstrated high specificity for detecting the C677T and A1298C loci,with no cross-reactivity between wild-type and mutant probes,enabling accurate genotype differentiation.Sensitivity experiments revealed detection limits of 1.13 × 103 copies/μL for C677T and 8.39 × 101 copies/μL for A1298C.Reproducibility experiments showed coefficients of variation below 1％,indicating stable and reliable results.Among the 56 clinical samples,the overall detection rate for the C677T locus was 86.99％,and for the A1298C locus,it was 97.92％.The TaqMan-MGB method exhibited good concordance with Sanger sequencing results.Conclusion:The TaqMan-MGB method exhibits high specificity,sensitivity,and excellent reproducibility in detecting the polymorphic loci C677T and A1298C of the MTHFR gene,making it suitable for rapid detection in large-scale clinical samples.This method provides an effective molecular diagnostic tool for the early diagnosis and prevention of folate-related diseases.

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]