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.

Introduction: The 2021 IDF-DAR risk calculator had been previously evaluated in multiple studies and subsequently widely accepted and applied in clinical practice as a practical standardized tool for patient risk stratification. Recently updated, the 2026 IDF-DAR Risk calculator enables a more individualized, evidence-related evaluation of patientrelated and disease-related risk factors, incorporating modern diabetes technologies, including continuous glucose monitoring (CGM), automated insulin delivery (AID) systems, and advanced insulin formulations to enhance risk stratification. This tool allows medical professionals to tailor Ramadan practices based on overall factors toward promoting safe fasting. Methodology: This prospective multicentre observational study recruited adults with Type 1 and Type 2 diabetes attending public hospitals nationwide. People with diabetes (PwD) intending to perform Ramadan fasting were invited to participate and assessed using the 2026 IDF-DAR Risk Calculator in the 6-week pre-Ramadan period between 30th January and 19th March 2026. Results: A total of 458 PwD were evaluated and stratified into low (15.7%), moderate (41%), and high risk (43.3%) categories. Most participants had Type 2 diabetes (83.6%), with 60.3% having a disease duration exceeding 10 years and 43% exhibiting poor glycemic control (hemoglobin A1c >9%). Insulin therapy was used by 76.4% of participants, including two individuals with Type 1 diabetes using AID systems. Most participants reported no recent hypoglycemia (76.4%), 81.0% performed glucose monitoring, and 3.3% used CGM. Severe comorbidities were uncommon, with 1.1% having unstable macrovascular disease and 4.4% advanced chronic kidney disease (estimated glomerular filtration rate <30). Notably, 72.2% received structured Ramadan education. Conclusion Majority of PwD attending tertiary diabetes clinics were in the moderate- to high-risk category and intended to fast despite medical advice against fasting in some cases. Although most participants were on insulin therapy, hypoglycemia was low in the pre-Ramadan period. Integration of modern technologies, advanced insulin therapies, and structured education may support safer fasting practices.
Risk Assessment ; Diabetes Mellitus ; Hospitals ; Fasting

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

The success of"New Medical Sciences"in higher education requires effective tools in evalua-ting students'performance in courses.Previously,we reported a teamwork(T),critique(C)and ap-preciation(A)(TCA)ideological and political model,a teaching model widely applied in Basic Medical courses.TCA is an abbreviation derived from Tricarboxylic Acid Cycle in Biochemistry as an analogy for nurturing the abilities of thinking and teamwork(T),critique(C)and appreciation(A),which hope-fully could provide students with moral norms for cognition,science and life.This paper further explores the tools to assess the educational outcomes of the TCA model,by which teachers can collect feedback and reflect on teaching quality and effectiveness.Addressing the challenges of individual differences in large classes,fragmented learning feedback,and the difficulty of measuring meta-cognition in educational evaluation,this study employs strategies of value-added assessment,matrix assessment and norm-transfer-able assessment to evaluate the TCA abilities from the aspects of thinking quality,thinking creativity,co-operation ability,iterative thinking,dialectical thinking and job responsibility.By modifying/using 18 e-valuation tools in Education and Psychology,we have established a rubric system composed of 30 primary indicators(with 11 newly designed,10 partly modified and 9 directly adopted),along with 49 secondary indicators and 98 tertiary indicators to enhance the feasibility of the evaluation process.This rubric sys-tem was applied to Biochemistry teaching among the five-year-program undergraduates at Air Force Medi-cal University.Specifically,thinking and teamwork are evaluated by creative works from"the magic bio-chemical-circle",while critiques are assessed in large classes under the guidance of basic and clinical teachers,coupled with appreciation measured by job responsibility in a task-driven virtual reality(VR)project.The results indicate that Biochemistry teaching not only accumulates knowledge in students,but also achieves the goals in nurturing values and cognition.The inclusion of creative performance evalua-tion,cooperative learning and clinical case studies,can enhance students'interpersonal skills,coopera-tion,quality of thinking,creative thinking,iterative thinking and dialectical thinking to varying degrees.TCA-based Biochemistry teaching has a long-lasting impact on character education,and is capable of in-ducing positive long-term changes in students'cognition and lifestyle.Taken together,with the help of this rubric system,teachers can promptly acknowledge the effectiveness of their teaching,thereby facilita-ting their teaching strategies.

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 investigate the effect of traditional Chinese medicine chronic disease management model based on empowerment theory in patients with chronic heart failure(CHF).Methods:A total of 115 CHF patients admitted in Guangdong Provincial Hospital of Chinese Medicine between January 2020 and December 2021 were se-lected.Patients received traditional Chinese medicine chronic disease management model based on empowerment theory according to voluntary principle,and were followed up for 12 months.Exercise capacity,scores of Tradition-al Chinese Medicine Symptom Grading and Quantification Scale,Hospital Anxiety and Depression Scale(HADS)and Minnesota Living with Heart Failure Questionnaire(MLHFQ)were compared between before and after inter-vention.Results:Compared to before intervention,scores of Traditional Chinese Medicine Symptom Grading and Quantification Scale[(6.40±6.11)points vs.(8.88±6.72)points],HADS[(5.95±4.68)points vs.(7.69±5.95)points],MLHFQ[(13.10±10.54)points vs.(25.53±11.16)points]and 3m round-trip movement time[(7.54±1.70)s vs.(8.86±3.65)s]were significantly lower,and right hand grip strength[(27.23±10.49)kg vs.(26.10±9.94)kg]and 6-minute walking distance[(464.79±80.78)m vs.(415.55±79.33)m]were sig-nificantly higher after 12-month intervention(P＜0.05 or＜0.01).Conclusion:The traditional Chinese medicine chronic disease management model based on empowerment theory may improve clinical symptoms of traditional Chi-nese medicine,mental state,exercise capacity and quality of life in patients with chronic heart failure.

Objective:To construct a multimodal induction educational system suitable for standardized pediatric residency training bases, and to evaluate its effectiveness, thereby obtaining suggestions for further improvement.Methods:Twelve residents newly enrolled in the 2023 standardized residency training program who commenced their first-year training were included as study subjects. The induction educational system comprised multiple modules: department introduction, training plan and assessment requirements, departmental workflow, routine diagnosis and treatment of major diseases, specialized skills/procedures, and lifestyle guidance. Training materials and methods were tailored to the characteristics of each training module. Checklists were used for supervision and review, and a competency checklist was designed to evaluate residents' mastery of the training at two weeks of induction, which would guarantee the effectiveness of the training. A questionnaire survey, powered by wjx.cn, was used to obtain the experience and suggestions from the residents and ward instructors on induction education, and content ranking analysis was performed on the survey results.Results:The survey revealed that, before starting a new rotation, residents' top three educational needs were departmental workflow, routine diagnosis and treatment of common diseases, and specialized skills/procedures. Residents preferred face-to-face lectures and demonstrations by attending physicians or senior residents; instructors suggested improving relevant materials (such as resident physician manuals and video materials) and face-to-face lectures. The residents considered the current induction educational system to be greatly beneficial in basic theories, treatment principles, basic skills, and auxiliary examination processes.Conclusions:Through the above research, a multimodal induction educational system suitable for the standardized pediatric residency training base in the Peking University First Hospital has been preliminarily established, and suggestions for further improvement have been obtained, which is conducive to further improving the system and residents' post competency.

Objective:To establish an arsenic free fully automatic online digestion iodine analyzer detection method for urinary iodine (hereinafter referred to as the method).Methods:Based on the principle of iodine catalyzed antimony cerium redox reaction, a fully automatic online digestion iodine analyzer was used to determine the iodine content in urine. The effectiveness of the method in terms of detection limit, precision, accuracy (determination of urinary iodine primary standard reference materials GBW09108z and GBW09110f and spiked recovery experiment), and interference experiments was validated. The method was compared with the arsenic cerium catalytic spectrophotometry method recommended by the National Reference Laboratory for Iodine Deficiency Disorders.Results:The linear range of the method was 0 - 300 μg/L, with a correlation coefficient │ r│> 0.999 5. The qualitative and quantitative detection limits were 7.41 and 18.01 μg/L, respectively. The relative standard deviation ( RSD) of urine samples with different iodine concentrations ranged from 1.0% to 1.7%. The results of the determination of iodine concentrations in urine using standard substances GBW09108z and GBW09110f were within the given standard range, with RSD < 2.5%. The range of spiked recovery rates for urine samples with different iodine concentrations was 101.3% to 104.8%, with an overall average spiked recovery rate of 103.0%. The average concentration of the baseline iodine standard solution was determined to be 116.21 μg/L, and the relative error of the concentration determination with the addition of interfering substances was less than 5.0%. The comparison results showed that there was no statistically significant difference in the measurement results between the two methods ( t = - 0.06, P = 0.952). Conclusions:The method adopts automated detection, which is simple to operate, labor-saving, and does not require the use of arsenic trioxide. It has high precision and accuracy, and is suitable for detection of large quantities of samples.

Objective:To analyze the symptoms,diagnosis and treatment of upper urinary tract calculi patients combined with mild and moderate benign prostatic hyperplasia(BPH)after ureteral stent implantation.Methods:One hundred and six BPH pa-tients who were hospitalized for upper urinary tract calculi and had ureteral stents retained from January 2019 to December 2022 were selected and divided into 2 weeks group and 4 weeks group according to the time of removal of ureteral stents after surgery.Their gener-al clinical data were analyzed and compared.International Prostatic Symptom Scale(IPSS),postoperative ureteral Stent Symptom Questionnaire(USSQ),and incidence of adverse events after ureteral stent removal were recorded before and after removal.Results:The scores of IPSS were significantly increased in all patients,and symptoms in urinary tract had improved significantly after discharge(P＜0.05).Compared with the 2 weeks group,the USSQ score of the 4 weeks group was significantly increased(P＜0.05).And no significant adverse event was observed in the 2 weeks group after the removal of ureteral sten.Conclusion:IPSS score and USSQ score increased significantly during stent implantation in BPH patients with lithiasis.And complications increased sig-nificantly over time.Following thorough clinical assessment,early ureteral stent removal demonstrates both safety and efficacy,repre-senting an optimal therapeutic approach in selected cases.