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.

This article reports a rare case of autoinflammatory disease presenting initially with skin induration and swelling after trauma as the initial manifestation, followed by progressive limb weakness. The patient was a middle-aged female who developed skin induration and swelling after trauma, which gradually progressed to limb weakness, dysarthria and bilateral facial paralysis, accompanied by livedo reticularis of the lower extremities, diffuse skin induration of the limbs, and beaded subcutaneous nodules in the right upper limb. The patient had a susceptibility to infection since childhood and a history of chronic livedo reticularis. Skin pathological examination revealed panniculitis. A comprehensive etiological screening for special infections and autoimmune diseases was completed with an unremarkable results, and whole-exome sequencing showed no abnormal findings. Following a multidisciplinary discussion combined with RNA sequencing results, the patient was diagnosed with an autoinflammatory disease, with a suspected type Ⅰ interferonopathy. Treatment with tofacitinib resulted in gradual improvement of clinical symptoms. This case highlights the importance of detailed medical history collection, systematic physical examination and multidisciplinary collaborative diagnosis and treatment, and underscores the pivotal role of molecular diagnosis in the confirmation of rare diseases. It can provide a reference for the clinical diagnosis and management of similar rare cases.

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.

Purpose To explore the feasibility of coronary CT angiography to predict major adverse cardiovascular events(MACE)in patients with grey zone of CT-derived fractional flow reserve(CT-FFR).Materials and Methods The imaging and clinical features of patients with suspected coronary heart disease who underwent coronary CT angiography examination and had a CT-FFR within 0.76-0.80 in Beijing Anzhen Hospital Affiliated to Capital Medical University from March 2017 to October 2018 were retrospectively collected.The incidence of MACE after coronary CT angiography was assessed by telephone at follow-up.The Cox regression model was used for feature selection,and the area under the receiver operating characteristic curve(AUC)was plotted to evaluate the predictive performance.Results The study included a total of 105 subjects,with an observed incidence rate of MACE at 31.4%(33/105).Multivariate Cox regression,adjusted for relevant parameters,indicated that △CT-FFR(HR=1.217,P=0.008),pericoronary fat attenuation index(HR=1.052,P=0.029)and plaque length(HR=1.068,P=0.047)were independent risk factors of MACE,and AUC were 0.705,0.656 and 0.701,respectively.The AUC of the combined model was 0.793,its predictive ability was higher than △CT-FFR(Z=-2.001,P=0.048),pericoronary fat attenuation index(Z=-2.402,P=0.016)and plaque length(Z=-2.004,P=0.045),respectively.Conclusion △CT-FFR,pericoronary fat attenuation index and plaque length are independent risk factors for predicting MACE in patients with grey zone of CT-FFR,and the combined model has best predictive efficacy.

Objective To investigate the damage characteristics of peri-implant bones with varying densities under impact and occlusal forces using numerical simulation.Methods A finite element model of the microstructure of an implant and bones with different densities was established.Impact and occlusal forces were applied sequentially to the implant.A user material subroutine was created for failure judgment using stress-based failure criteria,enabling the analysis of bone damage caused by impact and occlusal forces.Results No cortical bone damage was observed in bones of varying densities under impact force.Damage primarily occurred in the trabecular bone at the base of the implant,with the extent of damage worsening as bone density decreased.Additionally,the number of failed bone elements generated by the damage increased with reduced bone density.Bone tissues with pre-existing impact damage sustained secondary damage when subjected to occlusal force:the bonding interface between the implant and cortical bone was damaged,leading to implant displacement and fracture of peri-implant trabecular bone.The damage caused by occlusal force also worsened as bone density decreased.Conclusions The degree of damage from impact and occlusal forces is correlated with bone density,with damage worsening as bone density decreases.This underscores the protective role of cortical bone.The application of occlusal force exacerbates bone tissue damage,leading to implant displacement when the cortical bone is damaged.In clinical practice,patients with a history of impact damage should undergo thorough examination and evaluation.The occlusal force borne by damaged bones should be reduced;if necessary,the implant should be removed and reinserted after re-establishment of osseointegration.

Objective:To analyze the epidemiological characteristics of comorbidity of post-traumatic stress disorder and depression symptoms among active firefighters, and explore its influencing factors.Methods:In November 2021, a cross-sectional study was conducted using a combination of convenience sampling and cluster sampling. Active firefighters were selected as the research subjects for a questionnaire survey. 1100 questionnaires were distributed, 1032 were collected, and 1021 were valid, with an effective response rate of 98.93%. The PTSD prevalence and characteristics of firefighters were assessed by using the PTSD Checklist Civilian Version (PCL-C) . The degree of depression was assessed by the Patient Health Questionnaire (PHQ-9) . The coping style was assessed by the Trait Coping Style Questionnaire, and the Social Support Rate Scale was used to investigate the degree of social support. Combined with the general information, the influencing factors of comorbidity of PTSD and symptoms of depression in firefighters were analyzed with binary logistic regression based on single factor analysis.Results:Among 1021 firefighters, 379 had a PHQ-9 score of ≥5, and the prevalence rate of depression was 37.1% (379/1 021) . The prevalence rate of PTSD is 4.6% for 47 individuals with a total PCL-C score of ≥38, and the comorbidity rate of depressive symptoms among PTSD patients is 100%. Logistic regression analysis showed that injuries in the past six months, average/poor self-rated health status, and negative coping were all promoting factors for both the simple depression symptom group and the comorbidity group, while social support was the hindering factor ( P<0.05) . Two sets of OR values show that negative coping and social support have roughly the same degree of impact in both groups. The OR (95% CI) values of the two factors of being injured in the past six months and self-rated as average/poor health status have significantly increased in the comorbidity group. The OR (95% CI) values of being injured in the past six months has increased from 2.20 (1.24, 3.93) in the simple depression symptom group to 3.44 (1.30, 9.09) in the comorbidity group, and that of the self-rated as average and poor health status has increased from 4.91 (3.01, 8.00) to 6.56 (1.97, 21.87) and from 7.96 (2.25, 28.25) to 19.17 (4.75, 77.31) separately ( P<0.05) . Conclusion:The results indicate that firefighters with PTSD generally have comorbidity with depressive symptoms. The common influencing factor of being injured in the past six months is consistent with the pattern of PTSD symptoms triggered by depressive symptoms.

Objective:The purpose of this study was to analyze the epidemiological characteristics of hand, foot, and mouth disease (HFMD) among individuals aged 6 years and above in Guangzhou from 2010 to 2023, with the intention that a scientific basis be provided for effective prevention and control measures in older age groups.Methods:Data on HFMD incidence among individuals aged 6 years and above in Guangzhou from 2010 to 2023 were collected and analyzed. Descriptive epidemiological methods were used to analyze the distributions and pathogen components of HFMD cases in Guangzhou residents aged 6 years and above. Spatial autocorrelation analysis and Getis-Ord Gi* analysis were conducted to identify the spatial clustering patterns of HFMD at the street town level. Results:From 2010 to 2023, the gender ratio of HFMD cases in persons aged 6 and above was 1.49∶1 in Guangzhou. The average annual incidence rate of HFMD among individuals aged 6 years and above in Guangzhou was 25.75 per 100 000. Furthermore, the reported incidence rate indicated an increased tendency. The annual incidence showed a bimodal distribution, with the main peak occurring from May to July and the secondary peak from September to October. HFMD incidence rates vary by townships, with hotspots clustered in urban and urban-rural regions. The dominant pathogen shifts from year to year. Enterovirus 71 (EV71) was the prevalent strain in 2010, followed by other enteroviruses and Coxsackievirus (CV)-A16 from 2011 to 2016. Since 2017, CV-A6 has steadily become the major pathogen.Conclusions:The incidence of HFMD cases among individuals aged 6 years and above in Guangzhou increased generally from 2010 to 2023, with hotspots localized in urban and urban-rural areas. The pathogen composition altered dramatically, with the proportion of EV71 dropping overall, while CV-A6 eventually became the dominating strain. Therefore, it is imperative to focus on the prevention and control of HFMD in this age group, especially by strengthening measures in areas with high prevalence.

Owing to the insidious onset and limited awareness of early screening,many patients with esophageal squamous cell carcinoma(ESCC)are diagnosed at an advanced stage.Immunochemotherapy is the current standard first-line treatment for advanced ESCC;however,survival outcomes remain suboptimal.Radiotherapy,with its precise local control and potential immunomodulatory effects,is anticipated to act synergistically with immunochemotherapy,offering a novel direction for overcoming survival limitations.This review systematically sum-marizes the progress in the use of radiotherapy as a first-line treatment for advanced ESCC and discusses the synergistic mechanisms,clinical applications,and challenges associated with its combination with immunochemotherapy.