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.

Background and Aims:Intrahepatic cholangiocarcinoma(ICC)is a highly malignant liver tumor,with an increasing incidence worldwide,particularly in Asia.Although radical surgical resection is currently the only potentially curative treatment,the high recurrence rate and low postoperative overall survival(OS)rate of ICC remain major clinical challenges.Adjuvant therapy(AT)and neoadjuvant therapy(NAT)are important strategies to reduce postoperative recurrence and prolong OS.Several studies have shown certain efficacy of these treatments.However,the specific efficacy and safety of combined NAT and AT in ICC treatment require further validation.This study was conducted to evaluate the value of combining NAT and AT in improving the therapeutic outcomes of ICC patients through a multicenter retrospective analysis,so as to provide scientific evidence for optimizing treatment strategies.Methods:The clinicopathologic data of 576 patients with ICC who underwent radical resection and were pathologically confirmed from 13 hospitals in China between December 2011 and December 2017 were retrospectively collected.Patients were grouped based on their treatment modality:NAT+AT group,AT group,and non-NAT/AT group.The three patient groups were matched pairwise in a 1∶1 ratio using propensity score matching(PSM)to balance baseline data.The Kaplan-Meier method was used to analyze OS and disease-free survival(DFS),and subgroup analyses were conducted according to the 8th edition of the AJCC TNM staging system.Results:A total of 395 ICC patients were included in the final analysis,with 42 patients(10.6%)in the NAT+AT group,62 patients(15.7%)in the AT group,and 291 patients(73.7%)in the non-NAT/AT group.Before PSM,significant differences were observed between groups in terms of CA19-9,liver function Child-Pugh classification,intraoperative blood loss,surgical margin,differentiation grade,vascular invasion,ECOG score,and lymph node dissection ratio(all P<0.05).After PSM,there were no significant differences in baseline characteristics between the groups(all P>0.05).After matching,the median OS and DFS in the NAT+AT group were significantly better than in the AT and non-NAT/AT groups(both P<0.05),while there were no significant differences in OS and DFS between the AT and non-NAT/AT groups(both P>0.05).Subgroup analysis showed that in TNM stage I patients,DFS in the NAT+AT group was significantly better than in the non-NAT/AT group(P<0.05),but OS was not significantly different(P>0.05).In TNM stage Ⅱ and Ⅲ patients,both OS and DFS in the NAT+AT and AT groups were significantly better than in the non-NAT/AT group(both P<0.05),and DFS in the NAT+AT group was significantly better than in the AT group in TNM stage Ⅲ patients(P<0.05).Conclusion:NAT combined with AT provides better survival benefits for patients with locally advanced ICC,but its benefit for early-stage ICC patients is limited.However,the retrospective design and sample size limitations of this study may affect the stability of the results,and future large-sample,multicenter,prospective studies are needed for further validation.

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

Extracellular vesicles (EVs) are crucial for facilitating intercellular communication, promoting cell migration, and orchestrating the immune response. Recently, EVs can diagnose and treat tumors. EVs can be measured as biomarkers to provide information about the type of disease and therapeutic efficacy. Furthermore, EVs with lower immunogenicity and better biocompatibility are natural carriers of chemicals and gene drugs. Herein, we review the molecular composition, biogenesis, and separation methods of EVs. We also highlight the important role of EVs from different origins as biomarkers and drug delivery systems in tumor therapy. Finally, we provide deep insights into how EVs play a role in reversing the immunosuppressive microenvironment.

Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

Objective:To learn about both the distribution of resources of radiodiagnostic and radiotherapeutic and the frequencies of radiological examinations to provide a basis for rational allocation of medical resources and standardize medical ionizing radiation.Methods:Based on the data on permanent resident population and the data reported by the Suzhou medical institutions in possesion of radiological equipment to the " Suzhou radiological health information management platform", a summary was made of the number of items of radiological equipment and the frequencies of radiological examinations in Suzhou medical institutions in 2022 and 2023.Results:In 2023, there were 368 medical institutions with radiological equipment in Suzhou, including 28 tertiary hospitals, 58 secondary hospitals, 159 primary hospitals and 123 unrated others. The total number of the items of radiological equipment was 1 688, with 39 items more than in 2022, about 1.30 units per 10 000 population. There were 5 187 medical radiation workers in total, with 339 more than in 2022. The frequencies of radiological procedures were 1 157.961/per thousand population, with 37.70% being from computed tomography in 2023.Conclusions:The number of items of radiodiagnostic and radiotherapeutic equipment and the frequencies of radiological procedures was at a relatively high level in China, but the distribution of medical resources were in a unbanlanced state. Efforts should be focused on optimization of the allocation of medical resources for the sake of reducing the public radiation dose and protecting public health.

Aim To investigate the intervention effect of Rehmannia radix water extract on bleomycin(BLM)-induced pulmonary fibrosis in mice combined with metabolomics and to reveal the potential mechanism,in order to provide new ideas for clinical treatment of pul-monary fibrosis.Methods Male C57BL/6N mice were randomly divided into the control group,model group,pirfenidone group(positive control,PFD,270 mg·kg-1),and low dose(DH-L,4.55 g·kg-1)group,medium dose(DH-M,9.1 g·kg-1)group and high dose(DH-H,18.2 g·kg-1)group of Rehman-nia.Except for the control group,BLM(5 mg·kg-1)was instilled into the trachea to establish the model of pulmonary fibrosis in the other groups.The survival rate,lung index and blood oxygen saturation of mice in each group were evaluated.HE and Masson staining were used to observe the pathological changes of lung tissue.WBP was used to detect lung function.Flow cytometry was used to detect the apoptosis of primary lung cells,ROS and immune cells.ELISA was used to detect the levels of fibrosis markers and inflammatory factors(α-SMA,collagen Ⅰ,collagen Ⅲ,TGF-β1,TNF-α,IL-1 β,and IL-6).Biochemical method was employed to detect the contents of GSH-Px,T-SOD and MDA.Liquid chromatograph mass spectrometer(LC-MS)metabolomics was used to analyze the changes of serum metabolic profile.Results Water extract of Re-hmannia significantly increased the survival rate,oxy-gen saturation and lung function of mice with pulmona-ry fibrosis,reduced the lung coefficient,ameliorated pathological damage and collagen deposition in lung tissue,reduced the levels of apoptosis and oxidative stress,and down-regulated the levels of inflammatory factors in lung tissue.It regulated the levels of metabo-lites such as bile acid metabolism,sphingolipid metabo-lism,and unsaturated fatty acid metabolism.Conclu-sions Water extract of Rehmannia inhibits lung injury and collagen deposition in mice with pulmonary fibrosis by inhibiting inflammatory response,which may be a-chieved by regulating the levels of inflammatory factors through the metabolic pathways of bile acid and sphin-golipid.

Objective To develop and implement a drug treatment pathway for the initial treatment of diffuse large B-cell lymphoma(DLBCL)and to provide a foundation for refined medication use and cost control management under the Diagnosis Related Groups(DRG)payment system.Methods Clinical pharmacists collaborated to develop a drug treatment pathway for the initial treatment of DLBCL,utilizing evidence-based medicine and evidence-based pharmacy principles.The PDCA(Plan-Do-Check-Act)cycle method was employed for administrative intervention.The hematology department served as a pilot unit to assess the impact on economic indicators,including inpatient costs,drug expenses,and DRG payment balance,as well as treatment efficacy and the incidence of adverse reactions.Results Compared to the control group,the RG13 intervention group exhibited a significant reduction in average total hospitalization costs and drug expenses,along with a decreased DRG payment balance deficits.All differences were statistically significant(P＜0.05).Conclusion The development and implementation of a drug treatment pathway for the initial treatment of DLBCL can effectively reduce treatment costs,prevent DRG overspending,and alleviate the economic burden on patients,while ensuring the safety and effectiveness of the treatment.