Myocardial infarction （MI） and osteoporosis （OP）， as two prevalent metabolic diseases with high morbidity and mortality rates， are respectively characterized by cardiovascular system dysfunction and bone homeostasis imbalance， collectively posing significant global public health challenges. While clinically often considered as independent diseases， recent studies have revealed shared pathological mechanisms between the two. This study initiated its exploration from the traditional Chinese medicine concept of the "heart-bone" axis， systematically analyzing the correlation between MI and OP from perspectives including hemodynamics， neuroendocrinology， calcium homeostasis， inflammation and vascular injury， as well as hormone levels. By discussing the pathological mechanisms of "heart disease affecting the bones and bone disease affecting the heart"， the study also elucidated advancements in both Western and traditional Chinese medicine treatments. The goal is to provide novel insights and methodologies for the prevention and treatment of "heart-bone comorbidities"， thereby facilitating comprehensive management of cardiovascular and skeletal diseases.

Myocardial infarction （MI） and osteoporosis （OP）， as two prevalent metabolic diseases with high morbidity and mortality rates， are respectively characterized by cardiovascular system dysfunction and bone homeostasis imbalance， collectively posing significant global public health challenges. While clinically often considered as independent diseases， recent studies have revealed shared pathological mechanisms between the two. This study initiated its exploration from the traditional Chinese medicine concept of the "heart-bone" axis， systematically analyzing the correlation between MI and OP from perspectives including hemodynamics， neuroendocrinology， calcium homeostasis， inflammation and vascular injury， as well as hormone levels. By discussing the pathological mechanisms of "heart disease affecting the bones and bone disease affecting the heart"， the study also elucidated advancements in both Western and traditional Chinese medicine treatments. The goal is to provide novel insights and methodologies for the prevention and treatment of "heart-bone comorbidities"， thereby facilitating comprehensive management of cardiovascular and skeletal diseases.

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 Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective This study aimed to investigate the correlation of cerebral perfusion and cognitive function status in patients with minor stroke(MS)or transient ischemic attack(TIA)complicated by severe intracranial arterial stenosis or occlusion(hereafter referred to as ICAS-MSTIA).Methods Retrospectively enrol consecutive ICAS-MSTIA patients admitted to the Department of Neurology,the First Affiliated Hospital of Xi'an Jiaotong University,from June 2023 to May 2024.In the meantime,healthy controls were openly recruited.The ICAS-MSTIA patients were divided into two groups based on the side of intracranial large artery stenosis or occlusion:the left intracranial large artery involvement group and the right intracranial large artery involvement group.All patients with intracranial large artery stenosis or occlusion underwent MR scanning within 2 weeks after the first episode of TIA or MS,while there was no specific time requirement for MR examination in the healthy control group.On the day of MR scanning,the Montreal cognitive assessment(MoCA)scale was used to evaluate the participants'global cognitive function and performance in various cognitive domains,including visuospatial/executive function,naming,attention,language,abstraction,delayed recall,and orientation.General information of all participants was collected,including age,sex,educational level,body mass index,and history of smoking and alcohol consumption.Clinical data were collected from both left and right intracranial large artery involvement groups,including cerebrovascular risk factors(such as,diabetes mellitus,hypertension,and hyperlipidemia),National Institutes of Health stroke scale(NIHSS)score at admission,responsible stenotic or occluded arteries(internal carotid artery,middle cerebral artery),degree of stenosis in the responsible vessel(severe stenosis[stenosis rate 70%-99%],occlusion[stenosis rate100%])and non-responsible vessel(no stenosis[0],mild stenosis[stenosis rate＞0-49%]),collateral circulation compensation(American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology[ASTIN/SIR]collateral circulation classification),and responsible events(TIA,MS).General data and MoCA scale scores were compared across the three groups,while clinical data were compared between the left and right intracranial large artery involvement groups.Statistical parametric mapping 12(SPM 12)was used to perform voxel-wise independent samples t-tests on cerebral blood flow(CBF)differences among the left ICAS-MSTIA group,right ICAS-MSTIA group,and healthy control group,with cluster-level family-wise error(FWE)correction applied for adjustment.Multiple linear regression analysis was conducted to evaluate the relationship between global CBF values and total MoCA scores in ICAS-MSTIA patients with left or right intracranial large artery involvement.Results A total of 33 ICAS-MSTIA patients and 33 healthy controls were enrolled in the study.Among the ICAS-MSTIA patients,21 had left intracranial large artery involvement and 12 had right involvement.(1)Among the three groups,statistically significant differences were observed in the proportions of individuals with reported smoking history(P=0.024)and alcohol consumption history(P=0.011).The left intracranial large artery involvement group had a higher NIHSS score(0[0,2]vs.0[0,0],P=0.044)and a higher proportion of patients with internal carotid artery involvement(13/21 cases vs.2/12 cases,P=0.027)compared with the right side group.No statistically significant differences were observed in other general or clinical data across the three groups or between the two non-control groups(all P＞0.05).(2)Statistically significant differences were found across the three groups in the MoCA scale total score and scores of visuospatial/executive function,attention,language,abstraction,delayed recall,and orientation cognitive domains(all P＜0.05),while no significant difference was noted in the naming score(P=0.063).The left intracranial large artery involvement group had lower total MoCA score and lower scores in visuospatial/executive function,attention,language,abstraction,delayed recall,and orientation in comparison to the healthy control group(all P＜0.016 7).The right intracranial large artery involvement group had significantly lower scores in language,abstraction,and orientation domains than the healthy control group(all P＜0.016 7).Additionally,the left side group had a lower attention domain score than the right side group(P＜0.016 7).No other statistically significant differences were found in pairwise comparisons(all P＞0.016 7).(3)Patients in both the left and right intracranial large artery involvement groups exhibited a significant decrease in CBF in extensive regions on the affected side,including the temporal lobe,dorsolateral prefrontal cortex,and occipital lobe.Furthermore,after correction,in the left involvement group CBF was higher in the contralateral lingual gyrus,cuneus,and calcarine sulcus compared with the healthy control group(P＜0.05).While in the right involvement group,no regions had increased CBF compared to the healthy control group.(4)Multiple linear regression showed positive correlation between CBF in ipsilateral precentral gyrus and superior temporal gyrus,and the total MoCA score in patients with left intracranial large artery involvement(FWE-corrected,P＜0.05).In contrast,there was no correlation between CBF and total MoCA score in patients with right intracranial large artery involvement.Conclusions ICAS-MSTIA patients exhibited various degrees of impairment in cerebral perfusion and cognitive function.A significant positive correlation is observed between these two impairments in patients with left intracranial large artery involvement.

Objective To achieve efficient compression of on-board radiotherapy projection images using dynamic video encoding algorithms.Methods The on-board radiotherapy imaging system primarily provides 2D X-ray projection images for patient positioning verification and 3D tomographic image reconstruction.Since multiple projection images acquired continuously exhibit strong spatiotemporal correlations,their similarities could be used to eliminate redundant information,thereby improving the image compression ratio.During image compression,the image sets obtained at different times were arranged into an image sequence which was input into a video encoder and output as a video file.During image decompression,the video file was input into a video decoder and output as an image sequence,and the images in the sequence were then assigned back to their original image sets.Three current dynamic video encoding algorithms(AVC,HEVC,and AV1)and the classic static image coding algorithm(JPEG 2000)were tested on a database of 2D projection images.The performance of various compression algorithms was evaluated using indicators such as compression ratio(CR),peak signal-to-noise ratio(PSNR),and structural similarity(SSIM).Moreover,visual comparison of projection images before and after compression was evaluated by clinical radiation oncologists.Results Dynamic video encoding algorithms achieved higher CR than the static image coding algorithm.The average CR of the 3 dynamic video encoding algorithms was as followed:CRAVC=11.50,CRHEVC=30.74,and CRAV1=27.10,while the average CR of the static image coding algorithm(JPEG 2000)was 5.28.For abdominal projection images,well-defined contours and textural details were preserved even when the CR reached 42.37.For head-neck projection images,although mild contour blurring emerged at a CR of 20.71,subsequent evaluation by clinical radiation oncologists confirmed that the reconstructed CBCT images still satisfied clinical requirements.Conclusion These dynamic video encoding algorithms effectively utilize the strong correlation information between multiple projection images,reduce the storage of redundant information,and greatly improve the image CR.

AIM To establish an HPLC-MS/MS method for the simultaneous content determination of gallic acid,protocatechuic acid,oxypaeoniflorin,catechin,epicatechin,albiflorin,paeoniflorin,rutin,calycosin-7-glucoside,syringaldehyde,ferulic acid,coumarin,ononin,calycosin,cinnamic alcohol,cinnamic acid,benzoylpaeoniflorin,cinnamaldehyde,astragaloside,astragaloside Ⅲ,6-gingerol in Huangqi Guizhi Wuwu Decoction.METHODS The analysis was performed on a 30 ℃ thermostatic Thermo Scientific Hypersil GOLD column(150 mmx4.6 mm,3 μm),with the mobile phase comprising of 0.015％formic acid-acetonitrile flowing at 0.4 mL/min in a gradient elution manner,and electrospray ionization source was adopted in positive and negative ion modes with multiple reaction monitoring.RESULTS Twenty-one constituents showed good linear relationships within their own ranges(r＞0.990 5),whose average recoveries were 93.99％-108.52％with the RSDs of 1.04％-5.97％.CONCLUSION This simple,feasible,stable and reliable method can be used for the quality control of Huangqi Guizhi Wuwu Decoction.

Vaccine immunization is the most effective and cost-efficient method for infectious disease prevention and control.Since the outbreak of novel coronavirus pneumonia(caused by the novel coronavirus,COVID-19)at the end of 2019,third generation mRNA nucleic acid vaccines has been applied to stop viral spread.mRNA vaccines,rather than relying on the immune activation mode of traditional vaccines,are an innovative breakthrough using the body's own cells to produce antigens,thereby activating double specific immunity,forming immune memory,and providing more lasting specific immunity.Com-pared with the traditional first-generation(inactivated)and second-generation(genetically engineered)vaccines,mRNA vac-cines,because of the advantages provided by this platform,play important roles in the prevention and control of major sudden infectious diseases.Consequently,mRNA vaccines were the world's first COVID-19 vaccines to be applied clinically,thus ser-ving as a barometer in the field of vaccine research and development.Herein,the molecular design and presentation of mRNA vaccines,and the molecular mechanisms of their activation of the immune response are reviewed,to provide a theoretical basis for future application of novel mRNA vaccines in the prevention and control of animal infectious diseases.

Objective To analyze the research status,hot directions and frontier trends of traditional Chinese medicine in the prevention and treatment of diseases by regulating Notch signaling pathway based on bibliometrics.Methods Based on Citespace and Vosviewer,the literature on the regulation of Notch signaling pathway by traditional Chinese medicine in CNKI and WoSCC was visually analyzed.Results 362 and 85 related literatures were published in Chinese and English respectively until January 2024.Since 2013,the number of literatures published in this field has shown a fluctuating increasing trend.China is the country with the most publications;Hunan University of Chinese Medicine were the institutions with the most publications in the Chinese database,and Beijing University of Chinese Medicine was the institution with the most publications in the English literature database.Combined with the research direction of each research team and keyword clustering and burst analysis,the research hotspots of traditional Chinese medicine regulating Notch signaling pathway are focused on cerebral ischemia,myelosuppression and hepatic fibrosis.Diseases such as Asthma,colorectal cancer have become emerging research directions in recent years.Electroacupuncture therapy to promote stem cell proliferation and treat neurological diseases is one of the frontier research trends in this field.Conclusion Recent years have seen a rapid development of traditional Chinese medicine's disease prevention and treatment that targets Notch signaling pathway.Various expert teams have obtained rich research results,and the research hotspots show a diversified trend.In-depth exploration of this can provide strong evidence for the molecular mechanism of traditional Chinese medicine in the treatment of various diseases.