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 investigate the causal relationship between metabolic syndrome and breast cancer by using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) summary statistics for metabolic syndrome and breast cancer were acquired from the Integrative Epidemiology Unit GWAS database and the GWAS Catalog, with populations encompassing the United States and East Asia. A bidirectional causal design was employed: a forward analysis with metabolic syndrome as the exposure and breast cancer as the outcome, followed by a reverse analysis wherein their roles were interchanged. The inverse-variance weighting (IVW) method was primarily used for effect estimation, supplemented by MR-Egger regression, the weighted median method, the simple mode method, and the weighted mode method. Instrument variable strength was screened using the F-statistic (F>10). Robustness of the results was assessed through heterogeneity tests, horizontal pleiotropy tests, forest plots, and leave-one-out sensitivity analyses. Results The IVW analysis indicated no significant causal relationship between metabolic syndrome and breast cancer (OR=1.00, 95%CI: 0.97-1.03), P>0.05). Sensitivity analyses yielded consistent results, suggesting the good robustness of the study findings. Conclusion This study found no evidence to support a causal relationship, either positive or negative, between metabolic syndrome and breast cancer.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Hypertension ranks among the most prevalent chronic non-communicable diseases worldwide, with its prevalence rising steadily and exerting substantial impacts on the demographic composition of voluntary blood donors and the safety of blood supply. The eligibility of hypertensive individuals for safe blood donation and the relevant screening and management strategies have long remained controversial in transfusion medicine. This article systematically reviews the epidemiological characteristics of hypertension, donation-related physiological alterations and underlying risk mechanisms. By synthesizing evidence from international multicenter studies and regulatory practices across major nations, it conducts a comprehensive analysis of blood donation safety and donor admission criteria for hypertensive patients. Available evidence demonstrates that for hypertensives with well-stabilized blood pressure and no severe cardiac, cerebral or renal complications or target organ damage, the overall incidence of adverse reactions following blood donation is comparable to that in healthy donors, and no definitive correlation has been identified between blood pressure levels and vasovagal responses. Current mainstream international management frameworks are gradually shifting from screening reliant on a single blood pressure cutoff value toward an integrated strategy combining stratified risk classification and individualized dynamic assessment, with core focus on long-term blood pressure control, consistency of medication regimens and complication status. Meanwhile, emerging technologies including artificial intelligence, ambulatory blood pressure monitoring and wearable devices have opened innovative avenues for blood donation risk evaluation and full-cycle donor management. In light of existing clinical evidence, future efforts should further refine the multi-dimensional risk stratification system, facilitate the implementation of intelligent screening and continuous monitoring technologies, and scale up health education and follow-up management for hypertensive populations. Such measures aim to appropriately expand the pool of eligible blood donors while safeguarding donation safety, ultimately achieving coordinated improvement in blood safety and blood supply capacity.

ObjectiveTreadmill exercise intervention was evaluated for its effects on addictive behavior, learning and memory, and hippocampal neuroinflammation in methamphetamine (MA)-addicted mice, and transcriptomic screening was performed to identify candidate molecules involved in exercise-mediated attenuation of MA-related neuronal injury. MethodsTwo-month-old male C57BL/6 mice were randomly assigned to four groups: control (C), exercise control (CE), methamphetamine (M), and methamphetamine plus exercise (ME). Mice in the M and ME groups received intraperitoneal injections of MA (1 mg/kg) once daily for 7 consecutive days to establish the addiction model, whereas mice in the C and CE groups received equal volumes of saline. Subsequently, mice in the CE and ME groups underwent treadmill exercise at 12 m/min for 60 min/d for 2 weeks. Conditioned place preference (CPP), the Y-maze, and the Morris water maze (MWM) were used to assess addictive behavior, spatial recognition memory, and spatial learning and memory, respectively. Hippocampal neuronal ultrastructure was examined by transmission electron microscopy (TEM), and microglia-related responses were evaluated by immunofluorescence staining for ionized calcium-binding adapter molecule 1 (Iba-1) in the hippocampal CA1 region. Previously generated and publicly available RNA-seq data from brain tissue of the C, M, and ME groups were reanalyzed, with three biological samples per group. Differentially expressed genes (DEGs) were re-screened using the criteria of P<0.05 and fold change>1.5 or <0.67, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. NLR family CARD domain containing 5 (Nlrc5) was further validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and Western blot was used to determine the protein expression of NLRC5, nuclear factor kappa B (NF‑κB), interleukin-1β (IL-1β), postsynaptic density-95 (PSD-95), and synaptophysin. ResultsTreadmill exercise significantly attenuated MA-induced conditioned place preference and improved learning and memory performance in both the Y-maze and MWM tests. Exercise increased exploration time and distance in the novel arm of the Y-maze, shortened escape latency, and increased the number of platform crossings in the MWM. Average swimming speed during the probe trial did not differ significantly among groups, suggesting that the MWM differences were not attributable to obvious differences in swimming performance. TEM revealed that MA exposure induced mitochondrial swelling, disrupted cristae, reduced organelle abundance, and nuclear envelope abnormalities in hippocampal neurons, whereas these ultrastructural changes were alleviated after exercise. Immunofluorescence staining showed that MA increased Iba-1 fluorescence intensity in the hippocampal CA1 region, while treadmill exercise significantly reduced this change. Transcriptomic analysis identified 160 DEGs associated with MA exposure and 58 DEGs associated with exercise intervention, with 9 overlapping DEGs. KEGG enrichment analysis showed that MA-related DEGs were enriched in the NOD-like receptor signaling pathway. Among the overlapping DEGs, Nlrc5, which was downregulated after MA exposure and restored following exercise intervention, was selected as a candidate gene for further validation. RT-qPCR confirmed that treadmill exercise reversed the MA-induced decrease in Nlrc5 mRNA expression. Western blot analysis further showed that treadmill exercise increased NLRC5, PSD-95, and synaptophysin protein expression while reducing NF-κB and IL-1β expression. ConclusionTwo weeks of treadmill exercise attenuated MA-induced conditioned place preference and ameliorated learning and memory impairment, alleviated hippocampal neuroinflammation and neuronal ultrastructural damage, and restored the expression of synapse-related proteins. Transcriptomic screening combined with molecular validation demonstrated that exercise intervention was accompanied by restoration of NLRC5 expression, reduced NF‑κB and IL-1β expression, and increased PSD-95 and synaptophysin expression. These findings suggest that NLRC5 may represent a candidate molecule involved in exercise-mediated amelioration of MA-related neuronal injury. However, the present results mainly demonstrate coordinated changes in NLRC5 expression, inflammatory indicators, and cognitive outcomes rather than a direct causal relationship, and the specific role of NLRC5 requires further functional validation.

Objective:To investigate the pathogenetic characteristics of clinical isolates of Streptococcus suis in Henan Province from 2020 to 2023. Methods:Eight clinical isolates of S. suis in Henan Province from 2020 to 2023 were identified using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and real-time fluorescence polymerase chain reaction (PCR). Serotype and virulence genes were detected by the serum agglutination test and PCR, and antibiotic susceptibility was evaluated using the microbroth dilution method. Multilocus sequence typing (MLST), minimum core genome (MCG), identification of antibiotic resistance genes, and core genome single nucleotide polymorphism (cgSNP) analysis were conducted using whole genome sequencing. Results:The results showed that eight S. suis strains isolated from humans were mainly serotype 2 (75.0%), while the rest were serotype 14 (25.0%). ST353 (62.5%) was the predominant genotype, followed by ST1 (25.0%) and ST7 (12.5%). All isolates belonged to the MCG1 group. The virulence genotypes of these isolates were primarily mrp(NA2)/ sly+/ ef+/ gapdh+(75.0%), while the remaining were mrp(EU)/ sly+/ ef+/ gapdh+(25.0%). These isolates carried tetracycline, macrolide, lincosamide and aminoglycoside resistance genes, and their resistance rates to tetracycline, erythromycin and clindamycin were 100.0%, 87.5% and 87.5%, respectively, and 62.5% strains were intermediate-resistant to penicillin. The cgSNP analysis indicated that these isolates were closer to the isolates from Guangdong, Zhejiang and Guangxi Provinces, with five ST353 strains and one ST7 strain belonging to Clade Ⅰ, and two ST1 strains belonging to Clade Ⅱ. Conclusion:The human isolates of S. suis in Henan Province are mainly ST353, harboring multiple virulence and antibiotic resistance genes.

Objective:To explore the clinical characteristics and identification of the independent risk factors for disease progression in patients with anti-gp210 antibody-positive primary biliary cholangitis (PBC).Methods:A retrospective cohort study was performed. A total of 323 cases with PBC diagnosed in Tianjin Medical University General Hospital from January 2013 to June 2023 (125 patients with anti-gp210 antibody-positive and 198 patients with anti-gp210 antibody-negative) were included. Baseline and follow-up data were collected. The independent sample t-test and Mann-Whitney U rank sum test were used for comparison between groups of continuous data. The χ2 test was used to compare the data between groups for the count data. The Pearson test was used for correlation analysis between continuous variables. The Kaplan-Meier method was used to analyze the disease progression-free survival rate. The Cox regression model was used to analyze the risk factors for disease progression. Results:The male proportion (11.2% vs. 5.1%, P=0.040) and IgM level [3.29(1.88, 4.80) g/L vs. 2.56(1.44, 3.87) g/L, P=0.019] were significantly higher in patients with PBC with positive anti-gp210 antibodies than those of the negative group. Histopathological analysis showed that the Scheuer score [1(0,3) vs. 0(0,2)], bile duct inflammation [(2(1,3) vs. 1(1,2)] and bile duct reaction score [(2(1,3) vs. 1(1,2)] were higher in the positive group than those of the negative group ( P<0.05), and the maturity of the tertiary lymphoid structure was higher ( P=0.011). Kaplan-Meier analysis showed that the 5-year disease-free survival rate was significantly lower in patients with positive anti-gp210 antibodies than that of the negative group (55.8% vs. 79.7%, P=0.006) at a median follow-up of 3(2,6) years. Multivariate Cox regression analysis showed that γ-glutamyl transferase [ HR=1.002 (95% CI: 1.000～1.003)] and platelet count [ HR=0.993 (95% CI: 0.988～0.999)] were the independent influencing factors for disease progression in patients with anti-gp210 antibody-positive PBC ( P=0.002, 0.017). Conclusion:Patients with anti-gp210 antibody-positive PBC have more severe clinical pathological manifestations and a higher risk of disease progression. Higher levels of γ-glutamyl transferase and lower platelet counts during the first visit are independent risk factors for disease progression in patients with anti-gp210 antibody-positive PBC, which can be used as dynamic monitoring indicators for this population, suggesting the need for early intensive intervention.

Objective:To systematically evaluate the fairness of traditional Chinese medicine (TCM) healthcare resource allocation at the prefecture-level in China using the healthcare resource agglomeration degree (HRAD) method, so as to provide empirical evidence for optimizing resource distribution.Methods:Data on TCM healthcare resources (including the number of TCM institutions, public TCM hospitals, TCM hospital beds, and TCM healthcare technicians) were collected from 333 prefecture-level regions in 2023. The HRAD method was employed to assess fairness in geographic allocation (HRAD i) and population-based allocation (HRAD i/PAD i). A multi-indicator comprehensive evaluation was conducted using the entropy weight method to determine weighting coefficients. Results:Significant disparities were observed in the geographic agglomeration of TCM resources (HRAD i) in China. Resource-rich regions (HRAD i>5) were primarily concentrated in eastern and some central-western provinces, while resource-scarce regions (HRAD i<1) were mainly distributed in western, northeastern, and parts of central and eastern provinces. Analysis of population-based fairness (HRAD i/PAD i) revealed that most prefecture-level cities nationwide had ratios<1, with only 8 provinces having more cities with ratios>1 than<1. The comprehensive evaluation showed that top-ranked cities in the east (e.g., Hangzhou, Dongying, Shenzhen), central region (e.g., Taiyuan, Zhengzhou), and west (e.g., Hainan Prefecture, Alxa League) were predominantly core cities or sparsely populated areas. Conclusions:China′s prefecture-level TCM healthcare resource allocation exhibits significant geographic and population-based inequities, with excessive concentration in provincial capitals and developed cities. Urgent strategies are needed to optimize resource allocation, enhance fairness and accessibility, including promoting the decentralization of high-quality resources, strengthening regional collaborative support, enhancing talent attraction in underdeveloped areas, and leveraging information technology to improve efficiency.

AIM To improve the quality standard for Dahuang Sodium Bicarbonate Tablets.METHODS TLC was adopted in the qualitative identification of rhein,emodin,chrysophanol,aloe-emodin,physcion and rhapontin,after which UPLC fingerprints were established,content determination of aloe emodin-8-O-β-D-glucoside,rhein-8-O-β-D-glucoside,emodin-8-O-β-D-glucoside,chrysophanol-8-O-β-D-glucoside,physcion-8-O-β-D-glucoside,aloe-emodin,rhein,emodin,chrysophanol,physcion were performed.RESULTS The clear TLC plots demonstrated good specificity.There were 20 common peaks in the fingerprints for 8 batches of samples with the similarities of more than 0.535.Ten constituents showed good linear relationships within their own ranges(r≥0.997 0),whose average recoveries were 98.7％-104.1％with the RSDs of 0.59％-2.13％,whose content ranges were 0.274 1-2.005 9,0.547 8-5.192 2,1.209 2-3.936 3,1.039 3-3.330 2,0.307 0-1.248 1,0.118 2-0.674 7,0.115 1-0.970 3,0.224 5-1.789 3,0.881 4-4.882 6,0.801 4-5.099 1 mg/g,respectively.CONCLUSION This simple and stable method can effectively control the quality of Rhei Radix et Rhizoma in Dahuang Sodium Bicarbonate Tablets.