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.

Despite significant advances in the field of critical care medicine over the past three decades, veno-arterial extracorporeal membrane oxygenation (V-A ECMO) remains the primary temporary mechanical circulatory support modality for patients with acute severe circulatory failure. With the accumulation of clinical experience and the increasing maturity of operational techniques in V-A ECMO, its technical management—particularly hemodynamic management—has become a key factor influencing patient outcomes. To further improve patient survival, the Chinese Critical Care Ultrasound Study Group, in collaboration with the Hemodynamic Therapy of Critical Care Collaborative Group and the Critical Care Medicine Branch of the China International Exchange and Promotive Association for Medical and Health Care, organized experts in critical care medicine to develop the Consensus on Hemodynamic Management in Adult Veno-Arterial Extracorporeal Membrane Oxygenation (2026 Edition). Based on years of clinical experience and the latest evidence-based medical evidence, this consensus formulates 15 systematic recommendations covering the entire process of V-A ECMO, including initiation, management during support, and weaning, aiming to promote standardized application of hemodynamic management in V-A ECMO.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Background/Aims: Dexamethasone (DEX) is a widely used exogenous therapeutic glucocorticoid in clinical settings. Its long-term use leads to many side effects. However, its effect on metabolic disorders in individuals on a high-fat diet (HFD) remains poorly understood. Methods: In this study, HFD-fed mice were intraperitoneally injected with DEX 2.5 mg/kg/day for 30 days. Lipid metabolism, adipocyte proliferation, and inflammation were assayed using typical approaches. Results: DEX increased the epididymal fat index and epididymal adipocyte size in HFD-fed mice. The number of epididymal adipocytes with diameters > 70 μm accounted for 0.5% of the cells in the control group, 30% of the cells in the DEX group, 19% of the cells in the HFD group, and 38% of all the cells in the D+H group. Adipocyte proliferation in the D+H group was inhibited by DEX treatment. Adipocyte enlargement in the D+H group was associated with increased the lipid accumulation but not the adipocyte proliferation. In contrast, the liver triglyceride and total cholesterol levels and their metabolism were downregulated by the same treatment, indicating the therapeutic potential of DEX for nonalcoholic fatty liver disease. Conclusions DEX synergizes with HFD to promote lipid deposition in adipose tissues. A high risk of obesity development in patients receiving HFD and DEX treatment is suggested.

Objective:To analyze the efficacy of transjugular intrahepatic portosystemic shunt (TIPS) combined with main splenic artery embolization in the treatment of patients with portal hypertension upper gastrointestinal bleeding complicated with extensive portal vein thrombosis (PVT).Methods:This study was a prospective, single-center, open-label, single-arm clinical trial. In the first phase, 81 patients with portal hypertension upper gastrointestinal bleeding who were admitted to Beijing Shijitan Hospital, Capital Medical University from January 2018 to December 2018 were consecutively enrolled, including 57 males and 24 females, with the age of (51.3±10.4) years. During TIPS surgery, the pressure of the portal vein before and after the balloon blocking the splenic artery was measured to clarify the contribution of the splenic artery to portal hypertension. In the second stage, from January 2019 to December 2022, 104 patients with portal hypertension upper gastrointestinal bleeding complicated with extensive PVT were re-enrolled, including 71 males and 33 females, with the age of (50.9±12.5) years. TIPS combined with main splenic artery embolization was performed, and portal vein pressure was measured before and after embolization. Follow up on the postoperative esophageal and gastric varices of the patients in the second stage.Results:The portal vein pressures before and after the first stage of balloon occlusion of the splenic artery were (35.2±8.4) mmHg (1 mmHg=0.133 kPa) and (24.2±6.3) mmHg, respectively. The pressure after occlusion was lower than that before occlusion, and the difference was statistically significant ( t=10.54, P<0.001). The portal vein pressures before and after the second stage embolization were (36.1±9.5) mmHg and (21.1±4.7) mmHg respectively. The pressure after embolization was lower than that before embolization, and the difference was statistically significant ( t=13.47, P<0.001). In the second stage, among the 104 patients, the proportion of those whose varicose veins disappeared or improved 6 months after the operation was 43.3%(45/104) and 51.0%(53/104), respectively. There were no patients with aggravation or rebleeding due to rupture. One year later, 8 patients (7.7%) had aggravated or ruptured esophageal and gastric varices with bleeding. Two years later, 12 patients (11.5%) had aggravated or bleeding. Conclusion:TIPS combined with main splenic artery embolization can effectively reduce the portal vein pressure in patients with portal hypertension upper gastrointestinal bleeding complicated with extensive PVT, improve the degree of esophageal and gastric varices, and reduce the risk of gastrointestinal bleeding.

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.

Objective:To explore the effect of integrated Chinese and western medicine teaching method on improving the comprehensive competencies of Obstetrics and Gynecology professional graduate students during their clinical practice.Methods:This study was an interventional trial. Thirty-one Obstetrics and Gynecology professional graduated students who rotated in the Obstetrics and Gynecology Department of Beijing Friendship Hospital Affiliated with Capital Medical University, were enrolled. Sixteen Obstetrics and Gynecology professional graduate students from 2023 and 2024 cohorts (mean age (24.06±1.24) years old; 15 females, 1 male) were assigned to the intervention group and received training using an integrated Chinese and western medicine teaching method during their 6 months of Gynecology Department rotation in the first year of clinical practice. Fifteen Obstetrics and Gynecology professional graduate students from 2021 and 2022 cohorts (mean age (23.93±1.18)years old; 14 females, 1 male) served as control group and received conventional training in accordance with the Beijing resident doctor standardized training requirements during the 6-month period of Gynecology Department in the first year. Within 1 week after gynecology rotation, both groups completed a satisfaction survey and a standardized rotation-end assessment, which included a theoretical examination and a five-station practical skills assessment, to evaluate teaching effectiveness.Results:At the end of 6-month training, students in the intervention group reported higher satisfaction than the control group in terms of learning interest, course content, teaching methods, clinical teaching ability of instructors, and improvement of their own competencies (all P<0.05). Theoretical assessment scores and total scores were also higher in the intervention group compared to the control group (both P<0.05). In the clinical skills assessment, the intervention group outperformed the control group in medical history collection, interpretation of auxiliary examinations, diagnosis and treatment, and case presentation (all P<0.05); however, no significant difference was observed in gynecological internal examination scores between the two groups ( P>0.05). Conclusion:During the early stage of clinical practice, training Obstetrics and Gynecology professional graduate students using an integrated traditional Chinese and western medicine teaching method may enhance their satisfaction with the teaching process and improve their performance in rotation-end assessments.

Objective:To analyze the correlation between mental health status and metabolic syndrome (MetS) in health checkup people.Methods:It was a cross-sectional study, 2 920 participants who received health checkup in the Health Examination Center of Peking University Third Hospital from January 2019 to December 2023 were selected using cluster sampling method. Their general information, physical examination, biochemical indicators, body composition, and self-evaluation scores on the Symptom Checklist-90 (SCL-90) were collected. According to the inclusion and exclusion criteria, a total of 2 813 study subjects were included, and divided into the MetS group and the non-MetS group based on whether they had MetS. The differences in general demographic information, body composition, blood biochemistry, and SCL-90 scores between the two groups were compared. Binary Logistic regression analysis was used to explore the correlation between mental health status and MetS.Results:Of the 2 813 subjects included, 1 576 were males (56.0%) and 1 237 were females (44.0%), with an average age of (41.7±11.0) years, the MetS group had 586 cases (20.8%) and the non-MetS group had 2 227 cases (79.2%). The MetS group had higher levels of age, body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low density lipoprotein cholesterol (LDL-C), fasting blood glucose, glycosylated hemoglobin (HbA 1c), free thyroxine(FT4), total triiodothyronine (TT3), free triiodothyronine (FT3), waist-to-hip ratio, visceral fat area, body fat percentage, uric acid/creatinine, homocysteine (Hcy), aspartate aminotransferases (AST), and alanine transaminase (ALT) levels, as well as higher scores for somatization, hostility, paranoia, and other factor compared to the non-MetS group (all P<0.05), while high density lipoprotein cholesterol (HDL-C) and estimated glomerular filtration rate (eGFR) levels were lower than those in the non-MetS group (all P<0.05). The proportion of male, and the positive rates of SCL-90, somatization, interpersonal sensitivity, hostility, paranoia and other factor in the MetS group were higher than those in the non-MetS group (all P<0.05). Multifactorial analysis showed that individuals with a positive SCL-90 assessment had a 1.34 times higher risk of MetS than those with a negative assessment ( OR=1.34, 95% CI: 1.06-1.68; P=0.014). Among them, individuals with positive somatization ( OR=2.02, 95% CI: 1.25-3.28; P=0.004) and hostility ( OR=1.61, 95% CI: 1.02-2.56; P=0.042) had increased risk of MetS. Conclusion:Poor mental health status increases the risk of MetS.