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.

To investigate the association between sleep-related phenotypes and the risk of malignancy in pulmonary nodules, and to provide complementary evidence from a general population cohort and genetic analyses.

Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

Time rhythm and the immune system play crucial roles in the pathogenesis of allergic rhinitis.Traditional Chinese medicine(TCM)believes that the circulation of qi and blood in lung meridian follows the principle of"yang during the day,yin at night",which has a defensive function to protect the body from external pathogens.Qi stagnation in lung meridian and impaired qi and blood circulation can lead to the invasion of external pathogens,exacerbating allergic reactions,especially during the active period of the lung meridian,when the immune system is most sensitive to allergens.Based on this,this paper proposes the concept of"bidirectional regulation among meridian,time rhythm,and immune system",and in combination with TCM theory of midnight-noon and ebb-flow doctrine,analyzes the fluctuations of allergic rhinitis symptoms and the temporal changes of meridian qi and blood,and reveals the rhythmic relationship between meridian activity and immune response.This paper combines existing clinical and experimental studies to support this hypothesis,integrating the time dimension into traditional TCM syndrome differentiation and treatment,offering a more individualized treatment approach.This concept not only provides novel scientific evidence for TCM treatment of allergic rhinitis,but also offers theoretical support for optimizing treatment timing and intervention strategies.

The structure of intestinal tissue is complex. In vitro simulation of intestinal structure and function is important for studying intestinal development and diseases. Recently, organoids have been successfully constructed and they have come to play an important role in biomedical research. Organoids are miniaturized three-dimensional (3D) organs, derived from stem cells, which mimic the structure, cell types, and physiological functions of an organ, making them robust models for biomedical research. Intestinal organoids are 3D micro-organs derived from intestinal stem cells or pluripotent stem cells that can successfully simulate the complex structure and function of the intestine, thereby providing a valuable platform for intestinal development and disease research. In this article, we review the latest progress in the construction and application of intestinal organoids.
Organoids/cytology* ; Intestines/physiology* ; Humans ; Animals ; Pluripotent Stem Cells

OBJECTIVE: To assess health equity in the Yangtze River region to improve understanding of the correlation between hand, foot, and mouth disease (HFMD) and socioeconomic factors. METHODS: From 2014-2016, data on HFMD incidence, population statistics, economic indicators, and meteorology from 26 cities along the Yangtze River were analyzed. A multi-city random-effects meta-analysis was performed to study the relationship between temperature and HFMD transmission, and health equity was assessed with respect to socio-economic impact. RESULTS: Over the study period, 919,458 HFMD cases were reported, with Shanghai (162,303) having the highest incidence and Tongling (5,513) having the lowest. Males were more commonly affected (male-to-female ratio, 1.49:1). The exposure-response relationship had an M-shaped curve, with two HFMD peaks occurring at 4 °C and 26 °C. The relative risk had two peaks at 1.30 °C (1.834, 95% CI: 1.204-2.794) and 31.4 °C (1.143, 95% CI: 0.901-1.451), forming an M shape, with the first peak higher than the second. The most significant impact of temperature on HFMD was observed between -2 °C and 18.1 °C. The concentration index (0.2463) indicated moderate concentration differences, whereas the Theil index (0.0418) showed low inequality in distribution. CONCLUSION The incidence of HFMD varied across cities, particularly with changes in temperature. Economically prosperous areas showed higher risks, indicating disparities. Targeted interventions in these areas are crucial for mitigating the risk of HFMD.
Female ; Humans ; Male ; China/epidemiology* ; Cities/epidemiology* ; Hand, Foot and Mouth Disease/transmission* ; Incidence ; Risk Factors ; Temperature