Objective To analyze the case data of farmers' foodborne disease surveillance reports in Guizhou Province from 2022 to 2024, and to provide reference for the precise prevention and control of foodborne diseases among farmers in Guizhou Province. Methods Case data of foodborne disease surveillance reports of farmers were systematically collected from 2022 to 2024 in Guizhou Province. Descriptive epidemiological methods were used to analyze the temporal, geographical, and demographic distribution of foodborne diseases among farmers, along with their primary clinical symptoms and pathogen detection results. Results From 2022 to 2024, a total of 22,882 cases of foodborne diseases were reported among farmers in Guizhou Province. The majority of clinical symptoms (97.81%) were related to the digestive system, with summer being the peak season. While females outnumbered males, the gender difference was statistically insignificant (P >0.05). The 36-55 age group accounted for the highest proportion (38.83%), with Zunyi City (34.89%) and Qiandongnan Prefecture (23.21%) reporting the most cases. Fungal products were the most frequently reported suspected food items (26.96%), and home-made preparation was the primary processing method (58.63%). A total of 1 210 fecal samples were collected through active monitoring with an overall detection rate of 13.22%. Norovirus showed the highest detection rate (9.92%, 120/1 210). Statistically significant differences were observed among different seasons, age groups, regions, types and processing methods of suspected food exposure, and pathogen detection rates (P <0.001). Conclusion Foodborne disease prevention and control among farmers in Guizhou Province should focus on the risks of wild mushroom poisoning in summer and homemade foods, and continuously improve farmers' awareness of the dangers of foodborne diseases and food safety.

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.

ObjectiveTo analyze the epidemiological characteristics of a local dengue fever cluster outbreak in Qingpu District of Shanghai in 2024, and to provide a reference for subsequent dengue fever prevention and control. MethodsSeven confirmed local dengue fever cases reported through the National Notifiable Infectious Diseases Surveillance System in Qingpu District of Shanghai in 2024 were selected as the research subjects. Descriptive epidemiological methods were used to conduct investigation and analysis from the aspects of onset, medical treatment and reporting, clinical symptoms, travel and contact history within 15 days before onset, and activity trajectories. ResultsA total of 7 cases were identified in this outbreak. None of the cases had a travel history to dengue-endemic areas within 15 days prior to onset, while all had shared exposure environments and mosquito bite histories, indicating a local clustered transmission pattern. The main clinical manifestations included fever (100.00%) and myalgia (42.86%). All 7 cases were positive for dengue virus serotype 2 (DENV-2) by nucleic acid testing. Genetic sequencing showed that the virus strains belonged to the Cosmopolitan genotype and were most closely related to the epidemic DENV strains circulating in southern China in recent years. ConclusionThis outbreak might be a local secondary infection caused by the short-term stay of dengue fever-infected individuals, and the possible source of importation was dengue fever endemic areas in southern China.

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/Aims: Data from Asia regarding the short-term and long-term outcomes for acute severe ulcerative colitis (ASUC) are limited. We assessed the outcomes of ASUC, identified the risk factors for colectomy, and compared colectomy rates between the pre-biologics and post-biologics eras in Taiwan. Methods: The patients with an ASUC diagnosis between January 2013 and March 2022 at 5 tertiary medical centers were retrospectively analyzed. Results: In total, 98 patients were enrolled, with 68.4% diagnosed in the post-biologics era. In 78.6% of the ASUC patients initially received intravenous steroid therapy, for which the success rate was 74.1%. As for rescue therapy, 15 patients (93.8%) received biologics and 1 (6.3%) received cyclosporin. Biologics rescue therapy had a 93.3% success rate. One (1%) mortality due to septic shock occurred. The colectomy rate for index ASUC admission was 11.2%. Patients receiving colectomy were predominantly male (P= 0.012) and at older age (P= 0.016). Higher C-reactive protein (P= 0.035), lower albumin (P= 0.017), and hemoglobin (P= 0.023) levels were associated with colectomy risk. During a median follow-up of 24 months, 13 patients (15.1%) had recurrent ASUC and 23.1% of patients received colectomy. The accumulated colectomy rate at 3 years did not differ between the pre- and post-biologics eras (16.1% vs. 13.4%, P= 0.270). Conclusions This is the first Asian study on ASUC to compare colectomy rates between the prebiologics and post-biologics eras, revealing no significant difference. The recurrent ASUC had a higher colectomy rate than the index ASUC.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

AIM: To compare the preoperative ocular biometry between Pentacam AXL and IOL Master 700 in cataract patients.METHODS:Prospective study. A total of 150 patients(150 eyes)with cataracts who were treated in our hospital from May to December 2024 were selected. The IOL Master 700 and Pentacam AXL were preoperatively used to measure axial length(AL), corneal curvature(K1, K2 and Km), anterior chamber depth(ACD), and white-to-white(WTW). The difference and consistency of the results of the two instruments were compared.RESULTS: There was no significant difference between the two instruments in the AL, K1, K2, Km, ACD, and WTW(all P>0.05). The Spearman correlation analysis showed that the two instruments positively correlated with the AL, K1, K2, Km, ACD and WTW of the operated eye(all P<0.001). The Bland-Altman analysis showed that for the Pentacam AXL and IOL Master 700, there were 5/150(3.3%), 7/150(4.7%), 4/150(2.7%), 5/150(3.3%), and 0 points outside the 95%LoA for the AL, K1, K2, Km, ACD, and WTW of the examined eyes, respectively, with all of these values less than 5%, indicating good consistency.CONCLUSION:The AL, K1, K2, Km, ACD and WTW of Pentacam AXL and IOL Master 700 in cataract patients before cataract phacoemulsification combined with IOL implantation show no significant differences, and have good correlation and consistency. The two instruments can be used interchangeably.

ObjectiveTo investigate the molecular mechanism by which Yifei Xuanfei Jiangzhuo prescription regulates the nuclear factor-κB （NF-κB）/NOD-like receptor protein 3 （NLRP3） signaling pathway to improve neuronal function in vascular dementia （VaD） rats. MethodsA VaD model was established by intermittently clamping the bilateral common carotid arteries （CCA） combined with bilateral vascular occlusion （2-VO）. Eighty-four SD rats were randomly divided into a blank group， sham group， model group， piracetam group （0.2 g·kg^-1）， and low-， medium-， and high-dose Yifei Xuanfei Jiangzhuo prescription groups （6.09， 12.18， and 24.36 g·kg^-1）. Drug administration began on day 7 after surgery， once daily for 28 consecutive days. Behavioral experiments were used to evaluate learning and spatial memory. Hematoxylin-eosin （HE） staining was applied to observe pathological morphological changes in the CA1 region of the hippocampus. Transmission electron microscopy was used to examine the ultrastructure of hippocampal neurons. Terminal deoxynucleotidyl transferase dUTP nick end labeling （TUNEL） was used to detect neuronal apoptosis in the CA1 region. Immunohistochemistry was performed to determine the positive expression rate of neuronal nuclear antigen （NeuN）. Immunofluorescence single staining was used to assess nuclear expression of NF-κB p65 in brain tissue. Western blot was used to detect the protein expression levels of inhibitor of κB kinase （IKK）， NF-κB p65， NLRP3， Caspase-1， apoptosis-associated speck-like protein （ASC）， and interleukin-1β （IL-1β）. ResultsCompared with the blank group， the model group showed a significant reduction in platform-crossing frequency （P0.01）， aggravated hippocampal injury， a significant increase in neuronal apoptosis （P0.05）， decreased NeuN positivity in the CA1 region （P0.05）， increased nuclear expression of NF-κB p65 （P0.05）， and significantly elevated expression of p-IKK， p-NF-κB p65， NLRP3， cleaved Caspase-1， ASC， and cleaved IL-1β （P0.05）. Compared with the model group， all drug-treated groups improved learning and spatial memory in VaD rats， alleviated hippocampal pathological injury and neuronal apoptosis， and protected neuronal ultrastructure. Yifei Xuanfei Jiangzhuo prescription at doses of 12.18 and 24.36 g·kg^-1 reduced hippocampal expression levels of p-IKK， p-NF-κB p65， NLRP3， Caspase-1， ASC， and cleaved IL-1β in VaD rats （P0.05）， showing dose-dependent inhibition of the NF-κB/NLRP3 signaling pathway. ConclusionYifei Xuanfei Jiangzhuo prescription may exert neuroprotective effects by regulating the NF-κB/NLRP3 signaling pathway， thereby reducing neuroinflammation and inhibiting hippocampal neuronal apoptosis.

ObjectiveTo investigate the molecular mechanism by which Yifei Xuanfei Jiangzhuo prescription regulates the nuclear factor-κB （NF-κB）/NOD-like receptor protein 3 （NLRP3） signaling pathway to improve neuronal function in vascular dementia （VaD） rats. MethodsA VaD model was established by intermittently clamping the bilateral common carotid arteries （CCA） combined with bilateral vascular occlusion （2-VO）. Eighty-four SD rats were randomly divided into a blank group， sham group， model group， piracetam group （0.2 g·kg^-1）， and low-， medium-， and high-dose Yifei Xuanfei Jiangzhuo prescription groups （6.09， 12.18， and 24.36 g·kg^-1）. Drug administration began on day 7 after surgery， once daily for 28 consecutive days. Behavioral experiments were used to evaluate learning and spatial memory. Hematoxylin-eosin （HE） staining was applied to observe pathological morphological changes in the CA1 region of the hippocampus. Transmission electron microscopy was used to examine the ultrastructure of hippocampal neurons. Terminal deoxynucleotidyl transferase dUTP nick end labeling （TUNEL） was used to detect neuronal apoptosis in the CA1 region. Immunohistochemistry was performed to determine the positive expression rate of neuronal nuclear antigen （NeuN）. Immunofluorescence single staining was used to assess nuclear expression of NF-κB p65 in brain tissue. Western blot was used to detect the protein expression levels of inhibitor of κB kinase （IKK）， NF-κB p65， NLRP3， Caspase-1， apoptosis-associated speck-like protein （ASC）， and interleukin-1β （IL-1β）. ResultsCompared with the blank group， the model group showed a significant reduction in platform-crossing frequency （P0.01）， aggravated hippocampal injury， a significant increase in neuronal apoptosis （P0.05）， decreased NeuN positivity in the CA1 region （P0.05）， increased nuclear expression of NF-κB p65 （P0.05）， and significantly elevated expression of p-IKK， p-NF-κB p65， NLRP3， cleaved Caspase-1， ASC， and cleaved IL-1β （P0.05）. Compared with the model group， all drug-treated groups improved learning and spatial memory in VaD rats， alleviated hippocampal pathological injury and neuronal apoptosis， and protected neuronal ultrastructure. Yifei Xuanfei Jiangzhuo prescription at doses of 12.18 and 24.36 g·kg^-1 reduced hippocampal expression levels of p-IKK， p-NF-κB p65， NLRP3， Caspase-1， ASC， and cleaved IL-1β in VaD rats （P0.05）， showing dose-dependent inhibition of the NF-κB/NLRP3 signaling pathway. ConclusionYifei Xuanfei Jiangzhuo prescription may exert neuroprotective effects by regulating the NF-κB/NLRP3 signaling pathway， thereby reducing neuroinflammation and inhibiting hippocampal neuronal apoptosis.