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.

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.

OBJECTIVE To improve the inventory turnover rate of traditional Chinese medicine （TCM） decoction pieces in hospitals and achieve refined inventory management for cost reduction and efficiency improvement. METHODS Inventory data of TCM decoction pieces in our hospital from 2022 to 2023 were collected. Based on the sale amount and demand coefficient of variation respectively， the ABC classification method and XYZ analysis method were adopted for classification. The two classification results were combined through a cross matrix to divide them into three-level management priorities： level Ⅰ （AX， AY， BX）， level Ⅱ （AZ， BY， CX）， and level Ⅲ （BZ， CY， CZ）. Differentiated inventory strategies were formulated for each level， and core indicators such as turnover rate and inventory cost before and after inventory management optimization were compared. RESULTS There were 58 types （14.22%） in level Ⅰ， 85 types （20.83%） in level Ⅱ， and 265 types （64.95%） in level Ⅲ. After inventory management optimization， the average inventory value of TCM decoction pieces decreased by 341 800 yuan， the average turnover rate increased by 73.03%， and the average turnover days decreased by 4.98 days. The differences in all indicators before and after optimization were statistically significant （ P ＜0.01）. CONCLUSIONS The ABC-XYZ analysis method can break through the single-dimensional limitation of the traditional ABC classification method， adapt to characteristics such as the strong seasonality of TCM decoction pieces， significantly optimize the inventory structure， improve turnover efficiency， and reduce operating costs. It provides a feasible plan for the refined and scientific management of hospital TCM warehouses.

The Pharmacovigilance Guidelines for Clinical Application of Traditional Chinese Medicine Injections （hereinafter referred to as the Guidelines） were released by the China Association of Chinese Medicine， with the standard number T/CACM 1563.4—2024. It is the first specialized guideline in China on the approach to pharmacovigilance activities for the clinical application of traditional Chinese medicine injections （TCMIs）. The Guidelines were jointly developed by the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， along with 30 experts in TCM pharmacovigilance， clinical practice （TCM， as well as integrated traditional Chinese and Western medicine），and evidence-based medicine from across the country. This publication filled the gap in standard documents in this field， both domestically and internationally. The Guidelines were formulated according to GB/T1.1—2020 Directives for standardization—Part 1： Rules for the structure and drafting of standardizing documents， the WHO Handbook for Guideline Development，and other methodological norms. Based on international norms，national laws and regulations，and scientific research results in the field of pharmacovigilance， methods adopted included expert interviews，literature research，nominal group technique， and Delphi method. Then， key points for pharmacovigilance for TCM injections were summarized and clarified in the four critical sections of "monitoring"，"identification"，"assessment"，and "control". The development process of the Guidelines included project initiation， international registration， expert interviews， literature search， and evaluation. Based on the research results of these steps，a draft was formed and revised through multiple rounds of in-group expert discussion and peer evaluations by 56 external experts. After revisions by the working group based on the feedback， the final version was formed. The Guidelines came into effect on January 8，2024，providing suggestions and reference norms for pharmacovigilance in the clinical application of TCMIs. To further promote the application and popularization of the Guidelines and help pharmacovigilance personnel better understand the development process，this study elucidates the background，methodological framework，and key development steps of the Guidelines.

The Pharmacovigilance Guidelines for Clinical Application of Traditional Chinese Medicine Injections （hereinafter referred to as the Guidelines） were released by the China Association of Chinese Medicine， with the standard number T/CACM 1563.4—2024. It is the first specialized guideline in China on the approach to pharmacovigilance activities for the clinical application of traditional Chinese medicine injections （TCMIs）. The Guidelines were jointly developed by the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， along with 30 experts in TCM pharmacovigilance， clinical practice （TCM， as well as integrated traditional Chinese and Western medicine），and evidence-based medicine from across the country. This publication filled the gap in standard documents in this field， both domestically and internationally. The Guidelines were formulated according to GB/T1.1—2020 Directives for standardization—Part 1： Rules for the structure and drafting of standardizing documents， the WHO Handbook for Guideline Development，and other methodological norms. Based on international norms，national laws and regulations，and scientific research results in the field of pharmacovigilance， methods adopted included expert interviews，literature research，nominal group technique， and Delphi method. Then， key points for pharmacovigilance for TCM injections were summarized and clarified in the four critical sections of "monitoring"，"identification"，"assessment"，and "control". The development process of the Guidelines included project initiation， international registration， expert interviews， literature search， and evaluation. Based on the research results of these steps，a draft was formed and revised through multiple rounds of in-group expert discussion and peer evaluations by 56 external experts. After revisions by the working group based on the feedback， the final version was formed. The Guidelines came into effect on January 8，2024，providing suggestions and reference norms for pharmacovigilance in the clinical application of TCMIs. To further promote the application and popularization of the Guidelines and help pharmacovigilance personnel better understand the development process，this study elucidates the background，methodological framework，and key development steps of the Guidelines.

Diabetic kidney disease（DKD） is a chronic kidney structural and functional disorder caused by diabetes. With the global prevalence of diabetes continuing to rise， DKD has gradually become a major cause of chronic kidney disease and end-stage renal disease（ESRD）， posing a serious threat to patients' quality of life and long-term health outcomes. Studies have shown that apoptosis plays a pivotal role in the development and progression of DKD， with its mechanisms involving abnormal activation of multiple signaling pathways such as Toll-like receptor 4（TLR4）/nuclear transcription factor-κB（NF-κB）/B-cell lymphoma-2（Bcl-2）/cysteinyl aspartate-specific proteinase（Caspase）-3， protein kinase R-like endoplasmic reticulum kinase（PERK）/eukaryotic initiation factor 2α（eIF2α）/activating transcript factor 4（ATF4）/CCAAT enhancer-binding protein homologous protein（CHOP）， phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β）， Janus kinase 2（JAK2）/signal transducer and activator of transcription 3（STAT3）， adenosine monophosphate-activated protein kinase（AMPK）/mammalian target of rapamycin（mTOR） and silent information regulator 1（SIRT1）/tumor suppressor protein 53（p53）， thereby accelerating renal pathological damage in DKD. Extensive evidence-based medical studies have confirmed that traditional Chinese medicine（TCM）， leveraging its unique therapeutic advantages of multi-target， multi-component and multi-pathway approaches， has demonstrated remarkable efficacy and favorable safety profiles in treating DKD. Recent studies have demonstrated that active components of TCM can specifically target and modulate key effectors in apoptotic signaling pathways. Meanwhile， traditional compound formulations exert synergistic effects through multiple approaches such as replenishing deficiency and activating blood circulation， detoxifying and dredging collaterals， tonifying kidney essence， and removing stasis and purging turbidity， thereby comprehensively regulating critical pathological processes including endoplasmic reticulum stress and mitochondrial apoptosis pathways. This combined therapeutic approach of molecular targeting and holistic regulation provides novel strategies for delaying the progression of DKD. Based on this， this paper provides an in-depth analysis of key apoptotic signaling pathways and their regulatory mechanisms， while systematically summarizing recent research advances regarding the therapeutic effects of TCM active components， compound formulations， and proprietary Chinese medicines on DKD through modulation of these pathways， with particular emphasis on their underlying molecular mechanisms. These findings not only elucidate the modern scientific connotation and theoretical basis of TCM in treating DKD but also establish a solid theoretical and practical foundation for promoting the wider clinical application and further research of TCM in the field of DKD treatment.

OBJECTIVE To form an expert consensus on the clinical application of parenteral direct thrombin inhibitors （DTIs） in patients during the perioperative period. METHODS Led by Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital （the Affiliated Hospital of UESTC）， a multidisciplinary working group was established. Through literature review and the Delphi method， clinical questions related to the rational perioperative use of parenteral DTIs were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” framework； systematic searches were conducted in CNKI， Medline， Embase and other databases. Relevant evidence from randomized controlled trials and cohort studies was included and synthesized. Evidence quality was assessed using the Grades of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through multiple rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven recommendations （each with an expert consensus rate exceeding 90%） on the use of parenteral DTIs in perioperative patients were developed. These recommendations specify drug selection， dosing ranges， key monitoring points， and safety management strategies for parenteral DTIs in various scenarios， including the perioperative period of ventricular assist device implantation， the perioperative period of cardiac surgery， perioperative patients with lower-extremity atherosclerotic disease， the perioperative period of percutaneous coronary intervention in patients with acute coronary syndrome， the perioperative period of carotid artery stenting in patients with carotid stenosis， the perioperative period of patients with right heart thrombosis， and patients who develop related thrombosis and dysfunction after a central venous catheter insertion. In addition， warning and management pathways for perioperative bleeding and thrombotic events were proposed. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in perioperative period.