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.

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.

According to traditional Chinese medicine （TCM） theory， impaired spleen transportation function disrupts nutrient distribution， causing metabolic accumulation of lipids that transform into pathogenic phlegm-dampness. These pathological factors disseminate through the San Jiao and obstruct meridian pathways， ultimately forming the pathogenesis described as "all disorders involve phlegm". Phlegm and dampness share common pathogenic origins but manifest distinct clinical manifestations. Dampness， as the precursor， may congeal into phlegm， while existing phlegm accumulation can further exacerbate dampness stagnation， thereby establishing a self-perpetuating pathological cycle. Modern medical research has confirmed that the essence of "phlegm-dampness" syndrome is closely associated with energy metabolism disorders， serving as a common pathological basis for metabolic syndrome， type 2 diabetes mellitus， atherosclerosis， and other major chronic diseases. As a crucial vehicle for medical experimental research， disease-syndrome combination animal models serve as an indispensable means to advance the modernization of TCM. Currently， based on classical theories such as "rich and greasy foods produce phlegm" and "physical coldness combined with cold consumption causes external pathogens to invade the skin and hair， thereby generating internal dampness"， researchers primarily employ two paradigms to construct animal models of phlegm-turbidity， dampness obstruction， and phlegm-dampness syndromes： the first involves simulating TCM etiological factors （through methods like dietary irregularities， imblanace between work and rest， and combined internal-external dampness exposure）， while the second combines disease with syndrome differentiation （inducing pathological changes through physical， chemical， or biological interventions）. Through comprehensive evaluation incorporating macroscopic observation and microscopic index detection， model animals undergo systematic biological and pathological assessment， with further syndrome type verification achieved via the "prescription-based syndrome detection" approach. However， existing models still exhibit significant deficiencies in both the standardization of modeling methodologies and the systematization of evaluation criteria. This paper reviews the strategies for constructing "phlegm-dampness" syndrome animal models and their corresponding evaluation indices， focusing on the pathological correlations among different modeling approaches. The aim is to provide methodological guidance for research on TCM syndromes related to "phlegm-dampness" syndrome and to support the development of TCM therapies for resolving phlegm and eliminating dampness. This study not only contributes to advancing the standardization of TCM syndrome research but also provides crucial technical support for the modernization of TCM.

We analyzed the epidemiological features and spatial distribution characteristics of human brucellosis in Jining city from 2014 to 2023,to provide a reference for further development of targeted prevention and control strategies and measures.Descrip-tive epidemiological methods were used to analyze the epidemiological characteristics of brucellosis cases in Jining from 2014 to 2023.The spatial regional correlation of brucellosis incidence in Jining and the clustering patterns of local areas were studied through spatial autocorrelation analysis with townships as the basic unit.A total of 3 520 cases of brucellosis were reported in Jining from 2014 to 2023,and the average annual incidence rate was 4.23/100 000,thus indicating a fluctuating trend overall.Reported cases peaked from March to August,and a sex ratio of 2.71 males to 1 female was observed.The 40-59 year age group had the most reported cases(50.39％).The incidence of brucellosis in Jining showed an imbalanced spatial distribution.Brucellosis incidence showed a spatially clustered distribution(Moran's I>0,P<0.05).Hotspots were distributed primarily in Sishui,Qufu,and Zoucheng.A total of one class Ⅰ clustering area and one class Ⅱ clustering area were detected in the spatial and temporal scans,and were located in Sishui,Qufu,and Liangshan county.After pathogenic AMOS-PCR typing analysis,64 Brucella isolates collected from Jinan City from 2022 to 2024 were all of the sheep strain,and sheep biovar 3 was predominant(70.31％).In 2014-2023,although Jining City experienced a high incidence of brucellosis,a downward trend was observed.Brucellosis showed a spatial clustering pattern concentrated in the northeastern region.Therefore,awareness and education must be strengthened among brucellosis practitioners in cluster areas,to en-hance case surveillance,improve the level of protection,and achieve early detection and treatment.

The symptom science model identifies complex symptoms and measures their phenotypic characteristics.It provides an in-depth analysis of symptom behaviors and biological mechanisms,aiding healthcare professionals in early symptom detection and initiating appropriate diagnostic and treatment measures.The model supports personalized interventions,aiming to achieve precision care and ultimately improve patient health.This study reviews the development and scope of the symptom science model,analyzes its current applications in chronic kidney disease,and explores its implications for symptom management in this condition.The aim is to offer insights and references for the scientific management of chronic kidney disease symptoms.

Objective To evaluate the safety and efficacy of valve-in-valve transcatheter mitral valve replacement(ViV-TMVR)in patients with bioprosthetic valve degeneration who are at high surgical risk.Methods This study is a multi-center,retrospective cohort analysis of 20 consecutive patients who underwent transseptal ViV-TMVR using the Edwards SAPIEN 3 transcatheter heart valve(THV).The primary endpoints include technical success and procedural success,both defined according to the Mitral Valve Academic Research Consortium(MVARC)criteria,as well as mortality and functional change assessed based on New York Heart Association(NYHA)classification at 30-days and six months post-procedure.Clinical follow-up assessments are conducted at 30-days and six months.Results From February 2021 to October 2022,a total of 20 patients with symptoms of bioprosthetic valve degeneration were enrolled across nine sites in China.The patients had a mean age of(73.5±5.5)years,with 85.0％being females and 70.0％classified as NYHA class Ⅲ/Ⅳ.The study achieved a 100.0％technical success rate and a 90.0％procedural success rate finally.All patients remained alive during the 30-day follow-up period.However,six months post-intervention,two patients(10.0％)were re-hospitalized due to heart failure,and sadly,one of them(5.0％)died.None of the patients reported any adverse events related to ViV-TMVR during the follow-up period.Notably,there was a significant improvement in NYHA class compared to baseline(P=0.0004)at six-month follow-ups.Conclusions The transseptal ViV-TMVR technique proved to be highly successful and was associated with significant improvement in NYHA class function.These findings strongly suggest that it serves as a safe and efficient treatment alternative for high-risk patients suffering from bioprosthetic valve degeneration.

This study was aimed at exploring the mechanism underlying the effects of nitidine chloride against Talaromyces marnef-fei through network pharmacology analysis.We collected NC and TM action targets from various databases;constructed a protein-protein interaction(PPI)network by using common drug and disease targets;and performed KEGG pathway and GO enrichment analy-ses.In vitro cellular experiments were conducted to test the antibacterial ability of NC at various concentrations,qPCR was used to de-tect the mRNA expression of genes in the target pathway,and WB was used to examine the expression of proteins associated with tar-get signaling pathways in cells.We identified 153 target genes for NC and 2 095 target genes for TM,among which 23 targets over-lapped.By integrating the PPI network with KEGG enrichment analysis,we selected key target genes in the MAPK signaling pathway,such as FLT1,FLT3,CD38,and PRF1.The CFU results indicated that NC had favorable antibacterial capability.Moreover,qPCR demonstrated that NC downregulated the mRNA expression of FLT1,FLT3,and RPS6KA3,and upregulated the mRNA expression of MAP3K8.WB findings indicated that NC downregulated the expression of RSK2,VEGF,and FLT3 proteins,and upregulated the ex-pression of MAP3K8 protein.NC may exert its anti-TM effects by downregulating the expression of RSK2,VEGF,and FLT3 proteins,thereby inhibiting MAPK pathway activation.The potential targets and signaling pathways underlying NC's anti-TM action may pro-vide new insights to guide the clinical application of NC.

We analyzed the epidemiological features and spatial distribution characteristics of human brucellosis in Jining city from 2014 to 2023,to provide a reference for further development of targeted prevention and control strategies and measures.Descrip-tive epidemiological methods were used to analyze the epidemiological characteristics of brucellosis cases in Jining from 2014 to 2023.The spatial regional correlation of brucellosis incidence in Jining and the clustering patterns of local areas were studied through spatial autocorrelation analysis with townships as the basic unit.A total of 3 520 cases of brucellosis were reported in Jining from 2014 to 2023,and the average annual incidence rate was 4.23/100 000,thus indicating a fluctuating trend overall.Reported cases peaked from March to August,and a sex ratio of 2.71 males to 1 female was observed.The 40-59 year age group had the most reported cases(50.39％).The incidence of brucellosis in Jining showed an imbalanced spatial distribution.Brucellosis incidence showed a spatially clustered distribution(Moran's I>0,P<0.05).Hotspots were distributed primarily in Sishui,Qufu,and Zoucheng.A total of one class Ⅰ clustering area and one class Ⅱ clustering area were detected in the spatial and temporal scans,and were located in Sishui,Qufu,and Liangshan county.After pathogenic AMOS-PCR typing analysis,64 Brucella isolates collected from Jinan City from 2022 to 2024 were all of the sheep strain,and sheep biovar 3 was predominant(70.31％).In 2014-2023,although Jining City experienced a high incidence of brucellosis,a downward trend was observed.Brucellosis showed a spatial clustering pattern concentrated in the northeastern region.Therefore,awareness and education must be strengthened among brucellosis practitioners in cluster areas,to en-hance case surveillance,improve the level of protection,and achieve early detection and treatment.

Objective:To explore the clinical significance of chromosome microarray analysis (CMA) in the prenatal detection of DMD gene variants in fetuses without family history during prenatal diagnosis.Methods:A retrospective analysis was conducted on amniotic fluid samples from 12 629 pregnant women who underwent CMA prenatal diagnosis due to high-risk factors at Women and Children′s Hospital Affiliated to Qingdao University between January 2019 and December 2024. Samples with CMA-indicated DMD gene variants were further verified by multiplex ligation-dependent probe amplification (MLPA).Results:(1) Among 12 629 amniotic fluid samples, CMA detected 11 samples with DMD gene deletions or duplications (6 male and 5 female fetuses), which were confirmed by MLPA. (2) All 11 samples with DMD gene variants had no family history of genetic diseases, including 5 deletions and 6 duplications. All of the 5 DMD gene deletions occurred in male fetuses and were all pathogenic, and the pregnant women chose to terminate the pregnancies. Among the 6 DMD gene duplications cases, 1 male fetus was diagnosed as pathogenic and had pregnancy termination; the other 5 duplication cases were female fetuses, in which 1 were pathogenic and 4 were likely pathogenic. They continued pregnancy until delivery, and follow-up showed no DMD-related symptoms. (3) Pedigree analysis revealed that among the 11 samples with DMD gene variants, 3 were de novo mutations, 7 were inherited from mothers, and 1 had an unknown origin.Conclusions:For fetuses without pseudohypertrophic muscalar dystrophy family history but requiring invasive prenatal diagnosis for other reasons, CMA helps to increase the detection of DMD gene variants in fetuses. Testing pregnant women for DMD pathogenic gene carriers could effectively prevent the birth of pseudohypertrophic muscalar dystrophy children.