Objective: To assess the effect of 12-year-old children s pit and fissure sealants on the health of first permanent molars, so as to provide evidence for optimizing caries prevention strategies among children. Methods: In March 2025, a cluster random sampling method was used to conduct oral examinations on 965 students aged 12 from Chengdu s 2021 Comprehensive Intervention Program for Pediatric Oral Diseases. Data from the Comprehensive Intervention System for Children s Oral Diseases were referenced. Participants were divided into a sealed group ( n =755) and an unsealed group ( n =210) based on whether they had received sealants on their first permanent molars. Chi square test or analysis of variance were used to compare indicators such as caries incidence, new caries detection rate, and new caries mean (DMFT increment) between the two groups Results: The sealed group showed significantly lower caries incidence, new caries detection rate, and new caries mean (33.38%, 17.65%, 0.59±1.00) compared to the unsealed group (43.81%, 24.70%, 0.87±1.22)( χ 2/F =7.79, 18.26, 9.55, all P <0.05). However, no significant difference was found in the filled teeth ratio between the two groups (20.38% , 20.16%; χ 2=0.01, P =0.94). In girls, the sealed group exhibited significantly lower caries incidence, new caries detection rate, and new caries mean (36.78%, 20.99%, 0.69± 1.10 ) than the unsealed group (57.55%, 33.52%, 1.15±1.29) ( χ 2/F =14.42, 23.76, 10.92, all P <0.05), whereas no significant differences were observed between boys in the sealed (30.47%, 14.85%, 0.50±0.89) and unsealed groups (29.81%, 16.18%, 0.59± 1.08) ( χ 2/F =0.02, 0.41, 0.74, all P >0.05). Boys had significantly lower new caries detection rates and new caries means than girls in both groups ( χ 2/F =16.20, 6.94; 29.93, 11.84, all P <0.05). In urban areas, the sealed group had lower new caries detection rates and new caries means (19.37%, 0.68±1.04) than the unsealed group (24.66%, 0.90±1.20) ( χ 2/F =6.86, 3.94, both P <0.05). In suburban areas, all indicators for the sealed group (24.71%, 13.77%, 0.42±0.87) were significantly lower than those for the unsealed group (38.81%, 24.77%, 0.82±1.28) ( χ 2/F =5.28, 15.36, 6.00, all P <0.05). Indicators from specialized dental institutions (11.25%, 4.81%, 0.16±0.56) were significantly lower than those from county level or above general hospitals (33.33%, 19.11%, 0.38±1.00) and primary healthcare institutions (37.59%, 19.24%, 0.67±1.05) ( χ 2/F =20.99, 34.31, 21.08 , all P <0.01). Conclusions The 12-year-old children s pit and fissure sealants effectively reduce the caries incidence in first permanent molars, particularly showing significant effectiveness in girls and suburban children. Intervention strategies should be optimized according to gender.

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.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective To explore the influencing factors of physical activity(PA)in overweight and obese children from the individual,family and environment levels.Methods Using a stratified cluster random sampling method,315 children[mean age:9.57±1.45 years;201 boys(63.8%)and 114 girls(36.2%)]were selected from two classes of every grade of one public elementary school in the four main urban districts of Shijiazhuang.Hierarchical linear regression models were employed to ana-lyze the influence of 20 factors on individual,family and environment levels on PA among them.Re-sults Children's age(β=-0.02),sex(βmale=0.12),sedentary time(β=-0.07),ball skills(β=0.12),perceived motor competence(β=0.18),primary caregiver's PA(β=0.17),parental PA support(β=0.10)and home/neighborhood PA environment(β=0.40)were significant factors of their moderate-to-vigorous physical activities(P<0.05).For light physical activity(LPA)and total PA,only sedentary time(βLPA=-0.57,βtotal=-0.52),parental support for children's PA(βLPA=0.15,βtotal=0.16),and home/neighborhood PA environment(βLPA=0.17,βtotal=0.15)were significant predictors(Pall<0.05).Conclusion The influencing factors of PA among overweight and obese children are complex and multidimensional.Elements at the individual,family and environment levels all play significant roles.Therefore,future interventions and policies aimed at promoting PA in this population should take these multifaceted de-terminants into consideration.

Background and Aims:Pancreatic cancer is one of the most aggressive malignancies of the digestive system and is associated with an inferior prognosis.In recent years,its incidence has shown a trend toward younger onset.Early-onset pancreatic cancer(EOPC),defined as pancreatic cancer diagnosed at≤50 years of age,has been increasing annually and may possess distinct biological and prognostic characteristics.Given the limited data from China,this study aimed to investigate the clinicopathological features and prognostic outcomes of EOPC patients.Methods:Clinical data of 113 patients with EOPC admitted to Xiangya Hospital,Central South University,from January 2017 to December 2023 were retrospectively analyzed.Variables included demographic characteristics,clinicopathological features,and survival information.Kaplan-Meier survival curves were plotted,and differences in survival between the surgical and non-surgical groups were compared.Results:The median age at diagnosis was 46(42-49)years,and males accounted for 65.49%of cases.Blood type A(40.71%)and type O(34.51%)were most common.The main presenting symptoms were abdominal pain(69.91%),weight loss(62.83%),jaundice(43.36%),and abdominal distension(36.28%).Imaging findings showed bile duct dilation in 32.74%,pancreatic duct dilation in 39.82%,vascular invasion in 59.29%,and distant metastasis in 52.21%of patients.Histopathology revealed that adenocarcinoma and ductal adenocarcinoma accounted for 93.81%of all cases,with predominantly moderate or poor differentiation(76.10%).Tumors were the most frequently located in the pancreatic head(65.42%).TNM staging showed lymph node metastasis in 77.88%and stage Ⅳ disease in 52.21%.Laboratory tests demonstrated markedly elevated CA19-9 levels.Kaplan-Meier analysis indicated a median overall survival of 18.6 months for the entire cohort,with significantly longer survival in the surgical group compared with the non-surgical group(29.4 months vs.13.8 months,P=0.001 5).Conclusion:EOPC predominantly affects males and tends to arise in the pancreatic head.It is often diagnosed at an advanced stage or with distant metastasis and is characterized by poor differentiation and strong invasiveness.Surgical resection markedly improves survival and remains the key to prolonged prognosis.Young individuals presenting with unexplained abdominal pain,weight loss,or jaundice should be carefully evaluated through imaging to enable early diagnosis and timely surgical intervention.Future multicenter,large-sample prospective studies are warranted to validate these findings further.

Objective The aim of this study was to investigate the key genes that regulate colorectal cancer(CRC)metasta-sis,evaluate the effects of exosomal miR-151A-3P derived from CRC on the proliferation and migration,and explore the possibility of exosomal miR-151A-3P as a prognostic biomarker for CRC patients.Methods High-throughput sequencing was performed to screen the differentially expressed miRNAs in serum exosomes of metastatic CRC patients.RT-qPCR was used to verify the expression of differentially expressed miRNAs in CRC specimens.After mimics overexpression or knockdown of miR-151A-3P,CCK-8 and EdU assays were used to detect cell proliferation,and Scratch wound healing and Transwell assays were used to detect cell migration and in-vasion capability.A BALB/c nude mouse model was used to evaluate the effect of exosomal miR-151A-3P on the metastatic ability of CRC cells.Results The sequencing results showed that compared with non-metastatic CRC patients,the expression of miR-151A-3P was significantly increased in serum exosomes of metastatic CRC patients(P<0.001).The results were validated by RT-qPCR and found that miR-151A-3P was highly expressed in both serum exosomes and tumor tissues of metastatic CRC patients(P<0.001).The overall survival of CRC patients with high expression of serum exosomal miR-151A-3P was shorter than that of CRC pa-tients with low expression(P=0.029).After silencing miR-151A-3P,the cell proliferation,migration,and invasion abilities of CRC cells were decreased(P<0.05),while overexpression of miR-151A-3P could promote the proliferation,migration and invasion of CRC cells(P<0.05).In the BALB/c nude mouse colorectal cancer model,the administration of exosomal miR-151A-3P led to an increase in the number of lung metastases in BALB/c nude mice(P<0.05).Conclusion CRC-derived exosomal miR-151A-3P promotes the proliferation and migration of CRC cells,and is associated with poor prognosis of CRC patients.

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.

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.