Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

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.

ObjectiveTo investigate the association of the single nucleotide polymorphism （SNP） of the insulin-like growth factor binding protein-3 （IGFBP3） gene at rs10225396 （A>G） locus with the susceptibility to hepatocellular carcinoma， as well as its potential molecular regulatory mechanisms， and to provide novel genetic biomarkers and a theoretical basis for early screening and precise targeted therapy for hepatocellular carcinoma. MethodsA total of 192 patients with hepatocellular carcinoma who were admitted to The Affiliated Hospital of Yanbian University and Yanbian Cancer Hospital from January 2009 to August 2016 were enrolled as experimental group， and 190 healthy individuals who underwent physical examination in Physical Examination Center of Yanbian Hospital during the same period of time were enrolled as control group. Peripheral blood samples were collected from all subjects， and after DNA was extracted from whole blood， the DNA samples meeting quality standards were sent to Beijing Genomics Institute Research Center Co.， Ltd.， for Mass ARRAY mass spectrometry， while genotyping was completed. The independent-samples t test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. A binary Logistic regression model was used to analyze the association of the SNP of the IGFBP3 gene at rs10225396 locus with the susceptibility to hepatocellular carcinoma， and odds ratio （OR） and 95% confidence interval （CI） were calculated to assess the risk of developing hepatocellular carcinoma in individuals carrying different genotypes. ResultsThere were two alleles （G and A） at the rs10225396 locus of the IGFBP3 gene， yielding the three genotypes of AA， AG， and GG， and its genotype distribution was consistent with the Hardy-Weinberg equilibrium （χ²=0.072， P=0.789）. The stratified genetic analysis showed that carriers of the IGFBP3 rs10225396 AA genotype had a significant increased risk of hepatocellular carcinoma among individuals of age <63 years， male sex， smoking history， drinking history， and the Chinese Korean population （all P<0.001）. The binary Logistic regression analysis showed that after adjustment for related risk factors in the codominant model， the population with genotype AG and GG had a significant reduction in the risk of hepatocellular carcinoma compared with the population with genotype AA （P<0.001）， and in the dominant model， the population with genotype AG+GG had a significant reduction in the risk of hepatocellular carcinoma compared with the population with genotype AA （P<0.001）. ConclusionThrough a genotyping analysis of hepatocellular carcinoma patients and healthy individuals in Yanbian Korean Autonomous Prefecture of Jilin Province， China， this study shows that genotype AA at rs10225396 locus of the IGFBP3 gene is significantly associated with the susceptibility to hepatocellular carcinoma， and this genotype can significantly increase the risk of developing hepatocellular carcinoma with the presence of specific risk factors， which provides a potential genetic marker for early screening and precise treatment of hepatocellular carcinoma.

The Huangdi Neijing proposes the " using bitter herbs to nourish or purge" theory to guide clinical prescription and formulation of herbal remedies based on the physiological characteristics and functions of the five zang viscera, along with the properties and flavors of medicinal herbs. This study explored diabetic kidney disease pathogenesis and treatment based on the " using bitter herbs to nourish or purge" theory. Kidney dryness is a key pathological factor in diabetic kidney disease, and the disharmony of kidney dryness is an essential aspect of its pathogenesis. Strengthening is the primary therapeutic principle, and kidney dryness is a persistent factor throughout the occurrence and progression of diabetic kidney disease. In the early stage, the pathogenesis involves heat-consuming qi and injuring yin, leading to kidney dryness. In the middle stage, the pathogenesis manifests as qi deficiency and blood stasis in the collaterals, resulting in turbidity owing to kidney dryness. In the late stage, the pathogenesis involves yin and yang deficiency, with kidney dryness and disharmony. This study proposes the staging-based treatment based on the " need for firmness" characteristic of the kidney. The aim is to provide new insights for clinical diagnosis and treatment in traditional Chinese medicine by rationally using pungent, bitter, and salty medicinal herbs to nourish and moisturize the kidney. This approach seeks to promote precise syndrome differentiation and personalized treatment for different stages of diabetic kidney disease, thereby enhancing clinical efficacy.

Objective To evaluate the effects of fasting and high-fat diet on the pharmacokinetics of rabeprazole sodium enteric-coated tablets in healthy Chinese subjects.Methods A single-center,randomized,open,two-agent,two-sequence,four-cycle,fully repeated crossover,single-dose trial design was used in this study,healthy subjects were assigned to receive single dose of rabeprazole sodium enteric-coated tablets 0.1 g in either fasting or high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of rabeprazole sodium enteric-coated in plasma were determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS),the model method of the non-compartmental was used to calculate the pharmacokinetic parameters by Phoenix WinNonlin 8.2.Results The main pharmacokinetic parameters of rabeprazole sodium enteric-coated tablets in fasting state and high-fat diet state were as follows:Cmax were(339.63±156.47)and(318.86±132.13)ng·mL-1;t1/2 were(2.34±0.68)and(3.60±2.40)h;AUC0_t were(556.62±251.65)and(528.50±201.78)ng·mL-1·h;AUC0-∞ were(563.39±255.69)and(535.15±203.24)ng·mL-1·h;tmax were 3.65 and 6.99 h.After high-fat diet,the Cmax and AUC of rapeprazole sodium after high-fat and high-calorie diet decreased,Cmax decreased by 6.12％,AUC0-t decreased by 5.05％,AUC0-∞ decreased by 5.01％,andtmaxwas delayed by about 3.34 h.Cmax,AUC0-t and AUC0-∞ 90％confidence interval were 73.13％-115.10％,83.22％-112.28％and 83.40％-112.13％,respectively.Neither was between 85.00％-125.00％.Conclusion High-fat diet affects the absorption rate and degree of rabeprazole sodium enteric-coated,so it is suitable to be administered on an empty stomach.

Bovine rotavirus(BRV)is an important pathogen causing diarrhea in calves.To understand the genomic charac-teristics and genetic variations in bovine rotavirus,and to further enrich data on the biological characteristics of rotavirus,we aimed to amplify 11 gene segments of the isolated and cultured G6P[1]bovine rotavirus BLL strain,perform whole genome se-quencing,and analyze the molecular characteristics.MEGA7.0 and DNAMAN software were used for homology and typing a-nalysis,and the whole genome phylogenetic tree was constructed to analyze genetic evolution relationships.The complete geno-type of the BLL strain was G6-P[1]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis of the VP7 and VP4 genes of the BLL strain showed that the VP7 gene had the highest homology with RVA/Cow-wt/HB01/China/2021,and the VP4 gene of the BLL strain was in the same branch as RVA/Human-tc/ISR/Ro8059/1995.From the sequence alignment of VP8*amino acids,the sialic acid domain of the BLL strain was found to be similar to that in other P[1]strains,but different from those in other types of strains,except for residue 189,which was the same as that in Ro8059 but different from that in other strains.The results suggested that the BLL strain might potentially infect humans.Therefore,continued monitoring and study of the biological characteristics of this strain are necessary to provide more information and evidence supporting further research on the cross-species transmission of group A rotavirus in China.

Background and Aims:Studies have shown that the long non-coding RNA(lncRNA)FGD5-AS1 functions as an oncogene in gastric cancer(GC).Our previous bioinformatics analysis revealed potential binding sites between FGD5-AS1 and microRNA-142-3p(miR-142-3p),as well as between miR-142-3p and pyruvate dehydrogenase kinase 1(PDK1).Therefore,this study aimed to investigate the expression and functional role of the FGD5-AS1/miR-142-3p/PDK1 axis in GC cells.Methods:Dual-luciferase reporter assays were used to verify the targeting relationships between FGD5-AS1 and miR-142-3p,and between miR-142-3p and PDK1.qRT-PCR was conducted to measure the expression levels of FGD5-AS1,miR-142-3p,and PDK1 in GC tissues.A knockdown model of FGD5-AS1(sh-FGD5-AS1)and an miR-142-3p inhibitor were constructed and transfected,alone or in combination,into BGC823 GC cells.Cellular behaviors,including proliferation(CCK8,EdU),apoptosis(flow cytometry),migration,and invasion(Transwell assays),were assessed,along with related protein expression(Western blot).A subcutaneous xenograft model in nude mice was used to evaluate the effect of FGD5-AS1 on tumor growth in vivo.Results:The dual-luciferase assays demonstrated that miR-142-3p mimics significantly reduced the luciferase activity of wild-type(WT)FGD5-AS1 and PDK1 reporters(both P<0.05),but had no effect on mutant(MUT)reporters,confirming a direct binding relationship.Knockdown of FGD5-AS1 led to upregulation of miR-142-3p and downregulation of PDK1 in GC cells,with reduced proliferation,migration,and invasion,and enhanced apoptosis(all P<0.05);these effects were reversed by the miR-142-3p inhibitor.In vivo,FGD5-AS1 knockdown significantly inhibited tumor growth in nude mice and decreased Ki-67 and PDK1 expression in tumor tissues(all P<0.05).Conclusion:FGD5-AS1 may act as a ceRNA that sponges miR-142-3p,thereby relieving its suppression on PDK1,and promoting GC cell proliferation and invasion as well as tumor progression.The FGD5-AS1/miR-142-3p/PDK1 axis plays a critical role in the development of GC and may serve as a potential therapeutic target.

In order to the phage therapy for Clostridium perfringens(Cp),Cp was used as the host bacterium to screen specific phages from sewage collected from a large-scale beef cattle farm in a region of Shandong Province.Transmission electron microscopy was utilized to observe the mor-phological structure of the phages.Their characteristics were analyzed through the optimal multi-plicity of infection(MOI),host range,one-step growth curve,and antibacterial experiments.The re-sults showed that one phage was successfully isolated from 18 sewage samples.The plaque was transparent without a halo,exhibiting a broad host range and no lytic reaction with other tested bacteria.The optimal MOI was 0.1,and the phage entered the burst phase in 30 min.The phage maintained high titers at pH3-13 and remained active after treatment at 60℃ for 60 min,demon-strating good stability.Mice were infected with CP and treated with bacteriophage.Animal experi-ments showed that the isolated bacteriophage had a significant inhibitory effect on CP.The results indicated that the isolated phage,designated vB-CpP-Bp7,was a virulent phage with excellent lytic capability,acid-base stability,and thermal stability,laying a foundation for further application of this phage in phage therapy.