Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

ObjectiveTo obtain the gene sequences of major histocompatibility complex (MHC ) Ⅱgenes of Wuzhishan pigs, analyze their genetic information, and explore the biological functions of their MHC system. MethodsSpleen samples were collected from 3 adult male Wuzhishan pigs. Primers were designed according to MHCⅡ gene sequences, and the coding sequences of Wuzhishan pig MHCⅡ genes were amplified by RT-PCR. Sanger sequencing was performed to determine the full-length sequences. Bioinformatics tools were employed to analyze the physicochemical properties, phylogenetic relationships, conserved motifs, structural domains, chromosomal localization, and syntenic relationships of these genes. ResultsEight MHCⅡ genes were identified in Wuzhishan pigs, designated as SLA-DRA, SLA-DQA, SLA-DQB, SLA-DRB, SLA-DOB, SLA-DMB, SLA-DMA and SLA-DOA. The full-length sequences of these genes were determined by Sanger sequencing and subsequently deposited in GenBank under accession numbers PQ182796, PQ182797, PQ182798, PQ182799, PQ182800, PQ182801, PQ182802, and PQ164779. Phylogenetic analysis showed that the six MHCⅡ genes of Wuzhishan pigs clustered separately from their counterparts in Duroc, Meishan, Large White, and Bama pigs, indicating distinct evolutionary trajectories. Bioinformatics analysis demonstrated that most MHC Ⅱ proteins were hydrophobic, with molecular weights ranging from 27 700 to 30 000 Da. Genes within the same subregion shared conserved motifs. Specifically, four MHCⅡ proteins encoded by SLA-DQB, SLA-DRB, SLA-DOB, and SLA-DMB contained the MHCⅡβ conserved domain, while those encoded by the genes SLA-DRA, SLA-DQA, SLA-DMA, and SLA-DOA contained the MHCⅡα conserved domain. The eight MHCⅡ genes were scattered along the long arm of chromosome 7 in the Wuzhishan pigs, exhibiting syntenic relationships with three human genes and five Duroc pig genes. ConclusionThe MHCⅡ genes of Wuzhishan pigs may possess a unique evolutionary origin.

ObjectiveTo obtain the gene sequences of major histocompatibility complex (MHC ) Ⅱgenes of Wuzhishan pigs, analyze their genetic information, and explore the biological functions of their MHC system. MethodsSpleen samples were collected from 3 adult male Wuzhishan pigs. Primers were designed according to MHCⅡ gene sequences, and the coding sequences of Wuzhishan pig MHCⅡ genes were amplified by RT-PCR. Sanger sequencing was performed to determine the full-length sequences. Bioinformatics tools were employed to analyze the physicochemical properties, phylogenetic relationships, conserved motifs, structural domains, chromosomal localization, and syntenic relationships of these genes. ResultsEight MHCⅡ genes were identified in Wuzhishan pigs, designated as SLA-DRA, SLA-DQA, SLA-DQB, SLA-DRB, SLA-DOB, SLA-DMB, SLA-DMA and SLA-DOA. The full-length sequences of these genes were determined by Sanger sequencing and subsequently deposited in GenBank under accession numbers PQ182796, PQ182797, PQ182798, PQ182799, PQ182800, PQ182801, PQ182802, and PQ164779. Phylogenetic analysis showed that the six MHCⅡ genes of Wuzhishan pigs clustered separately from their counterparts in Duroc, Meishan, Large White, and Bama pigs, indicating distinct evolutionary trajectories. Bioinformatics analysis demonstrated that most MHC Ⅱ proteins were hydrophobic, with molecular weights ranging from 27 700 to 30 000 Da. Genes within the same subregion shared conserved motifs. Specifically, four MHCⅡ proteins encoded by SLA-DQB, SLA-DRB, SLA-DOB, and SLA-DMB contained the MHCⅡβ conserved domain, while those encoded by the genes SLA-DRA, SLA-DQA, SLA-DMA, and SLA-DOA contained the MHCⅡα conserved domain. The eight MHCⅡ genes were scattered along the long arm of chromosome 7 in the Wuzhishan pigs, exhibiting syntenic relationships with three human genes and five Duroc pig genes. ConclusionThe MHCⅡ genes of Wuzhishan pigs may possess a unique evolutionary origin.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

Structural optimization of lead compounds is a crucial step in drug discovery.One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties.One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules,thereby accelerating the molecular optimization process.Deep molecular diffusion generative models simulate a gradual process that creates novel,chemically feasible molecules from noise.However,the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules,leading to challenges in modifying the scaffold-based molecular structures,and creates limitations in the stability and diversity of the generated molecules.To address these challenges,we propose a deep molecular diffusion generative model,the three-dimensional(3D)equivariant diffusion-driven molecular generation(3D-EDiffMG)model.The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder(dual-SWLEE)is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions.Addi-tionally,a gate multilayer perceptron(gMLP)block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies.The experimental results show that 3D-EDiffMG effectively generates unique,novel,stable,and diverse drug-like molecules,highlighting its potential for lead optimization and accelerating drug discovery.

The PA-PB1 interface of the influenza polymerase is an attractive site for antiviral drug design. In this study, we designed and synthesized a mini-library of indazole-containing compounds based on rational structure-based design to target the PB1-binding interface on PA. Biological evaluation of these compounds through a viral yield reduction assay revealed that compounds 27 and 31 both had a low micromolar range of the half maximal effective concentration (EC₅₀) values against A/WSN/33 (H1N1) (8.03 μmol/L for 27; 14.6 μmol/L for 31), while the most potent candidate 24 had an EC₅₀ value of 690 nM. Compound 24 was effective against different influenza strains including a pandemic H1N1 strain and an influenza B strain. Mechanistic studies confirmed that compound 24 bound PA with a K _d which equals to 1.88 μmol/L and disrupted the binding of PB1 to PA. The compound also decreased the lung viral titre in mice. In summary, we have identified a potent anti-influenza candidate with potency comparable to existing drugs and is effective against different viral strains. The therapeutic options for influenza infection have been limited by the occurrence of antiviral resistance, owing to the high mutation rate of viral proteins targeted by available drugs. To alleviate the public health burden of this issue, novel anti-influenza drugs are desired. In this study, we present our discovery of a novel class of indazole-containing compounds which exhibited favourable potency against both influenza A and B viruses. The EC₅₀ of the most potent compounds were within low micromolar to nanomolar concentrations. Furthermore, we show that the mouse lung viral titre decreased due to treatment with compound 24. Thus our findings identify promising candidates for further development of anti-influenza drugs suitable for clinical use.

Gene therapy, harnessing the power of CRISPR-Cas9 and/or DNAzyme systems, stands as a pivotal approach in cancer therapy, enabling the meticulous manipulation of genes pivotal to tumorigenesis and immunity. However, the pursuit of precise gene therapy encounters formidable hurdles. Herein, a near-infrared upconversion theranostic nanomachine is devised and tailors for CRISPR-Cas9/DNAzyme systems mediate precise gene therapy. An ingenious logic DNAzyme system consists of Chain 1 (C1)/Chain 2 (C2) and endogenous lncRNA is designed. We employ manganese modified upconversion nanoparticles for carrying ultraviolet-responsive C1-PC linker-C2 (C₂P) chain and Cas9 ribonucleoprotein (RNP), with outermost coats with hyaluronic acid. Upon reaching tumor microenvironment (TME), the released Mn²⁺ ions orchestrate a trifecta: facilitating endosomal escape, activating cGAS-STING signaling, and enabling T1-magnetic resonance imaging. Under near-infrared irradiation, Cas9 RNP/C₂P complex dissociates, releasing Cas9 RNP into the nucleus to perform gene editing of Ptpn2, while C1/C2 chains self-assemble with endogenous lncRNA to form a functional DNAzyme system, targeting PD-L1 mRNA for gene silencing. This strategy remodels the TME by activating cGAS-STING signaling and dual immune checkpoints blockade, thus realizing tumor elimination. Our theranostic nanomachine armed with the CRISPR-Cas9/DNAzyme logic systems, represents a resourceful and promising strategy for advancing cancer systemic immunotherapy and precise gene therapy.

Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.

Objective To analyze the value of abdominal CT images combined with serological indicators in predicting the ureteral involvement in idiopathic retroperitoneal fibrosis(IRF). Methods The CT images of 79 IRF patients were analyzed retrospectively,including the involved sites and enhancement characteristics of the lesions.According to the inclusion and exclusion criteria,43 patients with complete serological data were selected and assigned into a ureteral involvement group(n=29)and a non-ureteral involvement group(n=14) according to whether ureters were involved in IRF.Logistic regression analysis was performed to select independent risk factors for ureteral involvement in IRF.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of the CT arterial phase enhancement magnitude and serum cystatin C(CysC)for ureteral involvement in IRF. Results The CT images of IRF usually showed a soft tissue density lesion encompassing the abdominal aorta,iliac arteries,ureters,and retroperitoneal tissue,with a wide range of distribution.The ureteral involvement group and the non-ureteral involvement group showed differences in gender(P=0.031),CT arterial phase enhancement amplitude(P=0.014),CT venous phase enhancement amplitude(P=0.032),and serum CysC(P=0.036).Logistic regression analysis showed that gender(P=0.034),CT arterial phase enhancement amplitude(P=0.046),and serum CysC(P=0.041)were independent risk factors for ureteral involvement in IRF.The area under the curve for CT arterial phase enhancement combined with serum CysC to predict ureteral involvement in IRF was 0.776.Ten patients had lower levels of erythrocyte sedimentation rate(P<0.001),C-reactive protein(P=0.021),and IgG4(P<0.001)in the follow-up period than before treatment. Conclusion The combination of abdominal CT images with serological indicators demonstrates high accuracy in predicting the ureteral involvement in IRF,providing reference for early clinical diagnosis.
Humans ; Male ; Female ; Retroperitoneal Fibrosis/pathology* ; Middle Aged ; Retrospective Studies ; Tomography, X-Ray Computed ; Aged ; Adult ; Ureter/diagnostic imaging* ; Predictive Value of Tests ; Cystatin C/blood*

The gut-brain axis is a bidirectional communication pathway connecting the central nervous system and gastrointestinal tract,playing a key role in the occurrence and development of diseases related to this axis.The vermiform appendix,as a part of the gut that is connected to the cecum,has a unique anatomical location,a rich microbiome,and abundant immune cells.Appendicitis and appendectomy have been found to be associated with the development of diseases related to the gut-brain axis.This review first introduces the anatomy and functions of the vermiform appendix and then expounds the associations of appendicitis and appendectomy with diseases related to the gut-brain axis.Furthermore,this review summarizes and prospects the mechanisms of the vermiform appendix in affecting the occurrence and development of diseases related to the gut-brain axis.
Humans ; Appendix/anatomy & histology* ; Brain ; Appendicitis ; Appendectomy/adverse effects* ; Gastrointestinal Microbiome ; Brain-Gut Axis