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 explore the effect of cluster scalp acupuncture combined with Taijiquan training on depressive symptom, motor function, activities of daily living, serum markers, as well as brain functional connectivity (FC) and network topological properties in patients with post-stroke depression (PSD). MethodsA total of 40 PSD patients in the Second Affiliated Hospital of Heilongjiang University of Chinese Medicine from September, 2022 to September, 2023 were enrolled and randomly divided into control group (n = 20) and experimental group (n = 20). The control group received cluster scalp acupuncture alone, while the experimental group underwent Taijiquan training in addition, for four weeks. They were assessed with Hamilton Depression Scale-17 (HAMD-17), Fugl-Meyer Assessment (FMA) and Barthel Index (BI) before and after treatment, while the serum levels of dopamine (DA), 5-hydroxytryptamine (5-HT), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were detected with enzyme-linked immunosorbent assay. Resting-state functional magnetic resonance imaging (rs-fMRI) was applied to assess brain FC, as well as the global efficiency (Eg) and small-world property (σ) of brain networks. ResultsThe scores of HAMD-17, FMA and BI improved in both groups (t > 2.922, P < 0.01) after treatment, and improved more in the experimental group than in the control group (t > 2.517, P < 0.05). The serum levels of DA and 5-HT increased in both groups (t > 2.637, P < 0.05), and increased more in the experimental group (t > 2.192, P < 0.05). The serum levels of IL-6 and TNF-α decreased in the experimental group after treatment (t > 4.059, P < 0.001), and they were less than those in the control group (t > 2.154, P < 0.05). FC between left middle frontal gyrus and right anterior cingulate gyrus, as well as between left hippocampus and right precuneus were higher in the experimental group than in the control group after treatment (t > 3.867, P < 0.001), while Eg and σ increased in both groups (t > 2.828, P < 0.05), and they were higher in the experimental group (t > 2.675, P < 0.05). ConclusionCombination of Taijiquan training is more effective on depressive symptoms, motor function and activities of daily living in PSD patients, which may be related to up-regulation of serum DA and 5-HT, reduction of inflammatory factors, enhancement of prefrontal-limbic system functional connectivity and optimization of brain network topological properties.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTranscranial magneto-acoustic stimulation (TMAS) is an emerging non-invasive neuromodulation technique that may provide a novel non-pharmacological intervention strategy for Parkinson's disease (PD). PD is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc), leading to motor impairments such as bradykinesia, tremor, and rigidity. Increasing evidence indicates that mitochondrial dysfunction and impaired mitochondrial quality control are central mechanisms underlying dopaminergic neuronal loss. In particular, abnormalities in mitophagy and mitochondrial fission-fusion balance contribute substantially to oxidative stress, energy metabolic failure, and neuronal injury. At present, most clinical treatments for PD mainly alleviate symptoms but do not effectively halt disease progression. Therefore, exploring new interventions targeting the core pathological mechanisms is of considerable significance. This study aims to investigate whether TMAS can improve neural damage and motor dysfunction in PD mice by regulating mitophagy and the fission/fusion dynamic balance, thereby providing theoretical and experimental support for its application in PD treatment. MethodsMale C57BL/6 mice were used in this study. A PD model was established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 7 consecutive days. After model induction, mice in the intervention group received TMAS once daily for 14 consecutive days, whereas the corresponding control group received sham stimulation. The stimulation target was positioned over the primary motor cortex (M1). Motor performance was evaluated using the pole test and the open-field test. To verify the activation effect of TMAS on the target cortical region, c-Fos immunohistochemistry was performed in the M1. To assess nigral dopaminergic neuronal injury, tyrosine hydroxylase (TH) immunohistochemistry was used to quantify TH-positive neurons in the SNc. Mitochondrial function was evaluated by measuring reactive oxygen species (ROS) levels and adenosine triphosphate (ATP) content in the SNc. Western blot was further performed to determine the expression of mitophagy-related proteins, including PINK1, Parkin, LC3-II, and p62, as well as mitochondrial dynamics-related proteins, including Drp1 and Opa1. ResultsTMAS significantly increased the number of c-Fos-positive cells in M1 (P<0.000 1), indicating effective activation of neurons in the targeted cortical region. Compared with the control group, MPTP-treated mice exhibited marked motor dysfunction, including a significant reduction in total distance traveled in the open-field test (P<0.000 1) and mean speed (P=0.000 1), as well as significant prolongation of turn time and total climbing time in the pole test (P<0.000 1). These behavioral impairments were accompanied by a substantial loss of TH-positive dopaminergic neurons in the SNc, whereas TMAS significantly increased TH-positive neuron survival (P<0.000 1). In parallel, MPTP induced a pronounced increase in ROS levels and a significant reduction in ATP content, indicating severe mitochondrial dysfunction and energy metabolism impairment (P<0.01). TMAS treatment significantly improved motor performance, as reflected by the reversal of MPTP-induced impairment in the open-field and pole tests, and significantly reduced ROS accumulation (P<0.01) while restoring ATP production (P<0.001). At the molecular level, MPTP markedly downregulated PINK1 and Parkin, decreased p62 expression, increased LC3-II accumulation, elevated Drp1 expression, and reduced Opa1 expression, whereas TMAS significantly reversed these abnormalities, suggesting restoration of mitophagy-related mitochondrial quality control and re-establishment of mitochondrial fission-fusion balance. Collectively, these findings indicate that TMAS ameliorates MPTP-induced neurotoxicity and restores mitochondrial homeostasis and energy metabolism. ConclusionTMAS effectively attenuates neural damage and improves motor dysfunction in MPTP-induced PD mice. Its neuroprotective effects are closely associated with multidimensional regulation of the mitochondrial quality control system, including restoration of PINK1/Parkin-mediated mitophagy and rebalancing of Drp1/Opa1-related mitochondrial dynamics. Rather than acting only as a symptomatic neuromodulatory intervention, TMAS may influence a key pathological axis of PD by improving mitochondrial homeostasis in SNc and protecting nigral dopaminergic neurons. These findings provide experimental evidence supporting TMAS as a promising non-invasive physical intervention for PD.

ObjectiveTo investigate the role and mechanism of ribosomal DNA （rDNA） transcription and ribosome biogenesis in muscle atrophy induced by acute kidney injury （AKI）. MethodsEight male C57BL/6 mice were randomly divided into a control group （Ctrl） and a model group （AKI）. An AKI model was established via intraperitoneal injection of cisplatin. Muscle atrophy was phenotypically assessed by measuring muscle mass， myofiber cross-sectional area （HE staining）， and mRNA expression levels of atrophy-related genes （Murf-1， Atrogin-1， Igf-1） using qRT-PCR. In vivo protein synthesis rates were determined via the SUnSET assay （puromycin incorporation）. Ribosome biogenesis was evaluated by assessing rRNA content and 47S pre-rRNA expression levels. Myotubes differentiated from mouse skeletal muscle cell lines （C2C12 myotubes） were treated with serum from AKI mice， and the effects on rDNA transcription， ribosome biogenesis， and protein metabolism were analyzed using chromatin immunoprecipitation followed by quantitative polymerase chain reaction （ChIP-qPCR） and Western blot. ResultsAKI successfully induced muscle atrophy， as evidenced by a significant reduction in skeletal muscle mass. The most pronounced decrease occurred in the extensor digitorum longus muscle （21.0%， P 0.01）， along with a trend toward reduced myofiber cross-sectional area. At the molecular level， AKI inhibited muscle protein synthesis （83.14% reduction in puromycin incorporation， P 0.000 1） and impaired ribosome biogenesis， manifested by suppressed rDNA transcription elongation （52.62% decrease in 47S pre-rRNA ITS-1 levels， P 0.01） and reduced total rRNA content （65.29%， P 0.000 1）. In contrast， serum from AKI mice promoted rDNA transcription initiation and protein synthesis in C2C12 myotubes in vitro. ConclusionAKI induces muscle atrophy by suppressing rDNA transcription and ribosome biogenesis in skeletal muscle， leading to impaired protein synthesis. Dysregulated ribosome biogenesis may play a critical role in AKI-induced muscle atrophy.

SMYD5 is a ribosomal methyltransferase with SET and MYND structural domains， which is a member of the SMYD family and is expressed in a variety of tissues， including ovary and testis. This enzyme participates in biological processes such as gene expression regulation， cell development and differentiation， and maintenance of genomic stability through ribosomal protein methylation modification. In recent years， research on SMYD5 has increased in cancers including hepatocellular carcinoma， gastric adenocarcinoma， and lung cancer. Studies have revealed that SMYD5 exhibits high expression levels in various diseases including hepatocellular carcinoma， gastric adenocarcinoma， lung cancer， and inflammatory bowel disease， influencing the progression of these conditions. This review summarizes the role of SMYD5 in hepatocellular carcinoma， inflammatory bowel disease， and other biological functions， aiming to provide a reference for related disease research.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.