Objective: To investigate the association between brain and muscle Arnt like protein 1( BMAL 1) gene and ambulatory blood pressure (ABP) parameters in college students, and to explore the influence of the interaction between the gene and weight status on the ABP levels, so as to provide reference for early prevention of chronic cardiovascular diseases related to hypertension. Methods: During September 2022 to June 2024, a total of 510 college students were recruited from a university in Changsha, China for on site questionnaire investigation, physical examination, ABP monitoring and genotyping testing. Multiple linear regression method was used to explore the association between the BMAL 1 gene and ABP indicators. An interaction term was included in the general linear model of multiple linear regression to analyze the interactive effects of BMAL 1 gene polymorphisms and weight status on ABP levels. Results: The prevalence of abnormal 24 hour blood pressure, abnormal daytime blood pressure, and abnormal nighttime blood pressure were 3.3%, 3.1%, and 3.9%, respectively. Multiple linear regression analysis showed that the BMAL 1/rs7950226 polymorphism was positively correlated with the 24 hour diastolic blood pressure(DBP) and the daytime DBP level after adjusting for gender, age, and body mass index( β =0.87,0.99, both P <0.05). Also, interaction between BMAL 1/ rs 11022775 and weight status on the nighttime DBP level ( P interaction =0.03) was found. The CC genotype carriers had significantly higher nighttime DBP level ( β =3.52, P <0.05) among overweight/obesity college students, but no differences in nocturnal DBP levels were observed between CC genotype carriers and TT+CT genotype carriers among college students with normal body weight( P > 0.05). Conclusions The rs 7950226 polymorphism is associated with 24 hours DBP and daytime DBP levels. Significant interaction between rs 11022775 with weight status on the nighttime DBP level is found among college students.

In recent years, China’s capacity for new drug research and development has been significantly strengthened, with major breakthroughs across multiple therapeutic areas, including cancer, autoimmune diseases, and metabolic disorders. An increasing number of domestically developed innovative drugs have been approved for marketing, gradually establishing a competitive position against imported drugs and expanding into global markets. This article systematically reviews the latest research progress of Class 1 innovative drugs in China from 2023 to 2024, categorizes representative approved drugs by therapeutic area, summarizes the clinical advantages and characteristics of representative drugs approved, analyzes in depth the current development trends of and challenges for China’s innovative pharmaceutical industry, and explores future directions, aiming to provide some reference for innovative drug research, industrial development, and policy-making in China.

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.

Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.

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.

ObjectiveTo investigate the expression of prefrontal cortical neurons， methyltransferase-like 3 （METTL3）， fat mass and obesity-associated gene （FTO）， and AlkB homolog 5 （ALKBH5） proteins in a mouse model of post-traumatic stress disorder （PTSD）. MethodsA PTSD mouse model was established using a single prolonged stress and foot shock stimulation （SPSS） method. The despair， anxiety， and learning and memory functions of PTSD mice were assessed through the open field test， Y-maze test， and forced swimming test. Neuronal damage was detected via HE and Nissl staining. The expression levels of METTL3， FTO， ALKBH5， and neuronal nuclear protein （NEUN） were assessed by Western blot and immunofluorescence staining. ResultsCompared to control group， PTSD mice subjected to SPSS exhibited signs of despair， anxiety， and impaired learning and memory. HE and Nissl staining results showed neuronal damage in the prefrontal cortex of PTSD mice. Western blot and immunofluorescence staining results showed that the expression of the m6A-related proteins METTL3 and FTO decreased， while the expression of ALKBH5 increased in the prefrontal cortex. Additionally， NEUN protein levels showed a declining trend. ConclusionThe pathogenesis of PTSD may be associated with neuronal damage in the prefrontal cortex and alterations in m6A methylation proteins.

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.

BACKGROUND:The inflammatory response of microglia is closely related to neuronal survival,regeneration,and functional recovery after spinal cord injury.Peroxiredoxin 1 is not only involved in the regulation of oxidative stress,but also has an important effect on cell proliferation,apoptosis,and inflammatory response.OBJECTIVE:To investigate the role and mechanism of peroxiredoxin 1 in the inflammatory response of microglia following spinal cord injury.METHODS:(1)Twelve female C57BL/6 mice were randomly divided into sham-operated(n=6)and spinal cord injury(n=6)groups.The sham-operated group was not modeled and acute spinal cord injury models were constructed in the spinal cord injury group using the modified Allen's method.Spinal cord tissue at the injured site was taken at 7 days after modeling and transcriptome sequencing was performed to identify differentially expressed genes.The expression of peroxiredoxin 1 in spinal cord tissues was verified using western blot and RT-qPCR.(2)Mouse microglia BV2 were divided into two groups:the control group was stimulated with lipopolysaccharide for 6 hours,and in the knockout group,lipopolysaccharide stimulation was applied for 6 hours at 24 hours after peroxiredoxin 1 was knocked down in the cells.RT-qPCR was performed to detect mRNA expression of peroxiredoxin 1,inflammatory factors(interleukin 1β,interleukin 6,inducible nitric oxide synthase,tumor necrosis factor α,C-C motif chemokine ligand 2,and C-X-C motif chemokine ligand 2),and western blot was performed to detect the expression of peroxiredoxin 1,inducible nitric oxide synthase,and reactive oxygen/mitogen-activated protein kinase signaling pathway proteins.Mouse microglia BV2 were treated in two groups:the control group was stimulated by hydrogen peroxide for 4 hours,and the knockout group was stimulated by hydrogen peroxide for 4 hours at 24 hours after knockdown of peroxiredoxin 1.The level of reactive oxygen species was detected by 2,7-dichlorodihydrofluorescein diacetate probe.RESULTS AND CONCLUSION:(1)Results from transcriptome sequencing,western blot and RT-qPCR confirmed that peroxiredoxin 1 expression levels in mouse spinal cord tissues were significantly higher in the spinal cord injury group than the sham-operated group(P＜0.05).(2)Peroxiredoxin 1 knockdown in microglial cells led to decreased expression of peroxiredoxin 1 mRNA and protein(P＜0.05),increased mRNA expression of interleukin 1β,interleukin 6,inducible nitric oxide synthase,tumor necrosis factor α,C-C motif chemokine ligand 2,and C-X-C motif chemokine ligand 2(P＜0.05),increased protein expression of inducible nitric oxide synthase,P-P38,P-JNK and P-ERK proteins(P＜0.05),and increased level of reactive oxygen species(P＜0.05).To conclude,peroxiredoxin 1 regulates microglial inflammation by targeting the reactive oxygen species/mitogen-activated protein kinase signaling pathway.