Objective: To investigate the association between injury prevention knowledge level and injury occurrence among primary and secondary school students in Dongguan, so as to provide scientific basis for formulating targeted and evidence based intervention strategies for child injury. Methods: From March to April 2024, stratified cluster random sampling method was applied to select 5 988 primary and secondary school students in grades 4-9 for a survey. The Revised Questionnaire for the 2016-2020 Child Injury Prevention Project (senior version) was used to collect demographic characteristics, family and caregiver information, injury event characteristics, and knowledge, attitude, and practice related to injury prevention. Mann-Whitney U test was used for inter group comparison. Propensity score matching (PSM) was applied to balance confounders, and conditional Logistic regression was used to analyze the association between injury prevention knowledge score and injury occurrence among primary and secondary school students, and a restricted cubic spline (RCS) model was employed to test the dose response relationship. Furthermore, interaction terms were introduced to examine the moderating effects of sex, grade level, and caregiver’s educational level. Results: The overall incidence of injuries among primary and secondary school students was 18.15%. The knowledge score of injury prevention was significantly lower in the injury group [20.0(18.0,22.0)] than in the non injury group [21.0(19.0,22.0)] ( Z = 8.24 , P <0.01). After PSM, 1 068 pairs were successfully matched, and the standardized mean difference for all covariates was <0.1. An increase in injury prevention awareness scores was associated with a reduced risk of injury occurrence among primary and secondary school students ( OR =0.92, P <0.05). The RCS analysis showed an approximately linear negative association between injury prevention knowledge score and injury risk among primary and secondary school students ( P non linear =0.72), with a decreased injury risk when score exceeded 24 ( OR = 0.69, P <0.05). Subgroup analyses indicated that the negative correlation between cognitive level and the risk of injury was common in different gender, grade and caregivers educational level groups ( OR =0.87- 0.93 , all P <0.05). Sensitivity analyses yielded results consistent with the primary analysis. Conclusions The incidence of injuries among primary and secondary school students in Dongguan City is relatively high. Injury prevention knowledge level is negatively associated with injury occurrence risk, exhibiting an approximately linear dose response relationship.

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.

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality, characterized by poor prognosis due to its high proliferative and invasive potential. Tumor metabolic reprogramming, particularly involving glucose metabolism, is essential for tumor survival. This study investigates the role of the Hippo pathway effector transcriptional co-activator with PDZ-binding motif (TAZ) in regulating gluconeogenesis and promoting tumorigenesis in HCC. Methods: TAZ expression in HCC was analyzed using The Cancer Genome Atlas data and validated in clinical samples and cell lines. TAZ was overexpressed or silenced in HCC cell lines to evaluate its effects on cell proliferation, apoptosis, migration, and invasion. The expression and prognostic relevance of the gluconeogenesis-related genes phosphoenolpyruvate carboxykinase 1 (PCK1) and glucose-6-phosphatase (G6PC) were examined, along with their correlation with TAZ expression. Tumor growth was assessed in nude mice. Interactions between TAZ and the glucocorticoid receptor (GR) were investigated using co-immunoprecipitation, immunofluorescence, and chromatin immunoprecipitation assays. Results: TAZ was significantly upregulated in HCC tissues and cell lines. TAZ overexpression enhanced proliferation, reduced apoptosis, and promoted migration and invasion. In contrast, PCK1 and G6PC were downregulated in HCC and showed a negative correlation with TAZ expression. Conclusion TAZ modulates gluconeogenesis and accelerates tumor growth, whereas its knockdown attenuates tumor progression. TAZ interacts with GR, suppressing its transcriptional activity on gluconeogenic gene promoters.

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.

Colorectal cancer (CRC) is a common malignant tumor. The treatment of patients with advanced disease still faces severe challenges. Among patients with metastatic colorectal cancer (mCRC), most of those with microsatellite stable (MSS)/proficient mismatch repair (pMMR) tumors are highly insensitive to monotherapy with immune checkpoint inhibitors. With in-depth investigations into the mechanisms of the tumor immune microenvironment in MSS/pMMR CRC, the combination strategies of immunotherapy and targeted therapy have become a key direction to break through the treatment bottleneck in this population. These strategies include combinations of immunotherapy with antiangiogenic agents, epidermal growth factor receptor inhibitors, histone deacetylase inhibitors, and MAPK pathway inhibitors. Although the current relevant evidence is mainly derived from early-phase clinical trials, a number of studies demonstrated that immunotherapy combined with targeted therapy can improve the objective response rate and survival benefit in patients with MSS/pMMR mCRC and shows remarkable efficacy advantages in specific subgroups. This article systematically reviews the biological basis and clinical research progress of relevant combination therapeutic strategies, discusses potential beneficiary subgroups, and prospects future research directions. It aims to provide theoretical evidence and clinical references for optimizing the individualized treatment paradigm for this large patient population.

ObjectiveTo analyze the application trends and research hotspots of action observation therapy (AOT) in the field of stroke rehabilitation over the past decade. MethodsLiteratures on AOT in stroke rehabilitation published from January, 2016 to December, 2025 were retrieved from the Web of Science Core Collection database. CiteSpace 6.4.R1 was used for visual analysis. ResultsA total of 463 articles were included. The annual publication volume showed a fluctuating upward trend. The country with the highest number of publications was China, the most productive institution was Chang Gung University and Consiglio Nazionale delle Ricerche, and the most prolific author was Avanzini Pietro. Mirror neuron system, motor imagery, upper limb and facilitation were identified as high-frequency keywords and bursting words. ConclusionIn the past decade, the number of publications on AOT in stroke rehabilitation has generally increased. Researches are focusing on the synergy of sensory-closed-loop multimodal technologies, reconstruction of fine upper limb function and neural facilitation mechanisms.

Extracellular vesicles (EVs) are pivotal mediators of intercellular communication within the tumor immune microenvironment (TME). They are broadly categorized into exosomes, microvesicles, and apoptotic bodies based on their distinct biogenesis pathways. Exosomes originate from the endosomal system via multivesicular body fusion, microvesicles bud directly from the plasma membrane, and apoptotic bodies are released during programmed cell death. By shuttling diverse bioactive cargoes—including proteins, lipids, and nucleic acids such as mRNA, miRNA, and DNA—EVs exert dual modulatory effects on tumor initiation, progression, and immune evasion. Importantly, EVs exhibit remarkable compositional heterogeneity that is intrinsically linked to their cellular origin. Tumor-derived EVs (TDEVs) are typically enriched with immunosuppressive molecules like PD-L1, TGF‑β, and miR-21, which promote tumor immune escape and metastasis. In contrast, EVs derived from immune cells, such as dendritic cells or cytotoxic T lymphocytes, often carry immunostimulatory components including antigens, co-stimulatory molecules, and granzymes, thereby potentiating anti-tumor immunity. This review systematically delineates the biogenesis and molecular composition of EVs, with a particular emphasis on their dynamic regulatory functions within the TME. Specifically, we discuss how EVs mediate intricate crosstalk between immune and tumor cells, facilitating signal transfer that reshapes immune surveillance. For instance, TDEVs can induce macrophage polarization toward an M2-like pro-tumor phenotype, while also suppressing natural killer cell cytotoxicity and dendritic cell maturation. The clinical utility of EV-associated biomarkers in liquid biopsy is increasingly recognized. Circulating EVs carry tumor-specific molecular signatures that mirror the genetic and proteomic alterations of primary tumors, enabling non-invasive early diagnosis, molecular subtyping, and real-time monitoring of therapeutic responses. Their natural biocompatibility, low immunogenicity, and intrinsic ability to traverse biological barriers make them ideal candidates for drug delivery systems. This review explores cutting-edge applications, including the use of EVs in immune checkpoint blockade therapy—for instance, engineered EVs displaying anti-PD-1 antibodies or carrying siRNA to silence immunosuppressive genes. Moreover, EV-based tumor vaccines are being developed, leveraging dendritic cell-derived EVs loaded with tumor antigens to elicit potent T cell responses. The feasibility of loading EVs with therapeutic molecules such as chemotherapeutic agents, oncolytic viruses, or CRISPR-Cas9 components is also under active investigation. The advent of engineered EVs has further expanded their therapeutic potential. Through surface modification or cargo encapsulation, EVs can be tailored for targeted delivery and controlled release, enhancing precision immunotherapy. However, several hurdles impede clinical translation. Current isolation and purification methods, such as ultracentrifugation and size-exclusion chromatography, suffer from low yield and purity. Distinguishing EV subpopulations remains technically challenging due to overlapping size and marker expression. Moreover, the lack of standardized protocols for EV production, characterization, and quality control poses significant barriers to regulatory approval and clinical adoption. Looking forward, the convergence of multi-omics technologies with artificial intelligence offers a powerful approach to decipher EV heterogeneity and identify robust diagnostic signatures. Machine learning algorithms can integrate proteomic, transcriptomic, and lipidomic data from large patient cohorts to construct predictive models for cancer diagnosis and prognosis. Concurrently, advances in bioengineering are enabling the design of next-generation EVs with enhanced targeting specificity, on-demand drug release, and reduced off-target effects. Future efforts should also focus on establishing good manufacturing practice (GMP)‑compliant production processes and conducting rigorous preclinical and clinical evaluations. In summary, this review provides a comprehensive overview of EV biology, their multifaceted roles in the TME, and their transformative potential in cancer diagnostics and therapeutics. By addressing current challenges and leveraging emerging technologies, EV-based strategies are poised to revolutionize precision oncology.

Objective To investigate the radon activity concentrations in subways of Nanning City and assess the average annual effective doses for subway staff and passengers due to radon exposure. Methods Sixty-three stations across the subway lines 2, 3, and 5 were selected as study sites. Radon activity concentrations were measured using the scintillation counting method with scintillation vials. Results The radon activity concentrations in subway lines 2, 3, and 5 were 7.9-24.4, 12.0-26.2, and 12.6-18.2 Bq/m³, respectively. The average radon activity concentrations for these three lines were (17.4 ± 4.6), (19.1 ± 4.1), and (14.6 ± 1.7) Bq/m³, respectively. Statistical analysis using SPSS 26.0 software revealed a significant difference in radon activity concentrations among these stations (P<0.01). Considering the data in previous research, the average radon activity concentration across all stations in the subway lines of Nanning City was determined to be 17.4 Bq/m³. The estimated average annual effective dose due to radon exposure was 0.131 mSv for subway staff and 0.033 mSv for passengers. Conclusion The radon activity concentrations in the subway lines of Nanning City were significantly lower than the national standard limit (400 Bq/m³). The annual effective doses from radon exposure for both subway staff and passengers were below the limits specified in the Basic Standards for Protection Against Ionizing Radiation and for the Safety of Radiation Sources (GB18871—2002). The health impact of radon and its progeny on subway staff and passengers in the subway lines of Nanning City was extremely low and can be considered negligible.

OBJECTIVE To investigate the ameliorative effect and mechanism of short-acting exenatide on diabetic cognitive dysfunction. METHODS Spontaneously diabetic db / db mice were randomly divided into model group （normal saline） and exenatide group （50 μg/kg）， with db / m mice as the normal control group （normal saline）， with 8 mice in each group. Mice in each group were subcutaneously injected with corresponding drugs or normal saline twice daily for 8 consecutive weeks. Body weight and fasting blood glucose were measured at a fixed time every week. Cognitive function was evaluated by Morris water maze test. The levels of oxidative st ress indicators [malondialdehyde （MDA）， superoxide dismutase （SOD）， glutathione （GSH） ] ， cyclic adenosine monophosphate （cAMP） and protein kinase A （PKA） were detected in hippocampus tissue of mice. The hippocampal neuronal HT22 cells of mice were divided into control group （25 mmol/L glucose）， high glucose group （125 mmol/L glucose）， high glucose+exenatide group （125 mmol/L glucose+20 nmol/L exenatide）， high glucose+exenatide+H89 （PKA inhibitor） group （125 mmol/L glucose+20 nmol/L exenatide+10 μmol/L H89）， and high glucose+H89 group （125 mmol/L glucose+10 μmol/L H89）. After 48 h of intervention with corresponding solutions/culture medium， the levels of oxidative stress indicators， cAMP and PKA， the activities of mitochondrial respiratory enzymes Ⅱ and Ⅳ， and the phosphorylation level of dynamin-related protein 1 （Drp1） were measured. RESULTS Animal experiments showed that compared with the normal control group， the model group exhibited significantly increased body weight， fasting blood glucose and MDA level in the hippocampus （ P ＜0.05）， as well as significantly prolonged escape latency （ P ＜0.05）； swimming speed significantly slowed down， the time spent in the target quadrant， the number of platform crossings， and the levels of SOD， GSH， cAMP and PKA in the hippocampus were significantly decreased （ P ＜0.05）. Compared with model group， all the above indicators （except for swimming speed） in the exenatide group were significantly reversed （ P ＜0.05）. Cell experiments showed that compared with high glucose group， the high glucose+exenatide group had significantly decreased MDA level （ P ＜0.05）， and significantly increased levels of SOD， GSH， cAMP and PKA， the activities of mitochondrial respiratory enzymes Ⅱ and Ⅳ， and phosphorylation level of Drp1 （ P ＜0.05）. Compared with high glucose+exenatide group， the above indicators in the high glucose+exenatide+H89 group were significantly reversed （ P ＜0.05）. CONCLUSIONS Short-acting exenatide can activate the cAMP/PKA pathway， promote Drp1 phosphorylation， and increase the activities of mitochondrial respiratory enzymes， thereby maintaining mitochondrial stability， reducing oxidative stress injury， and ultimately improving diabetic cognitive dysfunction.

Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.