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.

Objective To explore the clinical values of non-invasive myocardial work (MW) and tissue motion annular displacement (TMAD) in evaluation of anthracycline therapy-related cardiac dysfunction in patients with non-Hodgkin lymphoma. Methods A total of 62 patients with non-Hodgkin lymphoma who received standardized chemotherapy based on doxorubicin. Two and three dimensional transthoracic echocardiography, along with two dimensional speckle tracking echocardiography, were performed one day before chemotherapy and at 3, 6, and 9 months after chemotherapy to assess left ventricular ejection fraction, global longitudinal strain (GLS), MW parameters, and TMAD. Logistic regression analysis was used to evaluate the risk factors for cancer therapy-related cardiac dysfunction (CTRCD). The receiver operating characteristic curve was used to assess the diagnostic values of MW- and TMAD-related parameters for CTRCD. Results Compared to baseline, GLS, global work index (GWI), global constructive work (GCW), global work efficiency (GWE), TMAD at midpoint (TMADmid), and TMADmid percentage of left ventricular long-axis diameter (TMADmid%) decreased at 3 months after chemotherapy, while global wasted work (GWW) increased at 6 months after chemotherapy (P＜0.05). Logistic regression analysis showed that the relative reduction in GLS and TMADmid% at 3 months after chemotherapy were independent predictors for CTRCD （P＜0.05), while MW parameters were not independent predictors for CTRCD. GLS reduction≥10.3% and TMADmid% reduction≥15.8% at 3 months after chemotherapy predicted CTRCD with 0.866 and 0.824 of area under the curve (AUC), 92% and 75% of sensitivity, and 74% and 80% of specificity, respectively. AUC of combination of two indexes improved to 0.905, with 75% of sensitivity and 90% of specificity. Conclusions In non-Hodgkin lymphoma patients, the combination of GLS and TMADmid% is helpful of predicting CTRCD early, TMAD may be a novel diagnostic index for CTRCD, and GLS has superior predictive performance than MW for CTRCD.

Metabolic dysfunction-associated fatty liver disease （MAFLD）， as one of the most common chronic liver diseases in the world， poses a severe challenge to precision diagnosis and treatment due to its complex pathogenesis and highly heterogeneous disease progression. Existing clinical classification systems cannot meet the needs for comprehensively analyzing the complexity of the disease and the heterogeneity of its adverse outcomes. In recent years， data-driven prognostic risk classification methods have gradually emerged， optimizing the ability for predicting adverse outcomes and enhancing the accuracy of identifying different endpoint outcomes. However， such paradigm of “classify first， associate outcomes later” suffers from a “black-box” nature， and there are various indicators for classification， leading to limited stability and generalizability in clinical application. Future research needs to integrate or establish large-scale population cohorts， develop outcome-oriented prognostic risk classification models， incorporate dynamic data， refine classification algorithms， and validate their generalizability across multiple populations， thereby providing reliable support for the precision diagnosis and treatment of MAFLD.

Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Purpose To evaluate the value of preoperative MRI-based radiomic models for assessing tumor-infiltrating CD8+T-cell expression in glioblastoma patients,and to identify the most stable and efficient radiomic feature region for predicting prognosis following immunotherapy.Materials and Methods This retrospective study included 150 patients with histopathologically confirmed glioblastoma from Lanzhou University Second Hospital(January 2018 to April 2022).Tumor-infiltrating CD8+T-cell expression was quantitatively assessed using immunohistochemical staining,with patients stratified into CD8-high and CD8-low expression groups based on overall survival.A total of 1 185 radiomic features were extracted from each patient's contrast-enhanced T1C and T2WI images,covering the original tumor region and sequentially expanded peritumoral regions(2.5 mm,5.0 mm,7.5 mm,10.0 mm,12.5 mm,15.0 mm morphological dilation of tumor core+peritumoral area).Feature selection was performed using variance threshold,minimum redundancy maximum relevance,and least absolute shrinkage and selection operator methods.XGBoost classifier was employed to construct clinical,radiomic,and clinical-radiomic multimodal combined prediction models.Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Results The radiomic model based on tumor expansion of 7.5 mm(tumor+peritumoral region)demonstrated optimal predictive performance.The clinical-radiomic multimodal combined model showed superior predictive capability compared to clinical and radiomic models alone,achieving an area under the curve of 0.991 and accuracy of 99.0%in the training set,and area under the curve of 0.840 with accuracy of 80.0%in the validation set.Conclusion MRI radiomics provides a feasible approach for evaluating tumor-infiltrating CD8+T-cell expression in glioblastoma patients,offering potential for preoperative prognosis prediction.

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

Objective To develop and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.