Since its emergence in the 1980s, the human immunodeficiency virus (HIV) has caused a global pandemic, posing a severe threat to human life and health as well as social development. Although pre-exposure prophylaxis (PrEP) effectively curbs HIV transmission and antiretroviral therapy (ART) significantly extends the lifespan of patients, vaccines remain a pivotal tool for blocking transmission and ending the pandemic. The high genetic variability of HIV-1, the glycan shield of its envelope glycoproteins, and the long-term persistence of latent reservoirs have repeatedly led to bottlenecks in traditional vaccine strategies. In recent years, mRNA technology has offered a novel approach to addressing these challenges, leveraging advantages such as sequence programmability, short production cycles, native conformational expression of antigens, and self-adjuvant effects. In recent years, mRNA vaccine technology has emerged as a transformative solution to longstanding vaccinology challenges, characterized by its sequence programmability, rapid production cycles, native conformational antigen expression, and intrinsic self-adjuvanting properties. Unlike traditional platforms reliant on pathogen culture or recombinant proteins, mRNA vaccines can be expeditiously designed and updated based solely on viral genomic sequences. Lipid nanoparticle (LNP)-encapsulated mRNA facilitates endogenous antigen expression and presentation, simultaneously eliciting potent humoral and cellular immune responses. Within this landscape, self-amplifying mRNA (saRNA) further extends in vivo antigen expression to enhance the persistence of immune responses. Moreover, the LNP delivery system not only protects mRNA from degradation and mediates endosomal escape but also synergizes with mRNA to optimize immune activation via self-adjuvant effects. Importantly, mRNA platforms circumvent the pre-existing immunity associated with viral vectors and the genomic integration risks of DNA vaccines, positioning them as a cornerstone for global pandemic preparedness. This review systematically delineates recent advances in mRNA technology for HIV-1 vaccine development, focusing on four pivotal research frontiers. First, mRNA innovations building upon the RV144 trial optimize antigens through codon modification and multivalent designs to induce more durable and broad-spectrum immunity. Second, particulate mRNA vaccine strategies, utilizing virus-like particles (VLPs) and ferritin nanoparticles, achieve in situ antigen self-assembly, significantly enhancing B cell activation and reducing infection risks in non-human primate models. Third, germline-targeting mRNA vaccines address the low-affinity barrier of broadly neutralizing antibody (bNAp) precursors, efficiently activating rare precursor B cells and promoting affinity maturation. Fourth, therapeutic mRNA vaccines offer unique advantages for an HIV functional cure; combining immunogens with mRNA-encoded adjuvants potentiates cellular immunity, while LNP-mediated “shock-and-kill” strategies specifically activate latent reservoirs to guide immune clearance. Comparative analyses with traditional platforms reveal that mRNA technology redefines antigen production and presentation, simulating chronic infection through sustained expression and enabling dual-pathway presentation via endogenous synthesis. Furthermore, we explore the mechanistic innovations of mRNA vaccines in inducing bNAps: sustained in vivo production prolongs the activation window for precursor B cells and maintains germinal center (GC) reactions; endogenously expressed antigens adopt native conformations to expose conserved epitopes; and self-adjuvanting effects modulate the functions of antigen-presenting cells (APCs) and follicular helper T cells (Tfh), driving somatic hypermutation and affinity maturation. We also address critical clinical translation challenges, including immune durability, adaptability to special populations, and large-scale LNP manufacturing, while proposing targeted optimization strategies. In conclusion, this review establishes a theoretical framework for utilizing mRNA technology to overcome HIV-1 immune escape, transitioning from a descriptive paradigm to a problem-solving-based synthesis of evidence. By integrating preclinical and early clinical data, we bridge the gap between basic design and translational verification. mRNA technology is poised to become a central pillar inHIV-1 prevention and therapy, providing a robust toolset to achieve the global goal of ending the AIDS pandemic and offering a blueprint for vaccine development against other recalcitrant infectious diseases.

AIM: To investigate the diagnostic and prognostic value of differential expression of Cyclin D1 and p53 in eyelid tumors.METHODS: This retrospective study enrolled patients who underwent surgical resection for eyelid tumors at our hospital between March 2018 and March 2023. Participants were categorized into benign and malignant groups based on tumor characteristics. Clinical data were collected. Genetic data for eyelid tumors were obtained from the GEO database, and differential gene analysis, including volcano plot visualization and KEGG pathway enrichment analysis, was performed using the Sangerbox 3.0 platform. Immunohistochemistry was used to detect the expression levels of Cyclin D1, p53, and BAX in tissue samples. Correlations with clinical features were analyzed using Spearman analysis, and prognostic factors were identified via Logistic regression analysis.RESULTS: This study included 69 patients with eyelid tumors(78 eyes), categorized into a benign group(37 patients, 41 eyes)and a malignant group(32 patients, 37 eyes)based on tumor characteristics. There were significant differences between the two groups in histological subtype, TNM staging, vascular invasion, differentiation status, and local infiltration(all P<0.05). Among benign tumors: pigmented nevi in 11 eyes(27%), hemangiomas in 9 eyes(22%), squamous cell papillomas in 5 eyes(12%), epidermoid cysts in 5 eyes(12%), seborrheic keratoses in 4 eyes(10%), neurofibromas in 3 eyes(7%), and both calcifying epithelioma and xanthelasma in 2 eyes each(5%); among malignant tumors: basal cell carcinoma in 18 eyes(49%), meibomian gland carcinoma in 8 eyes(22%), squamous cell carcinoma in 5 eyes(14%), sebaceous gland carcinoma in 4 eyes(11%), lymphoma and malignant melanoma each in 1 eye(3%). At the follow-up cutoff date of March 2025, the 2-year survival rate in the benign group(95%)was significantly higher than that in the malignant group(78%; P<0.05). Bioinformatics analysis identified 4 103 differentially expressed genes, including Cyclin D1, p53, and BAX, which were predominantly involved in pathways such as the p53 signaling pathway and calcium-related signaling. Spearman analysis revealed that local invasion(rs=0.71, P<0.05)and TNM stage(rs=0.73, P<0.05)correlated with Cyclin D1 expression; local invasion(rs=0.76, P<0.05)and histological subtype(rs=0.65, P<0.05)correlated with p53 expression. Logistic regression results indicated that Cyclin D1, p53, TNM staging, and local invasion were prognostic risk factors. ROC curve analysis demonstrated that the combined detection of these four indicators had the highest predictive value for prognosis(AUC=0.83).CONCLUSION: High expression of cyclin D1 and p53 serves as molecular markers for distinguishing benign from malignant eyelid tumors and assessing prognosis. Combined detection of these markers with TNM staging and local invasion demonstrates high predictive value for prognosis.

Objective: To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control. Methods: Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence. Results: A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk. Conclusions SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.

Yttrium-90 selective internal radiation therapy (⁹⁰Y-SIRT) is a treatment technique that delivers radioactive microspheres precisely to the arterial vascular bed of neoplasms, utilizing beta radiation to administer a high local dose of radiation to the neoplasm tissues. This technology has demonstrated significant efficacy in patients with unresectable pirmary liver cancers and liver metastases. This article systematically reviews the development history and clinical application status of ⁹⁰Y-SIRT in the treatment of liver cancer, and looks forward to future development directions.

Objective To investigate the relationship between the expression of discoidin,CUB and LCCL domain containing protein 1(DCBLD1)and cytoskeleton associated protein 2(CKAP2)in cervical cancer(CC)tissues and epithelial mesenchymal transition(EMT)and clinical prognosis.Methods 94 CC patients diagnosed and treated in Shiyan Hospital of Traditional Chinese Medicine from February 2017 to February 2019 were selected.The expression of DCBLD1 messenger ribonucleic acid(mRNA),CKAP2 mRNA,N-cadherin(N-cad)mRNA,vimentin(Vim)mRNA and TWIST mRNA in tissues was detected by real-time fluorescence quantitative PCR(qRT-PCR).The expressions of DCBLD1 and CKAP2 were detected by immunohistochemistry(IHC).Pearson correlation analysis was used to analyze the relationship between DCBLD1 mRNA,CKAP2 mRNA and EMT-related indicators.Kaplan-Meier survival curve was drawn to compare the prognosis of CC patients with different DCBLD1 mRNA and CKAP2 mRNA expression.COX regression analysis was used to analyze the prognostic factors of CC patients.Results The expression of DCBLD1 mRNA,CKAP2 mRNA,N-cad mRNA,Vim mRNA and TWIST mRNA in CC cancer tissues was higher than that in adjacent tissues,and the differences were statistically significant(t=32.763～52.824,all P<0.05).The positive rates of DCBLD1 protein(89.36%)and CKAP2 protein(87.23%)in CC cancer tissues were higher than those in adjacent normal tissues(7.45%,6.38%),and the differences were statistically significant(χ2=126.278,123.396,all P<0.001).The expression of DCBLD1 mRNA and CKAP2 mRNA in CC cancer tissues were positively correlated with the expression of N-cad mRNA,Vim mRNA and TWIST mRNA(r=0.655～0.744,all P<0.001).The expression of DCBLD1 mRNA and CKAP2 mRNA in patients with FIGO stage IB2～IIB and lymph node metastasis were higher than those in patients with stage IA～IB1 and without lymph node metastasis(t=25.644～35.674,all P<0.05).The 5-year progression free survival rates of the high expression groups of DCBLD1 mRNA and CKAP2 mRNA were 63.04%and 62.22%,respectively,which were lower than those of the low expression groups of DCBLD1 mRNA and CKAP2 mRNA(91.67%and 91.84%),respectively,and the differences were statistically significant(Log-Rank χ2=7.181,6.527,all P<0.05).FIGO stage IB2～IIB,high DCBLD1 mRNA and high CKAP2 mRNA were risk factors affecting the prognosis of CC patients(Wald χ2=8.277,15.877,10.927,all P<0.05).Conclusion The expression of DCBLD1 and CKAP2 in CC cancer tissues is significantly increased,which is related to EMT related indicators and plays a promoting role in the progression of CC tumors.They are new prognostic markers for CC.

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.

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

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.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.