Objective: To classify the ABO blood group phenotypes of 5 cases from a family, and to explore the molecular mechanism for reduced B antigen expression in ABO blood group system. Methods: Serological identification of the ABO blood group was performed using microcolumn gel assay and saline tube method. The soluble antigens in saliva were detected by the agglutination inhibition assay. The full-length sequences and upstream promoter regions of ABO gene were sequenced for genotyping using PacBio SMRT sequencing technology. Results: The results of serological tests indicated the expression of B antigen decreased in 3 out of 5 blood samples. A mixed-field agglutination was observed with anti-B antibody. B antigen was not detected in all 5 saliva samples. The ABO genotype for all samples were ABO B.01/ABO O.01.02, and a novel mutation c. 28+5875C>T within the DNA-binding region of RUNX1 in +5.8-kb site were found in the B allele for 3 samples with reduced expression of B antigen. Conclusion: Results of serological and genetic analyses classify the 3 cases with reduced B antigen expression as B phenotype. The novel mutation c. 28+5875C>T of RUNX1 could be the key reason for reduced B antigen expression in 3 cases with B phenotype.

Antimicrobial resistance (AMR) has emerged as a major global public health challenge, with traditional prevention and control methods exhibiting significant limitations in detection efficiency, data processing, and clinical decision-making. Leveraging its robust capabilities in data analysis and pattern recognition, artificial intelligence (AI) technology has been widely applied across multiple critical aspects of AMR containment. Current evidence demonstrates that AI technologies can significantly enhance the efficiency of resistancediagnosis, optimize personalized treatment strategies, and improve real-time monitoring of resistant pathogen transmission. Despite persistent challenges such as data heterogeneity, model interpretability, and ethical compliance in practical applications, AI holds immense promise in supporting precision infection management and addressing the growing crisis of antimicrobial resistance.This article systematically reviews the clinical applications of AI in AMR prevention and control, including resistance detection and prediction based on mass spectrometry and genomic data, the use of clinical decision support systems in anti-infective therapy, as well as the role of AI in epidemiological surveillance, pathogen tracking, early warning systems, and novel antimicrobial drug discovery aiming to provide reference for clinical practice.

Enterobacterales are important pathogens responsible for hospital-acquired infections and can cause various severe infectious diseases. Since their first report, extended-spectrum β-lactamase-producing Enterobacterales(ESBL-E) have become widely prevalent worldwide. These strains often exhibit multidrug resistance, significantly increasing the risk of treatment failure and patient mortality. In China, the prevention and control of ESBL-E face numerous challenges, including high prevalence rates, significant regional distribution disparities, uneven laboratory testing capabilities, and variations in antimicrobial stewardship and prescribing practices. To address these issues, Professors Zhuo Chao, Xu Yingchun and Yu Yunsong initiated the developmentof the Expert Consensus on Clinical Management Strategies for Infections Caused by Extended-Spectrum β-Lactamase-Producing Enterobacterales (2025), in collaboration with multidisciplinary experts. This consensus systematically reviews the global and domestic epidemiological characteristics of ESBL-E, clinical laboratory detection techniques, treatment principles and key therapeutic agents, as well as infection prevention and control measures. Furthermore, it elaborates on the microbiological features and stratified treatment strategies for different infection sources (including bloodstream infections, intracranial infections, respiratory and mediastinal infections, intra-abdominal infections, and urinary tract infections) and special populations (such as neutropenic patients with fever, emergency patients, and pediatric patients). The consensus aims to enhance the detection capacity of clinical laboratories for ESBL-E, standardize diagnosis and treatment strategies in healthcare settings, and provide scientific guidance to curb the spread of ESBL-E in China, thereby reducing associated morbidity and mortality.

As a vital part of laboratory examination, morphological evaluation and identification play an important role in clinical diagnosis, treatment and prognosis assessment. Traditional morphological image analysis mainly relies on manual microscopy, and missed diagnosis and misuse are unavoidable by the human readout method. The rapid development of artificial intelligence (AI) technology provides a new solution for morphological image analysis. The purpose of this review is to introduce the application of AI in the field of morphological image recognition and the progress of clinical research related to morphological image examination.

To analyze the epidemiological characteristics of acute respiratory infections (ARIs) during the autumn-winter season in Beijing, providing evidence for the prevention, control, diagnosis, and treatment of ARIs.

miR-135 is a highly conserved miRNA in mammals and includes miR-135a and miR-135b.Recent studies have shown that miR-135b is a key regulatory factor in cardio-cerebrovascular diseases.It is involved in regulating the pathological process of myocardial infarction,myocardial ischemia/reperfusion injury,cardiac hypertrophy,atrial fibrillation,diabetic cardiomyopathy,atherosclerosis,pulmonary hyperten-sion,cerebral ischemia/reperfusion injury,Parkinson's disease,and Alzheimer's disease.Obviously,miR-135b is an emerging player in cardio-cerebrovascular diseases and is expected to be an important target for the treatment of cardio-cerebrovascular diseases.However,the crucial role of miR-135b in cardio-cerebrovascular diseases and its underlying mechanism of action has not been reviewed.Therefore,in this review,we aimed to comprehensively summarize the role of miR-135b and the signaling pathway mediated by miR-135b in cardio-cerebrovascular diseases.Drugs targeting miR-135b for the treatment of diseases and related patents,highlighting the importance of this target and its utility as a therapeutic target for cardio-cerebrovascular diseases,have been discussed.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.