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.

Polymyxins, a class of cyclic peptide antibiotics, have become the last line of defense against gram-negative bacterial infections as the number of multidrug-resistant bacteria continues to rise. Heteroresistance refers to the presence of subpopulations within the same strain with varying sensitivities to antibiotics, which cannot be detected by standard clinical tests and may result in treatment failure. In several common gram-negative bacteria, mutations in the PhoPQ and PmrAB two-component systems are key contributors to polymyxin heteroresistance. This review aims to summarize recent research on the mechanisms of polymyxin heteroresistance in gram-negative bacteria, so as to provide insights for developing rapid detection methods and improving clinical treatment strategies.

Antimicrobial susceptibility testing (AST) helps guide clinical rational selection of antibiotics, enabling patients to achieve better prognosis and reducing the development of drug resistance. However, traditional AST is time-consuming and labor-intensive, meaning that clinicians are not able to obtain susceptibility results in a timely manner, and have to rely on experience based on bacterial species and epidemiological data for empirical drug selection. This may be one of the reasons for the continuous increase in the number of drug-resistant strains. In recent years, researchers have focused on the development of rapid and simple AST assays and have made relevant research progress. This article reviews the new AST technologies based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), microfluidic chip systems, nucleic acid detection methods, immunological detection, and flow cytometry, in the hope of providing reference for improving the efficiency of AST testing in clinical microbiology laboratories.

Objective:To explore the impact of sleep duration, physical exercise, and their interactions on the risk of dyslipidemia in older adults aged ≥80 (the oldest old) in China.Methods:The study subjects were the oldest old from four rounds of Healthy Aging and Biomarkers Cohort Study (2008-2009, 2011-2012, 2014 and 2017-2018). The information about their demographic characteristics, lifestyles, physical examination results and others were collected, and fasting venous blood samples were collected from them for blood lipid testing. Competing risk model was used to analyze the causal associations of sleep duration and physical exercise with the risk for dyslipidemia. Restricted cubic spline (RCS) function was used to explore the dose-response relationship between sleep duration and the risk for dyslipidemia. Additive and multiplicative interaction model were used to explore the interaction of sleep duration and physical exercise on the risk for dyslipidemia.Results:The average age of 1 809 subjects was (93.1±7.7) years, 65.1% of them were women. The average sleep duration of the subjects was (8.0±2.5) hours/day, 28.1% of them had sleep duration for less than 7 hours/day, and 27.2% had sleep for duration more than 9 hours/day at baseline survey. During the 9-year cumulative follow-up of 6 150.6 person years (follow-up of average 3.4 years for one person), there were 304 new cases of dyslipidemia, with an incidence density of 4 942.6/100 000 person years. The results of competitive risk model analysis showed that compared with those who slept for 7-9 hours/day, the risk for dyslipidemia in oldest old with sleep duration >9 hours/day increased by 22% ( HR=1.22, 95% CI: 1.07-1.39). Compared with the oldest old having no physical exercise, the risk for dyslipidemia in the oldest old having physical exercise decreased by 33% ( HR=0.67, 95% CI: 0.57-0.78). The RCS function showed a linear positive dose-response relationship between sleep duration and the risk for hyperlipidemia. The interaction analysis showed that physical exercise and sleep duration had an antagonistic effect on the risk for hyperlipidemia. Conclusion:Physical exercise could reduce the adverse effects of prolonged sleep on blood lipids in the oldest old.

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.

Objective To investigate the effect of phlorizin on the apoptosis and oxidative stress of rat cardiomyocytes H9C2 induced by hypoxia/reoxygenation(H/R)and its possible mechanism.Methods H9C2 cells were cultured in vitro.H/R model was established after pretreatment with different doses(16,32,64 μmol/L)of phlorizin or transfection with anti-miR-125a-5p,anti-miR-NC,miR-125a-5p mimics and negative controls.Proliferation was detected by CCK-8,and apoptosis was detected by flow cytometry.The protein expression levels of B lymphoblastoma-2 associated X protein(Bax)and B lymphocytoma-2(Bcl-2)were detected by Western blot assay.The release of lactate dehydrogenase(LDH)and the activity of superoxide dismutase(SOD)were detected by colorimetric method.Real-time fluorescence quantitative PCR(qRT-PCR)was used to detect the expression of miR-125a-5p.Results Compared with the H/R group,inhibition rate,apoptosis rate,Bax protein expression,LDH content and miR-125a-5p expression were decreased after low,medium and high doses of phlorizin treatment(P＜0.05),and SOD activity,Bcl-2 protein expression were increased(P＜0.05).After inhibiting the expression of miR-125a-5p,the inhibition rate,apoptosis rate,Bax protein expression and LDH content of H9C2 cells induced by H/R were decreased(P＜0.05),and SOD activity,Bcl-2 protein expression were increased(P＜0.05).Overexpression of miR-125a-5p reversed the effect of phloridin on H/R-induced proliferation,apoptosis and oxidative stress of H9C2 cells.Conclusion Phlorizin may reduce H/R-induced apoptosis and oxidative stress in H9C2 cells by decreasing the expression of miR-125a-5p.