1.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
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.
2.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
3.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
4.Effects of Wenfei Jiangzhuo Formula on mitochondrial function of Aβ25-35-induced BV-2 cells based on PGAM5-Drp1 axis
Ding ZHANG ; Zhi-han HU ; Ke-qing ZHOU ; Wei CHEN ; Hong-ling QING ; Jun-jun XIANG ; Yue-qiang HU
Chinese Traditional Patent Medicine 2025;47(8):2558-2565
AIM To investigate the effects of Wenfei Jiangzhuo Formula on mitochondrial function of Aβ25-35-induced BV-2 cells.METHODS In the establishment of cell model of Alzheimer's disease(AD)using Aβ25-35 on the BV-2 cells,the optimal concentration and time point of Aβ25-35 intervention were determined;and the groups for the intervention of LFHP-1c group(inhibitor)or the serum containing Wenfei Jiangzhuo Formula were set up.The detection of the optimal intervention concentration and time point by CCK-8 assay;the observation of cell migration and apoptosis by Transwell assay and Hoechst 33342 staining;the detection of the positive expressions of PGAM5 and Drp1 by immunofluorescence;and the detection of cellular PGAM5,Drp1,OPA1,and Mfn1/2 mRNA and protein expressions by RT-qPCR and Western blot were conducted.RESULTS The best AD cell model was established by 48 h exposure to 5 μmol/L of Aβ25-35,and most active cell viability was achieved with the 48 h use of serum containing 20%Wenfei Jiangzhuo Formula.Compared with the control group,the model group displayed decreased number of cell migration,more bright blue positive apoptotic cells,increased number of PGAM5 and Drp1 positive cells and their mRNA and protein expressions(P<0.05);and decreased mRNA and protein expressions of OPA1 and Mfn1/2(P<0.05).Compared with the model group,the groups intervened with the medicines shared increased number of cell migration,less bright blue positive apoptotic cells,decreased number of PGAM5 and Drp1 positive cells and their mRNA and protein expressions(P<0.05);and elevated OPA1 and Mfn1/2 mRNA and protein expressions(P<0.05).CONCLUSION Wenfei Jiangzhuo Formula exerts cerebroprotective effects to improve cognition by reducing cell damage and improving the balance of mitochondrial homeostasis through PGAM5-Drp1 axis in AD model.
5.Progress in practice of infectious disease epidemiology in China
Weizhong YANG ; Luzhao FENG ; Zhongjie LI ; Yu LI ; Qiangru HUANG ; Xuancheng HU ; Zeni WU ; Xiaodan FAN ; Ting ZHANG ; Qing WANG ; Yanxia SUN ; Jianxing YU ; Enmin DING ; Mengmeng JIA
Chinese Journal of Epidemiology 2025;46(7):1276-1282
With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.
6.Expert consensus on visualized tele-round and quality control management based on the improvement of clinical practice ability
Wanhong YIN ; Xiaoting WANG ; Ran ZHOU ; Dawei LIU ; Yan KANG ; Yaoqing TANG ; Xiaochun MA ; Jianguo LI ; Zhenjie HU ; Haitao ZHANG ; Wei HE ; Lixia LIU ; Wenjin CHEN ; Ran ZHU ; Jun WU ; Hongmin ZHANG ; Lina ZHANG ; Wenzhao CHAI ; Shihong ZHU ; Wangbin XU ; Rongqing SUN ; Xiangyou YU ; Tianjiao SONG ; Ying ZHU ; Hong REN ; Ai SHANMU ; Qing ZHANG ; Wei FANG ; Xiuling SHANG ; Liwen LYU ; Shuhan CAI ; Xin DING ; Heng ZHANG ; Guang FENG ; Lipeng ZHANG ; Bo HU ; Dong ZHANG ; Weidong WU ; Feng SHEN ; Xiaojun YANG ; Zhenguo ZENG ; Qibing HUANG ; Xueying ZENG ; Tongjuan ZOU ; Milin PENG ; Yulong YAO ; Mingming CHEN ; Hui LIAN ; Jingmei WANG ; Yong LI ; Feng QU ; Gang YE ; Rongli YANG ; Xiukai CHEN ; Suwei LI ; Juxiang WANG ; Yangong CHAO
Chinese Journal of Internal Medicine 2025;64(2):101-109
Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.
7.Analysis of thickness changes in peripapillary retinal nerve fiber layer and associated risk factors in patients with Moyamoya disease
Shui-Qin CAO ; Xiao-Han HU ; Fang-Bing HAO ; Qing GUO ; Ran DING ; Hui LI ; Li-Li CHEN ; Li-Li ZHANG ; Ge LIANG
Medical Journal of Chinese People's Liberation Army 2025;50(7):855-861
Objective To investigate the characteristics of thickness changes in peripapillary retinal nerve fiber layer(pRNFL)and identify related risk factors in patients with Moyamoya disease(MMD).Methods A retrospective study was conducted on 150 MMD patients(150 eyes)aged 6-65 years admitted to the Neurosurgery Department of the Fifth Medical Center,Chinese PLA General Hospital from May 2016 to December 2023(observation group),and 150 age-matched healthy volunteers(150 eyes)from the hospital's ophthalmology outpatient department(control group).Both groups were subdivided into pediatric(≤18 years),young adult(18-40 years),and middle-aged(40-65 years)subgroups.The pRNFL thickness in four quadrants was measured by optical coherence tomography(OCT):superior(pRNFL-Sup),inferior(pRNFL-Inf),nasal(pRNFL-Nas),temporal(pRNFL-Tmp),and average thickness(pRNFL-Avg).General clinical data and pRNFL thickness were compared between two groups.Univariate and multivariate logistic regression analyses were performed to identify risk factors for pRNFL thinning in MMD patients.The cohort was randomly divided into training(n=210)and validation(n=90)sets at a 7:3 ratio.A predictive model for pRNFL thinning in MMD patients was constructed based on logistic regression results.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),and clinical utility was assessed via decision curve analysis.Results Compared with control group,MMD patients exhibited significantly reduced pRNFL-Avg,pRNFL-Sup,pRNFL-Tmp,and pRNFL-Inf thickness(P<0.05 or P<0.001),while pRNFL-Nas showed no significant difference(P>0.05).In the pediatric subgroup,pRNFL-Avg and pRNFL-Inf were thinner(P<0.05).In the young adult subgroup,pRNFL-Avg and pRNFL-Sup were reduced(P<0.001 or P<0.05).In the middle-aged subgroup,pRNFL-Avg,pRNFL-Sup,pRNFL-Inf,and pRNFL-Tmp were all thinner(P<0.05 or P<0.001).Multivariate logistic regression identified visual field defects(OR=15.28,95%CI 2.95-79.10),disease duration(OR=1.11,95%CI 1.05-1.18),and the number of involved cerebral vessels(OR=1.49,95%CI 1.01-2.22)as independent risk factors for pRNFL thinning.The predictive model achieved AUC of 0.94(95%CI 0.91-0.97)and 0.95(95%CI 0.91-0.99)in the training and validation sets,respectively.Decision curve analysis confirmed the model's favorable clinical net benefit.Conclusion Thinning of pRNFL was observed in Moyamoya disease patients with visual field defects,disease duration,and cerebral vascular involvement identified as independent risk factors for pRNFL atrophy.
8.Progress in practice of infectious disease epidemiology in China
Weizhong YANG ; Luzhao FENG ; Zhongjie LI ; Yu LI ; Qiangru HUANG ; Xuancheng HU ; Zeni WU ; Xiaodan FAN ; Ting ZHANG ; Qing WANG ; Yanxia SUN ; Jianxing YU ; Enmin DING ; Mengmeng JIA
Chinese Journal of Epidemiology 2025;46(7):1276-1282
With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.
9.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
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.
10.Analysis of Positive Results of Anti-M Unexpected Antibody in Pediatric Inpatients in Central China
Dong-Dong TIAN ; Ding ZHAO ; Wei LI ; Yong-Jun WANG ; Hong-Bing HU ; Yuan-Qing YANG ; Zheng-Feng LI
Journal of Experimental Hematology 2025;33(4):1155-1160
Objective:To analyze the positive rate and distribution of anti-M unexpected antibody in pediatric inpatients aged 0 to 14 years in central China.Methods:A total of 30 049 pediatric inpatients admitted to the Second Xiangya Hospital of Central South University,Wuhan Children's Hospital and Children's Hospital Affiliated of Zhengzhou University from May 2020 to August 2022 were enrolled in this study,and relevant clinical data were collected.Blood samples from the patients were tested for blood typing and screened for unexpected antibodies.For samples that screened positive for unexpected antibodies,identification was conducted using the identification panel to determine the specificity of the antibodies.The distribution and differences of anti-M antibodies in pediatric patients of different sexes,ages,blood groups,disease types,with or without a history of blood transfusion,and across different regions were analyzed.Results:Among 30 049 inpatients,the positive rate of unexpected antibodies was 0.91%(273/30 049),of which the positive rate of anti-M antibodies was 0.44%(131/30 049).The positive rate of anti-M antibodies in the neonates aged 0 to<1 month was 0.10%(5/4 881),and all of them were IgG antibodies from their mothers;The positive rate of anti-M antibodies for the group aged from 1 month to<1 year old was 0.23%(7/3 108),with no anti-M antibodies detected in patients aged 1-6 months;The positive rates of anti-M antibodies in the 1-4 years old group,5-9 years old group,and 10-14 years old group were 0.87%(88/10 064),0.38%(27/7 190),and 0.08%(4/4 806),respectively.The positive rate of anti-M antibodies in the 1-4 years old group was significantly higher than that of the other groups(P<0.001),and there were also statistical differences in the positive rate between the 5-9 years old group and the 0-<1 month and 10-14 years old groups(P<0.001).The prevalences of anti-M antibodies in ABO blood group A,B,O and AB were 0.32%(30/9 482),0.70%(58/8 293),0.32%(31/9 595)and 0.45%(12/2 679),respectively.The prevalence of anti-M antibodies in patients with blood group B was significantly higher than that in patients with blood groups A and O(P<0.05).The prevalences of anti-M antibodies in Hunan,Hubei and Henan was 0.18%,0.32%and 0.71%,respectively.The prevalence of anti-M antibodies in Henan was significantly higher than that in Hunan and Hubei(P<0.05),and the distribution showed obvious regional differences between the north and the south.There were no significant differences in the positive rate of anti-M antibodies between the children with different sexes,disease types,and with or without a history of blood transfusion(P>0.05).Conclusion:This study reveals the distribution pattern of anti-M antibodies in pediatric inpatients aged 0-14 years in central China,which has reference value for the research on unexpected red blood cell antibodies in Chinese children.

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