1.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
2.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
3.Research progress of immunotherapy in the frontline treatment of adult B cell-acute lymphoblastic leukemia
Tian YUN ; Li RUIPING ; Ma YANPING
Chinese Journal of Clinical Oncology 2025;52(12):628-632
In recent years,the application of immunotherapy has improved the prognosis of relapsed/refractory(R/R)B cell-acute lympho-blastic leukemia(B-ALL).Blinatumomab,Inotuzumab ozogamicin(InO),and chimeric antigen receptor(CAR)T-cell therapies are the three major immunotherapeutic agents approved for the treatment of R/R B-ALL.This new strategy incorporates immunotherapy into the first line of treatment to reduce the adverse effects of chemotherapy,prolong survival,and expand treatment options for elderly patients.This art-icle discusses new approaches for incorporating immunotherapeutic agents into firstline B-ALL treatment regimens,exploring the potential value of chemotherapy-free regimens in specific patient subgroups,to provide guidance for clinical practice.
4.Prevalence and risk factors of falls in patients with knee osteoarthritis:a Meta-analysis
Yueyue JIA ; Zhilan YANG ; Yanping ZHAI ; Hongrui SHI ; Huimin ZHAO ; Yuanyuan JIN ; Xingyu LIU ; Zhili YAN ; Ziwei TIAN
Chinese Journal of Nursing 2025;60(10):1177-1183
Objective To clarify the evidence of the frequency and risk factors for falls in knee osteoarthritis(KOA)of adults by meta-analysis.Methods Computerized searches of the CNKI,VIP,Wanfang data,CBM,PubMed,Cochrane Library,Embase,Web of Science were conducted for literature on risk factors for falls in adults with KOA from the inception of the databases to August 2024.After literature screening,data extraction,and quality evaluation,RevMan 5.4 software was used for Meta-analysis.Results A total of 26 articles were involved.Meta-analysis result showed that the rate of falls was 29.0%.Factors associated with increased risk of falls included being female(OR=1.35),decreased lower limb muscle strength(OR=1.72),decreased knee flexion muscle strength(OR=7.05),decreased static posture stability(OR=1.28),opioid use(OR=1.79),antidepressant use(OR=1.69),frequent stair climbing(OR=7.58),combined neurological disease(OR=1.77),history of falls(OR=3.29)and fear of falling(OR=2.54).Conclusion The rate of falls of patients with KOA is high.The adults with KOA who are women,have lower muscle strength of lower limbs and knee flexion muscle strength,poorer static posture stability,use opioids,antidepressant,frequent stair climbing,combined neurological disorders,previous falls in the past year and fear of falls are at higher risk of falls.Healthcare professionals should dynamically assess and detect the risk of falls in the patients with KOA and adopt targeted,individualized interventions to prevent falls.
5.Supplementing Denver model intervention with transcranial magnetic stimulation improves the treatment of young children with autism spectrum disorder
Wei LI ; Yanping TIAN ; Yanmei LAI ; Qinghong LI ; Qiao SUN ; Hong LI ; Xin ZHANG ; Zhihai LYU
Chinese Journal of Physical Medicine and Rehabilitation 2025;47(4):359-363
Objective:To observe any effect of supplementing treatment according to the Early Start Denver model (ESDM) with repeated transcranial magnetic stimulation (rTMS) in the treatment of children with autism spectrum disorder (ASD).Methods:Sixty-seven children on the autism spectrum aged 2 or 3 years were randomly divided into a control group of 33 and an observation group of 34. Both groups were treated as specified by the ESDM for 24 weeks, but the observation group additionally received rTMS. At 12 and 24 weeks, both groups were evaluated using the Autism Behavior Checklist, the Childhood Autism Rating Scale (CARS), the revised version of the Repetitive Behavior Scale (RBS-R), Gesell Development Schedules, and the Autism Treatment Evaluation Checklist (ATEC).Results:The CARS, Gesell, RBS-R and ATEC results of both groups had improved significantly after 12 weeks, with further improvements observed another 12 weeks later, when the average Autism Behavior Checklist scores had also improved significantly. At that point the results of the observation group were significantly better than those of the control group, on average.Conclusions:Combining ESDM and rTMS can significantly relieve the main symptoms of autism and improve the comprehensive development of children on the autism spectrum 2 or 3 years old. Therefore, such combination is worthy of application in clinical practice.
6.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(4):445-454
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.
7.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
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.
8.Mechanism of agomelatine alleviating anxiety-and depression-like behaviors in APP/PS1 transgenic mice
Tian LI ; Yuhua REN ; Yanping GAO ; Qiang SU
Chinese Journal of Tissue Engineering Research 2025;29(6):1176-1182
BACKGROUND:Agomelatine is a clinically proven treatment for neuropsychiatric symptoms,such as anxiety and depression.Furthermore,our previous study has demonstrated that agomelatine ameliorates cognitive behaviors,hippocampal synaptic plasticity,and brain pathology in a mouse model of Alzheimer's disease.However,it remains unclear whether agomelatine can improve anxiety and depression-like behaviors in Alzheimer's disease model mice. OBJECTIVE:To investigate the improving effects of agomelatine on anxiety-and depression-like behaviors in APP/PS1 transgenic mice and its underlying molecular mechanisms. METHODS:(1)Eighteen APP/PS1 transgenic mice were randomly divided into model control group(n=9)and model intervention group(n=9).Another wild-type mice were randomized into control group(n=9)and intervention group(n=9).Model intervention group and intervention group were intraperitoneally injected with 10 mg/kg agomelatine per day for 31 continuous days.Behavioral experiments,including the elevated cross maze and forced swimming tests,and mRNA sequencing of the hippocampus were then performed.(2)Mouse hippocampal neuronal cell lines(HT22)and brain microvascular endothelial cell lines(bEnd.3)were cultured and divided into four groups:blank group without any drug,drug group with 20 μmol/L agomelatine,model group with 10 μmol/L β-amyloid 1-42,and experimental group with 10 μmol/L β-amyloid 1-42+20 μmol/L agomelatine.After 24 hours of incubation,protein expression of S416p-tau and S9p-GSK3β in HT22 cells was detected by immunoblotting,and protein expression of low-density lipoprotein receptor-related protein 1 and glycosylation end-product receptor in bEnd.3 cells was detected by immunoblotting. RESULTS AND CONCLUSION:In the elevated plus maze test,the time spent in the open arms(P<0.01)and the entries into open arms(P<0.05)in the mice of model control group were evidently lower than those in the control group,whereas those were obviously increased in the model intervention group compared with the model control group(P<0.05).Forced swimming test results showed that the immobile time exhibited a marked increase in the model control group compared with the control group(P<0.05),but it was significantly decreased in the model intervention group compared with the model control group(P<0.05).Hippocampal tissue mRNA sequencing showed that agomelatine enhanced the expression of low-density lipoprotein receptor-related protein 1 in the hippocampus of APP/PS1 mice.Western blot analysis revealed that the level of S416p-tau in HT22 cells was higher in the model group than the blank group(P<0.05),while it was markedly decreased in the experimental group compared with the model group(P<0.05);the level of S9p-GSK3β in HT22 cells was higher in the drug group than the blank group(P<0.05)as well as higher in the experimental group than the model group(P<0.05).Moreover,the expression of low-density lipoprotein receptor-related protein 1 in bEnd.3 cells was higher in the experimental group than the model group(P<0.05).To conclude,agomelatine can alleviate anxiety-and depression-like behaviors in Alzheimer's disease mice by promoting the clearance of β-amyloid and phosphorylated tau.
9.Screening and identification of genes for exiting na?ve pluripotency in embryonic stem cells using the CRISPR-Cas9 knockout system
Yi YANG ; Yan RUAN ; Junlei ZHANG ; Yanping TIAN ; Meng YU ; Hongli LI
Journal of Army Medical University 2025;47(18):2223-2236
Objective To systematically identify the key genes regulating the exit from na?ve pluripotency in embryonic stem cells(ESCs)in order to provide novel targets and theoretical insights into the mechanisms for pluripotency transition and early cell fate determination.Methods Nanog-green fluorescent protein(Nanog-GFP)reporter-labeled ESCs were infected with a genome-wide Brie knockout library,and further cultured under leukemia inhibitory factor/serum(LIF/S)conditions for 14 d.Flow cytometry was used to sort Nanog-GFP?(na?ve-state)and Nanog-GFP-(primed state)cell populations,followed by genomic DNA extraction and high-throughput sequencing.Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout(MAGeCK)was applied to identify differential genes between GFP?/Input,GFP?/Input,and GFP?/GFP? groups.Metascape and Gene Set Enrichment Analysis(GSEA)were conducted for functional enrichment analysis.Then the obtained candidate genes were employed to construct knockout models,and their roles were assessed through cell morphology observation,Nanog-positive rate detection,colony formation assays,and pluripotency gene expression analysis.Results The GFP?/Input screening revealed 2 921 negatively regulated genes(mainly enriched in basic life processes,such as RNA metabolism and cell cycle)and 1 393 positively regulated genes(enriched in the processes of nervous system development,carbohydrate metabolism,and vascular system development).In the GFP?/Input screening,2 765 negatively regulated genes(enriched in RNA metabolism,cell cycle,and other fundamental processes)and 1 303 positively regulated genes(enriched in neural development,cell survival,and endothelial migration)were identified.The GFP?/GFP? comparison identified 1 001 negatively regulated genes[involved in stress response and inhibition of mitogen-activated protein kinase(MAPK)signaling]and 983 positively regulated genes[related to fibroblast growth factor/extracellular signal-regulated kinase(FGF/ERK)signaling pathway and glucose metabolism).These genes,were not only known pluripotency regulators(e.g.,Nanog,Nr5a2,Klf2,Klf4)and exit-associated genes(e.g.,Gata6,Grb2,Zeb1,Fgfr1),but also some novel candidates(e.g.,Dmrt1,Rxra,Zbtb14 and Tmem41b).Functional validation showed that transient knockout of Dmrt1,Tmem41b,and Hic2 significantly increased the proportion of Nanog? cells(P<0.01),suggesting their role in suppressing ground-state exit.ESCs with stable Dmrt1 knockout exhibited a more na?ve-state phenotype,presenting compact,dome-shaped colonies,with increased ratio of undifferentiated colonies(P<0.01),up-regulation of ground-state markers(Nanog,Nr5a2,Dppa3,P<0.01),and down-regulation of primed-state markers(Fgf5,Lefty1,Dnmt3b,P<0.01).Rescue experiments for Dmrt1 expression reversed these above phenotypes.Conclusion A candidate gene set regulating exit from na?ve pluripotency in ESC is screened out and identified with genome-wide CRISPR.Our findings implicate Dmrt1 plays a critical role in promoting the exit.
10.Identification of Medical Surge Risk Influencing Factors and Analysis of Causal Coupling Relationships Based on DEMATEL-ISM
Yiran GAO ; Nan MENG ; Tian YU ; Yanping WANG ; Min WEI ; Wanmeng TENG ; Jialin LU ; Peng WANG ; Kexin WANG ; Ning NING ; Yanhua HAO ; Avdeev SERGEY ; Qunhong WU
Chinese Hospital Management 2025;45(11):6-10
Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Result Analysis
Print
Save
E-mail