1.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.
2.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.
3.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.
4.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.
5.Analysis of multimorbidity trends and influencing factors of internet addiction and depression symptoms among middle school students in Zhejiang Province
Fang GU ; Ying YANG ; Weijun ZHENG ; Juanjuan LI ; Lei GAO ; Yu SHEN ; Jia MENG ; Ronghua ZHANG ; Bin DONG
Chinese Journal of Preventive Medicine 2025;59(2):167-173
Objective:To analyze the multimorbidity trends and influencing factors of internet addiction and depressive symptoms among middle school students in Zhejiang Province.Methods:From 2018 to 2023, a multistage stratified random cluster sampling method was used to select middle school students aged 12 to 18 in Zhejiang Province. Internet addiction and depression status were measured by the Internet Addiction Scale and the Center for Epidemiologic Studies Depression Scale. When both symptoms were present, it was defined as multimorbidity.The multivariate logistic regression model was used to analyze the influencing factors of multimorbidity among middle school students, and a trend Chi-square test was used to analyze the changing trends of internet addiction, depression and multimorbidity prevalence. Results:A total of 193 505 students were included in the study. From 2018 to 2023, the prevalence of multimorbidity of internet addiction and depressive symptoms among middle school students ranged from 2.7% to 3.5%. The prevalence of internet addiction ranged from 4.7% to 6.0%, while the prevalence of depressive symptoms ranged from 18.7% to 25.1%. Multivariate logistic regression showed that boarding students ( OR=1.34 , 95% CI: 1.26-1.42), low-frequency ( OR=1.59, 95% CI: 1.46-1.73), and high-frequency sugary drink consumption ( OR=3.91, 95% CI: 3.55-4.31) increased the risk of multimorbidity among middle school students. In contrast, higher frequencies of moderate-to-high-intensity exercise (medium: OR=0.54, 95% CI: 0.50-0.58; high: OR=0.49, 95% CI: 0.44-0.55) and sufficient sleep ( OR=0.52, 95% CI: 0.49-0.56) were protective factors. From 2018 to 2023, there was no significant change in the trend of multimorbidity prevalence among middle school students ( χ2trend=3.82, P=0.051). The prevalence of internet addiction showed an upward trend ( χ2trend=20.54, P<0.001), while depressive symptoms showed a downward trend ( χ2trend=181.41, P<0.001). Conclusion:The prevalence of internet addiction and depression symptoms among middle school students in Zhejiang Province remains stable from 2018 to 2023. The prevalence of internet addiction shows an upward trend, while the prevalence of depression symptoms shows a downward trend. The risk of multimorbidity is related to students′ boarding, consumption of sugary drinks, lack of exercise, and insufficient sleep.
6.Safety study on the simultaneous administration of oral pentavalent recombinant rotavirus attenuated live vaccine and other vaccines in Chaoyang District, Beijing City from 2019 to 2021
Tianjing CHEN ; Jiao ZHANG ; Shuping LI ; Li LI ; Bin JIA ; Jianxin MA ; Zheng ZHANG ; Jinbo HE ; Yunhua BAI
Chinese Journal of Preventive Medicine 2025;59(6):942-945
The incidence rate of suspected adverse events following immunization (AEFI) after single administration of pentavalent recombinant rotavirus attenuated live vaccine (RV5) in Chaoyang District, Beijing City from 2019 to 2021 was 362.3 per 100 000 doses. The incidence rate of AEFI after simultaneous administration with oral polio vaccine (OPV), inactivated polio vaccine (IPV), hepatitis B vaccine (HBV), Haemophilus influenzae type b (Hib), and pneumococcal conjugate vaccine 13-valent (PCV13) was 239.3 per 100 000, 643.4 per 100 000, 346.8 per 100 000, 438.1 per 100 000, and 434.0 per 100 000, respectively. The specific incidence rates for common AEFI symptoms such as fever, local allergic rash, irritability, and vomiting under different vaccination regimens were as follows: RV5 alone (fever: 88.3 per 100 000, rash: 9.1 per 100 000, irritability: 100.5 per 100 000, vomiting: 83.3 per 100 000), RV5 and IPV simultaneous administration (fever: 239.4 per 100 000, rash: 104.7 per 100 000, irritability: 134.7 per 100 000, vomiting: 89.8 per 100 000), RV5 and OPV simultaneous administration (fever: 119.6 per 100 000, rash: 32.6 per 100 000, irritability: 32.6 per 100 000, vomiting: 32.6 per 100 000), RV5 and HBV simultaneous administration (fever: 111.0 per 100 000, rash: 69.4 per 100 000, irritability: 83.2 per 100 000, vomiting: 41.6 per 100 000), RV5 and Hib simultaneous administration (fever: 159.3 per 100 000, rash: 238.9 per 100 000, irritability: 0 per 100 000, vomiting: 39.8 per 100 000), and RV5 and PCV13 simultaneous administration (fever: 142.8 per 100 000, rash: 98.0 per 100 000, irritability: 126.0 per 100 000, vomiting: 25.2 per 100 000).
7.Csde1 Mediates Neurogenesis via Post-transcriptional Regulation of the Cell Cycle.
Xiangbin JIA ; Wenqi XIE ; Bing DU ; Mei HE ; Jia CHEN ; Meilin CHEN ; Ge ZHANG ; Ke WANG ; Wanjing XU ; Yuxin LIAO ; Senwei TAN ; Yongqing LYU ; Bin YU ; Zihang ZHENG ; Xiaoyue SUN ; Yang LIAO ; Zhengmao HU ; Ling YUAN ; Jieqiong TAN ; Kun XIA ; Hui GUO
Neuroscience Bulletin 2025;41(11):1977-1990
Loss-of-function variants in CSDE1 have been strongly linked to neuropsychiatric disorders, yet the precise role of CSDE1 in neurogenesis remains elusive. In this study, we demonstrate that knockout of Csde1 during cortical development in mice results in impaired neural progenitor proliferation, leading to abnormal cortical lamination and embryonic lethality. Transcriptomic analysis revealed that Csde1 upregulates the transcription of genes involved in the cell cycle network. Applying a dual thymidine-labelling approach, we further revealed prolonged cell cycle durations of neuronal progenitors in Csde1-knockout mice, with a notable extension of the G1 phase. Intersection with CLIP-seq data demonstrated that Csde1 binds to the 3' untranslated region (UTR) of mRNA transcripts encoding cell cycle genes. Particularly, we uncovered that Csde1 directly binds to the 3' UTR of mRNA transcripts encoding Cdk6, a pivotal gene in regulating the transition from the G1 to S phases of the cell cycle, thereby maintaining its stability. Collectively, this study elucidates Csde1 as a novel regulator of Cdk6, sheds new light on its critical roles in orchestrating brain development, and underscores how mutations in Csde1 may contribute to the pathogenesis of neuropsychiatric disorders.
Animals
;
Neurogenesis/genetics*
;
Cell Cycle/genetics*
;
Mice, Knockout
;
Mice
;
Neural Stem Cells/metabolism*
;
DNA-Binding Proteins/metabolism*
;
Cyclin-Dependent Kinase 6/genetics*
;
Cell Proliferation
;
3' Untranslated Regions
;
Cerebral Cortex/embryology*
;
RNA-Binding Proteins
;
Mice, Inbred C57BL
8.RNA G-quadruplex (rG4) exacerbates cellular senescence by mediating ribosome pausing.
Haoxian ZHOU ; Shu WU ; Bin LI ; Rongjinlei ZHANG ; Ying ZOU ; Mibu CAO ; Anhua XU ; Kewei ZHENG ; Qinghua ZHOU ; Jia WANG ; Jinping ZHENG ; Jianhua YANG ; Yuanlong GE ; Zhanyi LIN ; Zhenyu JU
Protein & Cell 2025;16(11):953-967
Loss of protein homeostasis is a hallmark of cellular senescence, and ribosome pausing plays a crucial role in the collapse of proteostasis. However, our understanding of ribosome pausing in senescent cells remains limited. In this study, we utilized ribosome profiling and G-quadruplex RNA immunoprecipitation sequencing techniques to explore the impact of RNA G-quadruplex (rG4) on the translation efficiency in senescent cells. Our results revealed a reduction in the translation efficiency of rG4-rich genes in senescent cells and demonstrated that rG4 structures within coding sequence can impede translation both in vivo and in vitro. Moreover, we observed a significant increase in the abundance of rG4 structures in senescent cells, and the stabilization of the rG4 structures further exacerbated cellular senescence. Mechanistically, the RNA helicase DHX9 functions as a key regulator of rG4 abundance, and its reduced expression in senescent cells contributing to increased ribosome pausing. Additionally, we also observed an increased abundance of rG4, an imbalance in protein homeostasis, and reduced DHX9 expression in aged mice. In summary, our findings reveal a novel biological role for rG4 and DHX9 in the regulation of translation and proteostasis, which may have implications for delaying cellular senescence and the aging process.
G-Quadruplexes
;
Cellular Senescence
;
Ribosomes/genetics*
;
Humans
;
Animals
;
Mice
;
DEAD-box RNA Helicases/genetics*
;
Protein Biosynthesis
;
RNA/chemistry*
;
Neoplasm Proteins
9.Expert consensus on clinical randomized controlled trial design and evaluation methods for bone grafting or substitute materials in alveolar bone defects.
Xiaoyu LIAO ; Yang XUE ; Xueni ZHENG ; Enbo WANG ; Jian PAN ; Duohong ZOU ; Jihong ZHAO ; Bing HAN ; Changkui LIU ; Hong HUA ; Xinhua LIANG ; Shuhuan SHANG ; Wenmei WANG ; Shuibing LIU ; Hu WANG ; Pei WANG ; Bin FENG ; Jia JU ; Linlin ZHANG ; Kaijin HU
West China Journal of Stomatology 2025;43(5):613-619
Bone grafting is a primary method for treating bone defects. Among various graft materials, xenogeneic bone substitutes are widely used in clinical practice due to their abundant sources, convenient processing and storage, and avoidance of secondary surgeries. With the advancement of domestic production and the limitations of imported products, an increasing number of bone filling or grafting substitute materials isentering clinical trials. Relevant experts have drafted this consensus to enhance the management of medical device clinical trials, protect the rights of participants, and ensure the scientific and effective execution of trials. It summarizes clinical experience in aspects, such as design principles, participant inclusion/exclusion criteria, observation periods, efficacy evaluation metrics, safety assessment indicators, and quality control, to provide guidance for professionals in the field.
Humans
;
Bone Substitutes/therapeutic use*
;
Randomized Controlled Trials as Topic/methods*
;
Consensus
;
Bone Transplantation
;
Research Design

Result Analysis
Print
Save
E-mail