1.Needs for rehabilitation in China: Estimates based on the Global Burden of Disease Study 1990-2019.
Tian TIAN ; Lin ZHU ; Qingzhen FU ; Shiheng TAN ; Yukun CAO ; Ding ZHANG ; Mingxue WANG ; Ting ZHENG ; Lijing GAO ; Daria VOLONTOVICH ; Yongchen WANG ; Jinming ZHANG ; Zhimei JIANG ; Hongbin QIU ; Fan WANG ; Yashuang ZHAO
Chinese Medical Journal 2025;138(1):49-59
BACKGROUND:
As an essential part of health services, rehabilitation is of great significance to improve the health and quality of life of the whole population. Accelerating aging calls for a significant expansion of rehabilitation services in China, but rehabilitation needs remain unclear. We conducted the study to explore the rehabilitation needs in China and project the trend of rehabilitation needs from 2020 to 2034.
METHODS:
The data of health conditions that might potentially benefit from rehabilitation were obtained from Global Burden of Disease (GBD) study. Estimated annual percentage changes (EAPCs) were calculated to quantify the trends of the age-standardized rates. Projections of rehabilitation needs were made until 2034 using Bayesian age-period-cohort analysis (BAPC).
RESULTS:
Approximately 460 million persons (33.3% of the total population) need rehabilitation in China, contributing to 63 million years lived with disabilities (YLDs) in 2019. The number of prevalent cases that need rehabilitation increased from around 268 (95% uncertainty interval [UI]: 257-282) million in 1990 to almost 460 (95% UI: 443-479) million in 2019, representing an increase of 71.3%. The highest contribution to the need for rehabilitation was musculoskeletal disorders with about 322 (95% UI: 302-343) million persons in seven aggregate disease and injury categories, and hearing loss with over 95 (95% UI: 84-107) million people among 25 health conditions. Based on the projection results, there will be almost 636 million people (45% of the total population) needing rehabilitation services in China by 2034, representing an increase of 38.3%. The rehabilitation needs of neoplasms, cardiovascular diseases, and neurological disorders are expected to increase significantly from 2019 to 2034, with increases of 102.3%, 88.8% and 73.2%, respectively.
CONCLUSIONS
The need for rehabilitation in China substantially increased over the last 30 years. It is predicted that over two in five people will require rehabilitation by 2034, thus suggesting the need to develop rehabilitation services that meet individuals' rehabilitation needs.
Humans
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China/epidemiology*
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Global Burden of Disease
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Female
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Male
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Musculoskeletal Diseases/epidemiology*
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Rehabilitation/trends*
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Quality of Life
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Middle Aged
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Aged
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Bayes Theorem
2.Selection and validation of reference genes for quantitative real-time PCR analysis in Tujia medicine Xuetong.
Qian XIAO ; Chen-Si TAN ; Jiang ZENG ; Yuan-Shu XU ; Tian-Hao FU ; Lu-Yun NING ; Wei WANG
China Journal of Chinese Materia Medica 2025;50(3):682-692
Tujia ethnic group medicine Xuetong is derived from Kadsura heteroclita, the stem of which has the medicinal value for anti-rheumatoid arthritis, liver protection, anti-tumor, anti-oxidation effects, and has been widely used in Hunan and Guangdong in China. The selection of reliable and stable reference genes is the basis for subsequent molecular research on K. heteroclita. In this study, GAPDH, TUA, Actin, UBQ, EF-1α, 18S-rRNA, CYP, UBC, TUB, H2A, and RPL were selected as candidate reference genes in Kadsura heteroclita. The gene expression levels of the 11 candidate reference genes of K. heteroclita in its 6 different parts(stem-inside of the cambium, stem-outside of the cambium, fruit, flower, root, and leaf) and under different intervention conditions [drought stress, salt stress, and methyl jasmonate(MeJA) treatment] were detected by quantitative real-time polymerase chain reaction(qRT-PCR). The expression stability of the 11 candidate reference genes was comprehensively analyzed and evaluated by geNorm, NormFinder, ΔCT algorithm, and RefFinder software. The results showed that the expression of UBC and RPL was relatively stable in 6 different parts, and UBC and GAPDH genes were relatively stable under different intervention conditions. To verify the reliability of reference genes for K. heteroclita, this study further examined the relative expression levels of KhFPS, KhIDI, KhCAS, KhSQE, KhSQS, KhSQS-2, KhHMGS, KhHMGR, KhMVD, KhMVK, KhDXR, KhDXS, KhPMVK, and KhGGPS in different parts and under different intervention conditions, which might relate to the synthesis of the main component(Xuetongsu) of K. heteroclita. The results showed that with UBC and RPL or UBC and GAPDH as the reference genes, the expression trends of these 14 genes were basically consistent in different parts or under different intervention conditions for K. heteroclita. In conclusion, UBC can be used as a reference gene of K. heteroclita for its different parts and different intervention conditions, which lays a foundation for further research on the biosynthetic pathway of main components in K. heteroclita.
Real-Time Polymerase Chain Reaction/methods*
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Reference Standards
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Gene Expression Regulation, Plant
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Gene Expression Profiling
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Plant Proteins/metabolism*
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Drugs, Chinese Herbal
3.Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults (version 2025)
Bobin MI ; Faqi CAO ; Weixian HU ; Wu ZHOU ; Chenchen YAN ; Hui LI ; Yun SUN ; Yuan XIONG ; Jinmi ZHAO ; Qikai HUA ; Xinbao WU ; Xieyuan JIANG ; Dianying ZHANG ; Zhongguo FU ; Dankai WU ; Guangyao LIU ; Guodong LIU ; Tengbo YU ; Jinhai TAN ; Xi CHEN ; Fengfei LIN ; Zhangyuan LIN ; Dongfa LIAO ; Aiguo WANG ; Shiwu DONG ; Gaoxing LUO ; Zhao XIE ; Dong SUN ; Dehao FU ; Yunfeng CHEN ; Changqing ZHANG ; Kun LIU ; Deye SONG ; Yongjun RUI ; Fei WU ; Ximing LIU ; Junwen WANG ; Meng ZHAO ; Biao CHE ; Bing HU ; Chengjian HE ; Guanglin WANG ; Xiao CHEN ; Guandong DAI ; Shiyuan FANG ; Wenchao SONG ; Ming CHEN ; Guanghua GUO ; Yongqing XU ; Lei YANG ; Wenqian ZHANG ; Kun ZHANG ; Xin TANG ; Hua CHEN ; Weiguo XU ; Shuquan GUO ; Yong LIU ; Xiaodong GUO ; Zhewei YE ; Liming XIONG ; Tian XIA ; Hongbin WU ; Qisheng ZHOU ; Mengfei LIU ; Yiqiang HU ; Yanjiu HAN ; Hang XUE ; Kangkang ZHA ; Wei CHEN ; Zhiyong HOU ; Bin YU ; Jiacan SU ; Peifu TANG ; Baoguo JIANG ; Guohui LIU
Chinese Journal of Trauma 2025;41(5):421-432
Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.
4.Exploring Mechanism of Banxia Baizhu Tianma Decoction in the Treatment of Epilepsy Based on Network Pharmacology and Experimental Verification
Xin YANG ; Jin FU ; Cui JIANG ; Yinhua KAI ; Jiayi HE ; Xiangxin GUO ; Rong TIAN
World Science and Technology-Modernization of Traditional Chinese Medicine 2025;27(3):776-791
Objective To analyze the target,signal pathway and potential mechanism of Banxia Baizhu Tianma Decoction in the treatment of epilepsy based on network pharmacology,and to verify it by molecular docking technology and animal experiments.Methods The active ingredients and drug targets of Banxia Baizhu Tianma Decoction were screened by BATMAN and other databases.The targets of epilepsy-related diseases were obtained by GeneCards and other databases,and the intersection targets were taken.Constructing'drug-ingredient-target-disease'network and PPI network to screen the core targets.The core active ingredients were screened according to GO,KEGG functional enrichment analysis and'pathway-target-active ingredient'network.Molecular docking was used to verify the core targets and core active ingredients.In the animal experiment,the rat model of epilepsy was induced by lithium chloride-pilocarpine,and 40 Wistar rats were divided into normal control group,model control group,carbamazepine group and Banxia Baizhu Tianma Decoction group.The seizures were observed by behavior.Nissl staining was used to observe neuronal damage in hippocampus.Immunohistochemistry was used to detect the expression of BAX,BCL-2 and Caspase-3 protein.Results A total of 1072 targets of Banxia Baizhu Tianma Decoction were screened,1046 disease targets of epilepsy were screened,and 220 intersection targets of Banxia Baizhu Tianma Decoction in the treatment of epilepsy were screened.The core targets AKT1,ALB,ACTB,INS and TNF of PPI network were obtained.KEGG pathway mainly involves TNF signaling pathway,IL-17 signaling pathway,cAMP signaling pathway,pathways of neurodegeneration-multiple diseases,serotonergic synapse and Dopaminergic synapse.The core active ingredients with the highest correlation in the'pathway-target-active component'network were Betulin,Ephedrine,Ergotamine and Thymol.Results of molecular docking indicated that the core target had satisfactory affinity with those active ingredients.Animal experiments showed that Banxia Baizhu Tianma Decoction could effectively reduce epileptic seizures in rats,improve hippocampal neuronal damage in rats,significantly reduce the percentage of neuronal apoptosis,significantly down-regulate the expression of pro-apoptotic proteins BAX and Caspase-3,and up-regulate the expression of anti-apoptotic protein BCL-2.Conclusion Banxia Baizhu Tianma Decoction has the characteristics of multi-component,multi-target and multi-pathway in the treatment of epilepsy.Inhibiting neuronal apoptosis and reducing hippocampal neuronal damage may be one of the important mechanisms for its treatment of epilepsy.
5.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
6.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.
7.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.
8.Network pharmacology-based screening and validation of tea-derived small molecules against lung cancer
Rui YANG ; Sifen DU ; Lehui JIANG ; Tian FU ; Pengju REN ; Chengyu JIANG ; Yanli ZHANG
Basic & Clinical Medicine 2025;45(7):939-946
Objective To screen the active chemical components with potential therapeutic effects against lung cancer in tea and to provide new insights into the treatment and prevention of lung cancer.Methods Based on net-work pharmacology,the main active components from 13 types of tea samples were analyzed using liquid chromatog-raphy-mass spectrometry(LC-MS).The targets of these small molecules were obtained from the BATMAN-TCM da-tabase to construct a"component-target-disease"network.Lung cancer-related disease targets were retrieved from the GeneCard and Malacard databases followed by Gene Ontology(GO)functional and KEGG pathway enrichment analyses of potential pharmacological targets.A protein-protein interaction(PPI)network was constructed using the STRING database.The molecular docking was employed to screen small molecules with potential anti-cancer ac-tivity,and their potential inhibition to proliferation of human non-small cell lung cancer cell line A549 and human large cell lung cancer cell line H460.Results A total of 37 active components and 429 targets were identified in tea,with 182 overlapping targets associated with lung cancer.GO analysis revealed that these targets were primarily involved in biological processes such as cell proliferation,response to stimuli,and metabolic processes.KEGG pathway analysis indicated that these targets were mainly enriched in the p53 signaling pathway,ErbB signaling pathway,and PI3K-Akt signaling pathway.PPI network analysis identified key targets including MAPK1,AKT1,SRC,MAPK3,and p53.Molecular docking screened coumestrol as a molecule capable of binding to human estro-gen receptor 2(ESR2),and its inhibitory effect on the proliferation of A549 and H460 cells was experimentally validated(P<0.000 1).Conclusions The active components in tea may intervene in the development and progres-sion of lung cancer through a multi-component,multi-target,and multi-pathway mechanism,The results suggests po-tential components against lung cancer in tea,which may be applied in the prevention of human lung cancer.
9.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.
10.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.

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