1.Analysis on the current status of management and treatment of patients with severe mental disorders and their regional characteristics in Ningxia Hui Autonomous Region
Hong JIANG ; Wei HUANG ; Chao XU ; Yuan LIU ; Yongling ZHOU ; Lei TIAN ; Xia YANG ; Xuehui ZHANG ; Caixia LYU ; Xuebing XU
Sichuan Mental Health 2025;38(6):528-533
BackgroundSevere mental disorders are characterized by high recurrence rate, high disability rate, high rates of harmful incidents, and low treatment-seeking rate, with affected patients demonstrating increased frequencies of dangerous behaviors. Ningxia Hui Autonomous Region has implemented community management for patients with severe mental disorders across the region since 2004, while the current status and regional characteristics of the managed patients remain unclear. ObjectiveTo analyze the current status of management and treatment of patients with severe mental disorders in Ningxia Hui Autonomous Region, and to explore their regional distribution characteristics, so as to provide references for optimizing regional prevention and control strategies. MethodsPatients with severe mental disorders diagnosed and registered in the Severe Mental Disorder Management Information Platform of Ningxia Hui Autonomous Region from August 1, 2011 to December 31, 2021 were selected. Patients' basic information, management indicators, and treatment metrics were extracted from the platform, followed by descriptive statistical analysis of the corresponding data. ResultsAs of December 31, 2021, the permanent resident population of Ningxia Hui Autonomous Region was 6 946 540, with 29 787 registered patients with severe mental disorders. The majority of the patients were female (50.25%), aged 18-59 years (79.01%), with educational level of junior high school or below (84.63%), married (52.87%), farmers (56.01%), and diagnosed with schizophrenia (55.91%), while ethnic minority patients accounted for a relatively high proportion (31.35%). In 2021, the reported prevalence rate of severe mental disorders in Ningxia Hui Autonomous Region was 0.43%, with standardized management and regular medication adherence rates at 90.39% and 66.34%, respectively. The standardized management rate in 8 counties/districts (36.36%) was lower than the average level of Ningxia Hui Autonomous Region, while 10 counties/districts (45.45%) showed below-average medication adherence rates, of which 6 counties/districts(60.00%) were located in the south-central region. ConclusionPatients with severe mental disorders in Ningxia Hui Autonomous Region are predominantly young and middle-aged adults with low level of education, and those in the central-southern region demonstrate lower medication adherence. [Funded by Key Research and Development Program Project of Ningxia Hui Autonomous Region (number, 2023BEG02029)]
2.The integration of machine learning into traditional Chinese medicine
Yanfeng HONG ; Sisi ZHU ; Yuhong LIU ; Chao TIAN ; Hongquan XU ; Gongxing CHEN ; Lin TAO ; Tian XIE
Journal of Pharmaceutical Analysis 2025;15(8):1724-1737
Traditional Chinese medicine(TCM)is an ancient medical system distinctive and effective in treating cancer,depression,coronavirus disease 2019(COVID-19),and other diseases.However,the relatively abstract diagnostic methods of TCM lack objective measurement,and the complex mechanisms of action are difficult to comprehend,which hinders the application and internationalization of TCM.Recently,while breakthroughs have been made in utilizing methods such as network pharmacology and virtual screening for TCM research,the rise of machine learning(ML)has significantly enhanced their inte-gration with TCM.This article introduces representative methodological cases in quality control,mechanism research,diagnosis,and treatment processes of TCM,revealing the potential applications of ML technology in TCM.Furthermore,the challenges faced by ML in TCM applications are summarized,and future directions are discussed.
3.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.
4.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.
5.Current status of field(emergency)rapid inspection systems
Pei-pei WANG ; Yu-hong HUANG ; Jing LI ; Wen REN ; Shi-chao LIANG ; Yu-qi QIAN ; Yan-jiang LIU
Chinese Medical Equipment Journal 2025;46(2):80-86
The field(emergency)rapid inspection systems involving in the backpack,chest,vehicle and shelter had their research advances introduced and characteristics and deficiencies analyzed,and some improvement suggestions were put forward accordingly.It's pointed out the backpack,chest,vehicle and shelter be combined effectively to enhance the mobility and flexibility of field(emergency)rapid inspection systems.References were provided for the future enhancement and effecient operation of field(emergency)rapid inspection systems.[Chinese Medical Equipment Journal,2025,46(2):80-86]
6.Investigations into the Mechanism of Phycocyanin in Modulating the Wip1/p53 Pathway to Induce Apoptosis in Human Hepatocellular Carcinoma HepG2 Cells
Yun-Xi JIA ; Da HUO ; Chao YAO ; Min LI ; Fu-Ling LIU ; Hong YUAN ; Hui-Ting XUE ; Rui-Ping HU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(5):741-752
Hepatocellular carcinoma(HCC)is difficult to detect in its early stages and current treatment methods are associated with significant side effects and a high risk of developing drug resistance.This study aims to investigate the effect of phycocyanin(PC)on the apoptosis of human HCC HepG2 cells and its potential mechanism.HepG2 cells were treated with PC at concentrations of 0.1,0.25,0.5,1,2.5,5,and 10 μg/mL for 12 h,and with 10 μg/mL PC and 2.5 μmol/L Wip1 inhibitor(Wip1i)alone or in combination for 12 and 24 h,respectively.Cell proliferation levels were assessed using the CCK-8 cell proliferation-toxicity assay kit.Apoptosis levels were measured by Annexin V-FITC/Propidium Iodide double staining combined with flow cytometry.TMT(Tandem Mass Tag)proteomics quantitative technol-ogy was applied to analyze differential protein expression.Western blotting was used to detect the expres-sion levels of Wip1,p53,and phosphorylated-p53(Ser15)proteins.The CCK-8 assay revealed that PC effectively inhibited HepG2 cell proliferation in a concentration-dependent manner,with a half-maximal inhibitory concentration(IC50)of 19.37 μg/mL.Flow cytometry results showed that PC significantly in-duced apoptosis,with an apoptosis rate of 30.40%.Quantitative proteomics analysis indicated that PC induced activation of the p53 pathway.The CCK-8 assay showed that Wip1i enhanced the cytotoxic effect of PC on HepG2 cells.Western blotting confirmed that PC inhibited Wip1 expression,induced p53 pro-tein phosphorylation,and promoted the expression of total p53 protein.Additionally,Wip1i further en-hanced PC-mediated activation of the p53 pathway,increasing the expression of p53 and pP53(S15).In conclusion,PC may induce apoptosis by inhibiting the activity of the p53 negative regulator Wip1,thereby promoting apoptosis through the Wip1/p53 pathway.
7.Poly gala fallax Hemsl.improves diabetic kidney disease in rats via Nrf2/SLC7A11/GPX4 signaling pathway
Si-chao WANG ; Qiu-hong LIU ; Shi-wei ZHAO ; Yu-qiong LEI ; Min-chao FENG
Chinese Pharmacological Bulletin 2025;41(6):1186-1193
Aim To observe the interventional effects of Polygala fallax Hemsl.(PFH)on diabetic kidney disease(DKD)rats and the regulatory mechanism of ferroptosis.Methods Thirty-six SD rats were ran-domly divided into the control group,DKD group,fer-rostatin-1(Fer-1)group,PFH-L group,PFH-M group,and PFH-H group,with six rats in each group.Model-ing was induced by a one-time intraperitoneal injection of 35 mg·kg-1 streptozocin(STZ)in combination with high-sugar and high-fat feed.Ferrostatin-1(25μmol·kg-1)was injected intraperitoneally in Fer-1 group.The PFH-L,PFH-M,and PFH-H groups were gavaged with 50,100 and 200 mg·kg-1 of alcoholic extracts of PFH respectively,and the control and DKD groups were gavaged with an equal volume of distilled water once a day for eight weeks.At the end of drug administration,blood glucose,24h-UP,BUN and Scr levels were measured in each group of rats.HE stai-ning and Masson staining were used to observe renal histopathological changes.ELISA was employed to de-termine the levels of total iron,MDA and GSH activity.IHC was used to observe the expression of Nrf2,SLC7A11,and GPX4 in renal tissues.Western blot was used to detect the protein expression of COL1A1,α-SMA,TGF-,FTH-1,TFR-1,Nrf2,SLC7A1 1,GPX4,in renal tissues.RT-qPCR was used to detect the ex-pression levels of Nrf2,SLC7A11,GPX4 mRNA in re-nal tissues.Results Compared with the control group,blood glucose,24h-UP,BUN,Scr increased(P<0.05);glomerular volume increased,tubular dilata-tion and collagen fiber deposition were obvious;total i-ron,MDA content increased and GSH activity de-creased(P<0.05);there was increased protein ex-pression of COL1A1,α-SMA,TGF-β,TFR-1 and de-creased protein expression of FTH-1(P<0.01);there was decreased mRNA and protein expression of Nrf2,SLC7A11,GPX4 in DKD group rats(P<0.01).Compared with the DKD group,blood glucose,24h-UP,BUN and Scr decreased(P<0.05);renal tissue le-sions were significantly reduced;total iron and MDA content decreased,and GSH activity increased(P<0.05);COL1A1,α-SMA,TGF-β,and TFR-1 protein expression decreased and FTH-1 protein expression in-creased(P<0.05,P<0.01);Nrf2,SLC7A11,GPX4 mRNA and protein expression increased in Fer-1 and PFH dose groups(P<0.05,P<0.01).Conclusions PFH attenuates renal histopathological injury in DKD rats,and the mechanism may be related to the regula-tion of the Nrf2/SLC7A11/GPX4 signaling pathway.
8.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.
9.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.
10.Advances in Nanozymatic Colorimetric Sensing Technology in the Field of Environmental,Food and Drug Safety Detection
Zhi-Chao YANG ; Rui-Ting FENG ; Hong-Da LI ; Yu-Mu LIU
Chinese Journal of Analytical Chemistry 2025;53(9):1435-1446
Food,drug and environment related cases are becoming more and more frequent,and the demand for on-site rapid detection is also increasing.Nanozymes are nanomaterials with enzyme-like catalytic activity,which have the advantages of high catalytic efficiency,good stability,economy,adjustability,multifunctionality and large-scale preparation.The colorimetric sensing technology based on nanozymes combined with smart phones has wide range of applications in the field of food,drugs and environment detection,and is expected to become an important means for relevant departments to combat crime.This paper summarized the progresses of nanozymes in the field of environmental,food and drug crime(EFDC)detection,focusing on the detection mechanism of different types of nanozymes and the current status of research on the detection of EFDC,and prospected the future development of nanozymes.The possible future prospects of machine learning(ML)in the field of nanozymes colorimetric sensing technology and the challenges in detection of EFDC were also discussed.

Result Analysis
Print
Save
E-mail