1.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
2.Evaluation of the improved method for isolation of A(H1N1) pandemic 2009 and seasonal A(H3N2) influenza virus in embryonated chicken eggs
Hongwei ZHU ; Lei TANG ; Wei CHU ; Xue ZHAO ; Yiqun LOU ; Xiaojie CHU ; Lili SONG ; Yu WANG ; Zheng TENG
Chinese Journal of Experimental and Clinical Virology 2025;39(3):378-382
Objective:To improve the isolation and culture method of seasonal influenza virus in embryonated chicken eggs (ECEs), and evaluate their isolation efficiency.Methods:We randomly selected 80 positive samples of H1N1 (H1N1pdm09) and seasonal H3N2 (H3N2snl) influenza virus nucleic acid, and inoculated them into the amniotic and urinary sac cavities of 10-day-old (traditional method) and 14-day-old (improved method) ECEs respectively to adapt the virus to the ECEs (E1-E2). Both method were used to inoculate 10-day-old urinary sac amplification virus (E2-E3), and the final virus isolation positive rates of the two method were compared; using fluorescence quantitative PCR method to detect viral nucleic acids in the improved amniotic and urinary sac cultures, and evaluate the viral proliferation at different inoculation sites; we analyzed the correlation between virus content and isolation positivity rate in the original specimen based on the CT value of nucleic acid testing and the final virus isolation positivity rate using the improved method.Results:The improved method obtained 42 strains of H1N1pdm09 strain, with a positive rate of 52.5% ( χ2=38.571, P<0.01); obtained 54 strains of H3N2snl strain, with a positive rate of 67.5% ( χ2=40.921, P<0.01). Significant differences were observed in the isolation efficiency of H1N1pdm09 samples when the improved method was applied to different inoculation sites of chicken embryos ( χ2=30.476, P<0.01), and similar differences were noted for H3N2snl samples ( χ2=4.928, P=0.026). There was no significant difference in the isolation rate of different CT value intervals of the original samples ( χH1N1pdm092=10.226, χH3N2snl2=3.764, P>0.05). Conclusions:The improved method of inoculating 14-day old ECEs adapted the virus, and the final number of strains obtained was significantly higher than the traditional method of inoculating 10 day old ECEs, which can significantly improve the positive isolation rate of H1N1pdm09 and H3N2snl influenza virus in ECEs. The amniotic cavity is more sensitive to H1N1pdm09 and H3N2snl influenza viruses, which helps the virus adapt in ECEs. There was no significant difference in the sample isolation rate and total positive rate of virus isolation among different CT value ranges, and further verification is needed.
3.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
4.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 ; 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 WEN ; 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(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
5.Exploring the Path of Ideological and Political Construction in Biology Major Courses Empowered by Digital Intelligence
Wei-Ye SHI ; Xue-Ling GUO ; Yu FU ; Xiao-Lei ZHOU ; Ying-Ze WANG
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):914-923
The aim of this study is to explore a new path of empowering ideological and political educa-tion in courses with digital intelligence technology,therefore to improve the teaching quality of biology courses in universities,promote the comprehensive implementation of the fundamental task of cultivating morality and talents,and continuously improve the level of"three pronged education".By using the biol-ogy course"Immunology"as a practical carrier,we have constructed a dual-driven framework of"ideo-logical and political guidance+digital intelligence empowerment"utilizing digital tools to further highlight pedagogical feature enhancement,curricular optimization,innovative teaching models,multidimensional assessment,and enhanced teaching refinement.The empowerment of digital intelligence in the ideological and political construction of the course"Immunology"has achieved notable progress.Students' profes-sional abilities and ideological and political literacy have significantly improved,and the proportion of students with excellent grades has been increasing year by year(81.93%of students with good grades or above in 2024),demonstrating outstanding performance in various social practice activities;The course exhibits excellent demonstration and radiation effects on campus,and the teaching results have been sup-ported by the Ministry of Education and provincial-level education reform projects.This study serves as a practical example for the digital transformation of ideological and political education in higher education courses,providing reference and innovative insights for implementing ideological and political elements in other courses of biology majors.
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.Clinical research and characteristic analysis of patients with advanced colorectal cancer treated with Yinyang Gongji Pills and capecitabine.
Lei WANG ; Chao-Yue YAO ; Jie-Ru ZHAN ; Xiao-Xia SUN ; Zhong-Xin YU ; Xiao-Ya LIANG ; Jian WANG ; Xue GONG ; Da-Rong WEI
China Journal of Chinese Materia Medica 2025;50(5):1404-1411
Yinyang Gongji Pills have the effects of strengthening the body resistance to eliminate pathogenic factors, removing stasis, and reducing swelling, which is a commonly used traditional Chinese medicine(TCM) formula for treating intestinal accumulation. A real-world, registered, and single-arm clinical trial was conducted to observe the clinical efficacy and safety of Yinyang Gongji Pills combined with capecitabine in the treatment of advanced colorectal cancer and analyze the clinical characteristics of the patients. A total of 60 patients with advanced colorectal cancer who refused or could not tolerate standard treatment of western medicine were included in the study. They were treated with Yinyang Gongji Pills combined with capecitabine until disease progression or intolerable adverse events occurred. The main observation indicators were progression-free survival(PFS) and safety. The treatment effects of the patients under different baseline characteristics were analyzed. The clinical trial has found that the median PFS of all enrolled patients was 7.3 months, with 30.1% of patients having a PFS exceeding 12.0 months. Layered analysis showed that the median PFS of patients with the onset site being the colon and rectum were respectively 8.4 and 4.7 months. The median PFS of patients with high, medium, and low tumor burden were respectively 7.0, 4.7, and 10.8 months. The median PFS of patients with wild-type and mutant-type RAS/BRAF were respectively 7.9 and 6.9 months. The median PFS of patients with KPS scores ≥80 and ≤70 were respectively 7.9 and 6.5 months. The median PFS of patients treated with Yinyang Gongji Pills for ≥6, 3-6, and ≤3 months were respectively 8.0, 5.2, and 4.2 months. The median PFS of patients with spleen, kidney, liver, and lung syndrome differentiation in TCM were respectively 8.3, 6.7, 7.3, and 5.6 months. The median PFS of patients with TCM pathological factors including phlegm, dampness, and blood stasis were respectively 7.0, 7.3, and 6.5 months. Common adverse reactions include anemia, decreased white blood cells, decreased appetite, fatigue, and hand foot syndrome, with incidence rates being respectively 44.2%, 34.6%, 42.3%, 32.7%, and 17.3%. The results showed that the combination of Yinyang Gongji Pills and capecitabine demonstrated potential clinical efficacy and good safety in this study. The patients have clinical characteristics such as low tumor burden, onset site at the colon, KPS scores ≥ 80, long duration of oral TCM, and TCM syndrome differentiation including spleen or liver.
Humans
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Capecitabine/adverse effects*
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Colorectal Neoplasms/mortality*
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Drugs, Chinese Herbal/adverse effects*
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Male
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Middle Aged
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Female
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Aged
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Adult
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Treatment Outcome
9.Quality evaluation of Xinjiang Rehmannia glutinosa and Rehmannia glutinosa based on fingerprint and multi-component quantification combined with chemical pattern recognition.
Pan-Ying REN ; Wei ZHANG ; Xue LIU ; Juan ZHANG ; Cheng-Fu SU ; Hai-Yan GONG ; Chun-Jing YANG ; Jing-Wei LEI ; Su-Qing ZHI ; Cai-Xia XIE
China Journal of Chinese Materia Medica 2025;50(16):4630-4640
The differences in chemical quality characteristics between Xinjiang Rehmannia glutinosa and R. glutinosa were analyzed to provide a theoretical basis for the introduction and quality control of R. glutinosa. In this study, the high performance liquid chromatography(HPLC) fingerprints of 6 batches of Xinjiang R. glutinosa and 10 batches of R. glutinosa samples were established. The content of iridoid glycosides, phenylethanoid glycosides, monosaccharides, oligosaccharides, and polysaccharides in Xinjiang R. glutinosa and R. glutinosa was determined by high performance liquid chromatography-diode array detection(HPLC-DAD), high performance liquid chromatography-evaporative light scattering detection(HPLC-ELSD), and ultraviolet-visible spectroscopy(UV-Vis). The determination results were analyzed with by chemical pattern recognition and entropy weight TOPSIS method. The results showed that there were 19 common peaks in the HPLC fingerprints of the 16 batches of R. glutinosa, and catalpol, aucubin, rehmannioside D, rehmannioside A, hydroxytyrosol, leonuride, salidroside, cistanoside A, and verbascoside were identified. Hierarchical cluster analysis(HCA) and principal component analysis(PCA) showed that Qinyang R. glutinosa, Mengzhou R. glutinosa, and Xinjiang R. glutinosa were grouped into three different categories, and eight common components causing the chemical quality difference between Xinjiang R. glutinosa and R. glutinosa in Mengzhou and Qinyang of Henan province were screened out by orthogonal partial least squares discriminant analysis(OPLS-DA). The results of content determination showed that there were glucose, sucrose, raffinose, stachyose, polysaccharides, and nine glycosides in Xinjiang R. glutinosa and R. glutinosa samples, and the content of catalpol, rehmannioside A, leonuride, cistanoside A, verbascoside, sucrose, and glucose was significantly different between Xinjiang R. glutinosa and R. glutinosa. The analysis with entropy weight TOPSIS method showed that the comprehensive quality of R. glutinosa in Mengzhou and Qinyang of Henan province was better than that of Xinjiang R. glutinosa. In conclusion, the types of main chemical components of R. glutinosa and Xinjiang R. glutinosa were the same, but their content was different. The chemical quality of R. glutinosa was better than Xinjiang R. glutinosa, and other components in R. glutinosa from two producing areas and their effects need further study.
Rehmannia/classification*
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Drugs, Chinese Herbal/chemistry*
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Chromatography, High Pressure Liquid/methods*
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Quality Control
10.Simulation analysis of adaptability of large airborne negative pressure isolation cabin to aviation conditions.
Lei GUO ; Falin LI ; Lang JIANG ; Haibo DU ; Bingjie XUE ; Wei YONG ; Yuanyuan JIANG ; Muzhe ZHANG
Journal of Biomedical Engineering 2025;42(4):775-781
In order to solve the problems of difficult test, high cost and long cycle in the development of large-scale airborne negative pressure isolation system, the simulation analysis of negative pressure response characteristics is carried out around various aviation conditions such as aircraft ascending, leveling and descending, especially rapid decompression, based on the computational fluid dynamics (CFD) method. The results showed that the isolation cabin could achieve -50 Pa pressure difference environment and form a certain pressure gradient. The exhaust air volume reached the maximum value in the early stage of the aircraft's ascent, and gradually decreased with the increase of altitude until it was level flying. In the process of aircraft descent, the exhaust fan could theoretically maintain a pressure difference far below -50 Pa without working; Under the special condition of rapid pressure loss, it was difficult to deal with the rapid change of low pressure only by the exhaust fan, so it was necessary to design safety valve and other anti-leakage measures in the isolation cabin structure. Therefore, the initial stage of aircraft ascent is the key stage for the adjustment and control of the negative pressure isolation system. By controlling the exhaust air volume and adjusting parameters, it can adapt to the change of low pressure under normal flight conditions, form a relatively stable negative pressure environment, and meet the needs of biological control, isolation and transport.
Aircraft
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Computer Simulation
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Aviation/instrumentation*
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Humans
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Hydrodynamics
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Air Pressure
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Equipment Design
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Pressure

Result Analysis
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