1.Ablation of macrophage transcriptional factor FoxO1 protects against ischemia-reperfusion injury-induced acute kidney injury.
Yao HE ; Xue YANG ; Chenyu ZHANG ; Min DENG ; Bin TU ; Qian LIU ; Jiaying CAI ; Ying ZHANG ; Li SU ; Zhiwen YANG ; Hongfeng XU ; Zhongyuan ZHENG ; Qun MA ; Xi WANG ; Xuejun LI ; Linlin LI ; Long ZHANG ; Yongzhuo HUANG ; Lu TIE
Acta Pharmaceutica Sinica B 2025;15(6):3107-3124
Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.
2.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.
3.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.
4.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.
5.A qualitative study on the implementation status of family doctor contract services from the perspective of contracted residents
Jianhua CHEN ; Zihan PAN ; Xue JIN ; Wenping LI ; Yujing SU ; Hongjing PEI ; Jiapei XU ; Shan SUN ; Chunhua CHI
Chinese Journal of General Practitioners 2025;24(11):1360-1367
Objective:To explore the current implementation status and challenges of family doctor contract services (FDCS) from the perspective of contracted residents.Methods:This qualitative study used purposive sampling to select contracted residents from 11 primary healthcare institutions across five cities in China. Semi-structured interviews were conducted from March to December 2024, covering topics such as awareness of contracting, service experience, health needs, service continuity, and policy recommendations. Thematic framework analysis was applied to organize, code, and summarize the data.Results:A total of 25 contracted residents were interviewed (6 men, 19 women; 11 from central urban areas, 14 from suburban or rural towns; 8 with chronic diseases). Three main themes and ten sub-themes emerged: Theme Ⅰ: Pathways to improved service accessibility (optimized chronic disease management, more efficient referrals, and improved health education). Theme Ⅱ: Structural misalignment between supply and demand (limited specialty services despite patient needs, insufficient coverage and public awareness of home-based medical care, imbalanced human resources, and service disruption due to clinician turnover). Theme Ⅲ: Challenges in service awareness and communication mechanisms (information asymmetry and public misperception regarding FDCS, perverse incentives in administrative performance evaluation, and communication barriers in building patient-doctor trust).Conclusions:While FDCS has shown progress in chronic disease management, referral coordination, and health education, structural supply-demand gaps and communication challenges continue to hinder service quality. Improvements in resource allocation and service models are needed to support high-quality development.
6.Predictive value of changes in prealbumin for the prognosis of patients with acute-on-chronic liver failure after artificial liver treatment
Chengzhi BAI ; Bo DENG ; Huaqian XU ; Xue ZHANG ; Qunru WANG ; Xue WANG ; Beijin CHEN ; Si LIU ; Su YANG ; Shanhong TANG
Chinese Journal of Digestion 2025;45(7):462-468
Objective:To explore the predictive value of changes in prealbumin for the prognosis of patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) after artificial liver treatment.Methods:From January 1, 2018 to December 31, 2021, the clinical data (including prealbumin, platelet count, lymphocyte count, alanine transaminase (ALT), etc.) of 87 patients with HBV-ACLF who received artificial liver treatment at the Department of Gastroenterology of the General Hospital of Western Theater Command PLA were retrospectively collected. The 90-day survival status of all the patients was followed up, and the patients were divided into the survival group and the mortality group according to the survival status. The clinical characteristics and the changes of prealbumin on day 1 to 3, day 3 to 7, and day 1 to 7 after artificial liver treatment were compared between the 2 groups. Multivariate logistic regression analysis was used to analyze the independent influencing factors of the 90-day prognosis of HBV-ACLF patients after artificial liver treatment, and the nomogram prediction model was established and the receiver operating characteristic curve (ROC) was drawn to assess the area under the curve (AUC). Hosmer-Lemeshow goodness-of-fit test, calibration curve and clinical decision curve were performed to evaluate the goodness of fit, consistency and clinical value of the prediction model. Paired t-test and Mann-Whitney U test were used for statistical analysis. Results:There were 69 cases enrolled into the survival group, and 18 cases enrolled into the mortality group. The levels of albumin, prealbumin, platelet count, lymphocyte count, and ALT before treatment, and the level of prealbumin at the 3rd day after treatment of the survival group were all higher than those of the mortality group (32.5 (30.6, 35.2) g/L vs. 29.4 (27.6, 32.3) g/L, 66.0 (52.5, 81.5) mg/L vs. 56.5 (39.2, 65.0) mg/L, 103.0 (72.5, 145.0)×10 9/L vs. 63.5 (40.0, 92.5)×10 9/L, 1.1 (0.8, 1.4)×10 9/L vs. 0.9 (0.5, 1.1)×10 9/L, (514.7±86.4) U/L vs. (328.2±93.4) U/L, 90.0 (69.5, 102.5) mg/L vs.68.5(60.0, 75.8) mg/L), and the age, the level of total bilirubin, international normalized ratio, and prothrombin time before treatment of the survival group were all lower than those of the mortality group (48.0 (42.0, 57.0) years old vs. 48.5 (47.0, 56.0) years old, 323.9 (261.2, 409.2) μmol/L vs. 452.2 (405.8, 510.8) μmol/L, 1.5 (1.3, 1.9) vs. 1.9 (1.4, 2.1), 17.3 (14.6, 20.8) s vs. 21.4 (16.6, 23.2) s), and the differences were statistically significant ( Z=-3.38, -2.87, -2.38 and -2.01, t=2.39, Z=-4.11, 3.00, 3.64, 2.18 and 2.37; all P<0.05). The change of prealbumin on day 1 to 3 after treatment in the mortality group was greater than that in the survival group (-0.182 (-0.321, -0.026) vs. -0.043 (-0.133, 0.093)), and the difference was statistically significant ( Z=-3.42, P=0.001). The results of multivariate logistic regression analysis showed that the age, total bilirubin before treatment, and the change of prealbumin on day 1 to 3 after treatment were independent influencing factors for the 90-day prognosis in HBV-ACLF patients after artificial liver treatment (all P<0.05), and the nomogram model was established based on the above 3 factors. The results of ROC analysis showed that the AUC of the prediction model was 0.933 (95% confidence interval: 0.866 to 1.000, P<0.001), with a sensitivity of 0.933 and a specificity of 0.825. The results of the Hosmer-Lemeshow goodness-of-fit test showed that the prediction model had a good fit( P=0.700). The results of calibration curve analysis indicated that the actual curve of the prediction model was close to the calibration curve, with an average absolute error of 0.034, the consistency between the predicted probability and the actual probability was good. The clinical decision curve analysis suggested that the prediction model had significant clinical benefits. Conclusions:The changes of prealbumin after artificial liver treatment in HBV-ACLF patients can reflect the recovery of liver function. The nomogram prediction model based on the change of prealbumin on day 1 to 3 after treatment, age, and total bilirubin before treatment can better predict the 90-day prognosis of HBV-ACLF patients after artificial liver treatment.
7.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.
8.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.
10.Correlation between Glycolytic Pathway of Monocytes and Intracranial Pressure and Clinical Prognosis in Patients with Hypertensive Cerebral Hemorrhage
Hongsha PEI ; Mingyang XU ; Baoming JIA ; Jianlong SU ; Yigong FENG ; Sibo XUE ; Zhijun SONG
Journal of Kunming Medical University 2025;46(5):110-117
Objective To explore the correlation between glycolysis related indexes of peripheral blood mononuclear cells(PBMCs)[glucose transporter 1(GLUT1),fructose-2,6-diphosphatase 3(PFKFB3)and lactate kinase M2(PKM2)]and intracranial pressure and clinical prognosis of patients with hypertensive cerebral hemorrhage(HICH)who broke into the ventricle.Methods 85 HICH patients hospitalized in our hospital from January 2021 to June 2022 were retrospectively collected as the research participants.The levels of PKM2,GLUT1 and PFKFB3 in PBMCs were analyzed by enzyme-linked immunosorbent assay kit.Six months after the onset of HICH,the short-term outcome was evaluated by modified Rankin scale(mRS),and the patients were divided into good prognosis(mRS score≤2)and poor prognosis(mRS score≥3).Results The levels of PKM2,PFKFB3 and GLUT1 in PBMCs of HICH patients with ventricular rupture were further lower than those of the patients without ventricular rupture(P<0.05).Six months after discharge,8 patients(22.9%)with HICH in non-ventricular rupture group had poor prognosis,while 28 patients(56.0%)with HICH in ventricular rupture group had poor prognosis,and the difference was statistically significant(χ2=9.263,P=0.002).Compared with the group with good prognosis,the levels of PKM2 and GLUT1 in PBMCs of HICH patients with poor prognosis were lower(P<0.05).Compared with the good prognosis group,the levels of PKM2 and GLUT1 in PBMCs of HICH patients with poor prognosis group were lower in HICH patients with ventricular rupture(P<0.05).In HICH patients who broke into the ventricle,the AUC of PKM2 and GLUT1 in predicting the poor prognosis of HICH patients were 0.879(95%CI:0.807~0.951)and 0.897(95%CI:0.831~0.963),respectively.Conclusion The levels of PKM2 and GLUT1 in PBMCs of patients with HICH breaking into ventricles decrease significantly,and are negatively correlated with intracranial pressure,which can be used to predict the short-term prognosis of the patients.

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