1.Association between Per and Polyfluoroalkyl Substance and Abdominal Fat Distribution: A Trait Spectrum Exposure Pattern and Structure-Based Investigation.
Zhi LI ; Shi Lin SHAN ; Chen Yang SONG ; Cheng Zhe TAO ; Hong QIAN ; Qin YUAN ; Yan ZHANG ; Qiao Qiao XU ; Yu Feng QIN ; Yun FAN ; Chun Cheng LU
Biomedical and Environmental Sciences 2025;38(1):3-14
OBJECTIVE:
To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles.
METHODS:
Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk.
RESULTS:
Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk.
CONCLUSION
PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans
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Fluorocarbons/blood*
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Female
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Adult
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Middle Aged
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Male
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Environmental Pollutants/blood*
;
Abdominal Fat
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Nutrition Surveys
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Alkanesulfonic Acids/blood*
;
Obesity
;
Environmental Exposure
2.Study on the correlation between Xiaochengqitang pieces(decoction and granules)based on ultra high performance liquid chromatography fingerprint
Jiangping CHEN ; Shan WEN ; Guihai DENG ; Qiuyi MO ; Wenting SHI ; Caiyue QIU ; Yun LU
China Pharmacist 2024;27(1):46-56
Objective To study the correlation of an ultra high performance liquid chromatography(UPLC)fingerprint of Xiaochengqitang pieces(decoction and granules).Methods The UPLC method was used to establish the fingerprint of 15 batches of Xiaochengqitang pieces(decoction and granules).The correlation of the three UPLC fingerprints was evaluated by similarity analysis,pearson correlation analysis,cluster analysis(CA),principal component analysis(PCA)and orthogonal partial least squares-discriminant analysis(OPLS-DA).Results UPLC fingerprints of 15 batches of Xiaochengqitang pieces(decoction and granules)determined 16 common peaks,and 14 peaks were identified.The similarity of the fingerprints of the 15 batches of Xiaochengqitang pieces(decoction and granules)with the corresponding control fingerprints was greater than 0.90,and the similarity of the three control fingerprints was greater than 0.88.The results of pearson correlation analysis showed that 8 common peaks in Xiaochengqitang pieces(decoction and granules)had a very significant positive correlation.The results of CA showed that the properties of Xiaochengqitang decoction and granules were more similar.The results of PCA showed that the principal components with 4 eigenvalues greater than 1 contained 88%of the information of the original data.OPLS-DA screened 7 differential markers with variable importance projection value greater than 1.Conclusion The main chemical compositions of Xiaochengqitang pieces(decoction and granules)are consistent,which can provide data support for the quality control and clinical use of Xiaochengqitang compound preparation.
3.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
4.A multi-center epidemiological study on pneumococcal meningitis in children from 2019 to 2020
Cai-Yun WANG ; Hong-Mei XU ; Gang LIU ; Jing LIU ; Hui YU ; Bi-Quan CHEN ; Guo ZHENG ; Min SHU ; Li-Jun DU ; Zhi-Wei XU ; Li-Su HUANG ; Hai-Bo LI ; Dong WANG ; Song-Ting BAI ; Qing-Wen SHAN ; Chun-Hui ZHU ; Jian-Mei TIAN ; Jian-Hua HAO ; Ai-Wei LIN ; Dao-Jiong LIN ; Jin-Zhun WU ; Xin-Hua ZHANG ; Qing CAO ; Zhong-Bin TAO ; Yuan CHEN ; Guo-Long ZHU ; Ping XUE ; Zheng-Zhen TANG ; Xue-Wen SU ; Zheng-Hai QU ; Shi-Yong ZHAO ; Lin PANG ; Hui-Ling DENG ; Sai-Nan SHU ; Ying-Hu CHEN
Chinese Journal of Contemporary Pediatrics 2024;26(2):131-138
Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]
5.A survey on the management status and indicators of pathogen detection rate before antimicrobial treatment of inpatients in 265 medical institu-tions in Guangdong Province
Jia-jin CHEN ; Zhen-feng ZHONG ; Shi-yun WANG ; Ting HUANG ; Shu-xian CHEN ; Chen ZHU ; Yi-nan LI ; Li-li PENG ; Yuan-chun MO ; Min-shan CHEN ; Wei-qing LIN ; Xiu-juan QU ; Fang YU ; Zhi-xing LI ; Shu-mei SUN
Chinese Journal of Infection Control 2024;23(12):1499-1507
Objective To evaluate the management and indicators of pathogen detection before antimicrobial treat-ment for inpatients in second level and above medical institutions(MIs)in Guangdong Province,and provide direc-tion and decision-making basis for the improvement of pathogen detection quality in the region.Methods The ma-nagement status,information system functions,and pathogen detection rate indicators of secondary and above MIs in 21 cities in Guangdong Province was surveyed through online questionnaire surveys and system submission.A baseline survey on sentinel monitoring MIs was conducted from July 15th to August 8th,2023.From November 7th to 30th,a baseline survey on non-sentinel monitoring MIs was launched.Surveys on indicator information of all MIs were completed from January 15th to 30th,2024.Results A total of 265 MIs were surveyed,and the proportions of establishing special working groups(83.98%),developing special action improvement plans(79.01%),estab-lishing pathogen detection rate management systems(91.71%),and developing management assessment plans(76.80%)of tertiary MIs were all higher than that of secondary MIs,differences were all statistically significant(all P<0.05).The proportion of tertiary MIs with various information system functions was higher than that of secondary MIs(all P<0.05).The pathogen detection rate(61.07%)before antimicrobial treatment and health-care-associated infection(HAI)diagnosis-related pathogen detection rate(88.00%)of inpatients in tertiary MIs were both higher than those in secondary MIs(both P<0.05).Among different types of MIs,pathogen detection rate before antimicrobial treatment of inpatients in maternal and child health MIs was higher than that in other types of MIs.HAI diagnosis-related pathogen detection rate in other specialized hospitals was the highest,and pathogen detection rate before combined use of key antimicrobial treatment in traditional Chinese medicine hospitals was the lowest,differences were all statistically significant(all P<0.05).Conclusion Tertiary MIs have more advantages in management strategies and information technology construction than secondary MIs,secondary MIs need more guidance and support.Monitoring and analysis of pathogen detection rate indicators in MIs of different levels and types should be strengthened through special actions.
6.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
7.Protective effect of Naru-3 on collagen-induced arthritis in rats
Hai-Yue ZHAO ; Xiao-Shan ZHANG ; Sha-Sha DUAN ; Yi-Lu SHI ; Min-Jie ZHANG ; Shu-Rong YUN ; Ya-Xi WANG
Chinese Traditional Patent Medicine 2024;46(6):1842-1849
AIM To investigate the protective effect of Mongolian medicine Naru-3 on rat rheumatoid arthritis(RA)using imaging method.METHODS With the rats divided into the normal group,the model group,the positive medicine group,and the low,medium and high dose Naru-3 groups(0.1,0.2 and 0.4 g/kg),the rat model of collagen-induced arthritis(CIA)was established by immune induction method.After 4 weeks of corresponding drug administration,the rats had their changes of arthritis index(AI)level and body weight observed;their serum levels of VEGF,TNF-α and IL-1 detected by ELISA;their synovial hyperplasia and neovascularization evaluated by high-frequency ultrasound and contrast-enhanced ultrasound(CEUS);their bone destruction of ankle joint evaluated by X-ray and high-resolution micro-CT;and their synovial membrane and expressions of CD31,VEGF,TNF-α and IL-1 β observed by HE and immunohistochemistry.RESULTS Compared with the model group,the Naru-3 groups displayed increased rat weight(P<0.05);no significantly changed AI score(P>0.05);and overally decreased levels of serum VEGF,TNF-α,synovial membrane thickness,blood flow signal by power Doppler imaging(PDI)and contrast intensity revealed,X-ray score,and CD31 expression(P<0.05),in addition to the decreased level of IL-1 and HE score in high-dose group(P<0.05).CONCLUSION Naru-3 is protective to the joint tissue in rat model of RA through alleviating synovitis,bone erosion and delaying the progress of the disease by inhibiting synovial neovascularization and inflammatory cytokines.
8.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
9.A survey on the management status and indicators of pathogen detection rate before antimicrobial treatment of inpatients in 265 medical institu-tions in Guangdong Province
Jia-jin CHEN ; Zhen-feng ZHONG ; Shi-yun WANG ; Ting HUANG ; Shu-xian CHEN ; Chen ZHU ; Yi-nan LI ; Li-li PENG ; Yuan-chun MO ; Min-shan CHEN ; Wei-qing LIN ; Xiu-juan QU ; Fang YU ; Zhi-xing LI ; Shu-mei SUN
Chinese Journal of Infection Control 2024;23(12):1499-1507
Objective To evaluate the management and indicators of pathogen detection before antimicrobial treat-ment for inpatients in second level and above medical institutions(MIs)in Guangdong Province,and provide direc-tion and decision-making basis for the improvement of pathogen detection quality in the region.Methods The ma-nagement status,information system functions,and pathogen detection rate indicators of secondary and above MIs in 21 cities in Guangdong Province was surveyed through online questionnaire surveys and system submission.A baseline survey on sentinel monitoring MIs was conducted from July 15th to August 8th,2023.From November 7th to 30th,a baseline survey on non-sentinel monitoring MIs was launched.Surveys on indicator information of all MIs were completed from January 15th to 30th,2024.Results A total of 265 MIs were surveyed,and the proportions of establishing special working groups(83.98%),developing special action improvement plans(79.01%),estab-lishing pathogen detection rate management systems(91.71%),and developing management assessment plans(76.80%)of tertiary MIs were all higher than that of secondary MIs,differences were all statistically significant(all P<0.05).The proportion of tertiary MIs with various information system functions was higher than that of secondary MIs(all P<0.05).The pathogen detection rate(61.07%)before antimicrobial treatment and health-care-associated infection(HAI)diagnosis-related pathogen detection rate(88.00%)of inpatients in tertiary MIs were both higher than those in secondary MIs(both P<0.05).Among different types of MIs,pathogen detection rate before antimicrobial treatment of inpatients in maternal and child health MIs was higher than that in other types of MIs.HAI diagnosis-related pathogen detection rate in other specialized hospitals was the highest,and pathogen detection rate before combined use of key antimicrobial treatment in traditional Chinese medicine hospitals was the lowest,differences were all statistically significant(all P<0.05).Conclusion Tertiary MIs have more advantages in management strategies and information technology construction than secondary MIs,secondary MIs need more guidance and support.Monitoring and analysis of pathogen detection rate indicators in MIs of different levels and types should be strengthened through special actions.
10.Trend of age of menarche among Chinese Han girls aged 9 to 18 years from 2010 to 2019.
Ning MA ; Di SHI ; Shan CAI ; Jia Jia DANG ; Pan Liang ZHONG ; Yun Fei LIU ; Jing LI ; Yana Hui DONG ; Pei Jin HU ; Bin DONG ; Tian Jiao CHEN ; Yi SONG ; Jun MA
Chinese Journal of Preventive Medicine 2023;57(4):486-491
Objective: To analyze the trends of the age of menarche among Chinese Han girls aged 9 to 18 years from 2010 to 2019. Methods: Data were extracted from the Chinese National Surveys on Students' Constitution and Health in 2010, 2014 and 2019. A total of 253 037 Han girls aged 9 to 18 years with complete data on menarche were selected in this study. They were asked one-on-one about their menstrual status, age and residence information. The median age of menarche was estimated by probability regression. U tests were used to compare the difference in median age at menarche in different years. Results: The median age at menarche (95%CI) among Chinese Han girls was 12.47 (12.09-12.83) years in 2010, 12.17 (11.95-12.38) years in 2014 and 12.05 (10.82-13.08) years in 2019, respectively. Compared with that in 2010, the median age at menarche in 2019 decreased by 0.42 years (U=-77.27, P<0.001). The annual average changes were -0.076 years from 2010 to 2014 (U=-57.19, P<0.001) and -0.023 years from 2014 to 2019 (U=-21.41, P<0.001), respectively. The average annual changes in urban areas in the periods of 2010 to 2014 and 2014 to 2019 were -0.071 years and 0.006 years, respectively, while those in rural areas were -0.082 years and -0.053 years, respectively. The average annual changes in the regions of north, northeast, east, south central, southwest and northwest were -0.064, -0.099, -0.091, -0.080, -0.096 and -0.041 years in the period of 2010 to 2014 and 0.001, -0.040, -0.002, -0.005, -0.043 and -0.081 years in the period of 2014 to 2019. Conclusion: The age of menarche among Chinese Han girls aged 9 to 18 years shows an advanced trend from 2010 to 2019, and the trends in urban and rural areas and different regions have different characteristics.
Female
;
Humans
;
Menarche
;
Probability
;
East Asian People
;
Child
;
Adolescent

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