1.Predicting the Risk of Arterial Stiffness in Coal Miners Based on Different Machine Learning Models.
Qian Wei CHEN ; Xue Zan HUANG ; Yu DING ; Feng Ren ZHU ; Jia WANG ; Yuan Jie ZOU ; Yuan Zhen DU ; Ya Jun ZHANG ; Zi Wen HUI ; Feng Lin ZHU ; Min MU
Biomedical and Environmental Sciences 2024;37(1):108-111
2.Epidemiological characteristics of human respiratory syncytial virus among acute respiratory infection cases in 16 provinces of China from 2009 to 2023
Aili CUI ; Baicheng XIA ; Zhen ZHU ; Zhibo XIE ; Liwei SUN ; Jin XU ; Jing XU ; Zhong LI ; Linqing ZHAO ; Xiaoru LONG ; Deshan YU ; Bing ZHU ; Feng ZHANG ; Min MU ; Hui XIE ; Liang CAI ; Yun ZHU ; Xiaoling TIAN ; Bing WANG ; Zhenguo GAO ; Xiaoqing LIU ; Binzhi REN ; Guangyue HAN ; Kongxin HU ; Yan ZHANG
Chinese Journal of Preventive Medicine 2024;58(7):945-951
Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.
3.Epidemiological characteristics of human respiratory syncytial virus among acute respiratory infection cases in 16 provinces of China from 2009 to 2023
Aili CUI ; Baicheng XIA ; Zhen ZHU ; Zhibo XIE ; Liwei SUN ; Jin XU ; Jing XU ; Zhong LI ; Linqing ZHAO ; Xiaoru LONG ; Deshan YU ; Bing ZHU ; Feng ZHANG ; Min MU ; Hui XIE ; Liang CAI ; Yun ZHU ; Xiaoling TIAN ; Bing WANG ; Zhenguo GAO ; Xiaoqing LIU ; Binzhi REN ; Guangyue HAN ; Kongxin HU ; Yan ZHANG
Chinese Journal of Preventive Medicine 2024;58(7):945-951
Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.
4.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
5.Correlation analysis of ocular demodex infection and the composition of meibum lipid flora
Pei-Yan ZHU ; Shao-Qin LIN ; Wan-Ying LIN ; Mu-Ling LI ; Hong-Ying FAN ; Qiong-Xi LIN ; Yu-Han FENG ; Jing XU ; Juan YANG ; Qiong LIU
International Eye Science 2023;23(1):126-131
AIM: To investigate the correlation between the ocular demodex infection and the composition of meibum lipid flora.METHODS: A non-interventional and observational study was performed on recruited 39 patients in our hospital between July 2020 and February 2021. They were divided into control group(n=14), meibomian gland dysfunction(MGD)group(n=14), and demodex group(FM, n=11)according to the presence or absence of demodex infection or MGD. High-throughput sequencing of V3-V4 fragment of 16S rRNA gene was performed on the meibomian ester samples of the three groups of subjects, and bioinformatics analysis was performed on the sequencing data to study the composition and difference of meibum lipid flora in the subjects of ocular demodex.RESULTS: Pseudomonas and Comamonas in FM group were significantly higher than those in control group and MGD group(P<0.05), while Ralstonia in Demodex infection group was significantly lower than that in control group and MGD group(P<0.05). The microbial richness and community diversity of meibum lipid flora of the MGD group and the FM group were significantly higher than those of the control group(P<0.05).CONCLUSION: Ocular demodex infection changed the composition of meibum lipid flora and increased the microbial richness and community diversity of meibum lipid flora.
7.Structural and molecular basis for foot-and-mouth disease virus neutralization by two potent protective antibodies.
Hu DONG ; Pan LIU ; Manyuan BAI ; Kang WANG ; Rui FENG ; Dandan ZHU ; Yao SUN ; Suyu MU ; Haozhou LI ; Michiel HARMSEN ; Shiqi SUN ; Xiangxi WANG ; Huichen GUO
Protein & Cell 2022;13(6):446-453
8.Dynamic analysis of respirable dust concentration in the working environment of a large coal mine in 2013 - 2020
Hong ZHANG ; Guo-wei LI ; Min MU ; Yong-fang ZHANG ; Wei LI ; Wen-yang WANG ; Feng-lin ZHU ; Wei HUANG ; Jiang-jiang ZHANG ; Dong-ming WANG ; Wei-hong CHEN ; Min ZHOU
Journal of Public Health and Preventive Medicine 2022;33(6):24-27
Objective To analyze the characteristics and variation trend of respirable dust concentration in the working environment of a coal mine from 2013 to 2020. Methods A large coal mine in Shaanxi Province was selected as the research site. The inspection data regarding the respirable dust concentration across the years were collected. The characteristics and dynamic changes of respirable dust concentration were analyzed. Results The content of free silica in the main workplaces of the coal mine was less than 10% , and the dust was classified as the coal dust. The average annual concentrations of respirable dust varied in different workplaces, with the highest values in the fully mechanized winning and continuous mining face (0.32 mg/m3~18.68 mg/m3) and fully mechanized mining face (0.36 mg/m3~8.11 mg/m3). The average annual concentrations of respirable dust varied among different jobs, with the highest value among continuous miner drivers (1.30mg/m3~18.68 mg/m3), followed by shuttle truck drivers (0.32 mg/m3~14.77 mg/m3), crusher drivers (0.59 mg/m3~8.23 mg/m3), fully mechanized winning machine drivers (0.99 mg/m3~5.05 mg/m3), fully mechanized mining machine drivers (1.10 mg/m3~8.11 mg/m3), and timbermen (1.10mg/m3~6.09 mg/m3). The average concentration of respirable dust increased to the highest level during 2013-2014, then showed a downward trend during 2015-2018, and rebounded to a certain extent during2019-2020. Conclusion Respirable dust was widely distributed in the workplaces and across jobs. The concentrations of respirable dust were high, but the overall trend was downward.
9.Genetic variation and evolutionary characteristics of hemagglutinin-neuraminidase (HN) gene in human parainfluenza virus 3 in China
Jie JIANG ; Linqing ZHAO ; Min MU ; Wenyang WANG ; Jin XU ; Liang CAI ; Zhengde XIE ; Zhen ZHU ; Yan ZHANG ; Shanshan ZHOU ; Yi FENG ; Naiying MAO
Chinese Journal of Experimental and Clinical Virology 2022;36(2):141-149
Objective:To analyze the gene variation and evolutionary characteristics of human parainfluenza virus 3 (HPIV3) circulating in China based on hemagglutinin-neuraminidase (HN) gene.Methods:Multiple qPCR was used to screen nucleic acid of common pathogens in throat swabs from acute respiratory tract infection cases in five provinces (Beijing, Zhejiang, Anhui, Henan, Hunan) from 2007 to 2020. Subsequently, the HN gene sequence of HPIV3 positive samples was determined and compared with the HN gene sequence of HPIV3 strains from 10 provinces in China and abroad in the GenBank database. The molecular evolution analysis was carried out using a variety of bioinformatics method.Results:A total of 49 strains of HPIV3 HN gene sequences were obtained from 5 provinces, with nucleotide homology ranging from 96.6% to 100%. Among them, 48 strains were subtype C3 and 1 strain was subtype C5. Phylogenetic analysis showed that there were co-epidemics of C1, C3 and C5 strains in 12 provinces of China during 2003—2020, and the nucleotide and amino acid homology among the strains were 95.4%-99.8% and 97.9%-100%, respectively. Among them, C3 is the dominant subtype in China, which is divided into five evolutionary branches of C3a, C3b, C3c, C3e and C3f, and the C3f has the widest range and time of spread. The evolutionary analysis of the C3 subtype showed that the estimated time to the most recent common ancestor (tMRCA) of it dated back to 1990, and its effective population size tended to be stable after expansion from 2002 to 2010. The HN gene evolution rate of the evolutionary branches of C3 HPIV3 varied from 3.69×10 -4 to 5.82×10 -4 substitutions/sites/year; the HN protein of C3 subtype strains shared four potential N-glycosylation sites N308, N351, N485 and N523, and the selection pressure was mainly negative. Conclusions:The C3 is an endemic dominant genotype, which has been widely spread and continuously circulating in China, and has formed different evolutionary clades during epidemic.
10.Inverted U-Shaped Associations between Glycemic Indices and Serum Uric Acid Levels in the General Chinese Population: Findings from the China Cardiometabolic Disease and Cancer Cohort (4C) Study.
Yuan Yue ZHU ; Rui Zhi ZHENG ; Gui Xia WANG ; Li CHEN ; Li Xin SHI ; Qing SU ; Min XU ; Yu XU ; Yu Hong CHEN ; Xue Feng YU ; Li YAN ; Tian Ge WANG ; Zhi Yun ZHAO ; Gui Jun QIN ; Qin WAN ; Gang CHEN ; Zheng Nan GAO ; Fei Xia SHEN ; Zuo Jie LUO ; Ying Fen QIN ; Ya Nan HUO ; Qiang LI ; Zhen YE ; Yin Fei ZHANG ; Chao LIU ; You Min WANG ; Sheng Li WU ; Tao YANG ; Hua Cong DENG ; Jia Jun ZHAO ; Lu Lu CHEN ; Yi Ming MU ; Xu Lei TANG ; Ru Ying HU ; Wei Qing WANG ; Guang NING ; Mian LI ; Jie Li LU ; Yu Fang BI
Biomedical and Environmental Sciences 2021;34(1):9-18
Objective:
The relationship between serum uric acid (SUA) levels and glycemic indices, including plasma glucose (FPG), 2-hour postload glucose (2h-PG), and glycated hemoglobin (HbA1c), remains inconclusive. We aimed to explore the associations between glycemic indices and SUA levels in the general Chinese population.
Methods:
The current study was a cross-sectional analysis using the first follow-up survey data from The China Cardiometabolic Disease and Cancer Cohort Study. A total of 105,922 community-dwelling adults aged ≥ 40 years underwent the oral glucose tolerance test and uric acid assessment. The nonlinear relationships between glycemic indices and SUA levels were explored using generalized additive models.
Results:
A total of 30,941 men and 62,361 women were eligible for the current analysis. Generalized additive models verified the inverted U-shaped association between glycemic indices and SUA levels, but with different inflection points in men and women. The thresholds for FPG, 2h-PG, and HbA1c for men and women were 6.5/8.0 mmol/L, 11.0/14.0 mmol/L, and 6.1/6.5, respectively (SUA levels increased with increasing glycemic indices before the inflection points and then eventually decreased with further increases in the glycemic indices).
Conclusion
An inverted U-shaped association was observed between major glycemic indices and uric acid levels in both sexes, while the inflection points were reached earlier in men than in women.
Aged
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Asian Continental Ancestry Group
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Blood Glucose/analysis*
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China/epidemiology*
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Cohort Studies
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Diabetes Mellitus/blood*
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Female
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Glucose Tolerance Test
;
Glycated Hemoglobin A/analysis*
;
Glycemic Index
;
Humans
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Male
;
Middle Aged
;
Uric Acid/blood*


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