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Abstract
High-entropy alloys (HEAs) have been reported to have superior ability in hydrogen (H) storage and strong resistance to H embrittlement. These exceptional properties are directly related to the H solution in the HEAs. However, the diversity of atomic environments in the HEAs complicate the calculation of the H solution energy. With regard to this, we clarified an origin causing the variety of solution energy from the viewpoint of chemical and elastic interactions of H with the host atoms. Combining the semi-empirical atom potential and first-principles calculations regarding H in FeCrCoNi, NbMoTaW, and FeCuCrMnMo, we found that the elastic interaction presents a visibly linear relationship with the volume expansion caused by H insertion. By contrast, the chemical interaction shows a non-linear relationship with the volume of the interstitial polyhedron. A universal model was then established to generalize the solution energy of H. This model can expeditiously assess the H distribution and provide insight into evolution of the microstructure in HEAs.
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Affiliation(s)
- X L Ren
- Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Institute of Modern Physics, Department of Nuclear Science and Technology, Fudan University, Shanghai, 200433, China. .,College of Material and Metallurgy, Guizhou University, Guiyang, 550025, China
| | - P H Shi
- Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Institute of Modern Physics, Department of Nuclear Science and Technology, Fudan University, Shanghai, 200433, China.
| | - B D Yao
- Shandong Peninisula Engineering Research Center of Comprehensive Brine Utilization, Weifang University of Science and Technology, Shouguang 262700, Shandong, China
| | - L Wu
- The First Sub-Institute, Nuclear Power Institute of China, Chengdu, 610005, China
| | - X Y Wu
- The First Sub-Institute, Nuclear Power Institute of China, Chengdu, 610005, China
| | - Y X Wang
- Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Institute of Modern Physics, Department of Nuclear Science and Technology, Fudan University, Shanghai, 200433, China.
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Li J, Xu HL, Yao BD, Li WX, Fang H, Xu DL, Zhang ZF. Environmental tobacco smoke and cancer risk, a prospective cohort study in a Chinese population. Environ Res 2020; 191:110015. [PMID: 32818497 DOI: 10.1016/j.envres.2020.110015] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 05/30/2020] [Accepted: 07/27/2020] [Indexed: 06/11/2023]
Abstract
Few prospective cohort studies have investigated associations between environmental tobacco smoke (ETS) and other cancer sites, in addition to lung cancer. We assessed these associations in a population-based prospective cohort study started from 2008 to 2011 with average of 9.1 years of follow-up, in Minhang district, Shanghai, China. The study included a total of 23,415 participants (8388 men, 15,027 women) and 205,515 person-years. Epidemiological data were collected by a standardized questionnaire including ETS exposure. Newly diagnosed patients with primary cancers and deaths were identified by record linkage system with the Shanghai Cancer Registry and Shanghai Vital Statistics. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models, adjusting for potential confounders. During the study period, a total of 1462 patients with diagnoses of primary cancers were identified. Among all participants and non-smokers, ETS was associated with an increased risk of all smoking-related cancers (all: adjusted HR: 1.23, 95% CI: 1.05-1.43 and non-smokers: 1.24, 1.02-1.49), lung cancer (1.29, 0.98-1.71 and 1.27, 0.91-1.77), and stomach cancer (1.86, 1.21-2.85 and 1.75, 1.05-2.91), respectively. Furthermore, associations for lung and stomach cancers were the strongest among non-smoking females. The joint effects of both ETS and active smoking were strongest for all cancers, all smoking-related cancers, lung cancer, and stomach cancer. No clear interactions were observed. These results suggest that ETS exposure may increase the risk of smoking-related cancers in a Chinese population. Further studies on the relationship between ETS exposure and specific cancer sites are warranted to replicate our findings.
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Affiliation(s)
- Jun Li
- Department of Non-Communicable Diseases Prevention and Control, Shanghai Minhang Center for Disease Control and Prevention, Shanghai, 201101, China; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA
| | - Hui-Lin Xu
- Department of Non-Communicable Diseases Prevention and Control, Shanghai Minhang Center for Disease Control and Prevention, Shanghai, 201101, China
| | - Bao-Dong Yao
- Department of Non-Communicable Diseases Prevention and Control, Shanghai Minhang Center for Disease Control and Prevention, Shanghai, 201101, China
| | - Wei-Xi Li
- Department of Non-Communicable Diseases Prevention and Control, Shanghai Minhang Center for Disease Control and Prevention, Shanghai, 201101, China
| | - Hong Fang
- Department of Non-Communicable Diseases Prevention and Control, Shanghai Minhang Center for Disease Control and Prevention, Shanghai, 201101, China
| | - Dong-Li Xu
- Department of Non-Communicable Diseases Prevention and Control, Shanghai Minhang Center for Disease Control and Prevention, Shanghai, 201101, China.
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.
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Xu HL, Fang H, Xu WH, Qin GY, Yan YJ, Yao BD, Zhao NQ, Liu YN, Zhang F, Li WX, Wang N, Zhou J, Zhang JL, Zhao LY, Li LQ, Zhao YP. Cancer incidence in patients with type 2 diabetes mellitus: a population-based cohort study in Shanghai. BMC Cancer 2015; 15:852. [PMID: 26541196 PMCID: PMC4635996 DOI: 10.1186/s12885-015-1887-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Accepted: 10/30/2015] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) has been suggested to increase the risk of cancers. The aim of this study was to investigate the risk of common cancers in Chinese patients with T2DM. METHODS A population-based retrospective cohort study including 36,379 T2DM patients was conducted in Minhang District of Shanghai, China, during 2004 to 2010. All T2DM patients were enrolled from the standardized management system based on local electronic information system. Newly-diagnosed cancer cases were identified by record-linkage with the Shanghai Cancer Registry. Standardized incidence ratios (SIR) and 95% confidence interval (CI) were used to estimate the risk of cancers among T2DM patients. RESULTS Overall crude incidence rate (CIR) of cancers was 955.21 per 105 person-years in men and 829.57 per 105 person-years in women. Increased risk of cancer was found in both gender, with an SIR being 1.28 (95% CI = 1.17-1.38) in men and 1.44 (95% CI =1.32-1.55) in women. Increased risk of colon (SIR = 1.97; 95% CI = 1.49 to 2.46), rectum (1.72; 1.23 to 2.21), prostate (2.87; 2.19 to 3.56), and bladder cancers (1.98, 1.28 to 2.68) were observed in men and elevated risk of colon (1.67; 1.25 to 2.08), breast (1.66; 1.38 to 1.95), and corpus uteri cancers (2.87; 2.03 to 3.71) were observed in women. CONCLUSIONS Our results indicate that Chinese patients with T2DM may have an increased risk of some cancers, and the increase may vary by sub-sites of cancers.
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Affiliation(s)
- Hui-Lin Xu
- School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, People's Republic of China. .,Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Hong Fang
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Wang-Hong Xu
- School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, People's Republic of China.
| | - Guo-You Qin
- School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, People's Republic of China.
| | - Yu-Jie Yan
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Bao-Dong Yao
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Nai-Qing Zhao
- School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, People's Republic of China.
| | - Yi-Nan Liu
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Fen Zhang
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Wei-Xi Li
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Na Wang
- School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, People's Republic of China.
| | - Jie Zhou
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Jin-Ling Zhang
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Li-Yun Zhao
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Lun-Qiang Li
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
| | - Yan-Ping Zhao
- Shanghai Minhang Center for Disease Control and Prevention, 965 Zhong Yi Road, Shanghai, 201101, People's Republic of China.
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Wang ZL, Zhao F, Zhang ZJ, Yao BD, Jiang QL, Tao B, Zhai ML, Jiang QW. [Relationship between snails and recent water level in different marshlands in Xingzi County, Jiangxi Province]. Zhongguo Ji Sheng Chong Xue Yu Ji Sheng Chong Bing Za Zhi 2013; 31:49-53. [PMID: 24812838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
OBJECTIVE To study the longitudinal change of data on Oncomelania hupensis surveillance in different marshlands and the impact of recent water level in Xingzi County, Jiangxi Province. METHODS All information including water level of hydrometric station and the data of snails at the marshlands of Xiguanhu, Majiawan and Ximiaoqian was collected to explore the longitudinal change of snails and analyze the relationship between snail distribution and recent water level with Spearman rank correlation analysis. RESULTS The highest proportion of frames with living snails and living snail densities at Majiawan and Ximiaoqian was 89.66% (442/493) in 2002 and 66.72% (872/1 307) in 2007, 8.33 in 2001 and 7.39 snails per frame in 2006, respectively, and the lowest was 13.26% (126/950) in 2010 and 4.60% (55/1 195) in 2005, 0.42 in 2010 and 0.22 snails per frame in 2002, respectively, and tended to decrease gradually after 2007. At Majiawan, infected snails were found in 2005 and 2009, the density and proportion of infected snails were 0.0033 and 0.0025 snails per frame, 0.09% (3/3 306) and 0.22% (3/1 389). Infected snails were found in Ximiaoqian in 2001, 2003, 2005 and 2009, the highest density and proportion of infected snails were 0.005 0 snails per frame and 0.88% (6/684) in 2005. Infected snails were found in Xiguanhu in 2002 and 2003 with a density and proportion of 0.0029 and 0.0027 snails per frame, 0.10% (1/974) and 0.32% (1/312), respectively. The correlation analysis between proportion of frames with living snails and density at Xiguanhu with the average water level of the first and second month before snail survey showed statistical significance, the correlation coefficient was 0.76, 0.71, 0.82 and 0.78 (P<0.05), respectively. The correlation between proportion of frames with living snails and density at Majiawan showed no statistical significance with the average water level of recent three months before snail survey. The proportion of frames with living snails and density at Xiguanhu were negatively correlated with the average water level of the first and second month before snail survey, the correlation coefficient was -0.67, -0.75, -0.79 and -0.72 (P<0.05), respectively. CONCLUSION The change trend of snail indicators in different marshlands in the County and impact of water level in recent three months on snail population are both different, and the snail control strategy in marshlands should therefore be adjusted.
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Jiang QL, Tao B, Zhai ML, Wang JM, Wang ZL, Yao BD, Zhang ZJ. [Surveillance of schistosomiasis in Zhuxi Village, Xingzi County, 2005-2010]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2012; 24:607-608. [PMID: 23373280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To understand the effect of schistosomiasis control in Zhuxi Village, Xingzi County, Jiangxi Province. METHODS According to the national scheme of schistosomiasis surveillance, we investigated the schistosomiasis epidemic in Zhuxi Village from 2005-2010. The epidemic data of schistosomiasis on the humans, farm cattle, and Oncomelania snails were collected, respectively and analyzed by using the method of Cochran-Armitage test. RESULTS Human infections and snail infections showed dynamic fluctuations (Z = 3.35, P = 0.000 8) and the density of alive snails tended to decrease gradually. The majority of the infections were peasants and students. The infection rates of farm cattle were 12.31%, 3.23%, 2.94%, 3.33%, 4.44% and 2.15%, respectively from 2005-2010. CONCLUSION The effect of schistosomiasis control is very fine and schistosomiasis has been well controlled.
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Affiliation(s)
- Qiu-Lin Jiang
- Xingzi Anti-schistosomiasis Station, Jiangxi Province, Xingzi 332800, China
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Yao BD, Zhou YB, Wang ZL, Tian AP, Zhu SP, Wei CJ, Yang QY, Lu BK, Liao YZ, Hu BJ, Yi P, Jiang QW. [Study on spatial-temporal variation of infected snail in bottomland areas after an integrated control strategy at village level in the marshland and lake regions based on geographic information system]. Zhonghua Liu Xing Bing Xue Za Zhi 2012; 33:702-705. [PMID: 22968020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To evaluate the effect of an integrated control strategy and to quantify the spatial-temporal variation of infected snails in the bottomland areas after the strategy was implemented. METHODS Based on the geographic database of infected snail distribution at the village level during 2004 - 2010 in Anxiang county, Hunan province, spatial autocorrelation analysis and spatial scan statistics were applied to analyze the spatial-temporal characteristics on the distribution of infected snails. RESULTS The number of embankments with infected snails in Anxiang county decreased from 23 in 2004 to 10 in 2010, while the rate of frame with infected snail in embankments decreased from 4.32‰ in 2004 to 0.12‰ in 2010. The spatial distribution of infected snails was nonrandom, only in 2004 and 2005 with Moran's I = 0.21 (P < 0.10) and Moran's I = 0.13 (P < 0.10) respectively. Data from the local spatial auto-correlation analysis showed that the number of villages with H-H types of auto-correlation model had been gradually decreasing. The results of SaTScan statistics appeared the same as from the local spatial auto-correlation analysis, showing that the number of areas with increased risk was decreasing. CONCLUSION The comprehensive measures with emphasis on infectious source control seemed effective for schistosomiasis control program. The current distribution characteristics provided us with evidence that the resource assignment could be more reasonably implemented so as to control schistosomiasis in a more effective way.
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Affiliation(s)
- Bao-Dong Yao
- Department of Epidemiology, School of Public Health, Fudan University, Key Laboratory on Public Health Safety, Ministry of Education, Shanghai 200032, China
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Yao BD, Wang ZL, Zhang ZJ, Tian AP, Zhu SP, Hu BJ, Gao FH, Wang QZ, Yi P, Jiang QW. [Application of multi-temporal China-Brazil Earth Recourses Satellite-02 data on surveillance of dynamic changes of water body of rivers and Oncomelania snail habitats in Anxiang County]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2012; 24:160-167. [PMID: 22799159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To study the dynamic changes of the water body of rivers and Oncomelania snail habitats by using multi-temporal China-Brazil Earth Recourses Satellite-02 images taken in Anxiang County so as to establish the correct procedure for selecting images. METHODS CBERS-02 images were collected on 20th December 2003, 10th February 2004, 10th April 2004, 19th June 2004, 10th August 2004 and 27th October 2004. Then the water body information from the study areas based on NDWI was extracted and the areas of water body were calculated to determine the images. RESULTS The dynamic changes of the water body conformed to the rules of "water in summer and land in winter". Because of the rise of water, the water area in July was the biggest and the water area began to decline from August. The water area in April was the smallest. Then the wet season and the dry season should be June and April. CONCLUSION The multi-temporal CBERS-02 images could be used to surveillance the dynamic changes of the water area and helpful in choosing the right images of the wet season and dry season.
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Affiliation(s)
- Bao-Dong Yao
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
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Yao BD, Zhou YB, Wang ZL, Tian AP, Zhu SP, Hu BJ, Zhang ZJ, Song XX, Yi P, Jiang QW. [Study on spatial distribution of advanced schistosomiasis at village level in Anxiang County based on geographic information system]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2012; 24:72-75. [PMID: 22590869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
OBJECTIVE To explore the spatial distribution and pattern of advanced schistosomiasis in Anxiang County so as to provide the evidence for improving advanced schistosomiasis control. METHODS Based on the geographic database of advanced schistosomiasis distribution at the village level in Anxiang County, Hunan Province, the spatial autocorrelation analysis and spatial scan statistics were applied to analyze the spatial characteristics of distribution of advanced schistosomiasis. RESULTS The global Moran's I of prevalence rate of advanced schistosomiasis was 0.06 (P > 0.05) and there was no spatial auto-correlation as a whole. The local spatial auto-correlation analysis showed that there were 9 villages with statistically significant LISA value (P < 0.05), among which existed high-high, low-high and high-low types of auto-correlation model. The results of SaTScan statistics was the same as local spatial auto-correlation analysis and showed the existence of one cluster area. CONCLUSIONS There are local spatial auto-correlation and spatial aggregation of advanced schistosomiasis in Anxiang County. According to the distribution characteristics, we can assign resource more reasonably and control schistosomiasis more effectively.
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Affiliation(s)
- Bao-Dong Yao
- Department of Epidemiology, School of Public Health, Fudan University, Key Laboratory on Public Health Safety, Ministry of Education, Shanghai 200032, China
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Chen Y, Deng W, Wang SM, Mo QM, Jia H, Wang Q, Li SG, Li X, Yao BD, Liu CJ, Zhan YQ, Ji C, Lopez AL, Wang XY. Burden of pneumonia and meningitis caused by Streptococcus pneumoniae in China among children under 5 years of age: a systematic literature review. PLoS One 2011; 6:e27333. [PMID: 22110628 PMCID: PMC3217934 DOI: 10.1371/journal.pone.0027333] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2011] [Accepted: 10/14/2011] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND AND METHODS To understand the burden and epidemiology of Streptococcus pneumoniae disease among children between 1 and 59 months of age in China, we conducted a review of literature published between 1980 and 2008 applying standardized algorithms. Because of the absence of population-based surveillance for pneumococcal disease (PD), we identified all-cause pneumonia, bacteremia and meningitis burden, syndromes most commonly associated with S. pneumoniae, and applied the proportion of disease attributable to S. pneumoniae from studies that determined the etiology of these three syndromes to calculate PD burden. Because of the microbiologic difficulties in identifying S. pneumoniae-attributable pneumonia which likely underestimates the pneumonia burden, we also used the proportion obtained from vaccine efficacy trials. RESULTS Between 1980 and 2008, there were 12,815 cases/100,000/year of all-cause pneumonia among children between 1 month and 59 months, with 526 deaths/100,000 annually. There were 14 meningitis cases/100,000/year. We estimate that as of 2000, there were 260,768 (113,000 to 582,382) and 902 (114-4,463) cases of pneumococcal pneumonia and meningitis, respectively with 10,703 (4,638-23,904) and 75 (9-370) pneumococcal pneumonia and meningitis deaths, respectively. Pneumococcal pneumonia cases and deaths were more than two-fold higher, 695,382 (173,845-1,216,918) and 28,542 (7,136-49,949), respectively, when parameters from efficacy trials were used. Serotypes 19F, 19A and 14 were the most common serotypes obtained from pneumonia/meningitis patients. Currently available vaccines are expected to cover 79.5% to 88.4% of the prevalent serotypes. With high antibiotic resistance, introducing pneumococcal vaccines to the routine immunization program should be considered in China. Population-based studies are warranted.
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Affiliation(s)
- Ying Chen
- Institutes of Biomedical Sciences, Fudan University, Shanghai, People's Republic of China
| | - Wei Deng
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Song-Mei Wang
- Laboratory of Medical Molecular Biology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Qi-Mei Mo
- Institutes of Biomedical Sciences, Fudan University, Shanghai, People's Republic of China
| | - Huan Jia
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Qun Wang
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Song-Guang Li
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Xiang Li
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Bao-Dong Yao
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Cheng-Jun Liu
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Yi-Qiang Zhan
- Department of Health Statistics and Social Medicine, School of Public Health, Fudan University, Shanghai, People's Republic of China
| | - Chen Ji
- Pfizer Inc., New York, New York, United States of America
| | | | - Xuan-Yi Wang
- Institutes of Biomedical Sciences, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Medical Molecular Virology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
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