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Deng H, Qiu J, Zhang R, Xu J, Qu Y, Wang J, Liu Y, Gligorovski S. Ozone Chemistry on Greasy Glass Surfaces Affects the Levels of Volatile Organic Compounds in Indoor Environments. Environ Sci Technol 2024. [PMID: 38691770 DOI: 10.1021/acs.est.3c08196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
The chemistry of ozone (O3) on indoor surfaces leads to secondary pollution, aggravating the air quality in indoor environments. Here, we assess the heterogeneous chemistry of gaseous O3 with glass plates after being 1 month in two different kitchens where Chinese and Western styles of cooking were applied, respectively. The uptake coefficients of O3 on the authentic glass plates were measured in the dark and under UV light irradiation typical for indoor environments (320 nm < λ < 400 nm) at different relative humidities. The gas-phase product compounds formed upon reactions of O3 with the glass plates were evaluated in real time by a proton-transfer-reaction quadrupole-interface time-of-flight mass spectrometer. We observed typical aldehydes formed by the O3 reactions with the unsaturated fatty acid constituents of cooking oils. The formation of decanal, 6-methyl-5-hepten-2-one (6-MHO), and 4-oxopentanal (4-OPA) was also observed. The employed dynamic mass balance model shows that the estimated mixing ratios of hexanal, octanal, nonanal, decanal, undecanal, 6-MHO, and 4-OPA due to O3 chemistry with authentic grime-coated kitchen glass surfaces are higher in the kitchen where Chinese food was cooked compared to that where Western food was cooked. These results show that O3 chemistry on greasy glass surfaces leads to enhanced VOC levels in indoor environments.
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Affiliation(s)
- Huifan Deng
- State Key Laboratory of Organic Geochemistry and Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou 510640, China
- Chinese Academy of Science, Center for Excellence in Deep Earth Science, Guangzhou 510640, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jia Qiu
- Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing 100871, China
| | - Runqi Zhang
- Department of Materials Environmental Engineering, Shanxi Polytechnic College, Shanxi 237016, China
| | - Jinli Xu
- State Key Laboratory of Organic Geochemistry and Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou 510640, China
- Chinese Academy of Science, Center for Excellence in Deep Earth Science, Guangzhou 510640, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuekun Qu
- Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing 100871, China
| | - Jixuan Wang
- Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing 100871, China
| | - Yingjun Liu
- Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing 100871, China
| | - Sasho Gligorovski
- State Key Laboratory of Organic Geochemistry and Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou 510640, China
- Chinese Academy of Science, Center for Excellence in Deep Earth Science, Guangzhou 510640, China
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Chen HW, He Y, Ruan HH, Wu GB, Yu SJ, Wang Y, Chen GD, Qiu J, Wang CX, Chen LZ. [Mid-term efficacy evaluation of ABO incompatible living relative kidney transplantation based on protocol biopsy]. Zhonghua Yi Xue Za Zhi 2024; 104:944-949. [PMID: 38514343 DOI: 10.3760/cma.j.cn112137-20230719-00030] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Objective: To evaluate the mid-term efficacy of ABO incompatible living donor kidney transplantation (ABOi-KT) based on the results of routine renal biopsy for transplantation. Methods: Retrospective collection of clinical data from 23 pairs of ABOi-KT donors and recipients at the First Affiliated Hospital of Sun Yat-sen University from July 2015 to November 2021. ABOi-KT was performed on recipients after desensitization treatment, and the results of routine kidney transplant biopsy at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were analyzed. Combined with blood type antibody levels and renal function recovery, the mid-term efficacy of ABOi-KT was evaluated. Results: Among the 23 recipients, there were 19 males and 4 females; age range from 19 to 47 years old [(29.6±6.7) years old], all underwent ABOi-KT successfully after receiving desensitization treatment. The follow-up time was (44.6±22.4) months, of which 22 cases were followed up for more than 1 year. The incidence rates of rejection reactions at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were 15.0% (3/20), 11.1% (1/9), 7.7% (1/13), 25.0% (3/12), and 12.5% (1/8), respectively. For receptors with rejection reactions, targeted anti-rejection therapy was performed based on clinical symptoms and various indicators. Borderline T cell mediated rejection (TCMR) can be converted to mild tubular inflammation after anti-rejection treatment. The positive rate of complement C4d in peritubular capillaries was 95.0% (19/20) one week after surgery, and the positive rate of complement C4d was 100% at 3 and 12 months after surgery. The cumulative survival rates at 1, 3, 5, and 7 years after surgery were all 100%. The cumulative survival rates at 1, 3, 5, and 7 years after kidney transplantation were 100%, 93.3%, 84.0%, and 84.0%, respectively. Except for 2 recipients who underwent transplantation in 2017 and experienced kidney failure at 30 and 49 months after surgery, all other transplanted kidneys survived. Conclusions: The results of routine renal transplant biopsy show that ABOi-KT has a good mid-term therapeutic effect. The pathological changes of ABOi-KT can be dynamically observed through routine renal transplant biopsy and targeted treatment for rejection reactions can be provided accordingly.
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Affiliation(s)
- H W Chen
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - Y He
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - H H Ruan
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - G B Wu
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - S J Yu
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - Y Wang
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - G D Chen
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - J Qiu
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - C X Wang
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - L Z Chen
- Organ Transplantation Center of the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
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Shen B, Tong L, Qiu J, Zhong J, Tong Z, Li X. Suppurative Meningitis Complicated with Arthritis Caused by Streptococcus Suis Infection: A Case Report. Infect Drug Resist 2024; 17:561-569. [PMID: 38375100 PMCID: PMC10875338 DOI: 10.2147/idr.s416341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 01/31/2024] [Indexed: 02/21/2024] Open
Abstract
Background Streptococcus suis (S. suis) is a common gram-positive bacterium in pigs. Its natural infection sites are the upper respiratory tract (especially tonsils and nasal cavity), reproductive tract and digestive tract of pigs. It is a new emerging human and animal disease. A co-morbid pathogen that can cause serious infections in humans, including meningitis, sepsis, septic arthritis, and sometimes deafness. No cases have been reported in Huzhou City, Zhejiang Province, China. Case Presentation A 50-year-old male patient who had Worked as a butcher in a slaughterhouse for 20 years. Admitted to the hospital due to abdominal pain, joint pain, fever, and headache.His condition rapidly worsened causing altered consciousness, drowsiness and developed hearing loss. S. suis induced pyogenic meningitis complicated by arthritis was suspected based on the results of biochemical and culture analysis of the cerebrospinal fluid, and metagenomic next-generation sequencing, The patient's symptoms significantly improved after treatment with antibiotics such as ceftriaxone, meropenem, and linezolid, as well as supportive therapies including steroids and hyperbaric oxygen therapy, and his hearing improved significantly.After about 2 years of follow-up, the hearing was significantly better than before, but hearing impairment still remained. Conclusion Streptococcus suis is endemic in pork-consuming and pig-raising countries, but can occur throughout the world, especially among individuals with occupational exposure to pigs and/or pork, such as slaughterhouse workers, butchers, farmers, etc. Strengthen science education among key groups. This case was diagnosed as Streptococcus suis meningitis combined with arthritis. However, abdominal pain in the early stage of the disease is very rare and is easy to be misdiagnosed. It is necessary to identify whether it is complicated by peritonitis. For hearing loss caused by Streptococcus suis infection, the use of hyperbaric oxygen chamber treatment has obvious therapeutic effects.
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Affiliation(s)
- Bin Shen
- Department of Infectious Diseases, Huzhou Central Hospital, Huzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou, Zhejiang Province, 313000, People’s Republic of China
| | - Luyuan Tong
- Department of Infectious Diseases, Huzhou Central Hospital, Huzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou, Zhejiang Province, 313000, People’s Republic of China
| | - Jia Qiu
- Department of Infectious Diseases, Huzhou Central Hospital, Huzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou, Zhejiang Province, 313000, People’s Republic of China
| | - Jianfeng Zhong
- Department of Infectious Diseases, Huzhou Central Hospital, Huzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou, Zhejiang Province, 313000, People’s Republic of China
| | - Zhaowei Tong
- Department of Infectious Diseases, Huzhou Central Hospital, Huzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou, Zhejiang Province, 313000, People’s Republic of China
| | - Xiaofeng Li
- Department of Infectious Diseases, Huzhou Central Hospital, Huzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou, Zhejiang Province, 313000, People’s Republic of China
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Chen J, Huang S, Zhang Y, Chang Q, Zhang Y, Li D, Qiu J, Hu L, Peng X, Du Y, Gao Y, Chen DZ, Bellou A, Wu J, Liang H. Congenital heart disease detection by pediatric electrocardiogram based deep learning integrated with human concepts. Nat Commun 2024; 15:976. [PMID: 38302502 PMCID: PMC10834950 DOI: 10.1038/s41467-024-44930-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 01/10/2024] [Indexed: 02/03/2024] Open
Abstract
Early detection is critical to achieving improved treatment outcomes for child patients with congenital heart diseases (CHDs). Therefore, developing effective CHD detection techniques using low-cost and non-invasive pediatric electrocardiogram are highly desirable. We propose a deep learning approach for CHD detection, CHDdECG, which automatically extracts features from pediatric electrocardiogram and wavelet transformation characteristics, and integrates them with key human-concept features. Developed on 65,869 cases, CHDdECG achieved ROC-AUC of 0.915 and specificity of 0.881 on a real-world test set covering 12,000 cases. Additionally, on two external test sets with 7137 and 8121 cases, the overall ROC-AUC were 0.917 and 0.907 while specificities were 0.937 and 0.907. Notably, CHDdECG surpassed cardiologists in CHD detection performance comparison, and feature importance scores suggested greater influence of automatically extracted electrocardiogram features on CHD detection compared with human-concept features, implying that CHDdECG may grasp some knowledge beyond human cognition. Our study directly impacts CHD detection with pediatric electrocardiogram and demonstrates the potential of pediatric electrocardiogram for broader benefits.
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Affiliation(s)
- Jintai Chen
- State Key Laboratory of Transvascular Implantation Devices of the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, 310009, Hangzhou, China
| | - Shuai Huang
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Ying Zhang
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Department of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
| | - Qing Chang
- Liaoning Engineering Research Center of Intelligent Diagnosis and Treatment Ecosystem, 110004, Shenyang, Liaoning Province, China
- Clinical Research Center of Shengjing Hospital of China Medical University, 110004, Shenyang, Liaoning Province, China
| | - Yixiao Zhang
- Liaoning Engineering Research Center of Intelligent Diagnosis and Treatment Ecosystem, 110004, Shenyang, Liaoning Province, China
- Department of Urology Surgery, Shengjing Hospital of China Medical University, 110004, Shenyang, Liaoning Province, China
| | - Dantong Li
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Jia Qiu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Department of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
| | - Lianting Hu
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Xiaoting Peng
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Yunmei Du
- College of Information Technology and Engineering, Guangzhou College of Commerce, 510363, Guangzhou, Guangdong Province, China
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 510623, Guangzhou, Guangdong Province, China
| | - Yunfei Gao
- Zhuhai Precision Medical Center, Zhuhai People's Hospital/ Zhuhai Hospital Affiliated with Jinan University, Jinan University, 519000, Zhuhai, Guangdong Province, China
- The Biomedical Translational Research Institute, Jinan University Faculty of Medical Science, Jinan University, 510632, Guangzhou, Guangdong Province, China
| | - Danny Z Chen
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Abdelouahab Bellou
- Institute of Sciences in Emergency Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, China.
- Department of Emergency Medicine, Wayne State University School of Medicine, Detroit, MI, 48201, USA.
| | - Jian Wu
- State Key Laboratory of Transvascular Implantation Devices of the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, 310009, Hangzhou, China.
- School of Public Health, Zhejiang University, 310058, Hangzhou, China.
| | - Huiying Liang
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China.
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China.
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China.
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Liu G, Qiu J, Liu Y, Liu Z. Effectiveness and safety of cefotaxime combined with avibactam for treating multidrug-resistant E coli infections: A systematic review and meta-analysis. Medicine (Baltimore) 2024; 103:e36938. [PMID: 38241533 PMCID: PMC10798705 DOI: 10.1097/md.0000000000036938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024] Open
Abstract
BACKGROUND Multidrug-resistant Escherichia coli infections are a global health challenge, notably in North America, Europe, Asia, and Africa. This systematic review and meta-analysis evaluates the effectiveness and safety of cefotaxime combined with avibactam, aiming to mitigate these infections' impact and lessen their burden on healthcare systems worldwide. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and PICO frameworks, we conducted a comprehensive literature search across 4 primary databases on May 6, 2023. Studies evaluating the efficacy and safety of cefotaxime and avibactam were included. Key outcomes included treatment success, adverse effects, and microbiological eradication. Quality assessment utilized the Cochrane Collaboration Risk of Bias instrument. Heterogeneity was analyzed using chi-square statistics and the I2 index. Both fixed- and random-effects models were applied as appropriate. Publication bias was rigorously evaluated using Egger linear regression test and funnel plot analysis, ensuring the study's integrity and reliability. RESULTS The clinical cure rate derived from 8 studies showed no significant difference between the treatment groups (odds ratio [OR] = 1.97, 95% CI: 0.69 to 1.36, P = .86). Analysis of the bacterial clearance rate from the 5 studies also indicated no significant difference (OR = 0.97, 95% CI: 0.42 to 2.25, P = .36). Notably, a reduced mortality rate favoring the experimental group was observed in 6 studies (OR = 0.64, 95% CI: 0.44 to 0.92, P = .012). Comprehensive sensitivity analyses and the assessment of publication bias strengthened the reliability of the results. CONCLUSIONS Ceftazidime combined with avibactam significantly reduced mortality among patients with multidrug-resistant Escherichia coli infections, indicating its potential as a therapeutic option, especially for carbapenem-resistant Enterobacteriaceae. However, extensive large-scale clinical trials are required to validate these findings.
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Affiliation(s)
- Geming Liu
- Department of Pharmacy, Affiliated Hospital of Jilin Medical University, Jilin, Jilin Province, China
| | - Jia Qiu
- Department of Pharmacy, Affiliated Hospital of Beihua University, Jilin, Jilin Province, China
| | - Yang Liu
- Department of Pharmacy, Jilin Chemical Hospital, Jilin, Jilin Province, China
| | - Zhisen Liu
- Clinical Pharmacy, Affiliated Hospital of Jilin Medical University, Jilin, Jilin Province, China
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Duan JF, Guo X, Qiu J, Huang F, Li J, Li Z, Zheng YJ, Sun XD. [Analysis of the current status and related factors of human papillomavirus infection among community-dwelling women aged 18-24 years without a history of vaccination in Shanghai City]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:2056-2063. [PMID: 38186156 DOI: 10.3760/cma.j.cn112150-20230404-00257] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Objective: To understand the status of human papillomavirus (HPV) infection among young women without a history of vaccination in Shanghai, and analyze the related factors of HPV infection in this population. Methods: A total of 2 660 women aged 18-24 years old who had made an appointment for HPV vaccine at 36 community health service centers in Shanghai from July 2022 to February 2023 were selected as the study subjects. Basic information (including demographic characteristics, previous disease history, female menstrual and reproductive history, sexual life history, etc.) was collected by a self-filling electronic questionnaire. Cervical secretions were detected by HPV nucleic acid typing. The multivariate logistic regression model was used to analyze the factors related to high-risk HPV (HR-HPV) infection in the target population. Results: The age of the subjects was (23±1) years old, and the infection rate of HPV was 14.51% (386 cases), among which the infection rates of HR-HPV and low-risk HPV were 13.53% (360 cases) and 1.84% (49 cases), respectively. The main subtypes of HR-HPV infection were HPV52, 16, 58, 39 and 66. The multivariate logistic regression model analysis showed that compared with the control group, the OR (95%CI) values for HR-HPV infection in the group of married, earned less than 2 000 yuan/month, drank alcohol occasionally, gynecological disease history, had two or more sexual partners in the past year, and did not know whether the partners had other sexual partners were 0.41 (0.25-0.66), 0.39 (0.21-0.70), 1.45 (1.13-1.86), 1.29 (1.00-1.66), 2.18-5.18 (1.02-16.05), and 1.82 (1.31-2.54), respectively. Conclusion: The infection rate of HPV among women aged 18-24 years old in Shanghai remains at a high level. The main subtypes of HR-HPV infection are HPV52, 16, 58, 39 and 66. The marital status, economic income level, drinking status, gynecological disease history and sexual life history are related to HR-HPV infection.
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Affiliation(s)
- J F Duan
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
| | - X Guo
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Qiu
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - F Huang
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Li
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Z Li
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Y J Zheng
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
| | - X D Sun
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
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Li N, Qiu J, Liang NP, Wu MB, Zhang XT, Zhang H, Dong YF. [Relationship between the neutrophil-to-lymphocyte ratio and estimated glomerular filtration rate in patients with primary aldosteronism: a cross-sectional study]. Zhonghua Xin Xue Guan Bing Za Zhi 2023; 51:1145-1151. [PMID: 37963749 DOI: 10.3760/cma.j.cn112148-20230724-00019] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Objective: To investigate the associations between neutrophil-to-lymphocyte ratio (NLR) and estimated glomerular filtration rate (eGFR) in patients with primary aldosteronism (PA). Methods: This study was a cross-sectional study. Consecutive patients diagnosed with PA and admitted to the Second Affiliated Hospital of Nanchang University from October 2017 to April 2022 were enrolled. General information, blood routine, renal function, and other clinical data of the patients were collected. Based on the median NLR of the enrolled patients, NLR
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Affiliation(s)
- N Li
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - J Qiu
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - N P Liang
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - M B Wu
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - X T Zhang
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - H Zhang
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Y F Dong
- Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China Key Laboratory of Molecular Biology in Jiangxi Province, Nanchang 330006, China
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Wang W, Wang K, Qiu J, Li W, Wang X, Zhang Y, Wang X, Wu J. MRI-based radiomics analysis of bladder cancer: prediction of pathological grade and histological variant. Clin Radiol 2023; 78:e889-e897. [PMID: 37633748 DOI: 10.1016/j.crad.2023.07.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/08/2023] [Accepted: 07/26/2023] [Indexed: 08/28/2023]
Abstract
AIM To develop magnetic resonance imaging (MRI)-based radiomics models for the prediction of the pathological grade and histological variant of bladder cancer. MATERIALS AND METHODS A total of 227 patients who underwent bladder MRI and had histopathologically confirmed grades and variants were included retrospectively from January 2017 to March 2022. They were assigned to a training set (n=131) and a testing set (n=96) based on the MRI system. MRI-based radiomics features were extracted from manually segmented volumes of interest from high-b-value DWI images and ADC maps. The radiomics models were trained with all possible pipelines in the training set. One optimal model was selected using the fivefold cross-validation method and verified by the testing set according to the pathological results. Univariate and multivariate analyses were performed to identify the significant clinical and imaging factors for developing clinical-radiomics models. RESULTS The radiomics model for grade prediction had area under the curve (AUC) values of 0.784, 0.786, and 0.733 in the training, cross-validation, and testing sets, respectively. The radiomics model for variant prediction had AUC values of 0.748, 0.757, and 0.789 in the training, cross-validation, and testing sets, respectively. The performance of the clinical-radiomics model was significantly improved compared with the radiomics models alone for the total dataset (AUC for grade: 0.846 versus 0.756; AUC for variant: 0.810 versus 0.757, p<0.05). CONCLUSION MRI-based radiomics models could be used to predict the pathological grade and histological variants of bladder cancer with relatively good performance.
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Affiliation(s)
- W Wang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - K Wang
- Capital Medical University, School of Basic Medical Sciences, Beijing, China
| | - J Qiu
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - W Li
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - X Wang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Y Zhang
- Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China
| | - X Wang
- Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China
| | - J Wu
- Department of Radiology, Peking University First Hospital, Beijing, China.
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Wang J, Yu L, Qiu J, Yang B, Pang T, Wang Z, Zhu H, Liang Y. Application of the Ion Chamber Array in Magnetic Resonance Accelerator QA. Int J Radiat Oncol Biol Phys 2023; 117:e734. [PMID: 37786134 DOI: 10.1016/j.ijrobp.2023.06.2258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The magnetic resonance accelerator (MR-Linac) is gradually widely used due to high-quality soft tissue contrast and real-time tracking. However, the special dosimetry characteristics and wide field sizes of MR-Linac increase the QA difficulty with conventional measurement method. The purpose of this study was to confirm an ion chamber array could be used for measuring the beam quality, the profiles, as well as the positioning accuracy of all MLC leaves efficiently, by comparing results with the conventional method. To propose a new QA approach for solving the common problem in data acquisition caused by the wide fields of MR-Linac. MATERIALS/METHODS The research was based on a MR-Linac fixed with 1.5T MR and 7MeV energy photon beam. The conventional QA method adopted the MR water tank with a gantry angle of 0°and an SSD of 133.5 cm, both microdiamond and ionization chamber detector were used to acquire the dose profiles (PDD, inline, crossline and diagonal). Field sizes 1 × 1 cm2, 2 × 2 cm2, 3 × 3 cm2, 5 × 5 cm2, 10 × 10 cm2, 15 × 15 cm2, 22 × 22 cm2, 40 × 22 cm2,57 × 22 cm2 were measured with depth 13mm, 50mm, 100mm for vertical beam. As for the wide fields (larger than 15 × 15 cm2), two profiles of x axis (one from left to right, the other from right to left) needed to be gathered and then stitched into one final profile. A boot phantom with an ionization chamber detector was used for measuring beam quality. We defined the profiles measured by conventional method as the baseline. An ion chamber array was adopted to acquire TPR, PDD, profiles and MLC positioning, comparing to the conventional method. The center of ion chamber array was placed to the isocenter of MR-Linac, the array could move to the right and left offset positions through engaging the pin into correct hole of QA platform, such 'once positioning and twice movements' operation could finish within 3 minutes. The central detector of the ion chamber array was used for measuring beam quality. TPRs for different depths were acquired by stacking solid water on the ion chamber array. As for the profiles, we could get the final profile by 'once positioning and twice movements' efficiently. As for the positioning accuracy of MLC leaves, firstly the central leaf pair was put on y = 0 to measure 'open profile' under the open field. Then we moved the MLC leaves to different positions to get the n profile (n for different leaf positions). The ratio of n profile to open profile could show the positioning accuracy of MLC. RESULTS We adopted 2D gamma (1mm / 2%) to compare the profiles between the ion chamber array and the conventional method, the results were within 98%. The beam quality consistency of ion chamber array comparing to the wedge tank was within 1% according to daily measurement. The ion chamber array could reflect the MLC positioning differences, the sensitivity was 0.5 mm. CONCLUSION The ion chamber array showed a convenient QA method both for the dosimetry and for the MLC positioning accuracy which did reduce the overall measurement time, it was recommended for daily and monthly QA for MR-Linac.
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Affiliation(s)
- J Wang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - L Yu
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - J Qiu
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - B Yang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - T Pang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Z Wang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - H Zhu
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Y Liang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Ye Y, Liu Z, Zhu J, Wu J, Sun K, Peng Y, Qiu J, Gong L. Development trends and knowledge framework in the application of magnetic resonance imaging in prostate cancer: a bibliometric analysis from 1984 to 2022. Quant Imaging Med Surg 2023; 13:6761-6777. [PMID: 37869318 PMCID: PMC10585509 DOI: 10.21037/qims-23-446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/07/2023] [Indexed: 10/24/2023]
Abstract
Background Prostate cancer (PCa) is the most common tumor of the male genitourinary system. With the development of imaging technology, the role of magnetic resonance imaging (MRI) in the management of PCa is increasing. The present study summarizes research on the application of MRI in the field of PCa using bibliometric analysis and predicts future research hotspots. Methods Articles regarding the application of MRI in PCa between January 1, 1984 and June 30, 2022 were selected from the Web of Science Core Collection (WoSCC) on November 6, 2022. Microsoft Excel 2016 and the Bibliometrix Biblioshiny R-package software were used for data analysis and bibliometric indicator extraction. CiteSpace (version 6.1.R3) was used to visualize literature feature clustering, including co-occurrence analysis of countries, institutions, authors, references, and burst keywords analysis. Results A total of 10,230 articles were included in the study. Turkbey was the most prolific author. The USA was the most productive country and had strong partnerships with other countries. The most productive institution was Memorial Sloan Kettering Cancer Center. Journal of Magnetic Resonance Imaging and Radiology were the most productive and highest impact factor (IF) journals in the field, respectively. Timeline views showed that "#1 multiparametric magnetic resonance imaging", "#4 pi-rads", and "#8 psma" were currently the latest research hotspots. Keywords burst analysis showed that "machine learning", "psa density", "multi parametric mri", "deep learning", and "artificial intelligence" were the most frequently used keywords in the past 3 years. Conclusions MRI has a wide range of applications in PCa. The USA is the leading country in this field, with a concentration of highly productive and high-level institutions. Meanwhile, it can be projected that "deep learning", "radiomics", and "artificial intelligence" will be research hotspots in the future.
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Affiliation(s)
- Yinquan Ye
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Zhixuan Liu
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jianghua Zhu
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jialong Wu
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Ke Sun
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yun Peng
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jia Qiu
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Lianggeng Gong
- Department of Radiology, the Second Affiliated Hospital of Nanchang University, Nanchang, China
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Wang Z, Yang B, Meng X, Liang Y, Pang T, Qiu J. Performance Evaluation in Automatic Plan Generation for Ethos Intelligent Optimization Engine. Int J Radiat Oncol Biol Phys 2023; 117:e736. [PMID: 37786140 DOI: 10.1016/j.ijrobp.2023.06.2263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To evaluate the automatic optimization performance and clinical feasibility of the Intelligent Optimization Engine (IOE) of Ethos online adaptive radiotherapy platform. MATERIALS/METHODS Eleven patients with cervical cancer treated with Halcyon accelerator were retrospectively selected. All the patients manually planned with four full arc volume rotating intensity modulated radiotherapy (VMAT) (Manual-4Arc), and the prescription dose was 45 Gy/25F. All patient images and structures were imported into Ethos simulator, and clinical goals were added appropriately based on clinical requirements. The target coverage was normalized to 95%. 7F, 9F, 12F IMRT plans and 2Arc, 3Arc VMAT plans were automatically generated by IOE. Dosimetric index comparisons were made among the Manual-4Arc plans and five group IOE generated plan to evaluate the automatic optimization performance of IOE. RESULTS In terms of hot dose area, for PTV, D1% of IMRT-12F plans was the lowest, and there were significant differences between IMRT-12F plans and Manual-4Arc plans (46.936 ± 0.241 vs 48.639 ± 2.395, p = 0.004); In terms of target coverage, the CTVs of all groups meet clinical requirements. Although the Ethos online adaptive plans have been normalized during planning, the PTV coverage is slightly insufficient (12F: 94.913 ± 0.154; 9F: 94.585 ± 1.148). For OARs close to target, such as bladder, V30Gy, V40Gy and Dmean have significant differences among the six group plans. The order of bladder dose is basically followed by IMRT-12F CONCLUSION The plans automatically generated by Ethos IOE can achieve similar performance as the manual plan, and the automatically generated IMRT-12F and 9F plans are preferred for clinical use.
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Affiliation(s)
- Z Wang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - B Yang
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Meng
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Liang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - T Pang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - J Qiu
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Wang Q, Qiu J, Huang JL, Jiang M, Lu JQ, Wu D, Wei XB, Yu DQ. Prognostic Value of Blood Urea Nitrogen for Short-Term Mortality in Patients with Infective Endocarditis. Infect Dis Ther 2023; 12:2353-2366. [PMID: 37751020 PMCID: PMC10600074 DOI: 10.1007/s40121-023-00867-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 08/30/2023] [Indexed: 09/27/2023] Open
Abstract
INTRODUCTION Blood urea nitrogen (BUN) is a metabolic product validated to be an independent risk factor in the prognosis of several diseases. However, the prognostic value of BUN in patients with infective endocarditis (IE) remains unevaluated. METHODS A total of 1371 patients with a diagnosis of IE were included and divided into four groups according to BUN (mmol/L) at admission: < 3.5 (n = 343), 3.5-4.8 (n = 343), 4.8-6.8 (n = 341), and ≥ 6.8 (n = 344). Restricted cubic spline was used to assess the association of BUN with in-hospital mortality. Multivariate analysis was performed to identify the independent risk factors for adverse outcomes. RESULTS The in-hospital mortality reached 7.4%, while the 6-month mortality was 9.8%. The restricted cubic spline plot exhibited an approximately linear relationship between BUN and in-hospital mortality. Receiver operating characteristics curve analysis showed that the optimal cut-off of BUN for predicting in-hospital death was 6.8 mmol/L. Kaplan-Meier analysis showed that patients with BUN > 6.8 mmol/L had a higher 6-month mortality than other groups (log rank = 97.9, P < 0.001). Multivariate analysis indicated that BUN > 6.8 mmol/L was an independent predictor indicator for both in-hospital [adjusted odds ratio (aOR) = 2.365, 95% confidence interval (CI) 1.292-4.328, P = 0.005] and 6-month mortality [adjusted hazard ratio (aHR) = 2.171, 95% CI 1.355-3.479, P = 0.001]. CONCLUSIONS BUN is suitable for independently predicting short-term mortality in patients with IE.
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Affiliation(s)
- Qi Wang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Jia Qiu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Jie-Leng Huang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Mei Jiang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Jun-Quan Lu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Di Wu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Xue-Biao Wei
- Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China.
| | - Dan-Qing Yu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China.
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Yang T, Peng L, Qiu J, He X, Zhang D, Wu R, Liu J, Zhang X, Zha Z. A radiohybrid theranostics ligand labeled with fluorine-18 and lutetium-177 for fibroblast activation protein-targeted imaging and radionuclide therapy. Eur J Nucl Med Mol Imaging 2023; 50:2331-2341. [PMID: 36864362 PMCID: PMC10250256 DOI: 10.1007/s00259-023-06169-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 02/19/2023] [Indexed: 03/04/2023]
Abstract
PURPOSE A series of radiotracers targeting fibroblast activation protein (FAP) with great pharmacokinetics have been developed for cancer diagnosis and therapy. Nevertheless, the use of dominant PET tracers, gallium-68-labeled FAPI derivatives, was limited by the short nuclide half-life and production scale, and the therapeutic tracers exhibited rapid clearance and insufficient tumor retention. In this study, we developed a FAP targeting ligand, LuFL, containing organosilicon-based fluoride acceptor (SiFA) and DOTAGA chelator, capable of labeling fluorine-18 and lutetium-177 in one molecular with simple and highly efficient labeling procedure, to achieve cancer theranostics. METHODS The precursor LuFL (20) and [natLu]Lu-LuFL (21) were successfully synthesized and labeled with fluorine-18 and lutetium-177 using a simple procedure. A series of cellular assays were performed to characterize the binding affinity and FAP specificity. PET imaging, SPECT imaging, and biodistribution studies were conducted to evaluate pharmacokinetics in HT-1080-FAP tumor-bearing nude mice. A comparison study of [177Lu]Lu-LuFL ([177Lu]21) and [177Lu]Lu-FAPI-04 was carried out in HT-1080-FAP xenografts to determine the cancer therapeutic efficacy. RESULTS LuFL (20) and [natLu]Lu-LuFL (21) demonstrated excellent binding affinity towards FAP (IC50: 2.29 ± 1.12 nM and 2.53 ± 1.87 nM), compared to that of FAPI-04 (IC50: 6.69 ± 0.88 nM). In vitro cellular studies showed that 18F-/177Lu-labeled 21 displayed high specific uptake and internalization in HT-1080-FAP cells. Micro-PET, SPECT imaging and biodistribution studies with [18F]/[177Lu]21 revealed higher tumor uptake and longer tumor retention than those of [68 Ga]/[177Lu]Ga/Lu-FAPI-04. The radionuclide therapy studies showed significantly greater inhibition of tumor growth for the [177Lu]21 group, than for the control group and the [177Lu]Lu-FAPI-04 group. CONCLUSION The novel FAPI-based radiotracer containing SiFA and DOTAGA was developed as a theranostics radiopharmaceutical with simple and short labeling process, and showed promising properties including higher cellular uptake, better FAP binding affinity, higher tumor uptake and prolong retention compared to FAPI-04. Preliminary experiments with 18F- and 177Lu-labeled 21 showed promising tumor imaging properties and favorable anti-tumor efficacy.
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Affiliation(s)
- Tianhong Yang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Lei Peng
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Jia Qiu
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Xingjin He
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Dake Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Renbo Wu
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Jianbo Liu
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China
| | - Xiangsong Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China.
| | - Zhihao Zha
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, #58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, China.
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Guo X, Duan JF, Li Z, Qiu J, Ma XY, Huang ZY, Hu JY, Liang XF, Sun XD. [Analysis of the direct economic burden of measles cases and its influencing factors in Shanghai from 2017 to 2019]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:857-862. [PMID: 37357204 DOI: 10.3760/cma.j.cn112150-20220608-00591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/27/2023]
Abstract
Objective: To analyze the direct economic burden caused by measles cases in Shanghai from 2017 to 2019 and its influencing factors. Methods: A total of 161 laboratory-confirmed measles cases reported from January 1, 2017, to December 31, 2019, in Shanghai were included in the study through the "Measles Surveillance Information Reporting and Management System" of the "China Disease Surveillance Information Reporting and Management System". Through telephone follow-up and consulting hospital data, the basic information of population, medical treatment situation, medical treatment costs and other information were collected, and the direct economic burden of cases was calculated, including registration fees, examination fees, hospitalization fees, medical fees and other disease treatment expenses, as well as transportation and other expenses of cases. The multiple linear regression model was used to analyze the main influencing factors of the direct economic burden. Results: The age of 161 measles cases M (Q1, Q3) was 28.21 (13.33, 37.00) years. Male cases (56.52%) were more than female cases (43.48%). The largest number of cases was≥18 years old (70.81%). The total direct economic burden of 161 measles cases was 540 851.14 yuan, and the per capita direct economic burden was 3 359.32 yuan. The direct economic burden M (Q1, Q3) was 873.00 (245.01, 4 014.79) yuan per person. The results of multiple linear regression model analysis showed that compared with other and unknown occupations, central areas and non-hospitalized cases, the direct economic burden of measles cases was higher in scattered children, childcare children, students, and cadre staff in the occupational distribution, suburban areas and hospitalized, with the coefficient of β (95%CI) values of 0.388 (0.150-0.627), 0.297 (0.025-0.569), 0.327 (0.148-0.506) and 1.031 (0.853-1.209), respectively (all P values<0.05). Conclusion: The direct economic burden of some measles cases in Shanghai is relatively high. Occupation, area of residence and hospitalization are the main factors influencing the direct economic burden of measles cases.
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Affiliation(s)
- X Guo
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J F Duan
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
| | - Z Li
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Qiu
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - X Y Ma
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Z Y Huang
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Y Hu
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - X F Liang
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - X D Sun
- Department of immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
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Li ZY, Wang B, Zheng BB, Qiu J. [A preliminary report of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis to prevent parastomal hernia]. Zhonghua Wai Ke Za Zhi 2023; 61:481-485. [PMID: 37088480 DOI: 10.3760/cma.j.cn112139-20220903-00375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Objective: To examine the preliminary effect of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis for the prevention of parastomal hernia after abdominoperineal resection for rectal cancer. Methods: This study is a prospective case series study. From June 2021 to June 2022, patients with low rectal cancer underwent laparoscopic abdominoperineal resection combined with extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis at the First Department of General Surgery, Shaanxi Provincial People's Hospital were enrolled. The clinical data and postoperative CT images of patients were collected to analyze the incidence of surgical complication and parastomal hernia. Results: Totally 6 cases of patient were enrolled, including 3 males and 3 females, aging 72.5 (19.5) years (M(IQR)) (range: 55 to 79 years). The operation time was 250 (48) minutes (range: 190 to 275 minutes), the stoma operation time was 27.5 (10.7) minutes (range: 21 to 37 minutes), the bleeding volume was 30 (35) ml (range: 15 to 80 ml). All patients were cured and discharged without surgery-related complications. The follow-up time was 136 (105) days (range: 98 to 279 days). After physical examination and abdominal CT follow-up, no parastomal hernia occurred in the 6 patients up to this article. Conclusions: A method of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis is established. Permanent stoma can be completed with this method safely. It may have a preventive effect on the occurrence of parastomal hernia, which is worthy of further study.
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Affiliation(s)
- Z Y Li
- First Department of General Surgery, Shaanxi Provincial People's Hospital, Xi'an 710068, China
| | - B Wang
- First Department of General Surgery, Shaanxi Provincial People's Hospital, Xi'an 710068, China
| | - B B Zheng
- First Department of General Surgery, Shaanxi Provincial People's Hospital, Xi'an 710068, China
| | - J Qiu
- First Department of General Surgery, Shaanxi Provincial People's Hospital, Xi'an 710068, China
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Qiu J, Yang T, Long Y, He P, Shen W, Zhang B, Shi X, Peng L, Li Z, Zhang X. Mitochondrial respiration inhibitor enhances the anti-tumor effect of high-dose ascorbic acid in castration-resistant prostate cancer. J Mol Med (Berl) 2023; 101:125-138. [PMID: 36478125 DOI: 10.1007/s00109-022-02273-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 11/08/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022]
Abstract
Previous evidences have demonstrated that anti-tumor effect of high-dose ascorbic acid is associated with the generation of reactive oxygen species (ROS) via autoxidation. Hypoxia induces therapy resistance in castration-resistant prostate cancer. As a mitochondrial respiration inhibitor, metformin has the potential to improve tumor oxygenation. In this study, we evaluate the anti-tumor effect of ascorbic acid combined with metformin in prostate cancer. We demonstrated that ascorbic acid inhibits prostate cancer cells proliferation by generating ROS, and metformin enhances the anti-tumor effects of ascorbic acid. Mechanistically, metformin reduces oxygen consumption rate and NADP+/NADPH value in prostate cancer cells, thereby increases the ROS content induced by ascorbic acid. In addition, our data demonstrated that ascorbic acid inhibits p-AKT signaling in a ROS-dependent pathway, leading to inhibition of p-mTOR expression. And metformin inhibits the p-mTOR expression by activating the AMPK signaling pathway, exerting a synergistic effect on tumor suppression with ascorbic acid. Furthermore, metformin improves tumor oxygenation, and the combined treatment effect of ascorbic acid and metformin were demonstrated in a xenograft model of prostate cancer. Taken together, our data demonstrate that metformin enhances the anti-tumor proliferation effect of ascorbic acid by increasing ROS content in castration-resistant prostate cancer. This provides a new strategy for the clinical application of high-dose ascorbic acid as an anti-tumor drug. KEY MESSAGES: Ascorbic acid inhibits tumor growth by inducing ROS generation. As a mitochondrial respiration inhibitor, metformin inhibits cellular oxygen consumption rate to improve oxygenation of prostate cancer. Metformin enhances anti-tumor effect of ascorbic acid by increasing ROS content. Ascorbic acid inhibits the mTOR expression via PI3K-AKT pathway, and metformin inhibits the mTOR expression by inhibiting AMPK signaling in prostate cancer cells.
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Affiliation(s)
- Jia Qiu
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.,Medical Imaging Center, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Tianhong Yang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yali Long
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Peng He
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.,Department of Ultrasound Medicine & Ultrasonic Medical Engineering Key Laboratory of Nanchong City, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Wanqing Shen
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Bing Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xinchong Shi
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Lei Peng
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhoulei Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiangsong Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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Jin K, Lin G, Zhao Q, Liu Y, Qiu J, Jiang Y, Huang D. CFD Analysis on the Diffusion and Accumulation Characteristics of Microleakage LPG in an Integrated Stove. ACS Omega 2023; 8:1271-1281. [PMID: 36643524 PMCID: PMC9835542 DOI: 10.1021/acsomega.2c06715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 12/14/2022] [Indexed: 06/17/2023]
Abstract
Gas microleakage, which results in gas diffusion and accumulation in domestic gas appliances, is the leading cause of indoor gas explosion accidents. To research the diffusion and accumulation characteristics of microleakage gas in domestic gas appliances, this study took an integrated stove as the research object and analyzed the effects of different leakage rates and leakage locations on the diffusion and accumulation characteristics of microleakage liquefied petroleum gas (LPG) in its interior using the computational fluid dynamics (CFD) numerical simulation method. The results show that microleakage LPG is characterized by a downward diffusion flow driven by gravity and the concentration inside the integrated stove cavity generally increases with the increase of leakage time; however, the spatial distribution is extremely inhomogeneous. In addition, the volume of the dangerous area rapidly changes with the continuous accumulation of microleakage LPG, occupying more than 50% of the cavity volume. Microleakage LPG diffusion and accumulation process are highly similar under different leakage rates; on the contrary, the location of the leakage source is closely related to the diffusion and accumulation characteristics. The diffusion distribution and accumulation position of microleakage LPG at different leakage locations present obvious differences. Typically, there is a concentration difference of 0.1-0.2% between the top and the bottom when the leakage source is located above the gas stove baffle and a concentration difference of 1.0-1.3% between the top and the bottom when the leakage source is located below the gas stove baffle. In addition, the difference in the leakage location has a significant impact on the time the concentration of LPG reaches the critical concentration, which indicates that the combustion and explosion risk of different leakage locations are highly related to the leakage time. The research can provide certain technical support for microleakage gas explosion accident prevention.
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Affiliation(s)
- Kan Jin
- College
of Quality & Safety Engineering, China
Jiliang University, Hangzhou, Zhejiang 310018, China
- Zhejiang
Institute of Product Quality and Safety Science, Hangzhou, Zhejiang 310018, China
- Institute
of Process Equipment, College of Energy Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
- State
Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo, Henan 454000, China
| | - Gaofan Lin
- College
of Quality & Safety Engineering, China
Jiliang University, Hangzhou, Zhejiang 310018, China
| | - Qi Zhao
- Zhejiang
Institute of Product Quality and Safety Science, Hangzhou, Zhejiang 310018, China
| | - Yajing Liu
- Ministry
of Production Safety Supervision, Zhejiang
Provincial Energy Group Company Ltd., Hangzhou, Zhejiang 310007, China
| | - Jia Qiu
- Zhejiang
Institute of Product Quality and Safety Science, Hangzhou, Zhejiang 310018, China
| | - Yong Jiang
- Zhejiang
Institute of Product Quality and Safety Science, Hangzhou, Zhejiang 310018, China
| | - Dongmei Huang
- College
of Quality & Safety Engineering, China
Jiliang University, Hangzhou, Zhejiang 310018, China
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18
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Yuan H, Qiu J, Chiu KWH, Chan LWC, Zhang F, Wei X, Jiang L. PET/CT morphology and cardiac conduction disorders help discriminate primary cardiac lymphoma from primary cardiac sarcoma. J Nucl Cardiol 2022; 29:2866-2877. [PMID: 35790691 DOI: 10.1007/s12350-022-03042-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/09/2022] [Indexed: 01/18/2023]
Abstract
BACKGROUND Primary cardiac lymphoma (PCL) and primary cardiac sarcoma (PCS) are similar in clinical presentation but differ in management and outcomes. We aim to explore the role of PET morphology and clinical characteristics in distinguishing PCL from PCS. METHODS Pretreatment 18F-FDG PET/CT and contrast-enhanced CT were performed in PCL (n = 14) and PCS (n = 15) patients. Patient demographics, overall survival, and progression-free survival were reviewed. PET/CT morphological and metabolic features were extracted. Specifically, R_Kurtosis, a PET-morphology parameter reflecting the tumor expansion within the heart, was calculated. RESULTS Compared with PCS, PCL occurred at an older age, resulted in more cardiac dysfunctions and arrhythmias, and showed higher glucometabolism (SUVmax, SUVpeak, SUVmean, MTV, and TLG). Curative treatments improved survival for PCL but not for PCS. Multivariable logistic regression identified R_Kurtosis (OR = 27.025, P = .007) and cardiac conduction disorders (OR = 37.732, P = .016) independently predictive of PCL, and classification and regression tree analysis stratified patients into three subgroups: R_Kurtosis ≥ 0.044 (probability of PCL 88.9%), R_Kurtosis < 0.044 with conduction disorders (80.0%), and R_Kurtosis < 0.044 without conduction disorders (13.3%). CONCLUSION PET-derived tumor expansion pattern (R_Kurtosis) and cardiac conduction disorders were helpful in distinguishing PCL from PCS, which might assist the clinical management.
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Affiliation(s)
- Hui Yuan
- PET Center, Department of Nuclear Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China
| | - Jia Qiu
- Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Keith W H Chiu
- Department of Diagnostic and Interventional Radiology, Kwong Wah Hospital, Hong Kong SAR, China
| | - Lawrence W C Chan
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Fen Zhang
- Department of Pathology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiaojuan Wei
- Division of Lymphoma, Department of Clinical Oncology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China.
| | - Lei Jiang
- PET Center, Department of Nuclear Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China.
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
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19
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Chen X, Zhou S, Qiu J, Chen L, Xu Z, Ji M, Guo J, Zhang R. [Application of the "virtual-real combination" experimental teaching model in Human Parasitology teaching: a case study of comprehensive schistosome experiments]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2022; 35:180-183. [PMID: 37253568 DOI: 10.16250/j.32.1374.2022199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Information technology has become an important driver to facilitate higher education developments in the context of new medical sciences. A new "virtual-real combination" experimental teaching model was designed and created through integrating information technology with experimental teaching by Experimental Teaching Center of Basic Medical Sciences and Department of Pathogen Biology, Nanjing Medical University and was applied in Human Parasitology teaching, which achieved satisfactory teaching effectiveness. This new model showed effective to deepen the understanding of the basic human parasitology knowledge, improve the operative skills, and cultivate the moral literacy and comprehensive capability among medical students. This report presents the teaching protocols and implementation, teaching effectiveness and evaluation, and experiences of comprehensive schistosome experiments.
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Affiliation(s)
- X Chen
- Department of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing, Jiangsu 211166, China
| | - S Zhou
- Department of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing, Jiangsu 211166, China
| | - J Qiu
- Department of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing, Jiangsu 211166, China
| | - L Chen
- Department of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing, Jiangsu 211166, China
| | - Z Xu
- Department of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing, Jiangsu 211166, China
| | - M Ji
- Department of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing, Jiangsu 211166, China
| | - J Guo
- Personnel Department, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - R Zhang
- Experimental Teaching Center of Basic Medical Sciences, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
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20
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Xie X, Lu W, Qiu J, Cheng Z. Metabolic and Textural Changes in the Brain of Lung Cancer Patients: A Total-Body PET/CT Study. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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21
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Lin YW, Huang JL, Wei XB, Jiang M, Ran P, Li J, Qiu J, Zhong Q, Zhou YL, Chen JY, Yu DQ. Estimated glomerular filtration rate derived from different formulas and prognosis in acute coronary syndrome: Findings from the improving care for cardiovascular disease in China-acute coronary syndrome project. Am J Med Sci 2022; 364:565-574. [PMID: 35660542 DOI: 10.1016/j.amjms.2021.10.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 06/02/2021] [Accepted: 10/21/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND The optimal formula for the estimation of glomerular filtration rate (GFR) in patients with acute coronary syndrome (ACS) in terms of predicting in-hospital mortality and adverse events remains unclear. METHODS A nationwide registry study, Improving CCC (Care for Cardiovascular Disease in China) ACS project, was launched in 2014 as a collaborative study of the American Heart Association and Chinese Society of Cardiology. The Cockcroft-Gault, modification of diet in renal disease (MDRD) formula for Chinese (C-MDRD), Mayo, and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas were used to calculate estimated GFR in 61,545 ACS patients (38,734 with ST-segment elevation myocardial infarction [STEMI] and 22,811 with non-ST-segment-elevation ACS [NSTE-ACS]). RESULTS Prevalence of moderate to severe renal dysfunction was inconsistent among four formulas, ranging from 11.6% to 22.4% in NSTE-ACS and from 8.3% to 16.8% in STEMI, respectively. The in-hospital mortality rate in patients with ACS was inversely associated with estimated GFR. In STEMI, the Mayo-derived eGFR exhibited the highest predictive power for in-hospital death compared with the Cockcroft-Gault-derived eGFR (area under the curve [AUC]: 0.782 vs. 0.768, p=0.004), C-MDRD-derived eGFR (AUC: 0.782 vs. 0.740, p<0.001) and CKD-EPI-derived eGFR (AUC: 0.782 vs. 0.767, p<0.001). In NSTE-ACS, the Mayo-derived eGFR exhibited a similar predictive value with the Cockcroft-Gault (AUC: 0.781 vs. 0.787, p>0.05) and CKD-EPI-derived eGFR (AUC: 0.781 vs. 0.784, p>0.05). CONCLUSIONS The Mayo formula was superior to Cockcroft-Gault, C-MDRD, and CKD-EPI formulas for predicting in-hospital mortality in ACS patients, especially for STEMI. The Mayo-derived eGFR may serve as a risk-stratification tool for in-hospital adverse events in ACS patients. CLINICAL TRIAL REGISTRATION URL: http://www. CLINICALTRIALS gov. Unique identifier: NCT02306616.
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Affiliation(s)
- Ying-Wen Lin
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China; Shantou University Medical College, Shantou 515000, China
| | - Jie-Leng Huang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China; Southern Medical University, Guangzhou 510515, China
| | - Xue-Biao Wei
- Southern Medical University, Guangzhou 510515, China; Department of Critical Care Medicine, Guangdong Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Mei Jiang
- Southern Medical University, Guangzhou 510515, China; Department of Critical Care Medicine, Guangdong Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Peng Ran
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Jie Li
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Jia Qiu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Qi Zhong
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Ying-Ling Zhou
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Ji-Yan Chen
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.
| | - Dan-Qing Yu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.
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22
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Abstract
It is generally believed that marsupials are more primitive than placentals mammals and mainly solitary living, representing the ancestral form of social organization of all mammals. However, field studies have observed pair and group-living in marsupial species, but no comparative study about their social evolution was ever done. Here, we describe the results of primary literature research on marsupial social organization which indicates that most species can live in pairs or groups and many show intra-specific variation in social organization. Using Bayesian phylogenetic mixed-effects models with a weak phylogenetic signal of 0.18, we found that solitary living was the most likely ancestral form (35% posterior probability), but had high uncertainty, and the combined probability of a partly sociable marsupial ancestor (65%) should not be overlooked. For Australian marsupials, group-living species were less likely to be found in tropical rainforest, and species with a variable social organization were associated with low and unpredictable precipitation representing deserts. Our results suggest that modern marsupials are more sociable than previously believed and that there is no strong support that their ancestral state was strictly solitary living, such that the assumption of a solitary ancestral state of all mammals may also need reconsideration.
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Affiliation(s)
- J. Qiu
- School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, WITS 2050, Johannesburg, South Africa
- IPHC, UNISTRA, CNRS, 23 rue du Loess, 67200 Strasbourg, France
| | - C. A. Olivier
- School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, WITS 2050, Johannesburg, South Africa
- IPHC, UNISTRA, CNRS, 23 rue du Loess, 67200 Strasbourg, France
| | - A. V. Jaeggi
- Institute of Evolutionary Medicine, University of Zurich, Wintherthurerstrasse 190, 8057 Zurich, Switzerland
| | - C. Schradin
- School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, WITS 2050, Johannesburg, South Africa
- IPHC, UNISTRA, CNRS, 23 rue du Loess, 67200 Strasbourg, France
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23
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Qiu J, Xu Y, Su S, Gao Y, Yu P, Ruan Z, Liao K. Auto Machine Learning Assisted Preparation of Carboxylic Acid by
TEMPO
‐catalyzed Primary Alcohol Oxidation. CHINESE J CHEM 2022. [DOI: 10.1002/cjoc.202200555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jia Qiu
- Guangdong Laboratory Animals Monitoring Institute, Guangdong Provincial Key Laboratory of Laboratory Animals Guangzhou 510663 Guangdong Province P.R. China
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, the NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital Guangzhou Medical University Guangzhou 511436 P.R. China
- Bioland Laboratory Guangzhou 510005 Guangdong Province P.R. China
| | - Yougen Xu
- Bioland Laboratory Guangzhou 510005 Guangdong Province P.R. China
| | - Shimin Su
- Bioland Laboratory Guangzhou 510005 Guangdong Province P.R. China
| | - Yadong Gao
- Bioland Laboratory Guangzhou 510005 Guangdong Province P.R. China
| | - Peiyuan Yu
- Department of Chemistry Southern University of Science and Technology Shenzhen 518055 Guangdong Province P.R. China
| | - Zhixiong Ruan
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, the NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital Guangzhou Medical University Guangzhou 511436 P.R. China
| | - Kuangbiao Liao
- Guangdong Laboratory Animals Monitoring Institute, Guangdong Provincial Key Laboratory of Laboratory Animals Guangzhou 510663 Guangdong Province P.R. China
- Bioland Laboratory Guangzhou 510005 Guangdong Province P.R. China
- Guangzhou Laboratory Guangzhou 510320 Guangdong Province P.R. China
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24
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Li W, Kang Z, Li S, Lin Y, Li Y, Mao Y, Zhang J, Lei T, Wang H, Su Y, Yang Y, Qiu J. 302P A multicenter, open-label, dose-escalation (DE), first-in-human study of VEGFRs and CSF1R inhibitor SYHA1813 in patients (pts) with recurrent high-grade gliomas (HGG) or advanced solid tumors. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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25
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Qiu J, Zhang Q, Tan Y, Duan Q, Qi C, Sun T. 769P Analysis of PMS2 mutation as a potential biomarker for melanoma immunotherapy. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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26
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Qiu J, Xie J, Su S, Gao Y, Meng H, Yang Y, Liao K. Selective functionalization of hindered meta-C–H bond of o-alkylaryl ketones promoted by automation and deep learning. Chem 2022. [DOI: 10.1016/j.chempr.2022.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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27
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Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, Adler S, Alexopoulos GS, Anagnostou E, Areces-Gonzalez A, Astle DE, Auyeung B, Ayub M, Bae J, Ball G, Baron-Cohen S, Beare R, Bedford SA, Benegal V, Beyer F, Blangero J, Blesa Cábez M, Boardman JP, Borzage M, Bosch-Bayard JF, Bourke N, Calhoun VD, Chakravarty MM, Chen C, Chertavian C, Chetelat G, Chong YS, Cole JH, Corvin A, Costantino M, Courchesne E, Crivello F, Cropley VL, Crosbie J, Crossley N, Delarue M, Delorme R, Desrivieres S, Devenyi GA, Di Biase MA, Dolan R, Donald KA, Donohoe G, Dunlop K, Edwards AD, Elison JT, Ellis CT, Elman JA, Eyler L, Fair DA, Feczko E, Fletcher PC, Fonagy P, Franz CE, Galan-Garcia L, Gholipour A, Giedd J, Gilmore JH, Glahn DC, Goodyer IM, Grant PE, Groenewold NA, Gunning FM, Gur RE, Gur RC, Hammill CF, Hansson O, Hedden T, Heinz A, Henson RN, Heuer K, Hoare J, Holla B, Holmes AJ, Holt R, Huang H, Im K, Ipser J, Jack CR, Jackowski AP, Jia T, Johnson KA, Jones PB, Jones DT, Kahn RS, Karlsson H, Karlsson L, Kawashima R, Kelley EA, Kern S, Kim KW, Kitzbichler MG, Kremen WS, Lalonde F, Landeau B, Lee S, Lerch J, Lewis JD, Li J, Liao W, Liston C, Lombardo MV, Lv J, Lynch C, Mallard TT, Marcelis M, Markello RD, Mathias SR, Mazoyer B, McGuire P, Meaney MJ, Mechelli A, Medic N, Misic B, Morgan SE, Mothersill D, Nigg J, Ong MQW, Ortinau C, Ossenkoppele R, Ouyang M, Palaniyappan L, Paly L, Pan PM, Pantelis C, Park MM, Paus T, Pausova Z, Paz-Linares D, Pichet Binette A, Pierce K, Qian X, Qiu J, Qiu A, Raznahan A, Rittman T, Rodrigue A, Rollins CK, Romero-Garcia R, Ronan L, Rosenberg MD, Rowitch DH, Salum GA, Satterthwaite TD, Schaare HL, Schachar RJ, Schultz AP, Schumann G, Schöll M, Sharp D, Shinohara RT, Skoog I, Smyser CD, Sperling RA, Stein DJ, Stolicyn A, Suckling J, Sullivan G, Taki Y, Thyreau B, Toro R, Traut N, Tsvetanov KA, Turk-Browne NB, Tuulari JJ, Tzourio C, Vachon-Presseau É, Valdes-Sosa MJ, Valdes-Sosa PA, Valk SL, van Amelsvoort T, Vandekar SN, Vasung L, Victoria LW, Villeneuve S, Villringer A, Vértes PE, Wagstyl K, Wang YS, Warfield SK, Warrier V, Westman E, Westwater ML, Whalley HC, Witte AV, Yang N, Yeo B, Yun H, Zalesky A, Zar HJ, Zettergren A, Zhou JH, Ziauddeen H, Zugman A, Zuo XN, Bullmore ET, Alexander-Bloch AF. Brain charts for the human lifespan. Nature 2022; 604:525-533. [PMID: 35388223 PMCID: PMC9021021 DOI: 10.1038/s41586-022-04554-y] [Citation(s) in RCA: 372] [Impact Index Per Article: 186.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/16/2022] [Indexed: 02/02/2023]
Abstract
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Affiliation(s)
- R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - J Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
| | - S R White
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - K M Anderson
- Department of Psychology, Yale University, New Haven, CT, USA
| | - C Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S Adler
- UCL Great Ormond Street Institute for Child Health, London, UK
| | - G S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - E Anagnostou
- Department of Pediatrics University of Toronto, Toronto, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - A Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- University of Pinar del Río "Hermanos Saiz Montes de Oca", Pinar del Río, Cuba
| | - D E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - B Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - M Ayub
- Queen's University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
- University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, UK
| | - J Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - S Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - R Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S A Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - V Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - J Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - M Borzage
- Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J F Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
| | - N Bourke
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, Dementia Research Institute, London, UK
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - M M Chakravarty
- McGill University, Montreal, Quebec, Canada
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - C Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - C Chertavian
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - G Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Y S Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J H Cole
- Centre for Medical Image Computing (CMIC), University College London, London, UK
- Dementia Research Centre (DRC), University College London, London, UK
| | - A Corvin
- Department of Psychiatry, Trinity College, Dublin, Ireland
| | - M Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- Undergraduate program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
- Autism Center of Excellence, University of California, San Diego, San Diego, CA, USA
| | - F Crivello
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
| | - V L Cropley
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - J Crosbie
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - N Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Instituto Milenio Intelligent Healthcare Engineering, Santiago, Chile
| | - M Delarue
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - R Delorme
- Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, France
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - S Desrivieres
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - G A Devenyi
- Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M A Di Biase
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, London, UK
| | - K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - G Donohoe
- Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - K Dunlop
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, London, UK
| | - J T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - C T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - J A Elman
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - L Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - D A Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - E Feczko
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, and Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - P Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - C E Franz
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - A Gholipour
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - J Giedd
- Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - J H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - D C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P E Grant
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - F M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - C F Hammill
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Mouse Imaging Centre, Toronto, Ontario, Canada
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - T Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - R N Henson
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - K Heuer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Université de Paris, Paris, France
| | - J Hoare
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - B Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, India
- Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, India
| | - A J Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - R Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - K Im
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Ipser
- Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A P Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- National Institute of Developmental Psychiatry, Beijing, China
| | - T Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - K A Johnson
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - P B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - D T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R S Kahn
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - H Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - L Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - R Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - E A Kelley
- Queen's University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
| | - S Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - K W Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea
| | - M G Kitzbichler
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - W S Kremen
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - F Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - B Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - S Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - J Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - W Liao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - C Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - M V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - J Lv
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- School of Biomedical Engineering and Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - C Lynch
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - T T Mallard
- Department of Psychology, University of Texas, Austin, TX, USA
| | - M Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - R D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - B Mazoyer
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - P McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A Mechelli
- Bordeaux University Hospital, Bordeaux, France
| | - N Medic
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - D Mothersill
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
- School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - J Nigg
- Department of Psychiatry, School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - M Q W Ong
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - C Ortinau
- Department of Pediatrics, Washington University in St Louis, St Louis, MO, USA
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - M Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L Palaniyappan
- Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | - L Paly
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - P M Pan
- Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - M M Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - T Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Z Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - D Paz-Linares
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- Cuban Neuroscience Center, Havana, Cuba
| | - A Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - K Pierce
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - X Qian
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - A Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - A Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - T Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Rodrigue
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - C K Rollins
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - R Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - L Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - M D Rosenberg
- Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - D H Rowitch
- Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry (INPD), São Paulo, Brazil
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - H L Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany
| | - R J Schachar
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - A P Schultz
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - G Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- PONS-Centre, Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus Mitte, Berlin, Germany
| | - M Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen's Square Institute of Neurology, University College London, London, UK
| | - D Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, UK Dementia Research Institute, London, UK
| | - R T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - I Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - C D Smyser
- Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - R A Sperling
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - D J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - G Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Y Taki
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - B Thyreau
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - R Toro
- Université de Paris, Paris, France
- Department of Neuroscience, Institut Pasteur, Paris, France
| | - N Traut
- Department of Neuroscience, Institut Pasteur, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - K A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - J J Tuulari
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - C Tzourio
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France
| | - É Vachon-Presseau
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | | | - P A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, Quebec, Canada
| | - S L Valk
- Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T van Amelsvoort
- Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, The Netherlands
| | - S N Vandekar
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Vasung
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - L W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - S Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - P E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - K Wagstyl
- Wellcome Centre for Human Neuroimaging, London, UK
| | - Y S Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - S K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - V Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - M L Westwater
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
- Faculty of Medicine, CRC 1052 'Obesity Mechanisms', University of Leipzig, Leipzig, Germany
| | - N Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - B Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - H Yun
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - A Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - J H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Ziauddeen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazil
| | - X N Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China
| | - E T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - A F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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Hu H, Xu C, Lai T, Yang Q, Peng X, Liu J, Xiong Y, Qiu J. Sub-Nanometer Accuracy Combination Processing Technology for Nickel–Phosphorus Modified Surfaces Based on Aluminum Reflector Mirror. Micromachines 2022; 13:mi13040560. [PMID: 35457865 PMCID: PMC9025228 DOI: 10.3390/mi13040560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/25/2022] [Accepted: 03/27/2022] [Indexed: 11/16/2022]
Abstract
The surface of metal mirrors is often polished by electroless coating with a Ni–P modified layer after single-point diamond turning. In practice, however, improvements in mirror quality are closely related to the polishing environment, polishing medium, and polishing force. If not adequately controlled, processing defects such as visible scratches can lead to the deterioration of surface roughness. Based on the Ni–P modified surface of a metal reflector mirror, this study optimizes the configuration of magnetorheological figuring (MRF) fluid and polishing process parameters so that MRF high-efficiency surface modification can be realized and the scratch problem can be resolved. The processing method of a high-performance metal mirror is developed by studying the high-efficiency and high-precision processing technology based on small head smoothing. The surface roughness achieved by the proposed method was better than Ra = 0.39 nm. The ultrasonic cleaning process effectively improved the surface roughness after processing. According to the combined processing technology developed in this study, the modified layer of the parabolic mirror with a diameter of 370 mm was processed, and the surface quality was increased from RMS = 338.684 nm to RMS = 21.267 nm.
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Affiliation(s)
- Hao Hu
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
| | - Chao Xu
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
| | - Tao Lai
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
- Correspondence: (T.L.); (X.P.)
| | - Qilin Yang
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
| | - Xiaoqiang Peng
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
- Correspondence: (T.L.); (X.P.)
| | - Junfeng Liu
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
| | - Yupeng Xiong
- Laboratory of Science and Technology on Integrated Logistics Support, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (H.H.); (C.X.); (Q.Y.); (J.L.); (Y.X.)
- Hunan Key Laboratory of Ultra-Precision Machining Technology, Changsha 410073, China
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
| | - Jia Qiu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410022, China;
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29
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Yang JQ, Ran P, Li J, Zhong Q, Smith SC, Wang Y, Fonarow GC, Qiu J, Morgan L, Wei XB, Chen XB, Huang JL, Hao YC, Zhou YL, Siu CW, Zhao D, Chen JY, Yu DQ. A Risk Stratification Scheme for In-Hospital Cardiogenic Shock in Patients With Acute Myocardial Infarction. Front Cardiovasc Med 2022; 9:793497. [PMID: 35310985 PMCID: PMC8931535 DOI: 10.3389/fcvm.2022.793497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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: 10/12/2021] [Accepted: 01/24/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveCardiogenic shock (CS) is the leading cause of death in patients with acute myocardial infarction (AMI) despite advances in care. This study aims to derive and validate a risk score for in-hospital development of CS in patients with AMI.MethodsIn this study, we used the Improving Care for Cardiovascular Disease in China–Acute Coronary Syndrome (CCC–ACS) registry of 76,807 patients for model development and internal validation. These patients came from 158 tertiary hospitals and 82 secondary hospitals between 2014 and 2019, presenting AMI without CS upon admission. The eligible patients with AMI were randomly assigned to derivation (n = 53,790) and internal validation (n = 23,017) cohorts. Another cohort of 2,205 patients with AMI between 2014 and 2016 was used for external validation. Based on the identified predictors for in-hospital CS, a new point-based CS risk scheme, referred to as the CCC–ACS CS score, was developed and validated.ResultsA total of 866 (1.1%) and 39 (1.8%) patients subsequently developed in-hospital CS in the CCC–ACS project and external validation cohort, respectively. The CCC–ACS CS score consists of seven variables, including age, acute heart failure upon admission, systolic blood pressure upon admission, heart rate, initial serum creatine kinase-MB level, estimated glomerular filtration rate, and mechanical complications. The area under the curve for in-hospital development of CS was 0.73, 0.71, and 0.85 in the derivation, internal validation and external validation cohorts, respectively.ConclusionThis newly developed CCC–ACS CS score can quantify the risk of in-hospital CS for patients with AMI, which may help in clinical decision making.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier: NCT02306616.
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Affiliation(s)
- Jun-qing Yang
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Peng Ran
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jie Li
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Qi Zhong
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Sidney C. Smith
- Division of Cardiology, University of North Carolina, Chapel Hill, NC, United States
| | - Yan Wang
- Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Ministry of Education, Shanghai, China
| | - Gregg C. Fonarow
- Division of Cardiology, Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA, United States
| | - Jia Qiu
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Louise Morgan
- International Quality Improvement Department, American Heart Association, Dallas, TX, United States
| | - Xue-biao Wei
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiao-bo Chen
- Department of Pediatrics, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jie-leng Huang
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yong-chen Hao
- Department of Epidemiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China
| | - Ying-ling Zhou
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Chung-Wah Siu
- Cardiology Division, Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Dong Zhao
- Department of Epidemiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China
| | - Ji-yan Chen
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Ji-yan Chen
| | - Dan-qing Yu
- Guangdong Provincial Key Laboratory of Coronary Heart Disease, Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- *Correspondence: Dan-qing Yu
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Guo X, Li Z, Yang JP, Hu JY, Huang ZY, Qiu J, Ma XY, Duan JF, Sun XD. [Enlightment of routine vaccination under the prevention and control of COVID-19 based on the circulating event of type Ⅲ vaccine-derived poliovirus in Shanghai]. Zhonghua Yu Fang Yi Xue Za Zhi 2021; 55:1377-1382. [PMID: 34963232 DOI: 10.3760/cma.j.cn112150-20210809-00772] [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: 06/14/2023]
Abstract
Since the Global Polio Eradication Initiative was launched by the World Health Assembly in 1988, significant progress has been made in global polio prevention and control. But the occurrence of vaccine-associated paralytic poliomyelitis cases and vaccine-derived poliovirus related cases have become a major challenge during the post-polio era. While coronavirus disease 2019(COVID-19) has brought serious disease burden and economic burden to all countries in the world, prevention and control of vaccine-preventable infectious diseases such as polio should not be neglected under the background of the global common fight against COVID-19. Taking the type Ⅲ VDPV cycle event in Shanghai as an example, the paper discussed how to do a good job of routine inoculation under the prevention and control of COVID-19 to strictly prevent the outbreak of vaccine-preventable infectious diseases.
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Affiliation(s)
- X Guo
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Z Li
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J P Yang
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Y Hu
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Z Y Huang
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Qiu
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - X Y Ma
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J F Duan
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
| | - X D Sun
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
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31
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Quintanal-Villalonga A, Taniguchi H, Zhan Y, Hasan M, Chavan S, Uddin F, Allaj V, Manoj P, Shah N, Chan J, Chow A, Offin M, Bhanot U, Egger J, Qiu J, De Stanchina E, Chang J, Rekhtman N, Houck-Loomis B, Koche R, Yu H, Sen T, Rudin C. MA11.06 Multi-Omic Characterization of Lung Tumors Implicates AKT and MYC Signaling in Adenocarcinoma to Squamous Cell Transdifferentiation. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.08.167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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32
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Quintanal-Villalonga A, Taniguchi H, Hao Y, Chow A, Zhan Y, Chavan S, Uddin F, Allaj V, Manoj P, Shah N, Chan J, Offin M, Egger J, Bhanot U, Qiu J, De Stanchina E, Sen T, Poirier J, Rudin C. MA16.03 CRISPR Screen Reveals XPO1 as a Therapeutic Target Strongly Sensitizing to First and Second Line Therapy in Small Cell Lung Cancer. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.08.196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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33
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de Groot M, Anderson H, Bauer H, Bauguil C, Bellone RR, Brugidou R, Buckley RM, Dovč P, Forman O, Grahn RA, Kock L, Longeri M, Mouysset‐Geniez S, Qiu J, Sofronidis G, van der Goor LHP, Lyons LA. Standardization of a SNP panel for parentage verification and identification in the domestic cat (Felis silvestris catus). Anim Genet 2021; 52:675-682. [PMID: 34143521 PMCID: PMC8519126 DOI: 10.1111/age.13100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2021] [Indexed: 01/02/2023]
Abstract
The domestic cat (Felis silvestris catus) is a valued companion animal throughout the world. Over 60 different cat breeds are accepted for competition by the cat fancy registries in different countries. Genetic markers, including short tandem repeats and SNPs, are available to evaluate and manage levels of inbreeding and genetic diversity, population and breed structure relationships, and individual identification for forensic and registration purposes. The International Society of Animal Genetics (ISAG) hosts the Applied Genetics in Companion Animals Workshop, which supports the standardization of genetic marker panels and genotyping for the identification of cats via comparison testing. SNP panels have been in development for many species, including the domestic cat. An ISAG approved core panel of SNPs for use in cat identification and parentage analyses is presented. SNPs (n = 121) were evaluated by different university-based and commercial laboratories using 20 DNA samples as part of the ISAG comparison testing procedures. Different SNP genotyping technologies were examined, including DNA arrays, genotyping-by-sequencing and mass spectroscopy, to select a robust and efficient panel of 101 SNPs as the ISAG core panel for cats. The SNPs are distributed across all chromosomes including two on the X chromosome and an XY pseudo-autosomal sexing marker (zinc-finger XY; ZFXY). A population study demonstrated that the markers have an average polymorphic information content of 0.354 and a power of exclusion greater than 0.9999. The SNP panel should keep testing affordable while also allowing for the development of additional panels to monitor health, phenotypic traits, hybrid cats and highly inbred cats.
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Affiliation(s)
- M. de Groot
- MolGenTraverse 2VeenendaalUtrecht3905NLThe Netherlands
| | | | - H. Bauer
- Laboklin GMBH & Co. KGBad Kissingen97688Germany
| | | | - R. R. Bellone
- Veterinary Genetics LaboratorySchool of Veterinary MedicineUniversity of CaliforniaDavisCA95616USA
- Population Health and ReproductionSchool of Veterinary MedicineUniversity of CaliforniaDavisCA95616USA
| | | | - R. M. Buckley
- Department of Veterinary Medicine and SurgeryCollege of Veterinary MedicineUniversity of MissouriColumbiaMO65211USA
| | - P. Dovč
- Department of Animal ScienceBiotechnical FacultyUniversity of LjubljanaLjubljana1000Slovenia
| | | | - R. A. Grahn
- Veterinary Genetics LaboratorySchool of Veterinary MedicineUniversity of CaliforniaDavisCA95616USA
| | - L. Kock
- Neogen GenomicsLincolnNE68504USA
| | - M. Longeri
- Department of Veterinary MedicineUniversity of MilanMilan20133Italy
| | | | - J. Qiu
- Neogen GenomicsLincolnNE68504USA
| | - G. Sofronidis
- Orivet Genetic Pet CareSuite St. KildaMelbourneVic.3182Australia
| | | | - L. A. Lyons
- Department of Veterinary Medicine and SurgeryCollege of Veterinary MedicineUniversity of MissouriColumbiaMO65211USA
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Quintanal-Villalonga Á, Taniguchi H, Hao Y, Chow A, Zhan Y, Uddin F, Allaj V, Manoj P, Shah N, Chan J, Offin M, Ciampricotti M, Egger J, Qiu J, De Stanchina E, Hollmann T, Koche R, Sen T, Poirier J, Rudin C. 2MO XPO1 inhibition strongly sensitizes to first-line and second-line therapy in small cell lung cancer. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.1998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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35
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Quintanal-Villalonga Á, Taniguchi H, Zhan Y, Hasan M, Chavan S, Uddin F, Allaj V, Manoj P, Shah N, Ciampricotti M, Bhanot U, Egger J, Qiu J, De Stanchina E, Rekhtman N, Houck-Loomis B, Koche R, Yu H, Sen T, Rudin C. 1MO Multi-omic characterization of lung tumors identify AKT and EZH2 as potential therapeutic targets in adenocarcinoma-to-squamous transdifferentiation. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.1997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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36
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Chen J, Wei W, Zheng L, Li H, Feng Y, Wan T, Huang Q, Liu G, Tu H, Qiu J, Jiang X, Xiong Y, Zheng M, Li J, Huang H, Song L, Liu J, Zhang Y. 732P Anlotinib plus pemetrexed in patients with platinum-resistant ovarian cancer: A single-arm, open-label, phase II study. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.1175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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37
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Quintanal-Villalonga Á, Taniguchi H, Zhan Y, Hasan M, Chavan S, Uddin F, Allaj V, Manoj P, Shah N, Chan J, Ciampricotti M, Chow A, Bhanot U, Egger J, Qiu J, De Stanchina E, Rekhtman N, Yu H, Sen T, Rudin C. 1800O Multi-omic characterization of lung tumors implicates AKT and MYC signaling in adenocarcinoma to squamous cell transdifferentiation. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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38
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Wang CX, Liu C, Qiu L, Qiu J, Yan CF, Wang NN, Wang HQ. [Control study of chest CT imaging features of aluminosis and silicosis patients]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2021; 39:534-537. [PMID: 34365767 DOI: 10.3760/cma.j.cn121094-20200904-00517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To understand the chest CT features of aluminosis caused by alumina and to improve the understanding of the imaging findings of alumina pneumoconiosis. Methods: The chest CT findings of 17 cases of alumina-induced pneumoconiosis and 30 cases of silicosis (the control group) diagnosed in Zibo Occupational Disease Prevention Hospital from April 2015 to July 2020 were analyzed retrospectively. The characteristics of fibrosis of the two kinds of pneumoconiosis and the incidence of size, density, distribution, tractive bronchiectasis, pleural thickening and interlobular septal thickening of pneumoconiosis nodules were compared. Results: Alumina pneumoconiosis showed nodules with thickened interlobular septal of 66.67% (12/18) , honeycomb lung of 22.22% (4/18) , ground glass shadow of 61.11% (11/18) , simple nodules of 11.11% (2/18) , and no fusion mass. In the control group, the long-line fibrosis of nodules with thickened interlobular septal were 16.67% (5/30) , 6.67% (2/30) with honeycomb lung and ground glass density shadow, 23.33% (7/30) with fusion mass and 53.33% (16/30) with simple nodule. There were significant differences in CT findings of nodules with thickened interlobular septal, ground glass density shadow, fused mass and simple nodules between the two groups (P<0.05) . The interstitial beaded nodules were seen in 18 cases of alumina pneumoconiosis, 50.00% (9/18) of them were beaded nodules, 61.33% (46/75) of low density nodules and 38.89% (7/18) of central lobular nodules were seen in alumina pneumoconiosis. The average width of nodules was (1.29±0.38) mm. Central lobular nodules were seen in all 30 cases of silicosis, 10.00% (3/30) were mainly beaded nodules, low density nodules were 36.29% (90/248) , and the average width diameter of nodules was (1.85±0.58) mm. There were significant differences between the two groups (P<0.05) . Alumina pneumoconiosis was often accompanied by traction bronchiectasis, pleural thickening and interlobular septal thickening (11, 18, 17 cases, 61.11%, 100.00%, 94.44%) , compared with the control group (9, 18, 18 cases, 30.00%, 60.00%, 60.00%) . The differences were statistically significant (P<0.05) . The maximum CT value of noncalcified mediastinal lymphnodes in alumina pneumoconiosis was (103.43±26.33) HU, which was higher than that of the control group[ (75.22±16.70) HU], and the difference was statistically significant (P<0.05) . Conclusion: Alumina pneumoconiosis chest CT shows slightly low-density beaded nodules, thickened interlobular septal, and pulmonary interstitial fibrosis of ground-glass shadows, mostly combines with stretched bronchiectasis, thickened pleura, and mediastinum increased lymph node density.
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Affiliation(s)
- C X Wang
- Zibo Occupational Disease Prevention Hospital, Zibo 255000, China
| | - C Liu
- Shandong Medical Imaging Research Institute, Jinan 250021, China
| | - L Qiu
- Zibo Occupational Disease Prevention Hospital, Zibo 255000, China
| | - J Qiu
- Zibo Occupational Disease Prevention Hospital, Zibo 255000, China
| | - C F Yan
- Zibo Occupational Disease Prevention Hospital, Zibo 255000, China
| | - N N Wang
- Zibo Occupational Disease Prevention Hospital, Zibo 255000, China
| | - H Q Wang
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China
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39
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Affiliation(s)
- L J Zhao
- Hemodialysis Center, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
| | - X L Sun
- Hemodialysis Center, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
| | - J Qiu
- Hemodialysis Center, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
| | - B L Xiao
- Hemodialysis Center, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
| | - X Y Fan
- Hemodialysis Center, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
| | - T Wang
- Hemodialysis Center, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
| | - C L Li
- Department of Endocrinology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, China
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40
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Zhu H, Sha Y, Wu W, Chen R, Yang Y, Qiu J, Mi H, Peng C, Ding C, Wang Z, Fan L, Xu W, Li J. ZANUBRUTINIB, LENALIDOMIDE PLUS R‐CHOP (ZR
2
‐CHOP) AS THE TREATMENT FOR DIFFUSED LARGE B‐CELL LYMPHOMA (DLBCL). Hematol Oncol 2021. [DOI: 10.1002/hon.49_2881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- H. Zhu
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
| | - Y. Sha
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
| | - W. Wu
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
| | - R. Chen
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
| | - Y. Yang
- Pukou division of Jiangsu Province Hospital Pukou CLL Center Nanjing China
| | - J. Qiu
- Pukou division of Jiangsu Province Hospital Pukou CLL Center Nanjing China
| | - H. Mi
- Pukou division of Jiangsu Province Hospital Pukou CLL Center Nanjing China
| | - C. Peng
- Pukou division of Jiangsu Province Hospital Pukou CLL Center Nanjing China
| | - C. Ding
- The First Affiliated Hospital of Nanjing Medical University Department of Nuclear Medicine Nanjing China
| | - Z. Wang
- The First Affiliated Hospital of Nanjing Medical University Department of Pathology Nanjing China
| | - L. Fan
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
| | - W. Xu
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
| | - J. Li
- The First Affiliated Hospital of Nanjing Medical University Department of Hematology Nanjing China
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Long Y, Qiu J, Zhang B, He P, Shi X, He Q, Chen Z, Shen W, Li Z, Zhang X. Pharmacological Vitamin C Treatment Impedes the Growth of Endogenous Glutamine-Dependent Cancers by Targeting Glutamine Synthetase. Front Pharmacol 2021; 12:671902. [PMID: 34054545 PMCID: PMC8150514 DOI: 10.3389/fphar.2021.671902] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 03/29/2021] [Indexed: 11/21/2022] Open
Abstract
Purpose: Glutamine synthetase (GS) is the only currently known enzyme responsible for synthesizing endogenous glutamine (Gln). GS exerts a critical role in the oncogenesis of endogenous Gln-dependent cancers, making it an attractive target for anti-tumor therapies. A mixed-function oxidation system consisting of vitamin C (VC), oxygen, and trace metals can oxidize GS and promote its degradation. The current study aims to explore the effect of pharmacological VC treatment on GS. Methods: Endogenous Gln-dependent cancer lines (breast cancer MCF7 and prostate cancer PC3) were selected to establish chronic Gln-deprived MCF7 and PC3 cell models. The expression of GS in parental and chronic Gln-deprived tumor cells exposed to VC treatment and control was determined by Western blot analysis. The anti-cancer effects of VC on parental and chronic Gln-deprived tumor cells were assessed by CCK-8 and annexin V-FITC/PI FACS assays. In addition, changes in cellular reactive oxygen species (ROS), glutathione (GSH) levels and NADPH/NADP + ratio were analyzed to explore the underlying mechanisms. Moreover, BALB/c nude mice xenografting with parental and chronic Gln-deprived prostate cancer cells were constructed to evaluate the in vivo therapeutic effect of VC. Finally, tumor 13N-ammonia uptake in mice bearing prostate cancer xenografts was analyzed following treatment with VC and the expression of GS in xenografts were detected by immunohistochemistry. Results: Cells overexpressing GS were obtained by chronic Gln deprivation. We found that the cytotoxic effect of VC on cancer cells was positively correlated with the expression of GS. Additionally, VC treatment led to a significant increase in ROS production, as well as GSH depletion and NADPH/NADP + reduction. These changes could be reversed by the antioxidant N-acetyl-L-cysteine (NAC). Furthermore, pharmacological VC treatment exhibited a more significant therapeutic effect on xenografts of prostate cancer cells overexpressing GS, that could be well monitored by 13N-ammonia PET/CT imaging. Conclusion: Our findings indicate that VC can kill cancer cells by targeting glutamine synthetase to induce oxidative stress. VC could be used as an anti-cancer treatment for endogenous glutamine-dependent cancers.
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Affiliation(s)
- Yali Long
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Jia Qiu
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Bing Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Peng He
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xinchong Shi
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Qiao He
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhifeng Chen
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wanqing Shen
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhoulei Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiangsong Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Chan L, Qiu J. Practical cell counting method selection to increase the quality of cell counting results. Cytotherapy 2021. [DOI: 10.1016/s146532492100534x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Bell J, Huang Y, Yung S, Qazi H, Hernandez C, Qiu J, Chan L. High-speed and high-precision fluorescence-based cell count and viability assays using the Cellaca™ MX high-throughput cell counter. Cytotherapy 2021. [DOI: 10.1016/s1465324921004242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Bell J, Huang Y, Hoover W, Kuksin D, Qiu J, Chan L. Improved inter-instrument consistency and high precision for cho cell bioprocessing using the Cellaca™ MX high-throughput cell counter. Cytotherapy 2021. [DOI: 10.1016/s1465324921004412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Bai F, Wang DY, Fan YJ, Qiu J, Wang L, Dai Y, Song L. Assisted reproductive technology service availability, efficacy and safety in mainland China: 2016. Hum Reprod 2021; 35:446-452. [PMID: 32020190 DOI: 10.1093/humrep/dez245] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 09/19/2019] [Indexed: 11/14/2022] Open
Abstract
STUDY QUESTION What is the current status of assisted reproductive technology (ART) service availability, efficacy and safety in mainland China? SUMMARY ANSWER In this first national report on ART status in mainland China, data on treatment numbers, outcomes and complications in 2016 are provided and analyzed, respectively. WHAT IS KNOWN ALREADY National ART Service Provision Surveys are conducted in mainland China regularly. Data were analyzed, and this manuscript was written by team members from the National Center for Women and Children's Health, China CDC and the Department of Women and Children Health, National Health Commission of the People's Republic of China. STUDY DESIGN, SIZE AND DURATION A cross-sectional nationwide survey was completed in 2018, in which data regarding ART treatments, performed from 1st January to 31st December2016 in 445 ART clinics located in 31 provinces of mainland China, were collected. PARTICIPANTS/MATERIALS, SETTING AND METHODS There were in total 451 licensed ART clinics (including artificial insemination clinics) in mainland China in 2016, of which 445 submitted service data. A total of 906 840 cycles were provided by 323 in vitro fertilization (IVF) clinics, involving 375 770 conventional IVF cycles, 154 948 intracytoplasmic sperm injection (ICSI) cycles, 367 146 frozen embryo transfer (FET) thawing cycles and 8976 preimplantation genetic diagnosis (PGD) treatment cycles. A total of 161 376 artificial (i.e. intrauterine) insemination (AI) cycles were reported by 443 clinics, with 126 872 cycles using the husband's semen (AIH) and 34 504 using donor semen (AID). MAIN RESULTS AND THE ROLE OF CHANCE In total, 98.7% of the licensed clinics, contributing to 100% of the ART services (including AID and AIH cycles), were included in this report. (Six clinics provided institutional information only and were excluded.) There were 906 840 in vitro fertilization cycles performed in mainland China with a population of over 1.3 billion inhabitants, with cycles per million inhabitants (C/M) increasing from 360 in 2013 to 657 in 2016, nationwide (range among provinces: 45-3676). After treatment with conventional IVF, the clinical pregnancy rate (PR) per oocyte retrieval cycle was 23.2%, the delivery rate (DR) per oocyte retrieval cycle was 18.7% and the proportion of twin delivery among the total deliveries was 27.9%. For ICSI cycles, the PR, DR and TDR were 20.5%, 16.7% and 27.2%, respectively. For FET per thawing cycles, the PR, DR and TDR were 48.2%, 37.6% and 24.2%. For PGD per diagnosis cycles, the PR, DR and TDR were 38.1%, 29.7% and 4.2%. For AIH cycles, the PR and DR were 13.3% and 10.5%; for AID cycles, the PR and DR were 24.3% and 21.1%, respectively. The total number of live infants born in mainland China in 2016, was 18.46 million, and the number of infants born through ART conducted in 2016 was 311 309, which accounted for 1.69% of the total. The reported rate of birth defects was about 87/10 000. The incidence of moderate to severe ovarian hyper-stimulation syndrome (OHSS) was 11.5 per 1000 oocyte retrieval cycles, and other complications were much more rare. LIMITATIONS AND REASONS FOR CAUTION This report is based on the summary data of ART services provided. The success rates were not calculated by age stratification. A low rate of birth defects was reported, which might be confounded by variations in birth follow-up methods, statistical timing and record taking. WIDER IMPLICATIONS OF THE FINDINGS ART service availability has improved significantly in recent years in mainland China. Because China is a vast country, significant imbalances in ART service provision do exist; however, the main efficacy and safety indicators were close to those of western countries. TRIAL REGISTRATION NUMBER N/A. STUDY FUNDING/COMPETING INTEREST(S) The study was funded by the National Key R&D Program of China (2016YFC1000307-2). There are no competing interests.
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Affiliation(s)
- F Bai
- ART Management Department, National Center for Women and Children's Health, China CDC, No.12 Dahuisi Road, Haidian District, Beijing 100081, China
| | - D Y Wang
- ART Management Department, National Center for Women and Children's Health, China CDC, No.12 Dahuisi Road, Haidian District, Beijing 100081, China
| | - Y J Fan
- ART Management Department, National Center for Women and Children's Health, China CDC, No.12 Dahuisi Road, Haidian District, Beijing 100081, China
| | - J Qiu
- Department of Women and Children Health, National Health Commission of the People's Republic of China, No.14 Zhichun Road, Haidian District, Beijing 100191, China
| | - L Wang
- Department of Women and Children Health, National Health Commission of the People's Republic of China, No.14 Zhichun Road, Haidian District, Beijing 100191, China
| | - Y Dai
- Department of Women and Children Health, National Health Commission of the People's Republic of China, No.14 Zhichun Road, Haidian District, Beijing 100191, China
| | - L Song
- Department of Women and Children Health, National Health Commission of the People's Republic of China, No.14 Zhichun Road, Haidian District, Beijing 100191, China
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Ren K, Sun J, Liu L, Yang Y, Li H, Wang Z, Deng J, Hou M, Qiu J, Zhao W. TP53-Activated lncRNA GHRLOS Regulates Cell Proliferation, Invasion, and Apoptosis of Non-Small Cell Lung Cancer by Modulating the miR-346/APC Axis. Front Oncol 2021; 11:676202. [PMID: 33968785 PMCID: PMC8097184 DOI: 10.3389/fonc.2021.676202] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 03/29/2021] [Indexed: 12/21/2022] Open
Abstract
Non-small cell lung cancer (NSCLC) is the main type of lung cancer with high mortality worldwide. To improve NSCLC therapy, the exploration of molecular mechanisms involved in NSCLC progression and identification of their potential therapy targeting is important. Long noncoding RNAs (lncRNAs) have shown important roles in regulating various tumors progression, including NSCLC. We found lncRNA GHRLOS was decreased in NSCLC cell lines and tissues which correlated with poor prognosis of NSCLC patients. However, the role and underlying mechanisms of lncRNA GHRLOS in NSCLC progression remains elusive. The expression of lncRNA GHRLOS was examined in NSCLC cell lines and biopsy specimens of patients with NSCLC by quantitative real time polymerase chain reaction (qRT-PCR). The effects of GHRLOS on proliferation, invasion and apoptosis of NSCLC cells were determined by both in vitro and in vivo experiments. The interaction between GHRLOS and TP53 was determined by dual-luciferase reporter assay and chromatin immunoprecipitation (ChIP) combined with qRT-PCR analysis. RNA immunoprecipitation (RIP) was conducted to validate the binding between GHRLOS and microRNA-346 (miR-346). Dual-luciferase reporter assays were also carried out to reveal the interaction between miR-346 and the 3’ untranslated region (3’UTR) of adenomatous polyposis coli (APC) mRNA.Our data demonstrated that overexpression of lncRNA GHRLOS suppressed cancer cell proliferation and invasion as well as promoted cell apoptosis by regulating the expression of CDK2, PCNA, E-cadherin, N-cadherin, Bax, and Bcl-2 in NSCLC cells. Moreover, lncRNA GHRLOS was upregulated by the binding of TP53 to the GHRLOS promoter. The binding target of lncRNA GHRLOS was identified to be miR-346. Impressively, overexpression of miR-346 promoted cell proliferation and invasion, as well as inhibited cell apoptosis, however, these effects can be blocked by overexpression of lncRNA GHRLOS both in vitro and in vivo. In summary, this study reveals lncRNA GHRLOS, upregulated by TP53, acts as a molecule sponge of miR-346 to cooperatively modulates expression of APC, a miR-346 target, and potentially inhibits NSCLC progression via TP53/lncRNA GHRLOS/miR-346/APC axis, which represents a novel pathway that could be useful in targeted therapy against NSCLC.
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Affiliation(s)
- Ke Ren
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China.,Development and Regeneration Key Laboratory of Sichuan Province, Chengdu Medical College, Chengdu, China
| | - Jinghui Sun
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China
| | - Lingling Liu
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China.,Development and Regeneration Key Laboratory of Sichuan Province, Chengdu Medical College, Chengdu, China
| | - Yuping Yang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Honghui Li
- Department of Refractive Surgery, Chengdu Aier Eye Hospital, Chengdu, China
| | - Zhichao Wang
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China
| | - Jingzhu Deng
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China
| | - Min Hou
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China
| | - Jia Qiu
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China
| | - Wei Zhao
- School of Laboratory Medicine/Sichuan Provincial Engineering Laboratory for Prevention and Control Technology of Veterinary Drug Residue in Animal-origin Food, Chengdu Medical College, Chengdu, China.,Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China
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Zang CS, Huang HT, Qiu J, Sun J, Ge RF, Jiang LW. MiR-224-5p targets EGR2 to promote the development of papillary thyroid carcinoma. Eur Rev Med Pharmacol Sci 2021; 24:4890-4900. [PMID: 32432752 DOI: 10.26355/eurrev_202005_21178] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Various microRNAs (miRNAs) have been reported to be involved in the pathogenesis and development of human cancers, including papillary thyroid carcinoma (PTC). However, the role of miR-224-5p in PTC progression remains unclear. Therefore, the purpose of this study is to illuminate the function of miR-224-5p in PTC. PATIENTS AND METHODS Expression of miR-224-5p and EGR2 was examined in PTC by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Transwell assay was used to detect cell migration and invasion. Western blot analysis was used to detect epithelial-mesenchymal transition (EMT). The relationship between miR-224-5p and EGR2 was confirmed by Dual-Luciferase assay. RESULTS Upregulation of miR-224-5p and downregulation of EGR2 expression were detected in PTC tissues and cells. Upregulation of miR-224-5p was found to be associated with TNM stage and lymph node metastasis. Meanwhile, it also predicted poor prognosis in PTC patients. Functionally, upregulation of miR-224-5p promoted cell metastasis and EMT in PTC. In addition, miR-224-5p was detected to directly target EGR2. EGR2 expression was negatively correlated with EGR2 expression in PTC. Of note, overexpression of EGR2 attenuated the carcinogenic effects of miR-224-5p in PTC. CONCLUSIONS MiR-224-5p promotes cell migration, invasion, and EMT in PTC by targeting EGR2.
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Affiliation(s)
- C-S Zang
- Department of Otolaryngology Head and Neck Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, P.R. China.
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Guo X, Qiu J, Sun XD. [Application of expert consensus to guide the vaccination of children with special health status]. Zhonghua Yu Fang Yi Xue Za Zhi 2021; 55:284-287. [PMID: 34645195 DOI: 10.3760/cma.j.cn112150-20201013-01275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Vaccination of children with special health status has become one of the urgent difficulties to be solved in provinces or regions with high immunization planning vaccination rate. The relevant consensus opinions on vaccination compiled by different expert teams have been issued in China, which provides an important basis for vaccinators to scientifically understand the necessity of vaccination and to study and judge the safety and effectiveness of vaccination. Based on the author's experience of participating in the compilation of a series of consensus on vaccination for children in special health status, this paper discusses how to objectively understand the role of expert consensus and puts forward some suggestions on the wider application of consensus in the future.
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Affiliation(s)
- X Guo
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Qiu
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - X D Sun
- Department of Immunization, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
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Wang W, Qiu J, Qu P, Chen H, Lan J, Chen H, Li L, Gu M. Regulator of cullins-1 (ROC1) negatively regulates the Gli2 regulator SUFU to activate the hedgehog pathway in bladder cancer. Cancer Cell Int 2021; 21:75. [PMID: 33499884 PMCID: PMC7836478 DOI: 10.1186/s12935-021-01775-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 01/16/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The regulator of cullins-1 (ROC1) is an essential subunit in the cullin-RING ligase (CRL) protein complex and has been shown to be critical in bladder cancer cell survival and progression. This study aimed to explore the molecular mechanism of ROC1 action in the malignant progression of bladder cancer. METHODS This study utilized ex vivo, in vitro, and in vivo nude mouse experiments to assess the underlying mechanisms of ROC1 in bladder cancer cells. The expression of the components of the sonic hedgehog (SHH) pathway was determined by western blot analysis. ROC1 expression in human tumors was evaluated by immunohistochemistry. RESULTS ROC1 overexpression promoted the growth of bladder cancer cells, whereas knockdown of ROC1 expression had the opposite effect in bladder cancer cells. Mechanistically, ROC1 was able to target suppressor of fused homolog (SUFU) for ubiquitin-dependent degradation, allowing Gli2 release from the SUFU complex to activate the SHH pathway. Furthermore, knockdown of SUFU expression partially rescued the ROC1 knockdown-suppressed SHH activity as well as cancer cell growth inhibition. In ex vivo experiments, tissue microarray analysis of human bladder cancer specimens revealed a positive association of ROC1 expression with the SHH pathway activity. CONCLUSION This study demonstrated that dysregulation of the ROC1-SUFU-GLI2 axis plays an important role in bladder cancer progression and that targeting ROC1 expression is warranted in further investigations as a novel strategy for the future control of bladder cancer.
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Affiliation(s)
- W Wang
- Department of Urology, Jiangsu Provincial People's Hospital, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu, China.,Department of Urology, Yancheng First People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, 224000, Jiangsu, China
| | - J Qiu
- Department of Urology, Shanghai First People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200080, China
| | - P Qu
- Department of Urology, Yancheng First People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, 224000, Jiangsu, China
| | - H Chen
- Department of Haematology, Yancheng First People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, 224000, Jiangsu, China
| | - J Lan
- Department of Pathology, Yancheng First People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, 224000, Jiangsu, China
| | - H Chen
- Department of Pathology, Yancheng First People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, 224000, Jiangsu, China
| | - L Li
- Translational Medicine Center, Yancheng First People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, 224000, Jiangsu, China
| | - M Gu
- Department of Urology, Jiangsu Provincial People's Hospital, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
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Ran P, Yang JQ, Li J, Li G, Wang Y, Qiu J, Zhong Q, Wang Y, Wei XB, Huang JL, Siu CW, Zhou YL, Zhao D, Yu DQ, Chen JY. A risk score to predict in-hospital mortality in patients with acute coronary syndrome at early medical contact: results from the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) Project. Ann Transl Med 2021; 9:167. [PMID: 33569469 PMCID: PMC7867931 DOI: 10.21037/atm-21-31] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background A number of models have been built to evaluate risk in patients with acute coronary syndrome (ACS). However, accurate prediction of mortality at early medical contact is difficult. This study sought to develop and validate a risk score to predict in-hospital mortality among patients with ACS using variables available at early medical contact. Methods A total of 62,546 unselected ACS patients from 150 tertiary hospitals who were admitted between 2014 and 2017 and enrolled in the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) project, were randomly assigned (at a ratio of 7:3) to a training dataset (n=43,774) and a validation dataset (n=18,772). Based on the identified predictors which were available prior to any blood test, a new point-based risk score for in-hospital death, CCC-ACS score, was derived and validated. The CCC-ACS score was then compared with Global Registry of Acute Coronary Events (GRACE) risk score. Results The in-hospital mortality rate was 1.9% in both the training and validation datasets. The CCC-ACS score, a new point-based risk score, was developed to predict in-hospital mortality using 7 variables that were available before any blood test including age, systolic blood pressure, cardiac arrest, insulin-treated diabetes mellitus, history of heart failure, severe clinical conditions (acute heart failure or cardiogenic shock), and electrocardiographic ST-segment deviation. This new risk score had an area under the curve (AUC) of 0.84 (P=0.10 for Hosmer-Lemeshow goodness-of-fit test) in the training dataset and 0.85 (P=0.13 for Hosmer-Lemeshow goodness-of-fit test) in the validation dataset. The CCC-ACS score was comparable to the Global Registry of Acute Coronary Events (GRACE) score in the prediction of in-hospital death in the validation dataset. Conclusions The newly developed CCC-ACS score, which utilizes factors that are acquirable at early medical contact, may be able to stratify the risk of in-hospital death in patients with ACS. Clinical trial registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT02306616.
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Affiliation(s)
- Peng Ran
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jun-Qing Yang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jie Li
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Guang Li
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yan Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jia Qiu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Qi Zhong
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yu Wang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xue-Biao Wei
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jie-Leng Huang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Chung-Wah Siu
- Cardiology Division, Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong, China
| | - Ying-Ling Zhou
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Dong Zhao
- Department of Epidemiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China
| | - Dan-Qing Yu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ji-Yan Chen
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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