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Cai J, Zhang H, Zhu K, Zhu F, Wang Y, Wang S, Xie F, Zhang M, Rui L, Li S, Lin K, Xue Q, Yuan G, Wang H, Zhang Y, Fu Z, Song J, Zhang Y, Ai J, Zhang W. Risk of reinfection and severity with the predominant BA.5 Omicron subvariant China, from December 2022 to January 2023. Emerg Microbes Infect 2024; 13:2292071. [PMID: 38054806 PMCID: PMC10849001 DOI: 10.1080/22221751.2023.2292071] [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: 07/06/2023] [Accepted: 12/03/2023] [Indexed: 12/07/2023]
Abstract
Data on reinfection in large Asian populations are limited. In this study, we aimed to evaluate the reinfection rate, disease severity, and time interval between the infections in the symptomatic and asymptomatic populations which are firstl infected with BA.2 Omicron Variant. We retrospectively included adult patients with COVID-19 discharged from four designated hospitals between 27 April 2021 and 30 November 2022, who were interviewed via telephone from 29 January to 1 March 2023. Univariable and multivariable analyses were used to explore risk factors associated with reinfection. A total of 16,558 patients were followed up, during the telephone survey of an average of 310.0 days, 1610 (9.72%) participants self-reported reinfection. The mean time range of reinfection was 257.9 days. The risks for reinfection were analysed using multivariable logistic regression. Patients with severe first infection were at higher risk for reinfection (aORs, 2.50; P < 0.001). The male (aORs,0.82; P < 0.001), the elderly (aORs, 0.44; P < 0.001), and patients with full vaccination (aORs, 0.67; P < 0.001) or booster (aORs, 0.63; P < 0.001) had the lower risk of reinfection. Patients over 60 years of age (aORs,9.02; P = 0.006) and those with ≥2 comorbidities (aORs,11.51; P = 0.016). were at higher risk for severe reinfection. The number of clinical manifestations of reinfection increases in people with severe first infection (aORs, 2.82; P = 0.023). The overall reinfection rate was 9.72%, and the reinfection rate of Omicron-to-Omicron subvariants was 9.50% at one year. The severity of Omicron-Omicron reinfection decreased. Data from our clinical study may provide clinical evidence and bolster response preparedness for future COVID-19 reinfection waves.
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Affiliation(s)
- Jianpeng Cai
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Haocheng Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Kun Zhu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Feng Zhu
- Department of Respiratory and Critical Care Medicine, Affiliated Wuxi Fifth Hospital of Jiangnan University, Wuxi Fifth People's Hospital, Wuxi, People’s Republic of China
| | - Yan Wang
- Department of Infectious Diseases, The Sixth People’s Hospital of Shenyang, Shenyang, People’s Republic of China
| | - Sen Wang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Faren Xie
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, People’s Republic of China
| | - Meng Zhang
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, People’s Republic of China
| | - Lili Rui
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, People’s Republic of China
| | - Shuhong Li
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, People’s Republic of China
| | - Ke Lin
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Quanlin Xue
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Guanmin Yuan
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Hongyu Wang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Yi Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Zhangfan Fu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Jieyu Song
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Yanliang Zhang
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China
- Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, People’s Republic of China
| | - Jingwen Ai
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Wenhong Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
- Shanghai Huashen Institute of Microbes and Infections, Shanghai, People’s Republic of China
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Zhang Y, Fu Z, Zhang H, Lin K, Song J, Guo J, Zhang Q, Yuan G, Wang H, Fan M, Zhao Y, Sun R, Guo T, Jiang N, Qiu C, Zhang W, Ai J. Proteomic and cellular characterization of Omicron breakthrough infections and a third homologous or heterologous boosting vaccination in a longitudinal cohort. Mol Cell Proteomics 2024:100769. [PMID: 38641227 DOI: 10.1016/j.mcpro.2024.100769] [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: 07/18/2023] [Revised: 01/18/2024] [Accepted: 03/23/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND The understanding of dynamic plasma proteome features in hybrid immunity and breakthrough infection is limited. A deeper understanding of the immune differences between heterologous and homologous immunization could assist in the future establishment of vaccination strategies. METHODS In this study, 40 participants who received a third dose of either a homologous BBIBP-CorV or a heterologous ZF2001 protein subunit vaccine following two doses of inactivated coronavirus disease 2019 vaccines and 12 patients with BA.2.2 breakthrough infections were enrolled. Serum samples were collected at Days 0, 28, and 180 following the boosting vaccination and breakthrough and then analyzed using neutralizing antibody tests and mass spectrometer-based proteomics. Mass cytometry of peripheral blood mononuclear cell samples was also performed in this cohort. RESULTS The chemokine signaling pathway and humoral response markers (IgG2 and IgG3) associated with infection were found to be upregulated in breakthrough infections compared to vaccination-induced immunity. Elevated expression of IGKV, IGHV, IL-17 signaling, and the phagocytosis pathway, along with lower expression of FGL2, were correlated with higher antibody levels in the boosting vaccination groups. The MAPK signaling pathway and Fc gamma R-mediated phagocytosis were more enriched in the heterologous immunization groups than in the homologous immunization groups. CONCLUSION Breakthrough infections can trigger more intensive inflammatory chemokine responses than vaccination. T-cell and innate immune activation have been shown to be closely related to enhanced antibody levels after vaccination and therefore might be potential targets for vaccine adjuvant design.
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Affiliation(s)
- Yi Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhangfan Fu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Haocheng Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ke Lin
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jieyu Song
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jingxin Guo
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qiran Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Guanmin Yuan
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hongyu Wang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Mingxiang Fan
- Tongji Medical School, Tongji University, Shanghai, China
| | - Yuanhan Zhao
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Rui Sun
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Tiannan Guo
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Ning Jiang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chao Qiu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wenhong Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; Shanghai huashen institute of microbes and infections, Shanghai, China.
| | - Jingwen Ai
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
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Li D, Yuan G, Wang YO, Wang H, Zhang Q, Wang YA, Gu Y, Zhang H, Zhang Y, Song J, Fu Z, Lin K, Qiu C, Zhou Y, Fan M, Zhao Y, Guo J, Jiang N, Ai J, Liu H, Zhang W. Clinical Characteristics, Treatment, and Prognosis of Osteoarticular Brucellosis: A Retrospective Real-World Study in Shenyang, China, 2014-2019. Foodborne Pathog Dis 2024. [PMID: 38608217 DOI: 10.1089/fpd.2023.0027] [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] [Indexed: 04/14/2024] Open
Abstract
This study aimed to assess the clinical characteristics, treatment, and prognosis of osteoarticular brucellosis. We conducted a retrospective study enrolling brucellosis patients from the Sixth People's Hospital of Shenyang between September 2014 and June 2019. A total of 1917 participants were admitted during this period. After applying propensity score matching, we retrospectively analyzed 429 patients with osteoarthritis and 429 patients without osteoarthritis. The primary outcome was treatment completion. The secondary outcome was symptom disappearance and seroconversion. Brucellosis patients with osteoarthritis had longer treatment course (160 [134.3-185.7] vs. 120 [102.3-137.7] d, p = 0.008) than those without osteoarthritis. The most common involved site was lumbar vertebrae (290 [67.6%]) in brucellosis patients with osteoarthritis. Longer symptom duration (90 [83.0-97.0] vs. 42 [40.2-43.8], p < 0.001) along with no significant difference in seroconversion (180 [178.8-181.2] vs. 180 [135.1-224.9], p = 0.212) was observed in osteoarthritis patients with treatment course >90 d. Peripheral joint involvement (adjusted hazard ratio [95% confidence interval] 1.485 [1.103-1.999]; p = 0.009) had a shorter symptom duration compared with shaft joint involvement. No significant differences were observed in treatment therapy between doxycycline plus rifampin (DR) or plus cephalosporins (DRC) in treatment course (p = 0.190), symptom persistence (p = 0.294), and seroconversion (p = 0.086). Lumbar vertebra was the most commonly involved site. Even if all symptoms disappeared, Serum agglutination test potentially remained positive in some patients. Compared with peripheral arthritis, shaft arthritis was the high-risk factor for longer symptom duration. The therapeutic effects were similar between DR and DRC. In summary, our study provided important insights into the clinical characteristics, treatment, and outcomes of osteoarticular brucellosis. Clinical Trial Registration number: NCT04020536.
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Affiliation(s)
- Dan Li
- The Sixth People's Hospital of Shenyang, Shenyang, China
- Emergency Treatment and Innovation Center of Public Health Emergencies, Shenyang, China
| | - Guanmin Yuan
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yan O Wang
- The Sixth People's Hospital of Shenyang, Shenyang, China
- Emergency Treatment and Innovation Center of Public Health Emergencies, Shenyang, China
| | - Hongyu Wang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Qiran Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yan A Wang
- The Sixth People's Hospital of Shenyang, Shenyang, China
- Emergency Treatment and Innovation Center of Public Health Emergencies, Shenyang, China
| | - Ye Gu
- The Sixth People's Hospital of Shenyang, Shenyang, China
- Emergency Treatment and Innovation Center of Public Health Emergencies, Shenyang, China
| | - Haocheng Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Jieyu Song
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhangfan Fu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Ke Lin
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Chao Qiu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yang Zhou
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Mingxiang Fan
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuanhan Zhao
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Jinxin Guo
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Ning Jiang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingwen Ai
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongyan Liu
- The Sixth People's Hospital of Shenyang, Shenyang, China
- Emergency Treatment and Innovation Center of Public Health Emergencies, Shenyang, China
| | - Wenhong Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
- Huashen Institute of Microbes and Infections, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
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Liu ZX, Long ZL, Yang ZR, Shi SY, Xu XR, Zhao HY, Yang ZY, Fu Z, Song HB, Lin TF, Zhan SY, Sun F. [Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions(2): to improve the extrapolation of efficacy]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:579-584. [PMID: 38678356 DOI: 10.3760/cma.j.cn112338-20230925-00190] [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: 04/29/2024]
Abstract
Objective: Randomized controlled trials (RCT) usually have strict implementation criteria. The included subjects' characteristics of the conditions for the intervention implementation are quite different from the actual clinical environment, resulting in discrepancies between the risk-benefit of interventions in actual clinical use and the risk-benefit shown in RCT. Therefore, some methods are needed to enhance the extrapolation of RCT results to evaluate the real effects of drugs in real people and clinical practice settings. Methods: Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results: A total of 12 articles were included. Three methods in the included literature focused on: ①improving the design of traditional RCT to increase population representation; ②combining RCT Data with real-world data (RWD) for analysis;③calibrating RCT results according to real-world patient characteristics. Conclusions: Improving the design of RCT to enhance the population representation can improve the extrapolation of the results of RCT. Combining RCT data with RWD can give full play to the advantages of data from different sources; the results of the RCT were calibrated against real-world population characteristics so that the effects of interventions in real-world patient populations can be predicted.
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Affiliation(s)
- Z X Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Z L Long
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Z R Yang
- School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S Y Shi
- China Rehabilitation Science Institute, China Disability Control and Prevention Center, China Disable Persons' Federation, Beijing 100068, China
| | - X R Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Z Y Yang
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hongkong 999077, China
| | - Z Fu
- Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Hainan 571437, China
| | - H B Song
- Department of Traditional Chinese Medicine Monitoring and Evaluation, Center for Drug Reevalaution, National Medical Products Administration, Beijing 100076, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100076, China
| | - T F Lin
- Biomedical Information Technology Research Center , Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Hainan 571437, China
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5
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Liu ZX, Long ZL, Yang ZR, Shi SY, Xu XR, Zhao HY, Yang ZY, Fu Z, Song HB, Lin TF, Zhan SY, Sun F. [Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions (1): to improve the validity of real-world evidence]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:286-293. [PMID: 38413070 DOI: 10.3760/cma.j.cn112338-20230925-00189] [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: 02/29/2024]
Abstract
Objective: Differences between randomized controlled trial (RCT) results and real world study (RWS) results may not represent a true efficacy-effectiveness gap because efficacy-effectiveness gap estimates may be biased when RWS and RCT differ significantly in study design or when there is bias in RWS result estimation. Secondly, when there is an efficacy- effectiveness gap, it should not treat every patient the same way but assess the real-world factors influencing the intervention's effectiveness and identify the subgroup likely to achieve the desired effect. Methods: Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results: Ten articles were included to discuss how to use the RCT research protocol as a template to develop the corresponding RWS research protocol. Moreover, based on correctly estimating the efficacy-effectiveness gap, evaluate the intervention effect in the patient subgroup to confirm the subgroup that can achieve the expected benefit-risk ratio to bridge the efficacy-effectiveness gap. Conclusion: Using real-world data to simulate key features of randomized controlled clinical trial study design can improve the authenticity and effectiveness of study results and bridge the efficacy-effectiveness gap.
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Affiliation(s)
- Z X Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Z L Long
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Z R Yang
- School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S Y Shi
- China Rehabilitation Science Institute, China Disability Control and Prevention Center, China Disable Persons' Federation, Beijing 100068, China
| | - X R Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Z Y Yang
- School of Public Health and Primary Care, the Chinese University of Hong Kong, Hong Kong 999077, China
| | - Z Fu
- Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Haikou 571437, China
| | - H B Song
- Department of Traditional Chinese Medicine Monitoring and Evaluation, Center for Drug Reevalaution, National Medical Products Administration, Beijing 100076, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100076, China
| | - T F Lin
- Biomedical Information Technology Research Center , Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,Shenzhen 518055, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Haikou 571437, China
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6
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Lin K, Zhao Y, Xu B, Yu S, Fu Z, Zhang Y, Wang H, Song J, Fan M, Zhou Y, Ai J, Qiu C, Zhang H, Zhang W. Correction for Lin et al., "Clinical Diagnostic Performance of Droplet Digital PCR for Suspected Bloodstream Infections". Microbiol Spectr 2024; 12:e0153423. [PMID: 38099669 PMCID: PMC10783108 DOI: 10.1128/spectrum.01534-23] [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] [Received: 04/24/2023] [Accepted: 06/19/2023] [Indexed: 01/13/2024] Open
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Chao Qiu
- Address correspondence to Chao Qiu,
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7
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Fu Z, Ai J, Zhang H, Cui P, Xu T, Zhang Y, Zhang Y, Wu H, Shen A, Lin K, Zhang M, Qiu C, Jiang N, Zhou Y, Zhang W. Pathogen quantitative efficacy of different spike-in internal controls and clinical application in central nervous system infection with metagenomic sequencing. Microbiol Spectr 2023; 11:e0113923. [PMID: 37982612 PMCID: PMC10714923 DOI: 10.1128/spectrum.01139-23] [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: 03/27/2023] [Accepted: 10/01/2023] [Indexed: 11/21/2023] Open
Abstract
IMPORTANCE Metagenomic next-generation sequencing (mNGS) has been used broadly for pathogens detection of infectious diseases. However, there is a lack of method for the absolute quantitation of pathogens by mNGS. We compared the quantitative efficiency of three mNGS internal controls (ICs) Thermus thermophilus, T1 phages, and artificial DNA sequence and developed the most applicable strategies for pathogen quantitation via mNGS in central nervous system infection. The IC application strategy we developed will enable mNGS analysis to assess the pathogen load simultaneously with the detection of pathogens, which should provide critical information for quick decision-making of treatment as well as clinical prognosis.
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Affiliation(s)
- Zhangfan Fu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jingwen Ai
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Haocheng Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Peng Cui
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tao Xu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yumeng Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Honglong Wu
- BGI PathoGenesis Pharmaceutical Technology, BGI-Shenzhen, Shenzhen, China
| | - Ao Shen
- BGI PathoGenesis Pharmaceutical Technology, BGI-Shenzhen, Shenzhen, China
| | - Ke Lin
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Miaoqu Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chao Qiu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ning Jiang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yang Zhou
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wenhong Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Medical Molecular Virology (MOE/MOH), Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Huashen Institute of Microbes and Infections, Shanghai, China
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8
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Iraji A, Fu Z, Faghiri A, Duda M, Chen J, Rachakonda S, DeRamus T, Kochunov P, Adhikari BM, Belger A, Ford JM, Mathalon DH, Pearlson GD, Potkin SG, Preda A, Turner JA, van Erp TGM, Bustillo JR, Yang K, Ishizuka K, Faria A, Sawa A, Hutchison K, Osuch EA, Theberge J, Abbott C, Mueller BA, Zhi D, Zhuo C, Liu S, Xu Y, Salman M, Liu J, Du Y, Sui J, Adali T, Calhoun VD. Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets. Hum Brain Mapp 2023; 44:5729-5748. [PMID: 37787573 PMCID: PMC10619392 DOI: 10.1002/hbm.26472] [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: 10/12/2022] [Revised: 04/30/2023] [Accepted: 06/19/2023] [Indexed: 10/04/2023] Open
Abstract
Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.
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Affiliation(s)
- A. Iraji
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- Department of Computer ScienceGeorgia State UniversityAtlantaGeorgiaUSA
| | - Z. Fu
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - A. Faghiri
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - M. Duda
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - J. Chen
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - S. Rachakonda
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - T. DeRamus
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - P. Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, School of MedicineUniversity of MarylandBaltimoreMarylandUSA
| | - B. M. Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, School of MedicineUniversity of MarylandBaltimoreMarylandUSA
| | - A. Belger
- Department of PsychiatryUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - J. M. Ford
- Department of PsychiatryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- San Francisco VA Medical CenterSan FranciscoCaliforniaUSA
| | - D. H. Mathalon
- Department of PsychiatryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- San Francisco VA Medical CenterSan FranciscoCaliforniaUSA
| | - G. D. Pearlson
- Departments of Psychiatry and Neuroscience, School of MedicineYale UniversityNew HavenConnecticutUSA
| | - S. G. Potkin
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - A. Preda
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - J. A. Turner
- Department of Psychiatry and Behavioral HealthOhio State University Medical Center in ColumbusColumbusOhioUSA
| | - T. G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - J. R. Bustillo
- Department of Psychiatry and Behavioral SciencesUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - K. Yang
- Department of Psychiatry, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - K. Ishizuka
- Department of Psychiatry, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - A. Faria
- Department of Psychiatry, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - A. Sawa
- Departments of Psychiatry, Neuroscience, Biomedical Engineering, Pharmacology, and Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
- Department of Mental HealthJohns Hopkins University Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - K. Hutchison
- Department of PsychologyUniversity of ColoradoBoulderColoradoUSA
| | - E. A. Osuch
- Department of Psychiatry, Schulich School of Medicine and DentistryLondon Health Sciences Centre, Lawson Health Research InstituteLondonCanada
| | - J. Theberge
- Department of Psychiatry, Schulich School of Medicine and DentistryLondon Health Sciences Centre, Lawson Health Research InstituteLondonCanada
| | - C. Abbott
- Department of Psychiatry (CCA)University of New MexicoAlbuquerqueNew MexicoUSA
| | - B. A. Mueller
- Department of PsychiatryUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - D. Zhi
- The State Key Lab of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - C. Zhuo
- Tianjin Mental Health CenterNankai University Affiliated Anding HospitalTianjinChina
| | - S. Liu
- The Department of PsychiatryFirst Clinical Medical College/First Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Y. Xu
- The Department of PsychiatryFirst Clinical Medical College/First Hospital of Shanxi Medical UniversityTaiyuanChina
| | - M. Salman
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- School of Electrical & Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - J. Liu
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- Department of Computer ScienceGeorgia State UniversityAtlantaGeorgiaUSA
| | - Y. Du
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- School of Computer and Information TechnologyShanxi UniversityTaiyuanChina
| | - J. Sui
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- The State Key Lab of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - T. Adali
- Department of CSEEUniversity of Maryland Baltimore CountyBaltimoreMarylandUSA
| | - V. D. Calhoun
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State UniversityGeorgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- Department of Computer ScienceGeorgia State UniversityAtlantaGeorgiaUSA
- Department of Psychiatry, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
- School of Electrical & Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
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Hu X, Han C, Zhang M, Mu Z, Fu Z, Ren J, Qiao K, Jia J, Yu J, Yuan S, Wei Y. Predicting Radiation Esophagitis using 18F-FAPI-04 PET/CT in Patients with LA-ESCC Treated with Concurrent Chemoradiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e303-e304. [PMID: 37785107 DOI: 10.1016/j.ijrobp.2023.06.2323] [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) This prospective study examined whether 18F-FAPI-04 PET/CT can predict the development and severity of radiation esophagitis (RE) in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) treated with concurrent chemoradiotherapy. MATERIALS/METHODS From June 2021 to March 2022, images were prospectively collected from LA-ESCC patients who underwent 18F-FAPI-04 PET/CT examinations before and during radiotherapy. The development of RE was evaluated weekly according to Radiation Therapy Oncology Group criterion. The target-to-background ratio in blood (TBRblood) was analyzed at each time point and correlated with the onset and severity of RE. Factors that predicted RE were identified by multivariate logistic analyses. RESULTS Thirty patients (median age, 66.5 years [interquartile range: 56¨C71 years]; 22 men) were evaluated. Significantly higher TBRblood (during radiotherapy, mean: 3.06 vs 7.11, P = 0.003) and change in TBRblood compared with pre-RT (ΔTBRblood, mean: 0.67 vs 4.81, P = 0.002) were observed in patients with RE than patients without RE. Those with grade 3 RE had a significantly higher TBRblood (during radiotherapy, mean: 4.55 vs 9.66, P = 0.003) and ΔTBRblood (mean: 2.16 vs 7.50, P = 0.003) compared with those with RE CONCLUSION The ΔTBRblood on 18F-FAPI-04 PET/CT may be effective at identifying patients at risk for the development of RE, especially grade 3 RE.
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Affiliation(s)
- X Hu
- Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - C Han
- Department of Surgery II, Breast Cancer Center, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - M Zhang
- 1.Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, Shandong, China. 2.Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Z Mu
- Department of Pathology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Z Fu
- Shandong Cancer Hospital and Institute, Jinan, China
| | - J Ren
- Department of PET/CT Center, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, China
| | - K Qiao
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - J Jia
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China 2. Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - J Yu
- Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
| | - S Yuan
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Y Wei
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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10
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Song J, Zhu K, Wang X, Yang Q, Yu S, Zhang Y, Fu Z, Wang H, Zhao Y, Lin K, Yuan G, Guo J, Shi Y, Liu C, Ai J, Zhang H, Zhang W. Utility of clinical metagenomics in diagnosing malignancies in a cohort of patients with Epstein-Barr virus positivity. Front Cell Infect Microbiol 2023; 13:1211732. [PMID: 37674580 PMCID: PMC10477599 DOI: 10.3389/fcimb.2023.1211732] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 04/25/2023] [Accepted: 07/25/2023] [Indexed: 09/08/2023] Open
Abstract
Backgrounds Differentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease. Methods We enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019. Results Among the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately. Conclusions The application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach.
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Affiliation(s)
- Jieyu Song
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Kun Zhu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaojia Wang
- Medical Department, Matridx Biotechnology Co., Ltd., Hangzhou, Zhejiang, China
| | - Qingluan Yang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shenglei Yu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhangfan Fu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hongyu Wang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yuanhan Zhao
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ke Lin
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Guanmin Yuan
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jingxin Guo
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yingqi Shi
- Medical Department, Matridx Biotechnology Co., Ltd., Hangzhou, Zhejiang, China
| | - Chao Liu
- Medical Department, Matridx Biotechnology Co., Ltd., Hangzhou, Zhejiang, China
| | - Jingwen Ai
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Haocheng Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wenhong Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Huashan Institute of Microbes and Infections, Shanghai, China
- Shanghai Huashen Institute of Microbes and Infections, Shanghai, China
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11
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Iraji A, Chen J, Lewis N, Faghiri A, Fu Z, Agcaoglu O, Kochunov P, Adhikari BM, Mathalon D, Pearlson G, Macciardi F, Preda A, van Erp T, Bustillo JR, Díaz-Caneja CM, Andrés-Camazón P, Dhamala M, Adali T, Calhoun V. Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk. bioRxiv 2023:2023.07.18.548880. [PMID: 37503085 PMCID: PMC10370141 DOI: 10.1101/2023.07.18.548880] [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] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Background Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.
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Affiliation(s)
- A. Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - J. Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - N. Lewis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of CSE, Georgia Institute of Technology, Atlanta, Georgia
| | - A. Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Z. Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - O. Agcaoglu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - P. Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - B. M. Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - D.H. Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - G.D. Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - F. Macciardi
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - A. Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - T.G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - J. R. Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - C. M. Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - P. Andrés-Camazón
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - M. Dhamala
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA, USA
| | - T. Adali
- Department of CSEE, University of Maryland, Baltimore County, Baltimore, Maryland
| | - V.D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of CSE, Georgia Institute of Technology, Atlanta, Georgia
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Zhao X, Yang J, Chen R, Qiu C, Li Q, Qiu T, Fu Z, Wang Z, Wu Y, Huang Y, Yang R, Liu W. P150 Psychological distress during hospitalization for breast cancer patients in the outbreak, post-peak, and normalization stages of the COVID-19 pandemic. Breast 2023. [PMCID: PMC10013701 DOI: 10.1016/s0960-9776(23)00267-9] [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: 03/18/2023] Open
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13
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Lin K, Zhao Y, Xu B, Yu S, Fu Z, Zhang Y, Wang H, Song J, Fan M, Zhou Y, Ai J, Qiu C, Zhang H, Zhang W. Clinical Diagnostic Performance of Droplet Digital PCR for Suspected Bloodstream Infections. Microbiol Spectr 2023; 11:e0137822. [PMID: 36602351 PMCID: PMC9927361 DOI: 10.1128/spectrum.01378-22] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 11/01/2022] [Indexed: 01/06/2023] Open
Abstract
Accurate and timely etiological diagnosis is crucial for bloodstream infections (BSIs) due to their high disability and mortality. We conducted a single-center prospective cohort study to compare the digital droplet PCR (ddPCR) assay with traditional blood culture. A total of 169 blood samples from 122 patients with suspected BSIs were collected, mostly from the department of infectious diseases, the emergency department, and the intensive care units, and the clinical data were also recorded. Nucleic acid was extracted from the blood samples, and a 5-fluorescent-channel droplet digital PCR assay was performed and then fed back with the pathogen and its copies. In BSI patients, ddPCR reported an overall 85.71% (12/14) (95% confidence interval [CI], 56.15 to 97.48%) sensitivity, 100% (7/7) (95% CI, 56.09 to 100.00%) and 71.43% (5/7) (95% CI, 30.26 to 94.89%) sensitivity in patients without empirical treatment and in empirically treated patients, respectively. Compared to traditional blood culture, the overall detection rate of ddPCR was significantly higher, 11.27% (16/142) (95% CI, 6.78 to 17.93%) versus 30.28% (43/142) (95% CI, 23.01 to 38.64%), and the extra detection rate of ddPCR was 19.01% (27/142) (95% CI, 13.11 to 26.63%). Of the ddPCR-positive culture-negative cases, 74.19% (23/31) (95% CI, 55.07 to 87.46%) were consistent with the final clinical diagnosis, including 10 bacteria and fungi. The detection rate of ddPCR was significantly higher in patients with white blood cell (WBC) counts of >10 · 109/L, C-reactive protein (CRP) of >70 mg/L, or procalcitonin (PCT) of >0.9 ng/L. Pathogen loads detected by ddPCR are correlated with WBC, CRP, and especially, PCT levels, precisely and rapidly reflecting clinical disease progression. ddPCR has an important guiding value for the clinical use of antibiotics to achieve the best pathogen coverage and the antibacterial effect. Collectively, ddPCR showed a great diagnostic performance in BSIs and had an overall higher detection rate than blood culture. In addition, ddPCR could be used to dynamically monitor the disease progression and provide medication guidance on antibiotic use. IMPORTANCE ddPCR is a promising method to address the current challenges of BSI diagnosis and precise treatment, as it is highly efficient in DNA detection. It shortens the identification of BSI-related pathogens from several days of traditional bacterial culture to 4 to 5 h. It is extremely sensitive and more tolerant to PCR inhibitors, which may facilitate the amplification and enable the detection of a meager amount of DNA fragments in detecting BSI-related pathogens and drug-resistant genes. It can identify almost 20 pathogens in one reaction, which reduces the usage of clinical blood samples to no more than 2 mL. Additionally, dynamic monitoring, assessment of pathogens, and antibiotic resistance genes in patients could be used to guide timely and precise adjustment of antimicrobial prescription. The short turnaround time of ddPCR may have the potential to guide antimicrobial treatment in the very early stage of sepsis and reduce the mortality and disability rate of sepsis.
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Affiliation(s)
- Ke Lin
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Yuanhan Zhao
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Bin Xu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Shenglei Yu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Zhangfan Fu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Hongyu Wang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Jieyu Song
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Mingxiang Fan
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Yang Zhou
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Jingwen Ai
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Chao Qiu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Haocheng Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
| | - Wenhong Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, China
- Key Laboratory of Medical Molecular Virology (MOE/MOH) and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, China
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, China
- National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
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14
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Abe S, Asami S, Eizuka M, Futagi S, Gando A, Gando Y, Gima T, Goto A, Hachiya T, Hata K, Hayashida S, Hosokawa K, Ichimura K, Ieki S, Ikeda H, Inoue K, Ishidoshiro K, Kamei Y, Kawada N, Kishimoto Y, Koga M, Kurasawa M, Maemura N, Mitsui T, Miyake H, Nakahata T, Nakamura K, Nakamura K, Nakamura R, Ozaki H, Sakai T, Sambonsugi H, Shimizu I, Shirai J, Shiraishi K, Suzuki A, Suzuki Y, Takeuchi A, Tamae K, Ueshima K, Watanabe H, Yoshida Y, Obara S, Ichikawa AK, Chernyak D, Kozlov A, Nakamura KZ, Yoshida S, Takemoto Y, Umehara S, Fushimi K, Kotera K, Urano Y, Berger BE, Fujikawa BK, Learned JG, Maricic J, Axani SN, Smolsky J, Fu Z, Winslow LA, Efremenko Y, Karwowski HJ, Markoff DM, Tornow W, Dell'Oro S, O'Donnell T, Detwiler JA, Enomoto S, Decowski MP, Grant C, Li A, Song H. Search for the Majorana Nature of Neutrinos in the Inverted Mass Ordering Region with KamLAND-Zen. Phys Rev Lett 2023; 130:051801. [PMID: 36800472 DOI: 10.1103/physrevlett.130.051801] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/10/2022] [Accepted: 11/29/2022] [Indexed: 06/18/2023]
Abstract
The KamLAND-Zen experiment has provided stringent constraints on the neutrinoless double-beta (0νββ) decay half-life in ^{136}Xe using a xenon-loaded liquid scintillator. We report an improved search using an upgraded detector with almost double the amount of xenon and an ultralow radioactivity container, corresponding to an exposure of 970 kg yr of ^{136}Xe. These new data provide valuable insight into backgrounds, especially from cosmic muon spallation of xenon, and have required the use of novel background rejection techniques. We obtain a lower limit for the 0νββ decay half-life of T_{1/2}^{0ν}>2.3×10^{26} yr at 90% C.L., corresponding to upper limits on the effective Majorana neutrino mass of 36-156 meV using commonly adopted nuclear matrix element calculations.
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Affiliation(s)
- S Abe
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - S Asami
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - M Eizuka
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - S Futagi
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - A Gando
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - Y Gando
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - T Gima
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - A Goto
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - T Hachiya
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Hata
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - S Hayashida
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Hosokawa
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Ichimura
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - S Ieki
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - H Ikeda
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Inoue
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Ishidoshiro
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - Y Kamei
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - N Kawada
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - Y Kishimoto
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - M Koga
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - M Kurasawa
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - N Maemura
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - T Mitsui
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - H Miyake
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - T Nakahata
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Nakamura
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Nakamura
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - R Nakamura
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - H Ozaki
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
- Graduate Program on Physics for the Universe, Tohoku University, Sendai 980-8578, Japan
| | - T Sakai
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - H Sambonsugi
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - I Shimizu
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - J Shirai
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Shiraishi
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - A Suzuki
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - Y Suzuki
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - A Takeuchi
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Tamae
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - K Ueshima
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - H Watanabe
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - Y Yoshida
- Research Center for Neutrino Science, Tohoku University, Sendai 980-8578, Japan
| | - S Obara
- Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Sendai 980-8578, Japan
| | - A K Ichikawa
- Department of Physics, Tohoku University, Sendai 980-8578, Japan
| | - D Chernyak
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - A Kozlov
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Z Nakamura
- Kyoto University, Department of Physics, Kyoto 606-8502, Japan
| | - S Yoshida
- Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan
| | - Y Takemoto
- Research Center for Nuclear Physics, Osaka University, Ibaraki, Osaka 567-0047, Japan
| | - S Umehara
- Research Center for Nuclear Physics, Osaka University, Ibaraki, Osaka 567-0047, Japan
| | - K Fushimi
- Department of Physics, Tokushima University, Tokushima 770-8506, Japan
| | - K Kotera
- Graduate School of Integrated Arts and Sciences, Tokushima University, Tokushima 770-8502, Japan
| | - Y Urano
- Graduate School of Integrated Arts and Sciences, Tokushima University, Tokushima 770-8502, Japan
| | - B E Berger
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - B K Fujikawa
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - J G Learned
- Department of Physics and Astronomy, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA
| | - J Maricic
- Department of Physics and Astronomy, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA
| | - S N Axani
- Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - J Smolsky
- Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Z Fu
- Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - L A Winslow
- Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Y Efremenko
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - H J Karwowski
- Triangle Universities Nuclear Laboratory, Durham, North Carolina 27708, USA; Physics Departments at Duke University, Durham, North Carolina 27708, USA; North Carolina Central University, Durham, North Carolina 27707, USA; and The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - D M Markoff
- Triangle Universities Nuclear Laboratory, Durham, North Carolina 27708, USA; Physics Departments at Duke University, Durham, North Carolina 27708, USA; North Carolina Central University, Durham, North Carolina 27707, USA; and The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - W Tornow
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Triangle Universities Nuclear Laboratory, Durham, North Carolina 27708, USA; Physics Departments at Duke University, Durham, North Carolina 27708, USA; North Carolina Central University, Durham, North Carolina 27707, USA; and The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - S Dell'Oro
- Center for Neutrino Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - T O'Donnell
- Center for Neutrino Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - J A Detwiler
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Center for Experimental Nuclear Physics and Astrophysics, University of Washington, Seattle, Washington 98195, USA
| | - S Enomoto
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Center for Experimental Nuclear Physics and Astrophysics, University of Washington, Seattle, Washington 98195, USA
| | - M P Decowski
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan
- Nikhef and the University of Amsterdam, Science Park, Amsterdam, Netherlands
| | - C Grant
- Boston University, Boston, Massachusetts 02215, USA
| | - A Li
- Triangle Universities Nuclear Laboratory, Durham, North Carolina 27708, USA; Physics Departments at Duke University, Durham, North Carolina 27708, USA; North Carolina Central University, Durham, North Carolina 27707, USA; and The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Boston University, Boston, Massachusetts 02215, USA
| | - H Song
- Boston University, Boston, Massachusetts 02215, USA
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15
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Wang X, He X, Jiang S, Fu Z, Jiang S, Zhao X, Zhao C, Li Y, Li D, Zhang W, Ai J, Zhang Y, Xu C, Wang P. Limited enhancement of antibody and B-cell responses to prototype booster vaccination following SARS-CoV-2 Delta breakthrough infection. J Med Virol 2023; 95:e28540. [PMID: 36722359 DOI: 10.1002/jmv.28540] [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] [Received: 10/11/2022] [Revised: 12/14/2022] [Accepted: 01/29/2023] [Indexed: 02/02/2023]
Affiliation(s)
- Xun Wang
- Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai Institute of Infectious Disease and Biosecurity, State Key Laboratory of Genetic Engineering, MOE Engineering Research Center of Gene Technology, School of Life Sciences, Fudan University, Shanghai, China
| | - Xing He
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Shujun Jiang
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing, University of Chinese Medicine, Nanjing, Jiangsu, China.,Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, Jiangsu, China
| | - Zhangfan Fu
- Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Department of Infectious Diseases, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
| | - Shuai Jiang
- Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai Institute of Infectious Disease and Biosecurity, State Key Laboratory of Genetic Engineering, MOE Engineering Research Center of Gene Technology, School of Life Sciences, Fudan University, Shanghai, China
| | - Xiaoyu Zhao
- Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai Institute of Infectious Disease and Biosecurity, State Key Laboratory of Genetic Engineering, MOE Engineering Research Center of Gene Technology, School of Life Sciences, Fudan University, Shanghai, China
| | - Chaoyue Zhao
- Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai Institute of Infectious Disease and Biosecurity, State Key Laboratory of Genetic Engineering, MOE Engineering Research Center of Gene Technology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yaning Li
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Dianfan Li
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Wenhong Zhang
- Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Department of Infectious Diseases, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingwen Ai
- Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Department of Infectious Diseases, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
| | - Yanliang Zhang
- Department of Infectious Diseases, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing, University of Chinese Medicine, Nanjing, Jiangsu, China.,Nanjing Research Center for Infectious Diseases of Integrated Traditional Chinese and Western Medicine, Nanjing, Jiangsu, China
| | - Chenqi Xu
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Pengfei Wang
- Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai Institute of Infectious Disease and Biosecurity, State Key Laboratory of Genetic Engineering, MOE Engineering Research Center of Gene Technology, School of Life Sciences, Fudan University, Shanghai, China
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16
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Cao G, Lin K, Ai J, Cai J, Zhang H, Yu Y, Liu Q, Zhang X, Zhang Y, Fu Z, Song J, Wang H, Yuan G, Wang S, Guan M, Zhang W. A diagnostic accuracy study comparing RNA LAMP, direct LAMP, and rapid antigen testing from nasopharyngeal swabs. Front Microbiol 2022; 13:1063414. [PMID: 36620063 PMCID: PMC9813509 DOI: 10.3389/fmicb.2022.1063414] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction During the coronavirus disease 2019 (COVID-19) pandemic, the early detection and isolation of individuals infected with severe acute respiratory syndrome coronavirus disease 2 (SARS-CoV-2) through mass testing can effectively prevent disease transmission. SARS-CoV-2 nucleic acid rapid detection based on loop-mediated isothermal amplification (LAMP) may be appropriate to include in testing procedures. Methods We used 860 nasopharyngeal specimens from healthcare workers of Huashan Hospital and COVID-19 patients collected from April 7th to 21st, 2022, to assess the clinical diagnostic performance of the LAMP assay marketed by Shanghai GeneSc Biotech and compared it to the result of a rapid antigen test (RAT) head-to-head. Results Overall, the diagnostic performance of LAMP assay and RAT were as follows. The LAMP assay represented higher sensitivity and specificity than RAT, especially in the extracted RNA samples. The sensitivity was 70.92% and 92.91% for direct LAMP and RNA-LAMP assay, respectively, while the specificity was 99.86% and 98.33%. The LAMP assay had overall better diagnostic performance on the specimens with relatively lower C t values or collected in the early phase (≤7 days) of COVID-19. The combination of LAMP assay and RAT improved diagnostic efficiency, providing new strategies for rapidly detecting SARS-CoV-2. Conclusion The LAMP assay are suitable for mass screenings of SARS-CoV-2 infections in the general population.
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Affiliation(s)
- Guojun Cao
- Department of Laboratory Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ke Lin
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingwen Ai
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianpeng Cai
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Haocheng Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yiqi Yu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Qihui Liu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Xinyun Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhangfan Fu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Jieyu Song
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongyu Wang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Guanmin Yuan
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China
| | - Sen Wang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China,Shanghai Huashan Institute of Microbes and Infections, Shanghai, China,*Correspondence: Sen Wang,
| | - Ming Guan
- Department of Laboratory Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China,Shanghai Huashan Institute of Microbes and Infections, Shanghai, China,Ming Guan,
| | - Wenhong Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai, China,Shanghai Huashan Institute of Microbes and Infections, Shanghai, China,National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China,Wenhong Zhang,
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17
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Ai J, Zhang Y, Zhang H, Zhang Q, Fu Z, Lin K, Song J, Zhao Y, Fan M, Wang H, Zhou Y, Chen X, Qiu C, Zhang W. Safety and immunogenicity of a third-dose homologous BBIBP-CorV boosting vaccination: interim results from a prospective open-label study. Emerg Microbes Infect 2022; 11:639-647. [PMID: 35034582 PMCID: PMC8881062 DOI: 10.1080/22221751.2022.2025746] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [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] [Indexed: 01/07/2023]
Abstract
A COVID-19 booster vaccination is being comprehensively evaluated globally due to the emerging concern of reduced protection rate of previous vaccination and circulating Variants of Concern (VOC). But the safety and immunogenicity of homologous BBIBP-CorV boosting vaccination are yet to be thoroughly evaluated. We conducted this prospective, open-label study in Huashan Hospital using a third 6.5U BBIBP-CorV administered at an interval of 4–8 months following the previous two doses in healthy adults. Safety, anti-RBD response and neutralizing titers against SARS-CoV-2 and VOCs were examined. Sixty-three and forty participants entered the booster and the control group, respectively. A significant increase in IFN-γ SFU per million PBMCs was observed on day 14 against N peptide (20 vs. 5, P < 0.001). On day 14, pVNT GMTs increased over 15 folds of the baseline levels against prototype to reach 404.54 titers and over 9–13 folds against 4 VOCs and continuously increased by day 28. sVNT GMTs increased 112.51 and 127.45 folds by days 14 and 28 compared to the baseline level. Median anti-RBD antibody and IgG level significantly increased from 11.12 to 2607.50 BAU/ml and 4.07 to 619.20 BAU/ml on day 14. On day 14, females showed a significantly higher cell-mediated immune response against S1 peptide. The 7–8 months interval group had a higher humoral response than the 4–6 months interval group. No severe adverse event was reported. A third homologous BBIBP-CorV boosting vaccination was safe and highly immunogenic for healthy adults and broadened participants’ immunity against VOCs.
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Affiliation(s)
- Jingwen Ai
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Yi Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Haocheng Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Qiran Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Zhangfan Fu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Ke Lin
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Jieyu Song
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Yuanhan Zhao
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Mingxiang Fan
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Hongyu Wang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Yang Zhou
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Xiaohua Chen
- Department of Infectious Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
| | - Chao Qiu
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Wenhong Zhang
- Department of Infectious Diseases, National Medical Center for Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.,National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, People's Republic of China.,Key Laboratory of Medical Molecular Virology (MOE/MOH) Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
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Ai J, Zhang H, Zhang Y, Lin K, Zhang Y, Wu J, Wan Y, Huang Y, Song J, Fu Z, Wang H, Guo J, Jiang N, Fan M, Zhou Y, Zhao Y, Zhang Q, Liu Q, Lv J, Li P, Qiu C, Zhang W. Omicron variant showed lower neutralizing sensitivity than other SARS-CoV-2 variants to immune sera elicited by vaccines after boost. Emerg Microbes Infect 2022; 11:337-343. [PMID: 34935594 PMCID: PMC8788341 DOI: 10.1080/22221751.2021.2022440] [Citation(s) in RCA: 234] [Impact Index Per Article: 117.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 01/09/2023]
Abstract
ABSTRACTThe emerging new VOC B.1.1.529 (Omicron) variant has raised serious concerns due to multiple mutations, reported significant immune escape, and unprecedented rapid spreading speed. Currently, studies describing the neutralization ability of different homologous and heterologous booster vaccination against Omicron are still lacking. In this study, we explored the immunogenicity of COVID-19 breakthrough patients, BBIBP-CorV homologous booster group and BBIBP-CorV/ZF2001 heterologous booster group against SARS-CoV-2 pseudotypes corresponding to the prototype, Beta, Delta, and the emergent Omicron variant.Notably, at 14 days post two-dose inactivated vaccines, pVNT titre increased to 67.4 GMTs against prototype, 8.85 against Beta and 35.07 against Delta, while neutralization activity against Omicron was below the lower limit of quantitation in 80% of the samples. At day 14 post BBIBP-CorV homologous booster vaccination, GMTs of pVNT significantly increased to 285.6, 215.7, 250.8, 48.73 against prototype, Beta, Delta, and Omicron, while at day 14 post ZF2001 heterologous booster vaccination, GMTs of pVNT significantly increased to 1436.00, 789.6, 1501.00, 95.86, respectively. Post booster vaccination, 100% samples showed positive neutralization activity against Omicron, albeit illustrated a significant reduction (5.86- to 14.98-fold) of pVNT against Omicron compared to prototype at 14 days after the homologous or heterologous vaccine boosters.Overall, our study demonstrates that vaccine-induced immune protection might more likely be escaped by Omicron compared to prototypes and other VOCs. After two doses of inactivated whole-virion vaccines as the "priming" shot, a third heterologous protein subunit vaccine and a homologous inactivated vaccine booster could improve neutralization against Omicron.
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Affiliation(s)
- Jingwen Ai
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Haocheng Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Yi Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Ke Lin
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Yanliang Zhang
- Depatment of Infectious Disease, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Jiangsu, People’s Republic of China
| | - Jing Wu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Yanming Wan
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Yanfang Huang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Jieyu Song
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Zhangfan Fu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Hongyu Wang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Jingxin Guo
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Ning Jiang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Mingxiang Fan
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Yang Zhou
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Yuanhan Zhao
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Qiran Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Qiang Liu
- Gobond Testing Technology (Beijing) Co., Ltd, Beijing, People’s Republic of China
| | - Jing Lv
- Gobond Testing Technology (Beijing) Co., Ltd, Beijing, People’s Republic of China
| | - Peiyao Li
- Gobond Testing Technology (Beijing) Co., Ltd, Beijing, People’s Republic of China
| | - Chao Qiu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
| | - Wenhong Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People’s Republic of China
- Key Laboratory of Medical Molecular Virology (MOE/MOH) and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, People’s Republic of China
- National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, People’s Republic of China
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Jin P, Gao Y, Fu Z, Yang W, Meng X. 105P Neoadjuvant tislelizumab combined with chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma (ESCC): Single arm phase II study. Immuno-Oncology and Technology 2022. [DOI: 10.1016/j.iotech.2022.100209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Bai X, Fu Z, Sun Z, Xu R, Guo X, Tian Q, Dmytriw AA, Zhao H, Wang W, Wang X, Patel AB, Yang B, Jiao L. Thrombectomy Using the EmboTrap Clot-Retrieving Device for the Treatment of Acute Ischemic Stroke: A Glimpse of Clinical Evidence. AJNR Am J Neuroradiol 2022; 43:1736-1742. [PMID: 36456081 DOI: 10.3174/ajnr.a7708] [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: 06/21/2022] [Accepted: 10/11/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND The EmboTrap Recanalization Device is a novel stent retriever for thrombectomy in the setting of acute ischemic stroke due to large-vessel occlusion. PURPOSE Our aim was to summarize the safety and efficacy of the EmboTrap Recanalization Device in acute ischemic stroke-large-vessel occlusion through a systematic review and meta-analysis. DATA SOURCES Medline, EMBASE, the Cochrane Library, Web of Science, and Google Scholar were searched up to April 2022. STUDY SELECTION Nine observational studies using the EmboTrap Recanalization Device were selected. DATA ANALYSIS We adapted effect size with 95% CIs for dichotomous data. P value <.05 was statistically significant. DATA SYNTHESIS The estimated rate of successful recanalization (modified TICI 2b-3) was 90% (95% CI, 86%-95%; I 2 = 82.4%); 90-day favorable outcome (mRS 0-2), 53% (95% CI, 42%-63%; I 2 = 88.6%); modified first-pass effect, 43% (95% CI, 35%-51%; I 2 = 63.7%); and first-pass effect, 36% (95% CI, 29%-46%; I 2 = 10.7%). The rate of any intracerebral hemorrhage was 19% (95% CI, 16%-22%; I 2 = 0.0%); symptomatic intracerebral hemorrhage, 5% (95% CI, 1%-8%; I 2 = 84.6%); and 90-day mortality, 14% (95% CI, 9%-19%; I 2 = 79.3%). Subgroup analysis showed higher rates of complete recanalization for EmboTrap II than for the EmboTrap System. LIMITATIONS The included studies are single-arm without direct comparison with other stent retrievers. Some of the studies recruited had a small sample size and were limited by the retrospective study design. In addition, the uncertain heterogeneity among studies was high. CONCLUSIONS The EmboTrap Recanalization Device is safe and efficient in treating acute ischemic stroke due to large-vessel occlusion.
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Affiliation(s)
- X Bai
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.).,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
| | - Z Fu
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.).,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
| | - Z Sun
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.).,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
| | - R Xu
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.).,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
| | - X Guo
- Department of Neurology (X.G.), Loma Linda University Health, Loma Linda, California
| | - Q Tian
- Beijing Key Laboratory of Clinical Epidemiology (Q.T.), School of Public Health, Capital Medical University, Beijing, China
| | - A A Dmytriw
- Neuroendovascular Program (A.A.D.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - H Zhao
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.).,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
| | - W Wang
- Library (W.W., X.W., A.B.P.)
| | - X Wang
- Library (W.W., X.W., A.B.P.)
| | | | - B Yang
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.).,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
| | - L Jiao
- From the Departments of Neurosurgery (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.) .,Interventional Neuroradiology (L.J.), Xuanwu Hospital, Capital Medical University, Xicheng District, Beijing, China.,China International Neuroscience Institute (X.B., Z.F., Z.S., R.X., H.Z., B.Y., L.J.), Beijing, China
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Zhang Y, Jiang N, Qi W, Li T, Zhang Y, Wu J, Zhang H, Zhou M, Cui P, Yu T, Fu Z, Zhou Y, Lin K, Wang H, Wei T, Zhu Z, Ai J, Qiu C, Zhang W. SARS-CoV-2 intra-host single-nucleotide variants associated with disease severity. Virus Evol 2022; 8:veac106. [PMID: 36505092 PMCID: PMC9728387 DOI: 10.1093/ve/veac106] [Citation(s) in RCA: 2] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 10/24/2022] [Accepted: 11/26/2022] [Indexed: 11/30/2022] Open
Abstract
Variants of severe acute respiratory syndrome coronavirus 2 frequently arise within infected individuals. Here, we explored the level and pattern of intra-host viral diversity in association with disease severity. Then, we analyzed information underlying these nucleotide changes to infer the impetus including mutational signatures and immune selection from neutralizing antibody or T-cell recognition. From 23 January to 31 March 2020, a set of cross-sectional samples were collected from individuals with homogeneous founder virus regardless of disease severity. Intra-host single-nucleotide variants (iSNVs) were enumerated using deep sequencing. Human leukocyte antigen (HLA) alleles were genotyped by Sanger sequencing. Medical records were collected and reviewed by attending physicians. A total of 836 iSNVs (3-106 per sample) were identified and distributed in a highly individualized pattern. The number of iSNVs paced with infection duration peaked within days and declined thereafter. These iSNVs did not stochastically arise due to a strong bias toward C > U/G > A and U > C/A > G substitutions in reciprocal proportion with escalating disease severity. Eight nonsynonymous iSNVs in the receptor-binding domain could escape from neutralization, and eighteen iSNVs were significantly associated with specific HLA alleles. The level and pattern of iSNVs reflect the in vivo viral-host interaction and the disease pathogenesis.
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Affiliation(s)
| | | | | | | | - Yumeng Zhang
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Jing Wu
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Haocheng Zhang
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Mingzhe Zhou
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Peng Cui
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Tong Yu
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Zhangfan Fu
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yang Zhou
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Ke Lin
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Hongyu Wang
- Department of Infectious Diseases, National Clinical Research Center for Aging and Medicine, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Tongqing Wei
- State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China
| | | | | | - Chao Qiu
- *Corresponding authors: E-mail: ; ; ;
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Shi SY, Liu ZX, Zhao HY, Nie XL, Fu Z, Song HB, Yao C, Zhan SY, Sun F. [Real-world evidence and randomized controlled trials: the initiation, implementation, progress interpretation and revelation of RCT DUPLICATE (part 1)]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1828-1834. [PMID: 36444469 DOI: 10.3760/cma.j.cn112338-20220513-00408] [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: 06/16/2023]
Abstract
In recent years, researchers, pharmaceutical companies, and political makers gradually using more real-world data (RWD) to produce real-world evidence (RWE) for policy-making. A research team of Harvard University launched the RCT DUPLICATE project in 2018, aiming to replicate 30 randomized controlled trials using the medical claims database in order to explore methods for quantifying the efficacy-effectiveness gap and explain its potential sources, to enhance the credibility of the RWE. This paper reviews the background of RCT DUPLICATE Initiative, highlights the research purposes, research design and implementation process of the RCT DUPLICATE Initiative, to help domestic scholars better understand the scope and application value of RWE.
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Affiliation(s)
- S Y Shi
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China China Institute of Rehabilitation Sciences, Center for Prevention and Control of Disability of China Disabled Persons Federation, Beijing 100068, China
| | - Z X Liu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - X L Nie
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Center for Clinical Epidemiology and Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Z Fu
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
| | - H B Song
- Center for Drug Reevaluation, National Medical Products Administration, Beijing 100022, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100022, China
| | - C Yao
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China Peking University Clinical Research Institute, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
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Shi SY, Liu ZX, Zhao HY, Nie XL, Han S, Fu Z, Song HB, Yao C, Zhan SY, Sun F. [Real-world evidence and randomized controlled trials: the initiation, implementation, progress interpretation and revelation of RCT DUPLICATE (part 2)]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1835-1841. [PMID: 36444470 DOI: 10.3760/cma.j.cn112338-20220513-00409] [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: 06/16/2023]
Abstract
With the promotion and application of big medical data, non-interventional real-world evidence (RWE) has been used by regulators to assess the effectiveness of medical products. This paper briefly introduces the latest progress and research results of the RCT DUPLICATE Initiative launched by the research team of Harvard University in 2018 and summarizes relevant research experience based on the characteristics of China's medical service to provide inspiration and reference for domestic scholars to conduct related RWE research in the future.
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Affiliation(s)
- S Y Shi
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China China Institute of Rehabilitation Sciences, Center for Prevention and Control of Disability of China Disabled Persons Federation, Beijing 100068, China
| | - Z X Liu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - X L Nie
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Center for Clinical Epidemiology and Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - S Han
- Department of Pharmacy Management and Clinical Pharmacy, Peking University School of Pharmacy, Beijing 100191, China
| | - Z Fu
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
| | - H B Song
- Center for Drug Reevaluation, National Medical Products Administration, Beijing 100022, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100022, China
| | - C Yao
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China Peking University Clinical Research Institute, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
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Chai MY, Kou BX, Fu Z, Wei FL, Dou SS, Chen DX, Liu XN. [Sorafenib regulates vascular endothelial growth factor by runt-related transcription factor-3 to inhibit angiogenesis in hepatocellular carcinoma]. Zhonghua Gan Zang Bing Za Zhi 2022; 30:770-776. [PMID: 36038349 DOI: 10.3760/cma.j.cn501113-20201221-00670] [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: 06/15/2023]
Abstract
Objective: To investigate the molecular mechanism of sorafenib against hepatocellular carcinoma. Methods: Sorafenib efficacy was screened and verified by the hepatocellular carcinoma patient-derived tumor xenograft (PDX) model. Veterinary B-mode ultrasonography and in vivo confocal laser scanning microscopy were used to observe PDX angiogenesis. Immunohistochemistry was used to observe the expression of proliferation and angiogenesis-related proteins in PDX tissue. Real-time quantitative PCR technology was used to observe the RUNX3 gene in PDX tissues. SPSS 17.0 statistical software was used for statistical analysis. Results: Four cases of PDX were used to screen the efficacy of sorafenib. PDX1 had a significant response to sorafenib, with an inhibition rate of 68.07%. Compared with the control group, sorafenib had significantly inhibited PDX1 relative tumor volume (5.76±2.14 vs. 11.71±2.87, P<0.05). Cell division index (39.50±7.72 vs. 67.10±9.14, P<0.05) and Ki67 expression (288.6±43.40 vs. 531.70±55.60, P<0.05) were significantly decreased. Veterinary B-mode ultrasonography showed evident blood flow signals in PDX1 tumors. In vivo confocal laser scanning microscopy results showed that sorafenib had significantly reduced the total vessel length (1573.00±236.21 vs. 2675.03±162.00, P<0.05) and area (11 145.33±1931.97 vs. 20 105.37±885.93, P<0.05)) of PDX1 tumors. Immunohistochemical results showed that sorafenib had significantly down-regulated the protein expressions of CD34 (27.55±3.76 vs. 45.47±5.57, P<0.05), VEGF (16.33±2.86 vs. 22.77±3.20, P<0.05) and MVD (38.75±6.01 vs. 55.50±8.61, P<0.05). Real-time PCR results showed that sorafenib had significantly up-regulated RUNX3 gene expression (2.14±0.71 vs. 1.00±0.36, P<0.05). However, there was a negative correlation between the expression of RUNX3 gene and the ratio of VEGF-positive cells in sorafenib group (R2=0.509 7). Conclusion: Sorafenib may inhibit the PDX angiogenesis and the growth of hepatocellular carcinoma by regulating the RUNX3-VEGF pathway.
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Affiliation(s)
- M Y Chai
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China Beijing Institute of Hepatology, Beijing 100069, China
| | - B X Kou
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China Beijing Institute of Hepatology, Beijing 100069, China
| | - Z Fu
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China
| | - F L Wei
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China Beijing Institute of Hepatology, Beijing 100069, China
| | - S S Dou
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China Beijing Institute of Hepatology, Beijing 100069, China
| | - D X Chen
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China Beijing Institute of Hepatology, Beijing 100069, China
| | - X N Liu
- Beijing You'an Hospital,Capital Medical University, Beijing 100069, China Beijing Institute of Hepatology, Beijing 100069, China
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Wang H, Liu H, Zhang Q, Lu X, Li D, Zhang H, Wang YA, Zheng R, Zhang Y, Fu Z, Lin K, Qiu C, Wang YO, Gu Y, Ai J, Zhang W. Natural History of and Dynamic Changes in Clinical Manifestation, Serology, and Treatment of Brucellosis, China. Emerg Infect Dis 2022; 28:1460-1465. [PMID: 35731038 PMCID: PMC9239867 DOI: 10.3201/eid2807.211766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
In China, 13.3% of human brucellosis cases progressed to chronic disease; serum agglutination test might cause treatment elongation. Serum agglutination test plus exposure history were used to diagnose most cases of human brucellosis in 2 China provinces. After appropriate treatment, 13.3% of acute brucellosis cases progressed to chronic disease; arthritis was an early predictor. Seropositivity can persist after symptoms disappear, which might cause physicians to subjectively extend therapeutic regimens.
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Jiang X, Hu H, Fu Z, Su Y, Long J. ASSOCIATION BETWEEN THE CTLA-4 EXON 1+49A/G POLYMORPHISM AND THE RELAPSE OF GRAVE'S DISEASE AFTER ATD WITHDRAWAL: A META-ANALYSIS. Acta Endocrinol (Buchar) 2022; 18:324-332. [PMID: 36699166 PMCID: PMC9867805 DOI: 10.4183/aeb.2022.324] [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: 01/21/2023]
Abstract
Background The cytotoxic T lymphocyte-associated molecules-4 (CTLA-4) is related to the relapse of Graves' disease (GD) after anti-thyroid drugs (ATDs) withdrawal. We performed a meta-analysis to generate large-scale evidence on whether the CTLA-4 exon 1+49A/G polymorphism can predict the relapse of GD after ATDs withdrawal. Methods and Results The PubMed, EMBASE,the Cochrane Library and reference lists of relevant studies were searched to identify eligible studies from inception to Jan, 2021. Ten eligible studies consisting of 1450 GD patients with a total of 848 relapsed patients were included in the meta-analysis.In Caucasians patients, the CTLA-4 exon 1+49A/G polymorphism significantly elevated the relapse risk of GD in additive (OR = 2.07, 95% CI: 1.18-3.62, P=0.011), dominant (OR = 2.52, 95% CI: 1.17-5.41, P=0.02), homozygote model(OR = 3.264, 95% CI: 1.25-8.52, P=0.016), except recessive (OR = 2.18, 95% CI = 0.98-4.86, P = 0.062) and heterozygote model (OR = 2.141, 95% CI = 0.958-4.786, P = 0.064). In Asian subgroup, none of these genotypes show any associations with the relapse of GD after ATDs withdrawal. Conclusion This meta-analysis suggests that the CTLA-4 exon1 +49A/G polymorphism is associated with the relapse risk of GD after ATDs withdrawal in Caucasians, not Asians. Compared with the AA genotype, Caucasian patients with GG genotype have 3.264 times risk of relapse. A more aggressive treatment such as radioactive iodine or thyroidectomy, or longer periods treatment of ATDs should be recommended in Caucasian patients with the GG genotype.
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Affiliation(s)
- X. Jiang
- The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - H. Hu
- The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Z. Fu
- The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Y. Su
- The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - J. Long
- The Second Affiliated Hospital, Army Medical University, Chongqing, China
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Li R, Zhu X, Liu S, Zhang X, Xie C, Fu Z, Huang A, Sun L, Liu D, Zhao J, Wu L, Qin Z, Li S, Liu Y, Li Z. LB0005 ORELABRUTINIB, AN IRREVERSIBLE INHIBITOR OF BRUTON’S TYROSINE KINASE (BTK), FOR THE TREATMENT OF SYSTEMIC LUPUS ERYTHEMATOSUS (SLE): RESULTS OF A RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, PHASE IB/IIA DOSE-FINDING STUDY. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.5086a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundOrelabrutinib is an oral, highly-selective, irreversible inhibitor of Bruton’s tyrosine kinase (BTK). Orelabrutinib has been approved for the treatment of B cell malignancies in China. Two distinct lupus animal models showed significant efficacy of orelabrutinib in reducing disease activity, which supported the clinical development of orelabrutinib in Systemic Lupus Erythematosus (SLE).ObjectivesThis phase Ib/IIa, randomized, double-blind, placebo-controlled, dose-finding study aimed to evaluate the safety, tolerability, pharmacokinetics (PK), pharmacodynamics (PD), preliminary efficacy and biomarkers of orelabrutinib in patients with mild to moderate SLE who received standard of care (SoC) therapy.MethodsPatients diagnosed with SLE by the ACR classification criteria for ≥ 6 months, who had a SLEDAI-2K score ≥5 at screening, and were autoantibody-positive, were randomized 1:1:1:1 to receive oral orelabrutinib at 50mg, 80mg, 100mg or placebo once daily for 12 weeks, respectively.ResultsThis study randomized 60 patients with 55 patients who completed 12-week treatment. Age at baseline was 33.7±9.8 years and 96.7% were female. Baseline disease characteristics were generally balanced across treatment groups. Adverse events (AEs) were reported in 80%, 93.3% and 100% of orelabrutinib treated patients at doses of 50mg, 80mg and 100mg QD respectively versus 85.5% in placebo group. AEs were mostly mild or moderate. Treatment-related SAEs were reported in 3 patients treated with orelabrutinib, only 1 of which was grade 3. No deaths were reported. The plasma exposure of orelabrutinib (AUC and Cmax) was proportionally increased with doses. Nearly complete BTK occupancy was achieved at all dose levels, and the occupancy lasted for 24 hours without any decrease compared to that at 4 hour post-dosing. In all evaluable patients, the SLE Response Index (SRI)-4 response rates at week 12 were 50.0%, 61.5% and 64.3% in patients treated with orelabrutinib at 50mg (n=14), 80mg (n=13) and 100mg (n=14) respectively, compared with 35.7% in patients treated with placebo (n=14), which indicated the trend of dose-dependent improvement. Among the subgroup of patients with SLEDAI-2K≥8 at screening, SRI-4 response occurred in 70%, 70% and 66.7% of patients treated with orelabrutinib at 50mg (n=10), 80mg (n=10) and 100mg (n=9), respectively, compared with 30% who received placebo (n=10). Trends of reduced proteinuria, anti-dsDNA and IgG, total B cells and increased complements C4 were also observed following orelabrutinib treatment.ConclusionOrelabrutinib was generally safe and well tolerated in patients with SLE. Preliminary results also suggested encouraging efficacy which supports further development of orelabrutinib in larger and longer trials for SLE.Table 1.Efficacy results at week 12.All Evaluable PatientsPlaceboOrelabrutinibOrelabrutinibOrelabrutinib50 mg80 mg100 mgN=5514141314SRI-4 response, n (%)5 (35.7%)7 (50.0%)8 (61.5%)9 (64.3%)Treatment difference vs. PBO (%)14.3%25.8%28.6%SLEDAI-2K≥8, N=391010109SRI-4 response, n (%)3 (30.0%)7 (70.0%)7 (70.0%)6 (66.7%)Treatment difference vs. PBO (%)40.0%40.0%36.7%Note: All evaluable patients at week 12 efficacy data were included in the efficacy analysis.Figure 1.SRI-4 response rates at week 12.Disclosure of InterestsRu Li: None declared, Xiaoxia Zhu: None declared, Shengyun Liu: None declared, Xiao Zhang: None declared, Changhao Xie: None declared, Zili Fu: None declared, Anbin Huang: None declared, Lingyun Sun: None declared, Dongzhou Liu: None declared, Jinxia Zhao: None declared, Lin Wu: None declared, Zhoushuai Qin Employee of: InnoCare Pharma Limited., Sichen Li Employee of: InnoCare pharma Limited., Yaorong Liu Employee of: InnoCare pharma Limited., Zhanguo Li: None declared
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Iraji A, Faghiri A, Fu Z, Kochunov P, Adhikari BM, Belger A, Ford JM, McEwen S, Mathalon DH, Pearlson GD, Potkin SG, Preda A, Turner JA, Van Erp TGM, Chang C, Calhoun VD. Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping. Neuroimage 2022; 251:119013. [PMID: 35189361 PMCID: PMC9107614 DOI: 10.1016/j.neuroimage.2022.119013] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [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: 08/27/2021] [Revised: 02/11/2022] [Accepted: 02/17/2022] [Indexed: 11/05/2022] Open
Abstract
Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches.
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Affiliation(s)
- A Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, United States of America.
| | - A Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, United States of America
| | - Z Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, United States of America
| | - P Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, United States of America
| | - B M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, United States of America
| | - A Belger
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States of America
| | - J M Ford
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, United States of America; San Francisco VA Medical Center, San Francisco, CA, United States of America
| | - S McEwen
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States of America
| | - D H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, United States of America; San Francisco VA Medical Center, San Francisco, CA, United States of America
| | - G D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University, School of Medicine, New Haven, CT, United States of America
| | - S G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, United States of America
| | - A Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, United States of America
| | - J A Turner
- Department of Psychology, Georgia State University, Atlanta, GA, United States of America
| | - T G M Van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, United States of America
| | - C Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States of America
| | - 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, United States of America.
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Liu HM, Fu Z, Zhang XB, Zhang HL, Bao YX, Wu XD, Shang YX, Zhao DY, Zhao SY, Zhang JH, Chen ZM, Liu EM, Deng L, Liu CH, Xiang L, Cao L, Zou YX, Xu BP, Dong XY, Yin Y, Hao CL, Hong JG. [Expert consensus on rational usage of nebulization treatment on childhood respiratory system diseases]. Zhonghua Er Ke Za Zhi 2022; 60:283-290. [PMID: 35385931 DOI: 10.3760/cma.j.cn112140-20220118-00059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Affiliation(s)
- H M Liu
- Department of Pediatric Pulmonology and Immunology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Z Fu
- Department of Respiratory, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - X B Zhang
- Department of Respiratory Disease, Children's Hospital of Fudan University, Shanghai 201102, China
| | - H L Zhang
- Department of Pediatric Respiratory Medicine, the Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Y X Bao
- Tongxing Children's Clinic, Shanghai 200433, China
| | - X D Wu
- Department of Respiratory,Xiamen Children's Hospital (Children's Hospital of Fudan University at Xiamen), Xiamen 361006, China
| | - Y X Shang
- Department of Pediatric Pulmonology, Shengjing Hospital of China Medical University, Shenyang 110136, China
| | - D Y Zhao
- Department of Respiratory Medicine, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - S Y Zhao
- Department No.2 of Respiratory Medicine, Beijing Children's Hospital, Capital Medical University, Beijing 100045, China
| | - J H Zhang
- Department of Pediatric Respiratory, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
| | - Z M Chen
- Department of Pulmonology, the Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China
| | - E M Liu
- Department of Respiratory, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - L Deng
- Department of Respiratory,Guangzhou Women and Children's Medical Center, Guangzhou 510623, China
| | - C H Liu
- Department of Allergy,Children's Hospital Capital Institute of Pediatrics, Beijing 100020, China
| | - L Xiang
- Department of Allergic Medicine, Beijing Children's Hospital, Capital Medical University, Beijing 100045, China
| | - L Cao
- Department of Allergy,Children's Hospital Capital Institute of Pediatrics, Beijing 100020, China
| | - Y X Zou
- Department of Respiratory, Tianjin Children's Hospital, Tianjin 300134, China
| | - B P Xu
- Department of Respiratory Medicine, Beijing Children's Hospital, Capital Medical University, Beijing 100045, China
| | - X Y Dong
- Department of Pulmonology, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
| | - Y Yin
- Department of Respiratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
| | - C L Hao
- Department of Respiratory,Children's Hospital of Soochow University, Suzhou 215002, China
| | - J G Hong
- Department of Pediatrics, Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
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Jie YC, Jiang YW, Liang KJ, Zhou XO, Zhang CT, Fu Z, Zhao YH. [Mechanical circulatory support combined with immunomodulation treatment for patients with fulminant myocarditis: a single-center real-world study]. Zhonghua Xin Xue Guan Bing Za Zhi 2022; 50:277-281. [PMID: 35340147 DOI: 10.3760/cma.j.cn112148-20210519-00432] [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
Objective: To investigate the relationship between the mechanical circulatory support (MCS) combined with immunomodulation and the prognosis of patients with fulminant myocarditis. Methods: This is a retrospective study. A total of 88 patients with fulminant myocarditis admitted to Dongguan Kanghua hospital from Aug. 2008 to Dec. 2020 were included. Medical histories, results of laboratory tests, treatment regimens and clinical outcomes of these patients during their hospitalization were collected from the medical record system. According to the treatment methods, the patients were divided into MCS+immunomodulation group (38 cases), MCS group (20 cases) and traditional treatment group (30 cases). Patients in the MCS+immunomodulation group received intra-aortic balloon pump (IABP) or IABP combined with extracorporeal membrane oxygenation (ECMO) and immunoglobulin or glucocorticoid. Patients in the MCS group only received mechanical circulatory support. Patients in the traditional treatment group received neither mechanical circulatory support nor immunomodulatory therapy, and only used vasoactive drugs and cardiotonic drugs. The in-hospital mortality and length of stay were compared among the three groups. Results: A total of 88 patients with fulminant myocarditis aged (35.0±10.8) years were included, and there were 46 males (52.3%). The mortality of MCS+immunomodulation group (7.9% (3/38) vs. 56.7% (17/30), P=0.001 2) and MCS group (30.0% (6/20) vs. 56.7% (17/30), P=0.002 8) were lower than that of traditional treatment group. Compared with the MCS group, the in-hospital mortality in the MCS+immunomodulation group was lower (P=0.005 4). The most common cause of death was multiple organ dysfunction syndrome (MODS). The constituent ratios of death in MCS+immunomodulation group, MCS group and traditional treatment group were 3/3, 4/6 and 12/17, respectively. The incidence of MODS in the MCS group (20% (4/20)) and the traditional treatment group (40% (12/30)) was significantly higher than that in the MCS+immunomodulation group (7.9% (3/38)) (both P<0.01). In discharged patients, the hospitalization time of MCS+immunomodulation group was shorter than that of traditional treatment group ((13.4±5.5)d vs. (18.5±7.4)d, P<0.05) and MCS group ((13.4±5.5)d vs. (16.9±8.5)d, P<0.05). Conclusion: MCS combined with immunomodulatory therapy is associated with lower in-hospital mortality and shorter hospital stay in patients with fulminant myocarditis.
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Affiliation(s)
- Y C Jie
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
| | - Y W Jiang
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
| | - K J Liang
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
| | - X O Zhou
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
| | - C T Zhang
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
| | - Z Fu
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
| | - Y H Zhao
- Cardiovascular Intensive Care Unit, Dongguan Kanghua Hospital, Dongguan 523000, China
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Lin K, Zhou Y, Ai J, Wang YA, Zhang S, Qiu C, Lian C, Gao B, Liu T, Wang H, Zhang H, Zhang Y, Fu Z, Li D, Jiang N, Guo J, Wu J, Wang YO, Song S, Li Q, Yin Y, Xia J, Xu Y, Yeap LS, Zheng X, Gu Y, Liu H, Zhang W, Meng FL. B cell Receptor Signatures Associating with Strong and Poor SARS-CoV-2 Vaccine Response. Emerg Microbes Infect 2022; 11:452-464. [PMID: 35045787 PMCID: PMC8820815 DOI: 10.1080/22221751.2022.2030197] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [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] [Indexed: 01/07/2023]
Abstract
Breakthrough infection of SARS-CoV-2 is a serious challenge, as increased infections were documented in fully-vaccinated individuals. Recipients with poor antibody response are highly vulnerable to reinfection, whereas those with strong antibody responses achieve sterilizing immunity. Thus far, biomarkers associated with levels of vaccine-elicited antibody response are still lacking. Here, we studied the antibody response of age- and gender-controlled healthy cohort, who received inactivated SARS-CoV-2 vaccines and profiled the B cell receptor repertoires in longitudinally consecutive samples. Upon vaccination, all vaccinated individuals displayed a convergent antibody response with shared common antibody clones and public neutralizing antibodies. Strikingly, poor vaccine-responders are distinguishable from strong vaccine-responders by a biased V-usage before vaccination and IgG to IgM mRNA ratio. These findings reveal molecular signatures associated with the different levels of vaccine-induced antibody response, which could be further developed into biomarkers for the design of vaccination strategies.
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Affiliation(s)
- Ke Lin
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Yawen Zhou
- State Key Laboratory of Molecular Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Jingwen Ai
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Yan A Wang
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Senxin Zhang
- Department of Mathematics, Shanghai Normal University, Shanghai, China 200234
| | - Chao Qiu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China.,Key Laboratory of Medical Molecular Virology (MOE/MOH) and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Chaoyang Lian
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai, 200025, China
| | - Bo Gao
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai, 200025, China
| | - Tingting Liu
- State Key Laboratory of Molecular Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Hongyu Wang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Haocheng Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Yi Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Zhangfan Fu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Dan Li
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Ning Jiang
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai 200438, China
| | - Jingxin Guo
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Jing Wu
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China
| | - Yan O Wang
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Shusen Song
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Qiang Li
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Yanan Yin
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, P.R. China
| | - Jia Xia
- Department of Nephrology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, P.R. China
| | - Yingjie Xu
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, P.R. China
| | - Leng-Siew Yeap
- Shanghai Institute of Immunology, State Key Laboratory of Oncogenes and Related Genes, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai, 200025, China
| | - Xiaoqi Zheng
- Department of Mathematics, Shanghai Normal University, Shanghai, China 200234
| | - Ye Gu
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Hongyan Liu
- Liaoning Emergency Treatment and Innovation Center of Public Health Emergencies, The Sixth People's Hospital of Shenyang, Shenyang 110005, China
| | - Wenhong Zhang
- Department of Infectious Disease of Huashan Hospital, National Medical Center for Infectious Diseases and Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai 200040, China.,Key Laboratory of Medical Molecular Virology (MOE/MOH) and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.,State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai 200438, China.,National Clinical Research Centre for Aging & Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Fei-Long Meng
- State Key Laboratory of Molecular Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
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Yang J, Wang W, Luo Y, Huang S, Fu Z. Effect of pathological complete response after neoadjuvant chemoradiotherapy on postoperative complications of rectal cancer: a systematic review and meta-analysis. Tech Coloproctol 2022; 26:163-174. [PMID: 35048217 DOI: 10.1007/s10151-021-02564-y] [Citation(s) in RCA: 2] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 12/05/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Standard total mesorectal resection has become an important treatment option for locally advanced or high-risk rectal cancer after neoadjuvant chemo-radiotherapy. 15-27% of patients can achieve pathological complete response (PCR) after neoadjuvant chemo-radiotherapy (nCRT). However, the relationship between PCR and postoperative complications remains an important unsolved problem. The objective of this study was to determine whether PCR was associated with the rate of postoperative complications. METHODS This meta-analysis was implemented following the recommendations from Preferred Reporting Items for Systematic Reviews and Meta-Analyses. We searched electronic literature by PubMed, EMBASE, and Google Scholar. Major outcomes of interest included anastomotic leakage, surgical-site infection, reoperation, and any postoperative complications. Other outcomes comprised postoperative hemorrhage, ileus, and mortality. RESULTS Eleven thousand two hundred ninety patients in 9 studies were included in the meta-analysis. The pooled analysis revealed that patients with PCR did not have a higher risk of anastomotic leakage (OR = 1.22, 95% CI 0.92-1.62, p = 0.17), reoperation (OR = 1.13, 95% CI 0.93-1.37, p = 0.22), and any postoperative complications (OR = 1.02, 95% CI 0.91-1.15, p = 0.72) than patients with non-PCR. However, the meta-analysis showed that the PCR group was superior to the non-PCR group in terms of surgical-site infection (9.38% vs. 12.44%OR = 0.68, 95% CI 0.47-0.98; p = 0.04). CONCLUSION PCR might not be related to the occurrence of postoperative complications in rectal cancer patients following nCRT. In addition, PCR might be associated with a lower risk of surgical-site infection.
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Affiliation(s)
- J Yang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - W Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Y Luo
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - S Huang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Z Fu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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Fu Z, Yuan Y, Jiang M. Occupational burnout among clinical research associates in China. Occup Med (Lond) 2021; 71:336-342. [PMID: 34415348 DOI: 10.1093/occmed/kqab111] [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] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Clinical research associates (CRAs) play an important role in pharmaceutical research and development. Despite growing concern about occupational burnout among CRAs in China, little is known about this topic. AIMS We evaluated the factors associated with occupational burnout among CRAs in China and assessed the extent and nature of this syndrome in order to develop effective countermeasures. METHODS In October 2020, we collected data from a convenience sample of 438 CRAs from 26 major cities across China using a custom-designed questionnaire. We evaluated their psychopathological status and degree of occupational burnout based on the Maslach Burnout Inventory. Factors associated with burnout were identified using the Wilcoxon rank test, Kruskal-Wallis test, Spearman's rank correlation and multivariable ordinal logistic regression. RESULTS Of the 438 CRAs analyzed, 82% showed signs of occupational burnout, with a large proportion experiencing moderate burnout (50%). Burnout in Chinese CRAs manifested as emotional exhaustion (77%), depersonalization (66%) and low sense of accomplishment (15%). The severity of burnout was significantly affected by mode of working (odds ratio [OR] 1.56, 95% confidence interval [CI] 1.04-2.34), average number of working hours per week (OR 1.68, 95% CI 1.14-2.46), support provided by the hospital (OR 3.13, 95% CI 1.40-6.99) and likelihood of receiving a promotion (OR 4.05, 95% CI 1.34-12.22) (all P < 0.05). CONCLUSIONS The incidence of occupational burnout among CRAs in China is high. Companies and hospitals must take effective measures to establish support systems for CRAs in order to alleviate this situation and thereby ensure the quality of clinical trials.
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Affiliation(s)
- Z Fu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Drug Clinical Trial Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - Y Yuan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Drug Clinical Trial Center, Peking University Cancer Hospital & Institute, Beijing, China
| | - M Jiang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Drug Clinical Trial Center, Peking University Cancer Hospital & Institute, Beijing, China
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Liu Y, Liu J, Tan Z, Jiang X, Wang L, Lu Y, Fu X, Song Q, Zhao L, Yuan S, Bi N, Xu Y, Zhu Z, Zhu G, Li J, Xie C, Ma X, Xiao G, Ge H, Liu H, Zhao J, Liang J, Shen Q, Xu Q, Liu R, Zhou S, Kong W, Zhong W, Jin X, Wang Y, Jiang Y, Fu Z, Xie Y, Cai J, Li Z, Machtay M, Curran W, Kong F. P29.05 Gross Tumor Volume Contouring Variations in Radiation Therapy of Non-Small Cell Lung Cancer. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.08.400] [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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35
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Liu J, Jiang X, Tan Z, Li Z, Wang Y, Xie Y, Cai J, Zhu G, Li J, Xie C, Ma X, Xiao G, Liu H, Ge H, Zhao J, Liang J, Shen Q, Xu Q, Liu R, Zhou S, Zhong W, Kong W, Jiang Y, Xu Y, Fu Z, Liu Y, Zhu Z, Bi N, Yuan S, Zhao L, Song Q, Lu Y, Fu X, Wang L, Machtay M, Curran W, Kong F. P29.03 Thoracic Organs at Risk (OARs) Contouring Variations and Consensus in Radiation Therapy for Non-Small Cell Lung Cancer. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.08.398] [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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36
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Fu Z, Yang H, Han H, Jia D, Xu L, Su G, Wang Z. Effect of whole-grain rice on pellet quality, geese performance, and economic benefits. J APPL POULTRY RES 2021. [DOI: 10.1016/j.japr.2021.100176] [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] Open
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Xu ZW, Jiang ZL, Fu Z, Huang S. Changed expression of microRNAs may predict postoperative atrial fibrillation in patients with cardiac surgery. Eur Rev Med Pharmacol Sci 2021; 25:287-292. [PMID: 33506917 DOI: 10.26355/eurrev_202101_24394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Changes of microRNAs (miRNAs) may contribute to the pathogenesis and progression of postoperative atrial fibrillation (POAF) in patients undergoing cardiac valve surgery. This study aimed to measure the expression levels of miRNAs in peripheral blood, as well as their target mRNAs, in POAF patients and normal controls (non-POAF), and to evaluate the potential of miRNAs as promising biomarkers to predict POAF. PATIENTS AND METHODS The expression of miRNAs in peripheral blood, including miR-27b, miR-133a, miR-328, miR-499 and their target mRNAs, was analyzed in 109 POAF patients and 96 non-POAF patients via quantitative real-time polymerase chain reaction (RT-PCR). We compared differences between the two groups and also analyzed the treat reaction to amiodarone. RESULTS All miRNAs in POAF patients were significantly highly expressed. Compared to non-POAF, the expression of miR-27b, miR-133a, miR-328, miR-499 increased in both groups of POAF patients, and miR-499 was the only upregulated miRNAs in the amiodarone - group versus amiodarone + group and non-POAF. Among the upregulated miRNAs, miR-499 expression significantly changed in amiodarone + and amiodarone - patients (p = 0.005). The ROC curve analysis revealed that miR-499 might be a potential therapeutic response biomarker. The miRNA-mRNA interactions revealed 10 mRNAs regulated by miR-27b, miR-133a, and miR- 499. CONCLUSIONS We found an expression on miR-133a, miR-27b, miR-328, and miR-499 was significantly different between these groups, with a high expression being observed in POAF patients compared to non-POAF patients. Further, the present results showed that miR-499 was significantly upregulated in amiodarone - patients, compared to non-POAF, and amiodarone + patients. This finding indicates that miR-499 may be a potential biomarker for predicting the occurrence of POAF after cardiac valve surgery and treat the reaction to amiodarone.
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Affiliation(s)
- Z-W Xu
- Department of Cardiac Surgery, Huai'an First People's Hospital, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
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Chen H, Jin Z, Fu Z, Xia F. SK2 channel deletion reduces susceptibility to bupivacaine-induced cardiotoxicity in mouse. Hum Exp Toxicol 2021; 40:1796-1802. [PMID: 33887967 DOI: 10.1177/09603271211010912] [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] [Indexed: 11/17/2022]
Abstract
Bupivacaine is frequently used for regional anesthesia and postoperative analgesia. However, an inadvertent intravenous injection can cause severe cardiotoxicity, manifesting as arrhythmia, hypotension, and even cardiac asystole. The mechanism of bupivacaine-mediated cardiotoxicity remains unclear. SK2 knockout mice (SK) and wild-type mice (WT) were divided into four groups, with 12 mice per group. We determined the difference in bupivacaine cardiotoxicity between SK2 knockout and WT mice by measuring the time to the first arrhythmia (Tarrhythmia) and the time to asystole (Tasystole). Secondary indicators of cardiotoxicity were the time from the beginning of bupivacaine infusion to 20% prolongation of the QT interval (TQT) and the time to 20% widening of the QRS complex (TQRS). Tarrhythmia and Tasystole were significantly longer in the SK-bupi group than in the WT-bupi group (both P < 0.05). TQT and TQRS were longer in the SK-bupi group than in the WT-bupi group (all P < 0.05). The time to 25%, 50%, and 75% reduction in HR in the SK-bupi group was significantly longer than in the WT-bupi group (all P < 0.05). Knocking out the SK2 channel can reduce bupivacaine-induced cardiotoxicity in the mouse.
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Affiliation(s)
- H Chen
- Department of Anesthesiology, 89657First Affiliated Hospital, Wenzhou Medical University, Zhejiang, China
| | - Z Jin
- Department of Anesthesiology, 89657First Affiliated Hospital, Wenzhou Medical University, Zhejiang, China
| | - Z Fu
- Department of Pain Management, 66555Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - F Xia
- Department of Anesthesiology, 89657First Affiliated Hospital, Wenzhou Medical University, Zhejiang, China
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Abstract
Apelin has been reported to regulate mitochondrial function in myocardial ischemia-reperfusion injury and cerebral ischemia-reperfusion injury. However, the role of apelin-13 in lung ischemia-reperfusion injury (LIRI) remains unclear. This study established an experimental rat model to evaluate the underlying mechanisms of apelin-13 on LIRI. Twenty-four rats were randomly divided to sham operation group (group SM), ischemia/reperfusion group (group IR), and apelin-13 treatment group (group APL). The effects of apelin-13 on LIRI were determined histologically using H&E staining, while the wet/dry weight ratio was used to assess lung edema caused by LIRI. Inflammatory cytokines were also detected in Bronchoalveolar lavage (BAL) fluid by ELISA. The protein expression of UCP2 and the morphological changes of mitochondria were determined by western blotting and electromicroscopy, respectively. The results demonstrated the structural damage of lung tissues and lung edema in group IR. An increased level of inflammatory cytokines including IL-1β, IL-6 and TNF-α was observed in rats with LIRI using ELISA. After that, oxidative stress and morphological damage of mitochondria were also shown in group IR. Yet, the application of apelin-13 reversed all these deleterious effects in group APL. The protective effects of apelin-13 were indicated by decreased reactive oxygen species (ROS) and elevated UCP2 expression levels in rats. In conclusion, this study revealed that apelin-13 had protective effects against LIRI via attenuating lung edema, the production of inflammatory cytokines, oxidative stress and mitochondrial dysfunction.
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Affiliation(s)
- F Xia
- Department of Pain Management, Shandong Provincial Hospital, Cheeloo College of Medicine, 12589Shandong University, Jinan, Shandong Province, China
- Department of Anesthesiology, 89657The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - H Chen
- Department of Anesthesiology, 89657The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - Z Jin
- Department of Anesthesiology, 89657The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - Z Fu
- Department of Pain Management, Shandong Provincial Hospital, Cheeloo College of Medicine, 12589Shandong University, Jinan, Shandong Province, China
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Li H, Arslan M, Fu Z, Lee H, Mikula M. Family History of Crohn’s Disease (CD) May Be a Risk Factor for Developing de novo CD following Ileal Pouch Anal Anastomosis (IPAA) for Ulcerative Colitis (UC). Am J Clin Pathol 2020. [DOI: 10.1093/ajcp/aqaa161.328] [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: 11/13/2022] Open
Abstract
Abstract
Introduction/Objective
A subset of patients with an established diagnosis of UC develops signs of CD (de novo CD) following IPAA. While the etiology and risk factors of de novo CD remain largely unknown, preliminary studies have shown controversial results regarding family history of inflammatory bowel disease (IBD) and smoking history.
Methods
Patients that underwent IPAA for UC, with at least 1 year of follow-up, were identified (n=161; 1996 to 2018). We retrospectively reviewed the electronic medical records. Patients that were diagnosed with de novo CD during the follow-up period were further identified. Smoking history and family history of IBD were evaluated. Chi square test was performed to compare the frequencies. Odds ratio (OR) and 95% confidence intervals (CIs) were estimated by logistic regression model. P<0.05 was considered statistically significant.
Results
29 de novo CD were identified. At the time of proctocolectomy, the family history of IBD and smoking history was documented in 152 UC patients including 27 that subsequently developed de novo CD. 23 of 152 had a family history of IBD (12 UC, 9 CD and 2 IBD, NOS). 19/129 (14.7%) UC patients without a family history of any type of IBD, 4/9 (44.4%) with a family history of CD, and 4/12 (33.3%) with a family history of UC developed de novo CD. Patients with a family history of CD were more likely to develop de novo CD post IPAA than those without a family history of any type of IBD (OR 4.63, 95% CI 1.14-18.82, p=0.03). Family history of UC did not correlate with development of de novo CD (OR 2.90; 95% CI 0.79-10.57, p=0.108). At the time of proctocoletomy, 11 were current smokers, 25 were former smokers, and 116 never smoked. In de novo CD group, there were 4/27 (14.8 %) former smokers and 23/27 (85.2 %) never smokers. No de novo CD patient was current smoker. In the UC group that remained as UC following IPAA, 11/125 (8.8%) were current smokers, 21/125 (16.8 %) former smokers, and 93/125 (74.4 %) were never smokers. Current smoking status was not associated with development of de novo CD (p = 0.214).
Conclusion
Family history of CD may be a risk factor for developing de novo CD following IPAA for UC. Current smoking status was not associated with development of de novo CD following IPAA for UC.
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Affiliation(s)
- H Li
- Pathology, Albany Medical Center, Albany, New York, UNITED STATES
| | - M Arslan
- Pathology, Albany Medical Center, Albany, New York, UNITED STATES
| | - Z Fu
- Pathology, Albany Medical Center, Albany, New York, UNITED STATES
| | - H Lee
- Pathology, Albany Medical Center, Albany, New York, UNITED STATES
| | - M Mikula
- Albany Medical College, Albany, New York, UNITED STATES
- E. Lee, Department of Surgery, Albany Medical Center, Albany, New York, UNITED STATES
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Bastos A, Fu Z, Ciais P, Friedlingstein P, Sitch S, Pongratz J, Weber U, Reichstein M, Anthoni P, Arneth A, Haverd V, Jain A, Joetzjer E, Knauer J, Lienert S, Loughran T, McGuire PC, Obermeier W, Padrón RS, Shi H, Tian H, Viovy N, Zaehle S. Impacts of extreme summers on European ecosystems: a comparative analysis of 2003, 2010 and 2018. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190507. [PMID: 32892728 DOI: 10.1098/rstb.2019.0507] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In Europe, three widespread extreme summer drought and heat (DH) events have occurred in 2003, 2010 and 2018. These events were comparable in magnitude but varied in their geographical distribution and biomes affected. In this study, we perform a comparative analysis of the impact of the DH events on ecosystem CO2 fluxes over Europe based on an ensemble of 11 dynamic global vegetation models (DGVMs), and the observation-based FLUXCOM product. We find that all DH events were associated with decreases in net ecosystem productivity (NEP), but the gross summer flux anomalies differ between DGVMs and FLUXCOM. At the annual scale, FLUXCOM and DGVMs indicate close to neutral or above-average land CO2 uptake in DH2003 and DH2018, due to increased productivity in spring and reduced respiration in autumn and winter compensating for less photosynthetic uptake in summer. Most DGVMs estimate lower gross primary production (GPP) sensitivity to soil moisture during extreme summers than FLUXCOM. Finally, we show that the different impacts of the DH events at continental-scale GPP are in part related to differences in vegetation composition of the regions affected and to regional compensating or offsetting effects from climate anomalies beyond the DH centres. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
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Affiliation(s)
- A Bastos
- Department of Geography, Ludwig Maximilians Universität, Luisenstrasse 37, 80333 Munich, Germany
| | - Z Fu
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
| | - P Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
| | - P Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK
| | - S Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK
| | - J Pongratz
- Department of Geography, Ludwig Maximilians Universität, Luisenstrasse 37, 80333 Munich, Germany.,Max Planck Institute for Meteorology, 20146 Hamburg, Germany
| | - U Weber
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
| | - M Reichstein
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
| | - P Anthoni
- Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research / Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
| | - A Arneth
- Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research / Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
| | - V Haverd
- CSIRO Oceans and Atmosphere, Canberra 2601, Australia
| | - A Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
| | - E Joetzjer
- Laboratoire Evolution et Diversite Biologique UMR 5174, CNRS Universite Paul Sabatier, Toulouse, France
| | - J Knauer
- CSIRO Oceans and Atmosphere, Canberra 2601, Australia
| | - S Lienert
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
| | - T Loughran
- Department of Geography, Ludwig Maximilians Universität, Luisenstrasse 37, 80333 Munich, Germany
| | - P C McGuire
- Department of Meteorology, University of Reading, Earley Gate, Reading RG6 6BB, UK
| | - W Obermeier
- Department of Geography, Ludwig Maximilians Universität, Luisenstrasse 37, 80333 Munich, Germany
| | - R S Padrón
- Department of Environmental Systems Science, Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
| | - H Shi
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL 36849, USA
| | - H Tian
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL 36849, USA
| | - N Viovy
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
| | - S Zaehle
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
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Han DL, Wang LL, Zhang GF, Yang WF, Chai J, Lin HM, Fu Z, Yu JM. MiRNA-485-5p, inhibits esophageal cancer cells proliferation and invasion by down-regulating O-linked N-acetylglucosamine transferase. Eur Rev Med Pharmacol Sci 2020; 23:2809-2816. [PMID: 31002132 DOI: 10.26355/eurrev_201904_17556] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Previous reports suggest that miRNA-485-5p is dysregulated and contributes to tumorigenesis in some cancer types. Nevertheless, the biological role of miRNA-485-5p in esophageal cancer (EC) is not well understood. Additionally, we found that the expression of miR-485-5p in EC tissues was aberrant. PATIENTS AND METHODS Quantitative RT-PCR (qRT-PCR) was used to demonstrate the expression of miRNA-485-5p in EC cell lines. Cell counting kit-8 (CCK-8) assay and transwell assay indicated that miRNA-485-5p overexpression inhibited cell proliferation, migration, and invasion in EC cell lines. Additionally, Western blotting, dual-luciferase reporter assay, and rescue assay predicted that O-linked N-acetylglucosamine transferase (OGT) was a direct target of miRNA-485-5p. Moreover, we showed that miRNA-485-5p regulated EC tumorigenesis by down-regulating OGT expression in vitro and in vivo. RESULTS The upregulation of miR-485-5p (fold change = 44 and 26 in ECA109 and TE-1, respectively; p<0.001) was showed by qRT-PCR. Compared with the control groups, the expression miR-485-5p significantly suppressed the proliferation, migration, and invasion of EC cells. The bioinformatic analysis predicted that the 3' untranslated region (UTR) of OGT contains one miR-485-5p target sequences. Western blotting and dual-luciferase reporter assay showed that activation of OGT 3'UTR was increased by co-transfection with miR-485-5p. Finally, CCK-8 assay predicted that the rescue effects of OGT expression on miR-485-5p induced inhibition of cell growth and tumor weight in Eca109 and TE1 cells. CONCLUSIONS Our results suggest that miRNA-485-5p is a suppressor of EC tumorigenesis and could serve as a novel candidate for therapeutic applications in EC treatment.
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Affiliation(s)
- D-L Han
- Department of Radiation Oncology, Shandong University Affiliated Shandong Cancer Hospital and Institute, Jinan, Shandong Province, China.
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Bastos A, Ciais P, Friedlingstein P, Sitch S, Pongratz J, Fan L, Wigneron JP, Weber U, Reichstein M, Fu Z, Anthoni P, Arneth A, Haverd V, Jain AK, Joetzjer E, Knauer J, Lienert S, Loughran T, McGuire PC, Tian H, Viovy N, Zaehle S. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity. Sci Adv 2020; 6:eaba2724. [PMID: 32577519 PMCID: PMC7286671 DOI: 10.1126/sciadv.aba2724] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 04/14/2020] [Indexed: 05/23/2023]
Abstract
In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming.
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Affiliation(s)
- A. Bastos
- Department of Geography, Ludwig Maximilian University of Munich, Munich, Luisenstr. 37, 80333 Munich, Germany
| | - P. Ciais
- Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
| | - P. Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK
- LMD/IPSL, ENS, PSL Université, École Polytechnique, Institut Polytechnique de Paris, Sorbonne Université, CNRS, Paris, France
| | - S. Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK
| | - J. Pongratz
- Department of Geography, Ludwig Maximilian University of Munich, Munich, Luisenstr. 37, 80333 Munich, Germany
- Max Planck Institute for Meteorology, 20146 Hamburg, Germany
| | - L. Fan
- ISPA, UMR 1391, INRA Nouvelle-Aquitaine, Université de Bordeaux, Grande Ferrage, Villenave d’Ornon, France
| | - J. P. Wigneron
- ISPA, UMR 1391, INRA Nouvelle-Aquitaine, Université de Bordeaux, Grande Ferrage, Villenave d’Ornon, France
| | - U. Weber
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
| | - M. Reichstein
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
| | - Z. Fu
- Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
| | - P. Anthoni
- Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
| | - A. Arneth
- Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
| | - V. Haverd
- CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia
| | - A. K. Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
| | - E. Joetzjer
- CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
| | - J. Knauer
- CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia
| | - S. Lienert
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern CH-3012, Switzerland
| | - T. Loughran
- Department of Geography, Ludwig Maximilian University of Munich, Munich, Luisenstr. 37, 80333 Munich, Germany
| | - P. C. McGuire
- Department of Meteorology, Department of Geography & Environmental Science, and National Centre for Atmospheric Science, University of Reading, Earley Gate, RG66BB Reading, UK
| | - H. Tian
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL 36849, USA
| | - N. Viovy
- Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
| | - S. Zaehle
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
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Moya EA, Go A, CB K, Fu Z, TS S, FL P. Neuronal HIF-1α in the nucleus tractus solitarius contributes to ventilatory acclimatization to hypoxia. J Physiol 2020; 598:2021-2034. [PMID: 32026480 PMCID: PMC7230006 DOI: 10.1113/jp279331] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [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: 11/22/2019] [Accepted: 02/04/2020] [Indexed: 12/21/2022] Open
Abstract
KEY POINTS We hypothesized that hypoxia inducible factor 1α (HIF-1α) in CNS respiratory centres is necessary for ventilatory acclimatization to hypoxia (VAH); VAH is a time-dependent increase in baseline ventilation and the hypoxic ventilatory response (HVR) occurring over days to weeks of chronic sustained hypoxia (CH). Constitutive deletion of HIF-1α in CNS neurons in transgenic mice tended to blunt the increase in HVR that occurs in wild-type mice with CH. Conditional deletion of HIF-1α in glutamatergic neurons of the nucleus tractus solitarius during CH significantly decreased ventilation in acute hypoxia but not normoxia in CH mice. These effects are not explained by changes in metabolic rate, nor CO2 , and there were no changes in the HVR in normoxic mice. HIF-1α mediated changes in gene expression in CNS respiratory centres are necessary in addition to plasticity of arterial chemoreceptors for normal VAH. ABSTRACT Chronic hypoxia (CH) produces a time-dependent increase of resting ventilation and the hypoxic ventilatory response (HVR) that is called ventilatory acclimatization to hypoxia (VAH). VAH involves plasticity in arterial chemoreceptors and the CNS [e.g. nucleus tractus solitarius (NTS)], although the signals for this plasticity are not known. We hypothesized that hypoxia inducible factor 1α (HIF-1α), an O2 -sensitive transcription factor, is necessary in the NTS for normal VAH. We tested this in two mouse models using loxP-Cre gene deletion. First, HIF-1α was constitutively deleted in CNS neurons (CNS-HIF-1α-/- ) by breeding HIF-1α floxed mice with mice expressing Cre-recombinase driven by the calcium/calmodulin-dependent protein kinase IIα promoter. Second, HIF-1α was deleted in NTS neurons in adult mice (NTS-HIF-1α-/- ) by microinjecting adeno-associated virus that expressed Cre-recombinase in HIF-1α floxed mice. In normoxic control mice, HIF-1α deletion in the CNS or NTS did not affect ventilation, nor the acute HVR (10-15 min hypoxic exposure). In mice acclimatized to CH for 1 week, ventilation in hypoxia was blunted in CNS-HIF-1α-/- and significantly decreased in NTS-HIF-1α-/- compared to control mice (P < 0.0001). These changes were not explained by differences in metabolic rate or CO2 . Immunofluorescence showed that HIF-1α deletion in NTS-HIF-1α-/- was restricted to glutamatergic neurons. The results indicate that HIF-1α is a necessary signal for VAH and the previously described plasticity in glutamatergic neurotransmission in the NTS with CH. HIF-1α deletion had no effect on the increase in normoxic ventilation with acclimatization to CH, indicating this is a distinct mechanism from the increased HVR with VAH.
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Affiliation(s)
- Esteban A. Moya
- Section of Physiology, Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of California, San Diego, La Jolla, California, 92093-0623, USA
- Centro de Investigación en Fisiología del Ejercicio, Universidad Mayor, Santiago, 8340589, Chile
| | - A Go
- Section of Physiology, Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of California, San Diego, La Jolla, California, 92093-0623, USA
| | - Kim CB
- Providence Medical Institute, Torrance, California, 90503, USA
| | - Z Fu
- Section of Physiology, Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of California, San Diego, La Jolla, California, 92093-0623, USA
| | - Simonson TS
- Section of Physiology, Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of California, San Diego, La Jolla, California, 92093-0623, USA
| | - Powell FL
- Section of Physiology, Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of California, San Diego, La Jolla, California, 92093-0623, USA
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Yang H, Tan Q, Chen GH, Chen JS, Fu Z, Ren FL, Luo XY, Wang H. Plasma retinol as a predictive biomarker of disease activity and response to acitretin monotherapy in children with generalized pustular psoriasis. J Eur Acad Dermatol Venereol 2020; 34:e270-e272. [PMID: 31991497 DOI: 10.1111/jdv.16244] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- H Yang
- Department of Dermatology, Children's Hospital of Chongqing Medical University, Chongqing, China.,Chongqing Key Laboratory of Pediatrics, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Q Tan
- Chongqing Key Laboratory of Pediatrics, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - G H Chen
- Ministry of Education Key Laboratory of Child Development and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - J S Chen
- National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Z Fu
- China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - F L Ren
- Department of Dermatology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - X Y Luo
- National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - H Wang
- Department of Dermatology, Children's Hospital of Chongqing Medical University, Chongqing, China.,National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
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Xie WY, Fu Z, Pan NX, Yan HC, Wang XQ, Gao CQ. Leucine promotes the growth of squabs by increasing crop milk protein synthesis through the TOR signaling pathway in the domestic pigeon (Columba livia). Poult Sci 2020; 98:5514-5524. [PMID: 31172174 DOI: 10.3382/ps/pez296] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [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: 01/03/2019] [Accepted: 05/24/2019] [Indexed: 12/18/2022] Open
Abstract
Leucine (Leu) plays a critical regulatory role in protein synthesis, however, the effects and molecular mechanisms of Leu on crop milk protein in the domestic pigeons (Columba livia) are still unknown. Therefore, the study aimed to investigate the effects of dietary Leu supplementation on crop milk protein synthesis and the growth performance of squabs and the possible underlying mechanism. A total of 240 pairs of breeding pigeons (1102.3 ± 9.5 g/pair) were randomly assigned to 1 of 5 treatments, including a positive control (PC) diet that had adequate crude protein (crude protein, CP = 18%; Leu = 1.30%), a negative control (NC) diet that was low in CP (CP = 16%, Leu = 1.30%), and NC diets supplemented with Leu at 0.15%, 0.45%, or 1.05%. Compared with the NC diet, 0.15 to 0.45% Leu supplementation decreased BW loss and increased relative crop weight, crop thickness, and protein levels in the crop tissue and milk of breeding pigeons. However, dietary supplementation with 1.05% Leu inhibited ADFI in breeding pigeons. Dietary supplementation with 0.15 to 0.45% Leu decreased the mortality rate and increased the BW, eviscerated yield, and breast muscle yield of young squabs. The protein expression levels of the target of rapamycin (TOR), ribosomal protein S6 kinase 1 (S6K1), ribosomal protein S6 kinase (S6), eukaryotic initiation factor 4E binding protein 1 (4EBP1), and eukaryotic translation initiation factor 4E (eIF4E) were upregulated in the crop tissue of breeding pigeons in PC, 0.15% and 0.45% Leu-supplemented groups. Collectively, these results indicated that 0.15 to 0.45% Leu supplementation could decrease BW loss, increase milk protein synthesis in the crop of breeding pigeons, and enhance the survival rate and growth performance of young squabs through the TOR signaling pathway.
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Affiliation(s)
- W Y Xie
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, China
| | - Z Fu
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, China
| | - N X Pan
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, China
| | - H C Yan
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, China
| | - X Q Wang
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, China
| | - C Q Gao
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, China
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Chen MJ, Fu Z, Jiang SG, Wang XQ, Yan HC, Gao CQ. Targeted disruption of TORC1 retards young squab growth by inhibiting the synthesis of crop milk protein in breeding pigeon (Columba livia). Poult Sci 2020; 99:416-422. [PMID: 32416826 PMCID: PMC7587900 DOI: 10.3382/ps/pez513] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 08/22/2019] [Indexed: 12/18/2022] Open
Abstract
This study was conducted to explore the regulatory role of the target of rapamycin complex 1 (TORC1) signaling pathway in crop milk synthesis in breeding pigeons (Columba livia). Three groups of breeding pigeons in the lactation period (n = 30 pairs/group) were respectively injected with rapamycin (RAPA, a specific inhibitor of the target of rapamycin complex) at doses of 0 (vehicle, control), 0.6, or 1.2 mg/kg body weight (BW)/day via the wing vein for 7 days. The average daily feed intake (ADFI) and BW of the breeding pigeons and the BW of young squabs were respectively recorded throughout the experimental period. The breeding pigeons were sacrificed to collect their crop tissues, crop milk, and serum on the eighth day of the experiment. The results showed that neither 0.6 nor 1.2 mg/kg BW RAPA injection affected BW loss or ADFI in breeding pigeons (P > 0.05), while crop thickness and crop relative weight were significantly decreased (P < 0.05) in the 1.2 mg/kg BW rapamycin-injected group. Simultaneously, RAPA (especially at 1.2 mg/kg BW) decreased the crude protein, αs1-casein, αs2-casein, β-casein, and amino acid contents (Asp, Thr, Ser, Glu, Gly, Ala, Cys, Val, Met, Ile, Leu, Tyr, Lys, His, Arg, and Pro) of crop milk (P < 0.05) and the concentrations of albumin, total protein, and uric acid in the serum of breeding pigeons (P < 0.05). Additionally, the expression of TORC1 pathway-related proteins (TORC1, S6K1, S6, 4EBP1, and eIF4E) was downregulated in the crop tissues of breeding pigeons by 0.6 or 1.2 mg/kg BW/day RAPA injection (P < 0.05). Accordingly, the average daily gain (ADG) of young squabs declined, and the mortality rate increased significantly (P < 0.05). Together, the results showed that RAPA reduced protein and amino acid levels in the crop milk of breeding pigeons and retarded young squab growth, suggesting a crucial role of TORC1 in crop milk synthesis in breeding pigeons.
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Affiliation(s)
- M J Chen
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/National Engineering Research Center for Breeding Swine Industry, Guangzhou, Guangdong 510642, China
| | - Z Fu
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/National Engineering Research Center for Breeding Swine Industry, Guangzhou, Guangdong 510642, China
| | - S G Jiang
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/National Engineering Research Center for Breeding Swine Industry, Guangzhou, Guangdong 510642, China
| | - X Q Wang
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/National Engineering Research Center for Breeding Swine Industry, Guangzhou, Guangdong 510642, China
| | - H C Yan
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/National Engineering Research Center for Breeding Swine Industry, Guangzhou, Guangdong 510642, China
| | - C Q Gao
- College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/National Engineering Research Center for Breeding Swine Industry, Guangzhou, Guangdong 510642, China.
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Li L, Yuan S, Yu J, Liu N, Zhang H, Tao R, Zhao S, Chen Z, Fu Z, Li W, Gao Y. Potential Imaging Biomarkers Predictive of the Response to Bevacizumab Combined with Conventional Therapy in Newly Diagnosed Glioblastoma. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.2297] [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: 11/17/2022]
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Iacocca E, Liu TM, Reid AH, Fu Z, Ruta S, Granitzka PW, Jal E, Bonetti S, Gray AX, Graves CE, Kukreja R, Chen Z, Higley DJ, Chase T, Le Guyader L, Hirsch K, Ohldag H, Schlotter WF, Dakovski GL, Coslovich G, Hoffmann MC, Carron S, Tsukamoto A, Kirilyuk A, Kimel AV, Rasing T, Stöhr J, Evans RFL, Ostler T, Chantrell RW, Hoefer MA, Silva TJ, Dürr HA. Spin-current-mediated rapid magnon localisation and coalescence after ultrafast optical pumping of ferrimagnetic alloys. Nat Commun 2019; 10:1756. [PMID: 30988403 PMCID: PMC6465265 DOI: 10.1038/s41467-019-09577-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 03/13/2019] [Indexed: 11/09/2022] Open
Abstract
Sub-picosecond magnetisation manipulation via femtosecond optical pumping has attracted wide attention ever since its original discovery in 1996. However, the spatial evolution of the magnetisation is not yet well understood, in part due to the difficulty in experimentally probing such rapid dynamics. Here, we find evidence of a universal rapid magnetic order recovery in ferrimagnets with perpendicular magnetic anisotropy via nonlinear magnon processes. We identify magnon localisation and coalescence processes, whereby localised magnetic textures nucleate and subsequently interact and grow in accordance with a power law formalism. A hydrodynamic representation of the numerical simulations indicates that the appearance of noncollinear magnetisation via optical pumping establishes exchange-mediated spin currents with an equivalent 100% spin polarised charge current density of 107 A cm-2. Such large spin currents precipitate rapid recovery of magnetic order after optical pumping. The magnon processes discussed here provide new insights for the stabilization of desired meta-stable states.
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Affiliation(s)
- E Iacocca
- Department of Applied Mathematics, University of Colorado, Boulder, CO, 80309, USA
- National Institute of Standards and Technology, Boulder, CO, 80305, USA
- Department of Physics, Division for Theoretical Physics, Chalmers University of Technology, Gothenburg, 412 96, Sweden
| | - T-M Liu
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - A H Reid
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - Z Fu
- School of Physics, Science, and Engineering, Tongji University, Shanghai, 200092, China
| | - S Ruta
- Department of Physics, University of York, York, YO10 5DD, UK
| | - P W Granitzka
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - E Jal
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - S Bonetti
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
- Department of Physics, Stockholm University, Stockholm, 106 91, Sweden
- Department of Molecular Science and Nanosystems, Ca' Foscari University of Venice, Venezia-Mestre, 30172, Italy
| | - A X Gray
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
- Department of Physics, Temple University, 1925 N. 12th St., Philadelphia, PA, 19122, USA
| | - C E Graves
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - R Kukreja
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - Z Chen
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - D J Higley
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - T Chase
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - L Le Guyader
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
- Spectroscopy & Coherent Scattering, European X-Ray Free-Electron Laser Facility GmbH, Holzkoppel 4, 22869, Schenefeld, Germany
| | - K Hirsch
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - H Ohldag
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - W F Schlotter
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - G L Dakovski
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - G Coslovich
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - M C Hoffmann
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - S Carron
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - A Tsukamoto
- Department of Electronics and Computer Science, Nihon University, 7-24-1 Narashino-dai Funabashi, Chiba, 274-8501, Japan
| | - A Kirilyuk
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
| | - A V Kimel
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
| | - Th Rasing
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
| | - J Stöhr
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA
| | - R F L Evans
- Department of Physics, University of York, York, YO10 5DD, UK
| | - T Ostler
- Physique des Matériaux et Nanostructures, Université de Liège, Liège, B-4000, Sart Tilman, Belgium
- Faculty of Arts, Computing, Engineering and Sciences, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK
| | - R W Chantrell
- Department of Physics, University of York, York, YO10 5DD, UK
- Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
| | - M A Hoefer
- Department of Applied Mathematics, University of Colorado, Boulder, CO, 80309, USA
| | - T J Silva
- National Institute of Standards and Technology, Boulder, CO, 80305, USA
| | - H A Dürr
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA.
- Department of Physics and Astronomy, Uppsala University, Box 516, 751 20, Uppsala, Sweden.
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Fu Z, Li W, Wu H, Huang X, Li J, Sun C, Tang J, Yin Y. Abstract P5-07-15: Adipose-derived peptides from breast cancer patients promote the malignancy of breast cancer MCF-7 cells. Cancer Res 2019. [DOI: 10.1158/1538-7445.sabcs18-p5-07-15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Adipose stromal/stem cells (ADSCs) could regulate malignancy behaviors of breast cancer, which was due to adipose-derived cytokines in part, such as leptin and resistin. Recently, peptides have been demonstrated to be potential targets for cancer therapy. It's valuable to analyze the characters of adipose-secreted peptides systematically. In this study, we isolated primary adipocytes from adipose tissue adjacent to breast tumor and breast benign lesions respectively, and then co-cultured breast cancer cells MCF-7 with tumor adjacent adipocytes (TAAs)/breast benign adipocytes (BBAs) separately. Compared to BBAs, TAAs could promote proliferation and migration ability of MCF-7. Then we extracted and purified peptides from supernatant of TAAs and BBAs using ultrafiltration, and the effects of TAAs-derived peptides compound on breast cancer cells appeared accordance with the adipose cells. 100 peptides, which were derived from 90 protein precursors, were found to be differentially secreted between TAAs and BBAs by LC-MS/MS (p < 0.05). Gene Ontology (GO) and Pathway analyses appeared that these altered peptides were mainly contributed to cell adhesion, and regulation of Ras-protein signal transduction. These results showed that these differentially secreted peptides could regulate breast cancer cell malignancy, which indicated that they could be potential therapeutic targets and diagnostic bio-marker for breast cancer.
Citation Format: Fu Z, Li W, Wu H, Huang X, Li J, Sun C, Tang J, Yin Y. Adipose-derived peptides from breast cancer patients promote the malignancy of breast cancer MCF-7 cells [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-07-15.
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Affiliation(s)
- Z Fu
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - W Li
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - H Wu
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - X Huang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - J Li
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - C Sun
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - J Tang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
| | - Y Yin
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Nanjing Maternal and Child Health Medical Institute, The Affiliated Obstetrics and Gybecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China; Northwestern University, Chicago, IL
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