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Huang M, Fu B, Yin C, Gong P, Liu S, Yang J, Wei X, Liang J, Xue H, He C, Du T, Wang C, Ji Y, Hu J, Zhang R, Du H, Zhang Y, Yang X. Cytochrome P450 CYP6EM1 Underpins Dinotefuran Resistance in the Whitefly Bemisia tabaci. J Agric Food Chem 2024; 72:5153-5164. [PMID: 38427964 DOI: 10.1021/acs.jafc.3c06953] [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: 03/03/2024]
Abstract
Being a destructive pest worldwide, the whitefly Bemisia tabaci has evolved resistance to neonicotinoid insecticides. The third-generation neonicotinoid dinotefuran has commonly been applied to the control of the whitefly, but its underlying mechanism is currently unknown. On the base of our transcriptome data, here we aim to investigate whether the cytochrome P450 CYP6EM1 underlies dinotefuran resistance in the whitefly. Compared to the susceptible strain, the CYP6EM1 gene was found to be highly expressed in both laboratory and field dinotefuran-resistant populations. Upon exposure to dinotefuran, the mRNA levels of CYP6EM1 were increased. These results demonstrate the involvement of this gene in dinotefuran resistance. Loss and gain of functional studies in vivo were conducted through RNAi and transgenic Drosophila melanogaster assays, confirming the role of CYP6EM1 in conferring such resistance. In a metabolism assay in vitro, the CYP6EM1 protein could metabolize 28.11% of dinotefuran with a possible dinotefuran-dm-NNO metabolite via UPLC-QTOF/MS. Docking of dinotefuran to the CYP6EM1 protein showed a good binding affinity, with an energy of less than -6.0 kcal/mol. Overall, these results provide compelling evidence that CYP6EM1 plays a crucial role in the metabolic resistance of B. tabaci to dinotefuran. Our work provides new insights into the mechanism underlying neonicotinoid resistance and applied knowledge that can contribute to sustainable control of a global pest such as whitefly.
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Affiliation(s)
- Mingjiao Huang
- College of Plant Protection, Hunan Agricultural University, Changsha 410125, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- The Ministry of Agriculture and Rural Affairs Key Laboratory of Integrated Pest Management of Tropical Crops, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, P. R. China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, P. R. China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shaonan Liu
- College of Plant Protection, Hunan Agricultural University, Changsha 410125, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuegao Wei
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, P. R. China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, P. R. China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, P. R. China
| | - Yao Ji
- College of Plant Protection, Hunan Agricultural University, Changsha 410125, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - JinYu Hu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, P. R. China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, P. R. China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Youjun Zhang
- College of Plant Protection, Hunan Agricultural University, Changsha 410125, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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Kuraoka T, Goto S, Kanno M, Díaz-Tendero S, Reino-González J, Trinter F, Pier A, Sommerlad L, Melzer N, McGinnis OD, Kruse J, Wenzel T, Jahnke T, Xue H, Kishimoto N, Yoshikawa K, Tamura Y, Ota F, Hatada K, Ueda K, Martín F. Tracing Photoinduced Hydrogen Migration in Alcohol Dications from Time-Resolved Molecular-Frame Photoelectron Angular Distributions. J Phys Chem A 2024; 128:1241-1249. [PMID: 38324399 PMCID: PMC10895665 DOI: 10.1021/acs.jpca.3c07640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/12/2024] [Accepted: 01/16/2024] [Indexed: 02/09/2024]
Abstract
The recent implementation of attosecond and few-femtosecond X-ray pump/X-ray probe schemes in large-scale free-electron laser facilities has opened the way to visualize fast nuclear dynamics in molecules with unprecedented temporal and spatial resolution. Here, we present the results of theoretical calculations showing how polarization-averaged molecular-frame photoelectron angular distributions (PA-MFPADs) can be used to visualize the dynamics of hydrogen migration in methanol, ethanol, propanol, and isopropyl alcohol dications generated by X-ray irradiation of the corresponding neutral species. We show that changes in the PA-MFPADs with the pump-probe delay as a result of intramolecular photoelectron diffraction carry information on the dynamics of hydrogen migration in real space. Although visualization of this dynamics is more straightforward in the smaller systems, methanol and ethanol, one can still recognize the signature of that motion in propanol and isopropyl alcohol and assign a tentative path to it. A possible pathway for a corresponding experiment requires an angularly resolved detection of photoelectrons in coincidence with molecular fragment ions used to define a molecular frame of reference. Such studies have become, in principle, possible since the first XFELs with sufficiently high repetition rates have emerged. To further support our findings, we provide experimental evidence of H migration in ethanol-OD from ion-ion coincidence measurements performed with synchrotron radiation.
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Affiliation(s)
- T. Kuraoka
- Department
of Physics, University of Toyama, Gofuku 3190, Toyama 930-8555, Japan
| | - S. Goto
- Department
of Physics, University of Toyama, Gofuku 3190, Toyama 930-8555, Japan
| | - M. Kanno
- Department
of Chemistry, Tohoku University, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8578, Japan
| | - S. Díaz-Tendero
- Departamento
de Química, Universidad Autónoma
de Madrid, Madrid 28049, Spain
- Condensed
Matter Physics Center (IFIMAC), Universidad
Autónoma de Madrid, Madrid 28049, Spain
- Institute
for Advanced Research in Chemical Sciences (IAdChem), Universidad Autónoma de Madrid, Madrid 28049, Spain
| | - J. Reino-González
- Instituto
Madrileño de Estudios Avanzados en Nanociencia (IMDEA-Nano), Campus de Cantoblanco, Madrid 28049, Spain
| | - F. Trinter
- Molecular
Physics, Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, Berlin 14195, Germany
| | - A. Pier
- Institut
für Kernphysik, Goethe-Universität
Frankfurt, Max-von-Laue-Straβe 1, Frankfurt am
Main 60438, Germany
| | - L. Sommerlad
- Institut
für Kernphysik, Goethe-Universität
Frankfurt, Max-von-Laue-Straβe 1, Frankfurt am
Main 60438, Germany
| | - N. Melzer
- Institut
für Kernphysik, Goethe-Universität
Frankfurt, Max-von-Laue-Straβe 1, Frankfurt am
Main 60438, Germany
| | - O. D. McGinnis
- Institut
für Kernphysik, Goethe-Universität
Frankfurt, Max-von-Laue-Straβe 1, Frankfurt am
Main 60438, Germany
| | - J. Kruse
- Institut
für Kernphysik, Goethe-Universität
Frankfurt, Max-von-Laue-Straβe 1, Frankfurt am
Main 60438, Germany
| | - T. Wenzel
- Institut
für Kernphysik, Goethe-Universität
Frankfurt, Max-von-Laue-Straβe 1, Frankfurt am
Main 60438, Germany
| | - T. Jahnke
- Max-Planck-Institut
für Kernphysik, Saupfercheckweg 1, Heidelberg 69117, Germany
- European
XFEL, Holzkoppel
4, Schenefeld 22869, Germany
| | - H. Xue
- Department
of Chemistry, Tohoku University, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8578, Japan
| | - N. Kishimoto
- Department
of Chemistry, Tohoku University, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8578, Japan
| | - K. Yoshikawa
- Department
of Physics, University of Toyama, Gofuku 3190, Toyama 930-8555, Japan
| | - Y. Tamura
- Department
of Physics, University of Toyama, Gofuku 3190, Toyama 930-8555, Japan
| | - F. Ota
- Department
of Physics, University of Toyama, Gofuku 3190, Toyama 930-8555, Japan
| | - K. Hatada
- Department
of Physics, University of Toyama, Gofuku 3190, Toyama 930-8555, Japan
| | - K. Ueda
- Department
of Chemistry, Tohoku University, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8578, Japan
| | - F. Martín
- Departamento
de Química, Universidad Autónoma
de Madrid, Madrid 28049, Spain
- Instituto
Madrileño de Estudios Avanzados en Nanociencia (IMDEA-Nano), Campus de Cantoblanco, Madrid 28049, Spain
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Yi SH, Xiong WJ, Cao XX, Sun CY, Du J, Wang HH, Wang L, Niu T, Jiang ZX, Wei YQ, Xue H, Chu HL, Qiu LG, Li J. [Diagnosis and treatment understanding of Waldenström macroglobulinemia in China: a cross-sectional study]. Zhonghua Xue Ye Xue Za Zhi 2024; 45:148-155. [PMID: 38604791 DOI: 10.3760/cma.j.cn121090-20231017-00212] [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] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Objective: To conduct a nationwide physician survey to better understand clinicians' disease awareness, treatment patterns, and experience of Waldenström macroglobulinemia (WM) in China. Methods: This cross-sectional study was conducted from February 2022 to July 2022 by recruiting clinicians with WM treatment experience from hematology, hematology-oncology, and oncology departments throughout China. Quantitative surveys were designed based on the qualitative interviews. Results: The study included 415 clinicians from 219 hospitals spread across thirty-three cities and twenty-two provinces. As for diagnosis, the laboratory tests prescribed by physicians for suspected WM patients were relatively consistent (92% -99% recommendation for laboratory, 79% -95% recommendation for pathology, 96% recommendation for gene testing, and 63% -83% recommendation for imaging examination). However, from a physician's perspective, there was 22% misdiagnosis occurred in clinical practice. The rate of misdiagnosis was higher in lower-level hospitals than in tertiary grade A hospitals (29% vs 21%, P<0.001). The main reasons for misdiagnosis were that WM was easily confused with other diseases, and physicians lacked the necessary knowledge to make an accurate diagnosis. In terms of gene testing in clinical practice, 96% of participating physicians believed that WM patients would require gene testing for MYD88 and CXCR4 mutations because the results of gene testing would aid in confirming diagnosis and treatment options. In terms of treatment, 55% of physicians thought that the most important goal was to achieve remission, while 54% and 51% of physicians wanted to improve laboratory and/or examination results and extend overall survival time, respectively. Among patients with treatment indications, physicians estimated that approximately 21% of them refused to receive treatment, mainly owing to a lack of affordable care and disease awareness. When selecting the most appropriate treatment regimens, physicians would consider patient affordability (63% ), comorbidity (61% ), and risk level (54% ). Regimens containing Bruton tyrosine kinase inhibitor (BTKi) were most widely recommended for both treatment-naïve and relapsed/refractory patients (94% for all patients, 95% for treatment-naïve patients, and 75% for relapsed/refractory patients), and most physicians recommended Ibrutinib (84% ). For those patients who received treatment, physicians reported that approximately 23% of patients did not comply with the treatment regimen due to a lack of affordability and disease awareness. Furthermore, 66% of physicians believe that in the future, increasing disease awareness and improving diagnosis rates is critical. Conclusions: This study is the first national physician survey of WM conducted in China. It systematically describes the issues that exist in WM diagnosis and treatment in China, such as a high rate of misdiagnosis, limited access to gene testing and new drugs, and poor patient adherence to treatment. Chinese doctors believe that improving doctors' and patients' understanding of WM is one of the most urgent issues that must be addressed right now.
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Affiliation(s)
- S H Yi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China Tianjin Institutes of Health Science, Tianjin 301600, China
| | - W J Xiong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China Tianjin Institutes of Health Science, Tianjin 301600, China
| | - X X Cao
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - C Y Sun
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - J Du
- The Second Affiliated Hospital of Naval Medical University (Shanghai Changzheng Hospital), Shanghai 200003, China
| | - H H Wang
- Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - L Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - T Niu
- West China Hospital of Sichuan University, Chengdu 610044, China
| | - Z X Jiang
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Y Q Wei
- Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - H Xue
- The Affiliated Hospital of Hebei University, Baoding 071030, China
| | - H L Chu
- Peking University Third Hospital, Beijing 100083, China
| | - L G Qiu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China Tianjin Institutes of Health Science, Tianjin 301600, China
| | - J Li
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
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Yin C, O’Reilly AO, Liu SN, Du TH, Gong PP, Zhang CJ, Wei XG, Yang J, Huang MJ, Fu BL, Liang JJ, Xue H, Hu JY, Ji Y, He C, Du H, Wang C, Zhang R, Tan QM, Lu HT, Xie W, Chu D, Zhou XG, Nauen R, Gui LY, Bass C, Yang X, Zhang YJ. Dual mutations in the whitefly nicotinic acetylcholine receptor β1 subunit confer target-site resistance to multiple neonicotinoid insecticides. PLoS Genet 2024; 20:e1011163. [PMID: 38377137 PMCID: PMC10906874 DOI: 10.1371/journal.pgen.1011163] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 03/01/2024] [Accepted: 01/30/2024] [Indexed: 02/22/2024] Open
Abstract
Neonicotinoid insecticides, which target insect nicotinic acetylcholine receptors (nAChRs), have been widely and intensively used to control the whitefly, Bemisia tabaci, a highly damaging, globally distributed, crop pest. This has inevitably led to the emergence of populations with resistance to neonicotinoids. However, to date, there have been no reports of target-site resistance involving mutation of B. tabaci nAChR genes. Here we characterize the nAChR subunit gene family of B. tabaci and identify dual mutations (A58T&R79E) in one of these genes (BTβ1) that confer resistance to multiple neonicotinoids. Transgenic D. melanogaster, where the native nAChR Dβ1 was replaced with BTβ1A58T&R79E, were significantly more resistant to neonicotinoids than flies where Dβ1 were replaced with the wildtype BTβ1 sequence, demonstrating the causal role of the mutations in resistance. The two mutations identified in this study replace two amino acids that are highly conserved in >200 insect species. Three-dimensional modelling suggests a molecular mechanism for this resistance, whereby A58T forms a hydrogen bond with the R79E side chain, which positions its negatively-charged carboxylate group to electrostatically repulse a neonicotinoid at the orthosteric site. Together these findings describe the first case of target-site resistance to neonicotinoids in B. tabaci and provide insight into the molecular determinants of neonicotinoid binding and selectivity.
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Affiliation(s)
- Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei, P. R. China
| | - Andrias O. O’Reilly
- School of Biological & Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | - Shao-Nan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Tian-Hua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Pei-Pan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Cheng-Jia Zhang
- Hunan Provincial Key laboratory of Pesticide Biology and Precise Use Techology, Hunan Agricultural Biotechnology Research Institute, Changsha, P. R. China
| | - Xue-Gao Wei
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Ming-Jiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Bu-Li Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Jin-Jin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Jin-Yu Hu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Qi-Mei Tan
- Hunan Provincial Key laboratory of Pesticide Biology and Precise Use Techology, Hunan Agricultural Biotechnology Research Institute, Changsha, P. R. China
| | - Han-Tang Lu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Wen Xie
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - Dong Chu
- Key Laboratory of Integrated Crop Pest Management of Shandong Province, School of Agriculture and Plant Protection, Qingdao Agricultural University, Qingdao, Shandong Province, China
| | - Xu-Guo Zhou
- Department of Entomology, University of Kentucky, Lexington, Kentucky, United States of America
| | - Ralf Nauen
- Bayer AG, Crop Science Division, R&D, Monheim, Germany
| | - Lian-You Gui
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei, P. R. China
| | - Chris Bass
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, Cornwall, United Kingdom
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
| | - You-Jun Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, P. R. China
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5
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Hu J, Fu B, Liang J, Zhang R, Wei X, Yang J, Tan Q, Xue H, Gong P, Liu S, Huang M, Du T, Yin C, He C, Ji Y, Wang C, Zhang C, Du H, Su Q, Yang X, Zhang Y. CYP4CS5-mediated thiamethoxam and clothianidin resistance is accompanied by fitness cost in the whitefly Bemisia tabaci. Pest Manag Sci 2024; 80:910-921. [PMID: 37822143 DOI: 10.1002/ps.7826] [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] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/25/2023] [Accepted: 10/12/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND Understanding the trade-offs between insecticide resistance and the associated fitness is of particular importance to sustainable pest control. One of the most devastating pest worldwide, the whitefly Bemisia tabaci, has developed resistance to various insecticides, especially the neonicotinoid group. Although neonicotinoid resistance often is conferred by P450s-mediated metabolic resistance, the relationship between such resistance and the associated fitness phenotype remains largely elusive. By gene cloning, quantitative reverse transcription (qRT)-PCR, RNA interference (RNAi), transgenic Drosophila melanogaster, metabolism capacity in vitro and 'two sex-age stage' life table study, this study aims to explore the molecular role of a P450 gene CYP4CS5 in neonicotinoid resistance and to investigate whether such resistance mechanism carries fitness costs in the whitefly. RESULTS Our bioassay tests showed that a total of 13 field-collected populations of B. tabaci MED biotype displayed low-to-moderate resistance to thiamethoxam and clothianidin. Compared to the laboratory susceptible strain, we then found that an important P450 CYP4CS5 was remarkably upregulated in the field resistant populations. Such overexpression of CYP4CS5 had a good match with the resistance level among the whitefly samples. Further exposure to the two neonicotinoids resulted in an increase in CYP4CS5 expression. These results implicate that overexpression of CYP4CS5 is closely correlated with thiamethoxam and clothianidin resistance. RNAi knockdown of CYP4CS5 increased mortality of the resistant and susceptible populations after treatment with thiamethoxam and clothianidin in bioassay, but obtained an opposite result when using a transgenic line of D. melanogaster expressing CYP4CS5. Metabolic assays in vitro revealed that CYP4CS5 exhibited certain capacity of metabolizing thiamethoxam and clothianidin. These in vivo and in vitro assays indicate an essential role of CYP4CS5 in conferring thiamethoxam and clothianidin resistance in whitefly. Additionally, our life-table analysis demonstrate that the field resistant whitefly exhibited a prolonged development time, shortened longevity and reduced fecundity compared to the susceptible, suggesting an existing fitness cost as a result of the resistance. CONCLUSION Collectively, in addition to the important role of CYP4CS5 in conferring thiamethoxam and clothianidin resistance, this resistance mechanism is associated with fitness costs in the whitefly. These findings not only contribute to the development of neonicotinoids resistance management strategies, but also provide a new target for sustainable whitefly control. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Jinyu Hu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
- The Ministry of Agriculture and Rural Affairs Key Laboratory of Integrated Pest Management of Tropical Crops, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Rong Zhang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuegao Wei
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qimei Tan
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shaonan Liu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingjiao Huang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chengjia Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qi Su
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Youjun Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
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Ji Y, Zheng H, Zhang C, Tan X, He C, Fu B, Du T, Liang J, Wei X, Gong P, Liu S, Yang J, Huang M, Yin C, Xue H, Hu J, Du H, Xie W, Yang X, Zhang Y. Dynamic monitoring of the insecticide resistance status of Bemisia tabaci across China from 2019-2021. Pest Manag Sci 2024; 80:341-354. [PMID: 37688583 DOI: 10.1002/ps.7763] [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] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 09/01/2023] [Accepted: 09/07/2023] [Indexed: 09/11/2023]
Abstract
BACKGROUND Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a major agricultural insect pest that causes severe economic losses worldwide. Several insecticides have been applied to effectively control this key pest. However, owing to the indiscriminate use of chemical insecticides, B. tabaci has developed resistance against these chemical compounds over the past several years. RESULTS From 2019 to 2021, 23 field samples of B. tabaci were collected across China. Twenty species were identified as the Mediterranean 'Q' type (MED) and three were identified as MED/ Middle East-Asia Minor 1 mixtures. Subsequently, resistance of the selected populations to different insecticides was evaluated. The results showed that 13 populations developed low levels of resistance to abamectin. An overall upward trend in B. tabaci resistance toward spirotetramat, cyantraniliprole and pyriproxyfen was observed. In addition, resistance to thiamethoxam remained low-to-moderate in the 23 field populations. CONCLUSION These findings suggest that the overall resistance of the field-collected B. tabaci populations has shown an upward trend over the years in China. We believe our study can provide basic data to support integrated pest management and insecticide resistance management of field B. tabaci in China. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Yao Ji
- College of Plant Protection, Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huixin Zheng
- College of Plant Protection, Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chengjia Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
- Hunan Provincial Key Laboratory of Pesticide Biology and Precise Use Technology, Hunan Agricultural Biotechnology Research Institute, Hunan Academy of Agricultural Sciences, Changsha, China
| | - Xing Tan
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuegao Wei
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shaonan Liu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingjiao Huang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinyu Hu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - He Du
- College of Plant Protection, Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wen Xie
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Youjun Zhang
- College of Plant Protection, Hunan Agricultural University, Changsha, China
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He C, Li Y, Gan L, Lin Y, Zhang B, Ma L, Xue H. Notch signaling regulates Th17 cells differentiation through PI3K/AKT/mTORC1 pathway and involves in the thyroid injury of autoimmune thyroiditis. J Endocrinol Invest 2024:10.1007/s40618-023-02293-z. [PMID: 38285310 DOI: 10.1007/s40618-023-02293-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 12/25/2023] [Indexed: 01/30/2024]
Abstract
PURPOSE Autoimmune Thyroiditis (AIT) is the most common thyroid disease; however, there were no measures to prevent the progression of the disease. The present study attempts to identify that Notch signaling regulates the differentiation of T helper 17 (Th17) cells by activating downstream Phosphatidylinositol-3 kinase/protein kinase/mechanistic target of rapamycin complex 1 (PI3K/AKT/mTORC1) pathway participating in the thyroid injury of the experimental autoimmune thyroiditis (EAT). METHODS In vivo experiments, mice were randomly divided into 4 groups: a control group, an EAT group, and two groups with LY294002 treatment (pTg plus 25 mg/kg or 50 mg/kg LY294002, respectively). The degrees of thyroiditis were evaluated, and the percentage of Th17 cells, expression of interleukin-17A (IL-17A), and the main components of the Notch-PI3K signaling pathway were detected in different groups. In vitro experiments, two different dosages of LY294002 (25 and 50 μM) were used to intervene splenic mononuclear cells (SMCs) from EAT mice to further evaluate the regulatory effect of Notch-PI3K pathway on Th17 cells. RESULTS Our data demonstrate that the infiltration of Th17 cells and the expressions of IL-17A, Notch, hairy and split 1 (Hes1), p‑AKT (Ser473), p‑AKT (Thr308), p‑mTOR (Ser2448), S6K1, and S6K2 increased remarkably in EAT mice. After PI3K pathway was blocked, the degrees of thyroiditis were significantly alleviated, and the proportion of Th17 cells, the expression of IL-17A, and the above Notch-PI3K pathway-related molecules decreased in a dose-dependent manner. Additionally, the proportion of Th17 cells was positively correlated with the concentration of serum thyroglobulin antibody (TgAb), IL-17A, and Notch-PI3K pathway-related molecules mRNA levels. CONCLUSIONS Notch signal promotes the secretion of IL-17A from Th17 cells by regulating the downstream PI3K/AKT/mTORC1 pathway through Hes-Phosphatase and tensin homolog (PTEN) and participates in thyroid autoimmune damage, and the PI3K pathway inhibitor may play important effects on AIT by affecting Th17 cells differentiation.
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Affiliation(s)
- C He
- Department of Endocrinology and Metabolism, Binzhou Medical University Hospital, Binzhou, 256600, People's Republic of China
| | - Y Li
- Department of Endocrinology and Metabolism, Binzhou Medical University Hospital, Binzhou, 256600, People's Republic of China
| | - L Gan
- Department of Endocrinology and Metabolism, Binzhou Medical University Hospital, Binzhou, 256600, People's Republic of China
| | - Y Lin
- Department of Dermatology, Binzhou Medical University Hospital, Binzhou, 256600, People's Republic of China
| | - B Zhang
- Nanchang University Queen Mary School, Nanchang, 330031, People's Republic of China
| | - L Ma
- Department of Dermatology, Binzhou Medical University Hospital, Binzhou, 256600, People's Republic of China
| | - H Xue
- Department of Endocrinology and Metabolism, Binzhou Medical University Hospital, Binzhou, 256600, People's Republic of China.
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Staplin N, Haynes R, Judge PK, Wanner C, Green JB, Emberson J, Preiss D, Mayne KJ, Ng SYA, Sammons E, Zhu D, Hill M, Stevens W, Wallendszus K, Brenner S, Cheung AK, Liu ZH, Li J, Hooi LS, Liu WJ, Kadowaki T, Nangaku M, Levin A, Cherney D, Maggioni AP, Pontremoli R, Deo R, Goto S, Rossello X, Tuttle KR, Steubl D, Petrini M, Seidi S, Landray MJ, Baigent C, Herrington WG, Abat S, Abd Rahman R, Abdul Cader R, Abdul Hafidz MI, Abdul Wahab MZ, Abdullah NK, Abdul-Samad T, Abe M, Abraham N, Acheampong S, Achiri P, Acosta JA, Adeleke A, Adell V, Adewuyi-Dalton R, Adnan N, Africano A, Agharazii M, Aguilar F, Aguilera A, Ahmad M, Ahmad MK, Ahmad NA, Ahmad NH, Ahmad NI, Ahmad Miswan N, Ahmad Rosdi H, Ahmed I, Ahmed S, Ahmed S, Aiello J, Aitken A, AitSadi R, Aker S, Akimoto S, Akinfolarin A, Akram S, Alberici F, Albert C, Aldrich L, Alegata M, Alexander L, Alfaress S, Alhadj Ali M, Ali A, Ali A, Alicic R, Aliu A, Almaraz R, Almasarwah R, Almeida J, Aloisi A, Al-Rabadi L, Alscher D, Alvarez P, Al-Zeer B, Amat M, Ambrose C, Ammar H, An Y, Andriaccio L, Ansu K, Apostolidi A, Arai N, Araki H, Araki S, Arbi A, Arechiga O, Armstrong S, Arnold T, Aronoff S, Arriaga W, Arroyo J, Arteaga D, Asahara S, Asai A, Asai N, Asano S, Asawa M, Asmee MF, Aucella F, Augustin M, Avery A, Awad A, Awang IY, Awazawa M, Axler A, Ayub W, Azhari Z, Baccaro R, Badin C, Bagwell B, Bahlmann-Kroll E, Bahtar AZ, Baigent C, Bains D, Bajaj H, Baker R, Baldini E, Banas B, Banerjee D, Banno S, Bansal S, Barberi S, Barnes S, Barnini C, Barot C, Barrett K, Barrios R, Bartolomei Mecatti B, Barton I, Barton J, Basily W, Bavanandan S, Baxter A, Becker L, Beddhu S, Beige J, Beigh S, Bell S, Benck U, Beneat A, Bennett A, Bennett D, Benyon S, Berdeprado J, Bergler T, Bergner A, Berry M, Bevilacqua M, Bhairoo J, Bhandari S, Bhandary N, Bhatt A, Bhattarai M, Bhavsar M, Bian W, Bianchini F, Bianco S, Bilous R, Bilton J, Bilucaglia D, Bird C, Birudaraju D, Biscoveanu M, Blake C, Bleakley N, Bocchicchia K, Bodine S, Bodington R, Boedecker S, Bolduc M, Bolton S, Bond C, Boreky F, Boren K, Bouchi R, Bough L, Bovan D, Bowler C, Bowman L, Brar N, Braun C, Breach A, Breitenfeldt M, Brenner S, Brettschneider B, Brewer A, Brewer G, Brindle V, Brioni E, Brown C, Brown H, Brown L, Brown R, Brown S, Browne D, Bruce K, Brueckmann M, Brunskill N, Bryant M, Brzoska M, Bu Y, Buckman C, Budoff M, Bullen M, Burke A, Burnette S, Burston C, Busch M, Bushnell J, Butler S, Büttner C, Byrne C, Caamano A, Cadorna J, Cafiero C, Cagle M, Cai J, Calabrese K, Calvi C, Camilleri B, Camp S, Campbell D, Campbell R, Cao H, Capelli I, Caple M, Caplin B, Cardone A, Carle J, Carnall V, Caroppo M, Carr S, Carraro G, Carson M, Casares P, Castillo C, Castro C, Caudill B, Cejka V, Ceseri M, Cham L, Chamberlain A, Chambers J, Chan CBT, Chan JYM, Chan YC, Chang E, Chang E, Chant T, Chavagnon T, Chellamuthu P, Chen F, Chen J, Chen P, Chen TM, Chen Y, Chen Y, Cheng C, Cheng H, Cheng MC, Cherney D, Cheung AK, Ching CH, Chitalia N, Choksi R, Chukwu C, Chung K, Cianciolo G, Cipressa L, Clark S, Clarke H, Clarke R, Clarke S, Cleveland B, Cole E, Coles H, Condurache L, Connor A, Convery K, Cooper A, Cooper N, Cooper Z, Cooperman L, Cosgrove L, Coutts P, Cowley A, Craik R, Cui G, Cummins T, Dahl N, Dai H, Dajani L, D'Amelio A, Damian E, Damianik K, Danel L, Daniels C, Daniels T, Darbeau S, Darius H, Dasgupta T, Davies J, Davies L, Davis A, Davis J, Davis L, Dayanandan R, Dayi S, Dayrell R, De Nicola L, Debnath S, Deeb W, Degenhardt S, DeGoursey K, Delaney M, Deo R, DeRaad R, Derebail V, Dev D, Devaux M, Dhall P, Dhillon G, Dienes J, Dobre M, Doctolero E, Dodds V, Domingo D, Donaldson D, Donaldson P, Donhauser C, Donley V, Dorestin S, Dorey S, Doulton T, Draganova D, Draxlbauer K, Driver F, Du H, Dube F, Duck T, Dugal T, Dugas J, Dukka H, Dumann H, Durham W, Dursch M, Dykas R, Easow R, Eckrich E, Eden G, Edmerson E, Edwards H, Ee LW, Eguchi J, Ehrl Y, Eichstadt K, Eid W, Eilerman B, Ejima Y, Eldon H, Ellam T, Elliott L, Ellison R, Emberson J, Epp R, Er A, Espino-Obrero M, Estcourt S, Estienne L, Evans G, Evans J, Evans S, Fabbri G, Fajardo-Moser M, Falcone C, Fani F, Faria-Shayler P, Farnia F, Farrugia D, Fechter M, Fellowes D, Feng F, Fernandez J, Ferraro P, Field A, Fikry S, Finch J, Finn H, Fioretto P, Fish R, Fleischer A, Fleming-Brown D, Fletcher L, Flora R, Foellinger C, Foligno N, Forest S, Forghani Z, Forsyth K, Fottrell-Gould D, Fox P, Frankel A, Fraser D, Frazier R, Frederick K, Freking N, French H, Froment A, Fuchs B, Fuessl L, Fujii H, Fujimoto A, Fujita A, Fujita K, Fujita Y, Fukagawa M, Fukao Y, Fukasawa A, Fuller T, Funayama T, Fung E, Furukawa M, Furukawa Y, Furusho M, Gabel S, Gaidu J, Gaiser S, Gallo K, Galloway C, Gambaro G, Gan CC, Gangemi C, Gao M, Garcia K, Garcia M, Garofalo C, Garrity M, Garza A, Gasko S, Gavrila M, Gebeyehu B, Geddes A, Gentile G, George A, George J, Gesualdo L, Ghalli F, Ghanem A, Ghate T, Ghavampour S, Ghazi A, Gherman A, Giebeln-Hudnell U, Gill B, Gillham S, Girakossyan I, Girndt M, Giuffrida A, Glenwright M, Glider T, Gloria R, Glowski D, Goh BL, Goh CB, Gohda T, Goldenberg R, Goldfaden R, Goldsmith C, Golson B, Gonce V, Gong Q, Goodenough B, Goodwin N, Goonasekera M, Gordon A, Gordon J, Gore A, Goto H, Goto S, Goto S, Gowen D, Grace A, Graham J, Grandaliano G, Gray M, Green JB, Greene T, Greenwood G, Grewal B, Grifa R, Griffin D, Griffin S, Grimmer P, Grobovaite E, Grotjahn S, Guerini A, Guest C, Gunda S, Guo B, Guo Q, Haack S, Haase M, Haaser K, Habuki K, Hadley A, Hagan S, Hagge S, Haller H, Ham S, Hamal S, Hamamoto Y, Hamano N, Hamm M, Hanburry A, Haneda M, Hanf C, Hanif W, Hansen J, Hanson L, Hantel S, Haraguchi T, Harding E, Harding T, Hardy C, Hartner C, Harun Z, Harvill L, Hasan A, Hase H, Hasegawa F, Hasegawa T, Hashimoto A, Hashimoto C, Hashimoto M, Hashimoto S, Haskett S, Hauske SJ, Hawfield A, Hayami T, Hayashi M, Hayashi S, Haynes R, Hazara A, Healy C, Hecktman J, Heine G, Henderson H, Henschel R, Hepditch A, Herfurth K, Hernandez G, Hernandez Pena A, Hernandez-Cassis C, Herrington WG, Herzog C, Hewins S, Hewitt D, Hichkad L, Higashi S, Higuchi C, Hill C, Hill L, Hill M, Himeno T, Hing A, Hirakawa Y, Hirata K, Hirota Y, Hisatake T, Hitchcock S, Hodakowski A, Hodge W, Hogan R, Hohenstatt U, Hohenstein B, Hooi L, Hope S, Hopley M, Horikawa S, Hosein D, Hosooka T, Hou L, Hou W, Howie L, Howson A, Hozak M, Htet Z, Hu X, Hu Y, Huang J, Huda N, Hudig L, Hudson A, Hugo C, Hull R, Hume L, Hundei W, Hunt N, Hunter A, Hurley S, Hurst A, Hutchinson C, Hyo T, Ibrahim FH, Ibrahim S, Ihana N, Ikeda T, Imai A, Imamine R, Inamori A, Inazawa H, Ingell J, Inomata K, Inukai Y, Ioka M, Irtiza-Ali A, Isakova T, Isari W, Iselt M, Ishiguro A, Ishihara K, Ishikawa T, Ishimoto T, Ishizuka K, Ismail R, Itano S, Ito H, Ito K, Ito M, Ito Y, Iwagaitsu S, Iwaita Y, Iwakura T, Iwamoto M, Iwasa M, Iwasaki H, Iwasaki S, Izumi K, Izumi K, Izumi T, Jaafar SM, Jackson C, Jackson Y, Jafari G, Jahangiriesmaili M, Jain N, Jansson K, Jasim H, Jeffers L, Jenkins A, Jesky M, Jesus-Silva J, Jeyarajah D, Jiang Y, Jiao X, Jimenez G, Jin B, Jin Q, Jochims J, Johns B, Johnson C, Johnson T, Jolly S, Jones L, Jones L, Jones S, Jones T, Jones V, Joseph M, Joshi S, Judge P, Junejo N, Junus S, Kachele M, Kadowaki T, Kadoya H, Kaga H, Kai H, Kajio H, Kaluza-Schilling W, Kamaruzaman L, Kamarzarian A, Kamimura Y, Kamiya H, Kamundi C, Kan T, Kanaguchi Y, Kanazawa A, Kanda E, Kanegae S, Kaneko K, Kaneko K, Kang HY, Kano T, Karim M, Karounos D, Karsan W, Kasagi R, Kashihara N, Katagiri H, Katanosaka A, Katayama A, Katayama M, Katiman E, Kato K, Kato M, Kato N, Kato S, Kato T, Kato Y, Katsuda Y, Katsuno T, Kaufeld J, Kavak Y, Kawai I, Kawai M, Kawai M, Kawase A, Kawashima S, Kazory A, Kearney J, Keith B, Kellett J, Kelley S, Kershaw M, Ketteler M, Khai Q, Khairullah Q, Khandwala H, Khoo KKL, Khwaja A, Kidokoro K, Kielstein J, Kihara M, Kimber C, Kimura S, Kinashi H, Kingston H, Kinomura M, Kinsella-Perks E, Kitagawa M, Kitajima M, Kitamura S, Kiyosue A, Kiyota M, Klauser F, Klausmann G, Kmietschak W, Knapp K, Knight C, Knoppe A, Knott C, Kobayashi M, Kobayashi R, Kobayashi T, Koch M, Kodama S, Kodani N, Kogure E, Koizumi M, Kojima H, Kojo T, Kolhe N, Komaba H, Komiya T, Komori H, Kon SP, Kondo M, Kondo M, Kong W, Konishi M, Kono K, Koshino M, Kosugi T, Kothapalli B, Kozlowski T, Kraemer B, Kraemer-Guth A, Krappe J, Kraus D, Kriatselis C, Krieger C, Krish P, Kruger B, Ku Md Razi KR, Kuan Y, Kubota S, Kuhn S, Kumar P, Kume S, Kummer I, Kumuji R, Küpper A, Kuramae T, Kurian L, Kuribayashi C, Kurien R, Kuroda E, Kurose T, Kutschat A, Kuwabara N, Kuwata H, La Manna G, Lacey M, Lafferty K, LaFleur P, Lai V, Laity E, Lambert A, Landray MJ, Langlois M, Latif F, Latore E, Laundy E, Laurienti D, Lawson A, Lay M, Leal I, Leal I, Lee AK, Lee J, Lee KQ, Lee R, Lee SA, Lee YY, Lee-Barkey Y, Leonard N, Leoncini G, Leong CM, Lerario S, Leslie A, Levin A, Lewington A, Li J, Li N, Li X, Li Y, Liberti L, Liberti ME, Liew A, Liew YF, Lilavivat U, Lim SK, Lim YS, Limon E, Lin H, Lioudaki E, Liu H, Liu J, Liu L, Liu Q, Liu WJ, Liu X, Liu Z, Loader D, Lochhead H, Loh CL, Lorimer A, Loudermilk L, Loutan J, Low CK, Low CL, Low YM, Lozon Z, Lu Y, Lucci D, Ludwig U, Luker N, Lund D, Lustig R, Lyle S, Macdonald C, MacDougall I, Machicado R, MacLean D, Macleod P, Madera A, Madore F, Maeda K, Maegawa H, Maeno S, Mafham M, Magee J, Maggioni AP, Mah DY, Mahabadi V, Maiguma M, Makita Y, Makos G, Manco L, Mangiacapra R, Manley J, Mann P, Mano S, Marcotte G, Maris J, Mark P, Markau S, Markovic M, Marshall C, Martin M, Martinez C, Martinez S, Martins G, Maruyama K, Maruyama S, Marx K, Maselli A, Masengu A, Maskill A, Masumoto S, Masutani K, Matsumoto M, Matsunaga T, Matsuoka N, Matsushita M, Matthews M, Matthias S, Matvienko E, Maurer M, Maxwell P, Mayne KJ, Mazlan N, Mazlan SA, Mbuyisa A, McCafferty K, McCarroll F, McCarthy T, McClary-Wright C, McCray K, McDermott P, McDonald C, McDougall R, McHaffie E, McIntosh K, McKinley T, 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Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial. Lancet Diabetes Endocrinol 2024; 12:39-50. [PMID: 38061371 PMCID: PMC7615591 DOI: 10.1016/s2213-8587(23)00321-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001). INTERPRETATION Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor. FUNDING Boehringer Ingelheim and Eli Lilly.
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Liew A, Liew YF, Lilavivat U, Lim SK, Lim YS, Limon E, Lin H, Lioudaki E, Liu H, Liu J, Liu L, Liu Q, Liu WJ, Liu X, Liu Z, Loader D, Lochhead H, Loh CL, Lorimer A, Loudermilk L, Loutan J, Low CK, Low CL, Low YM, Lozon Z, Lu Y, Lucci D, Ludwig U, Luker N, Lund D, Lustig R, Lyle S, Macdonald C, MacDougall I, Machicado R, MacLean D, Macleod P, Madera A, Madore F, Maeda K, Maegawa H, Maeno S, Mafham M, Magee J, Maggioni AP, Mah DY, Mahabadi V, Maiguma M, Makita Y, Makos G, Manco L, Mangiacapra R, Manley J, Mann P, Mano S, Marcotte G, Maris J, Mark P, Markau S, Markovic M, Marshall C, Martin M, Martinez C, Martinez S, Martins G, Maruyama K, Maruyama S, Marx K, Maselli A, Masengu A, Maskill A, Masumoto S, Masutani K, Matsumoto M, Matsunaga T, Matsuoka N, Matsushita M, Matthews M, Matthias S, Matvienko E, Maurer M, Maxwell P, Mayne KJ, Mazlan N, Mazlan SA, Mbuyisa A, McCafferty K, McCarroll F, McCarthy T, McClary-Wright C, McCray K, McDermott P, McDonald C, McDougall R, McHaffie E, McIntosh K, McKinley T, McLaughlin S, McLean N, McNeil L, Measor A, Meek J, Mehta A, Mehta R, Melandri M, Mené P, Meng T, Menne J, Merritt K, Merscher S, Meshykhi C, Messa P, Messinger L, Miftari N, Miller R, Miller Y, Miller-Hodges E, Minatoguchi M, Miners M, Minutolo R, Mita T, Miura Y, Miyaji M, Miyamoto S, Miyatsuka T, Miyazaki M, Miyazawa I, Mizumachi R, Mizuno M, Moffat S, Mohamad Nor FS, Mohamad Zaini SN, Mohamed Affandi FA, Mohandas C, Mohd R, Mohd Fauzi NA, Mohd Sharif NH, Mohd Yusoff Y, Moist L, Moncada A, Montasser M, Moon A, Moran C, Morgan N, Moriarty J, Morig G, Morinaga H, Morino K, Morisaki T, Morishita Y, Morlok S, Morris A, Morris F, Mostafa S, Mostefai Y, Motegi M, Motherwell N, Motta D, Mottl A, Moys R, Mozaffari S, Muir J, Mulhern J, Mulligan S, Munakata Y, Murakami C, Murakoshi M, Murawska A, Murphy K, Murphy L, Murray S, Murtagh H, Musa MA, Mushahar L, Mustafa R, Mustafar R, Muto M, Nadar E, Nagano R, Nagasawa T, Nagashima E, Nagasu H, Nagelberg S, Nair H, Nakagawa Y, Nakahara M, Nakamura J, Nakamura R, Nakamura T, Nakaoka M, Nakashima E, Nakata J, Nakata M, Nakatani S, Nakatsuka A, Nakayama Y, Nakhoul G, Nangaku M, Naverrete G, Navivala A, Nazeer I, Negrea L, Nethaji C, Newman E, Ng SYA, Ng TJ, Ngu LLS, Nimbkar T, Nishi H, Nishi M, Nishi S, Nishida Y, Nishiyama A, Niu J, Niu P, Nobili G, Nohara N, Nojima I, Nolan J, Nosseir H, Nozawa M, Nunn M, Nunokawa S, Oda M, Oe M, Oe Y, Ogane K, Ogawa W, Ogihara T, Oguchi G, Ohsugi M, Oishi K, Okada Y, Okajyo J, Okamoto S, Okamura K, Olufuwa O, Oluyombo R, Omata A, Omori Y, Ong LM, Ong YC, Onyema J, Oomatia A, Oommen A, Oremus R, Orimo Y, Ortalda V, Osaki Y, Osawa Y, Osmond Foster J, O'Sullivan A, Otani T, Othman N, Otomo S, O'Toole J, Owen L, Ozawa T, Padiyar A, Page N, Pajak S, Paliege A, Pandey A, Pandey R, Pariani H, Park J, Parrigon M, Passauer J, Patecki M, Patel M, Patel R, Patel T, Patel Z, Paul R, Paul R, Paulsen L, Pavone L, Peixoto A, Peji J, Peng BC, Peng K, Pennino L, Pereira E, Perez E, Pergola P, Pesce F, Pessolano G, Petchey W, Petr EJ, Pfab T, Phelan P, Phillips R, Phillips T, Phipps M, Piccinni G, Pickett T, Pickworth S, Piemontese M, Pinto D, Piper J, Plummer-Morgan J, Poehler D, Polese L, Poma V, Pontremoli R, Postal A, Pötz C, Power A, Pradhan N, Pradhan R, Preiss D, Preiss E, Preston K, Prib N, Price L, Provenzano C, Pugay C, Pulido R, Putz F, Qiao Y, Quartagno R, Quashie-Akponeware M, Rabara R, Rabasa-Lhoret R, Radhakrishnan D, Radley M, Raff R, Raguwaran S, Rahbari-Oskoui F, Rahman M, Rahmat K, Ramadoss S, Ramanaidu S, Ramasamy S, Ramli R, Ramli S, Ramsey T, Rankin A, Rashidi A, Raymond L, Razali WAFA, Read K, Reiner H, Reisler A, Reith C, Renner J, Rettenmaier B, Richmond L, Rijos D, Rivera R, Rivers V, Robinson H, Rocco M, Rodriguez-Bachiller I, Rodriquez R, Roesch C, Roesch J, Rogers J, Rohnstock M, Rolfsmeier S, Roman M, Romo A, Rosati A, Rosenberg S, Ross T, Rossello X, Roura M, Roussel M, Rovner S, Roy S, Rucker S, Rump L, Ruocco M, Ruse S, Russo F, Russo M, Ryder M, Sabarai A, Saccà C, Sachson R, Sadler E, Safiee NS, Sahani M, Saillant A, Saini J, Saito C, Saito S, Sakaguchi K, Sakai M, Salim H, Salviani C, Sammons E, Sampson A, Samson F, Sandercock P, Sanguila S, Santorelli G, Santoro D, Sarabu N, Saram T, Sardell R, Sasajima H, Sasaki T, Satko S, Sato A, Sato D, Sato H, Sato H, Sato J, Sato T, Sato Y, Satoh M, Sawada K, Schanz M, Scheidemantel F, Schemmelmann M, Schettler E, Schettler V, Schlieper GR, Schmidt C, Schmidt G, Schmidt U, Schmidt-Gurtler H, Schmude M, Schneider A, Schneider I, Schneider-Danwitz C, Schomig M, Schramm T, Schreiber A, Schricker S, Schroppel B, Schulte-Kemna L, Schulz E, Schumacher B, Schuster A, Schwab A, Scolari F, Scott A, Seeger W, Seeger W, Segal M, Seifert L, Seifert M, Sekiya M, Sellars R, Seman MR, Shah S, Shah S, Shainberg L, Shanmuganathan M, Shao F, Sharma K, Sharpe C, Sheikh-Ali M, Sheldon J, Shenton C, Shepherd A, Shepperd M, Sheridan R, Sheriff Z, Shibata Y, Shigehara T, Shikata K, Shimamura K, Shimano H, Shimizu Y, Shimoda H, Shin K, Shivashankar G, Shojima N, Silva R, Sim CSB, Simmons K, Sinha S, Sitter T, Sivanandam S, Skipper M, Sloan K, Sloan L, Smith R, Smyth J, Sobande T, Sobata M, Somalanka S, Song X, Sonntag F, Sood B, Sor SY, Soufer J, Sparks H, Spatoliatore G, Spinola T, Squyres S, Srivastava A, Stanfield J, Staplin N, Staylor K, Steele A, Steen O, Steffl D, Stegbauer J, Stellbrink C, Stellbrink E, Stevens W, Stevenson A, Stewart-Ray V, Stickley J, Stoffler D, Stratmann B, Streitenberger S, Strutz F, Stubbs J, Stumpf J, Suazo N, Suchinda P, Suckling R, Sudin A, Sugamori K, Sugawara H, Sugawara K, Sugimoto D, Sugiyama H, Sugiyama H, Sugiyama T, Sullivan M, Sumi M, Suresh N, Sutton D, Suzuki H, Suzuki R, Suzuki Y, Suzuki Y, Suzuki Y, Swanson E, Swift P, Syed S, Szerlip H, Taal M, Taddeo M, Tailor C, Tajima K, Takagi M, Takahashi K, Takahashi K, Takahashi M, Takahashi T, Takahira E, Takai T, Takaoka M, Takeoka J, Takesada A, Takezawa M, Talbot M, Taliercio J, Talsania T, Tamori Y, Tamura R, Tamura Y, Tan CHH, Tan EZZ, Tanabe A, Tanabe K, Tanaka A, Tanaka A, Tanaka N, Tang S, Tang Z, Tanigaki K, Tarlac M, Tatsuzawa A, Tay JF, Tay LL, Taylor J, Taylor K, Taylor K, Te A, Tenbusch L, Teng KS, Terakawa A, Terry J, Tham ZD, Tholl S, Thomas G, Thong KM, Tietjen D, Timadjer A, Tindall H, Tipper S, Tobin K, Toda N, Tokuyama A, Tolibas M, Tomita A, Tomita T, Tomlinson J, Tonks L, Topf J, Topping S, Torp A, Torres A, Totaro F, Toth P, Toyonaga Y, Tripodi F, Trivedi K, Tropman E, Tschope D, Tse J, Tsuji K, Tsunekawa S, Tsunoda R, Tucky B, Tufail S, Tuffaha A, Turan E, Turner H, Turner J, Turner M, Tuttle KR, Tye YL, Tyler A, Tyler J, Uchi H, Uchida H, Uchida T, Uchida T, Udagawa T, Ueda S, Ueda Y, Ueki K, Ugni S, Ugwu E, Umeno R, Unekawa C, Uozumi K, Urquia K, Valleteau A, Valletta C, van Erp R, Vanhoy C, Varad V, Varma R, Varughese A, Vasquez P, Vasseur A, Veelken R, Velagapudi C, Verdel K, Vettoretti S, Vezzoli G, Vielhauer V, Viera R, Vilar E, Villaruel S, Vinall L, Vinathan J, Visnjic M, Voigt E, von-Eynatten M, Vourvou M, Wada J, Wada J, Wada T, Wada Y, Wakayama K, Wakita Y, Wallendszus K, Walters T, Wan Mohamad WH, Wang L, Wang W, Wang X, Wang X, Wang Y, Wanner C, Wanninayake S, Watada H, Watanabe K, Watanabe K, Watanabe M, Waterfall H, Watkins D, Watson S, Weaving L, Weber B, Webley Y, Webster A, Webster M, Weetman M, Wei W, Weihprecht H, Weiland L, Weinmann-Menke J, Weinreich T, Wendt R, Weng Y, Whalen M, Whalley G, Wheatley R, Wheeler A, Wheeler J, Whelton P, White K, Whitmore B, Whittaker S, Wiebel J, Wiley J, Wilkinson L, Willett M, Williams A, Williams E, Williams K, Williams T, Wilson A, Wilson P, Wincott L, Wines E, Winkelmann B, Winkler M, Winter-Goodwin B, Witczak J, Wittes J, Wittmann M, Wolf G, Wolf L, Wolfling R, Wong C, Wong E, Wong HS, Wong LW, Wong YH, Wonnacott A, Wood A, Wood L, Woodhouse H, Wooding N, Woodman A, Wren K, Wu J, Wu P, Xia S, Xiao H, Xiao X, Xie Y, Xu C, Xu Y, Xue H, Yahaya H, Yalamanchili H, Yamada A, Yamada N, Yamagata K, Yamaguchi M, Yamaji Y, Yamamoto A, Yamamoto S, Yamamoto S, Yamamoto T, Yamanaka A, Yamano T, Yamanouchi Y, Yamasaki N, Yamasaki Y, Yamasaki Y, Yamashita C, Yamauchi T, Yan Q, Yanagisawa E, Yang F, Yang L, Yano S, Yao S, Yao Y, Yarlagadda S, Yasuda Y, Yiu V, Yokoyama T, Yoshida S, Yoshidome E, Yoshikawa H, Young A, Young T, Yousif V, Yu H, Yu Y, Yuasa K, Yusof N, Zalunardo N, Zander B, Zani R, Zappulo F, Zayed M, Zemann B, Zettergren P, Zhang H, Zhang L, Zhang L, Zhang N, Zhang X, Zhao J, Zhao L, Zhao S, Zhao Z, Zhong H, Zhou N, Zhou S, Zhu D, Zhu L, Zhu S, Zietz M, Zippo M, Zirino F, Zulkipli FH. Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial. Lancet Diabetes Endocrinol 2024; 12:51-60. [PMID: 38061372 DOI: 10.1016/s2213-8587(23)00322-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). INTERPRETATION In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. FUNDING Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.
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Du TH, Yin C, Gui LY, Liang JJ, Liu SN, Fu BL, He C, Yang J, Wei XG, Gong PP, Huang MJ, Xue H, Hu JY, Du H, Ji Y, Zhang R, Wang C, Zhang CJ, Yang X, Zhang YJ. Over-expression of UDP-glycosyltransferase UGT353G2 confers resistance to neonicotinoids in whitefly (Bemisia tabaci). Pestic Biochem Physiol 2023; 196:105635. [PMID: 37945266 DOI: 10.1016/j.pestbp.2023.105635] [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] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 09/28/2023] [Accepted: 09/30/2023] [Indexed: 11/12/2023]
Abstract
The whitefly, Bemisia tabaci, comes up high metabolic resistance to most neonicotinoids in long-term evolution, which is the key problem of pest control. UGT glycosyltransferase, as a secondary detoxification enzyme, plays an indispensable role in detoxification metabolism. In this study, UGT inhibitors, 5-nitrouracil and sulfinpyrazone, dramatically augmented the toxic damage of neonicotinoids to B. tabaci. A UGT named UGT353G2 was identified in whitefly, which was notably up-regulated in resistant strain (3.92 folds), and could be induced by most neonicotinoids. Additionally, the using of RNA interference (RNAi) suppresses UGT353G2 substantially increased sensitivity to neonicotinoids in resistant strain. Our results support that UGT353G2 may be involved in the neonicotinoids resistance of whitefly. These findings will help further verify the functional role of UGTs in neonicotinoid resistance.
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Affiliation(s)
- Tian-Hua Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng Yin
- College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, China
| | - Lian-You Gui
- College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, China
| | - Jin-Jin Liang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shao-Nan Liu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Bu-Li Fu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xue-Gao Wei
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Pei-Pan Gong
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Ming-Jiao Huang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jin-Yu Hu
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng-Jia Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - You-Jun Zhang
- State Key Laboratory of Vegetable Biobreeding, Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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Wang A, Zhu B, Huang J, Wong MCS, Xue H. Quality of primary healthcare in China: challenges and strategies. Hong Kong Med J 2023; 29:372-374. [PMID: 37794614 DOI: 10.12809/hkmj235149] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023] Open
Affiliation(s)
- A Wang
- School of Economics and Management, Xidian University, Xi'an, China
| | - B Zhu
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - J Huang
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Editor-in-Chief, Hong Kong Medical Journal
| | - M C S Wong
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Editor-in-Chief, Hong Kong Medical Journal
- School of Public Health, Fudan University, Shanghai, China
- The Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- School of Public Health, Peking University, Beijing, China
| | - H Xue
- Stanford Center on China's Economy and Institutions, Freeman Spogli Institute for International Studies, Stanford University, Stanford, United States
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Liu S, Fu B, Zhang C, He C, Gong P, Huang M, Du T, Liang J, Wei X, Yang J, Yin C, Ji Y, Xue H, Hu J, Wang C, Zhang R, Du H, Yang X, Zhang Y. 20E biosynthesis gene CYP306A1 confers resistance to imidacloprid in the nymph stage of Bemisia tabaci by detoxification metabolism. Pest Manag Sci 2023; 79:3883-3892. [PMID: 37226658 DOI: 10.1002/ps.7569] [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] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 05/12/2023] [Accepted: 05/24/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND Difference in physiology level between the immature and mature stages of insects likely contribute to different mechanisms of insecticide resistance. It is well acknowledged that insect 20-hydroxyecdysone (20E) plays an important role in many biological processes in the immature stage, whether 20E confers insecticide resistance at this specific stage is still poorly understood. By gene cloning, reverse transcription quantitative real-time PCR, RNA interference (RNAi) and in vitro metabolism experiments, this study aimed to investigate the potential role of 20E-related genes in conferring imidacloprid (IMD) resistance in the immature stage of the whitefly Bemisia tabaci Mediterranean. RESULTS After identification of low to moderate IMD resistance in the whitefly, we found CYP306A1 of the six 20E-related genes was overexpressed in the nymph stage of the three resistant strains compared to a laboratory reference susceptible strain, but not in the adult stage. Further exposure to IMD resulted in an increase in CYP306A1 expression in the nymph stage. These results together imply that CYP306A1 may be implicated in IMD resistance in the nymph stage of the whitefly. RNAi knockdown of CYP306A1 increased the mortality of nymphs after treatment with IMD in bioassay, suggesting a pivotal role of CYP306A1 in conferring IMD resistance in the nymph stage. Additionally, our metabolism experiments in vivo showed that the content of IMD reduced by 20% along with cytochrome P450 reductase and heterologously expressed CYP306A1, which provides additional evidence for the important function of CYP306A1 in metabolizing IMD that leads to the resistance. CONCLUSION This study uncovers a novel function of the 20E biosynthesis gene CYP306A1 in metabolizing imidacloprid, thus contributing to such resistance in the immature stage of the insect. These findings not only advance our understanding of 20E-mediated insecticide resistance, but also provide a new target for sustainable pest control of global insect pests such as whitefly. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Shaonan Liu
- College of Plant Protection of Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chengjia Zhang
- Hunan Provincial Key Laboratory of Pesticide Biology and Precise Use Technology, Hunan Agricultural Biotechnology Research Institute, Changsha, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingjiao Huang
- College of Plant Protection of Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuegao Wei
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yao Ji
- College of Plant Protection of Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinyu Hu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - He Du
- College of Plant Protection of Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Youjun Zhang
- College of Plant Protection of Hunan Agricultural University, Changsha, China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
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13
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Yang J, Fu B, Gong P, Zhang C, Wei X, Yin C, Huang M, He C, Du T, Liang J, Liu S, Ji Y, Xue H, Wang C, Hu J, Du H, Zhang R, Yang X, Zhang Y. CYP6CX2 and CYP6CX3 mediate thiamethoxam resistance in field whitefly, Bemisia tabaci (Hemiptera:Aleyrodidae). J Econ Entomol 2023; 116:1342-1351. [PMID: 37208311 DOI: 10.1093/jee/toad089] [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] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/16/2023] [Accepted: 05/08/2023] [Indexed: 05/21/2023]
Abstract
Cytochrome P450 monooxygenases (P450s) are well-known for their crucial roles in the detoxification of xenobiotics. However, whether CYP6CX2 and CYP6CX3, 2 genes from our Bemisia tabaci (B. tabaci) MED/Q genome data were associated with detoxification metabolism and confer resistance to thiamethoxam is unclear. In this study, we investigated the role of CYP6CX2 and CYP6CX3 in mediating whitefly thiamethoxam resistance. Our results showed that mRNA levels of CYP6CX2 and CYP6CX3 were up-regulated after exposure to thiamethoxam. Transcriptional levels of 2 genes were overexpressed in laboratory and field thiamethoxam resistant strains by RT-qPCR. These results indicate that the enhanced expression of CYP6CX2 and CYP6CX3 appears to confer thiamethoxam resistance in B. tabaci. Moreover, linear regression analysis showed that the expression levels of CYP6CX2 and CYP6CX3 were positively correlated with thiamethoxam resistance levels among populations. The susceptibility of whitefly adults was markedly increased after silencing 2 genes by RNA interference (RNAi) which further confirming their major role in thiamethoxam resistance. Our findings provide information to better understand the roles of P450s in resistance to neonicotinoids and suggest that these genes may be applied to develop target genes for sustainable management tactic of agricultural pests such as B. tabaci.
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Affiliation(s)
- Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chengjia Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuegao Wei
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mingjiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shaonan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinyu Hu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Youjun Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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14
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Deng W, He M, Wang W, Xue H. Gastrointestinal: Pancreatic NETs with GCGR heterozygous mutation: Mahvash disease. J Gastroenterol Hepatol 2023; 38:1243. [PMID: 36698259 DOI: 10.1111/jgh.16104] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 11/25/2022] [Accepted: 01/01/2023] [Indexed: 01/27/2023]
Affiliation(s)
- W Deng
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
| | - M He
- Department of Radiology, Guangdong Provincial People's Hospital and Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - W Wang
- Department of Pathology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
| | - H Xue
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
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15
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Wei X, Hu J, Yang J, Yin C, Du T, Huang M, Fu B, Gong P, Liang J, Liu S, Xue H, He C, Ji Y, Du H, Zhang R, Wang C, Li J, Yang X, Zhang Y. Cytochrome P450 CYP6DB3 was involved in thiamethoxam and imidacloprid resistance in Bemisia tabaci Q (Hemiptera: Aleyrodidae). Pestic Biochem Physiol 2023; 194:105468. [PMID: 37532309 DOI: 10.1016/j.pestbp.2023.105468] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/23/2023] [Accepted: 05/14/2023] [Indexed: 08/04/2023]
Abstract
High level resistance for a variety of insecticides has emerged in Bemisia tabaci, a globally notorious insect. Neonicotinoid insecticides have been applied widely to control B. tabaci. Whether a differentially expressed gene CYP6DB3 discovered from transcriptome data of B. tabaci is involved in the resistance to neonicotinoid insecticides remains unclear. In the study, CYP6DB3 expression was significantly up-regulated in both thiamethoxam- and imidacloprid-resistant strains relative to the susceptive strains. We also found that CYP6DB3 expression was up-regulated after B. tabaci adults were exposed to thiamethoxam and imidacloprid. Moreover, knocking down CYP6DB3 expression via feeding corresponding dsRNA significantly reduced CYP6DB3 mRNA levels by 34.1%. Silencing CYP6DB3 expression increased the sensitivity of B. tabaci Q adults against both thiamethoxam and imidacloprid. Overexpression of CYP6DB3 gene reduced the toxicity of imidacloprid and thiamethoxam to transgenic D. melanogaster. In addition, metabolic studies showed that CYP6DB3 can metabolize 24.41% imidacloprid in vitro. Collectively, these results strongly support that CYP6DB3 plays an important role in the resistance of B. tabaci Q to imidacloprid and thiamethoxam. This work will facilitate a deeper insight into the part of cytochrome P450s in the evolution of insecticide resistance and provide a theoretical basis for the development of new integrated pest resistance management.
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Affiliation(s)
- Xuegao Wei
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinyu Hu
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng Yin
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mingjiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shaonan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hu Xue
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rong Zhang
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao Wang
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Junkai Li
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Youjun Zhang
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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16
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Gong PP, Wei XG, Liu SN, Yang J, Fu BL, Liang JJ, Huang MJ, Du TH, Yin C, Ji Y, He C, Hu JY, Xue H, Wang C, Zhang R, Du H, Zhang CJ, Yang X, Zhang YJ. Novel_miR-1517 mediates CYP6CM1 to regulate imidacloprid resistance in Bemisia tabaci (Hemiptera: Gennadius). Pestic Biochem Physiol 2023; 194:105469. [PMID: 37532310 DOI: 10.1016/j.pestbp.2023.105469] [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] [Received: 03/27/2023] [Revised: 05/09/2023] [Accepted: 05/14/2023] [Indexed: 08/04/2023]
Abstract
Bemisia tabaci (Hemiptera: Gennadius) is a notorious pest that is capable of feeding on >600 kinds of agricultural crops. Imidacloprid is critical in managing pest with sucking mouthparts, such as B. tabaci. However, the field population of B. tabaci has evolved resistance because of insecticide overuse. The overexpression of the detoxification enzyme cytochrome P450 monooxygenase is considered the main mechanism of imidacloprid resistance, but the mechanism underlying gene regulation remains unclear. MicroRNAs are a type of endogenous small molecule compounds that is fundamental in regulating gene expression at the post-transcriptional level. Whether miRNAs are related to the imidacloprid resistance of B. tabaci remains unknown. To gain deep insight into imidacloprid resistance, we conducted on miRNAs expression profiling of two B. tabaci Mediterranean (MED) strains with 19-fold resistance through deep sequencing of small RNAs. A total of 8 known and 1591 novel miRNAs were identified. In addition, 16 miRNAs showed significant difference in expression levels between the two strains, as verified by quantitative reverse transcription PCR. Among these, novel_miR-376, 1517, and 1136 significantly expressed at low levels in resistant samples, decreasing by 36.9%, 60.2%, and 15.6%, respectively. Moreover, modulating novel_miR-1517 expression by feeding with 1517 inhibitor and 1517 mimic significantly affected B. tabaci imidacloprid susceptibility by regulating CYP6CM1 expression. In this article, miRNAs related to imidacloprid resistance of B. tabaci were systematically screened and identified, providing important information for the miRNA-based technological innovation for this pest management.
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Affiliation(s)
- Pei-Pan Gong
- College of Plant Protection, Shenyang Agricultural University, Shenyang 110866, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xue-Gao Wei
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shao-Nan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Bu-Li Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jin-Jin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Ming-Jiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tian-Hua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jin-Yu Hu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng-Jia Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - You-Jun Zhang
- College of Plant Protection, Shenyang Agricultural University, Shenyang 110866, China; State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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17
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Pan L, Xue H, Yu F, Shan D, Zhang DP, Wang JJ. [Status and associated factors of pre-exposure prophylaxis use among men who have sex with men in 24 cities in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:905-911. [PMID: 37380411 DOI: 10.3760/cma.j.cn112338-20220831-00749] [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: 06/30/2023]
Abstract
Objective: To understand the cognition and medication use of pre-exposure prophylaxis (PrEP) among men who have sex with men (MSM) in China and its associated factors. Method: From August 25 to September 5, 2021, 2 447 MSM were recruited in 24 cities to complete the online questionnaire through a male social interaction platform, Blued 7.5 software. The survey contents included demographic information of the respondents, PrEP awareness and usage, and risk behaviors. Descriptive analysis and multi-level logistic regression were performed for data analysis. SPSS 24.0 and SAS 9.4 software were used for statistical analysis. Results: Among the 2 447 respondents of MSM, 1 712 (69.96%) had heard of PrEP, 437 (17.86%) ever used PrEP, 274 (11.20%) were on PrEP, and 163 (6.66%) had discontinued PrEP; among the 437 cases (whoever used PrEP), more than 61.88% (388/627) adopted emtricitabine/tenofovir disoproxil fumarate regimen, and most of them adopted on-demand regimen. The average PrEP dosage reported in the past year is 1.12 tabletsper person per week. PrEP purchase was primarily via an online channel, and the most concerned factor was the PrEP effectiveness on HIV prevention. The most common reasons for discontinuing PrEP, reported by 163 cases, were the lack of HIV risk perception, the use of a condom to prevent HIV, and the economic burden of PrEP use. The logistic regression analysis showed that PrEP use among MSM in 24 cities was statistically associated with age, monthly income, ever having unprotected anal sex in the past year, used sexual drugs and sexually transmitted disease (STD) diagnosis in the past year. Compared with MSM aged 18-24, the proportion of MSM was relatively lower among those aged 25-44, who discontinued the PrEP (aOR=0.54,95%CI:0.34-0.87) or never used PrEP (aOR=0.62,95%CI:0.44-0.87). The proportion of unprotected anal sex among MSM currently on PrEP use was higher than those who have stopped PrEP and never used PrEP (all P<0.05). Those MSM group, with monthly income higher than 5 000 Yuan, used sexual drugs and STD diagnosis in the past year were more likely to have a higher rate for PrEP usage (all P<0.05). Conclusions: Currently, pre-exposure prophylaxis in the MSM group is primarily obtained via the online channel and adopted in an on-demand mode. Although the PrEP users have reached a certain proportion, it is still necessary to strengthen health education on the PrEP effects and side effects of MSM and to improve the awareness and use rate, especially for young MSM group, which can be combined with the advantages of the internet targeting its needs and use barriers.
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Affiliation(s)
- L Pan
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - H Xue
- Danlan Goodness, Beijing 100022, China
| | - F Yu
- Danlan Goodness, Beijing 100022, China
| | - D Shan
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - D P Zhang
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - J J Wang
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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Wang CB, Wang TT, Ma CY, Xue H, Li Y, Piao CG, Jiang N. Phyllosticta rizhaoensis sp. nov. causing leaf blight of Ophiopogon japonicus in China. Fungal Syst Evol 2023; 11:43-50. [PMID: 38516385 PMCID: PMC10956614 DOI: 10.3114/fuse.2023.11.03] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/14/2023] [Indexed: 03/23/2024] Open
Abstract
Ophiopogon japonicus (Asparagaceae) is a perennial grass species which can be cultivated as an ornamental and medicinal plant. From April 2021 to September 2022, a serious leaf blight disease of O. japonicus was discovered in Rizhao City, Shandong Province, China. The initial disease symptoms were small yellow spots, finally developing as tip blight, often associated with many small, black, semi-immersed pycnidial conidiomata formed in lesions. To obtain isolates of the causal agent for this disease, samples were randomly collected from O. japonicus diseased leaves in Rizhao City. In total 97 Phyllosticta isolates were obtained from samples, and studied using morphological features and multi-locus phylogenetic analyses of a combined dataset using the internal transcribed spacers (ITS), the 28S large subunit of ribosomal RNA (LSU), and partial translation elongation factor 1-alpha (tef), actin (act) and glyceraldehyde-3-phosphate dehydrogenase (gapdh) loci. Phylogenetically, these Phyllosticta isolates formed a clade in the P. concentrica species complex, and clustered with P. pilospora and P. spinarum. Morphologically, isolates in this clade differed from P. pilospora and P. spinarum by the size of conidiogenous cells and conidia, and the absence of an apical conidial appendage. As a result, these isolates were described as a novel species Phyllosticta rizhaoensis. Pathogenicity was confirmed using Koch's postulates, which showed that P. rizhaoensis could induce leaf blight symptoms on O. japonicus in China. Citation: Wang C-B, Wang T-T, Ma C-Y, Xue H, Li Y, Piao C-G, Jiang N (2023). Phyllosticta rizhaoensis sp. nov. causing leaf blight of Ophiopogon japonicus in China. Fungal Systematics and Evolution 11: 43-50. doi: 10.3114/fuse.2023.11.03.
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Affiliation(s)
- C.-B. Wang
- Key Laboratory of Biodiversity Conservation of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - T.-T. Wang
- Forestry Protection and Development Service Center of Rizhao City, Rizhao 276800, China
| | - C.-Y. Ma
- Natural Resources and Planning Bureau of Rizhao City, Rizhao 276800, China
| | - H. Xue
- Key Laboratory of Biodiversity Conservation of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - Y. Li
- Key Laboratory of Biodiversity Conservation of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - C.-G. Piao
- Key Laboratory of Biodiversity Conservation of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - N. Jiang
- Key Laboratory of Biodiversity Conservation of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
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19
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Liu QZ, Yang X, Xue H, Tang HL. [Analysis of on-demand adherence and related factors in men who have sex with men who access HIV pre-exposure prophylaxis services via the internet]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:791-796. [PMID: 37221069 DOI: 10.3760/cma.j.cn112338-20221021-00902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Objective: To understand the compliancy to on-demand HIV pre-exposure prophylaxis (PrEP) and related factors in men who have sex with men (MSM) accessing to PrEP service through an Internet platform. Methods: A cross-sectional study method was used to recruit survey respondents through the Heer Health platform from July 6 to August 30, 2022, and a questionnaire survey on the current status of medication use was conducted in MSM who use PrEP through the platform and take medication on demand. The MSM's information collected in the survey mainly included socio-demographic characteristics, behavioral characteristics, risk perception characteristics, PrEP awareness and the status of dose taking. Univariate and multivariate logistic regression analyses were used to evaluate factors related with compliancy to PrEP. Results: A total of 330 MSM who met the recruitment criteria were included during the survey period, with a valid response rate of 96.7% (319/330) to the questionnaire survey. The age of the 319 MSM was (32.5±7.3) years. Most of them had education level of junior college or college and above (94.7%, 302/319), most of them were unmarried (90.3%, 288/319), most of them had full-time works (95.9%, 306/319), and 40.8% of them had average monthly income ≥10 000 yuan (130/319). The proportion of the MSM with good compliancy to PrEP was 86.5% (276/319). The results of univariate and multivariate logistic analyses showed that the MSM with good awareness of PrEP had relatively better compliancy to PrEP compared with those with poor awareness of PrEP (aOR=2.43, 95%CI:1.11-5.32). Conclusions: The compliancy to on-demand PrEP was good in MSM who accessed to the services through Internet platform, but there is still a need to strengthen PrEP promotion in MSM for the further improvement of PrEP compliancy and reduction of the risk for HIV infection in this population.
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Affiliation(s)
- Q Z Liu
- Division of Epidemiology, National Center for AIDS/STD Prevention and Control, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - X Yang
- Beijing Huilongguan Hospital, Beijing 100096, China
| | - H Xue
- Bluedhealth, Beijing 100022, China
| | - H L Tang
- Division of Epidemiology, National Center for AIDS/STD Prevention and Control, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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20
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Yin C, Gui LY, Du TH, Zhang CJ, Wei XG, Yang J, Huang MJ, Fu BL, Gong PP, Liang JJ, Liu SN, Xue H, Hu JY, Ji Y, He C, Du H, Wang C, Zhang R, Wu QJ, Yang X, Zhang YJ. Knockdown of the Nicotinic Acetylcholine Receptor β1 Subunit Decreases the Susceptibility to Five Neonicotinoid Insecticides in Whitefly ( Bemisia tabaci). J Agric Food Chem 2023; 71:7221-7229. [PMID: 37157975 DOI: 10.1021/acs.jafc.3c00782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
The sweet potato whitefly, Bemisia tabaci, (Gennadius) (Hemiptera:Aleyrodidae) is a global pest of crops. Neonicotinoids are efficient insecticides used for control of this pest. Insecticidal targets of neonicotinoids are insect nicotinic acetylcholine receptors (nAChRs). Here, we characterized and cloned the full length of the nAChR β1 subunit (BTβ1) in B. tabaci and confirmed the consistency of BTβ1 in B. tabaci MEAM1 and MED. Expression levels of BTβ1 in different developmental stages and body parts of adults were investigated and compared in B. tabaci MED. dsRNA was prepared to knock down BTβ1 in adult B. tabaci and significantly decreases the susceptibility to five neonicotinoid insecticides, including imidacloprid, clothianidin, thiacloprid, nitenpyram, and dinotefuran. This study indicated BTβ1 as a notable site influencing the susceptibility of B. tabaci to neonicotinoids.
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Affiliation(s)
- Cheng Yin
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, People's Republic of China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Lian-You Gui
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, Hubei 434025, People's Republic of China
| | - Tian-Hua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Cheng-Jia Zhang
- Hunan Provincial Key laboratory of Pesticide Biology and Precise Use Techology, Hunan Agricultural Biotechnology Research Institute, Changsha, Hunan 410125, People's Republic of China
| | - Xue-Gao Wei
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Ming-Jiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Bu-Li Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Pei-Pan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Jin-Jin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Shao-Nan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Jin-Yu Hu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Chao Wang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Qing-Jun Wu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - You-Jun Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
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21
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He C, Liang J, Yang J, Xue H, Huang M, Fu B, Wei X, Liu S, Du T, Ji Y, Yin C, Gong P, Hu J, Du H, Zhang R, Xie W, Wang S, Wu Q, Zhou X, Yang X, Zhang Y. Over-expression of CP9 and CP83 increases whitefly cell cuticle thickness leading to imidacloprid resistance. Int J Biol Macromol 2023; 233:123647. [PMID: 36780959 DOI: 10.1016/j.ijbiomac.2023.123647] [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: 12/14/2022] [Revised: 01/11/2023] [Accepted: 02/02/2023] [Indexed: 02/13/2023]
Abstract
Cuticular proteins (CPs) play an important role in protecting insects from adverse environmental conditions, like neonicotinoid insecticides, which are heavily used for numerous pests and caused environmental problems and public health concerns worldwide. However, the relationship between CPs and insecticides resistance in Bemisia tabaci, a serious and developed high insecticide resistance, is lacking. In this study, 125 CPs genes were identified in B. tabaci. Further phylogenetic tree showed the RR-2-type genes formed large gene groups in B. tabaci. Transcriptional expression levels of CPs genes at different developmental stages revealed that some CPs genes may play a specific role in insect development. The TEM results indicated that the cuticle thickness of susceptible strain was thinner than imidacloprid-resistance strain. Furthermore, 16 CPs genes (5 in RR-1 subfamily, 7 in RR-2 subfamily, 3 in CPAP3 subfamily and 1 in CPCFC subfamily) were activated in response to imidacloprid. And RNAi results indicated that CP9 and CP83 involved in imidacloprid resistance. In conclusion, this study was the first time to establish a basic information framework and evolutionary relationship between CPs and imidacloprid resistance in B. tabaci, which provides a basis for proposing integrated pest management strategies.
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Affiliation(s)
- Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hu Xue
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mingjiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuegao Wei
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shaonan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng Yin
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - JinYu Hu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rong Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Wen Xie
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shaoli Wang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Qingjun Wu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuguo Zhou
- Department of Entomology, University of Kentucky, S-225 Agricultural Science Center North, Lexington, KY 40546-0091, USA.
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Youjun Zhang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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Xue H, Wen J, Liu C, Shuai X, Zhang X, Kang N. Modified transcrestal sinus floor elevation with concomitant implant placement in edentulous posterior maxillae with residual bone height of 5 mm or less: a non-controlled prospective study. Int J Oral Maxillofac Surg 2023; 52:495-502. [PMID: 36058822 DOI: 10.1016/j.ijom.2022.08.014] [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: 10/27/2021] [Revised: 08/15/2022] [Accepted: 08/15/2022] [Indexed: 11/26/2022]
Abstract
The aim of this study was to describe a modified transcrestal sinus floor elevation (mTSFE) technique and to evaluate its clinical effectiveness and reliability when residual bone height is severely reduced. Forty-three maxillary edentulous patients who met the inclusion criteria were enrolled. All patients underwent the mTSFE technique; 66 dental implants were inserted simultaneously. Patient-reported outcomes were assessed 2 weeks after surgery. Prosthetic crowns were placed 6 months after surgery. Radiographic analyses and clinical analyses were conducted to assess the clinical effectiveness and feasibility of mTSFE during a follow-up period of 2-8 years. The mean vertical bone increase after surgery was 8.09 mm, and it decreased to 6.56 mm at 6 months after surgery. Two cases of membrane perforation occurred during surgery and one implant was lost in the third year after surgery; the survival rate at the implant level was 98.48%. No severe postoperative complication was reported and the subjective feeling of patients was acceptable. This mTSFE technique could simplify the operative procedure and might be helpful to reduce intraoperative trauma, as well as to alleviate postoperative discomfort.
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Affiliation(s)
- H Xue
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China; Department of Prosthodontics, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University, School of Medicine; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology and Shanghai Research Institute of Stomatology, Shanghai, China
| | - J Wen
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - C Liu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - X Shuai
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - X Zhang
- National Engineering Research Center for Biomaterials, Sichuan University, Chengdu, China
| | - N Kang
- National Engineering Research Center for Biomaterials, Sichuan University, Chengdu, China; Department of Oral Implantology (National Key Clinical Department), West China Hospital of Stomatology, Sichuan University, Chengdu, China.
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23
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Liu HH, Xue H, Chen RS. [ Yang Shoushan Medical Cases in the Wumen Medical School]. Zhonghua Yi Shi Za Zhi 2023; 53:107-110. [PMID: 37183625 DOI: 10.3760/cma.j.cn112155-20220809-00111] [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: 05/16/2023]
Abstract
The unique manuscript, Yang Shoushan Medical Cases, is now held by the library of Nanjing University of Chinese Medicine.It is the medical cases collection of Yang Shoushan, a well-known doctor of Suzhou in the late Qing Dynasty.It was found that the number of medical cases and the details of each case recorded in this book were much more than that in his other existing medical writings. It greatly enriches the historical materials for the study of Yang's clinical characteristics and academic thought.Its compiler was Huang Shounan, a physician and calligrapher in Suzhou in the late Qing Dynasty and the early Republic of China.This book was not recorded as a book compiled by Huang Shounan before now. This book was believed to be completed in 1890.
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Affiliation(s)
- H H Liu
- Institute of Literature in Chinese Medicine,Nanjing University of Chinese Medicine,Nanjing 210023,China Suzhou Hospital of Integrated Traditional Chinese and Western Medicine,Suzhou 215101,China
| | - H Xue
- Institute of Literature in Chinese Medicine,Nanjing University of Chinese Medicine,Nanjing 210023,China
| | - R S Chen
- Institute of Literature in Chinese Medicine,Nanjing University of Chinese Medicine,Nanjing 210023,China
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24
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Xue H, Jin S, Wu Q, Geng X. How did consumers’ self-protective behavior formed during the COVID-19 pandemic? Front Psychol 2023; 14:1075211. [PMID: 36968725 PMCID: PMC10034392 DOI: 10.3389/fpsyg.2023.1075211] [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: 10/22/2022] [Accepted: 02/20/2023] [Indexed: 03/11/2023] Open
Abstract
IntroductionThis study explored the formation mechanism of consumers’ self-protective behavior during the COVID-19 pandemic, which is very important for policy settings to regulate consumer behavior. Based on the basic framework of the Protective Action Decision Model (PADM), this study analyzed the formation mechanism of consumers’ self-protective willingness from the perspective of risk information, and explained the deviation between consumers’ self-protective willingness and behavior from the perspective of protective behavior attributes.MethodsBased on 1,265 consumer survey data during the COVID-19 pandemic, the empirical test was carried out.Results and DiscussionThe amount of risk information has a significant positive impact on the consumers’ self-protective willingness, where the credibility of risk information plays a positive moderating role between them. Risk perception plays a positive mediating role between the amount of risk information and the consumers’ self-protective willingness, and the positive mediating effect of risk perception is negatively moderated by the credibility of risk information. In the protective behavior attributes, hazard-related attributes play a positive moderating role between the consumers’ self-protective willingness and behavior, while resource-related attributes play the opposite role. Consumers pay more attention to hazard-related attributes than resource-related attributes, and they are willing to consume more resources to reduce risk.
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25
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Odoh CK, Kamal R, Xue H, Lyu L, Arnone JT, Zhao ZK. Glucosylglycerol Extends Chronological Lifespan of the Budding Yeast via an Increased Osmolarity Response. Indian J Microbiol 2023; 63:42-49. [PMID: 37188237 PMCID: PMC10172420 DOI: 10.1007/s12088-023-01055-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 01/03/2023] [Indexed: 01/10/2023] Open
Abstract
Glucosylglycerol (GG) is an osmolyte that protects cells from extreme conditions. It is produced by sucrose phosphorylase, an enzyme that uses sucrose and glycerol as substrate. GG protects tissue integrity in desert plants during harsh conditions and guards cyanobacteria against high salinity (halotolerant). However, no extensive research has been conducted on the lifespan application of this compound on the yeast Saccharomyces cerevisiae. We designed this study to (1) characterize GG's effect on yeast chronological lifespan (CLS) and (2) to determine the mechanisms underlying its lifespan promotion on strain DBY746. The results obtained in our study confirm that GG causes increased longevity when administered at moderate doses (48 mM and 120 mM). In addition, we discovered that GG promotes yeast cell longevity by increasing the osmolarity of the culture medium. The maximum lifespan increased by approximately 15.38% and 34.6%, (i.e., 115.38 and 134.61) respectively, upon administration of GG at 48 mM and 120 mM concentrations. Elucidation of the mechanisms underlying this positive response suggests that GG promotes CLS by activities that modulate reactive oxygen species (ROS) generation, as evident in its increased ROS generation (mitohormesis). An increase in medium osmolarity caused by GG supplementation triggers ROS production and promotes longevity in the yeast (S. cerevisiae). An in-depth study on the potential application of this molecule in aging research is crucial; this will aid in expounding the mechanisms of this geroprotector and its longevity supportive tendencies. Supplementary Information The online version contains supplementary material available at 10.1007/s12088-023-01055-y.
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Affiliation(s)
- C. K. Odoh
- Laboratory of Biotechnology, Dalian Institute of Chemical Physics, CAS, 457 Zhongshan Rd, Dalian, 116023 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - R. Kamal
- Laboratory of Biotechnology, Dalian Institute of Chemical Physics, CAS, 457 Zhongshan Rd, Dalian, 116023 China
| | - H. Xue
- Laboratory of Biotechnology, Dalian Institute of Chemical Physics, CAS, 457 Zhongshan Rd, Dalian, 116023 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - L. Lyu
- Laboratory of Biotechnology, Dalian Institute of Chemical Physics, CAS, 457 Zhongshan Rd, Dalian, 116023 China
| | - J. T. Arnone
- Department of Biology, William Paterson University, Wayne, NJ 07470 USA
| | - Z. K. Zhao
- Laboratory of Biotechnology, Dalian Institute of Chemical Physics, CAS, 457 Zhongshan Rd, Dalian, 116023 China
- Dalian Key Laboratory of Energy Biotechnology, Dalian Institute of Chemical Physics, CAS, 457 Zhongshan Rd, Dalian, 116023 China
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Xue H, Fu B, Huang M, He C, Liang J, Yang J, Wei X, Liu S, Du T, Ji Y, Yin C, Gong P, Hu J, Du H, Zhang R, Wang C, Khajehali J, Su Q, Yang X, Zhang Y. CYP6DW3 Metabolizes Imidacloprid to Imidacloprid-urea in Whitefly ( Bemisia tabaci). J Agric Food Chem 2023; 71:2333-2343. [PMID: 36705580 DOI: 10.1021/acs.jafc.2c08353] [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] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Bemisia tabaci has developed high resistance to many insecticides and causes substantial agricultural and economic losses annually. The insecticide resistance of whitefly has been widely reported in previous studies; however, the underlying mechanism remains little known. In this study, we cloned two P450 genes: CYP6DW3 and CYP6DW5v1; these genes were markedly overexpressed in imidacloprid-resistant whitefly populations compared with susceptible populations, and knockdown of these genes decreased the imidacloprid resistance of whitefly. Moreover, heterologous expression of whitefly P450 genes in SF9 cells and metabolic studies showed that the CYP6DW3 protein could metabolize 14.11% imidacloprid and produced imidacloprid-urea in vitro. Collectively, the expression levels of CYP6DW3 and CYP6DW5v1 are positively correlated with imidacloprid resistance in B. tabaci. Our study further reveals that cytochrome P450 enzymes affect the physiological activities related to resistance in insects, which helps scholars more deeply understand the resistance mechanism, and contributes to the development of integrated pest management framework.
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Affiliation(s)
- Hu Xue
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Buli Fu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- The Ministry of Agriculture and Rural Affairs Key Laboratory of Integrated Pest Management of Tropical Crops, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, P. R. China
| | - Mingjiao Huang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- College of Plant Protection, Hunan Agricultural University, Changsha 410125, P. R. China
| | - Chao He
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinjin Liang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuegao Wei
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shaonan Liu
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tianhua Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yao Ji
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Cheng Yin
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Peipan Gong
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - JinYu Hu
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - He Du
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rong Zhang
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chao Wang
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jahangir Khajehali
- Department of Plant Protection, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iran
| | - Qi Su
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
| | - Xin Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Youjun Zhang
- Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, P. R. China
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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27
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Yang F, Zhang X, Shen H, Xue H, Tian T, Zhang Q, Hu J, Tong H, Zhang Y, Su Q. Flavonoid-producing tomato plants have a direct negative effect on the zoophytophagous biological control agent Orius sauteri. Insect Sci 2023; 30:173-184. [PMID: 35633508 DOI: 10.1111/1744-7917.13085] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/16/2022] [Accepted: 05/11/2022] [Indexed: 06/15/2023]
Abstract
Orius sauteri (Poppius) (Hemiptera: Anthocoridae) is often used for biological control of small arthropod pests in greenhouse vegetable production systems in Asia. In addition to feeding on arthropod prey, O. sauteri consumes small quantities of plant material. Previous studies demonstrated that tomato plant chemistry confers antixenosis resistance to phloem-feeding whiteflies, but the potential nontarget effects of phytochemicals on the beneficial predator O. sauteri are unknown. Comparison of O. sauteri confined to near-isogenic lines (NILs) of tomatoes producing high levels of flavonoids (NIL-purple hypocotyl; resistant to whiteflies) and low levels of flavonoids (NIL-green hypocotyl; susceptible to whiteflies) revealed that O. sauteri had reduced oviposition, nymphal survival, and development on resistant plants, even if they were also provided with prey that did not feed on the host plant. Moreover, O. sauteri showed a significant ovipositional preference in choice assays, laying significantly more eggs on susceptible than on resistant plants. Molecular gut content analysis using the specific chloroplast trnL gene from tomato confirmed that adult and immature O. sauteri feed on both resistant and susceptible genotypes, and feeding behavior assays revealed that resistance did not affect plant feeding or prey acceptance by O. sauteri adults. These results demonstrate a direct negative effect of phytochemicals on a nontarget beneficial species and indicate that resistance mediated by phytochemicals can affect organisms that do not solely feed on phloem sap. The results also indicate that the mode of action and the potential ecological effects of phytochemical-mediated resistance are broader than previously recognized.
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Affiliation(s)
- Fengbo Yang
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
| | - Xinyi Zhang
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Haowei Shen
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
| | - Hu Xue
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tian Tian
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qinghe Zhang
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
| | - Jinyu Hu
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hong Tong
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
| | - Youjun Zhang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qi Su
- Hubei Engineering Technology Center for Forewarning and Management of Agricultural and Forestry Pests, College of Agriculture, Yangtze University, Jingzhou, Hubei Province, China
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28
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Li Y, Xue H, Chen RS. [Miao Zunyi - his life, writings and students]. Zhonghua Yi Shi Za Zhi 2023; 53:22-27. [PMID: 36925150 DOI: 10.3760/cma.j.cn112155-20220331-00039] [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: 03/18/2023]
Abstract
Miao Zunyi was an influential physician in the mid-Qing Dynasty. He was self-taught as he read a great amount of prescription books of traditional Chinese medicine. He was proficient in medical theories but flexible in treatment. It was recorded in Draft of Qing History that Miao Zunyi, Ye Tianshi and Xue Shengbai were named as "the three schools of Wuzhong". He began to write books in his later years. He wrote prefaces to Pulse Causes, Syndrome and Treatment (Mai Yin Zheng Zhi) and Wu Yi Hui Jiang. His existing works include Treatise on Febrile Disease (Shang Han Ji Zhu), Wen Re Lang Zhao, Song Xin Notes and Song Xin Medical Cases. Miao's Medical Cases and Song Xin Tang Yi An Jing Yan Chao. He had many remarkable students, such like Huang Tang, Guan Ding, Miao Song, and Shen Nianzu.
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Affiliation(s)
- Y Li
- Institute of Literature in Chinese Medicine,Nanjing University of Traditional Chinese Medicine ,Nanjing 210023,China
| | - H Xue
- Institute of Literature in Chinese Medicine,Nanjing University of Traditional Chinese Medicine ,Nanjing 210023,China
| | - R S Chen
- Institute of Literature in Chinese Medicine,Nanjing University of Traditional Chinese Medicine ,Nanjing 210023,China
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29
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Yang F, Zhang X, Xue H, Tian T, Tong H, Hu J, Zhang R, Tang J, Su Q. (Z)-3-hexenol primes callose deposition against whitefly-mediated begomovirus infection in tomato. Plant J 2022; 112:694-708. [PMID: 36086899 DOI: 10.1111/tpj.15973] [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] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 09/04/2022] [Accepted: 09/07/2022] [Indexed: 06/15/2023]
Abstract
Rapid callose accumulation has been shown to mediate defense in certain plant-virus interactions. Exposure to the green leaf volatile (Z)-3-hexenol (Z-3-HOL) can prime tomato (Solanum lycopersicum) for an enhanced defense against subsequent infection by whitefly-transmitted Tomato yellow leaf curl virus (TYLCV). However, the molecular mechanisms affecting Z-3-HOL-induced resistance are poorly understood. Here, we explored the mechanisms underlying Z-3-HOL-induced resistance against whitefly-transmitted TYLCV infection and the role of callose accumulation during this process. Tomato plants pre-treated with Z-3-HOL displayed callose priming upon whitefly infestation. The callose inhibitor 2-deoxy-d-glucose abolished Z-3-HOL-induced resistance, confirming the importance of callose in this induced resistance. We also found that Z-3-HOL pre-treatment enhanced salicylic acid levels and activated sugar signaling in tomato upon whitefly infestation, which increased the expression of the cell wall invertase gene Lin6 to trigger augmented callose deposition against TYLCV infection resulting from whitefly transmission. Using virus-induced gene silencing, we demonstrated the Lin6 expression is relevant for sugar accumulation mediated callose priming in restricting whitefly-transmitted TYLCV infection in plants that have been pre-treated with Z-3-HOL. Moreover, Lin6 induced the expression of the callose synthase gene Cals12, which is also required for Z-3-HOL-induced resistance of tomato against whitefly-transmitted TYLCV infection. These findings highlight the importance of sugar signaling in the priming of callose as a defense mechanism in Z-3-HOL-induced resistance of tomato against whitefly-transmitted TYLCV infection. The results will also increase our understanding of defense priming can be useful for the biological control of viral diseases.
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Affiliation(s)
- Fengbo Yang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Xinyi Zhang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Hu Xue
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Tian Tian
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Hong Tong
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Jinyu Hu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Rong Zhang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Juan Tang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Qi Su
- Ministry of Agriculture and Rural Affairs Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), Hubei Engineering Technology Center for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, 434025, China
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30
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Jex N, Chowdhary A, Thirunavukarasu S, Procter H, Sengupta A, Natarajan P, Kotha S, Poenar AM, Xue H, Cubbon R, Kellman P, Greenwood JP, Plein S, Page SP, Levelt E. Coexistent diabetes is associated with the presence of adverse phenotypic features in patients with hypertrophic cardiomyopathy. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.243] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Type 2 diabetes mellitus (DM) is associated with worsened clinical outcomes in hypertrophic cardiomyopathy (HCM) patients. The reasons for this adverse prognostic association are incompletely understood. Although distinct entities both HCM and DM share common features of impaired myocardial energetics and coronary microvascular function.
Purpose
We sought to test the hypothesis that co-existent diabetes is associated with greater reductions in myocardial energetics and perfusion, and higher scar burden in HCM.
Research design and methods
Seventy-five age- and sex-matched participants with concomitant HCM and DM (HCM-DM, n=20), isolated HCM (n=20), isolated DM (n=20) and healthy volunteers (HV, n=15) underwent 31phosphorus magnetic resonance spectroscopy and cardiovascular magnetic resonance imaging. The HCM groups were matched for HCM phenotype. The DM groups were matched for diabetes treatment, duration, HbA1c, body mass index and hypertension comorbidity.
Results
ESC sudden cardiac death risk scores were comparable between the HCM groups (HCM: 2.2±1.5%, HCM-DM: 1.9±1.2%; p=NS) and sarcomeric mutations were equally common. HCM-DM had the highest NT-proBNP levels (HV: 42 ng/L [IQR: 35–66], DM: 118 ng/L [IQR: 53–187], HCM: 298 ng/L [IQR: 157–837], HCM-DM: 726 ng/L [IQR: 213–8695]; p<0.0001). Left-ventricular ejection fraction, mass and wall thickness were similar between the HCM groups. HCM-DM displayed a greater degree of fibrosis burden with higher scar percentage, and lower global longitudinal strain compared to the isolated HCM. PCr/ATP was similarly decreased in the HCM-DM and DM (HV: 2.17±0.49, DM: 1.61±0.23, HCM: 1.93±0.38, HCM-DM: 1.54±0.27; p=0.0003). HCM-DM had the lowest stress myocardial blood flow (HV: 2.06±0.42 ml/min/g, DM: 1.78±0.45 ml/min/g, HCM: 1.74±0.44 ml/min/g, HCM-DM: 1.39±0.42 ml/min/g; p=0.004).
Conclusions
We show for the first time that HCM patients with DM comorbidity display greater reductions in myocardial energetics, perfusion, contractile function and higher myocardial scar burden and serum NT-proBNP levels compared to patients with isolated HCM despite similar LV mass and wall thickness and presence of sarcomeric mutations. These adverse phenotypic features may be important components of the adverse clinical manifestation attributable to a combined presence of HCM and DM.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): Diabetes UK
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Affiliation(s)
- N Jex
- University of Leeds , Leeds , United Kingdom
| | - A Chowdhary
- University of Leeds , Leeds , United Kingdom
| | | | - H Procter
- Leeds General Infirmary, Cardiology , Leeds , United Kingdom
| | - A Sengupta
- Leeds General Infirmary, Cardiology , Leeds , United Kingdom
| | - P Natarajan
- University of Leeds , Leeds , United Kingdom
| | - S Kotha
- University of Leeds , Leeds , United Kingdom
| | - A M Poenar
- Leeds General Infirmary, Cardiology , Leeds , United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - R Cubbon
- University of Leeds , Leeds , United Kingdom
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | | | - S Plein
- University of Leeds , Leeds , United Kingdom
| | - S P Page
- Leeds General Infirmary, Cardiology , Leeds , United Kingdom
| | - E Levelt
- University of Leeds , Leeds , United Kingdom
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31
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Yeo JL, Gulsin GS, Dattani A, Brady EM, Bilak JM, Arnold JR, Singh A, Xue H, Kellman P, McCann GP. Female sex and systolic blood pressure are independently associated with coronary microvascular dysfunction in asymptomatic adults with type 2 diabetes. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.282] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Introduction
Coronary microvascular dysfunction is frequently reported in people with type 2 diabetes (T2D), is associated with reduced exercise capacity, and is a prognostic marker. Identifying modifiable risk factors associated with microvascular dysfunction may facilitate early intervention to improve outcomes in these patients.
Purpose
To identify independent determinants of myocardial perfusion reserve (MPR) in asymptomatic adults with T2D and no prevalent cardiovascular disease.
Methods
Prospective cross-sectional study. People with and without T2D and no signs, symptoms or evidence of cardiovascular disease underwent comprehensive phenotyping with echocardiography, coronary artery calcium scoring, and multiparametric cardiac MRI including adenosine stress and rest perfusion with automated pixel-wise myocardial blood flow (MBF) mapping. Participants with regional perfusion defects indicating obstructive coronary disease or silent myocardial infarct on late-gadolinium enhancement were excluded from analysis. Univariable and multivariable linear regression was performed to identify independent determinants of MPR.
Results
Two-hundred people with T2D (diabetes duration 11±8 years) were compared with 39 sex- and ethnicity-matched non-diabetic controls (Table 1). People with T2D had higher body mass index (BMI) and ambulatory 24-hour systolic blood pressure (SBP). There was evidence of concentric left ventricular (LV) remodelling (higher LV mass/volume), extracellular matrix expansion (higher ECV fraction), and both systolic and diastolic dysfunction (lower global longitudinal systolic strain and E/A ratio, respectively) in those with T2D. Resting MBF was similar between groups, but stress MBF tended to be lower in T2D compared to controls with significantly reduced MPR in T2Ds (2.87±0.86 vs 3.18±0.82, p=0.043). In univariable analysis, MPR correlated with sex, 24-hour SBP, and E/e' ratio. In a multivariable model adjusting for clinical (age, sex, smoking status, BMI, ambulatory SBP, diabetes duration, HbA1c, low-density lipoprotein, albuminuria) and imaging variables (E/e' ratio, LV mass/volume, global longitudinal strain, myocardial ECV, coronary calcium score) known to affect coronary perfusion, female sex (β=−0.227, p=0.013) and 24-hour SBP (β=−0.275, p=0.001) were the only variables independently associated with MPR.
Conclusion
Female sex is associated with coronary microvascular dysfunction in asymptomatic people with T2D but not LV mass or myocardial extracellular volume. Systolic BP is the only modifiable independent determinant of MPR and may be an early target for intervention to prevent heart failure development in these patients.
Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): National Institute for Health Research (NIHR) United Kingdom through a Research Professorship award (RP-2017-08-ST2-007).British Heart Foundation through a Clinical Research Training Fellowship award (FS/16/47/32190).
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Affiliation(s)
- J L Yeo
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - G S Gulsin
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - A Dattani
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - E M Brady
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - J M Bilak
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - J R Arnold
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - A Singh
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute, National Institutes of Health , Bethesda , United States of America
| | - P Kellman
- National Heart Lung and Blood Institute, National Institutes of Health , Bethesda , United States of America
| | - G P McCann
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre , Leicester , United Kingdom
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32
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Jex N, Cubbon R, Chowdhary A, Thirunavukarasu S, Kotha S, Procter H, Xue H, Swoboda P, Kellman P, Greenwood JP, Plein S, Levelt E. Clinical outcomes and myocardial recovery in energetics, perfusion and contractile function after valve replacement surgery in severe aortic stenosis patients with diabetes comorbidity. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.1690] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Aortic stenosis (AS) and type 2 diabetes mellitus (DM) are increasingly frequent comorbidities in aging populations, and diabetes is associated with increased morbidity and mortality after aortic valve replacement (AVR). Although distinct pathological entities, AS and DM share common features of impaired myocardial energetics and coronary microvascular dysfunction (CMD). The mechanisms for the adverse prognostic association between AS and DM are incompletely understood.
Purpose
Utilising 31phosphorus magnetic resonance spectroscopy (31P-MRS) and CMR, we tested the hypotheses that the collective impact of severe AS and DM on the myocardium aggravates the impairment in energetics, function and perfusion.
Methods
Eighty-eight severe AS patients with (AS-DM) and without DM (Iso-AS) undergoing AVR and 15 healthy volunteers were recruited. Patients with coronary artery disease were excluded. Participants with AS underwent 31P-MRS and comprehensive CMR imaging 1 month prior to and 6 months after AVR.
Results
Demographic, biochemical and CMR/31P-MRS data are shown in Table-1. All groups were matched for age and sex distribution, with AS groups matched for surgical scores and frailty scores. NTproBNP levels were similarly elevated in AS groups. Left ventricular (LV) volumes and ejection fraction (EF) were similar between the groups, with no significant difference in LV mass or wall thickness between the AS groups. The baseline differences in myocardial energetics, stress myocardial blood flow (MBF) and global longitudinal strain (GLS) are shown in the Figure. AS-DM patients showed greater reductions in myocardial energetics (p<0.0001), global stress MBF (p<0.0001) and more significant reductions in GLS (p=0.001) than the Iso-AS patients. At 6 month post AVR both AS groups showed significant improvements in stress MBF and GLS. However, only the Iso-AS patients showed significant improvement in myocardial energetics.
AS patients were followed up for a median of 12 months. Cumulative incidence of the clinical events post AVR (composite of cardiovascular death, stroke, heart failure admission, infective endocarditis) were significantly higher in the AS-DM group than the Iso-AS group (Hazard Ratio: 3.35; 95% CI: 0.97–11.6; p=0.02).
Conclusion
Diabetes was associated with increased morbidity and mortality after AVR. We showed for the first time that the collective impact of T2DM and AS on the myocardium aggravates energetic impairment, CMD and contractile dysfunction. While myocardial recovery following AVR was associated with similar improvements in perfusion and contractile function in severe AS patients with and without T2DM, improvements in energetics were only detected in isolated AS patients. However, despite the significant improvements in contractile function and perfusion following AVR in diabetes patients, these parameters remained lower in the group with diabetes comorbidity compared to isolated AS patients.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): Wellcome Trust
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Affiliation(s)
- N Jex
- University of Leeds , Leeds , United Kingdom
| | - R Cubbon
- University of Leeds , Leeds , United Kingdom
| | - A Chowdhary
- University of Leeds , Leeds , United Kingdom
| | | | - S Kotha
- University of Leeds , Leeds , United Kingdom
| | - H Procter
- Leeds General Infirmary, Cardiology , Leeds , United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - P Swoboda
- University of Leeds , Leeds , United Kingdom
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | | | - S Plein
- University of Leeds , Leeds , United Kingdom
| | - E Levelt
- University of Leeds , Leeds , United Kingdom
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Hughes RK, Shiwani H, Rosmini S, Burke L, Pierce I, Castelletti S, Xue H, Kellman P, Lopes LR, Treibel T, Manisty C, Captur G, Davies R, Moon J. Improved diagnostic accuracy for apical hypertrophic cardiomyopathy. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.1553] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Introduction
The diagnosis of apical hypertrophic cardiomyopathy (ApHCM) is contingent on demonstrating apical maximum wall thickness (MWT) of ≥15mm; the same threshold as other HCM subtypes. However, the myocardium naturally tapers towards the apex in healthy individuals, so ≥15mm MWT is proportionately higher in the apex than in naturally thicker basal segments. Using cardiac magnetic resonance (CMR), relative ApHCM has been described (typical ECG features, loss of apical tapering, cavity obliteration but hypertrophy <15mm). Wall thickness measurement using machine learning now exceeds human performance.
Purpose
We aimed to redefine the optimal diagnostic threshold for ApHCM using segment-specific criteria based on a large cohort of healthy control subjects.
Methods
Segmental wall thickness was measured using healthy subjects from the UK Biobank using a clinically validated machine learning algorithm1,2. A normative reference range was established for all 16 segments, conditioned to body surface area (BSA), sex and age. Derived segment-specific wall thickness thresholds were used to define optimal disease thresholds for patients clinically managed with overt (MWT ≥15mm) and relative ApHCM (MWT <15mm, but typical ECG and imaging findings).
Results
4118 UK biobank subjects were used to define normal segmental thicknesses and reference ranges. These were applied to ApHCM (73 overt, 31 relative). There were no apical wall thickness age related differences. The upper limit of the 95% confidence interval corresponded to a combined maximum apical MWT for both males and females of 10.4mm using non-indexed measurement, or 5.6mm/m2 when indexed to BSA. Non-indexed segmental threshold identified 100% of ApHCM patients (true positives), 81% (25 of 31) relative ApHCM and 3% (115 of 4118) of healthy UK biobank subjects (false positives). Indexed segmental thresholds improved the diagnostic potential in relative ApHCM without an increase in false positives (100% of ApHCM patients, 84% (26 of 31) of relative ApHCM patients, and 3% healthy UK biobank (127 of 4118).
Conclusion
We propose new diagnostic criteria for ApHCM using segmental indexed apical wall thickness of >5.6 mm/m2 to better identify inappropriate apical hypertrophy in those whose wall thickness does not meet current criteria for diagnosis.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): British Heart Foundation
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Affiliation(s)
- R K Hughes
- Barts Heart Centre , London , United Kingdom
| | - H Shiwani
- Barts Heart Centre , London , United Kingdom
| | - S Rosmini
- King's College Hospital , London , United Kingdom
| | - L Burke
- University College London , London , United Kingdom
| | - I Pierce
- Barts Heart Centre , London , United Kingdom
| | - S Castelletti
- Italian Auxological Institute San Luca Hospital , Milan , Italy
| | - H Xue
- National Institutes of Health , Bethesda , United States of America
| | - P Kellman
- National Institutes of Health , Bethesda , United States of America
| | - L R Lopes
- Barts Heart Centre , London , United Kingdom
| | - T Treibel
- Barts Heart Centre , London , United Kingdom
| | - C Manisty
- Barts Heart Centre , London , United Kingdom
| | - G Captur
- University College London , London , United Kingdom
| | - R Davies
- University College London , London , United Kingdom
| | - J Moon
- Barts Heart Centre , London , United Kingdom
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Chowdhary A, Cubbon R, Thirunavukarasu S, Jex N, Kotha S, Xue H, Kellman P, Greenwood J, Plein S, Levelt E. Body mass index associated differences in cardiac stress energetics in type 2 diabetes. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.280] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
Patients with T2D and heart disease have normal body mass index (BMI), suggesting that diabetes and obesity mediate cardiovascular change by different mechanisms. Changes in cardiac energy metabolism in lean diabetic patients during exercise stress have not been previously reported.
Objectives
We aimed to assess if there are BMI-associated differences in cardiac stress metabolism in patients with T2D.
Methods
Twenty-five overweight T2D patients (O-T2D) and eleven lean T2D patients (LnT2D), age- and ethnicity-matched and with no other comorbidities were studied. Patients were on oral hypoglycaemics only and were free of diabetes complications. Participants underwent rest and dobutamine stress phosphorus magnetic resonance spectroscopy (31P-MRS) and cardiovascular magnetic resonance (CMR) at 3T for the assessment of myocardial phosphocreatine to ATP ratio (PCr/ATP) as a measure of myocardial energetics, biventricular volumes, rest and stress left ventricular (LV) ejection fraction, global longitudinal shortening, and mitral in-flow E/A ratio for assessment of diastolic function and perfusion.
Intravenous Dobutamine was administered at a dose of 10μg/kg/min, increasing at 90 second intervals up to a maximum of 40 μg/kg/min to achieve a target heart rate of 65% of the age-predicted maximal heart rate. Mean rate pressure product (RPP) was recorded at rest and stress. Heart rate was maintained at target for the duration of the 31P-MRS and stress CMR cine, mitral in-flow and perfusion acquisitions.
Results
The cardiac volumes, systolic or diastolic function and LV mass were similar between LnT2D and O-T2D. Although the O-T2D patients had a numerically lower rest and stress PCr/ATP ratio, this did not reach statistical significance. Resting PCr/ATP was reduced in LnT2D and O-T2D patients similarly. However, LnT2D showed a greater reduction in PCr/ATP (stress PCr/ATP LnT2D 1.51±0.2 vs O-T2D 1.41±0.25, p=0.02) despite similar increases in RPP. Stress myocardial blood flow (MBF) was also significantly lower in the O-T2D patients. There were significant correlations of BMI with LV mass (r=0.35, p=0.03); stress LVEF (r=−0.34, p=0.04); stress MBF stress (r=−0.53, p=0.001) and stress E/A (r=0.46, p=0.01) (figure 1).
Conclusions
Despite their better stress perfusion and similar glycaemic control, LnT2D show worse metabolic reserve characterised by more significant decrements in energetics in response to hemodynamic stress compared to overweight patients with T2D. Higher BMI correlates inversely with stress myocardial blood flow and with stress left ventricular ejection fraction. The presence of these subtle alterations in measures of stress metabolism and perfusion might signify a distinct metabolic phenotype of “lean diabetic cardiomyopathy”. Future studies are needed to further delineate alterations in cardiac energy metabolism in lean and overweight/obese type 2 diabetes patients, and their role in the development of cardiac dysfunction.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): Wellcome TrustBHF
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Affiliation(s)
- A Chowdhary
- University of Leeds , Leeds , United Kingdom
| | - R Cubbon
- University of Leeds , Leeds , United Kingdom
| | | | - N Jex
- University of Leeds , Leeds , United Kingdom
| | - S Kotha
- University of Leeds , Leeds , United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - J Greenwood
- University of Leeds , Leeds , United Kingdom
| | - S Plein
- University of Leeds , Leeds , United Kingdom
| | - E Levelt
- University of Leeds , Leeds , United Kingdom
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35
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Thiru S, Ansari F, Cubbon R, Forbes K, Chowdhary A, Jex N, Kotha S, Morley L, Xue H, Kellman P, Greenwood JP, Plein S, Everett T, Scott E, Levelt E. Gestational diabetes, preeclampsia and the maternal heart. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.2597] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Gestational diabetes mellitus (GDM) and preeclampsia (pE) are both associated with an increased risk of cardiovascular mortality and morbidity, including an increased risk of developing heart failure in later life. Both conditions are increasing in prevalence; GDM affects up to 12% and pE affects 3–5% of pregnancies worldwide. Compromised cardiac energy production is an important contributor to most forms of heart disease. The changes in myocardial energetics in GDM and pE have not been characterised previously.
Purpose
We sought to assess if women with GDM and women with pE in the third trimester of pregnancy exhibit adverse cardiac alterations in myocardial energetics, function or tissue characteristics.
Methods
Thirty-eight healthy pregnant (HP) women, thirty women with GDM and fifteen women with pE were recruited, matched for age and ethnicity. Participants underwent phosphorus magnetic resonance spectroscopy and cardiovascular magnetic resonance for assessment of myocardial energetics (phosphocreatine to ATP ratio (PCr/ATP)), tissue characteristics, biventricular volumes and ejection fractions, left ventricular (LV) mass, global longitudinal strain (GLS) and mitral in-flow E/A ratio.
Results
The biochemical characteristics and multiparametric MR results are given in Table 1.
The women in the GDM and the pE groups had higher body-mass index. There was a stepwise increase in the systolic and diastolic BP from the HP to the GDM to the pE group. There was no difference in NTproBNP concentrations between the groups. The gestational weight gain was higher in women with GDM and pE compared to the HP group.
The women in the GDM and the pE groups showed similar reductions in myocardial PCr/ATP ratios compared to HP group (Figure 1a), accompanied by lower LV end-diastolic volumes and higher LV mass (Figure 1b) and enhanced LV concentricity in both groups (Figure 1c). While LV ejection fractions were similar across the groups, the GLS was reduced in women with GDM and in women with pE (Figure 1d).
Conclusions
We show here for the first time that despite no prior diagnosis of diabetes or hypertension, women with GDM or pE manifest impaired myocardial contractility and higher LV mass, associated with reductions in myocardial energetics. These findings may aid our understanding of the long-term cardiovascular risks associated with these conditions.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): Wellcome Trust
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Affiliation(s)
- S Thiru
- Leeds General Infirmary , Leeds , United Kingdom
| | - F Ansari
- Leeds General Infirmary , Leeds , United Kingdom
| | - R Cubbon
- Leeds General Infirmary , Leeds , United Kingdom
| | - K Forbes
- Leeds General Infirmary , Leeds , United Kingdom
| | - A Chowdhary
- Leeds General Infirmary , Leeds , United Kingdom
| | - N Jex
- Leeds General Infirmary , Leeds , United Kingdom
| | - S Kotha
- Leeds General Infirmary , Leeds , United Kingdom
| | - L Morley
- Leeds General Infirmary , Leeds , United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | | | - S Plein
- Leeds General Infirmary , Leeds , United Kingdom
| | - T Everett
- Leeds General Infirmary , Leeds , United Kingdom
| | - E Scott
- Leeds General Infirmary , Leeds , United Kingdom
| | - E Levelt
- Leeds General Infirmary , Leeds , United Kingdom
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Gorecka M, Jex N, Thirunavukarasu S, Chowdhary A, Poenar AM, Sharrack N, Swoboda PP, Xue H, Vassiliou V, Kellman P, Plein S, Simms A, Greenwood JP, Levelt E. Evaluation of cardiac involvement in patients with clinical post-COVID-19 syndrome. Eur Heart J 2022. [PMCID: PMC9619493 DOI: 10.1093/eurheartj/ehac544.240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Introduction The underlying pathophysiology of Post-COVID-19 syndrome remains unknown, but increased cardiometabolic demand and state of mitochondrial dysfunction have emerged as candidate mechanisms. Cardiovascular magnetic resonance (CMR) provides insight into pathophysiological mechanisms underlying cardiovascular disease and 31-phosphorus magnetic resonance spectroscopy (31P-MRS) allows non-invasive assessment of the myocardial energetic state. Purpose We sought to assess whether Post-COVID-19 syndrome is associated with abnormalities of myocardial structure, function, perfusion and tissue characteristics or energetic derangement. Methods Prospective case-control study. A total of 20 patients with a clinical diagnosis of Post-COVID-19 syndrome (seropositive) and no prior underlying cardiovascular disease (CVD) and ten matching controls underwent 31P-MRS and CMR at 3T at a single time point. (Figure 1) All patients had been symptomatic with acute COVID-19, but none required hospital admission. Results Between the Post-COVID-19 syndrome patients and matched contemporary controls there were no differences in myocardial energetics (phosphocreatine to ATP ratio), in cardiac structure (biventricular volumes, left ventricular mass), function (biventricular ejection fractions, global longitudinal strain), tissue characterization (T1 and extracellular volume [ECV] fraction mapping, late gadolinium enhancement) or perfusion (myocardial rest and stress blood flow, myocardial perfusion reserve). One patient with Post-COVID-19 syndrome showed subepicardial hyperenhancement on the late gadolinium enhancement imaging compatible with prior myocarditis, but no accompanying abnormality in cardiac size, function, perfusion, ECV, T1, T2 mapping or energetics. This patient was excluded from statistical analyses. (Table 1) Conclusion In this study, the overwhelming majority of patients with a clinical Post-COVID-19 syndrome with no prior CVD did not exhibit any abnormalities in myocardial energetics, structure, function, blood flow or tissue characteristics. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Welcome Trust Clinical Career Development Fellowship (221690/Z/20/Z);NIHR-UKRI COVID-19 Rapid Response Rolling Call (COV0254)ESC Training Grant
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Affiliation(s)
- M Gorecka
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - N Jex
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - S Thirunavukarasu
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - A Chowdhary
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - A M Poenar
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - N Sharrack
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - P P Swoboda
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - V Vassiliou
- University of East Anglia , Norwich , United Kingdom
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - S Plein
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - A Simms
- Leeds Teaching Hospitals NHS Trust , Leeds , United Kingdom
| | - J P Greenwood
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
| | - E Levelt
- University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department , Leeds , United Kingdom
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Rehman A, Kellman P, Xue H, Pierce I, Davies RH, Fontana M, Moon JC. Convolutional neural network transformer (CNNT) for free-breathing real-time cine imaging. Eur Heart J Cardiovasc Imaging 2022. [DOI: 10.1093/ehjci/jeac141.001] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: None.
Background
Real-time cine imaging does not require breath-holding and is a robust cine imaging technique in the presence of irregular heartbeats. It is a good alternative to the conventional breath-hold retro-gated cine for simplified acquisition and improved patient comfort. Real-time acquisition is achieved with the single-shot BSSFP readout without retro-gating. To maintain good temporal and spatial resolution, higher acceleration (e.g. >4x parallel imaging) is required. As a result, the real-time cine images experience reduced signal-to-noise ratio (SNR), which limits its clinical acceptance.
Purpose
We developed a novel deep learning model architecture, the Convolutional Neural Network Transformer (CNNT), to improve the quality of real-time cine, under 4x, 5x and 6x acceleration.
Method
Convolutional Neural Networks (CNN) are widely used in CMR research to process cardiac images. Cardiac images are often acquired as a time series with strong inter-phase correlation. We combined the CNN with the more recent transformer model to develop a novel CNNT architecture. It takes in the entire 2D+T time series as input and has advantages of CNN for efficient computation and spatial invariance. It further inherits the advantages of attention layer in the transformer and is able to efficiently utilize the temporal correlation within a time series.
A CNNT model is developed to improve the SNR of real-time cine imaging. N=10 patients were scanned at a heart center, with 4x, 5x and 6x acceleration. Typical imaging parameters are: FOV 360×270mm2, flip angle 50°, acquired matrix size 160×90 for R=4 acceleration, 192×108 for R=5 and 6, temporal resolution 40ms for R=4, 42ms for R=5 and 35ms for R=6. The real-time images went through a TGRAPPA reconstruction [1] and the CNNT model. The SNR of TGRAPPA was measured with SNR units [2]. The Monte-Carlo pseudo-replica test was used to measure SNR for the CNNT model. For every cine series, two phases were picked for the end-systole and end-diastole. For every image picked, two region-of-interests were drawn in the myocardium and in the LV blood pool. The CNNT model was deployed inline on the MR scanner using the Gadgetron InlineAI [3].
Results
Figure 1 gives real-time cine images for three accelerations, reconstructed with TGRAPPA and CNNT. The parallel imaging TGRAPPA reconstruction suffers significant SNR loss from elevated g-factor and less acquired data. The deep learning CNNT model recovered SNR even at the very high 6x acceleration, without observed loss of boundary sharpness.
Table 1 lists the SNR measurement results. The TGRAPPA SNR decreased ∼4x from R=4 to R=6 for both the blood and myocardium. For the blood, the CNNT increased the SNR by 170%, 335%, 371% at R=4, 5 and 6. For the myocardium, the SNR increases were 335%, 634% and 828%.
Conclusion
We developed a convolutional neural network transformer model to recover the SNR for real-time cine imaging at higher acceleration.
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Affiliation(s)
- A Rehman
- National Institutes of Health (NIH) , Bethesda , United States of America
| | - P Kellman
- National Institutes of Health (NIH) , Bethesda , United States of America
| | - H Xue
- National Institutes of Health (NIH) , Bethesda , United States of America
| | - I Pierce
- Barts Health NHS Trust, Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - R H Davies
- Barts Health NHS Trust, Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - M Fontana
- Royal Free London NHS Foundation Trust , London , United Kingdom of Great Britain & Northern Ireland
| | - J C Moon
- Barts Health NHS Trust, Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
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Xue H, Rehman A, Davies RH, Moon JC, Fontana M, Kellman P. CNNT DB-LGE: free-breathing dark blood late enhancement imaging using the convolutional neural network transformer speeds acquisition by 50%. Eur Heart J Cardiovasc Imaging 2022. [DOI: 10.1093/ehjci/jeac141.006] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Supported in part by the Division of Intramural Research of the National Heart, Lung, and Blood Institute, National Institutes of Health (grants Z1A-HL006214-05 and Z1A-HL006242-02).
Background
Dark blood late gadolinium enhancement (DB-LGE) imaging shows superior delineation of myocardial infarction (MI), especially at the sub-endocardial boundary. Our previous study [1] developed a free-breathing DB-LGE with the single shot SSFP readout, phase sensitive inversion recovery (PSIR) reconstruction, and respiratory motion corrected averaging. To compensate the potential signal-to-noise ratio loss, our previous DB-LGE doubled the measurements, thereby increasing the acquisition time.
Purpose
In this study, we developed a deep learning image enhancement model using a novel neural network architecture called the convolutional neural network transformer (CNNT) to improve the image quality of DB-LGE and to reduce the acquisition time by decreasing the number of measurements.
Methods
A novel image enhancement model was developed using a novel network architecture called the Convolutional Neural Network Transformer (CNNT) proposed by us. This architecture is suitable for the 2D+Time CMR acquisition, by exploiting the temporal correlation between images over multiple averages.
The evaluation was first retrospectively conducted on a cohort of 12 patients acquired with the original protocol [1] using the full 16 measurements. For every subject, a complete short-axis stack (typically 12 slices) was acquired to cover the entire left ventricular. The imaging data was reconstructed in three ways. Original: using all acquired 16 measurements. This is our base-line protocol. Original 50%: using only the first 8 measurements. CNNT 50%: using only the first 8 averages, but performing the CNNT deep learning image enhancement before MOCO PSIR reconstruction. Two experienced imaging researchers (PK and MF, >10 years of experience for both) scored all DB-LGE images for the overall quality, diagnostic confidence and delineation of MI/boundaries (5 = excellent, 4 = good, 3 = fair, 2 = poor, and 1 = non-diagnostic). The CNNT DB-LGE was deployed to the MR scanner using the Gadgetron InlineAI [2].
Results
Figure 1 gives examples of DB-LGE with three reconstruction methods. The CNNT image has higher SNR and well delineated MI. The Original images with the longest acquisition have good quality and the Original-50% acquired with 8 measurements are good quality but have reduced SNR. The mean scores for overall image quality, diagnostic confidence and MI delineation of two reviewers were 4.88±0.23, 4.88±0.23, 4.83±0.25 for CNNT and 4.96±0.14, 4.96±0.14, 4.67±0.39 for the original approach. No significant differences were found between the original and the CNNT (P>0.15 for all).
Figure 2 shows an acute MI patient prospectively acquired with the 50% scan time reduction, with and without the CNNT enhancement. The resulting PSIR images well delineate the MVO due to the acute MI, with improved SNR.
Conclusion
A novel CNNT model was proposed and evaluated to speed up the free-breathing MOCO DB LGE by 50% without sacrificing image quality.
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Affiliation(s)
- H Xue
- National Institutes of Health (NIH) , Bethesda , United States of America
| | - A Rehman
- National Institutes of Health (NIH) , Bethesda , United States of America
| | - R H Davies
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - J C Moon
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - M Fontana
- Royal Free Hospital , London , United Kingdom of Great Britain & Northern Ireland
| | - P Kellman
- National Institutes of Health (NIH) , Bethesda , United States of America
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Shiwani H, Hughes RK, Camaioni C, Augusto JB, Knott K, Rosmini S, Khoury S, Malcolmson J, Kellman P, Xue H, Burke L, Pierce I, Moon JC, Davies RH. Improving the diagnostic accuracy of apical hypertrophic cardiomyopathy using machine learning. Eur Heart J Cardiovasc Imaging 2022. [DOI: 10.1093/ehjci/jeac141.009] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Dr Hughes is supported by the British Heart Foundation (grant number FS/17/82/33222).
Introduction
The imaging criteria for diagnosis of apical hypertrophic cardiomyopathy (ApHCM) is a maximum wall thickness (MWT) ≥15mm. CMR enables detection of subtle phenotypic features (e.g. loss of apical tapering, cavity obliteration) and coupled with characteristic electrocardiogram changes, ApHCM can be diagnosed without overt hypertrophy. However, these patients are not captured by current diagnostic criteria.
Purpose
We sought to use a machine learning tool to quantify wall thickness and identify patients with ‘relative’ ApHCM that do not reach current diagnostic thresholds.
Methods
CMR images from 4118 healthy participants from the UK Biobank were segmented automatically with a clinically validated machine learning algorithm and wall thickness measured at all point in the myocardium by solving a solution to Laplace’s equation. MWT were pooled into 16 AHA segments and indexed to body surface area (BSA). The non-indexed and indexed segmental upper limit of normal was calculated as the mean + 3 standard deviations (the equivalent of 95% confidence interval after correcting for multiple [16] comparisons using the Bonferroni method).
Results
73 overt ApHCM subjects (MWT>15mm) and 31 relative ApHCM subjects underwent CMR scanning. In healthy controls, the non-indexed (and indexed) upper limits were calculated for the apical-anterior 10.2mm (5.2 mm/m2), apical-septal 11.1mm (5.6 mm/m2), apical-inferior 10.5mm (5.3 mm/m2) and apical-lateral 10.1mm (5.2 mm/m2) segments. With a non-indexed cut-off, all (73 of 73) overt ApHCM and 84% (26 of 31) relative ApHCM were classified as having an abnormally thick apex. 3% (127 of 4118) of the healthy UK Biobank cohort were classified as abnormal, as expected. Using an indexed cut-off, all overt ApHCM and 87% (27/31) relative ApHCM were classified as abnormal, and 3% (123 of 4118) of the healthy UK Biobank cohort were misclassified.
Conclusion
We can successfully classify 87% of relative ApHCM patients from a normative reference range derived from a large cohort of healthy patients – a significant improvement on existing methods. We show that the specificity and sensitivity is increased when MWT is indexed to BSA. For practical clinical application, we recommend a cut-off of 10mm or an indexed cut-off of 5mm/m2 in any apical segment to diagnose apical LVH. Overt and relative apical HCM examplesHealthy controls AHA maps (non-indexed)
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Affiliation(s)
- H Shiwani
- University College London , London , United Kingdom of Great Britain & Northern Ireland
| | - R K Hughes
- University College London , London , United Kingdom of Great Britain & Northern Ireland
| | - C Camaioni
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - J B Augusto
- University College London , London , United Kingdom of Great Britain & Northern Ireland
| | - K Knott
- University College London , London , United Kingdom of Great Britain & Northern Ireland
| | - S Rosmini
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - S Khoury
- St George's University of London, Cardiovascular Clinical and Academic Group , London , United Kingdom of Great Britain & Northern Ireland
| | - J Malcolmson
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - L Burke
- University College London , London , United Kingdom of Great Britain & Northern Ireland
| | - I Pierce
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - J C Moon
- University College London , London , United Kingdom of Great Britain & Northern Ireland
| | - R H Davies
- University College London , London , United Kingdom of Great Britain & Northern Ireland
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40
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Hooper S, Wu S, Davies RH, Moon JC, Kellman P, Xue H, Langlotz C, Re C. Speeding up cardiac MR segmentation with semi-supervision: applications in cine imaging. Eur Heart J Cardiovasc Imaging 2022. [DOI: 10.1093/ehjci/jeac141.004] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Private company. Main funding source(s): This material is based upon work supported by the Google Cloud Research Credits program with the award GCP19980904.
Background
Segmentation is an important postprocessing step in cardiac magnetic resonance (CMR) imaging that enables quantitative assessment of functional parameters. Deep learning can automate the segmentation process, producing accurate contours of cardiac structures while reducing the time required to analyze images and the interobserver variation compared to manual analysis. However, common approaches to training neural networks (NNs) require large amounts of labeled data, which is costly to generate and slows down the development of CMR segmentation NNs for new applications. Semi-supervision is an approach to alleviate this labeling burden by relying on abundant unlabeled data and a smaller amount of labeled data to train NNs.
Purpose
We propose a novel semi-supervised method to train CMR segmentation NNs. We use the proposed method to train NNs to segment the left ventricle in CMR cine images. Ultimately, we aim to show that semi-supervision can drastically reduce the amount of labeled data required to develop machine learning segmentation applications for CMR while maintaining high performance.
Methods
Our dataset consists of 1,208 short-axis cine CMR images and 1,244 long-axis cine CMR images. An expert annotator manually segmented the endocardium on the end-diastolic and end-systolic short-axis and long-axis images and the epicardium on the end-diastolic short-axis images. We split the dataset randomly by patient into 60% training, 20% validation, and 20% testing data. We train semi-supervised segmentation networks using a supervised cross-entropy loss to learn from the labeled training data and a cosine embedding loss in addition to a pseudo-labeling step to learn from the unlabeled training data. To evaluate how performance changes with different amounts of labeled training data, we vary the percent of training data that has labels from <1%-100%. We evaluate the predicted segmentation masks using the Dice coefficient.
Results
Using only 100 labeled image slices, the semi-supervised segmentation NNs achieve a mean Dice coefficient within 1.10% of networks trained with fully labeled training sets, corresponding to >85% reduction in required labeled training data (Table 1). The proposed semi-supervised method improves performance over naïve training by 6.21% for the most limited labeled data setting (i.e., 10 labeled image slices; Figure 1).
Conclusion
We have shown that NNs trained with limited labeled data achieve high performance on left ventricle segmentation in short-axis and long-axis CMR cines. The proposed approach is flexible and broadly applicable to different CMR segmentation tasks, enabling rapid development of segmentation networks for many cardiac structures and applications. Table 1Figure 1
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Affiliation(s)
- S Hooper
- Stanford University , Stanford , United States of America
| | - S Wu
- Stanford University , Stanford , United States of America
| | - R H Davies
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - J C Moon
- Barts Heart Centre , London , United Kingdom of Great Britain & Northern Ireland
| | - P Kellman
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - H Xue
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - C Langlotz
- Stanford University , Stanford , United States of America
| | - C Re
- Stanford University , Stanford , United States of America
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Dong J, Jin S, Guo J, Yang R, Tian D, Xue H, Xiao L, Guo Q, Wang R, Xu M, Teng X, Wu Y. Pharmacological inhibition of eIF2alpha phosphorylation by integrated stress response inhibitor (ISRIB) ameliorates vascular calcification in rats. Physiol Res 2022; 71:379-388. [PMID: 35616039 DOI: 10.33549/physiolres.934797] [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: 11/25/2022] Open
Abstract
Vascular calcification (VC) is an independent risk factor for cardiovascular events and all-cause mortality with the absence of current treatment. This study aimed to investigate whether eIF2alpha phosphorylation inhibition could ameliorate VC. VC in rats was induced by administration of vitamin D3 (3×10(5) IU/kg, intramuscularly) plus nicotine (25 mg/kg, intragastrically). ISRIB (0.25 mg/kg·week), an inhibitor of eIF2alpha phosphorylation, ameliorated the elevation of calcium deposition and ALP activity in calcified rat aortas, accompanied by amelioration of increased SBP, PP, and PWV. The decreased protein levels of calponin and SM22alpha, and the increased levels of RUNX2 and BMP2 in calcified aorta were all rescued by ISRIB, while the increased levels of the GRP78, GRP94, and C/EBP homologous proteins in rats with VC were also attenuated. Moreover, ISRIB could prevent the elevation of eIF2alpha phosphorylation and ATF4, and partially inhibit PERK phosphorylation in the calcified aorta. These results suggested that an eIF2alpha phosphorylation inhibitor could ameliorate VC pathogenesis by blocking eIF2alpha/ATF4 signaling, which may provide a new target for VC prevention and treatment.
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Affiliation(s)
- J Dong
- Department of Physiology, Hebei Medical University, Shijiazhuang, China. and
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Dong ZY, Xue H, Tao LY, Li Y, Tian H. [Effect of tourniquet on morphology and stiffness of quadriceps in patients receiving total knee arthroplasty: a randomized controlled trial]. Zhonghua Yi Xue Za Zhi 2022; 102:1833-1838. [PMID: 35725362 DOI: 10.3760/cma.j.cn112137-20211230-02930] [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 evaluate tourniquet effect on the morphology and stiffness of quadriceps in patients receiving total knee arthroplasty (TKA). Methods: Total of 80 patients with primary knee osteoarthritis receiving unilateral primary TKA from August 2020 to June 2021 in Peking University Third Hospital were enrolled in this randomized controlled trial. The patients were randomly divided into tourniquet group and non-tourniquet group (40 cases in each group). The study measured and compared postoperative thickness and stiffness of quadriceps, as well as circumference of the affected thigh in two groups. Results: There were 11 males and 29 females in tourniquet group, 9 males and 31 females in non-tourniquet group, with mean age of (69.1±5.1) years and (67.4±5.3) years, respectively. There was no significant difference in demographic information such as gender, age and BMI (all P<0.05). Postoperative thickness of quadriceps, stiffness of quadriceps and circumference[x¯±s or M (Q1,Q3)]of the affected thigh in all patients were (2.76±0.69) cm, 25.20 (17.83, 32.90) m/s, 54.00 (51.13, 56.00) cm. These outcomes in tourniquet and non-tourniquet group[x¯±s or M (Q1,Q3)]were (2.78±0.76) cm and (2.73±0.61) cm, 24.00 (17.15, 33.13) m/s and 25.20 (18.68, 32.85) m/s, 54.00 (49.75, 55.00) cm and 54.50 (52.13, 57.53) cm, respectively; no significant deference was found in these indexes between the two groups (all P>0.05). Conclusion: Tourniquet has no significant effect on morphology and stiffness of quadriceps in patients undergoing TKA.
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Affiliation(s)
- Z Y Dong
- Department of Orthopedics, Peking University Third Hospital, Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing 100191, China
| | - H Xue
- Ultrasound Department, Peking University Third Hospital, Beijing 100191, China
| | - L Y Tao
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - Y Li
- Department of Orthopedics, Peking University Third Hospital, Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing 100191, China
| | - Hua Tian
- Department of Orthopedics, Peking University Third Hospital, Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing 100191, China
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Zhang W, Liu FQ, Zhang LP, Ding HG, Zhuge YZ, Wang JT, Li L, Wang GC, Wu H, Li H, Cao GH, Lu XF, Kong DR, Sun L, Wu W, Sun JH, Liu JT, Zhu H, Li DL, Guo WH, Xue H, Wang Y, Gengzang CJC, Zhao T, Yuan M, Liu SR, Huan H, Niu M, Li X, Ma J, Zhu QL, Guo WW, Zhang KP, Zhu XL, Huang BR, Li JN, Wang WD, Yi HF, Zhang Q, Gao L, Zhang G, Zhao ZW, Xiong K, Wang ZX, Shan H, Li MS, Zhang XQ, Shi HB, Hu XG, Zhu KS, Zhang ZG, Jiang H, Zhao JB, Huang MS, Shen WY, Zhang L, Xie F, Li ZW, Hou CL, Hu SJ, Lu JW, Cui XD, Lu T, Yang SS, Liu W, Shi JP, Lei YM, Bao JL, Wang T, Ren WX, Zhu XL, Wang Y, Yu L, Yu Q, Xiang HL, Luo WW, Qi XL. [Status of HVPG clinical application in China in 2021]. Zhonghua Gan Zang Bing Za Zhi 2022; 30:637-643. [PMID: 36038326 DOI: 10.3760/cma.j.cn501113-20220302-00093] [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: The investigation and research on the application status of Hepatic Venous Pressure Gradient (HVPG) is very important to understand the real situation and future development of this technology in China. Methods: This study comprehensively investigated the basic situation of HVPG technology in China, including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications and existing problems. Results: According to the survey, there were 70 hospitals in China carrying out HVPG technology in 2021, distributed in 28 provinces (autonomous regions and municipalities directly under the central Government). A total of 4 398 cases of HVPG were performed in all the surveyed hospitals in 2021, of which 2 291 cases (52.1%) were tested by HVPG alone. The average cost of HVPG detection was (5 617.2±2 079.4) yuan. 96.3% of the teams completed HVPG detection with balloon method, and most of the teams used thrombectomy balloon catheter (80.3%). Conclusion: Through this investigation, the status of domestic clinical application of HVPG has been clarified, and it has been confirmed that many domestic medical institutions have mastered this technology, but it still needs to continue to promote and popularize HVPG technology in the future.
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Affiliation(s)
- W Zhang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - F Q Liu
- Department of Interventional Radiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - L P Zhang
- Department of Radiology,Third Hospital of Taiyuan, Taiyuan 030012, China
| | - H G Ding
- Liver Disease Digestive Center,Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Y Z Zhuge
- Digestive Department,Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - J T Wang
- Department of Hepatobiliary Surgery, Xingtai People's Hospital, Xingtai 054001, China
| | - L Li
- Department of Interventional Radiology, the First Hospital of Lanzhou University, Lanzhou 730013, China
| | - G C Wang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - H Wu
- Digestive Department, West China Hospital, Sichuan University, Chengdu 610044, China
| | - H Li
- Institute of Hepatology and Department of Infectious Disease, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - G H Cao
- Department of Radiology, Shulan Hospital, Hangzhou 310022, China
| | - X F Lu
- Digestive Department, West China Hospital, Sichuan University, Chengdu 610044, China
| | - D R Kong
- Digestive Department, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - L Sun
- Department of Gastroenterology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325001, China
| | - W Wu
- Department of Gastroenterology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325001, China
| | - J H Sun
- Hepatobiliary and Pancreatic Intervention Center , the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J T Liu
- Digestive Department,Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - H Zhu
- The 1 st Department of Interventional Radiology, the Sixth People's Hospital of Shenyang, Shenyang 110006, China
| | - D L Li
- No. 900 Hospital of the Joint Logistic Support Force, Fuzhou 350025, China
| | - W H Guo
- Department of Interventional Radiology, Meng Chao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - H Xue
- Digestive Department, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Y Wang
- Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - C J C Gengzang
- Department of Interventional Radiology, the Fourth People's Hospital of Qinghai Province, Xining 810007, China
| | - T Zhao
- Department of Radiology,Sir Run Shaw Hospital, Zhejiang University, Hangzhou 310016, China
| | - M Yuan
- Department of Interventional Radiology Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - S R Liu
- Department of Infectious Disease,Qufu People's Hospital, Qufu 273199, China
| | - H Huan
- Digestive Department, Chengdu Office Hospital of Tibet Autonomous Region People's Government, Chengdu 610041, China
| | - M Niu
- Department of Interventional Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - X Li
- Department of Radiology,Tianjin Second People's Hospital, Tianjin 300192, China
| | - J Ma
- Department of Interventional Vascular Surgerg, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750002, China
| | - Q L Zhu
- Digestive Department,the Affiliated Hospital of Southwest Medical University, Luzhou 646099, China
| | - W W Guo
- Department of Interventional Radiology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - K P Zhang
- Department of Hepatobiliary Surgery, Xingtai People's Hospital, Xingtai 054001, China
| | - X L Zhu
- Department of Surgery, the First Hospital of Lanzhou University, Lanzhou 730013, China
| | - B R Huang
- Department of Interventional Vascular Surgery,Jingzhou First People's Hospital, Jingzhou, China
| | - J N Li
- Liver Diseases Department,Jiamusi Infectious Disease Hospital, Jiamusi 154015, China
| | - W D Wang
- Hepatobiliary, Pancreatic and Spleen Surgery Department,Shunde Hospital, Southern Medical University, Foshan 528427, China
| | - H F Yi
- Digestive Department,Wuhan First Hospital, Wuhan 430030, China
| | - Q Zhang
- Interventional Vascular Surgery Department, Affiliated Zhongda Hospital of Southeast University, Nanjing 210009, China
| | - L Gao
- Oncology and Vascular Interventional Department, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - G Zhang
- Digestive Department, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530016, China
| | - Z W Zhao
- Department of Interventional Radiology, Lishui Municipal Central Hospital, Zhejiang University School of Medicine, Lishui 323030, China
| | - K Xiong
- Digestive Department, the Second Affiliated Hospital of Nanchang University, Nanchang 330008, China
| | - Z X Wang
- Inner Mongolia Medical University Affiliated Hospital, Hohhot 010050, China
| | - H Shan
- Interventional Medicine Center, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China
| | - M S Li
- Department of Endovascular Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - X Q Zhang
- Digestive Department, the Second Hospital of Hebei Medical University, Shijiazhuang 050004, China
| | - H B Shi
- Department of Interventional Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - X G Hu
- Interventional Radiology Department,Jinhua Municipal Central Hospital, Jinhua 321099, China
| | - K S Zhu
- Interventional Radiology Department, the Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510260, China
| | - Z G Zhang
- Department of Liver Surgery,Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China
| | - H Jiang
- Infectious Disease Department,Second Affiliated Hospital, Military Medical University of the Air Force, Xi'an 710038, China
| | - J B Zhao
- Department of Vascular and Interventional Radiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - M S Huang
- Interventional Radiology Department, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510000, China
| | - W Y Shen
- Digestive Department,Fuling Hospital Affiliated to Chongqing University, Chongqing 400030, China
| | - L Zhang
- Hepatobiliary Pancreatic Center,Tsinghua Changgung Hospital, Beijing 102200, China
| | - F Xie
- Function Department,Lanzhou Second People's Hospital, Lanzhou 730030, China
| | - Z W Li
- Hepatobiliary Surgery Department,Shenzhen Third People's Hospital, Shenzhen518112, China
| | - C L Hou
- Department of Interventional Radiology, the First Affiliated Hospital of USTC, Hefei 230001, China
| | - S J Hu
- Digestive Department,People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750002, China
| | - J W Lu
- Department of Interventional Radiology, Qufu People's Hospital, Qufu 273199, China
| | - X D Cui
- Department of Interventional Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530016, China
| | - T Lu
- Department of Gastroenterology, Yangquan Third People's Hospital, Yangquan 045099,China
| | - S S Yang
- Department of Gastroenterology, General Hospital of Ningxia Medical University , Yinchuan 750003, China
| | - W Liu
- Department of Interventional Radiology, Lishui People's Hospital, Zhejiang Province, Lishui 323050, China
| | - J P Shi
- Department of Liver Diseases, Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, China
| | - Y M Lei
- Interventional Radiology Department, People's Hospital of Tibet Autonomous Region, Lhasa 850001, China
| | - J L Bao
- Department of Gastroenterology, Shannan people's Hospital,Shannan 856004, China
| | - T Wang
- Department of Interventional Radiology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai 264099,China
| | - W X Ren
- Interventional Treatment Center, the First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011,China
| | - X L Zhu
- Interventional Radiology Department, the First Affiliated Hospital of Suzhou University, Suzhou 215006, China
| | - Y Wang
- Department of Interventional Vascular Surgery, the Second Affiliated Hospital of Hainan Medical College, Haikou 570216, China
| | - L Yu
- Department of Interventional Radiology, Sanming First Hospital Affiliated to Fujian Medical University,Sanming 365001,China
| | - Q Yu
- Interventional Radiology Department, Fifth Medical Center of PLA General Hospital, Beijing 100039, China
| | - H L Xiang
- Department of Gastroenterology, Tianjin Third Central Hospital, Tianjin 300170, China
| | - W W Luo
- Deparment of Infectious Diseases, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - X L Qi
- Center of Portal Hypertension Department of Radiology, Zhongda Hospital of Southeast University, Nanjing 210009, China
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Yan LC, Miao L, Xue H, Li HM. Abstract 5758: Characteristic profile of blood-based ctDNA suggests angiogenesis and immune escape in hepatocellular carcinoma. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-5758] [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: 11/16/2022]
Abstract
Abstract
Background: Circulating tumor DNA (ctDNA) is a type of DNA released from tumor cells captured in blood circulation system. It provides a noninvasive approach to interrogate a patient’s genomic landscape and actionable mutations with well application prospect. However, the difference of genomic profiles between tissue and ctDNA still brings confusions to related researches. Therefore, we tried to elucidate whether blood-based ctDNA has its own characteristic profile to reflect tumor status in hepatocellular carcinoma (HCC).
Methods: Tumor tissue and blood samples from 118 HCC patients of Xiangya Hospital Central South University, were analyzed using NGS (panel on 147 gene). NGS data from a Chinese population extended cohort (385 tissues and 79 blood samples) of HCC were used to validate the mutation characteristics. Data from HCC cohorts of The Cancer Genome Atlas (TCGA) was used to analyze the disease-free survival (DFS) of different mutations.
Results: In the hospital cohort, there were 9 high-frequency mutant genes in tissue and blood, including TP53 (74.58% vs 74.58%), MSH2(23.73% vs 8.47%), LRP1B (20.34% vs 23.73%), ATM (18.64% vs 13.56%), CTNNB1 (11.86% vs 13.56%) et.al which consistent with previous reports. There were 32 genes (74.04%) with a mutation frequency of more than 6% that were unique to blood samples. In extended cohort, the mutation profile was similar to the hospital cohort, in which 35 genes (52.24%) specific in ctDNA profile and 18 genes of them identical to the hospital cohort. Interestingly, when these ctDNA-specific genes were analysed by gene ontology, most genes were involved in angiogenesis. The prognostic analysis in ctDNA-specific genes showed that patients with higher level of MAP3K1 had worse DFS (p=0.028). In addition, the gene co-expression network analysis showed MAP3K1 and NOTCH1/2/3 expression had a significant positive correlation, that Notch family members were also belonged to the ctDNA-specific genes and associated with tumor immune escape.
Conclusions: The results showed the mutation characteristic of tissues and ctDNA in HCC, and suggest that angiogenic and tumor immune escape related ctDNA-specific genes might be able to predict recurrence risk independently of baseline tissue samples.
Citation Format: Lin Chia Yan, Liu Miao, Hu Xue, Huang Meng Li. Characteristic profile of blood-based ctDNA suggests angiogenesis and immune escape in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5758.
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Affiliation(s)
- Lin Chia Yan
- 1Xiangya Hospital, Central South University, Changsha, China
| | - Liu Miao
- 2The Medical Department, 3D Medicines, Inc., Shanghai, China
| | - Hu Xue
- 2The Medical Department, 3D Medicines, Inc., Shanghai, China
| | - Huang Meng Li
- 2The Medical Department, 3D Medicines, Inc., Shanghai, China
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Fu B, Tao M, Xue H, Jin H, Liu K, Qiu H, Yang S, Yang X, Gui L, Zhang Y, Gao Y. Spinetoram resistance drives interspecific competition between Megalurothrips usitatus and Frankliniella intonsa. Pest Manag Sci 2022; 78:2129-2140. [PMID: 35170208 DOI: 10.1002/ps.6839] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 02/08/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Species displacement by the outcome of interspecific competition is of particular importance to pest management. Over the past decade, spinetoram has been extensively applied in control of the two closely related thrips Megalurothrips usitatus and Frankliniella intonsa worldwide, while whether its resistance is implicated in mediating interspecific interplay of the two thrips remains elusive to date. RESULTS Field population dynamics (from 2017 to 2019) demonstrated a trend toward displacement of F. intonsa by M. usitatus on cowpea crops, supporting an existing interspecific competition. Following exposure to spinetoram, M. usitatus became the predominate species, which suggests the use of spinetoram appears to be responsible for mediating interspecific interactions of the two thrips. Further annual and seasonal analysis (from 2016 to 2020) of field-evolved resistance dynamics revealed that M. usitatus developed remarkably higher resistance to spinetoram compared to that of F. intonsa, implying a close relationship between evolution of spinetoram resistance and their competitive interactions. After 12 generations of laboratory selection, resistance to spinetoram in M. usitatus and F. intonsa increased up to 64.50-fold and 28.33-fold, and the average realized heritability (h2 ) of resistance was calculated as 0.2550 and 0.1602, respectively. Interestingly, two-sex life table analysis showed that the spinetoram-resistant strain of F. intonsa exhibited existing fitness costs, but not the M. usitatus. These indicate that a rapid development of spinetoram resistance and the lack of associated fitness costs may be the mechanism underlying recent dominance of M. usitatus over F. intonsa. CONCLUSION Collectively, our results uncover the involvement of insecticide resistance in conferring displacement mechanism behind interspecific competition, providing a framework for understanding the significance of the evolutionary relationships among insects under ongoing changing environments. These findings also can be invaluable in proposing the most appropriate strategies for sustainable thrips control programs. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Buli Fu
- Hubei Engineering Technology for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, China
- The Ministry of Agriculture and Rural Affairs Key Laboratory of Integrated Pest Management of Tropical Crops, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
- Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Min Tao
- Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hu Xue
- Hubei Engineering Technology for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, China
- Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | | | - Kui Liu
- The Ministry of Agriculture and Rural Affairs Key Laboratory of Integrated Pest Management of Tropical Crops, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Haiyan Qiu
- The Ministry of Agriculture and Rural Affairs Key Laboratory of Integrated Pest Management of Tropical Crops, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | | | - Xin Yang
- Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lianyou Gui
- Hubei Engineering Technology for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, China
| | - Youjun Zhang
- Hubei Engineering Technology for Pest Forewarning and Management, College of Agriculture, Yangtze University, Jingzhou, China
- Department of Plant Protection, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yulin Gao
- State Key Laboratory for Biology of Plant Diseases and Insect Pest, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
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Wu R, Su R, Ding T, Xue H, LI XF, Wang C. POS0549 IMBALANCED Tfr/Tfh IN PERIPHERAL BLOOD OF NEW-ONSET RHEUMATOID ARTHRITIS. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.3019] [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: 11/03/2022]
Abstract
BackgroundRheumatoid arthritis (RA) is a kind of autoimmune disease characterized with chronic aggressive arthritis, presence of abnormal antibodies and persistent synovitis[1]. However, the pathogenesis of RA remained unclear by now. Several observations have showed that the breakdown of immune tolerance was involved in the development of RA. T follicular regulatory (Tfr) cells and T follicular helper (Tfh) cells, as a new subset of CD4+T cell, can exert an opposite effect in the regulation of humoral immunity[2]. Intensive researches have showed that the imbalance of Tfr/Tfh cell is related to the pathogenesis and development of autoimmune disease. There is still a lack of understanding of the relationship between Tfr/Tfh and RA, which needs further exploration.ObjectivesTo detect the expression of Tfh and Tfr cells in thr peripheral blood of patients with new-onset RA and healthy controls, and to explore the role of Tfh and Tfr cells in the pathogenesis and development of RA.MethodsWe enrolled 26 patients with new-onset RA who hospitalized at the Second Hospital of Shanxi Medical University from the June 2021 to the November 2021. And 17 age and gender-matched healthy adults were anticipated as controls. The absolute number of Tfh and Tfr cells in peripheral blood was detected by flow cytometry. Disease activity indicators were collected including erythrocyte sedimentation rate (ESR, mm/h) and Disease Activity Score in 28 joints (DAS28). Then we compared the expression of Tfh and Tfr cells between the patients and healthy controls and conducted the correlation analysis with disease activity.ResultsThere was significant decreased level of Tfr cells in the patients with new-onset RA compared with healthy controls (P<0.001) and a lower ratio of Tfr/Tfh in the patients (P<0.01). The reduced Tfr cells and Tfr/Tfh were significant negative correlation with the disease activity indicators including ESR and DAS28 (r=-0.305, P=0.033). There was no statistically significant in the absolute number of Tfh cells between patients and healthy controls, but the level of Tfh cell showed an increasing trend in new-onset RA.ConclusionThe results we investigated here showed that new-onset RA exhibited an imbalance of Tfr/Tfh, specifically reduced Tfr cells, compared with healthy controls, which were negatively correlated with higher disease activity in RA. It was likely that the imbalance of Tfr/Tfh in peripheral blood played an important role in the development of RA, which may be a target to treat RA.Table 1.A summary of data of all enrolled patients with RA and healthy controlsHC(n=17)New-onset RA(n=26)P valueAge(years)51.94±13.0355.88±13.56P=0.35Sex(male/female)4/137/19P=0.81ESR(mm/h) a-54.85±32.71-DAS28 a-5.09±1.56-Tfh cell count(cell/UL)b43.156(23.277,106.638)83.914(38.133,119.662)0.214Tfr cell count(cell/UL)b1.422(0.882,1.893)0.441(0.116,2.888)0.025*Tfr/Tfhb0.030(0.014,0.049)0.011(0.001,0.024)0.001**a Results are expressed as the mean ± standard error. b Results are expressed as the median(Q1,Q3).Normally distributed continuous variables were analyzed by the independent-samples Student’s t-test. And nonparametric variables were analyzed by Mann–Whitney U testFigure 1.The differences of Tfr and Tfh cells in peripheral blood between the healthy controls and patients with RA. Tfr cells were higher in new-onset RA leading to an imbalance of Tfr/Tfh. Statistical analyses were performed by the Mann-Whitney U test. (*P<0.05, **P<0.01)Figure 2.The correlation of disease activity with the level of Tfr cells and Tfr/Tfh. Tfr cells and Tfr/Tfh were negative associated with ESR and DAS28. Statistical analyses were performed by the Spearman correlation analysis.References[1]Sparks, J.A. Rheumatoid Arthritis [J]. Ann Intern Med, 2019, 170(1).DOI: 10.7326/AITC201901010.[2]Deng, J., Y. Wei, V.R. Fonseca, L. Graca, and D. Yu. T follicular helper cells and T follicular regulatory cells in rheumatic diseases [J]. Nat Rev Rheumatol, 2019, 15(8): 475-490.DOI: 10.1038/s41584-019-0254-2.Disclosure of InterestsNone declared.
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Wang X, Xue H, Chang X, Jin Z. Gastrointestinal: Epithelioid angiomyolipoma of the pancreas. J Gastroenterol Hepatol 2022; 37:781. [PMID: 34978112 DOI: 10.1111/jgh.15739] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 11/16/2021] [Indexed: 12/09/2022]
Affiliation(s)
- X Wang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - H Xue
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - X Chang
- Department of Pathology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Z Jin
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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Xu QY, Xue H, Yang J, He SN, Lan YJ, Zhang Q. [The influence of subjective comfort of working environment on occupational stress of railway station workers]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2022; 40:267-271. [PMID: 35545592 DOI: 10.3760/cma.j.cn121094-20210318-00154] [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] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To explore the influential factors of job stress suffered by workers in railway stations, the level of job stress of were measured and subjective comfort of employees targeting to working environment were reported. Methods: In March 2019, a cluster sampling study was designed to collect the personal characteristics, job characteristics and subjective comfort degree of working environment of 432 employees in Chongqing railway stations. Meanwhile, job stress was assessed using the effort-reward imbalance scale. Chi-square test was used to compare the difference of occupational stress detection rate among different stratified factors such as occupational characteristics. Logistic regression was applied to analyze the influential factors of occupational stress. Results: The detection rate of job stress of workers in the railway stations was 31.02% (134/432) . The detection rate of job stress was higher among the divorced workers in railway stations, those earning less than 5, 000 yuan per month, those with 10-20 years' length of service, those who worked as a conductor and other workers including baggageman, station master on duty and assistant engineer (χ(2)=9.61, 14.76, 23.28, 11.06, P=0.008, 0.002, 0.000, 0.011) . The detection rate of job stress was higher among those whose working environment subjective feelings were uncomfortable, the differences were statistically significant (P<0.001) . The results showed that the occupational stress of the staff in the railway stations was influenced by their subjective feeling of air quality, noise and Space Layout (P<0.05) . The risk factors of occupational stress were air quality, noise and uncomfortable space layout (OR=0.571, 0.068, 0.441, P=0.051, 0.054, 0.007) . Conductor, other (Bellboy, Duty Station Master, assistant engineer) were the risk factors of occupational stress (OR=1.884, 2.703, P=0.065, 0.019) . The employees of station A and station B were the risk factors of occupational stress (OR=4.681, 1.811, P=0.002, 0.067) . Conclusion: The higher detection rate of job stress of workers in the railway stations is correlated with the subjective comfort degree of the working environment of the workers.
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Affiliation(s)
- Q Y Xu
- Department of Occupational Health and Environmental Health, West China of Public Health (West China No. 4 Hospital), Sichuan University, Chengdu 610041, China
| | - H Xue
- Department of Health Examination, Chongqing Section of Center for Disease Prevention and Control, China Railway Chengdu Group Co., Ltd, Chongqing 400014, China
| | - J Yang
- Department of Occupational Health and Environmental Health, West China of Public Health (West China No. 4 Hospital), Sichuan University, Chengdu 610041, China
| | - S N He
- Department of Epidemiology and Health Statistics, West China of Public Health (West China No. 4 Hospital), Sichuan University, Chengdu 610041, China
| | - Y J Lan
- Department of Occupational Health and Environmental Health, West China of Public Health (West China No. 4 Hospital), Sichuan University, Chengdu 610041, China
| | - Q Zhang
- Department of Occupational Health and Environmental Health, West China of Public Health (West China No. 4 Hospital), Sichuan University, Chengdu 610041, China
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Chowdhary A, Thirunavukarasu S, Jex N, Bowers C, Cubbon R, Xue H, Kellman P, Greenwood JP, Plein S, Levelt E. Coronary microvascular dysfunction is only detectable in type 2 diabetes in the presence of obesity. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.0237] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Heart failure (HF) is a leading cardiovascular complication of type 2 diabetes (T2D). Coronary microvascular dysfunction (CMD) precedes HF in diabetes and carries important prognostic information. CMD is also evident in metabolically healthy obese individuals without diabetes or hypertension. Whether diabetes causes CMD in the absence of obesity is uncertain. The interrelation among visceral adiposity and CMD has not been assessed previously.
Objectives
We sought to better understand the links between visceral and epicardial adipose tissue (VAT and EAT respectively) distribution, insulin resistance with myocardial perfusion, energetics and function in asymptomatic lean (LnT2D) and overweight/obese T2D patients (ObT2D) without cardiovascular disease.
Methods
62 participants [27 Ob-T2D, 15 Ln-T2D, and 20 overweight controls] were recruited. Subjects underwent cardiac and abdominal magnetic resonance imaging and 31P-magnetic resonance spectroscopy, for measurements of EAT and VAT areas, rest and adenosine stress myocardial blood flow (MBF), cardiac function and phosphocreatine to ATP ratio (PCr/ATP). Fasting blood samples were taken for plasma homeostasis model assessment of insulin resistance (HOMA-IR) index calculations.
Results
The biochemical characteristics and multiparametric MR results are given in Table 1 and results of Pearson's regression analysis in the entire study population are given in Table 2.
Stress MBF was lowest in ObT2D, while rest MBF was highest in LnT2D. Left ventricular ejection fraction (LVEF) and myocardial PCr/ATP were similarly reduced in diabetes groups. In the absence of obesity, there was no significant increase in VAT, EAT or HOMA-IR in T2D patients compared to controls. BMI and VAT, negatively correlated with LVEF, and strain parameters. PCr/ATP correlated with LVEF, but not HOMA-IR. BMI, EAT and VAT all correlated significantly with HOMA-IR, and HOMA-IR correlated with cardiac functional parameters. There was no association between HOMA-IR and myocardial perfusion.
Conclusions
In this study CMD was only evident in ObT2D patients, with normal rest and stress MBF in LnT2D patients. Despite normal perfusion and no significant increase in insulin resistance, LVEF and myocardial PCr/ATP were similarly reduced in LnT2D and ObT2D, and PCr/ATP correlated with LVEF. This suggests that alterations in cardiac energy metabolism are mechanistically more relevant for the pathophysiology of diabetic cardiomyopathy in LnT2D patients. In the absence of correlation between insulin resistance and myocardial perfusion, factors like inflammation and altered adipokine profile may play important roles for the pathophysiology of CMD in ObT2D patients. A better understanding of the underlying pathophysiological mechanisms of diabetic cardiomyopathy in LnT2D and ObT2D may help to develop contemporary tailored treatment and prevention strategies to tackle excess heart failure risk.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): BHFWellcome trust Table 1Table 2
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Affiliation(s)
| | | | - N Jex
- University of Leeds, Leeds, United Kingdom
| | - C Bowers
- Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - R Cubbon
- University of Leeds, Leeds, United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute, Bethesda, United States of America
| | - P Kellman
- National Heart Lung and Blood Institute, Bethesda, United States of America
| | | | - S Plein
- University of Leeds, Leeds, United Kingdom
| | - E Levelt
- University of Leeds, Leeds, United Kingdom
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Thirunavukarasu S, Jex N, Chowdhary A, Hassan I, Straw S, Broadbent D, Swoboda P, Witte KK, Cubbon R, Xue H, Kellman P, Greenwood JP, Plein S, Levelt E. Mechanistic insights from a multiparametric magnetic resonance imaging study regarding the role of sodium glucose co-transporter 2 inhibitors. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.0263] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Type 2 diabetes (T2D) is associated with an increased risk of heart failure (HF) and cardiovascular (CV) mortality. Sodium–glucose-co transporter-2 (SGLT2) inhibitors reduce the risk of major adverse CV events and hospitalisation for HF in T2D patients with high cardiovascular risk, despite only a modest improvement in glycemic control. Restoring cellular energy homeostasis and reversing adverse cardiac remodelling in diabetes have been speculated as a potential metabolic modulatory effect of SGLT2 inhibitors leading to their beneficial CV outcomes. Myocardial energy deficient states can be detected non-invasively by 31-phosphorus magnetic resonance spectroscopy (31P-MRS).
Objectives
Utilising cardiovascular magnetic resonance imaging (CMR) and 31P-MRS in a single centre longitudinal cohort study, we aimed to investigate the effects of the selective SGLT2 inhibitor empagliflozin on myocardial energetics, function, perfusion, and myocardial cellular volume in patients with T2D.
Methods
Eighteen consecutive T2D patients who were commenced on empagliflozin in cardiometabolic optimisation clinics underwent CMR and 31P-MRS scans before and after twelve-week empagliflozin treatment, and plasma N-terminal pro hormone B-type natriuretic peptide (NT-proBNP) levels were measured. Ten controls with no diabetes underwent an identical 31P-MRS and CMR protocol on a single visit.
Results
When compared to controls, patients with T2D showed: lower myocardial energetics (1.52±0.40 vs 2.20±0.5, p=0.0005), lower stress myocardial blood flow (1.60±0.50 vs 2.10±0.50, p=0.02) and lower left ventricular ejection fraction (52±13% vs 63±4%, p=0.01). Treatment with empagliflozin led to significant improvements in myocardial energetics (PCr/ATP: 1.52 to 1.76, p=0.009). This was accompanied by a relative 13% improvement in left ventricular ejection fraction (p=0.001), 3% improvement in global longitudinal strain (p=0.01), 61% reduction in NTproBNP (p=0.05), and 9% reduction in myocardial cell volume (p=0.04). No significant change in myocardial blood flow or diastolic strain was detected.
Conclusions
For the first time, we demonstrate that empagliflizon improves myocardial energetics and function, reduces myocardial cellular volume, and reduces NT-proBNP levels in patients with T2D.
Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): British Heart Foundation PCr/ATPLVEF
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Affiliation(s)
| | - N Jex
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - A Chowdhary
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - I Hassan
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - S Straw
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - D Broadbent
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - P Swoboda
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - K K Witte
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - R Cubbon
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - H Xue
- National Heart Lung and Blood Institute, Bethesda, United States of America
| | - P Kellman
- National Heart Lung and Blood Institute, Bethesda, United States of America
| | | | - S Plein
- University of Leeds, LICAMM, Leeds, United Kingdom
| | - E Levelt
- University of Leeds, LICAMM, Leeds, United Kingdom
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