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Chen L, Xu J, Liu D, Ji B, Wang J, Zeng X, Zhang J, Feng L. High-resolution free-breathing hepatobiliary phase MRI of the liver using XD-GRASP. Magn Reson Imaging 2024; 109:42-48. [PMID: 38447629 DOI: 10.1016/j.mri.2024.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 02/25/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE To evaluate the performance of high-resolution free-breathing (FB) hepatobiliary phase imaging of the liver using the eXtra-Dimension Golden-angle RAdial Sparse Parallel (XD-GRASP) MRI technique. METHODS Fifty-eight clinical patients (41 males, mean age = 52.9 ± 12.9) with liver lesions who underwent dynamic contrast-enhanced MRI with a liver-specific contrast agent were prospectively recruited for this study. Both breath-hold volumetric interpolated examination (BH-VIBE) imaging and FB imaging were performed during the hepatobiliary phase. FB images were acquired using a stack-of-stars golden-angle radial sequence and were reconstructed using the XD-GRASP method. Two experienced radiologists blinded to acquisition schemes independently scored the overall image quality, liver edge sharpness, hepatic vessel clarity, conspicuity of lesion, and overall artifact level of each image. The non-parametric paired two-tailed Wilcoxon signed-rank test was used for statistical analysis. RESULTS Compared to BH-VIBE images, XD-GRASP images received significantly higher scores (P < 0.05) for the liver edge sharpness (4.83 ± 0.45 vs 4.29 ± 0.46), the hepatic vessel clarity (4.64 ± 0.67 vs 4.15 ± 0.56) and the conspicuity of lesion (4.75 ± 0.53 vs 4.31 ± 0.50). There were no significant differences (P > 0.05) between BH-VIBE and XD-GRASP images for the overall image quality (4.61 ± 0.50 vs 4.74 ± 0.47) and the overall artifact level (4.13 ± 0.44 vs 4.05 ± 0.61). CONCLUSION Compared to conventional BH-VIBE MRI, FB radial acquisition combined with XD-GRASP reconstruction facilitates higher spatial resolution imaging of the liver during the hepatobiliary phase. This enhancement can significantly improve the visualization and evaluation of the liver.
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Affiliation(s)
- Lihua Chen
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Jian Xu
- Department of General Surgery, 904th Hospital, Wuxi, Jiangsu, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Bing Ji
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xianchun Zeng
- Department of Radiology, Guizhou Provincial People's Hospital, Guizhou, China.
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.
| | - Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
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Xiao L, Yang J, Zhu H, Zhou M, Li J, Liu D, Tang Y, Feng L, Hu S. [ 18F]SynVesT-1 and [ 18F]FDG quantitative PET imaging in the presurgical evaluation of MRI-negative children with focal cortical dysplasia type II. Eur J Nucl Med Mol Imaging 2024; 51:1651-1661. [PMID: 38182838 DOI: 10.1007/s00259-024-06593-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 01/01/2024] [Indexed: 01/07/2024]
Abstract
PURPOSE MRI-negative children with focal cortical dysplasia type II (FCD II) are one of the most challenging cases in surgical epilepsy management. We aimed to utilize quantitative positron emission tomography (QPET) analysis to complement [18F]SynVesT-1 and [18F]FDG PET imaging and facilitate the localization of epileptogenic foci in pediatric MRI-negative FCD II patients. METHODS We prospectively enrolled 17 MRI-negative children with FCD II who underwent [18F]SynVesT-1 and [18F]FDG PET before surgical resection. The QPET scans were analyzed using statistical parametric mapping (SPM) with respect to healthy controls. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of [18F]SynVesT-1 PET, [18F]FDG PET, [18F]SynVesT-1 QPET, and [18F]FDG QPET in the localization of epileptogenic foci were assessed. Additionally, we developed a multivariate prediction model based on dual trace PET/QPET assessment. RESULTS The AUC values of [18F]FDG PET and [18F]SynVesT-1 PET were 0.861 (sensitivity = 94.1%, specificity = 78.2%, PPV = 38.1%, NPV = 98.9%) and 0.908 (sensitivity = 82.4%, specificity = 99.2%, PPV = 93.3%, NPV = 97.5%), respectively. [18F]FDG QPET showed lower sensitivity (76.5%) and NPV (96.6%) but higher specificity (95.0%) and PPV (68.4%) than visual assessment, while [18F]SynVesT-1 QPET exhibited higher sensitivity (94.1%) and NPV (99.1%) but lower specificity (97.5%) and PPV (84.2%). The multivariate prediction model had the highest AUC value (AUC = 0.996, sensitivity = 100.0%, specificity = 96.6%, PPV = 81.0%, NPV = 100%). CONCLUSIONS The multivariate prediction model based on [18F]SynVesT-1 and [18F]FDG PET/QPET assessments holds promise in noninvasively identifying epileptogenic regions in MRI-negative children with FCD II. Furthermore, the combination of visual assessment and QPET may improve the sensitivity and specificity of diagnostic tests in localizing epileptogenic foci and achieving a preferable surgical outcome in MRI-negative FCD II.
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Affiliation(s)
- Ling Xiao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jinhui Yang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Haoyue Zhu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ming Zhou
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dingyang Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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Liu C, How ZT, Ju Y, Feng L, Ren X, Gamal El-Din M. Experimental and theoretical insight into carbamazepine degradation by chlorine-based advanced oxidation processes: Efficiency, energy consumption, mechanism and DBPs formation. J Environ Sci (China) 2024; 139:72-83. [PMID: 38105079 DOI: 10.1016/j.jes.2023.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/10/2023] [Accepted: 05/10/2023] [Indexed: 12/19/2023]
Abstract
Chlorine has been widely used in different advanced oxidation processes (AOPs) for micropollutants removal. In this study, different chlorine-based AOPs, namely medium pressure (MP) UV/chlorine, low pressure (LP) UV/chlorine, and in-situ chlorination, were compared for carbamazepine (CBZ) removal efficiency, energy consumption, and disinfection by-products (DBPs) formation. All three processes could achieve nearly 100% CBZ removal, while the reaction time needed by in-situ chlorination was double the time required by UV/chlorine processes. The energy consumed per magnitude of CBZ removed (EE/O) of MP UV/chlorine was 13 times higher than that of LP UV/chlorine, and relative to that of in-situ chlorination process. Accordingly, MP and LP UV/chlorine processes generated one to two orders of magnitude more hydroxyl radicals (•OH) and reactive chlorine species (RCS) than in-situ chlorination. Besides, RCS were the dominant reactive species, contributing to 78.3%, 75.6%, and 71.6% of CBZ removal in MP, LP UV/chlorine, and in-situ chlorination, respectively. According to the Gibbs free energy barriers between CBZ and RCS/•OH calculated based on density functional theory (DFT), RCS had more reaction routes with CBZ and showed lower energy barrier in the main CBZ degradation pathways like epoxidation and formation of iminostilbene. When applied to secondary wastewater effluent, UV/chlorine and in-situ chlorination produced overall DBPs ranging from 104.77 to 135.41 µg/L. However, the production of chlorate during UV/chlorine processes was 15 times higher than that during in-situ chlorination.
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Affiliation(s)
- Chunwei Liu
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, School of Chemical Engineering and Technology, China University of Mining and Technology, Jiangsu 221116, China; Department of Civil and Environmental Engineering, University of Alberta, Edmonton T6G 1H9, Alberta, Canada
| | - Zuo Tong How
- Department of Civil and Environmental Engineering, University of Alberta, Edmonton T6G 1H9, Alberta, Canada; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Ecology and Environment, Hainan University, Hainan 570228, China
| | - Yue Ju
- Department of Civil and Environmental Engineering, University of Alberta, Edmonton T6G 1H9, Alberta, Canada; School of Environment and Spatial Informatics, China University of Mining and Technology, Jiangsu 221116, China
| | - Li Feng
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, School of Chemical Engineering and Technology, China University of Mining and Technology, Jiangsu 221116, China
| | - Xuefeng Ren
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, School of Chemical Engineering and Technology, China University of Mining and Technology, Jiangsu 221116, China
| | - Mohamed Gamal El-Din
- Department of Civil and Environmental Engineering, University of Alberta, Edmonton T6G 1H9, Alberta, Canada.
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Gao SH, Wang GZ, Wang LP, Feng L, Zhou YC, Yu XJ, Liang F, Yang FY, Wang Z, Sun BB, Wang D, Liang LJ, Xie DW, Zhao S, Feng HP, Li X, Li KK, Tang TS, Huang YC, Wang SQ, Zhou GB. Corrigendum to "Mutations and clinical significance of calcium voltage-gated channel subunit alpha 1E (CACNA1E) in non-small cell lung cancer" [Cell Calcium 102 (2022) 102527]. Cell Calcium 2024; 119:102866. [PMID: 38428281 DOI: 10.1016/j.ceca.2024.102866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Affiliation(s)
- S H Gao
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, 100101, China; State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - G Z Wang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - L P Wang
- State Key Laboratory of Membrane Biology, College of Life Sciences, Peking University, Beijing, 100091, China
| | - L Feng
- Department of Pathology, Chinese PLA General Hospital, Beijing, 100853, China
| | - Y C Zhou
- Department of Thoracic Surgery, the Third Affiliated Hospital of Kunming Medical University (Yunnan Tumor Hospital), Kunming, 650106, China
| | - X J Yu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, 100101, China
| | - F Liang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, 100101, China; State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - F Y Yang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Z Wang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - B B Sun
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - D Wang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - L J Liang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - D W Xie
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - S Zhao
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, 100101, China
| | - H P Feng
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, 100101, China
| | - X Li
- Computer Science Department, University of North Georgia, Dahlonega, GA, 30597, United States
| | - K K Li
- Computer Science Department, University of North Georgia, Dahlonega, GA, 30597, United States
| | - T S Tang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Y C Huang
- Department of Thoracic Surgery, the Third Affiliated Hospital of Kunming Medical University (Yunnan Tumor Hospital), Kunming, 650106, China
| | - S Q Wang
- State Key Laboratory of Membrane Biology, College of Life Sciences, Peking University, Beijing, 100091, China
| | - G B Zhou
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Jing Z, Wu L, Pan Y, Zhang L, Zhang X, Shi D, Shi H, Chen J, Ji Z, Zhang J, Feng T, Tian J, Feng L. Rotavirus infection inhibits SLA-I expression on the cell surface by degrading β2 M via ERAD-proteasome pathway. Vet Microbiol 2024; 292:110036. [PMID: 38458048 DOI: 10.1016/j.vetmic.2024.110036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/20/2024] [Accepted: 03/01/2024] [Indexed: 03/10/2024]
Abstract
Group A Rotavirus (RVA) is a major cause of diarrhea in infants and piglets. β2-microglobulin (β2 M), encoded by the B2M gene, serves as a crucial subunit of the major histocompatibility complex class I (MHC-I) molecules. β2 M is indispensable for the transport of MHC-I to the cell membrane. MHC-I, also known as swine leukocyte antigen class I (SLA-I) in pigs, presents viral antigens to the cell surface. In this study, RVA infection down-regulated β2 M expression in both porcine intestinal epithelial cells-J2 (IPEC-J2) and MA-104 cells. RVA infection did not down-regulate the mRNA level of the B2M gene, indicating that the down-regulation of β2 M occurred on the protein level. Mechanismly, RVA infection triggered β2 M aggregation in the endoplasmic reticulum (ER) and enhanced the Lys48 (K48)-linked ubiquitination of β2 M, leading to the degradation of β2 M through ERAD-proteasome pathway. Furthermore, we found that RVA infection significantly impeded the level of SLA-I on the surface, and the overexpression of β2 M could recover its expression. In this study, our study demonstrated that RVA infection degrades β2 M via ERAD-proteasome pathway, consequently hampering SLA-I expression on the cell surface. This study would enhance the understanding of the mechanism of how RVA infection induces immune escape.
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Affiliation(s)
- Zhaoyang Jing
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Ling Wu
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Yudi Pan
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Liaoyuan Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Xin Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Da Shi
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Hongyan Shi
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Jianfei Chen
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Zhaoyang Ji
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Jiyu Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Tingshuai Feng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China
| | - Jin Tian
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China.
| | - Li Feng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Harbin, People's Republic of China.
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Wu Z, Li X, Huang Y, Huang K, Xiao B, Chi Y, Feng L, Yang H. Effects of a Nurse-Led Cognitive Behavioral Intervention for Parents of Children With Epilepsy. Pediatr Neurol 2024; 154:70-78. [PMID: 38552337 DOI: 10.1016/j.pediatrneurol.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/18/2024] [Accepted: 03/03/2024] [Indexed: 04/15/2024]
Abstract
BACKGROUND This study aimed to evaluate the effects of a nurse-led cognitive behavioral intervention for parents of children with epilepsy (CWE). METHODS The study recruited 238 CWE from the neurology ward of Xiangya Hospital from March 2019 to August 2022. According to the interventions after discharge, the children and their parents were randomly divided into 117 parent-child dyads in the intervention group and 121 parent-child dyads in the control group. The seizure severity and treatment compliance in CWE as well as the parents' psychological states and satisfaction with the care provided by nurses were compared before and after intervention. RESULTS The follow-up six months after discharge showed that the seizure frequency among CWE in the intervention group was significantly less than the controls (P = 0.048). Compared with the controls, the intervention group also reported fewer symptoms of anxiety and depression, better sleep quality, and more positive attitudes toward epilepsy, as well as higher nursing satisfaction (P < 0.001). The correlation analysis indicated the correlation of CWE's seizure severity was correlated with the compliance, parents' psychological states, and parents' satisfaction with the care provided by nurses. CONCLUSIONS The adoption of the nurse-led cognitive behavioral intervention on parents of CWE can improve the parents' mental health status and their satisfaction with the nurses, which can have a positive association with the seizure severity of CWE. In light of this information, this nursing intervention may be a new method for the long-term disease management of CWE.
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Affiliation(s)
- Zhongling Wu
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Clinical Nursing Teaching and Research Section, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiaolei Li
- Department of Cardiology, Laizhou People's Hospital, Yantai, Shandong, China
| | - Yuanxin Huang
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Clinical Nursing Teaching and Research Section, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Kailing Huang
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Neurology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Neurology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yunfang Chi
- Department of Cardiology, Laizhou People's Hospital, Yantai, Shandong, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Neurology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Neurology, Xiangya Hospital, Central South University (Jiangxi Branch), Nanchang, Jiangxi, China.
| | - Haojun Yang
- Department of Anesthesiology, Xiangya Hospital of Central South University, Changsha, Hunan, China.
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Huang K, Tian Z, Zhang Q, Yang H, Wen S, Feng J, Tang W, Wang Q, Feng L. Reduced eye gaze fixation during emotion recognition among patients with temporal lobe epilepsy. J Neurol 2024; 271:2560-2572. [PMID: 38289536 DOI: 10.1007/s00415-024-12202-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 01/09/2024] [Accepted: 01/16/2024] [Indexed: 04/28/2024]
Abstract
OBJECTIVES To investigate the facial scan patterns during emotion recognition (ER) through the dynamic facial expression task and the awareness of social interference test (TASIT) using eye tracking (ET) technology, and to find some ET indicators that can accurately depict the ER process, which is a beneficial supplement to existing ER assessment tools. METHOD Ninety-six patients with TLE and 88 healthy controls (HCs) were recruited. All participants watched the dynamic facial expression task and TASIT including a synchronized eye movement recording and recognized the emotion (anger, disgust, happiness, or sadness). The accuracy of ER was recorded. The first fixation time, first fixation duration, dwell time, and fixation count were selected and analyzed. RESULTS TLE patients exhibited ER impairment especially for disgust (Z = - 3.391; p = 0.001) and sadness (Z = - 3.145; p = 0.002). TLE patients fixated less on the face, as evidenced by the reduced fixation count (Z = - 2.549; p = 0.011) of the face and a significant decrease in the fixation count rate (Z = - 1.993; p = 0.046). During the dynamic facial expression task, TLE patients focused less on the eyes, as evidenced by the decreased first fixation duration (Z = - 4.322; p = 0.000), dwell time (Z = - 4.083; p = 0.000), and fixation count (Z = - 3.699; p = 0.000) of the eyes. CONCLUSION TLE patients had ER impairment, especially regarding negative emotions, which may be attributable to their reduced fixation on the eyes during ER, and the increased fixation on the mouth could be a compensatory effect to improve ER performance. Eye-tracking technology could provide the process indicators of ER, and is a valuable supplement to traditional ER assessment tasks.
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Affiliation(s)
- Kailing Huang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China
| | - Ziwei Tian
- Key Laboratory of Biomedical Spectroscopy of Xi'an, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119, China
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119, China
- University of Chinese Academy of Sciences, Beijing, 101400, China
| | - Qiong Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China
| | - Haojun Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China
| | - Shirui Wen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China
| | - Jie Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China
| | - Weiting Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China
| | - Quan Wang
- Key Laboratory of Biomedical Spectroscopy of Xi'an, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119, China.
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119, China.
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People's Republic of China.
- Department of Neurology, Xiangya Hospital, Central South University (Jiangxi Branch), Nanchang, 330000, Jiangxi, China.
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Ye J, Wu H, Feng L, Huang Q, Li Q, Liao W, Wu JC. Characterization of Bacillus amyloliquefaciens PM415 as a potential bio-preserving probiotic. Arch Microbiol 2024; 206:222. [PMID: 38642140 DOI: 10.1007/s00203-024-03953-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 04/02/2024] [Accepted: 04/02/2024] [Indexed: 04/22/2024]
Abstract
Animal feed is vulnerable to fungal infections, and the use of bio-preserving probiotics has received increasing attention. In contrast to Lactobacillus and Bifidobacteria spp., fewer Bacillus spp. have been recognized as antifungal probiotics. Therefore, our objective was to screen antifungal strains and provide more Bacillus candidates to bridge this gap. Here, we screened 56 bacterial strains for cyclic lipopeptide genes and conducted an antifungal assay with Aspergillus niger as a representative fungus. We found that a Bacillus strain Bacillus amyloliquefaciens PM415, isolated from pigeon manure, exhibited the highest fungal inhibition activity as demonstrated by the confrontation assay and morphological observation under scanning electron microscope (SEM). Preliminary safety assessment and probiotic characterization revealed its non-pathogenic feature and stress tolerance capability. Whole genome sequencing of Bacillus amyloliquefaciens PM415 revealed a genome size of 4.16 Mbp and 84 housekeeping genes thereof were used for phylogenetic analysis showing that it is most closely related to Bacillus amyloliquefaciens LFB112. The in silico analysis further supported its non-pathogenic feature at the genomic level and revealed potential biosynthetic gene clusters responsible for its antifungal property. RNA-seq analysis revealed genome-wide changes in transportation, amino acid metabolism, non-ribosomal peptides (NRPs) biosynthesis and glycan degradation during fungal antagonism. Our results suggest that Bacillus amyloliquefaciens PM415 is a safe and effective probiotic strain that can prevent fungal growth in animal feeds.
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Affiliation(s)
- Jingkang Ye
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Haiyang Wu
- Guangdong Provincial Engineering Laboratory of Biomass High Value Utilization, Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510316, P. R. China
| | - Li Feng
- Guangdong Provincial Engineering Laboratory of Biomass High Value Utilization, Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510316, P. R. China
| | - Qinghua Huang
- Guangdong Provincial Engineering Laboratory of Biomass High Value Utilization, Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510316, P. R. China
| | - Qingxin Li
- Guangdong Provincial Engineering Laboratory of Biomass High Value Utilization, Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510316, P. R. China
| | - Weiming Liao
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China.
| | - Jin Chuan Wu
- Guangdong Provincial Engineering Laboratory of Biomass High Value Utilization, Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, Guangdong, 510316, P. R. China.
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Chen J, Feng L, Li S, Wang H, Huang X, Shen C, Feng H. Therapeutic Plasma Exchange in AChR-Ab Positive Generalized Myasthenia Gravis: A Real World Study About Its Early Response. J Inflamm Res 2024; 17:2299-2308. [PMID: 38645879 PMCID: PMC11032135 DOI: 10.2147/jir.s455104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 04/06/2024] [Indexed: 04/23/2024] Open
Abstract
Background Since there is no clear priority or selection principle in the guidelines for myasthenia crisis, therapeutic plasma exchange (TPE) and intravenous immunoglobulin are often administered randomly. However, it should be more prudent in taking TPE due to its higher cost and risk. Studying its early response factors is crucial for managing myasthenia crisis and can improve medical and economic benefits. Methods A prospective observational study was conducted, and patients classified as having "impending myasthenia crisis" or experiencing a myasthenia crisis and treated by TPE were included. The primary endpoint was the response after TPE. Univariate logistic regression analysis and repeated measurement were performed to analyze factors related to TPE efficacy. Results A total of 30 patients who treated with TPE as their fast-acting treatments were enrolled. After TPE, those whose QMGs and/or MGCs decreased by ≥5 points or ≥30% of the baseline were judged as "response group", accounting for 66.67% (20/30). Respiratory symptoms had a response rate of 72.00% (18/25), showing the most remarkable improvement. Meanwhile, extraocular symptoms were the least sensitive, with only 8.00% (2/25) showing efficacy. Thymoma (100.00% vs 50.00%, P=0.002) and a high concentration of AChR-Ab (37.37 nmol/L vs 25.4 nmol/L, P=0.039) were common in the early response group. Repeated measures showed significant changes in AChR-Ab and CD19+ B cells before and after TPE (all with P < 0.05). After treatment, the CD19+ B cells tended to decrease in the response group. Discussion These results indicated that, for AChR-Ab positive generalized MG, TPE can quickly improve respiratory symptoms. Thymoma and a high concentration of AChR-Ab before TPE predict an early better response. Additionally, TPE may work by decreasing AChR-Ab levels and inducing immune regulation. Future prospective and randomized controlled studies are needed.
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Affiliation(s)
- Jiaxin Chen
- Department of Neurology and Neurointensive Care Unit, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
| | - Li Feng
- Department of Neurology and Neurointensive Care Unit, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
| | - Shiyin Li
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
| | - Haiyan Wang
- Department of Neurology and Neurointensive Care Unit, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
| | - Xin Huang
- Department of Neurology and Neurointensive Care Unit, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
| | - Cunzhou Shen
- Department of Neurology and Neurointensive Care Unit, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
| | - Huiyu Feng
- Department of Neurology and Neurointensive Care Unit, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, People’s Republic of China
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Wang Y, He X, Gao P, Feng L, Zhang L. Enhanced photocatalytic gaseous formaldehyde degradation using N-CQDs/OVs-TiO 2 composite under visible light: Unraveling the synergistic effects of N-CQDs and oxygen vacancies. Environ Res 2024; 247:118301. [PMID: 38272291 DOI: 10.1016/j.envres.2024.118301] [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: 12/08/2023] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 01/27/2024]
Abstract
Limited utilization of photogenerated charge carriers in titanium dioxide under visible light have hinder its application development. To address this challenge, a novel N-doped carbon quantum dots (N-CQDs) and oxygen vacancies (OVs) synergistically decorated on TiO2 (P25) was synthesized through a facile one-step hydrothermal method. Under visible light irradiation, the first order reaction rate constants of formaldehyde (HCHO) photocatalytic oxidation by OVs-TiO2 and N-CQDs/OVs-TiO2 was significantly higher than that of pristine P25, with 10.1 and 16.7 folds increase, respectively. Characterization results confirmed the generation of OVs on the surface of N-CQDs/TiO2 composite. The optical and electrochemical experiments suggested the electron capture center effect of OVs and the properties of N-CQDs in unique up-converted photoluminescence, efficient charge separation, as well as significant adsorption in visible light region. In addition, the work function also clarified that photoelectrons could transfer from N-CQDs to OVs-TiO2. Furthermore, different relative humidity and electron paramagnetic resonance (EPR) experiments demonstrated that the hydroxyl radical (•OH) was the dominant reactive radical in HCHO photodegradation. The •O2- could also enhance the photodegradation efficiency of HCHO. This work provides an in-depth understanding on the complementary roles of N-CQDs and OVs and is helpful for designing metallic oxide photocatalysts for volatile organic compounds removal.
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Affiliation(s)
- Yang Wang
- Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China; Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China
| | - Xiaoqing He
- Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China; Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China
| | - Peng Gao
- Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China; Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China.
| | - Li Feng
- Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China; Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China
| | - Liqiu Zhang
- Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China; Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China.
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Jing C, Huang L, Tao S, Chen Y, Zhang S, Dong W, Ling F, Tang X, Li Y, Feng L, Zhang Y. Construction of MoB@LDH heterojunction and its derivates through phase and interface engineering for advanced supercapacitor applications. J Colloid Interface Sci 2024; 660:10-20. [PMID: 38241858 DOI: 10.1016/j.jcis.2023.12.184] [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: 12/05/2023] [Revised: 12/24/2023] [Accepted: 12/30/2023] [Indexed: 01/21/2024]
Abstract
Layered double hydroxide (LDH) has been attracted widespread attention in supercapacitor due to their unique layered structure and associated advantages. However, the inherent limitations of low electrical conductivity and reaction kinetics rate of LDH restrict its widespread application. Various modification techniques, such as heterojunction formation, phosphorization and introduction of phosphorus vacancies, are employed to modify LDH with the goal of improving the electrochemical performance. Preparation of composite materials using MoB MBene as conductive template and phosphorization are the effective ways for enhancing the electrical conductivity of electrode materials. MoB MBene is prepared using a modified method that combines NaOH etching and a high-temperature hydrothermal process. The presence of phosphorus vacancy is beneficial for enhancing the kinetics rate during electrode reactions. Through the synergistic effect of various modification methods, MP2 demonstrates an optimal electrochemical performance with a superior specific capacitance of 1731.19F/g (238.28 mAh g-1) at 1 A/g. It also demonstrates an impressive rate capacity of 81.28 % at 10 A/g and maintains a satisfactory capacitance retention of 88.14 % after 5000 cycles. In addition, a fabricated MP2//AC ASC device achieves an impressive energy density of 39.91 Wh kg-1 at the power density of 948.25 W kg-1 and demonstrates satisfactory cycling stability of 78.76 % after 5000 cycles. This work presents a comprehensive framework for analyzing the impact of material structure, components, and crystal phases on energy storage performance. It also examines the regulatory impact of different modification methods on energy storage mechanisms.
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Affiliation(s)
- Chuan Jing
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China; Water Environment Engineering Technology Innovation Center, Chongqing Academy of Eco-Environmental Sciences, Chongqing 401120, PR China.
| | - Leyi Huang
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Shengrong Tao
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Yancheng Chen
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Shuijie Zhang
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Wei Dong
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Faling Ling
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China.
| | - Xiao Tang
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Yanhong Li
- College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China
| | - Li Feng
- Water Environment Engineering Technology Innovation Center, Chongqing Academy of Eco-Environmental Sciences, Chongqing 401120, PR China.
| | - Yuxin Zhang
- College of Materials Science and Engineering, Chongqing University, Chongqing 400044, PR China
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Zhang T, Zhou L, Pu Y, Tang Y, Liu J, Yang L, Zhou T, Feng L, Wang X. A chromosome-level genome reveals genome evolution and molecular basis of anthraquinone biosynthesis in Rheum palmatum. BMC Plant Biol 2024; 24:261. [PMID: 38594606 PMCID: PMC11005207 DOI: 10.1186/s12870-024-04972-2] [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: 02/27/2024] [Accepted: 04/01/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Rhubarb is one of common traditional Chinese medicine with a diverse array of therapeutic efficacies. Despite its widespread use, molecular research into rhubarb remains limited, constraining our comprehension of the geoherbalism. RESULTS We assembled the genome of Rheum palmatum L., one of the source plants of rhubarb, to elucidate its genome evolution and unpack the biosynthetic pathways of its bioactive compounds using a combination of PacBio HiFi, Oxford Nanopore, Illumina, and Hi-C scaffolding approaches. Around 2.8 Gb genome was obtained after assembly with more than 99.9% sequences anchored to 11 pseudochromosomes (scaffold N50 = 259.19 Mb). Transposable elements (TE) with a continuous expansion of long terminal repeat retrotransposons (LTRs) is predominant in genome size, contributing to the genome expansion of R. palmatum. Totally 30,480 genes were predicted to be protein-coding genes with 473 significantly expanded gene families enriched in diverse pathways associated with high-altitude adaptation for this species. Two successive rounds of whole genome duplication event (WGD) shared by Fagopyrum tataricum and R. palmatum were confirmed. We also identified 54 genes involved in anthraquinone biosynthesis and other 97 genes entangled in flavonoid biosynthesis. Notably, RpALS emerged as a compelling candidate gene for the octaketide biosynthesis after the key residual screening. CONCLUSION Overall, our findings offer not only an enhanced understanding of this remarkable medicinal plant but also pave the way for future innovations in its genetic breeding, molecular design, and functional genomic studies.
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Affiliation(s)
- Tianyi Zhang
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Lipan Zhou
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yang Pu
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yadi Tang
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Jie Liu
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Li Yang
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Tao Zhou
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Li Feng
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.
| | - Xumei Wang
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.
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Zhang J, Shi H, Zhang L, Feng T, Chen J, Zhang X, Ji Z, Jing Z, Zhu X, Liu D, Yang X, Zeng M, Shi D, Feng L. Swine acute diarrhea syndrome coronavirus nucleocapsid protein antagonizes the IFN response through inhibiting TRIM25 oligomerization and functional activation of RIG-I/TRIM25. Vet Res 2024; 55:44. [PMID: 38589930 PMCID: PMC11000385 DOI: 10.1186/s13567-024-01303-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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 03/20/2024] [Indexed: 04/10/2024] Open
Abstract
Swine acute diarrhea syndrome coronavirus (SADS-CoV), an emerging Alpha-coronavirus, brings huge economic loss in swine industry. Interferons (IFNs) participate in a frontline antiviral defense mechanism triggering the activation of numerous downstream antiviral genes. Here, we demonstrated that TRIM25 overexpression significantly inhibited SADS-CoV replication, whereas TRIM25 deficiency markedly increased viral yield. We found that SADS-CoV N protein suppressed interferon-beta (IFN-β) production induced by Sendai virus (SeV) or poly(I:C). Moreover, we determined that SADS-CoV N protein interacted with RIG-I N-terminal two caspase activation and recruitment domains (2CARDs) and TRIM25 coiled-coil dimerization (CCD) domain. The interaction of SADS-CoV N protein with RIG-I and TRIM25 caused TRIM25 multimerization inhibition, the RIG-I-TRIM25 interaction disruption, and consequent the IRF3 and TBK1 phosphorylation impediment. Overexpression of SADS-CoV N protein facilitated the replication of VSV-GFP by suppressing IFN-β production. Our results demonstrate that SADS-CoV N suppresses the host IFN response, thus highlighting the significant involvement of TRIM25 in regulating antiviral immune defenses.
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Affiliation(s)
- Jiyu Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Hongyan Shi
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Liaoyuan Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Tingshuai Feng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Jianfei Chen
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Xin Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Zhaoyang Ji
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Zhaoyang Jing
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Xiaoyuan Zhu
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Dakai Liu
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Xiaoman Yang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Miaomiao Zeng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China
| | - Da Shi
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China.
| | - Li Feng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xiangfang District, Haping Road 678, Harbin, 150069, China.
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Hu B, He X, Sun H, Hu Y, Li F, Sun Y, Sun J, Feng L. Red and processed meat intake and risk of cardiovascular disease: A two-sample Mendelian randomization study. Clin Nutr ESPEN 2024; 60:289-297. [PMID: 38479924 DOI: 10.1016/j.clnesp.2024.02.014] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 01/20/2024] [Accepted: 02/16/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND & AIMS Previous observational studies have yielded inconsistent findings regarding associations between red/processed meat intake and the risk of cardiovascular disease (CVD). Some studies have suggested positive relationships, while others have demonstrated no significant associations. However, causal effects remain uncertain. This 2023 Mendelianrandomization (MR) study investigated the causal relationship between red and processed meat (porkmeat, mutton meat, beef meat)intake and CVD risk by analyzing summary data from the UK Biobank (exposure), CARDIoGRAMplusC4D (coronary artery disease [CAD]), MEGASTROKE (stroke), Nielsen et al. (atrial fibrillation [AF]), HERMES (heart failure [HF]), and FinnGen (cardiovascular outcomes) public databases. METHODS Genome-wide association studies (GWAS) of red meat (pork, beef, and mutton) and processed meat were sourced from the United Kingdom (UK) Biobank. GWAS data on CVD for this study were obtained from the Gene and FinnGen consortia. The primary method employed for the two-sample MR analysis was inverse variance weighting (IVW). Sensitivity analysis was performed to assess the reliability and consistency of the results. RESULTS Genetically predicted red and processed meat consumption did not demonstrate a causal association with any CVD outcomes when employing the IVW method. For processed meat intake, the odds ratios (ORs) (95% confidence intervals CIs) in large consortia were as follows: 0.88 (0.56-1.39) for CAD, 0.91 (0.65-1.27) for AF, 0.84 (0.58-1.21) for HF, and 1.00 (0.75-1.05) for stroke. In FinnGen, the ORs were as follows: 1.15 (0.83-1.59) for CAD, 1.25 (0.75-2.07) for AF, 1.09 (0.73-1.64) for HF, and 1.27 (0.85-1.91) for stroke. For beef intake, the ORs (95% CIs) in large consortia were as follows: 0.70 (0.28-1.73) for CAD, 0.85 (0.49-1.49) for AF, 0.80 (0.35-1.83) for HF, and 1.29 (0.85-1.95) for stroke. In FinnGen, the ORs were as follows: 2.01 (0.75-5.39) for CAD, 1.83 (0.60-5.56) for AF, 0.80 (0.30-2.13) for HF, and 1.30 (0.62-2.73) for stroke. For pork intake, the ORs (95% CIs) in large consortia were as follows: 1.25 (0.37-4.22) for CAD, 1.26 (0.73-2.15) for AF, 1.71 (0.86-3.39) for HF, and 1.15 (0.63-2.11) for stroke. In FinnGen, the ORs were as follows: 1.12 (0.43-2.88) for CAD, 0.39 (0.08-1.83) for AF, 0.62 (0.20-1.88) for HF, and 0.60 (0.21-1.65) for stroke. For mutton intake, the ORs (95% CIs) in large consortia were as follows: 0.84 (0.48-1.44) for CAD, 0.84 (0.56-1.26) for AF, 1.04 (0.65-1.67) for HF, and 1.06 (0.77-1.45) for stroke. In FinnGen, the ORs were as follows: 1.20 (0.65-2.21) for CAD, 0.92 (0.44-1.92) for AF, 0.74 (0.34-1.58) for HF, and 0.75 (0.45-1.24) for stroke. The results remained robust and consistent in both the meta-analysis and supplementary MR analysis. CONCLUSIONS This MR study demonstrated no significant causal relationships between red/processed meat intake and the risk of the four CVD outcomes examined. Further investigation is warranted to confirm these findings.
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Affiliation(s)
- Bing Hu
- Department of Cardiology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China
| | - Xin He
- Department of Hematology, Zhongshan City People's Hospital, Zhongshan City, Guangdong, China
| | - Hao Sun
- Tumor Surgery Department, Zhongshan City People's Hospital, Zhongshan City, Guangdong, China
| | - Yongyi Hu
- Department of Cardiology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China; Department of Chronic Disease Management, Zhongshan City People's Hospital, Zhongshan City, Guangdong, China
| | - Fei Li
- Department of Cardiology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China
| | - Yanxiang Sun
- Department of Cardiology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China
| | - Jie Sun
- Department of Cardiology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China
| | - Li Feng
- Department of Cardiology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China.
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Zhou C, Xie F, Wang D, Huang X, Guo D, Du Y, Xiao L, Liu D, Xiao B, Yang Z, Feng L. Preoperative structural-functional coupling at the default mode network predicts surgical outcomes of temporal lobe epilepsy. Epilepsia 2024; 65:1115-1127. [PMID: 38393301 DOI: 10.1111/epi.17921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/03/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024]
Abstract
OBJECTIVE Structural-functional coupling (SFC) has shown great promise in predicting postsurgical seizure recurrence in patients with temporal lobe epilepsy (TLE). In this study, we aimed to clarify the global alterations in SFC in TLE patients and predict their surgical outcomes using SFC features. METHODS This study analyzed presurgical diffusion and functional magnetic resonance imaging data from 71 TLE patients and 48 healthy controls (HCs). TLE patients were categorized into seizure-free (SF) and non-seizure-free (nSF) groups based on postsurgical recurrence. Individual functional connectivity (FC), structural connectivity (SC), and SFC were quantified at the regional and modular levels. The data were compared between the TLE and HC groups as well as among the TLE, SF, and nSF groups. The features of SFC, SC, and FC were categorized into three datasets: the modular SFC dataset, regional SFC dataset, and SC/FC dataset. Each dataset was independently integrated into a cross-validated machine learning model to classify surgical outcomes. RESULTS Compared with HCs, the visual and subcortical modules exhibited decoupling in TLE patients (p < .05). Multiple default mode network (DMN)-related SFCs were significantly higher in the nSF group than in the SF group (p < .05). Models trained using the modular SFC dataset demonstrated the highest predictive performance. The final prediction model achieved an area under the receiver operating characteristic curve of .893 with an overall accuracy of .887. SIGNIFICANCE Presurgical hyper-SFC in the DMN was strongly associated with postoperative seizure recurrence. Furthermore, our results introduce a novel SFC-based machine learning model to precisely classify the surgical outcomes of TLE.
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Affiliation(s)
- Chunyao Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Fangfang Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Dongcui Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaoting Huang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Danni Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yangsa Du
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Ling Xiao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Dingyang Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhiquan Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Department of Neurology, Xiangya Hospital, Central South University (Jiangxi Branch), Nanchang, China
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Huang K, Zhao T, Sun W, Feng L, Wang Q, Feng J. Memory deficit in patients with cerebral small vessel disease: evidence from eye tracking technology. Cereb Cortex 2024; 34:bhae138. [PMID: 38602738 DOI: 10.1093/cercor/bhae138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 03/14/2024] [Accepted: 03/16/2024] [Indexed: 04/12/2024] Open
Abstract
Cerebral small vessel disease is the one of the most prevalent causes of vascular cognitive impairment. We aimed to find objective and process-based indicators related to memory function to assist in the detection of memory impairment in patients with cerebral small vessel disease. Thirty-nine cerebral small vessel disease patients and 22 healthy controls were invited to complete neurological examinations, neuropsychological assessments, and eye tracking tasks. Eye tracking indicators were recorded and analyzed in combination with imaging features. The cerebral small vessel disease patients scored lower on traditional memory task and performed worse on eye tracking memory task performance compared to the healthy controls. The cerebral small vessel disease patients exhibited longer visit duration and more visit count within areas of interest and targets and decreased percentage value of total visit duration on target images to total visit duration on areas of interest during decoding stage among all levels. Our results demonstrated the cerebral small vessel disease patients performed worse in memory scale and eye tracking memory task, potentially due to their heightened attentional allocation to nontarget images during the retrieval stage. The eye tracking memory task could provide process-based indicators to be a beneficial complement to memory assessment and new insights into mechanism of memory impairment in cerebral small vessel disease patients.
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Affiliation(s)
- Kailing Huang
- Department of Neurology, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
| | - Tingting Zhao
- Department of Neurology, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
| | - Weifeng Sun
- Key Laboratory of Biomedical Spectroscopy of Xi'an, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, No. 17, Information Avenue, New Industrial Park, High-tech Zone, Xi'an 710119, Shaanxi Province, P.R. China
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, No. 17, Information Avenue, New Industrial Park, High-tech Zone, Xi'an 710119, Shaanxi Province, P.R. China
- University of Chinese Academy of Sciences, No. 1, Yanqihu East Road, Huairou District, Beijing 101408, P.R. China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
| | - Quan Wang
- Key Laboratory of Biomedical Spectroscopy of Xi'an, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, No. 17, Information Avenue, New Industrial Park, High-tech Zone, Xi'an 710119, Shaanxi Province, P.R. China
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, No. 17, Information Avenue, New Industrial Park, High-tech Zone, Xi'an 710119, Shaanxi Province, P.R. China
| | - Jie Feng
- Department of Neurology, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, No. 87, Xiangya Road, Kaifu District, Changsha 410008, Hunan Province, P.R. China
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17
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Song W, Wang W, Wang F, He X, Li X, Feng L, Cui W, Guo Q. Risk factors for high-stage histological chorioamnionitis among pregnancies with cervical incompetence. J Obstet Gynaecol Res 2024; 50:572-579. [PMID: 38196295 DOI: 10.1111/jog.15880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 12/28/2023] [Indexed: 01/11/2024]
Abstract
AIM The study aimed to identify predictive risk factor to identify high-stage histological chorioamnionitis (HCA) in pregnancies with cervical incompetence (CIC). METHODS A retrospective cohort study was conducted by including 116 pregnant women with cervical incompetence that required prophylactical and therapeutical cerclage. The histopathology examination on placenta was conducted with informed patient consent. All the cases included in this study were divided based on the severity degree of HCA. The demographic characteristic and the parameters related to maternal and fetal outcome were all analyzed. Besides, perioperative parameters of cerclage, including cervical length, cervical morphology, and laboratory indexes were also compared between two groups. Univariate and multivariate logistic regression analysis were used to determine the risk factor of severe chorioamnionitis. RESULTS Severe HCA was significantly associated with cervical morphology, cerclage indication, cerclage type, and cervical length measured via ultrasound and vaginal examination. After adjusted for confounders, V-type funneling and short cervix was indicated as independent risk factors of severe HCA by multivariate logistic regression analysis, respectively. CONCLUSIONS V-type funneling and short cervix may indicate the elevated risk of high-stage HCA. Due to the negative outcomes related with high-stage HCA, appropriate prenatal treatment would improve the pregnancy outcomes in cerclaged population. To facilitate postpartum treatment, placental histological examination should be routinely recommended to identify the high-stage HCA, especially in high risk pregnancies.
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Affiliation(s)
- Wenhui Song
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
| | - Wei Wang
- Hebei Medical University First Affiliated Hospital, Shijiazhuang, Hebei, PR China
| | - Fengjiao Wang
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
| | - Xueqing He
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
| | - Xia Li
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
| | - Li Feng
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
| | - Wenhua Cui
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
| | - Qing Guo
- The Fourth Hospital of Shijiazhuang, Shijiazhuang, Hebei, PR China
- Hebei Key Laboratory of Maternal and Fetal Medicine, Shijiazhuang, Hebei, PR China
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18
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Cao Z, Aharonian F, Axikegu, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Bian W, Bukevich AV, Cao Q, Cao WY, Cao Z, Chang J, Chang JF, Chen AM, Chen ES, Chen HX, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen S, Chen SH, Chen SZ, Chen TL, Chen Y, Cheng N, Cheng YD, Cui MY, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Danzengluobu, Dong XQ, Duan KK, Fan JH, Fan YZ, Fang J, Fang JH, Fang K, Feng CF, Feng H, Feng L, Feng SH, Feng XT, Feng Y, Feng YL, Gabici S, Gao B, Gao CD, Gao Q, Gao W, Gao WK, Ge MM, Geng LS, Giacinti G, Gong GH, Gou QB, Gu MH, Guo FL, Guo XL, Guo YQ, Guo YY, Han YA, Hasan M, He HH, He HN, He JY, He Y, Hor YK, Hou BW, Hou C, Hou X, Hu HB, Hu Q, Hu SC, Huang DH, Huang TQ, Huang WJ, Huang XT, Huang XY, Huang Y, Ji XL, Jia HY, Jia K, Jiang K, Jiang XW, Jiang ZJ, Jin M, Kang MM, Karpikov I, Kuleshov D, Kurinov K, Li BB, Li CM, Li C, Li C, Li D, Li F, Li HB, Li HC, Li J, Li J, Li K, Li SD, Li WL, Li WL, Li XR, Li X, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu DB, Liu H, Liu HD, Liu J, Liu JL, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Luo Q, Luo Y, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Min Z, Mitthumsiri W, Mu HJ, Nan YC, Neronov A, Ou LJ, Pattarakijwanich P, Pei ZY, Qi JC, Qi MY, Qiao BQ, Qin JJ, Raza A, Ruffolo D, Sáiz A, Saeed M, Semikoz D, Shao L, Shchegolev O, Sheng XD, Shu FW, Song HC, Stenkin YV, Stepanov V, Su Y, Sun DX, Sun QN, Sun XN, Sun ZB, Takata J, Tam PHT, Tang QW, Tang R, Tang ZB, Tian WW, Wang C, Wang CB, Wang GW, Wang HG, Wang HH, Wang JC, Wang K, Wang K, Wang LP, Wang LY, Wang PH, Wang R, Wang W, Wang XG, Wang XY, Wang Y, Wang YD, Wang YJ, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu QW, Wu S, Wu XF, Wu YS, Xi SQ, Xia J, Xiang GM, Xiao DX, Xiao G, Xin YL, Xing Y, Xiong DR, Xiong Z, Xu DL, Xu RF, Xu RX, Xu WL, Xue L, Yan DH, Yan JZ, Yan T, Yang CW, Yang CY, Yang F, Yang FF, Yang LL, Yang MJ, Yang RZ, Yang WX, Yao YH, Yao ZG, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Yue H, Zeng HD, Zeng TX, Zeng W, Zha M, Zhang BB, Zhang F, Zhang H, Zhang HM, Zhang HY, Zhang JL, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SB, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zhao XH, Zheng F, Zhong WJ, Zhou B, Zhou H, Zhou JN, Zhou M, Zhou P, Zhou R, Zhou XX, Zhou XX, Zhu BY, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zou YC, Zuo X. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A. Phys Rev Lett 2024; 132:131002. [PMID: 38613275 DOI: 10.1103/physrevlett.132.131002] [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] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/23/2024] [Accepted: 02/12/2024] [Indexed: 04/14/2024]
Abstract
We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at 3.67±0.05±0.15 PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±0.027, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -0.1200±0.0003±0.0341. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components.
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Affiliation(s)
- Zhen Cao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F Aharonian
- Dublin Institute for Advanced Studies, 31 Fitzwilliam Place, 2 Dublin, Ireland
- Max-Planck-Institut for Nuclear Physics, P.O. Box 103980, 69029 Heidelberg, Germany
| | - Axikegu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y X Bai
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y W Bao
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - D Bastieri
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - X J Bi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y J Bi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W Bian
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - A V Bukevich
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - Q Cao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - W Y Cao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Zhe Cao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - J Chang
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J F Chang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - A M Chen
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - E S Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H X Chen
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - Liang Chen
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - Lin Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Long Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - M J Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M L Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Q H Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - S Chen
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - S H Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - S Z Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - T L Chen
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - Y Chen
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - N Cheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y D Cheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Cui
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S W Cui
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - X H Cui
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - Y D Cui
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B Z Dai
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - H L Dai
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Z G Dai
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Danzengluobu
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - X Q Dong
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - K K Duan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J H Fan
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y Z Fan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J Fang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - J H Fang
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - K Fang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C F Feng
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - H Feng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
| | - L Feng
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S H Feng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X T Feng
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - Y Feng
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - Y L Feng
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - S Gabici
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - B Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C D Gao
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - Q Gao
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - W Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W K Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M M Ge
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - L S Geng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - G Giacinti
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - G H Gong
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Q B Gou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M H Gu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - F L Guo
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - X L Guo
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y Q Guo
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y Y Guo
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y A Han
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - M Hasan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H H He
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H N He
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J Y He
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y He
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y K Hor
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B W Hou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C Hou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X Hou
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - H B Hu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Q Hu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S C Hu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- China Center of Advanced Science and Technology, Beijing 100190, China
| | - D H Huang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - T Q Huang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W J Huang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - X T Huang
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - X Y Huang
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y Huang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X L Ji
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - H Y Jia
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - K Jia
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - K Jiang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - X W Jiang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z J Jiang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - M Jin
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - M M Kang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - I Karpikov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - D Kuleshov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - K Kurinov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - B B Li
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - C M Li
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Cheng Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Cong Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - H B Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H C Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Jian Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Jie Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - K Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - S D Li
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - W L Li
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - W L Li
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - X R Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Xin Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Y Z Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Zhe Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Zhuo Li
- School of Physics, Peking University, 100871 Beijing, China
| | - E W Liang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - Y F Liang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - S J Lin
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B Liu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - C Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Liu
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - D B Liu
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H Liu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H D Liu
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - J Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J L Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Liu
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - R Y Liu
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - S M Liu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - W Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y Liu
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y N Liu
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Q Luo
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - Y Luo
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H K Lv
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Q Ma
- School of Physics, Peking University, 100871 Beijing, China
| | - L L Ma
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X H Ma
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J R Mao
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Z Min
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W Mitthumsiri
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - H J Mu
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - Y C Nan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - A Neronov
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - L J Ou
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - P Pattarakijwanich
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Z Y Pei
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - J C Qi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Qi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Q Qiao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J J Qin
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - A Raza
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Ruffolo
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - A Sáiz
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - M Saeed
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Semikoz
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - L Shao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - O Shchegolev
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - X D Sheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F W Shu
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - H C Song
- School of Physics, Peking University, 100871 Beijing, China
| | - Yu V Stenkin
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - V Stepanov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - Y Su
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - D X Sun
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Q N Sun
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - X N Sun
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - Z B Sun
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - J Takata
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - P H T Tam
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - Q W Tang
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - R Tang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Z B Tang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - W W Tian
- University of Chinese Academy of Sciences, 100049 Beijing, China
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - C Wang
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - C B Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - G W Wang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - H G Wang
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - H H Wang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - J C Wang
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Kai Wang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Kai Wang
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - L P Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Y Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - P H Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - R Wang
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - W Wang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - X G Wang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - X Y Wang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Y Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y D Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y J Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z H Wang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - Z X Wang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - Zhen Wang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Zheng Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - D M Wei
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J J Wei
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y J Wei
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - T Wen
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - C Y Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H R Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Q W Wu
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - S Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X F Wu
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y S Wu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - S Q Xi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J Xia
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - G M Xiang
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - D X Xiao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - G Xiao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y L Xin
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y Xing
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - D R Xiong
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Z Xiong
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D L Xu
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - R F Xu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - R X Xu
- School of Physics, Peking University, 100871 Beijing, China
| | - W L Xu
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - L Xue
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - D H Yan
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - J Z Yan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - T Yan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C W Yang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - C Y Yang
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - F Yang
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - F F Yang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - L L Yang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - M J Yang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - R Z Yang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - W X Yang
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y H Yao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z G Yao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Q Yin
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - N Yin
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - X H You
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z Y You
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y H Yu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Q Yuan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - H Yue
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H D Zeng
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - T X Zeng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - W Zeng
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - M Zha
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B B Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - F Zhang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H Zhang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H M Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - H Y Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J L Zhang
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - Li Zhang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - P F Zhang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - P P Zhang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - R Zhang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S B Zhang
- University of Chinese Academy of Sciences, 100049 Beijing, China
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - S R Zhang
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - S S Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - X P Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y F Zhang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Yi Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Yong Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Zhao
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - J Zhao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Zhao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - L Z Zhao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - S P Zhao
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - X H Zhao
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - F Zheng
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - W J Zhong
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - B Zhou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H Zhou
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - J N Zhou
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - M Zhou
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - P Zhou
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - R Zhou
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - X X Zhou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X X Zhou
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - B Y Zhu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - C G Zhu
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - F R Zhu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H Zhu
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - K J Zhu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Y C Zou
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - X Zuo
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
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Zhang K, Xu Y, Chang X, Xu C, Xue W, Ding D, Nie M, Cai H, Xu J, Zhan L, Han J, Cai T, Ju D, Feng L, Zhang X, Yin K. Co-targeting CD47 and VEGF elicited potent anti-tumor effects in gastric cancer. Cancer Immunol Immunother 2024; 73:75. [PMID: 38532108 PMCID: PMC10965671 DOI: 10.1007/s00262-024-03667-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 03/01/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND CD47, serving as an intrinsic immune checkpoint, has demonstrated efficacy as an anti-tumor target in hematologic malignancies. Nevertheless, the clinical relevance of CD47 in gastric cancer and its potential as a therapeutic target remains unclear. METHODS The expression of CD47 in clinical gastric cancer tissues was assessed using immunohistochemistry and Western blot. Patient-derived cells were obtained from gastric cancer tissues and co-cultured with macrophages derived from human peripheral blood mononuclear cells. Flow cytometry analyses were employed to evaluate the rate of phagocytosis. Humanized patient-derived xenografts (Hu-PDXs) models were established to assess the efficacy of anti-CD47 immunotherapy or the combination of anti-CD47 and anti-VEGF therapy in treating gastric cancer. The infiltrated immune cells in the xenograft were analyzed by immunohistochemistry. RESULTS In this study, we have substantiated the high expression of CD47 in gastric cancer tissues, establishing a strong association with unfavorable prognosis. Through the utilization of SIRPα-Fc to target CD47, we have effectively enhanced macrophage phagocytosis of PDCs in vitro and impeded the growth of Hu-PDXs. It is noteworthy that anti-CD47 immunotherapy has been observed to sustain tumor angiogenic vasculature, with a positive correlation between the expression of VEGF and CD47 in gastric cancer. Furthermore, the successful implementation of anti-angiogenic treatment has further augmented the anti-tumor efficacy of anti-CD47 therapy. In addition, the potent suppression of tumor growth, prevention of cancer recurrence after surgery, and significant prolongation of overall survival in Hu-PDX models can be achieved through the simultaneous targeting of CD47 and VEGF using the bispecific fusion protein SIRPα-VEGFR1 or by combining the two single-targeted agents. CONCLUSIONS Our preclinical studies collectively offer substantiation that CD47 holds promise as a prospective target for gastric cancer, while also highlighting the potential of anti-angiogenic therapy to enhance tumor responsiveness to anti-CD47 immunotherapy.
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Affiliation(s)
- Kaiqi Zhang
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Yuan Xu
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Xusheng Chang
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Caili Xu
- Department of Biological Medicines & Shanghai Engineering Research Center of Immunotherapeutics, School of Pharmacy, Fudan University, Shanghai, 201203, China
| | - Wenjing Xue
- Department of Biological Medicines & Shanghai Engineering Research Center of Immunotherapeutics, School of Pharmacy, Fudan University, Shanghai, 201203, China
| | - Dan Ding
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Mingming Nie
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Hui Cai
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Jun Xu
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Lu Zhan
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Jiangbo Han
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Tiancai Cai
- Department of Sanatorium and Nursing Section, Xiamen Special Service Health Center, Xiamen, 361005, China
| | - Dianwen Ju
- Department of Biological Medicines & Shanghai Engineering Research Center of Immunotherapeutics, School of Pharmacy, Fudan University, Shanghai, 201203, China
| | - Li Feng
- Department of Endoscopy Center, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, China.
| | - Xuyao Zhang
- Department of Biological Medicines & Shanghai Engineering Research Center of Immunotherapeutics, School of Pharmacy, Fudan University, Shanghai, 201203, China.
| | - Kai Yin
- Department of Gastrointestinal Surgery, Changhai Hospital, Naval Medical University, Shanghai, 200433, China.
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Shu W, Li J, Liu JX, Zhu C, Wang T, Feng L, Ouyang R, Li WX. Structure Sensitivity of Metal Catalysts Revealed by Interpretable Machine Learning and First-Principles Calculations. J Am Chem Soc 2024; 146:8737-8745. [PMID: 38483446 DOI: 10.1021/jacs.4c01524] [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: 03/28/2024]
Abstract
The nature of the active sites and their structure sensitivity are the keys to rational design of efficient catalysts but have been debated for almost one century in heterogeneous catalysis. Though the Brønsted-Evans-Polanyi (BEP) relationship along with linear scaling relation has long been used to study the reactivity, explicit geometry, and composition properties are absent in this relationship, a fact that prevents its exploration in structure sensitivity of supported catalysts. In this work, based on interpretable multitask symbolic regression and a comprehensive first-principles data set, we discovered a structure descriptor, the topological under-coordinated number mediated by number of valence electrons and the lattice constant, to successfully address the structure sensitivity of metal catalysts. The database used for training, testing, and transferability investigation includes bond-breaking barriers of 20 distinct chemical bonds over 10 transition metals, two metal crystallographic phases, and 17 different facets. The resulting 2D descriptor composing the structure term and the reaction energy term shows great accuracy to predict the reaction barriers and generalizability over the data set with diverse chemical bonds in symmetry, bond order, and steric hindrance. The theory is physical and concise, providing a constructive strategy not only to understand the structure sensitivity but also to decipher the entangled geometric and electronic effects of metal catalysts. The insights revealed are valuable for the rational design of the site-specific metal catalysts.
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Affiliation(s)
- Wu Shu
- Department of Chemical Physics, Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, 230026, China
| | - Jiancong Li
- Hefei National Research Center for Physical Science at the Microscale, University of Science and Technology of China, Hefei, 230026, China
| | - Jin-Xun Liu
- Department of Chemical Physics, Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, 230026, China
| | - Chuwei Zhu
- Hefei National Research Center for Physical Science at the Microscale, University of Science and Technology of China, Hefei, 230026, China
| | - Tairan Wang
- Department of Chemical Physics, Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, 230026, China
| | - Li Feng
- Department of Chemical Physics, Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, 230026, China
| | - Runhai Ouyang
- Materials Genome Institute, Shanghai University, Shanghai, 200444, China
| | - Wei-Xue Li
- Department of Chemical Physics, Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, 230026, China
- Hefei National Laboratory, University of Science and Technology of China, Hefei, 230026, China
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21
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Dai Y, Yuan Y, Bi F, Feng L, Li J, Hu K, Chen S, Huang Q, Li J, Long L, Xiao B, Xie Y, Song Y. Clinical features of adult patients with positive NMDAR-IgG coexisting with MOG-IgG. Neurol Sci 2024:10.1007/s10072-024-07474-z. [PMID: 38523205 DOI: 10.1007/s10072-024-07474-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] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/13/2024] [Indexed: 03/26/2024]
Abstract
INTRODUCTION This study was designed to analyze clinical and radiographic features of adult patients coexisting with NMDAR-IgG and MOG-IgG. METHODS Eleven adult patients coexisting with NMDAR-IgG and MOG-IgG were collected from Xiangya Hospital, Central South University, between June 2017 and December 2021. Fifty-five patients with anti-NMDAR encephalitis and 49 with MOG-AD were served as controls. RESULTS Onset age was 27 (IQR 20-34) years old. Seizures and psychotic symptoms were prominent symptoms. Ten of eleven patients presented abnormal T2/FLAIR hyperintensity, mainly involving the cortex, brainstem, and optic nerve. Compared with the NMDAR IgG ( +)/MOG IgG ( -) group, the NMDAR IgG ( +)/MOG IgG ( +) group showed more ataxia symptoms (27.3% vs. 3.6%, P = 0.037), while more T2/FLAIR hyperintensity lesions were found in the brainstem (54.5% vs. 7.3%, P < 0.001) and optic nerve (27.3% vs. 1.8%, P = 0.011) with more abnormal MRI patterns (90.9% vs. 41.8%, P = 0.003). In comparison with the NMDAR IgG ( -)/MOG IgG ( +) group, the NMDAR IgG ( +)/MOG IgG ( +) group had more seizures (72.7% vs. 24.5%, P = 0.007) and mental symptoms (45.5% vs. 0, P < 0.001). The NMDAR IgG ( +)/MOG IgG ( +) group tended to be treated with corticosteroids alone (63.6% vs. 20.0%, P = 0.009), more prone to recur (36.5% vs. 7.3%, P = 0.028) and lower mRS score (P = 0.036) at the last follow-up than pure anti-NMDAR encephalitis. CONCLUSION The symptoms of the NMDAR IgG ( +)/MOG IgG ( +) group were more similar to anti-NMDAR encephalitis, while MRI patterns overlapped more with MOG-AD. Detecting both NMDAR-IgG and MOG-IgG maybe warranted in patients with atypical encephalitis symptoms and demyelinating lesions in infratentorial regions.
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Affiliation(s)
- Yuwei Dai
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Yu Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Department of Neurology, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, 519000, Guangdong Province, China
| | - Fangfang Bi
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Department of Neurology, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, 519000, Guangdong Province, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Jing Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Kai Hu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Si Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Qing Huang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Juan Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Lili Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China
| | - Yuanyuan Xie
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China.
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China.
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, 410008, Hunan Province, China.
| | - Yanmin Song
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China.
- Department of Emergency Medicine, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China.
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22
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Feng L, Shuai L, Zhou Y, Zhang X, Sun J. Improving the green space arrangement in residential areas from the perspective of tree leaf temperature utilizing scenario simulation in ENVI-met. Sci Total Environ 2024; 918:170650. [PMID: 38320699 DOI: 10.1016/j.scitotenv.2024.170650] [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: 01/09/2024] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/12/2024]
Abstract
Studying the differences in leaf temperature and their mechanisms can help us accurately understand the microenvironment in which plants are located. In this paper, typical residential areas in Jianye District, Nanjing, Jiangsu Province, China, are selected as the research area, we investigated the suitability of green space configurations from the perspective of tree leaf temperature of residential areas based on the scenario simulation in ENVI-met. Firstly, twenty abstract models were constructed, including four kinds of aspect ratio of trees (ARTs) which can be used to indicate the different green space arrangement and two typical tree species, camphora tree and platanus tree. And then three aspects were discussed including impacts of different Aspect Ratio of Trees (ART), different house-side configurations on tree leaf temperature and the relationship between temperature of tree leaves and land surface temperature (ΔSurfT) and the thermal comfort index of physiological equivalent temperature (ΔPET). The results showed that B-1 (camphor tree, ART = 2) demonstrates the most effective cooling effect in summer, with ΔPET of 3.09 °C and ΔSurfT of 3.34 °C. In winter, A-1 (platanus tree, ART = 2) proves to be the most effective in enhancing thermal comfort (ΔPET = -0.15 °C), while B-1 excels in improving surface temperature (ΔSurfT = 0.55 °C). In all, for residential area, especially in summer, planting dense camphora trees is better than platanus trees and house-side green space was very necessary. This research can help to determine appropriate tree species and green space configuration strategies for future residential areas to enhance thermal comfort.
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Affiliation(s)
- Li Feng
- College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China.
| | - Linru Shuai
- College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
| | - Yanan Zhou
- College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China.
| | - Xiao Zhang
- College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
| | - Jiaxin Sun
- College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
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23
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He H, Li Y, Chen Y, Chen J, Li Z, Li L, Shi D, Zhang X, Shi H, Xue M, Feng L. NLRP1 restricts porcine deltacoronavirus infection via IL-11 inhibiting the phosphorylation of the ERK signaling pathway. J Virol 2024; 98:e0198223. [PMID: 38411106 PMCID: PMC10949457 DOI: 10.1128/jvi.01982-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/08/2024] [Indexed: 02/28/2024] Open
Abstract
Continuously emerging highly pathogenic coronaviruses remain a major threat to human and animal health. Porcine deltacoronavirus (PDCoV) is a newly emerging enterotropic swine coronavirus that causes large-scale outbreaks of severe diarrhea disease in piglets. Unlike other porcine coronaviruses, PDCoV has a wide range of species tissue tropism, including primary human cells, which poses a significant risk of cross-species transmission. Nucleotide-binding oligomerization domain-like receptor (NLR) family pyrin domain-containing 1 (NLRP1) has a key role in linking host innate immunity to microbes and the regulation of inflammatory pathways. We now report a role for NLRP1 in the control of PDCoV infection. Overexpression of NLRP1 remarkably suppressed PDCoV infection, whereas knockout of NLRP1 led to a significant increase in PDCoV replication. A mechanistic study revealed that NLRP1 suppressed PDCoV replication in cells by upregulating IL-11 expression, which in turn inhibited the phosphorylation of the ERK signaling pathway. Furthermore, the ERK phosphorylation inhibitor U0126 effectively hindered PDCoV replication in pigs. Together, our results demonstrated that NLRP1 exerted an anti-PDCoV effect by IL-11-mediated inhibition of the phosphorylation of the ERK signaling pathway, providing a novel antiviral signal axis of NLRP1-IL-11-ERK. This study expands our understanding of the regulatory network of NLRP1 in the host defense against virus infection and provides a new insight into the treatment of coronaviruses and the development of corresponding drugs.IMPORTANCECoronavirus, which mainly infects gastrointestinal and respiratory epithelial cells in vivo, poses a huge threat to both humans and animals. Although porcine deltacoronavirus (PDCoV) is known to primarily cause fatal diarrhea in piglets, reports detected in plasma samples from Haitian children emphasize the potential risk of animal-to-human spillover. Finding effective therapeutics against coronaviruses is crucial for controlling viral infection. Nucleotide-binding oligomerization-like receptor (NLR) family pyrin domain-containing 1 (NLRP1), a key regulatory factor in the innate immune system, is highly expressed in epithelial cells and associated with the pathogenesis of viruses. We demonstrate here that NLRP1 inhibits the infection of the intestinal coronavirus PDCoV through IL-11-mediated phosphorylation inhibition of the ERK signaling pathway. Furthermore, the ERK phosphorylation inhibitor can control the infection of PDCoV in pigs. Our study emphasizes the importance of NLRP1 as an immune regulatory factor and may open up new avenues for the treatment of coronavirus infection.
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Affiliation(s)
- Haojie He
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Yongfeng Li
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Yunyan Chen
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Jianfei Chen
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Zhongyuan Li
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Liang Li
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Da Shi
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Xin Zhang
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Hongyan Shi
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Mei Xue
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
| | - Li Feng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, Heilongjiang, China
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Zhang Y, Feng L, Hemu X, Tan NH, Wang Z. OSMAC Strategy: A promising way to explore microbial cyclic peptides. Eur J Med Chem 2024; 268:116175. [PMID: 38377824 DOI: 10.1016/j.ejmech.2024.116175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/12/2024] [Accepted: 01/22/2024] [Indexed: 02/22/2024]
Abstract
Microbial secondary metabolites are pivotal for the development of novel drugs. However, conventional culture techniques, have left a vast array of unexpressed biosynthetic gene clusters (BGCs) in microorganisms, hindering the discovery of metabolites with distinct structural features and diverse biological functions. To address this limitation, several innovative strategies have been emerged. The "One Strain Many Compounds" (OSMAC) strategy, which involves altering microbial culture conditions, has proven to be particularly effective in mining numerous novel secondary metabolites for the past few years. Among these, microbial cyclic peptides stand out. These peptides often comprise rare amino acids, unique chemical structures, and remarkable biological function. With the advancement of the OSMAC strategy, a plethora of new cyclic peptides have been identified from diverse microbial genera. This work reviews the progress in mining novel compounds using the OSMAC strategy and the applications of this strategy in discovering 284 microbial cyclic peptides from 63 endophytic strains, aiming to offer insights for the further explorations into novel active cyclic peptides.
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Affiliation(s)
- Yu Zhang
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 211198, China
| | - Li Feng
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 211198, China
| | - Xinya Hemu
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 211198, China
| | - Ning-Hua Tan
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
| | - Zhe Wang
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
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25
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Xue WL, Li GQ, Chen H, Han YC, Feng L, Wang L, Gu XL, Hu SY, Deng YH, Tan L, Dove MT, Li W, Zhang J, Dong H, Chen Z, Deng WH, Xu G, Wang G, Wan CQ. Melt-quenched glass formation of a family of metal-carboxylate frameworks. Nat Commun 2024; 15:2040. [PMID: 38448429 PMCID: PMC10917788 DOI: 10.1038/s41467-024-46311-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 02/15/2024] [Indexed: 03/08/2024] Open
Abstract
Metal-organic framework (MOF) glasses are an emerging class of glasses which complement traditional inorganic, organic and metallic counterparts due to their hybrid nature. Although a few zeolitic imidazolate frameworks have been made into glasses, how to melt and quench the largest subclass of MOFs, metal carboxylate frameworks, into glasses remains challenging. Here, we develop a strategy by grafting the zwitterions on the carboxylate ligands and incorporating organic acids in the framework channels to enable the glass formation. The charge delocalization of zwitterion-acid subsystem and the densely filled channels facilitate the coordination bonding mismatch and thus reduce the melting temperature. Following melt-quenching realizes the glass formation of a family of carboxylate MOFs (UiO-67, UiO-68 and DUT-5), which are usually believed to be un-meltable. Our work opens up an avenue for melt-quenching porous molecular solids into glasses.
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Affiliation(s)
- Wen-Long Xue
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
- Anorganische Chemie, Fakultät für Chemie & Chemische Biologie, Technische Universität Dortmund, Otto-Hahn Straße 6, Dortmund, 44227, Germany
| | - Guo-Qiang Li
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Hui Chen
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
- School of Chemistry and Chemical Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Yu-Chen Han
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Li Feng
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Lu Wang
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Xiao-Ling Gu
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Si-Yuan Hu
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Yu-Heng Deng
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Lei Tan
- Department of Physics, School of Sciences, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Martin T Dove
- College of Computer Science, Sichuan University, Chengdu, 610065, Sichuan, China
| | - Wei Li
- School of Materials Science and Engineering & Tianjin Key Laboratory of Metal and Molecule-Based Material Chemistry, Nankai University, Tianjin, 300350, China.
| | - Jiangwei Zhang
- College of Energy Material and Chemistry, Inner Mongolia University, Hohhot, 010021, China.
| | - Hongliang Dong
- Center for High Pressure Science and Technology Advanced Research, Pudong, Shanghai, 201203, China
| | - Zhiqiang Chen
- Center for High Pressure Science and Technology Advanced Research, Pudong, Shanghai, 201203, China
| | - Wei-Hua Deng
- State Key Laboratory of Structural Chemistry, and Fujian Provincial Key Laboratory of Materials and Techniques toward Hydrogen Energy, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, China
| | - Gang Xu
- State Key Laboratory of Structural Chemistry, and Fujian Provincial Key Laboratory of Materials and Techniques toward Hydrogen Energy, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, China.
| | - Guo Wang
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China
| | - Chong-Qing Wan
- Beijing Key Laboratory for Optical Materials and Photonic Devices, Department of Chemistry, Capital Normal University, 100048, Beijing, China.
- State Key Laboratory of Structural Chemistry, and Fujian Provincial Key Laboratory of Materials and Techniques toward Hydrogen Energy, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, China.
- Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Department of Chemistry, Tsinghua University, 100084, Beijing, China.
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26
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Lenertz M, Li Q, Armstrong Z, Scheiwiller A, Ni G, Wang J, Feng L, MacRae A, Yang Z. Magnetic Multienzyme@Metal-Organic Material for Sustainable Biodegradation of Insoluble Biomass. ACS Appl Mater Interfaces 2024; 16:11617-11626. [PMID: 38410049 DOI: 10.1021/acsami.4c00651] [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] [Indexed: 02/28/2024]
Abstract
Biodegradation of insoluble biomass such as cellulose via carbohydrase enzymes is an effective approach to break down plant cell walls and extract valuable materials therein. Yet, the high cost and poor reusability of enzymes are practical concerns. We recently proved that immobilizing multiple digestive enzymes on metal-organic materials (MOMs) allows enzymes to be reused via gravimetric separation, improving the cost efficiency of cereal biomass degradation [ACS Appl. Mater. Interfaces 2021, 13, 36, 43085-43093]. However, this strategy cannot be adapted for enzymes whose substrates or products are insoluble (e.g., cellulose crystals). Recently, we described an alternative approach based on magnetic metal-organic frameworks (MOFs) using model enzymes/substrates [ACS Appl. Mater. Interfaces 2020, 12, 37, 41794-41801]. Here, we aim to prove the effectiveness of combining these two strategies in cellulose degradation. We immobilized multiple carbohydrase enzymes that cooperate in cellulose degradation via cocrystallization with Ca2+, a carboxylate ligand (BDC) in the absence and presence of magnetic nanoparticles (MNPs). We then compared the separation efficiency and enzyme reusability of the resultant multienzyme@Ca-BDC and multienzyme@MNP-Ca-BDC composites via gravimetric and magnetic separation, respectively, and found that, although both composites were effective in cellulose degradation in the first round, the multienzyme@MNP-Ca-BDC composites displayed significantly enhanced reusability. This work provides the first experimental demonstration of using magnetic solid supports to immobilize multiple carbohydrase enzymes simultaneously and degrade cellulose and promotes green/sustainable chemistry in three ways: (1) reusing the enzymes saves energy/sources to prepare them, (2) the synthetic conditions are "green" without generating unwanted wastes, and (3) using our composites to degrade cellulose is the first step of extracting valuable materials from sustainable biomasses such as plants whose growth does not rely on nonregeneratable resources.
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Affiliation(s)
- Mary Lenertz
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
| | - Qiaobin Li
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
| | - Zoe Armstrong
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
| | - Allison Scheiwiller
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
| | - Gigi Ni
- Department of Chemistry and Chemical Biology, Harvard University, Boston, Massachusetts 02138, United States
| | - Jien Wang
- California State University, San Marcos, San Marcos, California 92096, United States
| | - Li Feng
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
| | - Austin MacRae
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
| | - Zhongyu Yang
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58102, United States
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Liu Q, Wu J, Gao N, Zhang X, Gao M, Zhang X, Guo L, Wu Y, Shi D, Shi H, Chen J, Feng L. A novel antigenic epitope identified on the accessory protein NS6 of porcine deltacoronavirus. Virus Res 2024; 341:199329. [PMID: 38262568 PMCID: PMC10840108 DOI: 10.1016/j.virusres.2024.199329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/18/2024] [Accepted: 01/20/2024] [Indexed: 01/25/2024]
Abstract
Porcine deltacoronavirus (PDCoV) is a novel enteric coronavirus that can cause vomiting, watery diarrhea in pigs and the death of piglets. The open reading frame (ORF) 5 is one of the accessory genes in PDCoV genome and encodes an accessory protein NS6. To date, the function of NS6 is still unclear. In this study, the recombinant NS6 was successfully expressed in prokaryotic expression system and purified. To prepare monoclonal antibody (mAb), six-week-old female BALB/c mice were primed subcutaneously with purified NS6. A novel mouse mAb against NS6 was obtained and designated as 3D5. The isotype of 3D5 is IgG2b with kappa (κ) light chain. 3D5 can specifically recognizes the natural NS6 in swine testis (ST) cells infected with PDCoV and expressed NS6 in human embryonic kidney 293T (HEK 293T) cells transfected with mammalian vector. The minimal linear B cell epitope recognised by 3D5 on NS6 was 25VPELIDPLVK34 determined by peptide scanning and named EP-3D5. The sequence of EP-3D5 is completely conserved among PDCoV strains. Moreover, six to nine residues of EP-3D5 were identified to be conserved in non-PDCoV strains. These results provide valuable insights into the antigenic structure and function of NS6 in virus pathogenesis, and aid for the development of PDCoV epitope-associated diagnostics and vaccine design.
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Affiliation(s)
- Qiuge Liu
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Jianxiao Wu
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Na Gao
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China; College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing 163319, China
| | - Xiaorong Zhang
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China; College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing 163319, China
| | - Mingze Gao
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Xin Zhang
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Longjun Guo
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Yang Wu
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Da Shi
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Hongyan Shi
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Jianfei Chen
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China.
| | - Li Feng
- Division of Swine Digestive System Infectious Diseases, State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China.
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28
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Feng L, Wang L, Hernández-Wolters B, Prabahar K, Velu P, Kord-Varkaneh H. The impact of medroxyprogesterone acetate on lipid profiles in Women: A time and dose-response meta-analysis of randomized controlled trials. Diabetes Res Clin Pract 2024; 209:111073. [PMID: 38142749 DOI: 10.1016/j.diabres.2023.111073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 12/26/2023]
Abstract
BACKGROUND The effect of MPA on the lipid profile and CVD risk is still controversial; hence, this comprehensive dose-response meta-analysis of randomized controlled trials was conducted to assess the effect of MPA on lipid profiles in women. METHODS A comprehensive search was conducted in the following databases: Web of Science, Scopus, PubMed/Medline, and Embase, up to October 20, 2023. A random-effects meta-analysis approach based on the DerSimonian and Laird method was used to compute the combined estimates of the intervention's impact on the lipid profile. RESULTS 35 eligible studies with 58 arms were included in our meta-analyses analysis. Combined effect sizes suggested a significant effect of MPA on total cholesterol (TC) levels (WMD: -3.43 mg/dL, 95 % CI: -5.38 to -1.48, p < 0.001), HDL-C levels (WMD: -3.34 mg/dL, 95 % CI: -3.77 to -2.91, p < 0.001), and triglyceride (TG) levels (WMD: -9.13 mg/dL, 95 % CI: -10.92 to -7.33, p < 0.001). The subgroup meta-analysis revealed a more substantial reduction in TC in studies with dosages > 2.5 mg/day (WMD: -4.10 mg/dL), mean participant age lower than 60 years (WMD: -3.80 mg/dL), mean BMI lower than 25 kg/m2 (WMD: -5.61 mg/dL), duration of intervention of 12 months or more (WMD: -3.98 mg/dL), and when the baseline TC value was equal to or greater than 200 mg/dL (WMD: -4.13 mg/dL). CONCLUSIONS The current meta-analysis showed a statistically significant decrease in TC, TG, and HDL-C levels and a non-significant increase in LDL-C levels after MPA administration in women.
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Affiliation(s)
- Li Feng
- Department of Rehabilitation Medicine, The People's Hospital of Huaiyin. Jinan, Jinan-250001, China
| | - Le Wang
- Department of Emergency Medicine, The People's Hospital of Huaiyin. Jinan, Jinan-250001, China.
| | | | - Kousalya Prabahar
- Department of Pharmacy Practice, Faculty of Pharmacy, University of Tabuk, Tabuk, Saudi Arabia
| | - Periyannan Velu
- Galileovasan Offshore and Research and Development Pvt. Ltd., Nagapattinam, Tamil Nadu, India
| | - Hamed Kord-Varkaneh
- Department of Nutrition and Food Hygiene, School of Medicine, Nutrition Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
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29
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Zhao M, Shen D, Fan L, Hong K, Feng L, Benefield BC, Allen BD, Lee DC, Kim D. Incorporation of view sharing and KWIC filtering into GRASP-Pro improves spatial resolution of single-shot, multi-TI, late gadolinium enhancement MRI. NMR Biomed 2024; 37:e5059. [PMID: 37872862 PMCID: PMC10922561 DOI: 10.1002/nbm.5059] [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: 05/08/2023] [Revised: 08/14/2023] [Accepted: 09/19/2023] [Indexed: 10/25/2023]
Abstract
While single-shot late gadolinium enhancement (LGE) is useful for imaging patients with arrhythmia and/or dyspnea, it produces low spatial resolution. One approach to improve spatial resolution is to accelerate data acquisition using compressed sensing (CS). Our previous work described a single-shot, multi-inversion time (TI) LGE pulse sequence using radial k-space sampling and CS, but over-regularization resulted in significant image blurring that muted the benefits of data acceleration. The purpose of the present study was to improve the spatial resolution of the single-shot, multi-TI LGE pulse sequence by incorporating view sharing (VS) and k-space weighted contrast (KWIC) filtering into a GRASP-Pro reconstruction. In 24 patients (mean age = 61 ± 16 years; 9/15 females/males), we compared the performance of our improved multi-TI LGE and standard multi-TI LGE, where clinical standard LGE was used as a reference. Two clinical raters independently graded multi-TI images and clinical LGE images visually on a five-point Likert scale (1, nondiagnostic; 3, clinically acceptable; 5, best) for three categories: the conspicuity of myocardium or scar, artifact, and noise. The summed visual score (SVS) was defined as the sum of the three scores. Myocardial scar volume was quantified using the full-width at half-maximum method. The SVS was not significantly different between clinical breath-holding LGE (median 13.5, IQR 1.3) and multi-TI LGE (median 12.5, IQR 1.6) (P = 0.068). The myocardial scar volumes measured from clinical standard LGE and multi-TI LGE were strongly correlated (coefficient of determination, R2 = 0.99) and in good agreement (mean difference = 0.11%, lower limit of the agreement = -2.13%, upper limit of the agreement = 2.34%). The inter-rater agreement in myocardial scar volume quantification was strong (intraclass correlation coefficient = 0.79). The incorporation of VS and KWIC into GRASP-Pro improved spatial resolution. Our improved 25-fold accelerated, single-shot LGE sequence produces clinically acceptable image quality, multi-TI reconstruction, and accurate myocardial scar volume quantification.
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Affiliation(s)
- Mingyue Zhao
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
| | | | - Lexiaozi Fan
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Kyungpyo Hong
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, NY
| | - Brandon C. Benefield
- Division of Cardiology, Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Bradley D. Allen
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Daniel C. Lee
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Division of Cardiology, Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Daniel Kim
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
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30
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Huang B, Zhang Z, Sui W, Zhao L, Li Y, Feng L, Yang D, Zhou Y. Effectiveness of a novel rat model of off-target PLA2R1 knockout to renal impairment. Genomics 2024; 116:110796. [PMID: 38237745 DOI: 10.1016/j.ygeno.2024.110796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/24/2023] [Accepted: 01/14/2024] [Indexed: 01/21/2024]
Abstract
Phospholipase A2 receptor 1 (PLA2R1) plays a crucial role in various diseases, including membranous nephropathy. However, the precise implications of PLA2R1 deficiency remain poorly understood. In this study, we created PLA2R1 knockout rats to explore potential consequences resulting from the loss of the PLA2R1 gene. Unexpectedly, our PLA2R1 knockout rats exhibited symptoms resembling those of chronic kidney disease after an 8-week observation period. Notably, several rats developed persistent proteinuria, a hallmark of renal dysfunction. Immunohistochemical and immunofluorescence analyses revealed insignificant glomerular fibrosis, reduced podocyte count, and augmented glomerular expression of complement C3 (C3) compared to immunoglobin A (IgA) and immunoglobin G(IgG) in the rat model. These findings suggest that the loss of PLA2R1 may contribute to the pathogenesis of membranous nephropathy and related conditions. Our knockout rat model provides a valuable tool for investigating the underlying pathology of PLA2R1-associated diseases, and may facilitate the development of targeted therapies for membranous nephropathy and other related disorders.
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Affiliation(s)
- Bo Huang
- Shanxi Genetic Engineering Center for Experimental Animal Models, The Fifth Hospital (Shanxi Provincial People's Hospital) of Shanxi Medical University, Taiyuan, Shanxi 030012, China; Laboratory Animal Center, Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China; Nephrology Key Laboratory of Shanxi Province, Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China; Hospital of integrated traditional Chinese and Western medicine in Shanxi province, Taiyuan, Shanxi 030012, China.
| | - Zitong Zhang
- Shanxi Genetic Engineering Center for Experimental Animal Models, The Fifth Hospital (Shanxi Provincial People's Hospital) of Shanxi Medical University, Taiyuan, Shanxi 030012, China; Laboratory Animal Center, Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China; Hospital of integrated traditional Chinese and Western medicine in Shanxi province, Taiyuan, Shanxi 030012, China
| | - Wendong Sui
- Department of Physiology, School of Basic Medicine, Shanxi Medical University, Taiyuan, Shanxi 030001, China
| | - Lu Zhao
- Laboratory Animal Center, Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China
| | - Yinyin Li
- Laboratory Animal Center, Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China
| | - Li Feng
- Laboratory Animal Center, Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China
| | - Daihe Yang
- Department of Anesthesiology, the Affiliated Second People's Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou 350003, China
| | - Yun Zhou
- Shanxi Genetic Engineering Center for Experimental Animal Models, The Fifth Hospital (Shanxi Provincial People's Hospital) of Shanxi Medical University, Taiyuan, Shanxi 030012, China; Hospital of integrated traditional Chinese and Western medicine in Shanxi province, Taiyuan, Shanxi 030012, China.
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31
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Xu X, Zhang Q, Wang X, Jin J, Wu C, Feng L, Yang X, Zhao M, Chen Y, Lu S, Zheng Z, Lan X, Wang Y, Zheng Y, Lu X, Zhang Q, Zhang J. Discovery of a potent and highly selective inhibitor of SIRT6 against pancreatic cancer metastasis in vivo. Acta Pharm Sin B 2024; 14:1302-1316. [PMID: 38487000 PMCID: PMC10935062 DOI: 10.1016/j.apsb.2023.11.014] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/05/2023] [Accepted: 10/18/2023] [Indexed: 03/17/2024] Open
Abstract
Pancreatic cancer, one of the most aggressive malignancies, has no effective treatment due to the lack of targets and drugs related to tumour metastasis. SIRT6 can promote the migration of pancreatic cancer and could be a potential target for antimetastasis of pancreatic cancer. However, highly selective and potency SIRT6 inhibitor that can be used in vivo is yet to be discovered. Here, we developed a novel SIRT6 allosteric inhibitor, compound 11e, with maximal inhibitory potency and an IC50 value of 0.98 ± 0.13 μmol/L. Moreover, compound 11e exhibited significant selectivity against other histone deacetylases (HADC1‒11 and SIRT1‒3) at concentrations up to 100 μmol/L. The allosteric site and the molecular mechanism of inhibition were extensively elucidated by cocrystal complex structure and dynamic structural analyses. Importantly, we confirmed the antimetastatic function of such inhibitors in four pancreatic cancer cell lines as well as in two mouse models of pancreatic cancer liver metastasis. To our knowledge, this is the first study to reveal the in vivo effects of SIRT6 inhibitors on liver metastatic pancreatic cancer. It not only provides a promising lead compound for subsequent inhibitor development targeting SIRT6 but also provides a potential approach to address the challenge of metastasis in pancreatic cancer.
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Affiliation(s)
- Xinyuan Xu
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and BioinformaticsCenter, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Qian Zhang
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and BioinformaticsCenter, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xufeng Wang
- Department of General Surgery, Huashan Hospital, Cancer Metastasis Institute, Fudan University, Shanghai 200040, China
| | - Jing Jin
- Institute of Immunology and the CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medicine and Medical Center, University of Science and Technology of China, Hefei 230026, China
| | - Chengwei Wu
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and BioinformaticsCenter, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Li Feng
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and BioinformaticsCenter, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
| | - Xiuyan Yang
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Mingzhu Zhao
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
| | - Yingyi Chen
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shaoyong Lu
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zhen Zheng
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xiaobing Lan
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
| | - Yi Wang
- Institute of Immunology and the CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medicine and Medical Center, University of Science and Technology of China, Hefei 230026, China
| | - Yan Zheng
- Department of Pancreatic Surgery, Shanghai General Hospital, Shanghai Key Laboratory of Pancreatic Disease, Institute of Pancreatic Disease, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Xuefeng Lu
- Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
| | - Qiufen Zhang
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and BioinformaticsCenter, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Feng L, Wang Y, Niu LJ. [Ultrasound-guided percutaneous thermal ablation assisted by artificial ascites and soft tissue edema in the treatment of special-region hepatic tumors]. Zhonghua Zhong Liu Za Zhi 2024; 46:155-160. [PMID: 38418190 DOI: 10.3760/cma.j.cn112152-20231026-00269] [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: 03/01/2024]
Abstract
Objective: To explore the application value and operation skills of ultrasound-guided percutaneous thermal ablation assisted by artificial ascites or/and soft tissue edema in the treatment of special hepatic tumors located nearby the diaphragm, heart, stomach, gastrointestinal tract, gall bladder, kidney, and other organs. Methods: The clinical data of 132 patients with special-region hepatic tumors treated with ultrasound-guided percutaneous thermal ablation aided by artificial ascites and/or artificial soft tissue edema were retrospectively analyzed. Intraoperative contrast-enhanced ultrasound was used to guide ablation when necessary. During the operation, the ablation needle was lifted or pressed down, or the direction of the needle handle was changed to protect vital organs. The technical success rate of artificial ascites and/or soft tissue edema formation, the complete in activation rate of the tumor, and the complications were observed. Results: There were 74 patients (108 lesions) treated with radiofrequency ablation and 58 patients (82 lesions) treated with microwave ablation. Among them, 81 cases was successfully injected artificial abdominal ascites, with a water volume of (1 301±685) ml; artificial soft tissue edema was successfully formed for 19 patients, with a water volume of (534±258) ml. Both artificial ascites and artificial soft tissue edema were built for 30 patients. The success rate of this hydro-isolation technique was 98.5% (130/132). 129 patients successfully completed the treatment, and the complete inactivation rate of the tumor was 92.5% (172/186). The average postoperative hospital stay was three days. No patient had serious complications, such as surface tumor rupture, gastrointestinal injury, or diaphragm perforation. Conclusions: For hepatic tumors located adjacent to other organs such as the diaphragm, heart, gastrointestinal tract, gallbladder, and kidney, the application of artificial ascites and/or artificial soft tissue edema can reduce the damage to these organs, as well as reduce the possibility of tumor rupture and diaphragm perforation. These methods are safe and effective in ultrasound-guided percutaneous thermal ablation.
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Affiliation(s)
- L Feng
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Wang
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L J Niu
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Yu M, Feng L, Gan Z, Hua Y, Wu H, Ganss B, Yang H. Tubular Nanoclay-Enhanced Calcium Phosphate Mineralization and Assembly to Impart High Stiffness and Antimicrobial Properties. ACS Appl Mater Interfaces 2024; 16:9190-9200. [PMID: 38349042 DOI: 10.1021/acsami.3c19424] [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] [Indexed: 02/23/2024]
Abstract
Achieving superior mechanical properties of composite materials in artificially engineered materials is a great challenge due to technical bottlenecks in the size and morphological modulation of inorganic nanominerals. Hence, a "bioprocess-inspired fabrication" is proposed to create multilayered organic-inorganic columnar structures. The sequential assembly of halloysite nanotubes (HNTs), polyelectrolytes (PAAs), and calcium phosphates (CaPs) results in organic-inorganic structures. PAA plays a crucial role in controlling the formation of CaP, guiding it into amorphous particles with smaller nanosizes. The introduction of HNT induces the assembly and maturation of CaP-PAA, leading to the formation of a highly crystalline hydroxyapatite. Poly(vinyl alcohol) was then woven into HNT-encapsulated hydroxyapatite nanorods, resulting in composite materials with basic hierarchical structures across multiple scales. The fabricated composite exhibits exceptional hardness (4.27 ± 0.33 GPa) and flexural strength (101.25 ± 1.72 MPa), surpassing those of most previously developed biological hard tissue materials. Additionally, the composite demonstrates effective antibacterial properties and corrosion resistance, attributed to the dense crystalline phase of CaP. This innovative approach showcases the potential of clay minerals, particularly HNT, in the advancement of biomaterial design. The outstanding mechanical and antimicrobial properties of clay-based composites make them a promising candidate for applications in hard tissue repair, offering versatility in biomedicine and engineering.
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Affiliation(s)
- Menghan Yu
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, China
- Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
- Laboratory of Advanced Mineral Materials, China University of Geosciences, Wuhan 430074, China
| | - Li Feng
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, China
- Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
- Laboratory of Advanced Mineral Materials, China University of Geosciences, Wuhan 430074, China
| | - Zongle Gan
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, China
- Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
- Laboratory of Advanced Mineral Materials, China University of Geosciences, Wuhan 430074, China
| | - Yicheng Hua
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, China
- Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
- Laboratory of Advanced Mineral Materials, China University of Geosciences, Wuhan 430074, China
| | - Haiyan Wu
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, China
- Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
- Laboratory of Advanced Mineral Materials, China University of Geosciences, Wuhan 430074, China
| | - Bernhard Ganss
- Faculty of Dentistry and Institute for Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 1G6, Canada
| | - Huaming Yang
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, China
- Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
- Laboratory of Advanced Mineral Materials, China University of Geosciences, Wuhan 430074, China
- Hunan Key Laboratory of Mineral Materials and Application, School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China
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Wang X, Zhang S, Wang J, Zhang S, Feng L, Wu Q. Follow-up outcome analysis of 324 cases of early-onset and late-onset mild fetal ventriculomegaly: a retrospective cohort study. Eur J Med Res 2024; 29:128. [PMID: 38365795 PMCID: PMC10870476 DOI: 10.1186/s40001-024-01709-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/01/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Mild fetal ventriculomegaly (VM) is a nonspecific finding common to several pathologies with varying prognosis and is, therefore, a challenge in fetal consultation. We aimed to perform a constant, detailed analysis of prenatal findings and postnatal outcomes in fetuses with early-onset and late-onset mild ventriculomegaly, and provide a new evidence basis and new perspective for prenatal counseling. METHODS This is a retrospective cohort study of women with a diagnosis of mild fetal VM between January 2018 and October 2020. The population was divided into two groups according to the gestational ages (GAs) at initial diagnosis: the early-onset group (diagnosed at/before 24+6 weeks) and the late-onset group (diagnosed after 24+6 weeks). Clinical data and pregnancy outcomes were obtained from hospital records. The children's neurodevelopment status was assessed using the Ages and Stages Questionnaire, Third Edition (ASQ-3) and telephone interviews. RESULTS Our study cohort comprised 324 fetuses, out of which 94 (29%) were classified as early-onset group and 230 (71%) late-onset group. Early-onset group was more likely to have concurrent additional abnormalities, whereas in the late-onset group, isolated enlargement was more common (P = 0.01). Unilateral enlargement was more common in the late-onset group (P = 0.05), and symmetrical enlargement in the early-onset group (P < 0.01). In addition, early-onset mild VM cases were more likely to have intrauterine progression (P = 0.03), and many had a higher proportion of complex multisystem abnormalities. Compared with the late-onset group, the early-onset group was more often associated with congenital brain structure malformations. Approximately 11% of fetuses with mild VM had postnatal neurodevelopmental delay/disorders, and the risk was higher in the early-onset group (19.4% vs. 7.4%). Regression analysis showed that the GA at first diagnosis, non-isolated, and intrauterine progression significantly correlated with neurodevelopmental abnormalities. CONCLUSIONS Early-onset and late-onset mild VM had significantly different ultrasound features and outcomes. Early-onset mild VM may have more complex potential abnormalities and are more likely to predict poor prognosis than the late-onset.
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Affiliation(s)
- Xuemei Wang
- Ultrasound Department, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, No.251 Yaojiayuan Road, Chaoyang District, Beijing, 100026, People's Republic of China
- Ultrasound Department, The Second Affiliated Hospital of Shandong First Medical University, 271000, Taian, Shandong, People's Republic of China
| | - Shanlong Zhang
- Ultrasound Department, The Second Affiliated Hospital of Shandong First Medical University, 271000, Taian, Shandong, People's Republic of China
| | - Jingjing Wang
- Ultrasound Department, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, No.251 Yaojiayuan Road, Chaoyang District, Beijing, 100026, People's Republic of China
| | - Simin Zhang
- Ultrasound Department, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, No.251 Yaojiayuan Road, Chaoyang District, Beijing, 100026, People's Republic of China
| | - Li Feng
- Ultrasound Department, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, No.251 Yaojiayuan Road, Chaoyang District, Beijing, 100026, People's Republic of China
| | - Qingqing Wu
- Ultrasound Department, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, No.251 Yaojiayuan Road, Chaoyang District, Beijing, 100026, People's Republic of China.
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Li Z, Chen Y, Li L, Xue M, Feng L. Different Infectivity of Swine Enteric Coronaviruses in Cells of Various Species. Pathogens 2024; 13:174. [PMID: 38392912 PMCID: PMC10891669 DOI: 10.3390/pathogens13020174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Swine enteric coronaviruses (SECoVs), including porcine deltacoronavirus (PDCoV), transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), and swine acute diarrhea syndrome coronavirus (SADS-CoV), have caused high mortality in piglets and, therefore, pose serious threats to the pork industry. Coronaviruses exhibit a trend of interspecies transmission, and understanding the host range of SECoVs is crucial for improving our ability to predict and control future epidemics. Here, the replication of PDCoV, TGEV, and PEDV in cells from different host species was compared by measuring viral genomic RNA transcription and protein synthesis. We demonstrated that PDCoV had a higher efficiency in infecting human lung adenocarcinoma cells (A549), Madin-Darby bovine kidney cells (MDBK), Madin-Darby canine kidney cells (MDCK), and chicken embryonic fibroblast cells (DF-1) than PEDV and TGEV. Moreover, trypsin can enhance the infectivity of PDCoV to MDCK cells that are nonsusceptible to TGEV. Additionally, structural analyses of the receptor ectodomain indicate that PDCoV S1 engages Aminopeptidase N (APN) via domain II, which is highly conserved among animal species of different vertebrates. Our findings provide a basis for understanding the interspecies transmission potential of these three porcine coronaviruses.
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Affiliation(s)
| | | | | | - Mei Xue
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
| | - Li Feng
- State Key Laboratory for Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150069, China
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Wang XJ, Wang Z, Han J, Su SH, Gong YX, Zhang Y, Tan NH, Wang J, Feng L. Sativene Sesquiterpenoids from the Plant Endophytic Fungus Bipolaris victoriae S27 and Their Potential as Plant-Growth Regulators. J Agric Food Chem 2024; 72:2598-2611. [PMID: 38227461 DOI: 10.1021/acs.jafc.3c05815] [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] [Indexed: 01/17/2024]
Abstract
Thirteen new sativene sesquiterpenoids (1 and 3-14), one new natural product (2), and 16 known compounds (15-30) were isolated from the endophytic fungus Bipolaris victoriae S27. Their structures were elucidated by extensive spectroscopic analysis, NMR and ECD calculations, and X-ray crystal diffractions. Compound 1 represented the first example of sativene sesquiterpenoids with a 6/5/3/5-caged tetracyclic ring system. All obtained compounds were evaluated for their plant-growth regulatory activity. The results showed that 1, 3, 4, 6, 8, 11, 12, 17, 19, 26, and 27 could suppress the growth of Arabidopsis thaliana, while 2, 5, 13, 15, 18, and 25 showed promoting effects. Among them, compound 3 showed the most potent plant-growth inhibitory activity, which is obviously superior to that of the marked herbicide glyphosate.
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Affiliation(s)
- Xin-Jia Wang
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
| | - Zhe Wang
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
| | - Jing Han
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, People's Republic of China
| | - Shi-Huang Su
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
| | - Yuan-Xiang Gong
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
| | - Yu Zhang
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
| | - Ning-Hua Tan
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
| | - Jia Wang
- School of Pharmacy, Nanjing Medical University, Nanjing 211166, People's Republic of China
| | - Li Feng
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, People's Republic of China
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Armstrong Z, Jordahl D, MacRae A, Li Q, Lenertz M, Shen P, Botserovska A, Feng L, Ugrinov A, Yang Z. A Protocol for Custom Biomineralization of Enzymes in Metal-Organic Frameworks (MOFs). Bio Protoc 2024; 14:e4930. [PMID: 38379827 PMCID: PMC10875352 DOI: 10.21769/bioprotoc.4930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 11/16/2023] [Accepted: 01/04/2024] [Indexed: 02/22/2024] Open
Abstract
Enzyme immobilization offers a number of advantages that improve biocatalysis; however, finding a proper way to immobilize enzymes is often a challenging task. Implanting enzymes in metal-organic frameworks (MOFs) via co-crystallization, also known as biomineralization, provides enhanced reusability and stability with minimal perturbation and substrate selectivity to the enzyme. Currently, there are limited metal-ligand combinations with a proper protocol guiding the experimental procedures. We have recently explored 10 combinations that allow custom immobilization of enzymes according to enzyme stability and activity in different metals/ligands. Here, as a follow-up of that work, we present a protocol for how to carry out custom immobilization of enzymes using the available combinations of metal ions and ligands. Detailed procedures to prepare metal ions, ligands, and enzymes for their co-crystallization, together with characterization and assessment, are discussed. Precautions for each experimental step and result analysis are highlighted as well. This protocol is important for enzyme immobilization in various research and industrial fields. Key features • A wide selection of metal ions and ligands allows for the immobilization of enzymes in metal-organic frameworks (MOFs) via co-crystallization. • Step-by-step enzyme immobilization procedure via co-crystallization of metal ions, organic linkers, and enzymes. • Practical considerations and experimental conditions to synthesize the enzyme@MOF biocomposites are discussed. • The demonstrated method can be generalized to immobilize other enzymes and find other metal ion/ligand combinations to form MOFs in water and host enzymes.
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Affiliation(s)
- Zoe Armstrong
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | - Drew Jordahl
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | - Austin MacRae
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | - Qiaobin Li
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | - Mary Lenertz
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | | | | | - Li Feng
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | - Angel Ugrinov
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
| | - Zhongyu Yang
- Department of Chemistry and Biochemistry, North
Dakota State University, Fargo, ND, USA
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Yan H, Zhang T, Yang Y, Li J, Liu Y, Qu D, Feng L, Zhang L. Occurrence of iodinated contrast media (ICM) in water environments and their control strategies with a particular focus on iodinated by-products formation: A comprehensive review. J Environ Manage 2024; 351:119931. [PMID: 38154220 DOI: 10.1016/j.jenvman.2023.119931] [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: 09/15/2023] [Revised: 12/03/2023] [Accepted: 12/23/2023] [Indexed: 12/30/2023]
Abstract
Iodinated contrast media (ICM), one of the pharmaceutical and personal care products (PPCPs), are frequently detected in various water bodies due to the strong biochemical stability and recalcitrance to conventional water treatment. Additionally, ICM pose a risk of forming iodinated by-products that can be detrimental to the aquatic ecosystem. Consequently, effectively removing ICM from aqueous environments is a significant concern for environmental researchers. This article provides a comprehensive review of the structural characteristics of ICM, their primary source (e.g., domestic and hospital wastewater), detected concentrations in water environments, and ecological health hazards associated with them. The current wastewater treatment technologies for ICM control are also reviewed in detail with the aim of providing a reference for future research. Prior researches have demonstrated that traditional treatment processes (such as physical adsorption, biochemical method and chemical oxidation method) have inadequate efficiencies in the removal of ICM. Currently, the application of advanced oxidation processes to remove ICM has become extensive, but there are some issues like poor deiodination efficiency and the risk of forming toxic intermediates or iodinated by-products. Conversely, reduction technologies have a high deiodination rate, enabling the targeted removal of ICM. But the subsequent treatment issues related to iodine (such as I- and OI-) are often underestimated, potentially generating iodinated by-products during the subsequent treatment processes. Hence, we proposed using combined reduction-oxidation technologies to remove ICM and achieved synchronous control of iodinated by-products. In the future, it is recommended to study the degradation efficiency of ICM and the control efficiency of iodinated by-products by combining different reduction and oxidation processes.
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Affiliation(s)
- Hao Yan
- Beijing Key Lab for Source Control Technology of Water Pollution, Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China
| | - Tao Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yi Yang
- University of Science and Technology of China, Anhui 230026, China
| | - Juan Li
- Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai 519087, China
| | - Yongze Liu
- Beijing Key Lab for Source Control Technology of Water Pollution, Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China.
| | - Dan Qu
- Beijing Key Lab for Source Control Technology of Water Pollution, Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China
| | - Li Feng
- Beijing Key Lab for Source Control Technology of Water Pollution, Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China
| | - Liqiu Zhang
- Beijing Key Lab for Source Control Technology of Water Pollution, Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China
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Li S, Ding J, Sun X, Feng L, Zhou W, Gui Z, Mao J. Selenium Concentration Is Positively Associated with Triglyceride-Glucose Index and Triglyceride Glucose-Body Mass Index in Adults: Data from NHANES 2011-2018. Biol Trace Elem Res 2024; 202:401-409. [PMID: 37145256 PMCID: PMC10764531 DOI: 10.1007/s12011-023-03684-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 04/24/2023] [Indexed: 05/06/2023]
Abstract
Compiling evidence supports that selenium plays a vital role in glucose metabolism. Triglyceride-glucose index (TyG) and triglyceride-glucose-body mass index (TyG-BMI) are commonly used in epidemiologic studies to evaluate insulin resistance and cardiovascular disease (CVD) risks. This study is aimed to investigate the association between whole blood selenium concentration and TyG and TyG-BMI. A total of 6290 participants (age ≥ 20 years) from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were included. Multiple linear regression models were used to examine the association between blood selenium quartiles and TyG and TyG-BMI. Subgroup analysis stratified by diabetes status was also performed. The adjusted model showed a positive association between TyG and blood selenium concentration (β [95%CI] = 0.099 [0.063, 0.134], p < 0.001) and TyG-BMI (β [95%CI] = 3.185 [2.102, 4.268], p < 0.001). The association persisted after stratification by diabetes status (p < 0.001). Participants were stratified into four quartiles based on selenium concentration (Q1: 1.08-2.24 μmol/L, Q2: 2.25-2.42 μmol/L, Q3: 2.43-2.62 µmol/L, Q4: 2.63-8.08). Compared with the Q1 group, TyG in the Q3 and Q4 groups was significantly higher (β = 0.075 [95%CI 0.039 to 0.112] and β = 0.140 [95%CI 0.103 to 0.176], respectively). Additionally, TyG-BMI in the Q2, Q3, and Q4 groups was higher than that in the Q1 group (β = 1.189 [95%CI 0.065 to 2.314], β = 2.325 [95%CI 1.204 to 3.446], and β = 4.322 [95%CI 3.210 to 5.435], respectively). Blood level of selenium was positively associated with TyG and TyG-BMI, indicating that excessive blood selenium may be associated with impaired insulin sensitivity and increased risk of cardiovascular disease.
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Affiliation(s)
- Shuying Li
- Department of Health Management Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210000, China
| | - Jie Ding
- Department of Health Management Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210000, China
| | - Xiaoxiao Sun
- Department of Health Management Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210000, China
| | - Li Feng
- Department of Health Management Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210000, China
| | - Weihong Zhou
- Department of Health Management Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210000, China.
| | - Zhen Gui
- Department of Clinical Laboratory, Children's Hospital of Nanjing Medical University, Nanjing, 210008, China.
| | - Jiangfeng Mao
- Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China.
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Tang Y, Xiao L, Deng C, Zhu H, Gao X, Li J, Yang Z, Liu D, Feng L, Hu S. [ 18F]FDG PET metabolic patterns in mesial temporal lobe epilepsy with different pathological types. Eur Radiol 2024; 34:887-898. [PMID: 37581655 DOI: 10.1007/s00330-023-10089-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/23/2023] [Accepted: 07/01/2023] [Indexed: 08/16/2023]
Abstract
OBJECTIVES To investigate [18F]FDG PET patterns of mesial temporal lobe epilepsy (MTLE) patients with distinct pathologic types and provide possible guidance for predicting long-term prognoses of patients undergoing epilepsy surgery. METHODS This was a retrospective review of MTLE patients who underwent anterior temporal lobectomy between 2016 and 2021. Patients were classified as having chronic inflammation and gliosis (gliosis, n = 44), hippocampal sclerosis (HS, n = 43), or focal cortical dysplasia plus HS (FCD-HS, n = 13) based on the postoperative pathological diagnosis. Metabolic patterns and the severity of metabolic abnormalities were investigated among MTLE patients and healthy controls (HCs). The standardized uptake value (SUV), SUV ratio (SUVr), and asymmetry index (AI) of regions of interest were applied to evaluate the severity of metabolic abnormalities. Imaging processing was performed with statistical parametric mapping (SPM12). RESULTS With a mean follow-up of 2.8 years, the seizure freedom (Engel class IA) rates of gliosis, HS, and FCD-HS were 54.55%, 62.79%, and 69.23%, respectively. The patients in the gliosis group presented a metabolic pattern with a larger involvement of extratemporal areas, including the ipsilateral insula. SUV, SUVr, and AI in ROIs were decreased for patients in all three MTLE groups compared with those of HCs, but the differences among all three MTLE groups were not significant. CONCLUSIONS MTLE patients with isolated gliosis had the worst prognosis and hypometabolism in the insula, but the degree of metabolic decrease did not differ from the other two groups. Hypometabolic regions should be prioritized for [18F]FDG PET presurgical evaluation rather than [18F]FDG uptake values. CLINICAL RELEVANCE STATEMENT This study proposes guidance for optimizing the operation scheme in patients with refractory MTLE and emphasizes the potential of molecular neuroimaging with PET using selected tracers to predict the postsurgical histology of patients with refractory MTLE epilepsy. KEY POINTS • MTLE patients with gliosis had poor surgical outcomes and showed a distinct pattern of decreased metabolism in the ipsilateral insula. • In the preoperative assessment of MTLE, it is recommended to prioritize the evaluation of glucose hypometabolism areas over [18F]FDG uptake values. • The degree of glucose hypometabolism in the epileptogenic focus was not associated with the surgical outcomes of MTLE.
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Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, China
| | - Ling Xiao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, China
| | - Chijun Deng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Haoyue Zhu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiaomei Gao
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, China
| | - Zhiquan Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dingyang Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- Department of Neurology, Xiangya Hospital, Central South University (Jiangxi Branch), Nanchang, Jiangxi, China.
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- Key Laboratory of Biological, Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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Feng L, Zhang Y, Wei W, Qiu H, Shi M. Applying deep learning to recognize the properties of vitreous opacity in ophthalmic ultrasound images. Eye (Lond) 2024; 38:380-385. [PMID: 37596401 PMCID: PMC10810903 DOI: 10.1038/s41433-023-02705-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 07/20/2023] [Accepted: 08/09/2023] [Indexed: 08/20/2023] Open
Abstract
BACKGROUND To explore the feasibility of artificial intelligence technology based on deep learning to automatically recognize the properties of vitreous opacities in ophthalmic ultrasound images. METHODS A total of 2000 greyscale Doppler ultrasound images containing non-pathological eye and three typical vitreous opacities confirmed as physiological vitreous opacity (VO), asteroid hyalosis (AH), and vitreous haemorrhage (VH) were selected and labelled for each lesion type. Five residual networks (ResNet) and two GoogLeNet models were trained to recognize vitreous lesions. Seventy-five percent of the images were randomly selected as the training set, and the remaining 25% were selected as the test set. The accuracy and parameters were recorded and compared among these seven different deep learning (DL) models. The precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC) values for recognizing vitreous lesions were calculated for the most accurate DL model. RESULTS These seven DL models had significant differences in terms of their accuracy and parameters. GoogLeNet Inception V1 achieved the highest accuracy (95.5%) and minor parameters (10315580) in vitreous lesion recognition. GoogLeNet Inception V1 achieved precision values of 0.94, 0.94, 0.96, and 0.96, recall values of 0.94, 0.93, 0.97 and 0.98, and F1 scores of 0.94, 0.93, 0.96 and 0.97 for normal, VO, AH, and VH recognition, respectively. The AUC values for these four vitreous lesion types were 0.99, 1.0, 0.99, and 0.99, respectively. CONCLUSIONS GoogLeNet Inception V1 has shown promising results in ophthalmic ultrasound image recognition. With increasing ultrasound image data, a wide variety of confidential information on eye diseases can be detected automatically by artificial intelligence technology based on deep learning.
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Affiliation(s)
- Li Feng
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, Eye Hospital of China Medical University, The Key Laboratory of Lens in Liaoning Province, Shenyang, China
| | | | - Wei Wei
- Hebei Eye Hospital, Xingtai, China
| | - Hui Qiu
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, Eye Hospital of China Medical University, The Key Laboratory of Lens in Liaoning Province, Shenyang, China
| | - Mingyu Shi
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, Eye Hospital of China Medical University, The Key Laboratory of Lens in Liaoning Province, Shenyang, China.
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Wang L, Feng L, Prabahar K, Hernández-Wolters B, Wang Z. The effect of phytosterol supplementation on lipid profile: A critical umbrella review of interventional meta-analyses. Phytother Res 2024; 38:507-519. [PMID: 37905579 DOI: 10.1002/ptr.8052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 09/22/2023] [Accepted: 10/07/2023] [Indexed: 11/02/2023]
Abstract
Despite multiple investigations assessing the impact of phytosterol supplementation on serum lipid levels, there is still a great deal of debate regarding the benefits of this intervention in the management of dyslipidemia. Therefore, we aimed at clarifying this dilemma by conducting the present umbrella review of interventional meta-analyses. Scopus, PubMed, Web of Science, and EMBASE were used to search for pertinent publications on the effect of phytosterol supplementation on the lipid profile in humans up to June 2023. To compute the overall effect size (ES) and confidence intervals (CI), the random-effects model was used. The I2 statistic and Cochrane's Q-test were applied to estimate the heterogeneity among the studies. Seventeen meta-analyses with 23 study arms were included in the umbrella meta-analysis. Data pooled from the 23 eligible arms revealed that phytosterol supplementation reduces low-density lipoprotein cholesterol (LDL-C) (ES = -11.47 mg/dL; 95% CI: -12.76, -10.17, p < 0.001), total cholesterol (TC) (ES = -13.02 mg/dL; 95% CI: -15.68, -10.37, p < 0.001), and triglyceride (TG) (ES = -3.77 mg/dL; 95% CI: -6.04, -1.51, p = 0.001). Subgroup analyses showed that phytosterol administration with dosage ≥2 g/day and duration over 8 weeks and in hypercholesterolemic subjects was more likely to decrease LDL-C, TC, and TG. Phytosterol administration did not significantly modify HDL-C (ES = 0.18 mg/dL; 95% CI: -0.13, -0.51, p = 258) levels when compared to controls. The present umbrella meta-analysis confirms that phytosterol administration significantly reduces LDL-C, TC, and TG, with a greater effect with doses of ≥2 g/day and treatment duration >8 weeks, suggesting its possible application as a complementary therapy for cardiovascular risk reduction. Further studies are needed to determine the efficacy of phytosterols in patients with specific health conditions, as well as to ascertain the adverse effects, the maximum tolerable dose, and the maximum recommended duration of phytosterol administration.
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Affiliation(s)
- Le Wang
- Department of Emergency Medicine, People's Hospital of Huaiyin. Jinan, Jinan, China
- The First Clinical College, Nanjing University of Chinese Medicine, Nanjing, China
| | - Li Feng
- Department of Rehabilitation Medicine, Jinan Huaiyin People's Hospital, Jinan, China
| | - Kousalya Prabahar
- Department of Pharmacy Practice, Faculty of Pharmacy, University of Tabuk, Tabuk, Saudi Arabia
| | - Benjamin Hernández-Wolters
- School of medicine, University Center for Health Science, Universidad de Guadalajara, Guadalajara, Mexico
| | - Zhenxing Wang
- Department of Cardiovascular Medicine, Affiliated Hospital of Nanjing University of Traditional Chinese Medicine, Nanjing, China
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Feng L, Ye Z, Du Z, Pan Y, Canida T, Ke H, Liu S, Chen S, Hong LE, Kochunov P, Chen J, Lei DK, Shenassa E, Ma T. Causal association between allostatic load and accelerated white matter brain aging: findings from the UK Biobank. medRxiv 2024:2024.01.26.24301793. [PMID: 38343822 PMCID: PMC10854327 DOI: 10.1101/2024.01.26.24301793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its causal association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting and doubly robust methods, were used to evaluate the impact of AL on WM BAG adjusting for age, sex, socioeconomic, and lifestyle behaviors. We found increasing one AL score unit significantly increased WM BAG by 0.29 years in association analysis and by 0.33 years in Mendelian randomization causal analysis. The age- and sex-stratified analysis showed consistent results among participants 45-54 and 55-64 years old, with no significant sex difference. This study demonstrated that higher chronic stress caused accelerated brain aging, highlighting the importance of stress management in reducing dementia and neurodegenerative disease risks.
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Affiliation(s)
- Li Feng
- Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park, Maryland, United States of America
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States of America
| | - Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Zewen Du
- Department of Biostatistics, School of Global Public Health, New York University, New York, New York, United States of America
| | - Yezhi Pan
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Travis Canida
- Department of Mathematics, The college of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, Maryland, United States of America
| | - Hongjie Ke
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States of America
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - L. Elliot Hong
- Louis A. Faillace Department of Psychiatry & Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Peter Kochunov
- Louis A. Faillace Department of Psychiatry & Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Jie Chen
- Department of Health Policy and Management, School of Public Health, University of Maryland, College Park, Maryland, United States of America
| | - David K.Y. Lei
- Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park, Maryland, United States of America
| | - Edmond Shenassa
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States of America
- Maternal & Child Health Program, School of Public Health, University of Maryland, College Park, Maryland, United States of America
- Department of Epidemiology, School of Public Health, Brown University, Rhode Island, United States of America
- Department of Epidemiology & Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States of America
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Zhu Q, Qi S, Guo D, Li C, Su M, Wang J, Li Z, Yang D, Sun H, Wang X, Wang M, Wu H, Yu S, Bai W, Zhang Y, Yang X, Jiang L, Liu J, Zhao Y, Xing X, Shi D, Feng L, Sun D. A survey of fecal virome and bacterial community of the diarrhea-affected cattle in northeast China reveals novel disease-associated ecological risk factors. mSystems 2024; 9:e0084223. [PMID: 38108282 PMCID: PMC10804951 DOI: 10.1128/msystems.00842-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/06/2023] [Indexed: 12/19/2023] Open
Abstract
Limited information on the virome and bacterial community hampers our ability to discern systemic ecological risk factors that cause cattle diarrhea, which has become a pressing issue in the control of disease. A total of 110 viruses, 1,011 bacterial genera, and 322 complete viral genomes were identified from 70 sequencing samples mixed with 1,120 fecal samples from 58 farms in northeast China. For the diarrheic samples, the identified virome and bacterial community varied in terms of composition, abundance, diversity, and geographic distribution in relation to different disease-associated ecological factors; the abundance of identified viruses and bacteria was significantly correlated with the host factors of clinical status, cattle type, and age, and with environmental factors such as aquaculture model and geographical location (P < 0.05); a significant interaction occurred between viruses and viruses, bacteria and bacteria, as well as between bacteria and viruses (P < 0.05). The abundance of SMB53, Butyrivibrio, Facklamia, Trichococcus, and Turicibacter was significantly correlated with the health status of cattle (P < 0.05). The proportion of BRV, BCoV, BKV, BToV, BoNoV, BoNeV, BoAstV, BEV, BoPV, and BVDV in 1,120 fecal samples varied from 1.61% to 12.05%. A series of significant correlations were observed between the prevalence of individual viruses and the disease-associated ecological factors. A genome-based phylogenetic analysis revealed high variability of 10 bovine enteric viruses. The bovine hungarovirus was initially identified in both dairy and beef cattle in China. This study elucidates the fecal virome and bacterial community signatures of cattle affected by diarrhea, and reveals novel disease-associated ecological risk factors, including cattle type, cattle age, aquaculture model, and geographical location.IMPORTANCEThe lack of data on the virome and bacterial community restricts our capability to recognize ecological risk factors for bovine diarrhea disease, thereby hindering our overall comprehension of the disease's cause. In this study, we found that, for the diarrheal samples, the identified virome and bacterial community varied in terms of composition, abundance, diversity, configuration, and geographic distribution in relation to different disease-associated ecological factors. A series of significant correlations were observed between the prevalence of individual viruses and the disease-associated ecological factors. Our study aims to uncover novel ecological risk factors of bovine diarrheal disease by examining the pathogenic microorganism-host-environment disease ecology, thereby providing a new perspective on the control of bovine diarrheal diseases.
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Affiliation(s)
- Qinghe Zhu
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Shanshan Qi
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Donghua Guo
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Chunqiu Li
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Mingjun Su
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Jianfa Wang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Zijian Li
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Dan Yang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Haibo Sun
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Xiaoran Wang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Meijiao Wang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Haoyang Wu
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Shiping Yu
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Wenfei Bai
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Yongchen Zhang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Xu Yang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Limin Jiang
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Jiaying Liu
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Yingying Zhao
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Xiaoxu Xing
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
| | - Da Shi
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, China
| | - Li Feng
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin, China
| | - Dongbo Sun
- Key Laboratory of Bovine Disease Control in Northeast China, Ministry of Agriculture and Rural affairs of the People’s Republic of China, Heilongjiang Provincial Key Laboratory of Prevention and Control of Bovine Diseases, College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China
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Wu BL, Yao JN, Long XX, Tan ZQ, Liang X, Feng L, Wei K, Yang YR. Enantioselective Total Synthesis of (-)-Daphenylline. J Am Chem Soc 2024; 146:1262-1268. [PMID: 38180776 DOI: 10.1021/jacs.3c12741] [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: 01/06/2024]
Abstract
A concise enantioselective total synthesis of (-)-daphenylline, a hexacyclic Daphniphyllum alkaloid with a unique benzene ring, was achieved in 14 steps. The synthesis commences with two chiral stereocenters, C2 and C18, readily installed via Carreira's Ir/amine dual-catalyzed allylation. The allylic bridgehead amine 6 was rapidly prepared through Wickens' photoredox-catalyzed hydrocarboxylation of olefin and CuBr2-catalyzed α-amination of ketone. The tetracycle 4 was formed via Pd-catalyzed reductive Heck reaction or, more concisely, by Krische's Rh-catalyzed reductive 1,6-enyne cyclization. In this synthesis, newly reported Wickens' photoredox-catalyzed hydrocarboxylation was used twice, and Friedel-Crafts acylation thrice.
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Affiliation(s)
- Bing-Lu Wu
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jian-Neng Yao
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Xiang-Xi Long
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zong-Qin Tan
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiao Liang
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Li Feng
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kun Wei
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Yu-Rong Yang
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
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Shen M, Li K, Wang L, Feng L, Zhang X, Zhang H, Zhou H, Pei G. ZIP4 upregulation aggravates nucleus pulposus cell degradation by promoting inflammation and oxidative stress by mediating the HDAC4-FoxO3a axis. Aging (Albany NY) 2024; 16:685-700. [PMID: 38217540 PMCID: PMC10817398 DOI: 10.18632/aging.205412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 10/18/2023] [Indexed: 01/15/2024]
Abstract
BACKGROUND Extracellular matrix metabolism dysregulation in nucleus pulposus (NP) cells represents a crucial pathophysiological feature of intervertebral disc degeneration (IDD). Our study elucidates the role and mechanism of Testis expressed 11 (TEX11, also called ZIP4) extracellular matrix degradation in the NP. MATERIALS AND METHODS Interleukin-1β (IL-1β) and H2O2 were used to treat NP cells to establish an IDD cell model. Normal NP tissues and NP tissues from IDD patients were harvested. ZIP4 mRNA and protein profiles in NP cells and tissues were examined. Enzyme-linked immunosorbent assay (ELISA) confirmed the profiles of TNF-α, IL-6, MDA, and SOD in NP cells. The alterations of reactive oxygen species (ROS), lactate dehydrogenase (LDH), COX2, iNOS, MMP-3, MMP-13, collagen II, aggrecan, FoxO3a, histone deacetylase 4 (HDAC4), Sirt1 and NF-κB levels in NP cells were determined using different assays. RESULTS The ZIP4 profile increased in the NP tissues of IDD patients and IL-1β- or H2O2-treated NP cells. ZIP4 upregulation bolstered inflammation and oxidative stress in NP cells undergoing IL-1β treatment and exacerbated their extracellular matrix degradation, whereas ZIP4 knockdown produced the opposite outcome. Mechanistically, ZIP4 upregulated HDAC4 and enhanced NF-κB phosphorylation while repressing Sirt1 and FoxO3a phosphorylation levels. HDAC4 knockdown or Sirt1 promotion attenuated the effects mediated by ZIP4 overexpression in NP cells. CONCLUSIONS ZIP4 upregulation aggravates the extracellular matrix (ECM) degradation of NP cells by mediating inflammation and oxidative stress through the HDAC4-FoxO3a axis.
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Affiliation(s)
- Mingkui Shen
- Intervertebral Disc Center, Third Hospital of Henan Province, Zhengzhou 450006, Henan, China
| | - Kuankuan Li
- Intervertebral Disc Center, Third Hospital of Henan Province, Zhengzhou 450006, Henan, China
| | - Lulu Wang
- School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China
| | - Li Feng
- School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xinyu Zhang
- Intervertebral Disc Center, Third Hospital of Henan Province, Zhengzhou 450006, Henan, China
| | - Haoping Zhang
- Intervertebral Disc Center, Third Hospital of Henan Province, Zhengzhou 450006, Henan, China
| | - Honggang Zhou
- Intervertebral Disc Center, Third Hospital of Henan Province, Zhengzhou 450006, Henan, China
| | - Guoxian Pei
- School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China
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47
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Liang MY, Feng L, Zhu W, Yang QQ. Effect of frailty on medication deviation during the hospital-family transition period in older patients with cardiovascular disease: An observational study. Medicine (Baltimore) 2024; 103:e36893. [PMID: 38215090 PMCID: PMC10783343 DOI: 10.1097/md.0000000000036893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 12/18/2023] [Indexed: 01/14/2024] Open
Abstract
Studies have shown that frailty increases cardiovascular disease (CVD) incidence in older patients and is associated with poor patient prognosis. However, the relationship between medication deviation (MD) and frailty remains unclear. This study aimed to explore the influence of frailty on MD during the hospital-family transition period among older patients with CVD. Between February 2022 and February 2023, 231 older people CVD patients were selected from a class III hospital in Nantong City using a multi-stage sampling method. A general information questionnaire was used to collect the socio-demographic characteristics of the participants prior to discharge, the frailty assessment scale was used to assess the participants frailty, and a medication deviation instrument was used to assess the participants MD on the 10th day after discharge. Propensity score matching was used to examine the effect of frailty on MD in older patients with CVD during the hospital-family transition period. The incidences of frailty and MD were 32.9% (76/231) and 75.8% (175/231), respectively. After propensity score matching, the risk of MD in frail patients with CVD was 4.978 times higher than that in non-frail patients with CVD (95% CI: [1.616, 15.340]; P = .005). Incidences of frailty and MD during the hospital-family transition period are high in older patients with CVD, and frailty has an impact on MD. Medical staff in the ward should comprehensively examine older patients with CVD for frailty and actively promote quality medication management during the hospital-family transition period to reduce MD occurrence and delay disease progression.
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Affiliation(s)
- Meng-Yao Liang
- Department of Nursing, The Sixth People’s Hospital of Nantong, Jiangsu, China
| | - Li Feng
- Department of Nursing, The Sixth People’s Hospital of Nantong, Jiangsu, China
| | - Wuyang Zhu
- Department of Rehabilitation, Yi Jiangmen Community Health Service Center, Gulou District, Nanjing, China
| | - Qing-Qing Yang
- Department of Cardiology, The Sixth People’s Hospital of Nantong, Jiangsu, China
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48
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Feng X, Pan L, Qian Z, Liu D, Guan X, Feng L, Song B, Xu X, Tan N, Ma Y, Li Z, Wang Z, Bian J. Correction to "Discovery of Selenium-Containing STING Agonists as Orally Available Antitumor Agents". J Med Chem 2024; 67:782. [PMID: 38158561 DOI: 10.1021/acs.jmedchem.3c02318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
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49
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Zhao JW, Wang HY, Feng L, Zhu JZ, Liu JX, Li WX. Crystal-Phase Engineering in Heterogeneous Catalysis. Chem Rev 2024; 124:164-209. [PMID: 38044580 DOI: 10.1021/acs.chemrev.3c00402] [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: 12/05/2023]
Abstract
The performance of a chemical reaction is critically dependent on the electronic and/or geometric structures of a material in heterogeneous catalysis. Over the past century, the Sabatier principle has already provided a conceptual framework for optimal catalyst design by adjusting the electronic structure of the catalytic material via a change in composition. Beyond composition, it is essential to recognize that the geometric atomic structures of a catalyst, encompassing terraces, edges, steps, kinks, and corners, have a substantial impact on the activity and selectivity of a chemical reaction. Crystal-phase engineering has the capacity to bring about substantial alterations in the electronic and geometric configurations of a catalyst, enabling control over coordination numbers, morphological features, and the arrangement of surface atoms. Modulating the crystallographic phase is therefore an important strategy for improving the stability, activity, and selectivity of catalytic materials. Nonetheless, a complete understanding of how the performance depends on the crystal phase of a catalyst remains elusive, primarily due to the absence of a molecular-level view of active sites across various crystal phases. In this review, we primarily focus on assessing the dependence of catalytic performance on crystal phases to elucidate the challenges and complexities inherent in heterogeneous catalysis, ultimately aiming for improved catalyst design.
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Affiliation(s)
- Jian-Wen Zhao
- Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, iChem, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Hong-Yue Wang
- Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, iChem, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Li Feng
- Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, iChem, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Jin-Ze Zhu
- Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, iChem, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Jin-Xun Liu
- Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, iChem, University of Science and Technology of China, Hefei, Anhui 230026, China
- Hefei National Laboratory, University of Science and Technology of China, Hefei 230088, China
| | - Wei-Xue Li
- Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, iChem, University of Science and Technology of China, Hefei, Anhui 230026, China
- Hefei National Laboratory, University of Science and Technology of China, Hefei 230088, China
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50
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Zuo X, Han P, Yuan D, Xiao Y, Huang Y, Li R, Jiang X, Feng L, Li Y, Zhang Y, Zhu P, Wang H, Wang N, Kang YJ. Implantation of Adipose-Derived Mesenchymal Stromal Cells (ADSCs)-Lining Prosthetic Graft Promotes Vascular Regeneration in Monkeys and Pigs. Tissue Eng Regen Med 2024:10.1007/s13770-023-00615-z. [PMID: 38190095 DOI: 10.1007/s13770-023-00615-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] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/19/2023] [Accepted: 11/09/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Current replacement procedures for stenosis or occluded arteries using prosthetic grafts have serious limitations in clinical applications, particularly, endothelialization of the luminal surface is a long-standing unresolved problem. METHOD We produced a cell-based hybrid vascular graft using a bioink engulfing adipose-derived mesenchymal stromal cells (ADSCs) and a 3D bioprinting process lining the ADSCs on the luminal surface of GORE-Tex grafts. The hybrid graft was implanted as an interposition conduit to replace a 3-cm-long segment of the infrarenal abdominal aorta in Rhesus monkeys. RESULTS Complete endothelium layer and smooth muscle layer were fully developed within 21 days post-implantation, along with normalized collagen deposition and crosslinking in the regenerated vasculature in all monkeys. The regenerated blood vessels showed normal functionality for the longest observation of more than 1650 days. The same procedure was also conducted in miniature pigs for the interposition replacement of a 10-cm-long right iliac artery and showed the same long-term effective and safe outcome. CONCLUSION This cell-based vascular graft is ready to undergo clinical trials for human patients.
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Affiliation(s)
- Xiao Zuo
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
- Sichuan 3D Bioprinting Institute, Chengdu, China
| | - Pengfei Han
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
| | - Ding Yuan
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
- Division of Vascular Surgery, Department of General Surgery, Sichuan University West China Hospital, Chengdu, China
| | - Ying Xiao
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
| | - Yushi Huang
- Sichuan 3D Bioprinting Institute, Chengdu, China
| | - Rui Li
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
| | - Xia Jiang
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
| | - Li Feng
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
| | - Yijun Li
- Sichuan 3D Bioprinting Institute, Chengdu, China
| | - Yaya Zhang
- Sichuan 3D Bioprinting Institute, Chengdu, China
| | - Ping Zhu
- Sichuan 3D Bioprinting Institute, Chengdu, China
| | - Hongge Wang
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China
| | - Ning Wang
- Sichuan 3D Bioprinting Institute, Chengdu, China
| | - Y James Kang
- Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, 610093, China.
- Sichuan 3D Bioprinting Institute, Chengdu, China.
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