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Xu L, Cao F, Wang L, Liu W, Gao M, Zhang L, Hong F, Lin M. Machine learning model and nomogram to predict the risk of heart failure hospitalization in peritoneal dialysis patients. Ren Fail 2024; 46:2324071. [PMID: 38494197 PMCID: PMC10946267 DOI: 10.1080/0886022x.2024.2324071] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024] Open
Abstract
INTRODUCTION The study presented here aimed to establish a predictive model for heart failure (HF) and all-cause mortality in peritoneal dialysis (PD) patients with machine learning (ML) algorithm. METHODS We retrospectively included 1006 patients who initiated PD from 2010 to 2016. XGBoost, random forest (RF), and AdaBoost were used to train models for assessing risk for 1-year and 5-year HF hospitalization and mortality. The performance was validated using fivefold cross-validation. The optimal ML algorithm was used to construct the models to predictive the risk of the HF and all-cause mortality. The prediction performance of ML methods and Cox regression was compared. RESULTS Over a median follow-up of 49 months. Two hundred and ninety-eight patients developed HF required hospitalization; 199 patients died during the follow-up. The RF model (AUC = 0.853) was the best performing model for predicting HF, and the XGBoost model (AUC = 0.871) was the best model for predicting mortality. Baseline moderate or severe renal disease, systolic blood pressure (SBP), body mass index (BMI), age, Charlson Comorbidity Index (CCI) score were strongly associated with HF hospitalization, whereas age, CCI score, creatinine, age, high-density lipoprotein cholesterol (HDL-C), total cholesterol, baseline estimated glomerular filtration rate (eGFR) were the most significant predictors of mortality. For all the above endpoints, the ML models demonstrated better discrimination than Cox regression. CONCLUSIONS We developed and validated a novel method to predict the risk factors of HF and all-cause mortality that integrates readily available clinical, laboratory, and electrocardiographic variables to predict the risk of HF among PD patients.
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Affiliation(s)
- Liping Xu
- Department of Nephrology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China
| | - Fang Cao
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
- Department of Nursing, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Lian Wang
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Weihua Liu
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Meizhu Gao
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Li Zhang
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Fuyuan Hong
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Miao Lin
- Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
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Yan R, Zhang N, Liu W, Hu X, Wang W, Tang Y, Wang S, Wang X, Sheng Q. Novel Eu-dipeptide assemblies for a fluorescence sensing strategy to ultrasensitive determine trace sulfamethazine. Food Chem 2024; 448:139089. [PMID: 38518446 DOI: 10.1016/j.foodchem.2024.139089] [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: 01/07/2024] [Revised: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 03/24/2024]
Abstract
Self-assembled Eu-dipeptide (tryptophan-phenylalanine) microparticles with multi-emission fluorescence was prepared and modified with a single-stranded DNA corresponding to the sulfamethazine (SMZ) adapter (Eu-PMPs@cDNA). Aptamer-functionalized magnetic Fe3O4 (MNPs@aptamer) was used to specifically bind the target SMZ. Using Eu-PMPs@cDNA as fluorescent signal probe and MNPs@aptamer as catcher, a noncompetitive fluorescence sensing strategy was developed for determination of SMZ with good sensitivity, accuracy, selectivity, and stability. Under the optimized conditions, fluorescence increases linearly in the 0-20 ng/mL SMZ concentration range, and the detection limit is 0.014 ng/mL. The fluorescence sensing method was applied to analysis of water and fish muscle samples, and recoveries ranged from 81.78 to 119.46 % with relative standard deviations below 4.2 %. This study offered a reliable and sensitive fluorescence sensing strategy for SMZ determination in food samples, which owns great potential for wide-ranging application in harmful compounds assay by simply changing the type of aptamer and its complementary single-stranded DNA.
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Affiliation(s)
- Rongfang Yan
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Ning Zhang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Weihua Liu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Xuelian Hu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Wenxiu Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Yiwei Tang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China.
| | - Shuo Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China; Tianjin Key Laboratory of Food Science and Health, School of Medicine, Nankai University, Tianjin 300071, China
| | - Xianghong Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Qinghai Sheng
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
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Zhao G, Wang C, Kang M, Hao L, Liu W, Wang Z, Shi X, Wu Q. Construction of magnetic azo-linked porous polymer for highly-efficient enrichment and separation of phenolic endocrine disruptors from environmental water and fish. Food Chem 2024; 445:138698. [PMID: 38350198 DOI: 10.1016/j.foodchem.2024.138698] [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: 10/26/2023] [Revised: 01/27/2024] [Accepted: 02/05/2024] [Indexed: 02/15/2024]
Abstract
Developing effective methods for highly sensitive detection of phenolic endocrine disruptors (EDCs) is especially urgent. Herein, a magnetic hydroxyl-functional porous organic polymer (M-FH-POP) was facilely synthesized by green diazo-couple reaction using basic fuchsin and hesperetin as monomer for the first time. M-FH-POP delivered superior adsorption performance for phenolic EDCs. The adsorption mechanism was hydrogen bonds, hydrophobic interaction and π-π interplay. With M-FH-POP as adsorbent, a magnetic solid phase extraction method was established for extracting trace phenolic EDCs (bisphenol A, 4-tert-butylphenol, bisphenol F and bisphenol B) in water and fish before ultra-high performance liquid chromatography tandem mass spectrometry analysis. The method displayed low detection limit (S/N = 3) of 0.05-0.15 ng mL-1 for water and 0.08-0.3 ng g-1 for fish. The spiked recoveries were 88.3 %-109.8 % with the relative standard deviations of 2.4 %-6.4 %. The method offers a new strategy for sensitive determination of phenolic EDCs in water and fish samples.
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Affiliation(s)
- Guijiao Zhao
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Chenhuan Wang
- Department of Chemistry, University of South Florida, Tampa, FL 33620, United States
| | - Min Kang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Lin Hao
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Weihua Liu
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Zhi Wang
- College of Science, Hebei Agricultural University, Baoding 071001, China; College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Xiaodong Shi
- Department of Chemistry, University of South Florida, Tampa, FL 33620, United States.
| | - Qiuhua Wu
- College of Science, Hebei Agricultural University, Baoding 071001, China; College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China.
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4
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Li S, Liu W, Liu M, Chen Y, Zhang F, Wang X. A sensitive lateral flow immunoassay relying on time-resolved fluorescent microspheres immune probe for determination of ceftiofur and its metabolite. Talanta 2024; 271:125580. [PMID: 38219317 DOI: 10.1016/j.talanta.2023.125580] [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: 10/04/2023] [Revised: 12/14/2023] [Accepted: 12/19/2023] [Indexed: 01/16/2024]
Abstract
Ceftiofur (CEF) is an antimicrobial agent with high efficiency and low toxicity, desfuroylceftiofur is its main metabolite, but they are also have potential harm to human health. In this study, ceftiofur was combined with carrier proteins to get artificial antigens. A specific antibody (pAb) against CEF and desfuroylceftiofur was prepared. A sensitive and rapid paper-based sensor relying on time-resolved fluorescent microspheres (TRFMs) immune probes was developed, which were time-resolved fluorescent immunochromatographic strips (TRFMs-LFIA). The concentrations of T line and C line, activated pH, antibody volume and probe volume were optimized. Quantitative limits of detection (qLODs) of TRFMs-LFIA for CEF and desfuroylceftiofur were 0.97 ng/mL and 0.41 ng/mL, respectively. And 50 % inhibiting concentrations (IC50) were 12.92 ng/mL and 12.58 ng/mL, respectively. Pretreatment procedures of real samples were simple and rapid. Detection time of TRFMs-LFIA strip was 15 min. Qualitative analysis of CEF and desfuroylceftiofur was achieved under a UV light, quantitative analysis was implemented with a fluorescent immunoassay analyzer. The average recovery rates ranged from 91.4 % to 107.7 % and corresponding coefficients of variation (CV) was 1.5%-9.7 %. Concentration levels of artificially-spiked samples were measured by TRFMs-LFIA and compared with detection results of High performance liquid chromatography (HPLC), which showed a good accordance. These results indicated that the proposed assay can provide an effective strategy for on-site detection of CEF and desfuroylceftiofur simultaneously.
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Affiliation(s)
- Shuxian Li
- College of Food Science and Technology, Hebei Agricultural University, Baoding, 071000, PR China
| | - Weihua Liu
- College of Food Science and Technology, Hebei Agricultural University, Baoding, 071000, PR China
| | - Minxuan Liu
- College of Food Science and Technology, Hebei Agricultural University, Baoding, 071000, PR China
| | - Yuyang Chen
- College of Food Science and Technology, Hebei Agricultural University, Baoding, 071000, PR China
| | - Fuyuan Zhang
- College of Food Science and Technology, Hebei Agricultural University, Baoding, 071000, PR China
| | - Xianghong Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding, 071000, PR China.
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Han B, Wang X, Sun Y, Kang X, Zhang M, Luo J, Han H, Zhou S, Lu Y, Liu W, Yang X, Li X, Zhang J, Li L. Pre-breeding of spontaneous Robertsonian translocations for density planting architecture by transferring Agropyron cristatum chromosome 1P into wheat. Theor Appl Genet 2024; 137:110. [PMID: 38656338 DOI: 10.1007/s00122-024-04614-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] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 03/28/2024] [Indexed: 04/26/2024]
Abstract
KEY MESSAGE We developed T1AL·1PS and T1AS·1PL Robertsonian translocations by breakage-fusion mechanism based on wheat-A. cristatum 1P(1A) substitution line with smaller leaf area, shorter plant height, and other excellent agronomic traits Agropyron cristatum, a wild relative of wheat, is a valuable germplasm resource for improving wheat genetic diversity and yield. Our previous study confirmed that the A. cristatum chromosome 1P carries alien genes that reduce plant height and leaf size in wheat. Here, we developed T1AL·1PS and T1AS·1PL Robertsonian translocations (RobTs) by breakage-fusion mechanism based on wheat-A. cristatum 1P (1A) substitution line II-3-1c. Combining molecular markers and cytological analysis, we identified 16 spontaneous RobTs from 911 F2 individuals derived from the cross of Jimai22 and II-3-1c. Fluorescence in situ hybridization (FISH) was applied to detect the fusion structures of the centromeres in wheat and A. cristatum chromosomes. Resequencing results indicated that the chromosomal junction point was located at the physical position of Triticum aestivum chromosome 1A (212.5 Mb) and A. cristatum chromosome 1P (230 Mb). Genomic in situ hybridization (GISH) in pollen mother cells showed that the produced translocation lines could form stable ring bivalent. Introducing chromosome 1PS translocation fragment into wheat significantly increased the number of fertile tillers, grain number per spike, and grain weight and reduced the flag leaf area. However, introducing chromosome 1PL translocation fragment into wheat significantly reduced flag leaf area and plant height with a negative effect on yield components. The pre-breeding of two spontaneous RobTs T1AL·1PS and T1AS·1PL was important for wheat architecture improvement.
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Affiliation(s)
- Bohui Han
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiao Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yangyang Sun
- Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao, 266101, China
| | - Xilu Kang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Meng Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jiawen Luo
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Haiming Han
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shenghui Zhou
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yuqing Lu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Weihua Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xinming Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiuquan Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jinpeng Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China.
| | - Lihui Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China.
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Lu H, Jiang J, Min J, Huang X, McLeod P, Liu W, Haig A, Gunaratnam L, Jevnikar AM, Zhang ZX. The CaMK Family Differentially Promotes Necroptosis and Mouse Cardiac Graft Injury and Rejection. Int J Mol Sci 2024; 25:4428. [PMID: 38674016 PMCID: PMC11050252 DOI: 10.3390/ijms25084428] [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: 01/18/2024] [Revised: 03/27/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
Organ transplantation is associated with various forms of programmed cell death which can accelerate transplant injury and rejection. Targeting cell death in donor organs may represent a novel strategy for preventing allograft injury. We have previously demonstrated that necroptosis plays a key role in promoting transplant injury. Recently, we have found that mitochondria function is linked to necroptosis. However, it remains unknown how necroptosis signaling pathways regulate mitochondrial function during necroptosis. In this study, we investigated the receptor-interacting protein kinase 3 (RIPK3) mediated mitochondrial dysfunction and necroptosis. We demonstrate that the calmodulin-dependent protein kinase (CaMK) family members CaMK1, 2, and 4 form a complex with RIPK3 in mouse cardiac endothelial cells, to promote trans-phosphorylation during necroptosis. CaMK1 and 4 directly activated the dynamin-related protein-1 (Drp1), while CaMK2 indirectly activated Drp1 via the phosphoglycerate mutase 5 (PGAM5). The inhibition of CaMKs restored mitochondrial function and effectively prevented endothelial cell death. CaMKs inhibition inhibited activation of CaMKs and Drp1, and cell death and heart tissue injury (n = 6/group, p < 0.01) in a murine model of cardiac transplantation. Importantly, the inhibition of CaMKs greatly prolonged heart graft survival (n = 8/group, p < 0.01). In conclusion, CaMK family members orchestrate cell death in two different pathways and may be potential therapeutic targets in preventing cell death and transplant injury.
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Affiliation(s)
- Haitao Lu
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
- Department of Pathology, Western University, London, ON N6A 3K7, Canada
| | - Jifu Jiang
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
| | - Jeffery Min
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
| | - Xuyan Huang
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
| | - Patrick McLeod
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
| | - Weihua Liu
- Department of Pathology, Western University, London, ON N6A 3K7, Canada
| | - Aaron Haig
- Department of Pathology, Western University, London, ON N6A 3K7, Canada
| | - Lakshman Gunaratnam
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
- Department of Microbiology and Immunology, Western University, London, ON N6A 3K7, Canada
- Multi-Organ Transplant Program, London Health Sciences Centre, London, ON N6A 5A5, Canada
- Division of Nephrology, Department of Medicine, Western University, London, ON N6A 3K7, Canada
| | - Anthony M. Jevnikar
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
- Department of Microbiology and Immunology, Western University, London, ON N6A 3K7, Canada
- Multi-Organ Transplant Program, London Health Sciences Centre, London, ON N6A 5A5, Canada
- Division of Nephrology, Department of Medicine, Western University, London, ON N6A 3K7, Canada
| | - Zhu-Xu Zhang
- Matthew Mailing Centre for Translational Transplantation Studies, London Health Sciences Centre, London, ON N6A 5A5, Canada; (H.L.); (A.M.J.)
- Department of Pathology, Western University, London, ON N6A 3K7, Canada
- Multi-Organ Transplant Program, London Health Sciences Centre, London, ON N6A 5A5, Canada
- Division of Nephrology, Department of Medicine, Western University, London, ON N6A 3K7, Canada
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Zhang C, Shi R, Liu W, Xu Z, Mi S, Sang Y, Yu W, Wang X. Effect of different thermal processing methods on sensory, nutritional, physicochemical and structural properties of Penaeus vannamei. Food Chem 2024; 438:138003. [PMID: 37979258 DOI: 10.1016/j.foodchem.2023.138003] [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: 06/17/2023] [Revised: 11/12/2023] [Accepted: 11/13/2023] [Indexed: 11/20/2023]
Abstract
The aim of this study was to investigate the effect of different thermal processing methods on the nutritional and physicochemical qualities of Penaeus vannamei. Three different thermal processing methods, namely, drying (DS, 120 °C/40 min), steaming (SS, 100 °C/2 min), and microwaving (MS, 600 W/2 min) were used to treat the shrimps. Low-field nuclear magnetic resonance data indicated that fixed water was the main component of Penaeus vannamei. The ratio of fatty acids in MS and DS samples was more in line with the FAO/WHO recommended health requirements; The myofibrillar protein carbonyl group increased, whereas sulfhydryl content decreased after thermal processing, indicating that the proteins were oxidized by thermal processing. The magnitude of oxidation is: MS > SS > DS. Different thermal processing methods can exert great influence on color texture and nutrition to Penaeus vannamei, which can provide a theoretical knowledge for consumers to choose the appropriate processing method.
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Affiliation(s)
- Caiyu Zhang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China
| | - Renli Shi
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China
| | - Weihua Liu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China
| | - Zhiyue Xu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China
| | - Si Mi
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China
| | - Yaxin Sang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China
| | - Wenlong Yu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China.
| | - Xianghong Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071000, China.
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Jia Y, Liu W, Wang J, Zhang R, Li M, Liu S. A pair of twins with multicystic dysplastic kidney and hydrocephalus caused by a novel homozygous mutation in SPATA33 and CDK10. QJM 2024; 117:302-303. [PMID: 38180891 DOI: 10.1093/qjmed/hcad289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Indexed: 01/07/2024] Open
Affiliation(s)
- Y Jia
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - W Liu
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - J Wang
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - R Zhang
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - M Li
- Department of Urology, Qingdao Municipal Hospital Group, NO.5 Middle Dong Hai Road, Qingdao 266071, China
| | - S Liu
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
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9
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Rosenberg E, Andersen TI, Samajdar R, Petukhov A, Hoke JC, Abanin D, Bengtsson A, Drozdov IK, Erickson C, Klimov PV, Mi X, Morvan A, Neeley M, Neill C, Acharya R, Allen R, Anderson K, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bilmes A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Campero J, Chang HS, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Barba ADT, Demura S, Di Paolo A, Dunsworth A, Earle C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Garcia G, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hill G, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Mandrà S, Martin O, Martin S, McClean JR, McEwen M, Meeks S, Miao KC, Mieszala A, Montazeri S, Movassagh R, Mruczkiewicz W, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Omonije S, Opremcak A, Potter R, Pryadko LP, Quintana C, Rhodes DM, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Sivak V, Skruzny J, Smith WC, Somma RD, Sterling G, Strain D, Szalay M, Thor D, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Khemani V, Gopalakrishnan S, Prosen T, Roushan P. Dynamics of magnetization at infinite temperature in a Heisenberg spin chain. Science 2024; 384:48-53. [PMID: 38574139 DOI: 10.1126/science.adi7877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024]
Abstract
Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.
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Affiliation(s)
- E Rosenberg
- Google Research, Mountain View, CA, USA
- Department of Physics, Cornell University, Ithaca, NY, USA
| | | | - R Samajdar
- Department of Physics, Princeton University, Princeton, NJ, USA
- Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, USA
| | | | - J C Hoke
- Department of Physics, Stanford University, Stanford, CA, USA
| | - D Abanin
- Google Research, Mountain View, CA, USA
| | | | - I K Drozdov
- Google Research, Mountain View, CA, USA
- Department of Physics, University of Connecticut, Storrs, CT, USA
| | | | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - A Morvan
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - R Allen
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - A Bilmes
- Google Research, Mountain View, CA, USA
| | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - J Campero
- Google Research, Mountain View, CA, USA
| | - H-S Chang
- Google Research, Mountain View, CA, USA
| | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | - C Earle
- Google Research, Mountain View, CA, USA
| | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - G Garcia
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | - G Hill
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- QSI, Faculty of Engineering & Information Technology, University of Technology Sydney, Ultimo, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - S Mandrà
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | - S Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | - S Meeks
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - S Omonije
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - V Sivak
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | | | - R D Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - D Thor
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | | | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - V Khemani
- Department of Physics, Stanford University, Stanford, CA, USA
| | | | - T Prosen
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - P Roushan
- Google Research, Mountain View, CA, USA
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10
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Yu X, Xiang J, Zhang Q, Chen S, Tang W, Li X, Sui Y, Liu W, Kong Q, Guo Y. Corrigendum to Triple-negative breast cancer: predictive model of early recurrence based on MRI features [78 (11) e798-e807]. Clin Radiol 2024; 79:e640. [PMID: 38316571 DOI: 10.1016/j.crad.2024.01.001] [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: 02/07/2024]
Affiliation(s)
- X Yu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - J Xiang
- Guangdong Women and Children Hospital, No. 13 West Guangyuan Road, Guangzhou, Guangdong, 510010, China
| | - Q Zhang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - S Chen
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Tang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - X Li
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Y Sui
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Liu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
| | - Q Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China.
| | - Y Guo
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
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11
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Qi W, Cui L, Jiajue R, Pang Q, Chi Y, Liu W, Jiang Y, Wang O, Li M, Xing X, Tong A, Xia W. Deteriorated bone microarchitecture caused by sympathetic overstimulation in pheochromocytoma and paraganglioma. J Endocrinol Invest 2024; 47:843-856. [PMID: 37872466 DOI: 10.1007/s40618-023-02198-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/12/2023] [Indexed: 10/25/2023]
Abstract
PURPOSE Despite the potentially destructive effect of sympathetic activity on bone metabolism, its impact on bone microarchitecture, a key determinant of bone quality, has not been thoroughly investigated. This study aims to evaluate the impact of sympathetic activity on bone microarchitecture and bone strength in patients with pheochromocytoma and paraganglioma (PPGL). METHODS A cross-sectional study was conducted in 38 PPGL patients (15 males and 23 females). Bone turnover markers serum procollagen type 1 N-terminal propeptide (P1NP) and β-carboxy-terminal crosslinked telopeptide of type 1 collagen (β-CTX) were measured. 24-h urinary adrenaline (24hUE) and 24-h urinary norepinephrine levels (24hUNE) were measured to indicate sympathetic activity. High-resolution peripheral quantitative computed tomography (HR-pQCT) was conducted to evaluate bone microarchitecture in PPGL patients and 76 age-, sex-matched healthy controls (30 males and 46 females). Areal bone mineral density (aBMD) was measured by dual-energy X-ray absorptiometry (DXA) simultaneously. RESULTS PPGL patients had a higher level of β-CTX. HR-pQCT assessment revealed that PPGL patients had notably thinner and more sparse trabecular bone (decreased trabecular number and thickness with increased trabecular separation), significantly decreased volume BMD (vBMD), and bone strength at both the radius and tibia compared with healthy controls. The deterioration of Tt.vBMD, Tb.Sp, and Tb.1/N.SD was more pronounced in postmenopausal patients compared with the premenopausal subjects. Moreover, subjects in the highest 24hUNE quartile (Q4) showed markedly lower Tb.N and higher Tb.Sp and Tb.1/N.SD at the tibia than those in the lowest quartile (Q1). Age-related bone loss was also exacerbated in PPGL patients to a certain extent. CONCLUSIONS PPGL patients had significantly deteriorated bone microarchitecture and strength, especially in the trabecular bone, with an increased bone resorption rate. Our findings provide clinical evidence that sympathetic overstimulation may serve as a secondary cause of osteoporosis, especially in subjects with increased sympathetic activity.
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Affiliation(s)
- W Qi
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - L Cui
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - R Jiajue
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - Q Pang
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - Y Chi
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - W Liu
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - Y Jiang
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - O Wang
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - M Li
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - X Xing
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - A Tong
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China.
| | - W Xia
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China.
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12
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Wen X, Zhao C, Zhao B, Yuan M, Chang J, Liu W, Meng J, Shi L, Yang S, Zeng J, Yang Y. Application of deep learning in radiation therapy for cancer. Cancer Radiother 2024; 28:208-217. [PMID: 38519291 DOI: 10.1016/j.canrad.2023.07.015] [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: 06/26/2023] [Revised: 07/17/2023] [Accepted: 07/18/2023] [Indexed: 03/24/2024]
Abstract
In recent years, with the development of artificial intelligence, deep learning has been gradually applied to clinical treatment and research. It has also found its way into the applications in radiotherapy, a crucial method for cancer treatment. This study summarizes the commonly used and latest deep learning algorithms (including transformer, and diffusion models), introduces the workflow of different radiotherapy, and illustrates the application of different algorithms in different radiotherapy modules, as well as the defects and challenges of deep learning in the field of radiotherapy, so as to provide some help for the development of automatic radiotherapy for cancer.
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Affiliation(s)
- X Wen
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - C Zhao
- School of Biomedical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai, China
| | - B Zhao
- Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - M Yuan
- Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - J Chang
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - W Liu
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - J Meng
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - L Shi
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - S Yang
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - J Zeng
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - Y Yang
- Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
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13
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Yang Q, Yi SH, Fu BS, Zhang T, Zeng KN, Feng X, Yao J, Tang H, Li H, Zhang J, Zhang YC, Yi HM, Lyu HJ, Liu JR, Luo GJ, Ge M, Yao WF, Ren FF, Zhuo JF, Luo H, Zhu LP, Ren J, Lyu Y, Wang KX, Liu W, Chen GH, Yang Y. [Clinical application of split liver transplantation: a single center report of 203 cases]. Zhonghua Wai Ke Za Zhi 2024; 62:324-330. [PMID: 38432674 DOI: 10.3760/cma.j.cn112139-20231225-00297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Objective: To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application. Methods: This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group (χ2=5.560,P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group (χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion: SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.
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Affiliation(s)
- Q Yang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - S H Yi
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - B S Fu
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - T Zhang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - K N Zeng
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - X Feng
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J Yao
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - H Tang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - H Li
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J Zhang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - Y C Zhang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - H M Yi
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - H J Lyu
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - J R Liu
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - G J Luo
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - M Ge
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - W F Yao
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - F F Ren
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J F Zhuo
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - H Luo
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - L P Zhu
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J Ren
- Ultrasound Department of the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - Y Lyu
- Ultrasound Department of the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - K X Wang
- Organ Donation Department of the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - W Liu
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - G H Chen
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - Y Yang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
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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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15
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Mi X, Michailidis AA, Shabani S, Miao KC, Klimov PV, Lloyd J, Rosenberg E, Acharya R, Aleiner I, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Malone FD, Martin O, McClean JR, McEwen M, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Roushan P, Smelyanskiy V, Abanin DA. Stable quantum-correlated many-body states through engineered dissipation. Science 2024; 383:1332-1337. [PMID: 38513021 DOI: 10.1126/science.adh9932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/13/2024] [Indexed: 03/23/2024]
Abstract
Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.
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Affiliation(s)
- X Mi
- Google Research, Mountain View, CA, USA
| | - A A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - S Shabani
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | - J Lloyd
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | | | - R Acharya
- Google Research, Mountain View, CA, USA
| | - I Aleiner
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - C Chou
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | - A G Dau
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | | | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Software and Information (QSI), Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | | | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | | | | | - A Morvan
- Google Research, Mountain View, CA, USA
| | | | | | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | | | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Google Research, Mountain View, CA, USA
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - R Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z J Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | - P Roushan
- Google Research, Mountain View, CA, USA
| | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
- Department of Physics, Princeton University, Princeton, NJ, USA
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16
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Liu W, Zhou W, Zhang Y, Ge X, Qi W, Lin T, Cao Q, Cao L. Strictureplasty may lead to increased preference in the surgical management of Crohn's disease: a case-matched study. Tech Coloproctol 2024; 28:40. [PMID: 38507096 DOI: 10.1007/s10151-024-02915-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/05/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Resection and strictureplasty are the two surgical modalities used in the management of Crohn's disease (CD). The objective of this study was to compare morbidity and clinical recurrence between patients who underwent strictureplasty and patients who underwent resection. METHODS Patients with CD who underwent strictureplasty between January 2012 and December 2022 were enrolled. The patients were well matched with patients who underwent resection without strictureplasty. Patient- and disease-specific characteristics, postoperative morbidity, and clinical recurrence were also analyzed. RESULTS A total of 118 patients who underwent a total of 192 strictureplasties were well matched to 118 patients who underwent resection. The strictureplasty group exhibited significantly less blood loss (30 ml versus 50 ml, p < 0.001) and stoma creation (2.5% versus 16.9%, p < 0.001). No significant difference was found regarding postoperative complications or length of postoperative stay. At the end of the follow-up, the overall rate of clinical recurrence was 39.4%, and no difference was observed between the two groups. Postoperative prophylactic use of biologics (odds ratio = 0.2, p < 0.001) was the only protective factor against recurrence. CONCLUSION Strictureplasty does not increase the risk of complications or recurrence compared with resection. It represents a viable alternative to resection in selected patients, and as such, it should have a broader scope of indications and greater acceptance among surgeons.
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Affiliation(s)
- W Liu
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - W Zhou
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China.
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
| | - Y Zhang
- School of Medicine, Shantou University, Shantou, 515063, Guangdong Province, China
| | - X Ge
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - W Qi
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - T Lin
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
| | - Q Cao
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - L Cao
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China.
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17
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Lin Y, Zhou S, Yang W, Han B, Liang X, Zhang Y, Zhang J, Han H, Guo B, Liu W, Yang X, Li X, Li L. Chromosomal mapping of a major genetic locus from Agropyron cristatum chromosome 6P that influences grain number and spikelet number in wheat. Theor Appl Genet 2024; 137:82. [PMID: 38489037 DOI: 10.1007/s00122-024-04584-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 02/03/2024] [Indexed: 03/17/2024]
Abstract
KEY MESSAGE A novel locus on Agropyron cristatum chromosome 6P that increases grain number and spikelet number was identified in wheat-A. cristatum derivatives and across 3 years. Agropyron cristatum (2n = 4x = 28, PPPP), which has the characteristics of high yield with multiple flowers and spikelets, is a promising gene donor for wheat high-yield improvement. Identifying the genetic loci and genes that regulate yield could elucidate the genetic variations in yield-related traits and provide novel gene sources and insights for high-yield wheat breeding. In this study, cytological analysis and molecular marker analysis revealed that del10a and del31a were wheat-A. cristatum chromosome 6P deletion lines. Notably, del10a carried a segment of the full 6PS and 6PL bin (1-13), while del31a carried a segment of the full 6PS and 6PL bin (1-8). The agronomic characterization and genetic population analysis confirmed that the 6PL bin (9-13) brought about an increase in grain number per spike (average increase of 10.43 grains) and spikelet number per spike (average increase of 3.67) over the three growing seasons. Furthermore, through resequencing, a multiple grain number locus was mapped to the physical interval of 593.03-713.89 Mb on chromosome 6P of A. cristatum Z559. The RNA-seq analysis revealed the expression of 537 genes in the del10a young spike tissue, with the annotation indicating that 16 of these genes were associated with grain number and spikelet number. Finally, a total of ten A. cristatum-specific molecular markers were developed for this interval. In summary, this study presents novel genetic material that is useful for high-yield wheat breeding initiatives to meet the challenge of global food security through enhanced agricultural production.
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Affiliation(s)
- Yida Lin
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Shenghui Zhou
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Wenjing Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Bing Han
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Xuezhong Liang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Yuxin Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Jinpeng Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Haiming Han
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Baojin Guo
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Weihua Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Xinming Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Xiuquan Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Lihui Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Agronomy, Northwest A&F University, Yangling, 712100, China.
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18
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Xing L, Lu Y, Zhang H, Shi Z, Chang S, Liu W, Kou J, Zhang H. Mediating effect of psychological capital on the relationship between mental health literacy and coping styles among newly recruited nurses. BMC Nurs 2024; 23:178. [PMID: 38486261 PMCID: PMC10938680 DOI: 10.1186/s12912-024-01828-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 02/26/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Newly recruited nurses face multiple sources of stress and their coping styles need to be focused on to ensure good mental health. This study aimed to examine the relationship among mental health literacy, psychological capital and coping styles in newly recruited nurses. METHODS A cross-sectional study was conducted in August and September 2022. A total of 315 newly recruited nurses were recruited in a tertiary hospital in Henan Province, central China, employing the convenience sampling method. The self-reported questionnaires were sent through a QR code, including the Mental Health Literacy Scale for Healthcare Students, Psychological Capital Questionnaire, and Simplified Coping Style Questionnaire. Pearson correlation analysis was used to evaluate the relationships among the variables. Mediation analysis was performed to identify the mediating effect of psychological capital on the relationship between mental health literacy and coping styles. RESULTS Positive coping showed a positive relationship with psychological capital and mental health literacy, while negative coping showed a negative relationship with psychological capital and mental health literacy. For positive coping, psychological capital was a partial mediator with an effect of 0.140, accounting for 62.8%. For negative coping, a full mediating effect was shown by psychological capital between mental health literacy and negative coping, with an indirect effect of -0.048. CONCLUSION Psychological capital plays a partial and complete mediating role between mental health literacy and different coping styles among newly recruited nurses. Diversified training and personalized guidance in improving mental health literacy and increasing psychological capital simultaneously can be provided to newly recruited nurses continuously to adjust their coping styles.
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Affiliation(s)
- Liyuan Xing
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Ying Lu
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Haixin Zhang
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Zhiyi Shi
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Shuying Chang
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Weihua Liu
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Jie Kou
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China
- Henan University People's Hospital, Zhengzhou, China
| | - Hongmei Zhang
- Department of Nursing, Henan Provincial People's Hospital, No.7, Weiwu Road, 450003, Zhengzhou, China.
- Department of Nursing, Zhengzhou University People's Hospital, Zhengzhou, China.
- Henan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China.
- Henan University People's Hospital, Zhengzhou, China.
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Liu W, Zhao TT, Feng S, Ma H, Sun JC, Wei MH. [Follicular dendritic cell sarcoma of the tonsil: a case report]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2024; 59:260-262. [PMID: 38561267 DOI: 10.3760/cma.j.cn115330-20230921-00109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- W Liu
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - T T Zhao
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - S Feng
- Department of Pathology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - H Ma
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - J C Sun
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - M H Wei
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
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Chen J, Zhang Z, Feng L, Liu W, Wang X, Chen H, Zou H. Lrg1 silencing attenuates ischemia-reperfusion renal injury by regulating autophagy and apoptosis through the TGFβ1- Smad1/5 signaling pathway. Arch Biochem Biophys 2024; 753:109892. [PMID: 38246328 DOI: 10.1016/j.abb.2024.109892] [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: 06/10/2023] [Revised: 12/27/2023] [Accepted: 01/11/2024] [Indexed: 01/23/2024]
Abstract
BACKGROUND Dysfunction in the processes of autophagy and apoptosis within renal tubular epithelial cells (RTEc) contributes to renal ischemia-reperfusion injury (IRI). However, the factors influencing this dysfunction remain unclear. Leucine-rich alpha-2-glycoprotein 1 (Lrg1) plays a role in the progression of diabetic nephropathy and kidney fibrosis by modulating the activin receptor-like kinase 1 (ALK1)-Smad1/5/8 and TGF-β1/Smad3 pathways, respectively. Therefore, we aimed to investigate whether Lrg1 is involved in the pathological mechanisms of renal IRI and whether its effects are related to the dysregulation of autophagy and apoptosis in RTEc. METHODS We conducted in vitro and in vivo experiments using CoCl2-induced hypoxic human kidney-2 (HK-2) cells and mice with renal IRI, respectively. Lrg1 was silenced using siRNA and lentiviral vectors in HK-2 cells and mouse kidneys. Rapamycin (Rapa) and methyladenine were applied to regulate autophagy in renal IRI models. RESULTS Increased Lrg1 expression was observed in hypoxic HK-2 cells and in the kidneys of mice with renal IRI. Silencing of Lrg1 through siRNA and lentiviral approaches restored autophagy and suppressed apoptosis in CoCl2-induced hypoxic HK-2 cells and renal IRI models. Additionally, reduced Lrg1 expression alleviated kidney damage caused by renal IRI. The downregulation of Lrg1 expression restrained the TGFβ-Smad1/5 signaling pathway in hypoxic-induced HK-2 cells and renal IRI by reducing ALK1 expression. Lastly, the enhancement of autophagy, achieved through Rapa treatment, provided protection against renal IRI in mice. CONCLUSIONS Our findings suggest that Lrg1 silencing can be applied as a potential therapeutic target to inhibit the TGFβ1-Smad1/5 pathway, thereby enhancing autophagy and decreasing apoptosis in patients with acute kidney injury.
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Affiliation(s)
- Jianhui Chen
- Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, 510630, China
| | - Zuoman Zhang
- Department of Neonatology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Ling Feng
- Department of Nephrology, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Weihua Liu
- Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, 510630, China
| | - Xin Wang
- Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, 510630, China
| | - Haishan Chen
- Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, 510630, China
| | - Hequn Zou
- Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, 510630, China; School of Medicine, The Chinese University of Hong Kong, Shenzhen, China.
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Gao M, Chen H, Cao F, Zhang L, Ruan Y, Liu W, Hong F, Luo J, Lin M. Association between beta-blocker utilization and heart failure mortality in the peritoneal dialysis population: a cohort study. Clin Kidney J 2024; 17:sfae022. [PMID: 38444751 PMCID: PMC10913941 DOI: 10.1093/ckj/sfae022] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Indexed: 03/07/2024] Open
Abstract
Background The prognostic significance of beta(β)-blocker therapy in patients at end-stage renal disease, specifically those receiving peritoneal dialysis (PD) and presenting with heart failure, remains inadequately elucidated due to limited research conducted thus far. Methods A retrospective analysis was performed on a cohort comprising 608 patients receiving PD between September 2007 and March 2019, with a subsequent follow-up period extending until December 2020. Cox regression and propensity score matching weighted analysis was used to model adjusted hazard ratios for β-blocker use with heart failure-related mortality. Competing risk analysis and subgroup analysis were carried out to further elucidate the correlation. Results β-blockers were prescribed for 56.1% of the peritoneal dialysis patients. Heart failure occurred in 43.4% of the total population and 15.5% of deaths were due to heart failure. The prescription of β-blockers was associated with a 43% lower adjusted hazard ratio (HR) for heart failure death within the cohort (95% confidence interval [CI] = 0.36-0.89; P = 0.013). Even after accounting for competing risk events, patients in the group using β-blockers demonstrated a significantly lower cumulative risk of heart failure-related mortality compared to those not using β-blockers (P = 0.007). This protective effect of β-blockers was also observed in subgroup analyses. Conversely, β-blocker use had no statistically significant associations with all-cause mortality. Conclusion The use of β-blockers was associated with a reduced risk of heart failure-related mortality in the PD population. Future randomized clinical trials are warranted to confirm the beneficial effect of β-blockers in the context of PD.
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Affiliation(s)
- Meizhu Gao
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Han Chen
- The Third Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Fang Cao
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
- Department of Nursing, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Li Zhang
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Yiping Ruan
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Weihua Liu
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Fuyuan Hong
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Jiewei Luo
- Department of Traditional Chinese Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
| | - Miao Lin
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China
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Shi L, Huang S, Liu W. Infection prevention in induction chemotherapy for childhood acute leukaemia. J Hosp Infect 2024; 145:226-227. [PMID: 38103693 DOI: 10.1016/j.jhin.2023.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/28/2023] [Accepted: 11/06/2023] [Indexed: 12/19/2023]
Affiliation(s)
- L Shi
- Key Laboratory of Paediatric Haematology, Children's Hospital Affiliated to Zhengzhou University/Henan Children's Hospital, Zhengzhou, People's Republic of China.
| | - S Huang
- Department of Hematology and Oncology, Children's Hospital Affiliated to Zhengzhou University/Henan Children's Hospital, Zhengzhou, People's Republic of China
| | - W Liu
- Department of Hematology and Oncology, Children's Hospital Affiliated to Zhengzhou University/Henan Children's Hospital, Zhengzhou, People's Republic of China
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Lai FTT, Liu W, Hu Y, Wei C, Chu RYK, Lum DH, Leung JCN, Cheng FWT, Chui CSL, Li X, Wan EYF, Wong CKH, Cheung CL, Chan EWY, Hung IFN, Wong ICK. Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination. QJM 2024; 117:125-132. [PMID: 37824396 DOI: 10.1093/qjmed/hcad236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 10/05/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association. AIM To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination. DESIGN Nested case-control study. METHODS We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity. RESULTS In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger. CONCLUSIONS We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.
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Affiliation(s)
- F T T Lai
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - W Liu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Y Hu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - C Wei
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - R Y K Chu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - D H Lum
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - J C N Leung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - F W T Cheng
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - C S L Chui
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
- School of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - X Li
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - E Y F Wan
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - C K H Wong
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - C L Cheung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - E W Y Chan
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - I F N Hung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - I C K Wong
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
- Aston Pharmacy School, Aston University, Birmingham, England, UK
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Liu Z, Liu W, Chen Z, Kang H. In vitro differentiation of human CD45 + CD34 + induced hematopoietic progenitor cells from iPSCs using a monolayer system. Transfus Apher Sci 2024; 63:103866. [PMID: 38182435 DOI: 10.1016/j.transci.2023.103866] [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: 04/18/2023] [Revised: 11/01/2023] [Accepted: 12/17/2023] [Indexed: 01/07/2024]
Abstract
Hematopoietic stem cells (HSCs) represent crucial target cells in the management of hematopoietic and immune system disorders. Unfortunately, the primary source of hematopoietic stem cells is limited. Hematopoietic stem cells derived from induced pluripotent stem cells (iPSCs) hold great promise for applications in cell therapy, disease modeling, and drug screening. To achieve a consistent induction method, one specific induction scheme capable of reliably generating CD34 and CD45 double-positive cells from iPSCs was optimized, employing a comparative analysis and screening of various induction methods. The comprehensive induction procedures are outlined in this document.
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Affiliation(s)
- Zhongfeng Liu
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing 100069, China; Department of General Surgery, Center for Thyroid and Breast Surgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Weihua Liu
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing 100069, China; Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen 518055, China
| | - Zhiguo Chen
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing 100069, China.
| | - Hua Kang
- Department of General Surgery, Center for Thyroid and Breast Surgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
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Liu C, Wang Y, Yu W, Xiang J, Ding G, Liu W. Comparative effectiveness of noninvasive therapeutic interventions for myofascial pain syndrome: a network meta-analysis of randomized controlled trials. Int J Surg 2024; 110:1099-1112. [PMID: 37939115 PMCID: PMC10871620 DOI: 10.1097/js9.0000000000000860] [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: 06/17/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND Myofascial pain syndrome (MPS) has an impact on physical health and quality of life for patients, with various noninvasive methods used for relieving myofascial pain. The authors aimed to compare the effectiveness of different noninvasive therapeutic interventions for MPS. MATERIALS AND METHODS The authors searched PubMed, Embase, CINAHL Complete, Web of Science, Cochrane, and Scopus to identify randomized controlled trials describing the effects of any noninvasive treatments in patients with MPS. The primary outcome was pain intensity, while pressure pain threshold and pain-related disability were secondary outcomes. RESULTS The analysis included 40 studies. Manual therapy [mean difference (MD) of pain: -1.60, 95% CI: -2.17 to -1.03; MD of pressure pain threshold: 0.52, 95% CI: 0.19 to 0.86; MD of pain-related disability: -5.34, 95% CI: -8.09 to -2.58], laser therapy (MD of pain: -1.15, 95% CI: -1.83 to -0.46; MD of pressure pain threshold: 1.00, 95% CI: 0.46 to 1.54; MD of pain-related disability: -4.58, 95% CI: -7.80 to -1.36), extracorporeal shock wave therapy (MD of pain: -1.61, 95% CI: -2.43 to -0.78; MD of pressure pain threshold: 0.84, 95% CI: 0.33 to 1.35; MD of pain-related disability: -5.78, 95% CI: -9.45 to -2.12), and ultrasound therapy (MD of pain: -1.54, 95% CI: -2.24 to -0.84; MD of pressure pain threshold: 0.77, 95% CI: 0.31 to 1.22) were more effective than no treatment. CONCLUSION Our findings support that manual therapy, laser therapy, and extracorporeal shock wave therapy could effectively reduce pain intensity, pressure pain threshold, and pain-related disability with statistical significance when compared with placebo. This finding may provide clinicians with appropriate therapeutic modalities for patients with MPS among different scenarios.
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Affiliation(s)
| | - Yang Wang
- Department of Plastic and Reconstructive Surgery, Cell and Matrix Research Institute, Kyungpook National University School of Medicine, Daegu, Korea
| | - Wenli Yu
- Department of Anesthesiology, Tianjin First Center Hospital, Tianjin, People’s Republic of China
| | | | - Guoyong Ding
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong
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Ding WH, Li YF, Liu W, Li W, Wu N, Hu SY, Shi JJ. Effect of occlusal stabilisation splint with or without arthroscopic disc repositioning on condylar bone remodelling in adolescent patients. Int J Oral Maxillofac Surg 2024; 53:156-164. [PMID: 37357072 DOI: 10.1016/j.ijom.2023.06.005] [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: 12/23/2022] [Revised: 06/03/2023] [Accepted: 06/06/2023] [Indexed: 06/27/2023]
Abstract
The aim of this study was to investigate the treatment effects of a stabilisation splint (SS) with and without arthroscopic disc repositioning (ADR) on condylar bone remodelling in adolescent patients with anterior disc displacement without reduction (ADDwoR). Cone beam computed tomography and magnetic resonance imaging were used to analyse condylar bone remodelling, condyle position, and disc position. Twenty-two temporomandibular joints of 14 patients who underwent ADR (age range 12-20 years; mean follow-up 12.5 ± 7.8 months) and 21 temporomandibular joints of 14 patients who did not undergo ADR (age range 13-20 years; mean follow-up 11.1 ± 5.1 months) were included. The change in bone volume (P < 0.001), rate of bone volume change (P < 0.001), and change in condyle height (P = 0.031) were significantly greater in patients with ADR than in those without ADR. The changes in posterior joint space (P = 0.013), superior joint space (P = 0.020), and ratio of condyle sagittal position (P = 0.013) were significantly greater in patients with ADR than in those without ADR. All discs in patients who underwent ADR and one disc in those who did not undergo ADR were backward repositioned. In conclusion, in adolescent patients with ADDwoR, ADR with SS therapy achieved better condyle and disc position than SS therapy alone, and also induced bone generation.
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Affiliation(s)
- W H Ding
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Y F Li
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China
| | - W Liu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - W Li
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - N Wu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - S Y Hu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - J J Shi
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China.
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Liu W, Lin C, Chen D, Niu L, Zhang R, Pi Z. Shape-margin knowledge augmented network for thyroid nodule segmentation and diagnosis. Comput Methods Programs Biomed 2024; 244:107999. [PMID: 38194766 DOI: 10.1016/j.cmpb.2023.107999] [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: 09/04/2023] [Revised: 11/11/2023] [Accepted: 12/26/2023] [Indexed: 01/11/2024]
Abstract
BACKGROUND AND OBJECTIVE Thyroid nodule segmentation is a crucial step in the diagnostic procedure of physicians and computer-aided diagnosis systems. However, prevailing studies often treat segmentation and diagnosis as independent tasks, overlooking the intrinsic relationship between these processes. The sequencial steps of these independent tasks in computer-aided diagnosis systems may lead to the accumulation of errors. Therefore, it is worth combining them as a whole by exploring the relationship between thyroid nodule segmentation and diagnosis. According to the diagnostic procedure of thyroid imaging reporting and data system (TI-RADS), the assessment of shape and margin characteristics is the prerequisite for radiologists to discriminate benign and malignant thyroid nodules. Inspired by TI-RADS, this study aims to integrate these tasks into a cohesive process, leveraging the insights from TI-RADS, thereby enhancing the accuracy and interpretability of thyroid nodule analysis. METHODS Specifically, this paper proposes a shape-margin knowledge augmented network (SkaNet) for simultaneous thyroid nodule segmentation and diagnosis. Due to the visual feature similarities between segmentation and diagnosis, SkaNet shares visual features in the feature extraction stage and then utilizes a dual-branch architecture to perform thyroid nodule segmentation and diagnosis tasks respectively. In the shared feature extraction, the combination of convolutional feature maps and self-attention maps allows to exploitation of both local information and global patterns in thyroid nodule images. To enhance effective discriminative features, an exponential mixture module is introduced, combining convolutional feature maps and self-attention maps through exponential weighting. Then, SkaNet is jointly optimized by a knowledge augmented multi-task loss function with a constraint penalty term. The constraint penalty term embeds shape and margin characteristics through numerical computations, establishing a vital relationship between thyroid nodule diagnosis results and segmentation masks. RESULTS We evaluate the proposed approach on a public thyroid ultrasound dataset (DDTI) and a locally collected thyroid ultrasound dataset. The experimental results reveal the value of our contributions and demonstrate that our approach can yield significant improvements compared with state-of-the-art counterparts. CONCLUSIONS SkaNet highlights the potential of combining thyroid nodule segmentation and diagnosis with knowledge augmented learning into a unified framework, which captures the key shape and margin characteristics for discriminating benign and malignant thyroid nodules. Our findings suggest promising insights for advancing computer-aided diagnosis joint with segmentation.
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Affiliation(s)
- Weihua Liu
- School of Medical Technology, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian, 100081, Beijing, China; AthenaEyesCO., LTD., Building 14, No. 39 Jianshan Road, Changsha, 410205, Hunan, China.
| | - Chaochao Lin
- School of Computer Science and Technology, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian, 100081, Beijing, China.
| | - Duanduan Chen
- School of Medical Technology, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian, 100081, Beijing, China.
| | - Lijuan 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, No. 17 Nanli, Panjiayuan, Chaoyang, 100021, Beijing, China.
| | - Rui Zhang
- Department of Ultrasound, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Nanli, Panjiayuan, Chaoyang, 100021, Beijing, China.
| | - Zhaoqiong Pi
- Xiangya School of Medicine, Central South University, No. 172, Tongzipo Road, Changsha, 410083, Hunan, China.
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Liu W, Cai L, Li Y. Application of natural language processing to post-structuring of rectal cancer MRI reports. Clin Radiol 2024; 79:e204-e210. [PMID: 38042740 DOI: 10.1016/j.crad.2023.10.032] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/20/2023] [Accepted: 10/26/2023] [Indexed: 12/04/2023]
Abstract
AIM To evaluate a natural language processing (NLP) system for extracting structured information from the free-form text of rectal cancer magnetic resonance imaging (MRI) reports written in Chinese. MATERIALS AND METHODS A rule-based NLP model that could extract 11 key image features of rectal cancer was constructed using 358 MRI reports of rectal cancer written between 2015 and 2021. Fifty reports written before 2015 and 50 written after 2021 were used as test datasets, and the reference standard was determined by manual extraction of information by two radiologists. The length and reporting rate of image features in pre-2015 and post-2021 datasets, as well as the accuracy, precision, recall, and F1 score of feature extraction by the NLP system, were compared. The time required for the NLP to extract data was compared with that required by the radiologists. RESULTS Reports written after 2021 had longer diagnostic impression sections than reports written before 2015. The reporting rate of key imaging features of rectal cancer was 36.55% before 2015 and 79.82% after 2021. The accuracy, precision, recall, and F1 score of NLP for correct extraction of values from reports were 93.82%, 95.63%, 87.06%, and 91.15%, respectively, for pre-2015 reports, and 92.55%, 98.53%, 94.15%, and 96.29%, respectively, for post-2021 reports. NLP generated all the structured information in <1 second. CONCLUSIONS The NLP system with rule-based pattern matching achieved rapid and accurate structured processing of rectal cancer MRI reports. MRI reports with structured templates are more suitable for NLP-based extraction of information.
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Affiliation(s)
- W Liu
- Department of Radiology, Aerospace Center Hospital, Beijing, 100049, China; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - L Cai
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Y Li
- Department of General Surgery, Aerospace Center Hospital, Beijing, 100049, China.
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Guo Y, Wang J, Liu W, Liu J, Wang C, Wu Q, Wang Z. Construction of magnetic hydroxyl group-enriched hyper cross-linked polymers with functional triazine as the core for efficient enrichment of plant growth regulators. Food Chem 2024; 433:137309. [PMID: 37683476 DOI: 10.1016/j.foodchem.2023.137309] [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: 06/09/2023] [Revised: 08/07/2023] [Accepted: 08/26/2023] [Indexed: 09/10/2023]
Abstract
The determination of trace plant growth regulators (PGRs) residues in water and food samples make it crucial to develop novel sample pretreatment methods for the enrichment of PGRs. Herein, a novel magnetic hyper cross-linked polymer (M-CTT-9OH-HCP) was constructed and served as a magnetic adsorbent for the efficient extraction of some PGRs from water, watermelon, tomatoes, and milk samples for the first time. Combined with high performance liquid chromatography-fluorescence detection (HPLC-FLD), the established method presented a good linearity (0.03-60.0 ng g-1 (ng mL-1), (r) ≥ 0.9973), satisfactory accuracy with method recoveries (83.0%-119%) and acceptable precision with the intra-day and inter-day variations (expressed as the relative standard deviations (RSDs) ≤ 9.8%). The limits of detection (LODs) and limits of quantitation (LOQs) were in the range of 0.01-1.50 and 0.03-5.00 ng g-1/ ng mL-1. The results show that the established method is sensitive and efficient for the determination of PGRs in real samples.
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Affiliation(s)
- Yaxing Guo
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China; Department of Chemistry, College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Juntao Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Weihua Liu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Jiajia Liu
- China Petroleum Engineering & Construction Corp. North China Company, Renqiu 062550, Hebei, China
| | - Chun Wang
- Department of Chemistry, College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Qiuhua Wu
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China; Department of Chemistry, College of Science, Hebei Agricultural University, Baoding 071001, China.
| | - Zhi Wang
- College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China; Department of Chemistry, College of Science, Hebei Agricultural University, Baoding 071001, China.
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Lin J, Zhang Y, Lin S, Ding H, Liu W. Integrating Network Pharmacology and Experimental Verification to Explore the Pharmacological Mechanisms of Cordycepin against Pulmonary Arterial Hypertension in Rats. Comb Chem High Throughput Screen 2024; 27:CCHTS-EPUB-138146. [PMID: 38299286 DOI: 10.2174/0113862073267432230925112002] [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: 06/15/2023] [Revised: 07/28/2023] [Accepted: 08/09/2023] [Indexed: 02/02/2024]
Abstract
BACKGROUND Pulmonary Arterial Hypertension (PAH) is a fatal disease with high morbidity and mortality. Cordycepin has anti-inflammatory, antioxidant and immune enhancing effects. However, the role of Cordycepin in the treatment of PAH and its mechanism is not clear. METHODS The Cordycepin structure and PAH-related gene targets were obtained from public databases. The KEGG and GO enrichment analysis of common targets was performed in DAVID. PPI networks were also mapped using the STRING platform. AutoDock Vina, AutoDockTools, ChemBio3D and Pymol tools were selected for molecular docking of key targets. The therapeutic effects of Cordycepin on PAH were observed in Monocrotaline(MCT)-induced PAH rats and platelet-derived growth factor BB (PDGFBB)-induced rat pulmonary artery smooth muscle cells (PASMCs). The right ventricular systolic pressure (RVSP) was detected. HE staining, Western Blot, Scratch assay, EDU and TUNEL assays were used respectively. RESULTS Through Network Pharmacology and molecular docking , the Cordycepin-PAH core genes were found to be TP53, AKT1, CASP3, BAX and BCL2L1. In MCT-induced PAH rats, the administration of Cordycepin significantly reduced RVSP, and inhibited pulmonary vascular remodeling. In PDGFBB-induced PASMCs, Cordycepin reduced the migration and proliferation of PASMCs and promoted apoptosis. After the Cordycepin treatment, the protein expressions of TP53, Cleaved CASP3 and BAX were significantly increased, while the protein expressions of p-AKT1 and BCL2L1 were significantly decreased in MCT-PAH rats and PDGFBB-induced PASMCs. CONCLUSION This study identified that TP53, AKT1, CASP3, BAX, and BCL2L1 were the potential targets of Cordycepin against PAH by ameliorating pulmonary vascular remodeling, inhibiting the abnormal proliferation and migration of PASMCs and increasing apoptosis of PASMCs. which provided a new understanding of the pharmacological mechanisms of Cordycepin in the treatment of PAH.
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Affiliation(s)
- Jiangpeng Lin
- Department of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China,510260
| | - Yuzhuo Zhang
- Department of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China,510260
| | - Shuangfeng Lin
- The first Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China, 510405
| | - Haiming Ding
- Department of Laboratory Medicine, Panyu Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Weihua Liu
- Department of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China,510260
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Liu X, Onda M, Schlomer J, Bassel L, Kozlov S, Tai CH, Zhou Q, Liu W, Tsao HE, Hassan R, Ho M, Pastan I. Tumor resistance to anti-mesothelin CAR-T cells caused by binding to shed mesothelin is overcome by targeting a juxtamembrane epitope. Proc Natl Acad Sci U S A 2024; 121:e2317283121. [PMID: 38227666 PMCID: PMC10823246 DOI: 10.1073/pnas.2317283121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 11/27/2023] [Indexed: 01/18/2024] Open
Abstract
Despite many clinical trials, CAR-T cells are not yet approved for human solid tumor therapy. One popular target is mesothelin (MSLN) which is highly expressed on the surface of about 30% of cancers including mesothelioma and cancers of the ovary, pancreas, and lung. MSLN is shed by proteases that cleave near the C terminus, leaving a short peptide attached to the cell. Most anti-MSLN antibodies bind to shed MSLN, which can prevent their binding to target cells. To overcome this limitation, we developed an antibody (15B6) that binds next to the membrane at the protease-sensitive region, does not bind to shed MSLN, and makes CAR-T cells that have much higher anti-tumor activity than a CAR-T that binds to shed MSLN. We have now humanized the Fv (h15B6), so the CAR-T can be used to treat patients and show that h15B6 CAR-T produces complete regressions in a hard-to-treat pancreatic cancer patient derived xenograft model, whereas CAR-T targeting a shed epitope (SS1) have no anti-tumor activity. In these pancreatic cancers, the h15B6 CAR-T replicates and replaces the cancer cells, whereas there are no CAR-T cells in the tumors receiving SS1 CAR-T. To determine the mechanism accounting for high activity, we used an OVCAR-8 intraperitoneal model to show that poorly active SS1-CAR-T cells are bound to shed MSLN, whereas highly active h15B6 CAR-T do not contain bound MSLN enabling them to bind to and kill cancer cells.
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Affiliation(s)
- X.F. Liu
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - M. Onda
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - J. Schlomer
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - L. Bassel
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - S. Kozlov
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - C.-H. Tai
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Q. Zhou
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - W. Liu
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - H.-E. Tsao
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - R. Hassan
- Thoracic and Gastrointestinal Malignancies Branch, National Cancer Institute, NIH, Bethesda, MD20892
| | - M. Ho
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - I. Pastan
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
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Parshina EY, Liu W, Yusipovich AI, Gvozdev DA, He Y, Pirutin SK, Klimanova EA, Maksimov EG, Maksimov GV. Spectral and conformational characteristics of phycocyanin associated with changes of medium pH. Photosynth Res 2024:10.1007/s11120-023-01068-0. [PMID: 38224422 DOI: 10.1007/s11120-023-01068-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 12/09/2023] [Indexed: 01/16/2024]
Abstract
C-phycocyanin (C-PC) is the main component of water-soluble light-harvesting complexes (phycobilisomes, PBS) of cyanobacteria. PBS are involved in the absorption of quantum energy and the transfer of electronic excitation energy to the photosystems. A specific environment of C-PC chromophoric groups is provided by the protein matrix structure including protein-protein contacts between different subunits. Registration of C-PC spectral characteristics and the fluorescence anisotropy decay have revealed a significant pH influence on the chromophore microenvironment: at pH 5.0, a chromophore is more significantly interacts with the solvent, whereas at pH 9.0 the chromophore microenvironment becomes more viscous. Conformations of chromophores and the C-PC protein matrix have been studied by Raman and infrared spectroscopy. A decrease in the medium pH results in changes in the secondary structure either the C-PC apoproteins and chromophores, the last one adopts a more folded conformation.
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Affiliation(s)
- E Yu Parshina
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China.
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991.
| | - W Liu
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China
| | - A I Yusipovich
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - D A Gvozdev
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - Y He
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China
| | - S K Pirutin
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
- Institute of Theoretical and Experimental Biophysics of Russian Academy of Sciences, Institutskaya St. 3, Pushchino, Russia, 142290
| | - E A Klimanova
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - E G Maksimov
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - G V Maksimov
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
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Ren H, Wang Z, Shang X, Zhang X, Ma L, Bian Y, Wang D, Liu W. Involvement of GA3-oxidase in inhibitory effect of nitric oxide on primary root growth in Arabidopsis. Plant Biol (Stuttg) 2024; 26:117-125. [PMID: 38014496 DOI: 10.1111/plb.13600] [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: 09/19/2023] [Accepted: 11/13/2023] [Indexed: 11/29/2023]
Abstract
Both NO and GAs are essential for regulating various physiological processes and stress responses in plants. However, the interaction between these two molecules remains unclear. We investigated the distinct response patterns of Arabidopsis thaliana Col-0 and GA synthesis functional deficiency mutants to NO by measuring root length. To investigate underlying mechanisms, we detected bioactive GA content using UHPLC-ESI-MS/MS, assessed the accumulation of ROS by chemical staining Arabidopsis roots. We also conducted RNA-seq analysis and compared results between Col-0 and ga3ox1, with and without SNP (as NO donor) treatment. Phenotypic results revealed that the inhibitory effect of NO on primary roots of Arabidopsis was primarily mediated by GA3-oxidase, rather than GA20-oxidase or GA2-oxidase. The content of GA3 decreased in Col-0 treated with SNP, whereas this decrease was not observed in ga3ox1. The deficiency of GA3-oxidase alleviated the buildup of H2 O2 in roots when treated with SNP. We identified 222 DEGs. GO annotation of these DEGs revealed that all top 20 GO terms were related to stress responses. Moreover, three DEGs were annotated to GA-related processes (DDF1, DDF2, EXPA1), and seven DEGs were associated with root development (RAV1, RGF2, ERF71, ZAT6, MYB77, XT1, and DTX50). In summary, NO inhibits primary root growth partially by repressing GA3-oxidase catalysed GA3 synthesis in Arabidopsis. ROS, Ca2+ , DDF1, DDF2, EXPA1 and seven root development-related genes may be involved in crosstalk between NO and GAs.
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Affiliation(s)
- H Ren
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - Z Wang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - X Shang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - X Zhang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - L Ma
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - Y Bian
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - D Wang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - W Liu
- Shanxi Normal University, Taiyuan, Shanxi, China
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Zeng HQ, Li G, Zhou KX, Li AD, Liu W, Zhang Y. Causal link between gut microbiota and osteoporosis analyzed via Mendelian randomization. Eur Rev Med Pharmacol Sci 2024; 28:542-555. [PMID: 38305631 DOI: 10.26355/eurrev_202401_35052] [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: 02/03/2024]
Abstract
OBJECTIVE Osteoporosis (OP) is closely associated with gut microbiota (GM), yet the nature of their causal relationship remains elusive. Therefore, this study aims to reverse causality between GM and OP by using population cohorts and two-sample MR (TSMR) analysis. MATERIALS AND METHODS In this study, we conducted an extensive genome-wide association study (GWAS) using publicly accessible summary statistics data for GM and OP. Employing rigorous criteria (p < 1*e-5), we identified independent genetic loci that exhibited significant associations with GM relative abundances as instrumental variables (IVs). A causal evaluation was primarily carried out using the inverse variance-weighted (IVW) method, supplemented by additional analyses such as MR-Egger, weighted median, simple mode, and weighted mode. RESULTS We unveiled that increased abundances of the family Pasteurellaceae, order Pasteurellales, and genus Ruminococcaceae UCG004 were linked to an increased risk of OP. Conversely, the family Oxalobacteraceae, unknown family id.1000006161, genus Lachnospiraceae NK4A136 group, unknown genus id.1000006162, and order NB1n were associated with a reduced risk of OP. To ensure the reliability of our findings, we conducted quality assessments through Cochrane's Q test and a leave-one-out analysis. Furthermore, the stability and consistency of the results were confirmed by the MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) global test, and sensitivity analysis (p > 0.05). Our study reveals the causal relationships between 211 GM taxa and OP, pinpointing specific GM taxa associated with the risk of OP. This research sheds light on the genetic mechanisms that underlie GM-mediated OP and opens up promising avenues for identifying valuable biomarkers and potential therapeutic targets in future OP research. CONCLUSIONS This study establishes a substantial GM-OP link with specific taxa being identified, offering biomarkers for early detection, tailored interventions, and improved patient education. These findings enhance OP diagnosis, prevention, and treatment, promising more effective, individualized care and inspiring future research.
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Affiliation(s)
- H-Q Zeng
- Traditional Chinese Medicine Department of Rheumatism, Women and Children Health Institute Futian Shenzhen, Shenzhen, China.
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Nian Z, Zhao Q, He Y, Xie R, Liu W, Chen T, Huang S, Dong L, Huang R, Yang L. Efficacy and Safety of First-line Therapies for Advanced Unresectable Oesophageal Squamous Cell Cancer: a Systematic Review and Network Meta-analysis. Clin Oncol (R Coll Radiol) 2024; 36:30-38. [PMID: 37827946 DOI: 10.1016/j.clon.2023.09.011] [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: 06/15/2023] [Revised: 08/27/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023]
Abstract
AIM To compare the clinical efficacy and safety of first-line treatments for advanced unresectable oesophageal squamous cell cancer. MATERIALS AND METHODS A systematic review and network meta-analysis was carried out by retrieving and retaining relevant literature from databases. The studies were randomised controlled trials comparing first-line treatments for advanced unresectable oesophageal squamous cell cancer. A Bayesian network meta-analysis was used to assess clinical outcomes. RESULTS Nine studies including 4499 patients receiving first-line treatments were analysed. For all populations, toripalimab plus chemotherapy tended to provide the best overall survival (hazard ratio 0.58, 95% confidence intervals 0.43-0.78) and sintilimab plus chemotherapy provided the best progression-free survival (0.56, 0.46-0.68). Nivolumab plus chemotherapy presented the best objective response rate (odds ratio 2.45, 1.78-3.42) and camrelizumab plus chemotherapy (0.47, 0.29-0.74) appeared to be the safest. Sintilimab plus chemotherapy (0.55, 0.40-0.75) and nivolumab (0.54, 0.37-0.80) plus chemotherapy had the best overall survival in programmed death ligand 1 (PD-L1) tumour proportion score <1% and ≥1% subgroups. Toripalimab plus chemotherapy (0.61, 0.40-0.93) and pembrolizumab (0.57, 0.43-0.75) were the best in overall survival in combined positive score <10 and ≥10 subgroups, respectively. Toripalimab plus chemotherapy showed the best overall survival in the Asian group; pembrolizumab presented better overall survival in the Asian population than the non-Asian group. CONCLUSION Most immunotherapy combined with chemotherapy showed superior clinical benefits and sintilimab plus chemotherapy, toripalimab plus chemotherapy and tislelizumab plus chemotherapy had better comprehensive clinical efficacy. PD-L1 expression detection and ethnicity differences are still of great significance and most suitable regimens varied from each subgroup.
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Affiliation(s)
- Z Nian
- School of Pharmacy, Fujian Medical University, Fuzhou, China
| | - Q Zhao
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - Y He
- School of Pharmacy, Fujian Medical University, Fuzhou, China
| | - R Xie
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - W Liu
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - T Chen
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - S Huang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - L Dong
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - R Huang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - L Yang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
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Ji Q, Lian W, Meng Y, Liu W, Zhuang M, Zheng N, Karlsson IK, Zhan Y. Cytomegalovirus Infection and Alzheimer's Disease: A Meta-Analysis. J Prev Alzheimers Dis 2024; 11:422-427. [PMID: 38374748 DOI: 10.14283/jpad.2023.126] [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] [Indexed: 02/21/2024]
Abstract
BACKGROUND Evidence on the association of cytomegalovirus (CMV) infection with Alzheimer's disease (AD) is scarce and the results are inconsistent. OBJECTIVE To investigate the association of CMV infection with the risk of AD. METHODS Observational studies on the relationship between CMV infection and AD were identified from PubMed, Embase, Web of Science, and the Cochrane Library until September 30, 2022. The quality of included studies was assessed using the Newcastle-Ottawa Scale. Random-effect meta-analysis was performed using a generic inverse-variance method, followed by sensitivity analyses and subgroup analyses based on study designs, regions, adjustments, and population types. RESULTS Our search yielded 870 articles, of which 200 were duplicates and 663 did not meet the inclusion criteria, and finally yielded seven studies with 6,772 participants. No strong evidence was observed in the summary analysis for the association of CMV infection and risk of AD (odds ratio [OR] = 1.33; 95% confidence interval [CI]: 0.88, 2.03, I2 =69.9%). However, subgroup analysis showed that an increased risk of AD was detected in East Asians (OR = 2.39; 95% CI: 1.63, 3.50, I2 = 0.00%), cohort studies (OR = 1.99; 95% CI: 1.35, 2.94, I2 = 28.20%), and studies with confounder adjustment (OR = 2.05; 95% CI: 1.52, 2.77, I2 = 0.00%). CONCLUSIONS This meta-analysis provides evidence to support the heterogeneity of the associations between CMV infection and AD. Future studies with larger sample sizes and multi-ethnic populations are necessary.
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Affiliation(s)
- Q Ji
- Yiqiang Zhan, Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China; Tel: 0755-23260106; E-mail:
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Dai Y, Liu W, Hong F. Post reversible encephalopathy syndrome attributed to mycophenolate mofetil used in the treatment of SLE: A case report and review of literature. J Int Med Res 2024; 52:3000605231218620. [PMID: 38156668 PMCID: PMC10757442 DOI: 10.1177/03000605231218620] [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: 09/13/2023] [Accepted: 11/13/2023] [Indexed: 01/03/2024] Open
Abstract
Posterior reversible encephalopathy syndrome (PRES) is a rare clinical disease, which has been seen in patients with systemic lupus erythematosus (SLE). Its main manifestations are seizure, headache and other neurological symptoms. While the condition is reversible, if not treated in time, there can be risks of cerebral haemorrhage. We report here the case of a young patient with SLE who developed PRES after receiving the immunosuppressant, mycophenolate mofetil. Neurological symptoms, signs, or changes in a patient's condition that cannot be explained by lupus, should alert physicians to the possibility of the drug causing PRES, and prompt discontinuation should ensue.
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Affiliation(s)
- Yiping Dai
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China
| | - Weihua Liu
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Fuyuan Hong
- Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
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Li M, Dong Y, Wang Q, Hao L, Liu W, Wang C, Wang Z, Wu Q. A chitin-based magnetic hyper-cross-linked polymer for highly efficient enrichment of neonicotinoids in lemon juice and tomatoes. Int J Biol Macromol 2024; 256:128423. [PMID: 38008138 DOI: 10.1016/j.ijbiomac.2023.128423] [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: 09/28/2023] [Revised: 11/15/2023] [Accepted: 11/23/2023] [Indexed: 11/28/2023]
Abstract
A chitin-based magnetic hyper-cross-linked polymer (labeled as Ch-MHCP) has been successfully synthesized and utilized for highly-effective solid-phase extraction of neonicotinoid insecticides (NEOs). The extraction capability of Ch-MHCP for four common NEOs is higher than that of four commercial sorbents including octadecyl-silane C18, oasis hydrophilic/lipophilic balanced sorbent, oasis mixed anion sorbent and poly-phenylacetic mixed anion sorbent. The large number of hydroxyl and amide groups as well as benzene rings in Ch-MHCP allow the H-bond and π-π* interaction to be the principal adsorption mechanism of Ch-MHCP for NEOs. Besides, polar interaction was also involved in the adsorption process. In combination of Ch-MHCP based extraction technique with high-performance liquid chromatography, a novel analytical method for sensitive detection of NEOs in lemon juice and tomatoes has been established. At optimal conditions, wide linear ranges were obtained to be 0.20-100 ng mL-1 for lemon juice and 0.80-1000 ng g-1 for tomatoes. The detection limits were 0.06-0.12 ng mL-1 for lemon juice and 0.24-0.60 ng g-1 for tomatoes. This work not only provides a powerful tool for simultaneously detecting four NEOs in lemon juice and tomatoes, but also offers a new insight into the preparation of bio-based magnetic sorbents for adsorption/removal of pollutants.
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Affiliation(s)
- Meng Li
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Yanli Dong
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Qianqian Wang
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Lin Hao
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Weihua Liu
- College of Science, Hebei Agricultural University, Baoding 071001, China
| | - Chun Wang
- College of Science, Hebei Agricultural University, Baoding 071001, China.
| | - Zhi Wang
- College of Science, Hebei Agricultural University, Baoding 071001, China; College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China
| | - Qiuhua Wu
- College of Science, Hebei Agricultural University, Baoding 071001, China; College of Food Science and Technology, Hebei Agricultural University, Baoding 071001, China.
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He Q, Liu W, Chen Z, Wei G, Jiang J, Zhang L, Zhou L. Resveratrol modulates the Nrf2/NF-κB pathway and inhibits TSLP-mediated atopic march. Allergol Immunopathol (Madr) 2024; 52:1-8. [PMID: 38186188 DOI: 10.15586/aei.v52i1.963] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 09/25/2023] [Indexed: 01/09/2024]
Abstract
BACKGROUND Resveratrol has been found to have anti-inflammatory and anti-allergic properties. The effects of resveratrol on thymic stromal lymphopoietin (TSLP)-mediated atopic march remain unclear. PURPOSE To explore the potential role of resveratrol in TSLP-mediated atopic march. METHODS The atopic march mouse model was established by topical application of MC903 (a vitamin D3 analog). Following the treatment with resveratrol, airway resistance in mice was discovered by pulmonary function apparatus, and the number of total cells, neutrophils, and eosinophils in bronchoalveolar lavage fluid was counted. The histopathological features of pulmonary and ear skin tissues, inflammation, and cell infiltration were determined by hematoxylin and eosin staining. The messenger RNA (mRNA) levels of TSLP, immunoglobulin E, interleukin (IL)-4, IL-5, and IL-13 were measured by real-time quantitative polymerase chain reaction. The protein expression of nuclear factor kappa B (NF-κB)/nuclear factor erythroid 2-related factor 2 (Nrf2) signaling-associated molecules (p-p65, p65, p-I kappa B kinase alpha (IκBα), IκBα, Nrf2, and TSLP) in lung and ear skin tissues were assessed by Western blot analysis. RESULTS Resveratrol attenuated airway resistance and infiltration of total cells, eosinophils, and neutrophils in both lung and ear skin tissues. Resveratrol ameliorates serum inflammatory markers in allergic mice. Moreover, the phosphorylation levels of NF-κB pathway-related proteins were significantly reduced by administration of resveratrol in allergic lung and ear skin tissues. Similarly, the protein expression of TSLP in both lung and ear skin tissues was reduced by resveratrol, and Nrf2, a protector molecule, was increased with resveratrol treatment. CONCLUSION Resveratrol attenuates TSLP-reduced atopic march through ameliorating inflammation and cell infiltration in pulmonary and ear skin tissues by inhibiting the abnormal activation of NF-κB signaling pathway.
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Affiliation(s)
- Quan He
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Respiratory and Critical Care Medicine, Zhenjiang Hospital of Integrated Traditional Chinese and Western Medicine, Zhenjiang, Jiangsu, China
| | - Weihua Liu
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zi Chen
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Guangfei Wei
- Clinical Research Center (CRC), Zhenjiang Hospital of Integrated Traditional Chinese and Western Medicine, Zhenjiang, Jiangsu, China
| | - Jingxian Jiang
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Liuchao Zhang
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Linfu Zhou
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China;
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Wang C, Li M, Chen X, Wang Q, Li S, Liu W, Hao L, Wu Q, Shi X. Preparation of amino-functionalized triazine-based hyper-crosslinked polymer for efficient adsorption of endocrine disruptors. Talanta 2024; 266:125142. [PMID: 37660619 DOI: 10.1016/j.talanta.2023.125142] [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: 07/02/2023] [Revised: 08/17/2023] [Accepted: 08/29/2023] [Indexed: 09/05/2023]
Abstract
Herein, two novel amino-functionalized triazine-based hyper-crosslinked porous polymer (NH2-HCPs) (named as DPT-BB, DPT-DX) were designed and synthesized by direct crosslinking of 2,4-diamino-6-phenyl-1,3,5-triazine (DPT) with 4,4'-bis(chloromethyl)-1,1'-biphenyl (BB) or α, α'-dichloro-p-xylene (DX). Thanks to the amino functional group and hyper-crosslinked porous structure, NH2-HCPs displayed remarkable adsorption ability for phenolic EDCs. The adsorption mechanism mainly involved hydrogen bond, π-π interaction, hydrophobic interaction and pore filling. Thus DPT-BB was applied as solid phase extraction sorbent to extract phenolic EDCs from water and orange juice samples prior to quantitative analysis by high performance liquid chromatography. Under the optimal conditions, detection limit as low as 0.07-0.2 ng mL-1 for water and 0.1-0.27 ng mL-1 for orange juice was achieved. Good recoveries spanned the range of 83.5%-114% were obtained for spiked samples, with relative standard deviations below 8.9%. The results demonstrated that the developed method displayed excellent practicability for sensitive analysis of EDCs.
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Affiliation(s)
- Chenhuan Wang
- Department of Chemistry, University of South Florida, Tampa, FL, 33620, United States
| | - Min Li
- College of Science, Hebei Agricultural University, Baoding, 071001, China
| | - Xiaocui Chen
- College of Science, Hebei Agricultural University, Baoding, 071001, China
| | - Qianqian Wang
- College of Science, Hebei Agricultural University, Baoding, 071001, China
| | - Shuofeng Li
- College of Science, Hebei Agricultural University, Baoding, 071001, China
| | - Weihua Liu
- College of Science, Hebei Agricultural University, Baoding, 071001, China
| | - Lin Hao
- College of Science, Hebei Agricultural University, Baoding, 071001, China
| | - Qiuhua Wu
- College of Science, Hebei Agricultural University, Baoding, 071001, China.
| | - Xiaodong Shi
- Department of Chemistry, University of South Florida, Tampa, FL, 33620, United States.
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Ji L, Ahmann AJ, Ahrén B, Capehorn MS, Hu P, Lingvay I, Liu W, Rodbard HW, Shen Z, Sorli C. Proportion of participants with type 2 diabetes achieving a metabolic composite endpoint with once-weekly semaglutide treatment versus comparators: Post hoc pooled analysis from SUSTAIN 1-5, 7-10 and SUSTAIN China. Diabetes Obes Metab 2024; 26:233-241. [PMID: 37822270 DOI: 10.1111/dom.15309] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/15/2023] [Indexed: 10/13/2023]
Abstract
AIM To compare the proportion of participants with type 2 diabetes (T2D) treated with once-weekly (OW) subcutaneous (SC) semaglutide versus comparators who achieved a composite metabolic endpoint. MATERIALS AND METHODS SUSTAIN 1-5, 7-10 and SUSTAIN China trial data were pooled. Participants with T2D (aged ≥18 years) and glycated haemoglobin ≥7.0% (≥53 mmol/mol) who had been randomized to OW SC semaglutide (0.5 or 1.0 mg) or comparator in addition to background medication. Using patient-level data pooled by treatment, proportions of participants achieving the metabolic composite endpoint, defined as glycated haemoglobin <7% (<53 mmol/mol), blood pressure <140/90 mmHg and non-high-density lipoprotein cholesterol <130 mg/dl (<3.37 mmol/L), were evaluated following baseline adjustments. Endpoints were analysed per trial using a binomial logistic regression model with treatment, region/country and stratification factor as fixed effects and baseline value as covariate. Pooled analysis used logistic regression with treatment and trial as fixed effects and baseline value as covariate. RESULTS This post hoc analysis included data from 7633 participants across 10 trials. The proportion of participants who achieved the metabolic composite endpoint was significantly higher with OW SC semaglutide 0.5 and 1.0 mg versus comparators (23.7% and 32.0% vs. 11.5%, respectively; p < .0001). Likewise, when the OW SC semaglutide doses were pooled, significantly higher proportions of patients receiving semaglutide achieved the composite metabolic endpoint versus comparators (29.1% vs. 11.4%, respectively; p < .0001). CONCLUSIONS Treatment with OW SC semaglutide versus comparators was associated with increased proportions of participants with T2D meeting the composite metabolic endpoint.
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Affiliation(s)
- Linong Ji
- Peking University People's Hospital, Beijing, China
| | - A J Ahmann
- Oregon Health and Science University, Portland, Oregon, USA
| | - B Ahrén
- Lund University, Lund, Sweden
| | | | - P Hu
- Novo Nordisk (Shanghai) Pharma Trading Co., Ltd, Beijing, China
| | - I Lingvay
- University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - W Liu
- Novo Nordisk (Shanghai) Pharma Trading Co., Ltd, Beijing, China
| | - H W Rodbard
- Endocrine and Metabolic Consultants, Rockville, Maryland, USA
| | - Z Shen
- Novo Nordisk (Shanghai) Pharma Trading Co., Ltd, Beijing, China
| | - C Sorli
- Acerus Pharma, Toronto, Ontario, Canada
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Wang X, Li X, Wu Q, Yuan Y, Liu W, Han C, Wang X. A Nanoporous Polymer Modified with Hexafluoroisopropanol to Detect Dimethyl Methylphosphonate. Nanomaterials (Basel) 2023; 14:89. [PMID: 38202543 PMCID: PMC10781009 DOI: 10.3390/nano14010089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024]
Abstract
The increasing threat of nerve agents has prompted the need for gas sensors with fast response, high sensitivity, and good stability. In this work, the hexafluoroisopropanol functional group was modified on a porous aromatic framework material, which served as a sensitive material for detecting dimethyl methylphosphonate. A nerve agent sensor was made by coating sensitive materials on a surface acoustic wave device. Lots of pores in sensitive materials effectively increase the specific surface area and provide channels for diffusion of gas molecules. The introduction of hexafluoroisopropanols enables the sensor to specifically adsorb dimethyl methylphosphonate and improves the selectivity of the sensor. As a result, the developed gas sensor was able to detect dimethyl methylphosphonate at 0.8 ppm with response/recovery times of 29.8/43.8 s, and the detection limit of the gas sensor is about 0.11 ppm. The effects of temperature and humidity on the sensor were studied. The results show that the baseline of the sensor has a linear relationship with temperature and humidity, and the temperature and humidity have a significant effect on the response of the sensor. Furthermore, a device for real-time detection of nerve agent is reported. This work provides a new strategy for developing a gas sensor for detecting nerve agents.
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Affiliation(s)
- Xuming Wang
- Department of Microelectronics, Xi’an Jiaotong University, Xi’an 710049, China
| | - Xin Li
- Department of Microelectronics, Xi’an Jiaotong University, Xi’an 710049, China
| | - Qiang Wu
- Department of Microelectronics, Xi’an Jiaotong University, Xi’an 710049, China
| | - Yubin Yuan
- Department of Microelectronics, Xi’an Jiaotong University, Xi’an 710049, China
| | - Weihua Liu
- Department of Microelectronics, Xi’an Jiaotong University, Xi’an 710049, China
| | - Chuanyu Han
- Department of Microelectronics, Xi’an Jiaotong University, Xi’an 710049, China
| | - Xiaoli Wang
- School of Physics, Xi’an Jiaotong University, Xi’an 710049, China
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Wu Q, Yuan Y, Wang X, Bu X, Jiao M, Liu W, Han C, Hu L, Wang X, Li X. Highly Selective Ionic Gel-Based Gas Sensor for Halogenated Volatile Organic Compound Detection: Effect of Dipole-Dipole Interaction. ACS Sens 2023; 8:4566-4576. [PMID: 37989128 DOI: 10.1021/acssensors.3c01476] [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] [Indexed: 11/23/2023]
Abstract
Halogenated volatile organic compounds (abbreviated as X-VOCs) are a class of hazardous gas pollutants that are difficult to detect due to their thermal stability, chemical inertness, and poisoning effect on gas sensors at high temperatures. In this work, room-temperature detection of X-VOCs is achieved using a surface acoustic wave (SAW) gas sensor coated with a 1-ethyl-3-methylimidazolium bis(trifluoromethylsufonyl)imide (EMIM-TFSI)-based ionic gel film. We experimentally verify that the high selectivity of the ionic gel-based SAW gas sensor for X-VOCs is due to the presence of halogen atoms in these gas molecules. Meanwhile, the sensor has very little response to common organic gases such as ethanol, isopropanol, and acetone, reflecting a low cross-sensitivity to nonhalogenated VOCs. This unique advantage shows potential applications in selective detection of X-VOCs and is validated by comparison with a commercial metal oxide semiconductor (MOS) sensor. Furthermore, the internal sensing mechanism is explored by the density functional theory (DFT) method. The simulation results demonstrate that the X-VOC molecules are highly polarized by the inductive effect of halogen atom substitution, which is beneficial for being adsorbed by the EMIM-TFSI ionic liquid via dipole-dipole interaction.
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Affiliation(s)
- Qiang Wu
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Yubin Yuan
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Xuming Wang
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Xiangrui Bu
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Menglong Jiao
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Weihua Liu
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Chuanyu Han
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Long Hu
- Key Laboratory for Physical Electronics and Devices of the Ministry of Education, Xi'an Jiaotong University, Xi'an 710049, China
| | - Xiaoli Wang
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
- School of Science, Xi'an Jiaotong University, Xi'an 710049, China
| | - Xin Li
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
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Liu W, Li RY. [Enlightenment of World Health Organization fungal priority pathogens list]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1984-1987. [PMID: 38129157 DOI: 10.3760/cma.j.cn112338-20230701-00410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
The WHO established the first fungal priority pathogens list (FPPL) in October 2022 to focus on and promote further research and policy interventions to strengthen the global response to fungal infections and antifungal resistance. The FPPL and its formulation process provide new significant insights for managing pathogenic fungi and invasive fungal disease (IFD) in China, necessitating the following key actions: Strengthen public health interventions for IFD. Further, it improves the ability of laboratory testing and clinical supervision for IFD and pathogenic fungi. Increase targeted investment and support for innovative research and development in IFD diagnosis, treatment, and prevention.
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Affiliation(s)
- W Liu
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
| | - R Y Li
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
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Gong J, Geng YY, Zhang S, Liu W, Wu WW, Li RY, Zhang JZ. [Analysis of public health risks associated with pathogenic fungi in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1977-1983. [PMID: 38129156 DOI: 10.3760/cma.j.cn112338-20230615-00376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
At present, the public health risks caused by pathogenic fungi are greater in China and have attracted great attention from disease control departments. Due to the difficulty in diagnosing fungal infections, the public health risk of pathogenic fungi is currently hidden in the unexplained pneumonia/encephalitis/fever syndrome and is not effectively appreciated. From the public health perspective, the mainly focused fungal pathogens include highly pathogenic fungi (including dimorphic fungi and dematiaceous fungi), pathogenic fungi that cause regional aggregation infections, and drug-resistant pathogenic fungi. However, due to the lack of systematic monitoring data, the disease burden related to pathogenic fungi cannot be accurately quantified and evaluated. Therefore, to effectively reduce the serious harm of fungal infections to the public, systematic monitoring of pathogenic fungi should be carried out nationally.
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Affiliation(s)
- J Gong
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
| | - Y Y Geng
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
| | - S Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
| | - W Liu
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
| | - W W Wu
- Derpartment of Plastic and Dermatologic Surgery, the Fifth People's Hospital of Hainan Province, Haikou 570102, China
| | - R Y Li
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
| | - J Z Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
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Liu W, Zhao Y, Liu Z, Zhang G, Wu H, Zheng X, Tang X, Chen Z. Therapeutic effects against high-grade glioblastoma mediated by engineered induced neural stem cells combined with GD2-specific CAR-NK. Cell Oncol (Dordr) 2023; 46:1747-1762. [PMID: 37420122 DOI: 10.1007/s13402-023-00842-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2023] [Indexed: 07/09/2023] Open
Abstract
PURPOSE High-grade glioblastoma is extremely challenging to treat because of its aggressiveness and resistance to conventional chemo- and radio-therapies. On the contrary, genetic and cellular immunotherapeutic strategies based on the stem and immune cells are emerging as promising treatments against glioblastoma (GBM). We aimed to developed a novel combined immunotherapeutic strategy to improve the treatment efficacy using genetically engineered PBMC-derived induced neural stem cells (iNSCs) expressing HSV-TK and second-generation CAR-NK cells against GBM. METHODS iNSCs cells expressing HSV-TK (iNSCsTK) and GD2-specific CAR-NK92 (GD2NK92) were generated from PBMC-derived iNSCs and NK92 cell lines, respectively. The anti-tumor effect of iNSCsTK and the combinational therapeutics of iNSCsTK and GD2NK92 were evaluated by GBM cell line using in vitro and in vivo experiments. RESULTS PBMC-derived iNSCsTK possessed tumor-tropism migration ability in vitro and in vivo, which exhibited considerable anti-tumor activity via bystander effect in the presence of ganciclovir (GCV). iNSCsTK/GCV could slow GBM progression and prolong median survival in tumor-bearing mice. However, the anti-tumor effect was limited to single therapy. Therefore, the combinational therapeutic effect of iNSCsTK/GCV and GD2NK92 against GBM was investigated. This approach displayed a more significant anti-tumor effect in vitro and in xenograft tumor mice. CONCLUSIONS PBMC-derived iNSCsTK showed a significant tumor-tropic migration and an effective anti-tumor activity with GCV in vitro and in vivo. In addition, combined with GD2NK92, iNSCsTK therapeutic efficacy improved dramatically to prolong the tumor-bearing animal model's median survival.
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Affiliation(s)
- Weihua Liu
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Yu Zhao
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Zhongfeng Liu
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Guangji Zhang
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Huantong Wu
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Xin Zheng
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Xihe Tang
- Neurosurgery Center of Aeronautical General Hospital, Beijing, 100012, China
| | - Zhiguo Chen
- Cell Therapy Center, Beijing Institute of Geriatrics, Xuanwu Hospital Capital Medical University, National Clinical Research Center for Geriatric Diseases, and Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China.
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100069, China.
- , Beijing, China.
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47
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Bai HH, Wang XF, Zhang BY, Liu W. A comparison of size exclusion chromatography-based tandem strategies for plasma exosome enrichment and proteomic analysis. Anal Methods 2023; 15:6245-6251. [PMID: 37955202 DOI: 10.1039/d3ay01704d] [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] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
Proteomic analysis of exosomes from human plasma faces a tremendous challenge mainly due to the low abundance of the exosome itself and the complexity of the plasma matrix. Therefore, enrichment of exosomes from human plasma is an essential and indispensable step for large scale and in depth proteomic analysis. Size exclusion chromatography (SEC) is one of the most extensively used methods for exosome isolation from human plasma and many SEC-based tandem methods were established in order to increase the purity of the enriched exosomes and thus the accuracy of the proteomic analysis. To compare the advantages and disadvantages of the different isolation methods and subsequently to promote the establishment of a standardized method for plasma proteomic research, the capacities of the direct SEC method, the combination of SEC with ultracentrifugation (SEC-UC), ultrafiltration (SEC-UF), and titanium dioxide microspheres (SEC-TiO2) were systematically evaluated for exosome isolation from human plasma and thus proteomic analysis. The results demonstrated that the SEC-based tandem methods were superior to the direct SEC method in the purity of exosomes isolated from human plasma. Additionally, the SEC-UC method possessed the highest number of the total identified proteins and the overlapped proteins with the top 100 exosome markers in comparison with the other methods. The SEC-TiO2 method displayed the biggest capacity for plasma protein deleting. We expect that the research will have more beneficial values in the field of exosome research.
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Affiliation(s)
- H H Bai
- Department of Pharmacy, Beijing YouAn Hospital, Capital Medical University, Beijing 100069, PR China.
| | - X F Wang
- Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, PR China
| | - B Y Zhang
- Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, PR China
| | - W Liu
- Department of Pharmacy, Beijing YouAn Hospital, Capital Medical University, Beijing 100069, PR China.
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48
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Fang S, Sun Y, Xu J, Zhang T, Wu Z, Li J, Gao E, Wang W, Zhu J, Dai L, Liu W, Zhang B, Zhang J, Yao S. Revealing the intrinsic nature of Ni-, Mn-, and Y-doped CeO 2 catalysts with positive, additive, and negative effects on CO oxidation using operando DRIFTS-MS. Dalton Trans 2023; 52:16911-16919. [PMID: 37927054 DOI: 10.1039/d3dt03001f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
The catalytic activity of a transition metal (host) oxide can be influenced by doping with a second cation (dopant), but the key factors dominating the activity of the doped catalyst are still controversial. Herein, CeO2 doped with Ni, Mn, and Y catalysts prepared using aerosol pyrolysis were used to demonstrate the positive, negative, and additive effects on CO oxidation as a model reaction. Various characterization results indicated that Ni, Mn, and Y had been successfully doped into the CeO2 lattice. The catalytic activities of each catalyst for CO conversion were in the order of Ni-CeO2 > Mn-CeO2 > CeO2 > Y-CeO2. Operando DRIFTS-MS and various characterization methods were applied to reveal the intrinsic nature of the doping effects. The accumulation rate of the surface bidentate carbonates determined the CO oxidation. A definition to evaluate the doping effect was proposed, which is anticipated to be useful for developing a rational catalyst with a high CO oxidation activity. The CO oxidation reactivities displayed strong correlations with the surface factors obtained from operando DRIFTS-MS analysis and the structure factors from XPS and Raman analyses.
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Affiliation(s)
- Shiyu Fang
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
| | - Yan Sun
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
| | - Jiacheng Xu
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- School of Material Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Tiantian Zhang
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
| | - Zuliang Wu
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Jing Li
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Erhao Gao
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Wei Wang
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Jiali Zhu
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Lianxin Dai
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an 343100, China
| | - Weihua Liu
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an 343100, China
| | - Buhe Zhang
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an 343100, China
| | - Junwei Zhang
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an 343100, China
| | - Shuiliang Yao
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China.
- School of Material Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
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49
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Yu DD, Liu W, Zhang L. [Pathophysiology, diagnosis, and therapy for the management of acquired clotting factor deficiency]. Zhonghua Xue Ye Xue Za Zhi 2023; 44:956-962. [PMID: 38185529 PMCID: PMC10753255 DOI: 10.3760/cma.j.issn.0253-2727.2023.11.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Indexed: 01/09/2024]
Affiliation(s)
- D D Yu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin 300020, China Tianjin Institutes of Health Science, Tianjin 301600, China
| | - W Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin 300020, China Tianjin Institutes of Health Science, Tianjin 301600, China
| | - L Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Tianjin 300020, China Tianjin Institutes of Health Science, Tianjin 301600, China
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50
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Sun Y, Fang S, Xu J, Zhang T, Wu Z, Li J, Gao E, Wang W, Dai L, Liu W, Zhang B, Zhang J, Yao S, Zhu J. Unveiling the Surface Chemical Reactions during Multi-Phase Catalytic Oxidation of Soot on Nanoengineering/Interfacing/Doping-Prepared Mn-CeO 2 Catalysts Using TG-MS and Operando DRIFTS-MS. Langmuir 2023; 39:15773-15784. [PMID: 37883132 DOI: 10.1021/acs.langmuir.3c02409] [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] [Indexed: 10/27/2023]
Abstract
The aerosol pyrolysis method from nitrate precursors was used to prepare the Mn-CeO2 catalyst containing Mn2O3, CeO2, and Mn-doped CeO2 nanoparticles for catalyzing carbonous soot oxidation. The prepared Mn-CeO2 catalysts have high specific surface areas, Ce3+ ratio, and oxygen vacancy defects; these are a benefit for soot oxidation. The T50 for soot oxidation on the 0.57Mn-CeO2 catalyst is as low as 355 °C, which is 329 °C lower than that for soot oxidation without a catalyst. The catalysts were characterized using XRD, SEM-EDS, HRTEM, XPS, Raman spectroscopy, H2-TPR-MS, O2-TPD-MS, soot-TPR-MS, and operando DRIFTS-MS. The functions of Mn2O3, CeO2, and Mn-doped CeO2 in the 0.57Mn-CeO2 catalyst are unveiled. Mn-doped CeO2 plays a key role and CeO2 participates in soot oxidation, while Mn2O3 is used to enhance higher ratios of Ce3+, via the reaction of Mn3+ + Ce4+ = Mn4+ + Ce3+. The mechanism of soot oxidation on Mn-CeO2 was proposed.
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Affiliation(s)
- Yan Sun
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Shiyu Fang
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Jiacheng Xu
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- School of Material Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Tiantian Zhang
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Zuliang Wu
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Jing Li
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Erhao Gao
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Wei Wang
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Lianxin Dai
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an, Jiangxi 343100, China
| | - Weihua Liu
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an, Jiangxi 343100, China
| | - Buhe Zhang
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an, Jiangxi 343100, China
| | - Junwei Zhang
- Jiangxi Xintai Functional Materials Technology Co., Ltd., Ji'an, Jiangxi 343100, China
| | - Shuiliang Yao
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- School of Material Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
| | - Jiali Zhu
- School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
- Key Laboratory of Advanced Plasma Catalysis Engineering for China Petrochemical Industry, Changzhou 213164, China
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