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1. Improved Radiation Image Denoising Algorithm Based on Median Filtering

Author

Junlin WANG, Haifeng GUI, Xinglong LI, Yang LIU, and Jianhua WU

Subjects
intense irradiation field, radiation noise, noise recognition, image denoising, median filtering, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

In order to solve the problem of image denoising in irradiation fields such as nuclear waste disposal hot cells，this study made corresponding improvements to the algorithm based on the idea of median filtering for radiation noise points，and finally proposed an algorithm suitable for image denoising in strong irradiation fields. The algorithm process is divided into three steps: noise recognition，noise processing and detail protection. Noise recognition starts from visual perception. If the pixel value is higher than its surrounding value and reaches the set threshold，it is marked as suspicious. By setting the maximum area threshold of radiation noise，the area larger than the threshold is excluded. The idea of median filtering is used to deal with noise，and the size of filtering window is adjusted adaptively. The protection of detail borrows from the idea of image fusion. Compared with other noise reduction algorithms，the results show that the proposed algorithm is accurate in the identification of radiated noise points，has obvious noise reduction effect，and protects the details of the picture to the greatest extent. The algorithm demonstrates good robustness under radiation environments with different dose rates，and still achieves effective denoising even under a strong irradiation field of 100 Gy/h. This can provide technical support for intelligent applications in nuclear waste disposal.

Published
2024
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2. RGS19 activates the MYH9/β-catenin/c-Myc positive feedback loop in hepatocellular carcinoma

Author

Shanjia Ke, Shounan Lu, Yanan Xu, Miaoyu Bai, Hongjun Yu, Bing Yin, Chaoqun Wang, Zhigang Feng, Zihao Li, Jingjing Huang, Xinglong Li, Baolin Qian, Yongliang Hua, Yao Fu, Bei Sun, Yaohua Wu, and Yong Ma

Subjects
Medicine, Biochemistry, QD415-436
Abstract

Abstract Hepatocellular carcinoma (HCC) is one of the most common fatal cancers worldwide, and the identification of novel treatment targets and prognostic biomarkers is urgently needed because of its unsatisfactory prognosis. Regulator of G-protein signaling 19 (RGS19) is a multifunctional protein that regulates the progression of various cancers. However, the specific function of RGS19 in HCC remains unclear. The expression of RGS19 was determined in clinical HCC samples. Functional and molecular biology experiments involving RGS19 were performed to explore the potential mechanisms of RGS19 in HCC. The results showed that the expression of RGS19 is upregulated in HCC tissues and is significantly associated with poor prognosis in HCC patients. RGS19 promotes the proliferation and metastasis of HCC cells in vitro and in vivo. Mechanistically, RGS19, via its RGS domain, stabilizes the MYH9 protein by directly inhibiting the interaction of MYH9 with STUB1, which has been identified as an E3 ligase of MYH9. Moreover, RGS19 activates β-catenin/c-Myc signaling via MYH9, and RGS19 is also a transcriptional target gene of c-Myc. A positive feedback loop formed by RGS19, MYH9, and the β-catenin/c-Myc axis was found in HCC. In conclusion, our research revealed that competition between RGS19 and STUB1 is a critical mechanism of MYH9 regulation and that the RGS19/MYH9/β-catenin/c-Myc feedback loop may represent a promising strategy for HCC therapy.

Published
2024
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3. A comprehensive analysis of m6A/m7G/m5C/m1A-related gene expression and immune infiltration in liver ischemia–reperfusion injury by integrating bioinformatics and machine learning algorithms

Author

Zhanzhi Meng, Xinglong Li, Shounan Lu, Yongliang Hua, Bing Yin, Baolin Qian, Zhongyu Li, Yongzhi Zhou, Irina Sergeeva, Yao Fu, and Yong Ma

Subjects
Liver ischemia–reperfusion injury, Methylation modification, Immune infiltration, Machine learning, Bioinformatics, Medicine
Abstract

Abstract Background Liver ischemia–reperfusion injury (LIRI) is closely associated with immune infiltration, which commonly occurs after liver surgery, especially liver transplantation. Therefore, it is crucial to identify the genes responsible for LIRI and develop effective therapeutic strategies that target immune response. Methylation modifications in mRNA play various crucial roles in different diseases. This study aimed to identify potential methylation-related markers in patients with LIRI and evaluate the corresponding immune infiltration. Methods Two Gene Expression Omnibus datasets containing human liver transplantation data (GSE12720 and GSE151648) were downloaded for integrated analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted to investigate the functional enrichment of differentially expressed genes (DEGs). Differentially expressed methylation-related genes (DEMRGs) were identified by overlapping DEG sets and 65 genes related to N6-methyladenosine (m6A), 7-methylguanine (m7G), 5-methylcytosine (m5C), and N1-methyladenosine (m1A). To evaluate the relationship between DEMRGs, a protein–protein interaction (PPI) network was utilized. The core DEMRGs were screened using three machine learning algorithms: least absolute shrinkage and selection operator, random forest, and support vector machine-recursive feature elimination. After verifying the diagnostic efficacy using the receiver operating characteristic curve, we validated the expression of the core DEMRGs in clinical samples and performed relative cell biology experiments. Additionally, the immune status of LIRI was comprehensively assessed using the single sample gene set enrichment analysis algorithm. The upstream microRNA and transcription factors of the core DEMRGs were also predicted. Results In total, 2165 upregulated and 3191 downregulated DEGs were identified, mainly enriched in LIRI-related pathways. The intersection of DEGs and methylation-related genes yielded 28 DEMRGs, showing high interaction in the PPI network. Additionally, the core DEMRGs YTHDC1, METTL3, WTAP, and NUDT3 demonstrated satisfactory diagnostic efficacy and significant differential expression and corresponding function based on cell biology experiments. Furthermore, immune infiltration analyses indicated that several immune cells correlated with all core DEMRGs in the LIRI process to varying extents. Conclusions We identified core DEMRGs (YTHDC1, METTL3, WTAP, and NUDT3) associated with immune infiltration in LIRI through bioinformatics and validated them experimentally. This study may provide potential methylation-related gene targets for LIRI immunotherapy.

Published
2024
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4. Identification of MIR600HG/hsa-miR-342-3p/ANLN network as a potential prognosis biomarker associated with lmmune infiltrates in pancreatic cancer

Author

Baolin Qian, Qi Liu, Chaoqun Wang, Shounan Lu, Shanjia Ke, Bing Yin, Xinglong Li, Hongjun Yu, Yaohua Wu, and Yong Ma

Subjects
Medicine, Science
Abstract

Abstract Pancreatic cancer is one of the tumors with the worst prognosis, causing serious harm to human health. The RNA network and immune response play an important role in tumor progression. While a systematic RNA network linked to the tumor immune response remains to be further explored in pancreatic cancer. Based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, the MIR600HG/hsa-miR-342-3p/ANLN network was determined. WB and IHC were used to confirm the high expression of ANLN in pancreatic cancer. The prognostic model based on the RNA network could effectively predict the survival prognosis of patients. The analysis of immune infiltration showed that the MIR600HG/hsa-miR-342-3p/ANLN network altered the level of infiltration of T helper 2 (Th2) and effector memory T (Tem) cells. Furthermore, we found that the chemokines chemokine ligand (CCL) 5 and CCL14 may play a key role in immune cell infiltration mediated by the RNA network. In conclusion, this study constructed a prognostic model based on the MIR600HG/hsa-miR-342-3p/ANLN network and found that it may function in tumor immunity.

Published
2023
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5. Plasma‐Induced 2D Electron Transport at Hetero‐Phase Titanium Oxide Interface

Author

Kehan Yu, Xinglong Li, Haoyu Zhao, Chen Ma, Zhongyue Wang, Peng Lv, Ertao Hu, Jiajin Zheng, Wei Wei, and Kostya (Ken) Ostrikov

Subjects
electron transport, heterointerfaces, layered materials, plasma nanotechnology, titanium dioxide, Science
Abstract

Abstract Interfaces of metal oxide heterojunctions display a variety of intriguing physical properties that enable novel applications in spintronics, quantum information, neuromorphic computing, and high‐temperature superconductivity. One such LaAlO3/SrTiO3 (LAO/STO) heterojunction hosts a 2D electron liquid (2DEL) presenting remarkable 2D superconductivity and magnetism. However, these remarkable properties emerge only at very low temperatures, while the heterostructure fabrication is challenging even at the laboratory scale, thus impeding practical applications. Here, a novel plasma‐enabled fabrication concept is presented to develop the TiO2/Ti3O4 hetero‐phase bilayer with a 2DEL that exhibits features of a weakly localized Fermi liquid even at room temperature. The hetero‐phase bilayer is fabricated by applying a rapid plasma‐induced phase transition that transforms a specific portion of anatase TiO2 thin film into vacancy‐prone Ti3O4 in seconds. The underlying mechanism relies on the screening effect of the achieved high‐density electron liquid that suppresses the electron‐phonon interactions. The achieved “adiabatic” electron transport in the hetero‐phase bilayer offers strong potential for low‐loss electric or plasmonic circuits and hot electron harvesting and utilization. These findings open new horizons for fabricating diverse multifunctional metal oxide heterostructures as an innovative platform for emerging clean energy, integrated photonics, spintronics, and quantum information technologies.

Published
2024
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6. Comprehensive analysis of transcriptome‐wide M6A methylation for hepatic ischaemia reperfusion injury in mice

Author

yongliang hua, xinglong Li, Bing Yin, jingjing Huang, shounan Lu, chaoqun Wang, shanjia Ke, yanan Xu, baolin Qian, zhigang Feng, hongjun Yu, and yong Ma

Subjects
n6-methyladenosine, hepatic ischaemia reperfusion injury, merip-seq, posttranscriptional regulation, methyltransferase, Genetics, QH426-470
Abstract

N6-Methyladenosine (m6A) plays key roles in the regulation of biological functions and cellular mechanisms for ischaemia reperfusion (IR) injury in different organs. However, little is known about the underlying mechanisms of m6A-modified mRNAs in hepatic IR injury. In mouse models, liver samples were subjected to methylated RNA immunoprecipitation with high-throughput sequencing (MeRIP-seq) and RNA sequencing (RNA-seq). In total, 16917 m6A peaks associated with 4098 genes were detected in the sham group, whereas 21,557 m6A peaks associated with 5322 genes were detected in the IR group. There were 909 differentially expressed m6A peaks, 863 differentially methylated transcripts and 516 differentially m6A modification genes determined in both groups. The distribution of m6A peaks was especially enriched in the coding sequence and 3‘UTR. Furthermore, we identified a relationship between differentially m6A methylated genes (fold change≥1.5/≤ 0.667, p value≤0.05) and differentially expressed genes (fold change≥1.5 and p value≤0.05) to obtain three overlapping predicted target genes (Fnip2, Phldb2, and Pcf11). Our study revealed a transcriptome-wide map of m6A mRNAs in hepatic IR injury and might provide a theoretical basis for future research in terms of molecular mechanisms.

Published
2023
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7. HLTF promotes hepatocellular carcinoma progression by enhancing SRSF1 stability and activating ERK/MAPK pathway

Author

Yanan Xu, Shanjia Ke, Shounan Lu, Chaoqun Wang, Zihao Li, Zhigang Feng, Hongjun Yu, Miaoyu Bai, Baolin Qian, Bing Yin, Xinglong Li, Yongliang Hua, Hongchi Jiang, and Yong Ma

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Helicase-like transcription factor (HLTF) has been found to be involved in the progression of several tumors, but the role of HLTF in hepatocellular carcinoma (HCC) progression has not been studied. Here, our study explored the underlying mechanism of HLTF in HCC progression for the first time. Database analysis and clinical sample examination indicated that HLTF was upregulated in HCC tissues and was related to poor clinicopathological features in patients. Upregulation of HLTF accelerated the growth and metastasis of HCC cells both in vitro and in vivo. Bioinformatics analysis and subsequent experiments revealed that ERK/MAPK signaling pathway activation was vital to HLTF-mediated proliferation and metastasis in HCC cells. Moreover, HLTF was demonstrated to interact with SRSF1 and contribute to its protein stability to activate the ERK/MAPK signaling pathway and enhance HCC growth and metastasis. In addition, miR-511-5p was expressed at a low level in HCC tissues, was negatively correlated HLTF, and regulated HLTF expression. Our study shows that HLTF plays an oncogenic role in HCC progression and provides a novel biomarker and therapeutic target for the diagnosis and treatment of HCC.

Published
2023
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8. Mass testing and characterization of 20-inch PMTs for JUNO

Author

Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Abid Aleem, Tsagkarakis Alexandros, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Weidong Bai, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Ilya Butorov, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Chi Chan, Jinfan Chang, Yun Chang, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Chen, Jie Cheng, Yaping Cheng, Yu Chin Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Marta Colomer Molla, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Zhengyong Fei, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Yuduo Guan, Nunzio Guardone, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Yuxiang Hu, Zhuojun Hu, Guihong Huang, Hanxiong Huang, Kaixuan Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Ignacio Jeria, Xiaolu Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Daozheng Li, Demin Li, Fei Li, Fule Li, Gaosong Li, Huiling Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Rui Li, Shanfeng Li, Tao Li, Teng Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yichen Li, Yufeng Li, Zepeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Zonghai Li, Hao Liang, Jiajun Liao, Ayut Limphirat, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Haotian Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Daibin Luo, Fengjiao Luo, Guang Luo, Shu Luo, Wuming Luo, Xiaojie Luo, Vladimir Lyashuk, Bangzheng Ma, Bing Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Jingyu Mai, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Luca Pelicci, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Yu Peng, Zhaoyuan Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Mariia Redchuk, Bin Ren, Jie Ren, Barbara Ricci, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Xichao Ruan, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Utane Sawangwit, Julia Sawatzki, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Jun Su, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Eric Theisen, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Katharina von Sturm, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Apimook Watcharangkool, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiang Xiao, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Jiaxuan Ye, Mei Ye, Ziping Ye, Frédéric Yermia, Na Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Cenxi Yuan, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Baobiao Yue, Noman Zafar, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Bin Zhang, Binting Zhang, Feiyang Zhang, Guoqing Zhang, Honghao Zhang, Jialiang Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Mohan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xin Zhang, Xuantong Zhang, Xueyao Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yu Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Runze Zhao, Shujun Zhao, Dongqin Zheng, Hua Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou, and JUNO Collaboration

Subjects
Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Main goal of the JUNO experiment is to determine the neutrino mass ordering using a 20 kt liquid-scintillator detector. Its key feature is an excellent energy resolution of at least 3% at 1 MeV, for which its instruments need to meet a certain quality and thus have to be fully characterized. More than 20,000 20-inch PMTs have been received and assessed by JUNO after a detailed testing program which began in 2017 and elapsed for about four years. Based on this mass characterization and a set of specific requirements, a good quality of all accepted PMTs could be ascertained. This paper presents the performed testing procedure with the designed testing systems as well as the statistical characteristics of all 20-inch PMTs intended to be used in the JUNO experiment, covering more than fifteen performance parameters including the photocathode uniformity. This constitutes the largest sample of 20-inch PMTs ever produced and studied in detail to date, i.e. 15,000 of the newly developed 20-inch MCP-PMTs from Northern Night Vision Technology Co. (NNVT) and 5000 of dynode PMTs from Hamamatsu Photonics K. K.(HPK).

Published
2022
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9. Artificial light-harvesting systems and their applications in photocatalysis and cell labeling

Author

Ying Wang, Ning Han, Xinglong Li, Shengsheng Yu, and Lingbao Xing

Subjects
Light-harvesting systems, Sequential energy transfer, Photocatalysis, Cell labeling, Chemistry, QD1-999, Physics, QC1-999
Abstract

Photosynthesis is the basis for the survival of organisms in nature; consequently, the fabrication of artificial light-harvesting systems (LHSs) that simulate natural photosynthesis is of significant interest. Recently, a variety of artificial LHSs have been successfully constructed using fluorescence resonance energy transfer (FRET). However, it is crucial to fabricate artificial LHSs with a sequential energy transfer process when considering that the natural photosynthetic process involves a multistep sequential energy transfer process rather than a simple one-step energy transfer. Moreover, many previously reported LHSs have been used as imaging agents for cell labeling and bioimaging or as catalysts in photocatalytic reactions, showing promise for applications simulating natural photosynthesis. In this review, we have summarized recently published representative work on artificial LHSs. In addition, the application of LHSs in photocatalysis and cell labeling has been described in detail.

Published
2022
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10. Model-independent Approach of the JUNO 8B Solar Neutrino Program

Author

Jie Zhao, Baobiao Yue, Haoqi Lu, Yufeng Li, Jiajie Ling, Zeyuan Yu, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Abid Aleem, Tsagkarakis Alexandros, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Weidong Bai, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Ilya Butorov, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Chi Chan, Jinfan Chang, Yun Chang, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Chen, Jie Cheng, Yaping Cheng, Alexander Chepurnov, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Marta Colomer Molla, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Zhengyong Fei, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Maxim Gromov, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Yuduo Guan, Nunzio Guardone, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Yuxiang Hu, Zhuojun Hu, Guihong Huang, Hanxiong Huang, Kaixuan Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Ignacio Jeria, Xiaolu Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Xiaoping Jing, Cécile Jollet, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Daozheng Li, Demin Li, Fei Li, Fule Li, Gaosong Li, Huiling Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Rui Li, Shanfeng Li, Tao Li, Teng Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yichen Li, Zepeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Zonghai Li, Hao Liang, Jiajun Liao, Ayut Limphirat, Guey-Lin Lin, Shengxin Lin, Tao Lin, Ivano Lippi, Fang Liu, Haidong Liu, Haotian Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Daibin Luo, Fengjiao Luo, Guang Luo, Shu Luo, Wuming Luo, Xiaojie Luo, Vladimir Lyashuk, Bangzheng Ma, Bing Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Jingyu Mai, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Alexey Nikolaev, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Yu Peng, Zhaoyuan Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Mariia Redchuk, Bin Ren, Jie Ren, Barbara Ricci, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Xichao Ruan, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Utane Sawangwit, Julia Sawatzki, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Jun Su, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Katharina von Sturm, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Apimook Watcharangkool, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiang Xiao, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Jiaxuan Ye, Mei Ye, Ziping Ye, Frédéric Yermia, Na Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zezhong Yu, Cenxi Yuan, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Noman Zafar, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Bin Zhang, Binting Zhang, Feiyang Zhang, Guoqing Zhang, Honghao Zhang, Jialiang Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Mohan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xin Zhang, Xuantong Zhang, Xueyao Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yu Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Rong Zhao, Runze Zhao, Shujun Zhao, Dongqin Zheng, Hua Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou

Subjects
Solar neutrinos, Astrophysics, QB460-466
Abstract

The physics potential of detecting ^8 B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model-independent manner by using three distinct channels of the charged current (CC), neutral current (NC), and elastic scattering (ES) interactions. Due to the largest-ever mass of ^13 C nuclei in the liquid scintillator detectors and the expected low background level, ^8 B solar neutrinos are observable in the CC and NC interactions on ^13 C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC, and ES channels to guarantee the observation of the ^8 B solar neutrinos. From the sensitivity studies performed in this work, we show that JUNO, with 10 yr of data, can reach the 1 σ precision levels of 5%, 8%, and 20% for the ^8 B neutrino flux, ${\sin }^{2}{\theta }_{12}$ , and ${\rm{\Delta }}{m}_{21}^{2}$ , respectively. Probing the details of both solar physics and neutrino physics would be unique and helpful. In addition, when combined with the Sudbury Neutrino Observatory measurement, the world's best precision of 3% is expected for the measurement of the ^8 B neutrino flux.

Published
2024
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11. NNMT promotes the progression of intrahepatic cholangiocarcinoma by regulating aerobic glycolysis via the EGFR-STAT3 axis

Author

Shounan Lu, Shanjia Ke, Chaoqun Wang, Yanan Xu, Zihao Li, Keda Song, Miaoyu Bai, Menghua Zhou, Hongjun Yu, Bing Yin, Xinglong Li, Zhigang Feng, Yongliang Hua, Shangha Pan, Hongchi Jiang, Linqiang Li, Yaohua Wu, and Yong Ma

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Nicotinamide N-methyltransferase (NNMT), a member of the N-methyltransferase family, plays an important role in tumorigenesis. However, its expression and biological functions in intrahepatic cholangiocarcinoma (iCCA) remain to be established. In our study, we identified NNMT as an oncogene in iCCA and provided mechanistic insights into the roles of NNMT in iCCA progression. High NNMT expression in iCCA tissues was identified using western blotting and immunohistochemistry (IHC). We identified a significantly higher NNMT expression level in human iCCA tissues than that in adjacent normal tissues. Increased NNMT expression promoted iCCA cell proliferation and metastasis in vitro and in vivo. Mechanistically, NNMT inhibited the level of histone methylation in iCCA cells by consuming the methyl donor S-adenosyl methionine (SAM), thereby promoting the expression of epidermal growth factor receptor (EGFR). EGFR may activate the aerobic glycolysis pathway in iCCA cells by activating the STAT3 signaling pathway. In conclusion, we identified NNMT as an oncogene in iCCA and provided mechanistic insights into the roles of NNMT in iCCA progression.

Published
2022
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12. Damping signatures at JUNO, a medium-baseline reactor neutrino oscillation experiment

Author

The JUNO collaboration, Jun Wang, Jiajun Liao, Wei Wang, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou

Subjects
Neutrino Detectors and Telescopes (experiments), Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract We study damping signatures at the Jiangmen Underground Neutrino Observatory (JUNO), a medium-baseline reactor neutrino oscillation experiment. These damping signatures are motivated by various new physics models, including quantum decoherence, ν 3 decay, neutrino absorption, and wave packet decoherence. The phenomenological effects of these models can be characterized by exponential damping factors at the probability level. We assess how well JUNO can constrain these damping parameters and how to disentangle these different damping signatures at JUNO. Compared to current experimental limits, JUNO can significantly improve the limits on τ 3/m 3 in the ν 3 decay model, the width of the neutrino wave packet σ x , and the intrinsic relative dispersion of neutrino momentum σ rel.

Published
2022
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13. Machine learning reveals sex differences in clinical features of acute exacerbation of chronic obstructive pulmonary disease: A multicenter cross-sectional study

Author

Zhihong Chen, Jiajia Wang, Hanchao Wang, Yu Yao, Huojin Deng, Junnan Peng, Xinglong Li, Zhongruo Wang, Xingru Chen, Wei Xiong, Qin Wang, and Tao Zhu

Subjects
acute exacerbation of chronic obstructive pulmonary disease, sex, binary logistic regression, nomogram, machine learning, K-prototypes algorithm, Medicine (General), R5-920
Abstract

IntroductionIntrinsically, chronic obstructive pulmonary disease (COPD) is a highly heterogonous disease. Several sex differences in COPD, such as risk factors and prevalence, were identified. However, sex differences in clinical features of acute exacerbation chronic obstructive pulmonary disease (AECOPD) were not well explored. Machine learning showed a promising role in medical practice, including diagnosis prediction and classification. Then, sex differences in clinical manifestations of AECOPD were explored by machine learning approaches in this study.MethodsIn this cross-sectional study, 278 male patients and 81 female patients hospitalized with AECOPD were included. Baseline characteristics, clinical symptoms, and laboratory parameters were analyzed. The K-prototype algorithm was used to explore the degree of sex differences. Binary logistic regression, random forest, and XGBoost models were performed to identify sex-associated clinical manifestations in AECOPD. Nomogram and its associated curves were established to visualize and validate binary logistic regression.ResultsThe predictive accuracy of sex was 83.930% using the k-prototype algorithm. Binary logistic regression revealed that eight variables were independently associated with sex in AECOPD, which was visualized by using a nomogram. The AUC of the ROC curve was 0.945. The DCA curve showed that the nomogram had more clinical benefits, with thresholds from 0.02 to 0.99. The top 15 sex-associated important variables were identified by random forest and XGBoost, respectively. Subsequently, seven clinical features, including smoking, biomass fuel exposure, GOLD stages, PaO2, serum potassium, serum calcium, and blood urea nitrogen (BUN), were concurrently identified by three models. However, CAD was not identified by machine learning models.ConclusionsOverall, our results support that the clinical features differ markedly by sex in AECOPD. Male patients presented worse lung function and oxygenation, less biomass fuel exposure, more smoking, renal dysfunction, and hyperkalemia than female patients with AECOPD. Furthermore, our results also suggest that machine learning is a promising and powerful tool in clinical decision-making.

Published
2023
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14. The design and sensitivity of JUNO’s scintillator radiopurity pre-detector OSIRIS

Author

Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Guangpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Salvatore Costa, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Can Fang, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Christoph Genster, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, Daojin Hong, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Michael Karagounis, Narine Kazarian, Waseem Khan, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Jingjing Liang, Jiajun Liao, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Pavithra Muralidharan, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, MinhThuan NguyenThi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Nina Parkalian, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Gongxing Sun, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kangpu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou, and JUNO Collaboration

Subjects
Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract The OSIRIS detector is a subsystem of the liquid scintillator filling chain of the JUNO reactor neutrino experiment. Its purpose is to validate the radiopurity of the scintillator to assure that all components of the JUNO scintillator system work to specifications and only neutrino-grade scintillator is filled into the JUNO Central Detector. The aspired sensitivity level of $$10^{-16}\hbox { g/g}$$ 10 - 16 g/g of $$^{238}\hbox {U}$$ 238 U and $$^{232}\hbox {Th}$$ 232 Th requires a large ( $$\sim 20\,\hbox {m}^3$$ ∼ 20 m 3 ) detection volume and ultralow background levels. The present paper reports on the design and major components of the OSIRIS detector, the detector simulation as well as the measuring strategies foreseen and the sensitivity levels to U/Th that can be reached in this setup.

Published
2021
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15. Radioactivity control strategy for the JUNO detector

Author

The JUNO collaboration, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Oliviero Cremonesi, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Waseem Khan, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Jiajun Liao, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Moritz Cornelius Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou

Subjects
Neutrino Detectors and Telescopes (experiments), Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract JUNO is a massive liquid scintillator detector with a primary scientific goal of determining the neutrino mass ordering by studying the oscillated anti-neutrino flux coming from two nuclear power plants at 53 km distance. The expected signal anti-neutrino interaction rate is only 60 counts per day (cpd), therefore a careful control of the background sources due to radioactivity is critical. In particular, natural radioactivity present in all materials and in the environment represents a serious issue that could impair the sensitivity of the experiment if appropriate countermeasures were not foreseen. In this paper we discuss the background reduction strategies undertaken by the JUNO collaboration to reduce at minimum the impact of natural radioactivity. We describe our efforts for an optimized experimental design, a careful material screening and accurate detector production handling, and a constant control of the expected results through a meticulous Monte Carlo simulation program. We show that all these actions should allow us to keep the background count rate safely below the target value of 10 Hz (i.e. ∼1 cpd accidental background) in the default fiducial volume, above an energy threshold of 0.7 MeV.

Published
2021
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16. JUNO sensitivity to low energy atmospheric neutrino spectra

Author

Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Guangpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Eric Baussan, Marco Bellato, Antonio Bergnoli, Enrico Bernieri, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Salvatore Costa, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Can Fang, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Christoph Genster, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Oleg Gorchakov, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, Daojin Hong, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Qinhua Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Antonio Insolia, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Michael Karagounis, Narine Kazarian, Waseem Khan, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Zinovy Krumshteyn, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Jingjing Liang, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Salvatore Monforte, Paolo Montini, Michele Montuschi, Axel Müller, Pavithra Muralidharan, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Nina Parkalian, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Taras Rezinko, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Giuseppe Salamanna, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Jacky Schuler, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Gongxing Sun, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Moritz Cornelius Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Wenjie Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou, and The JUNO Collaboration

Subjects
Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Atmospheric neutrinos are one of the most relevant natural neutrino sources that can be exploited to infer properties about cosmic rays and neutrino oscillations. The Jiangmen Underground Neutrino Observatory (JUNO) experiment, a 20 kton liquid scintillator detector with excellent energy resolution is currently under construction in China. JUNO will be able to detect several atmospheric neutrinos per day given the large volume. A study on the JUNO detection and reconstruction capabilities of atmospheric $$\nu _e$$ ν e and $$\nu _\mu $$ ν μ fluxes is presented in this paper. In this study, a sample of atmospheric neutrino Monte Carlo events has been generated, starting from theoretical models, and then processed by the detector simulation. The excellent timing resolution of the 3” PMT light detection system of JUNO detector and the much higher light yield for scintillation over Cherenkov allow to measure the time structure of the scintillation light with very high precision. Since $$\nu _e$$ ν e and $$\nu _\mu $$ ν μ interactions produce a slightly different light pattern, the different time evolution of light allows to discriminate the flavor of primary neutrinos. A probabilistic unfolding method has been used, in order to infer the primary neutrino energy spectrum from the detector experimental observables. The simulated spectrum has been reconstructed between 100 MeV and 10 GeV, showing a great potential of the detector in the atmospheric low energy region.

Published
2021
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17. Comprehensive analysis of the prognostic value and functions of prefoldins in hepatocellular carcinoma

Author

Shanjia Ke, Shounan Lu, Chaoqun Wang, Yanan Xu, Miaoyu Bai, Hongjun Yu, Zhigang Feng, Bing Yin, Zihao Li, Jingjing Huang, Xinglong Li, Baolin Qian, Yongliang Hua, Shangha Pan, Yaohua Wu, and Yong Ma

Subjects
bioinformatics analysis, PFDNs, hepatocellular carcinoma, biomarkers, prognosis, Biology (General), QH301-705.5
Abstract

Prefoldins (PFDNs), a group of proteins known to be associated with cytoskeletal rearrangement, are involved in tumor progression in various cancer types. However, little is known about the roles of PFDNs in hepatocellular carcinoma (HCC). Herein, we investigated the transcriptional and survival data of PFDNs from The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO), Gene Set Enrichment Analysis (GSEA), and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate the potential functions of PFDN1/2/3/4. We also detected the expression of PFDN1/2/3/4 via immunohistochemistry (IHC), Western blotting, and real-time PCR in our clinical samples. We found that the PFDN family showed elevated expression in HCC tissues, while only PFDN1/2/3/4 were found to be significantly correlated with poor prognosis of patients with HCC in the TCGA database. Further investigation was associated with PFDN1–4. We found that the expression of PFDN1/2/3/4 was significantly associated with advanced clinicopathologic features. Apart from the TCGA database, IHC, real-time PCR, and immunoblotting identified the overexpression of PFDN1/2/3/4 in HCC tissues and HCC cell lines. Taken together, these results indicated that PFDN1/2/3/4 might be novel prognostic biomarkers and treatment targets for patients with HCC.

Published
2022
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18. LncRNA Hnf4αos exacerbates liver ischemia/reperfusion injury in mice via Hnf4αos/Hnf4α duplex-mediated PGC1α suppression

Author

Chaoqun Wang, Hongjun Yu, Shounan Lu, Shanjia Ke, Yanan Xu, Zhigang Feng, Baolin Qian, Miaoyu Bai, Bing Yin, Xinglong Li, Yongliang Hua, Liqian Dong, Yao Li, Bao Zhang, Zhongyu Li, Dong Chen, Bangliang Chen, Yongzhi Zhou, Shangha Pan, Yao Fu, Hongchi Jiang, Dawei Wang, and Yong Ma

Subjects
Hnf4αos, Liver, Ischemia/reperfusion, PGC1α, Reactive oxygen species, Medicine (General), R5-920, Biology (General), QH301-705.5
Abstract

LncRNAs are involved in the pathophysiologic processes of multiple diseases, but little is known about their functions in hepatic ischemia/reperfusion injury (HIRI). As a novel lncRNA, the pathogenetic significance of hepatic nuclear factor 4 alpha, opposite strand (Hnf4αos) in hepatic I/R injury remains unclear. Here, differentially expressed Hnf4αos and Hnf4α antisense RNA 1 (Hnf4α-as1) were identified in liver tissues from mouse ischemia/reperfusion models and patients who underwent liver resection surgery. Hnf4αos deficiency in Hnf4αos-KO mice led to improved liver function, alleviated the inflammatory response and reduced cell death. Mechanistically, we found a regulatory role of Hnf4αos-KO in ROS metabolism through PGC1α upregulation. Hnf4αos also promoted the stability of Hnf4α mRNA through an RNA/RNA duplex, leading to the transcriptional activation of miR-23a and miR-23a depletion was required for PGC1α function in hepatoprotective effects on HIRI. Together, our findings reveal that Hnf4αos elevation in HIRI leads to severe liver damage via Hnf4αos/Hnf4α/miR-23a axis-mediated PGC1α inhibition.

Published
2022
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19. A Study of a Model for Predicting Pneumatic Subsoiling Resistance Based on Machine Learning Techniques

Author

Xia Li, Zhangjun Jiang, Sichao Wang, Xinglong Li, Yu Liu, and Xuhui Wang

Subjects
drag reduction of subsoiling, pneumatic subsoiling, machine learning model, Agriculture
Abstract

In order to explore the drag reduction mechanism of pneumatic subsoiling and study the influence of pneumatic subsoiling on the soil, this study used machine learning models to predict the working resistance of a pneumatic subsoiler and adopted random forest (RF), error back-propagation (BP), eXtreme gradient boosting (XGBoost) and support vector regression (SVR) to analyze and compare the predictions of these four models. Field experiments were carried out in two fields with different bulk densities and moisture content. The effects of these parameters on the resistance of pneumatic subsoiling were studied by changing the working air pressure, depth and forward speed. In the RF, SVR, XGBoost and BP models, five parameters (working air pressure, working depth, forward speed, bulk density and moisture content) were inputted as independent variables, and the operating resistance of pneumatic subsoiling was used as the predicted value. After training the four models, the results showed that the R2 value of the RF model was the highest and the error was the smallest, which made it better than the SVR, XGBoost and BP models. The values of MAPE, R2 and RMSE for the RF model’s test set were 0.01, 0.99, and 3.61 N, respectively, indicating that the RF model could predict the resistance value of subsoiling well. When the RF model was used to analyze the five input parameters, the experimental results showed that the contribution of working air pressure to reducing the resistance of subsoiling reached 29%, indicating that pneumatic subsoiling can reduce the resistance, drag and consumption.

Published
2023
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20. Calibration strategy of the JUNO experiment

Author

The JUNO collaboration, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Guangpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Eric Baussan, Marco Bellato, Antonio Bergnoli, Enrico Bernieri, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Shenjian Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Anna Chuvashova, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Salvatore Costa, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Georgy Donchenko, Jianmeng Dong, Damien Dornic, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Can Fang, Jian Fang, Marco Fargetta, Anna Fatkina, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Alexandre Göttel, Christoph Genster, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Franco Giuliani, Maxim Gonchar, Guanghua Gong, Hui Gong, Oleg Gorchakov, Yuri Gornushkin, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, Daojin Hong, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Qinhua Huang, Wenhao Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Antonio Insolia, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Michael Karagounis, Narine Kazarian, Amir Khan, Waseem Khan, Khanchai Khosonthongkee, Patrick Kinz, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Svetlana Krokhaleva, Zinovy Krumshteyn, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Jin Li, Kaijie Li, Mengzhao Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Shuaijie Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhibing Li, Ziyuan Li, Hao Liang, Jingjing Liang, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hu Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Yan Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Davit Mayilyan, Axel Müller, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Salvatore Monforte, Paolo Montini, Michele Montuschi, Nikolay Morozov, Waqas Muhammad, Pavithra Muralidharan, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Hsiao-Ru Pan, Alessandro Paoloni, Nina Parkalian, Sergio Parmeggiano, Teerapat Payupol, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Luis Felipe Piñeres Rico, Oliver Pilarczyk, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Taras Rezinko, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Giuseppe Salamanna, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Jacky Schuler, Cédric Schwab, Konstantin Schweizer, Dmitry Selivanov, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Jingyan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondrej Sramek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Gongxing Sun, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Stefan van Waasen, Johannes van den Boom, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cristina Volpe, Vit Vorobel, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Wenjie Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Mengjiao Xiao, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Xiang Zhou, Jiang Zhu, Kejun Zhu, Honglin Zhuang, Liang Zong, and Jiaheng Zou

Subjects
Neutrino Detectors and Telescopes (experiments), Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract We present the calibration strategy for the 20 kton liquid scintillator central detector of the Jiangmen Underground Neutrino Observatory (JUNO). By utilizing a comprehensive multiple-source and multiple-positional calibration program, in combination with a novel dual calorimetry technique exploiting two independent photosensors and readout systems, we demonstrate that the JUNO central detector can achieve a better than 1% energy linearity and a 3% effective energy resolution, required by the neutrino mass ordering determination.

Published
2021
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21. Identification of CFHR4 as a Potential Prognosis Biomarker Associated With lmmune Infiltrates in Hepatocellular Carcinoma

Author

Hongjun Yu, Chaoqun Wang, Shanjia Ke, Miaoyu Bai, Yanan Xu, Shounan Lu, Zhigang Feng, Baolin Qian, Yue Xu, Menghua Zhou, Zihao Li, Bing Yin, Xinglong Li, Yongliang Hua, Yongzhi Zhou, Shangha Pan, Yao Fu, and Yong Ma

Subjects
CFHR4, prognosis, biomarker, immune Infiltrate, hepatocellular carcinoma, Immunologic diseases. Allergy, RC581-607
Abstract

BackgroundComplement factor H-related 4 (CFHR4) is a protein-coding gene that plays an essential role in multiple diseases. However, the prognostic value of CFHR4 in hepatocellular carcinoma (HCC) is unknown.MethodsUsing multiple databases, we investigated CFHR4 expression levels in HCC and multiple cancers. The relationship between CFHR4 expression levels and clinicopathological variables was further analyzed. Various potential biological functions and regulatory pathways of CFHR4 in HCC were identified by performing a Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA). Single-sample gene set enrichment analysis (ssGSEA) was performed to confirm the correlation between CFHR4 expression and immune cell infiltration. The correlations between CFHR4 expression levels in HCC and N6-methyladenosine (m6A) modifications and the competing endogenous RNA (ceRNA) regulatory networks were confirmed in TCGA cohort.ResultsCFHR4 expression levels were significantly decreased in HCC tissues. Low CFHR4 expression in HCC tissues was significantly correlated with the patients’ sex, race, age, TNM stage, pathological stage, tumor status, residual tumor, histologic grade and alpha fetal protein (AFP) level. GO and KEGG analyses revealed that differentially expressed genes related to CFHR4 may be involved in the synaptic membrane, transmembrane transporter complex, gated channel activity, chemical carcinogenesis, retinol metabolism, calcium signaling pathway, PPAR signaling pathway, insulin and gastric acid secretion. GSEA revealed that the FCGR-activated reaction, PLK1 pathway, ATR pathway, MCM pathway, cascade reactions of PI3K and FGFR1, reactant-mediated MAPK activation and FOXM1 pathway were significantly enriched in HCC with low CFHR4 expression. Moreover, CFHR4 expression was inversely correlated the levels of infiltrating Th2 cells, NK CD56bright cells and Tfh cells. In contrast, we observed positive correlations with the levels of infiltrating DCs, neutrophils, Th17 cells and mast cells. CFHR4 expression showed a strong correlation with various immunomarker groups in HCC. In addition, high CFHR4 expression significantly prolonged the overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI). We observed a substantial correlation between the expression of CFHR4 and multiple N6-methyladenosine genes in HCC and constructed potential CFHR4-related ceRNA regulatory networks.ConclusionsCFHR4 might be a potential therapeutic target for improving the HCC prognosis and is closely related to immune cell infiltration.

Published
2022
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22. KIF15 facilitates gastric cancer via enhancing proliferation, inhibiting apoptosis, and predict poor prognosis

Author

Lixian Ding, Bin Li, Xiaotong Yu, Zhongsheng Li, Xinglong Li, Shuwei Dang, Qiang Lv, Jiufeng Wei, Haixia Sun, Hongsheng Chen, Ming Liu, and Guodong Li

Subjects
KIF15, Gastric cancer, Apoptosis, Proliferation, Prognosis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282, Cytology, QH573-671
Abstract

Abstract Background Kinesin superfamily proteins (KIFs) can transport membranous organelles and protein complexes in an ATP-dependent manner. Kinesin family member 15 (KIF15) is overexpressed in various cancers. However, the function of KIF15 in gastric cancer (GC) is still unclear. Methods GC patients’ data from The Cancer Genome Atlas (TCGA) were analyzed by bioinformatics methods. The expression of KIF15 was examined in GC and paracarcinoma tissues from 41 patients to verify the analysis results. The relationship between KIF15 expression and clinical characteristics were also observed by bioinformatics methods. Kaplan–Meier survival analysis of 122 GC patients in our hospital was performed to explore the relationship between KIF15 expression levels and GC patients’ prognosis. KIF15 was downregulated in GC cell lines AGS and SGC-7901 by transfecting a lentivirus-mediated shRNA plasmid targeting KIF15. In vitro, GC cell proliferation and apoptosis were detected by MTT assay, colony formation assay, and Annexin V-APC staining. In vivo, xenograft experiments were used to verify the in vitro results. Furthermore, Human Apoptosis Antibody Array kit was used to screen possible targets of KIF15 in GC cell lines. Results The bioinformatics results showed that KIF15 expression levels were higher in GC tissues than in normal tissues. IHC showed same results. High expression of KIF15 was statistical correlated with high age and early histologic stage. Kaplan–Meier curves indicated that high KIF15 expression predict poor prognosis in patients with GC. MTT assay and colony formation assay showed that KIF15 promote GC cell proliferation. Annexin V-APC staining found that KIF15 can inhibit GC cell apoptosis. Xenograft experiments reveal that downregulating KIF15 can inhibit GC tumor growth and promote GC apoptosis. Through detection of 43 anti-apoptotic proteins by the Human Apoptosis Antibody Array kit, it was confirmed that knocking down KIF15 can reduce seven anti-apoptotic proteins expression. Conclusions Taken together, our study revealed a critical role for KIF15 to inhibit GC cell apoptosis and promote GC cell proliferation. KIF15 may decrease anti-apoptotic proteins expression by regulating apoptosis pathways. High expression of KIF15 predicts a poor prognosis in patients with GC. KIF15 might be a novel prognostic biomarker and a therapeutic target for GC.

Published
2020
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23. iTRAQ-based quantitative proteomic reveals proteomic changes in Serratia sp. CM01 and mechanism of Cr(Ⅵ) resistance

Author

Yuan Liu, Yanlun Qiu, Qi Yin, Xinglong Li, Qunhua Bai, Yingli Li, and Hong Xiao

Subjects
ITRAQ, Bacteria, Hexavalent chromium, Stress response, Environmental pollution, TD172-193.5, Environmental sciences, GE1-350
Abstract

Objective: Serratia sp. CM01 is a wild strain with the resistance and reduction ability of chromium(Ⅵ). The aim of this study it to investigate the underlying mechanisms of the Cr(Ⅵ) tolerance and reduction of strain CM01, and to explore its response to environmental pollution pressure at the molecular level. Methods: The iTRAQ technique was utilized to investigate the differentially expressed protein patterns related to the Cr(Ⅵ)-resistance in wild-type strain CM01 and domesticated CM01. RT-qPCR was used to verify the expression levels of several functional genes. The cell surface hydrophobicity and autoaggregation, the intracellular glucose content, and the total superoxide dismutase (SOD) activity were determined. Results: In total, 2750 proteins were detected and identified in WT CM01 and domesticated CM01. Compared with WT CM01, the iTRAQ results of 646 proteins were found to be significantly differentially expressed in domesticated CM01. There were 343 up-regulated and 303 down-regulated proteins, which mainly related to carbohydrate metabolism, stress responses, amino acid metabolism and some other systems. RT-qPCR results showed that the expression level of seven genes in domesticated CM01 were consistent with the iTRAQ proteomic profiles. The cell surface hydrophobicity, self-aggregation, intracellular glucose content and total SOD activity of domesticated CM01 with Cr(Ⅵ) treatment were significantly higher than without Cr(Ⅵ) treatment. Conclusion: Domesticated CM01 displayed a complex biological network to exhibit the tolerance of Cr(Ⅵ), which may be attributed to the following aspects: (a) CM01 reduced the consumption of glucose by inhibiting the metabolism of carbohydrates, which was an energy-saving survival mode. (b) The inositol phosphate metabolism pathway played an important role. (c) Oxidative stress proteins enhanced the adaptability. (d) CM01 enhanced biosynthesis of hydrophobic amino acids to resistance to Cr(Ⅵ). (e) Several key systems and proteins, such as UvrABC system, Lon protease, porin OmpC, also may play an important role.

Published
2021
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24. Effects of exogenous sulfate on the chromium(VI) metabolism of chromium(VI)-resistant engineered strains

Author

Xinglong Li, Qi Yin, Ruijia Gu, Mei Li, Jing Yan, Yuan Liu, Yanlun Qiu, Qunhua Bai, Yingli Li, Yan Ji, Jieying Gao, and Hong Xiao

Subjects
Sulfate, chrA/chrB, Cr(VI)-resistance, Cr(VI) metabolism, Environmental pollution, TD172-193.5, Environmental sciences, GE1-350
Abstract

Objective: To explore the effects of exogenous sulfate on the efficiency of chromium(VI) metabolism of three chromium(VI)-resistant Escherichia coli strains (eChrA / eChrB / eChrAB) by adding chromium(VI)-resistance genes chrA and/or chrB, for better understanding and further application of these Cr(VI)-resistant strains in environmental and industrial chromium removal. Methods: Based on three engineered Cr(VI)-resistant strains exposed to different concentrations of sulfate: i) Evaluation of Cr(VI) metabolism characteristics, including the growth rate, the Cr(VI) tolerance, the removal, absorption and efflux capacity of Cr(VI); ii) Detection the expressions of Cr(VI) resistance-related genes (chrA and chrB), and sulfate channel protein-related genes (sbp, cysA, cysU and cysW genes) by RT-qPCR. Results: Exogenous sulfate enhanced the Cr(VI) tolerance and the removal rate of these three engineered Cr(VI)-resistant strains, and promoted their growth rate under Cr(VI) stress, while suppressed their absorption and efflux capacity. Under a certain sulfate concentration, the Cr(VI) tolerance, removal ability and efflux capacity of these three strains were ranked as follow: eChrAB > eChrA > eChrB, while ranked as eChrB > eChrA > eChrAB for the Cr(VI) absorption rate, respectively. Opposite to the Cr(VI) treatment, exogenous sulfate suppressed the transcription levels of the Cr(VI) resistance-related genes (chrA and chrB) with gradually increased concentrations, and reduced those of sulfate channel protein related genes (sbp,cysA, cysU and cysW) under the medium and high concentrations. Conclusion: Sulfate can enhance the Cr(VI) tolerance and growth of Cr(VI)-resistant strains, via inhibiting the Cr(VI) absorption and efflux in a concentration-dependent manner. The underlying mode of action might be the competition of transport channels between sulfate and Cr(VI), and the suppression of sulfate channel protein related genes expressions by exogenous sulfate. Our results demonstrated an appropriate supplication of exogenous sulfate could contribute to the Cr(VI) pollution management by genes chrA/chrB related Cr(VI)-resistant strains. Additionally, the engineered E. coli strain eChrAB showed more potential for the actual Cr(VI) pollution application than strain eChrA and eChrB.

Published
2021
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25. Study on the metabolite difference of tricolor quinoa from different habitats based on GC-MS

Author

Yujie SHI, Xinglong LI, Yuan TANG, Yu DONG, and Xiaoyong WU

Subjects
crop cultivation, quinoa, GC-MS, XCMS, metabolic differences, stress resistance, Technology
Abstract

In order to study the effects of different habitats on the development of quinoa, taking quinoa seeds from different habitats as research objects, significant differences in metabolites and related metabolic pathways are screened. The metabolic profiles of the seeds of black quinoa, red quinoa and white quinoa from Dulan County, Qinghai Province and Yanyuan County, Sichuan Province are analyzed through non-targeted metabonomics analysis with GC-MS platform. The original data are pretreated by XCMS online platform for subsequent multivariate statistical analysis. The results show that the metabolic characteristics of black, red and white seeds in Dulan county and Yanyuan County are different. Among them, the difference between red and white seeds from the two counties is larger, while the difference of the black quinoa seeds is the smallest. There are 570 characteristic peaks in red seeds which have significant differences, and the up-regulated substances are less than the down-regulated. The difference between black quinoa from two habitats is the smallest, and the up- and down-regulated trends are like that of red quinoa. There is secondly significant difference between the white seeds from the two habitats, and the up- and down-regulated trends are the opposite of that of the red and black quinoas, and 486 characteristic peaks are detected, with more up-regulated substances than down-regulated. Different habitats have great impact on quinoa. Black and red quinoas are more suitable to be planted in Dulan County, Qinghai Province, while white quinoa is more suitable to be planted in Yanyuan County, Sichuan Province. The conclusions could guide the cultivation and breeding of quinoa in Dulan county and Yanyuan County, and provide theoretical basis for further study of the stress resistance mechanism of quinoa.

Published
2019
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26. Circular RNA circ-DONSON facilitates gastric cancer growth and invasion via NURF complex dependent activation of transcription factor SOX4

Author

Lixian Ding, Yuying Zhao, Shuwei Dang, Yue Wang, Xinglong Li, Xiaotong Yu, Zhongsheng Li, Jiufeng Wei, Ming Liu, and Guodong Li

Subjects
circ-DONSON, Gastric cancer, NURF, SOX4, Progression, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Circular RNAs (circRNAs) are a novel type of noncoding RNAs and play important roles in tumorigenesis, including gastric cancer (GC). However, the functions of most circRNAs remain poorly understood. In our study, we aimed to investigate the functions of a new circRNA circ-DONSON in GC progression. Methods The expression of circ-DONSON in gastric cancer tissues and adjacent normal tissues was analyzed by bioinformatics method, qRT-PCR, Northern blotting and in situ hybridization (ISH). The effects of circ-DONSON on GC cell proliferation, apoptosis, migration and invasion were measured by using CCK8, colony formation, EdU, immunofluorescence (IF), FACS and Transwell assays. qRT-PCR and Western blotting were utilized to validate how circ-DONSON regulates SOX4 expression. ChIP, DNA fluorescence in situ hybridization (DNA-FISH) and DNA accessibility assays were used to investigate how circ-DONSON regulates SOX4 transcription. The interaction between circ-DONSON and NURF complex was evaluated by mass spectrum, RNA immunoprecipitation (RIP), pulldown and EMSA assays. Xenograft mouse model was used to analyze the effect of circ-DONSON on GC growth in vivo. Results Elevated expression of circ-DONSON was observed in GC tissues and positively associated with advanced TNM stage and unfavorable prognosis. Silencing of circ-DONSON significantly suppressed the proliferation, migration and invasion of GC cells while promoting apoptosis. circ-DONSON was localized in the nucleus, recruited the NURF complex to SOX4 promoter and initiated its transcription. Silencing of the NURF complex subunit SNF2L, BPTF or RBBP4 similarly attenuated GC cell growth and increased apoptosis. circ-DONSON knockdown inhibited GC growth in vivo. Conclusion circ-DONSON promotes GC progression through recruiting the NURF complex to initiate SOX4 expression.

Published
2019
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27. Clinical Differences between Eosinophilic and Noneosinophilic Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Multicenter Cross-Sectional Study

Author

Guangming Dai, Yajuan Ran, Jiajia Wang, Xingru Chen, Junnan Peng, Xinglong Li, Huojin Deng, Min Xiao, and Tao Zhu

Subjects
Pathology, RB1-214
Abstract

Rationale. Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is highly heterogeneous with a plethora of different etiologic factors and inflammatory presentations. COPD with higher blood eosinophil count is associated with increased readmission rates and better corticosteroid responses. However, the clinical features of eosinophilic AECOPD are not well explored. Thus, this study was aimed at exploring the clinical differences between eosinophilic and noneosinophilic AECOPD. Methods. A total of 643 AECOPD patients were enrolled in this multicenter cross-sectional study. Finally, 455 were included, 214 in the normal-eosinophil AECOPD (NEOS-AECOPD) group, 63 in the mild increased-eosinophil AECOPD (MEOS-AECOPD) group, and 138 in the severe increased-eosinophil AECOPD (SEOS-AECOPD) group. Demographic data, underlying diseases, symptoms, and laboratory findings were collected. Multiple logistic regression analysis was performed to identify the independent factors associated with blood eosinophils (EOS). Correlations between blood EOS and its associated independent factors were evaluated. Results. The significant differences in 19 factors, including underlying diseases, clinical symptoms, and laboratory parameters, were identified by univariate analysis. Subsequently, multiple logistic regression analysis revealed that lymphocyte%, neutrophil% (NS%), procalcitonin (PCT), and anion gap (AG) were independently associated with blood EOS in AECOPD. Both blood EOS counts and EOS% were significantly correlated with lymphocyte%, NS%, PCT, and AG. Conclusions. Collectively, blood EOS was independently associated with lymphocyte%, NS%, PCT, and AG in AECOPD patients. Lymphocyte% was lower, and NS%, PCT, and AG were higher in eosinophilic AECOPD. Our results indicate that viral-dominant infections are the probable major etiologies of eosinophilic AECOPD. Noneosinophilic AECOPD is more likely associated with bacterial-dominant infections. The systemic inflammation in noneosinophilic AECOPD was more severe.

Published
2020
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28. Application of Metal Magnetic Memory Testing Technology to the Detection of Stress Corrosion Defect

Author

Bingxun Zhao, Kai Yao, Libo Wu, Xinglong Li, and Yue-Sheng Wang

Subjects
metal magnetic memory testing technology, stress corrosion, ferromagnetic materials, characterization parameters, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

The damage of equipment manufactured with ferromagnetic materials in service can be effectively detected by Metal Magnetic Memory Testing (MMMT) technology, which has received extensive attention in various industry fields. The effect of stress or strain on Magnetic Flux Leakage (MFL) signals of ferromagnetic materials has been researched by many scholars for assessing stress concentration and fatigue damage. However, there is still a lack of research on the detection of stress corrosion damage of ferromagnetic materials by MMMT technology. In this paper, the electrochemical corrosion system was designed for corrosion experiments, and three different experiments were performed to study the effect of corrosion on MFL signals. The distribution of MFL signals on the surface of the specimen was investigated. The results indicated that both the normal component Hn and tangential component Ht of MFL signals presented different signal characteristics when the specimen was subjected to different working conditions. Finally, two characterization parameters, Sn and St, were defined to evaluate the corrosion degree of the specimen, and St is better. The direct dependence of corrosion depth on the parameter was developed and the average error rates between the predicted and measured values are 8.94% under the same working condition. Therefore, the expression can be used to evaluate the corrosion degree of the specimen quantitatively. The results are significant for detecting and assessing the corrosion defect of ferromagnetic materials.

Published
2020
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29. Fault Localization Method for Ring-Shaped DC Microgrids Based on Line Model and Euclidean Distance

Author

Xinglong, Li, Bo, Feng, Yi, Yang, Jiayong, Zhong, Hongwei, Zhao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, and Cai, Li, editor

Published
2024
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37. MULTI-OUTPUT REGRESSION PREDICTION OF PNEUMATIC SUBMERGING RESISTANCE AND DISTURBANCE AREA BASED ON NEURAL NETWORK.

Author

Xia LI, Xuhui WANG, Jinyou XU, Xinglong LI, Zhangjun JIANG, and Birong YOU

Subjects
CONVOLUTIONAL neural networks, DEEP learning, REGRESSION analysis, FIELD research, AUTUMN
Abstract

The current field of pneumatic subsoiling prediction focuses on a single task and neglects the possible interrelationships between different outputs. In order to improve prediction accuracy and reduce the number of algorithmic model establishments, this study conducted field experiments on soil in autumn and winter. Neural network algorithms RBF (radial basis neural network), BP (backward propagation neural network), DNN (deep learning network), and CNN (convolutional neural network) were used to make multi-output regression predictions for changing the traction resistance and disturbance area affected by different levels of subsoiling velocity, depth, and pressure value in the process of pneumatic subsoiling. The evaluation indexes RMSE, MAE, and R² were compared with the single output regression model, and the accuracy of the four models with the highest accuracy was compared with that of its own single output model to prove the correlation between traction resistance and disturbance area. The results showed that the R² of the four model test sets of RBF, BP, DNN, and CNN were 0.9999, 0.9966, 0.9986, and 0.9762, respectively. The R² values of the disturbance area are 0.9997, 0.9924, 0.9968, and 0.9715, respectively. RBF has the highest R2 and the lowest RMSE and MAE, indicating that the RBF model has the best prediction effect. Compared with the single output regression model of the RBF model, the prediction accuracy of both outputs is higher, so it can be used to predict the subsoiling drag resistance and disturbance area. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Highly efficient oxygen evolution reaction enabled by phosphorus-boron facilitating surface reconstruction of amorphous high-entropy materials

Author

Xinglong, Li, Ziyun, Zhang, Ming, Shen, Zhiyuan, Wang, Runguo, Zheng, Hongyu, Sun, Yanguo, Liu, Dan, Wang, and Chunli, Liu

Subjects
Biomaterials, Colloid and Surface Chemistry, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials
Abstract

Efficient, cost-effective and durable electrocatalysts are highly required to overcome the slow kinetics and high overpotential of oxygen evolution reaction (OER). Here we report a series of novel amorphous high-entropy borophosphate catalysts FeCoNiMBPO

Published
2022
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42. Integrative analysis of the roles of lncRNAs and mRNAs in ischaemic preconditioning to alleviate liver ischaemia–reperfusion injury in mice

Author

Yongliang Hua, Yanan Xu, Xinglong Li, Bing Yin, Shounan Lu, Chaoqun Wang, Shanjia Ke, Baolin Qian, Hongjun Yu, Miaoyu Bai, and Yong Ma

Subjects
Gene Expression Profiling, Biophysics, Cell Biology, Biochemistry, Disease Models, Animal, Mice, Liver, Reperfusion Injury, Animals, RNA, Long Noncoding, RNA, Messenger, Ischemic Preconditioning, Molecular Biology, Oligonucleotide Array Sequence Analysis
Abstract

The objective of our study was to elucidate the possible underlying mechanism for the protective effect of ischaemic preconditioning (IPC) against ischaemia-reperfusion (I/R) injury and to provide new research perspectives of long non-coding RNAs (lncRNAs). In this study, serum and liver tissue samples were collected to measure indexes of liver injury from a mouse liver model in sham, I/R injury and I/R + IPC groups. Furthermore, liver samples from 5 randomly selected mice per group were extracted and subjected to the microarray and subsequent bioinformatics analysis. IPC ameliorated liver damage by lowered liver transaminase levels and pro-inflammatory cytokines. A total of 167 lncRNAs and 108 messenger RNAs (mRNAs) were significantly differentially expressed genes (DEGs) between the I/R + IPC and I/R groups. Gene Ontology (GO) analysis revealed that these genes were mainly related to unfolded proteins, responses to topologically incorrect proteins, responses to temperature stimuli, protein folding and protein refolding. Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis indicated that the DEGs were enriched in the following pathways: protein processing in the endoplasmic reticulum; antigen processing and presentation; and fructose and mannose metabolism. Additionally, the 7 selected DEGs (Hspa1ab, Chka, Clec2h, Mvd, Adra1a, AK085737 and AK088966) were validated in modules of the lncRNA-mRNA weighted coexpression network, which agreed with the qRT-PCR and chip data. And the identified differentially expressed lncRNAs and mRNAs may provide new clues to understand the pivotal pathophysiological mechanism by which IPC alleviates I/R-caused liver damage.

Published
2022
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43. PORTABLE X/γ-RAY SURVEY METER BASED ON THE INTERNET OF THINGS NETWORK FOR MEASURING THE ENVIRONMENTAL RADIATION DISTRIBUTION.

Author

Simin XIAO, Xinglong LI, Yang LIU, Zhiping LUO, Hongchao PANG, Jianhua WU, and Xiaopeng HUANG

Subjects
*NUCLEAR research, *INTERNET of things, *NUCLEAR science, *RADIATION doses, *TEMPERATURE detectors
Abstract

Real-time detection of X/gamma radiation dose rates holds particular significance in nuclear science research. In this study, we developed a portable X/gamma-ray survey meter for large-scale distributed real-time monitoring of ambient dose equivalent rates in the surrounding environment. This innovative device uses a silicon photomultiplier coupled with a CsI(Tl) scintillator and can connect to an Internet of Things network. Additionally, it facilitates a wide spectrum of dose rate measurements by modifying the frequency of a pulse-frequency modulation-type DC-DC power supply mode. The energy response of the survey meter, which is improved through Geant4 simulations and a multi-comparator design, ranges from 48 keV to 1.3 MeV, encompassing various common protection level applications. It effectively measures gamma radiation dose rates ranging between 0.1 p. Svh-1 and 100 mSvh-1 for 60Co. Temperature compensation of the detector was achieved through a series of experiments. The meter exhibits a deviation of -25 % to +25 % at temperatures between -40 °C and +40 °C. [ABSTRACT FROM AUTHOR]

Published
2024
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44. RNF125 attenuates hepatocellular carcinoma progression by downregulating SRSF1-ERK pathway

Author

Yong Ma, Zhigang Feng, Shanjia Ke, Chaoqun Wang, Shounan Lu, Yanan Xu, Hongjun Yu, Zihao Li, Bing Yin, Xinglong Li, Yongliang Hua, Baolin Qian, Miaoyu Bai, Yao Fu, Yingmei Zhang, and Yaohua Wu

Subjects
Cancer Research, Genetics, Molecular Biology
Abstract

Hepatocellular carcinoma (HCC) is one of the most deadly malignant cancers worldwide. Research into the crucial genes responsible for maintaining the aggressive behaviour of cancer cells is important for the clinical treatment of HCC. The purpose of this study was to determine whether the E3 ubiquitin ligase Ring Finger Protein 125 (RNF125) plays a role in the proliferation and metastasis of HCC. RNF125 expression in human HCC samples and cell lines was investigated using TCGA dataset mining, qRT‒PCR, western blot, and immunohistochemistry assays. In addition, 80 patients with HCC were studied for the clinical value of RNF125. Furthermore, the molecular mechanism by which RNF125 contributes to hepatocellular carcinoma progression was determined with mass spectrometry, coimmunoprecipitation (Co-IP), dual-luciferase reporter assays, and ubiquitin ladder assays. We found that RNF125 was markedly downregulated in HCC tumour tissues, which was associated with a poor prognosis for patients with HCC. Moreover, the overexpression of RNF125 inhibited HCC proliferation and metastasis both in vitro and in vivo, whereas the knockdown of RNF125 exerted antithetical effects. Mechanistically, mass spectrometry analysis revealed a protein interaction between RNF125 and SRSF1, and RNF125 accelerated the proteasome-mediated degradation of SRSF1, which impeded HCC progression by inhibiting the ERK signalling pathway. Furthermore, RNF125 was detected to be the downstream target of miR-103a-3p. In this study, we identified that RNF125 is a tumour suppressor in HCC and inhibits HCC progression by inhibiting the SRSF1/ERK pathway. These findings provide a promising treatment target for HCC.

Published
2023
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45. Systematic studies for the nuclear parton distribution with photon and hadron productions in nuclear collisions at the LHC

Author

Xinglong Li, Ya Zhu, Xiaoming Zhang, and Dai-Cui 周代翠 Zhou

Subjects
Nuclear and High Energy Physics, Astronomy and Astrophysics, Instrumentation
Abstract

A systematic study of the impact of widely-used nuclear-modified parton distribution function (nPDF) parameterizations on the production of direct photons and charged hadrons is per- formed by employing a next-to-leading order Monte Carlo event generator JETPHOX in hadronic collisions at LHC energies. The nuclear modification factors of photon and charged hadron produc- tions are studied in three types collision systems, small (p+p and p+Pb), medium (O+O), and large (P b + P b) in a wide rapidity acceptance. The results illustrate that the direct photon production process is a sensitive probe to decipher difference of the nPDF parameterization implementations, which provide new insights for the experimental measurements to refine the nuclear modifications on the parton distributions. To provide a benchmark for searching for quark gluon plasma in the upcoming small system measurements at LHC energies, we carry out a detailed studies of the cold nuclear matter effect in (O + O) collisions. Our outcomes show the cold nuclear matter effects are negligible for the charged hadron production in (O + O) collisions, which can be used to be as a baseline to subtract the initial state contribution.

Published
2023
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47. A single-dose circular RNA vaccine prevents Zika virus infection without enhancing dengue severity in mice

Author

Xinglong Liu, Zhengfeng Li, Xiaoxia Li, Weixuan Wu, Huadong Jiang, Yufen Zheng, Junjie Zhou, Xianmiao Ye, Junnan Lu, Wei Wang, Lei Yu, Yiping Li, Linbing Qu, Jianhua Wang, Feng Li, Ling Chen, Linping Wu, and Liqiang Feng

Subjects
Science
Abstract

Abstract Antibody-dependent enhancement (ADE) is a potential concern for the development of Zika virus (ZIKV) vaccines. Cross-reactive but poorly neutralizing antibodies, usually targeting viral pre-membrane or envelope (E) proteins, can potentially enhance dengue virus (DENV) infection. Although E domain III (EDIII) contains ZIKV-specific epitopes, its immunogenicity is poor. Here, we show that dimeric EDIII, fused to human IgG1 Fc fragment (EDIII-Fc) and encoded by circular RNA (circRNA), induces better germinal center reactions and higher neutralizing antibodies compared to circRNAs encoding monomeric or trimeric EDIII. Two doses of circRNAs encoding EDIII-Fc and ZIKV nonstructural protein NS1, another protective antigen, prevent lethal ZIKV infection in neonates born to immunized C57BL/6 mice and in interferon-α/β receptor knockout adult C57BL/6 mice. Importantly, a single-dose optimized circRNA vaccine with improved antigen expression confers potent and durable protection without inducing obvious DENV ADE in mice, laying the groundwork for developing flavivirus vaccines based on circRNAs encoding EDIII-Fc and NS1.

Published
2024
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48. Nanosized high entropy spinel oxide (FeCoNiCrMn)3O4 as a highly active and ultra-stable electrocatalyst for the oxygen evolution reaction

Author

Chanqin Duan, Xinglong Li, Dan Wang, Zhiyuan Wang, Hongyu Sun, Runguo Zheng, and Yanguo Liu

Subjects
Fuel Technology, Renewable Energy, Sustainability and the Environment, Energy Engineering and Power Technology
Abstract

High-entropy oxides (HEOs) with a multi-component single-phase structure are considered as promising electrocatalysts for the oxygen evolution reaction due to their good catalytic activity and tailorable electrochemical properties.

Published
2022
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50. Amorphous High-entropy Non-precious metal oxides with surface reconstruction toward highly efficient and durable catalyst for oxygen evolution reaction

Author

Kanghui Tian, Yanguo Liu, Chan-Qin Duan, Runguo Zheng, Shunda Jiang, Dan Wang, Hongyu Sun, Zhiyuan Wang, and Xinglong Li

Subjects
Tafel equation, Amorphous metal, Materials science, Oxygen evolution, Oxide, Overpotential, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials, Amorphous solid, Catalysis, Biomaterials, chemistry.chemical_compound, Colloid and Surface Chemistry, chemistry, Chemical engineering, Water splitting
Abstract

High-entropy materials (HEMs) have attracted extensive interests in exploring multicomponent systems for highly efficient and durable catalysts. Tuning composition and configuration of HEMs provides untapped opportunities for accessing better catalytic performance. Herein, we report three amorphous high-entropy transition metal oxides catalysts with uniform composition through a simple and controllable liquid phase non-equilibrium reduction method. The self-made catalyst FeCoNiMnBOx exhibits excellent oxygen evolution performance, including a low overpotential (266 mV at 10 mA cm−2), small Tafel slope (64.5 mV dec-1) and extremely high stability (only 3.71% increase of potential after 100 h test and no current decay after cyclic voltammetry of 31,000 cycles). The outstanding performance can be attributed to the in-situ electrochemical activation induced surface reconstruction to form a stable oxyhydroxide surface layer, the cocktail effect (multi-metal synergy) brought by high entropy, and the advantages of amorphous structure itself. The outstanding catalytic properties of the new high-entropy amorphous metal oxide, as well as its advantages of low cost and simple preparation, suggest its great potential in water splitting.

Published
2022
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