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| 1 | Prognostic factors of refractory NSCLC patients receiving anlotinib hydrochloride as the third-or further-line treatment显示文摘Objective:Anlotinib hydrochloride is a multitarget tyrosine kinase inhibitor that targets vascular endothelial growth factor receptor,fibroblast growth factor receptor,platelet-derived growth factor receptor,c-Kit,and c-MET;therefore,it exhibits both antitumor and anti-angiogenetic activities.A phase III trial has shown that anlotinib improved progression-free survival(PFS)and overall survival(OS)in patients with advanced non-small cell lung cancer(NSCLC),who presented with progressive disease or intolerance after standard chemotherapy.This study aimed to analyze the characteristics of patients receiving anlotinib treatment to determine the dominant populations who are fit for the treatment.Methods:Data were collected from March 2015 to January 2017 from a randomized,double-blind,placebo-controlled,multicenter,phase III trial of anlotinib(ALTER0303).A total of 437 patients were enrolled and randomly allocated(2:1)to the anlotinib and placebo groups.Kaplan–Meier analysis and log-rank test were performed to compare PFS and OS.Cox proportional hazards model was adopted for multivariate prognostic analysis.Results:Multivariate analysis indicated that high post-therapeutic peripheral blood granulocyte/lymphocyte ratio and elevated alkaline phosphatase levels were independent risk factors for PFS.Meanwhile,elevated thyroid-stimulating hormone,blood glucose,and triglyceride levels;hypertension;and hand–foot syndrome were independent protective factors of PFS.High posttherapeutic peripheral blood granulocyte/lymphocyte ratio,an Eastern Cooperative Oncology Group(ECOG)score≥2,and the sum of the maximal target lesion length at baseline were independent risk factors of OS,and hypertriglyceridemia was an independent protective factor of OS.Conclusions:This study preliminarily explored the possible factors that affected PFS and OS after anlotinib treatment in patients with advanced refractory NSCLC,and the baseline characteristics of the therapeutically dominant populations were then identified. | Jing Wang Yizhuo Zhao Qiming Wang Li Zhang Jianhua Shi Zhehai Wang Ying Cheng Jianxing He Yuankai Shi Hao Yu Yang Zhao Weiqiang Chen Yi Luo Xiuwen Wang Kejun Nan Faguang Jin Jian Dong Baolan Li Zhujun Liu Baohui Han Kai Li | 2018 | Cancer Biology & Medicine2018，15，4： | 46 |
| 2 | Vision,application scenarios,and key technology trends for 6G mobile communications显示文摘With the global commercialization of the fifth-generation(5G)network,many countries,including China,USA,European countries,Japan,and Korea,have started exploring 6G mobile communication network,following the tradition of“planning the next while commercializing one generation”.Currently,studies on 6G networks are at the infancy stage.Research on the vision and requirements for 6G is still ongoing,and the industry is yet to clarify the key enabling technologies for 6G.However,6G will certainly build on the success of 5G.Therefore,developing high-quality 5G networks and seamlessly integrating 5G with verticals are the priorities before 2030,when 6G is projected to be commercialized.Also,global 5G standards will keep evolving to better support vertical applications.As a milestone,the Third-Generation Partnership Project(3GPP)published Release 16 in July 2020,which continuously enhanced the capabilities of mobile broadband service based on Release 15 and realized the support for low-delay and high-reliability applications,such as Internet of Vehicles and industrial Internet.Currently,3GPP is working on Releases 17 and 18,focusing on meeting the demands of medium-and high-data-rate machine communication with low-cost and high-precision positioning,which will be published in June 2022.Thus,6G networks will further expand the application fields and scope of the Internet of Things to accommodate those services and applications that are beyond the capabilities of 5G networks.Herein,we present our vision,application scenarios,and key technological trends for 6G networks.Furthermore,we propose several future research opportunities in 6G networks with regard to industrialization and standardization. | Zhiqin WANG Ying DU Kejun WEI Kaifeng HAN Xiaoyan XU Guiming WEI Wen TONG Peiying ZHU Jianglei MA Jun WANG Guangjian WANG Xueqiang YAN Jiying XIANG He HUANG Ruyue LI Xinhui WANG Yingmin WANG Shaohui SUN Shiqiang SUO Qiubin GAO Xin SU | 2022 | Science China(Information Sciences)2022，65，5： | 17 |
| 3 | Phosphorylation of PLIN3 by AMPK promotes dispersion of lipid droplets during starvation显示文摘Dear Editor,Lipid droplets(LDs)are dynamic lipid-storage organelles of storage depots and sources of essential substrates for myriad cellular processes and protect cells from lipotoxicity(Ohsaki et al.,2006).Disrupted LD and fat storage homeostasis has been linked to metabolic diseases such as atherosclerosis,obesity,and type II diabetes(Levin et al.,2001).Structurally,the core of neutral lipids in LDs is surroun ded by a phospholipid mono layer and coated with specific proteins(Storey et al.,2011).Perilipin family of proteins are the predominant LD-associated proteins. | Jianxi Zhu Mingyang Xu Yi Liu Lisha Zhuang Kejun Ying Feng Liu Dan Liu Wenbin Ma Zhou Songyang | 2019 | Protein & Cell2019，10，5： | 7 |
| 4 | A Zigbee - based smart home system : An energy - saving method显示文摘 | Zang Xuan Ying Sun Li Kejun | | 0，，148： | 1 |
| 5 | A Zigbee-based smart home system:An energy- saving method显示文摘 | Zang Xuan Ying Sun Li Kejun | 2011 | Advanced Materials Research2011，，： | 1 |
| 6 | The initial exploration for ^(26)Al chronology in deep-sea ferromanganese crust显示文摘Background The deep-sea ferromanganese crust(DSFC)is a natural archive for recording the history of the Earth’s evolution,as one of the most common authigenic assemblages in marine sediments.Although the depositional age dating using meteoric ^(10)Be has been successfully used in the study on the chronology of DSFC,the research on ^(26)Al has not seen relevant reports in this aspect due to the influence of factors such as measurement sensitivity and ^(26)Al in situ production.Method The first exploration for ^(26)Al chronology in DSFC was carried out by using accelerator mass spectrometry(AMS)measurements of ^(10)Be and ^(26)Al,and the comparison of relationship between isotopic ratios and concentrations of Al and Be.Results The growth rates of G.R=(1.44±0.09)mm/Ma,(3.58±0.29)mm/Ma,(1.52±0.10)mm/Ma and(2.93±0.14)mm/Ma are derived using ^(10)Be/^(9)Be,^(26)Al/^(27)Al ratios,^(10)Be and ^(26)Al concentrations,respectively.Conclusion The ^(26)Al chronological methods have been explored based on a DSFC sample and encouraging results were obtained.The results are preliminary and insufficient;some information is still needed to explain the difference between ^(26)Al and ^(10)Be chronology. | Kejun Dong Ying Hu Lifeng Cui Jiaqi Zhang Sheng Xu Hongtao Shen | 2023 | Radiation Detection Technology and Methods2023，7，2： | 0 |
| 7 | Feasibility and physics potential of detecting ^(8)B solar neutrinos at JUNO显示文摘The Jiangmen Underground Neutrino Observatory(JUNO)features a 20 kt multi-purpose underground liquid scintillator sphere as its main detector.Some of JUNO's features make it an excellent location for^8B solar neutrino measurements,such as its low-energy threshold,high energy resolution compared with water Cherenkov detectors,and much larger target mass compared with previous liquid scintillator detectors.In this paper,we present a comprehensive assessment of JUNO's potential for detecting^8B solar neutrinos via the neutrino-electron elastic scattering process.A reduced 2 MeV threshold for the recoil electron energy is found to be achievable,assuming that the intrinsic radioactive background^(238)U and^(232)Th in the liquid scintillator can be controlled to 10^(-17)g/g.With ten years of data acquisition,approximately 60,000 signal and 30,000 background events are expected.This large sample will enable an examination of the distortion of the recoil electron spectrum that is dominated by the neutrino flavor transformation in the dense solar matter,which will shed new light on the inconsistency between the measured electron spectra and the predictions of the standard three-flavor neutrino oscillation framework.IfDelta m^(2)_(21)=4.8times10^(-5);(7.5times10^(-5))eV^(2),JUNO can provide evidence of neutrino oscillation in the Earth at approximately the 3sigma(2sigma)level by measuring the non-zero signal rate variation with respect to the solar zenith angle.Moreover,JUNO can simultaneously measureDelta m^2_(21)using^8B solar neutrinos to a precision of 20% or better,depending on the central value,and to sub-percent precision using reactor antineutrinos.A comparison of these two measurements from the same detector will help understand the current mild inconsistency between the value of Delta m^2_(21)reported by solar neutrino experiments and the KamLAND experiment. | Angel Abusleme Thomas Adam Shakeel Ahmad Sebastiano Aiello Muhammad Akram Nawab Ali 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 David Biare Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Max Buesken 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 Alexander Chepurnov 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 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 Maxim Gromov 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 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 Wenju Huo Cédric Huss Safeer Hussain Antonio Insolia Ara Ioannisian Daniel Ioannisyan Roberto Isocrate 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 Frederic Lefevre Liping Lei 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 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 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 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 MMari 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 Pavithra Muralidharan Massimiliano Nastasi Dmitry VNaumov Elena Naumova Igor Nemchenok Alexey Nikolaev 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 Muhammad Shahzad Vladislav Sharov Gang Shi Jingyan Shi Yongjiu Shi Vitaly Shutov Andrey Sidorenkov FedorŠimkovic 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 DušanŠtefánik 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 Yuguang Xie Zhangquan Xie Zhizhong Xing Benda 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 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 Pan Zeng 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 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 Jiaheng Zou | 2021 | Chinese Physics C2021，45，2： | 0 |
| 8 | Dynamic changes of genomic methylation profiles at different growth stages in Chinese Tan sheep显示文摘Background:Tan sheep,an important local sheep breed in China,is famous for their fur quality.One-month-old Tan sheep have white,curly hair with beautiful flower spikes,commonly known as“nine bends”,which has high economic value.However,the“nine bends”characteristic gradually disappears with age;consequently,the economic value of the Tan sheep decreases.Age-related changes in DNA methylation have been reported and may be responsible for age-induced changes in gene expression.Until now,no genome-wide surveys have been conducted to identify potential DNA methylation sites involved in different sheep growth stages.In this study we investigated the dynamic changes of genome-wide DNA methylation profiles in Tan sheep using DNA from skin and deep whole-genome bisulfite sequencing,and compared the DNA methylation levels at three different growth stages:1,24,and 48 months old(mon1,mon24,and mon48,respectively).Results:In this study,11 skin samples from three growth stages(four for mon1,four for mon24,and three for mon48)were used for DNA methylation analysis and gene expression profiling.There were 52,288 and 236 differentially methylated genes(DMGs)identified between mon1 and mon24,mon1 and mon48,and mon24 and mon48,respectively.Of the differentially methylated regions,1.11%,7.61%,and 7.65% were in the promoter in mon1 vs.mon24,mon24 vs.mon48,and mon1 vs.mon48,respectively.DMGs were enriched in the MAPK and WNT signaling pathways,which are related to age growth and hair follicle morphogenesis processes.There were 51 DMGs associated with age growth and curly fleece formation.Four DMGs between mon1 and mon48(KRT71,CD44,ROR2 and ZDHHC13)were further validated by bisulfite sequencing.Conclusions:This study revealed dynamic changes in the genomic methylation profiles of mon1,mon24,and mon48 sheep,and the percentages of methylated cytosines were 3.38%,2.85% and 4.17%,respectively.Of the DMGs,KRT71 and CD44 were highly methylated in mon1,and ROR2 and ZDHHC13 were highly methylated in mon48.These findings provide foundational information that may be used to develop strategies for potentially retaining the lamb fur and thus improving the economic value of Tan sheep. | Yufang Liu Qiao Xu Xiaolong Kang Kejun Wang Jve Wang Dengzhen Feng Ying Bai Meiying Fang | 2022 | Journal of Animal Science and Biotechnology2022，13，1： | 0 |
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