Biomarkers of aging
Hà Dương Xuân Bảo,Jiani Cao,Mengting Chen,Min Chen,Wei Chen,Xiao Chen,Yanhao Chen,Yu Chen,Yutian Chen,Zhiyang Chen,Jagadish K. Chhetri,Yingjie Ding,Junlin Feng,Jun Guo,Mengmeng Guo,Chuting He,Yujuan Jia,Haiping Jiang,Ying Jing,Dingfeng Li,Jiaming Li,Jingyi Li,Qinhao Liang,Rui Liang,Xiaoqian Liu,Zuojun Liu,Oscar Junhong Luo,Jianwei Lv,Jingyi Ma,Jiawei Nie,Xinhua Qiao,Xinpei Sun,Xiaoqiang Tang,Jianfang Wang,Qiaoran Wang,Siyuan Wang,Xuan Wang,Yaning Wang,Yuhan Wang,Kai Xia,Fuhui Liao,Lingyan Xu,Yingying Xu,Haoteng Yan,Liang Yang,Ruici Yang,Yuanxin Yang,Yilin Ying,Le Zhang,Weiwei Zhang,Wenwan Zhang,Xuning Zhang,Zhuo Zhang,Min Zhou,Rui Zhou,Qingchen Zhu,Zhengmao Zhu,Feng Cao,Zhongwei Cao,P. Chang,Chang Chen,Guobing Chen,Hou-Zao Chen,Jun Chen,Weimin Ci,Bi-Sen Ding,Qiurong Ding,Feng Gao,J.H. Han,Kai Huang,Zhenyu Ju,Qing-Peng Kong,Ji Li,Jian Li,Xin Li,Baohua Liu,Feng Liu,Lin Liu,Qiang Liu,Qiang Liu,Xingguo Liu,Yong Liu,Xianghang Luo,Shuai Ma,Xinran Ma,Zhiyong Mao,Jing Nie,Yaojin Peng,Jing Qu,Jie Ren,Ruibao Ren,Moshi Song,Zhou Songyang,Yi E. Sun,Mei Tian,Sheng Wang,Si Qi Wang,Xia Wang,Xiaoning Wang,Yan-Jiang Wang,Yunfang Wang,Catherine C L Wong,Andy Peng Xiang,Yichuan Xiao,Zhengwei Xie,Daichao Xu,Jing Ye,Rui Yue,Cuntai Zhang,Hongbo Zhang,Liang Zhang,Weiqi Zhang,Yong Zhang,Yun-wu Zhang,Zhuohua Zhang,Tongbiao Zhao,Yuzheng Zhao,Dahai Zhu,Weiguo Zou,Gang Pei,Guang-Hui Liu +120 more
TL;DR: Aging biomarkers are a combination of biological parameters to assess agerelated changes, track the physiological aging process, and predict the transition into a pathological status as discussed by the authors , which can help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower?
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Abstract: Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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References
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Chaolin Huang,Yeming Wang,Xingwang Li,Lili Ren,Jianping Zhao,Yi Hu,Li Zhang,Guohui Fan,Jiuyang Xu,Xiaoying Gu,Zhenshun Cheng,Ting Yu,Jia'an Xia,Yuan Wei,Wenjuan Wu,Xuelei Xie,Wen Yin,Li Hui,Min Liu,Yan Xiao,Hong Gao,Li Guo,Jungang Xie,Guang-Fa Wang,Rongmeng Jiang,Zhancheng Gao,Qi Jin,Jianwei Wang,Bin Cao +28 more
TL;DR: The epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of patients with laboratory-confirmed 2019-nCoV infection in Wuhan, China, were reported.
49.2K
Highly accurate protein structure prediction with AlphaFold
John M. Jumper,Richard O. Evans,Alexander Pritzel,Tim Green,Michael Figurnov,Olaf Ronneberger,Kathryn Tunyasuvunakool,Russell Bates,Augustin Žídek,Anna Potapenko,Alex Bridgland,Clemens Meyer,Simon A. A. Kohl,Andrew J. Ballard,Andrew Cowie,Bernardino Romera-Paredes,Stanislav Nikolov,R. D. Jain,Jonas Adler,Trevor Back,Stig Petersen,David Reiman,Ellen Clancy,Michal Zielinski,Martin Steinegger,Michalina Pacholska,Tamas Berghammer,Sebastian Bodenstein,David L. Silver,Oriol Vinyals,Andrew W. Senior,Koray Kavukcuoglu,Pushmeet Kohli,Demis Hassabis +33 more
TL;DR: For example, AlphaFold as mentioned in this paper predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture. But the accuracy is limited by the fact that no homologous structure is available.
Frailty in Older Adults Evidence for a Phenotype
Linda P. Fried,Catherine M. Tangen,Jeremy D. Walston,Anne B. Newman,Calvin H. Hirsch,John S. Gottdiener,Teresa E. Seeman,Russell P. Tracy,Willem J. Kop,B Gregory Burke,Mary Ann McBurnie +10 more
TL;DR: This study provides a potential standardized definition for frailty in community-dwelling older adults and offers concurrent and predictive validity for the definition, and finds that there is an intermediate stage identifying those at high risk of frailty.
22K
The Hallmarks of Aging
TL;DR: Nine tentative hallmarks that represent common denominators of aging in different organisms are enumerated, with special emphasis on mammalian aging, to identify pharmaceutical targets to improve human health during aging, with minimal side effects.
13K
Sarcopenia: Revised European consensus on definition and diagnosis
Alfonso J. Cruz-Jentoft,Gulistan Bahat,Jürgen M. Bauer,Yves Boirie,Olivier Bruyère,Tommy Cederholm,Cyrus Cooper,Francesco Landi,Yves Rolland,Avan Aihie Sayer,Stéphane M. Schneider,Cornel C. Sieber,Eva Topinkova,Maurits Vandewoude,Marjolein Visser,Mauro Zamboni +15 more
TL;DR: An emphasis is placed on low muscle strength as a key characteristic of sarcopenia, uses detection of low muscle quantity and quality to confirm the sarc Openia diagnosis, and provides clear cut-off points for measurements of variables that identify and characterise sarc openia.
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