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| 1 | Sodium oligomannate therapeutically remodels gut microbiota and suppresses gut bacterial amino acids-shaped neuroinflammation to inhibit Alzheimer's disease progression显示文摘Recently,increasing evidence has suggested the association between gut dysbiosis and Alzheimer's disease(AD)progression,yet the role of gut microbiota in AD pathogenesis remains obscure.Herein,we provide a potential mechanistic link between gut microbiota dysbiosis and neuroinflammation in AD progression.Using AD mouse models,we discovered that,during AD progression,the alteration of gut microbiota composition leads to the peripheral accumulation of phenylalanine and isoleucine,which stimulates the differentiation and proliferation of pro-inflammatory T helper 1(Thl)cells.The brain-infiltrated peripheral Th1 immune cells are associated with the Ml microglia aaivation,contributing to AD-associated neuroinflammation.Importantly,the elevation of phenylalanine and isoleucine concentrations and the increase of Th1 cell frequency in the blood were also observed in two small independent cohorts of patients with mild cognitive impairment(MCI)due to AD.Furthermore,GV-971,a sodium oligomannate that has demonstrated solid and consistent cognition improvement in a phase 3 clinical trial in China,suppresses gut dysbiosis and the associated phenylalanine/isoleucine accumulation,harnesses neuroinflammation and reverses the cognition impairment.Together,our findings highlight the role of gut dysbiosis-promoted neuroinflammation in AD progression and suggest a novel strategy for AD therapy by remodelling the gut microbiota. | Xinyi Wang Guangqiang Sun Teng Feng Jing Zhang Xun Huang Tao Wang Zuoquan Xie Xingkun Chu Jun Yang Huan Wang Shuaishuai Chang Yanxue Gong Lingfei Ruan Guanqun Zhang Siyuan Yan Wen Lian Chen Du Dabing Yang Qingli Zhang Feifei Lin Jia Liu Haiyan Zhang Changrong Ge Shifu Xiao Jian Ding Meiyu Geng | 2019 | Cell Research2019，29，10： | 192 |
| 2 | Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality显示文摘Enhancing the terrestrial ecosystem carbon sink(referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide(CO_(2)) concentration and to achieve carbon neutrality target.To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality,this review summarizes major progress in terrestrial C budget researches during the past decades,clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world,and examines the role of terrestrial C sinks in achieving carbon neutrality target.According to recent studies,the global terrestrial C sink has been increasing from a source of (-0.2±0.9) Pg C yr^(-1)(1 Pg=1015g)in the 1960s to a sink of (1.9±1.1) Pg C yr^(-1) in the 2010s.By synthesizing the published data,we estimate terrestrial C sink of 0.20–0.25 Pg C yr^(-1) in China during the past decades,and predict it to be 0.15–0.52 Pg C yr^(-1) by 2060.The terrestrial C sinks are mainly located in the mid-and high latitudes of the Northern Hemisphere,while tropical regions act as a weak C sink or source.The C balance differs much among ecosystem types:forest is the major C sink;shrubland,wetland and farmland soil act as C sinks;and whether the grassland functions as C sink or source remains unclear.Desert might be a C sink,but the magnitude and the associated mechanisms are still controversial.Elevated atmospheric CO_(2) concentration,nitrogen deposition,climate change,and land cover change are the main drivers of terrestrial C sinks,while other factors such as fires and aerosols would also affect ecosystem C balance.The driving factors of terrestrial C sink differ among regions.Elevated CO_(2) concentration and climate change are major drivers of the C sinks in North America and Europe,while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China.For future studies,we recommend the necessity for intensive and long-term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios. | Yuanhe Yang Yue Shi Wenjuan Sun Jinfeng Chang Jianxiao Zhu Leiyi Chen Xin Wang Yanpei Guo Hongtu Zhang Lingfei Yu Shuqing Zhao Kang Xu Jiangling Zhu Haihua Shen Yuanyuan Wang Yunfeng Peng Xia Zhao Xiangping Wang Huifeng Hu Shiping Chen Mei Huang Xuefa Wen Shaopeng Wang Biao Zhu Shuli Niu Zhiyao Tang Lingli Liu Jingyun Fang | 2022 | Science China(Life Sciences)2022，65，5： | 32 |
| 3 | Treatment of Phenol Wastewater Using High Gravity Electrochemical Reactor with Multi-concentric Cylindrical Electrodes显示文摘A novel high gravity electrochemical reactor with multi-concentric cylindrical electrodes was used in the electrochemical treatment of 5 000 mg/L phenol-containing wastewater at a petrochemical plant, which can operate continuously and process in a large scale. The results show that the high gravity technology used in electrochemical treatment of phenol-containing wastewater can shorten the electrolysis time, decrease the electrolysis voltage, and reduce the energy consumption. The COD removal efficiency was high in the high-gravity field, and reached up to about 48%, which was about 2 times the value achieved in the normal gravity field at a processing capacity of 6 L, a high gravity factor of 80, a voltage of 12 V, an electrolysis time of 40 min, and a wastewater flowrate of 80 L/h. | Gao Jing Liu Youzhi Chang Lingfei | 2012 | China Petroleum Processing & Petrochemical Technology2012，14，2： | 10 |
| 4 | Mutation of kri1l causes definitive hematopoiesis failure via PERK-dependent excessive autophagy induction显示文摘 | Xiao-E Jia Ke Ma Tao Xu Lei Gao Shuang Wu Cong Fu Wenjuan Zhang Zhizhang Wang Kaiyu Liu Mei Dong Changbin Jing Chunguang Ren Zhiwei Dong Yi Chen Yi Jin Qiuhua Huang Xing Chang Min Deng Li Li Lingfei Luo Jun Zhu Yongjun Dang Hung-Chun Chang Leonard I Zon Yi Zhou Saijuan Chen Weijun Pan | 2015 | Cell Research2015，25，8： | 8 |
| 5 | The interplay of aging,genetics and environmental factors in the pathogenesis of Parkinson’s disease显示文摘Background:Parkinson’s disease(PD)is characterized by dopaminergic neuronal loss in the substantia nigra pars compacta and intracellular inclusions called Lewy bodies(LB).During the course of disease,misfoldedα-synuclein,the major constituent of LB,spreads to different regions of the brain in a prion-like fashion,giving rise to successive non-motor and motor symptoms.Etiology is likely multifactorial,and involves interplay among aging,genetic susceptibility and environmental factors.Main body:The prevalence of PD rises exponentially with age,and aging is associated with impairment of cellular pathways which increases susceptibility of dopaminergic neurons to cell death.However,the majority of those over the age of 80 do not have PD,thus other factors in addition to aging are needed to cause disease.Discovery of neurotoxins which can result in parkinsonism led to efforts in identifying environmental factors which may influence PD risk.Nevertheless,the causality of most environmental factors is not conclusively established,and alternative explanations such as reverse causality and recall bias cannot be excluded.The lack of geographic clusters and conjugal cases also go against environmental toxins as a major cause of PD.Rare mutations as well as common variants in genes such as SNCA,LRRK2 and GBA are associated with risk of PD,but Mendelian causes collectively only account for 5%of PD and common polymorphisms are associated with small increase in PD risk.Heritability of PD has been estimated to be around 30%.Thus,aging,genetics and environmental factors each alone is rarely sufficient to cause PD for most patients.Conclusion:PD is a multifactorial disorder involving interplay of aging,genetics and environmental factors.This has implications on the development of appropriate animal models of PD which take all these factors into account.Common converging pathways likely include mitochondrial dysfunction,impaired autophagy,oxidative stress and neuroinflammation,which are associated with the accumulation and spread of misfoldedα-synuclein and neurodegeneration.Understanding the mechanisms involved in the initiation and progression of PD may lead to potential therapeutic targets to prevent PD or modify its course. | Shirley Yin-Yu Pang Philip Wing-Lok Ho Hui-Fang Liu Chi-Ting Leung Lingfei Li Eunice Eun Seo Chang David Boyer Ramsden Shu-Leong Ho | 2019 | Translational Neurodegeneration2019，8，1： | 5 |
| 6 | Exploring best‑matched embedding model and classifier for charging‑pile fault diagnosis显示文摘The continuous increase of electric vehicles is being facilitating the large-scale distributed charging-pile deployment.It is crucial to guarantee normal operation of charging piles,resulting in the importance of diagnosing charging-pile faults.The existing fault-diagnosis approaches were based on physical fault data like mechanical log data and sensor data streams.However,there are other types of fault data,which cannot be used for diagnosis by these existing approaches.This paper aims to fill this gap and consider 8 types of fault data for diagnosing,at least including physical installation error fault,charging-pile mechanical fault,charging-pile program fault,user personal fault,signal fault(offline),pile compatibility fault,charging platform fault,and other faults.We aim to find out how to combine existing feature-extraction and machine learning techniques to make the better diagnosis by conducting experiments on realistic dataset.4 word embedding models are investigated for feature extraction of fault data,including N-gram,GloVe,Word2vec,and BERT.Moreover,we classify the word embedding results using 10 machine learning classifiers,including Random Forest(RF),Support Vector Machine,K-Nearest Neighbor,Multilayer Perceptron,Recurrent Neural Network,AdaBoost,Gradient Boosted Decision Tree,Decision Tree,Extra Tree,and VOTE.Compared with original fault record dataset,we utilize paraphrasing-based data augmentation method to improve the classification accuracy up to 10.40%.Our extensive experiment results reveal that RF classifier combining the GloVe embedding model achieves the best accuracy with acceptable training time.In addition,we discuss the interpretability of RF and GloVe. | Wen Wang Jianhua Wang Xiaofeng Peng Ye Yang Chun Xiao Shuai Yang Mingcai Wang Lingfei Wang Lin Li Xiaolin Chang | 2023 | Cybersecurity2023，6，3： | 0 |
| 7 | BRIEF COMMUNICATION ARISING Geng et al.reply显示文摘The accompanying comment by Dr.Rao,suggests that there is an omission of citation of 12 previous publications in our Wang et al.paper.1 We disagree with the suggestion for the following reasons.We believe that the 12 publications cited by Dr.Rao do not have sufficient relevance to the Wang et al.paper.1 The past decades have witnessed an explosive growth in our understanding of the pathogenesis of Alzheimer's disease(AD),which is a very complicated process.The Wang et al. | Xinyi Wang Guangqiang Sun Teng Feng Jing Zhang Xun Huang Tao Wang Zuoquan Xie Xingkun Chu Jun Yang Huan Wang Shuaishuai Chang Yanxue Gong Lingfei Ruan Guanqun Zhang Siyuan Yan Wen Lian Chen Du Dabing Yang Qingli Zhang Feifei Lin Jia Liu Haiyan Zhang Changrong Ge Shifu Xiao Jian Ding Meiyu Geng | 2020 | Cell Research2020，30，9： | 0 |
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