scispace - formally typeset
Search or ask a question
Institution

Guangxi University

EducationNanning, Guangxi, China
About: Guangxi University is a education organization based out in Nanning, Guangxi, China. It is known for research contribution in the topics: Adsorption & Catalysis. The organization has 25740 authors who have published 20672 publications receiving 225406 citations. The organization is also known as: Guǎngxī Dàxué & GU.


Papers
More filters
Journal ArticleDOI
TL;DR: The prevalence of chronic kidney disease in China was high in north and southwest and southwest regions compared with other regions, and economic development was independently associated with the presence of albuminuria.

1,588 citations

Journal ArticleDOI
10 Apr 2020-Science
TL;DR: The structure of the COVID-19 virus polymerase essential for viral replication provides a basis for the design of new antiviral drugs that target viral RdRp, also named nsp12, and it appears to be a primary target for the antiviral drug remdesivir.
Abstract: A novel coronavirus (COVID-19 virus) outbreak has caused a global pandemic resulting in tens of thousands of infections and thousands of deaths worldwide. The RNA-dependent RNA polymerase (RdRp, also named nsp12) is the central component of coronaviral replication/transcription machinery and appears to be a primary target for the antiviral drug, remdesivir. We report the cryo-EM structure of COVID-19 virus full-length nsp12 in complex with cofactors nsp7 and nsp8 at 2.9-A resolution. In addition to the conserved architecture of the polymerase core of the viral polymerase family, nsp12 possesses a newly identified β-hairpin domain at its N terminus. A comparative analysis model shows how remdesivir binds to this polymerase. The structure provides a basis for the design of new antiviral therapeutics targeting viral RdRp.

1,180 citations

Journal ArticleDOI
Jens Kattge1, Gerhard Bönisch2, Sandra Díaz3, Sandra Lavorel  +751 moreInstitutions (314)
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

882 citations

Journal ArticleDOI
Fengpeng An1, Guangpeng An, Qi An2, Vito Antonelli3  +226 moreInstitutions (55)
TL;DR: The Jiangmen Underground Neutrino Observatory (JUNO) as mentioned in this paper is a 20kton multi-purpose underground liquid scintillator detector with the determination of neutrino mass hierarchy (MH) as a primary physics goal.
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purpose underground liquid scintillator detector, was proposed with the determination of the neutrino mass hierarchy (MH) as a primary physics goal. The excellent energy resolution and the large fiducial volume anticipated for the JUNO detector offer exciting opportunities for addressing many important topics in neutrino and astro-particle physics. In this document, we present the physics motivations and the anticipated performance of the JUNO detector for various proposed measurements. Following an introduction summarizing the current status and open issues in neutrino physics, we discuss how the detection of antineutrinos generated by a cluster of nuclear power plants allows the determination of the neutrino MH at a 3–4σ significance with six years of running of JUNO. The measurement of antineutrino spectrum with excellent energy resolution will also lead to the precise determination of the neutrino oscillation parameters ${\mathrm{sin}}^{2}{\theta }_{12}$, ${\rm{\Delta }}{m}_{21}^{2}$, and $| {\rm{\Delta }}{m}_{{ee}}^{2}| $ to an accuracy of better than 1%, which will play a crucial role in the future unitarity test of the MNSP matrix. The JUNO detector is capable of observing not only antineutrinos from the power plants, but also neutrinos/antineutrinos from terrestrial and extra-terrestrial sources, including supernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos, atmospheric neutrinos, and solar neutrinos. As a result of JUNO's large size, excellent energy resolution, and vertex reconstruction capability, interesting new data on these topics can be collected. For example, a neutrino burst from a typical core-collapse supernova at a distance of 10 kpc would lead to ∼5000 inverse-beta-decay events and ∼2000 all-flavor neutrino–proton ES events in JUNO, which are of crucial importance for understanding the mechanism of supernova explosion and for exploring novel phenomena such as collective neutrino oscillations. Detection of neutrinos from all past core-collapse supernova explosions in the visible universe with JUNO would further provide valuable information on the cosmic star-formation rate and the average core-collapse neutrino energy spectrum. Antineutrinos originating from the radioactive decay of uranium and thorium in the Earth can be detected in JUNO with a rate of ∼400 events per year, significantly improving the statistics of existing geoneutrino event samples. Atmospheric neutrino events collected in JUNO can provide independent inputs for determining the MH and the octant of the ${\theta }_{23}$ mixing angle. Detection of the (7)Be and (8)B solar neutrino events at JUNO would shed new light on the solar metallicity problem and examine the transition region between the vacuum and matter dominated neutrino oscillations. Regarding light sterile neutrino topics, sterile neutrinos with ${10}^{-5}\,{{\rm{eV}}}^{2}\lt {\rm{\Delta }}{m}_{41}^{2}\lt {10}^{-2}\,{{\rm{eV}}}^{2}$ and a sufficiently large mixing angle ${\theta }_{14}$ could be identified through a precise measurement of the reactor antineutrino energy spectrum. Meanwhile, JUNO can also provide us excellent opportunities to test the eV-scale sterile neutrino hypothesis, using either the radioactive neutrino sources or a cyclotron-produced neutrino beam. The JUNO detector is also sensitive to several other beyondthe-standard-model physics. Examples include the search for proton decay via the $p\to {K}^{+}+\bar{ u }$ decay channel, search for neutrinos resulting from dark-matter annihilation in the Sun, search for violation of Lorentz invariance via the sidereal modulation of the reactor neutrino event rate, and search for the effects of non-standard interactions. The proposed construction of the JUNO detector will provide a unique facility to address many outstanding crucial questions in particle and astrophysics in a timely and cost-effective fashion. It holds the great potential for further advancing our quest to understanding the fundamental properties of neutrinos, one of the building blocks of our Universe.

807 citations

Journal ArticleDOI
TL;DR: Comprehensive sequence analysis and comparison in conjunction with relative synonymous codon usage (RSCU) bias among different animal species based on the 2019-nCoV sequence suggest that homologous recombination may occur and contribute to the 2019‐n coV cross‐species transmission.
Abstract: The current outbreak of viral pneumonia in the city of Wuhan, China, was caused by a novel coronavirus designated 2019-nCoV by the World Health Organization, as determined by sequencing the viral RNA genome. Many initial patients were exposed to wildlife animals at the Huanan seafood wholesale market, where poultry, snake, bats, and other farm animals were also sold. To investigate possible virus reservoir, we have carried out comprehensive sequence analysis and comparison in conjunction with relative synonymous codon usage (RSCU) bias among different animal species based on the 2019-nCoV sequence. Results obtained from our analyses suggest that the 2019-nCoV may appear to be a recombinant virus between the bat coronavirus and an origin-unknown coronavirus. The recombination may occurred within the viral spike glycoprotein, which recognizes a cell surface receptor. Additionally, our findings suggest that 2019-nCoV has most similar genetic information with bat coronovirus and most similar codon usage bias with snake. Taken together, our results suggest that homologous recombination may occur and contribute to the 2019-nCoV cross-species transmission.

786 citations


Authors

Showing all 25954 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Jing Wang1844046202769
Kuo-Chen Chou14348757711
Jian Yang1421818111166
Jie Liu131153168891
Yang Liu1292506122380
Chao Zhang127311984711
Huijun Gao12168544399
Bing Zhang121119456980
Xifeng Ruan12080864951
Xiaoming Li113193272445
Jianjun Liu112104071032
Qian Wang108214865557
Yan Zhang107241057758
Qi Li102156346762
Network Information
Related Institutions (5)
Shandong University
99.1K papers, 1.6M citations

91% related

Zhejiang University
183.2K papers, 3.4M citations

91% related

Chinese Academy of Sciences
634.8K papers, 14.8M citations

90% related

Nanjing University
105.5K papers, 2.2M citations

90% related

Sichuan University
102.8K papers, 1.6M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023120
2022526
20213,631
20202,731
20192,087
20181,457