Institution
Hong Kong Baptist University
Education•Hong Kong, China•
About: Hong Kong Baptist University is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: China & Population. The organization has 7811 authors who have published 18919 publications receiving 555274 citations. The organization is also known as: Hong Kong Baptist College & HKBU.
Topics: China, Population, Catalysis, Context (language use), Computer science
Papers published on a yearly basis
Papers
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TL;DR: The results point toward an essential role of cytosine methylation in systemic mRNA mobility in plants and that TCTP1 mRNA mobility is required for its signaling function.
127 citations
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TL;DR: Range analysis revealed that the bromide and disinfectant levels were the major factors affecting THMs, HAAs and HNMs formation, in both chlorination and chloramination.
127 citations
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TL;DR: Skeletal muscle atrophy induced by either aging (sarcopenia) or mechanical unloading is associated with serious health consequences and long non‐coding RNAs (lncRNAs) are implicated as important regulators in numerous physiological and pathological processes.
Abstract: Background Skeletal muscle atrophy induced by either aging (sarcopenia) or mechanical unloading is associated with serious health consequences. Long non-coding RNAs (lncRNAs) are implicated as important regulators in numerous physiological and pathological processes. Methods Microarray analysis was performed to identify the differentially expressed lncRNAs in skeletal muscle between adult and aged mice. The most decreased lncRNA in aged skeletal muscle was identified. The C2C12 mouse myoblast cells were used to assess the biological function of the lncRNA in vitro. The target microRNA of lncRNA and the target protein of microRNA were predicted by bioinformatics analysis and validated in vitro. Furthermore, the biology function of the lncRNA in vivo was investigated by local overexpression or knockdown the lncRNA in skeletal muscle. The therapeutic effect of the lncRNA overexpression in age-related or mechanical unloading-induced muscle atrophy was also evaluated. Results We identified a novel lncRNA (muscle anabolic regulator 1, MAR1) which was highly expressed in mice skeletal muscle and positively correlated with muscle differentiation and growth in vitro and in vivo. We predicted and validated that microRNA-487b (miR-487b) was a direct target of MAR1. We also predicted and validated that Wnt5a, an important regulator during myogenesis, was a target of miR-487b in C2C12 cells. Our findings further demonstrated that enforced MAR1 expression in myoblasts led to derepression of Wnt5a. Moreover, MAR1 promoted skeletal muscle mass/strength and Wnt5a protein level in mice. Enforced MAR1 expression in mice attenuated muscle atrophy induced by either aging or unloading. Conclusions The newly identified lncRNA MAR1 acts as a miR-487b sponge to regulate Wnt5a protein, resulting in promoting muscle differentiation and regeneration. MAR1 could be a novel therapeutic target for treating muscle atrophy induced by either aging or mechanical unloading.
127 citations
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TL;DR: In this article, the authors consider several geometric approaches for combining forecasts in large samples, such as simple eigenvector approach, mean corrected eigen vector approach, and trimmed eigenvectors approach.
127 citations
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TL;DR: In this article, the accuracy of estimated precipitation in central Asia from three recently developed reanalysis data sets, Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF Interim Re-Analysis (ERA-Interim), and Climate Forecast System Reanalysis (CFSR), is evaluated through comparisons with observations from 399 stations during 1979-2010.
Abstract: The accuracy of any gridded climatic data sets is as important as their availability for regional climate and ecological studies. In this study, the accuracy of estimated precipitation in central Asia from three recently developed reanalysis data sets, Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF Interim Re-Analysis (ERA-Interim), and Climate Forecast System Reanalysis (CFSR), is evaluated through comparisons with observations from 399 stations during 1979–2010. An interpolated precipitation data set from station observations and a satellite remotely sensed data set, Tropical Rainfall Measuring Mission (TRMM) 3B42, are included in the evaluation. Major results show that MERRA data have higher accuracy than ERA-Interim and CFSR, although they all overestimate the observed precipitation especially in late spring and early summer months, suggesting errors in their ways of representing convective precipitation in that region. In comparison, the interpolated and satellite-sensed data, which provide no upper air information/data, have higher accuracy. While all these data sets have difficulty in describing stations' precipitation in mountainous areas, the reanalysis data sets have particularly large discrepancies. In examining the discrepancy in the reanalysis data, a Precipitation-Topography Partial Least Squares method is proposed to incorporate certain terrain/geographic effects on precipitation in mapping the gridded data to the station locations for comparison with the observation. The outcome suggests that the estimated station precipitation by this new method is closer to the observed than the method without considering those factors. The improvement by this method and by possible other methods taking into account different details/aspects of the influences indicates that it is only meaningful to compare the accuracy or relevance of gridded data sets to station observations in a relative sense among various data sets.
127 citations
Authors
Showing all 7946 results
Name | H-index | Papers | Citations |
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Weihong Tan | 140 | 892 | 67151 |
Bin Liu | 138 | 2181 | 87085 |
Jun Lu | 135 | 1526 | 99767 |
John P. Giesy | 114 | 1162 | 62790 |
Qiang Yang | 112 | 1117 | 71540 |
Ming Hung Wong | 103 | 710 | 39738 |
Wei Wang | 95 | 3544 | 59660 |
Jianhua Zhang | 92 | 415 | 28085 |
Xiaojun Wu | 91 | 1088 | 31687 |
Guibin Jiang | 88 | 850 | 34633 |
Shu Tao | 87 | 639 | 27304 |
Paul K.S. Lam | 87 | 485 | 25614 |
Cheng-Yong Su | 87 | 581 | 32322 |
Hai-Long Jiang | 86 | 198 | 30946 |
Baowen Li | 83 | 477 | 23080 |