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| 1 | Big Grain3, encoding a purine permease, regulates grain size via modulating cytokinin transport in rice显示文摘Grain size is an important agronomic trait affecting grain yield,but the underlying molecular mechanisms remain to be elucidated.Here,we isolated a dominant mutant,big grainy(bg3-D),which exhibits a remarkable increase of grain size caused by activation of the PURINE PERMEASE gene,OsPUP4.BC3/OSPUP4 is predominantly expressed in vascular tissues and is specifically suppressed by exogenous cytokinin application.Hormone profiling revealed that the distribution of different cytokinin forms,in roots and shoots of the bg3-D mutant,is altered.Quantitative reverse transcription-PCR(qRT-PCR)analysis indicated that expression of rice cytokinin type-A RESPONSE REGULATOR(OsRR)genes is enhanced in the roots of the bgj-D mutant.These results suggest that OSPUP4 might contribute to the long-distance transport of cytokinin,by reinforcing cytokinin loading into vascular bundle cells.Furthermore,plants overexpressing OsPUP7,the closest homolog of OsPUP4,also exhibited a similar phenotype to the bg3-D mutant.Interestingly,subcellular localization demonstrated that OSPUP4 was localized on the plasma membrane,whereas OSPUP7 was localized to the endoplasmic reticulum.Based on these findings,we propose that OSPUP4 and OSPUP7 function in a linear pathway to direct cytokinin cell-to-cell transport,affecting both its long-distance movement and local allocation. | Yunhua Xiao Dapu Liu Guoxia Zhang Shaopei Gao Linchuan Liu Fan Xu Ronghui Che Yiqin Wang Hongning Tong Chengcai Chu | 2019 | Journal of Integrative Plant Biology2019，61，5： | 7 |
| 2 | On the molecular mechanism of ion specific Hofmeister series显示文摘Hofmeister series ranks the ability of salt ions in influencing a variety of properties and processes in aqueous solutions.In this review,we reexamine how these ions and some other small molecules affect water structure and thermodynamic properties,such as surface tension and protein backbone solvation.We illustrate the difficulties in interpreting the thermodynamic information based on structural and dynamic arguments.As an alternative,we show that the solvation properties of ions and proteins/small molecules can be used to explain the salt effects on the thermodynamic properties of the solutions.Our analysis shows that the often neglected cation-anion cooperativity plays a very important role in these effects.We also argue that the change of hydrogen donor/acceptor equilibrium by added cosolutes/cosolvents can be used to explain their effects on protein secondary structure denaturation/protection:those increase hydrogen donor concentrations such as urea and salts with strongly solvated cations/weakly hydrated anions tend to dissolve protein backbone acting as secondary structure denaturants,whereas those lack of hydrogen donors but rich in acceptors have the opposite effect. | XIE WenJun LIU ChengWen YANG LiJiang GAO YiQin | 2014 | Science China Chemistry2014，57，1： | 2 |
| 3 | An interactive web-based solar energy prediction system using machine learning techniques显示文摘Solar energy being one of the most inexpensive renewable energy sources,has shown to be a viable alternative to traditional fossil-fuel and wood-based electricity generation.For the purpose of creating a more trustworthy and successful energy planning strategy,accurate projections of sun irradiation,solar energy generation,and revenues are crucial.Hence,in this work we have proposed webbased optimal prediction system that estimates solar radiation based on location and meteorological data using Machine Learning techniques.Furthermore,an interactive dashboard solar digital map has been developed that enables real-time investigation of solar energy consumption,production,solar radiation,and investment potential for a specific county in California.The model’s performance has been measured using Root Mean Square Error(RMSE),Mean Square Error(MSE),Mean Average Error(MAE),and Mean Absolute Percentage Error(MAPE)scores.Experimental results demonstrate that stacking model outperformed all the models with the lowest RMSE,MSE,and MAE. | Priyanka Chawla Jerry Zeyu Gao Teng Gao Chengchen Luo Huimin Li Yiqin We | 2023 | Journal of Management Analytics2023，10，2： | 0 |
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