Genomic insights into heading date variation of the different maturity types of japonica rice varieties in Jiangsu Province, China.
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Letter↗
Biomedical subjects
Qianfeng Li
Publications and source records attributed to Qianfeng Li.
Study of the reaction of proteins with 3-hydroxy-4-(2-hydroxy-4-sulfo-1-naphthalenyl)azo (Cal-Red) by Rayleigh light scattering technique.
This is the first report on the determination of proteins with 3-hydroxy-4-(2-hydroxy-4-sulfo-1-naphthalenyl)azo (Cal-Red) by Rayleigh light scattering (RLS). At pH 4.07, the weak RLS of Cal-Red can be enhanced greatly by the addition of proteins. On this basis, the reaction of Cal-Red and proteins was studied. A new quantitative determination method for proteins has been developed. This method is very sensitive (0.45-36.9 microgml(-1) for bovine serum albumen (BSA)), rapid (<2min), simple (one step), and tolerant of most interfering substances. The maximum binding number of Cal-Red to BSA was 143 and the binding constant was 4.1x10(6)mol(-1)L. Four samples of total protein in human serum were determined and the maximum relative error is no more than 3%.
Amino Acids↗
Field-amplified sample stacking in capillary electrophoresis for on-column concentration of alkaloids in Sophora flavescens Ait.
A simple and rapid capillary zone electrophoresis method was developed for the separation of the main alkaloids from Sophora flavescens Ait. with the optimum buffer solution containing 110 mM NaH(2)PO(4) and 15% 2-propanol (pH 3.0). The field-amplified sample stacking (FASS) technique was applied to the on-line concentration of the alkaloids. The data presented in this work demonstrate that the use of a short water plug at the column inlet is essential for improving the reproducibility of FASS with electro-injection, and that the water plug injection time affected the sensitivity significantly. The sample concentration was further increased by about 2-3-fold by the introduction of a relatively longer water plug. With this stacking measure, the concentration sensitivity was about 3-4 orders of magnitude higher than in hydrodynamic injection.
Alkaloids↗
Development of a quantitative structure-property relationship model for predicting the electrophoretic mobilities.
Electrophoretic mobility (mu0) is the most important parameter governing the separation of solutes in capillary zone electrophoresis. In this paper, a new model was constructed by means of a multilayer neural network using extended delta-bar-delta (EDBD) algorithm to estimate complex property of electrophoretic mobilities of aliphatic carboxylates and amines from simpler experimental properties. The molecular weight (W), molecular volume (V), the code (+1 or -1) of acid and base and pK value were used as input parameters to predict electrophoretic mobility. The networks' architecture and the learning times were optimized. The optimum artificial neural networks (ANNs) could give excellent prediction results.
Journal Article↗