Simultaneous fractionation of multiple classes of polyphenols from honeybush tea using solid-phase extraction

The structural diversity of polyphenols and the inherent limitations of current extraction techniques pose a challenge to extract polyphenols using a simple and green method. Hence, in this study, a method was developed to simultaneously fractionate multiple classes of polyphenols by only varying ethanol-water solutions. Honeybush tea, which is rich in polyphenols, was selected as a model for this study. Solvent extraction followed by solid-phase extraction (SPE) was developed to obtain a polyphenol-rich fraction from six honeybush samples. Based on a gradient elution programme (10%, 30%, 50%, 70% and 90% (v/v) ethanol-water solution) of SPE, the Strata X cartridge showed a better recovery of most targeted polyphenols under 0.9 mL of the drying volume and 1 mL min⁻¹ of the dispensing speed. The elution programme for fractionating most polyphenols was as follows: single elution with 50% ethanol, followed by twice elution with 70% ethanol. The antioxidant capacity was used to analyse the differences among the polyphenol-rich fractions from six honeybush samples. Principal component analysis (PCA) revealed that unfermented C. genistoides (GG) has the greatest antioxidant capacity among the honeybush species studied. Additionally, mangiferin, isomangiferin and vicenin-2 were the main contributors to the antioxidant capacity in six honeybush fractions according to the correlation study.     

HPCL法测定左亚叶酸钠的异构体

目的:常用的亚叶酸类制剂包括亚叶酸钙、亚叶酸钠及其他们的左旋单体左亚叶酸钙、左亚叶酸钠,亚叶酸类制剂在体内真正起活性作用的部分为左亚叶酸.在制备中一般通过2种单体成盐时不同溶解度进行分离,但现有测定含量的检测方法均无法分离左旋或右旋单体,容易造成含量测定误差.结论:因此我们用HPLC法对注射用左亚叶酸钠异构体测定方法进行了研究,该法测定重复性好,结果准确可靠.     

Optimized decomposition and two-step nonlinear integration model with error correction strategy coupled interval prediction for digital currency price forecast

Digital currency price prediction is vital to both sellers and purchasers. Over these years, decomposition and integration models have been applied more and more to realize the goal of precise prediction, however, many of them tend to neglect the reconstruction of features or the residual series. Altogether, one of the biggest drawbacks of the decomposition and integration framework is the method applied requires manual parameter setting whether it is for decomposition or integration. Still, for the results, they are merely satisfied with the point prediction which brings high uncertainty. In this paper, an optimized feature reconstruction decomposition and two-step nonlinear integration method is proposed which gives consideration to feature reconstruction, nonlinear integration, optimization and interval prediction. The original data series is decomposed through improved variational mode decomposition based approximate entropy feature reconstruction system. Then, improved particle swarm optimization-gated recurrent unit (iPSO-GRU) is utilized in the first and second nonlinear integration part separately. Meanwhile, the residual series is given attention, if it is not a white noise series, the residual will be the input of iPSO-GRU whose result will be added back to the second integration result to form the point prediction result. Based on the point prediction result, interval prediction estimate will be generated as well via maximum likelihood function. This study chooses three kinds of digital currency as cases and the results show that the MAPE values of point prediction are all below 3.5%, and CP values of interval prediction are all 1 with suitable MWP. In addition, compared with other benchmark models, the proposed model shows better performance.

     

Ferulic acid and EGCG alter the structural characteristics of ovalbumin and its application in mineral loading

This study aims to fabricate mineral-loading nanocarriers using natural materials. The interaction patterns between ovalbumin (OVA) and four water-soluble polyphenols, namely ferulic acid (FA), (-)-Epigallo-catechin 3-gallate (EGCG), gallic acid (GA) and epicatechin (EC), were investigated. Results showed that the optimised conditions for preparing stable OVA–polyphenol complexes are at the OVA–polyphenol ratio of 4:1 at pH 6, under which OVA–FA and OVA–EGCG showed the highest stability and mineral-loading capacity among four OVA–polyphenol complexes. The fluorescence results indicated that the addition of EGCG and FA induced a significant fluorescence quenching to OVA. The interaction between OVA and polyphenols involved hydrogen bonding, hydrophobic interaction and electrostatic interaction. Fourier transform infrared spectroscopy (FTIR) analysis suggested that both FA and EGCG enhanced the stability and orderliness of the structure of OVA. The transmission electron microscopy images also exhibited the spherical structure of OVA after the addition of FA and EGCG. Furthermore, scanning electron microscope–energy dispersive X-ray spectrum results suggested that OVA–FA and OVA–EGCG complexes were better mineral carriers than OVA–GA and OVA–EC. This study may serve as the theoretical support for the promising application of OVA in the fabrication of mineral-loading nanocarriers in functional food and pharmaceutic.