Optimization of Ultrasonic-Assisted Extraction of Total Phenolics from Citrus aurantium L. Blossoms and Evaluation of Free Radical Scavenging, Anti-HMG-CoA Reductase Activities.

The objective of this study was to develop an ultrasonic-assisted procedure for the extraction of total phenolics from Citrus aurantium L. blossoms (CAB) and evaluate the free radical scavenging activity and anti-HMG-CoA reductase activity of the total phenolics. In this work, a Box- Behnken design based on single-factor experiments was used to explore the optimum extraction process. Under the optimum conditions (extraction solvent 70.31% ethanol, extraction temperature 61.94 °C, extraction time 51.73 min, and liquid-to-solid ratio 35.63 mL/g), the extraction yield of total phenolics was 95.84 mg gallic acid equivalents (GAE)/g dry matter (DM), which was highly consistent with the theoretical value (96.12 mg GAE/g DM). The higher contents of total phenolics and five main phenolic compounds obtained from the optimized ultrasonic-assisted extraction (UAE) proved its efficiency when compared with conventional heat reflux extraction (HRE). The total phenolic extract showed excellent free radical scavenging properties against 1,1-diphenyl-2-picrylhydrazyl radical (DPPH·), 2,2'-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) radical (ABTS+·), hydroxyl radical (·OH) and superoxide anion radical (·O2-), with IC50 values of 197.007, 83.878, 218.643, and 158.885 µg/mL, respectively; the extracts also showed good inhibition of ß-hydroxy-ß-methylglutaryl-CoA reductase (HMG-CoA reductase) activity, with an IC50 value of 117.165 µg/mL. Total phenolics from CAB could be a potential source of natural free radical scavenger and HMG-CoA reductase inhibitor.

Ultrasound-Assisted Extraction of Total Flavonoids from Pteris cretica L.: Process Optimization, HPLC Analysis, and Evaluation of Antioxidant Activity.

In the present work, the ultrasonic-assisted extraction (UAE) of total flavonoids (TF) from Pteris cretica L. was optimized by response surface methodology (RSM) on the basis of a single-factor experiment. The optimized UAE parameters were as follows: Ethanol concentration 56.74%, extraction time 45.94 min, extraction temperature 74.27 °C, and liquid/solid ratio 33.69 mL/g. Under the optimized conditions, the total flavonoids yield (TFY) was 4.71 ± 0.04%, which was higher than that obtained by heat reflux extraction (HRE). The extracts were further analyzed by HPLC, and five major flavonoids, including rutin, quercitrin, luteolin, apigenin, and luteolin-7-O-glucoside, were identified and quantified. Furthermore, the results of the antioxidant test showed that the TF extract obtained under optimized UAE conditions exhibited good 2,2-diphenyl-1-picrylhydrazyl radical (DPPH•) and 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical (ABTS+•), nitric oxide radical (NO•) scavenging activities, and ferrous ion (Fe2+) chelating capacity, with IC50 values of 74.49, 82.92, 89.12, and 713.41 µg/mL, respectively. Results indicated that the UAE technique developed in this work was an efficient, rapid, and simple approach for the extraction of flavonoids with antioxidant activity from P. cretica.

Comparative study of the linear solvation energy relationship, linear solvent strength theory, and typical-conditions model for retention prediction in reversed-phase liquid chromatography.

This paper describes two new retention models for predicting retention under different reversed-phase liquid chromatography (RPLC) conditions. The first one is a global linear solvation energy relationship (LSER) that expresses retention as a function of both solute LSER descriptors and mobile phase composition. The second is a so-called "typical-conditions model" that expresses retention under a given chromatographic condition as a linear function of retention under different so-called "typical" conditions. The global LSER was derived by combining the local LSER model and the linear solvent strength theory (LSST) of RPLC. Compared to local LSER and the LSST models, the global LSER model requires far fewer retention measurements for calibrating the model when different solutes and different mobile phase compositions are involved. Its fitting performance is equal to the local LSER model but worse than that of LSST. The poor fit of the global LSER results primarily from the local LSER model and not from the LSST model. The typical-conditions model (TCM) was developed based on a concept of multivariate space that is conceptually compatible with LSER. However, no LSER descriptors are used in the TCM approach. The number of input conditions needed in the typical-conditions model is determined by the chemical diversity of the solutes and the conditions involved. Principal component analysis (PCA) and iterative key set factor analysis (IKSFA) were used to find the number of typical conditions needed for a given data set. Compared to LSER, LSST, and global LSER, the typical-conditions model is more precise and requires fewer retention measurements for calibrating the model when different solutes and different stationary and/or mobile phases are involved.