Ultrasound-assisted Extraction Coupling to High Performance Liquid Chromatography for Enantiomerically Quantitative Analysis of Two Preservatives in Cosmetics and the Potentially Cytotoxic Study

Microchemical Journal（2021）SCI 2区

Shenyang Pharmaceutical Univ

Cited 5|Views0

Abstract

A simple and efficient high performance liquid chromatography method based on a home-made 3, 5-dichlorophenylcarbamated mono-6-ethylenediamine-beta-cyclodextrin chiral column for simultaneously enantiomeric analysis of two preservatives in cosmetics, including chlorphenesin and climbazole was successfully developed. Ultrasound-assisted extraction in combination with a sample clean-up procedure allowed to provide satisfactory enrichment and purification of the target analytes from the cosmetics. Response surface methodology using a Box-Behnken design was applied to screen experimental variables that affected the extraction efficiency. The proposed method was fully validated in terms of system suitability test, specificity, limits of detection and quantitation, linearity, accuracy, and precision, showing a reliable performance. Good linearity (R-2 >= 0.9974), accuracy (% recovery >= 87.5), and intra-/inter-day precision (% RSD <= 9.3) with limits of quantitation from 0.5 to 1.0 mu g mL(-1) were obtained. This method was further applied to a broad range of cosmetics, in which the target analytes were detected in seven out of twenty-four analyzed samples at concentrations ranging from 0.32 to 1.20 mg g(-1). Additionally, the cytotoxicity of the enantiomers of chlorphenesin to HaCAT cells was measured by in vitro MTT assay. The enantiomers of chlorphenesin inhibited the proliferation of cells in a dose dependent manner with significant enantioselectivity.

Translated text

Key words

Cosmetics,Cytotoxicity,Enantioseparation,High performance liquid chromatography,Preservatives

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper