Quantitative Analysis of Sunflower Lecithin Adulteration with Soy Species by NMR Spectroscopy and PLS Regression

A Comprehensive Study for Determination of Free Fatty Acids in Selected Biological Materials: A Review

The quality of oil is highly dependent on its free fatty acid (FFA) content, especially due to increased restrictions on renewable fuels. As a result, there has been a growing interest in free fatty acid determination methods over the last few decades. While various standard methods are currently available, such as the American Oil Chemists Society (AOCS), International Union of Pure and Applied Chemistry (IUPAC), and Japan Oil Chemists' Society (JOCS), to obtain accurate results, there is a pressing need to investigate a fast, accurate, feasible, and eco-friendly methodology for determining FFA in biological materials. This is owing to inadequate characteristics of the methods, such as solvent consumption and reproducibility, among others. This study aims to investigate FFA determination methods to identify suitable approaches and introduce a fresh perspective.

Biocompatible Chitosan Nanobubbles for Ultrasound-Mediated Targeted Delivery of Doxorubicin

Ultrasound-targeted delivery of nanobubbles (NBs) has become a promising strategy for noninvasive drug delivery. The biosafety and drug-transporting ability of NBs have been a research hotspot, especially regarding chitosan NBs due to their biocompatibility and high biosafety. Since the drug-carrying capacity of chitosan NBs and the performance of ultrasound-assisted drug delivery remain unclear, the aim of this study was to synthesize doxorubicin hydrochloride (DOX)-loaded biocompatible chitosan NBs and assess their drug delivery capacity. In this study, the size distribution of chitosan NBs was measured by dynamic light scattering, while their drug-loading capacity and ultrasound-mediated DOX release were determined by a UV spectrophotometer. In addition, a clinical ultrasound imaging system was used to evaluate the ability of chitosan NBs to achieve imaging enhancement, while the biosafety profile of free chitosan NBs was evaluated by a cytotoxicity assay in MCF-7 cells. Furthermore, NB-mediated DOX uptake and the apoptosis of Michigan Cancer Foundation-7 (MCF-7) cells were measured by flow cytometry. The results showed that the DOX-loaded NBs (DOX-NBs) exhibited excellent drug-loading ability as well as the ability to achieve ultrasound enhancement. Ultrasound (US) irradiation promoted the release of DOX from DOX-NBs in vitro. Furthermore, DOX-NBs effectively delivered DOX into mammalian cancer cells. In conclusion, biocompatible chitosan NBs are suitable for ultrasound-targeted DOX delivery and are thus a promising strategy for noninvasive and targeted drug delivery worthy of further investigation.

Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

Automated multicomponent phospholipid analysis using 31P NMR spectroscopy: example of vegetable lecithin and krill oil

Nuclear magnetic resonance (NMR) spectroscopy is widely applied in the field of metabolomics due to its quantitative nature and the reproducibility of data generated. However, one of the main challenges in routine NMR analysis is to obtain valuable information from large datasets of raw data in a high-throughput, automatic, and reproducible manner. In this study, a method to automatically annotate and quantify 12 phospholipids (PLs) in vegetable lecithin (soy, sunflower, rape) and krill oil is introduced. Automated routines were written in MATLAB environment for quantification of phosphatidylcholine (PC), phosphatidylinositol (PI), lyso-phosphatidylcholine (LPC), phosphatidylserine (PS), phosphatidylethanolamine (PE), diphosphatidylglycerol or cardiolipin (DPG), phosphatidylglycerol (PG), and lyso-phosphatidylethanolamine (LPE) in lecithin and of PC, PC-ether, LPC, PE, N-acyl phosphatidylethanolamine (APE), and LPE in krill oil matrix. The routine includes NMR spectra import, extraction of data points, peaking of local minima and local maxima in the data, integration, quantitation against internal standard, reporting of results as Word file, and their importing in our internal database. Our extensive studies on a representative set of more than 1000 lecithin (soy, rape, sunflower) and krill samples showed that the routine can automatically and accurately calculate the concentrations of all PLs. No systematic or proportional differences between automated and manual evaluation were detected. The developed automated program produces accurate results and requires less than 5 s for each analysis. This tool is already used in high-throughput PL analysis of krill and lecithin and will be adjusted to other matrices (egg, milk, chocolate, etc.) as well.

Transfer of multivariate regression models between high-resolution NMR instruments: application to authenticity control of sunflower lecithin

In recent years the number of spectroscopic studies utilizing multivariate techniques and involving different laboratories has been dramatically increased. In this paper the protocol for calibration transfer of partial least square regression model between high-resolution nuclear magnetic resonance (NMR) spectrometers of different frequencies and equipped with different probes was established. As the test system previously published quantitative model to predict the concentration of blended soy species in sunflower lecithin was used. For multivariate modelling piecewise direct standardization (PDS), direct standardization, and hybrid calibration were employed. PDS showed the best performance for estimating lecithin falsification regarding its vegetable origin resulting in a significant decrease in root mean square error of prediction from 5.0 to 7.3% without standardization to 2.9-3.2% for PDS. Acceptable calibration transfer model was obtained by direct standardization, but this standardization approach introduces unfavourable noise to the spectral data. Hybrid calibration is least recommended for high-resolution NMR data. The sensitivity of instrument transfer methods with respect to the type of spectrometer, the number of samples and the subset selection was also discussed. The study showed the necessity of applying a proper standardization procedure in cases when multivariate model has to be applied to the spectra recorded on a secondary NMR spectrometer even with the same magnetic field strength. Copyright © 2016 John Wiley & Sons, Ltd.