Coupling of GC-MS/MS to Principal Component Analysis for Assessment of Matrix Effect: Efficient Determination of Ultra-Low Levels of Pesticide Residues in Some Functional Foods

Coupling of a streamlined solid-liquid extraction protocol with LC-ESI-MS/MS for the regular oversight of illegal bromate additive use: An accurate and sensitive determination method in preliminary and bakery products

A reliable solid-liquid extraction protocol coupled with liquid chromatography-electrospray ionization-tandem mass spectrometry in the negative-ion mode was developed and validated for illegal bromate determination in preliminary and bakery products. Crude and dried-treated samples were directly extracted with acetonitrile-water (4:1, v/v). Bromate was determined using a Phenomenex Synergi™ Polar reversed-phase column and MS/MS under multiple reaction monitoring. The chosen solvent efficiently extracted bromate with all applied extraction-assisting techniques (p > 0.05). Although this assay avoids cleanup procedures, matrix effect of <-11% was achieved. Rapid bromate separation in only 8 min was attained by a reversed-phase column. In both commodities, linearity range, R2, recovery%, repeatability, intermediate precision, LOD and LOQ results were 0.05-100 ng mL-1, >0.9999, 88.6-103%, 2.93-9.80% and 9.64-10.10%, 0.015 μg kg-1 and 0.05 μg kg-1, respectively. Out of 288 tested real samples, 13.9% of violations were observed. This high-sensitivity protocol offers effective oversight and consumer protection.

Fast DLLME-GC-MS Method for Determination of Pesticides in Carmelite Drops and Evaluation of Matrix Effects in Related Medicinal Products

The production of nutraceuticals is a growing trend, as many consumers consider them an important part of the modern active lifestyle. Others rely on the use of nutraceuticals instead of prescribing pharmaceuticals to improve their health more naturally. One of the major concerns in the nutraceutical industry is the potential presence of contaminants. Even low concentrations of contaminant residues can be harmful, so analytical methods that are sensitive at ultratrace levels are needed. Dispersive liquid-liquid microextraction method combined with fast gas chromatography and mass spectrometry was developed for the inspection of pesticide residues in Carmelite drops. The most suitable recoveries are presented when the alcohol content is fixed at 20% in Carmelite drops. The method was validated; the linearity, limits of detection/quantification, the method accuracy and precision were obtained. The complex nutraceutical matrix causes significant complications in quantitative analysis; therefore, the main target of the work was placed on studying the effects of the matrix on the correct expression of the resulting concentration of contaminants in different types of samples. An in-depth study of matrix factors was carried out, and its relationship with the content of potential interferents from the medicinal products as well as other components added during the drops' production was discussed. Related medicinal plant-derived nutraceuticals were tested, the method was applied for real-life samples, and positive findings are herein reported.

An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples

Principal component analysis (PCA) is currently one of the most used multivariate data analysis techniques for evaluating information from food analysis. In this review, a brief introduction to the theoretical principles that underlie PCA will be given, in addition to presenting the most commonly used computer programs. An example from the literature was discussed to illustrate the use of this chemometric tool and interpretation of graphs and parameters obtained. A list of recently published articles will also be presented, in order to show the applicability and potential of the technique in the food analysis field.

LC-MS/MS Investigation of nitrosamine impurities in certain Sartan group medicinal products available in Istanbul, Türkiye

Nitrosamines (NAs) are molecules that include the nitroso functional group. In 2018, the US Food and Drug Administration (FDA) received its first report of NAs in pharmaceuticals. The fact that NA impurities are likely human carcinogens is relevant to these compounds. Furthermore, prolonged exposure to NA contaminants above safe limits may raise the risk of cancer. The goal of this article was to assess the amounts of six different NAs in Sartan group medicines purchased from formal pharmacies in Istanbul, Türkiye, using a validated LC-MS/MS assay. An LC-MS/MS-based analytical assay was undertaken. The separation was performed with a HR ODS 150mm×3.0mm and 5-analytical columns, providing effective separation of major peaks from NA impurities. In mobile phase A, formic acid was 0.10% in water, while in mobile phase B, formic acid was 0.10% in methanol. The flow rate was 0.4mL/minute, and the total runtime was 18minutes with the gradient elution mode. The validation was conducted in line with ISO/IEC 17025 requirements. Up to 100μg/L, linearity was determined using correlation coefficients (r2>0.995) for all NAs. The limit of quantification values for all NAs analyses were below 1.0μg/L. The mean recovery value obtained during the spike experiment was 95.18%, demonstrating the accuracy of the procedure. In addition, the accuracy was shown by a certified reference analysis, which yielded relative standard deviation and relative error values of 1.82% and 3.34%, respectively. During the intermediate precision testing, bias and relative standard deviation were 0.96 and 2.87%, respectively. Of the 75 study samples involving Sartan group medical products, no nitrosamine impurities were detected, demonstrating that pharmaceutical companies have adequate medication safety precautions in place in accordance with FDA and European Medicines Agency (EMA) regulations published to prevent NA contaminants in human medicinal products.

Matrix Effect Evaluation in GC/MS-MS Analysis of Multiple Pesticide Residues in Selected Food Matrices

Multi-analyte methods based on QuEChERS sample preparation and chromatography/mass spectrometry determination are indispensable in monitoring pesticide residues in the feed and food chain. QuEChERS method, even though perceived as convenient and generic, can contribute to sample matrix constituents' introduction to the measuring system and possibly affect analytical results. In this study, matrix effects (ME) were investigated in four food matrices of plant origin (apples, grapes, spelt kernels, and sunflower seeds) during GC-MS/MS analysis of >200 pesticide residues using QuEChERS sample preparation. Data analysis revealed considerable analyte signal enhancement and suppression: strong enhancement was observed for the majority of analytes in two matrices within the commodity groups with high water content-apples, and high acid and water content-grapes (73.9% MES and 72.5% MEA, and 77.7% MES and 74.9% MEA, respectively), while strong suppression was observed for matrices within the commodity groups with high starch/protein content and low water and fat content-spelt kernels, and high oil content and very low water content-sunflower seeds (82.1% MES and 82.6% MEA, and 65.2% MES and 70.0% MEA, respectively). Although strong matrix effects were the most common for all investigated matrices, the use of matrix-matched calibration for each sample type enabled satisfactory method performance, i.e., recoveries for the majority of analytes (up to roughly 90%, depending on the fortification level and matrix type), which was also externally confirmed through participation in proficiency testing schemes for relevant food commodity groups with the achieved z-scores within acceptable range ≤ |2|.

Multiresidue analysis of pesticides in four different pomegranate cultivars: Investigating matrix effect variability by GC-MS/MS and LC-MS/MS

Matrix effect (ME) is unavoidable in multiresidue pesticide analysis, even when using highly advanced instruments, and differences in MEs can affect residue analytical accuracy due to pomegranate cultivar composition variations. However, literature to support this claim is limited.The study used GC-MS/MS and LC-MS/MS to investigate four different Indian pomegranate cultivar extracts and their MEs on multi-class pesticides.The whole fruit and arils of all cultivarswere tested for 22 GC-amenable and 21 LC-amenable pesticides. Principal component analysis of the data confirmed that each cultivar had unique MEs for each pesticide.The majority of pesticides showed acute variations in recovery rates with 95% confidence, while GC-MS/MS-amenablepesticides showed more variation. Although extrapolative dilution reduced the influence of MEs on analytical accuracy, a generalized matrix-matching for all cultivars was not possible to achieve.To reduce the variability in MEs, it is recommended that a cultivar-specific matrix-matched standard should be used.

Coupling of Trastuzumab chromatographic profiling with machine learning tools: A complementary approach for biosimilarity and stability assessment

Biosimilar products present a growing opportunity to improve the global healthcare systems. The amount of accepted variability during the comparative assessments of biosimilar products introduces a significant challenge for both the biosimilar developers and the regulatory authorities. The aim of this study was to explore unsupervised machine learning tools as a mathematical aid for the interpretation and visualization of such comparability under control and stress conditions using data extracted from high throughput analytical techniques. For this purpose, a head-to-head analysis of the physicochemical characteristics of three Trastuzumab (TTZ) approved biosimilars and the originator product (Herceptin®) was performed. The studied quality attributes included the primary structure and identity by peptide mapping (PM) with reversed-phase chromatography-UV detection, size and charge profiles by stability-indicating size exclusion and cation exchange chromatography. Stress conditions involved pH and thermal stress. Principal component analysis (PCA) and two of the widely used cluster analysis tools, namely, K-means and Density-based Spatial Clustering of Applications with Noise (DBSCAN), were explored for clustering and feature representation of varied analytical datasets. It has been shown that the clustering patterns delineated by the used algorithms changed based on the included chromatographic profiles. The applied data analysis tools were found effective in revealing patterns of similarity and variability between i) intact and stressed as well as ii) originator and biosimilar samples.

Comprehensive Strategy for Sample Preparation for the Analysis of Food Contaminants and Residues by GC-MS/MS: A Review of Recent Research Trends

Food safety and quality have been gaining increasing attention in recent years. Gas chromatography coupled to tandem mass spectrometry (GC-MS/MS), a highly sensitive technique, is gradually being preferred to GC-MS in food safety laboratories since it provides a greater degree of separation on contaminants. In the analysis of food contaminants, sample preparation steps are crucial. The extraction of multiple target analytes simultaneously has become a new trend. Thus, multi-residue analytical methods, such as QuEChERs and adsorption extraction, are fast, simple, cheap, effective, robust, and safe. The number of microorganic contaminants has been increasing worldwide in recent years and are considered contaminants of emerging concern. High separation in MS/MS might be, in certain cases, favored to sample preparation selectivity. The ideal sample extraction procedure and purification method should take into account the contaminants of interest. Moreover, these methods should cooperate with high-resolution MS, and other sensitive full scan MSs that can produce a more comprehensive detection of contaminants in foods. In this review, we discuss the most recent trends in preparation methods for highly effective detection and analysis of food contaminants, which can be considered tools in the control of food quality and safety.

Smart Multivariate Spectrophotometric Assisted Techniques for Simultaneous Determination of Ephedrine Hydrochloride and Naphazoline Nitrate in the Presence of Interfering Parabens

Background:

PARTIAL Least Squares (PLS) and Principal Component Regression (PCR) are two well-known chemometric methods based on dimension reduction techniques. They can be very practical analyzing a large data set of multiple correlated predictor variables.

Objective:

In the presented work, the resolving power of spectrophotometric assisted mathematical techniques was implemented for the simultaneous determination of two active ingredients; ephedrine hydrochloride (EPH) and naphazoline nitrate (NAPH), in a matrix of excipients.

Methods:

To build the PLS and PCR models, a calibration set was prepared where the two drugs, in combination with the interfering parabens, were modeled by multilevel multifactor design. The proposed models successfully predicted the concentrations of both drugs in validation samples with low Root Mean Squared Error of Prediction (RMSEP).

Results:

The results revealed the ability of the mentioned multivariate calibration models to analyze EPH and NAPH in the presence of the interfering parabens with high selectivity in the concentration ranges of 4.00-20.00 μg mL-1 and 1.00-9.00 μg mL-1, respectively.

Conclusion:

A commercially available nasal spray was successfully analyzed using the developed methods without interfering with other dosage form additives.

Chemometric-enhanced metabolic profiling of five Pinus species using HPLC-MS/MS spectrometry: Correlation to in vitro anti-aging, anti-Alzheimer and antidiabetic activities

Detailed metabolic profiling of needles of five Pinus species was investigated using complementary HPLC-MS/MS techniques together with supervised and unsupervised chemometric tools. This resulted in putative identification of 44 compounds belonging to flavonoids, phenolics, lignans, diterpenes and fatty acids. Unsupervised principal component analysis showed that differences were maintained across the metabolites characteristic of each Pinus species, are mainly related to di-O-p-coumaroyltrifolin, p-coumaroyl quinic acid derivative, arachidonic acid, hydroxypalmitic acid, isopimaric acid and its derivative. A supervised Partial Least Squares regression analysis was performed to correlate HPLC-MS/MS profiles with the variation observed in the in vitro anticholinesterase, antiaging and anti-diabetic potential. All investigated Pinus extracts exerted their antiaging activity via increasing telomerase and TERT levels in normal human melanocytes cells compared to the control (untreated cells). Profound inhibition activities of acetylcholinesterase and dipeptidyl peptidase-4 were also observed with P. pinea and P. canariensis extracts having comparable antidiabetic activities to sitagliptin as a standard antidiabetic drug. Our findings suggested that pine needles are a good source of phenolics and diterpenoids that have possible health promoting activities in management and alleviation of diabetic conditions and Alzheimer disease.