Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry

An update on the sample preparation and analytical methods for synthetic food colorants in food products

Colorants, especially synthetic colorants, play a crucial role in enhancing the aesthetic qualities of food owing to their cost-effectiveness and stability against environmental factors. Ensuring the safe and regulated use of colorants is essential for maintaining consumer trust in food safety. Various preparation and analytical technologies, which are continuously undergoing improvement, are currently used to quantify of synthetic colorants in food products. This paper reviews recent developments in analytical techniques for synthetic food colorants, detection and compares the operational principles, advantages, and disadvantages of each technology. Additionally, it also explores advancements in these technologies, discussing several invaluable tools of analysis, such as high-performance liquid chromatography, liquid chromatography-tandem mass spectrometry, electrochemical sensors, digital image analysis, near-infrared spectroscopy, and surface-enhanced Raman spectroscopy. This comprehensive overview aims to provide valuable insights into current progress and research in the field of food colorant analysis.

Development and Validation of an Analytical Method to Identify and Quantitate Novel Modafinil Analogs in Products Marketed as Dietary Supplements

Modafinil (brand name Provigil®) is a Schedule IV (U.S.) drug used for the treatment of narcolepsy and sleep disorders. It is also known to be used recreationally. Analogs of modafinil, including adrafinil, remain unapproved and/or unscheduled. The lack of scheduling has made these analogs a popular target for recreational use and inclusion in dietary supplements. However, the use of controlled substances (or their analogs) without the care of a physician presents a public health risk. Preliminary nontargeted analyses in our laboratory revealed the presence of adrafinil in several dietary supplements, highlighting the need for an analytical method to identify modafinil analogs in supplements. A liquid chromatography high resolution mass spectrometry (LC-HRMS) method was developed and validated to quantitate modafinil, plus four novel unscheduled modafinil analogs: adrafinil, CRL-40,940, CRL-40,941, and N-methyl-4,4-difluoromodafinil. This method was then applied to four samples of products marketed as dietary supplements collected via undercover purchase. These four products were marketed as nootropics or cognitive enhancers and labeled to contain adrafinil. Adrafinil was found in all four samples. The identification of modafinil analogs in this context is important so that consumers are not, knowingly or unknowingly, consuming these active pharmaceutical ingredients in products marketed as dietary supplements.

Nontarget and suspect screening reveals the presence of multiple plastic-related compounds in polar bear, killer whale, narwhal and long-finned pilot whale blubber from East Greenland

The monitoring of legacy contaminants in sentinel northern marine mammals has revealed some of the highest concentrations globally. However, investigations into the presence of chemicals of emerging Arctic concern (CEACs) and other lesser-known chemicals are rarely conducted, if at all. Here, we used a nontarget/suspect approach to screen for thousands of different chemicals, including many CEACs and plastic-related compounds (PRCs) in blubber/adipose from killer whales (Orcinus orca), narwhals (Monodon monoceros), long-finned pilot whales (Globicephala melas), and polar bears (Ursus maritimus) in East Greenland. 138 compounds were tentatively identified mostly as PRCs, and four were confirmed using authentic standards: di(2-ethylhexyl) phthalate (DEHP), diethyl phthalate (DEP), di(2-propylheptyl) phthalate (DPHP), and one antioxidant (Irganox 1010). Three other PRCs, a nonylphenol isomer, 2,6-di-tert-butylphenol, and dioctyl sebacate, exhibited fragmentation patterns matching those in library databases. While phthalates were only above detection limits in some polar bear and narwhal, Irganox 1010, nonylphenol, and 2,6-di-tert-butylphenol were detected in >50% of all samples. This study represents the first application of a nontarget/suspect screening approach in Arctic cetaceans, leading to the identification of multiple PRCs in their blubber. Further nontarget analyses are warranted to comprehensively characterize the extent of CEAC and PRC contamination within Arctic marine food webs.

Electrospun nanofiber-based sensors for the detection of chemical and biological contaminants/hazards in the food industries

Food contamination reveals a major health risk globally and presents a significant challenge for the food industry. It can stem from biological contaminants like pathogens, parasites, and viruses, or chemical contaminants such as heavy metals, pesticides, drugs, and hormones. There is also the possibility of naturally occurring hazardous chemicals. Consequently, the development of sensing platforms has become crucial to accurately and rapidly identify contaminants and hazards in food products. Electrospun nanofibers (NFs) offer a promising solution due to their unique three-dimensional architecture, large specific surface area, and ease of preparation. Moreover, NFs exhibit excellent biocompatibility, degradability, and adaptability, making monitoring more convenient and environmentally friendly. These characteristics also significantly reduce the detection process of contaminants. NF-based sensors have the ability to detect a wide range of biological, chemicals, and physical hazards. Recent research on NFs-based sensors for the detection of various food contaminants/hazards, such as pathogens, pesticide/drugs residues, toxins, allergens, and heavy metals, is presented in this review.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

Complementary methods for structural assignment of isomeric candidate structures in non-target liquid chromatography ion mobility high-resolution mass spectrometric analysis

Non-target screening with LC/IMS/HRMS is increasingly employed for detecting and identifying the structure of potentially hazardous chemicals in the environment and food. Structural assignment relies on a combination of multidimensional instrumental methods and computational methods. The candidate structures are often isomeric, and unfortunately, assigning the correct structure among a number of isomeric candidate structures still is a key challenge both instrumentally and computationally. While practicing non-target screening, it is usually impossible to evaluate separately the limitations arising from (1) the inability of LC/IMS/HRMS to resolve the isomeric candidate structures and (2) the uncertainty of in silico methods in predicting the analytical information of isomeric candidate structures due to the lack of analytical standards for all candidate structures. Here we evaluate the feasibility of structural assignment of isomeric candidate structures based on in silico-predicted retention time and database collision cross-section (CCS) values as well as based on matching the empirical analytical properties of the detected feature with those of the analytical standards. For this, we investigated 14 candidate structures corresponding to five features detected with LC/HRMS in a spiked surface water sample. Considering the predicted retention times and database CCS values with the accompanying uncertainty, only one of the isomeric candidate structures could be deemed as unlikely; therefore, the annotation of the LC/IMS/HRMS features remained ambiguous. To further investigate if unequivocal annotation is possible via analytical standards, the reversed-phase LC retention times and low- and high-resolution ion mobility spectrometry separation, as well as high-resolution MS2 spectra of analytical standards were studied. Reversed-phase LC separated the highest number of candidate structures while low-resolution ion mobility and high-resolution MS2 spectra provided little means for pinpointing the correct structure among the isomeric candidate structures even if analytical standards were available for comparison. Furthermore, the question arises which prediction accuracy is required from the in silico methods to par the analytical separation. Based on the experimental data of the isomeric candidate structures studied here and previously published in the literature (516 retention time and 569 CCS values), we estimate that to reduce the candidate list by 95% of the structures, the confidence interval of the predicted retention times would need to decrease to below 0.05 min for a 15-min gradient while that of CCS values would need to decrease to 0.15%. Hereby, we set a clear goal to the in silico methods for retention time and CCS prediction.

Lignin-based covalent organic polymers with improved crystallinity for non-targeted analysis of chemical hazards in food samples

Lignin, the most abundant source of renewable aromatic compounds derived from natural lignocellulosic biomass, has great potential for various applications as green materials due to its abundant active groups. However, it is still challenging to quickly construct green polymers with a certain crystallinity by utilizing lignin as a building block. Herein, new green lignin-based covalent organic polymers (LIGOPD-COPs) were one-pot fabricated with water as the reaction solvent and natural lignin as the raw material. Furthermore, by using paraformaldehyde as a protector and modulator, the LIGOPD-COPs prepared under optimized conditions displayed better crystallinity than reported lignin-based polymers, demonstrating the feasibility of preparing lignin-based polymers with improved crystallinity. The improved crystallinity confers LIGOPD-COPs with enhanced application performance, which was demonstrated by their excellent performances in sample treatment of non-targeted food safety analysis. Under optimized conditions, phytochromes, the main interfering matrices, were almost completely removed from different phytochromes-rich vegetables by LIGOPD-COPs, accompanied by "full recovery" of 90 chemical hazards. Green, low-cost, and reusable properties, together with improved crystallinity, will accelerate the industrialization and marketization of lignin-based COPs, and promote their applications in many fields.

Easily operated COF-based monolithic sponges as matrix clean-up materials for non-targeted analysis of chemical hazards in oil-rich foods

Non-targeted analysis of chemical hazards in foods plays a crucial role in controlling food safety. However, because it brings forward high demand for sample pretreatment, materials suitable for the pretreatment of foods, especially animal foods, are rare. Herein, covalent organic frameworks (COF)-based monolithic materials were constructed by three successive steps: preparation of polydimethylsiloxane (PDMS) sponge using sugar cube as a sacrificial template, loading of a heteroporous COF on PDMS sponge via ultrasonic or in-situ growth method, coating of the obtained PDMS@COF by polydopamine (PDA) network. As-prepared PDMS@COF@PDA sponges were demonstrated to work well in sample pretreatment of animal foods for non-targeted analysis of chemical hazards. After a simple vortex treatment for about 2 min, more than 98% triglycerides, the main interfering matrix components in animal foods, could be removed from lard and pork samples, accompanied by "full recovery" (recovery efficiencies: ≥63%) of 44 chemical hazards with different physicochemical properties. Besides providing promising sample pretreatment materials for non-targeted food safety analysis, this work also paves a feasible way to improve COF-based monolithic materials and thus promote their practical applications, because we found that the introduction of PDA network on COF-based monolithic material surface could play a role in "killing three birds with one stone": enhancing the stability of the materials by overcoming the detachment of COF during operations; controllably adjusting hydrophobic and hydrogen-bonding interactions on the material surface to promote the removal of triglycerides; weakening the hydrophobic and π-π interactions between COF and chemical hazards to increase the recoveries of chemical hazards.

Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions

PURPOSE OF REVIEW

We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale.

RECENT FINDINGS

Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

Seaweed metabolomics: A review on its nutrients, bioactive compounds and changes in climate change

Seaweed, an important food resource in several Asian countries, contains various metabolites, including sugars, organic acids, and amino acids; however, their content is affected by prevailing environmental conditions. This review discusses seaweed metabolomics, especially the distribution of primary and functional secondary metabolites (e.g., carotenoids, polyphenols) in seaweed. Additionally, the effects of global warming on seaweed metabolite profile changes are discussed. For example, high temperatures can increase amino acid levels in seaweeds. Overall, understanding the effects of global warming on seaweed metabolite profiles can be useful for evaluating the nutritional composition of seaweeds as food. This review provides an overview of recent applications of metabolomics in seaweed research as well as a perspective on the nutrient content and cultivation of seaweeds under climate change scenarios.

Portable sensor based on magnetic separation and enzyme-mediated immune nanomaterials for point-of-care testing of Listeria monocytogenes in food

Listeria monocytogenes (L. monocytogenes), a typical foodborne pathogen, poses a serious threat to public health safety. This stimulates to develop a point-of-care testing (POCT) method to achieve rapid, sensitive detection of L. monocytogenes. In this study, polyethylene glycol (PEG) mediated ampicillin functionalized magnetic beads (Amp-PEG-MBs) was prepared successfully and it achieved high efficiency (>90%) and rapid (5 min) capture for L. monocytogenes at room temperature. The innovative combination of antibody (Ab), glucose oxidase (GOD) and graphene oxide (GO) prepared Ab@GO@GOD for the specific recognition of L. monocytogenes. Finally, Amp-PEG-MBs and Ab@GO@GOD were successfully assembled into Amp-PEG-MBs@L. monocytogenes-Ab@GO@GOD sandwich structure which could catalyze the glucose, and the final detection results were recorded by a blood glucose meter (BGM). Magnetic separation (MS) combined with enzyme-catalyzed sensor (MS-Ab@GO@GOD-BGM) was successfully established to achieve the detection of L. monocytogenes in artificially contaminated juice within 66 min with the limit of detection was 10¹ CFU/mL. This sensor has potential for other pathogens detection by modifying specific antibodies.

Mass Spectrometric Methods for Non-Targeted Screening of Metabolites: A Future Perspective for the Identification of Unknown Compounds in Plant Extracts

Phyto products are widely used in natural products, such as medicines, cosmetics or as so-called “superfoods”. However, the exact metabolite composition of these products is still unknown, due to the time-consuming process of metabolite identification. Non-target screening by LC-HRMS/MS could be a technique to overcome these problems with its capacity to identify compounds based on their retention time, accurate mass and fragmentation pattern. In particular, the use of computational tools, such as deconvolution algorithms, retention time prediction, in silico fragmentation and sophisticated search algorithms, for comparison of spectra similarity with mass spectral databases facilitate researchers to conduct a more exhaustive profiling of metabolic contents. This review aims to provide an overview of various techniques and tools for non-target screening of phyto samples using LC-HRMS/MS.

Collision Cross Section Prediction with Molecular Fingerprint Using Machine Learning

High-resolution mass spectrometry is a promising technique in non-target screening (NTS) to monitor contaminants of emerging concern in complex samples. Current chemical identification strategies in NTS experiments typically depend on spectral libraries, chemical databases, and in silico fragmentation tools. However, small molecule identification remains challenging due to the lack of orthogonal sources of information (e.g., unique fragments). Collision cross section (CCS) values measured by ion mobility spectrometry (IMS) offer an additional identification dimension to increase the confidence level. Thanks to the advances in analytical instrumentation, an increasing application of IMS hybrid with high-resolution mass spectrometry (HRMS) in NTS has been reported in the recent decades. Several CCS prediction tools have been developed. However, limited CCS prediction methods were based on a large scale of chemical classes and cross-platform CCS measurements. We successfully developed two prediction models using a random forest machine learning algorithm. One of the approaches was based on chemicals' super classes; the other model was direct CCS prediction using molecular fingerprint. Over 13,324 CCS values from six different laboratories and PubChem using a variety of ion-mobility separation techniques were used for training and testing the models. The test accuracy for all the prediction models was over 0.85, and the median of relative residual was around 2.2%. The models can be applied to different IMS platforms to eliminate false positives in small molecule identification.

Approaches for assessing performance of high-resolution mass spectrometry-based non-targeted analysis methods

Non-targeted analysis (NTA) using high-resolution mass spectrometry has enabled the detection and identification of unknown and unexpected compounds of interest in a wide range of sample matrices. Despite these benefits of NTA methods, standardized procedures do not yet exist for assessing performance, limiting stakeholders’ abilities to suitably interpret and utilize NTA results. Herein, we first summarize existing performance assessment metrics for targeted analyses to provide context and clarify terminology that may be shared between targeted and NTA methods (e.g., terms such as accuracy, precision, sensitivity, and selectivity). We then discuss promising approaches for assessing NTA method performance, listing strengths and key caveats for each approach, and highlighting areas in need of further development. To structure the discussion, we define three types of NTA study objectives: sample classification, chemical identification, and chemical quantitation. Qualitative study performance (i.e., focusing on sample classification and/or chemical identification) can be assessed using the traditional confusion matrix, with some challenges and limitations. Quantitative study performance can be assessed using estimation procedures developed for targeted methods with consideration for additional sources of uncontrolled experimental error. This article is intended to stimulate discussion and further efforts to develop and improve procedures for assessing NTA method performance. Ultimately, improved performance assessments will enable accurate communication and effective utilization of NTA results by stakeholders.

Non-targeted analysis with liquid chromatography - high resolution mass spectrometry for the identification of food packaging migrants

Potential contamination of food with chemicals migrating from food packaging is an important, yet under-investigated area of food safety. In this study, we examined chemicals migrating from common paper-based food packaging: pizza boxes and pizza box liners, butcher paper and liquid egg containers. Migration tests were conducted with a food simulant for 10 days, and migrated chemicals were identified with liquid chromatography (LC) - high resolution mass spectrometry (HRMS) with mass error < 3 ppm. HRMS identification was based on spectra and/or structure matching against commercial databases (MzCloud, ChemSpider, and Extractable and Leachable high resolution accurate mass (HRAM) database). Following HRMS identification, orthogonal LC retention information was utilized to further refine the data and reduce false positive findings. A model for calculating retention times (t_R) based on octanol-water partition coefficient (log K_ow) values was evaluated and applied for HRMS data refining. Using this approach, 153 migrated chemicals were identified, of which five were further confirmed with reference analytical standards. Additionally, amounts of bisphenol A and bisphenol S, the chemicals of toxicological concerns, were measured at the levels below the established regulatory limits for migration, indicating no/low risk to consumer's health. This study demonstrated the utility of LC-HRMS for confident identification of food packaging migrants.

Present-Day Practice of Non-Target Chemical Analysis

Abstract

We review the main techniques, procedures, and information products used in non-target analysis (NTA) to reveal the composition of substances. Sampling and sample preparation methods are preferable that ensure the extraction of analytes from test samples in a wide range of analyte properties with the most negligible loss. The necessary techniques of analysis are versions of chromatography–high-resolution tandem mass spectrometry (HRMS), yielding individual characteristics of analytes (mass spectra, retention properties) to accurately identify them. The prioritization of the analytical strategy discards unnecessary measurements and thereby increases the performance of the NTA. Chemical databases, collections of reference mass spectra and retention characteristics, algorithms, and software for processing HRMS data are indispensable in NTA.

Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices

The developers of medical devices evaluate the biocompatibility of their device prior to FDA's review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.

Rapid detection of apple juice concentrate adulteration with date concentrate, fructose and glucose syrup using HPLC-RID incorporated with chemometric tools

The present study investigates the substitute of apple juice concentrate with some cheap sweeteners including glucose syrup, fructose syrup, and date concentrate, as the most common adulterants. For this purpose, pure and authenticated apple juice concentrate was individually adulterated with 10% to 50% of glucose syrup, fructose syrup, and date concentrate. High-performance liquid chromatography coupled with a refractive index detector (HPLC-RID) was applied to determine the carbohydrates profile of samples. The results of HPLC-RID were subjected to multivariate statistical analysis, namely principal component analysis (PCA) and linear discriminant analysis (LDA). The results showed that the glucose/fructose ratio and maltose content were the best indicators to detect adulteration of apple juice concentrate. A set of glucose, sorbitol, sucrose, maltose, and glucose/fructose ratio was used as a discriminating factor. Using this approach, adulteration of apple juice concentrate with cheaper sweeteners was detected at a limit of 10%, depending on the adulterant.

Nontargeted screening method for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry

Nontargeted screening of both veterinary drugs and their metabolites is important for comprehensive safety evaluation of animal-derived foods. In this study, a novel nontargeted screening strategy was developed for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry. First, an in-house database of mass spectra including 3,710 veterinary drugs and their metabolites was constructed. Second, fragmentation characteristics of parent drugs and their metabolites in mass spectrometry were investigated and summarized. Then, a nontargeted screening procedure was established based on fragmentation characteristics to screen unknown parent drugs and their metabolites. Finally, the strategy was applied to 33 egg samples, and four veterinary drugs and three drug metabolites were determined and identified. These results showed that the developed strategy can realize suspect and nontargeted screening of veterinary drugs and their metabolites, and can also be applied to other animal-derived foods.

Evaluation of different extractions for the metabolite identification of malachite green in brook trout and shrimp

Applications of mass spectrometry-based metabolomics in food science have developed fast in the last decade. Sample preparation and data processing are critical in non-target/metabolomic workflows but there is currently no standardized protocol for the development of these methods. The impact of data processing parameters or the inclusion of a different matrix is not often taken into account during the selection of an extraction. Thus, this study aimed to investigate the impact of different extractions, e.g., QuEChERS, and data processing on the determination of malachite green metabolites in two different organisms, brook trout and shrimp. The results obtained confirm the need for a harmonized approach for the validation of non-target workflows, as depending on the comparison criteria, the matrix, the mode of ionization or data processing, a different extraction could be chosen. This study also identified for the first time des-methylated leucomalachite green as another metabolite in the two organisms.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

Application of non-target analysis to study the thermal transformation of malachite and leucomalachite green in brook trout and shrimp

The fate of malachite green and its main metabolite leucomalachite green during thermal treatment was examined in seafood (brook trout and white shrimp) using non-target analysis. Samples were extracted using QuEChERS and analyzed using liquid chromatography coupled with quadruple time of flight mass spectrometry. Malachite green levels were reduced in meat during boiling (∼40%), microwaving (64%), and canning (96%). Only microwaving was successful in significantly decreasing leucomalachite green levels in brook trout. The reduction percentages of the two target analytes were not significantly different in shrimp (mean fat content = 0.8 ± 0.3%) and in brook trout (mean fat content = 3.5 ± 1.7%), suggesting that a higher fat content may not affect the reduction of the more lipophilic leucomalachite green in these two matrices. Three transformation products were tentatively identified in the cooked tissues, resulting from the cleavage of the conjugated structure or through demethylation. Further research is needed to determine possible adverse health effects. The findings of this study show how non-target analysis can complement targeted methodologies in identifying and evaluating risks to human health.

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Non-target analysis was applied to study the fate of malachite/leucomalachite green.

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Thermal processing significantly reduced malachite green in seafood by up to 96%.

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Leucomalachite green levels were significantly reduced only after microwaving.

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Three transformation products were tentatively identified.

Chemical contaminants in canned food and can-packaged food: a review

Canning, as a preservation technique, is widely used to extend the shelf life as well as to maintain the quality of perishable foods. During the canning process, most of the microorganisms are killed, reducing their impact on food quality and safety. However, the presence of a range of undesirable chemical contaminants has been reported in canned foods and in relation to the canning process. The present review provides an overview of these chemical contaminants, including metals, polymeric contaminants and biogenic amine contaminants. They have various origins, including migration from the can materials, formation during the canning process, or contamination during steps required prior to canning (e.g. the disinfection step). Some other can-packaged foods (e.g. beverages or milk powder), which are not canned foods by definition, were also discussed in this review, as they have been frequently studied simultaneously with canned foods in terms of contamination. The occurrence of these contaminants, the analytical techniques involved, and the factors influencing the presence of these contaminants in canned food and can-packaged food are summarized and discussed.

Large-Scale Implementation and Flaw Investigation of Human Serum Suspect Screening Analysis for Industrial Chemicals

Non-targeted analysis (NTA), including both suspect screening analysis (SSA) and unknown compound analysis, has gained increasing popularity in various fields for its capability in identifying new compounds of interests. Current major challenges for NTA SSA are that (1) tremendous effort and resources are needed for large-scale identification and confirmation of suspect chemicals and (2) suspect chemicals generally show low matching rates during identification and confirmation processes. To narrow the gap between these challenges and smooth implementation of NTA SSA methodology in the biomonitoring field, we present a thorough SSA workflow for the large-scale screen, identification, and confirmation of industrial chemicals that may pose adverse health effects in pregnant women and newborns. The workflow was established in a study of 30 paired maternal and umbilical cord serum samples collected at delivery in the San Francisco Bay area. By analyzing LC-HRMS and MS/MS data, together with the assistance of a combination of resources including online MS/MS spectra libraries, online in silico fragmentation tools, and the EPA CompTox Chemicals Dashboard, we confirmed the identities of 17 chemicals, among which monoethylhexyl phthalate, 4-nitrophenol, tridecanedioic acid, and octadecanedioic acid are especially interesting due to possible toxicities and their high-volume use in industrial manufacturing. Similar to other previous studies in the SSA field, the suspect compounds show relatively low MS/MS identification (16%) and standard confirmation (8%) rates. Therefore, we also investigated origins of false positive features and unidentifiable suspected features, as well as technical obstacles encountered during the confirmation process, which would promote a better understanding of the flaw of low confirmation rate and encourage gaining more effective tools for tackling this issue in NTA SSA.

Suspect screening of pharmaceuticals in fish livers based on QuEChERS extraction coupled with high resolution mass spectrometry

The presence of pharmaceuticals and personal care products (PPCPs) in aquatic environments is of increasing concern due to the presence of residues in fish and aquatic organisms, and emerging antibiotic resistance. Wastewater release is an important contributor to the presence of these compounds in aquatic ecosystems, where they may accumulate in food webs. The traditional environmental surveillance approach relies on the targeted analysis of specific compounds, but more suspect screening methods have been developed recently to allow for the identification of a variety of contaminants. In this study, a method based on QuEChERS extraction - using acetonitrile/water mixture as solvent and PSA/C₁₈ for sample clean-up - was applied to identify pharmaceuticals and their metabolites in fish livers. Both target and suspect screening workflows were used and fish were sampled upstream and downstream of wastewater treatment plants from the Scioto River, Ohio (USA). The method performed well in terms of extraction of some target PPCPs, with recoveries generally above 90%, good repeatability (<20%), and linearity. Based on target analysis, lincomycin and sulfamethoxazole were two antibiotics identified in fish livers at average concentrations of 30.3 and 25.6 ng g^-1 fresh weight, respectively. Using suspect screening, another antibiotic, azithromycin and an antidepressant metabolite, erythrohydrobupropion were identified (average concentrations: 27.8 and 13.8 ng g^-1, respectively). The latter, reported, to the best of our knowledge, for the first time in fish livers, was also found at higher concentrations in fish livers sampled downstream vs. upstream. The higher frequency of detection for azithromycin in benthic feeding fish species (63%) as well as clusters identified between different foraging groups suggest that foraging behavior may be an important mechanism in the bioaccumulation of PPCPs. This study shows how suspect screening is effective in identifying new contaminants in fish livers, notably using differential analysis among different spatially distributed samples.

Identification of Erythromycin and Clarithromycin Metabolites Formed in Chicken Liver Microsomes Using Liquid Chromatography-High-Resolution Mass Spectrometry

Nontargeted analysis can be used for the rapid screening and confirmatory analysis of veterinary drugs and their metabolites, which are important for the comprehensive safety evaluation of animal-derived foods. Here, a novel nontargeted screening approach based on liquid chromatography coupled with electrospray ionization-high-resolution mass spectrometry (LC/ESI-HR-MS) was developed to determine erythromycin, clarithromycin, and their metabolites in chicken liver microsomes. Erythromycin and clarithromycin were incubated in vitro in the presence of NADPH for 60 min to generate metabolites in chicken liver microsomes. After the incubation, the supernatant was extracted using ultrasonic shaking, orbital shaking, and centrifugation before analysis using LC/ESI-HR-MS in positive ion mode on an Agilent Eclipse Plus C18 column (100 mm × 2.1 mm; i.d. 3.5 µm) with 0.1 percent formic acid-water and acetonitrile as the mobile phases for gradient elution at 0.4 mL/min. The results show that erythromycin can produce N-desmethyl-erythromycin A in chicken liver microsomes, but clarithromycin cannot produce N-desmethyl-clarithromycin in chicken liver microsomes. The N-desmethyl-erythromycin A and N-desmethyl-clarithromycin were tentatively identified in chicken liver microsomes using the established quick analytic method, which will provide a theoretical foundation for future research on pharmacokinetics and drug elimination in poultry.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.

Rapid screening of 70 colorants in dyeable foods by using ultra-high-performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry with customized accurate-mass database and mass spectral library

A rapid screening method of 70 colorants for regulatory control in dyeable foods was established using ultra-high-performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q/Orbitrap MS) with customized accurate-mass database and mass spectral library. A rapid, high-throughput, and simple sample pretreatment condition with low reagent consumption and high recovery was developed on the basis of ultrasound-assisted extraction and dispersion solid-phase extraction. Rapid screening was conducted by comparing the experimentally measured exact mass of the parent and fragment ions, the isotope pattern, and the retention time with the accurate-mass database and by matching the acquired MS/MS spectra against the mass spectral library. The performance of the method was evaluated in terms of linearity, limits of detection, limits of quantitation, recovery, repeatability, reproducibility, and matrix effect. The proposed method was applied for simultaneous analysis of 70 colorants in seven kinds of dyeable foods, and it exhibited great potential for broad, sensitive, and reliable.

Resolving unknown isomers of emerging per- and polyfluoroalkyl substances (PFASs) in environmental samples using COSMO-RS-derived retention factor and mass fragmentation patterns

Chromatographic retention factors (k) and mass spectral fragmentation patterns of per- and polyfluoroalkyl substances (PFASs) were determined using the optimized parameters in liquid chromatography with tandem high-resolution mass spectrometry (LC-HRMS) analysis. Characteristic fragment ions obtained at various collision energies (MS² fragmentation) were used to determine the structures of newly discovered (emerging) PFASs detected from industrial effluent and surface water samples. Moreover, COnductor-like Screening MOdel for Realistic Solvents (COSMO-RS) derived octanol-water partition coefficients (K_ow), along with mean isotropic polarizabilities calculated from Density Functional Theory (DFT), of known PFASs were plotted against their experimental k values (k_exp) to obtain a multivariable regression model that can be used to predict k values of unknown PFASs. The k values of different structural isomers of unknown PFASs were calculated and compared to k_exp. The predicted k value for the isomer that matches the MS² fragmentation observed was found to be within 4.2 % of k_exp. This study demonstrates the applicability of an approach that combines the observed MS² fragmentation patterns and k values, together with computationally-derived log K_ow and polarizabilities, in assigning the structures of unknown PFASs at environmentally relevant conditions when no reference standards are available.

Occurrence, distribution and removal of organic micro-pollutants in a low saline water body

A low saline backwater canal, mainly utilized for domestic and agricultural purposes, has been analyzed for the possible presence of organic micropollutants (OMP) and their potential removal was explored by multilayered microfiltration membranes. The qualitative as well as quantitative analysis were carried out for a span of one year using the technique of liquid chromatography connected with high resolution mass spectrometry (LC-Q-TOF-MS). The identification of the formally unknown compounds was initially done using non-target analysis based on the mass accuracy, isotopic pattern and MS/MS spectral interpretation. Results of the non target screening revealed the presence of 11 OMPs. Five of these OMPs were confirmed using standards; these include chlorophene (CHP), oxybenzone (OXY), N, N-diethyl-meta-toluamide (DEET), N, N-diethyl-benzamide (DEB) and dibutyl phthalate (DBP). Among the confirmed OMPs, the highest concentration was observed for DBP (244.61 ng l^-1). The most frequently observed OMP in the study area was DBP while the least was DEB which is an insect repellent as well as a degradation product of DEET. The ecological risk associated with the target compounds has also been analyzed by calculating the risk quotient (RQ) and the results revealed that at the detected levels, these compounds are capable of causing low to medium risk. Low pressure (<0.3 bar) filtrations of the compounds were attempted using microfiltration (MF) and, poly(ethyleneimine)/poly(styrene sulfonate) (PEI/PSS) multi-layered MF membrane for spiked ultrapure water and also for natural water from the back-water canal. The batch mode illustrates nearly complete removal of CHP and OXY in spiked solutions and a good removal efficiency from natural water. The effect of coexisting ions and surfactants in feed is also illustrated. The high efficiency of the removal of both CHP and OXY, in such a complex medium highlights the potential application of the present method for the removal of similar OMPs in natural waters.

A Proposed Quality Control Standard Mixture and Its Uses for Evaluating Nontargeted and Suspect Screening LC/HR-MS Method Performance

Nontargeted (NTA) and suspect screening analyses (SSA) aim to detect and identify unknown compounds of interest from a given sample. The complexity and diversity of NTA and SSA methodologies necessitate the use of a comprehensive quality control standard mixture to determine if methods are fit for purpose, but to our knowledge, such a standard has not been developed that can be used by multiple disciplines, nor is one readily available. This work describes the development and analysis of a proposed nontargeted standard/quality control mixture for NTA and SSA applications using liquid chromatography/electrospray ionization-high resolution-mass spectrometry. Considerations in its development included achieving diversity of compounds with respect to elemental composition, molecular weight, retention time, and ionization in positive and/or negative ion modes, which resulted in the inclusion of 89 compounds. The utility of the standard mixture was applied on our own NTA and SSA workflows where sample preparation efficiency and potential sources of error due to instrumental and data processing methods were evaluated. Some areas in need of improvement were identified, such as hydrophilic compound detection and molecular formula generation for compounds containing fluorine. However, our overall methodology was found to be fit for purpose and we were able to establish thresholds to increase reliability and throughput of reported results.

Improving Target and Suspect Screening High-Resolution Mass Spectrometry Workflows in Environmental Analysis by Ion Mobility Separation

Currently, the most powerful approach to monitor organic micropollutants (OMPs) in environmental samples is the combination of target, suspect, and nontarget screening strategies using high-resolution mass spectrometry (HRMS). However, the high complexity of sample matrices and the huge number of OMPs potentially present in samples at low concentrations pose an analytical challenge. Ion mobility separation (IMS) combined with HRMS instruments (IMS-HRMS) introduces an additional analytical dimension, providing extra information, which facilitates the identification of OMPs. The collision cross-section (CCS) value provided by IMS is unaffected by the matrix or chromatographic separation. Consequently, the creation of CCS databases and the inclusion of ion mobility within identification criteria are of high interest for an enhanced and robust screening strategy. In this work, a CCS library for IMS-HRMS, which is online and freely available, was developed for 556 OMPs in both positive and negative ionization modes using electrospray ionization. The inclusion of ion mobility data in widely adopted confidence levels for identification in environmental reporting is discussed. Illustrative examples of OMPs found in environmental samples are presented to highlight the potential of IMS-HRMS and to demonstrate the additional value of CCS data in various screening strategies.

Strategies for data reduction in non-targeted screening analysis: The impact of sample variability for food safety applications

While analytical methods targeting specific compounds are critical for food safety, analytes excluded from the targeted list will not be identified. Non-targeted analyses (NTA) using LC/HR-MS complement these approaches by producing information-rich data sets where molecular formula can be generated for each detected compound; however, data mining can be labor intensive. Thus, we examined different NTA approaches to reduce the number of compounds needing further investigation, without relying on a suspect list or MS/MS database, both in single ingredient foods (i.e., oats) and more complex, oat-containing samples. We investigated inherent sample variability and utilized this information to build in-house databases for removing food compounds from sample data. While food databases were useful for data reduction, differential analysis was the most promising approach for single ingredient foods because it substantially reduced the number of features while retaining spiked QC compounds; however, a combination of approaches was necessary with greater sample complexity.

Untargeted Screening in a Case Control Study Using Apples as a Matrix

Untargeted screening using high resolution mass spectrometry (HRMS) is a promising approach for screening the food supply for contaminants, but the sheer amount of information inherent to the HRMS data set presents analytical challenges. Red apples, collected during the U.S. FDA's Total Diet Study, were studied to determine whether bioinformatic software can be used to distinguish spiked model compounds from those native to apples. A workflow was created, in which initial data sets of over 44,000 features in each of the two spiked samples were reduced by several orders of magnitude to a scale suitable for visual inspection. After visual inspection to address degeneracy and data quality, the final data sets contained 30 and 2 suspect compounds, respectively. To the best of our knowledge, this is the largest scale case-control study on food matrices to date and the first use of market basket samples as references in an untargeted screening study.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.

Limitations of deuterium-labeled internal standards for quantitative electrospray ionization mass spectrometry analysis of fatty acid metabolites

RATIONALE

The electrospray ionization mass spectrometry (ESI-MS) methodology often shows poor ionization reproducibility in the analysis of biological samples. Therefore, normalization of the measured peak intensities is essential. It is believed that quantitative data with high reproducibility can be obtained by adding a constant amount of an internal standard (IS) material labeled with stable isotopes to each sample, thus allowing the correction of the quantitative value of the target compound by that of the IS. We investigated whether the presence or absence of a labeled IS improves the accuracy of these quantitative values.

METHODS

Triple quadrupole MS coupled with liquid chromatography was used to analyze fatty acid metabolites in biological samples as target compounds. Two independent systems were used to provide a measure of reproducibility in two different laboratories.

RESULTS

Data having poor reproducibility in the raw peak areas were efficiently normalized using the IS, but, crucially, the IS method using stable isotopes was not always necessary. In some cases, the reproducibility was relatively good even without using the IS. In a contaminant matrix, the MS response behavior of the target compound and its stable isotope-labeled material was complicated. Since ion suppression by matrix contaminants was dependent on the concentration of the target compound, the added amounts of the ISs were also important, Furthermore, an equivalent normalization effect was obtained by using a pooled quality control sample as an external standard, thus obviating the need for labeled IS samples, which are often expensive and sometimes not commercially available.

CONCLUSIONS

Our results raise the question as to whether the quantitative method using stable-isotope-labeled ISs is always necessary and beneficial. However, the results obtained in this study cannot be generalized because only fatty acid metabolites were examined using ESI-MS and only a highly substituted deuterium-labeled IS was used.

An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer

Extra virgin olive oil (EVOO) represents a crucial ingredient of the Mediterranean diet. Being a first-choice product, consumers should be guaranteed its quality and geographical origin, justifying the high purchasing cost. For this reason, it is important to have new reliable tools able to classify products according to their geographical origin. The aim of this work was to demonstrate the efficiency of an open source visible and near infra-red (VIS-NIR) spectrophotometer, relying on a specific app, in assessing olive oil geographical origin. Thus, 67 Italian and 25 foreign EVOO samples were analyzed and their spectral data were processed through an artificial intelligence algorithm. The multivariate analysis of variance (MANOVA) results reported significant differences (p < 0.001) between the Italian and foreign EVOO VIS-NIR matrices. The artificial neural network (ANN) model with an external test showed a correct classification percentage equal to 94.6%. Both the MANOVA and ANN tested methods showed the most important spectral wavelengths ranges for origin determination to be 308–373 nm and 594–605 nm. These are related to the absorption of phenolic components, carotenoids, chlorophylls, and anthocyanins. The proposed tool allows the assessment of EVOO samples’ origin and thus could help to preserve the “Made in Italy” from fraud and sophistication related to its commerce.

Suspect and non-targeted screening of chemicals of emerging concern for human biomonitoring, environmental health studies and support to risk assessment: From promises to challenges and harmonisation issues

Large-scale suspect and non-targeted screening approaches based on high-resolution mass spectrometry (HRMS) are today available for chemical profiling and holistic characterisation of biological samples. These advanced techniques allow the simultaneous detection of a large number of chemical features, including markers of human chemical exposure. Such markers are of interest for biomonitoring, environmental health studies and support to risk assessment. Furthermore, these screening approaches have the promising capability to detect chemicals of emerging concern (CECs), document the extent of human chemical exposure, generate new research hypotheses and provide early warning support to policy. Whilst of growing importance in the environment and food safety areas, respectively, CECs remain poorly addressed in the field of human biomonitoring. This shortfall is due to several scientific and methodological reasons, including a global lack of harmonisation. In this context, the main aim of this paper is to present an overview of the basic principles, promises and challenges of suspect and non-targeted screening approaches applied to human samples as this specific field introduce major specificities compared to other fields. Focused on liquid chromatography coupled to HRMS-based data acquisition methods, this overview addresses all steps of these new analytical workflows. Beyond this general picture, the main activities carried out on this topic within the particular framework of the European Human Biomonitoring initiative (project HBM4EU, 2017-2021) are described, with an emphasis on harmonisation measures.

Identification of chemicals in a polyvinyl chloride/polyethylene multilayer film by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry and their migration into solution

An ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) method was employed for chemical identification in a commercial polyvinyl chloride/polyethylene (PVC/PE) multilayer film. Over 30 chemicals from different layers (PE layer, PVC layer, and adhesive layer) of the film were identified and were classified into 6 groups, including antioxidants, plasticizers, slip agents, antistatic agents, adhesive components, etc. Special attention was placed on the analysis of some non-intentionally added substances and oligomers in adhesive. Based on the identification results, six additives (all from PE layer) were selected and their migration behaviors were investigated via one-sided contact migration test. The migration test was performed by exposing the PE side of the film to different simulating solutions (water, 40% ethanol, and 95% ethanol) at 40°C, as well as recording the migration level as a function of time. No obvious migration was found into water for all additives, while the migration into 40% and 95% ethanol followed Fickian diffusion behavior, and could be described by Fick's diffusion equation. Diffusion coefficients derived from the equation were in a range of 10^-13 to 10^-10 cm²/s and were dependent on the type of additive and solution.