A Fast and Simple Solid Phase Extraction-Based Method for Glucosinolate Determination: An Alternative to the ISO-9167 Method.

Glucosinolates (GLSs) are a well-studied sulfur-containing compound found in Brassicaceae plants that play critical roles in plant resistance and human health. Correctly identifying and reliably quantifying the total and individual GLS content is of great importance. An improved method as an alternative to the ISO 9167-1 (ISO) method is developed in the present study. An efficient extraction and purification procedure is proposed with a commercially available dimethylaminopropyl (DEA)-based weak anion exchange solid-phase extraction (SPE) cartridge instead of using the self-prepared ion-exchange columns in the ISO method. The GLSs are identified and quantified by ultra high-performance liquid chromatography (UHPLC) high-resolution mass spectrometry (HRMS). The method demonstrates a comparable quantification of total and individual GLSs on certified rapeseeds and other Brassicaceae vegetables when compared to the ISO method. The developed SPE method is simpler and more efficient, thus allowing for applications to a large sample size with reduced analysis time, improved repeatability and accuracy, and possible automation.

Study of UV-Vis molar absorptivity variation and quantitation of anthocyanins using molar relative response factor.

The effects of anthocyanin's substitution groups on the UV-Vis molar absorptivity were examined by analyzing a group of 31 anthocyanidin/anthocyanin reference standards with ultra-high performance liquid chromatography-diode array detector (UHPLC-DAD). The substitution groups on aglycones were found to associate with molar absorptivity variations, often neglected in anthocyanin quantitation, resulting in significant analytical errors. A simple yet comprehensive strategy based on the molar relative response factors (MRRFs) and a single master reference calibration (i.e., cyanidin-3-glucoside) was proposed to quantify anthocyanins in red cabbage, blueberry, and strawberry samples with improved analytical accuracy. The results indicate this approach provides an effective, inexpensive, and accurate analytical method for anthocyanins in food materials without using individual reference standards. MRRFs of 617 anthocyanins/anthocyanidins were calculated, and the information is freely available at https://BotanicalDC.online/anthocyanin/. This study could be critical to developing new reference methods for anthocyanin analysis and harmonizing results and data from various sources.

Variation in Botanical Reference Materials: Similarity of Actaea Racemosa Analyzed by Flow Injection Mass Spectrometry.

BACKGROUND: Botanical reference materials (BRMs) generally account for the species, cultivar, and year and location of harvest that result in variability in the chemical composition that may lead to statistically significant differences using chemometric methods. OBJECTIVE: To compare the chemical composition of five species of Actaea root BRMs, four herbal sources of A. racemosa root BRMs, and A. racemosa BRMS, and commercial roots and supplements using chemometric methods and selected pre-processing approaches. METHOD: Samples were analyzed by flow injection mass spectrometry (FIMS), principal component analysis (PCA), and factorial multivariate analysis of variance (mANOVA). RESULTS: Statistically significant (P = 0.05) compositional differences were found between three genera (Actaea, Panax, and Ginkgo), five species of Actaea (A. racemosa, A. cimicifuga, A. dahurica, A. pachypoda, and A. rubra) root BRMs, four herbal sources of A. racemosa root BRMs, and A. racemosa BRMS and commercial roots and supplements. The variability of 6% of the BRM variables was found to be quantitatively conserved and reduced the compositional differences between the four sources of root BRMs. Compositional overlap of A. racemosa and other Actaea BRMs was influenced by variation in technical repeats, pre-processing methods, selection of variables, and selection of confidence limits. Sensitivity ranged from 94 to 97% and specificity ranged from 21 to 89% for the pre-processing protocols tested. CONCLUSIONS: Environmental, genetic, and chemometric factors can influence discrimination between species and authentic botanical reference materials. HIGHLIGHTS: Frequency distribution plots derived from soft independent modeling of class analogy provide excellent means for understanding the impact of experimental factors.

Mouse Choroid Proteome Revisited: Focus on Aging.

Age is a major risk factor for age-related macular degeneration (AMD), and age has a role in the disease phenotypes of heritable macular dystrophies. The proteomes of C57Bl6/J mouse choroids at 2 ages were analyzed to identify biochemical processes affected by aging. Proteins of interest were identified as those contributing most to the variance in principal component analysis and those showing the largest significant differences between ages. These proteins implicated altered ECM composition, immune system function, and lipid metabolism.

Botanical Authentication Using One-Class Modeling.

BACKGROUND: Authentication methods are necessary to guarantee the integrity of botanical supplements and their ingredients. In 2012, AOAC International published "Guidelines for Validation of Botanical Identification Methods" however these guidelines proved rather cumbersome. OBJECTIVE: Develop a simpler method for validatation based on one-class modeling that only considers authentic materials. METHODS: One-class modeling uses chemometric analysis based on soft independent modeling of class analogy and the specific pre-processing steps of sample vector normalization and autoscaling. RESULTS: Any unknown sample can be judged authentic or adulterated based on its agreement with the profile of the authentic samples. The sensitivity and accuracy of one-class modeling is improved using sample vector normalization and autoscaling. The limit of detection for any variable is statistically predictable. CONCLUSION: One-class modeling offers a simple approach to authentication and is applicable to any non-targeted analytical method. Only the characteristics of the authentic samples are necessary and no specification of an adulterant is necessary. HIGHLIGHTS: One-class modeling offers a simple approach to authentication and is easily implemented using any chemometrics platform.

Multi-Glycomic Characterization of Fiber from AOAC Methods Defines the Carbohydrate Structures.

Dietary fiber has long been known to be an essential component of a healthy diet, and recent investigations into the gut microbiome-health paradigm have identified fiber as a prime determinant in this interaction. Further, fiber is now known to impact the gut microbiome in a structure-specific manner, conferring differential bioactivities to these specific structures. However, current analytical methods for food carbohydrate analysis do not capture this important structural information. To address this need, we utilized rapid-throughput LC-MS methods to develop a novel analytical pipeline to determine the structural composition of soluble and insoluble fiber fractions from two AOAC methods (991.43 and 2017.16) at the total monosaccharide, glycosidic linkage, and free saccharide level. Two foods were chosen for this proof-of-concept study: oats and potato starch. For oats, both AOAC methods gave similar results. Insoluble fiber was found to be comprised of linkages corresponding to ß-glucan, arabinoxylan, xyloglucan, and mannan, while soluble fiber was found to be mostly ß-glucan, with small amounts of arabinogalactan. For raw potato starch, each AOAC method gave markedly different results in the soluble fiber fractions. These observed differences are attributable to the resistant starch content of potato starch and the different starch digestion conditions used in each method. Together, these tools are a means to obtain the complex structures present within dietary fiber while retaining "classical" determinations such as soluble and insoluble fiber. These efforts will provide an analytical framework to connect gravimetric fiber determinations with their constituent structures to better inform gut microbiome and clinical nutrition studies.

Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research.

Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.

Identification of High and Low Branched-Chain Fatty Acid-Producing Phenotypes in Holstein Cows following High-Forage and Low-Forage Diets in a Crossover Designed Trial.

BACKGROUND: Branched-chain fatty acids (BCFAs) are rumen-derived fatty acids comprising ∼2% of bovine-milk fatty acids. BCFAs possess anti-inflammatory properties and enriching the BCFA content of bovine milk may provide human health benefits. OBJECTIVE: We determined whether forage content impacts the BCFA content of milk from Holstein cows and identified fatty acid phenotypes in high vs. low BCFA-containing milks. METHODS: Holstein cows (n = 62), fed for 67 d in a crossover design, consumed a diet with high forage and low concentrate (HF:C) and a diet with low forage and high concentrate (LF:C). Milk samples were collected at the end of each treatment period and fatty acid content determined. Paired t-tests, 1-factor ANOVA, sparse partial least-squares discriminant analysis (sPLSDA), and Pearson's correlation analysis were used to analyze the data. RESULTS: The total milk fatty acid concentration for cows fed the HF:C diet was greater than that of cows fed the LF:C diet (4.2 ± 0.7 g/100 mL vs. 3.9 ± 0.9 g/100 mL). sPLSDA demonstrated separation of the dietary treatments, with BCFAs and odd-chain fatty acids as primary determinants. Total BCFA content in milk fat was elevated by HF:C intake compared with LF:C intake (1.80 vs. 1.68%). Quintile separation of high vs. low BCFA milks resulted in 4 groups: HF:C /low BCFAs, HF:C /high BCFAs; LF:C /low BCFAs, and LF:C /high BCFAs. Milks from the high BCFA quintiles had lower palmitic acid content (29.6% vs. 34.4%) but higher oleic acid content than milks from the low BCFA quintiles (19.7% vs. 17.0%). Some cows were identified as high BCFA producers or low BCFA producers regardless of diet. CONCLUSIONS: BCFA content of milk is diet-sensitive but variation in responses exists. The potential to produce milk with high BCFA content and lower SFA content needs further study.

USDA's FoodData Central: what is it and why is it needed today?

FoodData Central (FDC) is the center of the USDA-based food-composition information web. It is an integrated data system that presently provides-in 1 place-5 distinct types of data containing information on food and nutrient profiles. Each data type has a unique purpose. Two of the data types-Foundation Foods (FF) and Experimental Foods (EF)-represent "a bridge to the future" in food and nutrient composition. They provide data and metadata that have never previously been available from a database. The other 3 data types are well established and familiar to many users: Standard Reference (SR) Legacy, Food and Nutrient Database for Dietary Studies (FNDDS), and Global Branded Foods Products Database (GBFPD). After >100 y of maintaining food-composition data within the USDA, it was clear that change was needed to respond to the rapid increase in the number and variety of foods in the food supply, evolution of analytical approaches, and new agricultural practices and products. FDC is USDA's answer to the challenge of providing reliable, web-based, transparent, and easily accessible information about the nutrients and other components of foods to meet the increasingly diverse needs of many audiences, including public health professionals, agricultural and environmental researchers, policy makers, nutrition professionals, health care providers, product developers, and the public at large.

Analytical Challenges and Metrological Approaches to Ensuring Dietary Supplement Quality: International Perspectives.

The increased utilization of metrology resources and expanded application of its' approaches in the development of internationally agreed upon measurements can lay the basis for regulatory harmonization, support reproducible research, and advance scientific understanding, especially of dietary supplements and herbal medicines. Yet, metrology is often underappreciated and underutilized in dealing with the many challenges presented by these chemically complex preparations. This article discusses the utility of applying rigorous analytical techniques and adopting metrological principles more widely in studying dietary supplement products and ingredients, particularly medicinal plants and other botanicals. An assessment of current and emerging dietary supplement characterization methods is provided, including targeted and non-targeted techniques, as well as data analysis and evaluation approaches, with a focus on chemometrics, toxicity, dosage form performance, and data management. Quality assessment, statistical methods, and optimized methods for data management are also discussed. Case studies provide examples of applying metrological principles in thorough analytical characterization of supplement composition to clarify their health effects. A new frontier for metrology in dietary supplement science is described, including opportunities to improve methods for analysis and data management, development of relevant standards and good practices, and communication of these developments to researchers and analysts, as well as to regulatory and policy decision makers in the public and private sectors. The promotion of closer interactions between analytical, clinical, and pharmaceutical scientists who are involved in research and product development with metrologists who develop standards and methodological guidelines is critical to advance research on dietary supplement characterization and health effects.

Comparison of phytochemical composition of Ginkgo biloba extracts using a combination of non-targeted and targeted analytical approaches.

Ginkgo biloba extract (GbE) is a dietary supplement derived from an ethanolic extract of Ginkgo biloba leaves. Unfinished bulk GbE is used to make finished products that are sold as dietary supplements. The variable, complex composition of GbE makes it difficult to obtain consistent toxicological assessments of potential risk. The National Toxicology Program (NTP) observed hepatotoxicity in its rodent studies of a commercially available, unfinished GbE product, but the application of these results to the broader GbE supplement market is unclear. Here, we use a combination of non-targeted and targeted chromatographic and spectrophotometric methods to obtain profiles of 24 commercially available finished GbE products and unfinished standardized and unstandardized extracts with and without hydrolysis, then used principal component analysis to group unfinished products according to their similarity to each other and to National Institute of Standards and Technology (NIST) standard reference materials (SRM), and the finished products. Unfinished products were grouped into those that were characteristic and uncharacteristic of standardized GbE. Our work demonstrates that different analytical approaches produced similar classifications of characteristic and uncharacteristic products in unhydrolyzed samples, but the distinctions largely disappeared once the samples were hydrolyzed. Using our approach, the NTP GbE was most similar to two unfinished GbE products classified as characteristic, finished products, and the NIST GbE SRM. We propose that a simple analysis for the presence, absence, or amounts of compounds unique to GbE in unhydrolyzed samples could be sufficient to determine a sample's authenticity.Graphical abstract.

Characterization of Maca (Lepidium meyenii/Lepidium peruvianum) Using a Mass Spectral Fingerprinting, Metabolomic Analysis, and Genetic Sequencing Approach.

Maca (Lepidium meyenii, synonym L. peruvianum) was analyzed using a systematic approach employing principal component analysis of flow injection mass spectrometry fingerprints (no chromatographic separation) to guide the selection of samples for metabolite profiling and DNA next generation sequencing. Samples consisted of 39 commercial maca supplements from 11 manufacturers, 31 unprocessed maca tubers grown in Peru and China, and a historic non-tuber maca sample from Peru. Principal component analysis of flow injection mass spectrometry fingerprints initially placed all the maca samples in three classes with similar chemical composition: commercial maca samples, tubers grown in Peru, and tubers grown in China. Metabolite profiling identified 67 compounds in the negative mode and 51 compounds in the positive mode. Compounds identified by metabolite profiling (macamides, glucosinolates, amino acids, fatty acids, polyunsaturated fatty acids, saccharides, imidazoles) were then used to identify ions in the flow injection mass spectrometry fingerprints. The tuber fingerprints were analyzed by factorial multivariate analysis of variance revealing that black, red, and yellow maca from Peru and black and yellow maca from China were compositionally different with respect to color and country. Critical ions were identified that allowed for the differentiation of maca between colors from the same country or between two countries with the same color. Genetically, all samples were confirmed to be L. meyenii based on next generation sequencing at three gene regions (ITS2, psbA, and trnL) and comparison to recorded sequences of vouchered standards.

Identification of adulteration in botanical samples with untargeted metabolomics.

Adulteration remains an issue in the dietary supplement industry, including botanical supplements. While it is common to employ a targeted analysis to detect known adulterants, this is difficult when little is known about the sample set. With this study, untargeted metabolomics using liquid chromatography coupled to ultraviolet-visible spectroscopy (LC-UV) or high-resolution mass spectrometry (LC-MS) was employed to detect adulteration in botanical dietary supplements. A training set was prepared by combining Hydrastis canadensis L. with a known adulterant, Coptis chinensis Franch., in ratios ranging from 5 to 95% adulteration. The metabolomics datasets were analyzed using both unsupervised (principal component analysis and composite score) and supervised (SIMCA) techniques. Palmatine, a known H. canadensis metabolite, was quantified as a targeted analysis comparison. While the targeted analysis was the most sensitive method tested in detecting adulteration, statistical analyses of the untargeted metabolomics datasets detected adulteration of the goldenseal samples, with SIMCA providing the greatest discriminating potential. Graphical abstract.

Authentication of black cohosh (Actaea racemosa) dietary supplements based on chemometric evaluation of hydroxycinnamic acid esters and hydroxycinnamic acid amides.

Ester and amide derivatives of hydroxycinnamic acids are found in black cohosh (Actaea racemosa) and other Actaea plants. These two compound groups were evaluated for authentication of black cohosh dietary supplements. The hydroxycinnamic acid esters (HCAE) were profiled by ultra-performance liquid chromatography-photodiode array detection (UPLC-PDA). The hydroxycinnamic acid amides (HCAA) were acquired simultaneously by mass spectrometry-multiple reaction monitoring (UPLC-MRM) mode. In contrast with the traditional HCAE method using 8 compounds, profiles of HCAA using only 4 feruloyl dopamine-O-hexosides was more convenient for peak by peak comparison. Partial least square discriminant analysis (PLS-DA) was applied to both HCAE and HCAA datasets. Authenticated plant samples of five Actaea species were randomly divided into training and test sets to build and validate the two PLS-DA models. Both models provided reasonable estimates for the classification of A. racemosa and other Actaea plant samples. However, HCAA model performs better in sensitivity, specificity, and accuracy. Assessment of supplement samples provided quite different results for the solid and liquid dietary supplement samples, indicating the dosage form could affect the composition of marker compounds. Graphical abstract.

How similar is similar enough? A sufficient similarity case study with Ginkgo biloba extract.

Botanical dietary supplements are complex mixtures that can be highly variable in composition and quality, making safety evaluation difficult. A key challenge is determining how diverse products in the marketplace relate to chemically and toxicologically characterized reference samples (i.e., how similar must a product be in order to be well-represented by the tested reference sample?). Ginkgo biloba extract (GBE) was used as a case study to develop and evaluate approaches for determining sufficient similarity. Multiple GBE extracts were evaluated for chemical and biological-response similarity. Chemical similarity was assessed using untargeted and targeted chemistry approaches. Biological similarity was evaluated using in vitro liver models and short-term rodent studies. Statistical and data visualization methods were then used to make decisions about the similarity of products to the reference sample. A majority of the 26 GBE samples tested (62%) were consistently determined to be sufficiently similar to the reference sample, while 27% were different from the reference GBE, and 12% were either similar or different depending on the method used. This case study demonstrated that approaches to evaluate sufficient similarity allow for critical evaluation of complex mixtures so that safety data from the tested reference can be applied to untested materials.

Variance of Commercial Powdered Milks Analyzed by Proton Nuclear Magnetic Resonance and Impact on Detection of Adulterants.

Proton nuclear magnetic resonance spectra for 66 commercial powdered milk samples were analyzed by principal component analysis, soft independent modeling of class analogy, and pooled, crossed analysis of variance. It was found that the sample type (skim milk powder or non-fat dry milk), the supplier, the production site, the processing temperature (high, medium, or low temperature), and the day of analysis provided statistically significant sources of variation. Interestingly, inexact alignment (deviations of ±0.002 ppm) of the spectral reference peak was a significant source of variation, and fine alignment was necessary before the variation arising from the other experimental factors could be accurately evaluated. Using non-targeted analysis, the lowest detectable adulteration for dicyandiamide, melamine, and sucrose was 0.05%, the lowest detectable adulteration for maltodextrin and urea was 0.5%, the lowest detectable adulteration for ammonium sulfate and whey was 5%, and the lowest adulteration for soy protein isolate was undetectable using methods described herein. The measurement of variance and detection of adulteration were relatively unaffected by the resolution. Similar results were obtained with unbinned data (0.0003 ppm resolution) and binning of 333 data points (0.1 ppm resolution).

The Dietary Supplement Label Database: Recent Developments and Applications.

Objective: To describe the history, key features, recent enhancements, and common applications of the Dietary Supplement Label Database (DSLD). Background and History: Although many Americans use dietary supplements, databases of dietary supplements sold in the United States have not been widely available. The DSLD, an easily accessible public-use database was created in 2008 to provide information on dietary supplement composition for use by researchers and consumers. Rationale: Accessing current information easily and quickly is crucial for documenting exposures to dietary supplements because they contain nutrients and other bioactive ingredients that may have beneficial or adverse effects on human health. This manuscript details recent developments with the DSLD to achieve this goal and provides examples of how the DSLD has been used. Recent Developments: With periodic updates to track changes in product composition and capture new products entering the market, the DSLD currently contains more than 71,000 dietary supplement labels. Following usability testing with consumer and researcher user groups completed in 2016, improvements to the DSLD interface were made. As of 2017, both a desktop and mobile device version are now available. Since its inception in 2008, the use of the DSLD has included research, exposure monitoring, and other purposes by users in the public and private sectors. Future Directions: Further refinement of the user interface and search features to facilitate ease of use for stakeholders is planned. Conclusions: The DSLD can be used to track changes in product composition and capture new products entering the market. With over 71,000 DS labels it is a unique resource that policymakers, researchers, clinicians, and consumers may find valuable for multiple applications.