Authentic Standards Research Articles

Predicting hygroscopic growth of organosulfur aerosol particles using COSMOtherm

Abstract. Organosulfur (OS) compounds are important sulfur species in atmospheric aerosol particles, due to the reduction of global inorganic sulfur emissions. Understanding the physicochemical properties, such as hygroscopicity, of OS compounds is important for predicting future aerosol–cloud–climate interactions. However, their hygroscopicity is not yet well understood due to the scarcity of authentic standards. In this work, we investigated a group of OS compounds with short carbon chains (C1–C5) and oxygen-containing functional groups in the form of sodium, potassium, or ammonium salts and their mixtures with ammonium sulfate. The hygroscopic growth factors (HGFs) of these OS compounds have been experimentally studied. Here, the HGFs were calculated from mass fraction of water that was computed using the conductor-like screening model for real solvents (COSMO-RS). A good agreement was found between the model-estimated and experimental HGFs for the studied OS compounds. This quantum-chemistry-based approach for HGF estimation will open up the possibility of investigating the hygroscopicity of other OS compounds present in the atmosphere.

EMBL-MCF 2.0: an LC-MS/MS method and corresponding library for high-confidence targeted and untargeted metabolomics using low-adsorption HILIC chromatography

IntroductionOver the past two decades, liquid chromatography-mass spectrometry (LC-MS)-based metabolomics has experienced significant growth, playing a crucial role in various scientific disciplines. However, despite these advance-ments, metabolite identification (MetID) remains a significant challenge. To address this, stringent MetID requirements were established, emphasizing the necessity of aligning experimental data with authentic reference standards using multiple criteria. Establishing dependable methods and corresponding libraries is crucial for instilling confidence in MetID and driving further progress in metabolomics.ObjectiveThe EMBL-MCF 2.0 LC-MS/MS method and public library was designed to facilitate both targeted and untargeted metabolomics with exclusive focus on endogenous, polar metabolites, which are known to be challenging to analyze due to their hydrophilic nature. By accompanying spectral data with robust retention times obtained from authentic standards and low-adsorption chromatography, high confidence MetID is achieved and accessible to the metabolomics community.MethodsThe library is built on hydrophilic interaction liquid chromatography (HILIC) and state-of-the-art low adsorption LC hardware. Both high-resolution tandem mass spectra and manually optimized multiple reaction monitoring (MRM) transitions were acquired on an Orbitrap Exploris 240 and a QTRAP 6500+, respectively.ResultsImplementation of biocompatible HILIC has facilitated the separation of isomeric metabolites with significant enhancements in both selectivity and sensitivity. The resulting library comprises a diverse collection of more than 250 biologically relevant metabolites. The methodology was successfully applied to investigate a variety of biological matrices, with exemplary findings showcased using murine plasma samples.ConclusionsOur work has resulted in the development of the EMBL-MCF 2.0 library, a powerful resource for sensitive metabolomics analyses and high-confidence MetID. The library is freely accessible and available in the universal .msp file format under the CC-BY 4.0 license: mona.fiehnlab.ucdavis.edu https://mona.fiehnlab.ucdavis.edu/spectra/browse?query=exists(tags.text:%27EMBL-MCF_2.0_HRMS_Library%27), EMBL-MCF 2.0 HRMS https://www.embl.org/groups/metabolomics/instrumentation-and-software/#MCF-library.

A New Validated Method for Rapid Determination of OLEU Concentration in Dietary Supplements: Comparison with Total Phenol Content and Antioxidant Activity

The market for olive leaf dietary supplements is expanding rapidly and is valued at $437.15 million today. However, information on the control of these products is sketchy and the origin and variety of olives are rarely stated. The aim of this research was to validate a simple and rapid screening method for oleuropein determination in olive leaf dietary supplements. A matrix blank was prepared by removal of oleuropein from a mixture of dietary supplements and the matrix was then spiked with known concentrations to create a spiked matrix calibration curve in the range 5 - 40% oleuropein. Five replicate extractions and analyses of the matrix standards were carried out over 10 days. Precision was less than 6% RSD and linearity was demonstrated by the Fischer test. Extraction recovery was > 90% and there was a strong linear relationship between authentic and matrix standards. All tested products conformed to the label claim which was strongly correlated with total polyphenols measured by the Folin-Ciocalteau method. Antioxidant activity was measured by the DPPH assay and was found to be strongly correlated with total phenol content and oleuropein concentration.

A simplified tutorial on charged aerosol detection: Understanding the basics, optimization, and troubleshooting

The charged aerosol detector (CAD) measures the overall charge deposited on aerosolized particles to produce a signal proportional to the mass of analyte present, which applies to compounds with or without a chromophore. A significant benefit of CAD is the ability to quantitate a wide range of non-volatile compounds in absence of their authentic standards due to uniform response factor for such analytes. CAD is also a valuable tool to help detect and/or quantitate compounds with poor or no UV absorption. These can include salts, impurities, and a variety of other types of analytes.In this tutorial, fundamental principles of CAD and its utilization, troubleshooting, and maintenance will be demonstrated to ensure proper CAD usage. Successful operation of CAD includes optimizing power function value (PFV) to allow for a broader dynamic range and improve uniformity of response. The use of an inverse gradient (admixed post-column) enables more accurate quantitation, when employing a gradient analysis method. Several troubleshooting strategies, including diagnosing inverse gradient pump organic solvent delivery and determining volume match/mismatch between the inverse gradient and system pumps, will be presented along with important aspects of operating a CAD. Lastly, ensuring reliable results involves monitoring the performance of CAD over time to understand whether it is working sufficiently or if maintenance is required.

Concordant inter-laboratory derived concentrations of ceramides in human plasma reference materials via authentic standards

In this community effort, we compare measurements between 34 laboratories from 19 countries, utilizing mixtures of labelled authentic synthetic standards, to quantify by mass spectrometry four clinically used ceramide species in the NIST (National Institute of Standards and Technology) human blood plasma Standard Reference Material (SRM) 1950, as well as a set of candidate plasma reference materials (RM 8231). Participants either utilized a provided validated method and/or their method of choice. Mean concentration values, and intra- and inter-laboratory coefficients of variation (CV) were calculated using single-point and multi-point calibrations, respectively. These results are the most precise (intra-laboratory CVs ≤ 4.2%) and concordant (inter-laboratory CVs < 14%) community-derived absolute concentration values reported to date for four clinically used ceramides in the commonly analyzed SRM 1950. We demonstrate that calibration using authentic labelled standards dramatically reduces data variability. Furthermore, we show how the use of shared RM can correct systematic quantitative biases and help in harmonizing lipidomics. Collectively, the results from the present study provide a significant knowledge base for translation of lipidomic technologies to future clinical applications that might require the determination of reference intervals (RIs) in various human populations or might need to estimate reference change values (RCV), when analytical variability is a key factor for recall during multiple testing of individuals.

Quantification Approaches in Non-Target LC/ESI/HRMS Analysis: An Interlaboratory Comparison.

Nontargeted screening (NTS) utilizing liquid chromatography electrospray ionization high-resolution mass spectrometry (LC/ESI/HRMS) is increasingly used to identify environmental contaminants. Major differences in the ionization efficiency of compounds in ESI/HRMS result in widely varying responses and complicate quantitative analysis. Despite an increasing number of methods for quantification without authentic standards in NTS, the approaches are evaluated on limited and diverse data sets with varying chemical coverage collected on different instruments, complicating an unbiased comparison. In this interlaboratory comparison, organized by the NORMAN Network, we evaluated the accuracy and performance variability of five quantification approaches across 41 NTS methods from 37 laboratories. Three approaches are based on surrogate standard quantification (parent-transformation product, structurally similar or close eluting) and two on predicted ionization efficiencies (RandFor-IE and MLR-IE). Shortly, HPLC grade water, tap water, and surface water spiked with 45 compounds at 2 concentration levels were analyzed together with 41 calibrants at 6 known concentrations by the laboratories using in-house NTS workflows. The accuracy of the approaches was evaluated by comparing the estimated and spiked concentrations across quantification approaches, instrumentation, and laboratories. The RandFor-IE approach performed best with a reported mean prediction error of 15× and over 83% of compounds quantified within 10× error. Despite different instrumentation and workflows, the performance was stable across laboratories and did not depend on the complexity of water matrices.

New Bacterial Aryl Sulfotransferases: Effective Tools for Sulfation of Polyphenols.

The preparation of pure metabolites of bioactive compounds, particularly (poly)phenols, is essential for the accurate determination of their pharmacological profiles in vivo. Since the extraction of these metabolites from biological material is tedious and impractical, they can be synthesized enzymatically in vitro by bacterial PAPS-independent aryl sulfotransferases (ASTs). However, only a few ASTs have been studied and used for (poly)phenol sulfation. This study introduces new fully characterized recombinant ASTs selected according to their similarity to the previously characterized ASTs. These enzymes, produced in Escherichia coli, were purified, biochemically characterized, and screened for the sulfation of nine flavonoids and two phenolic acids using p-nitrophenyl sulfate. All tested compounds were proved to be substrates for the new ASTs, with kaempferol and luteolin being the best converted acceptors. ASTs from Desulfofalx alkaliphile (DalAST) and Campylobacter fetus (CfAST) showed the highest efficiency in the sulfation of tested polyphenols. To demonstrate the efficiency of the present sulfation approach, a series of new authentic metabolite standards, regioisomers of kaempferol sulfate, were enzymatically produced, isolated, and structurally characterized.

Annotation of DOM metabolomes with an ultrahigh resolution mass spectrometry molecular formula library

Increased accessibility of liquid chromatography mass spectrometry (LC-MS) metabolomics instrumentation and software have expanded their use in studies of dissolved organic matter (DOM) and exometabolites released by microbes. Current strategies to annotate metabolomes generally rely on matching tandem MS/MS spectra to databases of authentic standards. However, spectral matching approaches typically have low annotation rates for DOM. An alternative approach is to annotate molecular formula based on accurate mass and isotopic fine structure measurements that can be obtained from state-of-the-art ultrahigh resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FT-ICR MS), but instrument accessibility for large metabolomic studies is generally limited. Here, we describe a strategy to annotate exometabolomes obtained from lower resolution LC-MS systems by matching metabolomic features to a molecular formula library generated for a representative sample analyzed by LC 21T- FT-ICR MS. The molecular formula library approach successfully annotated 53% of exometabolome features of the marine diatom Phaeodactylum tricornutum – a nearly ten-fold increase over the 6% annotation rate achieved using a conventional MS/MS approach. There was 94% agreement between assigned formula that were annotated with both approaches, and mass error analysis of the discrepancies suggested that the FT-ICR MS formula assignments were more reliable. Differences in the exometabolome of P. tricornutum grown under iron replete and iron limited conditions revealed 668 significant metabolites, including a suite of peptide-like molecules released by P. tricornutum in response to iron deficiency. These findings demonstrate the utility of FT-ICR MS formula libraries for extending the accuracy and comprehensiveness of metabolome annotations.

Urinary Biomarkers of Strawberry and Blueberry Intake.

Introduction There is increasing interest in food biomarkers to address the shortcomings of self-reported dietary assessments. Berries are regarded as important fruits worldwide; however, there are no well-validated biomarkers of berry intake. Thus, the objective of this study is to identify urinary biomarkers of berry intake. Methods For the discovery study, participants consumed 192 g strawberries with 150 g blueberries, and urine samples were collected at 2, 4, 6, and 24 h post-consumption. A dose-response study was performed, whereby participants consumed three portions (78 g, 278 g, and 428 g) of mixed strawberries and blueberries. The urine samples were profiled by an untargeted LC-MS metabolomics approach in the positive and negative modes. Results Statistical analysis of the data revealed that 39 features in the negative mode and 15 in the positive mode significantly increased between fasting and 4 h following mixed berry intake. Following the analysis of the dose-response data, 21 biomarkers showed overall significance across the portions of berry intake. Identification of the biomarkers was performed using fragmentation matches in the METLIN, HMDB, and MoNA databases and in published papers, confirmed where possible with authentic standards. Conclusions The ability of the panel of biomarkers to assess intake was examined, and the predictability was good, laying the foundations for the development of biomarker panels.

Sequencing Sialic Acid Positioning in Gangliosides by High-Resolution Cyclic Ion Mobility Separations Coupled with Multiple Collision-Induced Dissociation-Based Tandem Mass Spectrometry Strategies.

Gangliosides, a diverse class of glycosphingolipids, are highly abundant in neural tissue and have been implicated in numerous aging-related diseases. Their characterization with methods such as liquid chromatography-tandem mass spectrometry is often precluded by their structural complexity, isomeric heterogeneity, and lack of commercially available authentic standards. In this work, we coupled high-resolution cyclic ion mobility spectrometry with multiple collision-induced dissociation-based tandem mass spectrometry strategies to sequence the sialic acid positions in various ganglioside isomers. Initially, as a proof-of-concept demonstration, we were able to characterize the sialic acid positions in several GD1 and GT1 species. From there, we extended our approach to identify the location of N-glycolylneuraminic acid (NeuGc) residues in previously uncharacterized GD1 and GQ1 isomers. Our results highlight the potential of this presented methodology for the de novo characterization of gangliosides within complex biological matrices without the need for authentic standards.

Novel odd-chain cyclopropane fatty acids: detection in a mammalian lipidome and uptake by hepatosplanchnic tissues

Microbe-produced molecules (xenometabolites) found in foods or produced by gut microbiota are increasingly implicated in microbe-microbe and microbe-host communication. Xenolipids, in particular, are a class of metabolites for which the full catalog remains to be elaborated in mammalian systems. We and others have observed that cis-3,4-methylene-heptanoylcarnitine is a lipid derivative that is one of the most abundant medium-chain acylcarnitines in human blood, hypothesized to be a product of incomplete β-oxidation of one or more “odd-chain” long-chain cyclopropane fatty acids (CpFAs). We deduced two possible candidates, cis-11,12-methylene-pentadecanoic acid (cis-11,12-MPD) and cis-13,14-methylene-heptadecanoic acid (cis-13,14-MHD). Authentic standards were synthesized: cis-11-pentadecenoic acid and cis-13-heptadecenoic acid were generated (using Jones reagent) from cis-11-pentadecene-1-ol and cis-13-heptadecene-1-ol, respectively, and these were converted to CpFAs via a reaction involving diiodomethane. Using these standards in mass spectrometry analyses, we determined the presence/absence of cis-11,12-MPD and cis-13,14-MHD in archived piglet biospecimens. Both CpFAs were detected in rectal contents of sow and soy-fed piglets. Archived mass spectra were analyzed post hoc from a second independent study that used tissue-specific catheterization to monitor net metabolite flux in growing pigs. This confirmed the presence of both CpFAs in plasma and revealed a significant net uptake of the odd-chain CpFAs across the splanchnic tissue bed and liver. The results confirm that the novel xenolipids cis-11,12-MPD and cis-13,14-MHD can be components of the mammalian lipidome and are viable candidate precursors of cis-3,4-methylene-heptanoylcarnitine produced from partial β-oxidation in liver or other tissues.

A Radioactivity-mass Spectrometry Calibration Method Coupled with Biosynthesis to Generate a Metabolite Standard for Enzyme Kinetics Studies

In early stages of drug development, the absence of authentic metabolite standards often results in semi-quantitative measurements of metabolite formation in reaction phenotyping studies using mass spectrometry (MS), leading to inaccuracies in the determination of enzyme kinetic parameters, such as the Michaelis constant (Km). Moreover, it is impossible to ascertain the maximum rate of enzyme-catalyzed reactions (kcat or Vmax). The use of radiolabeled parent compounds can circumvent this problem. However, radiometric detection exhibits significantly lower sensitivity compared to MS. To address these challenges, we have developed a stepwise approach that leverages biosynthesized radiolabeled and non-radiolabeled metabolites as standards, enabling accurate determination of Km, kcat or Vmax without the need for authentic metabolite standards. This approach, using the carbon-14 [14C] labeled metabolite to calibrate the unlabeled metabolite (14C calibration method), combines radiometric with LC-MS/MS detection to generate both [14C]-labeled and unlabeled metabolite standard curves to ensure that the sample concentrations measured are accurately quantitated. Two case studies were presented to demonstrate the utility of this method. We first compared the accuracy of the 14C calibration method to the use of authentic standards for quantitating imipramine metabolites. Next, we biosynthesized and quantitated the metabolites of BI 894416 using 14C calibration method and evaluated the enzyme kinetics of metabolite formation. The Km values of the metabolite formation demonstrated substantially improved accuracy compared to MS semi-quantitation. Moreover, the 14C calibration method offers a streamlined approach to prepare multiple metabolite standards from a single biosynthesis, reducing the time required for structure elucidation and metabolite synthesis.

Development of a cyclic ion mobility spectrometry-mass spectrometry-based collision cross-section database of permethylated human milk oligosaccharides.

Human milk oligosaccharides (HMOs) are an important class of biomolecules responsible for the healthy development of the brain-gut axis of infants. Unfortunately, their accurate characterization is largely precluded due to a variety of reasons - there are over 200 possible HMO structures whereas only 10s of these are available as authentic analytical standards. Furthermore, their isomeric heterogeneity stemming from their many possible glycosidic linkage positions and corresponding α/β anomericities further complicates their analyses. While liquid chromatography coupled to tandem mass spectrometry remains the gold standard for HMO analyses, it often times cannot resolve all possible isomeric species and thus warrants the development of other orthogonal approaches. High-resolution ion mobility spectrometry coupled to mass spectrometry has emerged as a rapid alternative to condensed-phase separations but largely has remained limited to qualitative information related to the resolution of isomers. In this work, we have assessed the use of permethylation to improve both the resolution and sensitivity of HMO analyses with cyclic ion mobility separations coupled with mass spectrometry. In addition to this, we have developed the first-ever high-resolution collision cross-section database for permethylated HMOs using our previously established calibration protocol. We envision that this internal reference database generated from high-resolution cyclic ion mobility spectrometry-mass spectrometry will greatly aid in the accurate characterization of HMOs and provide a valuable, orthogonal, approach to existing liquid chromatography-tandem mass spectrometry-based methods.

Comprehensive nontargeted analysis of fluorosurfactant byproducts and reaction products in wastewater from semiconductor manufacturing

Semiconductor manufacturing employs per- and polyfluoroalkyl substances (PFAS) as fluoroasurfactants to enhance the quality of photolithography lines. Our research, employing a fragment-based approach to investigate nontarget PFAS, overcomes conventional homologous series limitations. In a mixture of PFAS standards used as a quality control sample, 92% (36 out of 39 compounds spanning 11 compound classes) were detectable through the fragment-based nontarget procedure. This indicates the effectiveness of this approach in identifying the hydrophobic and hydrophilic characteristics of various fluorosurfactants. Eighty-three PFAS were detected in wastewater and effluent samples from semiconductor industry, including 29 newly discovered compounds, categorized into three groups. First, besides detecting perfluorobutane sulfonamido ethanol (FBSE), various fluoroalkyl chain structures of FBSE derivatives were initially identified in wastewater. These include perfluorobutyl ether sulfonamido ethanol, unsaturated FBSE, and hydrogen-substituted FBSE. These derivatives were also detected in trace amounts in commercial authentic standards of FBSE. To quantify their presence, we analyzed the FBSE derivatives from the authentic standard, and the relative proportions of these derivatives contribute to approximately 0.5%. This suggests that the FBSE derivative series detected in wastewater may arise from byproducts of chemical formulations used in the manufacturing of semiconductors. Second, transformation products from FBSE during oxidation, including the first identified intermediate transformation compounds, perfluorobutane sulfonamido acetaldehyde and its hydrate, were discovered. Third, diverse reaction products are generated from the intricate processes of semiconductor manufacturing, which utilize strong acids, bases, and solvents under UV light or heated conditions. These processes include the formation of PFAS-related compounds through hydration, sulfonation, oxidation, and nitrification. This study revealed 25 isomeric PFAS, encompassing headgroup isomers and functional tail group isomers. These findings underscore the importance of comprehending diverse reactions and the overall emission compositions of PFAS in semiconductor wastewater, highlighting its complexity and presenting challenges for subsequent wastewater treatment.

Identification of Predictive Biomarkers of Lameness in Transition Dairy Cows.

The aim of this study was to identify with a high level of confidence metabolites previously identified as predictors of lameness and understand their biological relevance by carrying out pathway analyses. For the dairy cattle sector, lameness is a major challenge with a large impact on animal welfare and farm economics. Understanding metabolic alterations during the transition period associated with lameness before the appearance of clinical signs may allow its early detection and risk prevention. The annotation with high confidence of metabolite predictors of lameness and the understanding of interactions between metabolism and immunity are crucial for a better understanding of this condition. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with authentic standards to increase confidence in the putative annotations of metabolites previously determined as predictive for lameness in transition dairy cows, it was possible to identify cresol, valproic acid, and gluconolactone as L1, L2, and L1, respectively which are the highest levels of confidence in identification. The metabolite set enrichment analysis of biological pathways in which predictors of lameness are involved identified six significant pathways (p < 0.05). In comparison, over-representation analysis and topology analysis identified two significant pathways (p < 0.05). Overall, our LC-MS/MS analysis proved to be adequate to confidently identify metabolites in urine samples previously found to be predictive of lameness, and understand their potential biological relevance, despite the challenges of metabolite identification and pathway analysis when performing untargeted metabolomics. This approach shows potential as a reliable method to identify biomarkers that can be used in the future to predict the risk of lameness before calving. Validation with a larger cohort is required to assess the generalization of these findings.

Rats exposed to Alternaria toxins in vivo exhibit altered liver activity highlighted by disruptions in riboflavin and acylcarnitine metabolism

Natural toxins produced by Alternaria fungi include the mycotoxins alternariol, tenuazonic acid and altertoxins I and II. Several of these toxins have shown high toxicity even at low levels including genotoxic, mutagenic, and estrogenic effects. However, the metabolic effects of toxin exposure from Alternaria are understudied, especially in the liver as a key target. To gain insight into the impact of Alternaria toxin exposure on the liver metabolome, rats (n = 21) were exposed to either (1) a complex culture extract with defined toxin profiles from Alternaria alternata (50 mg/kg body weight), (2) the isolated, highly genotoxic altertoxin-II (ATX-II) (0.7 mg/kg of body weight) or (3) a solvent control. The complex mixture contained a spectrum of Alternaria toxins including a controlled dose of ATX-II, matching the concentration of the isolated ATX-II. Liver samples were collected after 24 h and analyzed via liquid chromatography–high-resolution mass spectrometry (LC-HRMS). Authentic reference standards (> 100) were used to identify endogenous metabolites and exogenous compounds from the administered exposures in tandem with SWATH-acquired MS/MS data which was used for non-targeted analysis/screening. Screening for metabolites produced by Alternaria revealed several compounds solely isolated in the liver of rats exposed to the complex culture, confirming results from a previously performed targeted biomonitoring study. This included the altersetin and altercrasin A that were tentatively identified. An untargeted metabolomics analysis found upregulation of acylcarnitines in rats receiving the complex Alternaria extract as well as downregulation of riboflavin in rats exposed to both ATX-II and the complex mixture. Taken together, this work provides a mechanistic view of Alternari toxin exposure and new suspect screening insights into hardly characterized Alternaria toxins.

Elucidating the Gas-Phase Behavior of Nitazene Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry.

2-Benzylbenzimidazoles, or "nitazenes", are a class of novel synthetic opioids (NSOs) that are increasingly being detected alongside fentanyl analogs and other opioids in drug overdose cases. Nitazenes can be 20× more potent than fentanyl but are not routinely tested for during postmortem or clinical toxicology drug screens; thus, their prevalence in drug overdose cases may be under-reported. Traditional analytical workflows utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) often require additional confirmation with authentic reference standards to identify a novel nitazene. However, additional analytical measurements with ion mobility spectrometry (IMS) may provide a path toward reference-free identification, which would greatly accelerate NSO identification rates in toxicology laboratories. Presented here are the first IMS and collision cross section (CCS) measurements on a set of fourteen nitazene analogs using a structures for lossless ion manipulations (SLIM)-orbitrap MS. All nitazenes exhibited two high intensity baseline-separated IMS distributions, which fentanyls and other drug and druglike compounds also exhibit. Incorporating water into the electrospray ionization (ESI) solution caused the intensities of the higher mobility IMS distributions to increase and the intensities of the lower mobility IMS distributions to decrease. Nitazenes lacking a nitro group at the R1 position exhibited the greatest shifts in signal intensities due to water. Furthermore, IMS-MS/MS experiments showed that the higher mobility IMS distributions of all nitazenes possessing a triethylamine group produced fragment ions with m/z 72, 100, and other low intensity fragments while the lower mobility IMS distributions only produced fragment ions with m/z 72 and 100. The IMS, solvent, and fragmentation studies provide experimental evidence that nitazenes potentially exhibit three gas-phase protomers. The cyclic IMS capability of SLIM was also employed to partially resolve four sets of structurally similar nitazene isomers (e.g., protonitazene/isotonitazene, butonitazene/isobutonitazene/secbutonitazene), showcasing the potential of using high-resolution IMS separations in MS-based workflows for reference-free identification of emerging nitazenes and other NSOs.

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.

Isolation of a new flavonoid from Prasium majus L. with evaluation of its potential biological activities

In line with the importance of Prasium majus L. (Lamiaciatae) in traditional medicine as a calming and sedative remedy, the present study was designed to reveal its chemical constituents and bioactivity potentials. Thus, after extraction and fractionation of the plant material, the obtained butanol fraction (BPm) was subjected to conventional chromatographic separation of its constituents in addition to LC-MS/MS evaluation versus some authentic standards. The study resulted in the isolation and characterisation of 8 compounds, including one new chrysoeriol derivative, majusiode (1). Structural elucidation of all isolated compounds was based on detailed investigation of their spectral data (NMR (1 & 2D), ESI-MS, IR and UV-Vis). HPLC-MS/MS analysis versus authentic samples lead to the detection of 31 constituents, including all 8 isolated compounds. The new compound (1) showed moderate AChE inhibition power (IC50: 163.3 ± 3.4 µg/mL) as compared to the positive control galanthamine (91.4 ± 5.2 µg/mL) and moderate DPPH•/ABTS•+ scavenging power.

Prediction of mass spectrometry ionization efficiency based on COSMO-RS and machine learning algorithms.

Non-targeted analysis of high-resolution mass spectrometry (MS) can identify thousands of compounds, which also gives a huge challenge to their quantification. The aim of this study is to investigate the impact of mass spectrometry ionization efficiency on various compounds in food at different solvent ratios and to develop a predictive model for mass spectrometry ionization efficiency to enable non-targeted quantitative prediction of unknown compounds. This study covered 70 compounds in 14 different mobile phase ratio environments in positive ion mode to analyze the rules of the matrix effect. With the organic phase ratio from low to high, most compounds changed by 1.0 log units in log IE. The addition of formic acid enhanced the signal but also promoted the matrix effect, which often occurred in compounds with strong ionization capacity. It was speculated that the matrix effect was mainly in the form of competitive charge and charged droplet' gasification sites during MS detection. Subsequently, we present a log IE prediction method built using the COSMO-RS software and the artificial neural network (ANN) algorithm to address this difficulty and overcome the shortcomings of previous models, which always ignore the matrix effect. This model was developed following the principles of QSAR modeling recommended by the Organization for Economic Cooperation and Development (OECD). Furthermore, we validated this approach by predicting the log IE of 70 compounds, including those not involved in the log IE model development. The results presented demonstrate that the method we put forward has an excellent prediction accuracy for log IE (R2pred = 0.880), which means that it has the potential to predict the log IE of new compounds without authentic standards.