High-resolution Mass Spectrometry Research Articles

H3trica: Versatile Macrocyclic Chelator for [225Ac]Ac3+ and [155/161Tb]Tb3+ Theranostics.

H3trica is a nonadentate chelating ligand intended for coordinating large radiometal ions, such as those used in nuclear medicine. This chelator, featuring a triaza-18-crown-6 macrocycle with three pendant carboxylic acid functional groups, was synthesized and characterized. Complementary nuclear magnetic resonance (NMR) spectroscopy and high-resolution electrospray-ionization mass spectroscopy (HR-ESI-MS) studies were used to explore the coordination of H3trica with metal ions such as La3+, Y3+ (as a model for Tb3+), and Lu3+ at the bulk scale. Thermodynamic solution studies provided valuable insights, highlighting robust metal complexation of H3trica with La3+, Tb3+, and Lu3+, with the most noteworthy log KML value observed for Tb3+ (log KTbL = 17.08), followed by La3+ (log KLaL = 16.64) and Lu3+ (log KLuL = 16.25). Concentration-dependent radiolabeling studies with [225Ac]Ac3+, [155Tb]Tb3+, and [161Tb]Tb3+ demonstrated rapid complexation (5-30 min) under mild conditions (pH 6-7, 25 °C). Importantly, the radiolabeled complexes exhibited stability during incubation in human serum for one-half-life of the corresponding radiometal. Thus, H3trica emerges as a valuable chelator, demonstrating its potential to coordinate the theranostic couple [225Ac]Ac3+/[155Tb]Tb3+ as well as the powerful terbium quartet ([149/152/155/161Tb]Tb3+) with efficiency and stability.

QC-GN2oMS2: a Graph Neural Net for High Resolution Mass Spectra Prediction.

Predicting the mass spectrum of a molecular ion is often accomplished via three generalized approaches: rules-based methods for bond breaking, deep learning, or quantum chemical (QC) modeling. Rules-based approaches are often limited by the conditions for different chemical subspaces and perform poorly under chemical regimes with few defined rules. QC modeling is theoretically robust but requires significant amounts of computational time to produce a spectrum for a given target. Among deep learning techniques, graph neural networks (GNNs) have performed better than previous work with fingerprint-based neural networks in mass spectra prediction. To explore this technique further, we investigate the effects of including quantum chemically derived information as edge features in the GNN to increase predictive accuracy. The models we investigated include categorical bond order, bond force constants derived from extended tight-binding (xTB) quantum chemistry, and acyclic bond dissociation energies. We evaluated these models against a control GNN with no edge features in the input graphs. Bond dissociation enthalpies yielded the best improvement with a cosine similarity score of 0.462 relative to the baseline model (0.437). In this work we also apply dynamic graph attention which improves performance on benchmark problems and supports the inclusion of edge features. Between implementations, we investigate the nature of the molecular embedding for spectra prediction and discuss the recognition of fragment topographies in distinct chemistries for further development in tandem mass spectrometry prediction.

Fate of Carbamazepine and Its Metabolites in a Soil–Aromatic Plant System

The use of reclaimed wastewater for irrigation could result in the release of pharmaceutically active compounds (PhACs) and their metabolites into the agroecosystem. In this study, we investigated the fate of carbamazepine (CBZ) and its metabolites, with the aim of clarifying their behavior in a soil–plant system in a greenhouse experiment. The research was carried out using irrigation water especially fortified with high doses of CBZ (200 or 600 ppb) in order to evaluate the dynamics of CBZ and its metabolites in the soil and basil organs. The results of the study showed that CBZ is easily absorbed by the aerial part of the basil plant. The soil contained two metabolites of CBZ, namely acridine and carbamazepine-10,11-epoxide, as revealed by high-resolution mass spectrometry analyses. In addition, acridine was found in the aerial parts of basil plants. Furthermore, the greater presence of CBZ and its metabolites in bulk soil indicated a positive role of the basil rhizosphere in the degradation of such compounds or a positive role of the plant in the removal of the contaminant by uptake. Considering the observed morphological parameters and the mean CBZ content in wastewater, significantly lower than that used in the experiment, basil can be considered resistant to the application of irrigation water contaminated with CBZ.

A Quasi Real-Time Evaluation of High-Resolution Mass Spectra of Complex Chlorinated Paraffin Mixtures and Their Transformation Products.

Chlorinated paraffins (CPs) are complex mixtures of polychlorinated n-alkanes with multiple carbon- (C-, nC = 9-30) and chlorine homologues (Cl-, nCl = 3-18). The mass spectrometric analysis of CPs is time-consuming and challenging, especially when interferences between CPs, their transformation products, or from the matrix are numerous. These analytical challenges and the lack of appropriate and accessible data evaluation tools are obstacles to their analysis. CP-Hunter is a web-based, open-access data processing platform for the automatic analysis of mass spectra of CPs and their transformation products. Extracts of two consumer plastic materials and sewage sludge were evaluated with CP-Hunter. C- and Cl-homologue distributions were obtained in quasi-real-time and the posterior calculated fingerprints were in agreement with the ones obtained by traditional methods. However, the data extraction and evaluation time were now reduced from several minutes to seconds. The implemented signal deconvolution method, i.e., to resolve mass spectrometric interferences, provides robust results, even when severe matrix effects are present. CP-Hunter facilitates the untargeted analysis of unknown products and the detection and elimination of false positive signals. Finally, data evaluation with CP-Hunter is performed locally without the transfer of data to external servers. The tool is safe, public, and accessible at https://cphunter.cheminfo.org/.

Exploring formation of turanose in honey via stable isotope labelling and high-resolution mass spectrometry analysis

Turanose, an isomer of sucrose, naturally exists in honey. Previous study indicated that turanose content increased gradually in acacia honey as honeybees brewed honey in the hive. However, it is unclear how turanose is generated in honey. We hypothesised that turanose was produced by enzymes from honeybees and performed a series of simulation experiments to prove this hypothesis. We found turanose in honey was produced by honeybees processing sucrose. Furthermore, we determined that sugar composition of simulated nectar influenced the turanose concentration in honey: when sucrose concentration was below 5%, turanose was difficult to form, whereas high concentration of fructose and limited glucose were beneficial in producing turanose. Using 13C-labelled sucrose tests combined with proteomics analysis, we identified that α-glucosidase converted sucrose to turanose through an intermolecular isomerisation process. This study reveals the formation mechanism of turanose in honey and assists in the scientific control and improvement of honey quality.

Electrochemical investigation, DNA binding, DFT, and molecular docking analysis of phenolic acids isolated from Macrotyloma uniflorum

Macrotyloma uniflorum [M. uniflorum], is the members of the family Fabaceae. It has been demonstrated to have numerous health advantages and is high in nutritional value. The two isolated phenolic acids that are the subject of this study are ferulic acid and cinnamic acid, which are extracted from Macrotyloma uniflorum. NMR spectroscopy, high resolution mass spectrometry (HR-ESI-MS), UV–visible spectroscopy, and infrared (IR) spectroscopy were used to characterize the structures of the isolated compounds. When the separated phenolic acids interacted with CT-DNA, a hypochromic shift was observed. The MTT test on the separated chemicals in Hela cells revealed a higher level of cellular inhibition. The findings confirm the positive biological activities of the extracted phenolic compounds from horse gram seed, which are corroborated by docking experiments.

Synthesis of paeonol hydrazone derivatives and their anti-oomycete, anti-fungal, and nematicidal activities.

The natural product paeonol is a rich and sustainable natural bioresource, and its derivatives have various unique biological efficacy. As is well known, Schiff bases are a class of organic compounds with a wide range of biological activities, including anti-fungal, insecticidal, anti-viral, and nematicidal. To discover biorational natural product-based pesticides, nine intermediates (2-10), 12 sulfonylhydrazones (11a-11c, 12a-12c, 13a-13c, and 14a-14c) and 20 benzylidene hydrazones (18a-18r, 19a, and 20a) were synthesized by structural modification of paeonol, and their structures were characterized by proton nuclear magnetic resonance (1H NMR), carbon-13 (13C) NMR, and high-resolution mass spectrometry (HRMS). The stereochemical configurations of compounds 14a, 18d, and 18r were unambiguously confirmed by single-crystal X-ray diffraction. Furthermore, bioactivities of these compounds as anti-oomycete, anti-fungal, and nematicidal agents against three serious agricultural pests, Phytophthora capsici, Fusarium graminearum, and Heterodera glycines were evaluated. Among all tested compounds: (i) compound 7 exhibited promising anti-oomycete against Phytophthora capsici, with a half maximal effective concentration (EC50) value of 15.81 mg L-1; (ii) compounds 2, 7, 10, and 19a displayed promising anti-fungal against F. graminearum, with EC50 values of 12.22, 14.72, 23.39, and 33.10 mg L-1, respectively; (iii) ten compounds (12a-12c, 14c, 18g-18j, 18m, and 19a) showed significant nematicidal activity against H. glycines, with median lethal concentration (LC50) values all less than 30.00 mg L-1. Especially for compound 18g, its LC50 value is the smallest, at 12.65 mg L-1. The research results indicate that introducing nitro groups at the C5 position of paeonol, or introducing halogens at both C5 and C3 positions, can significantly enhance its biological activity against Phytophthora capsici, F. graminearum, and H. glycines. © 2024 Society of Chemical Industry.

Demethylation C–C coupling reaction facilitated by the repulsive Coulomb force between two cations

Carbon chain elongation (CCE) is normally carried out using either chemical catalysts or bioenzymes. Herein we demonstrate a catalyst-free approach to promote demethylation C–C coupling reactions for advanced CCE constructed with functional groups under ambient conditions. Accelerated by the electric field, two organic cations containing a methyl group (e.g., ketones, acids, and aldehydes) approach each other with such proximity that the energy of the repulsive Coulomb interaction between these two cations exceeds the bond energy of the methyl group. This results in the elimination of a methyl cation and the coupling of the residual carbonyl carbon groups. As confirmed by high-resolution mass spectrometry and isotope-labeling experiments, the C–C coupling reactions (yields up to 76.5%) were commonly observed in the gas phase or liquid phase, for which the mechanism was further studied using molecular dynamics simulations and stationary-point calculations, revealing deep insights and perspectives of chemistry.

High-Throughput Covalent Modifier Screening with Acoustic Ejection Mass Spectrometry.

Interests in covalent drugs have grown in modern drug discovery as they could tackle challenging targets traditionally considered "undruggable". The identification of covalent binders to target proteins typically involves directly measuring protein covalent modifications using high-resolution mass spectrometry. With a continually expanding library of compounds, conventional mass spectrometry platforms such as LC-MS and SPE-MS have become limiting factors for high-throughput screening. Here, we introduce a prototype high-resolution acoustic ejection mass spectrometry (AEMS) system for the rapid screening of a covalent modifier library comprising ∼10,000 compounds against a 50 kDa-sized target protein─Werner syndrome helicase. The screening samples were arranged in a 1536-well format. The sample buffer containing high-concentration salts was directly analyzed without any cleanup steps, minimizing sample preparation efforts and ensuring protein stability. The entire AEMS analysis process could be completed within a mere 17 h. An automated data analysis tool facilitated batch processing of the sample data and quantitation of the formation of various covalent protein-ligand adducts. The screening results displayed a high degree of fidelity, with a Z' factor of 0.8 and a hit rate of 2.3%. The identified hits underwent orthogonal testing in a biochemical activity assay, revealing that 75% were functional antagonists of the target protein. Notably, a comparative analysis with LC-MS showcased the AEMS platform's low risk of false positives or false negatives. This innovative platform has enabled robust high-throughput covalent modifier screening, featuring a 10-fold increase in library size and a 10- to 100-fold increase in throughput when compared with similar reports in the existing literature.

Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification - is it time for HT-EDA?

The rapid increase in the production and global use of chemicals and their mixtures has raised concerns about their potential impact on human and environmental health. With advances in analytical techniques, in particular, high-resolution mass spectrometry (HRMS), thousands of compounds and transformation products with potential adverse effects can now be detected in environmental samples. However, identifying and prioritizing the toxicity drivers among these compounds remain a significant challenge. Effect-directed analysis (EDA) emerged as an important tool to address this challenge, combining biotesting, sample fractionation, and chemical analysis to unravel toxicity drivers in complex mixtures. Traditional EDA workflows are labor-intensive and time-consuming, hindering large-scale applications. The concept of high-throughput (HT) EDA has recently gained traction as a means of accelerating these workflows. Key features of HT-EDA include the combination of microfractionation and downscaled bioassays, automation of sample preparation and biotesting, and efficient data processing workflows supported by novel computational tools. In addition to microplate-based fractionation, high-performance thin-layer chromatography (HPTLC) offers an interesting alternative to HPLC in HT-EDA. This review provides an updated perspective on the state-of-the-art in HT-EDA, and novel methods/tools that can be incorporated into HT-EDA workflows. It also discusses recent studies on HT-EDA, HT bioassays, and computational prioritization tools, along with considerations regarding HPTLC. By identifying current gaps in HT-EDA and proposing new approaches to overcome them, this review aims to bring HT-EDA a step closer to monitoring applications.

UPLC-LTQ-Orbitrap Study on Rat Urinary Metabolites of 5-Methoxy-Alpha-Methyltryptamine.

5-Methoxy-α-Methyltryptamine (5-MeO-AMT) is a new psychoactive substance which is abused due to its hallucinogenic and euphoric effects. This study aimed to study the metabolic characteristics of 5-MeO-AMT. Five rats were given intraperitoneal injection at a dose of 50 mg/kg of 5-MeO-AMT, and their urine was subsequently collected at different times within 7 days. Ultra-high performance liquid chromatography-- tandem high-resolution mass spectrometry (UPLC-LTQ-Orbitrap) was used to detect the precise molecular weight and fragment ions of 5-MeO-AMT and its possible metabolites in the urine sample extracted with benzene-ethyl acetate. Three metabolites, including OH-5-MeO-AMT, α-Me-5-HT, and N-Acetyl-5-MeO-AMT were identified in rats' urine. The major metabolic pathways involved O-demethylation, hydroxylation of indole ring, and Acetylation on aliphatic amines. The results of this study are an important reference for the identification and screening of toxicants of 5-MeO-AMT.

A stochastic approach for parameter optimization of feature detection algorithms for non-target screening in mass spectrometry.

Feature detection plays a crucial role in non-target screening (NTS), requiring careful selection of algorithm parameters to minimize false positive (FP) features. In this study, a stochastic approach was employed to optimize the parameter settings of feature detection algorithms used in processing high-resolution mass spectrometry data. This approach was demonstrated using four open-source algorithms (OpenMS, SAFD, XCMS, and KPIC2) within the patRoon software platform for processing extracts from drinking water samples spiked with 46 per- and polyfluoroalkyl substances (PFAS). The designed method is based on a stochastic strategy involving random sampling from variable space and the use of Pearson correlation to assess the impact of each parameter on the number of detected suspect analytes. Using our approach, the optimized parameters led to improvement in the algorithm performance by increasing suspect hits in case of SAFD and XCMS, and reducing the total number of detected features (i.e., minimizing FP) for OpenMS. These improvements were further validated on three different drinking water samples as test dataset. The optimized parameters resulted in a lower false discovery rate (FDR%) compared to the default parameters, effectively increasing the detection of true positive features. This work also highlights the necessity of algorithm parameter optimization prior to starting the NTS to reduce the complexity of such datasets.

Discovery of Unprecedented Human Stercobilin Conjugates.

Two unique metabolites (M18 & M19) were detected in feces of human volunteers dosed orally with [14C]inavolisib with a molecular ion of parent plus 304 Da. They were generated in vitro by incubation with fecal homogenates and we have evidence that they are formed chemically and possibly enzymatically. Structural elucidation by high resolution mass spectrometry and NMR spectroscopy showed that the imidazole ring of inavolisib was covalently bound to partial structures derived from stercobilin, an end-product of heme catabolism produced by the gut microbiome. The structural difference between the two metabolites was the position of methyl and ethyl groups on the pyrrolidin-2-one moieties. We propose a mechanism of M18 and M19 generation from inavolisib and stercobilin whereby nucleophilic attack from the imidazole ring of inavolisib occurs to the bridging carbon of a stercobilin molecule. The proposed mechanism was supported by computational calculations of molecular orbitals and transition geometry. Significance Statement We report the characterization of two previously undescribed conjugates of the PI3K inhibitor inavolisib, generated by reaction with stercobilin, an end-product of heme catabolism produced by gut microbiome. These conjugates were confirmed by generating them using in vitro fecal homogenate incubation via non-enzymatic and possibly enzymatic reactions. Given the unique nature of the conjugate, it is plausible that it may have been overlooked with other small molecule drugs in prior studies.

Gleditsiae Sinensis Fructus ingredients and mechanism in anti-asthmatic bronchitis research

BackgroundGleditsiae Sinensis Fructus (GSF) is commonly used in traditional medicine to treat respiratory diseases such as bronchial asthma. However, there is a lack of research on the chemical composition of GSF and the pharmacological substance and mechanism of action for GSF in treating bronchial asthma. PurposeThe chemical constituents of GSF were analyzed using ultrahigh-performance liquid chromatography-quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). In this study, we combined network pharmacology, molecular docking techniques, and experimental validation to explore the therapeutic efficacy and underlying mechanism of GSF in the treatment of bronchial asthma. MethodsCharacterization of the chemical constituents of GSF was conducted using UHPLC-Q-Orbitrap HRMS. The identified chemical components were subjected to screening for active ingredients in the Swiss Absorption, Distribution, Metabolism, and Excretion (ADME) database. Relevant databases were utilized to retrieve target proteins for the active ingredients and targets associated with bronchial asthma disease, and the common targets between the two were selected. Subsequently, the protein-protein interaction (PPI) network was constructed using the String database and Cytoscape software to identify key targets. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Metascape database. The "component-common target" network was constructed using Cytoscape to identify the primary active ingredients. Molecular docking validation was conducted using AutoDock software. The bronchial asthma mouse model was established using ovalbumin (OVA), and the lung organ index of the mice was measured. Lung tissue pathological changes were observed using hematoxylin and eosin (HE), Periodic Acid-Schiff (PAS), and Masson staining. The respiratory resistance (Penh) of the mice was assessed using a pulmonary function test instrument. An enzyme-linked immunosorbent assay (ELISA) was used to determine the levels of IgE, IL-4, IL-5, and IL-13 in the mouse serum. Immunofluorescence staining was performed to detect the protein expression levels of AKT and PI3K in the lung tissues. An in vitro experiment was performed to observe the effects of echinocystic acid (EA) on IL-4 stimulated Human ASMCs (hASMCs). Cell viability was measured using a CCK-8 assay to calculate the IC50 value of the EA. A wound healing test was conducted to observe the effect of EA on degree of healing. RT-qPCR was performed to detect the influence of EA on the mRNA expression levels of ALB, SRC, TNF-α, AKT1, and IL6 in the cells. ResultsA total of 95 chemical constituents were identified from the GSF. Of these, 37 were identified as active ingredients. There were 169 overlapping targets between the active ingredients and the disease targets. A topological analysis of the protein-protein interaction (PPI) network identified the core targets as IL6, TNF, ALB, AKT1, and SRC. An enrichment analysis revealed that the treatment of bronchial asthma with GSF primarily involved the AGE-RAGE signaling pathway and the PI3K-Akt signaling pathway, among others. The primary active ingredients included 13(s)-HOTRE, linolenic acid, and acacetin. The molecular docking results demonstrated a favorable binding activity between the critical components of GSF and the core targets. Animal experimental studies indicated that GSF effectively improved symptoms, lung function, and lung tissue pathological changes in the OVA-induced asthmatic mice, while alleviating inflammatory responses. GSF decreased the fluorescent intensity of the AKT and PI3K proteins. The IC50 value of EA was 30.02μg/ml. EA (30) significantly promoted the proliferation of IL4-stimulated hASMCs cells. EA (30) significantly increased the expression of ALB and SRC mRNA and decreased the expressions of TNF-α, AKT, and IL6 mRNA. ConclusionThe multiple active ingredients found in GSF exerted their anti-inflammatory effects through multiple targets and pathways. This preliminary study revealed the core target and the mechanism of action underlying its treatment of bronchial asthma. These findings provided valuable insights for further research on the pharmacological substances and quality control of GSF.

Detection of the GH analog somatrogon in sports drug testing: Immunological approaches and LC-HRMS/MS.

Due to the presumed lipolytic and anabolic properties, the misuse of human growth hormone (hGH) and its synthetic analogs in sports is prohibited both in- and out-of-competition. Within this research project, the detectability of somatrogon, a recombinant fusion glycoprotein of 22 kDa hGH and the C-terminal peptide (CTP) of the human chorionic gonadotropin (hCG) β-subunit, with current WADA-approved doping control assays for hGH and hCG was investigated. For that purpose, cross-reactivity tests and a somatrogon administration study were conducted, and only "Kit 2" of the GH isoform differential immunoassays proved applicable to the detection of somatrogon administration in serum. In urine, the immunoassay specific for total hCG yielded presumptively positive findings for several post-administration samples, which can probably be attributed to the presence of an immunoreactive fragment of the hCG β-subunit. As the detectability of somatrogon with these approaches was found to be limited, a highly specific detection assay (LOD: 10ng/mL) for the drug in serum samples was developed by using affinity purification with GH receptor (GHR)-conjugated magnetic beads, proteolytic digestion, and liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). Following optimization, the approach was comprehensively characterized, and authentic post-administration serum samples were successfully analyzed as proof-of-concept, indicating a detection window of at least 96 h. Consequently, the presented method can be employed to confirm the presence of somatrogon in serum samples, where only "Kit 2" of the currently used immunoassay kits yielded an abnormally high Rec/Pit ratio.

Practical synthesis of chenodeoxycholic acid from phocaecholic acid

In this study, we developed an effective method for the large-scale synthesis of chenodeoxycholic acid (CDCA) from phocaecholic acid (PhCA). A high total yield of up to 72 % was obtained via five steps including methyl esterification, Ts-protection, bromination, reduction, and hydrolysis. The structures of the intermediates were confirmed by 1H NMR (Nuclear Magnetic Resonance), 13C NMR, HRMS (High Resolution Mass Spectrometry), and IR (Infrared Spectroscopy) spectroscopies. This method offers a new and practical approach to the synthesizing of CDCA.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage.

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Study of the microRNA fraction in food waste and other biomasses. Assessment of its antioxidant and anti-inflammatory activity

MicroRNAs (miRNAs) are short non-coding RNAs with important biological functions. Their presence in food and their potential role as new bioactive molecules is generating great expectations. For the first time, the miRNA fraction within food waste and algae has been studied, highlighting their bioactivity and its potential upcycling. MiRNAs from barley malt rootles, brewer’s spent grains, Spirulina, Chlorella, orange peels, pomegranate and apricot seeds, and watermelon waste were extracted using two kits, one with chloroform and a more sustainable alternative. Higher extraction yields were obtained with the chloroform-containing kit. Purity of extracts was confirmed by UV spectroscopy and reversed-phase high performance liquid chromatography (RP-HPLC) with UV detection. Further analysis by RP-HPLC and high-resolution mass spectrometry (MS) demonstrated the potential and feasibility of this technique for the analysis of miRNA although there are still some limitations to overcome before its routine application. Apricot seed miRNAs demonstrated remarkable anti-inflammatory and antioxidant capacity.

Selective Profiling of Carboxylic Acid in Crude Oil by Halogen Labeling Combined with Liquid Chromatography and High-Resolution Mass Spectrometry.

Carboxylic acids are a small but essential compound class within petroleum chemistry, influencing crude oil behaviors in production and processing and causing environmental impacts. Detailed structural information is fundamental to understanding their influence on petroleum characteristics. However, characterizing acids in crude oil remains challenging due to matrix effects, structural diversity, and low abundance. In this work, we present a new methodology for profiling carboxylic acids by liquid-liquid extraction and selective derivatization using 4-bromo-N-methylbenzylamine (4-BNMA) followed by liquid chromatography and electrospray ionization Orbitrap mass spectrometry (LC-ESI-Orbitrap MS). The fragmentation of 4-BNMA derivatives produces a unique product ion pair, m/z 169/171, enabling the identification of chromatographic fractions containing carboxylic acids. The mass spectra of the corresponding fractions are extracted, and the acids are further computationally isolated based on the isotopic pattern. The method was optimized and validated using acid standards and systematic experimental designs, assuring robustness and sensitivity for nontarget screening purposes. This method detected up to 380 carboxylic acids in six Danish North Sea crude oils, with up to two carboxyl and other heteroatom functionalities (NSO). The results indicated that the most populated species are fatty acids (double bond equivalent (DBE) = 1) and small aromatic acids (DBE = 2-6). The predominance and diversities of compound classes in different samples are consistent with their corresponding bulk properties. Polyfunctional acids (Ox, NxOx, and SxOx) were observed due to exposure to oxidation and biodegradation. Also, the approach's applicability benefits high-resolution MS analysis by simplifying data processing for crude oil and potentially other high-organic and aqueous samples.

ICP-MS As a Contributing Tool to Nontarget Screening (NTS) Analysis for Environmental Monitoring.

Due to the increasing number of chemicals released into the environment, nontarget screening (NTS) analysis is a necessary tool for providing comprehensive chemical analysis of environmental pollutants. However, NTS workflows encounter challenges in detecting both known and unknown pollutants with common chromatography high-resolution mass spectrometry (HRMS) methods. Identification of unknowns is hindered by limited elemental composition information, and quantification without identical reference standards is prone to errors. To address these issues, we propose the use of inductively coupled plasma mass spectrometry (ICP-MS) as an element-specific detector. ICP-MS can enhance the confidence of compound identification and improve quantification in NTS due to its element-specific response and unambiguous chemical composition information. Additionally, mass balance calculations for individual elements (F, Br, Cl, etc.) enable assessment of total recovery of those elements and evaluation of NTS workflows. Despite its benefits, implementing ICP-MS in NTS analysis and environmental regulation requires overcoming certain shortcomings and challenges, which are discussed herein.