Investigating the Protonated Cannabinoid Dimer Detected in the Forensic Analysis of Cannabis by DART-MS: A Combined Mass Spectrometry and Computational Study

Direct analysis in real time–high-resolution mass spectrometry (DART-HRMS) enables the rapid chemical profiling of Cannabis samples. This approach reveals a prominent signal at nominal m/z 315, charac...

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Lessons Learned in Orbitrap MS-Based Isotope Ratio Analysis of Organic Acid Mixtures

Stable isotope analysis is a vital tool across chemistry, geology, and environmental science, but conventional Isotope Ratio Mass Spectrometry (IRMS) techniques have limited capabilities for site-specific or multiply substituted (“clumped”) isotope analyses, and are particularly limited for analyses of complex mixtures without prior analyte purification. This study addresses this gap by employing a high-resolution Orbitrap mass spectrometer to directly measure the 13C/12C ratio in a model naphthenic acid (1,2,3,4-tetrahydro-2-naphthoic acid, THN) within complex organic matrices. We applied a “zero-enrichment” experimental design to evaluate accuracy and precision by comparing pure standards to the same compound in synthetic samples resembling natural waters. Complementary experiments using low-molecular-weight organic acids and natural rumen fluid were conducted to define the method’s limits under controlled and severe ion-suppression conditions. The results demonstrated that matrix effects and ion statistics can substantially degrade both accuracy and precision under certain conditions. At very low analyte concentrations, incomplete ion accumulation led to heightened δ13C variability, a condition analogous to a “blank effect”. Paradoxically, adding 1% NH4OH improved the precision of 13C/12C measurements (reducing the relative standard error from ∼0.80‰ to ∼0.63‰ at 0.1 μM THN), despite a reduced signal, by promoting more stable deprotonation and minimizing ion suppression. We also identified that coaccumulated ions, even when baseline-resolved, such as a matrix-derived fragment at m/z 177, degrade precision by perturbing the space-charge balance. Removing this interference fully restored precision, underscoring the need to control coaccumulating ions. Crucially, experiments with small organic acids demonstrated that moderate ion suppression does not lead to isotopic bias, which emerges only when severe suppression reduces analyte ion counts below a critical statistical threshold. Finally, we identified an “isotopic stability plateau”─an optimal signal range where δ13C measurements are most precise and accurate, poised between noise-dominated and space-charge-distorted regimes. This work demonstrates that Orbitrap-MS can perform reliable isotope analysis in complex organic mixtures when instrumental and chemical parameters are carefully optimized, opening new applications in petroleum geochemistry, environmental forensics, and other topics.

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HPLC‐Orbitrap‐MS for the Determination of B‐Vitamins in Fruit Juices and Food Supplements

Accurate assay of vitamins in foods is a considerable analytical challenge due to the chemical complexity of matrices and molecular structures. Orbitrap MS technology coupled with liquid chromatograp...

analyticalsciencejournals.onlinelibrary.wiley.com

Simultaneous Quantification of Twelve Endogenous HPA Axis Compounds by Protein Precipitation and HILIC‐UPLC–MS/MS in a Mouse Model of Insomnia

Rationale Accurate quantification of neurotransmitters and hormones within the hypothalamic–pituitary–adrenal (HPA) axis is essential for elucidating their pathological roles in neurodegenerative di...

analyticalsciencejournals.onlinelibrary.wiley.com

Multiomics Analysis across the Life Cycle Identifies Zn2Cys6_61 as a Target for Enhancing Triterpenoid Production in Ganoderma lucidum

Ganoderic acids (GAs) are high-value lanostane-type triterpenoids derived from Ganoderma lucidum (G. lucidum) with broad applications in functional foods and nutraceuticals, yet their low natural abundance limits industrial production. In this study, an integrated life-cycle multiomics analysis combining metabolomics, transcriptomics, and proteomics was conducted across six developmental stages in four G. lucidum strains to elucidate regulatory mechanisms governing GA biosynthesis. Weighted gene coexpression network analysis identified candidate cytochrome P450 enzymes and transcription factors associated with GA accumulation. A Zn2Cys6-type transcription factor, Zn2Cys6_61, was identified as a central regulator and functionally validated through overexpression and RNA interference. Genetic manipulation of Zn2Cys6_61 expression significantly altered GA levels, with overexpression markedly enhancing GA accumulation. Further analysis demonstrated that Zn2Cys6_61 directly binds to and activates the promoter of squalene synthase, a key enzyme in triterpenoid backbone biosynthesis. Together, these findings identify Zn2Cys6_61 as an effective engineering target and provide a transcription factor-based strategy for improving GA production in medicinal mushrooms.

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Metabolomics-Guided Integration of a “Push–Pull-Restrain” Strategy for Enhanced LNnT Production in Saccharomyces cerevisiae

Lacto-N-neotetraose (LNnT) is a prominent neutral human milk oligosaccharide (HMO) with limited availability. Here, Saccharomyces cerevisiae (GRAS strain, Generally Recognized as Safe) was metabolically engineered to enhance LNnT production. Metabolomics analysis revealed that competition from chitin synthesis and insufficient metabolic driving force for heterologous glycosyltransferases in yeast constituted major metabolic bottlenecks. To overcome these limitations, a “push–pull-restraint” strategy was applied, integrating glycosyltransferase screening, protein tag fusion evaluation, targeted chitin disruption of chitin biosynthetic genes, and balanced modulation of UDP-Gal/UDP-GlcNAc supply. These interventions increased extracellular LNnT titer in shake-flask cultures from 14.65 mg/L to 1.66 g/L, with total LNnT reaching 2.01 g/L. Further scale-up in a 5 L bioreactor under fed-batch conditions resulted in a total LNnT titer of 4.70 g/L. These results demonstrate the potential for the production of LNnT by S. cerevisiae and open up an innovative framework for the effective synthesis of LNnT.

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Validating Direct Mass Spectrometry Screening for Grease-Proofers Containing 6:2 Fluorotelomer Alcohol in Fiber-Based Food Packaging

Recently, polymeric PFAS-containing grease-proofers were removed from the U.S. food contact market. Validated methods are needed to monitor the removal of polymeric grease-proofers containing 6:2-fluorotelomer alcohol (6:2-FTOH) from fiber-based food packaging. Small-molecule extraction methods are neither specific nor rapid enough to screen for the intentional use of polymers. Direct analysis in real time mass spectrometry (DART-MS) approaches have shown promise for screening polymeric grease-proofers containing 6:2-FTOH but require method validation for regulatory implementation. A hydrolysis isotope dilution DART-MS (ID-DART-MS) method was refined to meet the FDA compound identification and validation guidelines. Method validation experiments demonstrated that hydrolyzable 6:2-FTOH from grease-proofers was identified across all fiber-based food packaging types with less than 5% false positive or negative rates (95% confidence) and a linear response across 4 μg/kg–130 mg/kg hydrolyzed 6:2-FTOH. The method reliably identified six different fluorotelomer-containing grease-proofers with 14 min/sample of effort, making it fit to assess incidence and removal of these PFAS-based grease-proofers.

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Systematic Evaluation of the Impact of Storage Time on Label-Free Proteomics of Colorectal Adenocarcinoma Formalin-Fixed Paraffin-Embedded Tissues

Mass spectrometry (MS)-based proteomics has empowered comprehensive protein profiling of biological specimens. However, formalin-fixed paraffin-embedded (FFPE) tissues─critical resources for clinical biomarker discovery-remain underexplored in the setting of long-term storage (>15 years). Herein, we systematically evaluated the impact of storage time on proteomic analyses of 80 colorectal adenocarcinoma (CRC) FFPE samples, which were stratified by two key variables: storage time (>15 years vs <1 year) and tissue type (tumor vs adjacent normal tissue). We adopted a standardized protein extraction strategy, and subsequent proteomic profiling was performed via data-dependent acquisition and data-independent acquisition MS workflows. Our results demonstrated that FFPE tissue storage time impacts protein extraction efficiency, peptide yields, PTM identification, and protein quantification. The impacts were more pronounced on the peptide level. However, the biological enrichments (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis) from the global proteome profile and from differentially expressed proteins in CRC tissues were independent of archival time. Five clinically relevant biomarkers of CRC were further validated via immunohistochemistry. Collectively, our findings confirm that FFPE tissues retain stability for proteomic analyses even following >15 years of storage, thereby providing critical insights for leveraging archival FFPE biobanks to advance clinical proteomics and archival pathology research.

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Mapping the Spatial Distribution of Tryptic Peptides in Formalin-Fixed Paraffin-Embedded Tissues Using Desorption Electrospray Ionization Mass Spectrometry Imaging

Spatial proteomics visualizes protein localization within native cellular and tissue environments, providing critical insights into pathological processes, tissue heterogeneity, and diagnostic biomarkers. Mass spectrometry imaging (MSI) has emerged as a powerful tool for spatial proteomics, with matrix-assisted laser desorption/ionization (MALDI)-MSI being the most widely used platform. Recently, desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) has been explored for mapping proteins and peptides in tissue sections, with distinct sets of proteins detected compared to MALDI MSI. However, current studies have focused on fresh-frozen tissues, and the application of DESI-MSI to formalin-fixed paraffin-embedded (FFPE) tissues, the predominant form of clinical specimens, remains unexplored. Here, we report the optimization and application of DESI-MSI for proteomic analysis of FFPE tissues. Sample pretreatment procedures and DESI parameters were systematically optimized using FFPE mouse brain tissue sections to enhance tryptic peptide detection. The optimized workflow was further applied to FFPE canine melanocytoma tissue to discover protein biomarkers. Protein identification was performed using nanoLC-MS/MS. Overall, we demonstrate the potential of DESI-MSI as a platform for spatial proteomic analysis of FFPE tissues, expanding its applicability to archived clinical specimens.

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Global Profiling of Post-Translationally Modified Crustacean Neuropeptidome Trends Affiliated with Feeding Activity

Neuropeptides modulate a diverse range of physiological functions, including those associated with feeding. Post-translational modifications (PTMs) contribute significantly to the dynamic nature of neuropeptide isoforms, influencing their functional diversity. Mass spectrometry is the gold-standard analytical technique for peptidomic analyses and is complemented by computational methods for peptide identification; however, the computational search space becomes increasingly difficult to manage as more potential modifications are considered. Using innovative approaches capable of addressing the vast combinations of possible modifications, such as the PEAKS PTM search algorithm, we globally profiled the neuropeptidome ofCancer borealis(Jonah crab) to investigate the role of PTMs in feeding- and appetite-related processes over time. Through an in-depth examination of several notable modifications, we proposed PTM-associated motifs for neuropeptides, which may enhance future identification capabilities. Furthermore, this work revealed neuropeptides that were characteristically modified depending on the crab’s feeding status and time post-feeding, suggesting potential biological significance. This study represents the first large-scale investigation of the modified crustacean neuropeptidome, providing new insights into the regulatory implications of PTMs in biological systems.

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Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results

LC-HRMS is widely used in forensic toxicology for broad-scope screening. When a newly emerging or rarely encountered compound is tentatively identified, toxicologists must decide whether it may be relevant to a case and, if so, quantify it. However, acquiring reference material for quantification is costly and time-consuming. A rapid semiquantitative estimation method would help prioritize only compounds above the toxic threshold. This study presents a machine-learning (ML) framework that estimates drug concentrations in whole blood using molecular structure information and LC-HRMS signals. Using a data set of 191 drugs spiked into whole blood at multiple concentration levels, we trained and evaluated several ML models. Standard models, including Random Forests, achieved moderate performance. In contrast, a recently reported Graph Neural Network (GNN) leveraging atomic features and global molecular properties consistently produced the highest accuracy. Under cross-validation, the GNN predicted signal-to-concentration ratios for 79% of all molecules, corresponding to concentration estimates between 50% and 200% of the true value. Toxicological thresholds often span multiple orders of magnitude, making this precision acceptable. The GNN model was additionally evaluated on an external benchmark data set of ionization efficiencies (logIE), where it outperformed the current state of the art. Overall, the results demonstrate the feasibility of using graph-based ML to estimate drug concentrations in whole blood without reference material. This is a practical ML tool that can support decision-making in toxicological evaluation, particularly for newly emerging or rarely encountered drugs. The GNN model is open source, and the data set used for training and testing the models are publicly available.

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A Sugaromics Method for Combined Targeted and Untargeted Sugar Profiling: Fit-for-Purpose Validation of a Quantitative GC × GC-MS Approach

The composition of sugar compounds in human biofluids is affected by various factors, including diet, health, demographic background, and lifestyle. Accurate quantification of this profile enables identification and application of biomarkers linked to health and nutrition, offering valuable insights into the mechanistic background of sugar metabolism. However, existing methods typically quantify only a few sugar compounds simultaneously, constraining full assessment of the sugar profile. Hence, we propose a comprehensive two-dimensional gas chromatography coupled with a mass spectrometry-based detector sugaromics method applying a nonpolar-medium polar column setup. The method is a combination of a targeted and untargeted approach to absolutely quantify various sugars in urine (n = 40) and serum (n = 36) and simultaneously identify untargeted sugar compounds in urine (n = 35) and serum (n = 22). The method was evaluated through a fit-for-purpose validation using the guidelines of the U.S. Food and Drug Administration and of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use as guiding principles. The majority of sugars demonstrated satisfactory validity parameters in terms of linearity, lower and upper limit of quantification, precision, accuracy, and carryover. Furthermore, the validated method was applied to human urine and serum samples (n = 40), indicating quantifiable analyte concentrations within the expected range. In this respect, for healthy adults, absolute concentrations of seven sugars in urine and 14 in serum were reported for the first time. In conclusion, the newly developed method combining targeted and untargeted approaches demonstrates good performance and is promising for application in human studies investigating health and nutrition.

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Ion Mobility–Mass Spectrometry: A Powerful Platform for Structural Characterization of Metal Nanoclusters

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Evaluating the Sulfo-Phospho-Vanillin Assay for Total Lipid Sample Normalization as Compared to Gravimetric and Protein Sample Normalization Methods for Untargeted Lipidomic LC–MS/MS

Sample normalization is essential for lipid quantitation. While normalization methods involving pre- or postgravimetric measurements, counting, or protein prequantitation exist, a single, common sample normalization method is not widely accepted. Previously, we proposed and evaluated the sulfo-phospho-vanillin assay (SPVA), a total lipid quantitation reaction, for prequantifying total lipids for LC–MS/MS sample normalization purposes. This current investigation furthers our evaluation of the SPVA as a sample normalization method in untargeted lipidomic LC–MS/MS by comparing SPVA total lipid prequantitation to protein prequantitation and gravimetric measurements. This study was applied to a wide selection of matrices, including Escherichia coli, plasma, brain, heart, and kidney. Resulting relative lipid concentrations showed smaller bioreplica variation when a prequantitation method was applied, either measuring total lipid or total protein; however, several relative lipid abundances showed inverse concentration relationships when normalizing with total protein compared to total lipid (from SPVA measurements) or gravimetric sample normalization. Further investigation using lipid extracts linearly spiked with pure, non-native lipid showed that gravimetric and protein normalization nonlinearly overproduced significant lipids, while linear increases in significant lipid features were observed from SPVA normalization. Lipid extracts linearly spiked with pure, non-native protein yielded fewer significant lipid features using SPVA normalization, and this was unchanged as protein was added; however, both gravimetric and protein normalization continued to yield large numbers of significant lipid features. Together, these results suggest neither gravimetric nor protein sample normalization appropriately normalizes quantitative lipidomic experiments and greatly overgenerates statistically significant lipid features for biomarker investigation. SPVA normalization more accurately adjusts for lipid changes in bioreplicate samples, leading to fewer but more biologically relevant statistically significant lipid features.

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A Universal Buffer System for Native LC–MS Analysis of Antibody-Based Therapeutics

Liquid chromatography coupled to mass spectrometry (LC–MS) is a powerful analytical technique for analyzing biological macromolecules. A long-standing challenge has been applying LC–MS at physiological pH under native conditions using volatile buffers. The predominant “buffer” used, ammonium acetate (AmAc, pKa 4.75 for acetic acid and 9.25 for ammonium), does not offer sufficient buffering capacity in the physiological pH range of 7.0–7.4. To address this, we evaluated a set of fluorinated ethylamines, 2-fluoroethylamine (MFEA), 2,2-difluoroethylamine (DFEA), and 2,2,2-trifluoroethylamine (TFEA), producing conjugate acids with pKa values of 8.9, 7.2, and 5.5, respectively, that together provide buffering across the 4.5–9.8 pH range. We show that protein separations on strong cation- and anion-exchange resins in these volatile mobile phases perform comparably to traditional nonvolatile buffers, with similar elution profiles and analyte elution ranking, albeit with slightly broader peaks. Using fully volatile gradients of pH or ionic strength, we chromatographically resolved charge variants of protein analytes such as mAbs and bovine serum albumin. For many of the eluting LC peaks, we obtained high-resolution mass spectra capable of resolving glycoforms of antibodies. Hydrophobic interaction chromatography (HIC) in volatile mobile phases preserved native separation order and further resolved drug-to-antibody ratio (DAR) species of the antibody-drug conjugate brentuximab-vedotin. For each chromatography modality we further compare innovator and biosimilar antibodies, demonstrating the reproducibility of results in the proposed volatile compounds. Together, our results establish fluorinated ethylamines, in combination with ammonium acetate, as a universal volatile buffer system for native LC–MS, broadly applicable across major chromatographic modalities.

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A Miniature Ion Trap Particle Mass Spectrometer with an Integrated Optical and Charge Detection System

A miniature ion trap particle mass spectrometer with both optical and charge detection systems was constructed in this work. The instrument was initially constructed with an open architecture and mounted on a 600 × 450 mm optical bench. With further compact integration, the system can be accommodated within an aluminum enclosure with dimensions of 333 × 221 × 192 mm and a total mass of approximately 8 kg. In the optical detection mode, the stationary star pattern ion motion was observed by detecting the scattered light, and the m/Z value of the particle ion was calculated accurately. In the charge detection mode, the particle m/Z value, the charge number Z, and the particle mass were determined quickly. These two working modes can be switched freely. By using 3 μm polystyrene size standards and mice red blood cells as the sample, the feasibility of this instrument was demonstrated.

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Dissecting Metabolic Rewiring and Gene-Metabolite Interactions by Utilizing Untargeted Metabolomics and Single-Gene Knockouts in the Model Microorganism E. coli

Central carbon metabolism, comprising glycolysis, the tricarboxylic acid (TCA) cycle, and the pentose phosphate pathway (PPP), is essential for Escherichia coli survival and growth. While disruptions in these pathways are known to affect cellular physiology, the system-wide metabolite-level consequences of single-gene knockouts remain incompletely understood. Using untargeted LC-MS metabolomics, we systematically profiled E. coli knockouts of TCA core enzymes, isoforms, subunits, bypass routes, and TCA-associated pathways. Core TCA knockouts separated into two major metabolic clusters, with cluster 1 strains displaying strong divergence in amino acid metabolism and cluster 2 retaining partial similarity to the parent strain. Isoform-specific deletions revealed differential roles of aconitases (ΔacnA vs ΔacnB) and fumarases (ΔfumA vs ΔfumC), while subunit knockouts of 2-oxoglutarate dehydrogenase (ΔsucA, ΔsucB) and succinate dehydrogenase (ΔsdhA-D) produced localized but distinct metabolite shifts, particularly around glutamate- and 2-oxoglutarate-linked metabolism. Bypass enzyme deletions (ΔaceA, ΔaceB, ΔglcB, and ΔmaeB) disrupted carbohydrate- and redox-related metabolites, underscoring their role as metabolic safety nets. Importantly, knockouts also triggered off-target effects in glycolysis, PPP, and the electron transport chain, highlighting the interconnectivity of central carbon metabolism. Our systematic approach demonstrated the possibility of utilizing comprehensive and untargeted metabolomics to map gene-metabolite associations and decipher potential metabolic interlinks.

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Optimized Low-Field Differential Ion Mobility Separations with High-Resolution Mass Spectrometry for Top-Down Proteomics

Ion mobility spectrometry (IMS) with mass spectrometry (MS) is a versatile approach to simplify mixtures, distinguish isomers, and elucidate molecular geometries. While linear IMS relies on the mobility K at moderate normalized electric field E/N, field asymmetric waveform IMS (FAIMS) captures its increment ΔK at high E/N levels causing ion heating. A novel nonlinear low-field differential (LOD) IMS separates large macroions, leveraging their dipole alignment. The IMS/MS mass limit is set by and advances with the MS stages. As the ever-heavier macromolecules and more complex samples demand ultimate MS resolution and accuracy, coupling IMS to Fourier-Transform (FT) MS has become essential in proteomics and structural biology. Here, we integrate LODIMS using the bisinusoidal (bis) or augmented flexible rectangular waveforms with Orbitrap MS and MS/MS and employ this platform to explore Concanavalin A (ConA, 25.6 kDa) comprising the natural noncovalent forms. The isotopic envelopes for all pieces were disentangled by MS. The intact ConA strongly aligns for most charge states, trivially separating from the (rotary) pieces for improved detection of both. The rectangular and scaled bis waveforms yield consistent directional cross sections and dipole moments─duly smaller than for the larger proteins. The newly identified peptides uncover an endogenous cleavage at N162 (plus the known N118) and thus two additional ConA forms. This work demonstrates the capability of LODIMS to align smaller proteins, reliably assess their directional cross sections and (weaker) dipoles, and facilitate top-down proteomics with the discovery of novel proteoforms.

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Untargeted Multiple Reaction Monitoring

Multiple reaction monitoring (MRM) enables robust and sensitive quantification but traditionally requires predefined precursor–fragment transitions, limiting its use in discovery-driven studies. Here, we describe untargeted/micro/universal multiple reaction monitoring (uMRM), a workflow that converts high-resolution untargeted liquid chromatography–mass spectrometry/MS (LC–MS/MS) data into scheduled triple-quadrupole MRM transitions. Pooled-sample LC–MS and stepped-energy DDA MS/MS acquisitions (0, 10, 20, and 40 eV) are used to capture precursor and fragment information representative of each experimental set. Detected features undergo automated deisotoping and empirically validated in-source fragment filtering, followed by spline-based modeling of collision-energy–dependent fragmentation to define optimized precursor–fragment transitions. Transitions are scheduled using retention times observed in pooled samples and deployed on triple-quadrupole instruments without requiring nonlinear retention-time alignment or authentic standards. Across representative biological matrices, including urine, brain tissue, and cultured cells, uMRM enabled automated generation of quantitative MRM methods from untargeted discovery data. Benchmarking across seven triple-quadrupole platforms demonstrated strong agreement between uMRM-derived and experimentally optimized collision energies. By converting discovery-scale data sets into compact transition tables suitable for quantitative deployment, uMRM provides a reproducible approach for linking untargeted LC–MS/MS acquisition with targeted quantitation.

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Targeted and Nontargeted Detection and Quantitation of Arsenolipids in a Tuna Fish Reference Material (BCR-627) Using Reversed-Phase HPLC with High-Resolution Electrospray Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry

This study demonstrates the development of advanced mass spectrometric methodologies suitable for targeted and nontargeted arsenolipid (AsLp) determination in a tuna fish reference material (BCR-627) certified for its arsenobetaine, dimethylarsinic acid, and total arsenic content, thus enhancing its potential to also be used as a noncertified AsLp reference material. Twenty-five As-containing chromatographic peaks were initially detected using reversed-phase high-performance liquid chromatography (HPLC)-inductively coupled plasma–̵̵mass spectrometry (ICP-MS) with a mobile phase consisting of methanol in water ranging from 5 to 95%. Identification of arsenolipids in the detected As-containing peaks was achieved by using a combination of targeted and nontargeted high-resolution electrospray ionization mass spectrometry. Even though the targeted approach confirmed the presence of 11 AsLps already reported to be present in this material, a novel nontargeted approach not only confirmed their presence but also revealed the presence of an additional 26 AsLps, some of which are reported here for the first time. The nontargeted Full MS approach involved accurate mass measurements, better than 1 ppm using a lock mass, for high confidence detection of the AsLps. The resulting mass spectra were subsequently interrogated using the Mzmine software thus allowing for the rapid identification of candidate arsenolipid ions, which were designated to be precursor ions and fragmented in the MS/MS mode. Resulting product ion mass spectra were examined for 5 As-containing marker product ions, all of which are characteristic of the presence of compounds containing a dimethylarsinoyl moiety (CH3)2As(O). Precursor ions giving at least 3 marker product ions were identified to be dimethylarsinoyl-containing AsLps. The extracted ion chromatograms for the AsLp molecular ions were overlaid onto the As-specific HPLC-ICP-MS chromatograms for the final confirmation. Based on this approach, a high identification coverage of 84% was achieved, enabling more reliable quantitation of AsLps in BCR-627. By delivering both an analytically validated targeted and nontargeted workflow for AsLp analysis, and an expanded AsLp species dataset, this study provides essential groundwork for more routine, higher-coverage AsLp speciation in marine organisms, with possibilities for interlaboratory comparisons through the use of the BCR-627 tuna reference material. Thus, introducing a new era in AsLp speciation analysis expected to further promote the development of a field that may be referred to as arsenolipidomics.

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Comparison of Liquid Chromatography- and Nano-Electrospray Ionization-Mass Spectrometry Approaches for Single-Cell Metabolomics

Live single-cell metabolomics is a rapidly growing area of research, which offers the potential to provide unique insights into cellular function and heterogeneity. Single-cell isolation approaches ba...

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LC-MS Measurement of Triglyceride Hydrolysis: Application in Studies of Patatin-like Phospholipase Domain-Containing Protein 3 Activity.

The accumulation of triglycerides is associated with several disease states, consequently, modulation of lipid droplet biology by augmenting targets t…

sciencedirect.com

Ion-Specific Kinetic Energy Distributions in MeV-SIMS: Insights into Electronic Sputtering Processes

Kinetic energy distributions of secondary ions produced by fast heavy primary ions (3 – 10 MeV 35Cl, charge states 4+, 5+ and 7+) were measured to int…

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Extraction of air from ice core samples using trapping and detrapping on silica gel

Climate reconstructions from ice cores strongly rely on analysing the elemental and isotopic composition of fossil air occluded in the ice, as these p…

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Ultrahigh performance liquid chromatography mass spectrometry for the determination of azithromycin in canine serum and skin tissue

A simple and reproducible UHPLC–MS assay was developed and validated for quantifying azithromycin in canine serum and skin tissue homogenates. The met…

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Chromatography and mass spectrometry in therapeutic drug monitoring: Method performance, practical trade-offs, and implementation considerations

Therapeutic drug monitoring (TDM) is an essential clinical tool to individualize dosing for medications with narrow therapeutic indices or highly vari…

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Metabolic disparities of potentially toxic components derived from Psoraleae Fructus and Euodiae Fructus within the Sishen wan influenced by varying compatibilities and physiological conditions in an ...

Sishen wan (SSW) is utilized in the treatment of irritable bowel syndrome (IBS). This study aimed to compare gut microbiota-mediated metabolic profile…

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A universal immunocapture LC−MS/MS method for humanized IgG1−based drugs in cynomolgus monkeys

The application of immunocapture LC−MS/MS in drug testing has expanded considerably over the past decade, offering significant advantages in analysis,…

sciencedirect.com

Azetidination-based photocycloaddition enables regioisomer-resolved annotation of cholesteryl esters by negative-ion-mode LC-MS/MS

Cholesteryl esters (CE) play central roles in lipid transport and storage, yet their structural characterization remains challenging due to their extr…

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Spatial Lipidomic Combining DESI Imaging and LESA Mass Spectrometry to Evaluate Metabolic Alterations in Obese Zebrafish

Mass Spectrometry Imaging (MSI) enables spatial mapping of metabolites but often lacks in-situ structural confirmation. To address this, we validated a workflow combining histological staining, Desorp...

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