bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2026–10–25
sixty-five papers selected by
Sofia Costa, Matterworks
  1. High-Sensitivity LC-MS/MS Method for Simultaneous Determination of Structurally Related Impurities 2-Isoniazid, 3-Isoniazid and Isonicotinamide in Isoniazid Active Pharmaceutical Ingredient.
  2. A Validated Multi-Analyte Liquid Chromatography-Tandem Mass Spectrometry Method for Simultaneous Therapeutic Drug Monitoring and Targeted Toxicological Assessment of 54 Drugs and Metabolites in Human Serum.
  3. Advancing Spatial Lipidomics with MALDI-MS Imaging.
  4. A Novel Approach for Post-Acquisition Mass Calibration in Metabolomic Profiling by High-Resolution Mass Spectrometry.
  5. Application of Ion Mobility Mass Spectrometry in Lipidomics.
  6. Cyclic Ion Mobility Separations of Free Oxylipins.
  7. Analytical Methods for Mass Spectrometry-Based Metabolomics Studies.
  8. Bridging Speed and Confidence in Metabolomics: A Retention Time and MS2-Guided HILIC-Orbitrap Workflow.
  9. Simultaneous Quantification of Total Homocysteine and Methylmalonic Acid by LC-MS/MS for Comprehensive Assessment of Vitamin B12 and Folate deficiencies.
  10. Extensive Quantitative Profiling of Plasma Steroidome and Prostaglandin Metabolites for Studies of Female Reproductive Physiology.
  11. Drug Metabolism and Drug-Drug Interactions Studied Using High-Throughput Ambient Mass Spectrometry.
  12. Untargeted UHPLC-HRMS Lipidomic Profiling of Ticks for Alpha-Gal Syndrome Research.
  13. Analysis of Metabolomics Response to Tick Saliva in Human Cells.
  14. Ionic Solid Matrices Applied via Low-Temperature Evaporation Enable High-Resolution and Sensitive MALDI Imaging of Metabolites.
  15. Covalent Organic Framework-Based Solid Phase Microextraction Coating for Rapid Screening and Quantification of Drugs of Abuse and Artificial Sweeteners in Surface Waters.
  16. Enabling High-Throughput Tissue Sectioning for Robust Lipid Mass Spectrometry Imaging.
  17. A Liquid Chromatography-Mass Spectrometry Method to Quantify Total Coenzyme A Concentration and Isotopic Labeling.
  18. The Potential for Ion Mobility in Pharmaceutical and Clinical Analyses.
  19. Simultaneous quantification of remimazolam, midazolam, 1'-hydroxymidazolam, and dexmedetomidine in rat plasma by LC-MS/MS: application to biological samples and partial validation in ECMO-derived plasma.
  20. An N,N-Dimethylethylenediamine-Derivatized In Silico Mass Spectral Library for Comprehensive Profiling of Isothiocyanates in Brassicaceae Plants.
  21. Fully Automated Purification of Small Molecules Using Online MicroSPE-UPLC-SPE.
  22. High throughput analysis of contaminants of emerging concern in complex matrices.
  23. InSitu Untargeted Metabolite Identification and Spatial Mapping by Clustering Resampling Mass Spectrometry Imaging.
  24. Sample preparation and analytical determination of triazole antifungal agents in biological matrices: From conventional workflows to clinical monitoring.
  25. Analytical validation of a MALDI-TOF mass spectrometry method for serum IGF-1 measurement and its comparison with LC-MS/MS and CLIA.
  26. MSIonization: A Machine Learning Tool for Ionization Mode Prediction of Small Molecules.
  27. Accurate β-Casein Allergen Quantification in Processed Foods via an Isotope-Labeled Full-Length Protein Internal Standard.
  28. Targeted LC-MS/MS Analysis of Malonic Acid Biomarkers in Clinical Laboratory Applications.
  29. Isobaric Intramolecular Paternò-Büchi Reactions Enable Multiplexed Quantitation of Fatty Acids down to C═C Locations.
  30. Enzymatic Ligation Strategy to Enhance Electrospray Ionization Efficiency and Liquid Chromatography─Mass Spectrometry of DNA and RNA Oligonucleotides.
  31. Development and Validation of an Oral Fluid LC-MS/MS Method for Screening Emerging Synthetic Opioids Including Fentanyl Analogues, Nitazenes, and Xylazine.
  32. Separation-based bioanalysis of teicoplanin for therapeutic drug monitoring: Chromatographic selectivity, multicomponent quantification, and microsampling.
  33. MALDI MSI Workflow for Pharmaceutical Tablets: Toward a Reproducible Strategy for High-Resolution Imaging.
  34. Ion mobility mass spectrometry for suspect screening of environmental toxicants: Collision cross sections, structural annotation, and fit-for-purpose evidence evaluation.
  35. Metabolomics workbench: data-driven classification and correlation analysis between metabolite classes, biomarkers, and drugs.
  36. A Heating-Assisted Integrated Purification-Enrichment-Derivatization Paper Chip for Rapid MS/MS Quantification of Serum Steroid Hormones.
  37. Native, Memory-Bounded Conversion of Mass Spectrometry Imaging Data into the SpatialData Ecosystem.
  38. Enhancing Ion Yields in MALDI-2-MSI Using Dopant-Assisted Post Ionization for High-Resolution MS-Imaging of Lipids and Metabolites.
  39. Structurally informed metabolite measurements with ion mobility-mass spectrometry.
  40. Glycopyrronium bromide, formoterol fumarate dihydrate and their related compounds with UPLC/PDA-MS for simultaneous determination in pressurized metered-dose inhaler product.
  41. A novel UPLC-ECD method for simultaneous quantification of levodopa, benserazide, and their major metabolites in human plasma and cerebrospinal fluid.
  42. Novel method for extraction and quantitation of 6PPD-Q in solid matrices using ultrasonic-assisted extraction (UAE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS).
  43. Evaluation of Free and Released Sulfur Mustard Diols in Human Blood and Urine Using Multi-ionization GC-QQQ and GC-Q-TOF.
  44. MetaboT: an LLM-based multi-agent framework for interactive analysis of mass spectrometry metabolomics knowledge graphs.
  45. High-throughput mass spectrometry-based metabolomics for large-scale population studies: technical barriers and recent innovations.
  46. Seeing Chemistry in Context: Mass Spectrometry Imaging for Biomedical Research and Multi-Omic Integration.
  47. Metabolomics and Biomarker Discovery.
  48. RNabel─A Standalone Software Tool for Annotating Tandem Mass Spectra of Modified Ribonucleic Acids.
  49. MALDI Tandem Mass Spectrometry for Colony-Based Dereplication of Natural Products.
  50. AGENTi: APCI-ESI Analyte Ionization Fidelity Pre-Screening Workflow using Multimodel Inference.
  51. Exposomic Assessment of Endocrine-Disrupting Chemicals Using Hair: A Cross-Matrix Comparison with Serum and Urine by LC-HRMS and Metabolite Profiling.
  52. Rapid Simultaneous Quantification of Four Typical Phthalate Esters in Complex Food Matrices via Thermal Desorption-Dielectric Barrier Discharge Ionization Mass Spectrometry.
  53. Assessment of pesticide residues in rice-wheat based conservation agriculture fields using validated LC-MS/MS methodology.
  54. Multiway Modeling of 2D NMR Spectra for Enhanced Chemical Characterization of Complex Mixtures.
  55. Specificity Testing in Bioanalytical Assay Validations-Challenges and Opportunities.
  56. Electrospray-Orbitrap Analysis of Nitrate and Sulfate Isotopologues in Natural Samples: Performance and Constraints.
  57. Mass Spectrometry-Based Exposomics Is Not Metabolomics by Another Name.
  58. Rapid Species-Level Classification of Urinary Pathogens from Raw LC-MS/MS Signals Using Machine Learning.
  59. Recent advances in pretreatment and detection technologies for ergot alkaloids.
  60. Development and validation of an LC-MS/MS method for the determination of mycotoxins in the medicinal and edible herb dandelion.
  61. Hydraplexing: Design Principles for Fragment-Level Signal Amplification Using a Multi-Amine Model Analyte.
  62. Mass Spectrometry-Based Tissue Imaging of Small Molecules.
  63. Plasma-Assisted Functionalization of Hydrocarbons for Enhanced Mass Spectrometric Detection.
  64. IsoSwap: A Toeplitz Operator Framework for Isotope Transformations in Mass Spectrometry.
  65. Chromatograms: A Modular Infrastructure for Scalable Chromatographic Data Handling in R.
  1. J Mass Spectrom. 2026 ;61(11): e70124
    High-Sensitivity LC-MS/MS Method for Simultaneous Determination of Structurally Related Impurities 2-Isoniazid, 3-Isoniazid and Isonicotinamide in Isoniazid Active Pharmaceutical Ingredient.
    Rajesh Kumar Boggavarapu, Venkateswara Rao Yamarthi, Jithendra Chimakurthy.
      A sensitive, selective and rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the simultaneous quantification of trace impurities, namely, 2-isoniazid, 3-isoniazid and isonicotinamide, in isoniazid active pharmaceutical ingredient (API) at parts-per-million (ppm) levels. Chromatographic separation was achieved within 6 min using a Zorbax SB Aq column maintained at 40°C. The mobile phase consisted of 10 mM ammonium formate buffer (pH 4.0, adjusted with formic acid) and 0.1% (v/v) formic acid in acetonitrile (48:52, v/v), delivered at a flow rate of 1.0 mL/min. The optimized conditions provided efficient separation, reproducible peak responses and stable ionization for all analytes. The method was validated in accordance with ICH Q2 guidelines with respect to specificity, accuracy, precision, linearity, range, detection limit and quantitation limit. The limits of detection and quantification were established at 0.8 and 2.5 ppm, respectively, demonstrating the high sensitivity of the method for trace impurity determination. The validated method was successfully applied to the analysis of isoniazid bulk drug samples and enabled consistent and accurate quantification of the impurities. The developed LC-MS/MS method is rapid, robust and suitable for routine quality control testing and regulatory impurity monitoring of isoniazid API.
    Keywords:  LC–MS/MS; chromatographic separation; impurity profiling; isoniazid API; method validation (ICH Q2(R1)); parts per million; pharmaceutical analysis; pharmaceutical analytical method development; trace‐level quantification
    DOI:  https://doi.org/10.1002/jms.70124
  2. J Sep Sci. 2026 Oct;49(10): e70560
    A Validated Multi-Analyte Liquid Chromatography-Tandem Mass Spectrometry Method for Simultaneous Therapeutic Drug Monitoring and Targeted Toxicological Assessment of 54 Drugs and Metabolites in Human Serum.
    Katerina Kratka, Pavel Sistik, Radek Jerga, Ivana Olivkova, Hana Brozmanova, Romana Urinovska, Vladimira Gebauerova, Jan Jurica, Klara Handlosova, Petr Handlos, Ivana Kacirova, David Stejskal.
      Therapeutic drug monitoring and targeted toxicological assessment require quantitative methods capable of covering chemically diverse drugs over clinically relevant concentration ranges. We developed and validated a liquid chromatography-tandem mass spectrometry method for the simultaneous determination of 54 analytes in human serum, including antiepileptic drugs, antidepressants, antipsychotics, benzodiazepines, antifungal agents, theophylline, and selected clinically relevant metabolites. Serum samples were prepared by protein precipitation with perchloric acid. Chromatographic separation was achieved on an ACQUITY UPLC BEH C18 column using water/methanol mobile phases containing 2 mM ammonium acetate. Detection was performed in polarity-switching selected reaction monitoring mode using two transitions per analyte and 28 isotope-labeled or structurally related internal standards. The total run time was 8.5 min. Analyte-specific calibration models and validated concentration ranges covered 0.1-22,500 ng/mL, depending on the analyte. The method demonstrated acceptable selectivity, calibration performance, accuracy, precision, matrix effects, and stability under routine handling and storage conditions for analytes with available data. Within-run and between-run precision did not exceed 14.3% and 13.9%, respectively. Matrix effects ranged from -8.35% to +10.25%. Application to 120 remnant patient serum samples supported the feasibility of multiplex measurement of drugs from several therapeutic classes in a single analytical run. The method is suitable for routine serum-based therapeutic drug monitoring and for targeted toxicological interpretation of a predefined analyte panel.
    Keywords:  antiepileptics; human serum; multiparametric analysis; psychotropics; toxicology
    DOI:  https://doi.org/10.1002/jssc.70560
  3. Adv Exp Med Biol. 2026 ;1359 145-158
    Advancing Spatial Lipidomics with MALDI-MS Imaging.
    Estefania Garcia-Calvo, Gabriel A Peñalver, Jose Luis Luque-Garcia.
      Spatial lipidomics has emerged as a powerful approach for investigating the molecular organization of biological tissues by combining lipid analysis with spatially resolved information. Among the available techniques, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has become a key platform for mapping lipid distributions directly in tissue sections without the need for labeling. This chapter provides a comprehensive overview of recent advances in spatial lipidomics using MALDI-MSI, with particular emphasis on sample preparation strategies, matrix selection and deposition methods, and analytical approaches for lipid identification. Critical steps influencing data quality, including tissue preservation, sectioning, matrix application, and mitigation of ion suppression effects, are discussed in detail. Furthermore, the identification of major lipid classes, such as phospholipids, sphingolipids, neutral lipids, glycolipids, fatty acids, and cholesterol, is addressed through characteristic ionization behaviors and diagnostic fragmentation patterns. Finally, the integration of MALDI-MSI with thin-layer chromatography is presented as a complementary strategy to enhance lipid coverage and reduce ion suppression. Together, these approaches highlight the versatility of MALDI-MSI as a robust tool for advancing spatial lipidomics in biomedical research.
    Keywords:  Ion suppression; Lipid imaging; MALDI-MSI; Matrix selection; Sample preparation; Spatial lipidomics; Tandem mass spectrometry; Thin-layer chromatography
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_9
  4. Adv Exp Med Biol. 2026 ;1359 597-602
    A Novel Approach for Post-Acquisition Mass Calibration in Metabolomic Profiling by High-Resolution Mass Spectrometry.
    Newman Zhang, Guoan Zhang.
      High-resolution mass spectrometry (HRMS) is essential for metabolomics due to its ability to deliver high mass accuracy for confident metabolite identification. However, maintaining this accuracy during large-scale studies is challenging because of instrumental drift, which can compromise data quality. Existing correction strategies, such as frequent recalibration, QC-based adjustments, or internal standard spiking, are often disruptive, costly, or limited in robustness. We present a novel post-acquisition mass calibration approach that uses endogenous metabolites as internal references, eliminating the need for additional experimental steps. Using hydrophilic interaction liquid chromatography coupled with HRMS (HILIC-HRMS) and a predefined metabolite panel, we demonstrate that a preliminary mass matching using a wide mass tolerance window provides sufficient reference points for estimating drift and correcting mass errors. The method effectively removes m/z-dependent deviations and restores accurate mass measurements across diverse sample types. This strategy is robust, easy to implement, and broadly applicable to targeted metabolomics workflows, offering a practical solution for improving mass accuracy in large-scale studies without added cost or complexity.
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_37
  5. Adv Exp Med Biol. 2026 ;1359 679-692
    Application of Ion Mobility Mass Spectrometry in Lipidomics.
    Fereshteh Zandkarimi, Lewis M Brown.
      Lipids play significant roles in biological systems, and the study of lipid metabolism may provide a new insight into the diagnosis and pathophysiology of diseases. Recent developments in high-resolution mass spectrometry techniques combined with high-performance chromatographic methods provide deep insight into lipid analysis. Addition of ion mobility mass spectrometry orthogonal to LC-MS analysis workflow enhances the separation of complex lipids, improves isomer resolution, and increases confidence in lipid identification and characterization. In this chapter, we describe the principle of traveling wave ion mobility mass spectrometry (TWIMS) and its applications in untargeted LC-MS analysis for characterizing the structural diversity and complexity of lipid species in biological samples.
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_41
  6. Anal Chem. 2026 Sep 29. 98(38): 28218-28228
    Cyclic Ion Mobility Separations of Free Oxylipins.
    Eric C Gier, Facundo M Fernández.
      Oxylipins are oxygenated lipid metabolites derived from polyunsaturated fatty acids (PUFAs). They play interconnected roles in physiological processes such as inflammation and vascular function, and their dysregulation has been linked to diseases, including cardiovascular, metabolic, and immunological disorders. Liquid chromatography (LC) has a limited ability to resolve the large number of isomers and isobars within this diverse lipid class. Ion mobility spectrometry (IMS) offers an orthogonal gas-phase separation technique and has been shown to improve peak capacity for isomers that differ by more than 1-2% in collision cross section (CCS). High-resolution IMS platforms have progressively enabled the separation of isomers with increasingly similar gas-phase structures and offer the potential to separate complex mixtures in experiments such as mass spectrometry imaging where LC is not available. Here, we demonstrate the application of high-resolution cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS) to separate and characterize six complex mixtures of authentic oxylipin standards. Results show that deprotonated oxylipin species often exhibit multiple mobility features that emerge only after extended separations, whereas metal-adducted species, especially sodium adducts, yield clearer single peaks. Optimized traveling wave parameters enabled the separation of mixtures containing three to five oxylipins within 3-10 m of effective path length before ion wrap-around occurred, resolving features with ΔDTCCS% of approximately 0.5% without front-end chromatographic separation. Multipass cIMSCCSN2 measurements under optimized conditions were highly reproducible and closely matched the DTCCS reference values from Moran-Garrido et al. and da Silva et al., with average deviations of 0.33-0.76%. These findings support the use of multipass cIMS experiments and cIMSCCS measurements as valuable tools for oxylipin separation and annotation, particularly in the absence of chromatographic retention time data.
    DOI:  https://doi.org/10.1021/acs.analchem.6c03450
  7. Adv Exp Med Biol. 2026 ;1359 581-595
    Analytical Methods for Mass Spectrometry-Based Metabolomics Studies.
    Siyu Wang, Ian A Blair, Clementina Mesaros.
      The advancement of mass spectrometry-based analytical platforms largely facilitates small-molecule metabolomics studies, which allows analysis of a large number of metabolites from bio-samples simultaneously and gives a general picture of metabolic changes related to diseases or environmental alteration. Due to the large diversity of cellular metabolites, globally and precisely examining metabolic profile remains the most challenging part in metabolomic experiment. Mass spectrometry coupled with liquid chromatography enhances the sensitivity and resolving power of metabolites identification and quantification, as well as the versatility of analyzing a wide array of metabolites. In this chapter, we discussed the technical aspects of each step in the workflow of metabolomics studies we aimed to give technical guidelines for metabolomics investigation design and approach.
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_36
  8. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2442-2452
    Bridging Speed and Confidence in Metabolomics: A Retention Time and MS2-Guided HILIC-Orbitrap Workflow.
    Jonas Rösler, Constantin P Krempe, Feyza Cansiz, Jaqueline Leddin, Friederike Jahr, Jost Guinand, Sven W Meckelmann, Alpaslan Tasdogan, Oliver J Schmitz.
      Personalized treatment strategies are rising within modern medicine approaches to dynamic and heterogeneous diseases such as cancer. Human metabolism is important for the understanding of these diseases and their mechanisms, but metabolomics remains often unused in multiomics approaches due to practical challenges in sample analysis and, more importantly, data analysis. Automated feature analysis with many false-positive annotations and a rather long analysis time is effectively hindering rapid metabolite screening, as it would be needed in medical research. Here, we report a novel and efficient workflow for rapid metabolite screening with the capability of yielding high-quality metabolomics data, including data analysis. Therefore, a HILIC (superficially porous sulfobetaine) method has been optimized to separate polar metabolites in complex samples in less than 9 min, and an open-source compatible retention time database has been implemented for this rapid screening method, including about 400 metabolites in central metabolic pathways. The method operates on a Q-Exactive Plus Orbitrap in DDA full-scan acquisition based on an inclusion list and has been shown to be highly repeatable and sensitive. Moreover, false-positive annotations could be severely reduced, enabling a simplified and slim data analysis approach. Using the supplied database and the code for data filtering, a rapid metabolite screening can be conducted, suitable for the application as a rapid metabolic profiling strategy in biological and medical research.
    Keywords:  HILIC; cancer; metabolomics; suspected target screening; system medicine
    DOI:  https://doi.org/10.1021/jasms.6c00203
  9. Biochimie. 2026 Oct 22. pii: S0300-9084(26)00271-3. [Epub ahead of print]
    Simultaneous Quantification of Total Homocysteine and Methylmalonic Acid by LC-MS/MS for Comprehensive Assessment of Vitamin B12 and Folate deficiencies.
    Irina Rotaru, Elise Jeannesson, Maryline Schwartz, Jean-Louis Guéant, Rosa-Maria Guéant-Rodriguez.
      Vitamin B12 (cobalamin) and folate deficiencies are preventable causes of neurological and hematological disorders, particularly in vulnerable populations. Functional biomarkers such as total homocysteine (tHcy) and methylmalonic acid (MMA) are more sensitive indicators of metabolic impairment than circulating vitamin B12 concentration. However, their simultaneous quantification remains analytically challenging due to chemical diversity and the presence of structurally related endogenous compounds. Here, we present a robust, high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous quantification of tHcy and MMA in plasma, urine, and dried blood spots. The method employs a simple protein precipitation workflow, efficient disulfide reduction, and optimized chromatographic separation to achieve baseline resolution of MMA and tHcy within a 6-minute run, without derivatization. Validation demonstrated excellent linearity (R2 ≥ 0.999), precision (CV < 5%), and accuracy (bias < ±10%) across physiological and pathological concentration ranges. The lower limits of quantification were 0.78 μmol/L for tHcy and 0.13 μmol/L for MMA, with no significant matrix effects or carry-over. Clinical application in a local reference population (n = 400) confirmed age-dependent tHcy distributions and established an upper MMA reference limit of 0.40 μmol/L, aligning with published thresholds for cobalamin deficiency. This method supports improved detection of functional vitamin B12 deficiency, particularly in resource-limited settings, and has been successfully applied in neonatal screening, clinical research, and fundamental and population studies.
    Keywords:  LC–MS/MS; Vitamin B12 deficiency; clinical diagnostics; homocysteine; metabolic biomarkers; methylmalonic acid
    DOI:  https://doi.org/10.1016/j.biochi.2026.10.025
  10. Anal Chem. 2026 Sep 15. 98(36): 26818-26830
    Extensive Quantitative Profiling of Plasma Steroidome and Prostaglandin Metabolites for Studies of Female Reproductive Physiology.
    Haolin Chen, Luca Bürgi, Anna-Katharina Hankele, Reto Giacometti, Susanne E Ulbrich, Laurent Bigler.
      Steroid hormones and their metabolites orchestrate female reproductive physiology. Key analytes such as 17β-estradiol and progesterone are integral to standard clinical practice worldwide. For more advanced endocrine monitoring of female reproduction, current analytical approaches lack automated throughput, broad metabolite coverage, and sufficient sensitivity. Herein, we present an ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) workflow that targets 56 selected steroids (estrogens, progestogens, androgens, glucocorticoids, and steroid conjugates) and 5 prostaglandin metabolites for quantitative profiling using 250 μL of plasma within a single pipeline. The workflow integrates optimized, automated protein precipitation-enhanced solid-phase extraction and two complementary chromatographic separations with tailored eluent additives and ionization modes to accommodate the chemical diversity of the broad target panel. A full method validation demonstrated excellent performance, with low limits of quantification (5-200 pg/mL) determined in charcoal-stripped plasma as a surrogate matrix. The workflow was applied to authentic cattle (n = 5) and human (n = 18) plasma samples from males and, particularly, females across the female reproductive cycle and selected pregnancy stages. Both well-established endocrine hormones and their metabolites, as well as analytes whose roles in reproduction remain insufficiently characterized, were among the 42 and 48 targets detected in cattle and human samples, respectively. Compound-specific, valley-split, and composite quantification were reported separately. This demonstrates extensive target coverage and robust quantitative performance across biological matrices with distinct physiological contexts. The workflow thus offers a robust tool for steroidomic studies and enables broad-spectrum monitoring of endocrine dynamics for basic, translational, and clinical research.
    DOI:  https://doi.org/10.1021/acs.analchem.6c03626
  11. Anal Chem. 2026 Oct 20. 98(41): 29604-29615
    Drug Metabolism and Drug-Drug Interactions Studied Using High-Throughput Ambient Mass Spectrometry.
    Mousumi Saha, Nari Talaty, Nicolás M Morato, Mahdiyeh Shahi, Christopher J Welch, Yunfei Feng, Christina R Ferreira, David Wagner, Andreas Kaerner, Robert Graham Cooks.
      Rapid characterization of drug metabolism and drug-drug interactions (DDIs) with quantitative rigor remains challenging due to complex samples and labor-intensive workflows. We present a high-throughput (HT) ambient mass spectrometry (MS) approach using desorption electrospray ionization (DESI) that unites three complementary capabilities available using two different mass spectrometers: (A) untargeted screening to survey the metabolic space, (B) product ion scan tandem MS to characterize novel metabolites, and (C) multiple reaction monitoring (MRM) to deliver precise quantitation of substrates and metabolites. Applying the methodology to diverse in vitro systems, we track substrate depletion, metabolite formation, and DDIs with quantitative accuracy (error <9% for MRM quantitation) validated against liquid chromatography (LC) MS. The method operates two to three orders of magnitude faster (1 s/sample) than traditional LC-MS methods. This allows hundreds of substrate-enzyme-DDI combinations to be followed in time-resolved fashion using ∼4 × 104 individual DESI-MS measurements, acquired at a rate of >3,000 measurements/hour. By combining HT screening and targeted monitoring, the DESI-MS approach delivers metabolic discovery with robust quantitation, overcoming a central bottleneck in large-scale drug metabolism studies. This investigation aims to provide a high-throughput analytical approach with broad utility in drug discovery, toxicology, and precision medicine workflows.
    DOI:  https://doi.org/10.1021/acs.analchem.6c04039
  12. Methods Mol Biol. 2027 ;3092 133-139
    Untargeted UHPLC-HRMS Lipidomic Profiling of Ticks for Alpha-Gal Syndrome Research.
    Hanna Nikolaichuk, Anna Kozub-Pędrak, Joanna Kulisz, Zbigniew Zając, Aneta Woźniak, Alejandro Cabezas-Cruz, Emilia Fornal.
      Lipids are a fundamental group of biomolecules that play diverse roles in biological systems, including energy storage, membrane architecture, and intra- and extracellular signaling. They are classified into eight major categories, and more than 50 000 distinct lipid structures are currently reported in the Lipid Maps Structure Database (LMSD). Given their importance in cellular metabolism and physiology, accurate identification and quantification of lipids are essential. In ticks, lipid metabolism is closely associated with physiological processes related to survival, pathogen transmission, and host interaction. Tick blood-feeding has also been linked to the development of alpha-gal syndrome (AGS), a delayed allergic reaction to mammalian-derived products, suggesting that characterization of tick lipid and glycolipid composition may provide insights into mechanisms of host sensitization. This chapter describes a protocol for untargeted lipidomic analysis of tick samples using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). The workflow includes rapid sample freezing, tissue homogenization, solvent-based lipid extraction, protein precipitation, and sample reconstitution prior to analysis. Lipid separation is achieved using reverse-phase chromatography on a C18 column, followed by detection with a quadrupole time-of-flight (Q-TOF) mass spectrometer operating under optimized ionization conditions. The use of blanks and pooled quality control (QC) samples ensures analytical stability and reproducibility. The presented method enables comprehensive profiling of lipids in tick tissues and provides a reproducible platform for studies of tick biology, host-tick interactions, and tick-induced sensitization processes, supporting the mechanistic studies and the identification of potential lipid-based biomarkers.
    Keywords:  Arthropod metabolomics; High-resolution mass spectrometry; Tick lipidomics; Ultra-high pressure lipid chromatography
    DOI:  https://doi.org/10.1007/978-1-0716-5635-8_12
  13. Methods Mol Biol. 2027 ;3092 83-96
    Analysis of Metabolomics Response to Tick Saliva in Human Cells.
    Sara Samino, Rita Vaz-Rodrigues, Almudena González-García, José de la Fuente, Núria Amigó.
      This chapter describes a workflow for the analysis of the metabolomic response of the human basophilic cell line KU812 exposed to Ixodes ricinus tick saliva using ¹H-nuclear magnetic resonance (NMR) spectroscopy. The protocol includes procedures for cell culture, harvesting, washing, and metabolite extraction, followed by the separation of aqueous and lipid fractions. Detailed instructions for sample preparation and NMR data acquisition are provided for both fractions. Spectral processing and metabolite quantification are performed using targeted profiling approaches based on constrained line-shape fitting, enabling accurate analysis of complex biological samples. Metabolite identification is supported by spectral databases and literature references, and absolute concentrations are obtained using internal standard-based quantification methods. Finally, data normalization based on cell number ensures comparability across samples. Overall, this protocol provides a robust and reproducible strategy for investigating metabolic alterations induced by tick saliva in human cells.
    Keywords:  Allergy; KU812 cells; Lipidomics; Metabolic response; Metabolomics; Spectral deconvolution; Targeted profiling; Tick saliva; ¹H-NMR spectroscopy
    DOI:  https://doi.org/10.1007/978-1-0716-5635-8_8
  14. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2463-2471
    Ionic Solid Matrices Applied via Low-Temperature Evaporation Enable High-Resolution and Sensitive MALDI Imaging of Metabolites.
    Toufik Mahamdi, Nadia Moltó, Mireia Arasa, Roger Giné, Jordi Rofes, María García-Altares, Maria Vinaixa, Oscar Yanes.
      Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) enables spatially resolved molecular analysis of biological tissues. However, imaging low-molecular-weight metabolites remains challenging because conventional organic matrices generate intense background signals in the low m/z region. Ionic matrices can reduce matrix-related interferences, improve spectral reproducibility, and enhance sensitivity. However, their application in MALDI-MSI has remained limited, largely due to the need for additional matrix preparation and the challenging wet deposition of viscous ionic liquid matrices, and has mainly focused on lipid imaging above m/z 500. Here, we present a novel approach combining ionic solid matrices (ISMs) with low-temperature thermal evaporation (LTE) to enhance MALDI-MSI performance for small metabolites. ISMs based on α-cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB) provided superior sensitivity and reduced matrix background. In particular, CHCA + N,N-diethylaniline enabled the detection and annotation of 69 metabolites with m/z < 500 in mouse brain tissue at 20 μm spatial resolution. When applied to mouse pancreas, this ISM allowed the first specific localization of melatonin and 3-iodotyrosine within the islets of Langerhans, opening new avenues for spatial metabolomics in endocrine research.
    Keywords:  MALDI; ionic matrix; mass spectrometry Imaging; spatial metabolomics
    DOI:  https://doi.org/10.1021/jasms.6c00219
  15. Anal Chem. 2026 Sep 22. 98(37): 27280-27292
    Covalent Organic Framework-Based Solid Phase Microextraction Coating for Rapid Screening and Quantification of Drugs of Abuse and Artificial Sweeteners in Surface Waters.
    Diana M Cárdenas-Soracá, Kanchan Sinha Roy, Emir Nazdrajić, Janusz Pawliszyn.
      Solid-phase microextraction (SPME) has emerged as a powerful tool used for extracting analytes from complex matrices, offering high sensitivity, automation potential, and high-throughput efficiency. Despite its advantages, its performance is often limited by the selectivity and physicochemical properties of conventional coatings. This study addresses the limitations of conventional SPME coatings for monitoring environmental contaminants by introducing a nitrogen-rich covalent organic framework (COF) as an SPME extraction phase/coating. The COF-based SPME coating was implemented in a coated-blade spray (CBS) device format and was used to develop a robust analytical workflow that combined ambient mass spectrometry ionization via CBS for rapid screening, followed by LC-MS/MS for confirmation and quantification. Statistical validation using a t test showed that only 3 of 43 analytes exhibited statistically significant differences in loss during the microdesorption step of the CBS-MS/MS screening. The results demonstrate that the COF-based SPME coating facilitates simultaneous extraction of analytes with varying polarities from river samples without altering the sample matrix. The final protocol achieved limits of quantification ranging from 0.025 to 5 ng mL-1. The method was successfully applied to river samples, quantifying the target analytes and demonstrating that LC separation remains essential for confirmation. This work highlighted the effectiveness of a COF-based SPME coating as a next-generation extraction phase that simplifies rapid ambient MS screening, followed by traditional LC-MS/MS for confirmation and quantification, all within a single coated SPME device.
    DOI:  https://doi.org/10.1021/acs.analchem.6c00227
  16. Anal Chem. 2026 Oct 06. 98(39): 28629-28637
    Enabling High-Throughput Tissue Sectioning for Robust Lipid Mass Spectrometry Imaging.
    Ruben Jacobs, Ritesh Chidambaram, Vincent Steinbacher, Chenwei Wei, Tim Ragan, Michiel Vandenbosch, Ron M A Heeren.
      Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been established as a powerful tool for the spatial characterization of molecules. Recent advances have been driven by improvements in the spatial resolution, acquisition time, and sensitivity. Although MALDI-MSI excels in the label-free, multiplexed detection of biomolecules, variations in sample preparation remain a significant source of experimental variability. Here, we present a workflow demonstrating the integration of a robust, completely automated tissue section processing system into a MALDI workflow. Importantly, PFA fixation and agarose embedding are demonstrated to preserve lipid compositional distributions. Combined, it enables robust and stable lipid imaging across a completely sectioned mouse brain. The integration of the Marinus MP system advances mass-spectrometry imaging toward a fully automated workflow, significantly reduces sample-preparation variability, and enables more consistent, reliable data acquisition and improved biological interpretation. Parallel with sectioning, serial two-photon (STP) tomography is used to acquire high-resolution digital images of every single section, providing a structural reference for downstream analyses. We demonstrate how the Allen Mouse Brain Atlas can be seamlessly integrated with these multimodal imaging data sets. This workflow enables precise region-specific comparisons and enriches the anatomical context with robust molecular information.
    DOI:  https://doi.org/10.1021/acs.analchem.6c03106
  17. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2453-2462
    A Liquid Chromatography-Mass Spectrometry Method to Quantify Total Coenzyme A Concentration and Isotopic Labeling.
    Amelia L Taylor, Nathaniel W Snyder, Caroline R Bartman.
      Coenzyme A is an essential cofactor synthesized from pantothenate, which carries activated acyl groups in cellular metabolic reactions. Coenzyme A participates in catabolism of carbohydrates, fats, and amino acids; biosynthesis of fatty acids, cholesterol, and heme; and protein modification, including acetylation and 4-phosphopantetheinylation. Despite CoA's critical functions, the regulation of CoA levels and the rate of CoA synthesis in different cell types and disease states are not well understood. Acyl-CoA species are challenging to measure due to instability, poor ionization, and the wide range of biochemical properties conferred by different acyl chain lengths; moreover, most current methods cannot measure CoA isotopic labeling, required to quantify the CoA synthesis rate or to measure concentration using isotope-labeled internal standards. Here, we describe a method to quantify the concentration and isotopic labeling of total CoA, defined as the sum of CoASH plus all acyl-CoA species. Acyl-CoA species are hydrolyzed using sodium hydroxide to remove acyl chains; then, CoA is derivatized with N-ethylmaleimide (NEM). Following protein precipitation and solid-phase extraction, samples are analyzed by liquid chromatography-mass spectrometry. This method is linear in a wide range that captures mouse tissue CoA levels, with accuracy within 15% error and precision below 15% relative standard deviation for standards and tissue samples. We applied this method to measure total CoA concentration in five mouse tissues and the total CoA synthesis rate in mouse liver via infusion of 13C-15N-pantothenate. Overall, this method offers a tractable approach to measure total CoA concentration and synthesis rate in health and disease.
    DOI:  https://doi.org/10.1021/jasms.6c00206
  18. Adv Exp Med Biol. 2026 ;1359 159-180
    The Potential for Ion Mobility in Pharmaceutical and Clinical Analyses.
    Kelly L Wormwood, Liulin Deng, Ahmed Hamid, Daniel DeBord, Laura Maxon.
      The pharmaceutical and clinical industries are imperative for the maintenance of global health and welfare and require accurate, reproducible, and high-throughput analyses. Technological advancements, such as the development and implementation of liquid chromatography-tandem mass spectrometry (LC-MS), have allowed for improvements in these areas; however, there is still room for development. One way in which current analyses may be improved is by the implementation of ion mobility technology. Ion mobility has the capability to produce much more comprehensive data sets by providing separation of isomers as well as improving throughput, with separations being performed as fast as 60 ms. Here, we will discuss the potential for ion mobility to assist in the two specific areas of glycosylation monitoring of biological drugs and vitamin D analysis as representatives of ion mobility's potential in both the pharmaceutical and clinical industries, respectively, as well as the current hurdles of ion mobility adoption in both fields.
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_10
  19. J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Oct 19. pii: S1570-0232(26)00432-0. [Epub ahead of print]1285 125343
    Simultaneous quantification of remimazolam, midazolam, 1'-hydroxymidazolam, and dexmedetomidine in rat plasma by LC-MS/MS: application to biological samples and partial validation in ECMO-derived plasma.
    Rina Kakuba, Yuhki Sato, Yu Fujii, Yuka Nagatsuka, Takuya Abe, Yutaka Fujii.
      The objective of this study was to develop and validate a sensitive reversed-phase liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous quantification of remimazolam (RMZ), midazolam (MDZ), 1'-hydroxymidazolam (1'-OH-MDZ), and dexmedetomidine (DEX) in rat plasma, in compliance with current FDA bioanalytical guidelines. Protein precipitation with esterase inhibition was optimized for 50 μL of rat plasma. Calibration ranges were established to cover the expected in vivo concentrations in pharmacokinetic studies. Full validation was conducted using normal rat plasma, and assay performance was further confirmed by partial validation using extracorporeal membrane oxygenation (ECMO)-derived plasma. The method achieved lower limits of quantification (LLOQs) of 10 ng/mL for RMZ and MDZ, 5.0 ng/mL for 1'-OH-MDZ, and 1.0 ng/mL for DEX. Calibration curves were linear (r2 ≥ 0.99) using weighted (1/x or 1/x2) regression. Within- and between-run accuracy and precision met acceptance criteria (≤15%, and ≤ 20% at the LLOQ). Extraction recovery was consistent, and matrix effects were adequately controlled. RMZ stability was improved through the combined use of sodium fluoride, EDTA-2 K, cooling, and acidification during sample handling. The applicability of the method was demonstrated by quantifying all analytes in plasma samples obtained from rats following intravenous administration. This assay enables simultaneous quantification of clinically relevant sedatives and an active metabolite in small-volume rat samples and may facilitate future pharmacokinetic investigations in preclinical ECMO models.
    Keywords:  1′-Hydroxymidazolam; Dexmedetomidine; ECMO; LC–MS/MS; Midazolam; Rat plasma; Remimazolam
    DOI:  https://doi.org/10.1016/j.jchromb.2026.125343
  20. Anal Chem. 2026 Oct 06. 98(39): 29052-29062
    An N,N-Dimethylethylenediamine-Derivatized In Silico Mass Spectral Library for Comprehensive Profiling of Isothiocyanates in Brassicaceae Plants.
    Huidan Li, Ye Liu, Jun Ding.
      Isothiocyanates (ITCs) are bioactive hydrolysis products of glucosinolates in Brassicaceae plants with diverse health-promoting properties. However, comprehensive profiling of ITCs remains challenging due to the limited availability of authentic standards, the underexplored structural diversity of naturally occurring ITCs, and poor mass spectrometry (MS) detection sensitivity. Here, we established a N,N-dimethylethylenediamine (DMEDA) derivatization strategy and constructed an in silico MS/MS library for systematic ITC annotation. DMEDA derivatization markedly improved LC-MS detection sensitivity, enabling the reliable detection of low-abundance ITCs with limits of detection at the nanomolar level. Detailed characterization of the MS/MS fragmentation behaviors of derivatized ITC standards revealed subclass-dependent fragmentation patterns, which were subsequently translated into spectral prediction rules for the generation of an in silico mass spectral library with 2209 simulated ITC structures. Application of the developed workflow to Brassicaceae plant samples enabled the annotation of 50 endogenous ITCs, including 4 low-abundance compounds that were previously not reported. Our work provides a valuable resource for the systematic exploration of ITC structural diversity and facilitates functional studies of glucosinolate-derived bioactive metabolites.
    DOI:  https://doi.org/10.1021/acs.analchem.6c04198
  21. Anal Chem. 2026 Sep 29. 98(38): 27885-27894
    Fully Automated Purification of Small Molecules Using Online MicroSPE-UPLC-SPE.
    Venkata Ganesh Jarubula, Gerd Grewing, Pauline Stark, Maximilian Frey, Dario Esposto, Simon Isfort, Marvin Hempel, Guillaume Patoine, Henriette Uthe, Alain Tissier, Gerd U Balcke.
      Structural annotation of metabolites remains a key challenge in metabolomics, as NMR-based structure elucidation for every unknown UPLC peak is limited by low sensitivity and time-consuming purification. To overcome these constraints, we developed an online microSPE-UPLC platform that enables fully automated, high-throughput peak fractionation. The system allows the injection of up to 1 mL of organic extract onto microSPE cartridges in a 96-well format for metabolite enrichment and cleanup. A dual-pump loading and refocusing strategy ensures quantitative transfer to UPLC, maintaining high chromatographic resolution while collecting narrow fractions on postcolumn microSPE. Fractions can be directly eluted with deuterated solvents for NMR analysis, eliminating drying steps and preserving volatile compounds. This approach enables milligram-scale isolation of natural products per compound within a single day. The workflow was validated using plant and fungal extracts, enabling the successful purification and characterization of several sesquiterpenoids and a diterpenoid.
    DOI:  https://doi.org/10.1021/acs.analchem.6c00842
  22. MethodsX. 2026 Dec;17 104201
    High throughput analysis of contaminants of emerging concern in complex matrices.
    Tsz Yung Patrick Wong, Bent Speksnijder, Gayani R Kapukotuwa, Oksana Golovko.
      Contaminants of emerging concern (CECs) occur across diverse aquatic matrices, but their reliable quantification remains challenging because of large differences in matrix composition. This study developed and validated a rapid online solid-phase extraction coupled with ultra-high-performance liquid chromatography-tandem mass spectrometry (online-SPE-UPLC-MS/MS) method for the simultaneous determination of 46 pharmaceuticals, industrial chemicals, pesticides, and per- and polyfluoroalkyl substances (PFAS). Method performance was evaluated in six matrices: tap water, river water, wastewater influent and effluent, and untreated and treated landfill leachate. The method was validated by evaluating compound- and matrix-dependent limits of quantification (LOQs), matrix effects and recoveries. Pronounced matrix-induced ion suppression was observed before internal-standard correction, particularly in wastewater influent and untreated landfill leachate. Most analytes showed recoveries within 50-150% and precision below 30% relative standard deviation. In addition, stability was tested, which was highly matrix and storage dependent, with freezing generally providing improved preservation. Validation was included in method application for untreated and treated leachates from five Swedish landfills. A multi-class analytical method was developed and evaluated in six matrices The method was validated using matrix-specific assessment of sensitivity, accuracy, precision, recovery, matrix effects, and stability during storage. The method was applied to untreated and treated leachates from five Swedish landfills.
    Keywords:  Industrial chemicals; Online SPE; PFAS; Pharmaceuticals; UPLC-MS/MS
    DOI:  https://doi.org/10.1016/j.mex.2026.104201
  23. Anal Chem. 2026 Sep 29. 98(38): 28006-28016
    InSitu Untargeted Metabolite Identification and Spatial Mapping by Clustering Resampling Mass Spectrometry Imaging.
    Yu Wang, Chaoting Shi, Yilin Liu, Yu Ye, Zhuolin Jin, Wenjian Gu, Fan Wu, Fei Ran, Wenlin Wu, Bing Xia, Yan Zhou.
      Mass spectrometry imaging enables the spatially resolved analysis of molecular distributions in biological tissues. However, in situ untargeted metabolite identification remains challenging due to the inherent trade-off between spatial resolution and in situ tandem mass spectrometry (MS2) acquisition. Here, we developed clustering resampling mass spectrometry imaging (CR-MSI), a method that innovatively converts in situ MS2 acquisition from countless pixel scans to a few representative points testing. CR-MSI allows the acquisition of both spatial localization and structural fragmentation data for metabolites from a single tissue section. Additionally, we have engineered an integrated device that automates the CR-MSI workflow, transforming MS2 acquisition from an empirical, operator-dependent procedure to an objective, data-driven process. Moreover, the synchronization between MSI data acquisition and processing has improved the efficiency and overall MSI throughput. When applied to rat brain, CR-MSI collected 1,175 MS2 species, representing a 410% increase compared with conventional techniques. This approach will vastly enhance the structural elucidation of untargeted mass spectrometry imaging.
    DOI:  https://doi.org/10.1021/acs.analchem.6c02449
  24. J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Oct 18. pii: S1570-0232(26)00431-9. [Epub ahead of print]1285 125342
    Sample preparation and analytical determination of triazole antifungal agents in biological matrices: From conventional workflows to clinical monitoring.
    Chao Wang, Jiejin Song, Cuili Yao, Sha Li, Di Chen, Huiyu Wei.
      Reliable analytical determination of triazole antifungal agents is essential for therapeutic drug monitoring because of large interindividual pharmacokinetic variability, variable protein binding and clinically important drug interactions. This narrative review evaluates studies published from 2010 onward on fluconazole, itraconazole, hydroxyitraconazole, voriconazole, voriconazole N-oxide, posaconazole and isavuconazole in biological matrices. Across plasma, serum and low-volume matrices, protein precipitation provides rapid preparation for many routine assays, whereas liquid-liquid extraction, microextraction and solid-phase formats offer greater cleanup or enrichment when matrix interference or sensitivity is limiting. Liquid chromatography with ultraviolet or fluorescence detection remains accessible and effective for focused therapeutic drug monitoring when chromatographic resolution is adequate; liquid chromatography-mass spectrometry provides higher molecular selectivity for multiplex measurement of parent drugs and metabolites. Microsampling, online preparation, direct mass spectrometry and selective sorbents can reduce sampling or handling burdens, but their value depends on agreement with validated reference procedures. Method selection should therefore be governed by matrix fitness, the explicitly defined recovery metric, clinically relevant quantification limits, throughput, traceability and turnaround time rather than sensitivity or novelty alone.
    Keywords:  Biological matrices; Liquid chromatography; Mass spectrometry; Sample preparation; Therapeutic drug monitoring; Triazole antifungals
    DOI:  https://doi.org/10.1016/j.jchromb.2026.125342
  25. Pract Lab Med. 2026 Dec;52 e00559
    Analytical validation of a MALDI-TOF mass spectrometry method for serum IGF-1 measurement and its comparison with LC-MS/MS and CLIA.
    Ruiquan Cao, Huan Ding, Yong Xia, Xueting Ma, Anping Xu, Hou-Long Luo, Ling Ji.
       Background: Insulin-like growth factor 1 (IGF-1) is an important biomarker in the diagnosis and monitoring of growth hormone-related disorders. MALDI-TOF mass spectrometry has potential for high-throughput IGF-1 measurement, but its analytical performance for routine clinical application requires systematic validation.
    Methods: Analytical performance of a MALDI-TOF MS-based IGF-1 assay was evaluated following CLSI guidelines, including imprecision, accuracy, linearity, limit of quantitation (LOQ), analytical specificity, sample stability, and sample type comparison. Method comparison was performed against LC-MS/MS and CLIA using 287 patient serum samples.
    Results: Intra-assay coefficients of variation (CVs) were 3.66% and 1.82% at low (26.52 ng/mL) and high (375.49 ng/mL) concentrations, respectively; inter-assay CVs were 6.21% and 3.21%. The assay was linear (r = 0.998) with an LOQ of 5 ng/mL. Recoveries ranged from 87.70% to 91.73%. Cross-reactivity with IGF-2 and insulin was negligible. Serum IGF-1 remained stable for 3 days at 25°C, 9 days at 2-8°C, and 12 weeks at -20°C, and tolerated five freeze-thaw cycles. EDTA plasma and serum showed acceptable agreement (mean bias 0.36%-6.62%) for interchangeable use. Method comparison showed strong correlations: MALDI-TOF MS vs. LC-MS/MS (Passing-Bablok: Y = -5.602 + 0.746X, r = 0.996) and vs. CLIA (Y = 2.378 + 0.739X, r = 0.994).
    Conclusions: The MALDI-TOF MS method achieved acceptable analytical performance for serum IGF-1 measurement, including precision, linearity, stability, and specificity. The observed systematic bias relative to LC-MS/MS and CLIA suggests that method-specific reference intervals are needed. MALDI-TOF MS is a reliable and high-throughput alternative for clinical IGF-1 testing.
    Keywords:  Analytical performance; Chemiluminescence immunoassay; Insulin-like growth factor 1; Liquid chromatography-tandem mass spectrometry; MALDI-TOF mass spectrometry
    DOI:  https://doi.org/10.1016/j.plabm.2026.e00559
  26. Anal Chem. 2026 Sep 29. 98(38): 27976-27985
    MSIonization: A Machine Learning Tool for Ionization Mode Prediction of Small Molecules.
    Yatendra Singh, Bakhtyar Sepehri, Zeyad Ibrahim, Robert J Doerksen, Sixue Chen.
      Selection of the optimal ionization mode to use-positive or negative-is a critical step in liquid chromatography-mass spectrometry (LC-MS) analysis of small molecules acquired using electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI). However, determining which ionization mode provides higher ionization efficiency usually relies on empirical knowledge or trial-and-error, particularly for large and chemically diverse compound libraries, which is time-consuming and resource-intensive, representing a major barrier in MS analysis. To address this challenge, we developed MSIonization, a machine learning (ML)-driven tool that predicts the preferred ionization mode (positive or negative) of small molecules. It performs binary classification using molecular structure (SMILES) as input to deliver rapid, scalable predictions accompanied by probability scores and applicability domain assessments, thereby facilitating selection of the preferred ionization mode and improving experimental planning. It offers a user-friendly, offline ML model with a graphical user interface (GUI) that streamlines the MS workflow and minimizes trial-and-error. MSIonization provides a practical decision-support framework that complements chemical intuition and supports experimental planning across a wide range of scientific domains. Looking ahead, it holds significant potential to integrate into AI-driven MS pipelines to predict the ionization mode of chemically diverse small molecules at a large scale to support research across several scientific domains. The package is available in the PyPI repository (https://pypi.org/project/MSIonization/) and can be installed using 'pip install MSIonization' command.
    DOI:  https://doi.org/10.1021/acs.analchem.6c01937
  27. J Agric Food Chem. 2026 Oct 21. 74(41): 32677-32686
    Accurate β-Casein Allergen Quantification in Processed Foods via an Isotope-Labeled Full-Length Protein Internal Standard.
    Yige Wu, Qibin Liang, Rui Chang, Yizhu Chen, Chuncai Liang, Wenkai Cao, Xuan Wu, Sai Fan, Bing Shao, Hui Li.
      Accurate quantification of cow's milk allergens in processed foods by UPLC-MS/MS is challenged by enzymatic digestion variability and complex matrix effects. β-Casein, a major milk allergen, requires reliable quantification. Herein, we developed a novel method for quantifying bovine β-casein using a recombinant, isotope-labeled, full-length protein (β-casein-I) as an internal standard. With a high isotopic labeling rate and sequence homology to the native analyte, β-casein-I corrects errors from digestion, sample preparation, and MS analysis. The validated method showed excellent linearity from 0.1 to 50 ng/mL. In three processed food matrices, mean recoveries were 89-116% with RSD < 13% at three spiking levels, and LODs were 0.2-0.5 μg/g. Specificity was ensured by simultaneous monitoring of two signature peptides, minimizing false positives from cross-reactivity with goat milk. β-Casein was detected in all 11 commercial samples analyzed. This study provides an accurate, reliable approach for milk allergen quantification, significantly advancing traditional peptide-based methods.
    Keywords:  UPLC-MS/MS; accurate quantitation; food allergy; processed foods; β-casein
    DOI:  https://doi.org/10.1021/acs.jafc.6c09713
  28. Adv Exp Med Biol. 2026 ;1359 575-580
    Targeted LC-MS/MS Analysis of Malonic Acid Biomarkers in Clinical Laboratory Applications.
    Vivekananda Shetty.
      LC-MS/MS enables sensitive quantification of malonic acid (MA), methylmalonic acid (MMA), and ethylmalonic acid (EMA) across clinical matrices. MA provides emerging diagnostic value in metabolic assessments, while MMA remains the primary marker of functional vitamin B12 deficiency. EMA is essential for evaluating mitochondrial and fatty-acid oxidation disorders. Advances in extraction and chromatographic strategies continue to improve analytical performance for these biomarkers.
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_35
  29. J Am Chem Soc. 2026 Oct 21. 148(41): 44629-44638
    Isobaric Intramolecular Paternò-Büchi Reactions Enable Multiplexed Quantitation of Fatty Acids down to C═C Locations.
    Lipeng Qiao, Jing Zhao, Yu Xia.
      Fatty acids (FAs), as key lipids in energy storage and signaling, are dynamically regulated to maintain cellular homeostasis. FA profiling has become a valuable approach for investigating lipid reprogramming in disease. Although isomer-resolved mass spectrometry (MS) methods facilitate differentiation of FA isomers, quantitation is limited by the scarcity of isomer standards. Here, leveraging isobaric intramolecular Paternò-Büchi (i2PB) reactions, we develop an isomer-resolved multiplexed quantitation method for FA profiling. The i2PB reagents, synthesized via amidation of benzoyl-phenylalanine with the 6-plex TMT tags at near-quantitative conversion, overcome the low-yield limitations of conventional PB reactions for low-abundance lipids. Rapid i2PB reactions (4 s) enable online integration with liquid chromatography, while subsequent MS2 and MS3 analyses generate reporter ions for 6-channel FA quantitation at the sum composition and C═C location levels, respectively. For FA quantitation, this approach offers improved throughput, amol sensitivity, and a linear dynamic range of 2 orders of magnitude. Using i2PB, we achieve parallel quantitation of over 100 FAs with defined C═C locations in normal and breast cancer cells, providing new insights into metabolic reprogramming of FAs in breast cancer cells.
    DOI:  https://doi.org/10.1021/jacs.6c13601
  30. Anal Chem. 2026 Sep 29. 98(38): 27996-28005
    Enzymatic Ligation Strategy to Enhance Electrospray Ionization Efficiency and Liquid Chromatography─Mass Spectrometry of DNA and RNA Oligonucleotides.
    Max D Sharin, Nina J Fitzgerald, Stephen M Kennedy, Isabella G Park, Kevin D Clark.
      Mass spectrometry (MS) is a powerful technique for characterizing modified RNA as it directly maps and quantifies all mass-altering modifications simultaneously. However, the physicochemical properties of RNA result in poor ionization efficiencies during electrospray ionization, presenting a major barrier to sensitive MS measurements necessary for low-abundance RNA samples and RNAs with low modification stoichiometries. Here, we report a ligation-based approach to increase ionization efficiencies of RNA oligonucleotides. We show that short (∼5 nt), chemically modified DNA oligonucleotides can be enzymatically ligated to RNA to serve as MS signal enhancers. Among a series of signal enhancers appended with various alkyl and alkylimidazolium functional groups, we found that decyl-functionalized derivatives improved MS sensitivity by ∼15-fold compared to the unlabeled oligonucleotide. When ligated to RNA standards, the decyl-modified signal enhancer increased MS signals by an average of 2.1-fold with the additional benefit of improved retention during liquid chromatography (LC) separations without ion-pairing agents. To apply the ligation-based approach to RNase T1 digests of longer RNAs, a multi-step enzymatic approach was optimized to maximize ligation efficiencies. We then ligated signal enhancers to a yeast transfer RNA (tRNA) digest and observed increased MS signals for numerous sequence-informative digestion products. Importantly, the sequences of RNA oligonucleotides ligated to signal enhancers were readily determined by tandem mass spectrometry with collision-induced dissociation. This ligation-based strategy for enhancing LC-MS/MS characterization of RNA creates opportunities to measure low-abundance RNA samples and their modifications.
    DOI:  https://doi.org/10.1021/acs.analchem.6c02458
  31. J Anal Toxicol. 2026 Oct 23. pii: bkag091. [Epub ahead of print]
    Development and Validation of an Oral Fluid LC-MS/MS Method for Screening Emerging Synthetic Opioids Including Fentanyl Analogues, Nitazenes, and Xylazine.
    Chara Parpala, Sotirios Toskos, Christina Matiaki, Evdokia Brousa, Heleni Zaggelidou, Nikolaos Raikos, Orthodoxia Mastrogianni.
      The emergence of highly potent synthetic opioids, including fentanyl analogues, nitazenes, and xylazine-associated drug mixtures, has created significant analytical challenges for forensic and toxicological laboratories. The aim of this study was to develop and validate a qualitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the screening of emerging synthetic opioids in oral fluid. Sample preparation was based on direct extraction of paper swabs with 500 μL of methanol containing 1% formic acid, followed by vortex mixing, ultrasonication, centrifugation, and direct LC-MS/MS analysis without evaporation or reconstitution. Method validation included selectivity and specificity, detection capability, matrix effects, inter-individual matrix variability, processed-sample stability, carryover, and intra-day precision. All target analytes fulfilled the established identification criteria at 1 ng/mL, the lowest concentration evaluated. Intra-day precision was acceptable, with RSD values ranging from 0.6% to 14.8%. Matrix effects were within 80-120% for the majority of analytes at both evaluated concentration levels, although compound-dependent ion suppression or enhancement was observed. Processed samples met the predefined stability criterion for 48 h at 4 °C and 72 h at - 20 °C, and carryover remained below the predefined acceptance criterion. Limited inter-individual variability was observed among the five donor matrices for the subset of analytes evaluated. The developed method provides a simple qualitative screening approach for an expanded panel of emerging synthetic opioids in oral fluid. Evaluation using authentic positive specimens is required to further establish its performance in forensic and DUID applications.
    Keywords:  LC–MS/MS; fentanyl analogues; nitazenes; oral fluid; synthetic opioids; xylazine
    DOI:  https://doi.org/10.1093/jat/bkag091
  32. J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Oct 19. pii: S1570-0232(26)00428-9. [Epub ahead of print]1285 125339
    Separation-based bioanalysis of teicoplanin for therapeutic drug monitoring: Chromatographic selectivity, multicomponent quantification, and microsampling.
    Stefan Gavrilović.
      Teicoplanin is a highly protein-bound glycopeptide supplied as a mixture of structurally related components. Its therapeutic drug monitoring (TDM) result therefore depends on component coverage, calibrator composition, biological matrix, sample preparation, chromatography, and detector response. This critical review maps separation-based teicoplanin methods in human matrices, with emphasis on chromatographic selectivity and biomedical fitness. PubMed/MEDLINE was searched from January 2009 through 18 August 2026 and supplemented by citation searching. Twenty-six eligible primary method publications and three contextual comparison or interlaboratory studies were identified by the present search strategy; these counts do not imply exhaustive coverage. Plasma was the principal matrix in 16 primary methods, serum in seven, dried blood spots (DBS) in two, and urine in one. Twenty methods incorporated mass-spectrometric detection and nine were multiplex assays. HPLC-UV and micellar electrokinetic chromatography made component resolution visible but often required longer analysis or enrichment. Targeted LC-MS/MS supported low-volume and multiplex TDM, although retention, component summation, calibrators, and internal standards differed. High-resolution MS expanded analogue identification, while paired total/unbound assays addressed variable protein binding. A study-level matrix showed inconsistent reporting of matrix effect, carry-over, stability, dilution integrity, and patient-sample comparison. Interlaboratory evidence demonstrates variability but does not isolate calibrator, component-coverage, or internal-standard differences as proven causes. Analytical validity, method agreement, and clinical utility should therefore be evaluated separately. Serum or plasma remains the best-supported reference matrix for routine dose adjustment; DBS requires formal paired agreement and independent validation of any conversion equation. High-resolution MS is valuable for component identification but is not necessary for routine TDM once a targeted measurand and method are validated. Future assays should define the measurand before the platform, document component summation and calibrator traceability, and report matrix-appropriate validation and auditable resource use.
    Keywords:  Dried blood spot; HPLC–UV; Liquid chromatography; Tandem mass spectrometry; Teicoplanin; Therapeutic drug monitoring; Unbound drug
    DOI:  https://doi.org/10.1016/j.jchromb.2026.125339
  33. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2341-2351
    MALDI MSI Workflow for Pharmaceutical Tablets: Toward a Reproducible Strategy for High-Resolution Imaging.
    Athina Lisgara, Alvaro Santos-Neto, Georgia Charkoftaki, Reza Aalizadeh, Michelle Raikes, Scott Pennino, John A Smoliga, Michael Becker, Vladimir V Papov, Nina Gonnella, Vasilis Vasiliou.
      Mass spectrometry imaging (MSI) can complement liquid chromatography-mass spectrometry (LC-MS), the gold standard for impurity assessment, by enabling spatial visualization of active pharmaceutical ingredients (APIs), byproducts, and excipients in solid formulations. With new advances in matrix-assisted laser desorption/ionization (MALDI) MSI, critical factors such as ablated spot size, raster speed, and standardized tablet surface preparation still need to be properly addressed. This study presents an innovative sample holder and sample preparation protocol enabling reproducible up to 10-μm step size acquisition for MSI analysis of tablets. The workflow was validated by embedding several commercial tablets containing various APIs in blocks with epoxy resin, then transversally cut them to expose their surfaces. Following this, the tablet surfaces were trimmed using a cryostat and subsequently polished with lapping diamond films to achieve flat and even surfaces. The tablets were then placed in a custom metal holder for MALDI-trapped ion mobility spectrometry (TIMS)-MSI analysis using a timsTOF fleX. The optimized protocol provides high-quality sample preparation and avoids loss of laser focus, enabling high-throughput analysis with high sensitivity for tablet imaging. This robustness was essential for spatial resolution measurements using the Smartbeam 3D, where precise initial focusing is required to preserve data quality across imaging areas. Consistent high signal sensitivity was achieved for single pixels in 10 mg cetirizine or 20 mg famotidine tablets and digoxin fragments were detected in a 0.25 mg/130 mg tablet. This approach provides an important tool for pharmaceutical development by enabling reliable, high-resolution spatial analysis of active ingredients and impurities in solid dosage forms. Collision cross section (CCS) values from reference standards and tablets, as well as MS/MS data were used for confident identification. LC-MS-based workflows remain essential for quantitative analysis of impurity assessment, while infrared spectroscopy (IR) and nuclear magnetic resonance (NMR) can support formulation level characterization. MALDI-TIMS-MSI complements these approaches by adding direct spatial localization of APIs and API-related molecular features within the tablet matrix.
    DOI:  https://doi.org/10.1021/jasms.6c00161
  34. Talanta. 2026 Oct 21. pii: S0039-9140(26)01420-7. [Epub ahead of print]313(Pt B): 130764
    Ion mobility mass spectrometry for suspect screening of environmental toxicants: Collision cross sections, structural annotation, and fit-for-purpose evidence evaluation.
    Meiqing Jin, Qingwei Zhou, Weihong Wu.
      Ion mobility mass spectrometry (IM-MS) is increasingly used in suspect screening of environmental toxicants because it adds an orthogonal gas-phase separation dimension to LC-HRMS workflows. This review evaluates how ion mobility measurements and derived collision cross section (CCS) values support candidate rejection, structural annotation, and fit-for-purpose evidence evaluation for environmental chemicals. The discussion covers drift tube, traveling-wave, trapped ion mobility, and differential mobility approaches; experimentally derived and predicted CCS resources; and applications to PFAS, pesticides, pharmaceuticals, mycotoxins, petroleum contaminants, industrial chemicals, and exposure-related xenobiotics. Three quantitative tables compare CCS resources, application studies, and prediction or complementary annotation tools, with emphasis on compound coverage, tolerances, matrix-dependent ionization and mobility behavior, and evidence criteria. Experimentally derived CCS values can reduce candidate lists, resolve coeluting features, support homologous-series interpretation, and improve transfer of screening evidence across campaigns. Predicted CCS is useful for prioritization but requires class-aware applicability checks, especially for fluorinated, halogenated, surfactant-like, and polymer-associated chemicals that are sparse in training data. CCS is most defensible when reported with ion identity, adduct, drift gas, calibration or derivation method, replicate uncertainty, matrix behavior, and a stated confidence level. IM-MS should therefore be integrated as a supporting evidence layer and not treated as a stand-alone identifier.
    Keywords:  Analytical toxicology; Collision cross section; Environmental toxicants; Ion mobility mass spectrometry; PFAS; Suspect screening
    DOI:  https://doi.org/10.1016/j.talanta.2026.130764
  35. Brief Bioinform. 2026 Sep 01. pii: bbag576. [Epub ahead of print]27(5):
    Metabolomics workbench: data-driven classification and correlation analysis between metabolite classes, biomarkers, and drugs.
    Mikhail M Khandokhin, Aleksandr Sokolov, Nikolay Oskolkov, Robert Fredriksson, Olga E Titova, Helgi B Schiöth.
      Public repositories now accumulate an unprecedented amount of metabolomics data. Despite the opportunities for large-scale meta-analyses opened by these repositories, the deposited data rarely becomes systematically re-analyzed. We conducted a systematic metadata-based re-analysis of all human blood metabolomics studies in the Metabolomics Workbench performed using Orbitrap or QTOF mass spectrometry, encompassing 44 165 samples. After harmonizing metabolites with PubChem identifiers and embedding them using SMILES representations, we generated a map of 6752 blood metabolites forming 25 structural clusters, and subsequently performed correlation analysis between these clusters, biomarkers, and drugs. Analysis of 337 120 metabolite pairs detected in at least 10 studies showed that structurally related clusters display correlated abundances (ρ up to 0.6). Correlation patterns among established clinical biomarkers revealed candidate metabolic correlates, several with ρ > 0.7. We also developed open-source software enabling similar analyses for any metabolite across the Workbench data explored. Additionally, curating drug-containing datasets enabled meta-analyses for compounds such as acetaminophen, metoprolol, and atenolol, identifying both known and novel metabolic signatures. Besides the biological insights, we have found that Orbitrap and QTOF tend to detect different metabolites, but they give quantitatively coherent results on overlapping compounds. Overall, the present study provides the methodology and software to perform large-scale mining of public metabolomics data enabling its re-analysis to obtain novel biomedical insights.
    Keywords:  biomarkers; blood; drugs; human; meta-analysis; metabolomics
    DOI:  https://doi.org/10.1093/bib/bbag576
  36. Anal Chem. 2026 Sep 15. 98(36): 27077-27087
    A Heating-Assisted Integrated Purification-Enrichment-Derivatization Paper Chip for Rapid MS/MS Quantification of Serum Steroid Hormones.
    Can Tan, Zhangwu Chen, Jingxiong Lin, Yue Zhang, Xunliang Su, Xuan Yu, Zhenqing Cai, Le Wang, Shuo Lei, Yiyong Yan, Jianhua Zhou, Xinming Huo.
      Rapid and reliable simultaneous quantification of multiple steroid hormones is important for the diagnosis and monitoring of endocrine disorders such as polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS). Existing methods are susceptible to ion suppression in complex serum matrices and therefore usually require laborious sample preparation and time-consuming chromatographic separation, limiting their application in high-throughput screening and rapid testing. In this study, we developed an integrated purification-enrichment-derivatization paper chip, termed iPED chip, which integrates diatomaceous earth-assisted online cleanup at the tail end, thermal enrichment at the paper tip, and in situ hydroxylamine derivatization. A programmable induction heating device was also developed to provide a localized, controllable, and noncontact thermal field for the paper reaction zone, thereby promoting analyte enrichment and reaction. Coupled with tandem mass spectrometry, the iPED chip-MS/MS method enabled rapid simultaneous quantification of testosterone (T), androstenedione (4-AD), dehydroepiandrosterone (DHEA), and 17α-hydroxyprogesterone (17-OHP) in serum within 20 min. Method characterization demonstrated effective enrichment of the target hormones, broad linearity over 0.078-40 μg/L in spiked calf serum, low limits of detection of 0.042-0.093 μg/L, recoveries of 95-106%, and RSDs below 10%. In spiked hormone-depleted human serum samples at clinically relevant levels, the results agreed well with those obtained by conventional LC-MS/MS, supporting the reliability of iPED chip-MS/MS and its potential for rapid clinical testing and large-scale biofluid screening.
    DOI:  https://doi.org/10.1021/acs.analchem.6c04260
  37. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2379-2387
    Native, Memory-Bounded Conversion of Mass Spectrometry Imaging Data into the SpatialData Ecosystem.
    Theodoros Visvikis, Wouter-Michiel Vierdag, Luca Marconato, Angeliki Birmpili, Ron M A Heeren, Eva Cuypers.
      Mass spectrometry imaging (MSI) is now a routine modality for spatial molecular profiling and is increasingly combined with histology, multiplexed imaging, and spatial transcriptomics to build richer descriptions of tissue than any single technique can provide. The conceptual case for this multimodal paradigm was settled a decade ago, but the data infrastructure needed to operationalize it at scale has not kept up. Vendor binaries and the imzML exchange format keep MSI outside the OME-NGFF, Zarr, and SpatialData stacks on which the rest of spatial omics has converged, leaving each new experiment to rebuild ad hoc converters from scratch. Here, we present Thyra, an open-source Python library that converts raw vendor and imzML MSI data directly into the SpatialData format. A two-pass streaming sparse matrix engine writes the spectral matrix straight into the output Zarr store, keeping peak memory bounded near 200 MB regardless of data set size and supporting 100+ GB acquisitions. On a representative mouse brain MALDI data set, this yields three- to 4-fold storage reductions and an order-of-magnitude improvement in m/z range query latency, the bottleneck for ion image generation. Once converted, MSI data are directly composable with the scverse analysis ecosystem; we quantify this with an scverse readiness benchmark in which spatial autocorrelation, pixel clustering, and neighborhood enrichment, all standard operations in spatial transcriptomics, run as a one-liner on the converted object. A brief exploratory analysis of a skin biopsy from a psoriasis patient illustrates the analytical surface that the unified container exposes.
    DOI:  https://doi.org/10.1021/jasms.6c00169
  38. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2331-2340
    Enhancing Ion Yields in MALDI-2-MSI Using Dopant-Assisted Post Ionization for High-Resolution MS-Imaging of Lipids and Metabolites.
    Christoph Bookmeyer, Alexander Potthoff, Benedikt Stauff, Klaus Dreisewerd, Jens Soltwisch.
      Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is the most widely used label-free method for mapping the molecular distribution of lipids and metabolites from tissue sections and cell cultures. To mitigate the problem of partially low MALDI ion yields for several of these analyte classes, different post ionization techniques have recently been developed─for example, MALDI-2, where a second UV-laser pulse intersects the initial particle plume to generate additional charges. Here, we show that the MALDI-2 signal intensities of important analyte classes can be further increased upon introducing reactive dopant vapor into the MALDI-2 ion source. Dopant assistance as an optional add-on was realized in prototype form on MALDI-2 ion sources of a Spectroglyph Injector-Orbitrap MSI setup and a timsTOF fleX MALDI-2 instrument. Acetone, anisole, toluene, 2-propanol, and chlorobenzene were tested as dopants. Acetone proved to be the most effective and robust dopant for the given setup and MALDI matrix, and thus was used for further parameter optimization on both instruments. We demonstrate that with dopant-assisted (DA-)MALDI-2, a signal increase of up to 5 orders of magnitude, as compared to regular MALDI, is, for instance, achieved for several classes of sterols, glycerophospholipids, and sphingolipids. Next to the increased intensity of signals for abundant lipids, the total amount of annotated signals (based on MS1) was also majorly increased by the use of dopants. We demonstrate the potential for biomedical imaging applications with the examples of murine spleen and cerebellum sections, analyzed in the positive- and negative-ion mode.
    Keywords:  MALDI-2; dopant; high spatial resolution; ion source design; mass spectrometry imaging; post ionization; signal enhancement
    DOI:  https://doi.org/10.1021/jasms.6c00149
  39. Curr Opin Biotechnol. 2026 Oct 19. pii: S0958-1669(26)00155-2. [Epub ahead of print]102 103590
    Structurally informed metabolite measurements with ion mobility-mass spectrometry.
    Yu-Ting Tseng, Kelly M Hines.
      Although ion mobility-mass spectrometry (IM-MS) is no longer a new technology, new developments in instrumentation and resources for structurally informed measurements are enabling the use of IM-MS in emerging metabolomic applications. Once limited by experimental measurements, the growth of machine-learning strategies to predict collision cross-section values is rapidly increasing the coverage of IM-MS information in metabolite databases. IM-MS instrumentation capable of high-resolution separations is bringing new depth to the level of structural annotation that can be achieved, while creative strategies to combine IM-MS with complementary analytical or chemical methods are further leveraging its ability to resolve small molecule isomers and isobars. This brief review highlights the recent developments of IM-MS for metabolomics with a focus on applications to mass spectrometry imaging, rapid multi-omics, and single-cell analyses.
    DOI:  https://doi.org/10.1016/j.copbio.2026.103590
  40. J Chromatogr Sci. 2026 Oct 07. pii: bmag030. [Epub ahead of print]64(9):
    Glycopyrronium bromide, formoterol fumarate dihydrate and their related compounds with UPLC/PDA-MS for simultaneous determination in pressurized metered-dose inhaler product.
    Serdar Seckin, Serap Saglik Aslan.
      An ultra-performance liquid chromatography (UPLC) technique with photodiode array-mass spectrometry (PDA-MS) detectors has been developed and validated for the determination of glycopyrronium bromide (GB), formoterol fumarate dihydrate (FFD) and their related substances in pressurized meter dose inhalers. This marks the first time the method has been implemented. Chromatographic analyses have been carried out on a UPLC system with a single quadrupole mass spectrometer (QDa) and a PDA detector. A C18 column has been used prior to the injection valve. The column temperature was set to 40°C. For each analysis, 1 μL of sample was injected at a flow rate of 0.1 mL/minute. The mobile phases used were A (0.5% formic acid in methanol) and B (0.5% formic acid in water). The total run time of the method was 30 minutes. The PDA detector was employed at 215 nm while the mass detector was set to extracted ion chromatography (XIC) mode. The range for detecting impurities of GB was found to be between 0.28 and 0.30 ng/mL, with a limits of 0.92-1.01 ng/mL for quantification. GB and FFD demonstrated linear accuracy. We studied the accuracy of related substances within the limit of quantification value range of corresponding impurities and up to 400% of the limit value. The method we used was linear, rapid, reproducible and accurate. Our proposed method is fast, linear, accurate and reproducible. The UPLC-MS method, which utilized QDa with XIC mode, was developed to ascertain the related substances and assay of GB and FFD.
    DOI:  https://doi.org/10.1093/chromsci/bmag030
  41. J Pharm Biomed Anal. 2026 Oct 14. pii: S0731-7085(26)00438-3. [Epub ahead of print]284 117770
    A novel UPLC-ECD method for simultaneous quantification of levodopa, benserazide, and their major metabolites in human plasma and cerebrospinal fluid.
    Siqi Lu, Yuxin Qiu, Shanshan Ma, Qiaoying Huang, Mingtao Li, Lei Wu.
      Levodopa (LD) combined with peripheral dopa decarboxylase inhibitors (DDCIs) remains the cornerstone therapy for Parkinson's disease (PD). Benserazide (BZ), a widely used DDCI, is rapidly converted in vivo to 2,3,4-trihydroxybenzylhydrazine (THBH), an active metabolite with comparable inhibitory activity. Although BZ and THBH are generally considered to exhibit negligible penetration across the blood-brain barrier, evaluation of their potential central exposure requires highly sensitive quantification in cerebrospinal fluid (CSF). However, no validated method is currently available for simultaneous determination of LD, dopamine (DA), BZ, and THBH in paired human plasma and CSF. Here, we developed and validated a rapid ultra-performance liquid chromatography-electrochemical detection (UPLC-ECD) method enabling concurrent quantification of all four analytes in both matrices. The assay provides baseline separation with minimal endogenous interference, excellent linearity across clinically relevant ranges, and low limits of quantification. Precision, accuracy, recovery, and stability met current bioanalytical validation criteria. This method offers a robust analytical platform for clinical and translational studies of LD-BZ therapy.
    Keywords:  2,3,4-Trihydroxybenzylhydrazine; Benserazide; Dopamine; Levodopa; UPLC
    DOI:  https://doi.org/10.1016/j.jpba.2026.117770
  42. MethodsX. 2026 Dec;17 104178
    Novel method for extraction and quantitation of 6PPD-Q in solid matrices using ultrasonic-assisted extraction (UAE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS).
    Thomas Chontofalsky, Fatima Alsinai, Terri Torres, Monica Herbert, Tiffany Ryan.
      This study presents a UAE-LC-MS/MS method for the extraction and quantitation of 6PPD-Q in stormwater sediment matrices. The final method uses ultrasonic-assisted extraction with a hexane:ethyl acetate solvent system and LC-MS/MS instrumental analysis with matrix-matched calibration, and demonstrated acceptable sensitivity, selectivity, and reproducibility. This study addressed challenges specific to sediment matrix, a lack of commercially available reference material, and co-extracted chromatographic interferences. Matrix effects were reduced through optimized extraction parameters, rather than post-extraction cleanup procedures. A total of 28 sediment samples were analyzed using LC-MS/MS to evaluate 6PPD-Q concentrations, resulting in values ranging from 11.4 ng/g to 691 ng/g, with a mean value of 171 ng/g. The method achieved a method detection limit of 1.1 ng/g and limit of quantitation of 5 ng/g using a 250 mg sample size. The mean recovery rate of 6PPD-Q in laboratory control samples was 80.1% (range: 74.8% - 82.3%).•Extract sediment sample with hexane:ethyl acetate mix and dry.•Reconstitute with acetonitrile.•Analyze using LC-MS/MS.
    Keywords:  6PPD-Q; 6PPD-quinone; Liquid chromatography-tandem mass spectrometry (LC-MS/MS); Quinone; Sediment; Tire wear particles (TWPs); Ultrasonic-assisted extraction (UAE)
    DOI:  https://doi.org/10.1016/j.mex.2026.104178
  43. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2410-2421
    Evaluation of Free and Released Sulfur Mustard Diols in Human Blood and Urine Using Multi-ionization GC-QQQ and GC-Q-TOF.
    J Brett Kimbrell, Brian S Crow, Thomas B Tinkle, Thomas A Blake.
      Exposures to blister agents such as sulfur mustard (HD) have been documented in both military and civilian settings, underscoring the need for reliable clinical assays and biomarkers for confirming human exposure. Accordingly, the Organisation for the Prohibition of Chemical Weapons (OPCW) designates sulfur mustard hydrolysis products (diols) as biomarkers for exposure verification. Because confirmatory analyses in public health and forensic contexts often rely on qualitative identification rather than quantitation alone, we evaluated sensitive qualitative approaches for detecting the diol hydrolysis products of eight of the nine sulfur mustard analogs listed in Schedule 1.A.04 of the Chemical Weapons Convention (CWC) Annex on Chemicals. Human serum spiked with sulfur mustard analogs and plasma and urine spiked with corresponding diols underwent strong base treatment, solid-phase extraction (SPE), derivatization with N-heptafluorobutyrylimidazole (HFBI), and liquid-liquid extraction (LLE). The resulting diol bis-HFB derivatives were analyzed by gas chromatography-triple quadrupole mass spectrometry (GC-QQQ) using electron ionization (EI) and positive chemical ionization (PCI) with methane or ammonia reagent gases. Derivatized diols were detected at concentrations as low as 1.00 ng/mL across all matrices, with PCI-methane yielding signal-to-noise ratios (S/N) > 15. Gas chromatography-quadrupole time-of-flight (GC-Q-TOF) analysis provided high-resolution MS and MS/MS spectra to support molecular formula confirmation of precursor and product ions. By combining EI and PCI with high-resolution mass spectrometry for structural and molecular formula confirmation, this approach enables sensitive, matrix-independent detection, with PCI(CH4) providing the most effective balance between structural information and analytical performance for GC-MS/MS implementation.
    Keywords:  Chemical; EI; PCI; Weapons; analogs; biomarkers; diols; extraction; formula; high-resolution; hydrolysis; ionization; mass; molecular; mustard; products; qualitative; spectrometry; structural; sulfur
    DOI:  https://doi.org/10.1021/jasms.6c00197
  44. J Cheminform. 2026 Jul 24. pii: 146. [Epub ahead of print]18(1):
    MetaboT: an LLM-based multi-agent framework for interactive analysis of mass spectrometry metabolomics knowledge graphs.
    Madina Bekbergenova, Lucas Pradi, Benjamin Navet, Emma Tysinger, Franck Michel, Matthieu Feraud, Yousouf Taghzouti, Yan Zhou Chen, Olivier Kirchhoffer, Florence Mehl, Martin Legrand, Tao Jiang, Marco Pagni, Soha Hassoun, Jean-Luc Wolfender, Wout Bittremieux, Fabien Gandon, Louis-Félix Nothias.
      Mass spectrometry-based metabolomics generates complex, high-dimensional data that holds vast potential for biological discovery but remains difficult to integrate and interpret. Knowledge graphs (KGs) unify this heterogeneous information by representing spectra, annotations, taxa, chemical classes, and biological activities as a single interoperable network; however, their practical use is limited by the steep learning curve of corresponding specialized representation and query languages. Here we introduce MetaboT, an open-source multi-agent Large Language Model (LLM) framework that translates natural-language questions into executable SPARQL queries over metabolomics knowledge graphs. MetaboT is designed to mitigate the hallucination and schema-compliance limitations of single-model approaches through a modular architecture in which specialised agents handle scope validation, entity resolution against authoritative resources, schema-aware query generation, iterative refinement, and result interpretation. We validated MetaboT on the Experimental Natural Products Knowledge Graph (ENPKG), using an expert-authored benchmark of natural-language questions paired with reference SPARQL queries, and demonstrate its ability to answer complex questions about plant-metabolite relationships and biological activities, achieving 83.67% accuracy versus 8.16% for a single-shot baseline and reducing schema-mismatch errors to a single residual case in our benchmark. MetaboT lowers the technical barrier for metabolomics researchers and enables semantic data mining without specialised programming expertise.Scientific contributionMetaboT introduces a multi-agent LLM architecture that grounds each step of natural-language-to-SPARQL translation in authoritative identifier resolution and schema-aware validation, substantially reducing the hallucinations observed with single-model baselines. The framework couples orchestrated agents with domain-specific tools for chemical, taxonomic, and biological target resolution, and with an iterative refinement loop that distinguishes query-construction errors from genuine data absence. Released as open-source software with an archived evaluated version, a reusable benchmark, and a public web demonstrator, MetaboT provides a reproducible reference implementation for knowledge-graph-driven exploration of mass spectrometry metabolomics data.
    Keywords:  Cheminformatics software; ENPKG; Entity resolution; Knowledge graph; Large language models; Mass spectrometry; Metabolomics; Multi-agent LLM; Natural products; SPARQL
    DOI:  https://doi.org/10.1186/s13321-026-01257-8
  45. Curr Opin Biotechnol. 2026 Oct 22. pii: S0958-1669(26)00154-0. [Epub ahead of print]102 103589
    High-throughput mass spectrometry-based metabolomics for large-scale population studies: technical barriers and recent innovations.
    Mariana Buitrago-Oliveros, Zaineb Hamoodi, Philip Britz-Mckibbin.
      Large-scale metabolomic studies are needed to identify and validate biomarkers for their successful translation in emerging population health and precision medicine initiatives. Yet, untargeted mass spectrometry (MS)-based metabolomics remains hampered by low sample throughput, limited coverage, complicated data processing, poor standardization, and high operating costs. These challenges also contribute to a reproducibility crisis, with most reported biomarkers not independently replicated, given variations in study designs, sample workup protocols, instrumental methods, and data pre-processing workflows. This review will focus on new advances in high-throughput MS platforms and computational software with emerging artificial intelligence/machine learning tools that are scalable, faster, and less prone to error. Recent progress to improve data harmonization in population-level metabolomic, lipidomic, and exposomic studies (n > 1000) will also be discussed. This will include strategies to correct for long-term batch effects, improve metabolite identification, and derive biochemical insights into disease mechanisms when integrated with multi-omic studies.
    DOI:  https://doi.org/10.1016/j.copbio.2026.103589
  46. Adv Exp Med Biol. 2026 ;1359 117-132
    Seeing Chemistry in Context: Mass Spectrometry Imaging for Biomedical Research and Multi-Omic Integration.
    Emily R Sekera.
      Mass spectrometry imaging (MSI) has become a pivotal technology for exploiting the strengths of liquid chromatography-based mass spectrometry while providing spatial context. This technique has gained rapid traction in the field of biomedical research to enable scientists to interrogate difficult questions in drug discovery and disease mechanisms through enabling -omics unavailable by other spatial methodologies. In this chapter, we will discuss the fundamentals of a basic MSI experiment and a small selection of ionization methods available to be used for such studies. We will further discuss how to design an MSI experiment, providing insight into how to choose a model system and considerations for sample preparation, including embedding, fixation, and preparing sections for MALDI MSI. With this discussion, we will also touch on leveraging multi-omics experiments and how to plan accordingly. Through recent literature examples, we will further illustrate how integrating MSI with other omics layers, such as bulk analyses and spatial transcriptomics, reveals molecular changes that inform both mechanistic biology and translational research.
    Keywords:  -Omics; Drug discovery pipeline; MALDI; Mass spectrometry imaging; Multiomics; Spatial biology
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_7
  47. Adv Exp Med Biol. 2026 ;1359 31-56
    Metabolomics and Biomarker Discovery.
    Kathryn Sinclair, Ed Dudley.
      Recently, metabolomics-the study of metabolite profiles within biological samples-has found a wide range of applications. This chapter describes the different techniques available for metabolomic analysis, the various samples that can be utilised for analysis and applications of both global and targeted metabolomic analysis to biomarker discovery in medicine.
    Keywords:  Biomarkers; Metabolomics; Pancreatic cancer
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_2
  48. Anal Chem. 2026 Oct 13. 98(40): 29188-29201
    RNabel─A Standalone Software Tool for Annotating Tandem Mass Spectra of Modified Ribonucleic Acids.
    Ge Song, Yi-Jie Nathan Du, Rui-Xiang Sun, Meng-Qiu Dong.
      Ribonucleic acid (RNA) modifications, with over 170 identified types, play diverse roles in cellular processes. The past decade has witnessed a surging demand for accurate identification and localization of RNA modifications in both endogenous and synthetic therapeutic RNAs. With accurate spectral annotation for RNA, tandem mass spectrometry (MS/MS) can meet this demand. Here, we present RNabel, a user-friendly software tool for in-depth annotation of MS/MS spectra of RNA oligonucleotides. RNabel considers a full set of backbone-cleavage ions (a, b, c, d, a-B, w, x, y, z) in which the ribonucleotide unit could be A, U, C, G, Y (pseudouridine), or I (Inosine). Additionally, RNabel considers 196 modifications on the base, the phosphoribose linkage, the 5' or the 3' terminus, or the detachment of a subnucleotide fragment as a neutral or charged group. Users can create new components if needed, including ribonucleotides, modifications, and neutral or charged groups that could detach from a ribonucleotide. RNabel efficiently processes large data sets in four acceptable formats including .mgf, .raw, .txt from msConvert, and RNabel batch files. Multiple statistical metrics are provided for quality assessment of spectral annotation. To accelerate RNA modification analysis, RNabel is made freely available for Mac and Windows users at https://github.com/songge1111/RNabel/releases.
    DOI:  https://doi.org/10.1021/acs.analchem.6c02176
  49. J Nat Prod. 2026 Sep 25. 89(9): 2643-2655
    MALDI Tandem Mass Spectrometry for Colony-Based Dereplication of Natural Products.
    Robert A Shepherd, Limar Y Gad, Michael Strobel, Gordon T Luu, Jin Feng, Carlo De Silva, Shaun M K McKinnie, Mingxun Wang, Laura M Sanchez.
      Microbial libraries remain an important resource for natural product discovery; however, constructing taxonomically and chemically diverse collections remains a challenge. Advances in dereplication strategies, including molecular networking, have reduced the rediscovery of known bioactive molecules and facilitated the identification of novel chemical scaffolds, but these approaches are typically applied after library construction. Furthermore, many dereplication workflows require fermentation and extraction, increasing the time needed to assess a microbe's metabolite profile. Here, we integrate matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) into the bioinformatics platform IDBac, enabling characterization of microbial taxonomic identity, metabolite production potential, and preliminary metabolite annotation through GNPS2 molecular networking. This workflow facilitates strain prioritization by providing metabolite annotations directly from single microbial colonies prior to scale-up and extraction. Application of this approach to marine actinomycetes enabled the annotation of lavanducyanin and multiple napyradiomycin analogs. Subsequent investigation led to the discovery of napyradiomycin B8 from marine Streptomyces sp. CNZ-289, which was confirmed by 1D and 2D NMR spectroscopy and MALDI-MS/MS. Expanding this workflow to 25 commensal marine vertebrate-derived bacterial isolates resulted in the annotation of known bioactive natural products, including surugamides, antimycins, desferrioxamine siderophores, and the isolation and elucidation of harmane derivatives using NMR.
    DOI:  https://doi.org/10.1021/acs.jnatprod.6c00765
  50. J Chem Inf Model. 2026 Oct 12. 66(19): 12316-12325
    AGENTi: APCI-ESI Analyte Ionization Fidelity Pre-Screening Workflow using Multimodel Inference.
    Mithony Keng, Kenneth M Merz.
      Ionization sources convert neutral analytes into ions, enabling their subsequent separation and detection by mass spectrometry. Depending on the technique, this mechanism occurs within a solution or in the gas phase. The two most common methods to generate ions are electrospray ionization (ESI) and atmospheric-pressure chemical ionization (APCI), respectively. Both ESI and APCI can generate the same resultant ion species; however, it has been shown that preferential charge sites can change in response to an ionization source environment. Therefore, an additional quality control is warranted a priori to delineate erroneous analyte identification and/or unequivocal structural assignment. For protonation, protomer fidelity can be assessed by comparing the ion-mobility collision cross section (CCS) values obtained for both ESI and APCI. In this work, we utilized proxy standards (i.e., controls) derived from the available literature to develop a proof-of-concept multimodel inference application called AGENTi to probe differences in ionization for high-throughput protomer shift exploratory analysis. AGENTi uses in sequence the TensorFlow Autoencoder anomaly detection and the YDF Gradient Boosted Tree machine learning frameworks to generate more balanced and robust anomaly scores. We found that using a multimodel screening approach can reduce false positive capture at an acceptable loss of true positives. Moreover, we expect to achieve a better recovery of true positives with an improvement on the current Gradient Boosted Tree regression model for ΔCCS prediction as more ESI-APCI dual data are obtained for training. In all, we demonstrated in this pilot study that our foundation model for a priori probing of ionization pathway fidelity is feasible and efficient with AGENTi. The AGENTi prototype application and documentation are accessible at https://github.com/mitkeng/AGENTi.
    DOI:  https://doi.org/10.1021/acs.jcim.6c01085
  51. Environ Sci Technol. 2026 Sep 22. 60(37): 26100-26115
    Exposomic Assessment of Endocrine-Disrupting Chemicals Using Hair: A Cross-Matrix Comparison with Serum and Urine by LC-HRMS and Metabolite Profiling.
    Ana González-Ruiz, Adrià Sunyer-Caldú, Rodrigo Braz Carneiro, Esteban Restrepo-Montes, Olivia Ballester-Miró, Alejandro Lobato-Berezo, Ramón M Pujol, Montse Marquès, Rubén Gil-Solsona, Pablo Gago-Ferrero.
      Endocrine-disrupting chemicals (EDCs) are increasingly implicated in chronic diseases, yet their biomonitoring in human studies still relies mainly on urine and serum, which capture only short-term exposure to these fast-elimination compounds. Here, we evaluated hair as a complementary and long-term biomonitoring matrix for EDC mixtures by integrating it into an LC-HRMS exposomics workflow together with paired serum and urine samples. We developed and validated a method targeting 44 endocrine disruptors from five chemical families (benzophenones, phthalates, parabens, bisphenols, and organophosphate esters), combining quantitative analysis with suspect screening and semi-quantification of phase II metabolites. Applied to samples from 20 postmenopausal women, the hair-based approach provided the broadest coverage and highest concentrations (31/44 compounds), up to about three orders of magnitude higher than in urine or serum, consistent with distinct accumulation mechanisms and temporal integration windows. In hair, EDCs were present in unconjugated form (>99%), whereas urine was dominated by conjugated metabolites and serum showed limited detection. Overall, these findings demonstrate that integrating hair into multimatrix exposomics designs substantially expands both the chemical and temporal resolution of human exposure assessment.
    Keywords:  EDCs; environmental exposure; exposomics; hair analysis; high-resolution mass spectrometry; human biomonitoring
    DOI:  https://doi.org/10.1021/acs.est.6c05029
  52. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2598-2608
    Rapid Simultaneous Quantification of Four Typical Phthalate Esters in Complex Food Matrices via Thermal Desorption-Dielectric Barrier Discharge Ionization Mass Spectrometry.
    Qisen Huang, Weipeng Cai, Xiaokang Guan, Chencheng Wei, Shuxian Liu, Xiaowen Yan, Renato Zenobi.
      Conventional analytical methods for detecting and quantifying phthalate esters (PAEs) in foods generally require lengthy sample pretreatment procedures and suffer from severe matrix interferences. To address these shortcomings, a fast analytical platform based on a thermal desorption unit that is directly interfaced with dielectric barrier discharge ionization mass spectrometry (TD-DBDI-MS) was developed. The integration of a heated nitrogen purge system effectively suppressed atmospheric background interference and improved signal stability. Moreover, a simplified liquid-liquid extraction pretreatment protocol was established that eliminates the need for centrifugation and solid-phase extraction (SPE) cleanup steps. The complete analysis cycle time per sample was reduced by approximately 55% compared to conventional GC-MS/LC-MS workflows, and each analysis by TD-DBDI-MS was completed in only 10 seconds. The method exhibited excellent linearity for four typical PAEs in the range of 0.5-200.0 μg/L with correlation coefficients (R2) > 0.998. The limits of detection (LOD) ranged from 0.11 to 0.52 μg/kg, spike recoveries were between 82% and 106%, and relative standard deviations (RSDs) were <10%. Application to 19 commercially available food samples revealed widespread PAE contamination, with butyl benzyl phthalate (BBP) being detected in every sample. Contamination levels followed the order premade dishes > milk > sugary beverages. PAE migration levels from plastic bag packaging were significantly higher than those from plastic bottle and carton packaging. Fortunately, the measured PAE concentrations were all well below the specific migration limits (SMLs) specified in China's GB 5009.271-2016 regulation and EU Regulation 10/2011. This rapid, efficient, and robust method provides a novel approach for large-scale screening of PAEs in complex food matrices.
    DOI:  https://doi.org/10.1021/jasms.6c00286
  53. Environ Monit Assess. 2026 Oct 22. pii: 1243. [Epub ahead of print]198(11):
    Assessment of pesticide residues in rice-wheat based conservation agriculture fields using validated LC-MS/MS methodology.
    Aravindh M, Sumit Shekhar, Rishi Raj, Priya Saini, Suman Gupta, Tirthankar Banerjee.
      Pesticide residues in soil are a significant environmental concern in intensive rice-wheat cropping systems, especially under conservation agriculture (CA), where reduced soil disturbance and residue retention may alter pesticide dissipation and vertical distribution. This study developed and validated a robust Liquid Chromatography tandem Mass Spectrometry (LC-MS/MS) method for the simultaneous detection of 93 pesticides in soil and applied it to long-term CA fields of the rice-wheat system. A modified QuEChERS method, involving soil hydration, acetonitrile extraction, buffer salt addition, and dispersive-Solid Phase Cleanup (dSPE) cleanup, was optimized for soil samples. Method validation was performed according to SANTE/11312/2021 guidelines, demonstrating satisfactory specificity (0-26% interference), linearity (R2 > 0.99), recovery within 70 to 120%, precision (Relative Standard Deviation [RSD]) ≤ 20%, HorRat between 0.15 and 2.0), Limit of Quantification (LOQ) ranging from 0.01 to 0.10 mg/kg depending on the analyte and measurement uncertainty (50%) was within acceptable limits. Matrix effects varied across pesticides, with most showing medium suppression (20-50%), and matrix-matched calibration was used for accurate quantification. Application of this validated method to field soils revealed that few pesticides, including chlorantraniliprole, metribuzin, pendimethalin, pretilachlor, and tebuconazole, primarily accumulated at a depth of 0-5 cm under CA practices. Seasonal variation showed higher pesticide persistence during the Rabi season. Long-term CA affects the persistence and surface accumulation of selected pesticides, emphasizing the need for careful pesticide management in CA-based rice-wheat systems.
    Keywords:  Conservation agriculture; LC–MS/MS; Method validation; Pesticide residues; Rice–wheat system; Soil
    DOI:  https://doi.org/10.1007/s10661-026-16068-5
  54. Anal Chem. 2026 Oct 20. 98(41): 29417-29432
    Multiway Modeling of 2D NMR Spectra for Enhanced Chemical Characterization of Complex Mixtures.
    Pia S Mayer, Søren B Engelsen, Jesper L Hinrich, Morten Mørup, Bekzod Khakimov.
      One-dimensional (1D) proton nuclear magnetic resonance (NMR) spectroscopy is widely used for complex mixture analysis because of its high reproducibility, minimal sample preparation, and inherent quantitative capabilities. However, 1D NMR remains constrained by three interrelated limitations: signal overlap among compounds, chemical-shift variability of the same compounds across samples, and masking of low signal-to-noise features by neighboring high-intensity resonances. Two-dimensional (2D) NMR spectroscopy can reduce these limitations by dispersing spectral information over a second dimension and providing additional structural information. Yet its broader implementation in large-scale studies remains limited by a major data-processing bottleneck: the analysis of multisample, high-dimensional 2D NMR data sets. When acquired across multiple samples, 2D NMR spectra form three-way tensors that contain richer chemical information than conventional 1D data sets but are not readily handled by standard NMR data analysis workflows. In this paper, we discuss how localized 2D spectral alignment combined with tensor decomposition and shift-tolerant multilinear modeling, including PARAFAC, PARAFAC2, and shift-invariant approaches, can recover overlapped, shifted, and low-intensity signals from complex 2D NMR spectra. These workflows hold considerable promise for advancing NMR-based complex mixture analysis by expanding metabolite coverage, improving deconvolution of elusive signals, and enabling more reliable quantification of low-abundance biomarkers in large-scale studies.
    DOI:  https://doi.org/10.1021/acs.analchem.6c04147
  55. Biomed Chromatogr. 2026 Dec;pii: e70643. [Epub ahead of print]40(12): e70643
    Specificity Testing in Bioanalytical Assay Validations-Challenges and Opportunities.
    Raja Reddy Kallem, Michael G Bartlett, Nuggehally R Srinivas.
      Specificity assessment is essential in bioanalytical method development to ensure accurate analyte quantification in the presence of endogenous matrix components and potential exogenous interferences. Regulatory expectations have evolved over time, culminating in the harmonized ICH M10 guideline, which establishes a globally aligned framework for bioanalytical method validation. Although LC-MS/MS provides high analytical specificity, challenges remain, particularly from isobaric interferences and increasingly complex multi-analyte assays. A common practical issue is trace contamination of authentic reference standards, such as parent drug in metabolite standards or vice versa, which can generate unacceptable cross-signal contributions and compromise specificity assessments. When such impurities preclude conventional specificity testing, this perspective discusses scientifically justified approaches, including predetermined baseline corrections to account for contaminated standards. It also highlights incurred sample reanalysis (ISR) as a more meaningful assessment of assay specificity under these constrained conditions because it reflects the true in vivo composition of parent drug and metabolites. The application of ISR has emerged as a robust, regulatory-endorsed tool for confirming assay reliability over time and, as such, could also serve as an alternative for some of the issues discussed.
    Keywords:  ISR; analytical challenges; bioanalysis; contaminants; specificity
    DOI:  https://doi.org/10.1002/bmc.70643
  56. Anal Chem. 2026 Sep 15. 98(36): 26323-26338
    Electrospray-Orbitrap Analysis of Nitrate and Sulfate Isotopologues in Natural Samples: Performance and Constraints.
    Jack Saville, Julien Witwicky, Elsa Gautier, Alexis Lamothe, Nils Johannes Kuhlbusch, Becky Alexander, Andrew Schauer, Andrea Burke, Priyesh Prabhat, Eva Stüeken, Joshua Garber, Nicolas Caillon, Joël Savarino.
      Traditional isotope ratio mass spectrometers are not optimally designed to analyze nonvolatile molecular solutes such as oxyanions or organics. Necessary sample conversion steps, often demanding micromole-scale samples, break chemical bonds and limit oxyanion analyses to elemental isotope ratios. Recent studies enthusiastically promote soft electrospray ionization coupled to high-resolution Orbitrap mass spectrometry (ESI-Orbitrap-MS) for intact-molecule isotopologue analysis. This combination uses widely accessible instrumentation to provide simultaneous multi-isotopologue and clumped isotope analyses using tens of nanomoles of dissolved sample. However, its isotopic capabilities have been evaluated primarily through technical assessments rather than on natural samples, despite the need for matrix sensitivity assessments and robust isotopic calibrations. Here, we establish a framework for natural-sample ESI-Orbitrap-MS isotopologue analysis of nitrate and sulfate, addressing matrix effects, isotopologue calibration, and instrumental stability. We demonstrate strong sensitivity to contaminants at concentrations 1000 times below target analytes and strong temperature-correlated drift over >30 min, highlighting the enhanced need for rigorous sample purification to suppress matrix effects, sample-reference bracketing to overcome drift, and isotopologue calibration to reduce biases and robustly quantify uncertainties. We achieve 0.4-1.3‰ precision and accurate measurements of δ15N-NO3-, δ18O-NO3-, Δ17O-NO3-, δ34S-SO42-, and Δ17O-SO42- relative to traditional techniques, consuming only 20 nmol nitrate or 10 nmol sulfate. We resolve relative nitrate clumped isotope values in ice core samples (Δ15N18O-NO3-: ±2.3‰; Δ18O18O-NO3-: ±3.3‰) yet observe no correlations with bulk nitrate isotopes. These results establish practical guidelines for applying ESI-Orbitrap-MS to isotopologue and clumped isotope analysis of trace analytes in challenging sample matrices under real-world conditions.
    DOI:  https://doi.org/10.1021/acs.analchem.6c00183
  57. Environ Sci Technol. 2026 Sep 22. 60(37): 25953-25956
    Mass Spectrometry-Based Exposomics Is Not Metabolomics by Another Name.
    Peng Gao.
      
    Keywords:  exposomics; mass spectrometry; metabolomics
    DOI:  https://doi.org/10.1021/acs.est.6c10462
  58. Anal Chem. 2026 Oct 06. 98(39): 28810-28823
    Rapid Species-Level Classification of Urinary Pathogens from Raw LC-MS/MS Signals Using Machine Learning.
    Simon J Pelletier, Antoine Lacombe-Rastoll, Florence Roux-Dalvai, Mickaël Leclercq, Clarisse Gotti, Eve Bérubé, Pascaline Bories, Marie-Ève Thibeault, Dorte B Bekker-Jensen, Nicolai Bache, Maciej Bromirski, Sandra Isabel, Frederic Precioso, Arnaud Droit.
      Urinary tract infections are among the most common infections in humans, yet their diagnosis still depends on time-consuming workflows based on microbial culture, followed by MALDI-TOF mass spectrometry. Although LC-MS/MS offers the sensitivity and specificity needed to bypass culture, conventional pipelines depend on lengthy analyses and peptide/protein identification steps, limiting the throughput and hindering its adoption in clinical settings. Here, we introduce a direct, identification-free LC-MS/MS workflow that analyzes raw ion signal and produces species-level microbial identification in about 5 min after preparation, fast enough to meet clinical throughput requirements. Our machine learning-enabled raw-signal pipeline bypasses peptide identification entirely, preserving information and eliminating the traditional interpretation stack. Across 15 independent analytical batches covering 28 clinically relevant pathogens, the method achieved high-confidence classification (MCC = 0.86). Applied to 206 clinical urine specimens across three batches, the approach reached 91% accuracy at clinically actionable microbial loads (greater than 105 CFU/mL) and, critically, 0 false positives in control specimens. The performance was lower for specimens below this threshold. These results show that raw LC-MS/MS spectra contain sufficient biological information for direct microbial diagnosis, establishing an analytical framework for clinical mass spectrometry. This proof-of-concept demonstrates that rapid, culture-free, fast microbial identification is achievable and positions raw signal inference as a promising direction for next-generation diagnostic mass spectrometry.
    DOI:  https://doi.org/10.1021/acs.analchem.6c02725
  59. J Chromatogr A. 2026 Oct 14. pii: S0021-9673(26)00873-3. [Epub ahead of print]1789 467547
    Recent advances in pretreatment and detection technologies for ergot alkaloids.
    Yi-Nan Wang, Yu Bian, Yuan Zhang, Han-Shu Zhao, Xue-Song Feng.
      Ergot alkaloids (EAs) are a class of mycotoxins widely present in complex matrices such as grains, pharmaceuticals, and biological samples. EAs possess vasoconstrictive and neurotoxic properties, which can lead to severe health issues such as gangrene and hallucinations. However, significant matrix effects, numerous co-existing interferents, and tedious sample pretreatment procedures in complex matrices pose substantial challenges for high-sensitivity and high-selectivity analysis. Accurate analysis of EAs is crucial for food safety and public health. This paper systematically reviews the research progress in sample pretreatment and detection technologies for EAs in recent years. It highlights innovative pretreatment advancements, including miniaturized, solvent-minimizing formats (e.g., microextraction and dispersive solid-phase extraction), integrated online SPE, and the high-throughput QuEChERS approach, to address diverse matrix challenges. Meanwhile, the performance and limitations of detection platforms including liquid chromatography-mass spectrometry and sensors are reviewed, with particular attention paid to the applications of high-resolution mass spectrometry and novel functional materials in this field. By conducting a horizontal comparison of various techniques across multiple matrices, this study offers methodological guidance for the selection and optimization of high-sensitivity and high-selectivity analytical methods for EAs in complex samples. Furthermore, it highlights emerging trends toward greener, miniaturized, and automated analytical approaches in this field.
    Keywords:  Ergot alkaloids; High-resolution mass spectrometry; Micro-solid-phase extraction; Molecularly imprinted polymer; Sensor
    DOI:  https://doi.org/10.1016/j.chroma.2026.467547
  60. J Pharm Biomed Anal. 2026 Oct 14. pii: S0731-7085(26)00437-1. [Epub ahead of print]283 117769
    Development and validation of an LC-MS/MS method for the determination of mycotoxins in the medicinal and edible herb dandelion.
    Gang Wang, Chuanben Tian, Mingyue Jiao, Yuhan Wang, Xiaoyun Zhang, Sherif Ramzy Mohamed, Jianrong Shi, Jianhong Xu.
      Dandelion (Taraxacum mongolicum Hand.-Mazz.) is a medicinal and edible herb widely used in traditional Chinese medicine; however, studies on mycotoxin contamination in dandelion remain limited. Herein, we developed a liquid chromatography-triple quadrupole-tandem mass spectrometry (LC-QqQ-MS/MS) method for the simultaneous quantification of five common mycotoxins: aflatoxin B1 (AFB1), deoxynivalenol (DON), fumonisin B1 (FB1), ochratoxin A (OTA), and zearalenone (ZEN) in dandelion. The mycotoxins were extracted from dandelion herb, cleaned up by solvent dilution, and analyzed in multiple reaction monitoring (MRM) mode on an LC-QqQ-MS/MS system. Key parameters were optimized to achieve the best performance, including chromatographic conditions, MRM ion pairs, extraction solvents, and sample cleanup methods. Method validation was conducted in terms of specificity, limit of determination, limit of quantitation, linearity, intraday and interday precision, and matrix effect. Finally, a total of 54 dandelion samples collected from different regions of China were analyzed using the developed method. AFB1 and FB1 were detected in all the dandelion samples, while OTA was found in 45 samples. DON was detected in nine samples from three regions, whereas ZEN was not detected in any of the samples. FB1 was found to be the most prevalent mycotoxin in the samples, ranging from 9.77 to 35.86 μg/kg, followed by AFB1 and OTA, indicating co-occurrence of mycotoxins in this herb.
    Keywords:  Dandelion; Herbal medicine; LC-MS/MS; Method validation; Mycotoxin; Taraxacum mongolicum Hand.-Mazz.
    DOI:  https://doi.org/10.1016/j.jpba.2026.117769
  61. Anal Chem. 2026 Sep 29. 98(38): 27918-27926
    Hydraplexing: Design Principles for Fragment-Level Signal Amplification Using a Multi-Amine Model Analyte.
    Ailing Li, Navid J Ayon, Peter Nemes.
      Fragment-ion signals are often too weak to support confident quantification at trace levels. This challenge is particularly acute for limited-input measurements, including single cells. We introduce hydraplexing, a fragment-readout strategy that installs multiple isobaric barcodes on a single analyte so that barcode-derived fragment ions add in tandem mass spectrometry (MS2). Unlike conventional isobaric labeling that increases sample plexity, hydraplexing multiplexes barcode-release pathways within a single precursor to amplify signal quantitation. Here, hydraplexing is established using a standalone multiamine model analyte, 1,2,4,5-tetraaminobenzene (TAB), bearing 2-4 tandem mass tags as TAB-TMT2, TAB-TMT3, and TAB-TMT4 derivatives, which isolates barcode multiplicity without coupling the scaffold to target analytes. Using this controlled system, we mapped barcode-release dissociation networks and defined collision-energy regimes that maximize reporter-ion (RI) output while maintaining precursor transmission during higher-energy collisional dissociation. RI output increased with tag number across direct-infusion electrospray as well as liquid chromatography and capillary electrophoresis separations using parallel-reaction monitoring. Complementary fragment ions (TMTc) peaked at lower collision energies and were more condition-sensitive, identifying RIs as the more robust quantitative channel under the conditions tested. This amplification persisted in a peptide-rich single-cell Xenopus laevis digest matrix, where TAB-TMT4 produced an ∼3.5-fold higher RI/precursor response than TAB-TMT2. Hydraplexing was further transferred to 3,4,5-triaminobenzoic acid (TABA), a carboxylate-functionalized scaffold forming 1×-3× TMT derivatives, for which the 2× and 3× derivatives yielded 1.4-fold and 2.7-fold higher RI output than the 1× derivative. Hydraplexing establishes fragment-level signal summation as a tunable design principle for engineering additive tag-derived fragment-ion outputs.
    DOI:  https://doi.org/10.1021/acs.analchem.6c01384
  62. Adv Exp Med Biol. 2026 ;1359 103-116
    Mass Spectrometry-Based Tissue Imaging of Small Molecules.
    Carly N Ferguson, Joseph W M Fowler, Jonathan F Waxer, Richard A Gatti, Joseph A Loo.
      Mass spectrometry imaging (MSI) of tissue samples is a promising analytical tool that has quickly become associated with biomedical and pharmacokinetic studies. It eliminates several labor-intensive protocols associated with more classical imaging techniques and provides accurate, histological data at a rapid pace. Because mass spectrometry is used as the readout, MSI can be applied to almost any molecule, especially those that are biologically relevant. Many examples of its utility in the study of peptides and proteins have been reported; here we discuss its value in the mass range of small molecules. We explore its success and potential in the analysis of lipids, medicinals, and metal-based compounds by featuring representative studies from mass spectrometry imaging laboratories around the globe.
    Keywords:  Drug compounds; Lipids; Mass spectrometry tissue imaging; Nanoparticles; Small molecules
    DOI:  https://doi.org/10.1007/978-3-032-29437-1_6
  63. J Am Soc Mass Spectrom. 2026 Oct 07. 37(10): 2515-2524
    Plasma-Assisted Functionalization of Hydrocarbons for Enhanced Mass Spectrometric Detection.
    Muhammad Mujahid Ali, Manish Jana, Myles Q Edwards, Shiva Ataei, R Graham Cooks.
      The detection and structural analysis of hydrocarbons by mass spectrometry (MS) are challenging because of poor ionization. Here, we report a plasma-based strategy that selectively converts nonpolar hydrocarbons to derivatives that are mass spectrometry-friendly by controlled oxygen and nitrogen insertion reactions. A subatmospheric pressure plasma facilitates stable discharges under mild conditions, allowing the formation of ketones, unsaturated ketones, and imines without structural fragmentation or extensive oxidation. The reaction pathways can be tuned by adjusting the carrier gas and sample introduction mode, allowing controlled switching between simple oxidation, dehydrogenation, and nitrogen insertion. Mass spectrometric analysis reveals well-defined molecular ions that show characteristic fragmentation behavior in tandem MS, facilitating improved detection and structural interpretation across linear, branched, cyclic, and aromatic hydrocarbons. Furthermore, a scalable method has been developed to achieve preparative levels of modified samples for NMR analysis, and this confirmed ketone formation as the dominant oxygen-insertion pathway. Overall, this work demonstrates a simple and versatile plasma-based approach for enhancing the detection and structural characterization of otherwise challenging hydrocarbon species.
    Keywords:  alkanes; derivatization; fragmentation; ionization; plasma chemistry
    DOI:  https://doi.org/10.1021/jasms.6c00269
  64. Anal Chem. 2026 Oct 06. 98(39): 28678-28688
    IsoSwap: A Toeplitz Operator Framework for Isotope Transformations in Mass Spectrometry.
    Frédérique Vilenne, Piotr Prostko, Dirk Valkenborg.
      Accurate prediction of isotope distributions is essential for biomolecule identification and quantitation in mass spectrometry. Existing algorithms, such as recursive expansions or generating-function methods, achieve high accuracy but suffer from limited scalability, specialized handling of polyisotopic elements such as sulfur, and poor adaptability to chemical modifications. We present IsoSwap, a convolution-based framework that reformulates isotope distribution calculations as structured linear algebra operations. By representing isotopic profiles as discrete probability vectors indexed by neutron count, we express convolution as outer-product expansions and introduce Hankel and Toeplitz matrices. This formulation directly yields both aggregated isotope probabilities and centroid masses, and naturally extends to deconvolution for modeling leaving groups. IsoSwap computes complete isotopic envelopes in milliseconds, supports GPU acceleration, and generalizes to higher-order convolutions without element-specific adaptations. On simulated phosphorothioate-modified oligonucleotides, IsoSwap reproduces distributions computed directly from the modified elemental formula to floating-point precision, at approximately 5.6 times the speed of direct recomputation. Applied to an experimental mass spectrum of myoglobin, the operators interconvert the apo and heme-bound holo forms in both directions, with centroid-mass accuracy below 1 ppm. This provides a scalable, algebraically transparent method for predicting and transforming isotope distributions.
    DOI:  https://doi.org/10.1021/acs.analchem.6c01495
  65. Anal Chem. 2026 Sep 29. 98(38): 28337-28344
    Chromatograms: A Modular Infrastructure for Scalable Chromatographic Data Handling in R.
    Philippine Louail, Laurent Gatto, Sebastian Gibb, Johannes Rainer.
      Chromatographic traces are central to LC-MS analysis, yet most software treats them as transient intermediates inside a fixed pipeline rather than as data objects users can inspect and manipulate directly. In R, xcms provides the established infrastructure for large-scale LC-MS analysis, but the way it represents chromatograms limits what can be done with them once extracted. We present chromatograms, an open-source R/Bioconductor package and a core component of the R for mass spectrometry ecosystem, built on two design principles: interchangeable storage backends, which keep the analysis code independent of where the data reside (in memory, on disk, etc.), and delayed evaluation, which applies queued operations only to the chromatograms actually requested and processed at a time. Chromatograms was fully integrated into xcms hence enabling the efficient extraction of EICs for identified features, exemplified on public data, for which extraction of 4980 features across 4000 samples took only a few hours, against a full day with the legacy infrastructure. For targeted data analysis or inspection, a peak table from any external software, or published with a study, is enough to recover the corresponding chromatograms from the raw files, with annotation columns preserved; four published biomarkers were recovered from all 4063 samples of a cohort even without parallel processing in just under an hour. Chromatograms does not perform peak detection: it provides the infrastructure for working with chromatographic data once peaks are defined, giving a scalable foundation for targeted and untargeted LC-MS analysis in R.
    DOI:  https://doi.org/10.1021/acs.analchem.6c03926
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