bims-metlip 2025-12-14 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2025–12–14
28 papers selected by
Sofia Costa, Matterworks

[Determination of tetracyclines in animal muscle tissues by ultra performance liquid chromatography- tandem mass spectrometry].
Mapping the unknown: an anchor-based molecular networking workflow for comprehensive identification of new psychoactive substances and analogues.
Ultra high-performance supercritical fluid chromatography-mass spectrometry emerging as a complementary approach for targeted steroid analysis.
[Simultaneous determination of vitamins K1 and K2 in cosmetics by QuEChERS-high performance liquid chromatography and verification by high performance liquid chromatography-tandem mass spectrometry].
Development and Validation of an LC-MS/MS Method for Quantifying Phytohormones Related to Tomato Shelf Life.
Targeted LC-MS/MS method for quantifying respiratory pharmaceuticals in wastewater.
A resource to empirically establish drug exposure records directly from untargeted metabolomics data.
[Determination of caffeine and taurine in electronic cigarette oil by high performance liquid chromatography- tandem mass spectrometry].
A Validated LC-MS/MS Method for the Determination of Sulindac and Its Metabolite Su-EP‑C in Human Plasma and Their Pharmacokinetic Application in Healthy Volunteers.
Quantitative Analysis of Diazepam Residues in Aquatic Products Using Magnetic Solid-Phase Extraction Combined with Ultra-High-Performance Liquid Chromatography-Tandem Mass Spectrometry.
NMR-based metabolomics: Where are we now and where are we going?
A sulfatide-centered ultra-high resolution magnetic resonance MALDI imaging benchmark dataset for MS1-based lipid annotation tools.
Development and validation of UPLC-MS/MS method for detecting nootropic misuse in oral fluids: A step towards combating doping in Esports.
Machine Learning-Assisted False Positive Detection in Metabolite Identification Workflows.
A universal LC-HRMS workflow integrating targeted and untargeted strategies for rapid and comprehensive metabolite profiling of oligonucleotide-based therapeutics.
GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction.
FIDDLE: a deep learning method for chemical formulas prediction from tandem mass spectra.
Synthesis of Reference Standards and Optimization of UPLC-ESI-MS/MS Method for Quantification of Organosulfates in PM2.5.
HDSE-MS: Tandem Mass Spectrum Prediction for Small Molecules via Hierarchical Distance Structural Encoding.
[Determination of 26 herbicide residues in soil， sediment， and surface water samples using modified QuEChERS method combined with ultra-high performance liquid chromatography-tandem mass spectrometry].
A Comparative Metabolomics Study of Multiple Urological Diseases by Highly Sensitive Dansylation Isotope Labeling LC-MS.
Application of acoustic ejection mass spectrometry for plasma protein binding assay using flux dialysis.
Predicting xenobiotic metabolism: a computational approach mining LC-MS/MS data with SIRIUS and BioTransformer.
3D-printed serpentine columns for size-exclusion chromatography with mass spectrometric detection.
Development and validation of a two-dimensional liquid chromatography method for therapeutic drug monitoring of pyrotinib in human plasma.
Advances in food metabolomics: Validating NMR-based non-targeted methods and fostering collaborative NMR applications.
Semi-Quantitative On-Site Microfluidic Assay to Detect 11-Nor-9-carboxy-delta 9-Tetrahydrocannabinol (THC-COOH) in Urine.
[Simultaneous screening of pesticides and mycotoxins in dried goji berries and mulberries by QuEChERS-liquid chromatography-quadrupole-time of flight mass spectrometry].

Se Pu. 2025 Dec;43(12): 1354-1363

[Determination of tetracyclines in animal muscle tissues by ultra performance liquid chromatography- tandem mass spectrometry].

Kun Chu, Jin-Hua Li, Qian-Qian Wang, Xiao-Tong Li, Shuai Wu, Chen Chen.

  Tetracyclines （TCs） are broad-spectrum antibiotics that are classified as natural or semi-synthetic. Natural TCs include chlortetracycline， tetracycline， and oxytetracycline， while semi-synthetic ones include doxycycline， minocycline， methacycline， and demeclocycline， among others. While TCs are widely used in the livestock， poultry， and aquaculture industries， their indiscriminate use detrimentally affects ecosystems， and residual TCs in animals can adversely affect human health. In this study， we developed an ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method for determining TCs， including minocycline， 4-epioxytetracycline， 4-epitetracycline， oxytetracycline， tetracycline， demeclocycline， 4-epichlortetracycline， chlortetracycline， methacycline， and doxycycline. The developed protocol was used to establish a method for qualitatively and quantitatively analyzing TCs in animal muscle tissue （pork， chicken， and fish meat）. To this end， we systematically optimized the mass spectrometry （MS） parameters， solid-phase extraction （SPE） cartridge， and extraction conditions of the method. Animal muscle-tissue samples were homogenized and extracted with 10 mL of 80% acetonitrile aqueous solution containing 0.2% formic acid. How the acetonitrile/formic acid ratio affects the TC-extraction efficiency was investigated using one-way analysis. The supernatant was purified using an Oasis PRiME HLB solid-phase-extraction cartridge， evaporated under flowing nitrogen， and redissolved. Two different C18 UPLC columns were systematically evaluated， and the optimal UPLC conditions were established for the TCs. The Eclipse Plus C18 column （100 mm×2.1 mm， 3.5 μm） was used for separation. The effects of mobile phases A （0.1% formic acid aqueous solution， 5 mmol/L ammonium acetate aqueous solution， and 5 mmol/L ammonium formate aqueous solution） and B （methanol or acetonitrile） on the separation and response values of the TCs were investigated. Optimal response values and peak shapes were obtained using 0.1% formic acid aqueous solution as mobile phase A and 0.1% formic acid acetonitrile solution as mobile phase B， at a flow rate of 0.2 mL/min and a sample injection volume of 5 μL. Gradient elution was performed as follows： 0-2.0 min， 5%B； 2.0-3.5 min， 5%B-15%B； 3.5-7.0 min， 15%B-20%B； 7.0-9.0 min， 20%B-65%B； 9.0-9.1 min， 65%B-90%B； 9.1-10.0 min， 90%B； 10.0-10.1 min， 90%B-5%B； 10.1-12 min， 5%B. The effect of the glass sample bottle on adsorption was also investigated. Both positive- and negative-ion modes were explored in the UPLC-MS/MS experiment to fully scan the parent ions. Positive mode was selected for electrospray ionization （ESI）. Two product ions that exhibit strong signals and minimal interference were selected for quantitative and qualitative ion analyses， with quantification performed using the external standard method. Tandem mass spectrometry （MS/MS） was performed in positive electrospray ionization （ESI+） and multiple reaction monitoring （MRM） modes. The following MS/MS parameters were used： capillary voltage， 0.5 kV； cone voltage （CV）， 30 V； ion-source temperature， 150 ℃； desolvation temperature， 300 ℃； desolvation gas flow， 800 L/h. Other instrument settings， such as the collision energy （CE） and collision gas flow， were also optimized. The TCs exhibited good linearities within the 1-500 ng/mL mass-concentration range， with all correlation coefficients （r2） above 0.994， and limits of detection and quantification （LODs and LOQs） of 0.10-0.15 and 0.20-0.50 μg/kg， respectively. The target analytes exhibited average recoveries of between 62.6% and 119.0% at three levels （1.0， 5.0， and 10.0 μg/kg）， with relative standard deviations （RSDs， n=7） ranging from 2.0% to 9.8%. The developed method was used to determine TCs in 60 animal muscle-tissue samples acquired from a fresh-food supermarket. Tetracycline was detected at a rate of 10% in 20 pork samples， while doxycycline was detected at a rate of 15% in 20 chicken samples， and oxytetracycline was detected at a rate of 5% in 20 fish-meat samples. Minocycline， 4-epioxytetracycline， 4-epitetracycline， tetracycline， demeclocycline， 4-epichlortetracycline， chlortetracycline， and methacycline were not detected. The developed method is simple to operate， highly sensitive， and can be used to precisely and accurately determine TCs. Accordingly， it is suitable for determining the abovementioned ten tetracycline antibiotics in animal muscle tissue.

Keywords:  animal muscle tissue; solid-phase extraction （SPE）; tetracyclines （TCs）; ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）

DOI:  https://doi.org/10.3724/SP.J.1123.2025.03014
Anal Bioanal Chem. 2025 Dec 11.

Mapping the unknown: an anchor-based molecular networking workflow for comprehensive identification of new psychoactive substances and analogues.

Carla Fournié, Laurence Labat, Mathieu Le Seigle, Bruno Mégarbane, Pascal Houzé, Romain Magny.

  The rapid emergence and structural diversity of New Psychoactive Substances (NPS) challenge toxicological screening, which usually relies on targeted detection of known compounds. To address this limitation, we developed a novel, database-independent analytical workflow capable of anticipating unknown or emerging NPS in complex biological matrices. A comprehensive workflow combining sample preparation, orthogonal liquid chromatography, and high-resolution tandem mass spectrometry (LC-HRMS/MS) was developed for the identification of new structures and their metabolites. Three extraction protocols were benchmarked in both reversed-phase (RP-LC) and hydrophilic interaction (HILIC) chromatographic modes to maximize analyte coverage. The method was optimized using 77 drug standards and extended to a mixture of 122 compounds (Mix122) to build an Anchor-Based Molecular Network (ABMN). Biological samples from presumed NPS consumers were integrated into the reference network to connect patient-derived features with anchor compounds. Data were processed with MZmine for feature extraction, MetGem for molecular networking, and SIRIUS for in silico structure prediction. Protocol P1 (protein precipitation and analyte concentration) provided the best extraction, recovering 90% of analytes with high chromatographic quality. P1 achieved the lowest limit of identification, enabling MS/MS acquisition for 100% of compounds at 50 ng/mL, 97% at 5 ng/mL, and 42% at 0.5 ng/mL. RP-LC and HILIC proved complementary, improving analyte coverage. The Mix122 dataset yielded chemically coherent clusters, supporting integration of clinical samples. Several structurally related analogues such as bromazolam, fluoromethamphetamine, or MDPHP were identified. The ABMN-based LC-HRMS/MS strategy provides a robust and transferable analytical platform for comprehensive and sensitive screening of unknown NPS, even at trace levels down to 1 ng/mL.

Keywords:  Analytical workflow; Liquid chromatography-high-resolution tandem mass spectrometry; New psychoactive substances; Orthogonal chromatography; Sample preparation; Untargeted metabolomics

DOI:  https://doi.org/10.1007/s00216-025-06262-8
Anal Chim Acta. 2026 Jan 15. pii: S0003-2670(25)01297-8. [Epub ahead of print]1383 344903

Ultra high-performance supercritical fluid chromatography-mass spectrometry emerging as a complementary approach for targeted steroid analysis.

Taťána Gazárková, Kateřina Plachká, Hana Kočová Vlčková, Lucie Nováková.

   BACKGROUND: Steroid analysis plays a crucial role in biomedical research, yet the simultaneous quantification of multiple steroid classes in biological fluids remains challenging because of their high structural similarity and the resulting crosstalk. Ultra-high-performance supercritical fluid chromatography (UHPSFC) has emerged as a promising alternative to traditional liquid and gas chromatography approaches, offering improved separation of isomers. However, the limited ionization efficiency of 3-hydroxy steroids constrains MS sensitivity not only in UHPSFC-MS/MS. UniSpray (US) represents an alternative ionization source with the potential to enhance method sensitivity compared to a common electrospray ionization (ESI) source, given the improved droplet dispersion and desolvation mechanism of US. Yet, the implementation of US in UHPSFC-MS/MS in steroidomics has not been systematically explored.
RESULTS: A UHPSFC-US-MS/MS method was developed as a complementary approach for profiling and quantification of 36 steroids, comprising a complex mixture of 15 stereoisomers, 17 positional isomers, and 4 additional non-interfering compounds. Despite the high level of isomer coverage, the UHPSFC exhibited excellent chromatographic performance with separation scores higher by 13-17% over UHPLC, observed already during the column screening. Using an optimized CO2/methanol gradient on a Torus 1-AA column, a complete separation of critical isomers was achieved in 14 min, reducing the analysis time by 25% compared to published UHPLC-MS/MS methods. Compared to ESI, US resulted in a 5-12.3× increase in S/N-related MS response for both 3-keto-4-ene and poorly ionizing 3-hydroxy steroids, and exhibited lower matrix effects in human plasma, especially at low concentration levels. The validated UHPSFC-US-MS/MS method matched or exceeded the performance and limits of quantification of published UHPSFC-MS/MS and UHPLC-MS/MS studies while simultaneously resolving a uniquely broad panel of steroid isomers.
SIGNIFICANCE: This study presents a comprehensive UHPSFC-MS/MS method for steroid profiling, integrating the complete separation of an extensive number of steroid isomers, achieved in a shorter analysis time compared to UHPLC, and the first systematic characterization of US in this field. Enhanced method sensitivity, improved limits of quantification, and reduced matrix effects reinforced the potential of US as a complementary ionization source to ESI and provided a valuable reference point for future UHPSFC-US-MS/MS studies. The viability of UHPSFC-MS/MS approaches in biomedical applications has been further supported by successful method validation.

Keywords:  Electrospray; Mass spectrometry; Matrix effects; Steroid crosstalk; Steroids; Supercritical fluid chromatography; UniSpray

DOI:  https://doi.org/10.1016/j.aca.2025.344903
Se Pu. 2025 Dec;43(12): 1389-1396

[Simultaneous determination of vitamins K1 and K2 in cosmetics by QuEChERS-high performance liquid chromatography and verification by high performance liquid chromatography-tandem mass spectrometry].

Qian Sun, Chun-Xiao Chen.

  Vitamins K1 and K2 are both essential fat-soluble vitamins for the human body. K1 was once used in cosmetics for its efficacy in improving dark circles by promoting periorbital circulation. However， due to its potential to cause severe allergic reactions， it is now banned in cosmetics in China and the European Union. K2， particularly the MK-7 form， has a similar structure to K1 but features a different side chain. It has gained attention for its skin benefits， including soothing， antioxidant， and anti-aging properties. Although there are no reports of its use in cosmetics in China yet， it has been registered three times as a new cosmetic ingredient， indicating significant market potential. Most existing methods for detecting vitamins K1 and K2 focus on pharmaceuticals and dietary supplements， with few studies addressing their analysis in cosmetics， especially vitamin K2. Given the structural similarity between the two compounds， a reliable method for their simultaneous determination in cosmetic products is needed. However， cosmetic matrices are complex and often interfere with analysis. Conventional sample preparation techniques， such as liquid-liquid extraction and solid-phase extraction， are time-consuming and labor-intensive. The QuEChERS method offers a faster， simpler， and more cost-effective alternative. In this study， we selected six common types of cosmetics-water-based liquids， emulsions， creams， gels， powders， and oils， to develop and validate a simultaneous quantification method for vitamins K1 and K2. A QuEChERS-based sample preparation method coupled with high performance liquid chromatography （HPLC） was developed for the simultaneous quantification of vitamins K1 and K2 in cosmetics. To enhance specificity and confirmation capability， a complementary method using high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS） was also established. Samples were first pre-dispersed with saturated sodium chloride solution， extracted by n-hexane under ultrasonication， and purified using QuEChERS pretreatment technique （containing 150 mg MgSO4， 50 mg PSA， and 25 mg C18）. For HPLC analysis， separation was performed on a CAPCELL PAK C18 AQ column （250 mm×4.6 mm， 5 µm） using methanol-isopropanol （80∶20， volume ratito） as the mobile phase， with detection at 270 nm. For HPLC-MS/MS confirmation， an ACQUITY UPLC BEH C18 column （50 mm×2.1 mm， 1.7 µm） was employed， with methanol containing 0.05% （volume fraction） formic acid and 5 mmol/L ammonium formate as the mobile phase. Electrospray ionization in positive mode （ESI+） and multiple reaction monitoring （MRM） were used for detection. Both HPLC and HPLC-MS/MS methods demonstrated excellent performance for the determination of vitamins K1 and K2. In the HPLC method， both analytes showed good linearity over the range of 0.1-50 μg/mL （r>0.999）， with limits of detection （LOD） and quantification （LOQ） of 0.3 μg/g and 1.0 μg/g， respectively. The spiked recoveries ranged from 93.2%-104.5% with RSDs below 5%. For the HPLC-MS/MS method， linearity was observed in the range of 0.005-0.5 μg/mL （r>0.999）， with LOD and LOQ values of 0.02 μg/g and 0.05 μg/g， respectively. Recoveries in this case fell within 89.4%-108.2%， accompanied by RSDs of less than 10%. The method was successfully applied to analyze 30 cosmetic samples spanning six different matrix types. Neither vitamin K1 nor K2 was detected in any sample. The proposed methodology is rapid， simple， sensitive， and accurate， making it suitable for routine determination of vitamins K1 and K2 in diverse cosmetic products. It offers reliable technical support for quality control and regulatory compliance and demonstrates the utility of QuEChERS sample preparation for the analysis of other cosmetic ingredients.

Keywords:  QuEChERS; cosmetic; high performance liquid chromatography （HPLC）; high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS）; vitamin K1; vitamin K2

DOI:  https://doi.org/10.3724/SP.J.1123.2025.06011
Foods. 2025 Nov 25. pii: 4040. [Epub ahead of print]14(23):

Development and Validation of an LC-MS/MS Method for Quantifying Phytohormones Related to Tomato Shelf Life.

Muhammad K Hakeem, Haneen Abufarajallah, Maryam Abushahab, Gamilah Abdulgabar, Hind Alneyadi, Shaikha Alnaqbi, Sampathkumar Elangovan, Iltaf Shah.

  Phytohormones are key signaling molecules that regulate plant growth, stress adaptation, and fruit ripening. However, their low abundance and structural diversity complicate accurate quantification in food matrices. This study presents a validated LC-MS/MS method for the simultaneous detection of seven phytohormones in tomato fruit, including two synthetic analogs that mimic natural auxins and cytokinins. Method optimization focused on extraction efficiency, solid-phase cleanup, and mobile phase composition, achieving high recovery (85-95%) and reduced matrix effects. Chromatographic separation was performed on a C18 column, with detection by triple quadrupole mass spectrometry in MRM mode. The method demonstrated excellent linearity (R2 > 0.98), precision, and robustness, with detection limits as low as 0.05 ng/mL for abscisic acid and 6-benzylaminopurine. Validation followed US-FDA and EC 2021/808 guidelines, ensuring regulatory compliance and analytical reliability. Analysis of tomato samples from five geographic origins revealed significant differences in phytohormone profiles, particularly in abscisic and salicylic acids, highlighting the method's ability to capture biologically and agriculturally relevant variation. This workflow offers a sensitive, transferable platform for monitoring bioactive compounds in tomatoes and other food crops, supporting post-harvest quality assessment and food metabolomics research.

Keywords:  LC-MS/MS; liquid chromatography-mass spectrometry; method validation; phytohormones; plant hormone; tomato

DOI:  https://doi.org/10.3390/foods14234040
Environ Sci (Camb). 2025 Nov 28.

Targeted LC-MS/MS method for quantifying respiratory pharmaceuticals in wastewater.

Regina L Gasparetto, Scott Bickel, Xinmin Yin, Ted Smith, Aruni Bhatnagar, Rochelle H Holm, Xiang Zhang.

Background: Wastewater-based epidemiology (WBE) enables the population-level surveillance of molecular and chemical targets. Despite the high prevalence of respiratory diseases, there is a lack of sensitive analytical methods for detecting associated medications in complex wastewater matrices. Methods: We developed and validated a liquid chromatography-mass spectrometry (LC-MS)/MS method using multiple reaction monitoring for 10 common respiratory pharmaceuticals. The workflow integrated freeze-drying for preconcentration, online solid-phase extraction for cleanup, and stable isotope-labeled internal standards (SILs) to compensate for matrix effects. Results: Detection and quantification limits ranged from 0.7 to 19 ng L-1 and 3 to 125 ng L-1, respectively, with recoveries of 82-194% and precision within 0.14-7.2% relative standard deviation. Matrix effects (64-228%) were effectively corrected using SILs. Application to 12 neighborhood-level wastewater samples detected 9 of the 10 target compounds, with 6 (albuterol, amoxicillin, azithromycin, cetirizine, diphenhydramine, and fexofenadine), detected above their quantification limits. Fexofenadine was the most abundant, reaching 3309 ng L-1. Conclusion: This robust, low-volume, high-throughput LC-MS/MS method enables the reliable detection of respiratory pharmaceuticals in wastewater, supporting WBE applications for pharmaceutical use surveillance.

DOI: https://doi.org/10.1039/d5ew00894h
Nat Commun. 2025 Dec 09. 16(1): 10600

A resource to empirically establish drug exposure records directly from untargeted metabolomics data.

Haoqi Nina Zhao, Kine Eide Kvitne, Corinna Brungs, Siddharth Mohan, Vincent Charron-Lamoureux, Wout Bittremieux, Runbang Tang, Robin Schmid, Santosh Lamichhane, Shipei Xing, Yasin El Abiead, Mohammadsobhan S Andalibi, Helena Mannochio-Russo, Madison Ambre, Nicole E Avalon, MacKenzie Bryant, Lindsey A Burnett, Andrés Mauricio Caraballo-Rodríguez, Martin Casas Maya, Loryn Chin, Lluís Corominas, Ronald J Ellis, Donald Franklin, Sagan Girod, Paulo Wender P Gomes, Lauren Hansen, Robert K Heaton, Jennifer E Iudicello, Alan K Jarmusch, Lora Khatib, Scott Letendre, Sarolt Magyari, Daniel McDonald, Ipsita Mohanty, Andrés Cumsille, David J Moore, Prajit Rajkumar, Dylan H Ross, Harshada Sapre, Mohammad Reza Zare Shahneh, Ruben Gil-Solsona, Sydney P Thomas, Caitlin Tribelhorn, Helena M Tubb, Corinn Walker, Crystal X Wang, Jasmine Zemlin, Simone Zuffa, David S Wishart, Pablo Gago-Ferrero, Rima Kaddurah-Daouk, Mingxun Wang, Manuela Raffatellu, Karsten Zengler, Tomáš Pluskal, Libin Xu, Rob Knight, Shirley M Tsunoda, Pieter C Dorrestein.

Despite extensive efforts, extracting medication exposure information from clinical records remains challenging. To complement this approach, here we show the Global Natural Product Social Molecular Networking (GNPS) Drug Library, a tandem mass spectrometry (MS/MS) based resource designed for drug screening with untargeted metabolomics. This resource integrates MS/MS references of drugs and their metabolites/analogs with standardized vocabularies on their exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action. It enables direct analysis of drug exposure and metabolism from untargeted metabolomics data, supporting flexible summarization at multiple ontology levels to align with different research goals. We demonstrate its application by stratifying participants in a human immunodeficiency virus (HIV) cohort based on detected drug exposures. We uncover drug-associated alterations in microbiota-derived N-acyl lipids that are not captured when stratifying by self-reported medication use. Overall, GNPS Drug Library provides a scalable resource for empirical drug screening in clinical, nutritional, environmental, and other research disciplines, facilitating insights into the ecological and health consequences of drug exposures. While not intended for immediate clinical decision-making, it supports data-driven exploration of drug exposures where traditional records are limited or unreliable.

DOI: https://doi.org/10.1038/s41467-025-65993-5
Se Pu. 2025 Dec;43(12): 1374-1379

[Determination of caffeine and taurine in electronic cigarette oil by high performance liquid chromatography- tandem mass spectrometry].

Xiao Sun, Qi-Zhi Chang, Chang Wang, Wen-Hao Shao, Feng Feng.

  Electronic cigarette refers to electronic delivery systems designed to generate aerosols for human inhalation. In recent years， the global electronic cigarette market has experienced rapid expansion， drawing widespread international attention to its potential health impacts. To protect consumer health， China's mandatory National Standard for electronic cigarettes issued in 2022 explicitly prohibits the addition of additives and stimulants associated with energy and vitality in electronic cigarette oil. However， to attract consumers， many illicit manufacturers illegally incorporate various stimulating substances into e-liquids. While detection methods have been reported for some illegal additives such as industrial cannabinoids and sweeteners in electronic cigarette oil， there is no fast and reliable detection method for the determination of caffeine and taurine in electronic cigarette oil available to this day. In order to ensure human health， a method was developed for the simultaneous determination of caffeine and taurine in electronic cigarette oil using high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS） with a mixed-functional column. Sample preparation involved a simple dilution and filtration step， which was optimized prior to analysis. The analytes were separated on a FMD Comixsil ACRP column （100 mm×2.1 mm， 3.0 μm）. The column temperature was maintained at 30 ℃. The mobile phase consisted of acetonitrile and a 0.1% formic acid solution containing 10 mmol/L ammonium formate with gradient elution. The flow rate was 0.2 mL/min and the injection volume was 1μL. Mass spectrometric detection was carried out using electrospray ionization in positive mode （ESI+） with multiple reaction monitoring （MRM）. Under the optimized conditions， both caffeine and taurine were well retained on the chromatographic column， exhibiting excellent， tailing-free peak shapes. The method demonstrated that the limits of detection of caffeine and taurine were 0.100 and 1.00 mg/kg， and the limits of quantification were 0.250 and 2.50 mg/kg， respectively. The linear correlation coefficient （r） was ≥0.997. The average recovery of each component was 88.2%-99.0%， with relative standard deviation （RSD， n=6） between 2.2% and 6.6%. These results indicate that the method is simple， rapid and accurate. It has been successfully applied to the detection of caffeine and taurine in real electronic cigarette oil samples.

Keywords:  caffeine; electronic cigarette oil; high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS）; taurine

DOI:  https://doi.org/10.3724/SP.J.1123.2025.09003
ACS Omega. 2025 Dec 02. 10(47): 57592-57606

A Validated LC-MS/MS Method for the Determination of Sulindac and Its Metabolite Su-EP‑C in Human Plasma and Their Pharmacokinetic Application in Healthy Volunteers.

Tingting Lou, Benkai Qin, Jiaqi He, Hongliu Qu, Haiyan Rong, Qunan Cheng, Weiyong Lu, Yaqin Liu, Yonghua Yu.

A rapid, specific, and sensitive LC-MS/MS method for the determination of sulindac and its metabolite Su-EP-C in human EDTA-K2 plasma was developed. The method was fully validated using sulindac-d3 and Su-EP-C-d3 as internal standards. Separation was performed on a Kinetex C18 analytical column (100 Å, 50 × 2.1 mm, 5 μm). MPA consisted of 0.05% formic acid (FA) in water, while MPB comprised 0.05% FA in ACN. The flow rate was maintained at 0.300 mL/min, and the injection volume was 3 μL. Mass spectrometry conditions: ESI, positive mode, MRM. The linear range of detection was from 60.00 to 24,000.00 ng/mL for sulindac and from 30.00 to 12,000.00 ng/mL for Su-EP-C. The intra- and interbatch accuracy deviations of sulindac ranged from -5.1 to 5.0%, and the intra- and interbatch precision ranged from 3.3 to 4.2%. The intra- and interbatch accuracy of Su-EP-C ranged from -3.9 to 6.9%, and the intra- and interbatch precision ranged from 4.8 to 7.2% at all concentration levels. At a dilution of 10, the deviation for sulindac was 3.5% and the precision was 1.5%; the deviation for Su-EP-C was 2.7%, and the precision was 4.4%. The plasma matrix, at both -20 °C and -70 °C, remained stable for 52 days with 5 freeze-thaw cycles. The method was successfully applied to fasting and postprandial pharmacokinetic clinical trials of orally administered sulindac tablets.

DOI: https://doi.org/10.1021/acsomega.5c08386
Foods. 2025 Nov 28. pii: 4087. [Epub ahead of print]14(23):

Quantitative Analysis of Diazepam Residues in Aquatic Products Using Magnetic Solid-Phase Extraction Combined with Ultra-High-Performance Liquid Chromatography-Tandem Mass Spectrometry.

Mengqiong Yang, Guangming Mei, Daoxiang Huang, Xiaojun Zhang, Pengfei He.

  A method combining magnetic solid-phase extraction (MSPE) with ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was developed for the determination of diazepam residues in aquatic products. A novel magnetic nanoparticle material, Fe3O4@SiO2@DVB-NVP, was synthesized and applied as an adsorbent for sample cleanup. The sample preparation procedure involved extraction with 1% ammonia-acetonitrile, followed by purification using the MSPE technique to efficiently remove matrix interferents. Chromatographic separation was achieved on an ACQUITY UPLC BEH C18 column with a gradient elution program using a mobile phase composed of 0.1% formic acid-2 mM ammonium acetate solution and methanol. Detection was performed under multiple-reaction monitoring (MRM) mode with positive electrospray ionization (ESI+). Quantification was carried out using the external standard method. The synthesized magnetic material was characterized using SEM, TEM, FTIR, XRD, BET, and VSM, confirming its mesoporous structure, strong adsorption capacity, and excellent magnetic responsiveness. The method demonstrated good linearity over the concentration range of 0.25-50 μg/L (r2 = 0.997). The limits of detection and quantification were 0.20 μg/kg and 0.50 μg/kg, respectively. Average recoveries from spiked blank matrices at three levels (0.5, 2.5, and 5.0 μg/kg) ranged from 89.3% to 119.7%, with relative standard deviations (RSDs) between 0.8% and 10.2%. The proposed method is highly selective, exhibits minimal matrix interference, and provides reliable quantitative performance, making it suitable for the qualitative and quantitative analysis of diazepam residues in aquatic products.

Keywords:  UPLC–MS/MS; aquatic products; diazepam; magnetic solid-phase extraction

DOI:  https://doi.org/10.3390/foods14234087
Prog Nucl Magn Reson Spectrosc. 2025 Nov-Dec;150-151:pii: S0079-6565(25)00008-1. [Epub ahead of print]150-151 101564

NMR-based metabolomics: Where are we now and where are we going?

G A Nagana Gowda, Wentao Zhu, Daniel Raftery.

  The fast-growing field of metabolomics focuses on the analyses of complicated mixtures of small molecules present in biological samples. To date, metabolomics has provided a wealth of information on biological systems and impacted numerous areas of basic and life sciences. A major focus of metabolomics has been on biomedicine with the goal of biomarker discovery, drug discovery and improved mechanistic understanding of the pathogenesis of many human diseases. Analytical methods play a pivotal role in metabolomics, with the two most widely used platforms being nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Among their many complementary capabilities, NMR is generally more reproducible and quantitative, whereas MS is more sensitive. Recent technological advances in NMR have resulted in multifaceted developments, including improvements in sensitivity, resolution and speed, along with expanded metabolite identification and quantitation, which together provide exciting potential for future studies. In addition to NMR developments, the combination of NMR with MS provides numerous benefits that are becoming more evident over time. Hence, the metabolomics field has witnessed an increased number of studies and applications that combine NMR with MS in numerous areas, including new methods development for unknown identification, metabolite quantitation, disease biomarker discovery, mechanistic understanding of disease pathogenesis, and dietary risk factors of diseases among others. This report describes the current status of state-of-the-art methods in NMR-based metabolomics, along with recent advances and future prospects, with an emphasis on the benefits of combining NMR with MS.

Keywords:  Biomarker discovery; Health; Mass spectrometry; NMR spectroscopy; Nutrition; Quantitation; Unknown identification

DOI:  https://doi.org/10.1016/j.pnmrs.2025.101564
Gigascience. 2025 Dec 09. pii: giaf150. [Epub ahead of print]

A sulfatide-centered ultra-high resolution magnetic resonance MALDI imaging benchmark dataset for MS1-based lipid annotation tools.

Lars Gruber, Stefan Schmidt, Thomas Enzlein, Carsten Hopf.

  Spatial 'omics techniques are indispensable for studying complex biological systems and for the discovery of spatial biomarkers. While several current matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) instruments are capable of localizing numerous metabolites at high spatial and spectral resolution, the majority of MSI data is acquired at the MS1 level only. Assigning molecular identities based on MS1 data presents significant analytical and computational challenges, as the inherent limitations of MS1 data preclude confident annotations beyond the sum formula level. To enable future advancements of computational lipid annotation tools, well-characterized benchmark - or ground truth - datasets are crucial, which exceed the scope of synthetic data or data derived from mimetic tissue models. To this end, we provide two sulfatide-centered, biology-driven magnetic resonance MSI (MR-MSI) datasets at different mass resolving powers that characterize lipids in a mouse model of human metachromatic dystrophy. This data includes an ultra-high-resolution (R ∼1,230,000) quantum cascade laser mid-infrared imaging-guided MR-MSI dataset that enables isotopic fine structure analysis and therefore enhances the level of confidence substantially. To highlight the usefulness of the data, we compared 118 manual sulfatide annotations with the number of decoy database-controlled sulfatide annotations performed in Metaspace (67 at FDR < 10%). Overall, our datasets can be used to benchmark annotation algorithms, validate spatial biomarker discovery pipelines, and serve as a reference for future studies that explore sulfatide metabolism and its spatial regulation.

Keywords:  MALDI imaging; MALDI mass spectrometry; MRMS; isotope fine structure; lipidomics; mass spectrometry imaging; metabolite annotation tools; metabolomics; mid-infrared imaging

DOI:  https://doi.org/10.1093/gigascience/giaf150
Anal Chim Acta. 2026 Jan 15. pii: S0003-2670(25)01265-6. [Epub ahead of print]1383 344871

Development and validation of UPLC-MS/MS method for detecting nootropic misuse in oral fluids: A step towards combating doping in Esports.

Kassim Ali Salum, Meng-Tsang Hsieh, Shao-Hsin Hung, Hung-Chih Chen, William Chih-Wei Chang.

   BACKGROUND: Esports, now officially recognised by the Olympic movement, requires effective anti-doping measures tailored to its unique performance demands. Traditional tests target substances enhancing strength or endurance, yet Esports performance is often influenced by nootropics or "smart drugs"-compounds improving focus, reaction time, and cognition. This study presents a validated sample preparation protocol and UPLC-MS/MS method for detecting nootropics of concern, including substances currently prohibited, under review, or potentially capable of enhancing Esports performance. Oral fluid is employed as a rapid, non-invasive specimen, offering a practical approach for doping control in Esports.
RESULTS: Extraction and quantification of 13 nootropics and their metabolites in oral fluid, collected via self-administered oral swabs, were successfully optimised. Solid-phase extraction yielded the highest recoveries for analytes across a wide range of physicochemical properties, outperforming both dilute-and-shoot and supported liquid extraction approaches. The analytes were separated within 4 min using a UPLC BEH C18 column. The analytical method was fully validated, demonstrating good precision, accuracy, and lower quantification limits ranging from 0.01 to 50 ng/mL. Most analytes remained stable for one day at room temperature, three days under refrigeration, and one month when frozen. Oral fluid sampling proved effective in detecting nootropics in authentic volunteer samples for up to 4 h post-administration. Detected concentrations included pentoxifylline (7.9-97.2 ng/mL), piracetam (2.8-215.2 μg/mL), and nicergoline (as its main metabolite; 0.6-5.3 ng/mL). Variability in concentrations was influenced by swab positioning and food intake prior to sampling.
SIGNIFICANCE: This study establishes a robust and practical analytical method utilising oral fluid for the detection of nootropics relevant to doping control in Esports. The approach enables rapid, non-invasive sample collection and reliable quantification, offering the potential for routine pre-game and in-competition monitoring. While the method is validated, further investigation is warranted to define drug excretion profiles and detection windows in oral fluid under real-use conditions.

Keywords:  Alternative matrix; Gamers; Performance enhancing drug; Saliva; Sports drug testing; World Anti-Doping Agency

DOI:  https://doi.org/10.1016/j.aca.2025.344871
Anal Chem. 2025 Dec 10.

Machine Learning-Assisted False Positive Detection in Metabolite Identification Workflows.

Ramon Adàlia, Paula Cifuentes, Joyce Liu, Lionel Cheruzel, Gemma Sanjuan, Tomàs Margalef, Ismael Zamora.

Metabolite identification is a pivotal step in drug discovery and development, enabling the comprehensive analysis of drug-derived compounds within biological systems. However, the complexity of liquid chromatography-mass spectrometry data often results in numerous false positives, complicating the identification of true metabolites. This study introduces a machine-learning-based approach to improve the accuracy of false positive detection in metabolite identification workflows. By incorporating expert knowledge, we develop a feature set for metabolite-related chromatographic peaks that characterizes true and false positives with high accuracy, integrating data from mass spectra, chromatographic signals, and kinetic profiles. We validate this method via gradient boosting decision tree classifiers on both publicly available and proprietary "real-world" data sets, including small molecules and new modalities. Our findings demonstrate that machine learning-assisted techniques significantly reduce false positive identifications, thereby increasing the efficiency and accuracy of metabolite identification processes.

DOI: https://doi.org/10.1021/acs.analchem.5c02745
J Pharm Biomed Anal. 2025 Dec 04. pii: S0731-7085(25)00639-9. [Epub ahead of print]270 117298

A universal LC-HRMS workflow integrating targeted and untargeted strategies for rapid and comprehensive metabolite profiling of oligonucleotide-based therapeutics.

Yuqing Zhao, Yue Yang, Mingshe Zhu, Chongzhuang Tang.

  Metabolite profiling and identification of oligonucleotide-based therapeutics (OBTs) is important in drug discovery and development. Conventional liquid chromatography-high resolution mass spectrometry (LC-HRMS) methods (using ProMass, BioPharma Finder) are effective for targeted analysis of predictable nuclease-derived metabolites but often miss unexpected non-nuclease-mediated ones. This study aimed to develop a universal analytical workflow for comprehensive metabolite profiling of multiple classes OBTs by integrating BioPharma Finder for targeted identification with a Background Subtraction Filter (BSF) for untargeted detection of unexpected biotransformation products. Inclisiran, a GalNAc-conjugated siRNA, was used as a model compound. Samples incubated with rat, monkey, and human liver S9 fractions were analyzed by the LC-HRMS workflow. As a result, a total of 25 (22 predicted +3 unpredicted) inclisiran metabolites were identified across the three species. BioPharma Finder enabled rapid and sensitive identification of 22 predicted metabolites, supported by automated fragment ion assignment. The BSF data processing revealed 22 metabolites not present in control samples, including SS-1GalNAc, SS-2GalNAc, and SS-3GalNAc, which were missed by BioPharma Finder and likely formed via β-N-acetylglucosaminidase-mediated biotransformation. The structures of BSF-detected metabolites were confirmed by comparison with BioPharma Finder-identified metabolites or characterized through manual MS/MS interpretation. Product ion spectra of these metabolites showed weak or absent diagnostic ion (m/z 94.936), a characteristic fragment of phosphorothioate-containing oligonucleotides, suggesting that the product ion filtering of this ion exhibits limited utility in discovering inclisiran metabolites. Overall, the integrated LC-HRMS workflow shows strong potential as a universal platform for biotransformation studies of OBTs.

Keywords:  Background subtraction filter; BioPharma finder; Metabolites identification; Oligonucleotide-based therapeutics; Universal LC-HRMS workflow

DOI:  https://doi.org/10.1016/j.jpba.2025.117298
Anal Chem. 2025 Dec 09.

GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction.

Yihui Ren, Dongbo Bu, Bo Duan, Chunming Zhang, Bin Cong, Shiwei Sun.

Protein glycosylation is a critical post-translational modification involved in numerous biological processes and disease states. While mass spectrometry has emerged as the primary tool for glycoproteomics analysis, the structural complexity and heterogeneity of glycopeptides pose significant analytical challenges. Existing glycopeptide identification tools primarily rely on mass matching, underutilizing intensity information from mass spectra, which limits their ability to discriminate between similar glycopeptides (glycopeptides bearing analogous glycans/peptide backbones). Here we present GPMassSimulator, an innovative deep learning framework for accurate prediction of intact N-glycopeptide tandem mass spectrometry (MS/MS) spectra and retention time. GPMassSimulator employs the GpepFormer module to effectively represent and integrate both peptide sequences and glycan structures, capturing their complex dependencies. The integrated representation is then passed through the Prediction module to generate the theoretical MS/MS spectra and the retention time of the glycopeptides. Our method demonstrated an outstanding performance on the benchmark set. In the experiment distinguishing similar glycan compositions, GPMassSimulator achieved an identification accuracy of 97.1%. Furthermore, in distinguishing isomeric structures, our method achieved more accurate Top-1 identifications than the current approaches. Additionally, the rescoring experiment on pGlyco3 highlighted the significant improvement in the sensitivity of our model for glycopeptide identification. These excellent results showcased the promising potential of our approach in glycoproteomics.

DOI: https://doi.org/10.1021/acs.analchem.5c02375
Nat Commun. 2025 Dec 12. 16(1): 11102

FIDDLE: a deep learning method for chemical formulas prediction from tandem mass spectra.

Yuhui Hong, Sujun Li, Yuzhen Ye, Haixu Tang.

Molecular identification through tandem mass spectrometry is fundamental in small molecule analysis, with formula identification serving as an initial step in the process. Current computational methods often struggle with accuracy, speed, and scalability for relatively larger molecules, limiting high-throughput workflows. We present FIDDLE (Formula IDentification by Deep LEarning), a deep learning-based method trained on over 38,000 molecules and 1 million MS/MS spectra from various Quadrupole Time-of-Flight (Q-TOF) and Orbitrap instruments. FIDDLE accelerates formula identification by more than 10-fold and achieves top-1 and top-5 accuracies of 88.3% and 93.6%, respectively, outperforming state-of-the-art methods based on top-down (SIRIUS) and bottom-up (BUDDY) approaches by over 10%. On external metabolomics datasets, FIDDLE achieves top-5 accuracies of 75.1% (positive ion mode) and 66.2% (negative ion mode), with further improvements to 80.0% and 73.8% when combined with SIRIUS and BUDDY.

DOI: https://doi.org/10.1038/s41467-025-66060-9
Rapid Commun Mass Spectrom. 2026 Mar 15. 40(5): e70008

Synthesis of Reference Standards and Optimization of UPLC-ESI-MS/MS Method for Quantification of Organosulfates in PM2.5.

Zhichao Dong, Subba Rao Devineni, Xiaoli Fu, Zhanjie Xu, Mingyu Li, Pingqing Fu, Cong-Qiang Liu, Chandra Mouli Pavuluri.

RATIONALE: Atmospheric PM2.5 affects climate by altering radiative forcing and harms human health. Organosulfates (OSs) intensify these impacts, as cloud condensation nuclei modify the radiation balance and increase toxicological risks. We synthesized OSs reference standards and optimized a sensitive UPLC-MS/MS method, enabling precise quantification to mitigate PM2.5 pollution on climate and health.
METHODS: We synthesized five organosulfates (ethyl-, 3-methylbenzyl-, cyclohexyl-, benzyl-, and phenethyl sulfate) as reference standards. These, combined with four commercial standards (methyl-, phenyl-, octyl-, and 4-nitrophenyl sulfate), were quantified by ultra-high performance liquid chromatography coupled with electrospray ionization (ESI) tandem mass spectrometry (UPLC-ESI-MS/MS). Separation used a Waters HSS T3 column with a gradient mobile phase (0.1% formic acid in H2O/CH3OH). ESI in negative mode enabled sensitive MS/MS detection.
RESULTS: A nine-point calibration curve ranging from 0.08 to 20 ng mL-1 of standards in solvent was used to establish instrument response. The method was validated by analysis of three replicate environmental samples fortified with 5 ng mL-1 of mixed standard. The recoveries of various OSs were 44%-126%, and their method detection limits were 0.10 ng mL-1 and the method limits of quantification were 0.50 ng mL-1.
CONCLUSIONS: The optimized UPLC-ESI-MS/MS method was successfully applied for the determination of various OSs in PM2.5 collected from Tianjin, China. It enables the precise measurement of OSs in aerosols that provide a critical tool to improve air quality monitoring and develop strategies to reduce pollution-related health impacts.

DOI: https://doi.org/10.1002/rcm.70008
Anal Chem. 2025 Dec 09.

HDSE-MS: Tandem Mass Spectrum Prediction for Small Molecules via Hierarchical Distance Structural Encoding.

Zhangqiang Liu, Bingyi Wang, Congcong Yang, Nannan Bai, Weihua Li.

Tandem mass spectrometry (MS/MS) is a core technology for small molecule structural elucidation in nontargeted metabolomics. However, the limited coverage of experimental spectral libraries presents a major challenge to MS-based small molecule identification. Although spectrum prediction methods offer a promising alternative, existing approaches often suffer from limitations in combinatorial enumeration strategies or insufficient molecular representation capabilities, leading to poor generalizability. To address this, we propose HDSE-MS, an MS/MS spectrum prediction model that integrates a message passing neural network (MPNN) with a Transformer architecture enhanced by hierarchical distance structural encoding (HDSE). By applying graph coarsening, the model transforms molecular graphs into multilevel cluster structures and encodes the hierarchical distances between clusters as structural biases in the Transformer. This enables the joint modeling of molecular substructures, their hierarchical relationships, and long-range dependencies, thereby improving the model's ability to represent complex molecular structures. We conducted a comprehensive evaluation of HDSE-MS on three benchmark data sets: NIST23, MoNA, and MassBank. Experimental results show that HDSE-MS outperforms existing methods, achieving mean spectral entropy similarities of 0.759, 0.567, and 0.483 under the [M + H]+ ionization mode, respectively. Furthermore, on the external CASMI2022 test set, HDSE-MS achieved a Rank of 220.8 and a Top-1 accuracy of 0.098, demonstrating its strong predictive accuracy, robust generalization, and scalability. The source code is publicly available at https://github.com/lzjforyou/HDSE-MS, and an interactive web service is accessible at https://huggingface.co/spaces/liuzhijin/hdse-ms-attn-viz.

DOI: https://doi.org/10.1021/acs.analchem.5c04111
Se Pu. 2025 Dec;43(12): 1364-1373

[Determination of 26 herbicide residues in soil， sediment， and surface water samples using modified QuEChERS method combined with ultra-high performance liquid chromatography-tandem mass spectrometry].

Li Zhao, Lin Ma, Lan-Qi Huang, Jian-Bo Chen, Wei-Fang Zhu.

  As chemical agents that selectively inhibit weed growth， herbicides play a crucial role in enhancing crop yields. With increasing weed resistance， the environmental residue problems caused by excessive application have become increasingly prominent. Studies indicate that only 20%-30% of field-applied herbicides are effectively utilized， with the remainder entering environmental media such as the atmosphere， soil， sediment， and surface water through runoff and leaching. Recent frequent occurrences of vegetable phytotoxicity incidents in Shanghai have been traced to potential associations with herbicide residues in surface water， further highlighting the urgent need to establish multi-residue analytical methods for environmental media. An analytical method was established based on ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS） for determining 26 herbicide residues in soil， sediment， and surface water. Instrumental detection parameters were optimized， including electrospray ionization mode， mobile phase， and chromatographic column. The mobile phase consisted of 0.1% formic acid aqueous solution （A） and acetonitrile （B） with the following gradient elution program： 0-0.5 min， 2%B； 0.5-1 min， 2%B-50%B； 1-4 min， 50%B-65%B； 4-6 min， 65%B-75%B； 6-8 min，75%B-85%B； 8-10 min， 85%B-95% B； 10-11 min， 95%B. Soil and sediment samples were extracted via acetonitrile oscillation followed by salting-out and purified using the QuEChERS method. Surface water samples were directly analyzed after acetonitrile extraction without purification. Different amounts of purification agents were investigated during sample pretreatment. Calibration curves were established by plotting the relationship between analyte concentration and measured peak area using pure solvent and matrix-matched standards. All 26 herbicides showed good linearity in the range of 0.1-50 μg/L with correlation coefficients exceeding 0.999 0. Matrix effects ranged from -35.2% to 14.6% across different matrices. Limits of quantification （LOQs） were 0.5 μg/kg for soil and sediment， 0.1 μg/L for water samples. The herbicides were spiked into soil and sediment at spiked levels of 0.5， 1， and 10 μg/kg， and into surface water at 0.1， 1， and 10 μg/L， respectively. The average recoveries for the 26 herbicides in soil， sediment， and surface water were in the ranges of 73%-108%， 73%-102%， and 74%-110%， respectively. The RSDs for the 26 herbicides were in the ranges of 4.5%-16.2%， 3.8%-19.7%， and 4.0%-15.0%， respectively. The developed method was applied to analyze the contamination status of the 26 herbicides in environmental samples collected from six vegetable cultivation zones in Shanghai. Results revealed distinct pollution patterns： In soil matrices， prometryn （PMT）， metolachlor （MTA）， and sulfometuron-methyl （SMTM） showed higher detection rates of 52.9%， 52.9%， and 29.4%， respectively， with content ranges of 0.8-490.4 μg/kg， 0.5-219.8 μg/kg， and 1.0-562.6 μg/kg. Sediment samples exhibited an 83.3% detection rate for PMT （1.5-6.7 μg/kg）. In surface water， SMTM， PMT， and simetryne （STN） were detected with maximum contents of 12， 2.5 and 1.1 μg/L， respectively， indicating differential migration behaviors across environmental compartments. The proposed method is simple， rapid， accurate， stable， and highly practical. It can be used to detect the 26 herbicide residues in soil， sediment， and surface water and provides a reference for monitoring the residual pollution and environmental behavior of herbicides.

Keywords:  QuEChERS; herbicide; sediment; soil; surface water; ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS）

DOI:  https://doi.org/10.3724/SP.J.1123.2025.02016
Int J Mol Sci. 2025 Nov 24. pii: 11353. [Epub ahead of print]26(23):

A Comparative Metabolomics Study of Multiple Urological Diseases by Highly Sensitive Dansylation Isotope Labeling LC-MS.

Wei-Hsuan Wang, Ya-Ju Hsieh, Chien-Lun Chen, Ying-Hsu Chang, Yi-Huai Tsai, Chih-Hsiang Chang, Liang Li, Wei-Ju Tu, Jau-Song Yu, Yi-Ting Chen.

  Urine analysis is a straightforward, non-invasive testing method that, when integrated with metabolomics, shows great potential for detecting small-molecule metabolites as biomarkers of abnormal metabolic activity in the urinary tract, including drug interactions, toxicity, and diseases. However, integrated and comparative analyses of multiple urinary tract pathologies are currently limited. In this study, 12C2/13C2-chemical dansylation labeling was used to explore the urinary amine/phenol-metabolome profiles of eight urological conditions compared with normal profiles. We obtained ten samples for each condition (disease and normal) from a total of 90 participants, pooling them as representative samples, and constructed metabolite panels to differentiate various urological conditions. We discovered nine metabolites that were dysregulated between urine samples from patients with and without cancer. Another seven metabolites were differentially expressed between the benign prostatic hyperplasia group and the prostate cancer group. Among 1854 peak pairs of metabolites in an amine/phenol submetabolome analyzed by dansyl chloride derivatization coupled with LC-MS/MS, 1747 (94.2%) were detectable in urine specimens from all nine groups. Notably, 18 identified metabolites showed substantial stability across all urological conditions. Given the considerable variability in urine metabolite composition, these metabolites could potentially be used for normalization in urine metabolome analysis, addressing the need for stably expressed molecules as internal standards in the development of urinary biomarkers. Our findings provide the preliminary insights into the stability of urinary metabolomics and the metabolic perturbations associated with different urinary tract-related pathologies.

Keywords:  isotope labeling LC-MS; metabolomics; urinary metabolome; urinary tract diseases

DOI:  https://doi.org/10.3390/ijms262311353
Drug Metab Dispos. 2025 Nov 10. pii: S0090-9556(25)09509-1. [Epub ahead of print]53(12): 100200

Application of acoustic ejection mass spectrometry for plasma protein binding assay using flux dialysis.

Xinxin Wen, Jie Wang, Xiaotong Li, Lili Xing, Genfu Chen, Yi Tao, Liang Shen.

  Flux dialysis, a superior method for plasma protein binding (PPB) measurement of compounds with challenging properties, has limitations in early-stage drug discovery due to multi-timepoint sampling and prolonged testing cycles. This study combines flux dialysis with acoustic ejection mass spectrometry (AEMS) to develop an innovative method that accelerates analytical throughput in PPB assays during drug discovery and demonstrates its application for the rapid and precise determination of the unbound fraction (fu) in plasma. Herein, we validated this approach using 10 commercially available compounds with known fu values-imipramine, indomethacin, itraconazole, lapatinib, nicardipine, warfarin, chlorpromazine, rivastigmine, zonisamide, and ritonavir-with a wide fu range covering from very high binding (fu ≤ 0.01) to low binding (fu > 0.10) in human plasma. By leveraging the advantages of chromatography-free analysis and nanoliter droplet ejection mode, AEMS achieves a speed of 3 seconds per sample using only 30 nL of sample volume. Our results showed that the fu values measured correlate strongly (R2 > 0.96) with those measured by liquid chromatography-tandem mass spectrometry. Additionally, fu values by AEMS correlate highly (R2 > 0.95) with those reported in the literature. In conclusion, this method presents a high-throughput, accurate, and efficient solution for PPB assays, improving speed by 25-fold compared to the liquid chromatography-tandem mass spectrometry method. SIGNIFICANCE STATEMENT: This study bridges the gap between flux dialysis and acoustic ejection mass spectrometry by creating a synergistic analytical framework for plasma protein binding assays, addressing limitations of both methods and enabling high-throughput applications with improved accuracy and efficiency. The combination of flux dialysis and acoustic ejection mass spectrometry will make a positive contribution to the development of high-throughput in vitro absorption, distribution, metabolism and excretion assays in drug discovery.

Keywords:  Acoustic ejection mass spectrometry; Flux dialysis; High-throughput; Plasma protein binding; Unbound fraction

DOI:  https://doi.org/10.1016/j.dmd.2025.100200
Arch Toxicol. 2025 Dec 08.

Predicting xenobiotic metabolism: a computational approach mining LC-MS/MS data with SIRIUS and BioTransformer.

Victoria Pozo Garcia, Mengqiu Zhang, Tuğçe S Çobanoğlu, Kasper Holm, Paul Jennings, David A Poole, Sofia Moco.

  Drug biotransformation and bioactivation play a pivotal role in drug discovery, driving the development of analytical methods to investigate xenobiotic metabolism. However, the identification of drug metabolism products (i.e., drug metabolites) remains challenging. Drug metabolites are difficult to predict, and they are often missed without prior knowledge of the drug's metabolic fate. Untargeted approaches overcome this requirement, but demand strategies for metabolite identification. In this study, we developed a computational workflow, using high resolution LC-MS/MS metabolomics data, integrating BioTransformer and SIRIUS for the prediction and putative identification of drug metabolite structures. We challenged our workflow to the analysis of human metabolites from 6 well-known drugs, administered to primary human hepatocytes and human liver microsomes: amitriptyline (10 µM), carbamazepine (12.5 µM), cyclophosphamide (20 µM), fipronil (20 µM), phenytoin (50 µM), and verapamil (6 µM). Of the drugs' metabolites, 62-100% were found using this computational approach. Furthermore, 4 new metabolite structures (1 amitriptyline metabolite and 3 verapamil metabolites) were proposed using de novo predictions in SIRIUS. This strategy proved efficient in accelerating the study of drug metabolism, potentially avoiding tedious manual metabolite identification. In sum, we demonstrate that this computational workflow holds potential in automating metabolite identification, expanding metabolite coverage, and elucidating metabolites of newly developed drugs.

Keywords:  BioTransformer; Drug; LC–MS; Metabolomics; SIRIUS; Xenobiotic metabolism

DOI:  https://doi.org/10.1007/s00204-025-04248-0
Anal Chim Acta. 2026 Jan 15. pii: S0003-2670(25)01281-4. [Epub ahead of print]1383 344887

3D-printed serpentine columns for size-exclusion chromatography with mass spectrometric detection.

Olanrewaju Awoyemi, Jing Wang, Madison Pursell, Amanda Overby, Riley White, Stephen J Valentine, Peng Li.

BACKGROUND: LC-MS is an important tool for analyzing various biomolecules. In recent years, 3D printing has shown great potential in customizing and improving LC-MS experiments. However, the direct coupling of stereolithography-based (SLA) LC column with mass spectrometry (MS) for biomolecule analysis has not been demonstrated.
RESULTS: In this work, we report the development of compact 3D-printed serpentine size exclusion chromatography (SEC) columns, which are effectively coupled with MS detection for biomolecule separations under native conditions. We utilized a simple surface coating strategy that effectively prevents chemical leaching in our compact 3D-printed serpentine size exclusion chromatography (SEC) columns. The 3D-printed serpentine SEC column (1.60 mm diameter x 150 mm length) shows highly reproducible peak retention times with a relative standard deviation (RSD) of less than <1.80 %. Additionally, it maintains a peak asymmetry factor <1.50 (RSD <8 %), confirming the reliability and consistency of the column performance. This column also demonstrates compatibility with high pressures, reaching up to 1.1 × 107 Pa (110 bar). Finally, we demonstrated the separation of a mixture of ubiquitin and angiotensin and a mixture of myoglobin and insulin with baseline resolutions and a tailing factor below 1.40.
SIGNIFICANCE: This work presents the first 3D-printed serpentine SEC columns compatible with spray-based MS analysis. It also paves the way for creating LC columns with custom geometry and integrating additional functional units for various LC-MS applications.

DOI: https://doi.org/10.1016/j.aca.2025.344887
Front Pharmacol. 2025 ;16 1704594

Development and validation of a two-dimensional liquid chromatography method for therapeutic drug monitoring of pyrotinib in human plasma.

Chunxia Gao, Yuzhi Cao, Mengna An, Zhihui Li, Chao Meng, Jingjing Lan, Haisheng You, Siying Chen.

   Objective: To develop and validate a method for therapeutic drug monitoring (TDM) of pyrotinib in human plasma using two-dimensional liquid chromatography (2D-LC) system.
Method: The plasma samples were pretreated with acetonitrile for protein precipitation. The mobile phase consisted of two parts: a first-dimensional mobile phase (methanol, acetonitrile, and 65 mmol/L ammonium phosphate in a ratio of 1:3:3, V/V/V) and a second-dimensional mobile phase (acetonitrile, isopropanol, and 10 mmol/L ammonium phosphate in a ratio of 16:7:1, V/V/V). The analysis cycle time was completed within 9.50 min. The method was validated for linearity, recovery, precision, accuracy, and stability.
Results: Pyrotinib demonstrated excellent linearity within the range of 10.10-810.40 ng/mL with regression equation y = 556.4044× + 462.40 (R 2 = 0.9995). The relative recovery rate of plasma samples was stable and reproducible, ranging from 96.82% to 100.12%. The intra-day and inter-day precisions were ≤5.30% and ≤3.80% for pyrotinib concentrations, respectively. Stability tests confirmed that pyrotinib in plasma remained stable under the following conditions: room temperature for 8 h, 4 °C for 48 h, -20 °C for 3 weeks, three freeze-thaw cycles. This method was validated in twenty patients with advanced HER2-positive breast cancer (dose range: 240-400 mg/day) The trough and peak plasma concentrations of pyrotinib ranged from 17.75-92.56 ng/mL and 51.17-232.94 ng/mL, respectively, which demonstrated significant pharmacokinetic heterogeneity.
Conclusion: The developed 2D-LC analytical method not only demonstrates good precision, accuracy, recovery, and stability, but also is simple, rapid, feasible, and practical for TDM. It can be used for the concentration monitoring of pyrotinib in clinic, providing more scientific evidence for clinical practice.

Keywords:  HER2-positive breast cancer; plasma drug concentration; pyrotinib; therapeutic drug monitoring; two-dimensional liquid chromatography; validation

DOI:  https://doi.org/10.3389/fphar.2025.1704594
Prog Nucl Magn Reson Spectrosc. 2025 Nov-Dec;150-151:pii: S0079-6565(25)00006-8. [Epub ahead of print]150-151 101562

Advances in food metabolomics: Validating NMR-based non-targeted methods and fostering collaborative NMR applications.

Biagia Musio, Antonino Rizzuti, Piero Mastrorilli, Vito Gallo.

  Food metabolomics has emerged as a powerful tool for characterizing complex food systems, offering a non-targeted highly discriminative approach for detecting authenticity, assessing quality, and ensuring safety across an array of food matrices. By capturing the complete spectral signature of a sample and reducing it to manageable variables, this technique provides an extensive metabolite snapshot that encompasses everything from minor compounds to major constituents. A key advantage lies in the reproducibility and robustness of NMR spectroscopy, allowing the comparison of spectra even across different instruments and laboratories. Such comparability fosters collaborative efforts and facilitates the establishment of large, community-built datasets, which are critical for advancing reliable classification models and enabling wide-scale deployment of non-targeted protocols. Rigor in each step, ranging from selecting representative authentic samples to optimizing acquisition parameters, data processing, and classification algorithms, proves essential for achieving consistent, high-quality metabolomics data. As validation and standardization practices become more widely accepted, NMR-based non-targeted approaches will accelerate innovations in food product monitoring and labeling, reduce analytical uncertainties, and address emerging challenges in food fraud detection. Ultimately, by combining best-in-class protocols, collaborative networks, and open-access data repositories, non-targeted NMR metabolomics has the potential to revolutionize traceability and foster global consumer confidence in the authenticity and quality of the food supply chain.

Keywords:  Collaborative analysis; Food metabolomics, non-targeted analysis, authenticity; Food quality control; Validation

DOI:  https://doi.org/10.1016/j.pnmrs.2025.101562
Sensors (Basel). 2025 Nov 21. pii: 7115. [Epub ahead of print]25(23):

Semi-Quantitative On-Site Microfluidic Assay to Detect 11-Nor-9-carboxy-delta 9-Tetrahydrocannabinol (THC-COOH) in Urine.

YeJi Jung, Isaac Choi, Hyunjun Bae, Joonseok Seo, Sunchun Kim, Sangki Lee, Jeongmin Lee, Yohan Jeong, Juhyung Kim, Heesun Chung, Hyunho Kim, Seok Chung.

  The rapid detection of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH), a primary cannabis metabolite, is critical for forensic and workplace drug testing. However, conventional immunoassays often lack sensitivity and objectivity. We developed a portable lateral flow immunoassay device with a microfluidic cartridge and fluorescent reader for the semi-quantitative detection of THC-COOH in urine. A test-to-reference fluorescence ratio was employed to mitigate matrix effects and ensure objective results. The device was validated for accuracy, repeatability, and stability using spiked urine samples and compared against validated LC-MS/MS results on 100 authentic urine samples (50 positive and 50 negative). At a cutoff of 20 ng/mL, the device achieved 100% sensitivity and specificity, with repeatability and reproducibility CVs of below 15%. The cutoff index (COI) strongly correlated with LC-MS/MS results (R2 = 0.9471). Crucially, this high correlation with hydrolyzed LC-MS/MS data demonstrates that the antibody recognizes both free and glucuronide-conjugated metabolites, validating its reliability without enzymatic pre-treatment. This microfluidic device enables rapid, sensitive on-site THC-COOH detection, featuring automated data management via Wi-Fi connectivity, enhancing its forensic applicability.

Keywords:  THC-COOH; biosensor; fluorescence-based LFA; forensic toxicology; lab-on-a-chip (LOC); matrix effect; microfluidic cartridge; point-of-care testing (POCT); portable analytical device; semi-quantitative analysis

DOI:  https://doi.org/10.3390/s25237115
Se Pu. 2025 Dec;43(12): 1327-1341

[Simultaneous screening of pesticides and mycotoxins in dried goji berries and mulberries by QuEChERS-liquid chromatography-quadrupole-time of flight mass spectrometry].

Hang Yin, Yu-Jie Xie, Meng-Jie Shi, Xing-Qiang Wu, Kai-Xuan Tong, Qiao-Ying Chang, Chun-Lin Fan, Hui Chen.

  Goji berries and mulberries are susceptible to pest and pathogen invasion due to their high sugar content and the impact of growth environment. Their quality and safety are primarily influenced by pesticide residues and mycotoxins. This study has developed a simple， high-throughput， and sensitive analytical method for the simultaneous determination of 172 pesticides and 11 mycotoxins in the medicinal and edible substances of goji berries and mulberries using an improved QuEChERS method coupled with liquid chromatography-quadrupole-time of flight mass spectrometry （LC-Q-TOF/MS）. The sample was hydrated with 7 mL of purified water， and 10 mL of 5% formic acid in acetonitrile was added as the extraction solvent， along with 4 g of anhydrous MgSO4 and 1 g of NaCl as extraction salts. The extract was purified using 400 mg of anhydrous MgSO4， 150 mg of primary secondary amine （PSA）， 100 mg of octadecylsilane （C18）， and 5 mg of multi walled carbon nanotubes （MWCNTs）. The supernatant was dried under nitrogen， and the residue was reconstituted in 1.0 mL of a methanol-water solution （3∶2， volume ratio）， homogenized by ultrasonication， and filtered through a 0.22 μm membrane prior to analysis. Separation was performed on a ZORBAX SB-C18 column （100 mm×2.1 mm， 3.5 μm） using a mobile phase consisting of 0.1% formic acid in aqueous solution （containing 5 mmol/L ammonium acetate） and 0.1% formic acid in methanol. Detection was carried out using electrospray ionization in positive mode with full ion MS/MS （All Ions MS/MS） scanning. Quantitation was achieved using a matrix-matched external calibration method. The results showed that this method can effectively reduce matrix effects， and 183 compounds exhibited good linearity within their respective ranges， with linear correlation coefficients （R2） greater than 0.995. The screening detection limits （SDLs） and limits of quantification （LOQs） for 172 pesticides in goji berries ranged from 1 to 50 μg/kg and 5 to 50 μg/kg， respectively. For mulberries， the SDLs and LOQs ranged from 1 to 20 μg/kg and 5 to 20 μg/kg， respectively. Additionally， the SDLs for 11 mycotoxins in goji berries were between 1 and 20 μg/kg， with corresponding LOQs of 5 to 50 μg/kg. In mulberries， the SDLs ranged from 1 to 10 μg/kg， while the LOQs were between 5 and 20 μg/kg. Overall， the LOQs of 183 compounds in mulberries were less than 20 μg/kg， and the proportions of pesticides and mycotoxins with LOQs less than 20 μg/kg in goji berries were 98.3% and 81.8%， respectively. At the spiked levels of 1， 2， and 10 times LOQs， the recoveries of 183 compounds ranged from 70.0% to 118.5%， 70.6% to 118.8%， and 71.2% to 119.0%， respectively， with relative standard deviations （RSDs） all less than 20.0%. The intra-day precision and inter-day precision of goji berries were 0.7%-9.8% and 1.0%-17.3%， respectively， whereas for mulberries were 0.8%-9.9% and 1.5%-16.0%， respectively. This method was applied to detect pesticides and mycotoxins in 15 batches of goji berries and 10 batches of mulberries， and a total of 16 compounds （including 13 pesticides and 3 mycotoxins） were detected with contents ranging from 5.61 to 622.47 μg/kg. Both detection rate and average content of pesticides and mycotoxins in goji berries were higher than those in mulberries. In addition， a preliminary risk assessment was conducted on the neonicotinoid pesticides with high detection rates （acetamiprid and imidacloprid）. The results showed that the chronic dietary intake risk values （%ADI） of acetamiprid and imidacloprid in goji berries were 0.04% and 0.02%， respectively. Both values are below 100% of the ADI in goji berries and are within acceptable limits. To ensure the safety and quality of goji berry and mulberry products， it is necessary to enhance the management and storage condition control of pesticides and mycotoxins. The results indicated that this method is simple to operate， highly sensitive， and suitable for high-throughput qualitative screening and accurate quantification of multiple pesticide residues and mycotoxins in both goji berries and mulberries. This method can provide reference for high-throughput screening of pesticide residues and mycotoxins in other berry medicinal and edible substances. Furthermore， it can indirectly promote industrial upgrading， facilitate the internationalization of medicinal and edible substances， and achieve a win-win situation regarding health value and economic benefits through technological innovation and the enhancement of standards.

Keywords:  QuEChERS; goji berry; liquid chromatography-quadrupole-time of flight mass spectrometry （LC-Q-TOF/MS）; medicinal and edible substances; mulberry; mycotoxins; pesticide residues

DOI:  https://doi.org/10.3724/SP.J.1123.2025.06009