Analytical Chemistry最新文献_第2页

Flow-LAMP: Label-Free Digital LAMP Using Scatter-Based Flow Cytometry on Vortex-Generated Polydisperse Gel Beads. Flow-LAMP：使用基于散射的流式细胞术对涡流产生的多分散凝胶珠进行无标签数字LAMP。

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-12 DOI: 10.1021/acs.analchem.5c04768

Yuchong Zheng,Wanjun Yao,Zerui Wu,Liqun He,Weidong Zheng,Zida Li

{"title":"Flow-LAMP: Label-Free Digital LAMP Using Scatter-Based Flow Cytometry on Vortex-Generated Polydisperse Gel Beads.","authors":"Yuchong Zheng,Wanjun Yao,Zerui Wu,Liqun He,Weidong Zheng,Zida Li","doi":"10.1021/acs.analchem.5c04768","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c04768","url":null,"abstract":"Accurate nucleic acid quantification is vital for clinical diagnostics, yet the widespread adoption of digital PCR remains limited due to its reliance on fluorescence detection and specialized microfluidics. We present Flow-LAMP, a label-free digital assay integrating loop-mediated isothermal amplification with scatter-based flow cytometric analysis of agarose gel beads. Polydisperse gel beads are formed by vortex emulsification and retain magnesium pyrophosphate precipitate in positive reactions. Flow cytometry enables volume and amplification readouts via forward (FSC) and side scattering (SSC) signals, respectively. We confirmed that SSC was strongly correlated with amplification products, while FSC-Height accurately reflected the bead volume. Using Epstein-Barr virus plasmid, Flow-LAMP achieved accurate quantification with a limit of detection of 38.15 copies/μL. Results from testing clinical plasma samples correlated well with qPCR and digital PCR. By eliminating fluorescent labeling and microfluidics, Flow-LAMP offers a cost-effective and accessible platform for digital nucleic acid detection using standard lab equipment.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"40 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145277345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biochemometric 2D NMR-Based Heterocovariance Analysis: A Targeted Approach for Identifying Bioactive Compounds in Complex Mixtures. 基于二维核磁共振的生物化学异质性分析：一种在复杂混合物中鉴定生物活性化合物的靶向方法。

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-12 DOI: 10.1021/acs.analchem.5c02419

Sigrid Adelsberger,Alexander F Perhal,Lorenza Bertaina,Patrik F Schwarz,Verena M Dirsch,Judith M Rollinger,Ulrike Grienke

{"title":"Biochemometric 2D NMR-Based Heterocovariance Analysis: A Targeted Approach for Identifying Bioactive Compounds in Complex Mixtures.","authors":"Sigrid Adelsberger,Alexander F Perhal,Lorenza Bertaina,Patrik F Schwarz,Verena M Dirsch,Judith M Rollinger,Ulrike Grienke","doi":"10.1021/acs.analchem.5c02419","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c02419","url":null,"abstract":"Biochemometric approaches, which integrate bioactivity data with spectroscopic or spectrometric data, offer significant potential to streamline the discovery of bioactive compounds in targeted isolation strategies. However, the complexity of natural extracts and the presence of structurally similar analogs make this process time-consuming and resource intensive. This study introduces a 2D nuclear magnetic resonance (NMR)-based heterocovariance analysis (HetCA) workflow to identify chemical features that correlate positively or negatively with bioactivity in complex mixtures. As a proof-of-concept, the workflow was established using artificially mixed samples of pentacyclic triterpenes which were screened for modulatory activities of the retinoic acid receptor-related orphan receptor gamma (RORγ) and the G protein-coupled bile acid receptor (TGR5). The validated concept was then exemplified using a triterpene-rich Eriobotrya japonica leaf extract. The applied workflow enabled the targeted and accurate identification of bioactive constituents from E. japonica that modulate RORγ and/or TGR5 using this newly developed biochemometric 2D NMR HetCA approach.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"23 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145277349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computer Vision-Assisted Data Analysis for Correlative Electron Microscopy and Secondary Ion Mass Spectrometry Imaging. 相关电子显微镜和二次离子质谱成像的计算机视觉辅助数据分析。

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-12 DOI: 10.1021/acs.analchem.5c04489

André du Toit,Alicia A Lork,Carl Ernst,Nhu T N Phan

{"title":"Computer Vision-Assisted Data Analysis for Correlative Electron Microscopy and Secondary Ion Mass Spectrometry Imaging.","authors":"André du Toit,Alicia A Lork,Carl Ernst,Nhu T N Phan","doi":"10.1021/acs.analchem.5c04489","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c04489","url":null,"abstract":"Correlative imaging is a powerful analytical approach in bioimaging, as it offers complementary information on the samples measured by different modalities. Particularly, correlative transmission electron microscopy (EM) and nanoscale secondary ion mass spectrometry (NanoSIMS) imaging enable high-resolution morphological and chemical analysis at the subcellular level. However, manual segmentation and correlation of regions of interest (ROIs) in large EM and NanoSIMS data sets are time-consuming, prone to user bias, and limited in throughput. To address this, we developed a computer vision-assisted image analysis pipeline for automatic classification and segmentation of subcellular organelles in EM images, enabling rapid and reproducible correlation with NanoSIMS ion data. Using human neuronal progenitor cells (hNPCs) and differentiated postmitotic neurons, we trained a YOLOv8 deep learning model to recognize six major organelle types. The pipeline included EM image preprocessing, segmentation via YOLOv8, morphological filtering, and image registration with NanoSIMS ion maps. Performance evaluation demonstrated a robust model accuracy. We applied the pipeline to measure 15N-leucine abundance to study protein turnover in single organelles across different cell states. Results showed distinct turnover dynamics among organelles, with slower turnover observed in differentiated neurons compared to hNPCs. The automated pipeline significantly reduced the analysis time (from hours to minutes) while maintaining consistency with manual segmentation. Our approach demonstrates how computer vision can streamline correlative imaging workflows, improve data quality, and enable deeper insights into subcellular processes such as protein turnover, making it especially valuable for SIMS users and broader bioimaging applications.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"7 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI One-Click-Processing-Assisted Ratiometric RTP Paper-Based Sensor Array for the Rapid Discrimination and Detection of Mixtures of Oxolinic Acid and Flumequine 人工智能一键处理辅助比率RTP纸基传感器阵列快速鉴别检测氧喹啉酸与氟喹混合物

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-11 DOI: 10.1021/acs.analchem.5c04191

Henggang Wang, Beibei Zhang, Yaole Qin, Yu-e Shi, Yulu Wang, Shikao Shi, Zhenguang Wang

{"title":"AI One-Click-Processing-Assisted Ratiometric RTP Paper-Based Sensor Array for the Rapid Discrimination and Detection of Mixtures of Oxolinic Acid and Flumequine","authors":"Henggang Wang, Beibei Zhang, Yaole Qin, Yu-e Shi, Yulu Wang, Shikao Shi, Zhenguang Wang","doi":"10.1021/acs.analchem.5c04191","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c04191","url":null,"abstract":"The rapid and precise detection and discrimination of structurally analogous analytes remain highly desirable yet challenging. In this work, a ratiometric room-temperature phosphorescence (RTP) sensor array integrated with phosphorescence amplification and artificial intelligence (AI)-driven data processing was developed for the rapid discrimination and quantification of the mixture of oxolinic acid (OLA) and flumequine (FMQ). The sensor array leverages paper substrates to amplify the blue RTP signals of the OLA and FMQ and the green RTP signals of 1,5-naphthalenedisulfonic acid through a confinement and thermal annealing mechanism. By coupling these amplified signals with automated AI processing and pattern recognition, quantification, and discrimination, the mixture of OLA and FMQ was realized, as low as 1.96 μM, within 10 min. In addition, the entire process could be executed by using a smartphone-based camera, eliminating the need for specialized instrumentation. The sensor array also demonstrated exceptional performance in practical samples, including environmental and food matrices, and paved the way for innovative sensor design.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"28 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thermodynamic Microenvironment Engineering in Mesoporous Nanoreactors to Enhance Biocatalysis for AI-Empowered Ultrasensitive Pathogen Detection 介孔纳米反应器的热力学微环境工程增强人工智能超灵敏病原体检测的生物催化

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-11 DOI: 10.1021/acs.analchem.5c03889

Yuechun Li, Chenjie Nie, Chenxin Ji, Zhaowen Cui, Yanwei Ji, Min Ma, Wentao Zhang, Leina Dou, Qianjin Liu, Jianlong Wang

{"title":"Thermodynamic Microenvironment Engineering in Mesoporous Nanoreactors to Enhance Biocatalysis for AI-Empowered Ultrasensitive Pathogen Detection","authors":"Yuechun Li, Chenjie Nie, Chenxin Ji, Zhaowen Cui, Yanwei Ji, Min Ma, Wentao Zhang, Leina Dou, Qianjin Liu, Jianlong Wang","doi":"10.1021/acs.analchem.5c03889","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c03889","url":null,"abstract":"Harmonizing enzyme-support microenvironments to govern thermodynamic interaction landscapes presents a critical yet underexplored frontier in nanobiocatalysis for pathogen detection. Herein, we architecturally engineer mesoporous resorcinol formaldehyde nanospheres (mRFNSs, 9.95 nm pores) with tailored surface chemistry to elucidate how microenvironment modulation dictates enzyme immobilization energetics. Thermodynamic dissection demonstrates that betaine-tailored mRFNSs with optimal immobilization efficiency and activity dramatically reshape binding energetics, achieving record affinity through optimized electrostatic complementarity, hydrogen-bond networks, and hydrophobic effect. This microenvironment engineering strategy delivers an unprecedented 4.01-fold enhancement in binding constant (Ka = 1.12 × 108 vs 2.79 × 107 M–1) and superior thermodynamic spontaneity (ΔG = −46.0 vs −42.5 kJ mol–1). Leveraging this, we develop a paradigm-shifting ratiometric fluorescence immunoassay where ALP triggers in situ silicon quantum dot (SiQDs) synthesis (530 nm) against tetraphenylbenzidine reference (620 nm), achieving ultrasensitive Salmonella typhimurium (S. typhimurium) detection (100 CFU mL–1), which is 50-fold lower than that of conventional ELISA. A convolutional neural network (CNN) decodes smartphone-captured fluorescence hues, enabling portable classification (93.75% accuracy) of pathogen levels. Validated in food matrices (81.44–116.93% recovery), this work establishes thermodynamic-microenvironment correlations as a blueprint for next-generation nanobiocatalysts, bridging biointerface science with artificial intelligence (AI)-enhanced diagnostics.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"122 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multicenter Validation of Metabolomic Fingerprints for Accurate Diagnosis, Subtyping, and Severity Stratification of Glaucoma 代谢组学指纹图谱用于青光眼准确诊断、分型和严重程度分层的多中心验证

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-11 DOI: 10.1021/acs.analchem.5c05057

Fangying Shi, Shengjie Li, Jun Ren, Xinyi Li, Yuhang Zhang, Yinghua Yan, Chuan-Fan Ding, Wenjun Cao

{"title":"Multicenter Validation of Metabolomic Fingerprints for Accurate Diagnosis, Subtyping, and Severity Stratification of Glaucoma","authors":"Fangying Shi, Shengjie Li, Jun Ren, Xinyi Li, Yuhang Zhang, Yinghua Yan, Chuan-Fan Ding, Wenjun Cao","doi":"10.1021/acs.analchem.5c05057","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c05057","url":null,"abstract":"Timely and accurate diagnosis of primary glaucoma, along with reliable subtype and severity stratification, remains a major clinical challenge. Here, we develop a serum-based metabolomic fingerprint strategy that leverages flower-like hierarchical metal oxide heterojunctions as the matrix for laser desorption/ionization mass spectrometry, combined with a neural network algorithm. A total of 591 serum samples from two independent hospital cohorts were analyzed. In the internal test set, the model achieved exceptionally high diagnostic performance, with accuracy, F1 score, precision, and recall all reaching 1.000. External validation further confirmed its robustness, with an area under the curve (AUC) value of 1.000 and classification accuracy, F1 score, and recall each at 0.990. Subtype classification for primary angle-closure glaucoma (PACG) achieved an accuracy of 97.6%. Severity assessment of severe glaucoma showed strong performance, with an AUC of 0.990 and accuracy of 0.831. These results support the applicability of the proposed approach for precise glaucoma diagnosis and longitudinal monitoring across multicenter clinical cohorts.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"88 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-Pathway Enhanced Single-Molecule Electrochemiluminescence Imaging of T Cell Early Activation Biomarkers T细胞早期活化生物标志物的双途径增强单分子电化学发光成像

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-11 DOI: 10.1021/acs.analchem.5c04037

Yajuan Yan, Jialian Ding, Wenxuan Fu, Lurong Ding, Wei Hu, Guangzhong Ma, Bin Su

{"title":"Dual-Pathway Enhanced Single-Molecule Electrochemiluminescence Imaging of T Cell Early Activation Biomarkers","authors":"Yajuan Yan, Jialian Ding, Wenxuan Fu, Lurong Ding, Wei Hu, Guangzhong Ma, Bin Su","doi":"10.1021/acs.analchem.5c04037","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c04037","url":null,"abstract":"Immunotherapy using activated T cells as the weapon for controlling and eliminating tumor cells represents a promising therapeutic strategy for cancer treatment, in which accurate detection of T cell activation is critical for evaluating the immunotherapy efficacy. Activated T cells upregulate specific plasma membrane biomarkers, such as CD69, that can act as an indicator of activation status. In this work, we report a novel strategy of assessing T cell activation by electrochemiluminescence (ECL) imaging of CD69 expression on the plasma membrane. Mesoporous silica nanoparticles functionalized by polyethylenimine (PEI-SiO2) were prepared as both “nanocoreactant” and “nanoreactor” to remarkably enhance the ECL reaction through a dual-pathway scheme, in which both the catalytic route and the low-oxidation-potential route contribute to produce an enhanced ECL signal. Based on this strategy, subsequent conjugation of PEI-SiO2 with anti-CD69 antibodies allowed us to detect individual CD69 proteins by single-molecule ECL imaging, visualize their spatial distribution on the plasma membrane of activated T cell, and reveal their expression dynamics. The results establish a novel dark-field imaging strategy for assessing T cell activation, offering a low-background tool for investigating immune cell dynamics and immunotherapy efficacy through single-cell-level analysis of key biomarkers.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"72 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultrafast Detection of Small Molecules Using a U-Shaped Transmission Terminal and Straight Plasmonic Sensing Region Fiber Probe Biokinetic Platform: A Case Study of Label-Free Hcy Detection via Indirect Competitive Immunoassay 利用u型传输终端和直等离子体传感区光纤探针生物动力学平台进行小分子超快检测：间接竞争免疫法无标记Hcy检测的案例研究

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-10 DOI: 10.1021/acs.analchem.5c03937

Jian Yang, Jinghan Zhang, Xuejin Li, Xiping Xu, Yan Wang, Xinghong Chen, Shiya Qi, Feng Yan, Youbin Li, Xueming Hong, Yuzhi Chen

{"title":"Ultrafast Detection of Small Molecules Using a U-Shaped Transmission Terminal and Straight Plasmonic Sensing Region Fiber Probe Biokinetic Platform: A Case Study of Label-Free Hcy Detection via Indirect Competitive Immunoassay","authors":"Jian Yang, Jinghan Zhang, Xuejin Li, Xiping Xu, Yan Wang, Xinghong Chen, Shiya Qi, Feng Yan, Youbin Li, Xueming Hong, Yuzhi Chen","doi":"10.1021/acs.analchem.5c03937","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c03937","url":null,"abstract":"Immunoassays face significant challenges, including the precise measurement of small molecules, rapid testing, and background interference. This study constructs a biokinetic sensing platform using a late-model plasmonic fiber probe that incorporates an indirect competitive immunoassay system on its surface for the rapid detection of target small molecules. Our plasmonic fiber probe transforms the conventional online transmission-type fiber surface plasmon resonance (SPR) into a probing structure with a U-shaped fiber termination, preserving the high performance of a straight fiber SPR sensing region and enabling direct sample detection via an insertable probe. Taking the detection of homocysteine (Hcy), a key indicator of cardiovascular diseases, as an example, our fiber probe has achieved rapid immunoassay for small molecules within 10 s while eliminating background interference by measuring target molecular binding rates. The probe sensitively identifies concentration gradients based on binding rates, even in serum, demonstrating high selectivity. The Hcy detection range is 0 to 100 μM, covering low to high abnormal concentrations typically observed in humans, with a detection limit of 2.23 nM. This fiber-optic kinetic method provides rapid, accurate Hcy testing; and multichannel networked potential for various small molecules, macromolecules, and genes detection.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"51 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Creation of an Open-Access High-Resolution Tandem Mass Spectral Library of 1000 Food Toxicants 创建1000种食品毒物的开放获取高分辨率串联质谱库

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-10 DOI: 10.1021/acs.analchem.5c03020

Federico Padilla-González, Serena Rizzo, Caroline Dirks, Wout Bergkamp, Sjors Rasker, Ivan Aloisi

{"title":"Creation of an Open-Access High-Resolution Tandem Mass Spectral Library of 1000 Food Toxicants","authors":"Federico Padilla-González, Serena Rizzo, Caroline Dirks, Wout Bergkamp, Sjors Rasker, Ivan Aloisi","doi":"10.1021/acs.analchem.5c03020","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c03020","url":null,"abstract":"Spectral library searching is a key method for compound annotation in mass spectrometry; however, existing libraries often suffer from high data heterogeneity, varying spectral quality, or limited accessibility. These issues are particularly significant in food safety, where the lack of comprehensive reference data hampers the identification of hazardous compounds. To address these limitations, we developed the WFSR Food Safety Mass Spectral Library, a freely accessible tandem mass spectral library focused on food contaminants, residues, and hazardous compounds. This library contains 6993 manually curated spectra from 1001 compounds acquired in positive ionization mode using ultrahigh-performance liquid chromatography coupled to an Orbitrap IQ-X Tribrid mass spectrometer. Spectra were recorded at seven collision energies under standardized conditions. Comprehensive metadata are provided, including common names, CAS, SMILES, InChIKeys, retention times, and compound classes. The library is publicly available via a dedicated website (https://www.wur.nl/en/show/food-safety-mass-spectral-library.htm) and through the GNPS repository, adhering to FAIR data principles to facilitate community reuse. Comparisons with major repositories (GNPS, MassBank, MoNA, and MSnLib) showed that 216 compounds (22.2%) are unique to our library. Further analysis using molecular networking and MS2Query revealed that about 38% of the compounds lack reliable matches in public libraries. The WFSR spectral library is designed to improve the annotation of food toxicants and facilitate the identification of structural analogues using computational tools. This library is part of an ongoing initiative with future updates planned to include negative ionization mode spectra and an expanded compound repertoire, aiming to advance food safety monitoring.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"37 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NMRMind: A Transformer-Based Model Enabling the Elucidation from Multidimensional NMR to Structures 核磁共振思维：一个基于变压器的模型，实现了从多维核磁共振到结构的解析

IF 7.4 1区化学

Analytical Chemistry Pub Date : 2025-10-10 DOI: 10.1021/acs.analchem.5c03783

Xi Xue, Hanyu Sun, Jingying Sun, Luc Patiny, Xiangying Liu, Kai Chen, Jingjie Yan, Liangning Li, Xue Liu, Shu Xu, Dongming Zhang, Yafeng Deng, Yingda Zang, Yaling Gong, Jie Ma, Xiaojian Wang

{"title":"NMRMind: A Transformer-Based Model Enabling the Elucidation from Multidimensional NMR to Structures","authors":"Xi Xue, Hanyu Sun, Jingying Sun, Luc Patiny, Xiangying Liu, Kai Chen, Jingjie Yan, Liangning Li, Xue Liu, Shu Xu, Dongming Zhang, Yafeng Deng, Yingda Zang, Yaling Gong, Jie Ma, Xiaojian Wang","doi":"10.1021/acs.analchem.5c03783","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c03783","url":null,"abstract":"Nuclear magnetic resonance (NMR) data provides rich quantum information on molecular structure, which is closely related to chemical structure and widely used for structural characterization in chemical discovery. Despite substantial advances in spectral analysis techniques, few existing models have demonstrated satisfactory performance in accurate NMR interpretation. Herein, we introduce NMRMind, a Transformer-based generative framework that directly elucidates molecular structures from NMR spectral data. NMRMind was pretrained on a data set comprising 45 million 1D NMR spectra and subsequently fine-tuned on a self-curated benchmark consisting of 2.2 million 1D and 2D NMR spectra. Using a mixed-modality dropout strategy during training, NMRMind achieved excellent performance, attaining a Top-1 accuracy of 92.07% across all input conditions on the structure elucidation task with a speed of <0.05 s per elucidation. Additionally, NMRMind maintained a Top-1 accuracy of 85.10% when only one-dimensional and two-dimensional NMR data were used as input, without considering molecular formulas or fragments. Moreover, the application of NMRMind facilitated the discovery of six previously uncharacterized natural products from Magnolia officinalis and successfully elucidated the structures of six unexpected products resulting from synthetic reactions, thereby expanding the accessible chemical space and providing novel insights into chemical mechanisms. These results demonstrate that NMRMind is a powerful and generalizable platform for chemistry research.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"114 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145255129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0