Evaluating the generalizability of graph neural networks for predicting collision cross section DOI Creative Commons
Chloe Engler Hart, António J. Preto, Shaurya Chanana

et al.

Published: May 17, 2024

Ion Mobility coupled with Mass Spectrometry (IM-MS) is a promising analytical technique that enhances molecular characterization by measuring collision cross-section (CCS) values, which are indicative of the size and shape. However, effective application CCS values in structural analysis still constrained limited availability experimental data, necessitating development accurate machine learning (ML) models for silico predictions. In this study, we evaluated state-of-the-art Graph Neural Networks (GNNs), trained to predict using largest publicly available dataset date. Although our results confirm high accuracy these within chemical spaces similar their training environments, performance significantly declines when applied structurally novel regions. This discrepancy raises concerns about reliability predictions underscores need releasing further datasets. To mitigate this, demonstrate how generalization can be partially improved extending account additional features such as fingerprints, descriptors, molecule types. Lastly, also show confidence support enhancing estimates.

Language: Английский

Emerging contaminants: A One Health perspective DOI Creative Commons
Fang Wang, Leilei Xiang, Kelvin Sze‐Yin Leung

et al.

The Innovation, Journal Year: 2024, Volume and Issue: 5(4), P. 100612 - 100612

Published: March 13, 2024

Language: Английский

Citations

138
High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage DOI Creative Commons
Yunjia Lai, Jeremy P. Koelmel, Douglas G. Walker

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(29), P. 12784 - 12822

Published: July 10, 2024

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

Language: Английский

Citations

20
Computational tools and algorithms for ion mobility spectrometry‐mass spectrometry DOI Creative Commons
Dylan H. Ross, Harsh Bhotika, Xueyun Zheng

et al.

PROTEOMICS, Journal Year: 2024, Volume and Issue: 24(12-13)

Published: March 4, 2024

Abstract Ion mobility spectrometry‐mass spectrometry (IMS‐MS or IM‐MS) is a powerful analytical technique that combines the gas‐phase separation capabilities of IM with identification and quantification MS. IM‐MS can differentiate molecules indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, contaminant ions). The importance this reflected by staged increase in number applications for characterization across variety fields, from MS‐based omics (proteomics, metabolomics, lipidomics, etc.) to structural glycans, organic matter, proteins, macromolecular complexes. With increasing application there pressing need effective accessible computational tools. This article presents an overview most recent free open‐source software tools specifically tailored analysis interpretation data derived instrumentation. review enumerates these outlines their main algorithmic approaches, while highlighting representative fields. Finally, discussion current limitations expectable improvements presented.

Language: Английский

Citations

9
Ultra-high performance liquid chromatography ion mobility-high-resolution mass spectrometry for the assessment of raw milk traceability DOI Creative Commons
Nicolò Riboni, Maurizio Piergiovanni, Monica Mattarozzi

et al.

Food Chemistry, Journal Year: 2025, Volume and Issue: 471, P. 142796 - 142796

Published: Jan. 9, 2025

The complexity of modern food supply chains limits the effectiveness targeted approaches to address traceability issues. Untargeted metabolomics provides a comprehensive profile small molecules present within biological samples. In this study, potential ultra-high performance liquid chromatography-ion mobility-high resolution mass spectrometry (UHPLC-IMS-HRMS) discriminate bovine milk samples collected at individual level was evaluated for purposes. For first time, IMS coupled with UHPLC-HRMS applied analysis, increasing confidence in metabolite annotation. Supervised Partial Least Squares-Discriminant Analysis backward elimination variable selection allowed 52 and 153 features able belonging different dairy trace herd level, respectively. Amino acids, glycerolipids, glycerophospholipids were most represented classes, influencing biological/technological properties final product. perfect classification external test sets demonstrated reliability proposed approach.

Language: Английский

Citations

0
Prioritization Strategies in Non-Target Screening of Environmental Samples by Chromatography – High-Resolution Mass Spectrometry: A Tutorial DOI
Jonathan Zweigle, Selina Tisler, Giorgio Tomasi

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Artificial intelligence driven approaches in phytochemical research: trends and prospects DOI Creative Commons

Ressin Varghese,

Harshita Shringi,

Thomas Efferth

et al.

Phytochemistry Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Language: Английский

Citations

0
Multidimensional-Constrained Suspect Screening of Hydrophobic Contaminants Using Gas Chromatography-Atmospheric Pressure Chemical Ionization-Ion Mobility-Mass Spectrometry DOI Creative Commons
Xiaodi Shi, Anna Sobek, Jonathan P. Benskin

et al.

Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: March 6, 2025

Suspect screening strives to rapidly monitor a large number of substances in sample using mass spectral libraries. For hydrophobic organic contaminants (HOCs), these libraries are traditionally based on electron ionization spectra. However, with the growing use state-of-the-art spectrometers, which often alternative approaches and separation techniques, new suspect workflows urgently needed. This study established library for 1,590 HOCs, including exact combination measured model-predicted values retention time (RT) collision cross section (CCS). The accuracy silico predictions was assessed standards 102 HOCs. Thereafter, gas chromatography-atmospheric pressure chemical ionization-ion mobility-mass spectrometry, workflow constrained by full scan spectrum (quasi-)molecular ions (including isotope patterns), RT, CCS, fragmentation spectra, together continuous scoring system, reduce false positives improve identification confidence. Application method fortified standard reference sediment samples demonstrated true positive rates 79% 64%, respectively, all attributed isomers. offers improved HOCs multidimensional information highlights need enrich databases extend applicable space current tools substances.

Language: Английский

Citations

0
Prioritization Strategies for Non-Target Screening in Environmental Samples by Chromatography – High-Resolution Mass Spectrometry: A Tutorial DOI
Jonathan Zweigle, Selina Tisler, Marta Bevilacqua

et al.

Journal of Chromatography A, Journal Year: 2025, Volume and Issue: unknown, P. 465944 - 465944

Published: April 1, 2025

Language: Английский

Citations

0
Coupling Capillary Electrophoresis With a Shifted Inlet Potential High‐Resolution Ion Mobility Spectrometer DOI Creative Commons

Klaus Welters,

Christian Thoben, Christian‐Robert Raddatz

et al.

Electrophoresis, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

ABSTRACT We present the coupling of capillary electrophoresis to a custom‐built high‐resolution ion mobility spectrometer (IMS). This system integrates shifted inlet potential IMS configuration with customised nanoflow ESI sheath interface. It enables rapid analysis quaternary ammonium compounds (QACs) and their impurities in real‐world samples. allowed detection six non‐chromophoric about 3 min. The assignment signals was supported by matching experimentally determined collision cross‐section (CCS) values predicted values. achieved limit single‐digit picogram range resolutions over 80.

Language: Английский

Citations

0
Application of the Ginsenoside Multidimensional Information Library (GinMIL) Enables Accurate Characterization of Ginsenosides from Diverse Ginseng Products and Accelerates the Discovery of New Saponin Compounds DOI
Hongda Wang,

Huizhen Cheng,

Min Zhang

et al.

Journal of Agricultural and Food Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Accurate characterization of ginsenosides from ginseng relying on liquid chromatography-mass spectrometry (LC-MS) is challenging due to the lack sufficient structural information. By machine learning techniques, we have established a ginsenoside multidimensional information library, namely, GinMIL, covering four dimensions 579 ginsenosides. This work was designed accurately characterize Panax notoginseng products and rapidly discover novel quinquefolius flowers by ion-mobility LC/MS profiling efficient GinMIL matching UNIFI. Consequently, characterized 334/356/738/545 three parts/two extracts/four single preparations/seven compound preparations notoginseng, respectively. 45/99/59/116 masses were discovered in types products, Four ginsenosides, including rare dimalonyl one methylated malonyl ginsenoside, isolated feat analysis. can verify superiority thus greatly enhancing multicomponent discovery new compounds functional herbs.

Language: Английский

Citations

0