Mass Spectrometry Imaging for Spatial Toxicology Research DOI Creative Commons
Tian Qiu

Journal of Mass Spectrometry, Journal Year: 2024, Volume and Issue: 59(12)

Published: Dec. 1, 2024

ABSTRACT The spatial information of xenobiotics distribution, metabolism, and toxicity mechanisms in situ has drawn increasing attention both pharmaceutical environmental toxicology research to aid drug development risk assessments. Mass spectrometry imaging (MSI) provides a label‐free, multiplexed, high‐throughput tool characterize xenobiotics, their metabolites, endogenous molecules with resolution, providing knowledge on spatially resolved absorption, excretion, the molecular level. In this perspective, we briefly summarize applications MSI xenobiotic distribution quantification, mechanisms, biomarker discovery. We identified several challenges regarding how can fully harness power fundamental regulatory practices. First, increase coverage, sensitivity, specificity detecting metabolites complex biological matrices? Second, link consequences understand predict exposure outcomes, discovery? Finally, standardize experiment data analysis workflow provide robust conclusions for regulation development? With these questions mind, our perspectives future directions as promising research.

Language: Английский

AI-Enhanced Real-Time Monitoring of Marine Pollution: Part 2—A Spectral Analysis Approach DOI Creative Commons
Navya Prakash, Oliver Zielinski

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(4), P. 636 - 636

Published: March 22, 2025

Oil spills and marine litter pose significant threats to ecosystems, necessitating innovative real-time monitoring solutions. This research presents a novel AI-driven multisensor system that integrates RGB, thermal infrared, hyperspectral radiometers detect classify pollutants in dynamic offshore environments. The features dual-unit design: an overview unit for wide-area detection directional equipped with autonomous pan-tilt mechanism focused high-resolution analysis. By leveraging multi-hyperspectral data fusion, this overcomes challenges such as variable lighting, water surface reflections, environmental interferences, significantly enhancing pollutant classification accuracy. YOLOv5 deep learning model was validated using extensive synthetic real-world datasets, achieving F1-score of 0.89 mAP 0.90. These results demonstrate the robustness scalability proposed system, enabling pollution monitoring, improving conservation strategies, supporting regulatory enforcement sustainability.

Language: Английский

Citations

0
A MALDI-MSI-Based Approach to Characterize the Spatial Distribution of Cylindrospermopsin and Lipid Alterations in Rat Intestinal Tissue. DOI
Antonio Casas-Rodríguez, Carmen López‐Vázquez, Remedios Guzmán‐Guillén

et al.

Chemico-Biological Interactions, Journal Year: 2025, Volume and Issue: unknown, P. 111479 - 111479

Published: March 1, 2025

Language: Английский

Citations

0
Advancing Environmental Toxicology: The Role of Mass Spectrometry Imaging DOI Creative Commons
Albert Menéndez-Pedriza, Lidia Molina-Millán, Eva Cuypers

et al.

Trends in Environmental Analytical Chemistry, Journal Year: 2024, Volume and Issue: unknown, P. e00253 - e00253

Published: Dec. 1, 2024

Language: Английский

Citations

1
Mass Spectrometry Imaging for Spatial Toxicology Research DOI Creative Commons
Tian Qiu

Journal of Mass Spectrometry, Journal Year: 2024, Volume and Issue: 59(12)

Published: Dec. 1, 2024

ABSTRACT The spatial information of xenobiotics distribution, metabolism, and toxicity mechanisms in situ has drawn increasing attention both pharmaceutical environmental toxicology research to aid drug development risk assessments. Mass spectrometry imaging (MSI) provides a label‐free, multiplexed, high‐throughput tool characterize xenobiotics, their metabolites, endogenous molecules with resolution, providing knowledge on spatially resolved absorption, excretion, the molecular level. In this perspective, we briefly summarize applications MSI xenobiotic distribution quantification, mechanisms, biomarker discovery. We identified several challenges regarding how can fully harness power fundamental regulatory practices. First, increase coverage, sensitivity, specificity detecting metabolites complex biological matrices? Second, link consequences understand predict exposure outcomes, discovery? Finally, standardize experiment data analysis workflow provide robust conclusions for regulation development? With these questions mind, our perspectives future directions as promising research.

Language: Английский

Citations

0